A Comparative Study to Predict Student’s Performance Using Educational Data Mining Techniques

NASA Astrophysics Data System (ADS)

Uswatun Khasanah, Annisa; Harwati

2017-06-01

Student’s performance prediction is essential to be conducted for a university to prevent student fail. Number of student drop out is one of parameter that can be used to measure student performance and one important point that must be evaluated in Indonesia university accreditation. Data Mining has been widely used to predict student’s performance, and data mining that applied in this field usually called as Educational Data Mining. This study conducted Feature Selection to select high influence attributes with student performance in Department of Industrial Engineering Universitas Islam Indonesia. Then, two popular classification algorithm, Bayesian Network and Decision Tree, were implemented and compared to know the best prediction result. The outcome showed that student’s attendance and GPA in the first semester were in the top rank from all Feature Selection methods, and Bayesian Network is outperforming Decision Tree since it has higher accuracy rate.

Improvement of a method for positioning of pithead by considering motion of the surface water

NASA Astrophysics Data System (ADS)

Yi, H.; Lee, D. K.

2016-12-01

Underground mining has weakness compared with open pit mining in aspects of efficiency, economy and working environment. However, the method has applied for the development of a deep orebody. Development plan is established when the economic valuation and technical analysis of the deposits is completed through exploration of mineral resources. Development is a process to open a passage from the ground surface to the orebody as one of the steps of mining process. In the planning, there are details such as pithead positioning, mining method selection, and shaft design, etc. Among these, pithead positioning is implemented by considering infrastructures, watershed, geology, and economy. In this study, we propose a method to consider the motion of the surface waters in order to improve the existing pithead positioning techniques. The method contemplates the terrain around the mine and makes the surface water flow information. Then, the drainage treatment cost for each candidate location of pithead is suggested. This study covers the concept and design of the scheme.

A hybrid feature selection method using multiclass SVM for diagnosis of erythemato-squamous disease

NASA Astrophysics Data System (ADS)

Maryam, Setiawan, Noor Akhmad; Wahyunggoro, Oyas

2017-08-01

The diagnosis of erythemato-squamous disease is a complex problem and difficult to detect in dermatology. Besides that, it is a major cause of skin cancer. Data mining implementation in the medical field helps expert to diagnose precisely, accurately, and inexpensively. In this research, we use data mining technique to developed a diagnosis model based on multiclass SVM with a novel hybrid feature selection method to diagnose erythemato-squamous disease. Our hybrid feature selection method, named ChiGA (Chi Square and Genetic Algorithm), uses the advantages from filter and wrapper methods to select the optimal feature subset from original feature. Chi square used as filter method to remove redundant features and GA as wrapper method to select the ideal feature subset with SVM used as classifier. Experiment performed with 10 fold cross validation on erythemato-squamous diseases dataset taken from University of California Irvine (UCI) machine learning database. The experimental result shows that the proposed model based multiclass SVM with Chi Square and GA can give an optimum feature subset. There are 18 optimum features with 99.18% accuracy.

Information Gain Based Dimensionality Selection for Classifying Text Documents

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dumidu Wijayasekara; Milos Manic; Miles McQueen

2013-06-01

Selecting the optimal dimensions for various knowledge extraction applications is an essential component of data mining. Dimensionality selection techniques are utilized in classification applications to increase the classification accuracy and reduce the computational complexity. In text classification, where the dimensionality of the dataset is extremely high, dimensionality selection is even more important. This paper presents a novel, genetic algorithm based methodology, for dimensionality selection in text mining applications that utilizes information gain. The presented methodology uses information gain of each dimension to change the mutation probability of chromosomes dynamically. Since the information gain is calculated a priori, the computational complexitymore » is not affected. The presented method was tested on a specific text classification problem and compared with conventional genetic algorithm based dimensionality selection. The results show an improvement of 3% in the true positives and 1.6% in the true negatives over conventional dimensionality selection methods.« less

Economic baselines for current underground coal mining technology

NASA Technical Reports Server (NTRS)

Mabe, W. B.

1979-01-01

The cost of mining coal using a room pillar mining method with continuous miner and a longwall mining system was calculated. Costs were calculated for the years 1975 and 2000 time periods and are to be used as economic standards against which advanced mining concepts and systems will be compared. Some assumptions were changed and some internal model stored data was altered from the original calculations procedure chosen, to obtain a result that more closely represented what was considered to be a standard mine. Coal seam thicknesses were varied from one and one-half feet to eight feet to obtain the cost of mining coal over a wide range. Geologic conditions were selected that had a minimum impact on the mining productivity.

Monitoring of Soil Remediation Process in the Metal Mining Area

NASA Astrophysics Data System (ADS)

Kim, Kyoung-Woong; Ko, Myoung-Soo; Han, Hyeop-jo; Lee, Sang-Ho; Na, So-Young

2016-04-01

Stabilization using proper additives is an effective soil remediation technique to reduce As mobility in soil. Several researches have reported that Fe-containing materials such as amorphous Fe-oxides, goethite and hematite were effective in As immobilization and therefore acid mine drainage sludge (AMDS) may be potential material for As immobilization. The AMDS is the by-product from electrochemical treatment of acid mine drainage and mainly contains Fe-oxide. The Chungyang area in Korea is located in the vicinity of the huge abandoned Au-Ag Gubong mine which was closed in the 1970s. Large amounts of mine tailings have been remained without proper treatment and the mobilization of mine tailings can be manly occurred during the summer heavy rainfall season. Soil contamination from this mobilization may become an urgent issue because it can cause the contamination of groundwater and crop plants in sequence. In order to reduce the mobilization of the mine tailings, the pilot scale study of in-situ stabilization using AMDS was applied after the batch and column experiments in the lab. For the monitoring of stabilization process, we used to determine the As concentration in crop plants grown on the field site but it is not easily applicable because of time and cost. Therefore, we may need simple monitoring technique to measure the mobility or leachability which can be comparable with As concentration in crop plants. We compared several extraction methods to suggest the representative single extraction method for the monitoring of soil stabilization efficiency. Several selected extraction methods were examined and Mehlich 3 extraction method using the mixture of NH4F, EDTA, NH4NO3, CH3COOH and HNO3 was selected as the best predictor of the leachability or mobility of As in the soil remediation process.

Combined data mining/NIR spectroscopy for purity assessment of lime juice

NASA Astrophysics Data System (ADS)

Shafiee, Sahameh; Minaei, Saeid

2018-06-01

This paper reports the data mining study on the NIR spectrum of lime juice samples to determine their purity (natural or synthetic). NIR spectra for 72 pure and synthetic lime juice samples were recorded in reflectance mode. Sample outliers were removed using PCA analysis. Different data mining techniques for feature selection (Genetic Algorithm (GA)) and classification (including the radial basis function (RBF) network, Support Vector Machine (SVM), and Random Forest (RF) tree) were employed. Based on the results, SVM proved to be the most accurate classifier as it achieved the highest accuracy (97%) using the raw spectrum information. The classifier accuracy dropped to 93% when selected feature vector by GA search method was applied as classifier input. It can be concluded that some relevant features which produce good performance with the SVM classifier are removed by feature selection. Also, reduced spectra using PCA do not show acceptable performance (total accuracy of 66% by RBFNN), which indicates that dimensional reduction methods such as PCA do not always lead to more accurate results. These findings demonstrate the potential of data mining combination with near-infrared spectroscopy for monitoring lime juice quality in terms of natural or synthetic nature.

The Problem of Multiple Criteria Selection of the Surface Mining Haul Trucks

NASA Astrophysics Data System (ADS)

Bodziony, Przemysław; Kasztelewicz, Zbigniew; Sawicki, Piotr

2016-06-01

Vehicle transport is a dominant type of technological processes in rock mines, and its profit ability is strictly dependent on overall cost of its exploitation, especially on diesel oil consumption. Thus, a rational design of transportation system based on haul trucks should result from thorough analysis of technical and economic issues, including both cost of purchase and its further exploitation, having a crucial impact on the cost of minerals extraction. Moreover, off-highway trucks should be selected with respect to all specific exploitation conditions and even the user's preferences and experience. In this paper a development of universal family of evaluation criteria as well as application of evaluation method for haul truck selection process for a specific exploitation conditions in surface mining have been carried out. The methodology presented in the paper is based on the principles of multiple criteria decision aiding (MCDA) using one of the ranking method, i.e. ELECTRE III. The applied methodology has been allowed for ranking of alternative solution (variants), on the considered set of haul trucks. The result of the research is a universal methodology, and it consequently may be applied in other surface mines with similar exploitation parametres.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chironis, N.P.

This book contains a wealth of valuable information carefully selected and compiled from recent issues of Coal Age magazine. Much of the source material has been gathered by Coal Age Editors during their visits to coal mines, research establishments, universities and technical symposiums. Equally important are the articles and data contributed by over 50 top experts, many of whom are well known to the mining industry. Specifically, this easy-to-use handbook is divided into eleven key areas of underground mining. Here you will find the latest information on continuous mining techniques, longwall and shortwall methods and equipment, specialized mining and boringmore » systems, continuous haulage techniques, improved roof control and ventilation methods, mine communications and instrumentation, power systems, fire control methods, and new mining regulations. There is also a section on engineering and management considerations, including the modern use of computer terminals, practical techniques for picking leaders and for encouraging more safety consciousness in employees, factors affecting absenteeism, and some highly important financial considerations. All of this valuable information has been thoroughly indexed to provide immediate access to the specific data needed by the reader.« less

A review of soil heavy metal pollution from mines in China: pollution and health risk assessment.

PubMed

Li, Zhiyuan; Ma, Zongwei; van der Kuijp, Tsering Jan; Yuan, Zengwei; Huang, Lei

2014-01-15

Heavy metal pollution has pervaded many parts of the world, especially developing countries such as China. This review summarizes available data in the literature (2005-2012) on heavy metal polluted soils originating from mining areas in China. Based on these obtained data, this paper then evaluates the soil pollution levels of these collected mines and quantifies the risks these pollutants pose to human health. To assess these potential threat levels, the geoaccumulation index was applied, along with the US Environmental Protection Agency (USEPA) recommended method for health risk assessment. The results demonstrate not only the severity of heavy metal pollution from the examined mines, but also the high carcinogenic and non-carcinogenic risks that soil heavy metal pollution poses to the public, especially to children and those living in the vicinity of heavily polluted mining areas. In order to provide key management targets for relevant government agencies, based on the results of the pollution and health risk assessments, Cd, Pb, Cu, Zn, Hg, As, and Ni are selected as the priority control heavy metals; tungsten, manganese, lead-zinc, and antimony mines are selected as the priority control mine categories; and southern provinces and Liaoning province are selected as the priority control provinces. This review, therefore, provides a comprehensive assessment of soil heavy metal pollution derived from mines in China, while identifying policy recommendations for pollution mitigation and environmental management of these mines. © 2013.

Comparison of Basic and Ensemble Data Mining Methods in Predicting 5-Year Survival of Colorectal Cancer Patients.

PubMed

Pourhoseingholi, Mohamad Amin; Kheirian, Sedigheh; Zali, Mohammad Reza

2017-12-01

Colorectal cancer (CRC) is one of the most common malignancies and cause of cancer mortality worldwide. Given the importance of predicting the survival of CRC patients and the growing use of data mining methods, this study aims to compare the performance of models for predicting 5-year survival of CRC patients using variety of basic and ensemble data mining methods. The CRC dataset from The Shahid Beheshti University of Medical Sciences Research Center for Gastroenterology and Liver Diseases were used for prediction and comparative study of the base and ensemble data mining techniques. Feature selection methods were used to select predictor attributes for classification. The WEKA toolkit and MedCalc software were respectively utilized for creating and comparing the models. The obtained results showed that the predictive performance of developed models was altogether high (all greater than 90%). Overall, the performance of ensemble models was higher than that of basic classifiers and the best result achieved by ensemble voting model in terms of area under the ROC curve (AUC= 0.96). AUC Comparison of models showed that the ensemble voting method significantly outperformed all models except for two methods of Random Forest (RF) and Bayesian Network (BN) considered the overlapping 95% confidence intervals. This result may indicate high predictive power of these two methods along with ensemble voting for predicting 5-year survival of CRC patients.

Chapter 3: Selecting materials for mine soil construction when establishing forests on Appalachian mined lands

Treesearch

Jeff Skousen; Carl Zipper; Jim Burger; Christopher Barton; Patrick. Angel

2017-01-01

The Forestry Reclamation Approach (FRA), a method for reclaiming coal-mined land to forest (Chapter 2, this volume), is based on research, knowledge, and experience of forest soil scientists and reclamation practitioners. Step 1 of the FRA is to create a suitable rooting medium for good tree growth that is no less than 4 feet deep and consists of topsoil, weathered...

Optimal selection of biochars for remediating metals contaminated mine soils

EPA Science Inventory

Approximately 500,000 abandoned mines across the U.S. pose a considerable, pervasive risk to human health and the environment due to possible exposure to the residuals of heavy metal extraction. Historically, a variety of chemical and biological methods have been used to reduce ...

Manipulating measurement scales in medical statistical analysis and data mining: A review of methodologies

PubMed Central

Marateb, Hamid Reza; Mansourian, Marjan; Adibi, Peyman; Farina, Dario

2014-01-01

Background: selecting the correct statistical test and data mining method depends highly on the measurement scale of data, type of variables, and purpose of the analysis. Different measurement scales are studied in details and statistical comparison, modeling, and data mining methods are studied based upon using several medical examples. We have presented two ordinal–variables clustering examples, as more challenging variable in analysis, using Wisconsin Breast Cancer Data (WBCD). Ordinal-to-Interval scale conversion example: a breast cancer database of nine 10-level ordinal variables for 683 patients was analyzed by two ordinal-scale clustering methods. The performance of the clustering methods was assessed by comparison with the gold standard groups of malignant and benign cases that had been identified by clinical tests. Results: the sensitivity and accuracy of the two clustering methods were 98% and 96%, respectively. Their specificity was comparable. Conclusion: by using appropriate clustering algorithm based on the measurement scale of the variables in the study, high performance is granted. Moreover, descriptive and inferential statistics in addition to modeling approach must be selected based on the scale of the variables. PMID:24672565

Method to Select Technical Terms for Glossaries in Support of Joint Task Force Operations

DTIC Science & Technology

2012-01-01

have been prohibitively time-consuming. Instead, we identified two publicly available terminology extractor tools: TerMine (NaCTEM, 2011) and Alchemy ...and that from the latter, by high recall. The Alchemy approach contrasts with that used in TerMine in that Alchemy will process the text with...information categories, such as person, location, and organization, in addition to returning topic keywords. Output from both TerMine and Alchemy

Mine Planning for Asteroid Orebodies

NASA Astrophysics Data System (ADS)

Gertsch, L. S.; Gertsch, R. E.

2000-01-01

Given that an asteroid (or comet) has been determined to contain sufficient material of value to be potentially economic to exploit, a mining method must be selected and implemented. This paper discusses the engineering necessary to bring a mine online, and the opportunities and challenges inherent in asteroid mineral prospects. The very important step of orebody characterization is discussed elsewhere. The mining methods discussed here are based on enclosing the asteroid within a bag in some fashion, whether completely or partially. In general, asteroid mining methods based on bags will consist of the following steps. Not all will be required in every case, nor necessarily in this particular sequence. Some steps will be performed simultaneously. Their purpose is to extract the valuable material from the body of the asteroid in the most efficient, cost-effective manner possible. In approximate order of initiation, if not of conclusion, the steps are: 1. Tether anchoring to the asteroid. 2. Asteroid motion control. 3. Body/fragment restraint system placement. 4. Operations platform construction. 5. Bag construction. 6. Auxiliary and support equipment placement. 7. Mining operations. 8. Processing operations. 9. Product transport to markets.

A simplified economic filter for open-pit mining and heap-leach recovery of copper in the United States

USGS Publications Warehouse

Long, Keith R.; Singer, Donald A.

2001-01-01

Determining the economic viability of mineral deposits of various sizes and grades is a critical task in all phases of mineral supply, from land-use management to mine development. This study evaluates two simple tools for estimating the economic viability of porphyry copper deposits mined by open-pit, heap-leach methods when only limited information on these deposits is available. These two methods are useful for evaluating deposits that either (1) are undiscovered deposits predicted by a mineral resource assessment, or (2) have been discovered but for which little data has been collected or released. The first tool uses ordinary least-squared regression analysis of cost and operating data from selected deposits to estimate a predictive relationship between mining rate, itself estimated from deposit size, and capital and operating costs. The second method uses cost models developed by the U.S. Bureau of Mines (Camm, 1991) updated using appropriate cost indices. We find that the cost model method works best for estimating capital costs and the empirical model works best for estimating operating costs for mines to be developed in the United States.

Monitoring of the stability of underground workings in Polish copper mines conditions

NASA Astrophysics Data System (ADS)

Fuławka, Krzysztof; Mertuszka, Piotr; Pytel, Witold

2018-01-01

One of the problems associated with the excavation of deposit in underground mines is the local disturbance in a state of unstable equilibrium results in the sudden release of energy, mainly in the form of roof falls. The scale and intensity of this type of events depends on a number of factors. To minimize the risk of instability occurrence, continuous observations of the roof strata condition are recommended. Different roof strata observation methods used in the Polish copper mines have been analysed within the framework of presented paper. In addition, selected prospective methods, which could significantly increase efficiency of rock fall prevention are presented.

Mining and beneficiation: A review of possible lunar applications

NASA Technical Reports Server (NTRS)

Chamberlain, Peter G.

1991-01-01

Successful exploration of Mars and outer space may require base stations strategically located on the Moon. Such bases must develop a certain self-sufficiency, particularly in the critical life support materials, fuel components, and construction materials. Technology is reviewed for the first steps in lunar resource recovery-mining and beneficiation. The topic is covered in three main categories: site selection; mining; and beneficiation. It will also include (in less detail) in-situ processes. The text described mining technology ranging from simple diggings and hauling vehicles (the strawman) to more specialized technology including underground excavation methods. The section of beneficiation emphasizes dry separation techniques and methods of sorting the ore by particle size. In-situ processes, chemical and thermal, are identified to stimulate further thinking by future researchers.

Recent developments in the reclamation of surface mined lands

USGS Publications Warehouse

Sharma, K.D.; Gough, L.P.; Kumar, S.; Sharma, B.K.; Saxena, S.K.

1997-01-01

A broad review of mine land reclamation problems and challenges in arid lands is presented with special emphasis on work recently completed in India. The economics of mining in the Indian Desert is second only to agriculture in importance. Lands disturbed by mining, however, have only recently been the focus of reclamation attempts. Studies were made and results compiled of problems associated with germplasm selection, soil, plant and overburden characterization and manipulation, plant establishment methods utilized, soil amendment needs, use and conservation of available water and the evaluation of ecosystem sustainability. Emphasis is made of the need for multi-disciplinary approaches to mine land reclamation research and for the long-term monitoring of reclamation success.

Exploring Student Characteristics of Retention That Lead to Graduation in Higher Education Using Data Mining Models

ERIC Educational Resources Information Center

Raju, Dheeraj; Schumacker, Randall

2015-01-01

The study used earliest available student data from a flagship university in the southeast United States to build data mining models like logistic regression with different variable selection methods, decision trees, and neural networks to explore important student characteristics associated with retention leading to graduation. The decision tree…

Predicting Dropout Student: An Application of Data Mining Methods in an Online Education Program

ERIC Educational Resources Information Center

Yukselturk, Erman; Ozekes, Serhat; Turel, Yalin Kilic

2014-01-01

This study examined the prediction of dropouts through data mining approaches in an online program. The subject of the study was selected from a total of 189 students who registered to the online Information Technologies Certificate Program in 2007-2009. The data was collected through online questionnaires (Demographic Survey, Online Technologies…

Selective sequential precipitation of dissolved metals in mine drainage from coal mine

NASA Astrophysics Data System (ADS)

Yim, Giljae; Bok, Songmin; Ji, Sangwoo; Oh, Chamteut; Cheong, Youngwook; Han, Youngsoo; Ahn, Joosung

2017-04-01

In abandoned mines in Korea, a large amount of mine drainage continues to flow out and spread pollution. In purification of the mine drainage a massive amount of sludge is generated as waste. Since this metal sludge contains high Fe, Al and Mn oxides, developing the treatment method to recover homogeneous individual metal with high purity may beneficial to recycle waste metals as useful resources and reduce the amount of sludge production. In this regard, we established a dissolved metals selective precipitation process to treat Waryong Industry's mine drainage. The process that selectively precipitates metals dissolved in mine drainage is a continuous Fe-buffer-Al process, and each process consists of the neutralization tank, the coagulation tank, and the settling tank. Based on this process, this study verified the operational applicability of the Fe and Al selective precipitation. Our previous study revealed that high-purity Fe and Al precipitates could be recovered at a flow rate of 1.5 ton/day, while the lower purity was achieved when the rate was increased to about 3 ton/day due to the difficulty in reagent dosage control. In the current study was conducted to increase the capacity of the system to recover Fe and Al as high-purity precipitates at a flow rate of 10 ton/day with the ensured continuous operations by introducing an automatic reagent injection system. The previous study had a difficulty in controlling the pH and operating system continuously due to the manually controlled reagent injection system. To upgrade this and ensure the optimal pH in a stable way, a continuous reagent injection system was installed. The result of operation of the 10 ton/day system confirmed that the scaled-up process could maintain the stable recovery rates and purities of precipitates on site.

Knowledge mining from clinical datasets using rough sets and backpropagation neural network.

PubMed

Nahato, Kindie Biredagn; Harichandran, Khanna Nehemiah; Arputharaj, Kannan

2015-01-01

The availability of clinical datasets and knowledge mining methodologies encourages the researchers to pursue research in extracting knowledge from clinical datasets. Different data mining techniques have been used for mining rules, and mathematical models have been developed to assist the clinician in decision making. The objective of this research is to build a classifier that will predict the presence or absence of a disease by learning from the minimal set of attributes that has been extracted from the clinical dataset. In this work rough set indiscernibility relation method with backpropagation neural network (RS-BPNN) is used. This work has two stages. The first stage is handling of missing values to obtain a smooth data set and selection of appropriate attributes from the clinical dataset by indiscernibility relation method. The second stage is classification using backpropagation neural network on the selected reducts of the dataset. The classifier has been tested with hepatitis, Wisconsin breast cancer, and Statlog heart disease datasets obtained from the University of California at Irvine (UCI) machine learning repository. The accuracy obtained from the proposed method is 97.3%, 98.6%, and 90.4% for hepatitis, breast cancer, and heart disease, respectively. The proposed system provides an effective classification model for clinical datasets.

A non-linear data mining parameter selection algorithm for continuous variables

PubMed Central

Razavi, Marianne; Brady, Sean

2017-01-01

In this article, we propose a new data mining algorithm, by which one can both capture the non-linearity in data and also find the best subset model. To produce an enhanced subset of the original variables, a preferred selection method should have the potential of adding a supplementary level of regression analysis that would capture complex relationships in the data via mathematical transformation of the predictors and exploration of synergistic effects of combined variables. The method that we present here has the potential to produce an optimal subset of variables, rendering the overall process of model selection more efficient. This algorithm introduces interpretable parameters by transforming the original inputs and also a faithful fit to the data. The core objective of this paper is to introduce a new estimation technique for the classical least square regression framework. This new automatic variable transformation and model selection method could offer an optimal and stable model that minimizes the mean square error and variability, while combining all possible subset selection methodology with the inclusion variable transformations and interactions. Moreover, this method controls multicollinearity, leading to an optimal set of explanatory variables. PMID:29131829

Optimal location of emergency stations in underground mine networks using a multiobjective mathematical model.

PubMed

Lotfian, Reza; Najafi, Mehdi

2018-02-26

Background Every year, many mining accidents occur in underground mines all over the world resulting in the death and maiming of many miners and heavy financial losses to mining companies. Underground mining accounts for an increasing share of these events due to their special circumstances and the risks of working therein. Thus, the optimal location of emergency stations within the network of an underground mine in order to provide medical first aid and transport injured people at the right time, plays an essential role in reducing deaths and disabilities caused by accidents Objective The main objective of this study is to determine the location of emergency stations (ES) within the network of an underground coal mine in order to minimize the outreach time for the injured. Methods A three-objective mathematical model is presented for placement of ES facility location selection and allocation of facilities to the injured in various stopes. Results Taking into account the radius of influence for each ES, the proposed model is capable to reduce the maximum time for provision of emergency services in the event of accident for each stope. In addition, the coverage or lack of coverage of each stope by any of the emergency facility is determined by means of Floyd-Warshall algorithm and graph. To solve the problem, a global criterion method using GAMS software is used to evaluate the accuracy and efficiency of the model. Conclusions 7 locations were selected from among 46 candidates for the establishment of emergency facilities in Tabas underground coal mine. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

New approach for reduction of diesel consumption by comparing different mining haulage configurations.

PubMed

Rodovalho, Edmo da Cunha; Lima, Hernani Mota; de Tomi, Giorgio

2016-05-01

The mining operations of loading and haulage have an energy source that is highly dependent on fossil fuels. In mining companies that select trucks for haulage, this input is the main component of mining costs. How can the impact of the operational aspects on the diesel consumption of haulage operations in surface mines be assessed? There are many studies relating the consumption of fuel trucks to several variables, but a methodology that prioritizes higher-impact variables under each specific condition is not available. Generic models may not apply to all operational settings presented in the mining industry. This study aims to create a method of analysis, identification, and prioritization of variables related to fuel consumption of haul trucks in open pit mines. For this purpose, statistical analysis techniques and mathematical modelling tools using multiple linear regressions will be applied. The model is shown to be suitable because the results generate a good description of the fuel consumption behaviour. In the practical application of the method, the reduction of diesel consumption reached 10%. The implementation requires no large-scale investments or very long deadlines and can be applied to mining haulage operations in other settings. Copyright © 2016 Elsevier Ltd. All rights reserved.

Research of mine water source identification based on LIF technology

NASA Astrophysics Data System (ADS)

Zhou, Mengran; Yan, Pengcheng

2016-09-01

According to the problem that traditional chemical methods to the mine water source identification takes a long time, put forward a method for rapid source identification system of mine water inrush based on the technology of laser induced fluorescence (LIF). Emphatically analyzes the basic principle of LIF technology. The hardware composition of LIF system are analyzed and the related modules were selected. Through the fluorescence experiment with the water samples of coal mine in the LIF system, fluorescence spectra of water samples are got. Traditional water source identification mainly according to the ion concentration representative of the water, but it is hard to analysis the ion concentration of the water from the fluorescence spectra. This paper proposes a simple and practical method of rapid identification of water by fluorescence spectrum, which measure the space distance between unknown water samples and standard samples, and then based on the clustering analysis, the category of the unknown water sample can be get. Water source identification for unknown samples verified the reliability of the LIF system, and solve the problem that the current coal mine can't have a better real-time and online monitoring on water inrush, which is of great significance for coal mine safety in production.

Mining protein function from text using term-based support vector machines

PubMed Central

Rice, Simon B; Nenadic, Goran; Stapley, Benjamin J

2005-01-01

Background Text mining has spurred huge interest in the domain of biology. The goal of the BioCreAtIvE exercise was to evaluate the performance of current text mining systems. We participated in Task 2, which addressed assigning Gene Ontology terms to human proteins and selecting relevant evidence from full-text documents. We approached it as a modified form of the document classification task. We used a supervised machine-learning approach (based on support vector machines) to assign protein function and select passages that support the assignments. As classification features, we used a protein's co-occurring terms that were automatically extracted from documents. Results The results evaluated by curators were modest, and quite variable for different problems: in many cases we have relatively good assignment of GO terms to proteins, but the selected supporting text was typically non-relevant (precision spanning from 3% to 50%). The method appears to work best when a substantial set of relevant documents is obtained, while it works poorly on single documents and/or short passages. The initial results suggest that our approach can also mine annotations from text even when an explicit statement relating a protein to a GO term is absent. Conclusion A machine learning approach to mining protein function predictions from text can yield good performance only if sufficient training data is available, and significant amount of supporting data is used for prediction. The most promising results are for combined document retrieval and GO term assignment, which calls for the integration of methods developed in BioCreAtIvE Task 1 and Task 2. PMID:15960835

Possibilities of surface waters monitoring at mining areas using UAV

NASA Astrophysics Data System (ADS)

Lisiecka, Ewa; Motyka, Barbara; Motyka, Zbigniew; Pierzchała, Łukasz; Szade, Adam

2018-04-01

The selected, remote measurement methods are discussed, useful for determining surface water properties using mobile unmanned aerial platforms (UAV). The possibilities of using this type of solutions in the scope of measuring spatial, physicochemical and biological parameters of both natural and anthropogenic water reservoirs, including flood polders, water-filled pits, settling tanks and mining sinks were analyzed. Methods of remote identification of the process of overgrowing this type of ecosystems with water and coastal plant formations have also been proposed.

Mining Feature of Data Fusion in the Classification of Beer Flavor Information Using E-Tongue and E-Nose

PubMed Central

Men, Hong; Shi, Yan; Fu, Songlin; Jiao, Yanan; Qiao, Yu; Liu, Jingjing

2017-01-01

Multi-sensor data fusion can provide more comprehensive and more accurate analysis results. However, it also brings some redundant information, which is an important issue with respect to finding a feature-mining method for intuitive and efficient analysis. This paper demonstrates a feature-mining method based on variable accumulation to find the best expression form and variables’ behavior affecting beer flavor. First, e-tongue and e-nose were used to gather the taste and olfactory information of beer, respectively. Second, principal component analysis (PCA), genetic algorithm-partial least squares (GA-PLS), and variable importance of projection (VIP) scores were applied to select feature variables of the original fusion set. Finally, the classification models based on support vector machine (SVM), random forests (RF), and extreme learning machine (ELM) were established to evaluate the efficiency of the feature-mining method. The result shows that the feature-mining method based on variable accumulation obtains the main feature affecting beer flavor information, and the best classification performance for the SVM, RF, and ELM models with 96.67%, 94.44%, and 98.33% prediction accuracy, respectively. PMID:28753917

A case study of multi-seam coal mine entry stability analysis with strength reduction method

PubMed Central

Tulu, Ihsan Berk; Esterhuizen, Gabriel S; Klemetti, Ted; Murphy, Michael M.; Sumner, James; Sloan, Michael

2017-01-01

In this paper, the advantage of using numerical models with the strength reduction method (SRM) to evaluate entry stability in complex multiple-seam conditions is demonstrated. A coal mine under variable topography from the Central Appalachian region is used as a case study. At this mine, unexpected roof conditions were encountered during development below previously mined panels. Stress mapping and observation of ground conditions were used to quantify the success of entry support systems in three room-and-pillar panels. Numerical model analyses were initially conducted to estimate the stresses induced by the multiple-seam mining at the locations of the affected entries. The SRM was used to quantify the stability factor of the supported roof of the entries at selected locations. The SRM-calculated stability factors were compared with observations made during the site visits, and the results demonstrate that the SRM adequately identifies the unexpected roof conditions in this complex case. It is concluded that the SRM can be used to effectively evaluate the likely success of roof supports and the stability condition of entries in coal mines. PMID:28239503

A case study of multi-seam coal mine entry stability analysis with strength reduction method.

PubMed

Tulu, Ihsan Berk; Esterhuizen, Gabriel S; Klemetti, Ted; Murphy, Michael M; Sumner, James; Sloan, Michael

2016-03-01

In this paper, the advantage of using numerical models with the strength reduction method (SRM) to evaluate entry stability in complex multiple-seam conditions is demonstrated. A coal mine under variable topography from the Central Appalachian region is used as a case study. At this mine, unexpected roof conditions were encountered during development below previously mined panels. Stress mapping and observation of ground conditions were used to quantify the success of entry support systems in three room-and-pillar panels. Numerical model analyses were initially conducted to estimate the stresses induced by the multiple-seam mining at the locations of the affected entries. The SRM was used to quantify the stability factor of the supported roof of the entries at selected locations. The SRM-calculated stability factors were compared with observations made during the site visits, and the results demonstrate that the SRM adequately identifies the unexpected roof conditions in this complex case. It is concluded that the SRM can be used to effectively evaluate the likely success of roof supports and the stability condition of entries in coal mines.

Ultrasound-assisted extraction for total sulphur measurement in mine tailings.

PubMed

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

2012-10-15

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. Copyright © 2012 Elsevier B.V. All rights reserved.

International SUSMIN-project aims at sustainable gold mining in EU

NASA Astrophysics Data System (ADS)

Backnäs, Soile; Neitola, Raisa; Turunen, Kaisa; Lima, Alexandre; Fiúza, António; Szlachta, Malgorzata; Wójtowicz, Patryk; Maftei, Raluca; Munteanu, Marian; Alakangas, Lena; Baciu, Calin; Fernández, Dámaris

2015-04-01

Although the gold demand has been constantly increasing in past years, the commodity findings have been decreasing and the extraction of gold has complicated due to increasing complexity and decreasing grade of the ores. Additionally, even gold mining could increase economical development, it has also challenges in eco-efficiency and extraction methods (e.g. cyanide). Thus, the novel energy and resource-efficient methods and technologies for mineral processing should be developed to concentrate selectively different gold bearing minerals. Furthermore, technologies for efficient treatment of mine waters, sustainable management of wastes, and methods to diminish environmental and social impacts of mining are needed. These problems will be addressed by the three year long project SUSMIN. The SUSMIN-project identifies and evaluates environmental impacts and economical challenges of gold mining within EU. The objective of the project is to increase the transnational cooperation and to support environmentally, socially and economically sustainable viable gold production. The focus is to develop and test geophysical techniques for gold exploration, eco-efficient ore beneficiation methods and alternatives for cyanide leaching. Additionally, the research will improve treatment methods for mine waters by the development and testing of advanced adsorbents. The research on socio-economic issues pursues to develop tools for enhancing the mechanisms of the corporate social responsibility as well as community engagement and management of the relations with the stakeholders. Moreover, with the environmental risk assessment and better knowledge of the geochemistry and long-term transformation of the contaminants in mining wastes and mine waters, the mining companies are able to predict and prevent the impacts to the surrounding environment, resulting in an improved environmental management solution. The SUSMIN consortium led by Geological Survey of Finland (GTK) includes seven research partners from six EU member states Finland, Sweden, Portugal, Romania, Poland and Ireland. Additionally eight globally on mining industry working industry partners will contribute in the SUSMIN consortium, so implementation of results from the project will translate into direct and significant economic benefits.

An Evaluation of Practical Applicability of Multi-Assortment Production Break-Even Analysis based on Mining Companies

NASA Astrophysics Data System (ADS)

Fuksa, Dariusz; Trzaskuś-Żak, Beata; Gałaś, Zdzisław; Utrata, Arkadiusz

2017-03-01

In the practice of mining companies, the vast majority of them produce more than one product. The analysis of the break-even, which is referred to as CVP (Cost-Volume-Profit) analysis (Wilkinson, 2005; Czopek, 2003) in their case is significantly constricted, given the necessity to include multi-assortment structure in the analysis, which may have more than 20 types of assortments (depending on the grain size) in their offer, as in the case of open-pit mines. The article presents methods of evaluation of break-even (volume and value) for both a single-assortment production and a multi-assortment production. The complexity of problem of break-even evaluation for multi-assortment production has resulted in formation of many methods, and, simultaneously, various approaches to its analysis, especially differences in accounting fixed costs, which may be either totally accounted for among particular assortments, relating to the whole company or partially accounted for among particular assortments and partially relating to the company, as a whole. The evaluation of the chosen methods of break-even analysis, given the availability of data, was based on two examples of mining companies: an open-pit mine of rock materials and an underground hard coal mine. The selection of methods was set by the available data provided by the companies. The data for the analysis comes from internal documentation of the mines - financial statements, breakdowns and cost calculations.

Selection of Most Proper Blasting Pattern in Mines Using Linear Assignment Method: Sungun Copper Mine / Wybór Najodpowiedniejszego Schematu Prowadzenia Prac Strzałowych W Kopalni Miedzi Sungun Z Użyciem Metody Przyporządkowania Liniowego

NASA Astrophysics Data System (ADS)

Yari, Mojtaba; Bagherpour, Raheb; Jamali, Saeed; Asadi, Fatemeh

2015-03-01

One of the most important operations in mining is blasting. Improper design of blasting pattern will cause technical and safety problems. Considering impact of results of blasting on next steps of mining, correct pattern selection needs a great cautiousness. In selecting of blasting pattern, technical, economical and safety aspects should be considered. Thus, most appropriate pattern selection can be defined as a Multi Attribute Decision Making (MADM) problem. Linear assignment method is one of the very applicable methods in decision making problems. In this paper, this method was used for the first time to evaluate blasting patterns in mine. In this ranking, safety and technical parameters have been considered to evaluate blasting patterns. Finally, blasting pattern with burden of 3.5 m, spacing of 4.5 m, stemming of 3.8 m and hole length of 12.1 m has been presented as the most suitable pattern obtained from linear assignment model for Sungun Copper Mine. Jedną z najpoważniejszych operacji wykonywanych w ramach prac wydobywczych są prace strzałowe. Niewłaściwe rozplanowanie prac powoduje problemy techniczne i stanowi zagrożenie dla bezpieczeństwa. Z uwagi na potencjalne skutki prac strzałowych i ich wpływ na kolejne etapy procesu wydobycia, właściwe rozplanowanie tych prac wymaga wielkiej uwagi i uwzględnienia kwestii technicznych, ekonomicznych a także bezpieczeństwa pracy. Dlatego też wybór najodpowiedniejszego schematu prowadzenia prac strzałowych zdefiniować można jako wieloatrybutowy problem decyzyjny (MADM - Multi Attribute Decision Making). Metoda przyporządkowania liniowego jest jedną z metod mających zastosowanie w rozwiązywaniu problemów decyzyjnych. W obecnej pracy metoda ta wykorzystana została po raz pierwszy do oceny schematów prowadzenia prac strzałowych w kopalni, w procedurze uwzględniono parametry techniczne oraz parametry związane z bezpieczeństwem. Zaprezentowano wybrany przy pomocy metody najkorzystniejszy schemat prowadzenia prac strzałowych w kopalni miedzi Sungun: nadkład 3.5m, odległości pomiędzy otworami 4.5 m, zastosowana przybitka 3.8 m, długość otworu strzałowego 12.1 m.

Weighting Criteria and Prioritizing of Heat stress indices in surface mining using a Delphi Technique and Fuzzy AHP-TOPSIS Method.

PubMed

Asghari, Mehdi; Nassiri, Parvin; Monazzam, Mohammad Reza; Golbabaei, Farideh; Arabalibeik, Hossein; Shamsipour, Aliakbar; Allahverdy, Armin

2017-01-01

Heat stress as a physical harmful agent can increase the risk of health and safety problems in different workplaces such as mining. Although there are different indices to assess the heat stress imposed on workers, choosing the best index for a specific workplace is so important. Since various criteria affect an index applicability, extracting the most effective ones and determining their weights help to prioritize the existing indices and select the optimal index. In order to achieve this aim, present study compared some heat stress indices using effective methods. The viewpoints of occupational health experts and the qualitative Delphi methods were used to extract the most important criteria. Then, the weights of 11 selected criteria were determined by Fuzzy Analytic Hierarchy Process. Finally, fuzzy TOPSIS technique was applied for choosing the most suitable heat stress index. According to result, simplicity, reliability, being low cost, and comprehensiveness were the most determinative criteria for a heat stress index. Based on these criteria and their weights, the existing indices were prioritized. Eventually, wet bulb glob temperature appropriated the first priority and it was proposed as an applicable index for evaluating the heat stress at outdoor hot environments such as surface mines. The use of these strong methods allows introducing the most simple, precise, and applicable tool for evaluation the heat stress in hot environments. It seems that WBGT acts as an appropriate index for assessing the heat stress in mining activities at outdoors.

Ontology-guided data preparation for discovering genotype-phenotype relationships.

PubMed

Coulet, Adrien; Smaïl-Tabbone, Malika; Benlian, Pascale; Napoli, Amedeo; Devignes, Marie-Dominique

2008-04-25

Complexity and amount of post-genomic data constitute two major factors limiting the application of Knowledge Discovery in Databases (KDD) methods in life sciences. Bio-ontologies may nowadays play key roles in knowledge discovery in life science providing semantics to data and to extracted units, by taking advantage of the progress of Semantic Web technologies concerning the understanding and availability of tools for knowledge representation, extraction, and reasoning. This paper presents a method that exploits bio-ontologies for guiding data selection within the preparation step of the KDD process. We propose three scenarios in which domain knowledge and ontology elements such as subsumption, properties, class descriptions, are taken into account for data selection, before the data mining step. Each of these scenarios is illustrated within a case-study relative to the search of genotype-phenotype relationships in a familial hypercholesterolemia dataset. The guiding of data selection based on domain knowledge is analysed and shows a direct influence on the volume and significance of the data mining results. The method proposed in this paper is an efficient alternative to numerical methods for data selection based on domain knowledge. In turn, the results of this study may be reused in ontology modelling and data integration.

Reconstructing disturbance history for an intensively mined region by time-series analysis of Landsat imagery.

PubMed

Li, Jing; Zipper, Carl E; Donovan, Patricia F; Wynne, Randolph H; Oliphant, Adam J

2015-09-01

Surface mining disturbances have attracted attention globally due to extensive influence on topography, land use, ecosystems, and human populations in mineral-rich regions. We analyzed a time series of Landsat satellite imagery to produce a 28-year disturbance history for surface coal mining in a segment of eastern USA's central Appalachian coalfield, southwestern Virginia. The method was developed and applied as a three-step sequence: vegetation index selection, persistent vegetation identification, and mined-land delineation by year of disturbance. The overall classification accuracy and kappa coefficient were 0.9350 and 0.9252, respectively. Most surface coal mines were identified correctly by location and by time of initial disturbance. More than 8 % of southwestern Virginia's >4000-km(2) coalfield area was disturbed by surface coal mining over the 28-year period. Approximately 19.5 % of the Appalachian coalfield surface within the most intensively mined county (Wise County) has been disturbed by mining. Mining disturbances expanded steadily and progressively over the study period. Information generated can be applied to gain further insight concerning mining influences on ecosystems and other essential environmental features.

Selecting Proper Plant Species for Mine Reclamation Using Fuzzy AHP Approach (Case Study: Chadormaloo Iron Mine of Iran)

NASA Astrophysics Data System (ADS)

Ebrahimabadi, Arash

2016-12-01

This paper describes an effective approach to select suitable plant species for reclamation of mined lands in Chadormaloo iron mine which is located in central part of Iran, near the city of Bafgh in Yazd province. After mine's total reserves are excavated, the mine requires to be permanently closed and reclaimed. Mine reclamation and post-mining land-use are the main issues in the phase of mine closure. In general, among various scenarios for mine reclamation process, i.e. planting, agriculture, forestry, residency, tourist attraction, etc., planting is the oldest and commonly-used technology for the reclamation of lands damaged by mining activities. Planting and vegetation play a major role in restoring productivity, ecosystem stability and biological diversity to degraded areas, therefore the main goal of this research work is to choose proper and suitable plants compatible with the conditions of Chadormaloo mined area, providing consistent conditions for future use. To ensure the sustainability of the reclaimed landscape, the most suitable plant species adapted to the mine conditions are selected. Plant species selection is a Multi Criteria Decision Making (MCDM) problem. In this paper, a fuzzy MCDM technique, namely Fuzzy Analytic Hierarchy Process (FAHP) is developed to assist chadormaloo iron mine managers and designers in the process of plant type selection for reclamation of the mine under fuzzy environment where the vagueness and uncertainty are taken into account with linguistic variables parameterized by triangular fuzzy numbers. The results achieved from using FAHP approach demonstrate that the most proper plant species are ranked as Artemisia sieberi, Salsola yazdiana, Halophytes types, and Zygophyllum, respectively for reclamation of Chadormaloo iron mine.

Text mining approach to predict hospital admissions using early medical records from the emergency department.

PubMed

Lucini, Filipe R; S Fogliatto, Flavio; C da Silveira, Giovani J; L Neyeloff, Jeruza; Anzanello, Michel J; de S Kuchenbecker, Ricardo; D Schaan, Beatriz

2017-04-01

Emergency department (ED) overcrowding is a serious issue for hospitals. Early information on short-term inward bed demand from patients receiving care at the ED may reduce the overcrowding problem, and optimize the use of hospital resources. In this study, we use text mining methods to process data from early ED patient records using the SOAP framework, and predict future hospitalizations and discharges. We try different approaches for pre-processing of text records and to predict hospitalization. Sets-of-words are obtained via binary representation, term frequency, and term frequency-inverse document frequency. Unigrams, bigrams and trigrams are tested for feature formation. Feature selection is based on χ 2 and F-score metrics. In the prediction module, eight text mining methods are tested: Decision Tree, Random Forest, Extremely Randomized Tree, AdaBoost, Logistic Regression, Multinomial Naïve Bayes, Support Vector Machine (Kernel linear) and Nu-Support Vector Machine (Kernel linear). Prediction performance is evaluated by F1-scores. Precision and Recall values are also informed for all text mining methods tested. Nu-Support Vector Machine was the text mining method with the best overall performance. Its average F1-score in predicting hospitalization was 77.70%, with a standard deviation (SD) of 0.66%. The method could be used to manage daily routines in EDs such as capacity planning and resource allocation. Text mining could provide valuable information and facilitate decision-making by inward bed management teams. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

Improve Data Mining and Knowledge Discovery Through the Use of MatLab

NASA Technical Reports Server (NTRS)

Shaykhian, Gholam Ali; Martin, Dawn (Elliott); Beil, Robert

2011-01-01

Data mining is widely used to mine business, engineering, and scientific data. Data mining uses pattern based queries, searches, or other analyses of one or more electronic databases/datasets in order to discover or locate a predictive pattern or anomaly indicative of system failure, criminal or terrorist activity, etc. There are various algorithms, techniques and methods used to mine data; including neural networks, genetic algorithms, decision trees, nearest neighbor method, rule induction association analysis, slice and dice, segmentation, and clustering. These algorithms, techniques and methods used to detect patterns in a dataset, have been used in the development of numerous open source and commercially available products and technology for data mining. Data mining is best realized when latent information in a large quantity of data stored is discovered. No one technique solves all data mining problems; challenges are to select algorithms or methods appropriate to strengthen data/text mining and trending within given datasets. In recent years, throughout industry, academia and government agencies, thousands of data systems have been designed and tailored to serve specific engineering and business needs. Many of these systems use databases with relational algebra and structured query language to categorize and retrieve data. In these systems, data analyses are limited and require prior explicit knowledge of metadata and database relations; lacking exploratory data mining and discoveries of latent information. This presentation introduces MatLab(R) (MATrix LABoratory), an engineering and scientific data analyses tool to perform data mining. MatLab was originally intended to perform purely numerical calculations (a glorified calculator). Now, in addition to having hundreds of mathematical functions, it is a programming language with hundreds built in standard functions and numerous available toolboxes. MatLab's ease of data processing, visualization and its enormous availability of built in functionalities and toolboxes make it suitable to perform numerical computations and simulations as well as a data mining tool. Engineers and scientists can take advantage of the readily available functions/toolboxes to gain wider insight in their perspective data mining experiments.

Improve Data Mining and Knowledge Discovery through the use of MatLab

NASA Technical Reports Server (NTRS)

Shaykahian, Gholan Ali; Martin, Dawn Elliott; Beil, Robert

2011-01-01

Data mining is widely used to mine business, engineering, and scientific data. Data mining uses pattern based queries, searches, or other analyses of one or more electronic databases/datasets in order to discover or locate a predictive pattern or anomaly indicative of system failure, criminal or terrorist activity, etc. There are various algorithms, techniques and methods used to mine data; including neural networks, genetic algorithms, decision trees, nearest neighbor method, rule induction association analysis, slice and dice, segmentation, and clustering. These algorithms, techniques and methods used to detect patterns in a dataset, have been used in the development of numerous open source and commercially available products and technology for data mining. Data mining is best realized when latent information in a large quantity of data stored is discovered. No one technique solves all data mining problems; challenges are to select algorithms or methods appropriate to strengthen data/text mining and trending within given datasets. In recent years, throughout industry, academia and government agencies, thousands of data systems have been designed and tailored to serve specific engineering and business needs. Many of these systems use databases with relational algebra and structured query language to categorize and retrieve data. In these systems, data analyses are limited and require prior explicit knowledge of metadata and database relations; lacking exploratory data mining and discoveries of latent information. This presentation introduces MatLab(TradeMark)(MATrix LABoratory), an engineering and scientific data analyses tool to perform data mining. MatLab was originally intended to perform purely numerical calculations (a glorified calculator). Now, in addition to having hundreds of mathematical functions, it is a programming language with hundreds built in standard functions and numerous available toolboxes. MatLab's ease of data processing, visualization and its enormous availability of built in functionalities and toolboxes make it suitable to perform numerical computations and simulations as well as a data mining tool. Engineers and scientists can take advantage of the readily available functions/toolboxes to gain wider insight in their perspective data mining experiments.

Application of Three Existing Stope Boundary Optimisation Methods in an Operating Underground Mine

NASA Astrophysics Data System (ADS)

Erdogan, Gamze; Yavuz, Mahmut

2017-12-01

The underground mine planning and design optimisation process have received little attention because of complexity and variability of problems in underground mines. Although a number of optimisation studies and software tools are available and some of them, in special, have been implemented effectively to determine the ultimate-pit limits in an open pit mine, there is still a lack of studies for optimisation of ultimate stope boundaries in underground mines. The proposed approaches for this purpose aim at maximizing the economic profit by selecting the best possible layout under operational, technical and physical constraints. In this paper, the existing three heuristic techniques including Floating Stope Algorithm, Maximum Value Algorithm and Mineable Shape Optimiser (MSO) are examined for optimisation of stope layout in a case study. Each technique is assessed in terms of applicability, algorithm capabilities and limitations considering the underground mine planning challenges. Finally, the results are evaluated and compared.

Patent data mining method and apparatus

DOEpatents

Boyack, Kevin W.; Grafe, V. Gerald; Johnson, David K.; Wylie, Brian N.

2002-01-01

A method of data mining represents related patents in a multidimensional space. Distance between patents in the multidimensional space corresponds to the extent of relationship between the patents. The relationship between pairings of patents can be expressed based on weighted combinations of several predicates. The user can select portions of the space to perceive. The user also can interact with and control the communication of the space, focusing attention on aspects of the space of most interest. The multidimensional spatial representation allows more ready comprehension of the structure of the relationships among the patents.

Method of data mining including determining multidimensional coordinates of each item using a predetermined scalar similarity value for each item pair

DOEpatents

Meyers, Charles E.; Davidson, George S.; Johnson, David K.; Hendrickson, Bruce A.; Wylie, Brian N.

1999-01-01

A method of data mining represents related items in a multidimensional space. Distance between items in the multidimensional space corresponds to the extent of relationship between the items. The user can select portions of the space to perceive. The user also can interact with and control the communication of the space, focusing attention on aspects of the space of most interest. The multidimensional spatial representation allows more ready comprehension of the structure of the relationships among the items.

Emergency Braking of a Mine Hoist in the Context of the Braking System Selection

NASA Astrophysics Data System (ADS)

Wolny, Stanisław

2017-03-01

The paper addresses the selected aspects of the dynamic behaviour of mine hoists during the emergency braking phase. Basing on the model of the hoist and supported by theoretical backgrounds provided by the author (Wolny, 2016), analytical formulas are derived to determine the parameters of the braking system such that during an emergency braking it should guarantee that: - the maximal loading of the hoisting ropes should not exceed the rope breaking force, - deceleration of the conveyances being stopped should not exceed the admissible levels Results of the dynamic analysis of the mine hoist behaviour during an emergency braking phase summarised in this study can be utilised to support the design of conveyance and rope attachments by the fatigue endurance methods, with an aim to adapt it to the specified operational parameters of the hoisting installation (Eurokod 3).

[Characteristics of acupoint selection of acupuncture-moxibustion for vertigo in history: a data mining research].

PubMed

Li, Xiang; Shou, Yi-Xia; Ren, Yu-Lan; Liang, Fan-Rong

2014-05-01

The data mining technique is adopted to analyze characteristics and rules of acupoint and meridian selection of acupuncture-moxibustion for treatment of vertigo at different time periods in the ancient. The data is collected from literature regarding acupuncture-moxibustion from the pre-Qin period to the end of Qing Dynasty, so as to establish a clinical literature database of ancient acupuncture-moxibustion for treatment of vertigo. Data mining method is applied to analyze the commonly used meridians, acupoints and special acupoints in different dynasties, also possible rules are explored. Totally 82 pieces of prescription of acupuncture-moxibustion for treatment of vertigo are included. In the history the leading selection of acupoitns are Fengchi (GB 20), Hegu (LI 4), Shangxing (GV 23) and Jiexi (ST 41) while that of meridians are mainly three yang meridians of foot and the Governor Vessel, especially the acupoints on the Bladder Meridian of foot yangming had the highest utilization rate, accounting for 23.04%. The acupoint selection is characterized by special acupoint, accounting for 80.6%, among which the crossing points are the most common choice. Distal-proximal acupoints combination is the most frequent method. The results indicate that the ancient acupuncture-moxibustion for treatment of vertigo focused on acupoints in the yang meridians, and the specific acupoints play an essential role in prescription; also the principle of syndrome differentiation and selecting acupoints along the meridians could be seen.

Feature selection method based on multi-fractal dimension and harmony search algorithm and its application

NASA Astrophysics Data System (ADS)

Zhang, Chen; Ni, Zhiwei; Ni, Liping; Tang, Na

2016-10-01

Feature selection is an important method of data preprocessing in data mining. In this paper, a novel feature selection method based on multi-fractal dimension and harmony search algorithm is proposed. Multi-fractal dimension is adopted as the evaluation criterion of feature subset, which can determine the number of selected features. An improved harmony search algorithm is used as the search strategy to improve the efficiency of feature selection. The performance of the proposed method is compared with that of other feature selection algorithms on UCI data-sets. Besides, the proposed method is also used to predict the daily average concentration of PM2.5 in China. Experimental results show that the proposed method can obtain competitive results in terms of both prediction accuracy and the number of selected features.

Method for inhibiting oxidation of metal sulfide-containing material

DOEpatents

Elsetinow, Alicia; Borda, Michael J.; Schoonen, Martin A.; Strongin, Daniel R.

2006-12-26

The present invention provides means for inhibiting the oxidation of a metal sulfide-containing material, such as ore mine waste rock or metal sulfide taiulings, by coating the metal sulfide-containing material with an oxidation-inhibiting two-tail lipid coating (12) thereon, thereby inhibiting oxidation of the metal sulfide-containing material in acid mine drainage conditions. The lipids may be selected from phospholipids, sphingolipids, glycolipids and combinations thereof.

Optimal selection of biochars for remediating metals ...

EPA Pesticide Factsheets

Approximately 500,000 abandoned mines across the U.S. pose a considerable, pervasive risk to human health and the environment due to possible exposure to the residuals of heavy metal extraction. Historically, a variety of chemical and biological methods have been used to reduce the bioavailability of the metals at mine sites. Biochar with its potential to complex and immobilize heavy metals, is an emerging alternative for reducing bioavailability. Furthermore, biochar has been reported to improve soil conditions for plant growth and can be used for promoting the establishment of a soil-stabilizing native plant community to reduce offsite movement of metal-laden waste materials. Because biochar properties depend upon feedstock selection, pyrolysis production conditions, and activation procedures used, they can be designed to meet specific remediation needs. As a result biochar with specific properties can be produced to correspond to specific soil remediation situations. However, techniques are needed to optimally match biochar characteristics with metals contaminated soils to effectively reduce metal bioavailability. Here we present experimental results used to develop a generalized method for evaluating the ability of biochar to reduce metals in mine spoil soil from an abandoned Cu and Zn mine. Thirty-eight biochars were produced from approximately 20 different feedstocks and produced via slow pyrolysis or gasification, and were allowed to react with a f

An AK-LDMeans algorithm based on image clustering

NASA Astrophysics Data System (ADS)

Chen, Huimin; Li, Xingwei; Zhang, Yongbin; Chen, Nan

2018-03-01

Clustering is an effective analytical technique for handling unmarked data for value mining. Its ultimate goal is to mark unclassified data quickly and correctly. We use the roadmap for the current image processing as the experimental background. In this paper, we propose an AK-LDMeans algorithm to automatically lock the K value by designing the Kcost fold line, and then use the long-distance high-density method to select the clustering centers to further replace the traditional initial clustering center selection method, which further improves the efficiency and accuracy of the traditional K-Means Algorithm. And the experimental results are compared with the current clustering algorithm and the results are obtained. The algorithm can provide effective reference value in the fields of image processing, machine vision and data mining.

Near surface IP investigations: Four case studies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hearst, R.B.; Morris, W.A.; Clark, M.A.

1995-12-31

The use of the Induced Polarisation (IP) method of geophysical surveying for near surface site investigations is gaining acceptance within the geophysical community. In this study the IP method is evaluated as a tool for the delineation of ground water resources; contamination plume detection in a lateritic horizon; and acid mine drainage leak detection from decommissioned mine tailings. A time domain IP system was selected for this study primarily for the flexibility in the selection and setting of receiver time windows and diagnostic characteristics attributed to submitting the data to Cole-Cole analysis. Analysis of the acquired data in conjunction withmore » available borehole and geological information illustrates the effectiveness and usefulness of the survey method for solving near surface problems. In all of the locations tested, it was found that with a properly designed IP survey it was possible to resolve the target and/or related structures.« less

Comparison of different static methods for assessment of AMD generation potential in mining waste dumps in the Muteh Gold Mines, Iran.

PubMed

Mohammadi, Zohreh; Modabberi, Soroush; Jafari, Mohammad Reza; Ajayebi, Kimia Sadat

2015-06-01

Acid mine drainage (AMD) gives rise to several problems in sulfide-bearing mineral deposits whether in an ore body or in the mining wastes and tailings. Hence, several methods and parameters have been proposed to evaluate the acid-producing and acid-neutralizing potential of a material. This research compares common static methods for evaluation of acid-production potential of mining wastes in the Muteh gold mines by using 62 samples taken from six waste dumps around Senjedeh and Chah-Khatoun mines. According to a detailed mineralogical study, the waste materials are composed of mica-schist and quartz veins with a high amount of pyrite and are supposed to be susceptible to acid production, and upon a rainfall, they release acid drainage. All parameters introduced in different methods were calculated and compared in this research in order to predict the acid-generating and neutralization potential, including APP, NNP, MPA, NPR, and NAGpH. Based on the analytical results and calculation of different parameters, all methods are in a general consensus that DWS-02 and DWS-03 waste dumps are acid-forming which is clearly attributed to high content of pyrite in samples. DWS-04 is considered as non-acid forming in all methods except method 8 which is uncertain about its acid-forming potential and method 7 which considers a low potential for it. DWC-01 is acid-forming based on all methods except 8, 9, 10, and 11 which are also uncertain about its potential. The methods used are not reached to a compromise on DWS-01 and DWC-02 waste dumps. It is supposed that method 7 gives the conservationist results in all cases. Method 8 is unable to decide on some cases. It is recommended to use and rely on results provided by methods 1, 2, 3, and 12 for taking decisions for further studies. Therefore, according to the static tests used, the aforementioned criteria in selected methods can be used with much confidence as a rule of thumb estimation.

Methodology of selecting dozers for lignite open pit mines in Serbia

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stojanovic, D.; Ignjatovic, D.; Kovacevic, S.

1996-12-31

Apart from the main production processes (coal and overburden mining, rail conveyors transportation and storage of excavated masses) performed by great-capacity mechanization at open pit mines, numerous and different auxiliary works, that often have crucial influence on both the work efficiency of main equipment and the maintenance of optimum technical conditions of machines and plants covering technological system of open pit, are present. Successful realization of work indispensably requires a proper and adequate selection of auxiliary machines according to their type quantity, capacity, power etc. thus highly respecting specific conditions existing at each and every open pit mine. A dozermore » is certainly the most important and representative auxiliary machine at single open pit mine. It is widely used in numerous works that, in fact, are preconditions for successful work of the main mechanization and consequently the very selection of a dozer ranges among the most important operations when selecting mechanization. This paper presents the methodology of dozers selection when lignite open pit mines are concerned. A mathematical model defining the volume of work required for dozers to perform at open pit mines and consequently the number of necessary dozers was designed. The model underwent testing in practice at big open pit mines and can be used in design of future open pits mines.« less

Developing image processing meta-algorithms with data mining of multiple metrics.

PubMed

Leung, Kelvin; Cunha, Alexandre; Toga, A W; Parker, D Stott

2014-01-01

People often use multiple metrics in image processing, but here we take a novel approach of mining the values of batteries of metrics on image processing results. We present a case for extending image processing methods to incorporate automated mining of multiple image metric values. Here by a metric we mean any image similarity or distance measure, and in this paper we consider intensity-based and statistical image measures and focus on registration as an image processing problem. We show how it is possible to develop meta-algorithms that evaluate different image processing results with a number of different metrics and mine the results in an automated fashion so as to select the best results. We show that the mining of multiple metrics offers a variety of potential benefits for many image processing problems, including improved robustness and validation.

Analysis of conditions and the concept of multidirectional revitalization of the dolomite quarry in Siewierz

NASA Astrophysics Data System (ADS)

Pawełczyk, Katarzyna

2018-01-01

The development of mining of rock raw materials in Poland has significantly contributed to economic growth and the quality of life of local communities. However, mining activity, besides a number of positive effects, also implies broadly understood changes in the environment and the formation of brownfields. Reclamation and redevelopment of post-industrial areas, and especially post-mining areas, is currently a huge environmental and socio-economic challenge. Revitalization of post-mining areas is particularly important for small towns and municipalities, where mining was one of the main pillars of development and prosperity. An example of such a municipality is Siewierz in Silesian Voivodship. In the paper analysis the conditions have been conducted and the concept of revitalization of dolomite quarry Górnicze Zakłady Dolomitowe S.A. has been proposed. The AHP method has been used to analyse and select the optimal method of revitalization. As a result of the analysis, the concept of multidirectional revitalization with socially, economically and environmentally beneficial functions has been created, maximizing the potential of the quarry.

Asteroid mining

NASA Astrophysics Data System (ADS)

Gertsch, Richard E.

The earliest studies of asteroid mining proposed retrieving a main belt asteroid. Because of the very long travel times to the main asteroid belt, attention has shifted to the asteroids whose orbits bring them fairly close to the Earth. In these schemes, the asteroids would be bagged and then processed during the return trip, with the asteroid itself providing the reaction mass to propel the mission homeward. A mission to one of these near-Earth asteroids would be shorter, involve less weight, and require a somewhat lower change in velocity. Since these asteroids apparently contain a wide range of potentially useful materials, our study group considered only them. The topics covered include asteroid materials and properties, asteroid mission selection, manned versus automated missions, mining in zero gravity, and a conceptual mining method.

Asteroid mining

NASA Technical Reports Server (NTRS)

Gertsch, Richard E.

1992-01-01

The earliest studies of asteroid mining proposed retrieving a main belt asteroid. Because of the very long travel times to the main asteroid belt, attention has shifted to the asteroids whose orbits bring them fairly close to the Earth. In these schemes, the asteroids would be bagged and then processed during the return trip, with the asteroid itself providing the reaction mass to propel the mission homeward. A mission to one of these near-Earth asteroids would be shorter, involve less weight, and require a somewhat lower change in velocity. Since these asteroids apparently contain a wide range of potentially useful materials, our study group considered only them. The topics covered include asteroid materials and properties, asteroid mission selection, manned versus automated missions, mining in zero gravity, and a conceptual mining method.

Collective feature selection to identify crucial epistatic variants.

PubMed

Verma, Shefali S; Lucas, Anastasia; Zhang, Xinyuan; Veturi, Yogasudha; Dudek, Scott; Li, Binglan; Li, Ruowang; Urbanowicz, Ryan; Moore, Jason H; Kim, Dokyoon; Ritchie, Marylyn D

2018-01-01

Machine learning methods have gained popularity and practicality in identifying linear and non-linear effects of variants associated with complex disease/traits. Detection of epistatic interactions still remains a challenge due to the large number of features and relatively small sample size as input, thus leading to the so-called "short fat data" problem. The efficiency of machine learning methods can be increased by limiting the number of input features. Thus, it is very important to perform variable selection before searching for epistasis. Many methods have been evaluated and proposed to perform feature selection, but no single method works best in all scenarios. We demonstrate this by conducting two separate simulation analyses to evaluate the proposed collective feature selection approach. Through our simulation study we propose a collective feature selection approach to select features that are in the "union" of the best performing methods. We explored various parametric, non-parametric, and data mining approaches to perform feature selection. We choose our top performing methods to select the union of the resulting variables based on a user-defined percentage of variants selected from each method to take to downstream analysis. Our simulation analysis shows that non-parametric data mining approaches, such as MDR, may work best under one simulation criteria for the high effect size (penetrance) datasets, while non-parametric methods designed for feature selection, such as Ranger and Gradient boosting, work best under other simulation criteria. Thus, using a collective approach proves to be more beneficial for selecting variables with epistatic effects also in low effect size datasets and different genetic architectures. Following this, we applied our proposed collective feature selection approach to select the top 1% of variables to identify potential interacting variables associated with Body Mass Index (BMI) in ~ 44,000 samples obtained from Geisinger's MyCode Community Health Initiative (on behalf of DiscovEHR collaboration). In this study, we were able to show that selecting variables using a collective feature selection approach could help in selecting true positive epistatic variables more frequently than applying any single method for feature selection via simulation studies. We were able to demonstrate the effectiveness of collective feature selection along with a comparison of many methods in our simulation analysis. We also applied our method to identify non-linear networks associated with obesity.

A study of unstable rock failures using finite difference and discrete element methods

NASA Astrophysics Data System (ADS)

Garvey, Ryan J.

Case histories in mining have long described pillars or faces of rock failing violently with an accompanying rapid ejection of debris and broken material into the working areas of the mine. These unstable failures have resulted in large losses of life and collapses of entire mine panels. Modern mining operations take significant steps to reduce the likelihood of unstable failure, however eliminating their occurrence is difficult in practice. Researchers over several decades have supplemented studies of unstable failures through the application of various numerical methods. The direction of the current research is to extend these methods and to develop improved numerical tools with which to study unstable failures in underground mining layouts. An extensive study is first conducted on the expression of unstable failure in discrete element and finite difference methods. Simulated uniaxial compressive strength tests are run on brittle rock specimens. Stable or unstable loading conditions are applied onto the brittle specimens by a pair of elastic platens with ranging stiffnesses. Determinations of instability are established through stress and strain histories taken for the specimen and the system. Additional numerical tools are then developed for the finite difference method to analyze unstable failure in larger mine models. Instability identifiers are established for assessing the locations and relative magnitudes of unstable failure through measures of rapid dynamic motion. An energy balance is developed which calculates the excess energy released as a result of unstable equilibria in rock systems. These tools are validated through uniaxial and triaxial compressive strength tests and are extended to models of coal pillars and a simplified mining layout. The results of the finite difference simulations reveal that the instability identifiers and excess energy calculations provide a generalized methodology for assessing unstable failures within potentially complex mine models. These combined numerical tools may be applied in future studies to design primary and secondary supports in bump-prone conditions, evaluate retreat mining cut sequences, asses pillar de-stressing techniques, or perform backanalyses on unstable failures in select mining layouts.

Toxic element mobility assessment and modeling for regional geo-scientific survey to support Risk Assessment in a European Union context

NASA Astrophysics Data System (ADS)

Abdaal, Ahmed; Jordan, Gyozo; Bartha, Andras; Fugedi, Ubul

2013-04-01

The Mine Waste Directive 2006/21/EC requires the risk-based inventory of all mine waste sites in Europe. The geochemical documentation concerning inert classification and ranking of the mine wastes requires detailed field study and laboratory testing and analyses of waste material to assess the Acid Mine Drainage potential and toxic element mobility. The procedure applied in this study used a multi-level decision support scheme including: 1) expert judgment, 2) data review, 3) representative field sampling and laboratory analysis of formations listed in the Inert Mining Waste List, and 4) requesting available laboratory analysis data from selected operating mines. Based on expert judgment, the listed formations were classified into three categories. A: inert B: probably inert, but has to be checked, C: probably not inert, has to be examined. This paper discusses the heavy metal contamination risk assessment (RA) in leached quarry-mine waste sites in Hungary. In total 34 mine waste sites (including tailing lagoons and heaps of both abandoned mines and active quarries) have been selected for scientific testing using the EU Pre-selection Protocol. Over 93 field samples have been collected from the mine sites including Ore (Andesite and Ryolite), Coal (Lignite, black and brown coals), Peat, Alginite, Bauxite, Clay and Limestone. Laboratory analyses of the total toxic element content (aqua regia extraction), the mobile toxic element content (deionized water leaching) and the analysis of different forms of sulfur (sulfuric acid potential) ) on the base of Hungarian GKM Decree No. 14/2008. (IV. 3) concerning mining waste management. A detailed geochemical study together with spatial analysis and GIS has been performed to derive a geochemically sound contamination RA of the mine waste sites. Key parameters such as heavy metal and sulphur content, in addition to the distance to the nearest surface and ground water bodies, or to sensitive receptors such as settlements and protected areas are calculated and statistically evaluated using STATGRAPHICS® in order to calibrate the RA methods. Results show that some of the waste rock materials assumed to be inert were found non/inert. Thus, regional RA needs more spatial and petrological examination with special care to rock and mineral deposit genetics.

Data mining and computationally intensive methods: summary of Group 7 contributions to Genetic Analysis Workshop 13.

PubMed

Costello, Tracy J; Falk, Catherine T; Ye, Kenny Q

2003-01-01

The Framingham Heart Study data, as well as a related simulated data set, were generously provided to the participants of the Genetic Analysis Workshop 13 in order that newly developed and emerging statistical methodologies could be tested on that well-characterized data set. The impetus driving the development of novel methods is to elucidate the contributions of genes, environment, and interactions between and among them, as well as to allow comparison between and validation of methods. The seven papers that comprise this group used data-mining methodologies (tree-based methods, neural networks, discriminant analysis, and Bayesian variable selection) in an attempt to identify the underlying genetics of cardiovascular disease and related traits in the presence of environmental and genetic covariates. Data-mining strategies are gaining popularity because they are extremely flexible and may have greater efficiency and potential in identifying the factors involved in complex disorders. While the methods grouped together here constitute a diverse collection, some papers asked similar questions with very different methods, while others used the same underlying methodology to ask very different questions. This paper briefly describes the data-mining methodologies applied to the Genetic Analysis Workshop 13 data sets and the results of those investigations. Copyright 2003 Wiley-Liss, Inc.

Image Mining in Remote Sensing for Coastal Wetlands Mapping: from Pixel Based to Object Based Approach

NASA Astrophysics Data System (ADS)

Farda, N. M.; Danoedoro, P.; Hartono; Harjoko, A.

2016-11-01

The availably of remote sensing image data is numerous now, and with a large amount of data it makes “knowledge gap” in extraction of selected information, especially coastal wetlands. Coastal wetlands provide ecosystem services essential to people and the environment. The aim of this research is to extract coastal wetlands information from satellite data using pixel based and object based image mining approach. Landsat MSS, Landsat 5 TM, Landsat 7 ETM+, and Landsat 8 OLI images located in Segara Anakan lagoon are selected to represent data at various multi temporal images. The input for image mining are visible and near infrared bands, PCA band, invers PCA bands, mean shift segmentation bands, bare soil index, vegetation index, wetness index, elevation from SRTM and ASTER GDEM, and GLCM (Harralick) or variability texture. There is three methods were applied to extract coastal wetlands using image mining: pixel based - Decision Tree C4.5, pixel based - Back Propagation Neural Network, and object based - Mean Shift segmentation and Decision Tree C4.5. The results show that remote sensing image mining can be used to map coastal wetlands ecosystem. Decision Tree C4.5 can be mapped with highest accuracy (0.75 overall kappa). The availability of remote sensing image mining for mapping coastal wetlands is very important to provide better understanding about their spatiotemporal coastal wetlands dynamics distribution.

Kernel Methods for Mining Instance Data in Ontologies

NASA Astrophysics Data System (ADS)

Bloehdorn, Stephan; Sure, York

The amount of ontologies and meta data available on the Web is constantly growing. The successful application of machine learning techniques for learning of ontologies from textual data, i.e. mining for the Semantic Web, contributes to this trend. However, no principal approaches exist so far for mining from the Semantic Web. We investigate how machine learning algorithms can be made amenable for directly taking advantage of the rich knowledge expressed in ontologies and associated instance data. Kernel methods have been successfully employed in various learning tasks and provide a clean framework for interfacing between non-vectorial data and machine learning algorithms. In this spirit, we express the problem of mining instances in ontologies as the problem of defining valid corresponding kernels. We present a principled framework for designing such kernels by means of decomposing the kernel computation into specialized kernels for selected characteristics of an ontology which can be flexibly assembled and tuned. Initial experiments on real world Semantic Web data enjoy promising results and show the usefulness of our approach.

Proceedings of Twenty-Seventh Annual Institute on Mining Health, Safety and Research

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bockosh, G.R.; Langton, J.; Karmis, M.

1996-12-31

This Proceedings contains the presentations made during the program of the Twenty-Seventh Annual Institute on Mining Health, Safety and Research held at Virginia Polytechnic Institute and State University, Blacksburg, Virginia, on August 26-28, 1996. The Twenty-Seventh Annual Institute on Mining, Health, Safety and Research was the latest in a series of conferences held at Virginia Polytechnic Institute and State University, cosponsored by the Mine Safety and Health Administration, United States Department of Labor, and the Pittsburgh Research Center, United States Department of Energy (formerly part of the Bureau of Mines, U. S. Department of Interior). The Institute provides an informationmore » forum for mine operators, managers, superintendents, safety directors, engineers, inspectors, researchers, teachers, state agency officials, and others with a responsible interest in the important field of mining health, safety and research. In particular, the Institute is designed to help mine operating personnel gain a broader knowledge and understanding of the various aspects of mining health and safety, and to present them with methods of control and solutions developed through research. Selected papers have been processed separately for inclusion in the Energy Science and Technology database.« less

Analysis by the Residual Method for Estimate Market Value of Land on the Areas with Mining Exploitation in Subsoil under Future New Building

NASA Astrophysics Data System (ADS)

Gwozdz-Lason, Monika

2017-12-01

This paper attempts to answer some of the following questions: what is the main selling advantage of a plot of land on the areas with mining exploitation? which attributes influence on market value the most? and how calculate the mining influence in subsoil under future new building as market value of plot with commercial use? This focus is not accidental, as the paper sets out to prove that the subsoil load bearing capacity, as directly inferred from the local geotechnical properties with mining exploitation, considerably influences the market value of this type of real estate. Presented in this elaborate analysis and calculations, are part of the ongoing development works which aimed at suggesting a new technology and procedures for estimating the value of the land belonging to the third category geotechnical. Analysed the question was examined both in terms of the theoretical and empirical. On the basis of the analysed code calculations in residual method, numerical, statistical and econometric defined results and final conclusions. A market analysis yielded a group of subsoil stabilization costs which depend on the mining operations interaction, subsoil parameters, type of the contemplated structure, its foundations, selected stabilization method, its overall area and shape.

Developing Image Processing Meta-Algorithms with Data Mining of Multiple Metrics

PubMed Central

Cunha, Alexandre; Toga, A. W.; Parker, D. Stott

2014-01-01

People often use multiple metrics in image processing, but here we take a novel approach of mining the values of batteries of metrics on image processing results. We present a case for extending image processing methods to incorporate automated mining of multiple image metric values. Here by a metric we mean any image similarity or distance measure, and in this paper we consider intensity-based and statistical image measures and focus on registration as an image processing problem. We show how it is possible to develop meta-algorithms that evaluate different image processing results with a number of different metrics and mine the results in an automated fashion so as to select the best results. We show that the mining of multiple metrics offers a variety of potential benefits for many image processing problems, including improved robustness and validation. PMID:24653748

Data Mining of Macromolecular Structures.

PubMed

van Beusekom, Bart; Perrakis, Anastassis; Joosten, Robbie P

2016-01-01

The use of macromolecular structures is widespread for a variety of applications, from teaching protein structure principles all the way to ligand optimization in drug development. Applying data mining techniques on these experimentally determined structures requires a highly uniform, standardized structural data source. The Protein Data Bank (PDB) has evolved over the years toward becoming the standard resource for macromolecular structures. However, the process selecting the data most suitable for specific applications is still very much based on personal preferences and understanding of the experimental techniques used to obtain these models. In this chapter, we will first explain the challenges with data standardization, annotation, and uniformity in the PDB entries determined by X-ray crystallography. We then discuss the specific effect that crystallographic data quality and model optimization methods have on structural models and how validation tools can be used to make informed choices. We also discuss specific advantages of using the PDB_REDO databank as a resource for structural data. Finally, we will provide guidelines on how to select the most suitable protein structure models for detailed analysis and how to select a set of structure models suitable for data mining.

A novel artificial immune clonal selection classification and rule mining with swarm learning model

NASA Astrophysics Data System (ADS)

Al-Sheshtawi, Khaled A.; Abdul-Kader, Hatem M.; Elsisi, Ashraf B.

2013-06-01

Metaheuristic optimisation algorithms have become popular choice for solving complex problems. By integrating Artificial Immune clonal selection algorithm (CSA) and particle swarm optimisation (PSO) algorithm, a novel hybrid Clonal Selection Classification and Rule Mining with Swarm Learning Algorithm (CS2) is proposed. The main goal of the approach is to exploit and explore the parallel computation merit of Clonal Selection and the speed and self-organisation merits of Particle Swarm by sharing information between clonal selection population and particle swarm. Hence, we employed the advantages of PSO to improve the mutation mechanism of the artificial immune CSA and to mine classification rules within datasets. Consequently, our proposed algorithm required less training time and memory cells in comparison to other AIS algorithms. In this paper, classification rule mining has been modelled as a miltiobjective optimisation problem with predictive accuracy. The multiobjective approach is intended to allow the PSO algorithm to return an approximation to the accuracy and comprehensibility border, containing solutions that are spread across the border. We compared our proposed algorithm classification accuracy CS2 with five commonly used CSAs, namely: AIRS1, AIRS2, AIRS-Parallel, CLONALG, and CSCA using eight benchmark datasets. We also compared our proposed algorithm classification accuracy CS2 with other five methods, namely: Naïve Bayes, SVM, MLP, CART, and RFB. The results show that the proposed algorithm is comparable to the 10 studied algorithms. As a result, the hybridisation, built of CSA and PSO, can develop respective merit, compensate opponent defect, and make search-optimal effect and speed better.

Selecting an appropriate method to remove cyanide from the wastewater of Moteh gold mine using a mathematical approach.

PubMed

Seyyed Alizadeh Ganji, Seyyed Mohammad; Hayati, Mohammad

2018-06-05

The presence of cyanide ions in wastewater is dangerous to the health and life of living creatures, especially humans. Cyanide concentration should not exceed the acceptable limit in wastewaters to avoid their adverse effects to the environment. In this paper, in order to select the most appropriate method to remove cyanide from the wastewater of the Moteh gold mine, based on the experts' opinions, the use of calcium hypochlorite, sodium hypochlorite, and hydrogen peroxide was chosen as forerunning alternative in the form of a multi-stage model. Then, seven criteria including the amount of material consumed, ease of implementation, safety, ability to remove cyanide, pH, time, and cost of the process to assess the considered methods were determined. Afterwards, seven experts conducted numerous experiments to examine the conditions of each of these criteria. Then, by employing a mathematical method called "numerical taxonomy," the use of sodium hypochlorite was suggested as the best method to remove cyanide from the wastewater of the Moteh gold mine. Finally, the TOPSIS model was used to validate the proposed model, which led to the same results of the suggested method. Also, the results of employing taxonomic analysis and TOPSIS method suggested the use of sodium hypochlorite as the best method for cyanide removal from wastewater. In addition, according to the analysis of various experiments, conditions for complete removal of cyanide using sodium hypochlorite included concentration (8.64 g/L), pH (12.3), and temperature (12 °C).

An Efficient Pattern Mining Approach for Event Detection in Multivariate Temporal Data

PubMed Central

Batal, Iyad; Cooper, Gregory; Fradkin, Dmitriy; Harrison, James; Moerchen, Fabian; Hauskrecht, Milos

2015-01-01

This work proposes a pattern mining approach to learn event detection models from complex multivariate temporal data, such as electronic health records. We present Recent Temporal Pattern mining, a novel approach for efficiently finding predictive patterns for event detection problems. This approach first converts the time series data into time-interval sequences of temporal abstractions. It then constructs more complex time-interval patterns backward in time using temporal operators. We also present the Minimal Predictive Recent Temporal Patterns framework for selecting a small set of predictive and non-spurious patterns. We apply our methods for predicting adverse medical events in real-world clinical data. The results demonstrate the benefits of our methods in learning accurate event detection models, which is a key step for developing intelligent patient monitoring and decision support systems. PMID:26752800

Geological modelling of mineral deposits for prediction in mining

NASA Astrophysics Data System (ADS)

Sides, E. J.

Accurate prediction of the shape, location, size and properties of the solid rock materials to be extracted during mining is essential for reliable technical and financial planning. This is achieved through geological modelling of the three-dimensional (3D) shape and properties of the materials present in mineral deposits, and the presentation of results in a form which is accessible to mine planning engineers. In recent years the application of interactive graphics software, offering 3D database handling, modelling and visualisation, has greatly enhanced the options available for predicting the subsurface limits and characteristics of mineral deposits. A review of conventional 3D geological interpretation methods, and the model struc- tures and modelling methods used in reserve estimation and mine planning software packages, illustrates the importance of such approaches in the modern mining industry. Despite the widespread introduction and acceptance of computer hardware and software in mining applications, in recent years, there has been little fundamental change in the way in which geology is used in orebody modelling for predictive purposes. Selected areas of current research, aimed at tackling issues such as the use of orientation data, quantification of morphological differences, incorporation of geological age relationships, multi-resolution models and the application of virtual reality hardware and software, are discussed.

ABC for AIDS prevention in Guinea: migrant gold mining communities address their risks.

PubMed

Kis, Adam Daniel

2010-04-01

Contrary to expectation when compared with other migrant mining zones of sub-Saharan Africa, the nation of Guinea has a comparatively low and stable HIV rate. In addition, the regions with the largest gold, diamond, and bauxite mining operations report the lowest HIV rates within the country. This research set out to explain practices and beliefs within gold mining communities near Siguiri, Guinea--the highest-producing gold mining zone in the country--that may contribute to this phenomenon, particularly as they relate to the Abstinence, Be faithful, use a Condom approach to AIDS prevention. Structured interviews on a randomly selected sample of 460 adults and regular visitation to 16 pharmacies and health clinics within the mining zone yielded data showing that abstinence and condom use are minimally practiced for AIDS prevention. Instead, faithfulness to partners was overwhelmingly reported as the method of choice for AIDS avoidance. In addition, this research explored ways in which local conceptions of fidelity differed from those generally understood in other contexts, including engagement in short-term marriages at the gold mining sites.

Sentiment analysis of feature ranking methods for classification accuracy

NASA Astrophysics Data System (ADS)

Joseph, Shashank; Mugauri, Calvin; Sumathy, S.

2017-11-01

Text pre-processing and feature selection are important and critical steps in text mining. Text pre-processing of large volumes of datasets is a difficult task as unstructured raw data is converted into structured format. Traditional methods of processing and weighing took much time and were less accurate. To overcome this challenge, feature ranking techniques have been devised. A feature set from text preprocessing is fed as input for feature selection. Feature selection helps improve text classification accuracy. Of the three feature selection categories available, the filter category will be the focus. Five feature ranking methods namely: document frequency, standard deviation information gain, CHI-SQUARE, and weighted-log likelihood -ratio is analyzed.

Zoning method for environmental engineering geological patterns in underground coal mining areas.

PubMed

Liu, Shiliang; Li, Wenping; Wang, Qiqing

2018-09-01

Environmental engineering geological patterns (EEGPs) are used to express the trend and intensity of eco-geological environment caused by mining in underground coal mining areas, a complex process controlled by multiple factors. A new zoning method for EEGPs was developed based on the variable-weight theory (VWT), where the weights of factors vary with their value. The method was applied to the Yushenfu mining area, Shaanxi, China. First, the mechanism of the EEGPs caused by mining was elucidated, and four types of EEGPs were proposed. Subsequently, 13 key control factors were selected from mining conditions, lithosphere, hydrosphere, ecosphere, and climatic conditions; their thematic maps were constructed using ArcGIS software and remote-sensing technologies. Then, a stimulation-punishment variable-weight model derived from the partition of basic evaluation unit of study area, construction of partition state-variable-weight vector, and determination of variable-weight interval was built to calculate the variable weights of each factor. On this basis, a zoning mathematical model of EEGPs was established, and the zoning results were analyzed. For comparison, the traditional constant-weight theory (CWT) was also applied to divide the EEGPs. Finally, the zoning results obtained using VWT and CWT were compared. The verification of field investigation indicates that VWT is more accurate and reliable than CWT. The zoning results are consistent with the actual situations and the key of planning design for the rational development of coal resources and protection of eco-geological environment. Copyright © 2018 Elsevier B.V. All rights reserved.

Real -time dispatching modelling for trucks with different capacities in open pit mines / Modelowanie w czasie rzeczywistym przewozów ciężarówek o różnej ładowności w kopalni odkrywkowej

NASA Astrophysics Data System (ADS)

Ahangaran, Daryoush Kaveh; Yasrebi, Amir Bijan; Wetherelt, Andy; Foster, Patrick

2012-10-01

Application of fully automated systems for truck dispatching plays a major role in decreasing the transportation costs which often represent the majority of costs spent on open pit mining. Consequently, the application of a truck dispatching system has become fundamentally important in most of the world's open pit mines. Recent experiences indicate that by decreasing a truck's travelling time and the associated waiting time of its associated shovel then due to the application of a truck dispatching system the rate of production will be considerably improved. Computer-based truck dispatching systems using algorithms, advanced and accurate software are examples of these innovations. Developing an algorithm of a computer- based program appropriated to a specific mine's conditions is considered as one of the most important activities in connection with computer-based dispatching in open pit mines. In this paper the changing trend of programming and dispatching control algorithms and automation conditions will be discussed. Furthermore, since the transportation fleet of most mines use trucks with different capacities, innovative methods, operational optimisation techniques and the best possible methods for developing the required algorithm for real-time dispatching are selected by conducting research on mathematical-based planning methods. Finally, a real-time dispatching model compatible with the requirement of trucks with different capacities is developed by using two techniques of flow networks and integer programming.

Detector Apparatus and Method

NASA Technical Reports Server (NTRS)

Arndt, G. Dickey (Inventor); Ngo, Phong H. (Inventor); Carl, James R. (Inventor); Byerly, Kent A. (Inventor); Dusl, John (Inventor)

2003-01-01

Transceiver and methods are included that are especially suitable for detecting metallic materials, such as metallic mines, within an environment. The transceiver includes a digital waveform generator used to transmit a signal into the environment and a receiver that produces a digital received signal. A tracking module preferably compares an in-phase and quadrature transmitted signal with an in-phase and quadrature received signal to produce a spectral transfer function of the magnetic transceiver over a selected range of frequencies. The transceiver initially preferably creates a reference transfer function which is then stored in a memory. Subsequently measured transfer functions will vary depending on the presence of metal in the environment which was not in the environment when the reference transfer function was determined. The system may be utilized in the presence of other antennas, metal, and electronics which may comprise a plastic mine detector for detecting plastic mines. Despite the additional antennas and other metallic materials that may be in the environment due to the plastic mine detector, the magnetic transceiver remains highly sensitive to metallic material which may be located in various portions of the environment and which may be detected by sweeping the detector over ground that may contain metals or mines.

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

NASA Astrophysics Data System (ADS)

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.

Analysis on composition rules of Chinese patent drugs treating pain-related diseases based on data mining method.

PubMed

Tang, Shi-Huan; Shen, Dan; Yang, Hong-Jun

2017-08-24

To analyze the composition rules of oral prescriptions in the treatment of headache, stomachache and dysmenorrhea recorded in National Standard for Chinese Patent Drugs (NSCPD) enacted by Ministry of Public Health of China and then make comparison between them to better understand pain treatment in different regions of human body. Constructed NSCPD database had been constructed in 2014. Prescriptions treating the three pain-related diseases were searched and screened from the database. Then data mining method such as association rules analysis and complex system entropy method integrated in the data mining software Traditional Chinese Medicine Inheritance Support System (TCMISS) were applied to process the data. Top 25 drugs with high frequency in the treatment of each disease were selected, and 51, 33 and 22 core combinations treating headache, stomachache and dysmenorrhea respectively were mined out as well. The composition rules of the oral prescriptions for treating headache, stomachache and dysmenorrhea recorded in NSCPD has been summarized. Although there were similarities between them, formula varied according to different locations of pain. It can serve as an evidence and reference for clinical treatment and new drug development.

Comprehensive Fractal Description of Porosity of Coal of Different Ranks

PubMed Central

Ren, Jiangang; Zhang, Guocheng; Song, Zhimin; Liu, Gaofeng; Li, Bing

2014-01-01

We selected, as the objects of our research, lignite from the Beizao Mine, gas coal from the Caiyuan Mine, coking coal from the Xiqu Mine, and anthracite from the Guhanshan Mine. We used the mercury intrusion method and the low-temperature liquid nitrogen adsorption method to analyze the structure and shape of the coal pores and calculated the fractal dimensions of different aperture segments in the coal. The experimental results show that the fractal dimension of the aperture segment of lignite, gas coal, and coking coal with an aperture of greater than or equal to 10 nm, as well as the fractal dimension of the aperture segment of anthracite with an aperture of greater than or equal to 100 nm, can be calculated using the mercury intrusion method; the fractal dimension of the coal pore, with an aperture range between 2.03 nm and 361.14 nm, can be calculated using the liquid nitrogen adsorption method, of which the fractal dimensions bounded by apertures of 10 nm and 100 nm are different. Based on these findings, we defined and calculated the comprehensive fractal dimensions of the coal pores and achieved the unity of fractal dimensions for full apertures of coal pores, thereby facilitating, overall characterization for the heterogeneity of the coal pore structure. PMID:24955407

Continuous Rating for Diggability Assessment in Surface Mines

NASA Astrophysics Data System (ADS)

IPHAR, Melih

2016-10-01

The rocks can be loosened either by drilling-blasting or direct excavation using powerful machines in opencast mining operations. The economics of rock excavation is considered for each method to be applied. If blasting operation is not preferred and also the geological structures and rock mass properties in site are convenient (favourable ground conditions) for ripping or direct excavation method by mining machines, the next step is to determine which machine or excavator should be selected for the excavation purposes. Many researchers have proposed several diggability or excavatability assessment methods for deciding on excavator type to be used in the field. Most of these systems are generally based on assigning a rating for the parameters having importance in rock excavation process. However, the sharp transitions between the two adjacent classes for a given parameter can lead to some uncertainties. In this paper, it has been proposed that varying rating should be assigned for a given parameter called as “continuous rating” instead of giving constant rating for a given class.

Prediction of acid mine drainage generation potential of various lithologies using static tests: Etili coal mine (NW Turkey) as a case study.

PubMed

Yucel, Deniz Sanliyuksel; Baba, Alper

2016-08-01

The Etili neighborhood in Can County (northwestern Turkey) has large reserves of coal and has been the site of many small- to medium-scale mining operations since the 1980s. Some of these have ceased working while others continue to operate. Once activities cease, the mining facilities and fields are usually abandoned without rehabilitation. The most significant environmental problem is acid mine drainage (AMD). This study was carried out to determine the acid generation potential of various lithological units in the Etili coal mine using static test methods. Seventeen samples were selected from areas with high acidic water concentrations: from different alteration zones belonging to volcanic rocks, from sedimentary rocks, and from coals and mine wastes. Static tests (paste pH, standard acid-base accounting, and net acid generation tests) were performed on these samples. The consistency of the static test results showed that oxidation of sulfide minerals, especially pyrite-which is widely found not only in the alteration zones of volcanic rocks but also in the coals and mine wastes-is the main factor controlling the generation of AMD in this mine. Lack of carbonate minerals in the region also increases the occurrence of AMD.

A numerical calculation method of environmental impacts for the deep sea mining industry - a review.

PubMed

Ma, Wenbin; van Rhee, Cees; Schott, Dingena

2018-03-01

Since the gradual decrease of mineral resources on-land, deep sea mining (DSM) is becoming an urgent and important emerging activity in the world. However, until now there has been no commercial scale DSM project in progress. Together with the reasons of technological feasibility and economic profitability, the environmental impact is one of the major parameters hindering its industrialization. Most of the DSM environmental impact research focuses on only one particular aspect ignoring that all the DSM environmental impacts are related to each other. The objective of this work is to propose a framework for the numerical calculation methods of the integrated DSM environmental impacts through a literature review. This paper covers three parts: (i) definition and importance description of different DSM environmental impacts; (ii) description of the existing numerical calculation methods for different environmental impacts; (iii) selection of a numerical calculation method based on the selected criteria. The research conducted in this paper provides a clear numerical calculation framework for DSM environmental impact and could be helpful to speed up the industrialization process of the DSM industry.

Recent Developments for Remediating Acidic Mine Waters Using Sulfidogenic Bacteria

PubMed Central

Bitencourt, José A. P.; Sahoo, Prafulla K.; Alves, Joner Oliveira; Siqueira, José O.

2017-01-01

Acidic mine drainage (AMD) is regarded as a pollutant and considered as potential source of valuable metals. With diminishing metal resources and ever-increasing demand on industry, recovering AMD metals is a sustainable initiative, despite facing major challenges. AMD refers to effluents draining from abandoned mines and mine wastes usually highly acidic that contain a variety of dissolved metals (Fe, Mn, Cu, Ni, and Zn) in much greater concentration than what is found in natural water bodies. There are numerous remediation treatments including chemical (lime treatment) or biological methods (aerobic wetlands and compost bioreactors) used for metal precipitation and removal from AMD. However, controlled biomineralization and selective recovering of metals using sulfidogenic bacteria are advantageous, reducing costs and environmental risks of sludge disposal. The increased understanding of the microbiology of acid-tolerant sulfidogenic bacteria will lead to the development of novel approaches to AMD treatment. We present and discuss several important recent approaches using low sulfidogenic bioreactors to both remediate and selectively recover metal sulfides from AMD. This work also highlights the efficiency and drawbacks of these types of treatments for metal recovery and points to future research for enhancing the use of novel acidophilic and acid-tolerant sulfidogenic microorganisms in AMD treatment. PMID:29119111

An Evaluation of Text Mining Tools as Applied to Selected Scientific and Engineering Literature.

ERIC Educational Resources Information Center

Trybula, Walter J.; Wyllys, Ronald E.

2000-01-01

Addresses an approach to the discovery of scientific knowledge through an examination of data mining and text mining techniques. Presents the results of experiments that investigated knowledge acquisition from a selected set of technical documents by domain experts. (Contains 15 references.) (Author/LRW)

Plant Type Selection for Reclamation of Sarcheshmeh Copper Mine Using Fuzzy-Topsis Approach / Wybór Gatunków Roślin Do Wykorzystania W Projekcie Rekultywacji Terenów Kopalni Miedzi Sarcheshmeh Z Wykorzystaniem Metod Logiki Rozmytej Topsis

NASA Astrophysics Data System (ADS)

Ebrahimabadi, Arash; Alavi, Iraj

2013-09-01

Plant species selection is a multi-criteria evaluation decision and has a strategic importance for many companies. The conventional methods for plant species selection are inadequate for dealing with the imprecise or vague nature of linguistic assessment. To overcome this difficulty, fuzzy multi-criteria decision-making methods are proposed. The aim of this study is to use the fuzzy technique for order preference by similarity to ideal solution (F.TOPSIS) methods for the selection of plant species in mine reclamation plan. Plant type selection and planting to protect the environment and the reclamation of the mine are some of the most important solutions. Therefore, the objective of the current research study is to choose the proper plant types for reclamation of Sarcheshmeh Copper Mine using Fuzzy-topsis method. In this regard, primarily, surrounding area of Sarcheshmeh copper mine, one of the world's 10 biggest copper mine which is located near Kerman city of Iran, are surveyed, to choose the best plant type for reclamation of disturbance area. With this respect, based on reclamation plan, primary criteria were consisted of kinds of post mining land use, climate, and nature of soil. Comparison matrixes were then obtained based on experts' opinion and plant types were subsequently prioritized using the Fuzzy Topsis method. Secondary factors considered through the analysis were as follows: perspective of the region, resistance against disease and insects, strength and method of growth, availability to plant type, economic efficiency, protection of soil, storing water, and prevention of pollution. Finally, suitable plant types in the mining perimeter were prioritized as: Amygdalus scoparia, Tamarix, Pistachio Wild, Ephedra, Astragalus, Salsola, respectively. Wybór gatunków roślin jest decyzją podejmowaną w oparciu o wiele kryteriów i stanowi poważne wyzwanie strategiczne dla wielu firm. Konwencjonalne metody wyboru gatunków roślin okazują się niewystarczające w przypadku nieprecyzyjnej oceny i nie w pełni zdefiniowanych określeń językowych. W celu przezwyciężenia tych trudności, zaproponowano wielo-kryterialną metodę decyzyjną wykorzystującą logikę rozmytą. Celem tego opracowania jest ukazanie zastosowania podejścia rozmytego do uzyskania kolejnych przybliżeń do rozwiązania idealnego (F.TOPSIS) przy wyborze odpowiednich gatunków roślin do użycia w projekcie rekultywacji terenów kopalni. Wybór gatunków roślin i ich kultywacja dla zapewnienia ochrony środowiska i projektu rekultywacji terenu pogórniczego to bardzo ważne zagadnienia. Głównym celem obecnego studium jest wybór odpowiednich gatunków roślin do wykorzystania projekcie rekultywacji terenów kopalni miedzi Sarcheshmeh z wykorzystaniem metod logiki rozmytej TOPSIS. W pierwszym rzędzie przeprowadzono badania gruntów wokół kopalni miedzi Sarchesmeh, w pobliżu miejscowości Kerman w Iranie (jednej z dziesięciu największych na świecie kopalni miedzi) w celu wyboru najlepszych typów roślin do wykorzystania do rekultywacji naruszonych działalnością górniczą terenów. Określono podstawowe kryteria wyboru, biorąc pod uwagę plan rekultywacji: sposoby wykorzystania terenu, klimat oraz rodzaje gleb. Otrzymano macierze porównawcze uzyskane na podstawie opinii ekspertów, następnie dokonano określenia priorytetów dla poszczególnych roślin przy pomocy metody TOPSIS, wykorzystującej logikę rozmytą. W analizie uwzględniono następujące czynniki drugorzędne: perspektywy dla regionu, odporność na choroby i owady szkodniki, wytrzymałość i sposób uprawy, dostępność danego gatunku roślin, wydajność ekonomiczna, ochrona gleb, zdolność zatrzymywania wody, zapobieganie zanieczyszczeniom. W końcowym etapie dokonano wyboru najkorzystniejszych dla danego terenu górniczego gatunków roślin, podając kolejno: Amygdalus scoparia, Tamarix, Pistachio Wild, Ephedra, Astragalus, Salsola.

Water quality data at selected sites in the Mississippi Valley-type Zn-Pb ore district of upper Silesia, Poland, 1995-97

USGS Publications Warehouse

Wirt, Laurie; Motyka, Jacek; Leach, David; Sass-Gustkiewicz, Maria; Szuwarzynski, Marek; Adamczyk, Zbigniew; Briggs, Paul; Meiers, Al

2003-01-01

The water chemistry of aquifers and streams in the Upper Silesia Ore District, Poland are affected by their proximity to zinc, lead, and silver ores and by ongoing mining activities that date back to the 11th century. This report presents hydrologic and water-quality data collected as part of a collaborative research effort of the U.S. Geological Survey and the University of Mining and Metallurgy in Cracow, Poland to study Mississippi-Valley-Type lead-zinc deposits. MVT deposits in the Upper Silesia Ore District (Fig. 1) were selected for detailed study because the Polish mining industry allowed access to collect samples from underground mines and mine-land property. Water-quality samples were collected from streams, springs, wells, underground mine seeps and drains; and mine-tailings ponds. Data include field measurements of specific conductance, pH, water temperature, and dissolved oxygen and laboratory analyses of major and minor inorganic constituents and selected trace-element constituents.

An application of data mining in district heating substations for improving energy performance

NASA Astrophysics Data System (ADS)

Xue, Puning; Zhou, Zhigang; Chen, Xin; Liu, Jing

2017-11-01

Automatic meter reading system is capable of collecting and storing a huge number of district heating (DH) data. However, the data obtained are rarely fully utilized. Data mining is a promising technology to discover potential interesting knowledge from vast data. This paper applies data mining methods to analyse the massive data for improving energy performance of DH substation. The technical approach contains three steps: data selection, cluster analysis and association rule mining (ARM). Two-heating-season data of a substation are used for case study. Cluster analysis identifies six distinct heating patterns based on the primary heat of the substation. ARM reveals that secondary pressure difference and secondary flow rate have a strong correlation. Using the discovered rules, a fault occurring in remote flow meter installed at secondary network is detected accurately. The application demonstrates that data mining techniques can effectively extrapolate potential useful knowledge to better understand substation operation strategies and improve substation energy performance.

[The method and application to construct experience recommendation platform of acupuncture ancient books based on data mining technology].

PubMed

Chen, Chuyun; Hong, Jiaming; Zhou, Weilin; Lin, Guohua; Wang, Zhengfei; Zhang, Qufei; Lu, Cuina; Lu, Lihong

2017-07-12

To construct a knowledge platform of acupuncture ancient books based on data mining technology, and to provide retrieval service for users. The Oracle 10 g database was applied and JAVA was selected as development language; based on the standard library and ancient books database established by manual entry, a variety of data mining technologies, including word segmentation, speech tagging, dependency analysis, rule extraction, similarity calculation, ambiguity analysis, supervised classification technology were applied to achieve text automatic extraction of ancient books; in the last, through association mining and decision analysis, the comprehensive and intelligent analysis of disease and symptom, meridians, acupoints, rules of acupuncture and moxibustion in acupuncture ancient books were realized, and retrieval service was provided for users through structure of browser/server (B/S). The platform realized full-text retrieval, word frequency analysis and association analysis; when diseases or acupoints were searched, the frequencies of meridian, acupoints (diseases) and techniques were presented from high to low, meanwhile the support degree and confidence coefficient between disease and acupoints (special acupoint), acupoints and acupoints in prescription, disease or acupoints and technique were presented. The experience platform of acupuncture ancient books based on data mining technology could be used as a reference for selection of disease, meridian and acupoint in clinical treatment and education of acupuncture and moxibustion.

New method for the direct determination of dissolved Fe(III) concentration in acid mine waters

USGS Publications Warehouse

To, T.B.; Nordstrom, D. Kirk; Cunningham, K.M.; Ball, J.W.; McCleskey, R. Blaine

1999-01-01

A new method for direct determination of dissolved Fe(III) in acid mine water has been developed. In most present methods, Fe(III) is determined by computing the difference between total dissolved Fe and dissolved Fe(II). For acid mine waters, frequently Fe(II) >> Fe(III); thus, accuracy and precision are considerably improved by determining Fe(III) concentration directly. The new method utilizes two selective ligands to stabilize Fe(III) and Fe(II), thereby preventing changes in Fe reduction-oxidation distribution. Complexed Fe(II) is cleanly removed using a silica-based, reversed-phase adsorbent, yielding excellent isolation of the Fe(III) complex. Iron(III) concentration is measured colorimetrically or by graphite furnace atomic absorption spectrometry (GFAAS). The method requires inexpensive commercial reagents and simple procedures that can be used in the field. Calcium(II), Ni(II), Pb(II), AI(III), Zn(II), and Cd(II) cause insignificant colorimetric interferences for most acid mine waters. Waters containing >20 mg of Cu/L could cause a colorimetric interference and should be measured by GFAAS. Cobalt(II) and Cr(III) interfere if their molar ratios to Fe(III) exceed 24 and 5, respectively. Iron(II) interferes when its concentration exceeds the capacity of the complexing ligand (14 mg/L). Because of the GFAAS elemental specificity, only Fe(II) is a potential interferent in the GFAAS technique. The method detection limit is 2 ??g/L (40 nM) using GFAAS and 20 ??g/L (0.4 ??M) by colorimetry.A new method for direct determination of dissolved Fe(III) in acid mine water has been developed. In most present methods, Fe(III) is determined by computing the difference between total dissolved Fe and dissolved Fe(II). For acid mine waters, frequently Fe(II)???Fe(III); thus, accuracy and precision are considerably improved by determining Fe(III) concentration directly. The new method utilizes two selective ligands to stabilize Fe(III) and Fe(II), thereby preventing changes in Fe reduction-oxidation distribution. Complexed Fe(II) is cleanly removed using a silica-based, reversed-phase adsorbent, yielding excellent isolation of the Fe(III) complex. Iron(III) concentration is measured colorimetrically or by graphite furnace atomic absorption spectrometry (GFAAS). The method requires inexpensive commercial reagents and simple procedures that can be used in the field. Calcium(II), Ni(II), Pb(II), Al(III), Zn(II), and Cd(II) cause insignificant colorimetric interferences for most acid mine waters. Waters containing >20 mg of Cu/L could cause a colorimetric interference and should be measured by GFAAS. Cobalt(II) and Cr(III) interfere if their molar ratios to Fe(III) exceed 24 and 5, respectively. Iron(II) interferes when its concentration exceeds the capacity of the complexing ligand (14 mg/L). Because of the GFAAS elemental specificity, only Fe(II) is a potential interferent in the GFAAS technique. The method detection limit is 2/??g/L (40 nM) using GFAAS and 20 ??g/L (0.4 ??M) by colorimetry.

The systematic assessment of traditional evidence from the premodern Chinese medical literature: a text-mining approach.

PubMed

May, Brian H; Zhang, Anthony; Lu, Yubo; Lu, Chuanjian; Xue, Charlie C L

2014-12-01

This project aimed to develop an approach to evaluating information contained in the premodern Traditional Chinese Medicine (TCM) literature that was (1) comprehensive, systematic, and replicable and (2) able to produce quantifiable output that could be used to answer specific research questions in order to identify natural products for clinical and experimental research. The project involved two stages. In stage 1, 14 TCM collections and compendia were evaluated for suitability as sources for searching; 8 of these were compared in detail. The results were published in the Journal of Alternative and Complementary Medicine. Stage 2 developed a text-mining approach for two of these sources. The text-mining approach was developed for Zhong Hua Yi Dian; Encyclopaedia of Traditional Chinese Medicine, 4th edition) and Zhong Yi Fang Ji Da Ci Dian; Great Compendium of Chinese Medical Formulae). This approach developed procedures for search term selection; methods for screening, classifying, and scoring data; procedures for systematic searching and data extraction; data checking procedures; and approaches for analyzing results. Examples are provided for studies of memory impairment and diabetic nephropathy, and issues relating to data interpretation are discussed. This approach to the analysis of large collections of the premodern TCM literature uses widely available sources and provides a text-mining approach that is systematic, replicable, and adaptable to the requirements of the particular project. Researchers can use these methods to explore changes in the names and conceptions of a disease over time, to identify which therapeutic methods have been more or less frequently used in different eras for particular disorders, and to assist in the selection of natural products for research efforts.

OligoIS: Scalable Instance Selection for Class-Imbalanced Data Sets.

PubMed

García-Pedrajas, Nicolás; Perez-Rodríguez, Javier; de Haro-García, Aida

2013-02-01

In current research, an enormous amount of information is constantly being produced, which poses a challenge for data mining algorithms. Many of the problems in extremely active research areas, such as bioinformatics, security and intrusion detection, or text mining, share the following two features: large data sets and class-imbalanced distribution of samples. Although many methods have been proposed for dealing with class-imbalanced data sets, most of these methods are not scalable to the very large data sets common to those research fields. In this paper, we propose a new approach to dealing with the class-imbalance problem that is scalable to data sets with many millions of instances and hundreds of features. This proposal is based on the divide-and-conquer principle combined with application of the selection process to balanced subsets of the whole data set. This divide-and-conquer principle allows the execution of the algorithm in linear time. Furthermore, the proposed method is easy to implement using a parallel environment and can work without loading the whole data set into memory. Using 40 class-imbalanced medium-sized data sets, we will demonstrate our method's ability to improve the results of state-of-the-art instance selection methods for class-imbalanced data sets. Using three very large data sets, we will show the scalability of our proposal to millions of instances and hundreds of features.

First experience with Remote Sensing methods and selected sensors in the monitoring of mining areas - a case study of the Belchatow open cast mine

NASA Astrophysics Data System (ADS)

Wajs, Jaroslaw

2018-01-01

The paper presents satellite imagery from active SENTINEL-1A and passive SENTINEL-2A/2B sensors for their application in the monitoring of mining areas focused on detecting land changes. Multispectral scenes of SENTINEL-2A/2B have allowed for detecting changes in land-cover near the region of interest (ROI), i.e. the Szczercow dumping site in the Belchatow open cast lignite mine, central Poland, Europe. Scenes from SENTINEL-1A/1B satellite have also been used in the research. Processing of the SLC signal enabled creating a return intensity map in VV polarization. The obtained SAR scene was reclassified and shows a strong return signal from the dumping site and the open pit. This fact may be used in detection and monitoring of changes occurring within the analysed engineering objects.

Seminal quality prediction using data mining methods.

PubMed

Sahoo, Anoop J; Kumar, Yugal

2014-01-01

Now-a-days, some new classes of diseases have come into existences which are known as lifestyle diseases. The main reasons behind these diseases are changes in the lifestyle of people such as alcohol drinking, smoking, food habits etc. After going through the various lifestyle diseases, it has been found that the fertility rates (sperm quantity) in men has considerably been decreasing in last two decades. Lifestyle factors as well as environmental factors are mainly responsible for the change in the semen quality. The objective of this paper is to identify the lifestyle and environmental features that affects the seminal quality and also fertility rate in man using data mining methods. The five artificial intelligence techniques such as Multilayer perceptron (MLP), Decision Tree (DT), Navie Bayes (Kernel), Support vector machine+Particle swarm optimization (SVM+PSO) and Support vector machine (SVM) have been applied on fertility dataset to evaluate the seminal quality and also to predict the person is either normal or having altered fertility rate. While the eight feature selection techniques such as support vector machine (SVM), neural network (NN), evolutionary logistic regression (LR), support vector machine plus particle swarm optimization (SVM+PSO), principle component analysis (PCA), chi-square test, correlation and T-test methods have been used to identify more relevant features which affect the seminal quality. These techniques are applied on fertility dataset which contains 100 instances with nine attribute with two classes. The experimental result shows that SVM+PSO provides higher accuracy and area under curve (AUC) rate (94% & 0.932) among multi-layer perceptron (MLP) (92% & 0.728), Support Vector Machines (91% & 0.758), Navie Bayes (Kernel) (89% & 0.850) and Decision Tree (89% & 0.735) for some of the seminal parameters. This paper also focuses on the feature selection process i.e. how to select the features which are more important for prediction of fertility rate. In this paper, eight feature selection methods are applied on fertility dataset to find out a set of good features. The investigational results shows that childish diseases (0.079) and high fever features (0.057) has less impact on fertility rate while age (0.8685), season (0.843), surgical intervention (0.7683), alcohol consumption (0.5992), smoking habit (0.575), number of hours spent on setting (0.4366) and accident (0.5973) features have more impact. It is also observed that feature selection methods increase the accuracy of above mentioned techniques (multilayer perceptron 92%, support vector machine 91%, SVM+PSO 94%, Navie Bayes (Kernel) 89% and decision tree 89%) as compared to without feature selection methods (multilayer perceptron 86%, support vector machine 86%, SVM+PSO 85%, Navie Bayes (Kernel) 83% and decision tree 84%) which shows the applicability of feature selection methods in prediction. This paper lightens the application of artificial techniques in medical domain. From this paper, it can be concluded that data mining methods can be used to predict a person with or without disease based on environmental and lifestyle parameters/features rather than undergoing various medical test. In this paper, five data mining techniques are used to predict the fertility rate and among which SVM+PSO provide more accurate results than support vector machine and decision tree.

ASCOT: a text mining-based web-service for efficient search and assisted creation of clinical trials

PubMed Central

2012-01-01

Clinical trials are mandatory protocols describing medical research on humans and among the most valuable sources of medical practice evidence. Searching for trials relevant to some query is laborious due to the immense number of existing protocols. Apart from search, writing new trials includes composing detailed eligibility criteria, which might be time-consuming, especially for new researchers. In this paper we present ASCOT, an efficient search application customised for clinical trials. ASCOT uses text mining and data mining methods to enrich clinical trials with metadata, that in turn serve as effective tools to narrow down search. In addition, ASCOT integrates a component for recommending eligibility criteria based on a set of selected protocols. PMID:22595088

ASCOT: a text mining-based web-service for efficient search and assisted creation of clinical trials.

PubMed

Korkontzelos, Ioannis; Mu, Tingting; Ananiadou, Sophia

2012-04-30

Clinical trials are mandatory protocols describing medical research on humans and among the most valuable sources of medical practice evidence. Searching for trials relevant to some query is laborious due to the immense number of existing protocols. Apart from search, writing new trials includes composing detailed eligibility criteria, which might be time-consuming, especially for new researchers. In this paper we present ASCOT, an efficient search application customised for clinical trials. ASCOT uses text mining and data mining methods to enrich clinical trials with metadata, that in turn serve as effective tools to narrow down search. In addition, ASCOT integrates a component for recommending eligibility criteria based on a set of selected protocols.

Hydrologic data collected in the vicinity of the proposed gamma-ray and neutrino detector site, Hot Spring County, Arkansas, 1988-89

USGS Publications Warehouse

Fitzpatrick, D.J.; Westerfield, P.W.

1990-01-01

An abandoned barite mine in Hot Spring County, Arkansas, has been selected as the location for a proposed gamma-ray and neutrino detector site. As part of the hydrologic evaluation of the site, the U.S. Geological Survey in cooperation with the Arkansas Geological Commission collected hydrologic data at selected locations in the vicinity of the abandoned barite mine. Data collected as part of the project included water quality, pond-evaluation, and precipitation data within the abandoned barite mine and flow and water quality data at selected sites in the vicinity of the mine. Water quality samples from within the abandoned mine were collected at three locations in the pond at selected depths. These data included field measurements of specific conductance, pH, water temperature, dissolved oxygen, major ions, and trace metals. Major ion and trace-metal samples were collected at six stream sites, one lake site, and two wastewater pond sites. Pond elevation and precipitation data from within the abandoned barite mine were measured during the period between July 1, 1988 and June 30, 1989. Twevle discharge measurements during the period between June 21, 1988, and June 26, 1989, were collected at six sites in the vicinity of the abandoned barite mine. (USGS)

Multiband infrared inversion for low-concentration methane monitoring in a confined dust-polluted atmosphere.

PubMed

Wang, Wenzheng; Wang, Yanming; Song, Wujun; Li, Xueqin

2017-03-20

A multiband infrared diagnostic (MBID) method for methane emission monitoring in limited underground environments was presented considering the strong optical background of gas/solid attenuation. Based on spatial distribution of aerosols and complex refractive index of dust particles, forward calculations were carried out with/without methane to obtain the spectral transmittance through the participating atmosphere in a mine roadway. Considering the concurrent attenuation and absorption behavior of dust and gases, four infrared wavebands were selected to retrieve the methane concentration combined with a stochastic particle swarm optimization (SPSO) algorithm. Inversion results prove that the presented MBID method is robust and effective in identifying methane at concentrations of 0.1% or even lower with inversed relative error within 10%. Further analyses illustrate that the four selected wavebands are indispensable, and the MBID method is still valid with transmission signal disturbance in a conventional dust-polluted atmosphere under mechanized mining condition. However, the effective detection distance should be limited within 50 m to ensure inversed relative error less than 5% at 1% methane concentration.

FIFS: A data mining method for informative marker selection in high dimensional population genomic data.

PubMed

Kavakiotis, Ioannis; Samaras, Patroklos; Triantafyllidis, Alexandros; Vlahavas, Ioannis

2017-11-01

Single Nucleotide Polymorphism (SNPs) are, nowadays, becoming the marker of choice for biological analyses involving a wide range of applications with great medical, biological, economic and environmental interest. Classification tasks i.e. the assignment of individuals to groups of origin based on their (multi-locus) genotypes, are performed in many fields such as forensic investigations, discrimination between wild and/or farmed populations and others. Τhese tasks, should be performed with a small number of loci, for computational as well as biological reasons. Thus, feature selection should precede classification tasks, especially for Single Nucleotide Polymorphism (SNP) datasets, where the number of features can amount to hundreds of thousands or millions. In this paper, we present a novel data mining approach, called FIFS - Frequent Item Feature Selection, based on the use of frequent items for selection of the most informative markers from population genomic data. It is a modular method, consisting of two main components. The first one identifies the most frequent and unique genotypes for each sampled population. The second one selects the most appropriate among them, in order to create the informative SNP subsets to be returned. The proposed method (FIFS) was tested on a real dataset, which comprised of a comprehensive coverage of pig breed types present in Britain. This dataset consisted of 446 individuals divided in 14 sub-populations, genotyped at 59,436 SNPs. Our method outperforms the state-of-the-art and baseline methods in every case. More specifically, our method surpassed the assignment accuracy threshold of 95% needing only half the number of SNPs selected by other methods (FIFS: 28 SNPs, Delta: 70 SNPs Pairwise FST: 70 SNPs, In: 100 SNPs.) CONCLUSION: Our approach successfully deals with the problem of informative marker selection in high dimensional genomic datasets. It offers better results compared to existing approaches and can aid biologists in selecting the most informative markers with maximum discrimination power for optimization of cost-effective panels with applications related to e.g. species identification, wildlife management, and forensics. Copyright © 2017 Elsevier Ltd. All rights reserved.

Subnetwork mining on functional connectivity network for classification of minimal hepatic encephalopathy.

PubMed

Zhang, Daoqiang; Tu, Liyang; Zhang, Long-Jiang; Jie, Biao; Lu, Guang-Ming

2018-06-01

Hepatic encephalopathy (HE), as a complication of cirrhosis, is a serious brain disease, which may lead to death. Accurate diagnosis of HE and its intermediate stage, i.e., minimal HE (MHE), is very important for possibly early diagnosis and treatment. Brain connectivity network, as a simple representation of brain interaction, has been widely used for the brain disease (e.g., HE and MHE) analysis. However, those studies mainly focus on finding disease-related abnormal connectivity between brain regions, although a large number of studies have indicated that some brain diseases are usually related to local structure of brain connectivity network (i.e., subnetwork), rather than solely on some single brain regions or connectivities. Also, mining such disease-related subnetwork is a challenging task because of the complexity of brain network. To address this problem, we proposed a novel frequent-subnetwork-based method to mine disease-related subnetworks for MHE classification. Specifically, we first mine frequent subnetworks from both groups, i.e., MHE patients and non-HE (NHE) patients, respectively. Then we used the graph-kernel based method to select the most discriminative subnetworks for subsequent classification. We evaluate our proposed method on a MHE dataset with 77 cirrhosis patients, including 38 MHE patients and 39 NHE patients. The results demonstrate that our proposed method can not only obtain the improved classification performance in comparison with state-of-the-art network-based methods, but also identify disease-related subnetworks which can help us better understand the pathology of the brain diseases.

A malware detection scheme based on mining format information.

PubMed

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.

A Malware Detection Scheme Based on Mining Format Information

PubMed Central

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. PMID:24991639

Influences Determining European Coal Seam Gas Deliverability

NASA Astrophysics Data System (ADS)

Clark, G.

2009-04-01

Technically the coal basins of Europe have generated significant Gas In Place figures that has historically generated investor's interest in the development of this potential coal seam gas (CSG) resource. In the early 1980's, a wave of international, principally American, companies arrived, established themselves, drilled and then left with a poor record of success and disappointed investors. Recently a second wave of investment started after 2002, with the smaller companies leading the charge but have the lesson been learned from the past failures? To select a CSG investment project the common European approach has been to: 1. Find an old mining region; 2. Look to see if it had a coal mine methane gas problem; 3. Look for the non-mined coal seams; and 4. Peg the land. This method is perhaps the reason why the history of CSG exploration in Europe is such a disappointment as generally the coal mining regions of Europe do not have commercial CSG reservoir attributes. As a result, investors and governments have lost confidence that CSG will be a commercial success in Europe. New European specific principles for the determination of commercial CSG prospects have had to be delineated that allow for the selection of coal basins that have a strong technical case for deliverability. This will result in the return of investor confidence.

A proposed configurable approach for recommendation systems via data mining techniques

NASA Astrophysics Data System (ADS)

Khedr, Ayman E.; Idrees, Amira M.; Hegazy, Abd El-Fatah; El-Shewy, Samir

2018-02-01

This study presents a configurable approach for recommendations which determines the suitable recommendation method for each field based on the characteristics of its data, the method includes determining the suitable technique for selecting a representative sample of the provided data. Then selecting the suitable feature weighting measure to provide a correct weight for each feature based on its effect on the recommendations. Finally, selecting the suitable algorithm to provide the required recommendations. The proposed configurable approach could be applied on different domains. The experiments have revealed that the approach is able to provide recommendations with only 0.89 error rate percentage.

TRUNCATED RANDOM MEASURES

DTIC Science & Technology

2018-01-12

sequential representations, a method is required for deter- mining which to use for the application at hand and, once a representation is selected, for...DISTRIBUTION UNLIMITED Methods , Assumptions, and Procedures 3.1 Background 3.1.1 CRMs and truncation Consider a Poisson point process on R+ := [0...the heart of the study of truncated CRMs. They provide an itera- tive method that can be terminated at any point to yield a finite approximation to the

Sparse generalized linear model with L0 approximation for feature selection and prediction with big omics data.

PubMed

Liu, Zhenqiu; Sun, Fengzhu; McGovern, Dermot P

2017-01-01

Feature selection and prediction are the most important tasks for big data mining. The common strategies for feature selection in big data mining are L 1 , SCAD and MC+. However, none of the existing algorithms optimizes L 0 , which penalizes the number of nonzero features directly. In this paper, we develop a novel sparse generalized linear model (GLM) with L 0 approximation for feature selection and prediction with big omics data. The proposed approach approximate the L 0 optimization directly. Even though the original L 0 problem is non-convex, the problem is approximated by sequential convex optimizations with the proposed algorithm. The proposed method is easy to implement with only several lines of code. Novel adaptive ridge algorithms ( L 0 ADRIDGE) for L 0 penalized GLM with ultra high dimensional big data are developed. The proposed approach outperforms the other cutting edge regularization methods including SCAD and MC+ in simulations. When it is applied to integrated analysis of mRNA, microRNA, and methylation data from TCGA ovarian cancer, multilevel gene signatures associated with suboptimal debulking are identified simultaneously. The biological significance and potential clinical importance of those genes are further explored. The developed Software L 0 ADRIDGE in MATLAB is available at https://github.com/liuzqx/L0adridge.

Exposure of miners to diesel exhaust particulates in underground nonmetal mines.

PubMed

Cohen, H J; Borak, J; Hall, T; Sirianni, G; Chemerynski, S

2002-01-01

A study was initiated to examine worker exposures in seven underground nonmetal mines and to examine the precision of the National Institute for Occupational Safety and Health (NIOSH) 5040 sampling and analytical method for diesel exhaust that has recently been adopted for compliance monitoring by the Mine Safety and Health Administration (MSHA). Approximately 1000 air samples using cyclones were taken on workers and in areas throughout the mines. Results indicated that worker exposures were consistently above the MSHA final limit of 160 micrograms/m3 (time-weighted average; TWA) for total carbon as determined by the NIOSH 5040 method and greater than the proposed American Conference of Governmental Industrial Hygienists TLV limit of 20 micrograms/m3 (TWA) for elemental carbon. A number of difficulties were documented when sampling for diesel exhaust using organic carbon: high and variable blank values from filters, a high variability (+/- 20%) from duplicate punches from the same sampling filter, a consistent positive interference (+26%) when open-faced monitors were sampled side-by-side with cyclones, poor correlation (r 2 = 0.38) to elemental carbon levels, and an interference from limestone that could not be adequately corrected by acid-washing of filters. The sampling and analytical precision (relative standard deviation) was approximately 11% for elemental carbon, 17% for organic carbon, and 11% for total carbon. An hypothesis is presented and supported with data that gaseous organic carbon constituents of diesel exhaust adsorb onto not only the submicron elemental carbon particles found in diesel exhaust, but also mining ore dusts. Such mining dusts are mostly nonrespirable and should not be considered equivalent to submicron diesel particulates in their potential for adverse pulmonary effects. It is recommended that size-selective sampling be employed, rather than open-faced monitoring, when using the NIOSH 5040 method.

Sulphates Removal from Acid Mine Drainage

NASA Astrophysics Data System (ADS)

Luptáková, Alena; Mačingová, Eva; Kotuličová, Ingrida; Rudzanová, Dominika

2016-10-01

Acid mine drainage (AMD) are a worldwide problem leading to ecological destruction in river basins and the contamination of water sources. AMD are characterized by low pH and high content of heavy metals and sulphates. In order to minimize negative impacts of AMD appropriate treatment techniques has to be chosen. Treatment processes are focused on neutralizing, stabilizing and removing pollutants. From this reason efficient and environmental friendly methods are needed to be developed in order to reduce heavy metals as well as sulphates. Various methods are used for remediation of acid mine drainage, but any of them have been applied under commercial-scale conditions. Their application depends on geochemical, technical, natural, financial, and other factors. The aim of the present work was to interpret the study of biological methods for sulphates removal from AMD out-flowing from the shaft Pech of the deposit Smolmk in Slovak Republic. In the experimental works AMD were used after removal of heavy metals by precipitation and sorption using the synthetic sorbent Slovakite. The base of the studied method for the sulphates elimination was the anaerobic bacterial sulphate reduction using sulphate-reducing bacteria (SRB) genera Desulfovibrio. SRB represent a group of bacteria that uses sulphates as a terminal electron acceptor for their metabolism. These bacteria realize the conversion of sulphate to hydrogen sulphide under anaerobic conditions. For the purposes of experiments a few variants of the selective medium DSM-63 culture media were used in term of the sulphates and sodium lactate contents in the selective medium as well as sulphates in the studied AMD.

Features of the Asynchronous Correlation between the China Coal Price Index and Coal Mining Accidental Deaths.

PubMed

Huang, Yuecheng; Cheng, Wuyi; Luo, Sida; Luo, Yun; Ma, Chengchen; He, Tailin

2016-01-01

The features of the asynchronous correlation between accident indices and the factors that influence accidents can provide an effective reference for warnings of coal mining accidents. However, what are the features of this correlation? To answer this question, data from the China coal price index and the number of deaths from coal mining accidents were selected as the sample data. The fluctuation modes of the asynchronous correlation between the two data sets were defined according to the asynchronous correlation coefficients, symbolization, and sliding windows. We then built several directed and weighted network models, within which the fluctuation modes and the transformations between modes were represented by nodes and edges. Then, the features of the asynchronous correlation between these two variables could be studied from a perspective of network topology. We found that the correlation between the price index and the accidental deaths was asynchronous and fluctuating. Certain aspects, such as the key fluctuation modes, the subgroups characteristics, the transmission medium, the periodicity and transmission path length in the network, were analyzed by using complex network theory, analytical methods and spectral analysis method. These results provide a scientific reference for generating warnings for coal mining accidents based on economic indices.

Developing an Intelligent System for Diagnosis of Asthma Based on Artificial Neural Network.

PubMed

Alizadeh, Behrouz; Safdari, Reza; Zolnoori, Maryam; Bashiri, Azadeh

2015-08-01

Lack of proper diagnosis and inadequate treatment of asthma, leads to physical and financial complications. This study aimed to use data mining techniques and creating a neural network intelligent system for diagnosis of asthma. The study population is the patients who had visited one of the Lung Clinics in Tehran. Data were analyzed using the SPSS statistical tool and the chi-square Pearson's coefficient was the basis of decision making for data ranking. The considered neural network is trained using back propagation learning technique. According to the analysis performed by means of SPSS to select the top factors, 13 effective factors were selected, in different performances, data was mixed in various forms, so the different modes was made for training the data and testing networks and in all different modes, the network was able to predict correctly 100% of all cases. Using data mining methods before the design structure of system, aimed to reduce the data dimension and the optimum choice of the data, will lead to a more accurate system. So considering the data mining approaches due to the nature of medical data is necessary.

Diagnostic support for selected neuromuscular diseases using answer-pattern recognition and data mining techniques: a proof of concept multicenter prospective trial.

PubMed

Grigull, Lorenz; Lechner, Werner; Petri, Susanne; Kollewe, Katja; Dengler, Reinhard; Mehmecke, Sandra; Schumacher, Ulrike; Lücke, Thomas; Schneider-Gold, Christiane; Köhler, Cornelia; Güttsches, Anne-Katrin; Kortum, Xiaowei; Klawonn, Frank

2016-03-08

Diagnosis of neuromuscular diseases in primary care is often challenging. Rare diseases such as Pompe disease are easily overlooked by the general practitioner. We therefore aimed to develop a diagnostic support tool using patient-oriented questions and combined data mining algorithms recognizing answer patterns in individuals with selected neuromuscular diseases. A multicenter prospective study for the proof of concept was conducted thereafter. First, 16 interviews with patients were conducted focusing on their pre-diagnostic observations and experiences. From these interviews, we developed a questionnaire with 46 items. Then, patients with diagnosed neuromuscular diseases as well as patients without such a disease answered the questionnaire to establish a database for data mining. For proof of concept, initially only six diagnoses were chosen (myotonic dystrophy and myotonia (MdMy), Pompe disease (MP), amyotrophic lateral sclerosis (ALS), polyneuropathy (PNP), spinal muscular atrophy (SMA), other neuromuscular diseases, and no neuromuscular disease (NND). A prospective study was performed to validate the automated malleable system, which included six different classification methods combined in a fusion algorithm proposing a final diagnosis. Finally, new diagnoses were incorporated into the system. In total, questionnaires from 210 individuals were used to train the system. 89.5 % correct diagnoses were achieved during cross-validation. The sensitivity of the system was 93-97 % for individuals with MP, with MdMy and without neuromuscular diseases, but only 69 % in SMA and 81 % in ALS patients. In the prospective trial, 57/64 (89 %) diagnoses were predicted correctly by the computerized system. All questions, or rather all answers, increased the diagnostic accuracy of the system, with the best results reached by the fusion of different classifier methods. Receiver operating curve (ROC) and p-value analyses confirmed the results. A questionnaire-based diagnostic support tool using data mining methods exhibited good results in predicting selected neuromuscular diseases. Due to the variety of neuromuscular diseases, additional studies are required to measure beneficial effects in the clinical setting.

Text mining for search term development in systematic reviewing: A discussion of some methods and challenges.

PubMed

Stansfield, Claire; O'Mara-Eves, Alison; Thomas, James

2017-09-01

Using text mining to aid the development of database search strings for topics described by diverse terminology has potential benefits for systematic reviews; however, methods and tools for accomplishing this are poorly covered in the research methods literature. We briefly review the literature on applications of text mining for search term development for systematic reviewing. We found that the tools can be used in 5 overarching ways: improving the precision of searches; identifying search terms to improve search sensitivity; aiding the translation of search strategies across databases; searching and screening within an integrated system; and developing objectively derived search strategies. Using a case study and selected examples, we then reflect on the utility of certain technologies (term frequency-inverse document frequency and Termine, term frequency, and clustering) in improving the precision and sensitivity of searches. Challenges in using these tools are discussed. The utility of these tools is influenced by the different capabilities of the tools, the way the tools are used, and the text that is analysed. Increased awareness of how the tools perform facilitates the further development of methods for their use in systematic reviews. Copyright © 2017 John Wiley & Sons, Ltd.

Effective integrated frameworks for assessing mining sustainability.

PubMed

Virgone, K M; Ramirez-Andreotta, M; Mainhagu, J; Brusseau, M L

2018-05-28

The objectives of this research are to review existing methods used for assessing mining sustainability, analyze the limited prior research that has evaluated the methods, and identify key characteristics that would constitute an enhanced sustainability framework that would serve to improve sustainability reporting in the mining industry. Five of the most relevant frameworks were selected for comparison in this analysis, and the results show that there are many commonalities among the five, as well as some disparities. In addition, relevant components are missing from all five. An enhanced evaluation system and framework were created to provide a more holistic, comprehensive method for sustainability assessment and reporting. The proposed framework has five components that build from and encompass the twelve evaluation characteristics used in the analysis. The components include Foundation, Focus, Breadth, Quality Assurance, and Relevance. The enhanced framework promotes a comprehensive, location-specific reporting approach with a concise set of well-defined indicators. Built into the framework is quality assurance, as well as a defined method to use information from sustainability reports to inform decisions. The framework incorporates human health and socioeconomic aspects via initiatives such as community-engaged research, economic valuations, and community-initiated environmental monitoring.

Assessing semantic similarity of texts - Methods and algorithms

NASA Astrophysics Data System (ADS)

Rozeva, Anna; Zerkova, Silvia

2017-12-01

Assessing the semantic similarity of texts is an important part of different text-related applications like educational systems, information retrieval, text summarization, etc. This task is performed by sophisticated analysis, which implements text-mining techniques. Text mining involves several pre-processing steps, which provide for obtaining structured representative model of the documents in a corpus by means of extracting and selecting the features, characterizing their content. Generally the model is vector-based and enables further analysis with knowledge discovery approaches. Algorithms and measures are used for assessing texts at syntactical and semantic level. An important text-mining method and similarity measure is latent semantic analysis (LSA). It provides for reducing the dimensionality of the document vector space and better capturing the text semantics. The mathematical background of LSA for deriving the meaning of the words in a given text by exploring their co-occurrence is examined. The algorithm for obtaining the vector representation of words and their corresponding latent concepts in a reduced multidimensional space as well as similarity calculation are presented.

Directed Selection of Biochars for Amending Metal ...

EPA Pesticide Factsheets

Approximately 500,000 abandoned mines across the U.S. pose a considerable, pervasive risk to human health and the environment. World-wide the problem is even larger. Lime, organic matter, biosolids and other amendments have been used to decrease metal bioavailability in contaminated mine wastes and to promote the development of a mine waste stabilizing plant cover. The demonstrated properties of biochar make it a viable candidate as an amendment for remediating metal contaminated mine soils. In addition to sequestering potentially toxic metals, biochar can also be a source of plant nutrients, used to adjust soil pH, improve soil water holding characteristics, and increase soil carbon content. However, methods are needed for matching biochar beneficial properties with mine waste toxicities and soil health deficiencies. In this presentation we will report on a study in which we used mine soil from an abandoned Cu and Zn mine to develop a three-step procedure for identifying biochars that are most effective at reducing heavy metal bioavailability. Step 1: a slightly acidic extract of the mine spoil soil was produced, representing the potentially available metals, and used to identify metal removal properties of a library of 38 different biochars (e.g., made from a variety of feedstocks and pyrolysis or gasification conditions). Step 2: evaluation of how well these biochars retained (i.e., did not desorb) previously sorbed metals. Step 3: laboratory evalua

30 CFR 75.203 - Mining methods.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 1 2011-07-01 2011-07-01 false Mining methods. 75.203 Section 75.203 Mineral... SAFETY STANDARDS-UNDERGROUND COAL MINES Roof Support § 75.203 Mining methods. (a) The method of mining... faulty pillar recovery methods. Pillar dimensions shall be compatible with effective control of the roof...

30 CFR 75.203 - Mining methods.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 30 Mineral Resources 1 2013-07-01 2013-07-01 false Mining methods. 75.203 Section 75.203 Mineral... SAFETY STANDARDS-UNDERGROUND COAL MINES Roof Support § 75.203 Mining methods. (a) The method of mining... faulty pillar recovery methods. Pillar dimensions shall be compatible with effective control of the roof...

30 CFR 75.203 - Mining methods.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 30 Mineral Resources 1 2012-07-01 2012-07-01 false Mining methods. 75.203 Section 75.203 Mineral... SAFETY STANDARDS-UNDERGROUND COAL MINES Roof Support § 75.203 Mining methods. (a) The method of mining... faulty pillar recovery methods. Pillar dimensions shall be compatible with effective control of the roof...

30 CFR 75.203 - Mining methods.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Mining methods. 75.203 Section 75.203 Mineral... SAFETY STANDARDS-UNDERGROUND COAL MINES Roof Support § 75.203 Mining methods. (a) The method of mining... faulty pillar recovery methods. Pillar dimensions shall be compatible with effective control of the roof...

30 CFR 75.203 - Mining methods.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 30 Mineral Resources 1 2014-07-01 2014-07-01 false Mining methods. 75.203 Section 75.203 Mineral... SAFETY STANDARDS-UNDERGROUND COAL MINES Roof Support § 75.203 Mining methods. (a) The method of mining... faulty pillar recovery methods. Pillar dimensions shall be compatible with effective control of the roof...

Evolutionary optimization of radial basis function classifiers for data mining applications.

PubMed

Buchtala, Oliver; Klimek, Manuel; Sick, Bernhard

2005-10-01

In many data mining applications that address classification problems, feature and model selection are considered as key tasks. That is, appropriate input features of the classifier must be selected from a given (and often large) set of possible features and structure parameters of the classifier must be adapted with respect to these features and a given data set. This paper describes an evolutionary algorithm (EA) that performs feature and model selection simultaneously for radial basis function (RBF) classifiers. In order to reduce the optimization effort, various techniques are integrated that accelerate and improve the EA significantly: hybrid training of RBF networks, lazy evaluation, consideration of soft constraints by means of penalty terms, and temperature-based adaptive control of the EA. The feasibility and the benefits of the approach are demonstrated by means of four data mining problems: intrusion detection in computer networks, biometric signature verification, customer acquisition with direct marketing methods, and optimization of chemical production processes. It is shown that, compared to earlier EA-based RBF optimization techniques, the runtime is reduced by up to 99% while error rates are lowered by up to 86%, depending on the application. The algorithm is independent of specific applications so that many ideas and solutions can be transferred to other classifier paradigms.

Detection and Recovery of Palladium, Gold and Cobalt Metals from the Urban Mine Using Novel Sensors/Adsorbents Designated with Nanoscale Wagon-wheel-shaped Pores.

PubMed

El-Safty, Sherif A; Shenashen, Mohamed A; Sakai, Masaru; Elshehy, Emad; Halada, Kohmei

2015-12-06

Developing low-cost, efficient processes for recovering and recycling palladium, gold and cobalt metals from urban mine remains a significant challenge in industrialized countries. Here, the development of optical mesosensors/adsorbents (MSAs) for efficient recognition and selective recovery of Pd(II), Au(III), and Co(II) from urban mine was achieved. A simple, general method for preparing MSAs based on using high-order mesoporous monolithic scaffolds was described. Hierarchical cubic Ia3d wagon-wheel-shaped MSAs were fabricated by anchoring chelating agents (colorants) into three-dimensional pores and micrometric particle surfaces of the mesoporous monolithic scaffolds. Findings show, for the first time, evidence of controlled optical recognition of Pd(II), Au(III), and Co(II) ions and a highly selective system for recovery of Pd(II) ions (up to ~95%) in ores and industrial wastes. Furthermore, the controlled assessment processes described herein involve evaluation of intrinsic properties (e.g., visual signal change, long-term stability, adsorption efficiency, extraordinary sensitivity, selectivity, and reusability); thus, expensive, sophisticated instruments are not required. Results show evidence that MSAs will attract worldwide attention as a promising technological means of recovering and recycling palladium, gold and cobalt metals.

Detection and Recovery of Palladium, Gold and Cobalt Metals from the Urban Mine Using Novel Sensors/Adsorbents Designated with Nanoscale Wagon-wheel-shaped Pores

PubMed Central

El-Safty, Sherif A.; Shenashen, Mohamed A.; Sakai, Masaru; Elshehy, Emad; Halada, Kohmei

2015-01-01

Developing low-cost, efficient processes for recovering and recycling palladium, gold and cobalt metals from urban mine remains a significant challenge in industrialized countries. Here, the development of optical mesosensors/adsorbents (MSAs) for efficient recognition and selective recovery of Pd(II), Au(III), and Co(II) from urban mine was achieved. A simple, general method for preparing MSAs based on using high-order mesoporous monolithic scaffolds was described. Hierarchical cubic Ia3d wagon-wheel-shaped MSAs were fabricated by anchoring chelating agents (colorants) into three-dimensional pores and micrometric particle surfaces of the mesoporous monolithic scaffolds. Findings show, for the first time, evidence of controlled optical recognition of Pd(II), Au(III), and Co(II) ions and a highly selective system for recovery of Pd(II) ions (up to ~95%) in ores and industrial wastes. Furthermore, the controlled assessment processes described herein involve evaluation of intrinsic properties (e.g., visual signal change, long-term stability, adsorption efficiency, extraordinary sensitivity, selectivity, and reusability); thus, expensive, sophisticated instruments are not required. Results show evidence that MSAs will attract worldwide attention as a promising technological means of recovering and recycling palladium, gold and cobaltmetals. PMID:26709467

Abandoned mines and their impact on the environment: Case studies from Franklin and Sterling Mines, NJ and Rondout Quarry, NY

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kolkas, M.M.; Nehru, C.E.

1995-09-01

Water logged abandoned mines have an impact on the environment. In this project we selected abandoned mines from two sets of different ore bodies to learn about their environmental impact. Franklin and Sterling Pb-Zn mines, NJ and the limestone quarry in Rondout formation, NY were selected as case study examples. In the Pb-Zn mines metalimestone is the country rock and in the Rondout quarry limestone is the country rock. Soil water samples from selected strategic locations were analyzed for toxic and related heavy metal elements such as Pb, Zn, Cd, Cr and U. The levels of concentrations of these elementsmore » varied from one location to another according to the chemistry of the ore body and the ground movement throughout the area. In particular Cd, Cr and U concentration were variable from Franklin to Sterling mine. However, in the Rondout limestone (cement) quarry, higher concentrations of Cr and lower concentrations of Pb and Zn were noted. We conclude that ore body chemistry, mine dumps and tailing contaminated ponds along with the ground water movement throughout the area have an impact on the ground water and nearby river/stream contaminant chemistry in the areas.« less

Mine Water Treatment in Hongai Coal Mines

NASA Astrophysics Data System (ADS)

Dang, Phuong Thao; Dang, Vu Chi

2018-03-01

Acid mine drainage (AMD) is recognized as one of the most serious environmental problem associated with mining industry. Acid water, also known as acid mine drainage forms when iron sulfide minerals found in the rock of coal seams are exposed to oxidizing conditions in coal mining. Until 2009, mine drainage in Hongai coal mines was not treated, leading to harmful effects on humans, animals and aquatic ecosystem. This report has examined acid mine drainage problem and techniques for acid mine drainage treatment in Hongai coal mines. In addition, selection and criteria for the design of the treatment systems have been presented.

Optimizing Functional Network Representation of Multivariate Time Series

NASA Astrophysics Data System (ADS)

Zanin, Massimiliano; Sousa, Pedro; Papo, David; Bajo, Ricardo; García-Prieto, Juan; Pozo, Francisco Del; Menasalvas, Ernestina; Boccaletti, Stefano

2012-09-01

By combining complex network theory and data mining techniques, we provide objective criteria for optimization of the functional network representation of generic multivariate time series. In particular, we propose a method for the principled selection of the threshold value for functional network reconstruction from raw data, and for proper identification of the network's indicators that unveil the most discriminative information on the system for classification purposes. We illustrate our method by analysing networks of functional brain activity of healthy subjects, and patients suffering from Mild Cognitive Impairment, an intermediate stage between the expected cognitive decline of normal aging and the more pronounced decline of dementia. We discuss extensions of the scope of the proposed methodology to network engineering purposes, and to other data mining tasks.

Optimizing Functional Network Representation of Multivariate Time Series

PubMed Central

Zanin, Massimiliano; Sousa, Pedro; Papo, David; Bajo, Ricardo; García-Prieto, Juan; Pozo, Francisco del; Menasalvas, Ernestina; Boccaletti, Stefano

2012-01-01

By combining complex network theory and data mining techniques, we provide objective criteria for optimization of the functional network representation of generic multivariate time series. In particular, we propose a method for the principled selection of the threshold value for functional network reconstruction from raw data, and for proper identification of the network's indicators that unveil the most discriminative information on the system for classification purposes. We illustrate our method by analysing networks of functional brain activity of healthy subjects, and patients suffering from Mild Cognitive Impairment, an intermediate stage between the expected cognitive decline of normal aging and the more pronounced decline of dementia. We discuss extensions of the scope of the proposed methodology to network engineering purposes, and to other data mining tasks. PMID:22953051

Lunar resource evaluation and mine site selection

NASA Technical Reports Server (NTRS)

Bence, A. Edward

1992-01-01

Two scenarios in this evaluation of lunar mineral resources and the selection of possible mining and processing sites are considered. The first scenario assumes that no new surface or near-surface data will be available before site selection (presumably one of the Apollo sites). The second scenario assumes that additional surface geology data will have been obtained by a lunar orbiter mission, an unmanned sample return mission (or missions), and followup manned missions. Regardless of the scenario, once a potentially favorable mine site has been identified, a minimum amount of fundamental data is needed to assess the resources at that site and to evaluate its suitability for mining and downstream processing. Since much of the required data depends on the target mineral(s), information on the resource, its beneficiation, and the refining, smelting, and fabricating processes must be factored into the evaluation. The annual capacity and producing lifetime of the mine and its associated processing plant must be estimated before the resource reserves can be assessed. The available market for the product largely determines the capacity and lifetime of the mine. The Apollo 17 site is described as a possible mining site. The use of new sites is briefly addressed.

Biomining with bacteriophage: selectivity of displayed peptides for naturally occurring sphalerite and chalcopyrite.

PubMed

Curtis, Susan B; Hewitt, Jeff; Macgillivray, Ross T A; Dunbar, W Scott

2009-02-01

During mineral processing, concentrates of sulfide minerals of economic interest are formed by froth flotation of fine ore particles. The method works well but recovery and selectivity can be poor for ores with complex mineralogy. There is considerable interest in methods that improve the selectivity of this process while avoiding the high costs of using flotation chemicals. Here we show the first application of phage biotechnology to the processing of economically important minerals in ore slurries. A random heptapeptide library was screened for peptide sequences that bind selectively to the minerals sphalerite (ZnS) and chalcopyrite (CuFeS2). After several rounds of enrichment, cloned phage containing the surface peptide loops KPLLMGS and QPKGPKQ bound specifically to sphalerite. Phage containing the peptide loop TPTTYKV bound to both sphalerite and chalcopyrite. By using an enzyme-linked immunosorbant assay (ELISA), the phage was characterized as strong binders compared to wild-type phage. Specificity of binding was confirmed by immunochemical visualization of phage bound to mineral particles but not to silica (a waste mineral) or pyrite. The current study focused primarily on the isolation of ZnS-specific phage that could be utilized in the separation of sphalerite from silica. At mining sites where sphalerite and chalcopyrite are not found together in natural ores, the separation of sphalerite from silica would be an appropriate enrichment step. At mining sites where sphalerite and chalcopyrite do occur together, more specific phage would be required. This bacteriophage has the potential to be used in a more selective method of mineral separation and to be the basis for advanced methods of mineral processing.

A Comparative Analysis of the Influence of Surface Mining on Hydrological and Geochemical Response of Selected Headwater Streams in the Elk Valley, British Columbia, Canada.

NASA Astrophysics Data System (ADS)

Carey, S. K.; Shatilla, N. J.; Szmudrowska, B.; Rastelli, J.; Wellen, C.

2014-12-01

Surface mining is a common method of accessing coal. Blasting of overburden rock allows access to mineable ore. In high-elevation environments, the removed overburden rock is deposited in adjacent valleys as waste rock spoils. As part of a multi-year R&D program examining the influence of surface mining on watershed hydrological and water quality responses in the Elk Valley, British Columbia, this study reports on how surface mining affects streamflow hydrological and geochemical response at four reference and four mine-influenced catchments. The hydrology of this environment is dominated by snowmelt and steep topographic gradients. Flows were attenuated in mine-influenced catchments, with spring freshet delayed and more muted responses to precipitation events observed. Dissolved ions were an order of magnitude greater in mine-influenced streams, with more dilution-based responses to flows compared with chemostatic behavior observed in reference streams. Stable isotope signatures in stream water suggested that in both mine-influenced and reference watersheds, stream water was derived from well mixed groundwater as annual variability of stream isotope signatures was dampened compared with precipitation signatures. However, deflection of stream isotopes in response to precipitation were more apparent in reference watersheds. As a group, mine influenced catchments had a heavier isotope signature than reference watersheds, suggesting an enhanced influence of rainfall on recharge. Transit time distributions indicate existing waste rock spoils increase the average time water takes to move through the catchment.

GPR monitoring of rock mass stability in selected post-mining region in Poland

NASA Astrophysics Data System (ADS)

Golebiowski, T.

2012-04-01

Mining activity conducted over a period of many years may cause significant changes in the geological medium and in effect leads to strong degradation of the surface in mining and post-mining regions. One of the most dangerous effects of mining activity is appearance of sinkholes on the ground surface. These phenomena are related to the changes of initial stress-strain state of the rock mass as a result of mining works and the creation of fractures which migrate from excavations to the ground surface. The paper presents the results of selected GPR surveys carried out in the area of the coal mine "Siersza" in two sites, i.e. in the town of Siersza and in the village of Mloszowa (Upper Silesia, South Poland). The aim of the GPR research was 3D visualisation of fractured zones distribution generated by the mining activity and an attempt to make prediction where sinkholes would appear. In order to realize this aim the measurements were conducted in 4D mode (i.e. time-space analysis), which allowed to observe the fractured zones migration towards the ground surface. In order to obtain 4D information (x-y-z-t) GPR surveys were conducted for several years, along the same parallel profiles, separated by a constant distance equals 2.5m. The terrain measurements were carried out with RAMAC and PROEX GPR systems using 250, 200, 100 and 50 MHz antennae. Because of the limited length of this paper, only selected results from the 200-250 MHz antennae are presented. The results were presented in the form of the distribution of GPR signals energies calculated from Hilbert transform, applying the technique of energy inversion. In the site of Siersza, on the basis of 4D GPR visualisation, regions threatened with the formation of sinkholes were distinguished. A few years after the research, 2 cavities appeared in this site which proved that the interpretation was correct. Another fractured zone in this site was confirmed by a borehole. In the site of Mloszowa the GPR measurements were carried out in the region of already existing sinkhole (with the diameter of about 15m and the depth of about 10m) in order to detect the distribution of dangerous fractures around this sinkhole. As the results of GPR research has shown, fractured zones in this site developed quickly as a result of superimposition of fractures induced by mining activity and the processes of suffusion and congelifraction. GPR monitoring of the rock mass stability in mining and post-mining areas is very important because sinkholes threaten the live of people and stability of structures and installations. As it was shown in the paper, the GPR method gives very good results for the prediction of sinkholes creation if it is applied in 4D mode. A limitation of this method is the depth penetration, i.e. a dozen or so meters with resolution which allows to detect fractures and strong attenuation of electromagnetic waves in the clay formations. The research was financed from the funds of National Science Center, on the basis of agreement no. UMO-2011/01/B/ST7/06178 and decision no. DEC-2011/01/B/ST7/06178.

The Analysis of Object-Based Change Detection in Mining Area: a Case Study with Pingshuo Coal Mine

NASA Astrophysics Data System (ADS)

Zhang, M.; Zhou, W.; Li, Y.

2017-09-01

Accurate information on mining land use and land cover change are crucial for monitoring and environmental change studies. In this paper, RapidEye Remote Sensing Image (Map 2012) and SPOT7 Remote Sensing Image (Map 2015) in Pingshuo Mining Area are selected to monitor changes combined with object-based classification and change vector analysis method, we also used R in highresolution remote sensing image for mining land classification, and found the feasibility and the flexibility of open source software. The results show that (1) the classification of reclaimed mining land has higher precision, the overall accuracy and kappa coefficient of the classification of the change region map were 86.67 % and 89.44 %. It's obvious that object-based classification and change vector analysis which has a great significance to improve the monitoring accuracy can be used to monitor mining land, especially reclaiming mining land; (2) the vegetation area changed from 46 % to 40 % accounted for the proportion of the total area from 2012 to 2015, and most of them were transformed into the arable land. The sum of arable land and vegetation area increased from 51 % to 70 %; meanwhile, build-up land has a certain degree of increase, part of the water area was transformed into arable land, but the extent of the two changes is not obvious. The result illustrated the transformation of reclaimed mining area, at the same time, there is still some land convert to mining land, and it shows the mine is still operating, mining land use and land cover are the dynamic procedure.

Determination of the Zone Endangered by Methane Explosion in Goaf with Caving of Longwalls Ventilated on "Y" System

NASA Astrophysics Data System (ADS)

Brodny, Jarosław; Tutak, Magdalena

2016-12-01

One of the most dangerous and most commonly present risks in hard coal mines is methane hazard. During exploitation by longwall system with caving, methane is emitted to mine heading from the mined coal and coal left in a pile. A large amount of methane also flows from neighboring seams through cracks and fissures formed in rock mass. In a case of accumulation of explosive methane concentration in goaf zone and with appropriate oxygen concentration and occurrence of initials (e.g. spark or endogenous fire), it may come to the explosion of this gas. In the paper there are presented results of numerical analysis of mixture of air and methane streams flow through the real heading system of a mine, characterized by high methane hazard. The aim of the studies was to analyze the ventilation system of considered heading system and determination of braking zones in goaf zone, in which dangerous and explosive concertation of methane can occur with sufficient oxygen concentration equal to at least 12%. Determination of position of these zones is necessary for the selection of appropriate parameters of the ventilation system to ensure safety of the crew. Analysis of the scale of methane hazard allows to select such a ventilation system of exploitation and neighboring headings that ensures chemical composition of mining atmosphere required by regulation, and required efficiency of methane drainage. The obtained results clearly show that numerical methods, combined with the results of tests in real conditions can be successfully used for the analysis of variants of processes related to ventilation of underground mining, and also in the analysis of emergency states.

Poly(vinyl alcohol)/hydroxyapatite Monolithic In-Needle Extraction (MINE) device: Preparation and examination of drug affinity.

PubMed

Pietrzyńska, Monika; Czerwiński, Michał; Voelkel, Adam

2017-07-15

Polymer-ceramic materials based on poly(vinyl alcohol) (PVA) and hydroxyapatite were applied as sorption material in Monolithic In-Needle Extraction (MINE) device. The presented device provides new possibilities for the examination of bisphosphonates affinity for bone and will be a helpful tool in evaluation of potential antiresorptive drugs suitability. A ceramic part of monoliths was prepared by incorporation of hydroxyapatite (HA) into the reaction mixture or by using a soaking method (mineralization of HA on the PVA). The parameters of synthesis conditions were optimized to achieve a monolithic material having the appropriate dimensions after the soaking process enabling placing of the monolithic material inside the needle. Furthermore, the material must have had optimal dimensions after the re-soaking process to fit perfectly to the needle. Among the sixteen monolithic materials, eight of them were selected for further study, and then four of them were selected as a sorbent material for the MINE device. The material properties were examined on the basis of several parameters: swelling ratio, initial mass reversion and initial diameter reversion, mass growth due to the HA formation, and antiresorptive drug sorption. The MINE device might be then used as a tool for examination of interactions between bisphosphonate and bone. The simulated body fluid containing sodium risedronate (RSD) as a standard compound was passed through the MINE device. The obtained device allowed for sorption about 0.38mg of RSD. The desorption process was carried out in five steps allowing insightful analysis. The MINE device turned out to be a helpful tool for determination of the bisphosphonates affinity to the ceramic part of sorbent (hydroxyapatite) and to assess the usefulness of them as antiresorptive drugs in the future. Copyright © 2017 Elsevier B.V. All rights reserved.

[An investigation of lanthanum and other metals levels in blood, urine and hair among residents in the rare earth mining area of a city in China].

PubMed

Bao, T M; Tian, Y; Wang, L X; Wu, T; Lu, L N; Ma, H Y; Wang, L

2018-02-20

Objective: To investigate the levels of lanthanum, cerium, praseodymium, and neodymium in the blood, urine, and hair samples from residents in the rare earth mining area of a city in China, and to provide a scientific basis for the control of rare earth pollution and the protection of population health. Methods: A total of 147 residents who had lived in the rare earth mining area of a city for a long time were selected as the exposure group, and 108 residents in Guyang County of this city who lived 91 km away from the rare earth mining area were selected as the control group. Blood, urine, and hair samples were collected from the residents in both groups. Inductively coupled plasma mass spectrometry was used to determine the content of lanthanum, cerium, praseodymium, and neodymium in blood, urine, and hair samples. Results: In the exposure group, the median levels of lanthanum, cerium, praseodymium, and neodymium were 0.854, 1.724, 0.132, and 0.839 μg/L, respectively, in blood samples, 0.420, 0.920, 0.055, and 0.337 μg/L, respectively, in urine samples, and 0.052, 0.106, 0.012, and 0.045 μg/g, respectively, in hair samples. The exposure group had significantly higher levels of the four rare earth elements in blood, urine, and hair samples than the control group ( P <0.01) . Conclusion: The residents in the rare earth mining area of this city have higher content of lanthanum, cerium, praseodymium, and neodymium in blood, urine, and hair than those in the non-mining area; the content of cerium is highest, followed by lanthanum, neodymium, and praseodymium.

Study of the Rock Mass Failure Process and Mechanisms During the Transformation from Open-Pit to Underground Mining Based on Microseismic Monitoring

NASA Astrophysics Data System (ADS)

Zhao, Yong; Yang, Tianhong; Bohnhoff, Marco; Zhang, Penghai; Yu, Qinglei; Zhou, Jingren; Liu, Feiyue

2018-05-01

To quantitatively understand the failure process and failure mechanism of a rock mass during the transformation from open-pit mining to underground mining, the Shirengou Iron Mine was selected as an engineering project case study. The study area was determined using the rock mass basic quality classification method and the kinematic analysis method. Based on the analysis of the variations in apparent stress and apparent volume over time, the rock mass failure process was analyzed. According to the recent research on the temporal and spatial change of microseismic events in location, energy, apparent stress, and displacement, the migration characteristics of rock mass damage were studied. A hybrid moment tensor inversion method was used to determine the rock mass fracture source mechanisms, the fracture orientations, and fracture scales. The fracture area can be divided into three zones: Zone A, Zone B, and Zone C. A statistical analysis of the orientation information of the fracture planes orientations was carried out, and four dominant fracture planes were obtained. Finally, the slip tendency analysis method was employed, and the unstable fracture planes were obtained. The results show: (1) The microseismic monitoring and hybrid moment tensor analysis can effectively analyze the failure process and failure mechanism of rock mass, (2) during the transformation from open-pit to underground mining, the failure type of rock mass is mainly shear failure and the tensile failure is mostly concentrated in the roof of goafs, and (3) the rock mass of the pit bottom and the upper of goaf No. 18 have the possibility of further damage.

MANAGEMENT AND TREATMENT OF WATER FROM HARD-ROCK MINES {ENGINEERING ISSUE}

EPA Science Inventory

This Engineering Issue document on treatment of mining waters is a practical guide to understanding and selecting technologies for the environmental management of waste materials and effluents at hard-rock mines. For the purposes of this discussion, hard-rock mining primarily ref...

Mitigating Impacts Of Arsenic Contaminated Materials Via Two (2) Stabilization Methods Based On Polymeric And Cement Binders

EPA Science Inventory

The primary objective of this study was to evaluate the performance of two selected chemical stabilization and solidification (S/S) techniques to treat three types of arsenic-contaminated wastes 1) chromated copper arsenate (CCA) wood treater waste, 2) La Trinidad Mine tailings, ...

Unsupervised MDP Value Selection for Automating ITS Capabilities

ERIC Educational Resources Information Center

Stamper, John; Barnes, Tiffany

2009-01-01

We seek to simplify the creation of intelligent tutors by using student data acquired from standard computer aided instruction (CAI) in conjunction with educational data mining methods to automatically generate adaptive hints. In our previous work, we have automatically generated hints for logic tutoring by constructing a Markov Decision Process…

[Retrieval of Copper Pollution Information from Hyperspectral Satellite Data in a Vegetation Cover Mining Area].

PubMed

Qu, Yong-hua; Jiao, Si-hong; Liu, Su-hong; Zhu, Ye-qing

2015-11-01

Heavy metal mining activities have caused the complex influence on the ecological environment of the mining regions. For example, a large amount of acidic waste water containing heavy metal ions have be produced in the process of copper mining which can bring serious pollution to the ecological environment of the region. In the previous research work, bare soil is mainly taken as the research target when monitoring environmental pollution, and thus the effects of land surface vegetation have been ignored. It is well known that vegetation condition is one of the most important indictors to reflect the ecological change in a certain region and there is a significant linkage between the vegetation spectral characteristics and the heavy metal when the vegetation is effected by the heavy metal pollution. It means the vegetation is sensitive to heavy metal pollution by their physiological behaviors in response to the physiological ecology change of their growing environment. The conventional methods, which often rely on large amounts of field survey data and laboratorial chemical analysis, are time consuming and costing a lot of material resources. The spectrum analysis method using remote sensing technology can acquire the information of the heavy mental content in the vegetation without touching it. However, the retrieval of that information from the hyperspectral data is not an easy job due to the difficulty in figuring out the specific band, which is sensitive to the specific heavy metal, from a huge number of hyperspectral bands. Thus the selection of the sensitive band is the key of the spectrum analysis method. This paper proposed a statistical analysis method to find the feature band sensitive to heavy metal ion from the hyperspectral data and to then retrieve the metal content using the field survey data and the hyperspectral images from China Environment Satellite HJ-1. This method selected copper ion content in the leaves as the indicator of copper pollution level, using stepwise multiple linear regression and cross validation on the dataset which is consisting of 44 groups of copper ion content information in the polluted vegetation leaves from Dexing Copper Mine in Jiangxi Province to build up a statistical model by also incorporating the HJ-1 satellite images. This model was then used to estimate the copper content distribution over the whole research area at Dexing Copper Mine. The result has shown that there is strong statistical significance of the model which revealed the most sensitive waveband to copper ion is located at 516 nm. The distribution map illustrated that the copper ion content is generally in the range of 0-130 mg · kg⁻¹ in the vegetation covering area at Dexing Copper Mine and the most seriously polluted area is located at the South-east corner of Dexing City as well as the mining spots with a higher value between 80 and 100 mg · kg⁻¹. This result is consistent with the ground observation experiment data. The distribution map can certainly provide some important basic data on the copper pollution monitoring and treatment.

Application and Exploration of Big Data Mining in Clinical Medicine

PubMed Central

Zhang, Yue; Guo, Shu-Li; Han, Li-Na; Li, Tie-Ling

2016-01-01

Objective: To review theories and technologies of big data mining and their application in clinical medicine. Data Sources: Literatures published in English or Chinese regarding theories and technologies of big data mining and the concrete applications of data mining technology in clinical medicine were obtained from PubMed and Chinese Hospital Knowledge Database from 1975 to 2015. Study Selection: Original articles regarding big data mining theory/technology and big data mining's application in the medical field were selected. Results: This review characterized the basic theories and technologies of big data mining including fuzzy theory, rough set theory, cloud theory, Dempster–Shafer theory, artificial neural network, genetic algorithm, inductive learning theory, Bayesian network, decision tree, pattern recognition, high-performance computing, and statistical analysis. The application of big data mining in clinical medicine was analyzed in the fields of disease risk assessment, clinical decision support, prediction of disease development, guidance of rational use of drugs, medical management, and evidence-based medicine. Conclusion: Big data mining has the potential to play an important role in clinical medicine. PMID:26960378

Fluvial sediment study of Fishtrap and Dewey Lakes drainage basins, Kentucky - Virginia

USGS Publications Warehouse

Curtis, William F.; Flint, Russell F.; George, Frederick H.; Santos, John F.

1978-01-01

Fourteen drainage basins above Fishtrap and Dewey Lakes in the Levisa Fork and Johns Creek drainage basins of eastern Kentucky and southwestern Virginia were studied to determine sedimentation rates and origin of sediment entering the two lakes. The basins ranged in size from 1.68 to 297 square miles. Sediment yields ranged from 2,890 to 21,000 tons per square mile where surface-mining techniques predominated, and from 732 to 3 ,470 tons per square mile where underground mining methods predominated. Yields, in terms of tons per acre-foot of runoff, ranged from 2.2 to 15 for surface-mined areas, and from 0.5 to 2.7 for underground-mined areas. Water and sediment discharges from direct runoff during storms were compared for selected surface-mined and underground-mined areas. Data points of two extensively surface-mined areas, one from the current project and one from a previous project in Beaver Creek basin, McCreary County, Kentucky, grouped similarly in magnitude and by season. Disturbed areas from mining activities determined from aerial photographs reached 17 percent in one study area where extensive surface mining was being practiced. For most areas where underground mining was practiced, percentage disturbed area was almost negligible. Trap efficiency of Fishtrap Lake was 89 percent, and was 62 percent for Dewey Lake. Average annual deposition rates were 464 and 146 acre-feet for Fishtrap and Dewey Lakes, respectively. The chemical quality of water in the Levisa Fork basin has been altered by man 's activities. (Woodard-USGS)

Mining Available Data from the United States Environmental ...

EPA Pesticide Factsheets

Demands for quick and accurate life cycle assessments create a need for methods to rapidly generate reliable life cycle inventories (LCI). Data mining is a suitable tool for this purpose, especially given the large amount of available governmental data. These data are typically applied to LCIs on a case-by-case basis. As linked open data becomes more prevalent, it may be possible to automate LCI using data mining by establishing a reproducible approach for identifying, extracting, and processing the data. This work proposes a method for standardizing and eventually automating the discovery and use of publicly available data at the United States Environmental Protection Agency for chemical-manufacturing LCI. The method is developed using a case study of acetic acid. The data quality and gap analyses for the generated inventory found that the selected data sources can provide information with equal or better reliability and representativeness on air, water, hazardous waste, on-site energy usage, and production volumes but with key data gaps including material inputs, water usage, purchased electricity, and transportation requirements. A comparison of the generated LCI with existing data revealed that the data mining inventory is in reasonable agreement with existing data and may provide a more-comprehensive inventory of air emissions and water discharges. The case study highlighted challenges for current data management practices that must be overcome to successfu

Optimizing longwall mine layouts

DOE Office of Scientific and Technical Information (OSTI.GOV)

Minkel, M.J.

1996-12-31

Before spending the time to design an underground mine in detail, the mining engineer should be assured of the economic viability of the location of the layout. This has historically been a trial-and-error, iterative process. Traditional underground mine planning usually bases the layout on the geological characteristics of a deposit such as minimum seam height, quality, and the absence of faults. Whether one attempts to make a decision manually. or use traditional mine planning software, the process works something like this: First you build geological model. Then you impose a {open_quotes}best guess{close_quotes} as to which geological layers will become partmore » of the mined product, or will influence mining. Next you place your design where you believe is the best location to make a mine. Then you select equipment which you believe will cost-effectively mine the area. Finally, you schedule your equipment selection through the design over the mine life, run financial analyses and see if the rate of return is acceptable. If the NPV is acceptable, the design is accepted. If the NPV is not acceptable, the engineer has to restart the cycle of redesigning the layout, rescheduling the equipment, and restudying the economics again.« less

Assessing the Impact of Removing Select Materials from Coal Mine Overburden, Central Appalachia Region, USA

EPA Science Inventory

The exposure of readily soluble components of overburden materials from surface coal mining to air and water results in mineral oxidation and carbonate mineral dissolution, thus increasing coal mine water conductivity. A conductivity benchmark of 300 µS/cm for mine water dischar...

Assessing the Environmental and Socio-Economic Impacts of Artisanal Gold Mining on the Livelihoods of Communities in the Tarkwa Nsuaem Municipality in Ghana.

PubMed

Obiri, Samuel; Mattah, Precious A D; Mattah, Memuna M; Armah, Frederick A; Osae, Shiloh; Adu-kumi, Sam; Yeboah, Philip O

2016-01-26

Gold mining has played an important role in Ghana's economy, however the negative environmental and socio-economic effects on the host communities associated with gold mining have overshadowed these economic gains. It is within this context that this paper assessed in an integrated manner the environmental and socio-economic impacts of artisanal gold mining in the Tarkwa Nsuaem Municipality from a natural and social science perspective. The natural science group collected 200 random samples on bi-weekly basis between January to October 2013 from water bodies in the study area for analysis in line with methods outlined by the American Water Works Association, while the social science team interviewed 250 residents randomly selected for interviews on socio-economic issues associated with mining. Data from the socio-economic survey was analyzed using logistic regression with SPSS version 17. The results of the natural science investigation revealed that the levels of heavy metals in water samples from the study area in most cases exceeded GS 175-1/WHO permissible guideline values, which are in tandem with the results of inhabitants' perceptions of water quality survey (as 83% of the respondents are of the view that water bodies in the study area are polluted). This calls for cost-benefits analysis of mining before new mining leases are granted by the relevant authorities.

Assessing the Environmental and Socio-Economic Impacts of Artisanal Gold Mining on the Livelihoods of Communities in the Tarkwa Nsuaem Municipality in Ghana

PubMed Central

Obiri, Samuel; Mattah, Precious A. D.; Mattah, Memuna M.; Armah, Frederick A.; Osae, Shiloh; Adu-kumi, Sam; Yeboah, Philip O.

2016-01-01

Gold mining has played an important role in Ghana’s economy, however the negative environmental and socio-economic effects on the host communities associated with gold mining have overshadowed these economic gains. It is within this context that this paper assessed in an integrated manner the environmental and socio-economic impacts of artisanal gold mining in the Tarkwa Nsuaem Municipality from a natural and social science perspective. The natural science group collected 200 random samples on bi-weekly basis between January to October 2013 from water bodies in the study area for analysis in line with methods outlined by the American Water Works Association, while the social science team interviewed 250 residents randomly selected for interviews on socio-economic issues associated with mining. Data from the socio-economic survey was analyzed using logistic regression with SPSS version 17. The results of the natural science investigation revealed that the levels of heavy metals in water samples from the study area in most cases exceeded GS 175-1/WHO permissible guideline values, which are in tandem with the results of inhabitants’ perceptions of water quality survey (as 83% of the respondents are of the view that water bodies in the study area are polluted). This calls for cost-benefits analysis of mining before new mining leases are granted by the relevant authorities. PMID:26821039

Text feature extraction based on deep learning: a review.

PubMed

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.

Geomechanical Assessments of Simultaneous Operation in the Case of Transition from Open Pit to Underground Mine in Vietnam

NASA Astrophysics Data System (ADS)

Niedbalski, Zbigniew; Nguyen, Phu Minh Vuong; Widzyk-Capehart, Eleonora

2018-03-01

Nowadays, for a number of reasons, many open pit mines are considering a transition from Open Pit (OP) to Underground (UG) to remain competitive. In OP-UG transition, UG operation is operated simultaneously with the OP operation for a certain period of time. Guidelines for the simultaneous operation of OP and UG are very difficult to establish, as there are very few case studies available. Yet, because of the OP-UG interactions; the operation has a higher safety, technical and management requirements than the OP or UG methods when considered separately. In Vietnam, Cao Son is one of many OP mines, which decided to change the operational system from OP to UG. Simultaneous operation started in 2015 and will be conducted until 2030 when the OP mine Cao Son ends its mining activities. In this paper, selected geomechanical considerations of the simultaneous operation are presented. A number of numerical modelling calculations using finitedifference software with code FLAC were carried out for calibration process, slope stability analysis and the OP-UG interaction analysis for the Cao Son - Khe Cham II-IV mine. Based on the results obtained from numerical modelling, the geomechanical assessments of simultaneous operation Cao Son - Khe Cham II-IV are discussed in this paper.

Mechanization for Optimal Landscape Reclamation

NASA Astrophysics Data System (ADS)

Vondráčková, Terezie; Voštová, Věra; Kraus, Michal

2017-12-01

Reclamation is a method of ultimate utilization of land adversely affected by mining or other industrial activity. The paper explains the types of reclamation and the term “optimal reclamation”. Technological options of the long-lasting process of mine dumps reclamation starting with the removal of overlying rocks, transport and backfilling up to the follow-up remodelling of the mine dumps terrain. Technological units and equipment for stripping flow division. Stripping flow solution with respect to optimal reclamation. We recommend that the application of logistic chains and mining simulation with follow-up reclamation to open-pit mines be used for the implementation of optimal reclamation. In addition to a database of local heterogeneities of the stripped soil and reclaimed land, the flow of earths should be resolved in a manner allowing the most suitable soil substrate to be created for the restoration of agricultural and forest land on mine dumps. The methodology under development for the solution of a number of problems, including the geological survey of overlying rocks, extraction of stripping, their transport and backfilling in specified locations with the follow-up deployment of goal-directed reclamation. It will make possible to reduce the financial resources needed for the complex process chain by utilizing GIS, GPS and DGPS technologies, logistic tools and synergistic effects. When selecting machines for transport, moving and spreading of earths, various points of view and aspects must be taken into account. Among such aspects are e.g. the kind of earth to be operated by the respective construction machine, the kind of work activities to be performed, the machine’s capacity, the option to control the machine’s implement and economic aspects and clients’ requirements. All these points of view must be considered in the decision-making process so that the selected machine is capable of executing the required activity and that the use of an unsuitable machine is eliminated as it would result in a delay and increase in the project costs. Therefore, reclamation always includes extensive earth-moving work activities restoring the required relief of the land being reclaimed. Using the earth-moving machine capacity, the kind of soil in mine dumps, the kind of the work activity performed and the machine design, a SW application has been developed that allows the most suitable machine for the respective work technology to be selected with a view to preparing the land intended for reclamation.

Discovery: an interactive resource for the rational selection and comparison of putative drug target proteins in malaria

PubMed Central

Joubert, Fourie; Harrison, Claudia M; Koegelenberg, Riaan J; Odendaal, Christiaan J; de Beer, Tjaart AP

2009-01-01

Background Up to half a billion human clinical cases of malaria are reported each year, resulting in about 2.7 million deaths, most of which occur in sub-Saharan Africa. Due to the over-and misuse of anti-malarials, widespread resistance to all the known drugs is increasing at an alarming rate. Rational methods to select new drug target proteins and lead compounds are urgently needed. The Discovery system provides data mining functionality on extensive annotations of five malaria species together with the human and mosquito hosts, enabling the selection of new targets based on multiple protein and ligand properties. Methods A web-based system was developed where researchers are able to mine information on malaria proteins and predicted ligands, as well as perform comparisons to the human and mosquito host characteristics. Protein features used include: domains, motifs, EC numbers, GO terms, orthologs, protein-protein interactions, protein-ligand interactions and host-pathogen interactions among others. Searching by chemical structure is also available. Results An in silico system for the selection of putative drug targets and lead compounds is presented, together with an example study on the bifunctional DHFR-TS from Plasmodium falciparum. Conclusion The Discovery system allows for the identification of putative drug targets and lead compounds in Plasmodium species based on the filtering of protein and chemical properties. PMID:19642978

Comparsion analysis of data mining models applied to clinical research in traditional Chinese medicine.

PubMed

Zhao, Yufeng; Xie, Qi; He, Liyun; Liu, Baoyan; Li, Kun; Zhang, Xiang; Bai, Wenjing; Luo, Lin; Jing, Xianghong; Huo, Ruili

2014-10-01

To help researchers selecting appropriate data mining models to provide better evidence for the clinical practice of Traditional Chinese Medicine (TCM) diagnosis and therapy. Clinical issues based on data mining models were comprehensively summarized from four significant elements of the clinical studies: symptoms, symptom patterns, herbs, and efficacy. Existing problems were further generalized to determine the relevant factors of the performance of data mining models, e.g. data type, samples, parameters, variable labels. Combining these relevant factors, the TCM clinical data features were compared with regards to statistical characters and informatics properties. Data models were compared simultaneously from the view of applied conditions and suitable scopes. The main application problems were the inconsistent data type and the small samples for the used data mining models, which caused the inappropriate results, even the mistake results. These features, i.e. advantages, disadvantages, satisfied data types, tasks of data mining, and the TCM issues, were summarized and compared. By aiming at the special features of different data mining models, the clinical doctors could select the suitable data mining models to resolve the TCM problem.

A baseline lunar mine

NASA Technical Reports Server (NTRS)

Gertsch, Richard E.

1992-01-01

A models lunar mining method is proposed that illustrates the problems to be expected in lunar mining and how they might be solved. While the method is quite feasible, it is, more importantly, a useful baseline system against which to test other, possible better, methods. Our study group proposed the slusher to stimulate discussion of how a lunar mining operation might be successfully accomplished. Critics of the slusher system were invited to propose better methods. The group noted that while nonterrestrial mining has been a vital part of past space manufacturing proposals, no one has proposed a lunar mining system in any real detail. The group considered it essential that the design of actual, workable, and specific lunar mining methods begin immediately. Based on an earlier proposal, the method is a three-drum slusher, also known as a cable-operated drag scraper. Its terrestrial application is quite limited, as it is relatively inefficient and inflexible. The method usually finds use in underwater mining from the shore and in moving small amounts of ore underground. When lunar mining scales up, the lunarized slusher will be replaced by more efficient, high-volume methods. Other aspects of lunar mining are discussed.

Features of the Asynchronous Correlation between the China Coal Price Index and Coal Mining Accidental Deaths

PubMed Central

Huang, Yuecheng; Cheng, Wuyi; Luo, Sida; Luo, Yun; Ma, Chengchen; He, Tailin

2016-01-01

The features of the asynchronous correlation between accident indices and the factors that influence accidents can provide an effective reference for warnings of coal mining accidents. However, what are the features of this correlation? To answer this question, data from the China coal price index and the number of deaths from coal mining accidents were selected as the sample data. The fluctuation modes of the asynchronous correlation between the two data sets were defined according to the asynchronous correlation coefficients, symbolization, and sliding windows. We then built several directed and weighted network models, within which the fluctuation modes and the transformations between modes were represented by nodes and edges. Then, the features of the asynchronous correlation between these two variables could be studied from a perspective of network topology. We found that the correlation between the price index and the accidental deaths was asynchronous and fluctuating. Certain aspects, such as the key fluctuation modes, the subgroups characteristics, the transmission medium, the periodicity and transmission path length in the network, were analyzed by using complex network theory, analytical methods and spectral analysis method. These results provide a scientific reference for generating warnings for coal mining accidents based on economic indices. PMID:27902748

[Evaluation of environmental conditions: air, water and soil in areas of mining activity in Boyacá, Colombia].

PubMed

Agudelo-Calderón, Carlos A; Quiroz-Arcentales, Leonardo; García-Ubaque, Juan C; Robledo-Martínez, Rocío; García-Ubaque, Cesar A

2016-02-01

Objectives To determine concentrations of PM10, mercury and lead in indoor air of homes, water sources and soil in municipalities near mining operations. Method 6 points were evaluated in areas of influence and 2 in control areas. For measurements of indoor air, we used the NIOSH 600 method (PM10), NIOSH 6009 (mercury) and NIOSH 7300 (lead). For water analysis we used the IDEAM Guide for monitoring discharges. For soil analysis, we used the cold vapor technique (mercury) and atomic absorption (lead). Results In almost all selected households, the average PM10 and mercury concentrations in indoor air exceeded applicable air quality standards. Concentrations of lead were below standard levels. In all water sources, high concentrations of lead were found and in some places within the mining areas, high levels of iron, aluminum and mercury were also found. In soil, mercury concentrations were below the detection level and for lead, differences between the monitored points were observed. Conclusions The results do not establish causal relationships between mining and concentration of these pollutants in the evaluated areas because of the multiplicity of sources in the area. However, such studies provide important information, useful to agents of the environmental health system and researchers. Installation of networks for environmental monitoring to obtain continuous reports is suggested.

Consideration of Kaolinite Interference Correction for Quartz Measurements in Coal Mine Dust

PubMed Central

Lee, Taekhee; Chisholm, William P.; Kashon, Michael; Key-Schwartz, Rosa J.; Harper, Martin

2015-01-01

Kaolinite interferes with the infrared analysis of quartz. Improper correction can cause over- or underestimation of silica concentration. The standard sampling method for quartz in coal mine dust is size selective, and, since infrared spectrometry is sensitive to particle size, it is intuitively better to use the same size fractions for quantification of quartz and kaolinite. Standard infrared spectrometric methods for quartz measurement in coal mine dust correct interference from the kaolinite, but they do not specify a particle size for the material used for correction. This study compares calibration curves using as-received and respirable size fractions of nine different examples of kaolinite in the different correction methods from the National Institute for Occupational Safety and Health Manual of Analytical Methods (NMAM) 7603 and the Mine Safety and Health Administration (MSHA) P-7. Four kaolinites showed significant differences between calibration curves with as-received and respirable size fractions for NMAM 7603 and seven for MSHA P-7. The quartz mass measured in 48 samples spiked with respirable fraction silica and kaolinite ranged between 0.28 and 23% (NMAM 7603) and 0.18 and 26% (MSHA P-7) of the expected applied mass when the kaolinite interference was corrected with respirable size fraction kaolinite. This is termed “deviation,” not bias, because the applied mass is also subject to unknown variance. Generally, the deviations in the spiked samples are larger when corrected with the as-received size fraction of kaolinite than with the respirable size fraction. Results indicate that if a kaolinite correction with reference material of respirable size fraction is applied in current standard methods for quartz measurement in coal mine dust, the quartz result would be somewhat closer to the true exposure, although the actual mass difference would be small. Most kinds of kaolinite can be used for laboratory calibration, but preferably, the size fraction should be the same as the coal dust being collected. PMID:23767881

Consideration of kaolinite interference correction for quartz measurements in coal mine dust.

PubMed

Lee, Taekhee; Chisholm, William P; Kashon, Michael; Key-Schwartz, Rosa J; Harper, Martin

2013-01-01

Kaolinite interferes with the infrared analysis of quartz. Improper correction can cause over- or underestimation of silica concentration. The standard sampling method for quartz in coal mine dust is size selective, and, since infrared spectrometry is sensitive to particle size, it is intuitively better to use the same size fractions for quantification of quartz and kaolinite. Standard infrared spectrometric methods for quartz measurement in coal mine dust correct interference from the kaolinite, but they do not specify a particle size for the material used for correction. This study compares calibration curves using as-received and respirable size fractions of nine different examples of kaolinite in the different correction methods from the National Institute for Occupational Safety and Health Manual of Analytical Methods (NMAM) 7603 and the Mine Safety and Health Administration (MSHA) P-7. Four kaolinites showed significant differences between calibration curves with as-received and respirable size fractions for NMAM 7603 and seven for MSHA P-7. The quartz mass measured in 48 samples spiked with respirable fraction silica and kaolinite ranged between 0.28 and 23% (NMAM 7603) and 0.18 and 26% (MSHA P-7) of the expected applied mass when the kaolinite interference was corrected with respirable size fraction kaolinite. This is termed "deviation," not bias, because the applied mass is also subject to unknown variance. Generally, the deviations in the spiked samples are larger when corrected with the as-received size fraction of kaolinite than with the respirable size fraction. Results indicate that if a kaolinite correction with reference material of respirable size fraction is applied in current standard methods for quartz measurement in coal mine dust, the quartz result would be somewhat closer to the true exposure, although the actual mass difference would be small. Most kinds of kaolinite can be used for laboratory calibration, but preferably, the size fraction should be the same as the coal dust being collected.

Explosion-assisted preparation of dispersed gold-bearing different-grade ore for selective mining

NASA Astrophysics Data System (ADS)

Trubachev, AI; Zykov, NV

2017-02-01

It is found that there are transient zones (between quality and off-quality ore areas) with the respective content of useful component in an ore body, and a variant of explosive treatment of such zones before the selective mining is put forward. Practicability of two processing technologies is evaluated: processing of high-grade and low-grade ore from the transient zones and heap leaching of metals from the low-grade and impoverished ore. Open mining technology is conventional truck-and-shovel scheme, with distributed ore flows to processing plant and (or) to heap leaching, which generally enhances the mine efficiency.

Selection of the open pit mining cut-off grade strategy under price uncertainty using a risk based multi-criteria ranking system / Wybór strategii określania warunku opłacalności wydobycia w kopalniach odkrywkowych w warunkach niepewności cen w oparciu o wielokryterialny system rankingowy z uwzględnieniem czynników ryzyka

NASA Astrophysics Data System (ADS)

Azimi, Yousue; Osanloo, Montza; Esfahanipour, Akbar

2012-12-01

Cut-off Grade Strategy (COGS) is a concept that directly influences the financial, technical, economic, environmental, and legal issues in relation to exploitation of a mineral resource. A decision making system is proposed to select the best technically feasible COGS under price uncertainty. In the proposed system both the conventional discounted cash flow and modern simulation based real option valuations are used to evaluate the alternative strategies. Then the conventional expected value criterion and a multiple criteria ranking system were used to rank the strategies based on the two valuation methods. In the multiple criteria ranking system besides the expected value other stochastic orders expressing abilities of strategies in producing extra profits, minimizing losses and achieving the predefined goals of the exploitation strategy are considered. Finally, the best strategy is selected based on the overall average rank of strategies through all ranking systems. The proposed system was examined using the data of Sungun Copper Mine. To assess the merits of the alternatives better, ranking process was done at both high (prevailing economic condition) and low price conditions. Ranking results revealed that at different price conditions and valuation methods, different results would be obtained. It is concluded that these differences are due to the different behavior of the embedded option to close the mine early, which is more likely to be exercised under low price condition rather than high price condition. The proposed system would enhance the quality of decision making process by providing a more informative and certain platform for project evaluation.

An examination of the effects of mountaintop removal coal mining on respiratory symptoms and COPD using propensity scores.

PubMed

Hendryx, Michael; Luo, Juhua

2015-01-01

Previous research on public health consequences of mountaintop removal (MTR) coal mining has been limited by the observational nature of the data. The current study used propensity scores, a method designed to overcome this limitation, to draw more confident causal inferences about mining effects on respiratory health using non-experimental data. These data come from a health survey of 682 adults residing in two rural areas of Virginia, USA characterized by the presence or absence of MTR mining. Persons with a history of occupational exposure as coal miners were excluded. Nine covariates including age, sex, current and former smoking, overweight, obesity, high school education, college education, and exposure to coal as a home-heating source were selected to estimate propensity scores. Propensity scores were tested for balance and then used as weights to create quasi-experimental exposed and unexposed groups. Results indicated that persons in the mountaintop mining group had significantly (p < 0.0001) elevated prevalence of respiratory symptoms and chronic obstructive pulmonary disease. The results suggest that impaired respiratory health results from exposure to MTR environments and not from other risks.

Habitat manipulation influences northern bobwhite resource selection on a reclaimed surface mine

USGS Publications Warehouse

Brooke, Jarred M.; Peters, David C.; Unger, Ashley M.; Tanner, Evan P.; Harper, Craig A.; Keyser, Patrick D.; Clark, Joseph D.; Morgan, John J.

2015-01-01

More than 600,000 ha of mine land have been reclaimed in the eastern United States, providing large contiguous tracts of early successional vegetation that can be managed for northern bobwhite (Colinus virginianus). However, habitat quality on reclaimed mine land can be limited by extensive coverage of non-native invasive species, which are commonly planted during reclamation. We used discrete-choice analysis to investigate bobwhite resource selection throughout the year on Peabody Wildlife Management Area, a 3,330-ha reclaimed surface mine in western Kentucky. We used a treatment-control design to study resource selection at 2 spatial scales to identify important aspects of mine land vegetation and whether resource selection differed between areas with habitat management (i.e., burning, disking, herbicide; treatment) and unmanaged units (control). Our objectives were to estimate bobwhite resource selection on reclaimed mine land and to estimate the influence of habitat management practices on resource selection. We used locations from 283 individuals during the breeding season (1 Apr–30 Sep) and 136 coveys during the non-breeding season (1 Oct–Mar 31) from August 2009 to March 2014. Individuals were located closer to shrub cover than would be expected at random throughout the year. During the breeding season, individuals on treatment units used areas with smaller contagion index values (i.e., greater interspersion) compared with individuals on control units. During the non-breeding season, birds selected areas with greater shrub-open edge density compared with random. At the microhabitat scale, individuals selected areas with increased visual obstruction >1 m aboveground. During the breeding season, birds were closer to disked areas (linear and non-linear) than would be expected at random. Individuals selected non-linear disked areas during winter but did not select linear disked areas (firebreaks) because they were planted to winter wheat each fall and lacked cover during the non-breeding season. Individuals also selected areas treated with herbicide to control sericea lespedeza (Lespedeza cuneata) throughout the year. During the breeding season, bobwhites avoided areas burned during the previous dormant season. Habitat quality of reclaimed mine lands may be limited by a lack of shrub cover and extensive coverage of non-native herbaceous vegetation. Managers aiming to increase bobwhite abundance should focus on increasing interspersion of shrub cover, with no area >100 m from shrub cover. We suggest disking and herbicide application to control invasive species and improve the structure and composition of vegetation for bobwhites.

Data mining in bioinformatics using Weka.

PubMed

Frank, Eibe; Hall, Mark; Trigg, Len; Holmes, Geoffrey; Witten, Ian H

2004-10-12

The Weka machine learning workbench provides a general-purpose environment for automatic classification, regression, clustering and feature selection-common data mining problems in bioinformatics research. It contains an extensive collection of machine learning algorithms and data pre-processing methods complemented by graphical user interfaces for data exploration and the experimental comparison of different machine learning techniques on the same problem. Weka can process data given in the form of a single relational table. Its main objectives are to (a) assist users in extracting useful information from data and (b) enable them to easily identify a suitable algorithm for generating an accurate predictive model from it. http://www.cs.waikato.ac.nz/ml/weka.

A Power-Efficient Clustering Protocol for Coal Mine Face Monitoring with Wireless Sensor Networks Under Channel Fading Conditions

PubMed Central

Ren, Peng; Qian, Jiansheng

2016-01-01

This study proposes a novel power-efficient and anti-fading clustering based on a cross-layer that is specific to the time-varying fading characteristics of channels in the monitoring of coal mine faces with wireless sensor networks. The number of active sensor nodes and a sliding window are set up such that the optimal number of cluster heads (CHs) is selected in each round. Based on a stable expected number of CHs, we explore the channel efficiency between nodes and the base station by using a probe frame and the joint surplus energy in assessing the CH selection. Moreover, the sending power of a node in different periods is regulated by the signal fade margin method. The simulation results demonstrate that compared with several common algorithms, the power-efficient and fading-aware clustering with a cross-layer (PEAFC-CL) protocol features a stable network topology and adaptability under signal time-varying fading, which effectively prolongs the lifetime of the network and reduces network packet loss, thus making it more applicable to the complex and variable environment characteristic of a coal mine face. PMID:27338380

Forecasting of Energy Expenditure of Induced Seismicity with Use of Artificial Neural Network

NASA Astrophysics Data System (ADS)

Cichy, Tomasz; Banka, Piotr

2017-12-01

Coal mining in many Polish mines in the Upper Silesian Coal Basin is accompanied by high levels of induced seismicity. In mining plants, the methods of shock monitoring are improved, allowing for more accurate localization of the occurring phenomena and determining their seismic energy. Equally important is the development of ways of forecasting seismic hazards that may occur while implementing mine design projects. These methods, depending on the length of time for which the forecasts are made, can be divided into: longterm, medium-term, short-term and so-called alarm. Long-term forecasts are particularly useful for the design of seam exploitations. The paper presents a method of predicting changes in energy expenditure of shock using a properly trained artificial neural network. This method allows to make long-term forecasts at the stage of the mine’s exploitation design, thus enabling the mining work plans to be reviewed to minimize the potential for tremors. The information given at the input of the neural network is indicative of the specific energy changes of the elastic deformation occurring in the selected, thick, resistant rock layers (tremor-prone layers). Energy changes, taking place in one or more tremor-prone layers are considered. These indicators describe only the specific energy changes of the elastic deformation accumulating in the rock as a consequence of the mining operation, but does not determine the amount of energy released during the destruction of a given volume of rock. In this process, the potential energy of elastic strain transforms into other, non-measurable energy types, including the seismic energy of recorded tremors. In this way, potential energy changes affect the observed induced seismicity. The parameters used are characterized by increases (declines) of specific energy with separation to occur before the hypothetical destruction of the rock and after it. Additional input information is an index characterizing the rate of tectonic faults. This parameter was not included in previous research by authors. At the output of the artificial neural network, the values of the energy density of the mining tremors [J/m3] are obtained. An example of the predicted change in seismicity induced for a highly threatened region is presented. Relatively good predicted and observed energy expenditure of tremors was obtained. The presented method can complement existing methods (analytical and geophysical) forecasting seismic hazard. This method can be used primarily in those areas where the seismic level is determined by the configuration of the edges and residues in the operating seam, as well as in adjacent seams, and to a lesser extent, the geological structure of the rock The method is local, it means that the artificial neural network prediction can only be performed for the region from which the data have been used for its originated learning. The developed method cannot be used in areas where mining is just beginning and it is not possible to predict the level of seismicity induced in areas where no mining tremors have been recorded so far.

Mining Very High Resolution INSAR Data Based On Complex-GMRF Cues And Relevance Feedback

NASA Astrophysics Data System (ADS)

Singh, Jagmal; Popescu, Anca; Soccorsi, Matteo; Datcu, Mihai

2012-01-01

With the increase in number of remote sensing satellites, the number of image-data scenes in our repositories is also increasing and a large quantity of these scenes are never received and used. Thus automatic retrieval of de- sired image-data using query by image content to fully utilize the huge repository volume is becoming of great interest. Generally different users are interested in scenes containing different kind of objects and structures. So its important to analyze all the image information mining (IIM) methods so that its easier for user to select a method depending upon his/her requirement. We concentrate our study only on high-resolution SAR images and we propose to use InSAR observations instead of only one single look complex (SLC) images for mining scenes containing coherent objects such as high-rise buildings. However in case of objects with less coherence like areas with vegetation cover, SLC images exhibits better performance. We demonstrate IIM performance comparison using complex-Gauss Markov Random Fields as texture descriptor for image patches and SVM relevance- feedback.

Improving Prediction Accuracy of “Central Line-Associated Blood Stream Infections” Using Data Mining Models

PubMed Central

Noaman, Amin Y.; Jamjoom, Arwa; Al-Abdullah, Nabeela; Nasir, Mahreen; Ali, Anser G.

2017-01-01

Prediction of nosocomial infections among patients is an important part of clinical surveillance programs to enable the related personnel to take preventive actions in advance. Designing a clinical surveillance program with capability of predicting nosocomial infections is a challenging task due to several reasons, including high dimensionality of medical data, heterogenous data representation, and special knowledge required to extract patterns for prediction. In this paper, we present details of six data mining methods implemented using cross industry standard process for data mining to predict central line-associated blood stream infections. For our study, we selected datasets of healthcare-associated infections from US National Healthcare Safety Network and consumer survey data from Hospital Consumer Assessment of Healthcare Providers and Systems. Our experiments show that central line-associated blood stream infections (CLABSIs) can be successfully predicted using AdaBoost method with an accuracy up to 89.7%. This will help in implementing effective clinical surveillance programs for infection control, as well as improving the accuracy detection of CLABSIs. Also, this reduces patients' hospital stay cost and maintains patients' safety. PMID:29085836

A Demonstration of Regression False Positive Selection in Data Mining

ERIC Educational Resources Information Center

Pinder, Jonathan P.

2014-01-01

Business analytics courses, such as marketing research, data mining, forecasting, and advanced financial modeling, have substantial predictive modeling components. The predictive modeling in these courses requires students to estimate and test many linear regressions. As a result, false positive variable selection ("type I errors") is…

Quantum-enhanced feature selection with forward selection and backward elimination

NASA Astrophysics Data System (ADS)

He, Zhimin; Li, Lvzhou; Huang, Zhiming; Situ, Haozhen

2018-07-01

Feature selection is a well-known preprocessing technique in machine learning, which can remove irrelevant features to improve the generalization capability of a classifier and reduce training and inference time. However, feature selection is time-consuming, particularly for the applications those have thousands of features, such as image retrieval, text mining and microarray data analysis. It is crucial to accelerate the feature selection process. We propose a quantum version of wrapper-based feature selection, which converts a classical feature selection to its quantum counterpart. It is valuable for machine learning on quantum computer. In this paper, we focus on two popular kinds of feature selection methods, i.e., wrapper-based forward selection and backward elimination. The proposed feature selection algorithm can quadratically accelerate the classical one.

Fusing Data Mining, Machine Learning and Traditional Statistics to Detect Biomarkers Associated with Depression

PubMed Central

Dipnall, Joanna F.

2016-01-01

Background Atheoretical large-scale data mining techniques using machine learning algorithms have promise in the analysis of large epidemiological datasets. This study illustrates the use of a hybrid methodology for variable selection that took account of missing data and complex survey design to identify key biomarkers associated with depression from a large epidemiological study. Methods The study used a three-step methodology amalgamating multiple imputation, a machine learning boosted regression algorithm and logistic regression, to identify key biomarkers associated with depression in the National Health and Nutrition Examination Study (2009–2010). Depression was measured using the Patient Health Questionnaire-9 and 67 biomarkers were analysed. Covariates in this study included gender, age, race, smoking, food security, Poverty Income Ratio, Body Mass Index, physical activity, alcohol use, medical conditions and medications. The final imputed weighted multiple logistic regression model included possible confounders and moderators. Results After the creation of 20 imputation data sets from multiple chained regression sequences, machine learning boosted regression initially identified 21 biomarkers associated with depression. Using traditional logistic regression methods, including controlling for possible confounders and moderators, a final set of three biomarkers were selected. The final three biomarkers from the novel hybrid variable selection methodology were red cell distribution width (OR 1.15; 95% CI 1.01, 1.30), serum glucose (OR 1.01; 95% CI 1.00, 1.01) and total bilirubin (OR 0.12; 95% CI 0.05, 0.28). Significant interactions were found between total bilirubin with Mexican American/Hispanic group (p = 0.016), and current smokers (p<0.001). Conclusion The systematic use of a hybrid methodology for variable selection, fusing data mining techniques using a machine learning algorithm with traditional statistical modelling, accounted for missing data and complex survey sampling methodology and was demonstrated to be a useful tool for detecting three biomarkers associated with depression for future hypothesis generation: red cell distribution width, serum glucose and total bilirubin. PMID:26848571

Hydroseeding on anthracite coal-mine spoils

Treesearch

Miroslaw M. Czapowskyj; Ross Writer

1970-01-01

A study was made of the performance of selected species of legumes, grasses, and trees hydroseeded on anthracite coal-mine spoils in a slurry of lime, fertilizer, and mulch. Hydroseeding failed on coal-breaker refuse, but was partially successful on strip-mine spoils.

Implementation of Data Mining to Analyze Drug Cases Using C4.5 Decision Tree

NASA Astrophysics Data System (ADS)

Wahyuni, Sri

2018-03-01

Data mining was the process of finding useful information from a large set of databases. One of the existing techniques in data mining was classification. The method used was decision tree method and algorithm used was C4.5 algorithm. The decision tree method was a method that transformed a very large fact into a decision tree which was presenting the rules. Decision tree method was useful for exploring data, as well as finding a hidden relationship between a number of potential input variables with a target variable. The decision tree of the C4.5 algorithm was constructed with several stages including the selection of attributes as roots, created a branch for each value and divided the case into the branch. These stages would be repeated for each branch until all the cases on the branch had the same class. From the solution of the decision tree there would be some rules of a case. In this case the researcher classified the data of prisoners at Labuhan Deli prison to know the factors of detainees committing criminal acts of drugs. By applying this C4.5 algorithm, then the knowledge was obtained as information to minimize the criminal acts of drugs. From the findings of the research, it was found that the most influential factor of the detainee committed the criminal act of drugs was from the address variable.

Literature-based discovery of diabetes- and ROS-related targets

PubMed Central

2010-01-01

Background Reactive oxygen species (ROS) are known mediators of cellular damage in multiple diseases including diabetic complications. Despite its importance, no comprehensive database is currently available for the genes associated with ROS. Methods We present ROS- and diabetes-related targets (genes/proteins) collected from the biomedical literature through a text mining technology. A web-based literature mining tool, SciMiner, was applied to 1,154 biomedical papers indexed with diabetes and ROS by PubMed to identify relevant targets. Over-represented targets in the ROS-diabetes literature were obtained through comparisons against randomly selected literature. The expression levels of nine genes, selected from the top ranked ROS-diabetes set, were measured in the dorsal root ganglia (DRG) of diabetic and non-diabetic DBA/2J mice in order to evaluate the biological relevance of literature-derived targets in the pathogenesis of diabetic neuropathy. Results SciMiner identified 1,026 ROS- and diabetes-related targets from the 1,154 biomedical papers (http://jdrf.neurology.med.umich.edu/ROSDiabetes/). Fifty-three targets were significantly over-represented in the ROS-diabetes literature compared to randomly selected literature. These over-represented targets included well-known members of the oxidative stress response including catalase, the NADPH oxidase family, and the superoxide dismutase family of proteins. Eight of the nine selected genes exhibited significant differential expression between diabetic and non-diabetic mice. For six genes, the direction of expression change in diabetes paralleled enhanced oxidative stress in the DRG. Conclusions Literature mining compiled ROS-diabetes related targets from the biomedical literature and led us to evaluate the biological relevance of selected targets in the pathogenesis of diabetic neuropathy. PMID:20979611

Mining Available Data from the United States Environmental Protection Agency to Support Rapid Life Cycle Inventory Modeling of Chemical Manufacturing.

PubMed

Cashman, Sarah A; Meyer, David E; Edelen, Ashley N; Ingwersen, Wesley W; Abraham, John P; Barrett, William M; Gonzalez, Michael A; Randall, Paul M; Ruiz-Mercado, Gerardo; Smith, Raymond L

2016-09-06

Demands for quick and accurate life cycle assessments create a need for methods to rapidly generate reliable life cycle inventories (LCI). Data mining is a suitable tool for this purpose, especially given the large amount of available governmental data. These data are typically applied to LCIs on a case-by-case basis. As linked open data becomes more prevalent, it may be possible to automate LCI using data mining by establishing a reproducible approach for identifying, extracting, and processing the data. This work proposes a method for standardizing and eventually automating the discovery and use of publicly available data at the United States Environmental Protection Agency for chemical-manufacturing LCI. The method is developed using a case study of acetic acid. The data quality and gap analyses for the generated inventory found that the selected data sources can provide information with equal or better reliability and representativeness on air, water, hazardous waste, on-site energy usage, and production volumes but with key data gaps including material inputs, water usage, purchased electricity, and transportation requirements. A comparison of the generated LCI with existing data revealed that the data mining inventory is in reasonable agreement with existing data and may provide a more-comprehensive inventory of air emissions and water discharges. The case study highlighted challenges for current data management practices that must be overcome to successfully automate the method using semantic technology. Benefits of the method are that the openly available data can be compiled in a standardized and transparent approach that supports potential automation with flexibility to incorporate new data sources as needed.

Protective and control relays as coal-mine power-supply ACS subsystem

NASA Astrophysics Data System (ADS)

Kostin, V. N.; Minakova, T. E.

2017-10-01

The paper presents instantaneous selective short-circuit protection for the cabling of the underground part of a coal mine and central control algorithms as a Coal-Mine Power-Supply ACS Subsystem. In order to improve the reliability of electricity supply and reduce the mining equipment down-time, a dual channel relay protection and central control system is proposed as a subsystem of the coal-mine power-supply automated control system (PS ACS).

Mining and characterization of microsatellites from a genome of Venturia carpophila

USDA-ARS?s Scientific Manuscript database

A total of 4,021 microsatellites were mined from a genome of Venturia carpophila and 192 were selected to screen 39 isolates of the fungus collected from peach and nectarine in the southeastern USA. Of the 192 selected, 32 primers consistently and reliably produced polymorphic amplicons. Subsequentl...

Moment tensor clustering: a tool to monitor mining induced seismicity

NASA Astrophysics Data System (ADS)

Cesca, Simone; Dahm, Torsten; Tolga Sen, Ali

2013-04-01

Automated moment tensor inversion routines have been setup in the last decades for the analysis of global and regional seismicity. Recent developments could be used to analyse smaller events and larger datasets. In particular, applications to microseismicity, e.g. in mining environments, have then led to the generation of large moment tensor catalogues. Moment tensor catalogues provide a valuable information about the earthquake source and details of rupturing processes taking place in the seismogenic region. Earthquake focal mechanisms can be used to discuss the local stress field, possible orientations of the fault system or to evaluate the presence of shear and/or tensile cracks. Focal mechanism and moment tensor solutions are typically analysed for selected events, and quick and robust tools for the automated analysis of larger catalogues are needed. We propose here a method to perform cluster analysis for large moment tensor catalogues and identify families of events which characterize the studied microseismicity. Clusters include events with similar focal mechanisms, first requiring the definition of distance between focal mechanisms. Different metrics are here proposed, both for the case of pure double couple, constrained moment tensor and full moment tensor catalogues. Different clustering approaches are implemented and discussed. The method is here applied to synthetic and real datasets from mining environments to demonstrate its potential: the proposed cluserting techniques prove to be able to automatically recognise major clusters. An important application for mining monitoring concerns the early identification of anomalous rupture processes, which is relevant for the hazard assessment. This study is funded by the project MINE, which is part of the R&D-Programme GEOTECHNOLOGIEN. The project MINE is funded by the German Ministry of Education and Research (BMBF), Grant of project BMBF03G0737.

The Traversella mining site as Piedmont geosite

NASA Astrophysics Data System (ADS)

Costa, Emanuele; Benna, Piera; Antonella Dino, Giovanna; Rossetti, Piergiorgio

2017-04-01

The multidisciplinary research project PROGEOPiemonte, started in 2012, selected nine strategic geothematic areas that have been and are still investigated as representative of the geodiversity of Piedmont region. The dissemination of the knowledge connected to geological history, climate and environmental changes, natural hazards, soil processes, and georesources, not only of the geosites but also of the museum collections, has been and will be spread, evidencing the mining and quarrying activities, and by means of science exhibits and Nature trails. Among the nine selected geosites, there is the Traversella mining area, object of the present research. Traversella mine is located nearly 50 km north of Torino, and it was (together with the neighbor site of Brosso) one of the most important mining location for iron exploitation. The Traversella orebody was exploited from late medieval age up to the middle XX century. It is a representative contact-metasomatic deposit at the border between granodiorite and preexisting host rocks (micaschists, gneisses and marbles of the Sesia-Lanzo Zone), and the mining district represents the only exploited skarn-type mineralization in the Alps. The iron mineral, exploited from different veins and mass (pertaining to the contact aureola) was primarily magnetite, an iron oxide easy to treat in cast iron even employing the technology locally available before 1900. After the beginning of XX century the extraction involved also pyrite and chalcopyrite (iron and copper-iron sulfide), used mainly for the production of sulfuric acid. The mine, after some interruptions and re-openings, was officially closed in the second half of the XX century, due to the high exploitation costs and the competition of the foreign mine deposits interested by iron extraction. The area still presents several signs of mining and dressing activities (underground pits, explorable under severe restrictions, traces of dressing plant, offices, and miners changing room and canteens, etc..); such signs are the tangible trace of a remarkable industrial activity, which can be considered as cultural heritage of historical industrial activities ("industrial archeology"). To enrich such cultural heritage, a museum for minerals and mining tools exposition is still active. Furthermore, to evidence the importance of Traversella mining site, outstanding mineralogical samples coming from Traversella area are displayed in the most famous museum all over the world. The present research aims at emphasize the extraordinary importance of this mining site both from a scientific and a historical point of view, examining the methods and the amount of production during the last three centuries, and highlighting how these activities contributed to the industrial development of the surrounding area and of the whole Piedmont Region. We also want to illustrate the sociological and environmental impact of mining activities at regional level, highlighting the importance of the site from a geoturistic point of view, thanks to of the cultural exploitation of the mining site remains, the developing and upgrade of the already existing mining museum, and the organization of geoturistic itinerary.

UNEXMIN H2020 Project: an underwater explorer for flooded mines

NASA Astrophysics Data System (ADS)

Lopes, Luís; Zajzon, Norbert; Bodo, Balázs; Henley, Stephen; Žibret, Gorazd; Almeida, José; Vörös, Csaba; Horvath, Janos; Dizdarevič, Tatjana; Rossi, Claudio; McLoughlin, Mike

2017-04-01

UNEXMIN (Underwater Explorer for Flooded Mines, Grant Agreement No. 690008, www.unexmin.eu) is a project funded by the European Commission's HORIZON2020 Framework Programme. The project is developing a multi-platform robotic system for the autonomous exploration and mapping of Europe's flooded mines. The robotic system - UX-1 - will use non-invasive methods for the 3D mapping of abandoned flooded mines, bringing new important geological and mineralogical data that cannot be currently obtained by any other means. This technology will allow the development or update of geological models at local and regional levels. The data collected will then be used to consider new exploration scenarios for the possible re-opening of some of Europe's abandoned mines which may still contain valuable resources of strategic minerals. The deployment of a multi-robotic system in such a confined environment poses challenges that must be overcome so that the robots can work autonomously, without damaging the equipment and the mine itself. Key challenges are related to the i) structural design for robustness and resilience, ii) localization, navigation and 3D mapping, iii) guidance, propulsion and control, iv) autonomous operation and supervision, v) data processing, interpretation and evaluation. The scientific instrument array is currently being tested, built and tailored for the submersible: pH, electrical conductivity, pressure and temperature analyzers and a water sampler (water sampling methods), a magnetic field analyzer, a gamma-ray counter and a sub-bottom profiler (geophysical methods) and a multispectral and UV fluorescence imaging units (optical observation methods). The instruments have been selected to generate data of maximum geoscientific interest, considering the limiting factors of the submerged underground environment, the necessary robotic functions, the size for the robot and other constraints. Other crucial components for the robot's functionality (such as movement, control, autonomy, mapping, interpretation and evaluation) include cameras, SONARs, thrusters, DVL, inertial navigation system, laser scanner, computer, batteries and the integrated pressure hull. The UNEXMIN project is currently ongoing with the development of the first mechanical model as well as the scientific instruments. The robot prototype is being developed with a spherical shape with a diameter such that will allow it to fit into the sometimes narrow underground mine openings and to freely move around them, to a depth of 500m. Component/instrument validations and simulations are being worked out to understand the behavior of the technology in the flooded mine environment. At the same time post-processing and data analysis tools are also being developed and prepared. After the groundwork and setup phases, the first robot prototype is going to be tested in four sites under real life conditions corresponding to increasingly difficult mission objectives in terms of mine layout, geometry and topology. The test sites include the Kaatiala pegmatite mine in Finland, the Urgeiriça uranium mine in Portugal and the Idrija mercury mine in Slovenia. The final, most ambitious demonstration will occur in the UK with the resurveying of the entire flooded section of the Ecton underground copper mine that nobody has seen for over 150 years.

Predicting the graft survival for heart-lung transplantation patients: an integrated data mining methodology.

PubMed

Oztekin, Asil; Delen, Dursun; Kong, Zhenyu James

2009-12-01

Predicting the survival of heart-lung transplant patients has the potential to play a critical role in understanding and improving the matching procedure between the recipient and graft. Although voluminous data related to the transplantation procedures is being collected and stored, only a small subset of the predictive factors has been used in modeling heart-lung transplantation outcomes. The previous studies have mainly focused on applying statistical techniques to a small set of factors selected by the domain-experts in order to reveal the simple linear relationships between the factors and survival. The collection of methods known as 'data mining' offers significant advantages over conventional statistical techniques in dealing with the latter's limitations such as normality assumption of observations, independence of observations from each other, and linearity of the relationship between the observations and the output measure(s). There are statistical methods that overcome these limitations. Yet, they are computationally more expensive and do not provide fast and flexible solutions as do data mining techniques in large datasets. The main objective of this study is to improve the prediction of outcomes following combined heart-lung transplantation by proposing an integrated data-mining methodology. A large and feature-rich dataset (16,604 cases with 283 variables) is used to (1) develop machine learning based predictive models and (2) extract the most important predictive factors. Then, using three different variable selection methods, namely, (i) machine learning methods driven variables-using decision trees, neural networks, logistic regression, (ii) the literature review-based expert-defined variables, and (iii) common sense-based interaction variables, a consolidated set of factors is generated and used to develop Cox regression models for heart-lung graft survival. The predictive models' performance in terms of 10-fold cross-validation accuracy rates for two multi-imputed datasets ranged from 79% to 86% for neural networks, from 78% to 86% for logistic regression, and from 71% to 79% for decision trees. The results indicate that the proposed integrated data mining methodology using Cox hazard models better predicted the graft survival with different variables than the conventional approaches commonly used in the literature. This result is validated by the comparison of the corresponding Gains charts for our proposed methodology and the literature review based Cox results, and by the comparison of Akaike information criteria (AIC) values received from each. Data mining-based methodology proposed in this study reveals that there are undiscovered relationships (i.e. interactions of the existing variables) among the survival-related variables, which helps better predict the survival of the heart-lung transplants. It also brings a different set of variables into the scene to be evaluated by the domain-experts and be considered prior to the organ transplantation.

A novel method for estimating methane emissions from underground coal mines: The Yanma coal mine, China

NASA Astrophysics Data System (ADS)

Ji, Zhong-Min; Chen, Zhi-Jian; Pan, Jie-Nan; Niu, Qing-He

2017-12-01

As the world's largest coal producer and consumer, China accounts for a relatively high proportion of methane emissions from coal mines. Several estimation methods had been established for the coal mine methane (CMM) emission. However, with large regional differences, various reservoir formation types of coalbed methane (CBM) and due to the complicated geological conditions in China, these methods may be deficient or unsuitable for all the mining areas (e.g. Jiaozuo mining area). By combing the CMM emission characteristics and considering the actual situation of methane emissions from underground coal mine, we found that the methane pre-drainage is a crucial reason creating inaccurate evaluating results for most estimation methods. What makes it so essential is the extensive pre-drainage quantity and its irrelevance with annual coal production. Accordingly, the methane releases were divided into two categories: methane pre-drainage and methane release during mining. On this basis, a pioneering method for estimating CMM emissions was proposed. Taking the Yanma coal mine in the Jiaozuo mining area as a study case, the evaluation method of the pre-drainage methane quantity was established after the correlation analysis between the pre-drainage rate and time. Thereafter, the mining activity influence factor (MAIF) was first introduced to reflect the methane release from the coal and rock seams around where affected by mining activity, and the buried depth was adopted as the predictor of the estimation for future methane emissions. It was verified in the six coal mines of Jiaozuo coalfield (2011) that the new estimation method has the minimum errors of 12.11%, 9.23%, 5.77%, -5.20%, -8.75% and 4.92% respectively comparing with other methods. This paper gives a further insight and proposes a more accurate evaluation method for the CMM emissions, especially for the coal seams with low permeability and strong tectonic deformation in methane outburst coal mines.

Enhancing the Performance of LibSVM Classifier by Kernel F-Score Feature Selection

NASA Astrophysics Data System (ADS)

Sarojini, Balakrishnan; Ramaraj, Narayanasamy; Nickolas, Savarimuthu

Medical Data mining is the search for relationships and patterns within the medical datasets that could provide useful knowledge for effective clinical decisions. The inclusion of irrelevant, redundant and noisy features in the process model results in poor predictive accuracy. Much research work in data mining has gone into improving the predictive accuracy of the classifiers by applying the techniques of feature selection. Feature selection in medical data mining is appreciable as the diagnosis of the disease could be done in this patient-care activity with minimum number of significant features. The objective of this work is to show that selecting the more significant features would improve the performance of the classifier. We empirically evaluate the classification effectiveness of LibSVM classifier on the reduced feature subset of diabetes dataset. The evaluations suggest that the feature subset selected improves the predictive accuracy of the classifier and reduce false negatives and false positives.

Evaluation of selected static methods used to estimate element mobility, acid-generating and acid-neutralizing potentials associated with geologically diverse mining wastes

USGS Publications Warehouse

Hageman, Philip L.; Seal, Robert R.; Diehl, Sharon F.; Piatak, Nadine M.; Lowers, Heather

2015-01-01

A comparison study of selected static leaching and acid–base accounting (ABA) methods using a mineralogically diverse set of 12 modern-style, metal mine waste samples was undertaken to understand the relative performance of the various tests. To complement this study, in-depth mineralogical studies were conducted in order to elucidate the relationships between sample mineralogy, weathering features, and leachate and ABA characteristics. In part one of the study, splits of the samples were leached using six commonly used leaching tests including paste pH, the U.S. Geological Survey (USGS) Field Leach Test (FLT) (both 5-min and 18-h agitation), the U.S. Environmental Protection Agency (USEPA) Method 1312 SPLP (both leachate pH 4.2 and leachate pH 5.0), and the USEPA Method 1311 TCLP (leachate pH 4.9). Leachate geochemical trends were compared in order to assess differences, if any, produced by the various leaching procedures. Results showed that the FLT (5-min agitation) was just as effective as the 18-h leaching tests in revealing the leachate geochemical characteristics of the samples. Leaching results also showed that the TCLP leaching test produces inconsistent results when compared to results produced from the other leaching tests. In part two of the study, the ABA was determined on splits of the samples using both well-established traditional static testing methods and a relatively quick, simplified net acid–base accounting (NABA) procedure. Results showed that the traditional methods, while time consuming, provide the most in-depth data on both the acid generating, and acid neutralizing tendencies of the samples. However, the simplified NABA method provided a relatively fast, effective estimation of the net acid–base account of the samples. Overall, this study showed that while most of the well-established methods are useful and effective, the use of a simplified leaching test and the NABA acid–base accounting method provide investigators fast, quantitative tools that can be used to provide rapid, reliable information about the leachability of metals and other constituents of concern, and the acid-generating potential of metal mining waste.

Comparison of the common spatial interpolation methods used to analyze potentially toxic elements surrounding mining regions.

PubMed

Ding, Qian; Wang, Yong; Zhuang, Dafang

2018-04-15

The appropriate spatial interpolation methods must be selected to analyze the spatial distributions of Potentially Toxic Elements (PTEs), which is a precondition for evaluating PTE pollution. The accuracy and effect of different spatial interpolation methods, which include inverse distance weighting interpolation (IDW) (power = 1, 2, 3), radial basis function interpolation (RBF) (basis function: thin-plate spline (TPS), spline with tension (ST), completely regularized spline (CRS), multiquadric (MQ) and inverse multiquadric (IMQ)) and ordinary kriging interpolation (OK) (semivariogram model: spherical, exponential, gaussian and linear), were compared using 166 unevenly distributed soil PTE samples (As, Pb, Cu and Zn) in the Suxian District, Chenzhou City, Hunan Province as the study subject. The reasons for the accuracy differences of the interpolation methods and the uncertainties of the interpolation results are discussed, then several suggestions for improving the interpolation accuracy are proposed, and the direction of pollution control is determined. The results of this study are as follows: (i) RBF-ST and OK (exponential) are the optimal interpolation methods for As and Cu, and the optimal interpolation method for Pb and Zn is RBF-IMQ. (ii) The interpolation uncertainty is positively correlated with the PTE concentration, and higher uncertainties are primarily distributed around mines, which is related to the strong spatial variability of PTE concentrations caused by human interference. (iii) The interpolation accuracy can be improved by increasing the sample size around the mines, introducing auxiliary variables in the case of incomplete sampling and adopting the partition prediction method. (iv) It is necessary to strengthen the prevention and control of As and Pb pollution, particularly in the central and northern areas. The results of this study can provide an effective reference for the optimization of interpolation methods and parameters for unevenly distributed soil PTE data in mining areas. Copyright © 2018 Elsevier Ltd. All rights reserved.

Applications of Geomatics in Surface Mining

NASA Astrophysics Data System (ADS)

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 for a potential large-scale surface mining project, modelling mineral deposit (granite) management, concept of a system for management of conveyor belt network technical condition, project of a geoinformation system of former mining terrains and objects, and monitoring and control of impact of surface mining on mine surroundings with satellite radar interferometry.

Reuse and Securing of Mining Waste : Need of the hour

NASA Astrophysics Data System (ADS)

Mehta, Neha; Dino, Giovanna; Ajmone-Marsan, Franco; De Luca, Domenico Antonio

2016-04-01

With recent advancements in technology and rising standards of living the demand for minerals has increased drastically. Increased reliance on mining industry has led to unmanageable challenges of Mining waste generated out of Mining and Quarrying activities. According to Statistics from EuroStat Mining and Quarrying generated 734 million Tons in Europe in 2012 which accounted for 29.19 % of the total waste, becoming second most important sector in terms of waste generation after Construction Industry. Mining waste can be voluminous and/ or chemically active and can cause environmental threats like groundwater pollution due to leaching of pollutants, surface water pollution due to runoffs during rainy season, river and ocean pollution due to intentional dumping of tailings by mining companies. Most of the big mining companies have not adopted policies against dumping of tailings in rivers and oceans. Deep Sea Tailings Placement (DSTP) is creating havoc in remote and pristine environment of deep-sea beds e.g. Bismarck Sea. Furthermore, mining waste is contaminating soil in nearby areas by disturbing soil microbial activity and other physio-chemical and biological properties of soil (e.g. Barruecopardo village - Spain). Mining waste stored in heaps and dams has led to many accidents and on an average, worldwide, there is one major accident in a year involving tailings dams (e.g. Myanmar, Brazil, 2015). Pollution due to tailings is causing local residents to relocate and become 'ecological migrants'. The above issues linked to mining waste makes reuse and securing of mining waste one of the urgent challenge to deal with. The studies done previously on mining show that most of the researches linked with mining waste reuse and securing are very site specific. For instance, the type of recovery method should not only provide environmental clean-up but also economic benefits to promise sustainability of the method. Environmental risk assessment of using mining waste as agricultural soils can depend on Bio-accumulation factor, Translocation factor of heavy metals, species of plant grown and type of the natural biota of the surroundings and effect of different exposure routes. This also leads to the fact that more research is required in this area. Accordingly the same problem statement was chosen as part of a PhD research Project. The PhD research is part of REMEDIATE project (A Marie Sklodowska-Curie Action Initial Training Network for Improved decision making in contaminated land site investigation and risk assessment, Grant Agreement No. 643087). In this project the researcher will select a mining site in Italy to find possible solutions to the environmental impact of mining waste collected there. The project will focus on 1) physical and chemical characterization of waste 2)environmental risk assessment study of the mining waste 3) impact of mining waste on water bodies and soil 4) to discover possible routes of reuse and recovery of minerals from the waste. Thus project focuses on environmental sustainability of mining waste reuse and clean up. Keywords : Mining waste ; environmental risk assessment ;reuse and recovery.

Closedure - Mine Closure Technologies Resource

NASA Astrophysics Data System (ADS)

Kauppila, Päivi; Kauppila, Tommi; Pasanen, Antti; Backnäs, Soile; Liisa Räisänen, Marja; Turunen, Kaisa; Karlsson, Teemu; Solismaa, Lauri; Hentinen, Kimmo

2015-04-01

Closure of mining operations is an essential part of the development of eco-efficient mining and the Green Mining concept in Finland to reduce the environmental footprint of mining. Closedure is a 2-year joint research project between Geological Survey of Finland and Technical Research Centre of Finland that aims at developing accessible tools and resources for planning, executing and monitoring mine closure. The main outcome of the Closedure project is an updatable wiki technology-based internet platform (http://mineclosure.gtk.fi) in which comprehensive guidance on the mine closure is provided and main methods and technologies related to mine closure are evaluated. Closedure also provides new data on the key issues of mine closure, such as performance of passive water treatment in Finland, applicability of test methods for evaluating cover structures for mining wastes, prediction of water effluents from mine wastes, and isotopic and geophysical methods to recognize contaminant transport paths in crystalline bedrock.

Hydrologic and geochemical data for the Big Brown lignite mine area, Freestone County, Texas

USGS Publications Warehouse

Dorsey, Michael E.

1985-01-01

Lignite mining in east and east-central Texas is increasing in response to increased energy needs throughout the State. Associated with the increase in mining activities is a greater need to know the effects of mining activities on the water quantity and quality of near-surface aquifers. The near-surface lignite beds mined at the Big Brown Lignite Mine are from the Calvert Bluff Formation of the Wilcox Group of Eocene age, which is a minor aquifer generally having water suitable for all uses, in eastern Freestone County, Texas. One of the potential hydro!ogic effects of surface-coal mining is a change in the quality of ground water associated with replacement of aquifer materials by mine spoils. The purpose of this report is to compile and categorize geologic, mineralogic, geochemical, and hydrologic data for the Big Brown Lignite Mine and surrounding area in east-central Texas. Included are results of pasteextract analyses, constituent concentrations in water from batch-mixing experiments, sulfur analyses, and minerals or mineral groups detected by X-ray diffraction in 12 spoil material samples collected from 3 locations at the mine site. Also, common-constituent and trace-constituent concentrations in water from eight selected wells, located updip and downdip from the mine, are presented. Dissolved-solids concentrations in water from batch-mixing experiments vary from 12 to 908 milligrams per liter. Water from selected wells contain dissolved-solids concentrations ranging from 75 to 510 milligrams per liter.

Use of data mining techniques to classify soil CO2 emission induced by crop management in sugarcane field.

PubMed

Farhate, Camila Viana Vieira; Souza, Zigomar Menezes de; Oliveira, Stanley Robson de Medeiros; Tavares, Rose Luiza Moraes; Carvalho, João Luís Nunes

2018-01-01

Soil CO2 emissions are regarded as one of the largest flows of the global carbon cycle and small changes in their magnitude can have a large effect on the CO2 concentration in the atmosphere. Thus, a better understanding of this attribute would enable the identification of promoters and the development of strategies to mitigate the risks of climate change. Therefore, our study aimed at using data mining techniques to predict the soil CO2 emission induced by crop management in sugarcane areas in Brazil. To do so, we used different variable selection methods (correlation, chi-square, wrapper) and classification (Decision tree, Bayesian models, neural networks, support vector machine, bagging with logistic regression), and finally we tested the efficiency of different approaches through the Receiver Operating Characteristic (ROC) curve. The original dataset consisted of 19 variables (18 independent variables and one dependent (or response) variable). The association between cover crop and minimum tillage are effective strategies to promote the mitigation of soil CO2 emissions, in which the average CO2 emissions are 63 kg ha-1 day-1. The variables soil moisture, soil temperature (Ts), rainfall, pH, and organic carbon were most frequently selected for soil CO2 emission classification using different methods for attribute selection. According to the results of the ROC curve, the best approaches for soil CO2 emission classification were the following: (I)-the Multilayer Perceptron classifier with attribute selection through the wrapper method, that presented rate of false positive of 13,50%, true positive of 94,20% area under the curve (AUC) of 89,90% (II)-the Bagging classifier with logistic regression with attribute selection through the Chi-square method, that presented rate of false positive of 13,50%, true positive of 94,20% AUC of 89,90%. However, the (I) approach stands out in relation to (II) for its higher positive class accuracy (high CO2 emission) and lower computational cost.

Use of data mining techniques to classify soil CO2 emission induced by crop management in sugarcane field

PubMed Central

de Souza, Zigomar Menezes; Oliveira, Stanley Robson de Medeiros; Tavares, Rose Luiza Moraes; Carvalho, João Luís Nunes

2018-01-01

Soil CO2 emissions are regarded as one of the largest flows of the global carbon cycle and small changes in their magnitude can have a large effect on the CO2 concentration in the atmosphere. Thus, a better understanding of this attribute would enable the identification of promoters and the development of strategies to mitigate the risks of climate change. Therefore, our study aimed at using data mining techniques to predict the soil CO2 emission induced by crop management in sugarcane areas in Brazil. To do so, we used different variable selection methods (correlation, chi-square, wrapper) and classification (Decision tree, Bayesian models, neural networks, support vector machine, bagging with logistic regression), and finally we tested the efficiency of different approaches through the Receiver Operating Characteristic (ROC) curve. The original dataset consisted of 19 variables (18 independent variables and one dependent (or response) variable). The association between cover crop and minimum tillage are effective strategies to promote the mitigation of soil CO2 emissions, in which the average CO2 emissions are 63 kg ha-1 day-1. The variables soil moisture, soil temperature (Ts), rainfall, pH, and organic carbon were most frequently selected for soil CO2 emission classification using different methods for attribute selection. According to the results of the ROC curve, the best approaches for soil CO2 emission classification were the following: (I)–the Multilayer Perceptron classifier with attribute selection through the wrapper method, that presented rate of false positive of 13,50%, true positive of 94,20% area under the curve (AUC) of 89,90% (II)–the Bagging classifier with logistic regression with attribute selection through the Chi-square method, that presented rate of false positive of 13,50%, true positive of 94,20% AUC of 89,90%. However, the (I) approach stands out in relation to (II) for its higher positive class accuracy (high CO2 emission) and lower computational cost. PMID:29513765

DOE Office of Scientific and Technical Information (OSTI.GOV)

Greenwalt, R J; Magnoli, D

The purpose of this study is to determine battlefield effectiveness of the self-healing minefield (''Frogs'') concept system compared to basecases of the standard AP/AT (anti-personnel/anti-tank) mixed minefield, the AT (anti-tank) pure minefield, and no minefields. This involves tactical modeling where a basecase with and without mines is compared to the concept system. However, it is first necessary to establish system characteristics and behavior of the Frog mine and minefield in order to do the tactical modeling. This initial report provides emerging insights into various minefield parameters in order to allow better program definition early in the conceptual development. In themore » following sections of this report, we investigate the self-healing minefield's ground pattern and several concepts for movement (''jump'') of a mine. Basic enemy breaching techniques are compared for the different mine movement concepts. These results are then used in the (Joint Conflict and Tactical Simulation) JCATS tactical model to evaluate minefield effects in a combat situation. The three basecases and the Frogs concept are used against a North Korean mechanized rifle battalion and outcomes are compared. Preliminary results indicate: (1) Possible breaching techniques for the self-healing minefield were proposed and compared through simulation modeling. Of these, the best breaching counter to the self-healing minefield is the ''wide-lane'' breach technique. (2) Several methods for mine movement are tested and the optimal method from this group was selected for use in the modeling. However, continued work is needed on jump criteria; a more sophisticated model may reduce the advantage of the breach counter. (3) The battle scenario used in this study is a very difficult defense for Blue. In the three baseline cases (no mines, AT mines only, and mixed AT/AP minefield), Blue loses. Only in the Frog case does Blue win, and it is a high casualty win.« less

Determining a pre-mining radiological baseline from historic airborne gamma surveys: a case study.

PubMed

Bollhöfer, Andreas; Beraldo, Annamarie; Pfitzner, Kirrilly; Esparon, Andrew; Doering, Che

2014-01-15

Knowing the baseline level of radioactivity in areas naturally enriched in radionuclides is important in the uranium mining context to assess radiation doses to humans and the environment both during and after mining. This information is particularly useful in rehabilitation planning and developing closure criteria for uranium mines as only radiation doses additional to the natural background are usually considered 'controllable' for radiation protection purposes. In this case study we have tested whether the method of contemporary groundtruthing of a historic airborne gamma survey could be used to determine the pre-mining radiological conditions at the Ranger mine in northern Australia. The airborne gamma survey was flown in 1976 before mining started and groundtruthed using ground gamma dose rate measurements made between 2007 and 2009 at an undisturbed area naturally enriched in uranium (Anomaly 2) located nearby the Ranger mine. Measurements of (226)Ra soil activity concentration and (222)Rn exhalation flux density at Anomaly 2 were made concurrent with the ground gamma dose rate measurements. Algorithms were developed to upscale the ground gamma data to the same spatial resolution as the historic airborne gamma survey data using a geographic information system, allowing comparison of the datasets. Linear correlation models were developed to estimate the pre-mining gamma dose rates, (226)Ra soil activity concentrations, and (222)Rn exhalation flux densities at selected areas in the greater Ranger region. The modelled levels agreed with measurements made at the Ranger Orebodies 1 and 3 before mining started, and at environmental sites in the region. The conclusion is that our approach can be used to determine baseline radiation levels, and provide a benchmark for rehabilitation of uranium mines or industrial sites where historical airborne gamma survey data are available and an undisturbed radiological analogue exists to groundtruth the data. © 2013.

Recognition physical activities with optimal number of wearable sensors using data mining algorithms and deep belief network.

PubMed

Al-Fatlawi, Ali H; Fatlawi, Hayder K; Sai Ho Ling

2017-07-01

Daily physical activities monitoring is benefiting the health care field in several ways, in particular with the development of the wearable sensors. This paper adopts effective ways to calculate the optimal number of the necessary sensors and to build a reliable and a high accuracy monitoring system. Three data mining algorithms, namely Decision Tree, Random Forest and PART Algorithm, have been applied for the sensors selection process. Furthermore, the deep belief network (DBN) has been investigated to recognise 33 physical activities effectively. The results indicated that the proposed method is reliable with an overall accuracy of 96.52% and the number of sensors is minimised from nine to six sensors.

Novel strategies to mine alcoholism-related haplotypes and genes by combining existing knowledge framework.

PubMed

Zhang, RuiJie; Li, Xia; Jiang, YongShuai; Liu, GuiYou; Li, ChuanXing; Zhang, Fan; Xiao, Yun; Gong, BinSheng

2009-02-01

High-throughout single nucleotide polymorphism detection technology and the existing knowledge provide strong support for mining the disease-related haplotypes and genes. In this study, first, we apply four kinds of haplotype identification methods (Confidence Intervals, Four Gamete Tests, Solid Spine of LD and fusing method of haplotype block) into high-throughout SNP genotype data to identify blocks, then use cluster analysis to verify the effectiveness of the four methods, and select the alcoholism-related SNP haplotypes through risk analysis. Second, we establish a mapping from haplotypes to alcoholism-related genes. Third, we inquire NCBI SNP and gene databases to locate the blocks and identify the candidate genes. In the end, we make gene function annotation by KEGG, Biocarta, and GO database. We find 159 haplotype blocks, which relate to the alcoholism most possibly on chromosome 1 approximately 22, including 227 haplotypes, of which 102 SNP haplotypes may increase the risk of alcoholism. We get 121 alcoholism-related genes and verify their reliability by the functional annotation of biology. In a word, we not only can handle the SNP data easily, but also can locate the disease-related genes precisely by combining our novel strategies of mining alcoholism-related haplotypes and genes with existing knowledge framework.

Using random forest for the risk assessment of coal-floor water inrush in Panjiayao Coal Mine, northern China

NASA Astrophysics Data System (ADS)

Zhao, Dekang; Wu, Qiang; Cui, Fangpeng; Xu, Hua; Zeng, Yifan; Cao, Yufei; Du, Yuanze

2018-04-01

Coal-floor water-inrush incidents account for a large proportion of coal mine disasters in northern China, and accurate risk assessment is crucial for safe coal production. A novel and promising assessment model for water inrush is proposed based on random forest (RF), which is a powerful intelligent machine-learning algorithm. RF has considerable advantages, including high classification accuracy and the capability to evaluate the importance of variables; in particularly, it is robust in dealing with the complicated and non-linear problems inherent in risk assessment. In this study, the proposed model is applied to Panjiayao Coal Mine, northern China. Eight factors were selected as evaluation indices according to systematic analysis of the geological conditions and a field survey of the study area. Risk assessment maps were generated based on RF, and the probabilistic neural network (PNN) model was also used for risk assessment as a comparison. The results demonstrate that the two methods are consistent in the risk assessment of water inrush at the mine, and RF shows a better performance compared to PNN with an overall accuracy higher by 6.67%. It is concluded that RF is more practicable to assess the water-inrush risk than PNN. The presented method will be helpful in avoiding water inrush and also can be extended to various engineering applications.

Reclaimed mineland curve number response to temporal distribution of rainfall

USGS Publications Warehouse

Warner, R.C.; Agouridis, C.T.; Vingralek, P.T.; Fogle, A.W.

2010-01-01

The curve number (CN) method is a common technique to estimate runoff volume, and it is widely used in coal mining operations such as those in the Appalachian region of Kentucky. However, very little CN data are available for watersheds disturbed by surface mining and then reclaimed using traditional techniques. Furthermore, as the CN method does not readily account for variations in infiltration rates due to varying rainfall distributions, the selection of a single CN value to encompass all temporal rainfall distributions could lead engineers to substantially under- or over-size water detention structures used in mining operations or other land uses such as development. Using rainfall and runoff data from a surface coal mine located in the Cumberland Plateau of eastern Kentucky, CNs were computed for conventionally reclaimed lands. The effects of temporal rainfall distributions on CNs was also examined by classifying storms as intense, steady, multi-interval intense, or multi-interval steady. Results indicate that CNs for such reclaimed lands ranged from 62 to 94 with a mean value of 85. Temporal rainfall distributions were also shown to significantly affect CN values with intense storms having significantly higher CNs than multi-interval storms. These results indicate that a period of recovery is present between rainfall bursts of a multi-interval storm that allows depressional storage and infiltration rates to rebound. ?? 2010 American Water Resources Association.

Various Approaches for Targeting Quasar Candidates

NASA Astrophysics Data System (ADS)

Zhang, Y.; Zhao, Y.

2015-09-01

With the establishment and development of space-based and ground-based observational facilities, the improvement of scientific output of high-cost facilities is still a hot issue for astronomers. The discovery of new and rare quasars attracts much attention. Different methods to select quasar candidates are in bloom. Among them, some are based on color cuts, some are from multiwavelength data, some rely on variability of quasars, some are based on data mining, and some depend on ensemble methods.

Underground coal mine instrumentation and test

NASA Technical Reports Server (NTRS)

Burchill, R. F.; Waldron, W. D.

1976-01-01

The need to evaluate mechanical performance of mine tools and to obtain test performance data from candidate systems dictate that an engineering data recording system be built. Because of the wide range of test parameters which would be evaluated, a general purpose data gathering system was designed and assembled to permit maximum versatility. A primary objective of this program was to provide a specific operating evaluation of a longwall mining machine vibration response under normal operating conditions. A number of mines were visited and a candidate for test evaluation was selected, based upon management cooperation, machine suitability, and mine conditions. Actual mine testing took place in a West Virginia mine.

Recognizing explosion sites with a self-organizing network for unsupervised learning

NASA Astrophysics Data System (ADS)

Tarvainen, Matti

1999-06-01

A self-organizing neural network model has been developed for identifying mining explosion locations in different environments in Finland and adjacent areas. The main advantage of the method is its ability to automatically find a suitable network structure and naturally correctly identify explosions as such. The explosion site recognition was done using extracted waveform attributes of various kind event records from the small-aperture array FINESS in Finland. The recognition was done by using P-S phase arrival differences and rough azimuth estimates to provide a first robust epicentre location. This, in turn, leads to correct mining district identification where more detailed tuning was performed using different phase amplitude and signal-to-noise attributes. The explosions studied here originated in mines and quarries located in Finland, coast of Estonia and in the St. Petersburg area, Russia. Although the Helsinki bulletins in 1995 and 1996 listed 1649 events in these areas, analysis was restricted to the 380 (ML≥2) events which, besides, were found in the reviewed event bulletins (REB) of the CTBTO/UN prototype international data centre (pIDC) in Arlington, VA, USA. These 380 events with different attributes were selected for the learning stage. Because no `ground-truth' information was available the corresponding mining, `code' coordinates used earlier to compile Helsinki bulletins were utilized instead. The novel self-organizing method was tested on 18 new event recordings in the mentioned area in January-February 1997, out of which 15 were connected to correct mines. The misconnected three events were those which did not have all matching attributes in the self-organizing maps (SOMs) network.

Roadway backfill method to prevent geohazards induced by room and pillar mining: a case study in Changxing coal mine, China

NASA Astrophysics Data System (ADS)

Zhou, Nan; Li, Meng; Zhang, Jixiong; Gao, Rui

2016-11-01

Coal mines in the western areas of China experience low mining rates and induce many geohazards when using the room and pillar mining method. In this research, we proposed a roadway backfill method during longwall mining to target these problems. We tested the mechanical properties of the backfill materials to determine a reasonable ratio of backfill materials for the driving roadway during longwall mining. We also introduced the roadway layout and the backfill mining technique required for this method. Based on the effects of the abutment stress from a single roadway driving task, we designed the distance between roadways and a driving and filling sequence for multiple-roadway driving. By doing so, we found the movement characteristics of the strata with quadratic stabilization for backfill mining during roadway driving. Based on this research, the driving and filling sequence of the 3101 working face in Changxing coal mine was optimized to avoid the superimposed influence of mining-induced stress. According to the analysis of the surface monitoring data, the accumulated maximum subsidence is 15 mm and the maximum horizontal deformation is 0.8 mm m-1, which indicated that the ground basically had no obvious deformation after the implementation of the roadway backfill method at 3101 working face.

Decision support methods for the environmental assessment of contamination at mining sites.

PubMed

Jordan, Gyozo; Abdaal, Ahmed

2013-09-01

Polluting mine accidents and widespread environmental contamination associated with historic mining in Europe and elsewhere has triggered the improvement of related environmental legislation and of the environmental assessment and management methods for the mining industry. Mining has some unique features such as natural background pollution associated with natural mineral deposits, industrial activities and contamination located in the three-dimensional sub-surface space, the problem of long-term remediation after mine closure, problem of secondary contaminated areas around mine sites and abandoned mines in historic regions like Europe. These mining-specific problems require special tools to address the complexity of the environmental problems of mining-related contamination. The objective of this paper is to review and evaluate some of the decision support methods that have been developed and applied to mining contamination. In this paper, only those methods that are both efficient decision support tools and provide a 'holistic' approach to the complex problem as well are considered. These tools are (1) landscape ecology, (2) industrial ecology, (3) landscape geochemistry, (4) geo-environmental models, (5) environmental impact assessment, (6) environmental risk assessment, (7) material flow analysis and (8) life cycle assessment. This unique inter-disciplinary study should enable both the researcher and the practitioner to obtain broad view on the state-of-the-art of decision support methods for the environmental assessment of contamination at mine sites. Documented examples and abundant references are also provided.

A Novel Hybrid Intelligent Indoor Location Method for Mobile Devices by Zones Using Wi-Fi Signals

PubMed Central

Castañón–Puga, Manuel; Salazar, Abby Stephanie; Aguilar, Leocundo; Gaxiola-Pacheco, Carelia; Licea, Guillermo

2015-01-01

The increasing use of mobile devices in indoor spaces brings challenges to location methods. This work presents a hybrid intelligent method based on data mining and Type-2 fuzzy logic to locate mobile devices in an indoor space by zones using Wi-Fi signals from selected access points (APs). This approach takes advantage of wireless local area networks (WLANs) over other types of architectures and implements the complete method in a mobile application using the developed tools. Besides, the proposed approach is validated by experimental data obtained from case studies and the cross-validation technique. For the purpose of generating the fuzzy rules that conform to the Takagi–Sugeno fuzzy system structure, a semi-supervised data mining technique called subtractive clustering is used. This algorithm finds centers of clusters from the radius map given by the collected signals from APs. Measurements of Wi-Fi signals can be noisy due to several factors mentioned in this work, so this method proposed the use of Type-2 fuzzy logic for modeling and dealing with such uncertain information. PMID:26633417

A Novel Hybrid Intelligent Indoor Location Method for Mobile Devices by Zones Using Wi-Fi Signals.

PubMed

Castañón-Puga, Manuel; Salazar, Abby Stephanie; Aguilar, Leocundo; Gaxiola-Pacheco, Carelia; Licea, Guillermo

2015-12-02

The increasing use of mobile devices in indoor spaces brings challenges to location methods. This work presents a hybrid intelligent method based on data mining and Type-2 fuzzy logic to locate mobile devices in an indoor space by zones using Wi-Fi signals from selected access points (APs). This approach takes advantage of wireless local area networks (WLANs) over other types of architectures and implements the complete method in a mobile application using the developed tools. Besides, the proposed approach is validated by experimental data obtained from case studies and the cross-validation technique. For the purpose of generating the fuzzy rules that conform to the Takagi-Sugeno fuzzy system structure, a semi-supervised data mining technique called subtractive clustering is used. This algorithm finds centers of clusters from the radius map given by the collected signals from APs. Measurements of Wi-Fi signals can be noisy due to several factors mentioned in this work, so this method proposed the use of Type-2 fuzzy logic for modeling and dealing with such uncertain information.

30 CFR 77.1703 - First-Aid training; supervisory employees.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false First-Aid training; supervisory employees. 77... UNDERGROUND COAL MINES Miscellaneous § 77.1703 First-Aid training; supervisory employees. The mine operator shall conduct first-aid training courses for selected supervisory employees at the mine. Within 60 days...

Atmospheric Mining in the Outer Solar System: Aerial Vehicle Mission and Design Issues

NASA Technical Reports Server (NTRS)

Palaszewski, Bryan

2015-01-01

Atmospheric mining in the outer solar system has been investigated as a means of fuel production for high energy propulsion and power. Fusion fuels such as Helium 3 (3He) and deuterium can be wrested from the atmospheres of Uranus and Neptune and either returned to Earth or used in-situ for energy production. Helium 3 and deuterium were the primary gases of interest with hydrogen being the primary propellant for nuclear thermal solid core and gas core rocket-based atmospheric flight. A series of analyses were undertaken to investigate resource capturing aspects of atmospheric mining in the outer solar system. This included the gas capturing rate, storage options, and different methods of direct use of the captured gases. While capturing 3He, large amounts of hydrogen and 4He are produced. With these two additional gases, the potential for fueling small and large fleets of additional exploration and exploitation vehicles exists. The mining aerospacecraft (ASC) could fly through the outer planet atmospheres, for global weather observations, localized storm or other disturbance investigations, wind speed measurements, polar observations, etc. Analyses of orbital transfer vehicles (OTVs), landers, and in-situ resource utilization (ISRU) mining factories are included. Preliminary observations are presented on near-optimal selections of moon base orbital locations, OTV power levels, and OTV and lander rendezvous points.

Proceedings of the 92nd regular meeting of the Rocky Mountain Coal Mining Institute

DOE Office of Scientific and Technical Information (OSTI.GOV)

Finnie, D.G.

1996-12-31

The proceedings of the 92nd Regular Meeting of the Rocky Mountain Coal Mining Institute held June 29-July 2, 1996 in Durango, CO. are presented. Attention was focused on the following areas: plots, plans, and partnerships in US mining; partnerships at McKinley; deregulation of the electric utility industry; environmental partnerships; Federal Mine Safety and Health Act; injury prevention in the coal mining industry; new trend in back injury prevention; and automated high wall mining. Selected papers are indexed separately for inclusion in the Energy Science and Technology Database.

Designing Meaning with Multiple Media Sources: A Case Study of an Eight-Year-Old Student's Writing Processes

ERIC Educational Resources Information Center

Ranker, Jason

2007-01-01

This case study closely examines how John (a former student of mine, age eight, second grade) composed during an informal writing group at school. Using qualitative research methods, I found that John selectively took up conventions, characters, story grammars, themes, and motifs from video games, television, Web pages, and comics. Likening his…

Moment tensor inversion with three-dimensional sensor configuration of mining induced seismicity (Kiruna mine, Sweden)

NASA Astrophysics Data System (ADS)

Ma, Ju; Dineva, Savka; Cesca, Simone; Heimann, Sebastian

2018-06-01

Mining induced seismicity is an undesired consequence of mining operations, which poses significant hazard to miners and infrastructures and requires an accurate analysis of the rupture process. Seismic moment tensors of mining-induced events help to understand the nature of mining-induced seismicity by providing information about the relationship between the mining, stress redistribution and instabilities in the rock mass. In this work, we adapt and test a waveform-based inversion method on high frequency data recorded by a dense underground seismic system in one of the largest underground mines in the world (Kiruna mine, Sweden). A stable algorithm for moment tensor inversion for comparatively small mining induced earthquakes, resolving both the double-couple and full moment tensor with high frequency data, is very challenging. Moreover, the application to underground mining system requires accounting for the 3-D geometry of the monitoring system. We construct a Green's function database using a homogeneous velocity model, but assuming a 3-D distribution of potential sources and receivers. We first perform a set of moment tensor inversions using synthetic data to test the effects of different factors on moment tensor inversion stability and source parameters accuracy, including the network spatial coverage, the number of sensors and the signal-to-noise ratio. The influence of the accuracy of the input source parameters on the inversion results is also tested. Those tests show that an accurate selection of the inversion parameters allows resolving the moment tensor also in the presence of realistic seismic noise conditions. Finally, the moment tensor inversion methodology is applied to eight events chosen from mining block #33/34 at Kiruna mine. Source parameters including scalar moment, magnitude, double-couple, compensated linear vector dipole and isotropic contributions as well as the strike, dip and rake configurations of the double-couple term were obtained. The orientations of the nodal planes of the double-couple component in most cases vary from NNW to NNE with a dip along the ore body or in the opposite direction.

Moment Tensor Inversion with 3D sensor configuration of Mining Induced Seismicity (Kiruna mine, Sweden)

NASA Astrophysics Data System (ADS)

Ma, Ju; Dineva, Savka; Cesca, Simone; Heimann, Sebastian

2018-03-01

Mining induced seismicity is an undesired consequence of mining operations, which poses significant hazard to miners and infrastructures and requires an accurate analysis of the rupture process. Seismic moment tensors of mining-induced events help to understand the nature of mining-induced seismicity by providing information about the relationship between the mining, stress redistribution and instabilities in the rock mass. In this work, we adapt and test a waveform-based inversion method on high frequency data recorded by a dense underground seismic system in one of the largest underground mines in the world (Kiruna mine, Sweden). Stable algorithm for moment tensor inversion for comparatively small mining induced earthquakes, resolving both the double couple and full moment tensor with high frequency data is very challenging. Moreover, the application to underground mining system requires accounting for the 3D geometry of the monitoring system. We construct a Green's function database using a homogeneous velocity model, but assuming a 3D distribution of potential sources and receivers. We first perform a set of moment tensor inversions using synthetic data to test the effects of different factors on moment tensor inversion stability and source parameters accuracy, including the network spatial coverage, the number of sensors and the signal-to-noise ratio. The influence of the accuracy of the input source parameters on the inversion results is also tested. Those tests show that an accurate selection of the inversion parameters allows resolving the moment tensor also in presence of realistic seismic noise conditions. Finally, the moment tensor inversion methodology is applied to 8 events chosen from mining block #33/34 at Kiruna mine. Source parameters including scalar moment, magnitude, double couple, compensated linear vector dipole and isotropic contributions as well as the strike, dip, rake configurations of the double couple term were obtained. The orientations of the nodal planes of the double-couple component in most cases vary from NNW to NNE with a dip along the ore body or in the opposite direction.

Constructing and Classifying Email Networks from Raw Forensic Images

DTIC Science & Technology

2016-09-01

data mining for sequence and pattern mining ; in medical imaging for image segmentation; and in computer vision for object recognition” [28]. 2.3.1...machine learning and data mining suite that is written in Python. It provides a platform for experiment selection, recommendation systems, and...predictivemod- eling. The Orange library is a hierarchically-organized toolbox of data mining components. Data filtering and probability assessment are at the

A Comprehensive Workflow of Mass Spectrometry-Based Untargeted Metabolomics in Cancer Metabolic Biomarker Discovery Using Human Plasma and Urine

PubMed Central

Zou, Wei; She, Jianwen; Tolstikov, Vladimir V.

2013-01-01

Current available biomarkers lack sensitivity and/or specificity for early detection of cancer. To address this challenge, a robust and complete workflow for metabolic profiling and data mining is described in details. Three independent and complementary analytical techniques for metabolic profiling are applied: hydrophilic interaction liquid chromatography (HILIC–LC), reversed-phase liquid chromatography (RP–LC), and gas chromatography (GC). All three techniques are coupled to a mass spectrometer (MS) in the full scan acquisition mode, and both unsupervised and supervised methods are used for data mining. The univariate and multivariate feature selection are used to determine subsets of potentially discriminative predictors. These predictors are further identified by obtaining accurate masses and isotopic ratios using selected ion monitoring (SIM) and data-dependent MS/MS and/or accurate mass MSn ion tree scans utilizing high resolution MS. A list combining all of the identified potential biomarkers generated from different platforms and algorithms is used for pathway analysis. Such a workflow combining comprehensive metabolic profiling and advanced data mining techniques may provide a powerful approach for metabolic pathway analysis and biomarker discovery in cancer research. Two case studies with previous published data are adapted and included in the context to elucidate the application of the workflow. PMID:24958150

Joint L2,1 Norm and Fisher Discrimination Constrained Feature Selection for Rational Synthesis of Microporous Aluminophosphates.

PubMed

Qi, Miao; Wang, Ting; Yi, Yugen; Gao, Na; Kong, Jun; Wang, Jianzhong

2017-04-01

Feature selection has been regarded as an effective tool to help researchers understand the generating process of data. For mining the synthesis mechanism of microporous AlPOs, this paper proposes a novel feature selection method by joint l 2,1 norm and Fisher discrimination constraints (JNFDC). In order to obtain more effective feature subset, the proposed method can be achieved in two steps. The first step is to rank the features according to sparse and discriminative constraints. The second step is to establish predictive model with the ranked features, and select the most significant features in the light of the contribution of improving the predictive accuracy. To the best of our knowledge, JNFDC is the first work which employs the sparse representation theory to explore the synthesis mechanism of six kinds of pore rings. Numerical simulations demonstrate that our proposed method can select significant features affecting the specified structural property and improve the predictive accuracy. Moreover, comparison results show that JNFDC can obtain better predictive performances than some other state-of-the-art feature selection methods. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Estimation of volume and mass and of changes in volume and mass of selected chat piles in the Picher mining district, Ottawa County, Oklahoma, 2005-10

USGS Publications Warehouse

Smith, S. Jerrod

2013-01-01

From the 1890s through the 1970s the Picher mining district in northeastern Ottawa County, Oklahoma, was the site of mining and processing of lead and zinc ore. When mining ceased in about 1979, as much as 165–300 million tons of mine tailings, locally referred to as “chat,” remained in the Picher mining district. Since 1979, some chat piles have been mined for aggregate materials and have decreased in volume and mass. Currently (2013), the land surface in the Picher mining district is covered by thousands of acres of chat, much of which remains on Indian trust land owned by allottees. The Bureau of Indian Affairs manages these allotted lands and oversees the sale and removal of chat from these properties. To help the Bureau of Indian Affairs better manage the sale and removal of chat, the U.S. Geological Survey, in cooperation with the Bureau of Indian Affairs, estimated the 2005 and 2010 volumes and masses of selected chat piles remaining on allotted lands in the Picher mining district. The U.S. Geological Survey also estimated the changes in volume and mass of these chat piles for the period 2005 through 2010. The 2005 and 2010 chat-pile volume and mass estimates were computed for 34 selected chat piles on 16 properties in the study area. All computations of volume and mass were performed on individual chat piles and on groups of chat piles in the same property. The Sooner property had the greatest estimated volume (4.644 million cubic yards) and mass (5.253 ± 0.473 million tons) of chat in 2010. Five of the selected properties (Sooner, Western, Lawyers, Skelton, and St. Joe) contained estimated chat volumes exceeding 1 million cubic yards and estimated chat masses exceeding 1 million tons in 2010. Four of the selected properties (Lucky Bill Humbah, Ta Mee Heh, Bird Dog, and St. Louis No. 6) contained estimated chat volumes of less than 0.1 million cubic yards and estimated chat masses of less than 0.1 million tons in 2010. The total volume of all selected chat piles was estimated to be 18.073 million cubic yards in 2005 and 16.171 million cubic yards in 2010. The total mass of all selected chat piles was estimated to be 20.445 ± 1.840 million tons in 2005 and 18.294 ± 1.646 million tons in 2010. All of the selected chat piles decreased in volume and mass for the period 2005 through 2010. Chat piles CP022 (Ottawa property) and CP013 (Sooner property) had some within-property chat-pile redistribution, with both chat piles having net decreases in volume and mass for the period 2005 through 2010. The Sooner property and the St. Joe property had the greatest volume (and mass) changes, with 1.266 million cubic yards and 0.217 million cubic yards (1.432 ± 0.129 million tons and 0.246 ± 0.022 million tons) of chat being removed, respectively. The chat removed from the Sooner and St. Joe properties accounts for about 78 percent of the chat removed from all selected chat piles and properties. The total volume and mass removed from all selected chat piles for the period 2005 through 2010 were estimated to be 1.902 million cubic yards and 2.151 ± 0.194 million tons, respectively.

Seamount characteristics and mine-site model applied to exploration- and mining-lease-block selection for cobalt-rich ferromanganese crusts

USGS Publications Warehouse

Hein, James R.; Conrad, Tracey A.; Dunham, Rachel E.

2009-01-01

Regulations are being developed through the International Seabed Authority (ISBA) for the exploration and mining of cobalt-rich ferromanganese crusts. This paper lays out geologic and geomorphologic criteria that can be used to determine the size and number of exploration and mine-site blocks that will be the focus of much discussion within the ISBA Council deliberations. The surface areas of 155 volcanic edifices in the central equatorial Pacific were measured and used to develop a mine-site model. The mine-site model considers areas above 2,500 m water depth as permissive, and narrows the general area available for exploration and mining to 20% of that permissive area. It is calculated that about eighteen 100 km2 explora-tion blocks, each composed of five 20km2 contiguous sub-blocks, would be adequate to identify a 260 km2 20-year-mine site; the mine site would be composed of thirteen of the 20km2 sub-blocks. In this hypothetical example, the 260 km2 mine site would be spread over four volcanic edifices and comprise 3.7% of the permissive area of the four edifices and 0.01% of the total area of those four edifices. The eighteen 100km2 exploration blocks would be selected from a limited geographic area. That confinement area is defined as having a long dimension of not more than 1,000 km and an area of not more than 300,000 km2.

Chemical stabilization of metals in mine wastes by transformed red mud and other iron compounds: laboratory tests.

PubMed

Ardau, C; Lattanzi, P; Peretti, R; Zucca, A

2014-01-01

A series of static and kinetic laboratory-scale tests were designed in order to evaluate the efficacy of transformed red mud (TRM) from bauxite refining residues, commercial zero-valent iron, and synthetic iron (III) hydroxides as sorbents/reagents to minimize the generation of acid drainage and the release of toxic elements from multi-contaminant-laden mine wastes. In particular, in some column experiments the percolation of meteoric water through a waste pile, alternated with periods of dryness, was simulated. Wastes were placed in columns together with sorbents/reagents in three different set-ups: as blended amendment (mixing method), as a bed at the bottom of the column (filtration method), or as a combination of the two previous methods. The filtration methods, which simulate the creation of a permeable reactive barrier downstream of a waste pile, are the most effective, while the use of sorbents/reagents as amendments leads to unsatisfactory results, because of the selective removal of only some contaminants. The efficacy of the filtration method is not significantly affected by the periods of dryness, except for a temporary rise of metal contents in the leachates due to dissolution of soluble salts formed upon evaporation in the dry periods. These results offer original information on advantages/limits in the use of TRM for the treatment of multi-contaminant-laden mine wastes, and represent the starting point for experimentation at larger scale.

High-frequency, long-duration water sampling in acid mine drainage studies: a short review of current methods and recent advances in automated water samplers

USGS Publications Warehouse

Chapin, Thomas

2015-01-01

Hand-collected grab samples are the most common water sampling method but using grab sampling to monitor temporally variable aquatic processes such as diel metal cycling or episodic events is rarely feasible or cost-effective. Currently available automated samplers are a proven, widely used technology and typically collect up to 24 samples during a deployment. However, these automated samplers are not well suited for long-term sampling in remote areas or in freezing conditions. There is a critical need for low-cost, long-duration, high-frequency water sampling technology to improve our understanding of the geochemical response to temporally variable processes. This review article will examine recent developments in automated water sampler technology and utilize selected field data from acid mine drainage studies to illustrate the utility of high-frequency, long-duration water sampling.

Warfighter Information Network-Tactical Increment 3 (WIN-T Inc 3)

DTIC Science & Technology

2013-12-01

T vehicles employed at BCT, Fires, (Ch-1) WIN-T Inc 3 December 2013 SAR April 16, 2014 16:49:41 UNCLASSIFIED 13 AVN , BfSB, and select force...passengers and crew from small arms fire, mines, IED and other anti-vehicle/ personnel threats. AVN , BfSB, and select force pooled assets...small arms fire, mines, IED and other anti-vehicle/ personnel threats. AVN , BfSB, and select force pooled assets operating within the

Survey of Natural Language Processing Techniques in Bioinformatics.

PubMed

Zeng, Zhiqiang; Shi, Hua; Wu, Yun; Hong, Zhiling

2015-01-01

Informatics methods, such as text mining and natural language processing, are always involved in bioinformatics research. In this study, we discuss text mining and natural language processing methods in bioinformatics from two perspectives. First, we aim to search for knowledge on biology, retrieve references using text mining methods, and reconstruct databases. For example, protein-protein interactions and gene-disease relationship can be mined from PubMed. Then, we analyze the applications of text mining and natural language processing techniques in bioinformatics, including predicting protein structure and function, detecting noncoding RNA. Finally, numerous methods and applications, as well as their contributions to bioinformatics, are discussed for future use by text mining and natural language processing researchers.

Solid-phase partitioning of mercury in artisanal gold mine tailings from selected key areas in Mindanao, Philippines, and its implications for mercury detoxification.

PubMed

Opiso, Einstine M; Aseneiro, John Paul J; Banda, Marybeth Hope T; Tabelin, Carlito B

2018-03-01

The solid-phase partitioning of mercury could provide necessary data in the identification of remediation techniques in contaminated artisanal gold mine tailings. This study was conducted to determine the total mercury content of mine wastes and identify its solid-phase partitioning through selective sequential extraction coupled with cold vapour atomic absorption spectroscopy. Samples from mine tailings and the carbon-in-pulp (CIP) process were obtained from selected key areas in Mindanao, Philippines. The results showed that mercury use is still prevalent among small-scale gold miners in the Philippines. Tailings after ball mill-gravity concentration (W-BM and Li-BM samples) from Mt Diwata and Libona contained high levels of mercury amounting to 25.024 and 6.5 mg kg -1 , respectively. The most prevalent form of mercury in the mine tailings was elemental/amalgamated mercury, followed by water soluble, exchangeable, organic and strongly bound phases, respectively. In contrast, mercury content of carbon-in-pulp residues were significantly lower at only 0.3 and 0.06 mg kg -1 for P-CIP (Del Pilar) and W-CIP (Mt Diwata), respectively. The bulk of mercury in P-CIP samples was partitioned in residual fraction while in W-CIP samples, water soluble mercury predominated. Overall, this study has several important implications with regards to mercury detoxification of contaminated mine tailings from Mindanao, Philippines.

Luobei graphite mines surrounding ecological environment monitoring based on high-resolution satellite data

NASA Astrophysics Data System (ADS)

Zhang, Lifeng; Liu, Xiaosha; Wan, Huawei; Liu, Xiaoman

2014-11-01

Graphite is one of the important industrial mineral raw materials, but the high content of heavy metals in tailings may cause soil pollution and other regional ecological environmental problems. Luobei has already become the largest production base of graphite. To find out the ecological situation in the region, further ecological risk analysis has been carried out. Luobei graphite mine which is located in Yabdanhe basin has been selected as the study area, SVM classifiers method with the support of GF-1 Satellite remote sensing data has been used, which is the first high-resolution earth observation satellite in China. The surrounding ecological environment was monitored and its potential impact on the ecological environment was analyzed by GIS platform. The results showed that the Luobei graphite mine located Yadanhe basin covers an area of 499.65 km2, the main types of forest ecosystems ( 44.05% of the total basin area ), followed by agricultural area( 35.14% ), grass area( 15.52% ), residential area ( 4.34% ), mining area ( 0.64% ) and water area( 0.30% ). By confirming the classification results, the total accuracy is 91.61%, the Kappa coefficient is 0.8991. Overall, GF-1 Satellite data can obtain regional ecosystems quickly, and provide a better data support for regional ecological resource protection zone. For Luobei graphite mines area, farmland and residential areas within its watershed are most vulnerable to mining, the higher proportion of farmland in duck river basin. The regulatory tailings need to be strengthened in the process of graphite mining processing.

Gene prioritization and clustering by multi-view text mining

PubMed Central

2010-01-01

Background Text mining has become a useful tool for biologists trying to understand the genetics of diseases. In particular, it can help identify the most interesting candidate genes for a disease for further experimental analysis. Many text mining approaches have been introduced, but the effect of disease-gene identification varies in different text mining models. Thus, the idea of incorporating more text mining models may be beneficial to obtain more refined and accurate knowledge. However, how to effectively combine these models still remains a challenging question in machine learning. In particular, it is a non-trivial issue to guarantee that the integrated model performs better than the best individual model. Results We present a multi-view approach to retrieve biomedical knowledge using different controlled vocabularies. These controlled vocabularies are selected on the basis of nine well-known bio-ontologies and are applied to index the vast amounts of gene-based free-text information available in the MEDLINE repository. The text mining result specified by a vocabulary is considered as a view and the obtained multiple views are integrated by multi-source learning algorithms. We investigate the effect of integration in two fundamental computational disease gene identification tasks: gene prioritization and gene clustering. The performance of the proposed approach is systematically evaluated and compared on real benchmark data sets. In both tasks, the multi-view approach demonstrates significantly better performance than other comparing methods. Conclusions In practical research, the relevance of specific vocabulary pertaining to the task is usually unknown. In such case, multi-view text mining is a superior and promising strategy for text-based disease gene identification. PMID:20074336

Data Mine and Forget It?: A Cautionary Tale

NASA Technical Reports Server (NTRS)

Tada, Yuri; Kraft, Norbert Otto; Orasanu, Judith M.

2011-01-01

With the development of new technologies, data mining has become increasingly popular. However, caution should be exercised in choosing the variables to include in data mining. A series of regression trees was created to demonstrate the change in the selection by the program of significant predictors based on the nature of variables.

30 CFR 72.710 - Selection, fit, use, and maintenance of approved respirators.

Code of Federal Regulations, 2012 CFR

2012-07-01

.../code_of_federal_regulations/ibr_locations.html. This incorporation by reference was approved by the..., DEPARTMENT OF LABOR COAL MINE SAFETY AND HEALTH HEALTH STANDARDS FOR COAL MINES Miscellaneous § 72.710...; http://www.ansi.org, and may be inspected at any MSHA Coal Mine Safety and Health district office, or...

30 CFR 72.710 - Selection, fit, use, and maintenance of approved respirators.

Code of Federal Regulations, 2013 CFR

2013-07-01

.../code_of_federal_regulations/ibr_locations.html. This incorporation by reference was approved by the..., DEPARTMENT OF LABOR COAL MINE SAFETY AND HEALTH HEALTH STANDARDS FOR COAL MINES Miscellaneous § 72.710...; http://www.ansi.org, and may be inspected at any MSHA Coal Mine Safety and Health district office, or...

30 CFR 72.710 - Selection, fit, use, and maintenance of approved respirators.

Code of Federal Regulations, 2014 CFR

2014-07-01

.../code_of_federal_regulations/ibr_locations.html. This incorporation by reference was approved by the..., DEPARTMENT OF LABOR COAL MINE SAFETY AND HEALTH HEALTH STANDARDS FOR COAL MINES Miscellaneous § 72.710...; http://www.ansi.org, and may be inspected at any MSHA Coal Mine Safety and Health district office, or...

Coal resource assessments using coal availability and recoverability methods

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rohrbacher, T.J.

1997-12-01

The U.S. Geological Survey (USGS), in conjunction with state geological surveys and other federal agencies, has initiated a study and developed methodology to reassess the nation`s major coal resources. This study differs from previous coal resource assessments of the USGS, U.S. Bureau of Mines, and the Department of Energy`s Energy Information Administration, because this program: (1) Identifies and characterizes the coal beds and coal zones that will provide the bulk of the nation`s coal-derived energy during the first quarter of the twenty-first century; (2) organizes geologic, chemical, environmental, and geographic information in digital format and makes these data available tomore » the public through the Internet or other digital media, such as CD ROMs; (3) includes coal resource availability and coal recoverability analyses for selected areas; (4) provides economic assessments and coal recoverability analyses for selected areas; (5) provides methodology to perform socio-economic impact analysis related to coal mining in specific geographical areas as small as a county.« less

EDULISS: a small-molecule database with data-mining and pharmacophore searching capabilities

PubMed Central

Hsin, Kun-Yi; Morgan, Hugh P.; Shave, Steven R.; Hinton, Andrew C.; Taylor, Paul; Walkinshaw, Malcolm D.

2011-01-01

We present the relational database EDULISS (EDinburgh University Ligand Selection System), which stores structural, physicochemical and pharmacophoric properties of small molecules. The database comprises a collection of over 4 million commercially available compounds from 28 different suppliers. A user-friendly web-based interface for EDULISS (available at http://eduliss.bch.ed.ac.uk/) has been established providing a number of data-mining possibilities. For each compound a single 3D conformer is stored along with over 1600 calculated descriptor values (molecular properties). A very efficient method for unique compound recognition, especially for a large scale database, is demonstrated by making use of small subgroups of the descriptors. Many of the shape and distance descriptors are held as pre-calculated bit strings permitting fast and efficient similarity and pharmacophore searches which can be used to identify families of related compounds for biological testing. Two ligand searching applications are given to demonstrate how EDULISS can be used to extract families of molecules with selected structural and biophysical features. PMID:21051336

A review of oxygen removal from oxygen-bearing coal-mine methane.

PubMed

Zhao, Peiyu; Zhang, Guojie; Sun, Yinghui; Xu, Ying

2017-06-01

In this article, a comparison will be made concerning the advantages and disadvantages of five kinds of coal mine methane (CMM) deoxygenation method, including pressure swing adsorption, combustion, membrane separation, non-metallic reduction, and cryogenic distillation. Pressure swing adsorption has a wide range of application and strong production capacity. To achieve this goal, adsorbent must have high selectivity, adsorption capacity, and adequate adsorption/desorption kinetics, remain stable after several adsorption/desorption cycles, and possess good thermal and mechanical stabilities. Catalytic combustion deoxygenation is a high-temperature exothermic redox chemical reaction, which releases large amounts of thermal energy. So, the stable and accurate control of the temperature is not easy. Meanwhile partial methane is lost. The key of catalytic combustion deoxygenation lies in the development of high-efficiency catalyst. Membrane separation has advantages of high separation efficiency and low energy consumption. However, there are many obstacles, including higher costs. Membrane materials have the requirements of both high permeability and high selectivity. The development of new membrane materials is a key for membrane separation. Cryogenic distillation has many excellence advantages, such as high purity production and high recovery. However, the energy consumption increases with decreasing CH 4 concentrations in feed gas. Moreover, there are many types of operational security problems. And that several kinds of deoxygenation techniques mentioned above have an economic value just for oxygen-bearing CMM with methane content above 30%. Moreover, all the above methods are not applicable to deoxygenation of low concentration CMM. Non-metallic reduction method cannot only realize cyclic utilization of deoxidizer but also have no impurity gases generation. It also has a relatively low cost and low loss rate of methane, and the oxygen is removed thoroughly. In particular, the non-metallic reduction method has good development prospects for low concentration oxygen-bearing CMM. This article also points out the direction of future development of coal mine methane deoxygenation.

Towards "Precision Mining" of wastewater: Selective recovery of Cu from acid mine drainage onto diatomite supported nanoscale zerovalent iron particles.

PubMed

Crane, R A; Sapsford, D J

2018-07-01

This paper introduces the concept of 'Precision Mining' of metals which can be defined as a process for the selective in situ uptake of a metal from a material or media, with subsequent retrieval and recovery of the target metal. In order to demonstrate this concept nanoscale zerovalent iron (nZVI) was loaded onto diatomaceous earth (DE) and tested for the selective uptake of Cu from acid mine drainage (AMD) and subsequent release. Batch experiments were conducted using the AMD and nZVI-DE at 4.0-16.0 g/L. Results demonstrate nZVI-DE as highly selective for Cu removal with >99% uptake recorded after 0.25 h when using nZVI-DE concentrations ≥12.0 g/L, despite appreciable concentrations of numerous other metals in the AMD, namely: Co, Ni, Mn and Zn. Cu uptake was maintained in excess of 4 and 24 h when using nZVI-DE concentrations of 12.0 and 16.0 g/L respectively. Near-total Cu release from the nZVI-DE was then recorded and attributed to the depletion of the nZVI component and the subsequent Eh, DO and pH recovery. This novel Cu uptake and release mechanism, once appropriately engineered, holds great promise as a novel 'Precision Mining' process for the rapid and selective Cu recovery from acidic wastewater, process effluents and leach liquors. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

Atmospheric Mining in the Outer Solar System: Outer Planet Orbital Transfer and Lander Analyses

NASA Technical Reports Server (NTRS)

Palaszewski, Bryan

2016-01-01

Atmospheric mining in the outer solar system has been investigated as a means of fuel production for high energy propulsion and power. Fusion fuels such as Helium 3 (3He) and deuterium can be wrested from the atmospheres of Uranus and Neptune and either returned to Earth or used in-situ for energy production. Helium 3 and deuterium were the primary gases of interest with hydrogen being the primary propellant for nuclear thermal solid core and gas core rocket-based atmospheric flight. A series of analyses were undertaken to investigate resource capturing aspects of atmospheric mining in the outer solar system. This included the gas capturing rate, storage options, and different methods of direct use of the captured gases. While capturing 3He, large amounts of hydrogen and 4He are produced. Analyses of orbital transfer vehicles (OTVs), landers, and the issues with in-situ resource utilization (ISRU) mining factories are included. Preliminary observations are presented on near-optimal selections of moon base orbital locations, OTV power levels, and OTV and lander rendezvous points. For analyses of round trip OTV flights from Uranus to Miranda or Titania, a 10-Megawatt electric (MWe) OTV power level and a 200-metric ton (MT) lander payload were selected based on a relative short OTV trip time and minimization of the number of lander flights. A similar optimum power level is suggested for OTVs flying from low orbit around Neptune to Thalassa or Triton. Several moon base sites at Uranus and Neptune and the OTV requirements to support them are also addressed.

Atmospheric Mining in the Outer Solar System: Outer Planet Orbital Transfer and Lander Analyses

NASA Technical Reports Server (NTRS)

Palaszewski, Bryan

2016-01-01

Atmospheric mining in the outer solar system has been investigated as a means of fuel production for high energy propulsion and power. Fusion fuels such as Helium 3 (3He) and deuterium can be wrested from the atmospheres of Uranus and Neptune and either returned to Earth or used in-situ for energy production. Helium 3 and deuterium were the primary gases of interest with hydrogen being the primary propellant for nuclear thermal solid core and gas core rocket-based atmospheric flight. A series of analyses were undertaken to investigate resource capturing aspects of atmospheric mining in the outer solar system. This included the gas capturing rate, storage options, and different methods of direct use of the captured gases. While capturing 3He, large amounts of hydrogen and 4He are produced. Analyses of orbital transfer vehicles (OTVs), landers, and the issues with in-situ resource utilization (ISRU) mining factories are included. Preliminary observations are presented on near-optimal selections of moon base orbital locations, OTV power levels, and OTV and lander rendezvous points. For analyses of round trip OTV flights from Uranus to Miranda or Titania, a 10- Megawatt electric (MWe) OTV power level and a 200 metricton (MT) lander payload were selected based on a relative short OTV trip time and minimization of the number of lander flights. A similar optimum power level is suggested for OTVs flying from low orbit around Neptune to Thalassa or Triton. Several moon base sites at Uranus and Neptune and the OTV requirements to support them are also addressed.

Intelligent Scheduling for Underground Mobile Mining Equipment.

PubMed

Song, Zhen; Schunnesson, Håkan; Rinne, Mikael; Sturgul, John

2015-01-01

Many studies have been carried out and many commercial software applications have been developed to improve the performances of surface mining operations, especially for the loader-trucks cycle of surface mining. However, there have been quite few studies aiming to improve the mining process of underground mines. In underground mines, mobile mining equipment is mostly scheduled instinctively, without theoretical support for these decisions. Furthermore, in case of unexpected events, it is hard for miners to rapidly find solutions to reschedule and to adapt the changes. This investigation first introduces the motivation, the technical background, and then the objective of the study. A decision support instrument (i.e. schedule optimizer for mobile mining equipment) is proposed and described to address this issue. The method and related algorithms which are used in this instrument are presented and discussed. The proposed method was tested by using a real case of Kittilä mine located in Finland. The result suggests that the proposed method can considerably improve the working efficiency and reduce the working time of the underground mine.

Modern methods of surveyor observations in opencast mining under complex hydrogeological conditions.

NASA Astrophysics Data System (ADS)

Usoltseva, L. A.; Lushpei, V. P.; Mursin, VA

2017-10-01

The article considers the possibility of linking the modern methods of surveying security of open mining works to improve industrial safety in the Primorsky Territory, as well as their use in the educational process. Industrial Safety in the management of Surface Mining depends largely on the applied assessment methods and methods of stability of pit walls and slopes of dumps in the complex mining and hydro-geological conditions.

Comparison of ALE and SPH Methods for Simulating Mine Blast Effects on Structures

DTIC Science & Technology

2010-12-01

Comparison of ALE and SPH methods for simulating mine blast effects on struc- tures Geneviève Toussaint Amal Bouamoul DRDC Valcartier Defence R&D...Canada – Valcartier Technical Report DRDC Valcartier TR 2010-326 December 2010 Comparison of ALE and SPH methods for simulating mine blast...Valcartier TR 2010-326 iii Executive summary Comparison of ALE and SPH methods for simulating mine blast effects on structures

Mining Land Subsidence Monitoring Using SENTINEL-1 SAR Data

NASA Astrophysics Data System (ADS)

Yuan, W.; Wang, Q.; Fan, J.; Li, H.

2017-09-01

In this paper, DInSAR technique was used to monitor land subsidence in mining area. The study area was selected in the coal mine area located in Yuanbaoshan District, Chifeng City, and Sentinel-1 data were used to carry out DInSAR techniqu. We analyzed the interferometric results by Sentinel-1 data from December 2015 to May 2016. Through the comparison of the results of DInSAR technique and the location of the mine on the optical images, it is shown that DInSAR technique can be used to effectively monitor the land subsidence caused by underground mining, and it is an effective tool for law enforcement of over-mining.

Prediction of wastewater quality indicators at the inflow to the wastewater treatment plant using data mining methods

NASA Astrophysics Data System (ADS)

Szeląg, Bartosz; Barbusiński, Krzysztof; Studziński, Jan; Bartkiewicz, Lidia

2017-11-01

In the study, models developed using data mining methods are proposed for predicting wastewater quality indicators: biochemical and chemical oxygen demand, total suspended solids, total nitrogen and total phosphorus at the inflow to wastewater treatment plant (WWTP). The models are based on values measured in previous time steps and daily wastewater inflows. Also, independent prediction systems that can be used in case of monitoring devices malfunction are provided. Models of wastewater quality indicators were developed using MARS (multivariate adaptive regression spline) method, artificial neural networks (ANN) of the multilayer perceptron type combined with the classification model (SOM) and cascade neural networks (CNN). The lowest values of absolute and relative errors were obtained using ANN+SOM, whereas the MARS method produced the highest error values. It was shown that for the analysed WWTP it is possible to obtain continuous prediction of selected wastewater quality indicators using the two developed independent prediction systems. Such models can ensure reliable WWTP work when wastewater quality monitoring systems become inoperable, or are under maintenance.

Experimental Study on Comprehensive Performance of Full Tailings Paste Filling in Jiaojia Gold Mine.

NASA Astrophysics Data System (ADS)

Zhang, Z. H.; Zou, Q. B.; Wang, P. Z.

2017-11-01

Filling mining method is the main method of modern underground mining. High concentration cementation is carried out using coarse tailing of +37 μm, and the mine has maturely used classified tailings paste filling technology. The gold mine studied on the performance of full tailings paste filling in order to maximize the use of tailings, reduce -37 μm fine tailings discharged into the tailing pond, reduce mining cost and eliminate security risks. The results show that: comprehensive index of full tailings paste filling is higher than that of classified tailings high concentration cementation filling, and the full tailings paste filling of 76% mass concentration has the best comprehensive index of slump, expansibility, yield stress and viscosity to meet the mining method requirements, which can effectively reduce the mining loss rate and dilution rate.

Application of an integrated biomarker response index to assess ground water contamination in the vicinity of a rare earth mine tailings site.

PubMed

Si, Wantong; He, Xiaoying; Li, Ailing; Liu, Li; Li, Jisheng; Gong, Donghui; Liu, Juan; Liu, Jumei; Shen, Weishou; Zhang, Xuefeng

2016-09-01

We utilized a multi-biomarker approach (Integrated Biomarker Response version 2, IBRv2) to investigate the scope and dispersion of groundwater contamination surrounding a rare earth mine tailings impoundment. Parameters of SD rat included in our IBRv2 analyses were glutathione levels, superoxide dismutase, catalase, and glutathione peroxidase activities, total anti-oxidative capacity, chromosome aberration, and micronucleus formation. The concentration of 20 pollutants including Cl(-), SO4 (2-), Na(+), K(+), Mg(2+), Ca(2+), TH, CODMn, As, Se, TDS, Be, Mn, Co, Ni, Cu, Zn, Mo, Cd, and Pb in the groundwater were also analyzed. The results of this study indicated that groundwater polluted by tailings impoundment leakage exhibited significant ecotoxicological effects. The selected biomarkers responded sensitively to groundwater pollution. Analyses showed a significant relationship between IBRv2 values and the Nemerow composite index. IBRv2 could serve as a sensitive ecotoxicological diagnosis method for assessing groundwater contamination in the vicinity of rare earth mine tailings. According to the trend of IBRv2 value and Nemerow composite index, the maximum diffusion distance of groundwater pollutants from rare earth mine tailings was approximately 5.7 km.

Mining a clinical data warehouse to discover disease-finding associations using co-occurrence statistics.

PubMed

Cao, Hui; Markatou, Marianthi; Melton, Genevieve B; Chiang, Michael F; Hripcsak, George

2005-01-01

This paper applies co-occurrence statistics to discover disease-finding associations in a clinical data warehouse. We used two methods, chi2 statistics and the proportion confidence interval (PCI) method, to measure the dependence of pairs of diseases and findings, and then used heuristic cutoff values for association selection. An intrinsic evaluation showed that 94 percent of disease-finding associations obtained by chi2 statistics and 76.8 percent obtained by the PCI method were true associations. The selected associations were used to construct knowledge bases of disease-finding relations (KB-chi2, KB-PCI). An extrinsic evaluation showed that both KB-chi2 and KB-PCI could assist in eliminating clinically non-informative and redundant findings from problem lists generated by our automated problem list summarization system.

A Comparison of different learning models used in Data Mining for Medical Data

NASA Astrophysics Data System (ADS)

Srimani, P. K.; Koti, Manjula Sanjay

2011-12-01

The present study aims at investigating the different Data mining learning models for different medical data sets and to give practical guidelines to select the most appropriate algorithm for a specific medical data set. In practical situations, it is absolutely necessary to take decisions with regard to the appropriate models and parameters for diagnosis and prediction problems. Learning models and algorithms are widely implemented for rule extraction and the prediction of system behavior. In this paper, some of the well-known Machine Learning(ML) systems are investigated for different methods and are tested on five medical data sets. The practical criteria for evaluating different learning models are presented and the potential benefits of the proposed methodology for diagnosis and learning are suggested.

Linear data mining the Wichita clinical matrix suggests sleep and allostatic load involvement in chronic fatigue syndrome.

PubMed

Gurbaxani, Brian M; Jones, James F; Goertzel, Benjamin N; Maloney, Elizabeth M

2006-04-01

To provide a mathematical introduction to the Wichita (KS, USA) clinical dataset, which is all of the nongenetic data (no microarray or single nucleotide polymorphism data) from the 2-day clinical evaluation, and show the preliminary findings and limitations, of popular, matrix algebra-based data mining techniques. An initial matrix of 440 variables by 227 human subjects was reduced to 183 variables by 164 subjects. Variables were excluded that strongly correlated with chronic fatigue syndrome (CFS) case classification by design (for example, the multidimensional fatigue inventory [MFI] data), that were otherwise self reporting in nature and also tended to correlate strongly with CFS classification, or were sparse or nonvarying between case and control. Subjects were excluded if they did not clearly fall into well-defined CFS classifications, had comorbid depression with melancholic features, or other medical or psychiatric exclusions. The popular data mining techniques, principle components analysis (PCA) and linear discriminant analysis (LDA), were used to determine how well the data separated into groups. Two different feature selection methods helped identify the most discriminating parameters. Although purely biological features (variables) were found to separate CFS cases from controls, including many allostatic load and sleep-related variables, most parameters were not statistically significant individually. However, biological correlates of CFS, such as heart rate and heart rate variability, require further investigation. Feature selection of a limited number of variables from the purely biological dataset produced better separation between groups than a PCA of the entire dataset. Feature selection highlighted the importance of many of the allostatic load variables studied in more detail by Maloney and colleagues in this issue [1] , as well as some sleep-related variables. Nonetheless, matrix linear algebra-based data mining approaches appeared to be of limited utility when compared with more sophisticated nonlinear analyses on richer data types, such as those found in Maloney and colleagues [1] and Goertzel and colleagues [2] in this issue.

Selective Guide to Literature on Mining Engineering. Engineering Literature Guides, Number 6.

ERIC Educational Resources Information Center

Erdmann, Charlotte A., Comp.

The multidisciplinary field of mining engineering offers many challenges. Often, many sources must be used to solve a problem. This document is a survey of information sources in mining engineering and is intended to identify those core resources which can help engineers and librarians to find information about the discipline. Sections include:…

A case–control study of mesothelioma in Minnesota iron ore (taconite) miners

PubMed Central

Lambert, Christine S; Alexander, Bruce H; Ramachandran, Gurumurthy; MacLehose, Richard F; Nelson, Heather H; Ryan, Andrew D; Mandel, Jeffrey H

2018-01-01

Objectives An excess of mesothelioma has been observed in iron ore miners in Northeastern Minnesota. Mining and processing of taconite iron ore generate exposures that include elongate mineral particles (EMPs) of amphibole and non-amphibole origin. We conducted a nested case–control study of mesothelioma in a cohort of 68 737 iron ore miners (haematite and taconite ore miners) to evaluate the association between mesothelioma, employment and EMP exposures from taconite mining. Methods Mesothelioma cases (N=80) were identified through the Minnesota Cancer Surveillance System (MCSS) and death certificates. Four controls of similar age were selected for each case with 315 controls ultimately eligible for inclusion. Mesothelioma risk was evaluated by estimating rate ratios and 95% CIs with conditional logistic regression in relation to duration of taconite industry employment and cumulative EMP exposure [(EMP/cc)×years], defined by the National Institute for Occupational Safety and Health (NIOSH) 7400 method. Models were adjusted for employment in haematite mining and potential exposure to commercial asbestos products used in the industry. Results All mesothelioma cases were male and 57 of the cases had work experience in the taconite industry. Mesothelioma was associated with the number of years employed in the taconite industry (RR=1.03, 95% CI 1.00 to 1.06) and cumulative EMP exposure (RR=1.10, 95% CI 0.97 to –1.24). No association was observed with employment in haematite mining. Conclusions These results support an association between mesothelioma and employment duration and possibly EMP exposure in taconite mining and processing. The type of EMP was not determined. The potential role of commercial asbestos cannot be entirely ruled out. PMID:26655961

Study of application of ERTS-A imagery to fracture-related mine safety hazards in the coal mining industry

NASA Technical Reports Server (NTRS)

Wier, C. E.; Wobber, F. J.; Russell, O. R.; Martin, K. R. (Principal Investigator)

1973-01-01

The author has identified the following significant results. Mined land reclamation analysis procedures developed within the Indiana portion of the Illinois Coal Basin were independently tested in Ohio utilizing 1:80,000 scale enlargements of ERTS-1 image 1029-15361-7 (dated August 21, 1972). An area in Belmont County was selected for analysis due to the extensive surface mining and the different degrees of reclamation occurring in this area. Contour mining in this area provided the opportunity to extend techniques developed for analysis of relatively flat mining areas in Indiana to areas of rolling topography in Ohio. The analysts had no previous experience in the area. Field investigations largely confirmed office analysis results although in a few areas estimates of vegetation percentages were found to be too high. In one area this error approximated 25%. These results suggest that systematic ERTS-1 analysis in combination with selective field sampling can provide reliable vegetation percentage estimates in excess of 25% accuracy with minimum equipment investment and training. The utility of ERTS-1 for practical and reasonably reliable update of mined lands information for groups with budget limitations is suggested. Many states can benefit from low cost updates using ERTS-1 imagery from public sources.

Analyzing Large Gene Expression and Methylation Data Profiles Using StatBicRM: Statistical Biclustering-Based Rule Mining

PubMed Central

Maulik, Ujjwal; Mallik, Saurav; Mukhopadhyay, Anirban; Bandyopadhyay, Sanghamitra

2015-01-01

Microarray and beadchip are two most efficient techniques for measuring gene expression and methylation data in bioinformatics. Biclustering deals with the simultaneous clustering of genes and samples. In this article, we propose a computational rule mining framework, StatBicRM (i.e., statistical biclustering-based rule mining) to identify special type of rules and potential biomarkers using integrated approaches of statistical and binary inclusion-maximal biclustering techniques from the biological datasets. At first, a novel statistical strategy has been utilized to eliminate the insignificant/low-significant/redundant genes in such way that significance level must satisfy the data distribution property (viz., either normal distribution or non-normal distribution). The data is then discretized and post-discretized, consecutively. Thereafter, the biclustering technique is applied to identify maximal frequent closed homogeneous itemsets. Corresponding special type of rules are then extracted from the selected itemsets. Our proposed rule mining method performs better than the other rule mining algorithms as it generates maximal frequent closed homogeneous itemsets instead of frequent itemsets. Thus, it saves elapsed time, and can work on big dataset. Pathway and Gene Ontology analyses are conducted on the genes of the evolved rules using David database. Frequency analysis of the genes appearing in the evolved rules is performed to determine potential biomarkers. Furthermore, we also classify the data to know how much the evolved rules are able to describe accurately the remaining test (unknown) data. Subsequently, we also compare the average classification accuracy, and other related factors with other rule-based classifiers. Statistical significance tests are also performed for verifying the statistical relevance of the comparative results. Here, each of the other rule mining methods or rule-based classifiers is also starting with the same post-discretized data-matrix. Finally, we have also included the integrated analysis of gene expression and methylation for determining epigenetic effect (viz., effect of methylation) on gene expression level. PMID:25830807

Analyzing large gene expression and methylation data profiles using StatBicRM: statistical biclustering-based rule mining.

PubMed

Maulik, Ujjwal; Mallik, Saurav; Mukhopadhyay, Anirban; Bandyopadhyay, Sanghamitra

2015-01-01

Microarray and beadchip are two most efficient techniques for measuring gene expression and methylation data in bioinformatics. Biclustering deals with the simultaneous clustering of genes and samples. In this article, we propose a computational rule mining framework, StatBicRM (i.e., statistical biclustering-based rule mining) to identify special type of rules and potential biomarkers using integrated approaches of statistical and binary inclusion-maximal biclustering techniques from the biological datasets. At first, a novel statistical strategy has been utilized to eliminate the insignificant/low-significant/redundant genes in such way that significance level must satisfy the data distribution property (viz., either normal distribution or non-normal distribution). The data is then discretized and post-discretized, consecutively. Thereafter, the biclustering technique is applied to identify maximal frequent closed homogeneous itemsets. Corresponding special type of rules are then extracted from the selected itemsets. Our proposed rule mining method performs better than the other rule mining algorithms as it generates maximal frequent closed homogeneous itemsets instead of frequent itemsets. Thus, it saves elapsed time, and can work on big dataset. Pathway and Gene Ontology analyses are conducted on the genes of the evolved rules using David database. Frequency analysis of the genes appearing in the evolved rules is performed to determine potential biomarkers. Furthermore, we also classify the data to know how much the evolved rules are able to describe accurately the remaining test (unknown) data. Subsequently, we also compare the average classification accuracy, and other related factors with other rule-based classifiers. Statistical significance tests are also performed for verifying the statistical relevance of the comparative results. Here, each of the other rule mining methods or rule-based classifiers is also starting with the same post-discretized data-matrix. Finally, we have also included the integrated analysis of gene expression and methylation for determining epigenetic effect (viz., effect of methylation) on gene expression level.

Sustainable mineral resources management: from regional mineral resources exploration to spatial contamination risk assessment of mining

NASA Astrophysics Data System (ADS)

Jordan, Gyozo

2009-07-01

Wide-spread environmental contamination associated with historic mining in Europe has triggered social responses to improve related environmental legislation, the environmental assessment and management methods for the mining industry. Mining has some unique features such as natural background contamination associated with mineral deposits, industrial activities and contamination in the three-dimensional subsurface space, problem of long-term remediation after mine closure, problem of secondary contaminated areas around mine sites, land use conflicts and abandoned mines. These problems require special tools to address the complexity of the environmental problems of mining-related contamination. The objective of this paper is to show how regional mineral resources mapping has developed into the spatial contamination risk assessment of mining and how geological knowledge can be transferred to environmental assessment of mines. The paper provides a state-of-the-art review of the spatial mine inventory, hazard, impact and risk assessment and ranking methods developed by national and international efforts in Europe. It is concluded that geological knowledge on mineral resources exploration is essential and should be used for the environmental contamination assessment of mines. Also, sufficient methodological experience, knowledge and documented results are available, but harmonisation of these methods is still required for the efficient spatial environmental assessment of mine contamination.

Personalized Privacy-Preserving Frequent Itemset Mining Using Randomized Response

PubMed Central

Sun, Chongjing; Fu, Yan; Zhou, Junlin; Gao, Hui

2014-01-01

Frequent itemset mining is the important first step of association rule mining, which discovers interesting patterns from the massive data. There are increasing concerns about the privacy problem in the frequent itemset mining. Some works have been proposed to handle this kind of problem. In this paper, we introduce a personalized privacy problem, in which different attributes may need different privacy levels protection. To solve this problem, we give a personalized privacy-preserving method by using the randomized response technique. By providing different privacy levels for different attributes, this method can get a higher accuracy on frequent itemset mining than the traditional method providing the same privacy level. Finally, our experimental results show that our method can have better results on the frequent itemset mining while preserving personalized privacy. PMID:25143989

Personalized privacy-preserving frequent itemset mining using randomized response.

PubMed

Sun, Chongjing; Fu, Yan; Zhou, Junlin; Gao, Hui

2014-01-01

Frequent itemset mining is the important first step of association rule mining, which discovers interesting patterns from the massive data. There are increasing concerns about the privacy problem in the frequent itemset mining. Some works have been proposed to handle this kind of problem. In this paper, we introduce a personalized privacy problem, in which different attributes may need different privacy levels protection. To solve this problem, we give a personalized privacy-preserving method by using the randomized response technique. By providing different privacy levels for different attributes, this method can get a higher accuracy on frequent itemset mining than the traditional method providing the same privacy level. Finally, our experimental results show that our method can have better results on the frequent itemset mining while preserving personalized privacy.

Feature Selection in Classification of Eye Movements Using Electrooculography for Activity Recognition

PubMed Central

Mala, S.; Latha, K.

2014-01-01

Activity recognition is needed in different requisition, for example, reconnaissance system, patient monitoring, and human-computer interfaces. Feature selection plays an important role in activity recognition, data mining, and machine learning. In selecting subset of features, an efficient evolutionary algorithm Differential Evolution (DE), a very efficient optimizer, is used for finding informative features from eye movements using electrooculography (EOG). Many researchers use EOG signals in human-computer interactions with various computational intelligence methods to analyze eye movements. The proposed system involves analysis of EOG signals using clearness based features, minimum redundancy maximum relevance features, and Differential Evolution based features. This work concentrates more on the feature selection algorithm based on DE in order to improve the classification for faultless activity recognition. PMID:25574185

Feature selection in classification of eye movements using electrooculography for activity recognition.

PubMed

Mala, S; Latha, K

2014-01-01

Activity recognition is needed in different requisition, for example, reconnaissance system, patient monitoring, and human-computer interfaces. Feature selection plays an important role in activity recognition, data mining, and machine learning. In selecting subset of features, an efficient evolutionary algorithm Differential Evolution (DE), a very efficient optimizer, is used for finding informative features from eye movements using electrooculography (EOG). Many researchers use EOG signals in human-computer interactions with various computational intelligence methods to analyze eye movements. The proposed system involves analysis of EOG signals using clearness based features, minimum redundancy maximum relevance features, and Differential Evolution based features. This work concentrates more on the feature selection algorithm based on DE in order to improve the classification for faultless activity recognition.

Mine Winder Drives in Integrated Copper Complex

NASA Astrophysics Data System (ADS)

Dey, Pranab Kumar

2018-04-01

This paper describes various features required to be evaluated before selecting mine winder drives. In handling such project, the selection of proper equipments is necessary at the initial design stage of planning and how the electrical system design considers all aspects to protect the grid from unwarranted influence of the connected loads and minimize the generation of harmonics due to network configurations adopted to keep it within the stipulated value dictated by the supply authorities has been discussed. The design should cover all aspects to provide quality power with effective braking system required as per the mining statute for operational safety. It also emphasizes on the requirement of quality maintenance.

Text Mining in Biomedical Domain with Emphasis on Document Clustering

PubMed Central

2017-01-01

Objectives 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. Methods 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. Results 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. Conclusions 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. PMID:28875048

Rehabilitation of gypsum-mined lands in the Indian desert

USGS Publications Warehouse

Sharma, K.D.; Kumar, S.; Gough, L.P.

2001-01-01

The economic importance of mining in the Indian Desert is second only to agriculture. Land disturbed by mining, however, has only recently been the focus of rehabilitation efforts. This research assesses the success of rehabilitation plans used to revegetate gypsum mine spoils within the environmental constraints of the north-west Indian hot-desert ecosystem. The rehabilitation plan first examined both mined and unmined areas and established assessments of existing vegetative cover and the quality of native soils and mine spoils. Tests were made on the effect of the use, and conservation, of available water through rainwater harvesting, amendment application (for physical and chemical spoil modification), plant establishment protocols, and the selection of appropriate germ plasm. Our results show that the resulting vegetative cover is capable of perpetuating itself under natural conditions while concurrently meeting the needs of farmers. Although the mine spoils are deficient in organic matter and phosphorus, they possess adequate amounts of all other nutrients. Total boron concentrations (>5.0 mg kg-1) in both the topsail and mine spoil indicate potentially phytotoxic conditions. Electrical conductance of mine spoil is 6-10 times higher than for topsail with a near-neutral pH. Populations of spoil fungi, Azotobactor, and nitrifying bacteria are low. The soil moisture storage in rainwater harvesting plots increased by 8% over the control and 48% over the unmined area. As a result of rehabilitation efforts, mine spoils show a steady buildup in organic carbon, and P and K due to the decomposition of farmyard manure and the contribution of nitrogen fixation by the established leguminous plant species. The rehabilitation protocol used at the site appears to have been successful. Following revegetation of the area with a mixture of trees, shrubs, and grasses, native implanted species have become established. Species diversity, measured in terms of species richness, increased after one year and then gradually declined over time; the decline was the result of the loss of annual species. The study not only develops methods of gypsum mine land rehabilitation but also helps in understanding processes of rehabilitation success in arid regions and emphasizes the importance of long-term monitoring of rehabilitation success. Copyright ?? 2001 Taylor & Francis.

Selected Water- and Sediment-Quality, Aquatic Biology, and Mine-Waste Data from the Ely Copper Mine Superfund Site, Vershire, VT, 1998-2007

USGS Publications Warehouse

Argue, Denise M.; Kiah, Richard G.; Piatak, Nadine M.; Seal, Robert R.; Hammarstrom, Jane M.; Hathaway, Edward; Coles, James F.

2008-01-01

The data contained in this report are a compilation of selected water- and sediment-quality, aquatic biology, and mine-waste data collected at the Ely Copper Mine Superfund site in Vershire, VT, from August 1998 through May 2007. The Ely Copper Mine Superfund site is in eastern, central Vermont (fig. 1) within the Vermont Copper Belt (Hammarstrom and others, 2001). The Ely Copper Mine site was placed on the U.S. Environmental Protection Agency (USEPA) National Priorities List in 2001. Previous investigations conducted at the site documented that the mine is contributing metals and highly acidic waters to local streams (Hammarstrom and others, 2001; Holmes and others, 2002; Piatak and others, 2003, 2004, and 2006). The U.S. Geological Survey (USGS), in cooperation with the USEPA, compiled selected data from previous investigations into uniform datasets that will be used to help characterize the extent of contamination at the mine. The data may be used to determine the magnitude of biological impacts from the contamination and in the development of remediation activities. This report contains analytical data for samples collected from 98 stream locations, 6 pond locations, 21 surface-water seeps, and 29 mine-waste locations. The 98 stream locations are within 3 streams and their tributaries. Ely Brook flows directly through the Ely Copper Mine then into Schoolhouse Brook (fig. 2), which joins the Ompompanoosuc River (fig. 1). The six pond locations are along Ely Brook Tributary 2 (fig. 2). The surface-water seeps and mine-waste locations are near the headwaters of Ely Brook (fig. 2 and fig. 3). The datasets 'Site_Directory' and 'Coordinates' contain specific information about each of the sample locations including stream name, number of meters from the mouth of stream, geographic coordinates, types of samples collected (matrix of sample), and the figure on which the sample location is depicted. Data have been collected at the Ely Copper Mine Superfund site by the USEPA, the Vermont Department of Environmental Conservation (VTDEC), and the USGS. Data also have been collected on behalf of USEPA by the following agencies: Arthur D. Little Incorporated (ADL), U.S. Army Cold Region Research and Engineering Laboratory (CRREL), URS Corporation (URS), USEPA, and USGS. These data provide information about the aquatic communities and their habitats, including chemical analyses of surface water, pore water, sediments, and fish tissue; assessments of macroinvertebrate and fish assemblages; physical characteristics of sediments; and chemical analyses of soil and soil leachate collected in and around the piles of mine waste.

Intelligent Scheduling for Underground Mobile Mining Equipment

PubMed Central

Song, Zhen; Schunnesson, Håkan; Rinne, Mikael; Sturgul, John

2015-01-01

Many studies have been carried out and many commercial software applications have been developed to improve the performances of surface mining operations, especially for the loader-trucks cycle of surface mining. However, there have been quite few studies aiming to improve the mining process of underground mines. In underground mines, mobile mining equipment is mostly scheduled instinctively, without theoretical support for these decisions. Furthermore, in case of unexpected events, it is hard for miners to rapidly find solutions to reschedule and to adapt the changes. This investigation first introduces the motivation, the technical background, and then the objective of the study. A decision support instrument (i.e. schedule optimizer for mobile mining equipment) is proposed and described to address this issue. The method and related algorithms which are used in this instrument are presented and discussed. The proposed method was tested by using a real case of Kittilä mine located in Finland. The result suggests that the proposed method can considerably improve the working efficiency and reduce the working time of the underground mine. PMID:26098934

30 CFR 77.703-1 - Approved methods of grounding.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 1 2011-07-01 2011-07-01 false Approved methods of grounding. 77.703-1 Section 77.703-1 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE... COAL MINES Grounding § 77.703-1 Approved methods of grounding. The methods of grounding stated in § 77...

30 CFR 77.703-1 - Approved methods of grounding.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 30 Mineral Resources 1 2013-07-01 2013-07-01 false Approved methods of grounding. 77.703-1 Section 77.703-1 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE... COAL MINES Grounding § 77.703-1 Approved methods of grounding. The methods of grounding stated in § 77...

30 CFR 77.703-1 - Approved methods of grounding.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Approved methods of grounding. 77.703-1 Section 77.703-1 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE... COAL MINES Grounding § 77.703-1 Approved methods of grounding. The methods of grounding stated in § 77...

Use of the method for addressing the challenges of resources procurement management at a mining enterprise

NASA Astrophysics Data System (ADS)

Petrova, T. V.; Strekalov, S. V.; Novichikhin, A. V.

2017-09-01

The article is devoted to the analysis of possible application of the total cost of ownership method for the purchase of resources at a mining enterprise. The description of the total cost of ownership method and experience of using this method in other spheres is provided. The article identifies the essential components needed to calculate the total cost of ownership of a resource. Particular attention is paid to the ratio of the price of the purchased resource and the total cost of ownership. To justify the relevance of application of this method at a mining enterprise for resources purchase, the technical and economic conditions of mining enterprises have been analyzed, which are quite specific and force to introduce certain adjustments to the application of the considered method and opens up new possibilities for its use. Specific spheres for application of this method at a mining enterprise are determined. The main result of the study is the proposed practical recommendations for the introduction and extension of the practice of using the method when a mining enterprise purchases resources.

Hazards and occupational risk in hard coal mines - a critical analysis of legal requirements

NASA Astrophysics Data System (ADS)

Krause, Marcin

2017-11-01

This publication concerns the problems of occupational safety and health in hard coal mines, the basic elements of which are the mining hazards and the occupational risk. The work includes a comparative analysis of selected provisions of general and industry-specific law regarding the analysis of hazards and occupational risk assessment. Based on a critical analysis of legal requirements, basic assumptions regarding the practical guidelines for occupational risk assessment in underground coal mines have been proposed.

Data mining mining data: MSHA enforcement efforts, underground coal mine safety, and new health policy implications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kniesner, T.J.; Leeth, J.D.

2004-09-15

Using recently assembled data from the Mine Safety and Health Administration (MSHA) we shed new light on the regulatory approach to workplace safety. Because all underground coal mines are inspected quarterly, MSHA regulations will not be ineffective because of infrequent inspections. From over 200 different specifications of dynamic mine safety regressions we select the specification producing the largest MSHA impact. Even using results most favorable to the agency, MSHA is not currently cost effective. Almost 700,000 life years could be gained for typical miners if a quarter of MSHA's enforcement budget were reallocated to other programs (more heart disease screeningmore » or defibrillators at worksites).« less

Condition-Based Conveyor Belt Replacement Strategy in Lignite Mines with Random Belt Deterioration

NASA Astrophysics Data System (ADS)

Blazej, Ryszard; Jurdziak, Leszek

2017-12-01

In Polish lignite surface mines, condition-based belt replacement strategies are applied in order to assure profitable refurbishment of worn out belts performed by external firms specializing in belt maintenance. In two of three lignite mines, staff asses belt condition subjectively during visual inspections. Only one mine applies specialized diagnostic device (HRDS) allowing objective magnetic evaluation of belt core condition in order to choose the most profitable moment for the dismantling of worn out belt segments from conveyors and sending them to the maintenance firm which provides their refurbishment. This article describes the advantages of a new diagnostic device called DiagBelt. It was developed at the Faculty of Geoengineering, Mining and Geology, Wroclaw University of Science and Technology. Economic gains from its application are calculated for the lignite mine and for the belt maintenance firm, taking into account random life (durability) of new and reconditioned belts (after the 1st and the 2nd refurbishment). Recursive calculations for following years allow the estimation of the length and costs of replaced, reconditioned and purchased belts on an annual basis, while the use of the Monte Carlo method allows the estimation of their variability caused by random deterioration of belts. Savings are obtained due to better selection of moments (times) for the replacement of belt segments and die to the possibility to qualify worn out belts for refurbishment without the need to remove their covers. In effect, increased belt durability and lowered share of waste belts (which were not qualified for reconditioning) create savings which can quickly cover expenditures on new diagnostic tools and regular belt inspections in the mine.

Social cost of land mines in four countries: Afghanistan, Bosnia, Cambodia, and Mozambique.

PubMed Central

Andersson, N.; da Sousa, C. P.; Paredes, S.

1995-01-01

OBJECTIVES--To document the effects of land mines on the health and social conditions of communities in four affected countries. DESIGN--A cross design of cluster survey and rapid appraisal methods including a household questionnaire and qualitative data from key informants, institutional reviews, and focus groups of survivors of land mines from the same communities. SETTING--206 communities, 37 in Afghanistan, 66 in Bosnia, 38 in Cambodia, and 65 in Mozambique. SUBJECTS--174,489 people living in 32,904 households in the selected communities. MAIN OUTCOME MEASURES--Effects of land mines on food security, residence, livestock, and land use; risk factors: extent of individual land mine injuries; physical, psychological, social, and economic costs of injuries during medical care and rehabilitation. RESULTS--Between 25% and 87% of households had daily activities affected by land mines. Based on expected production without the mines, agricultural production could increase by 88-200% in different regions of Afghanistan, 11% in Bosnia, 135% in Cambodia, and 3.6% in Mozambique. A total of 54,554 animals was lost because of land mines, with a minimum cash value of $6.5m, or nearly $200 per household. Overall, 6% of households (1964) reported a land mine victim; a third of victims died in the blast. One in 10 of the victims was a child. The most frequent activities associated with land mine incidents were agricultural or pastoral, except in Bosnia where more than half resulted from military activities, usually during patrols. Incidences have more than doubled between 1980-3 and 1990-3, excluding the incidents in Bosnia. Some 22% of victims (455/2100) were from households reporting attempts to remove land mines; in these households there was a greatly increased risk of injury (odds ratio 4.2 and risk difference 19% across the four countries). Lethality of the mines varied; in Bosnia each blast killed an average of 0.54 people and injured 1.4, whereas in Mozambique each blast killed 1.45 people and wounded 1.27. Households with a land mine victim were 40% more likely to experience difficulty in providing food for the family. Family relationships were affected for around one in every four victims and relationships with colleagues in 40%. CONCLUSIONS--Land mines seriously undermine the economy and food security in affected countries; they kill and maim civilians at an increasing rate. The expense of medical care and rehabilitation add economic disability to the physical burden. Awareness of land mines can be targeted at high risk attitudes, such as those associated with tampering with mines. PMID:7549685

Social cost of land mines in four countries: Afghanistan, Bosnia, Cambodia, and Mozambique.

PubMed

Andersson, N; da Sousa, C P; Paredes, S

1995-09-16

To document the effects of land mines on the health and social conditions of communities in four affected countries. A cross design of cluster survey and rapid appraisal methods including a household questionnaire and qualitative data from key informants, institutional reviews, and focus groups of survivors of land mines from the same communities. 206 communities, 37 in Afghanistan, 66 in Bosnia, 38 in Cambodia, and 65 in Mozambique. 174,489 people living in 32,904 households in the selected communities. Effects of land mines on food security, residence, livestock, and land use; risk factors: extent of individual land mine injuries; physical, psychological, social, and economic costs of injuries during medical care and rehabilitation. Between 25% and 87% of households had daily activities affected by land mines. Based on expected production without the mines, agricultural production could increase by 88-200% in different regions of Afghanistan, 11% in Bosnia, 135% in Cambodia, and 3.6% in Mozambique. A total of 54,554 animals was lost because of land mines, with a minimum cash value of $6.5m, or nearly $200 per household. Overall, 6% of households (1964) reported a land mine victim; a third of victims died in the blast. One in 10 of the victims was a child. The most frequent activities associated with land mine incidents were agricultural or pastoral, except in Bosnia where more than half resulted from military activities, usually during patrols. Incidences have more than doubled between 1980-3 and 1990-3, excluding the incidents in Bosnia. Some 22% of victims (455/2100) were from households reporting attempts to remove land mines; in these households there was a greatly increased risk of injury (odds ratio 4.2 and risk difference 19% across the four countries). Lethality of the mines varied; in Bosnia each blast killed an average of 0.54 people and injured 1.4, whereas in Mozambique each blast killed 1.45 people and wounded 1.27. Households with a land mine victim were 40% more likely to experience difficulty in providing food for the family. Family relationships were affected for around one in every four victims and relationships with colleagues in 40%. Land mines seriously undermine the economy and food security in affected countries; they kill and maim civilians at an increasing rate. The expense of medical care and rehabilitation add economic disability to the physical burden. Awareness of land mines can be targeted at high risk attitudes, such as those associated with tampering with mines.

Hydrologic data collected in and around a surface coal mine, Clay and Vigo counties, Indiana, 1977-80

USGS Publications Warehouse

Bobo, Linda L.; Eikenberry, Stephen E.

1982-01-01

Few data are available for evaluating water-quality and other hydrologic properties in and around surface coal mines, particularly in areas where material having a high potential for acid-production is selectively buried. This report contains hydrologic data collected in an active coal mining area in Clay and Vigo Counties, Indiana, from September 1977 through February 1980. Methods of sampling and analysis used in collecting the data also are summarized. The data include field and laboratory measurements of water at 41 wells and 24 stream sites. Variables measured in the field include water temperature, specific conductance, pH, Eh, dissolved oxygen, ground-water levels, and streamflow; and in the laboratory, concentrations of major ions, alkalinity, hardness, trace elementsl, organic carbon, phosphorus, and dissolved solids. Other variables measured in the laboratory include ferrous iron concentration of water samples from selected wells, percent sulfur by weight and the potential acidity of core samples of reclaimed cast overburden, concentrations of elements absorbed on streambed materials, concentrations and particle size of suspended sediment in water, and populations and Shannon diversity indices of phytoplankton in water. Dissolved-solids concentrations and pH of ground water ranged from 173 to 5,130 milligrams per liter and from 6.1 to 8.9, respectively, and of surface water, from 120 to 4,100 milligrams per liter and from 6.1 to 8.8 respectively. 

Statistical learning and selective inference.

PubMed

Taylor, Jonathan; Tibshirani, Robert J

2015-06-23

We describe the problem of "selective inference." This addresses the following challenge: Having mined a set of data to find potential associations, how do we properly assess the strength of these associations? The fact that we have "cherry-picked"--searched for the strongest associations--means that we must set a higher bar for declaring significant the associations that we see. This challenge becomes more important in the era of big data and complex statistical modeling. The cherry tree (dataset) can be very large and the tools for cherry picking (statistical learning methods) are now very sophisticated. We describe some recent new developments in selective inference and illustrate their use in forward stepwise regression, the lasso, and principal components analysis.

The Detection Method of Fire Abnormal Based on Directional Drilling in Complex Conditions of Mine

NASA Astrophysics Data System (ADS)

Huijun, Duan; Shijun, Hao; Jie, Feng

2018-06-01

In the light of more and more urgent hidden fire abnormal detection problem in complex conditions of mine, a method which is used directional drilling technology is put forward. The method can avoid the obstacles in mine, and complete the fire abnormal detection. This paper based on analyzing the trajectory control of directional drilling, measurement while drilling and the characteristic of open branch process, the project of the directional drilling is formulated combination with a complex condition mine, and the detection of fire abnormal is implemented. This method can provide technical support for fire prevention, which also can provide a new way for fire anomaly detection in the similar mine.

Hydrogeochemical assessment of mine-impacted water and sediment of iron ore mining

NASA Astrophysics Data System (ADS)

Nur Atirah Affandi, Fatin; Kusin, Faradiella Mohd; Aqilah Sulong, Nur; Madzin, Zafira

2018-04-01

This study was carried out to evaluate the hydrogeochemical behaviour of mine-impacted water and sediment of a former iron ore mining area. Sampling of mine water and sediment were carried out at selected locations within the mine including the former mining ponds, mine tailings and the nearby stream. The water samples were analysed for their hydrochemical facies, major and trace elements including heavy metals. The water in the mining ponds and the mine tailings was characterised as highly acidic (pH 2.54-3.07), but has near-neutral pH in the nearby stream. Results indicated that Fe and Mn in water have exceeded the recommended guidelines values and was also supported by the results of geochemical modelling. The results also indicated that sediments in the mining area were contaminated with Cd and As as shown by the potential ecological risk index values. The total risk index of heavy metals in the sediment were ranked in the order of Cd>As>Pb>Cu>Zn>Cr. Overall, the extent of potential ecological risks of the mining area were categorised as having low to moderate ecological risk.

Automating an integrated spatial data-mining model for landfill site selection

NASA Astrophysics Data System (ADS)

Abujayyab, Sohaib K. M.; Ahamad, Mohd Sanusi S.; Yahya, Ahmad Shukri; Ahmad, Siti Zubaidah; Aziz, Hamidi Abdul

2017-10-01

An integrated programming environment represents a robust approach to building a valid model for landfill site selection. One of the main challenges in the integrated model is the complicated processing and modelling due to the programming stages and several limitations. An automation process helps avoid the limitations and improve the interoperability between integrated programming environments. This work targets the automation of a spatial data-mining model for landfill site selection by integrating between spatial programming environment (Python-ArcGIS) and non-spatial environment (MATLAB). The model was constructed using neural networks and is divided into nine stages distributed between Matlab and Python-ArcGIS. A case study was taken from the north part of Peninsular Malaysia. 22 criteria were selected to utilise as input data and to build the training and testing datasets. The outcomes show a high-performance accuracy percentage of 98.2% in the testing dataset using 10-fold cross validation. The automated spatial data mining model provides a solid platform for decision makers to performing landfill site selection and planning operations on a regional scale.

An empirical method for estimating instream pre-mining pH and dissolved Cu concentration in catchments with acidic drainage and ferricrete

USGS Publications Warehouse

Nimick, D.A.; Gurrieri, J.T.; Furniss, G.

2009-01-01

Methods for assessing natural background water quality of streams affected by historical mining are vigorously debated. An empirical method is proposed in which stream-specific estimation equations are generated from relationships between either pH or dissolved Cu concentration in stream water and the Fe/Cu concentration ratio in Fe-precipitates presently forming in the stream. The equations and Fe/Cu ratios for pre-mining deposits of alluvial ferricrete then were used to reconstruct estimated pre-mining longitudinal profiles for pH and dissolved Cu in three acidic streams in Montana, USA. Primary assumptions underlying the proposed method are that alluvial ferricretes and modern Fe-precipitates share a common origin, that the Cu content of Fe-precipitates remains constant during and after conversion to ferricrete, and that geochemical factors other than pH and dissolved Cu concentration play a lesser role in determining Fe/Cu ratios in Fe-precipitates. The method was evaluated by applying it in a fourth, naturally acidic stream unaffected by mining, where estimated pre-mining pH and Cu concentrations were similar to present-day values, and by demonstrating that inflows, particularly from unmined areas, had consistent effects on both the pre-mining and measured profiles of pH and Cu concentration. Using this method, it was estimated that mining has affected about 480 m of Daisy Creek, 1.8 km of Fisher Creek, and at least 1 km of Swift Gulch. Mean values of pH decreased by about 0.6 pH units to about 3.2 in Daisy Creek and by 1-1.5 pH units to about 3.5 in Fisher Creek. In Swift Gulch, mining appears to have decreased pH from about 5.5 to as low as 3.6. Dissolved Cu concentrations increased due to mining almost 40% in Daisy Creek to a mean of 11.7 mg/L and as much as 230% in Fisher Creek to 0.690 mg/L. Uncertainty in the fate of Cu during the conversion of Fe-precipitates to ferricrete translates to potential errors in pre-mining estimates of as much as 0.25 units for pH and 22% for dissolved Cu concentration. The method warrants further testing in other mined and unmined watersheds. Comparison of pre-mining water-quality estimates derived from the ferricrete and other methods in single watersheds would be particularly valuable. The method has potential for use in monitoring remedial efforts at mine sites with ferricrete deposits. A reasonable remediation objective might be realized when the downstream pattern of Fe/Cu ratios in modern streambed Fe-precipitates corresponds to the pattern in pre-mining alluvial ferricrete deposits along a stream valley.

30 CFR 75.703-1 - Approved method of grounding.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Approved method of grounding. 75.703-1 Section 75.703-1 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE SAFETY AND HEALTH MANDATORY SAFETY STANDARDS-UNDERGROUND COAL MINES Grounding § 75.703-1 Approved method...

30 CFR 75.703-1 - Approved method of grounding.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 1 2011-07-01 2011-07-01 false Approved method of grounding. 75.703-1 Section 75.703-1 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE SAFETY AND HEALTH MANDATORY SAFETY STANDARDS-UNDERGROUND COAL MINES Grounding § 75.703-1 Approved method...

30 CFR 75.703-1 - Approved method of grounding.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 30 Mineral Resources 1 2013-07-01 2013-07-01 false Approved method of grounding. 75.703-1 Section 75.703-1 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE SAFETY AND HEALTH MANDATORY SAFETY STANDARDS-UNDERGROUND COAL MINES Grounding § 75.703-1 Approved method...

Illustrated surface mining methods

DOE Office of Scientific and Technical Information (OSTI.GOV)

Not Available

1979-01-01

This manual provides a visual synopsis of surface coal mining methods in the United States. The manual presents various surface mining methods and techniques through artist renderings and appropriate descriptions. The productive coal fields of the United States were divided into four regions according to geology and physiography. A glossay of terminology is included. (DP)

Prediction model for peninsular Indian summer monsoon rainfall using data mining and statistical approaches

NASA Astrophysics Data System (ADS)

Vathsala, H.; Koolagudi, Shashidhar G.

2017-01-01

In this paper we discuss a data mining application for predicting peninsular Indian summer monsoon rainfall, and propose an algorithm that combine data mining and statistical techniques. We select likely predictors based on association rules that have the highest confidence levels. We then cluster the selected predictors to reduce their dimensions and use cluster membership values for classification. We derive the predictors from local conditions in southern India, including mean sea level pressure, wind speed, and maximum and minimum temperatures. The global condition variables include southern oscillation and Indian Ocean dipole conditions. The algorithm predicts rainfall in five categories: Flood, Excess, Normal, Deficit and Drought. We use closed itemset mining, cluster membership calculations and a multilayer perceptron function in the algorithm to predict monsoon rainfall in peninsular India. Using Indian Institute of Tropical Meteorology data, we found the prediction accuracy of our proposed approach to be exceptionally good.

Data mining in soft computing framework: a survey.

PubMed

Mitra, S; Pal, S K; Mitra, P

2002-01-01

The present article provides a survey of the available literature on data mining using soft computing. A categorization has been provided based on the different soft computing tools and their hybridizations used, the data mining function implemented, and the preference criterion selected by the model. The utility of the different soft computing methodologies is highlighted. Generally fuzzy sets are suitable for handling the issues related to understandability of patterns, incomplete/noisy data, mixed media information and human interaction, and can provide approximate solutions faster. Neural networks are nonparametric, robust, and exhibit good learning and generalization capabilities in data-rich environments. Genetic algorithms provide efficient search algorithms to select a model, from mixed media data, based on some preference criterion/objective function. Rough sets are suitable for handling different types of uncertainty in data. Some challenges to data mining and the application of soft computing methodologies are indicated. An extensive bibliography is also included.

Selected Black-Coal Mine Waste Dumps in the Ostrava-Karviná Region: An Analysis of Their Potential Use

NASA Astrophysics Data System (ADS)

Niemiec, Dominik; Duraj, Miloš; Cheng, Xianfeng; Marschalko, Marian; Kubáč, Jan

2017-12-01

The paper aims to analyse the options for the use of selected black-coal mine waste dump bodies in the Ostrava-Karviná Region. In the Czech Republic there are approximately 70 mine waste dumps, out of which 50 are located in the Ostrava-Karviná Coal District. The issue is highly topical, particularly in the region, because the dump bodies significantly affect the landscape character of the Ostrava-Karviná Region and pose ecological risks. In such cases, their redevelopment and land reclamation are not easy either from the environmental or economic points of view. It is clear that the redevelopment of such geological environment is difficult, and it is vital to make the right decisions as for what purposes the mine waste dumps should be used. Next, it is important to take into account all the economic and environmental aspects of the locality in question.

Study on environment detection and appraisement of mining area with RS

NASA Astrophysics Data System (ADS)

Yang, Fengjie; Hou, Peng; Zhou, Guangzhu; Li, Qingting; Wang, Jie; Cheng, Jianguang

2006-12-01

In this paper, the big coal mining area Yanzhou is selected as the typical research area. According to the special dynamic change characteristic of the environment in the mining area, the environmental dynamic changes are timely monitored with the remote sensing detection technology. Environmental special factors, such as vegetation, water, air, land-over, are extracted by the professional remote sensing image processing software, then the spatial information is managed and analyzed in the geographical information system (GIS) software. As the result, the dynamic monitor and query for change information is achieved, and the special environmental factor dynamic change maps are protracted. On the base of the data coming from the remote sensing image, GIS and the traditional environment monitoring, the environmental quality is appraised with the method of indistinct matrix analysis, the multi-index and the analytical hierarchy process. At last, those provide the credible science foundation for the local environment appraised and the sustained development. In addition, this paper apply the hyper spectrum graphs by the FieldSpec Pro spectroradiometer, together with the analytical data from environmental chemical, to study the growth of vegetation which were seed in the land-over consisting of gangue, which is a new method to study the impact to vegetation that are growing in the soil.

A data mining framework for time series estimation.

PubMed

Hu, Xiao; Xu, Peng; Wu, Shaozhi; Asgari, Shadnaz; Bergsneider, Marvin

2010-04-01

Time series estimation techniques are usually employed in biomedical research to derive variables less accessible from a set of related and more accessible variables. These techniques are traditionally built from systems modeling approaches including simulation, blind decovolution, and state estimation. In this work, we define target time series (TTS) and its related time series (RTS) as the output and input of a time series estimation process, respectively. We then propose a novel data mining framework for time series estimation when TTS and RTS represent different sets of observed variables from the same dynamic system. This is made possible by mining a database of instances of TTS, its simultaneously recorded RTS, and the input/output dynamic models between them. The key mining strategy is to formulate a mapping function for each TTS-RTS pair in the database that translates a feature vector extracted from RTS to the dissimilarity between true TTS and its estimate from the dynamic model associated with the same TTS-RTS pair. At run time, a feature vector is extracted from an inquiry RTS and supplied to the mapping function associated with each TTS-RTS pair to calculate a dissimilarity measure. An optimal TTS-RTS pair is then selected by analyzing these dissimilarity measures. The associated input/output model of the selected TTS-RTS pair is then used to simulate the TTS given the inquiry RTS as an input. An exemplary implementation was built to address a biomedical problem of noninvasive intracranial pressure assessment. The performance of the proposed method was superior to that of a simple training-free approach of finding the optimal TTS-RTS pair by a conventional similarity-based search on RTS features. 2009 Elsevier Inc. All rights reserved.

Mining a clinical data warehouse to discover disease-finding associations using co-occurrence statistics

PubMed Central

Cao, Hui; Markatou, Marianthi; Melton, Genevieve B.; Chiang, Michael F.; Hripcsak, George

2005-01-01

This paper applies co-occurrence statistics to discover disease-finding associations in a clinical data warehouse. We used two methods, χ2 statistics and the proportion confidence interval (PCI) method, to measure the dependence of pairs of diseases and findings, and then used heuristic cutoff values for association selection. An intrinsic evaluation showed that 94 percent of disease-finding associations obtained by χ2 statistics and 76.8 percent obtained by the PCI method were true associations. The selected associations were used to construct knowledge bases of disease-finding relations (KB-χ2, KB-PCI). An extrinsic evaluation showed that both KB-χ2 and KB-PCI could assist in eliminating clinically non-informative and redundant findings from problem lists generated by our automated problem list summarization system. PMID:16779011

Development of Soil Characteristics and Plant Communities On Reclaimed and Unreclaimed Spoil Heaps After Coal Mining

NASA Astrophysics Data System (ADS)

Cudlín, Ondřej; Řehák, Zdeněk; Cudlín, Pavel

2016-10-01

The aim of this study was to compare soil characteristics, plant communities and the rate of selected ecosystem function performance on reclaimed and unreclaimed plots (left for spontaneous succession) of different age on spoil heaps. Twelve spoil heaps (three circle plots of radius 12.5 m) near the town Kladno in north-west direction from Prague, created after deep coal mining, were compared. Five mixed soil samples from organo-mineral horizons in each plot were analysed for total content of carbon, nitrogen and phosphorus. In addition, active soil pH (pHH2O) was determined. Plant diversity was determined by vegetation releves. The biodiversity value of the habitat according to the Habitat Valuation Method was assessed and the rate of evapotranspiration function by the Method of Valuation Functions and Services of Ecosystems in the Czech Republic were determined. The higher organo-mineral layers and higher amount of total nitrogen content were found on the older reclaimed and unreclaimed plots than in younger plots. The number of plant species and the total contents of carbon and nitrogen were significantly higher at the unreclaimed plots compared to reclaimed plots. The biodiversity values and evapotranspiration function rate were also higher on unreclaimed plots. From this perspective, it is possible to recommend using of spontaneous succession, together with routine reclamation methods to restore habitats after coal mining. Despite the relatively high age of vegetation in some of selected plots (90 years), both the reclaimed and unreclaimed plots have not reached the stage of potential vegetation near to natural climax. Slow development of vegetation was probably due to unsuitable substrate of spoil heaps and a lack of plant and tree species of natural forest habitats in this area. However, it is probable that vegetation communities on observed spoil heaps in both type of management (reclaimed and unreclaimed) will achieve the stage of natural climax and they will provide ecosystem functions more effectively in the future.

Data Mining and Homeland Security: An Overview

DTIC Science & Technology

2006-01-27

which government agencies should use and mix commercial data with government data, whether data sources are being used for purposes other than those...example, a hardware store may compare their customers’ tool purchases with home ownership, type of CRS-2 3 John Makulowich, “ Government Data Mining...cleaning, data integration, data selection, data transformation , (data mining), pattern evaluation, and knowledge presentation.4 A number of advances in

Appraisement of environment remote sensing method in mining area

NASA Astrophysics Data System (ADS)

Yang, Fengjie; Zhen, Han; Jiang, Tao; Lei, Liqing; Gong, Cailan

1998-08-01

Coal mining is attached great importance by society as a key profession of environmental pollution. The monitor and protection of coal-mine environment is a developing profession in China. The sulfur dioxide, carbon dioxide, carbon monoxide and other waste gases, which are put out by the spontaneous combustion or weathering of gangue are an important pollution resource of atmosphere. The stack of gangue held down many farmlands. Smoke, coal dust and powder coal ash pollute the environment of mining area and surroundings though the affection of monsoon. The pH value of water which coal mine drained off is low, and the drinking, farming and animal husbandry water where it flowed are affected. The surface subsidence which mining caused is a typical destruction of ground environment. The people pay attention to remote sensing as a method of rapidly, cheaply regional environment investigation. The paper tires making an appraisement of mining area environment monitor by many kind methods of remote sensing from the characteristic of mining area environment.

Anchor-Free Localization Method for Mobile Targets in Coal Mine Wireless Sensor Networks

PubMed Central

Pei, Zhongmin; Deng, Zhidong; Xu, Shuo; Xu, Xiao

2009-01-01

Severe natural conditions and complex terrain make it difficult to apply precise localization in underground mines. In this paper, an anchor-free localization method for mobile targets is proposed based on non-metric multi-dimensional scaling (Multi-dimensional Scaling: MDS) and rank sequence. Firstly, a coal mine wireless sensor network is constructed in underground mines based on the ZigBee technology. Then a non-metric MDS algorithm is imported to estimate the reference nodes’ location. Finally, an improved sequence-based localization algorithm is presented to complete precise localization for mobile targets. The proposed method is tested through simulations with 100 nodes, outdoor experiments with 15 ZigBee physical nodes, and the experiments in the mine gas explosion laboratory with 12 ZigBee nodes. Experimental results show that our method has better localization accuracy and is more robust in underground mines. PMID:22574048

Anchor-free localization method for mobile targets in coal mine wireless sensor networks.

PubMed

Pei, Zhongmin; Deng, Zhidong; Xu, Shuo; Xu, Xiao

2009-01-01

Severe natural conditions and complex terrain make it difficult to apply precise localization in underground mines. In this paper, an anchor-free localization method for mobile targets is proposed based on non-metric multi-dimensional scaling (Multi-dimensional Scaling: MDS) and rank sequence. Firstly, a coal mine wireless sensor network is constructed in underground mines based on the ZigBee technology. Then a non-metric MDS algorithm is imported to estimate the reference nodes' location. Finally, an improved sequence-based localization algorithm is presented to complete precise localization for mobile targets. The proposed method is tested through simulations with 100 nodes, outdoor experiments with 15 ZigBee physical nodes, and the experiments in the mine gas explosion laboratory with 12 ZigBee nodes. Experimental results show that our method has better localization accuracy and is more robust in underground mines.

Diverse Power Iteration Embeddings and Its Applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huang H.; Yoo S.; Yu, D.

2014-12-14

Abstract—Spectral Embedding is one of the most effective dimension reduction algorithms in data mining. However, its computation complexity has to be mitigated in order to apply it for real-world large scale data analysis. Many researches have been focusing on developing approximate spectral embeddings which are more efficient, but meanwhile far less effective. This paper proposes Diverse Power Iteration Embeddings (DPIE), which not only retains the similar efficiency of power iteration methods but also produces a series of diverse and more effective embedding vectors. We test this novel method by applying it to various data mining applications (e.g. clustering, anomaly detectionmore » and feature selection) and evaluating their performance improvements. The experimental results show our proposed DPIE is more effective than popular spectral approximation methods, and obtains the similar quality of classic spectral embedding derived from eigen-decompositions. Moreover it is extremely fast on big data applications. For example in terms of clustering result, DPIE achieves as good as 95% of classic spectral clustering on the complex datasets but 4000+ times faster in limited memory environment.« less

A comparative life cycle assessment of material handling systems for sustainable mining.

PubMed

Erkayaoğlu, M; Demirel, N

2016-06-01

In this comprehensive LCA comparison study, main objectives are to investigate life cycle environmental impacts of off-highway mining trucks and belt conveyors in surface mining. The research methodology essentially entails determination of the functional unit as 20,000 tons/day coal production transported for 5 km distance. After the system boundary was selected as the entire life cycle of material handling systems including pre-manufacturing of steel parts and plastic components, manufacturing, transportation, and utilization data was compiled from equipment manufacturers and the Eco-invent database. Life cycle impact categories for both material-handling systems were identified and the developed model was implemented using SIMAPRO 7.3. Climate change and acidification were selected as major impact categories as they were considered to be major concerns in mining industry. Although manufacturing stage had a significant impact on all of the environmental parameters, utilization stage was the hotspot for the selected impact categories. The results of this study revealed that belt conveyors have a greater environmental burden in climate change impact category when compared to the trucks. On the other hand, trucks have a greater environmental burden in acidification impact category when compared to the belt conveyors. This study implied that technological improvement in fuel combustion and electricity generation is crucial for the improvement of environmental profiles of off-highway trucks and belt conveyors in the mining industry. The main novelty of this study is that it is the first initiative in applying LCA in the Turkish mining industry. Copyright © 2016 Elsevier Ltd. All rights reserved.

Environmental geochemical studies of selected mineral deposits in Wrangell-St. Elias National Park and Preserve, Alaska

USGS Publications Warehouse

Eppinger, Robert G.; Briggs, Paul H.; Rosenkrans, Danny; Ballestrazze, Vanessa

2000-01-01

Environmental geochemical investigations at Wrangell-St. Elias National Park and Preserve, Alaska, between 1994 and 1997 included studies of the Kennecott stratabound copper mines and mill area; historic mines and mill in the Bremner District, gold placer mines at Gold Hill; the undisturbed porphyry, Cu-Mo deposits at Orange Hill and Bond Creek, and the historic mines and mill at Nabesna, The study was in cooperation with the National Park Service and focused on sample media including surface water, bedload sediment, rock, mine waste, and mill tailings samples. Results demonstrate that bedrock geology and mineral deposit type must be considered when environmental geochemical effects of historic or active mine areas are evaluated.

Occupational Malfunctioning and Fatigue Related Work Stress Disorders (FRWSDs): An Emerging Issue in Indian Underground Mine (UGM) Operations

NASA Astrophysics Data System (ADS)

Dey, Shibaji Ch.; Dey, Netai Chandra; Sharma, Gourab Dhara

2018-04-01

Indian underground mining (UGM) transport system largely deals with different fore and back bearing work processes associated with different occupational disorders and fatigue related work stress disorders (FRWSDs). Therefore, this research study is specifically aimed to determine the fatigue related problems in general and determination of Recovery Heart Rate (Rec HR) pattern and exact cause of FRWSDs in particular. A group of twenty (N = 20) UGM operators are selected for the study. Heart rate profiles and work intensities of selected workforces have been recorded continuously during their regular mine operation and the same workforces are tested on a treadmill on surface with almost same work intensity (%Maximal Heart Rate) which was earlier observed in the mine. Recovery Heart Rate (Rec HR) in both the experiment zones is recorded. It is observed that with almost same work intensity, the recovery patterns of submaximal prolonged work in mine are different as compared to treadmill. This research study indicates that non-biomechanical muscle activity along with environmental stressors may have an influence on recovery pattern and FRWSDs.

Mining nutrigenetics patterns related to obesity: use of parallel multifactor dimensionality reduction.

PubMed

Karayianni, Katerina N; Grimaldi, Keith A; Nikita, Konstantina S; Valavanis, Ioannis K

2015-01-01

This paper aims to enlighten the complex etiology beneath obesity by analysing data from a large nutrigenetics study, in which nutritional and genetic factors associated with obesity were recorded for around two thousand individuals. In our previous work, these data have been analysed using artificial neural network methods, which identified optimised subsets of factors to predict one's obesity status. These methods did not reveal though how the selected factors interact with each other in the obtained predictive models. For that reason, parallel Multifactor Dimensionality Reduction (pMDR) was used here to further analyse the pre-selected subsets of nutrigenetic factors. Within pMDR, predictive models using up to eight factors were constructed, further reducing the input dimensionality, while rules describing the interactive effects of the selected factors were derived. In this way, it was possible to identify specific genetic variations and their interactive effects with particular nutritional factors, which are now under further study.

The stabilization of the rock mass of the wieliczka salt mine through the backfilling of the witos chamber with the use of injection methods / Stabilizacji górotworu kopalni soli "wieliczka" poprzez likwidację komór "witos" z zastosowaniem metod iniekcji

NASA Astrophysics Data System (ADS)

D'Obyrn, Kajetan

2012-10-01

The Wieliczka Salt Mine is the most famous and the most visited mining industry monument in the world and it requires modern methods to ensure rock mass stability and tourists' security. Both for conservation and tourism organization reasons, the group of Warszawa-Wisla-Budryk-Lebzeltern-Upper Witos Chambers (Photo. 1, 2. 3) located the Kazanów mid-level at a depth of 117 m underground is extremely important. Discontinuous deformation occurring in this Chamber complex was eliminated by comprehensive securing work with anchor housing, but their final securing and stability is conditioned by further backfilling and sealing the Witos Chambers situated directly beneath. In the 1940s and 1950s, the Witos Chamber was backfilled with slag from the mine boilerhouse. However, slags with 80% compressibility are not backfilling material which would ensure the stability of the rock mass. The chambers were exploited in the early nineteenth century in the Spizit salts of the central part of the layered deposit. The condition of the Upper Witos, Wisla, Warszawa, Budryk, and Lebzeltern Chambers is generally good. The western part if the Lebzeltern Chamber (Fig. 1), which was threatened with collapse, was backfilled with sand. In all the chambers of the Witos complex, local deformation of ceiling rock of varying intensity is observed as well as significant destruction of the side walls of pillars between chambers. No hydrogeological phenomena are observed in the chambers. It has been attempted to solve the problem of stability of the rock mass in this region of the mine by extracting the slag and backfilling with sand, erecting concrete supporting pillars, backfilling the voids with sand, anchoring the ceiling and the side walls, the use of the pillar housing. The methods have either not been applied or have been proved insufficient to properly protect the excavation situated above. In order to select the optimal securing method, a geomechanical analysis was conducted in order to determine the condition of the chambers with particular emphasis on the pillars between the chambers. The analysis demonstrated the need to backfilling the Witos Chambers in order to improve the strength parameters of the pillars and the cross-level ledge. The next step consisted of selecting the sealing mix and testing how the additional burden and improving the slag strength parameters shall affect the stability of the excavations of the Kazanów mid-level. In order to determine the optimal composition of the backfilling mixtures, formulas of sealing brine slurries have been developed. Laboratory tests were also conducted concerning the strain parameters specifications of slags extracted from the Witos Chamber. Taking into account the slurry tests, and in particular, the density, strength and strain parameters, the optimal composition of the sealing mix was selected. The analysis of the results of numerical recalculations demonstrate that even the use of highest-density mixtures, backfilling(sealing) of the Witos Chambers should not cause significant disturbance of the current tension in the surrounding rock mass. The longterm impact of sealing should lead to improvement of the strain levels on the ledges between Level III and Kazanów mid-level chambers. The positive results of applying in the Mine of injection slurries for sealing and stabilizing the rock mass and the construction of the injection node on the surface of the Kosciuszko shaft area have allowed resuming work in the Witos Chambers. The main injection over 1,000 m long pipeline was constructed from the injection node through the Kosciuszko Shaft and along Level III of the mine. The sealing of the Witos Chambers complex was divided into three areas (Fig. 2) separated by backfilling dams. Each region was connected to an injection and venting pipeline, and areas of possible injection material off-flow from backfilling locations were secured. Once that the Chambers are sealed with the use of the pipeline seven bore holes will be drilled from excavations situated above through which the sealing slurry will be administered. The operation will serve to eliminate any voids and re-seal the slag, and it will be conducted until pressures of approximately 0.5 MPa on the bore hole collar is achieved. As past experience indicates, injection slurry formula can be regularly adjusted adequately to the changing geomechanical parameters and the type of sealing work at the Wieliczka Mine. Once that the backfilling and sealing process in the Witos Chambers complex is completed, it shall be necessary to conduct monitoring activities in order to determine the processes occurring in the rock mass after the backfilling. The properties of sealing mixtures qualify those for use in the environment both of salt mines and other mineral ore mines to stabilize the rock mass in the mining-geomechanical context precluding the possibility of weakening the rock mass strength parameters and at the same time sealing the rock mass and the loose material deposited in the excavation.

Occupational Respiratory Diseases of Miners from Two Gold Mines in Ghana

PubMed Central

Ayaaba, Esther; Li, Yan; Yuan, Jiali; Ni, Chunhui

2017-01-01

Objective: This study investigated respiratory disorders among gold miners in Ghana, a sub-Saharan African country. Material and Methods: A cross-sectional exploratory design that employed quantitative methods was conducted among 1001 male workers from the Obuasi and Tarkwa mines from December 2015 to April 2016. A total of 1001 workers, consisting of 505 and 496 underground and surface miners, respectively, were involved. The cross-sectional descriptive design was used because data was collected from participants of different experiences by selected participants at a time. Results: The study found significant association between age, educational background, marital status and drinking alcohol on respiratory disorders. The prevalence of asthma, pneumonia, bronchitis and emphysema were respectively 47.55%, 14.29%, 9.69% and 5.10%. Coughing was the most cited respiratory symptom (35.4%). Conclusions: The study documents important evidence on the level of respiratory disorders among miners in Ghana. Instituting appropriate health education interventions and improving the working environment is critical to improving the overall health and preventing respiratory disorders among miners. PMID:28327542

Application of machine learning algorithms for clinical predictive modeling: a data-mining approach in SCT.

PubMed

Shouval, R; Bondi, O; Mishan, H; Shimoni, A; Unger, R; Nagler, A

2014-03-01

Data collected from hematopoietic SCT (HSCT) centers are becoming more abundant and complex owing to the formation of organized registries and incorporation of biological data. Typically, conventional statistical methods are used for the development of outcome prediction models and risk scores. However, these analyses carry inherent properties limiting their ability to cope with large data sets with multiple variables and samples. Machine learning (ML), a field stemming from artificial intelligence, is part of a wider approach for data analysis termed data mining (DM). It enables prediction in complex data scenarios, familiar to practitioners and researchers. Technological and commercial applications are all around us, gradually entering clinical research. In the following review, we would like to expose hematologists and stem cell transplanters to the concepts, clinical applications, strengths and limitations of such methods and discuss current research in HSCT. The aim of this review is to encourage utilization of the ML and DM techniques in the field of HSCT, including prediction of transplantation outcome and donor selection.

Trees for strip-mined lands

Treesearch

George Hart; William R. Byrnes

1960-01-01

Open-pit or strip mining has become an important method of mining bituminous coal in Pennsylvania. In 1958 some 19.5 million tons of soft coal - 29 percent of the total bituminous production in the State - were produced by this method.

New Forces at Work in Mining: Industry View of Critical Technologies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Peterson, D. J.; LaTourrette, Tom; Bartis, James T.

2007-04-01

RAND has just published a report entitled, "New Forces at Work in Mining: Industry Views of Critical Technologies," by D. J. Peterson, Tom LaTourrette, and James T. Bartis. The report presents the results of a series of in-depth discussions with leading mining industry representatives selected for their prominent position and their ability to think broadly about technology trends. The discussions highlighted the importance of collaborative technology research, development, and implementation strategies and the increasingly critical role of mine personnel in the utilization of new technologies.

Application and Exploration of Big Data Mining in Clinical Medicine.

PubMed

Zhang, Yue; Guo, Shu-Li; Han, Li-Na; Li, Tie-Ling

2016-03-20

To review theories and technologies of big data mining and their application in clinical medicine. Literatures published in English or Chinese regarding theories and technologies of big data mining and the concrete applications of data mining technology in clinical medicine were obtained from PubMed and Chinese Hospital Knowledge Database from 1975 to 2015. Original articles regarding big data mining theory/technology and big data mining's application in the medical field were selected. This review characterized the basic theories and technologies of big data mining including fuzzy theory, rough set theory, cloud theory, Dempster-Shafer theory, artificial neural network, genetic algorithm, inductive learning theory, Bayesian network, decision tree, pattern recognition, high-performance computing, and statistical analysis. The application of big data mining in clinical medicine was analyzed in the fields of disease risk assessment, clinical decision support, prediction of disease development, guidance of rational use of drugs, medical management, and evidence-based medicine. Big data mining has the potential to play an important role in clinical medicine.

Association between Selective Beta-adrenergic Drugs and Blood Pressure Elevation: Data Mining of the Japanese Adverse Drug Event Report (JADER) Database.

PubMed

Ohyama, Katsuhiro; Inoue, Michiko

2016-01-01

Selective beta-adrenergic drugs are used clinically to treat various diseases. Because of imperfect receptor selectivity, beta-adrenergic drugs cause some adverse drug events by stimulating other adrenergic receptors. To examine the association between selective beta-adrenergic drugs and blood pressure elevation, we reviewed the Japanese Adverse Drug Event Reports (JADERs) submitted to the Japan Pharmaceuticals and Medical Devices Agency. We used the Medical Dictionary for Regulatory Activities (MedDRA) Preferred Terms extracted from Standardized MedDRA queries for hypertension to identify events related to blood pressure elevation. Spontaneous adverse event reports from April 2004 through May 2015 in JADERs, a data mining algorithm, and the reporting odds ratio (ROR) were used for quantitative signal detection, and assessed by the case/non-case method. Safety signals are considered significant if the ROR estimates and lower bound of the 95% confidence interval (CI) exceed 1. A total of 2021 reports were included in this study. Among the nine drugs examined, significant signals were found, based on the 95%CI for salbutamol (ROR: 9.94, 95%CI: 3.09-31.93) and mirabegron (ROR: 7.52, 95%CI: 4.89-11.55). The results of this study indicate that some selective beta-adrenergic drugs are associated with blood pressure elevation. Considering the frequency of their indications, attention should be paid to their use in elderly patients to avoid adverse events.

Big data mining analysis method based on cloud computing

NASA Astrophysics Data System (ADS)

Cai, Qing Qiu; Cui, Hong Gang; Tang, Hao

2017-08-01

Information explosion era, large data super-large, discrete and non-(semi) structured features have gone far beyond the traditional data management can carry the scope of the way. With the arrival of the cloud computing era, cloud computing provides a new technical way to analyze the massive data mining, which can effectively solve the problem that the traditional data mining method cannot adapt to massive data mining. This paper introduces the meaning and characteristics of cloud computing, analyzes the advantages of using cloud computing technology to realize data mining, designs the mining algorithm of association rules based on MapReduce parallel processing architecture, and carries out the experimental verification. The algorithm of parallel association rule mining based on cloud computing platform can greatly improve the execution speed of data mining.

Theoretical Study of Oxovanadium(IV) Complexation with Formamidoximate: Implications for the Design of Uranyl-Selective Adsorbents

DOE PAGES

Mehio, Nada; Ivanov, Alexander S.; Ladshaw, Austin P.; ...

2015-11-22

Poly(acrylamidoxime) fibers are the current state of the art adsorbent for mining uranium from seawater. However, the competition between uranyl (UO 2 2+) and vanadium ions poses a challenge to mining on the industrial scale. In this work, we employ density functional theory (DFT) and coupled-cluster methods (CCSD(T)) in the restricted formalism to investigate potential binding motifs of the oxovanadium(IV) ion (VO 2+) with the formamidoximate ligand. Consistent with experimental EXAFS data, the hydrated six-coordinate complex is predicted to be preferred over the hydrated five-coordinate complex. Here, our investigation of formamidoximate-VO 2+ complexes universally identified the most stable binding motifmore » formed by chelating a tautomerically rearranged imino hydroxylamine via the imino nitrogen and hydroxylamine oxygen. The alternative binding motifs for amidoxime chelation via a non-rearranged tautomer and 2 coordination are found to be ~11 kcal/mol less stable. Ultimately, the difference in the most stable VO 2+ and UO 2 2+ binding conformation has important implications for the design of more selective UO 2 2+ ligands.« less

Mutation rates at the glycophorin A and HPRT loci in uranium miners exposed to radon progeny.

PubMed Central

Shanahan, E M; Peterson, D; Roxby, D; Quintana, J; Morely, A A; Woodward, A

1996-01-01

OBJECTIVES--To find whether a relation exists between estimated levels of exposure to radon and its progeny and mutations in hypoxanthine phosphoribosyl transferase (HPRT) and glycophorin A in a cohort of former uranium miners. METHODS--A cohort study involving a sample of miners from the Radium Hill uranium mine in South Australia, which operated from 1952 to 1961. Radiation exposures underground at Radium Hill were estimated from historical radon gas measures with a job exposure matrix. Workers from the mine who worked exclusively above ground according to mine records were selected as controls. In 1991-2 miners were interviewed and blood taken for measurement of somatic mutations. Mutation rates for HPRT and glycophorin A were estimated with standard assay techniques. RESULTS--Homozygous mutations of glycophorin A were increased in underground miners (P = 0.0027) and the mutation rate tended to rise with increasing exposure with the exception of the highest exposure (> 10 working level months). However, there was no association between place of work and either the hemizygous mutations of glycophorin A or the HPRT mutation. CONCLUSIONS--There may be an association between glycophorin A mutations and previous occupational exposure to ionising radiation. However, not enough is known at present to use these assays as biomarkers for historical exposure in underground mining cohorts. PMID:8704866

The Prevalence of Selected Potentially Hazardous Workplace Exposures in the US: Findings From the 2010 National Health Interview Survey

PubMed Central

Calvert, Geoffrey M.; Luckhaupt, Sara E.; Sussell, Aaron; Dahlhamer, James M.; Ward, Brian W.

2015-01-01

Objective Assess the national prevalence of current workplace exposure to potential skin hazards, secondhand smoke (SHS), and outdoor work among various industry and occupation groups. Also, assess the national prevalence of chronic workplace exposure to vapors, gas, dust, and fumes (VGDF) among these groups. Methods Data were obtained from the 2010 National Health Interview Survey (NHIS). NHIS is a multistage probability sample survey of the civilian non-institutionalized population of the US. Prevalence rates and their variances were calculated using SUDAAN to account for the complex NHIS sample design. Results The data for 2010 were available for 17,524 adults who worked in the 12 months that preceded interview. The highest prevalence rates of hazardous workplace exposures were typically in agriculture, mining, and construction. The prevalence rate of frequent handling of or skin contact with chemicals, and of non-smokers frequently exposed to SHS at work was highest in mining and construction. Outdoor work was most common in agriculture (85%), construction (73%), and mining (65%). Finally, frequent occupational exposure to VGDF was most common among mining (67%), agriculture (53%), and construction workers (51%). Conclusion We identified industries and occupations with the highest prevalence of potentially hazardous workplace exposures, and provided targets for investigation and intervention activities. PMID:22821700

Relative effects of mammal herbivory and plant spacing on seedling recruitment following fire and mining

PubMed Central

Parsons, Michael H; Rafferty, Christine M; Lamont, Byron B; Dods, Kenneth; Fairbanks, Meredith M

2007-01-01

Background There is much debate concerning which ecological constraints are the most limiting factors to seedling recruitment in disturbed communities. We provide the first comparison between selective herbivory and plant competition effects among two post-mined forest ecosystems (primary succession) and one post-fire woodland ecosystem (secondary succession). Animal exclosure assessments of nine common species across eight sites were performed for comparison within three locations separated by up to 200 km. Additionally, we asked whether pre-browsed plants differed in nutrient content between or within species in the separate systems. Results Among the nine common species, seven of these were affected by mammal herbivory while five shared a similar vulnerability to predation regardless of system. One species was limited by competition (planting density). There was a strong linear correlation between herbivore selectivity (% browsed) and impact (biomass loss) on the fertilized minesites, but not post-fire sites. Phosphorus and potassium were higher for most species in the post-mined system. Principal components analyses revealed that nutrients in shortest supply may be the most likely components of selection within each system. Among all locations, species with highest levels of phosphorus, ADF and leaf water content were often favoured, while high tannins and nitrogen content were generally selected against. Conclusion Herbivory, rather than seedling competition, was the limiting factor for plant performance among post-fire and post-mined reclamation areas. The post-fire seedlings were smaller and more water and nutrient limited, nevertheless browsing prevalence was equivalent at all locations with nearly all seedlings predated. Kangaroo density in the post-fire community declined from the beginning of the experiment, while numbers in the post-mined revegetation increased fourfold within one year. Differences in water and nutrient availability may explain why herbivores are more likely to be attracted to post-mined communities. PMID:17967196

Knowledge Discovery and Data Mining: An Overview

NASA Technical Reports Server (NTRS)

Fayyad, U.

1995-01-01

The process of knowledge discovery and data mining is the process of information extraction from very large databases. Its importance is described along with several techniques and considerations for selecting the most appropriate technique for extracting information from a particular data set.

Automatic target validation based on neuroscientific literature mining for tractography

PubMed Central

Vasques, Xavier; Richardet, Renaud; Hill, Sean L.; Slater, David; Chappelier, Jean-Cedric; Pralong, Etienne; Bloch, Jocelyne; Draganski, Bogdan; Cif, Laura

2015-01-01

Target identification for tractography studies requires solid anatomical knowledge validated by an extensive literature review across species for each seed structure to be studied. Manual literature review to identify targets for a given seed region is tedious and potentially subjective. Therefore, complementary approaches would be useful. We propose to use text-mining models to automatically suggest potential targets from the neuroscientific literature, full-text articles and abstracts, so that they can be used for anatomical connection studies and more specifically for tractography. We applied text-mining models to three structures: two well-studied structures, since validated deep brain stimulation targets, the internal globus pallidus and the subthalamic nucleus and, the nucleus accumbens, an exploratory target for treating psychiatric disorders. We performed a systematic review of the literature to document the projections of the three selected structures and compared it with the targets proposed by text-mining models, both in rat and primate (including human). We ran probabilistic tractography on the nucleus accumbens and compared the output with the results of the text-mining models and literature review. Overall, text-mining the literature could find three times as many targets as two man-weeks of curation could. The overall efficiency of the text-mining against literature review in our study was 98% recall (at 36% precision), meaning that over all the targets for the three selected seeds, only one target has been missed by text-mining. We demonstrate that connectivity for a structure of interest can be extracted from a very large amount of publications and abstracts. We believe this tool will be useful in helping the neuroscience community to facilitate connectivity studies of particular brain regions. The text mining tools used for the study are part of the HBP Neuroinformatics Platform, publicly available at http://connectivity-brainer.rhcloud.com/. PMID:26074781

Practical applications of sulfate-reducing bacteria to control acid mine drainage at the Lilly/Orphan Boy Mine near Elliston, Montana

DOE Office of Scientific and Technical Information (OSTI.GOV)

Canty, M.

The overall purpose of this document is to provide a detailed technical description of a technology, biological sulfate reduction, which is being demonstrated under the Mine Waste Technology Pilot Program, and provide the technology evaluation process undertaken to select this technology for demonstration. In addition, this document will link the use of the selected technology to an application at a specific site. The purpose of this project is to develop technical information on the ability of biological sulfate reduction to slow the process of acid generation and, thus, improve water quality at a remote mine site. Several technologies are screenedmore » for their potential to treat acid mine water and to function as a source control for a specific acid-generating situation: a mine shaft and associated underground workings flooded with acid mine water and discharging a small flow from a mine opening. The preferred technology is the use of biological sulfate reduction. Sulfate-reducing bacteria are capable of reducing sulfate to sulfide, as well as increasing the pH and alkalinity of water affected by acid generation. Soluble sulfide reacts with the soluble metals in solution to form insoluble metal sulfides. The environment needed for efficient sulfate-reducing bacteria growth decreases acid production by reducing the dissolved oxygen in water and increasing pH. A detailed technical description of the sulfate-reducing bacteria technology, based on an extensive review of the technical literature, is presented. The field demonstration of this technology to be performed at the Lilly/Orphan Boy Mine is also described. Finally, additional in situ applications of biological sulfate reduction are presented.« less

Assessment of the suitability of trees for brownfields reuse in the post-mining landscape

NASA Astrophysics Data System (ADS)

Mec, J.; Lokajickova, B.; Sotkova, N.; Svehlakova, H.; Stalmachova, B.

2017-10-01

The post-mining landscape of Upper Silesian is deterioration of the original landscape caused by underground coal mining. There are huge ecosystems changes, which have been reclaimed by nature-friendly procedures. The aim of the work is to evaluate the suitability of selected trees for reuse of brownfields in this landscape and proposals for reclamation in the interest areas of Upper Silesian.

Semisupervised Clustering by Iterative Partition and Regression with Neuroscience Applications

PubMed Central

Qian, Guoqi; Wu, Yuehua; Ferrari, Davide; Qiao, Puxue; Hollande, Frédéric

2016-01-01

Regression clustering is a mixture of unsupervised and supervised statistical learning and data mining method which is found in a wide range of applications including artificial intelligence and neuroscience. It performs unsupervised learning when it clusters the data according to their respective unobserved regression hyperplanes. The method also performs supervised learning when it fits regression hyperplanes to the corresponding data clusters. Applying regression clustering in practice requires means of determining the underlying number of clusters in the data, finding the cluster label of each data point, and estimating the regression coefficients of the model. In this paper, we review the estimation and selection issues in regression clustering with regard to the least squares and robust statistical methods. We also provide a model selection based technique to determine the number of regression clusters underlying the data. We further develop a computing procedure for regression clustering estimation and selection. Finally, simulation studies are presented for assessing the procedure, together with analyzing a real data set on RGB cell marking in neuroscience to illustrate and interpret the method. PMID:27212939

Occupational injuries and fatalities in a tanzanite mine: Need to improve workers safety in Tanzania

PubMed Central

Boniface, Respicious; Museru, Lawrence; Munthali, Victoria; Lett, Ronald

2013-01-01

Introduction Work related injuries are common, and the mining industry accounts for a significant proportion of these injuries. Tanzania is among the countries with high rates of mining injuries, nevertheless pre-hospital care is almost non existant and health care service deliveries are poor. This study sought to identify factors associated with injuries and fatalities among miners in Mererani, Tanzania. Methods A Cross - Sectional study of miners who sustained injuries and seen at Mererani health centre between January 2009 and May 2012. Results In the selected period 248 injury patients were seen. All were males, and 54% were between 18 - 30 years age-group. Almost all (98.7%) didn’t use protective gears at work, and worked for more than 12 hours daily. Falling rocks were the leading cause of injury (18.2%), and majority sustained multiple injuries (33%). Of the patients seen, 41.3% died. The following were more likely to die than others; Primary education (p = 0.04), Less than 5 years work experience (p = 0.000), unintentional injuries (p = 0.000), fall injuries (p = 0.000) and sustaining multiple injuries (p = 0.000). Conclusion The burden of injuries and fatalities demonstrated in this study, point to the need for implementation and monitoring of the use of safety equipment and operating procedures of the mines by government and other regulatory authorities. Initiation of pre hospital care at the mines and improved emergency medical service delivery at health centers in Tanzania. PMID:24778757

Mine safety assessment using gray relational analysis and bow tie model

PubMed Central

2018-01-01

Mine safety assessment is a precondition for ensuring orderly and safety in production. The main purpose of this study was to prevent mine accidents more effectively by proposing a composite risk analysis model. First, the weights of the assessment indicators were determined by the revised integrated weight method, in which the objective weights were determined by a variation coefficient method and the subjective weights determined by the Delphi method. A new formula was then adopted to calculate the integrated weights based on the subjective and objective weights. Second, after the assessment indicator weights were determined, gray relational analysis was used to evaluate the safety of mine enterprises. Mine enterprise safety was ranked according to the gray relational degree, and weak links of mine safety practices identified based on gray relational analysis. Third, to validate the revised integrated weight method adopted in the process of gray relational analysis, the fuzzy evaluation method was used to the safety assessment of mine enterprises. Fourth, for first time, bow tie model was adopted to identify the causes and consequences of weak links and allow corresponding safety measures to be taken to guarantee the mine’s safe production. A case study of mine safety assessment was presented to demonstrate the effectiveness and rationality of the proposed composite risk analysis model, which can be applied to other related industries for safety evaluation. PMID:29561875

Selected water-quality data for the Standard Mine, Gunnison County, Colorado, 2006-2007

USGS Publications Warehouse

Verplanck, Philip L.; Manning, Andrew H.; Mast, M. Alisa; Wanty, Richard B.; McCleskey, R. Blaine; Todorov, Todor I.; Adams, Monique

2007-01-01

Mine drainage and underground water samples were collected for analysis of inorganic solutes as part of a 1-year, hydrogeologic investigation of the Standard Mine and vicinity. The U.S. Environmental Protection Agency has listed the Standard Mine in the Elk Creek drainage near Crested Butte, Colorado, as a Superfund Site because discharge from the Standard Mine enters Elk Creek, contributing dissolved and suspended loads of zinc, cadmium, copper, and other metals to Coal Creek, which is the primary drinking-water supply for the town of Crested Butte. Water analyses are reported for mine-effluent samples from Levels 1 and 5 of the Standard Mine, underground samples from Levels 3 and 5 of the Standard Mine, mine effluent from an adit located on the Elk Lode, and two spring samples that emerged from waste-rock material below Level 5 of the Standard Mine and the adit located on the Elk Lode. Reported analyses include field parameters (pH, specific conductance, water temperature, dissolved oxygen, and redox potential) and major constituents and trace elements.

Method for assessing coal-floor water-inrush risk based on the variable-weight model and unascertained measure theory

NASA Astrophysics Data System (ADS)

Wu, Qiang; Zhao, Dekang; Wang, Yang; Shen, Jianjun; Mu, Wenping; Liu, Honglei

2017-11-01

Water inrush from coal-seam floors greatly threatens mining safety in North China and is a complex process controlled by multiple factors. This study presents a mathematical assessment system for coal-floor water-inrush risk based on the variable-weight model (VWM) and unascertained measure theory (UMT). In contrast to the traditional constant-weight model (CWM), which assigns a fixed weight to each factor, the VWM varies with the factor-state value. The UMT employs the confidence principle, which is more effective in ordered partition problems than the maximum membership principle adopted in the former mathematical theory. The method is applied to the Datang Tashan Coal Mine in North China. First, eight main controlling factors are selected to construct the comprehensive evaluation index system. Subsequently, an incentive-penalty variable-weight model is built to calculate the variable weights of each factor. Then, the VWM-UMT model is established using the quantitative risk-grade divide of each factor according to the UMT. On this basis, the risk of coal-floor water inrush in Tashan Mine No. 8 is divided into five grades. For comparison, the CWM is also adopted for the risk assessment, and a differences distribution map is obtained between the two methods. Finally, the verification of water-inrush points indicates that the VWM-UMT model is powerful and more feasible and reasonable. The model has great potential and practical significance in future engineering applications.

DEVELOPING AND EXPLOITING A UNIQUE DATASET FROM SOUTH AFRICAN GOLD MINES FOR SOURCE CHARACTERIZATION AND WAVE PROPAGATION

DOE Office of Scientific and Technical Information (OSTI.GOV)

Julia, J; Nyblade, A; Gok, R

2009-07-06

In this project, we are developing and exploiting a unique seismic dataset to address the characteristics of small seismic events and the associated seismic signals observed at local (< 200 km) and regional (< 2000 km) distances. The dataset is being developed using mining-induced events from three deep gold mines in South Africa recorded on in-mine networks (< 1 km) composed of tens of high-frequency sensors, a network of four broadband stations installed as part of this project at the surface around the mines (1-10 km), and a network of existing broadband seismic stations at local/regional distances (50-1000 km) frommore » the mines. Data acquisition has now been completed and includes: (1) {approx}2 years (2007 and 2008) of continuous recording by the surface broadband array, and (2) tens of thousands of mine tremors in the -3.4 < ML < 4.4 local magnitude range. Events with positive magnitudes are generally well recorded by the surface-mine stations, while magnitudes of 3.0 and larger are seen at regional distances (up to {approx} 600 km) in high-pass filtered recordings. We have now completed the quality control of the in-mine data gathered at the three gold mines included in this project. The quality control consisted of: (1) identification and analysis of outliers among the P- and S-wave travel-time picks reported by the in-mine network operator and (2) verification of sensor orientations. The outliers have been identified through a 'Wadati filter' that searches for the largest subset of P- and S-wave travel-time picks consistent with a medium of uniform wave-speed. They have observed that outliers are generally picked at a few select stations. They have also detected that trigger times were mistakenly reported as origin times by the in-mine network operator, and corrections have been obtained from the intercept times in the Wadati diagrams. Sensor orientations have been verified through rotations into the local ray-coordinate system and, when possible, corrected by correlating waveforms obtained from theoretical and empirical rotation angles. Full moment tensor solutions have been obtained for selected events within the Savuka network volume, with moment magnitudes in the 0.5 < M{sub W} < 2.6 range. The solutions were obtained by inverting P-, SV-, and SH-spectral amplitudes measured on the theoretically rotated waveforms with visually assigned polarities. Most of the solutions have a non-zero implosive contribution (47 out of 76), while a small percentage is purely deviatoric (10 out of 76). The deviatoric moment tensors range from pure double couple to pure non-double couple mechanisms. We have also calibrated the regional stations for seismic coda-derived source spectra and moment magnitude using the envelope methodology of Mayeda et al. (2003). they tie the coda M{sub w} to independent values from waveform modeling. The resulting coda-based source spectra of shallow mining-related events show significant spectral peaking that is not seen in deeper tectonic earthquakes. This coda peaking may be an independent method of identifying shallow events and is similar to coda peaking with previously observed for Nevada explosions, where the frequency of the observed spectral peak correlates with the depth of burial (Murphy et al., 2009).« less

Traffic accident in Cuiabá-MT: an analysis through the data mining technology.

PubMed

Galvão, Noemi Dreyer; de Fátima Marin, Heimar

2010-01-01

The traffic road accidents (ATT) are non-intentional events with an important magnitude worldwide, mainly in the urban centers. This article aims to analyzes data related to the victims of ATT recorded by the Justice Secretariat and Public Security (SEJUSP) in hospital morbidity and mortality incidence at the city of Cuiabá-MT during 2006, using data mining technology. An observational, retrospective and exploratory study of the secondary data bases was carried out. The three database selected were related using the probabilistic method, through the free software RecLink. One hundred and thirty-nine (139) real pairs of victims of ATT were obtained. In this related database the data mining technology was applied with the software WEKA using the Apriori algorithm. The result generated 10 best rules, six of them were considered according to the parameters established that indicated a useful and comprehensible knowledge to characterize the victims of accidents in Cuiabá. Finally, the findings of the associative rules showed peculiarities of the road traffic accident victims in Cuiabá and highlight the need of prevention measures in the collision accidents for males.

Thermal comfort sustained by cold protective clothing in Arctic open-pit mining-a thermal manikin and questionnaire study.

PubMed

Jussila, Kirsi; Rissanen, Sirkka; Aminoff, Anna; Wahlström, Jens; Vaktskjold, Arild; Talykova, Ljudmila; Remes, Jouko; Mänttäri, Satu; Rintamäki, Hannu

2017-12-07

Workers in the Arctic open-pit mines are exposed to harsh weather conditions. Employers are required to provide protective clothing for workers. This can be the outer layer, but sometimes also inner or middle layers are provided. This study aimed to determine how Arctic open-pit miners protect themselves against cold and the sufficiency, and the selection criteria of the garments. Workers' cold experiences and the clothing in four Arctic open-pit mines in Finland, Sweden, Norway and Russia were evaluated by a questionnaire (n=1,323). Basic thermal insulation (I cl ) of the reported clothing was estimated (ISO 9920). The I cl of clothing from the mines were also measured by thermal manikin (standing/walking) in 0.3 and 4.0 m/s wind. The questionnaire showed that the I cl of the selected clothing was on average 1.2 and 1.5 clo in mild (-5 to +5°C) and dry cold (-20 to -10°C) conditions, respectively. The I cl of the clothing measured by thermal manikin was 1.9-2.3 clo. The results show that the Arctic open-pit miners' selected their clothing based on occupational (time outdoors), environmental (temperature, wind, moisture) and individual factors (cold sensitivity, general health). However, the selected clothing was not sufficient to prevent cooling completely at ambient temperatures below -10°C.

RADSS: an integration of GIS, spatial statistics, and network service for regional data mining

NASA Astrophysics Data System (ADS)

Hu, Haitang; Bao, Shuming; Lin, Hui; Zhu, Qing

2005-10-01

Regional data mining, which aims at the discovery of knowledge about spatial patterns, clusters or association between regions, has widely applications nowadays in social science, such as sociology, economics, epidemiology, crime, and so on. Many applications in the regional or other social sciences are more concerned with the spatial relationship, rather than the precise geographical location. Based on the spatial continuity rule derived from Tobler's first law of geography: observations at two sites tend to be more similar to each other if the sites are close together than if far apart, spatial statistics, as an important means for spatial data mining, allow the users to extract the interesting and useful information like spatial pattern, spatial structure, spatial association, spatial outlier and spatial interaction, from the vast amount of spatial data or non-spatial data. Therefore, by integrating with the spatial statistical methods, the geographical information systems will become more powerful in gaining further insights into the nature of spatial structure of regional system, and help the researchers to be more careful when selecting appropriate models. However, the lack of such tools holds back the application of spatial data analysis techniques and development of new methods and models (e.g., spatio-temporal models). Herein, we make an attempt to develop such an integrated software and apply it into the complex system analysis for the Poyang Lake Basin. This paper presents a framework for integrating GIS, spatial statistics and network service in regional data mining, as well as their implementation. After discussing the spatial statistics methods involved in regional complex system analysis, we introduce RADSS (Regional Analysis and Decision Support System), our new regional data mining tool, by integrating GIS, spatial statistics and network service. RADSS includes the functions of spatial data visualization, exploratory spatial data analysis, and spatial statistics. The tool also includes some fundamental spatial and non-spatial database in regional population and environment, which can be updated by external database via CD or network. Utilizing this data mining and exploratory analytical tool, the users can easily and quickly analyse the huge mount of the interrelated regional data, and better understand the spatial patterns and trends of the regional development, so as to make a credible and scientific decision. Moreover, it can be used as an educational tool for spatial data analysis and environmental studies. In this paper, we also present a case study on Poyang Lake Basin as an application of the tool and spatial data mining in complex environmental studies. At last, several concluding remarks are discussed.

MINING METHODS AND COSTS, CALYX NOS. 3 AND 8 URANIUM MINES, TEMPLE MOUNTAIN DISTRICT, EMERY COUNTY, UTAH

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dare, W.L.

1957-04-01

Descriptions are given of the Calyx No. 3 mine operated by American Reduc Uranium Corp. and Calyx No. 8 operated by Cline Co. The deposits are composed of numerous small, irregular bodies and are worked through 36 inch Calyx drill holes. The U--V ores are concentrated chiefly in the lower 30 feet of the Moss Back sandstone. In general it follows the strnta. The mine is worked by open stoping with random pillar support. The operations and mining practices of these two mines are very similar and typify the mining methods and practioes used by many small U producers onmore » the Colorado Plateau. (R.V.J.)« less

An evaluation of problems arising from acid mine drainage in the vicinity of Shasta Lake, Shasta County, California

USGS Publications Warehouse

Fuller, Richard H.; Shay, J.M.; Ferreira, R.F.; Hoffman, R.J.

1978-01-01

Streams draining the mined areas of massive sulfide ore deposits in the Shasta Mining Districts of northern California are generally acidic and contain large concentrations of dissolved metals, including iron, copper, and zinc. The streams, including Flat, Little Backbone, Spring, West Squaw, Horse, and Zinc Creeks, discharge into Shasta Reservoir and the Sacramento River and have caused numerous fish kills. The sources of pollution are discharge from underground mines, streams that flow into open pits, and streams that flow through pyritic mine dumps where the oxidation of pyrite and other sulfide minerals results in the production of acid and the mobilization of metals. Suggested methods of treatment include the use of air and hydraulic seals in the mines, lime neutralization of mine effluent, channeling of runoff and mine effluent away from mine and tailing areas, and the grading and sealing of mine dumps. A comprehensive preabatement and postabatement program is recommended to evaluate the effects of any treatment method used. (Woodard-USGS)

Causes Of Low Efficiency Of Combined Ventilation System In Coal Mines In Resolving The Problem Of Air Leaks (Inflows) Between Levels And Surface

NASA Astrophysics Data System (ADS)

Popov, Valeriy; Filatov, Yuriy; Lee, Hee; Golik, Anatoliy

2017-11-01

The paper discusses the problem of the underground mining safety control. The long-term air intake to coal accumulations is reviewed as one of the reasons of endogenous fires during mining. The methods of combating air leaks (inflows) in order to prevent endogenous fires are analyzed. The calculations showing the discrepancy between the design calculations for the mine ventilation, disregarding a number of mining-andgeological and mining-engineering factors, and the actual conditions of mining are given. It is proved that the conversion of operating mines to combined (pressure and exhaust) ventilation system in order to reduce the endogenous fire hazard of underground mining is unreasonable due to impossibility of providing an optimal distribution of aerodynamic pressure in mines. The conversion does not exclude the entry of air into potentially hazardous zones of endogenous fires. The essence of the combined application of positive and negative control methods for the distribution of air pressure is revealed. It consists of air doors installation in easily ventilated airways and installation of pressure equalization chambers equipped with auxiliary fans near the stoppings, working sections and in parallel airways.The effectiveness of the combined application of negative and positive control methods for the air pressure distribution in order to reduce endogenous fire hazard of mining operations is proved.

Evaluation of the Kloswall longwall mining system

NASA Astrophysics Data System (ADS)

Guay, P. J.

1982-04-01

A new longwal mining system specifically designed to extract a very deep web (48 inches or deeper) from a longwall panel was studied. Productivity and cost analysis comparing the new mining system with a conventional longwall operation taking a 30 inch wide web is presented. It is shown that the new system will increase annual production and return on investment in most cases. Conceptual drawings and specifications for a high capacity three drum shearer and a unique shield type of roof support specifically designed for very wide web operation are reported. The advantages and problems associated with wide web mining in general and as they relate specifically to the equipment selected for the new mining system are discussed.

International Asteroid Mission (IAM)

NASA Astrophysics Data System (ADS)

Yamaguchi, Ryuuji

1991-07-01

International Asteroid Mission (IAM) is a program aimed at developing resources of asteroids abundantly existing near the earth. This report describes the research results of design project of the International Space University (ISU) held in 1990 at Tront-York University. ISU research and asteroid survey results, and the manned asteroid mining mission are outlined. Classification of asteroids existing near the earth and asteroid resource processing and use analyses are conducted. Asteroid selection flow charts are introduced, and the 1982HR-Orpheus is selected as a candidate asteroid because it takes an approaching orbit toward the earth, requires small delta V, and possesses abundant carbonaceous chondrites. Characteristics of 1982HR-Orpheus are presented. Mission requirements, mission outlines, transportation systems, and mining and processing systems for manned asteroid mining missions are presented.

Fusing Data Mining, Machine Learning and Traditional Statistics to Detect Biomarkers Associated with Depression.

PubMed

Dipnall, Joanna F; Pasco, Julie A; Berk, Michael; Williams, Lana J; Dodd, Seetal; Jacka, Felice N; Meyer, Denny

2016-01-01

Atheoretical large-scale data mining techniques using machine learning algorithms have promise in the analysis of large epidemiological datasets. This study illustrates the use of a hybrid methodology for variable selection that took account of missing data and complex survey design to identify key biomarkers associated with depression from a large epidemiological study. The study used a three-step methodology amalgamating multiple imputation, a machine learning boosted regression algorithm and logistic regression, to identify key biomarkers associated with depression in the National Health and Nutrition Examination Study (2009-2010). Depression was measured using the Patient Health Questionnaire-9 and 67 biomarkers were analysed. Covariates in this study included gender, age, race, smoking, food security, Poverty Income Ratio, Body Mass Index, physical activity, alcohol use, medical conditions and medications. The final imputed weighted multiple logistic regression model included possible confounders and moderators. After the creation of 20 imputation data sets from multiple chained regression sequences, machine learning boosted regression initially identified 21 biomarkers associated with depression. Using traditional logistic regression methods, including controlling for possible confounders and moderators, a final set of three biomarkers were selected. The final three biomarkers from the novel hybrid variable selection methodology were red cell distribution width (OR 1.15; 95% CI 1.01, 1.30), serum glucose (OR 1.01; 95% CI 1.00, 1.01) and total bilirubin (OR 0.12; 95% CI 0.05, 0.28). Significant interactions were found between total bilirubin with Mexican American/Hispanic group (p = 0.016), and current smokers (p<0.001). The systematic use of a hybrid methodology for variable selection, fusing data mining techniques using a machine learning algorithm with traditional statistical modelling, accounted for missing data and complex survey sampling methodology and was demonstrated to be a useful tool for detecting three biomarkers associated with depression for future hypothesis generation: red cell distribution width, serum glucose and total bilirubin.

Text Mining in Biomedical Domain with Emphasis on Document Clustering.

PubMed

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.

Efficacy Evaluation of Current and Future Naval Mine Warfare Neutralization Method

DTIC Science & Technology

2016-12-01

Distribution is unlimited. EFFICACY EVALUATION OF CURRENT AND FUTURE NAVAL MINE WARFARE NEUTRALIZATION METHOD by Team MIW Cohort SE311-152O...EFFICACY EVALUATION OF CURRENT AND FUTURE NAVAL MINE WARFARE NEUTRALIZATION METHOD 5. FUNDING NUMBERS 6. AUTHOR (S) Team MIW, Systems Engineering...NEUTRALIZATION METHOD Team MIW, Systems Engineering Cohort SE311-152O Submitted in partial fulfillment of the requirements for the degrees of

Innovative computer-aided methods for the discovery of new kinase ligands.

PubMed

Abuhammad, Areej; Taha, Mutasem

2016-04-01

Recent evidence points to significant roles played by protein kinases in cell signaling and cellular proliferation. Faulty protein kinases are involved in cancer, diabetes and chronic inflammation. Efforts are continuously carried out to discover new inhibitors for selected protein kinases. In this review, we discuss two new computer-aided methodologies we developed to mine virtual databases for new bioactive compounds. One method is ligand-based exploration of the pharmacophoric space of inhibitors of any particular biotarget followed by quantitative structure-activity relationship-based selection of the best pharmacophore(s). The second approach is structure-based assuming that potent ligands come into contact with binding site spots distinct from those contacted by weakly potent ligands. Both approaches yield pharmacophores useful as 3D search queries for the discovery of new bioactive (kinase) inhibitors.

Combined mining: discovering informative knowledge in complex data.

PubMed

Cao, Longbing; Zhang, Huaifeng; Zhao, Yanchang; Luo, Dan; Zhang, Chengqi

2011-06-01

Enterprise data mining applications often involve complex data such as multiple large heterogeneous data sources, user preferences, and business impact. In such situations, a single method or one-step mining is often limited in discovering informative knowledge. It would also be very time and space consuming, if not impossible, to join relevant large data sources for mining patterns consisting of multiple aspects of information. It is crucial to develop effective approaches for mining patterns combining necessary information from multiple relevant business lines, catering for real business settings and decision-making actions rather than just providing a single line of patterns. The recent years have seen increasing efforts on mining more informative patterns, e.g., integrating frequent pattern mining with classifications to generate frequent pattern-based classifiers. Rather than presenting a specific algorithm, this paper builds on our existing works and proposes combined mining as a general approach to mining for informative patterns combining components from either multiple data sets or multiple features or by multiple methods on demand. We summarize general frameworks, paradigms, and basic processes for multifeature combined mining, multisource combined mining, and multimethod combined mining. Novel types of combined patterns, such as incremental cluster patterns, can result from such frameworks, which cannot be directly produced by the existing methods. A set of real-world case studies has been conducted to test the frameworks, with some of them briefed in this paper. They identify combined patterns for informing government debt prevention and improving government service objectives, which show the flexibility and instantiation capability of combined mining in discovering informative knowledge in complex data.

Effects of abandoned arsenic mine on water resources pollution in north west of iran.

PubMed

Hajalilou, Behzad; Mosaferi, Mohammad; Khaleghi, Fazel; Jadidi, Sakineh; Vosugh, Bahram; Fatehifar, Esmail

2011-01-01

Pollution due to mining activities could have an important role in health and welfare of people who are living in mining area. When mining operation finishes, environ-ment of mining area can be influenced by related pollution e.g. heavy metals emission to wa-ter resources. The present study was aimed to evaluate Valiloo abandoned arsenic mine ef-fects on drinking water resources quality and possible health effects on the residents of min-ing area in the North West of Iran. Water samples and some limited composite wheat samples in downstream of min-ing area were collected. Water samples were analyzed for chemical parameters according to standard methods. For determination of arsenic in water samples, Graphite Furnace Atomic Absorption Spectrometric Method (GFAAS) and for wheat samples X - Ray Fluorescence (XRF) and Inductively Coupled Plasma Method (ICP) were used. Information about possible health effects due to exposure to arsenic was collected through interviews in studied villages and health center of Herris City. The highest concentrations of arsenic were measured near the mine (as high as 2000 µg/L in Valiloo mine opening water). With increasing distance from the mine, concentration was decreased. Arsenic was not detectable in any of wheat samples. Fortunately, no health effects had been reported between residents of studied area due to exposure to arsenic. Valiloo abandoned arsenic mine has caused release of arsenic to the around en-vironment of the mine, so arsenic concentration has been increased in the groundwater and also downstream river that requires proper measures to mitigate spread of arsenic.

Integrated method of RS and GPR for monitoring the changes in the soil moisture and groundwater environment due to underground coal mining

NASA Astrophysics Data System (ADS)

Bian, Zhengfu; Lei, Shaogang; Inyang, Hilary I.; Chang, Luqun; Zhang, Richen; Zhou, Chengjun; He, Xiao

2009-03-01

Mining affects the environment in different ways depending on the physical context in which the mining occurs. In mining areas with an arid environment, mining affects plants’ growth by changing the amount of available water. This paper discusses the effects of mining on two important determinants of plant growth—soil moisture and groundwater table (GWT)—which were investigated using an integrated approach involving a field sampling investigation with remote sensing (RS) and ground-penetrating radar (GPR). To calculate and map the distribution of soil moisture for a target area, we initially analyzed four models for regression analysis between soil moisture and apparent thermal inertia and finally selected a linear model for modeling the soil moisture at a depth 10 cm; the relative error of the modeled soil moisture was about 6.3% and correlation coefficient 0.7794. A comparison of mined and unmined areas based on the results of limited field sampling tests or RS monitoring of Landsat 5-thermatic mapping (TM) data indicated that soil moisture did not undergo remarkable changes following mining. This result indicates that mining does not have an effect on soil moisture in the Shendong coal mining area. The coverage of vegetation in 2005 was compared with that in 1995 by means of the normalized difference vegetation index (NDVI) deduced from TM data, and the results showed that the coverage of vegetation in Shendong coal mining area has improved greatly since 1995 because of policy input RMB¥0.4 per ton coal production by Shendong Coal Mining Company. The factor most affected by coal mining was GWT, which dropped from a depth of 35.41 m before mining to a depth of 43.38 m after mining at the Bulianta Coal Mine based on water well measurements. Ground-penetrating radar at frequencies of 25 and 50 MHz revealed that the deepest GWT was at about 43.4 m. There was a weak water linkage between the unsaturated zone and groundwater, and the decline of water table primarily resulted from the well pumping for mining safety rather than the movement of cracking strata. This result is in agreement with the measurements of the water wells. The roots of nine typical plants in the study area were investigated. Populus was found to have the deepest root system with a depth of about 26 m. Based on an assessment of plant growth demands and the effect of mining on environmental factors, we concluded that mining will have less of an effect on plant growth at those sites where the primary GWT depth before mining was deep enough to be unavailable to plants. If the primary GWT was available for plant growth before mining, especially to those plants with deeper roots, mining will have a significant effect on the growth of plants and the mechanism of this effect will include the loss of water to roots and damage to the root system.

Influence of the Roof Movement Control Method on the Stability of Remnant

NASA Astrophysics Data System (ADS)

Adach-Pawelus, Karolina

2017-12-01

In the underground mines, there are geological and mining situations that necessitate leaving behind remnants in the mining field. Remnants, in the form of small, irregular parcels, are usually separated in the case of: significant problems with maintaining roof stability, high rockburst hazard, the occurrence of complex geological conditions and for random reasons (ore remnants), as well as for economic reasons (undisturbed rock remnants). Remnants left in the mining field become sites of high stress values concentration and may affect the rock in their vicinity. The values of stress inside the remnant and its vicinity, as well as the stability of the remnant, largely depend on the roof movement control method used in the mining field. The article presents the results of the numerical analysis of the influence of roof movement control method on remnant stability and the geomechanical situation in the mining field. The numerical analysis was conducted for the geological and mining conditions characteristic of Polish underground copper mines owned by KGHM Polska Miedz S.A. Numerical simulations were performed in a plane strain state by means of Phase 2 v. 8.0 software, based on the finite element method. The behaviour of remnant and rock mass in its vicinity was simulated in the subsequent steps of the room and pillar mining system for three types of roof movement control method: roof deflection, dry backfill and hydraulic backfill. The parameters of the rock mass accepted for numerical modelling were calculated by means of RocLab software on the basis of the Hoek-Brown classification. The Mohr-Coulomb strength criterion was applied.

Survival and growth of wildlife shrubs and trees on acid mine spoil

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fowler, D.K.; Adkisson, L.F.

1980-01-01

The purpose of this study was to assess the survival and growth of selected wildlife plants over a wide range of acid mine spoil conditions and to identify species suitable for surface mine reclamation. A major criterion in selection of study sites was inclusion of a wide range of spoil acidity conditions. The Ollis Creek (Study Area A) and Farrell (Study Area B) coal surface mines located in Campbell and Scott Counties, Tennessee, were selected for study. Seven plant species, all of which had been used in past reclamation demonstrations, were introduced on the 22 plots during March 1972. Autumnmore » olive (Elaeagnus umbellata) was included as a control plant. Ten additional plant species were introduced during March 1973. With the exception of highbush blueberry (Vaccinium corymbosum var.). European filbert (Corylus avellana), and red maple (Acer rubrum), these species had not been used in TVA reclamation demonstrations. To assess the effects of spoil pH on the plants, the plots were grouped into seven pH categories, and mean percent survival and growth for each species were calculated. Results indicate that autumn olive, elaeagnus cherry, arnot locust, sawtooth oak, red maple, and Toringo crabapple are suitable for quick improvement of surface mine habitat over a wide range of spoil acidity in the Appalachian coalfield. Bessey cherry and European filbert need further study before a decision can be made regarding their reclamation utility. Species that are not recommended for quick habitat improvement over a wide range of surface mine spoil pH conditions include bush honeysuckle, barberry, Siberian crabapple, Manchu cherry, American beautyberry, bear oak, blueberry, rem-red honeysuckle, and redcedar.« less

Land mine detection using multispectral image fusion

DOE Office of Scientific and Technical Information (OSTI.GOV)

Clark, G.A.; Sengupta, S.K.; Aimonetti, W.D.

1995-03-29

Our system fuses information contained in registered images from multiple sensors to reduce the effects of clutter and improve the ability to detect surface and buried land mines. The sensor suite currently consists of a camera that acquires images in six bands (400nm, 500nm, 600nm, 700nm, 800nm and 900nm). Past research has shown that it is extremely difficult to distinguish land mines from background clutter in images obtained from a single sensor. It is hypothesized, however, that information fused from a suite of various sensors is likely to provide better detection reliability, because the suite of sensors detects a varietymore » of physical properties that are more separable in feature space. The materials surrounding the mines can include natural materials (soil, rocks, foliage, water, etc.) and some artifacts. We use a supervised learning pattern recognition approach to detecting the metal and plastic land mines. The overall process consists of four main parts: Preprocessing, feature extraction, feature selection, and classification. These parts are used in a two step process to classify a subimage. We extract features from the images, and use feature selection algorithms to select only the most important features according to their contribution to correct detections. This allows us to save computational complexity and determine which of the spectral bands add value to the detection system. The most important features from the various sensors are fused using a supervised learning pattern classifier (the probabilistic neural network). We present results of experiments to detect land mines from real data collected from an airborne platform, and evaluate the usefulness of fusing feature information from multiple spectral bands.« less

Improving surface stability of elevated spoil landforms using natural landform analogy and geological information

NASA Astrophysics Data System (ADS)

Emmerton, Bevan; Burgess, Jon; Esterle, Joan; Erskine, Peter; Baumgartl, Thomas

2017-04-01

Large-scale open cut mining in the Bowen Basin, Queensland, Australia has undergone an evolutionary process over the period of a few decades, transitioning from shallow mining depths, limited spoil elevation and pasture based rehabilitation to increased mining depths, escalating pre-stripping, elevated mesa-like landforms and native woody species rehabilitation. As a consequence of this development, the stabilisation of recent constructed landforms has to be assured through means other than the establishment of vegetative cover. Recent developments are the specific selection and partitioning of resilient fragmental spoil types for the construction of final landform surface. They can also be used as cladding resources for stabilizing steep erosive batters and this has been identified as a practical methodology that has the potential to significantly improve rehabilitation outcomes. Examples of improvements are an increase of the surface rock cover, roughness and infiltration and reducing inherent erodibility and runoff and velocity of surface flow. However, a thorough understanding of the properties and behavior of individual spoil materials disturbed during mining is required. Relevant information from published literature on the geological origins, lithology and weathering characteristics of individual strata within the Bowen Basin Coal Measures located in Queensland, Australia (and younger overlying weathered strata) has been studied, and related both to natural landforms and to the surface stability of major strata types when disturbed by mining. The resulting spoil classification developed from this study is based primarily on inherent geological characteristics and weathering behaviour of identifiable lithologic components, and as such describes the expected fragmental resilience likely within disturbed materials at Bowen Basin coal mines. The proposed classification system allows the allocation of spoil types to use categories which have application in pre-mine feasibility investigations, landform design and material selection and placement. It finds its application by practitioners who find encouragement in using this approach of a relatively easy usable classification system to improve the overall outcome of rehabilitation through selection of optimal substrates.

Protein Hydrogel Microbeads for Selective Uranium Mining from Seawater.

PubMed

Kou, Songzi; Yang, Zhongguang; Sun, Fei

2017-01-25

Practical methods for oceanic uranium extraction have yet to be developed in order to tap into the vast uranium reserve in the ocean as an alternative energy. Here we present a protein hydrogel system containing a network of recently engineered super uranyl binding proteins (SUPs) that is assembled through thiol-maleimide click chemistry under mild conditions. Monodisperse SUP hydrogel microbeads fabricated by a microfluidic device further enable uranyl (UO 2 2+ ) enrichment from natural seawater with great efficiency (enrichment index, K = 2.5 × 10 3 ) and selectivity. Our results demonstrate the feasibility of using protein hydrogels to extract uranium from the ocean.

Text mining applied to electronic cardiovascular procedure reports to identify patients with trileaflet aortic stenosis and coronary artery disease.

PubMed

Small, Aeron M; Kiss, Daniel H; Zlatsin, Yevgeny; Birtwell, David L; Williams, Heather; Guerraty, Marie A; Han, Yuchi; Anwaruddin, Saif; Holmes, John H; Chirinos, Julio A; Wilensky, Robert L; Giri, Jay; Rader, Daniel J

2017-08-01

Interrogation of the electronic health record (EHR) using billing codes as a surrogate for diagnoses of interest has been widely used for clinical research. However, the accuracy of this methodology is variable, as it reflects billing codes rather than severity of disease, and depends on the disease and the accuracy of the coding practitioner. Systematic application of text mining to the EHR has had variable success for the detection of cardiovascular phenotypes. We hypothesize that the application of text mining algorithms to cardiovascular procedure reports may be a superior method to identify patients with cardiovascular conditions of interest. We adapted the Oracle product Endeca, which utilizes text mining to identify terms of interest from a NoSQL-like database, for purposes of searching cardiovascular procedure reports and termed the tool "PennSeek". We imported 282,569 echocardiography reports representing 81,164 individuals and 27,205 cardiac catheterization reports representing 14,567 individuals from non-searchable databases into PennSeek. We then applied clinical criteria to these reports in PennSeek to identify patients with trileaflet aortic stenosis (TAS) and coronary artery disease (CAD). Accuracy of patient identification by text mining through PennSeek was compared with ICD-9 billing codes. Text mining identified 7115 patients with TAS and 9247 patients with CAD. ICD-9 codes identified 8272 patients with TAS and 6913 patients with CAD. 4346 patients with AS and 6024 patients with CAD were identified by both approaches. A randomly selected sample of 200-250 patients uniquely identified by text mining was compared with 200-250 patients uniquely identified by billing codes for both diseases. We demonstrate that text mining was superior, with a positive predictive value (PPV) of 0.95 compared to 0.53 by ICD-9 for TAS, and a PPV of 0.97 compared to 0.86 for CAD. These results highlight the superiority of text mining algorithms applied to electronic cardiovascular procedure reports in the identification of phenotypes of interest for cardiovascular research. Copyright © 2017. Published by Elsevier Inc.

Remediation and rehabilitation of abandoned mining sites in Cyprus

NASA Astrophysics Data System (ADS)

Helsen, S.; Rommens, T.; De Ridder, A.; Panayiotou, C.; Colpaert, J.

2009-04-01

Due to a particular geological setting, Cyprus is rich in ore deposits, many of them subject to extensive mining. Most of the mines have a long history, sometimes dating back to prehistorical times. These abandoned mines cause severe off-site environmental problems and health risks for the local population. Groundwater supplies are affected by the leaching of pollutants, surface water is contaminated because of water erosion, and harmful dust containing heavy metals or asbestos is spread due to wind erosion. In addition to the environmental risks associated with the abandoned mines, many of these sites are aestethically unattractive, and remain an economic burden to stakeholders and the public in general, due to the downgrading of surrounding areas, non-development and hence loss of revenue. These factors are important in Cyprus where tourism is a significant source of income for local communities. An EUREKA-project addresses the issue of abandoned mine clean-up and restoration. The main objectives of this study are : (1) To develop phytostabilization and -remediation techniques to stabilize and clean up sites characterized by high nickel and copper concentrations in the soil, using endemic plants (Alyssum spp. and mycorrhizal Pinus brutia). In some old mines, efforts were already made to stabilize slopes in an attempt to minimize soil erosion and spreading of pollutants. These restoration efforts, however, remained largely unsuccessful because vegetation that was planted could not cope with the harsh hydrogeochemical soil characteristics. Regeneration of the vegetation cover therefore failed ; (2) to demonstrate the risks associated to the environmental hazard of metal polluted mine spoils and outline a method by which to accomplish this type of risk assessment ; (3) to analyse costs and benefits of phytostabilization- and phytoremediation-based solution for the problem. Results of the first experiments are still preliminary and incomplete. However, it is expected that a better knowledge on growing conditions of the selected plant species will contribute to the development of a phytoremediation technique for a low-cost and sustainable restoration of the old mine sites. Moreover, this will have direct utility to other areas in the Mediterranean region, that are similarly threatened by the presence of heavy metals in the environment.

Occupational Exposures and Lung Cancer Risk among Minnesota Taconite Mining Workers

PubMed Central

Allen, Elizabeth M; Alexander, Bruce H; MacLehose, Richard F; Nelson, Heather H; Ryan, Andrew D; Ramachandran, Gurumurthy; Mandel, Jeffrey H

2015-01-01

Objective To examine the association between employment duration, elongate mineral particle (EMP) exposure, and silica exposure and the risk of lung cancer in the taconite mining industry. Methods We conducted a nested case control study of lung cancer within a cohort of Minnesota taconite iron mining workers employed by any of the mining companies in operation in 1983. Lung cancer cases were identified by vital records and cancer registry data through 2010. Two age-matched controls were selected from risk sets of cohort members alive and lung cancer free at the time of case diagnosis. Calendar time-specific exposure estimates were made for every job and were used to estimate workers’ cumulative exposures. Odds ratios (OR) and 95% confidence intervals (CI) were estimated using conditional logistic regression. We evaluated total lung cancer risk and risk of histological subtype by total work duration and by cumulative EMP and silica exposure by quartile of the exposure distribution. Results A total of 1,706 cases and 3,381 controls were included in the analysis. After adjusting for work in hematite mining, asbestos exposure, and sex, the OR for total duration of employment was 0.99 (95% CI: 0.96–1.01). The ORs for quartile 4 versus 1 of EMP and silica exposure were 0.82 (95% CI: 0.57–1.19) and 0.97 (95% CI: 0.70–1.35) respectively. The risk of each histological subtype of lung cancer did not change with increasing exposure. Conclusions This study suggests that the estimated taconite mining exposures do not increase the risk for the development of lung cancer. PMID:25977445

Factors associated with health-related quality of life among Indian women in mining and agriculture

PubMed Central

2013-01-01

Background Women facing social and economic disadvantage in stressed communities of developing countries are at greater risk due to health problems. This paper investigates the relationships between structural, health and psychosocial predictors among women in mining and agricultural communities. This paper is a report of a study of the predictors of the health-related quality of life among Indian women in mining and agricultural communities. Methods A descriptive cross-sectional research design was used. The instruments used are SF-36 Health Survey and Coping Strategy Checklist. ANOVA, MANOVA and GLM were used in the analysis. The study was conducted between January-September 2008 with randomly selected women in a mining (145) and an agricultural community (133) in India. Results Women in the agricultural community had significantly increased Physical Health, Mental Health and SF36 scores compared with those in the mining community. Years of stay, education and employment were significant predictors among women in the agricultural community. 39% (33%) and 40% (26%) of the variance in Physical and Mental health respectively among women in agricultural and mining communities are predicted by the structural, health and psychosocial variables. Conclusion Perceived health status should be recognised as an important assessment of Physical and Mental Health among women in rural stressed communities. Cognitive, emotional and behavioural coping strategies are significant predictors of health related quality of life. Implications. Nurses should use the SF-36 as a diagnostic tool for assessing health related quality of life among women and discuss coping strategies, so that these can target women’s adaptive behaviour. This should be an essential part of the nursing process for facilitating adaptive process for improved health related quality of life. PMID:23336256

Factors associated with severe occupational injuries at mining company in Zimbabwe, 2010: a cross-sectional study

PubMed Central

Chimamise, Chipo; Gombe, Notion Tafara; Tshimanga, Mufuta; Chadambuka, Addmore; Shambira, Gerald; Chimusoro, Anderson

2013-01-01

Introduction Injury rate among mining workers in Zimbabwe was 789/1000 workers in 2008. The proportion of severe occupational injuries increased from 18% in 2008 to 37% in 2009. We investigated factors associated with severe injuries at the mine. Methods An unmatched 1:1 case-control study was carried out at the mine, a case was any worker who suffered severe occupational injury at the mine and was treated at the mine or district hospital from January 2008 to April 2010, a control was any worker who did not suffer occupational injury during same period. We randomly selected 156 cases and 156 controls and used interviewer administered questionnaires to collect data from participants. Results Majority of cases, 155(99.4%) and of controls 142(91%) were male, 127(81.4%) of cases and 48(30.8%) of controls worked underground. Majority (73.1%) of severe occupational injuries occurred during night shift. Underground temperatures reached 500C. Factors independently associated with getting severe occupational injuries included working underground (AOR = 10.55; CI 5.97-18.65), having targets per shift (AOR = 12.60; CI 3.46-45.84), inadequate PPE (AOR= 3.65 CI 1.34-9.89) and working more than 8 hours per shift (AOR = 8.65 CI 2.99-25.02). Conclusion Having targets exerts pressure to perform on workers. Prolonged working periods decrease workers’ attention and concentration resulting in increased risk to severe injuries as workers become exhausted, lose focus and alertness. Underground work environment had environmental hazards so managers to install adequate ventilation and provide adequate PPE. Management agreed to standardize shifts to eight hours and workers in some departments have been supplied with adequate PPE. PMID:23504270

Challenges in recovering resources from acid mine drainage

USGS Publications Warehouse

Nordstrom, D. Kirk; Bowell, Robert J.; Campbell, Kate M.; Alpers, Charles N.

2017-01-01

Metal recovery from mine waters and effluents is not a new approach but one that has occurred largely opportunistically over the last four millennia. Due to the need for low-cost resources and increasingly stringent environmental conditions, mine waters are being considered in a fresh light with a designed, deliberate approach to resource recovery often as part of a larger water treatment evaluation. Mine water chemistry is highly dependent on many factors including geology, ore deposit composition and mineralogy, mining methods, climate, site hydrology, and others. Mine waters are typically Ca-Mg-SO4±Al±Fe with a broad range in pH and metal content. The main issue in recovering components of these waters having potential economic value, such as base metals or rare earth elements, is the separation of these from more reactive metals such as Fe and Al. Broad categories of methods for separating and extracting substances from acidic mine drainage are chemical and biological. Chemical methods include solution, physicochemical, and electrochemical technologies. Advances in membrane techniques such as reverse osmosis have been substantial and the technique is both physical and chemical. Biological methods may be further divided into microbiological and macrobiological, but only the former is considered here as a recovery method, as the latter is typically used as a passive form of water treatment.

Helium mining on the Moon: Site selection and evaluation

NASA Technical Reports Server (NTRS)

Cameron, Eugene N.

1992-01-01

The feasibility of recovering helium (He) from the Moon as a source of fusion energy on Earth is currently being studied at the University of Wisconsin. Part of this study is selection and evaluation of potential sites for lunar He mining. Selection and evaluation of potential mining sites are based on four salient findings by various investigators of lunar samples: (1) Regoliths from areas underlain by highland materials contain less than 20 wppm He; (2) Certain maria regoliths contain less than 20 wppm He, but other contain 25 to 49 wppm; (3) The He content of a mare regolith is a function of its composition; regoliths rich in Ti are relatively rich in He; and (4) He is concentrated in the less than 100-micron size fractions of regoliths. The first three findings suggest that maria are the most promising mining sites, specifically, those that have high-Ti regoliths. Information on the regional distribution and extent of high-Ti regoliths comes mainly from two sources: direct sampling by various Apollo and Luna missions, and remote sensing by gamma-ray spectroscopy and Earth-based measurements of lunar spectral reflectance. Sampling provides essential control on calibration and interpretation of data from remote sensing. These data indicate that Mare Tranquillitatis is the principal area of high-Ti regolith of the eastern nearside, but large areas of high-Ti regolith are indicated in the Imbrium and Procellarum regions. Recovery of significant amounts of He-3 will require mining billions of tonnes of regolith. Large individual areas suitable for mining must therefore be delineated. The concentration of He in the finer size fractions and considerations of ease of mining mean that mining areas must be as free as possible of sizable craters and blocks of rock. Pending additional lunar missions, information regarding these features must be obtained from lunar photographs, photogeologic maps, and radar surveys. The present study is decidedly preliminary; available information is much to limited to permit even a close approach to final evaluations. As a prelude to recovery of He from the Moon, systematic exploration and sampling of high-Ti regoliths should therefore have a high priority in future lunar missions.

Learning Behavior Characterization with Multi-Feature, Hierarchical Activity Sequences

ERIC Educational Resources Information Center

Ye, Cheng; Segedy, James R.; Kinnebrew, John S.; Biswas, Gautam

2015-01-01

This paper discusses Multi-Feature Hierarchical Sequential Pattern Mining, MFH-SPAM, a novel algorithm that efficiently extracts patterns from students' learning activity sequences. This algorithm extends an existing sequential pattern mining algorithm by dynamically selecting the level of specificity for hierarchically-defined features…

Directed Selection of Biochars for Amending Metal Contaminated Mine Soils

EPA Science Inventory

Approximately 500,000 abandoned mines across the U.S. pose a considerable, pervasive risk to human health and the environment. World-wide the problem is even larger. Lime, organic matter, biosolids and other amendments have been used to decrease metal bioavailability in contami...

Automatic photointerpretation for land use management in Minnesota

NASA Technical Reports Server (NTRS)

Swanlund, G. D. (Principal Investigator); Pile, D. R.

1973-01-01

The author has identified the following significant results. The Minnesota Iron Range area was selected as one of the land use areas to be evaluated. Six classes were selected: (1) hardwood; (2) conifer; (3) water (including in mines); (4) mines, tailings and wet areas; (5) open area; and (6) urban. Initial classification results show a correct classification of 70.1 to 95.4% for the six classes. This is extremely good. It can be further improved since there were some incorrect classifications in the ground truth.

Rehabilitation of lands mined for limestone in the Indian desert

USGS Publications Warehouse

Sharma, K.D.; Kumar, S.; Gough, L.P.

2000-01-01

In the Indian desert, the economics of mining is second only to agriculture in importance. However, research on the rehabilitation of land disturbed by mining has only recently received serious attention. An attempt has been made to determine both the qualitative and quantitative success of rehabilitation plans used to revegetate limestone mine spoils in an area near Barna, northwest arid India. Rehabilitation success was achieved using a combination of rainwater harvesting techniques, soil amendment application approaches, plant establishment methods and the selection of appropriate germplasm material (trees, shrubs and grasses). It is expected that the resulting vegetative cover will be capable of self-perpetuation under natural conditions while at the same time meeting the land-use needs of the local people. The minespoils have adequate levels of the major nutrients (except P, Mo and Se) for proper plant and grazing animal health. Levels of organic matter are low whereas total B concentrations are exceptionally high. Also, the population of soil fungi, Azotobactor, and nitrifying bacteria is negligible. Enhanced plant growth was achieved in treated plots, compared to control plots, where spoil moisture storage was improved by 5-45 per cent. Due to the decomposition of farmyard manure and nitrogen fixation by planted leguminous plant species, the electrical conductance of treated mine spoils increased threefold, CaCO3 content decreased from 20??0 to 5??2 per cent, and organic carbon, P, K, and biological activity increased significantly. The rehabilitation protocol used at the site appears to have been successful because plant self-regeneration is occurring. The increased diversity of woody perennials resulted in 'dominance' being better shared among species and 'evenness' being increased within the plant community elements. The early to mid-successional trends are continuing for six years following initial rehabilitation. This study developed methods for the rehabilitation of lands mined for limestone and has also resulted in an understanding of rehabilitation processes in arid regions with an emphasis on the long-term monitoring of rehabilitation success. Copyright ?? 2000 John Wiley & Sons, Ltd.

Knowledge modeling of coal mining equipments based on ontology

NASA Astrophysics Data System (ADS)

Zhang, Baolong; Wang, Xiangqian; Li, Huizong; Jiang, Miaomiao

2017-06-01

The problems of information redundancy and sharing are universe in coal mining equipment management. In order to improve the using efficiency of knowledge of coal mining equipments, this paper proposed a new method of knowledge modeling based on ontology. On the basis of analyzing the structures and internal relations of coal mining equipment knowledge, taking OWL as ontology construct language, the ontology model of coal mining equipment knowledge is built with the help of Protégé 4.3 software tools. The knowledge description method will lay the foundation for the high effective knowledge management and sharing, which is very significant for improving the production management level of coal mining enterprises.

Spectral methods to detect surface mines

NASA Astrophysics Data System (ADS)

Winter, Edwin M.; Schatten Silvious, Miranda

2008-04-01

Over the past five years, advances have been made in the spectral detection of surface mines under minefield detection programs at the U. S. Army RDECOM CERDEC Night Vision and Electronic Sensors Directorate (NVESD). The problem of detecting surface land mines ranges from the relatively simple, the detection of large anti-vehicle mines on bare soil, to the very difficult, the detection of anti-personnel mines in thick vegetation. While spatial and spectral approaches can be applied to the detection of surface mines, spatial-only detection requires many pixels-on-target such that the mine is actually imaged and shape-based features can be exploited. This method is unreliable in vegetated areas because only part of the mine may be exposed, while spectral detection is possible without the mine being resolved. At NVESD, hyperspectral and multi-spectral sensors throughout the reflection and thermal spectral regimes have been applied to the mine detection problem. Data has been collected on mines in forest and desert regions and algorithms have been developed both to detect the mines as anomalies and to detect the mines based on their spectral signature. In addition to the detection of individual mines, algorithms have been developed to exploit the similarities of mines in a minefield to improve their detection probability. In this paper, the types of spectral data collected over the past five years will be summarized along with the advances in algorithm development.

North American Bats and Mines Project: A cooperative approach for integrating bat conservation and mine-land reclamation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ducummon, S.L.

Inactive underground mines now provide essential habitat for more than half of North America`s 44 bat species, including some of the largest remaining populations. Thousands of abandoned mines have already been closed or are slated for safety closures, and many are destroyed during renewed mining in historic districts. The available evidence suggests that millions of bats have already been lost due to these closures. Bats are primary predators of night-flying insects that cost American farmers and foresters billions of dollars annually, therefore, threats to bat survival are cause for serious concern. Fortunately, mine closure methods exist that protect both batsmore » and humans. Bat Conservation International (BCI) and the USDI-Bureau of Land Management founded the North American Bats and Mines Project to provide national leadership and coordination to minimize the loss of mine-roosting bats. This partnership has involved federal and state mine-land and wildlife managers and the mining industry. BCI has trained hundreds of mine-land and wildlife managers nationwide in mine assessment techniques for bats and bat-compatible closure methods, published technical information on bats and mine-land management, presented papers on bats and mines at national mining and wildlife conferences, and collaborated with numerous federal, state, and private partners to protect some of the most important mine-roosting bat populations. Our new mining industry initiative, Mining for Habitat, is designed to develop bat habitat conservation and enhancement plans for active mining operations. It includes the creation of cost-effective artificial underground bat roosts using surplus mining materials such as old mine-truck tires and culverts buried beneath waste rock.« less

New directions in biomedical text annotation: definitions, guidelines and corpus construction

PubMed Central

Wilbur, W John; Rzhetsky, Andrey; Shatkay, Hagit

2006-01-01

Background While biomedical text mining is emerging as an important research area, practical results have proven difficult to achieve. We believe that an important first step towards more accurate text-mining lies in the ability to identify and characterize text that satisfies various types of information needs. We report here the results of our inquiry into properties of scientific text that have sufficient generality to transcend the confines of a narrow subject area, while supporting practical mining of text for factual information. Our ultimate goal is to annotate a significant corpus of biomedical text and train machine learning methods to automatically categorize such text along certain dimensions that we have defined. Results We have identified five qualitative dimensions that we believe characterize a broad range of scientific sentences, and are therefore useful for supporting a general approach to text-mining: focus, polarity, certainty, evidence, and directionality. We define these dimensions and describe the guidelines we have developed for annotating text with regard to them. To examine the effectiveness of the guidelines, twelve annotators independently annotated the same set of 101 sentences that were randomly selected from current biomedical periodicals. Analysis of these annotations shows 70–80% inter-annotator agreement, suggesting that our guidelines indeed present a well-defined, executable and reproducible task. Conclusion We present our guidelines defining a text annotation task, along with annotation results from multiple independently produced annotations, demonstrating the feasibility of the task. The annotation of a very large corpus of documents along these guidelines is currently ongoing. These annotations form the basis for the categorization of text along multiple dimensions, to support viable text mining for experimental results, methodology statements, and other forms of information. We are currently developing machine learning methods, to be trained and tested on the annotated corpus, that would allow for the automatic categorization of biomedical text along the general dimensions that we have presented. The guidelines in full detail, along with annotated examples, are publicly available. PMID:16867190

Effects of underground mining and mine collapse on the hydrology of selected basins in West Virginia

USGS Publications Warehouse

Hobba, William A.

1993-01-01

The effects of underground mining and mine collapse on areal hydrology were determined at one site where the mined bed of coal lies above major streams and at two sites where the bed of coal lies below major streams. Subsidence cracks observed at land surface generally run parallel to predominant joint sets in the rocks. The mining and subsidence cracks increase hydraulic conductivity and interconnection of water-bearing rock units, which in turn cause increased infiltration of precipitation and surface water, decreased evapotranspiration, and higher base flows in some small streams. Water levels in observation wells in mined areas fluctuate as much as 100 ft annually. Both gaining and losing streams are found in mined areas. Mine pumpage and drainage can cause diversion of water underground from one basin to another. Areal and single-well aquifer tests indicated that near-surface rocks have higher transmissivity in a mine-subsided basin than in unmined basins. Increased infiltration and circulation through shallow subsurface rocks increase dissolved mineral loads in streams, as do treated and untreated contributions from mine pumpage and drainage. Abandoned and flooded underground mines make good reservoirs because of their increased transmissivity and storage. Subsidence cracks were not detectable by thermal imagery, but springs and seeps were detectable.

Combined mine tremors source location and error evaluation in the Lubin Copper Mine (Poland)

NASA Astrophysics Data System (ADS)

Leśniak, Andrzej; Pszczoła, Grzegorz

2008-08-01

A modified method of mine tremors location used in Lubin Copper Mine is presented in the paper. In mines where an intensive exploration is carried out a high accuracy source location technique is usually required. The effect of the flatness of the geophones array, complex geological structure of the rock mass and intense exploitation make the location results ambiguous in such mines. In the present paper an effective method of source location and location's error evaluations are presented, combining data from two different arrays of geophones. The first consists of uniaxial geophones spaced in the whole mine area. The second is installed in one of the mining panels and consists of triaxial geophones. The usage of the data obtained from triaxial geophones allows to increase the hypocenter vertical coordinate precision. The presented two-step location procedure combines standard location methods: P-waves directions and P-waves arrival times. Using computer simulations the efficiency of the created algorithm was tested. The designed algorithm is fully non-linear and was tested on the multilayered rock mass model of the Lubin Copper Mine, showing a computational better efficiency than the traditional P-wave arrival times location algorithm. In this paper we present the complete procedure that effectively solves the non-linear location problems, i.e. the mine tremor location and measurement of the error propagation.

Noise-based body-wave seismic tomography in an active underground mine.

NASA Astrophysics Data System (ADS)

Olivier, G.; Brenguier, F.; Campillo, M.; Lynch, R.; Roux, P.

2014-12-01

Over the last decade, ambient noise tomography has become increasingly popular to image the earth's upper crust. The seismic noise recorded in the earth's crust is dominated by surface waves emanating from the interaction of the ocean with the solid earth. These surface waves are low frequency in nature ( < 1 Hz) and not usable for imaging smaller structures associated with mining or oil and gas applications. The seismic noise recorded at higher frequencies are typically from anthropogenic sources, which are short lived, spatially unstable and not well suited for constructing seismic Green's functions between sensors with conventional cross-correlation methods. To examine the use of ambient noise tomography for smaller scale applications, continuous data were recorded for 5 months in an active underground mine in Sweden located more than 1km below surface with 18 high frequency seismic sensors. A wide variety of broadband (10 - 3000 Hz) seismic noise sources are present in an active underground mine ranging from drilling, scraping, trucks, ore crushers and ventilation fans. Some of these sources generate favorable seismic noise, while others are peaked in frequency and not usable. In this presentation, I will show that the noise generated by mining activity can be useful if periods of seismic noise are carefully selected. Although noise sources are not temporally stable and not evenly distributed around the sensor array, good estimates of the seismic Green's functions between sensors can be retrieved for a broad frequency range (20 - 400 Hz) when a selective stacking scheme is used. For frequencies below 100 Hz, the reconstructed Green's functions show clear body-wave arrivals for almost all of the 153 sensor pairs. The arrival times of these body-waves are picked and used to image the local velocity structure. The resulting 3-dimensional image shows a high velocity structure that overlaps with a known ore-body. The material properties of the ore-body differ from the host rock and is likely the cause of the observed high velocity structure. For frequencies above 200 Hz, the seismic waves are multiply scattered by the tunnels and excavations and used to determine the scattering properties of the medium. The results of this study should be useful for future imaging and exploration projects in mining and oil and gas industries.

Effects of Occupational Education Programs Offered by the Oklahoma Department of Career and Technology Education, Skills Centers Division, on the Recidivism Rate of Selected Groups of Released Offenders in Oklahoma

ERIC Educational Resources Information Center

Ely, Joseph William

2012-01-01

Scope and Method of Study: The purpose of this study was to describe the effects of career and technical education (CTE) on recidivism for offenders enrolled in the Oklahoma Department of Corrections CareerTech Skills Center School Systems (SCSS) programs. Specifically, the study mined existing CareerTech and ODOC data to: (a) compare the…

Combination of minimum enclosing balls classifier with SVM in coal-rock recognition.

PubMed

Song, QingJun; Jiang, HaiYan; Song, Qinghui; Zhao, XieGuang; Wu, Xiaoxuan

2017-01-01

Top-coal caving technology is a productive and efficient method in modern mechanized coal mining, the study of coal-rock recognition is key to realizing automation in comprehensive mechanized coal mining. In this paper we propose a new discriminant analysis framework for coal-rock recognition. In the framework, a data acquisition model with vibration and acoustic signals is designed and the caving dataset with 10 feature variables and three classes is got. And the perfect combination of feature variables can be automatically decided by using the multi-class F-score (MF-Score) feature selection. In terms of nonlinear mapping in real-world optimization problem, an effective minimum enclosing ball (MEB) algorithm plus Support vector machine (SVM) is proposed for rapid detection of coal-rock in the caving process. In particular, we illustrate how to construct MEB-SVM classifier in coal-rock recognition which exhibit inherently complex distribution data. The proposed method is examined on UCI data sets and the caving dataset, and compared with some new excellent SVM classifiers. We conduct experiments with accuracy and Friedman test for comparison of more classifiers over multiple on the UCI data sets. Experimental results demonstrate that the proposed algorithm has good robustness and generalization ability. The results of experiments on the caving dataset show the better performance which leads to a promising feature selection and multi-class recognition in coal-rock recognition.

Combination of minimum enclosing balls classifier with SVM in coal-rock recognition

PubMed Central

Song, QingJun; Jiang, HaiYan; Song, Qinghui; Zhao, XieGuang; Wu, Xiaoxuan

2017-01-01

Top-coal caving technology is a productive and efficient method in modern mechanized coal mining, the study of coal-rock recognition is key to realizing automation in comprehensive mechanized coal mining. In this paper we propose a new discriminant analysis framework for coal-rock recognition. In the framework, a data acquisition model with vibration and acoustic signals is designed and the caving dataset with 10 feature variables and three classes is got. And the perfect combination of feature variables can be automatically decided by using the multi-class F-score (MF-Score) feature selection. In terms of nonlinear mapping in real-world optimization problem, an effective minimum enclosing ball (MEB) algorithm plus Support vector machine (SVM) is proposed for rapid detection of coal-rock in the caving process. In particular, we illustrate how to construct MEB-SVM classifier in coal-rock recognition which exhibit inherently complex distribution data. The proposed method is examined on UCI data sets and the caving dataset, and compared with some new excellent SVM classifiers. We conduct experiments with accuracy and Friedman test for comparison of more classifiers over multiple on the UCI data sets. Experimental results demonstrate that the proposed algorithm has good robustness and generalization ability. The results of experiments on the caving dataset show the better performance which leads to a promising feature selection and multi-class recognition in coal-rock recognition. PMID:28937987

Elaboration of the Charge Constructions of Explosives for the Structure of Facing Stone

NASA Astrophysics Data System (ADS)

Khomeriki, Sergo; Mataradze, Edgar; Chikhradze, Nikoloz; Losaberidze, Marine; Khomeriki, Davit; Shatberashvili, Grigol

2017-12-01

Increased demand for high-strength facing material caused the enhancement of the volume of explosives use in modern technologies of blocks production. The volume of broken rocks and crushing quality depends on the rock characteristics and on the properties of the explosive, in particular on its brisance and serviceability. Therefore, the correct selection of the explosive for the specific massif is of a considerable practical importance. For efficient mining of facing materials by explosion method the solving of such problems as determination of the method of blasthole drilling as well as of the regime and charge values, selection of the explosive, blastholes distribution in the face and their order is necessary. This paper focuses on technical solutions for conservation of rock natural structure in the blocks of facing material, mined by the use of the explosives. It has been established that the efficient solving of mentioned problem is attained by reducing of shock pulse duration. In such conditions the rigidity of crystalline lattice increases in high pressure area. As a result, the hazard if crack formation in structural unites and the increases of natural cracks are excluded. Short-time action of explosion pulse is possible only by linear charges of the explosives, characterized by high detonation velocity which detonate by the velocity of 7-7.5 km/sec and are characterized by very small critical diameter.

Air quality assessment on human well-being in the vicinity of quarry site

NASA Astrophysics Data System (ADS)

Ibrahim, W. H. W.; Marinie, E.; Yunus, J.; Asra, N.; Sukor, K. Mohd

2018-02-01

This study aims to investigate the variation of air pollutants associated with the quarry activities prior to classified distance from quarry site. Air pollutants were monitored with the use of instruments which are Rae System Multirae Lite Pumped (PGM-6208) to measure indoor air quality while TSI 8533 Dusttrack Drx Desktop Aerosol Monitor to measure outdoor air quality. Sampling will be replicated two times. The locations of quarry are at Bandar Saujana Putra and Taman Kajang Perdana 2, Selangor. The objectives of this study are to investigate the impact of quarry mining by preparing the suitable Indoor Air Quality Index and to prepare preventive measure for residential that caused from quarry mining activities. Both Qualitative and Quantitative approaches will be implemented in this study, which employed case study and interview survey. Both quarries identified previously will be the main case study. The Respondent’s interviews are from Local Authority and Quarry Management Staff while questionnaire surveys from selected residences. Measurement method will be used to measure the Particle Matter (PM2.5) for indoor and outdoor in selected resident’s area. However, this paper is primed to discuss the method used in this study. It is not only presents the beneficial information for future research on methodologies employed but also it is anticipated the benefit to environment which can increased residents’ well-being in the vicinity of quarry sites.

A proposed framework on hybrid feature selection techniques for handling high dimensional educational data

NASA Astrophysics Data System (ADS)

Shahiri, Amirah Mohamed; Husain, Wahidah; Rashid, Nur'Aini Abd

2017-10-01

Huge amounts of data in educational datasets may cause the problem in producing quality data. Recently, data mining approach are increasingly used by educational data mining researchers for analyzing the data patterns. However, many research studies have concentrated on selecting suitable learning algorithms instead of performing feature selection process. As a result, these data has problem with computational complexity and spend longer computational time for classification. The main objective of this research is to provide an overview of feature selection techniques that have been used to analyze the most significant features. Then, this research will propose a framework to improve the quality of students' dataset. The proposed framework uses filter and wrapper based technique to support prediction process in future study.

Method for Location of An External Dump in Surface Mining Using the A-Star Algorithm

NASA Astrophysics Data System (ADS)

Zajączkowski, Maciej; Kasztelewicz, Zbigniew; Sikora, Mateusz

2014-10-01

The construction of a surface mine always involves the necessity of accessing deposits through the removal of the residual overburden above. In the beginning phase of exploitation, the masses of overburden are located outside the perimeters of the excavation site, on the external dump, until the moment of internal dumping. In the case of lignite surface mines, these dumps can cover a ground surface of several dozen to a few thousand hectares. This results from a high concentration of lignite extraction, counted in millions of Mg per year, and the relatively large depth of its residual deposits. Determining the best place for the location of an external dump requires a detailed analysis of existing options, followed by a choice of the most favorable one. This article, using the case study of an open-cast lignite mine, presents the selection method for an external dump location based on graph theory and the A-star algorithm. This algorithm, based on the spatial distribution of individual intersections on the graph, seeks specified graph states, continually expanding them with additional elementary fields until the required surface area for the external dump - defined by the lowest value of the occupied site - is achieved. To do this, it is necessary to accurately identify the factors affecting the choice of dump location. On such a basis, it is then possible to specify the target function, which reflects the individual costs of dump construction on a given site. This is discussed further in chapter 3. The area of potential dump location has been divided into elementary fields, each represented by a corresponding geometrical locus. Ascribed to this locus, in addition to its geodesic coordinates, are the appropriate attributes reflecting the degree of development of its elementary field. These tasks can be carried out automatically thanks to the integration of the method with the system of geospatial data management for the given area. The collection of loci, together with geodesic coordinates, constitutes the points on the graph used during exploration. This is done using the A-star algorithm, which uses a heuristic function, allowing it to identify the optimal solution; therefore, the collection of elementary fields, which occupy the potential construction area of a dump, characterized by the lowest value representing the cost of occupation and dumping of overburden in the area. The precision of the boundary, generated by the algorithm, is dependent on the established size of the elementary field, and should be refined each time by the designer of the surface mine. This article presents the application of the above method of dump location using the example of "Tomisławice," a lignite surface mine owned by PAK KWB Konin S. A. The method made it possible to identify the most favorable dump location on the northeast side of the initial pit, within 2 kilometers of its surrounding area (discussed further in chapter 3). This method is universal in nature and, after certain modifications, can be implemented for other surface mines as well.

30 CFR 75.215 - Longwall mining systems.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Longwall mining systems. 75.215 Section 75.215... MANDATORY SAFETY STANDARDS-UNDERGROUND COAL MINES Roof Support § 75.215 Longwall mining systems. For each longwall mining section, the roof control plan shall specify— (a) The methods that will be used to maintain...

30 CFR 75.215 - Longwall mining systems.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 1 2011-07-01 2011-07-01 false Longwall mining systems. 75.215 Section 75.215... MANDATORY SAFETY STANDARDS-UNDERGROUND COAL MINES Roof Support § 75.215 Longwall mining systems. For each longwall mining section, the roof control plan shall specify— (a) The methods that will be used to maintain...

A watershed-scale approach to tracing metal contamination in the environment

USGS Publications Warehouse

Church, Stanley E

1996-01-01

IntroductionPublic policy during the 1800's encouraged mining in the western United States. Mining on Federal lands played an important role in the growing economy creating national wealth from our abundant and diverse mineral resource base. The common industrial practice from the early days of mining through about 1970 in the U.S. was for mine operators to dispose of the mine wastes and mill tailings in the nearest stream reach or lake. As a result of this contamination, many stream reaches below old mines, mills, and mining districts and some major rivers and lakes no longer support aquatic life. Riparian habitats within these affected watersheds have also been impacted. Often, the water from these affected stream reaches is generally not suitable for drinking, creating a public health hazard. The recent Department of Interior Abandoned Mine Lands (AML) Initiative is an effort on the part of the Federal Government to address the adverse environmental impact of these past mining practices on Federal lands. The AML Initiative has adopted a watershed approach to determine those sites that contribute the majority of the contaminants in the watershed. By remediating the largest sources of contamination within the watershed, the impact of metal contamination in the environment within the watershed as a whole is reduced rather than focusing largely on those sites for which principal responsible parties can be found.The scope of the problem of metal contamination in the environment from past mining practices in the coterminous U.S. is addressed in a recent report by Ferderer (1996). Using the USGS1:2,000,000-scale hydrologic drainage basin boundaries and the USGS Minerals Availability System (MAS) data base, he plotted the distribution of 48,000 past-producing metal mines on maps showing the boundaries of lands administered by the various Federal Land Management Agencies (FLMA). Census analysis of these data provided an initial screening tool for prioritization of watersheds in the western U.S. A different approach to the scope of the abandoned mine problem (Church et al., 1996a) is shown by the water quality data collected by the States under the Clean Water Act, section 305(b). These data document the stream reaches affected by metals from naturally occurring sources as well as from mining, or mineral resource extraction. Permitted discharges from active industrial and mine sites are not covered in the 305(b) data base.Local citizens and state and federal agencies are all part of the collaborative decision process used to select the drainage basins chosen for the AML Initiative pilot studies. Data gathered by these three entities were brought to bear on the watershed selection process. The USGS prepared data available from Federal data bases in the form of interpretative GIS products. Maps of the states of Colorado (Plumlee et al., 1995) and a similar study of the state of Montana (USGS, unpublished data) were used to select the Animas watershed in southwestern Colorado and the Boulder watershed southwest of Helena Montana as the pilot study areas for the AML Initiative. Thus, the watersheds selected for study were public decisions made on the basis of available scientific data. The role of the U.S. Geological Survey in the Abandoned Mine Land Initiative is outlined in Buxton et al. (1997).The watershed approach to metals contamination in the environment has been studied in several drainage basins (Church et al., 1993, 1994, 1995, 1996b; Kimball et al., 1995). The underlying principles used to successfully discriminate between sources and to quantify the impact of these sources on the environment are the subject of this report.

Identification of ex-sand mining area using optical and SAR imagery

NASA Astrophysics Data System (ADS)

Indriasari, Novie; Kusratmoko, Eko; Indra, Tito Latif; Julzarika, Atriyon

2018-05-01

Open mining activities in Sumedang Regency has been operated since 1984 impacted to degradation of environment due to large area of ex-mining. Therefore, identification of ex-mining area which generally been used for sand mining is crucial and important to detect and monitor recent environmental degradation impacted from the ex-mining activities. In this research, identification ex-sand mining area using optical and SAR data in Sumedang Regency will be discussed. We use Landsat 5 TM acquisition date August 01, 2009 and Landsat 8 OLI acquired on June 24, 2016 to identify location of sand mining area, processed using Tasselled Cap Trasformation (TCT), while the landform deformation approached using ALOS PALSAR in 2009 and ALOS PALSAR 2 in 2016 processed using SAR interferometry (InSAR) method. The results show that TCT and InSAR method can can be used to identify the areas of ex-sand mining clearly. In 2016 the total area of ex-mining were 352.92 Ha. The land deformation show that during 7 years period since 2009 has impacted to the deformation at 7 meters.

Applying Data Mining Principles to Library Data Collection.

ERIC Educational Resources Information Center

Guenther, Kim

2000-01-01

Explains how libraries can use data mining techniques for more effective data collection. Highlights include three phases: data selection and acquisition; data preparation and processing, including a discussion of the use of XML (extensible markup language); and data interpretation and integration, including database management systems. (LRW)

40 CFR 440.50 - Applicability; description of the titanium ore subcategory.

Code of Federal Regulations, 2010 CFR

2010-07-01

...) mills beneficiating titanium ores by electrostatic methods, magnetic and physical methods, or flotation methods; and (c) mines engaged in the dredge mining of placer deposits of sands containing rutile... methods in conjunction with electrostatic or magnetic methods). ...

Development of Multiscale Biological Image Data Analysis: Review of 2006 International Workshop on Multiscale Biological Imaging, Data Mining and Informatics, Santa Barbara, USA (BII06)

PubMed Central

Auer, Manfred; Peng, Hanchuan; Singh, Ambuj

2007-01-01

The 2006 International Workshop on Multiscale Biological Imaging, Data Mining and Informatics was held at Santa Barbara, on Sept 7–8, 2006. Based on the presentations at the workshop, we selected and compiled this collection of research articles related to novel algorithms and enabling techniques for bio- and biomedical image analysis, mining, visualization, and biology applications. PMID:17634090

[Lead exposure of people living in a lead high exposure area from local diet].

PubMed

Zhou, Yong; He, Liping; Huang, Xiao; He, Junshan

2011-11-01

To study the lead exposure of people living in a lead high exposure area from local diet, and to assess its health risks. Thirty five subjects were selected by random from a mining area and another 30 subjects were selected from a non-polluted area. The exposure of lead was estimated by the content of lead in drinking water and vegetables, and health risks was estimated by the levels of lead in blood and urine. The content of lead in drinking water and vegetables in the mining area was 20.6 microg/L and 1.61mg/kg (geometric mean) respectively, which were higher than that in the unpolluted area (6.0 microg/L and 0.56 mg/kg, geometric mean) (P < 0.01). The daily lead exposure of male and female inhabitants in the mining area from diet was 16.88 microg/kg and 16.09 microg/kg respectively, which was higher than that in the unpolluted area (P < 0.01), but the sex difference was not significant statistically (P > 0.05). Blood lead and urine lead of inhabitants in the mining-area were higher than those in the unpolluted area. The health risks for male and female inhabitants in the mining area were 4.73 and 4.51. The health risks of lead exposure caused by diet (drinking water and food) were relatively high in the mining area.

Geophysical Technologies to Image Old Mine Works

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kanaan Hanna; Jim Pfeiffer

2007-01-15

ZapataEngineering, Blackhawk Division performed geophysical void detection demonstrations for the US Department of Labor Mine Safety and Health Administration (MSHA). The objective was to advance current state-of-practices of geophysical technologies for detecting underground mine voids. The presence of old mine works above, adjacent, or below an active mine presents major health and safety hazards to miners who have inadvertently cut into locations with such features. In addition, the presence of abandoned mines or voids beneath roadways and highway structures may greatly impact the performance of the transportation infrastructure in terms of cost and public safety. Roads constructed over abandoned minesmore » are subject to potential differential settlement, subsidence, sinkholes, and/or catastrophic collapse. Thus, there is a need to utilize geophysical imaging technologies to accurately locate old mine works. Several surface and borehole geophysical imaging methods and mapping techniques were employed at a known abandoned coal mine in eastern Illinois to investigate which method best map the location and extent of old works. These methods included: 1) high-resolution seismic (HRS) using compressional P-wave (HRPW) and S-wave (HRSW) reflection collected with 3-D techniques; 2) crosshole seismic tomography (XHT); 3) guided waves; 4) reverse vertical seismic profiling (RVSP); and 5) borehole sonar mapping. In addition, several exploration borings were drilled to confirm the presence of the imaged mine voids. The results indicated that the RVSP is the most viable method to accurately detect the subsurface voids with horizontal accuracy of two to five feet. This method was then applied at several other locations in Colorado with various topographic, geologic, and cultural settings for the same purpose. This paper presents the significant results obtained from the geophysical investigations in Illinois.« less

Assessment of vegetation establishment on tailings dam at an iron ore mining site of suburban Beijing, China, 7 years after reclamation with contrasting site treatment methods.

PubMed

Yan, Demin; Zhao, Fangying; Sun, Osbert Jianxin

2013-09-01

Strip-mining operations greatly disturb soil, vegetation and landscape elements, causing many ecological and environmental problems. Establishment of vegetation is a critical step in achieving the goal of ecosystem restoration in mining areas. At the Shouyun Iron Ore Mine in suburban Beijing, China, we investigated selective vegetation and soil traits on a tailings dam 7 years after site treatments with three contrasting approaches: (1) soil covering (designated as SC), (2) application of a straw mat, known as "vegetation carpet", which contains prescribed plant seed mix and water retaining agent (designated as VC), on top of sand piles, and (3) combination of soil covering and application of vegetation carpet (designated as SC+VC). We found that after 7 years of reclamation, the SC+VC site had twice the number of plant species and greater biomass than the SC and VC sites, and that the VC site had a comparable plant abundance with the SC+VC site but much less biodiversity and plant coverage. The VC site did not differ with the SC site in the vegetation traits, albeit low soil fertility. It is suggested that application of vegetation carpet can be an alternative to introduction of topsoil for treatment of tailings dam with fine-structured substrate of ore sands. However, combination of topsoil treatment and application of vegetation carpet greatly increases vegetation coverage and plant biodiversity, and is therefore a much better approach for assisting vegetation establishment on the tailings dam of strip-mining operations. While application of vegetation carpet helps to stabilize the loose surface of fine-structured mine wastes and to introduce seed bank, introduction of fertile soil is necessary for supplying nutrients to plant growth in the efforts of ecosystem restoration of mining areas.

Research of land resources comprehensive utilization of coal mining in plain area based on GIS: case of Panyi Coal Mine of Huainan Mining Group Corp.

NASA Astrophysics Data System (ADS)

Dai, Chunxiao; Wang, Songhui; Sun, Dian; Chen, Dong

2007-06-01

The result of land use in coalfield is important to sustainable development in resourceful city. For surface morphology being changed by subsidence, the mining subsidence becomes the main problem to land use with the negative influence of ecological environment, production and steadily develop in coal mining areas. Taking Panyi Coal Mine of Huainan Mining Group Corp as an example, this paper predicted and simulated the mining subsidence in Matlab environment on the basis of the probability integral method. The change of land use types of early term, medium term and long term was analyzed in accordance with the results of mining subsidence prediction with GIS as a spatial data management and spatial analysis tool. The result of analysis showed that 80% area in Panyi Coal Mine be affected by mining subsidence and 52km2 perennial waterlogged area was gradually formed. The farmland ecosystem was gradually turned into wetland ecosystem in most study area. According to the economic and social development and natural conditions of mining area, calculating the ecological environment, production and people's livelihood, this paper supplied the plan for comprehensive utilization of land resource. In this plan, intervention measures be taken during the coal mining and the mining subsidence formation and development, and this method can solve the problems of Land use at the relative low cost.

Northern bobwhite breeding season ecology on a reclaimed surface mine

USGS Publications Warehouse

Brooke, Jarred M.; Tanner, Evan P.; Peters, David C.; Tanner, Ashley M.; Harper, Craig A.; Keyser, Patrick D.; Clark, Joseph D.; Morgan, John J.

2017-01-01

Surface coal mining and subsequent reclamation of surface mines have converted large forest areas into early successional vegetative communities in the eastern United States. This reclamation can provide a novel opportunity to conserve northern bobwhite (Colinus virginianus). We evaluated the influence of habitat management activities on nest survival, nest-site selection, and brood resource selection on managed and unmanaged units of a reclaimed surface mine, Peabody Wildlife Management Area (Peabody), in west-central Kentucky, USA, from 2010 to 2013. We compared resource selection, using discrete-choice analysis, and nest survival, using the nest survival model in Program MARK, between managed and unmanaged units of Peabody at 2 spatial scales: the composition and configuration of vegetation types (i.e., macrohabitat) and vegetation characteristics at nest sites and brood locations (i.e., microhabitat). On managed sites, we also investigated resource selection relative to a number of different treatments (e.g., herbicide, disking, prescribed fire). We found no evidence that nest-site selection was influenced by macrohabitat variables, but bobwhite selected nest sites in areas with greater litter depth than was available at random sites. On managed units, bobwhite were more likely to nest where herbicide was applied to reduce sericea lespedeza (Lespedeza cuneata) compared with areas untreated with herbicide. Daily nest survival was not influenced by habitat characteristics or by habitat management but was influenced by nest age and the interaction of nest initiation date and nest age. Daily nest survival was greater for older nests occurring early in the breeding season (0.99, SE < 0.01) but was lower for older nests occurring later in the season (0.08, SE = 0.13). Brood resource selection was not influenced by macrohabitat or microhabitat variables we measured, but broods on managed units selected areas treated with herbicide to control sericea lespedeza and were located closer to firebreaks and disked native-warm season grass stands than would be expected at random. Our results suggest the vegetation at Peabody was sufficient without manipulation to support nesting and brood-rearing northern bobwhite at a low level, but habitat management practices improved vegetation for nesting and brood-rearing resource selection. Reproductive rates (e.g., nest survival and re-nesting rates) at Peabody were lower than reported in other studies, which may be related to nutritional deficiencies caused by the abundance of sericea lespedeza. On reclaimed mine lands dominated by sericea lespedeza, we suggest continuing practices such as disking and herbicide application that are targeted at reducing sericea lespedeza to improve the vegetation for nesting and brood-rearing bobwhite.

Graph-based biomedical text summarization: An itemset mining and sentence clustering approach.

PubMed

Nasr Azadani, Mozhgan; Ghadiri, Nasser; Davoodijam, Ensieh

2018-06-12

Automatic text summarization offers an efficient solution to access the ever-growing amounts of both scientific and clinical literature in the biomedical domain by summarizing the source documents while maintaining their most informative contents. In this paper, we propose a novel graph-based summarization method that takes advantage of the domain-specific knowledge and a well-established data mining technique called frequent itemset mining. Our summarizer exploits the Unified Medical Language System (UMLS) to construct a concept-based model of the source document and mapping the document to the concepts. Then, it discovers frequent itemsets to take the correlations among multiple concepts into account. The method uses these correlations to propose a similarity function based on which a represented graph is constructed. The summarizer then employs a minimum spanning tree based clustering algorithm to discover various subthemes of the document. Eventually, it generates the final summary by selecting the most informative and relative sentences from all subthemes within the text. We perform an automatic evaluation over a large number of summaries using the Recall-Oriented Understudy for Gisting Evaluation (ROUGE) metrics. The results demonstrate that the proposed summarization system outperforms various baselines and benchmark approaches. The carried out research suggests that the incorporation of domain-specific knowledge and frequent itemset mining equips the summarization system in a better way to address the informativeness measurement of the sentences. Moreover, clustering the graph nodes (sentences) can enable the summarizer to target different main subthemes of a source document efficiently. The evaluation results show that the proposed approach can significantly improve the performance of the summarization systems in the biomedical domain. Copyright © 2018. Published by Elsevier Inc.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schuman, G.E.; Vicklund, L.E.; Belden, S.E.

In 1996, the Wyoming Department of Environmental Quality enacted regulations governing the reestablishment of woody shrubs on mined lands. The regulation required that an average density of one shrub m{sup -2} be reestablished on at least 20% of the disturbed land area and that the shrub composition must include dominant premine species. In Wyoming, and much of the Northern Great Plains, that meant that Artemisia tridentata Nutt. ssp. wyomingensis (Beetle and Young) (Wyoming big sagebrush) had to be reestablished on mined lands. Artemisia tridentata Nutt. ssp. wyomingensis had proven difficult to reestablish on mined lands because of poor quality seed,more » seed dormancy and a poor understanding of the seedbed ecology of this species. Research in the last two decades has produced significant knowledge in the area of direct-seed establishment of Artemisia tridentata Nutt. ssp. wyomingensis on mined lands. Our research has shown that reducing grass seeding rates will reduce competition and result in larger sagebrush plants that are more likely to survive and provide greater structural diversity to the plant community. Economic analyses demonstrated that big sagebrush can be established at a cost of $0.01-0.05 per seedling using direct seeding methods compared to transplanting nursery grown seedlings, estimated to cost $0.72-$1.65 per seedling (depending on size) to grow and from $1.30-$2.40 to plant (flat land to 2:1 slopes). An adequate level of precipitation will be necessary to ensure successful establishment of this species no matter what method of propagation is selected and direct seeding gives greater opportunity for success because of the demonstrated longevity of the seed to germinate 3-5 years after the initial seeding.« less

A software tool for determination of breast cancer treatment methods using data mining approach.

PubMed

Cakır, Abdülkadir; Demirel, Burçin

2011-12-01

In this work, breast cancer treatment methods are determined using data mining. For this purpose, software is developed to help to oncology doctor for the suggestion of application of the treatment methods about breast cancer patients. 462 breast cancer patient data, obtained from Ankara Oncology Hospital, are used to determine treatment methods for new patients. This dataset is processed with Weka data mining tool. Classification algorithms are applied one by one for this dataset and results are compared to find proper treatment method. Developed software program called as "Treatment Assistant" uses different algorithms (IB1, Multilayer Perception and Decision Table) to find out which one is giving better result for each attribute to predict and by using Java Net beans interface. Treatment methods are determined for the post surgical operation of breast cancer patients using this developed software tool. At modeling step of data mining process, different Weka algorithms are used for output attributes. For hormonotherapy output IB1, for tamoxifen and radiotherapy outputs Multilayer Perceptron and for the chemotherapy output decision table algorithm shows best accuracy performance compare to each other. In conclusion, this work shows that data mining approach can be a useful tool for medical applications particularly at the treatment decision step. Data mining helps to the doctor to decide in a short time.

A Data Mining Approach to Reveal Representative Collaboration Indicators in Open Collaboration Frameworks

ERIC Educational Resources Information Center

Anaya, Antonio R.; Boticario, Jesus G.

2009-01-01

Data mining methods are successful in educational environments to discover new knowledge or learner skills or features. Unfortunately, they have not been used in depth with collaboration. We have developed a scalable data mining method, whose objective is to infer information on the collaboration during the collaboration process in a…

Methods and costs of thin-seam mining. Final report, 25 September 1977-24 January 1979. [Thin seam in association with a thick seam

DOE Office of Scientific and Technical Information (OSTI.GOV)

Finch, T.E.; Fidler, E.L.

1981-02-01

This report defines the state of the art (circa 1978) in removing thin coal seams associated with vastly thicker seams found in the surface coal mines of the western United States. New techniques are evaluated and an innovative method and machine is proposed. Western states resource recovery regulations are addressed and representative mining operations are examined. Thin seam recovery is investigated through its effect on (1) overburden removal, (2) conventional seam extraction methods, and (3) innovative techniques. Equations and graphs are used to accommodate the variable stratigraphic positions in the mining sequence on which thin seams occur. Industrial concern andmore » agency regulations provided the impetus for this study of total resource recovery. The results are a compendium of thin seam removal methods and costs. The work explains how the mining industry recovers thin coal seams in western surface mines where extremely thick seams naturally hold the most attention. It explains what new developments imply and where to look for new improvements and their probable adaptability.« less

Preliminary study of detection of buried landmines using a programmable hyperspectral imager

NASA Astrophysics Data System (ADS)

McFee, John E.; Ripley, Herb T.; Buxton, Roger; Thriscutt, Andrew M.

1996-05-01

Experiments were conducted to determine if buried mines could be detected by measuring the change in reflectance spectra of vegetation above mine burial sites. Mines were laid using hand methods and simulated mechanical methods and spectral images were obtained over a three month period using a casi hyperspectral imager scanned from a personnel lift. Mines were not detectable by measurement of the shift of the red edge of vegetative spectra. By calculating the linear correlation coefficient image, some mines in light vegetative cover (grass, grass/blueberries) were apparently detected, but mines buried in heavy vegetation cover (deep ferns) were not detectable. Due to problems with ground truthing, accurate probabilities of detection and false alarm rates were not obtained.

20 CFR 725.710 - Objective of vocational rehabilitation.

Code of Federal Regulations, 2010 CFR

2010-04-01

... FEDERAL COAL MINE HEALTH AND SAFETY ACT OF 1969, AS AMENDED CLAIMS FOR BENEFITS UNDER PART C OF TITLE IV OF THE FEDERAL MINE SAFETY AND HEALTH ACT, AS AMENDED Medical Benefits and Vocational Rehabilitation...-evaluation and redirection of the miner's abilities, or retraining in another occupation, and selective job...

Selection of basic data for numerical modeling of rock mass stress state at Mirny Mining and Processing Works, Alrosa Group of Companies

NASA Astrophysics Data System (ADS)

Bokiy, IB; Zoteev, OV; Pul, VV; Pul, EK

2018-03-01

The influence of structural features on the strength and elasticity modulus is studied in rock mass in the area of Mirny Mining and Processing Works. The authors make recommendations on the values of physical properties of rocks.

Classification of patients by severity grades during triage in the emergency department using data mining methods.

PubMed

Zmiri, Dror; Shahar, Yuval; Taieb-Maimon, Meirav

2012-04-01

To test the feasibility of classifying emergency department patients into severity grades using data mining methods. Emergency department records of 402 patients were classified into five severity grades by two expert physicians. The Naïve Bayes and C4.5 algorithms were applied to produce classifiers from patient data into severity grades. The classifiers' results over several subsets of the data were compared with the physicians' assessments, with a random classifier, and with a classifier that selects the maximal-prevalence class. Positive predictive value, multiple-class extensions of sensitivity and specificity combinations, and entropy change. The mean accuracy of the data mining classifiers was 52.94 ± 5.89%, significantly better (P < 0.05) than the mean accuracy of a random classifier (34.60 ± 2.40%). The entropy of the input data sets was reduced through classification by a mean of 10.1%. Allowing for classification deviations of one severity grade led to mean accuracy of 85.42 ± 1.42%. The classifiers' accuracy in that case was similar to the physicians' consensus rate. Learning from consensus records led to better performance. Reducing the number of severity grades improved results in certain cases. The performance of the Naïve Bayes and C4.5 algorithms was similar; in unbalanced data sets, Naïve Bayes performed better. It is possible to produce a computerized classification model for the severity grade of triage patients, using data mining methods. Learning from patient records regarding which there is a consensus of several physicians is preferable to learning from each physician's patients. Either Naïve Bayes or C4.5 can be used; Naïve Bayes is preferable for unbalanced data sets. An ambiguity in the intermediate severity grades seems to hamper both the physicians' agreement and the classifiers' accuracy. © 2010 Blackwell Publishing Ltd.

Machine learning approaches to analysing textual injury surveillance data: a systematic review.

PubMed

Vallmuur, Kirsten

2015-06-01

To synthesise recent research on the use of machine learning approaches to mining textual injury surveillance data. Systematic review. The electronic databases which were searched included PubMed, Cinahl, Medline, Google Scholar, and Proquest. The bibliography of all relevant articles was examined and associated articles were identified using a snowballing technique. For inclusion, articles were required to meet the following criteria: (a) used a health-related database, (b) focused on injury-related cases, AND used machine learning approaches to analyse textual data. The papers identified through the search were screened resulting in 16 papers selected for review. Articles were reviewed to describe the databases and methodology used, the strength and limitations of different techniques, and quality assurance approaches used. Due to heterogeneity between studies meta-analysis was not performed. Occupational injuries were the focus of half of the machine learning studies and the most common methods described were Bayesian probability or Bayesian network based methods to either predict injury categories or extract common injury scenarios. Models were evaluated through either comparison with gold standard data or content expert evaluation or statistical measures of quality. Machine learning was found to provide high precision and accuracy when predicting a small number of categories, was valuable for visualisation of injury patterns and prediction of future outcomes. However, difficulties related to generalizability, source data quality, complexity of models and integration of content and technical knowledge were discussed. The use of narrative text for injury surveillance has grown in popularity, complexity and quality over recent years. With advances in data mining techniques, increased capacity for analysis of large databases, and involvement of computer scientists in the injury prevention field, along with more comprehensive use and description of quality assurance methods in text mining approaches, it is likely that we will see a continued growth and advancement in knowledge of text mining in the injury field. Copyright © 2015 Elsevier Ltd. All rights reserved.

Evaluation of Wheel Loaders in Open Pit Marble Quarrying by Using the AHP and Topsis Approaches / Ocena pracy ładowarki na podwoziu kołowym w odkrywkowej kopalni marmuru w oparciu o metody AHP i topsis

NASA Astrophysics Data System (ADS)

Kun, Mete; Topaloǧlu, Şeyda; Malli, Tahir

2013-03-01

The marble mining in Turkey has been rising since the early 80's. In relation to that, the marble income has become noticeably bigger than those of other mining sectors. In recent years, marble and natural stone export composes half of the total mine export with a value of two billion dollars. This rapid development observed in marble operation has increased the importance of mining economics, income-expenditure balance and cost analysis. The most important cost elements observed in marble quarrying are machinery and equipment, labor costs and geological structures of the field. The aim of this study is to is to propose a multi-criteria decision making (MCDM) approach to evaluate the wheel loader alternatives and select the best loader under multiple criteria. A two-step methodology based on two MCDM methods, which are namely the Analytic Hierarchy Process (AHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), are used in the evaluation procedure. More precisely, AHP is applied to determine the relative weights of evaluation criteria and TOPSIS is applied to rank the wheel loader alternatives. The proposed approach also provides a relatively simple and very well suited decision making tool for this type of decision making problems.

Effect of adaptation and pulp density on bioleaching of mine waste using indigenous acidophilic bacteria

NASA Astrophysics Data System (ADS)

Cho, K.; Kim, B.; Lee, D.; Choi, N.; Park, C.

2011-12-01

Adaptation to environment is a natural phenomena that takes place in many animals, plants and microorganisms. These adapted organisms achieve stronger applicability than unadapted organisms after habitation in a specific environment for a long time. In the biohydrometallurgical industry, adaptation to special environment conditions by selective culturing is the most popular method for improving bioleaching activity of strains-although that is time consuming. This study investigated the influence of the bioleaching efficiency of mine waste under batch experimental conditions (adaptation and pulp density) using the indigenous acidophilic bacteria collected from acid mine drainage in Go-seong and Yeon-hwa, Korea. We conducted the batch experiments at the influences of parameters, such as the adaptation of bacteria and pulp density of the mine waste. In the adaptation case, the value of pH in 1'st adaptation bacteria sample exhibited lower than in 2'nd adaptation bacteria sample. And the content of both Cu and Zn at 1'st adaptation bacteria sample appeared lower than at 2'nd adaptation bacteria sample. In the SEM analysis, the rod-shaped bacteria with 1μm in length were observed on the filter paper (pore size - 0.45μm). The results of pulp density experiments revealed that the content of both Cu and Zn increased with increasing pulp density, since the increment of pulp density resulted in the enhancement of bioleaching capacity.

Data Mining Application in Customer Relationship Management for Hospital Inpatients

PubMed Central

2012-01-01

Objectives This study aims to discover patients loyal to a hospital and model their medical service usage patterns. Consequently, this study proposes a data mining application in customer relationship management (CRM) for hospital inpatients. Methods A recency, frequency, monetary (RFM) model has been applied toward 14,072 patients discharged from a university hospital. Cluster analysis was conducted to segment customers, and it modeled the patterns of the loyal customers' medical services usage via a decision tree. Results Patients were divided into two groups according to the variables of the RFM model and the group which had significantly high frequency of medical use and expenses was defined as loyal customers, a target market. As a result of the decision tree, the predictable factors of the loyal clients were; length of stay, certainty of selectable treatment, surgery, number of accompanying treatments, kind of patient room, and department from which they were discharged. Particularly, this research showed that when a patient within the internal medicine department who did not have surgery stayed for more than 13.5 days, their probability of being a classified as a loyal customer was 70.0%. Conclusions To discover a hospital's loyal patients and model their medical usage patterns, the application of data-mining has been suggested. This paper suggests practical use of combining segmentation, targeting, positioning (STP) strategy and the RFM model with data-mining in CRM. PMID:23115740

Chemical Sensing for Buried Landmines - Fundamental Processes Influencing Trace Chemical Detection

DOE Office of Scientific and Technical Information (OSTI.GOV)

PHELAN, JAMES M.

2002-05-01

Mine detection dogs have a demonstrated capability to locate hidden objects by trace chemical detection. Because of this capability, demining activities frequently employ mine detection dogs to locate individual buried landmines or for area reduction. The conditions appropriate for use of mine detection dogs are only beginning to emerge through diligent research that combines dog selection/training, the environmental conditions that impact landmine signature chemical vapors, and vapor sensing performance capability and reliability. This report seeks to address the fundamental soil-chemical interactions, driven by local weather history, that influence the availability of chemical for trace chemical detection. The processes evaluated include:more » landmine chemical emissions to the soil, chemical distribution in soils, chemical degradation in soils, and weather and chemical transport in soils. Simulation modeling is presented as a method to evaluate the complex interdependencies among these various processes and to establish conditions appropriate for trace chemical detection. Results from chemical analyses on soil samples obtained adjacent to landmines are presented and demonstrate the ultra-trace nature of these residues. Lastly, initial measurements of the vapor sensing performance of mine detection dogs demonstrates the extreme sensitivity of dogs in sensing landmine signature chemicals; however, reliability at these ultra-trace vapor concentrations still needs to be determined. Through this compilation, additional work is suggested that will fill in data gaps to improve the utility of trace chemical detection.« less

Finding novel relationships with integrated gene-gene association network analysis of Synechocystis sp. PCC 6803 using species-independent text-mining.

PubMed

Kreula, Sanna M; Kaewphan, Suwisa; Ginter, Filip; Jones, Patrik R

2018-01-01

The increasing move towards open access full-text scientific literature enhances our ability to utilize advanced text-mining methods to construct information-rich networks that no human will be able to grasp simply from 'reading the literature'. The utility of text-mining for well-studied species is obvious though the utility for less studied species, or those with no prior track-record at all, is not clear. Here we present a concept for how advanced text-mining can be used to create information-rich networks even for less well studied species and apply it to generate an open-access gene-gene association network resource for Synechocystis sp. PCC 6803, a representative model organism for cyanobacteria and first case-study for the methodology. By merging the text-mining network with networks generated from species-specific experimental data, network integration was used to enhance the accuracy of predicting novel interactions that are biologically relevant. A rule-based algorithm (filter) was constructed in order to automate the search for novel candidate genes with a high degree of likely association to known target genes by (1) ignoring established relationships from the existing literature, as they are already 'known', and (2) demanding multiple independent evidences for every novel and potentially relevant relationship. Using selected case studies, we demonstrate the utility of the network resource and filter to ( i ) discover novel candidate associations between different genes or proteins in the network, and ( ii ) rapidly evaluate the potential role of any one particular gene or protein. The full network is provided as an open-source resource.

A contribution to improve the calculation of the acid generating potential of mining wastes.

PubMed

Chopard, Aurélie; Benzaazoua, Mostafa; Bouzahzah, Hassan; Plante, Benoît; Marion, Philippe

2017-05-01

Mine wastes from sulfide-bearing ore extraction and processing are often stored at the surface of mine sites and could generate mine drainage. Prediction tests are completed to predict the water quality associated with the deposition of mining wastes. Static tests can quickly assess the acid-generating potential (AP) and the neutralization potential (NP). Whereas some studies recommend to take into account a mineral reactivity factor for the NP determination, the reactivity rates of acidifying minerals are not considered in the AP calculation. The aim of this study is to bring contribution to the improvement of the static test determination by adding kinetic factors in the AP determination. Eight sulfides (pyrite, Ni-pyrite, pyrrhotite, Ni-pyrrhotite, chalcopyrite, galena, sphalerite, arsenopyrite) and a sulfosalt (gersdorffite) were separately submitted to kinetic tests in modified weathering cells. This test was selected for its rapidity of results and for the low amount of material used, as it is somewhat difficult to obtain pure minerals samples. Five synthetic tailings were composed by mixing pure sulfides in various proportions and submitted to the same kinetic tests. The oxidation rates of synthetic tailings were compared with the weighted combined oxidation rates of individual pure sulfides. The oxidation rates of the synthetic tailings calculated from those of pure sulfides are within the same order of magnitude than those obtained through the kinetic experiments. The AP of synthetic tailings were calculated according to standard equations of the literature and compared with the new method. Copyright © 2017 Elsevier Ltd. All rights reserved.

Drug safety data mining with a tree-based scan statistic.

PubMed

Kulldorff, Martin; Dashevsky, Inna; Avery, Taliser R; Chan, Arnold K; Davis, Robert L; Graham, David; Platt, Richard; Andrade, Susan E; Boudreau, Denise; Gunter, Margaret J; Herrinton, Lisa J; Pawloski, Pamala A; Raebel, Marsha A; Roblin, Douglas; Brown, Jeffrey S

2013-05-01

In post-marketing drug safety surveillance, data mining can potentially detect rare but serious adverse events. Assessing an entire collection of drug-event pairs is traditionally performed on a predefined level of granularity. It is unknown a priori whether a drug causes a very specific or a set of related adverse events, such as mitral valve disorders, all valve disorders, or different types of heart disease. This methodological paper evaluates the tree-based scan statistic data mining method to enhance drug safety surveillance. We use a three-million-member electronic health records database from the HMO Research Network. Using the tree-based scan statistic, we assess the safety of selected antifungal and diabetes drugs, simultaneously evaluating overlapping diagnosis groups at different granularity levels, adjusting for multiple testing. Expected and observed adverse event counts were adjusted for age, sex, and health plan, producing a log likelihood ratio test statistic. Out of 732 evaluated disease groupings, 24 were statistically significant, divided among 10 non-overlapping disease categories. Five of the 10 signals are known adverse effects, four are likely due to confounding by indication, while one may warrant further investigation. The tree-based scan statistic can be successfully applied as a data mining tool in drug safety surveillance using observational data. The total number of statistical signals was modest and does not imply a causal relationship. Rather, data mining results should be used to generate candidate drug-event pairs for rigorous epidemiological studies to evaluate the individual and comparative safety profiles of drugs. Copyright © 2013 John Wiley & Sons, Ltd.

Pattern mining of user interaction logs for a post-deployment usability evaluation of a radiology PACS client.

PubMed

Jorritsma, Wiard; Cnossen, Fokie; Dierckx, Rudi A; Oudkerk, Matthijs; van Ooijen, Peter M A

2016-01-01

To perform a post-deployment usability evaluation of a radiology Picture Archiving and Communication System (PACS) client based on pattern mining of user interaction log data, and to assess the usefulness of this approach compared to a field study. All user actions performed on the PACS client were logged for four months. A data mining technique called closed sequential pattern mining was used to automatically extract frequently occurring interaction patterns from the log data. These patterns were used to identify usability issues with the PACS. The results of this evaluation were compared to the results of a field study based usability evaluation of the same PACS client. The interaction patterns revealed four usability issues: (1) the display protocols do not function properly, (2) the line measurement tool stays active until another tool is selected, rather than being deactivated after one use, (3) the PACS's built-in 3D functionality does not allow users to effectively perform certain 3D-related tasks, (4) users underuse the PACS's customization possibilities. All usability issues identified based on the log data were also found in the field study, which identified 48 issues in total. Post-deployment usability evaluation based on pattern mining of user interaction log data provides useful insights into the way users interact with the radiology PACS client. However, it reveals few usability issues compared to a field study and should therefore not be used as the sole method of usability evaluation. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Data Mining and Pattern Recognition Models for Identifying Inherited Diseases: Challenges and Implications.

PubMed

Iddamalgoda, Lahiru; Das, Partha S; Aponso, Achala; Sundararajan, Vijayaraghava S; Suravajhala, Prashanth; Valadi, Jayaraman K

2016-01-01

Data mining and pattern recognition methods reveal interesting findings in genetic studies, especially on how the genetic makeup is associated with inherited diseases. Although researchers have proposed various data mining models for biomedical approaches, there remains a challenge in accurately prioritizing the single nucleotide polymorphisms (SNP) associated with the disease. In this commentary, we review the state-of-art data mining and pattern recognition models for identifying inherited diseases and deliberate the need of binary classification- and scoring-based prioritization methods in determining causal variants. While we discuss the pros and cons associated with these methods known, we argue that the gene prioritization methods and the protein interaction (PPI) methods in conjunction with the K nearest neighbors' could be used in accurately categorizing the genetic factors in disease causation.

CoBOP: Electro-Optic Identification Laser Line Sean Sensors

DTIC Science & Technology

1998-01-01

Electro - Optic Identification Sensors Project[1] is to develop and demonstrate high resolution underwater electro - optic (EO) imaging sensors, and associated image processing/analysis methods, for rapid visual identification of mines and mine-like contacts (MLCs). Identification of MLCs is a pressing Fleet need. During MCM operations, sonar contacts are classified as mine-like if they are sufficiently similar to signatures of mines. Each contact classified as mine-like must be identified as a mine or not a mine. During MCM operations in littoral areas,

Application of text mining for customer evaluations in commercial banking

NASA Astrophysics Data System (ADS)

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.

SULI Final Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Clevenger, E.

2018-02-02

This project looks at alternative water sources, specifically in the field of desalination and selective ion removal through capacitive deionization (CDI). It project aims to both scale up the desalination capabilities of CDI cells as well as determine the selectivity of CDI for particular ions. My task is to design and build cells that have reproducible performance and characterize the materials for building these cells. The scientific methods I’ve learned through my work in CDI and the data mining and analysis tools I’ve become familiar with through CAES will be important catalysts in my future success in a graduate program.more » The purpose of this presentation is to give a standard of practice for my current method of building of capacitive deionization cells. Parts 1 and 2 will be discussed in which the electrodes are prepared, and the cell is built.« less

Hibernacula selection by Townsend's big-eared bat in Southwestern Colorado

USGS Publications Warehouse

Hayes, Mark A.; Schorr, Robert A.; Navo, Kirk W.

2011-01-01

In western United States, both mine reclamations and renewed mining at previously abandoned mines have increased substantially in the last decade. This increased activity may adversely impact bats that use these mines for roosting. Townsend's big-eared bat (Corynorhinus townsendii) is a species of conservation concern that may be impacted by ongoing mine reclamation and renewed mineral extraction. To help inform wildlife management decisions related to bat use of abandoned mine sites, we used logistic regression, Akaike's information criterion, and multi-model inference to investigate hibernacula use by Townsend's big-eared bats using 9 years of data from surveys inside abandoned mines in southwestern Colorado. Townsend's big-eared bats were found in 38 of 133 mines surveyed (29%), and occupied mines averaged 2.6 individuals per mine. The model explaining the most variability in our data included number of openings and portal temperature at abandoned mines. In southwestern Colorado, we found that abandoned mine sites with more than one opening and portal temperatures near 0°C were more likely to contain hibernating Townsend's big-eared bats. However, mines with only one opening and portal temperatures of ≥10°C were occasionally occupied by Townsend's big-eared bat. Understanding mine use by Townsend's big-eared bat can help guide decisions regarding allocation of resources and placement of bat-compatible closures at mine sites scheduled for reclamation. When feasible we believe that surveys should be conducted inside all abandoned mines in a reclamation project at least once during winter prior to making closure and reclamation recommendations.

Raman spectroscopy of efflorescent sulfate salts from Iron Mountain Mine Superfund Site, California.

PubMed

Sobron, Pablo; Alpers, Charles N

2013-03-01

The Iron Mountain Mine Superfund Site near Redding, California, is a massive sulfide ore deposit that was mined for iron, silver, gold, copper, zinc, and pyrite intermittently for nearly 100 years. As a result, both water and air reached the sulfide deposits deep within the mountain, producing acid mine drainage consisting of sulfuric acid and heavy metals from the ore. Particularly, the drainage water from the Richmond Mine at Iron Mountain is among the most acidic waters naturally found on Earth. The mineralogy at Iron Mountain can serve as a proxy for understanding sulfate formation on Mars. Selected sulfate efflorescent salts from Iron Mountain, formed from extremely acidic waters via drainage from sulfide mining, have been characterized by means of Raman spectroscopy. Gypsum, ferricopiapite, copiapite, melanterite, coquimbite, and voltaite are found within the samples. This work has implications for Mars mineralogical and geochemical investigations as well as for terrestrial environmental investigations related to acid mine drainage contamination.

Raman spectroscopy of efflorescent sulfate salts from Iron Mountain Mine Superfund Site, California

USGS Publications Warehouse

Sobron, Pablo; Alpers, Charles N.

2013-01-01

The Iron Mountain Mine Superfund Site near Redding, California, is a massive sulfide ore deposit that was mined for iron, silver, gold, copper, zinc, and pyrite intermittently for nearly 100 years. As a result, both water and air reached the sulfide deposits deep within the mountain, producing acid mine drainage consisting of sulfuric acid and heavy metals from the ore. Particularly, the drainage water from the Richmond Mine at Iron Mountain is among the most acidic waters naturally found on Earth. The mineralogy at Iron Mountain can serve as a proxy for understanding sulfate formation on Mars. Selected sulfate efflorescent salts from Iron Mountain, formed from extremely acidic waters via drainage from sulfide mining, have been characterized by means of Raman spectroscopy. Gypsum, ferricopiapite, copiapite, melanterite, coquimbite, and voltaite are found within the samples. This work has implications for Mars mineralogical and geochemical investigations as well as for terrestrial environmental investigations related to acid mine drainage contamination.

KNODWAT: A scientific framework application for testing knowledge discovery methods for the biomedical domain

PubMed Central

2013-01-01

Background Professionals in the biomedical domain are confronted with an increasing mass of data. Developing methods to assist professional end users in the field of Knowledge Discovery to identify, extract, visualize and understand useful information from these huge amounts of data is a huge challenge. However, there are so many diverse methods and methodologies available, that for biomedical researchers who are inexperienced in the use of even relatively popular knowledge discovery methods, it can be very difficult to select the most appropriate method for their particular research problem. Results A web application, called KNODWAT (KNOwledge Discovery With Advanced Techniques) has been developed, using Java on Spring framework 3.1. and following a user-centered approach. The software runs on Java 1.6 and above and requires a web server such as Apache Tomcat and a database server such as the MySQL Server. For frontend functionality and styling, Twitter Bootstrap was used as well as jQuery for interactive user interface operations. Conclusions The framework presented is user-centric, highly extensible and flexible. Since it enables methods for testing using existing data to assess suitability and performance, it is especially suitable for inexperienced biomedical researchers, new to the field of knowledge discovery and data mining. For testing purposes two algorithms, CART and C4.5 were implemented using the WEKA data mining framework. PMID:23763826

KNODWAT: a scientific framework application for testing knowledge discovery methods for the biomedical domain.

PubMed

Holzinger, Andreas; Zupan, Mario

2013-06-13

Professionals in the biomedical domain are confronted with an increasing mass of data. Developing methods to assist professional end users in the field of Knowledge Discovery to identify, extract, visualize and understand useful information from these huge amounts of data is a huge challenge. However, there are so many diverse methods and methodologies available, that for biomedical researchers who are inexperienced in the use of even relatively popular knowledge discovery methods, it can be very difficult to select the most appropriate method for their particular research problem. A web application, called KNODWAT (KNOwledge Discovery With Advanced Techniques) has been developed, using Java on Spring framework 3.1. and following a user-centered approach. The software runs on Java 1.6 and above and requires a web server such as Apache Tomcat and a database server such as the MySQL Server. For frontend functionality and styling, Twitter Bootstrap was used as well as jQuery for interactive user interface operations. The framework presented is user-centric, highly extensible and flexible. Since it enables methods for testing using existing data to assess suitability and performance, it is especially suitable for inexperienced biomedical researchers, new to the field of knowledge discovery and data mining. For testing purposes two algorithms, CART and C4.5 were implemented using the WEKA data mining framework.

LANDSAT inventory of surface-mined areas using extendible digital techniques

NASA Technical Reports Server (NTRS)

Anderson, A. T.; Schultz, D. T.; Buchman, N.

1975-01-01

Multispectral LANDSAT imagery was analyzed to provide a rapid and accurate means of identification, classification, and measurement of strip-mined surfaces in Western Maryland. Four band analysis allows distinction of a variety of strip-mine associated classes, but has limited extendibility. A method for surface area measurements of strip mines, which is both geographically and temporally extendible, has been developed using band-ratioed LANDSAT reflectance data. The accuracy of area measurement by this method, averaged over three LANDSAT scenes taken between September 1972 and July 1974, is greater than 93%. Total affected acreage of large (50 hectare/124 acre) mines can be measured to within 1.0%.

Sensor feature fusion for detecting buried objects

DOE Office of Scientific and Technical Information (OSTI.GOV)

Clark, G.A.; Sengupta, S.K.; Sherwood, R.J.

1993-04-01

Given multiple registered images of the earth`s surface from dual-band sensors, our system fuses information from the sensors to reduce the effects of clutter and improve the ability to detect buried or surface target sites. The sensor suite currently includes two sensors (5 micron and 10 micron wavelengths) and one ground penetrating radar (GPR) of the wide-band pulsed synthetic aperture type. We use a supervised teaming pattern recognition approach to detect metal and plastic land mines buried in soil. The overall process consists of four main parts: Preprocessing, feature extraction, feature selection, and classification. These parts are used in amore » two step process to classify a subimage. Thee first step, referred to as feature selection, determines the features of sub-images which result in the greatest separability among the classes. The second step, image labeling, uses the selected features and the decisions from a pattern classifier to label the regions in the image which are likely to correspond to buried mines. We extract features from the images, and use feature selection algorithms to select only the most important features according to their contribution to correct detections. This allows us to save computational complexity and determine which of the sensors add value to the detection system. The most important features from the various sensors are fused using supervised teaming pattern classifiers (including neural networks). We present results of experiments to detect buried land mines from real data, and evaluate the usefulness of fusing feature information from multiple sensor types, including dual-band infrared and ground penetrating radar. The novelty of the work lies mostly in the combination of the algorithms and their application to the very important and currently unsolved operational problem of detecting buried land mines from an airborne standoff platform.« less

A systematic review of data mining and machine learning for air pollution epidemiology.

PubMed

Bellinger, Colin; Mohomed Jabbar, Mohomed Shazan; Zaïane, Osmar; Osornio-Vargas, Alvaro

2017-11-28

Data measuring airborne pollutants, public health and environmental factors are increasingly being stored and merged. These big datasets offer great potential, but also challenge traditional epidemiological methods. This has motivated the exploration of alternative methods to make predictions, find patterns and extract information. To this end, data mining and machine learning algorithms are increasingly being applied to air pollution epidemiology. We conducted a systematic literature review on the application of data mining and machine learning methods in air pollution epidemiology. We carried out our search process in PubMed, the MEDLINE database and Google Scholar. Research articles applying data mining and machine learning methods to air pollution epidemiology were queried and reviewed. Our search queries resulted in 400 research articles. Our fine-grained analysis employed our inclusion/exclusion criteria to reduce the results to 47 articles, which we separate into three primary areas of interest: 1) source apportionment; 2) forecasting/prediction of air pollution/quality or exposure; and 3) generating hypotheses. Early applications had a preference for artificial neural networks. In more recent work, decision trees, support vector machines, k-means clustering and the APRIORI algorithm have been widely applied. Our survey shows that the majority of the research has been conducted in Europe, China and the USA, and that data mining is becoming an increasingly common tool in environmental health. For potential new directions, we have identified that deep learning and geo-spacial pattern mining are two burgeoning areas of data mining that have good potential for future applications in air pollution epidemiology. We carried out a systematic review identifying the current trends, challenges and new directions to explore in the application of data mining methods to air pollution epidemiology. This work shows that data mining is increasingly being applied in air pollution epidemiology. The potential to support air pollution epidemiology continues to grow with advancements in data mining related to temporal and geo-spacial mining, and deep learning. This is further supported by new sensors and storage mediums that enable larger, better quality data. This suggests that many more fruitful applications can be expected in the future.

Automated Analysis of Renewable Energy Datasets ('EE/RE Data Mining')

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bush, Brian; Elmore, Ryan; Getman, Dan

This poster illustrates methods to substantially improve the understanding of renewable energy data sets and the depth and efficiency of their analysis through the application of statistical learning methods ('data mining') in the intelligent processing of these often large and messy information sources. The six examples apply methods for anomaly detection, data cleansing, and pattern mining to time-series data (measurements from metering points in buildings) and spatiotemporal data (renewable energy resource datasets).

Numerical linear algebra in data mining

NASA Astrophysics Data System (ADS)

Eldén, Lars

Ideas and algorithms from numerical linear algebra are important in several areas of data mining. We give an overview of linear algebra methods in text mining (information retrieval), pattern recognition (classification of handwritten digits), and PageRank computations for web search engines. The emphasis is on rank reduction as a method of extracting information from a data matrix, low-rank approximation of matrices using the singular value decomposition and clustering, and on eigenvalue methods for network analysis.

A Bayesian Scoring Technique for Mining Predictive and Non-Spurious Rules

PubMed Central

Batal, Iyad; Cooper, Gregory; Hauskrecht, Milos

2015-01-01

Rule mining is an important class of data mining methods for discovering interesting patterns in data. The success of a rule mining method heavily depends on the evaluation function that is used to assess the quality of the rules. In this work, we propose a new rule evaluation score - the Predictive and Non-Spurious Rules (PNSR) score. This score relies on Bayesian inference to evaluate the quality of the rules and considers the structure of the rules to filter out spurious rules. We present an efficient algorithm for finding rules with high PNSR scores. The experiments demonstrate that our method is able to cover and explain the data with a much smaller rule set than existing methods. PMID:25938136

A Bayesian Scoring Technique for Mining Predictive and Non-Spurious Rules.

PubMed

Batal, Iyad; Cooper, Gregory; Hauskrecht, Milos

Rule mining is an important class of data mining methods for discovering interesting patterns in data. The success of a rule mining method heavily depends on the evaluation function that is used to assess the quality of the rules. In this work, we propose a new rule evaluation score - the Predictive and Non-Spurious Rules (PNSR) score. This score relies on Bayesian inference to evaluate the quality of the rules and considers the structure of the rules to filter out spurious rules. We present an efficient algorithm for finding rules with high PNSR scores. The experiments demonstrate that our method is able to cover and explain the data with a much smaller rule set than existing methods.

Comparisons and Selections of Features and Classifiers for Short Text Classification

NASA Astrophysics Data System (ADS)

Wang, Ye; Zhou, Zhi; Jin, Shan; Liu, Debin; Lu, Mi

2017-10-01

Short text is considerably different from traditional long text documents due to its shortness and conciseness, which somehow hinders the applications of conventional machine learning and data mining algorithms in short text classification. According to traditional artificial intelligence methods, we divide short text classification into three steps, namely preprocessing, feature selection and classifier comparison. In this paper, we have illustrated step-by-step how we approach our goals. Specifically, in feature selection, we compared the performance and robustness of the four methods of one-hot encoding, tf-idf weighting, word2vec and paragraph2vec, and in the classification part, we deliberately chose and compared Naive Bayes, Logistic Regression, Support Vector Machine, K-nearest Neighbor and Decision Tree as our classifiers. Then, we compared and analysed the classifiers horizontally with each other and vertically with feature selections. Regarding the datasets, we crawled more than 400,000 short text files from Shanghai and Shenzhen Stock Exchanges and manually labeled them into two classes, the big and the small. There are eight labels in the big class, and 59 labels in the small class.

Feature engineering for drug name recognition in biomedical texts: feature conjunction and feature selection.

PubMed

Liu, Shengyu; Tang, Buzhou; Chen, Qingcai; Wang, Xiaolong; Fan, Xiaoming

2015-01-01

Drug name recognition (DNR) is a critical step for drug information extraction. Machine learning-based methods have been widely used for DNR with various types of features such as part-of-speech, word shape, and dictionary feature. Features used in current machine learning-based methods are usually singleton features which may be due to explosive features and a large number of noisy features when singleton features are combined into conjunction features. However, singleton features that can only capture one linguistic characteristic of a word are not sufficient to describe the information for DNR when multiple characteristics should be considered. In this study, we explore feature conjunction and feature selection for DNR, which have never been reported. We intuitively select 8 types of singleton features and combine them into conjunction features in two ways. Then, Chi-square, mutual information, and information gain are used to mine effective features. Experimental results show that feature conjunction and feature selection can improve the performance of the DNR system with a moderate number of features and our DNR system significantly outperforms the best system in the DDIExtraction 2013 challenge.

A Principal Component Analysis/Fuzzy Comprehensive Evaluation for Rockburst Potential in Kimberlite

NASA Astrophysics Data System (ADS)

Pu, Yuanyuan; Apel, Derek; Xu, Huawei

2018-02-01

Kimberlite is an igneous rock which sometimes bears diamonds. Most of the diamonds mined in the world today are found in kimberlite ores. Burst potential in kimberlite has not been investigated, because kimberlite is mostly mined using open-pit mining, which poses very little threat of rock bursting. However, as the mining depth keeps increasing, the mines convert to underground mining methods, which can pose a threat of rock bursting in kimberlite. This paper focuses on the burst potential of kimberlite at a diamond mine in northern Canada. A combined model with the methods of principal component analysis (PCA) and fuzzy comprehensive evaluation (FCE) is developed to process data from 12 different locations in kimberlite pipes. Based on calculated 12 fuzzy evaluation vectors, 8 locations show a moderate burst potential, 2 locations show no burst potential, and 2 locations show strong and violent burst potential, respectively. Using statistical principles, a Mahalanobis distance is adopted to build a comprehensive fuzzy evaluation vector for the whole mine and the final evaluation for burst potential is moderate, which is verified by a practical rockbursting situation at mine site.

Mines Systems Safety Improvement Using an Integrated Event Tree and Fault Tree Analysis

NASA Astrophysics Data System (ADS)

Kumar, Ranjan; Ghosh, Achyuta Krishna

2017-04-01

Mines systems such as ventilation system, strata support system, flame proof safety equipment, are exposed to dynamic operational conditions such as stress, humidity, dust, temperature, etc., and safety improvement of such systems can be done preferably during planning and design stage. However, the existing safety analysis methods do not handle the accident initiation and progression of mine systems explicitly. To bridge this gap, this paper presents an integrated Event Tree (ET) and Fault Tree (FT) approach for safety analysis and improvement of mine systems design. This approach includes ET and FT modeling coupled with redundancy allocation technique. In this method, a concept of top hazard probability is introduced for identifying system failure probability and redundancy is allocated to the system either at component or system level. A case study on mine methane explosion safety with two initiating events is performed. The results demonstrate that the presented method can reveal the accident scenarios and improve the safety of complex mine systems simultaneously.

High-resolution topography along surface rupture of the 16 October 1999 Hector Mine, California (Mw 7.1) from airborne laser swath mapping

USGS Publications Warehouse

Hudnutt, K.W.; Borsa, A.; Glennie, C.; Minster, J.-B.

2002-01-01

In order to document surface rupture associated with the Hector Mine earthquake, in particular, the area of maximum slip and the deformed surface of Lavic Lake playa, we acquired high-resolution data using relatively new topographic-mapping methods. We performed a raster-laser scan of the main surface breaks along the entire rupture zone, as well as along an unruptured portion of the Bullion fault. The image of the ground surface produced by this method is highly detailed, comparable to that obtained when geologists make particularly detailed site maps for geomorphic or paleoseismic studies. In this case, however, for the first time after a surface-rupturing earthquake, the detailed mapping is along the entire fault zone rather than being confined to selected sites. These data are geodetically referenced, using the Global Positioning System, thus enabling more accurate mapping of the rupture traces. In addition, digital photographs taken along the same flight lines can be overlaid onto the precise topographic data, improving terrain visualization. We demonstrate the potential of these techniques for measuring fault-slip vectors.

76 FR 20940 - Troy Mine, Incorporated, Troy Mine Revised Reclamation Plan, Kootenai National Forest, Lincoln...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-04-14

... mine. The ore is mined using the ``room-and-pillar method.'' The mine permit area covers 2,782 acres of.... Production stopped in 1993 and reinitiated in 2005 and is projected to continue for 3-5 years until the... evaluations necessary to complete design of reclamation elements that include a short-term water management...

Mercury contamination from historical gold mining in California

USGS Publications Warehouse

Alpers, Charles N.; Hunerlach, Michael P.; May, Jason T.; Hothem, Roger L.

2005-01-01

Mercury contamination from historical gold mines represents a potential risk to human health and the environment. This fact sheet provides background information on the use of mercury in historical gold mining and processing operations in California, with emphasis on historical hydraulic mining areas. It also describes results of recent USGS projects that address the potential risks associated with mercury contamination. Miners used mercury (quicksilver) to recover gold throughout the western United States. Gold deposits were either hardrock (lode, gold-quartz veins) or placer (alluvial, unconsolidated gravels). Underground methods (adits and shafts) were used to mine hardrock gold deposits. Hydraulic, drift, or dredging methods were used to mine the placer gold deposits. Mercury was used to enhance gold recovery in all the various types of mining operations; historical records indicate that more mercury was used and lost at hydraulic mines than at other types of mines. On the basis of USGS studies and other recent work, a better understanding is emerging of mercury distribution, ongoing transport, transformation processes, and the extent of biological uptake in areas affected by historical gold mining. This information has been used extensively by federal, state, and local agencies responsible for resource management and public health in California.

Mine wastes and human health

USGS Publications Warehouse

Plumlee, Geoffrey S.; Morman, Suzette A.

2011-01-01

Historical mining and mineral processing have been linked definitively to health problems resulting from occupational and environmental exposures to mine wastes. Modern mining and processing methods, when properly designed and implemented, prevent or greatly reduce potential environmental health impacts. However, particularly in developing countries, there are examples of health problems linked to recent mining. In other cases, recent mining has been blamed for health problems but no clear links have been found. The types and abundances of potential toxicants in mine wastes are predictably influenced by the geologic characteristics of the deposit being mined. Hence, Earth scientists can help understand, anticipate, and mitigate potential health issues associated with mining and mineral processing.

Are Lithium Ion Cells Intrinsically Safe?

PubMed Central

Dubaniewicz, Thomas H.; DuCarme, Joseph P.

2015-01-01

National Institute for Occupational Safety and Health researchers are studying the potential for Li-ion-battery thermal runaway from an internal short circuit in equipment approved as permissible for use in underground coal mines. Researchers used a plastic wedge to induce internal short circuits for thermal runaway susceptibility evaluation purposes, which proved to be a more severe test than the flat plate method for selected Li-ion cells. Researchers conducted cell crush tests within a 20-L chamber filled with 6.5% CH4–air to simulate the mining hazard. Results indicate that LG Chem ICR18650S2 LiCoO2 cells pose a CH4 explosion hazard from a cell internal short circuit. Under specified test conditions, A123 Systems 26650 LiFePO4 cells were safer than the LG Chem ICR18650S2 LiCoO2 cells at a conservative statistical significance level. PMID:26166911

Multi-objective evolutionary optimization for constructing neural networks for virtual reality visual data mining: application to geophysical prospecting.

PubMed

Valdés, Julio J; Barton, Alan J

2007-05-01

A method for the construction of virtual reality spaces for visual data mining using multi-objective optimization with genetic algorithms on nonlinear discriminant (NDA) neural networks is presented. Two neural network layers (the output and the last hidden) are used for the construction of simultaneous solutions for: (i) a supervised classification of data patterns and (ii) an unsupervised similarity structure preservation between the original data matrix and its image in the new space. A set of spaces are constructed from selected solutions along the Pareto front. This strategy represents a conceptual improvement over spaces computed by single-objective optimization. In addition, genetic programming (in particular gene expression programming) is used for finding analytic representations of the complex mappings generating the spaces (a composition of NDA and orthogonal principal components). The presented approach is domain independent and is illustrated via application to the geophysical prospecting of caves.

An Evaluation of Pixel-Based Methods for the Detection of Floating Objects on the Sea Surface

NASA Astrophysics Data System (ADS)

Borghgraef, Alexander; Barnich, Olivier; Lapierre, Fabian; Van Droogenbroeck, Marc; Philips, Wilfried; Acheroy, Marc

2010-12-01

Ship-based automatic detection of small floating objects on an agitated sea surface remains a hard problem. Our main concern is the detection of floating mines, which proved a real threat to shipping in confined waterways during the first Gulf War, but applications include salvaging, search-and-rescue operation, perimeter, or harbour defense. Detection in infrared (IR) is challenging because a rough sea is seen as a dynamic background of moving objects with size order, shape, and temperature similar to those of the floating mine. In this paper we have applied a selection of background subtraction algorithms to the problem, and we show that the recent algorithms such as ViBe and behaviour subtraction, which take into account spatial and temporal correlations within the dynamic scene, significantly outperform the more conventional parametric techniques, with only little prior assumptions about the physical properties of the scene.

A study of fuzzy logic ensemble system performance on face recognition problem

NASA Astrophysics Data System (ADS)

Polyakova, A.; Lipinskiy, L.

2017-02-01

Some problems are difficult to solve by using a single intelligent information technology (IIT). The ensemble of the various data mining (DM) techniques is a set of models which are able to solve the problem by itself, but the combination of which allows increasing the efficiency of the system as a whole. Using the IIT ensembles can improve the reliability and efficiency of the final decision, since it emphasizes on the diversity of its components. The new method of the intellectual informational technology ensemble design is considered in this paper. It is based on the fuzzy logic and is designed to solve the classification and regression problems. The ensemble consists of several data mining algorithms: artificial neural network, support vector machine and decision trees. These algorithms and their ensemble have been tested by solving the face recognition problems. Principal components analysis (PCA) is used for feature selection.

Application of remote-sensing techniques to hydrologic studies in selected coal-mine areas of southeastern Kansas

USGS Publications Warehouse

Kenny, J.F.; McCauley, J.R.

1983-01-01

Disturbances resulting from intensive coal mining in the Cherry Creek basin of southeastern Kansas were investigated using color and color-infrared aerial photography in conjunction with water-quality data from simultaneously acquired samples. Imagery was used to identify the type and extent of vegetative cover on strip-mined lands and the extent and success of reclamation practices. Drainage patterns, point sources of acid mine drainage, and recharge areas for underground mines were located for onsite inspection. Comparison of these interpretations with water-quality data illustrated differences between the eastern and western parts of the Cherry Creek basin. Contamination in the eastern part is due largely to circulation of water from unreclaimed strip mines and collapse features through the network of underground mines and subsequent discharge of acidic drainage through seeps. Contamination in the western part is primarily caused by runoff and seepage from strip-mined lands in which surfaces have frequently been graded and limed but are generally devoid of mature stands of soil-anchoring vegetation. The successful use of aerial photography in the study of Cherry Creek basin indicates the potential of using remote-sensing techniques in studies of other coal-mined regions. (USGS)

Assessment of elemental concentrations in streams of the New Lead Belt in southeastern Missouri, 2002-05

USGS Publications Warehouse

Brumbaugh, William G.; May, Thomas W.; Besser, John M.; Allert, Ann L.; Schmitt, Christopher J.

2007-01-01

Concerns about possible effects of lead-mining activities on the water quality of federally protected streams located in southeastern Missouri prompted a suite of multidisciplinary studies to be conducted by the U.S. Geological Survey. As part of this investigation, a series of biological studies were initiated in 2001 for streams in the current mining region and the prospecting area. In this report, results are examined for trace elements and other selected chemical measurements in sediment, surface water, and sediment interstitial (pore) water sampled between 2002 and 2005 in association with these biological studies. Compared to reference sites, fine sediments collected downstream from mining areas were enriched in metals by factors as large as 75 for cadmium, 62 for cobalt, 171 for nickel, 95 for lead, and 150 for zinc. Greatest metal concentrations in sediments collected in 2002 were from sites downstream from mines on Strother Creek, Courtois Creek, and the West Fork Black River. Sediments from sites on Bee Fork, Logan Creek, and Sweetwater Creek also were noticeably enriched in lead. Sediments in Clearwater Lake, at least 75 kilometers downstream from mining activity, had metal concentrations that were 1.5 to 2.1 times greater than sediments in an area of the lake with no upstream mining activity. Longitudinal sampling along three streams in 2004 indicated that sediment metal concentrations decreased considerably a few kilometers downstream from mining activities; however, in Strother Creek some metals were still enriched by a factor of five or more as far as 13 kilometers downstream from the Buick tailings impoundment. Compared with 2002 samples, metals concentrations were dramatically lower in sediments collected in 2004 at an upper West Fork Black River site, presumably because beneficiation operations at the West Fork mill ceased in 2000. Concentrations of metals and sulfate in sediment interstitial (pore) waters generally tracked closely with metal concentrations in sediments. Metals, including cobalt, nickel, lead, and zinc, were elevated substantially in laboratory-produced pore waters of fine sediments collected near mining operations in 2002 and 2004. Passive diffusion samplers (peepers) buried 4 to 6 centimeters deep in riffle-run stream sediments during 2003 and 2005 had much lower pore-water metal concentrations than the laboratory-produced pore waters of fine sediments collected in 2002 and 2004, but each sampling method produced similar patterns among sites. The combined mean concentration of lead in peeper samples from selected sites located downstream from mining activities for six streams was about 10-fold greater than the mean of the reference sites. In most instances, metals concentrations in surface water and peeper water were not greatly different, indicating considerable exchange between the surface water and pore water at the depths and locations where peepers were situated. Passive sampling probes used to assess metal lability in pore waters of selected samples during 2004 sediment toxicity tests indicated that most of the filterable lead in the laboratory-prepared pore water was relatively non-labile, presumably because lead was complexed by organic matter, or was present as colloidal species. In contrast, large percentages of cobalt and nickel in pore water appeared to be labile. Passive integrative samplers deployed in surface water for up to 3 weeks at three sites in July 2005 confirmed the presence of elevated concentrations of labile metals downstream from mining operations on Strother Creek and, to a lesser extent, Bee Fork. These samplers also indicated a considerable increase in metal loadings occurred for a few days at the Strother Creek site, which coincided with moderate increases in stream discharges in the area.

43 CFR 3930.12 - Performance standards for underground mining.

Code of Federal Regulations, 2014 CFR

2014-10-01

... reserves. (c) Operators/lessees must adopt measures consistent with known technology to prevent or, where the mining method used requires subsidence, control subsidence, maximize mine stability, and maintain... temporarily abandon a mine or portions thereof. (e) The operator/lessee must have the BLM's prior approval to...

43 CFR 3930.12 - Performance standards for underground mining.

Code of Federal Regulations, 2013 CFR

2013-10-01

... reserves. (c) Operators/lessees must adopt measures consistent with known technology to prevent or, where the mining method used requires subsidence, control subsidence, maximize mine stability, and maintain... temporarily abandon a mine or portions thereof. (e) The operator/lessee must have the BLM's prior approval to...

43 CFR 3930.12 - Performance standards for underground mining.

Code of Federal Regulations, 2012 CFR

2012-10-01

... reserves. (c) Operators/lessees must adopt measures consistent with known technology to prevent or, where the mining method used requires subsidence, control subsidence, maximize mine stability, and maintain... temporarily abandon a mine or portions thereof. (e) The operator/lessee must have the BLM's prior approval to...

43 CFR 3930.12 - Performance standards for underground mining.

Code of Federal Regulations, 2011 CFR

2011-10-01

... reserves. (c) Operators/lessees must adopt measures consistent with known technology to prevent or, where the mining method used requires subsidence, control subsidence, maximize mine stability, and maintain... temporarily abandon a mine or portions thereof. (e) The operator/lessee must have the BLM's prior approval to...

Surface mining

Treesearch

Robert Leopold; Bruce Rowland; Reed Stalder

1979-01-01

The surface mining process consists of four phases: (1) exploration; (2) development; (3) production; and (4) reclamation. A variety of surface mining methods has been developed, including strip mining, auger, area strip, open pit, dredging, and hydraulic. Sound planning and design techniques are essential to implement alternatives to meet the myriad of laws,...

Do post-mining constructed channels replace functional characteristics of headwater streams?

EPA Science Inventory

Mountaintop mining and valley fill (MTMVF) is a method of coal mining common in eastern Kentucky and southern West Virginia. Over 1200 miles of stream channel have been buried by MTMVF. Permits for surface coal mining have recognized constructed drainage ditches associated with ...

Land Ecological Security Evaluation of Underground Iron Mine Based on PSR Model

NASA Astrophysics Data System (ADS)

Xiao, Xiao; Chen, Yong; Ruan, Jinghua; Hong, Qiang; Gan, Yong

2018-01-01

Iron ore mine provides an important strategic resource to the national economy while it also causes many serious ecological problems to the environment. The study summed up the characteristics of ecological environment problems of underground iron mine. Considering the mining process of underground iron mine, we analysis connections between mining production, resource, environment and economical background. The paper proposed a land ecological security evaluation system and method of underground iron mine based on Pressure-State-Response model. Our application in Chengchao iron mine proves its efficiency and promising guide on land ecological security evaluation.

Monitoring and inversion on land subsidence over mining area with InSAR technique

USGS Publications Warehouse

Wang, Y.; Zhang, Q.; Zhao, C.; Lu, Z.; Ding, X.

2011-01-01

The Wulanmulun town, located in Inner Mongolia, is one of the main mining areas of Shendong Company such as Shangwan coal mine and Bulianta coal mine, which has been suffering serious mine collapse with the underground mine withdrawal. We use ALOS/PALSAR data to extract land deformation under these regions, in which Small Baseline Subsets (SBAS) method was applied. Then we compared InSAR results with the underground mining activities, and found high correlations between them. Lastly we applied Distributed Dislocation (Okada) model to invert the mine collapse mechanism. ?? 2011 Copyright Society of Photo-Optical Instrumentation Engineers (SPIE).

Screening and prioritisation of chemical risks from metal mining operations, identifying exposure media of concern.

PubMed

Pan, Jilang; Oates, Christopher J; Ihlenfeld, Christian; Plant, Jane A; Voulvoulis, Nikolaos

2010-04-01

Metals have been central to the development of human civilisation from the Bronze Age to modern times, although in the past, metal mining and smelting have been the cause of serious environmental pollution with the potential to harm human health. Despite problems from artisanal mining in some developing countries, modern mining to Western standards now uses the best available mining technology combined with environmental monitoring, mitigation and remediation measures to limit emissions to the environment. This paper develops risk screening and prioritisation methods previously used for contaminated land on military and civilian sites and engineering systems for the analysis and prioritisation of chemical risks from modern metal mining operations. It uses hierarchical holographic modelling and multi-criteria decision making to analyse and prioritise the risks from potentially hazardous inorganic chemical substances released by mining operations. A case study of an active platinum group metals mine in South Africa is used to demonstrate the potential of the method. This risk-based methodology for identifying, filtering and ranking mining-related environmental and human health risks can be used to identify exposure media of greatest concern to inform risk management. It also provides a practical decision-making tool for mine acquisition and helps to communicate risk to all members of mining operation teams.

Surface water monitoring in the mercury mining district of Asturias (Spain).

PubMed

Loredo, Jorge; Petit-Domínguez, María Dolores; Ordóñez, Almudena; Galán, María Pilar; Fernández-Martínez, Rodolfo; Alvarez, Rodrigo; Rucandio, María Isabel

2010-04-15

Systematic monitoring of surface waters in the area of abandoned mine sites constitutes an essential step in the characterisation of pollution from historic mine sites. The analytical data collected throughout a hydrologic period can be used for hydrological modelling and also to select appropriate preventive and/or corrective measures in order to avoid pollution of watercourses. Caudal River drains the main abandoned Hg mine sites (located in Mieres and Pola de Lena districts) in Central Asturias (NW Spain). This paper describes a systematic monitoring of physical and chemical parameters in eighteen selected sampling points within the Caudal River catchment. At each sampling station, water flow, pH, specific conductance, dissolved oxygen, salinity, temperature, redox potential and turbidity were controlled "in situ" and major and trace elements were analysed in the laboratory. In the Hg-mineralised areas, As is present in the form of As-rich pyrite, realgar and occasionally arsenopyrite. Mine drainage and leachates from spoil heaps exhibit in some cases acidic conditions and high As contents, and they are incorporated to Caudal River tributaries. Multivariate statistical analysis aids to the interpretation of the spatial and temporary variations found in the sampled areas, as part of a methodology applicable to different environmental and geological studies. 2009 Elsevier B.V. All rights reserved.

Computational selection of antibody-drug conjugate targets for breast cancer

PubMed Central

Fauteux, François; Hill, Jennifer J.; Jaramillo, Maria L.; Pan, Youlian; Phan, Sieu; Famili, Fazel; O'Connor-McCourt, Maureen

2016-01-01

The selection of therapeutic targets is a critical aspect of antibody-drug conjugate research and development. In this study, we applied computational methods to select candidate targets overexpressed in three major breast cancer subtypes as compared with a range of vital organs and tissues. Microarray data corresponding to over 8,000 tissue samples were collected from the public domain. Breast cancer samples were classified into molecular subtypes using an iterative ensemble approach combining six classification algorithms and three feature selection techniques, including a novel kernel density-based method. This feature selection method was used in conjunction with differential expression and subcellular localization information to assemble a primary list of targets. A total of 50 cell membrane targets were identified, including one target for which an antibody-drug conjugate is in clinical use, and six targets for which antibody-drug conjugates are in clinical trials for the treatment of breast cancer and other solid tumors. In addition, 50 extracellular proteins were identified as potential targets for non-internalizing strategies and alternative modalities. Candidate targets linked with the epithelial-to-mesenchymal transition were identified by analyzing differential gene expression in epithelial and mesenchymal tumor-derived cell lines. Overall, these results show that mining human gene expression data has the power to select and prioritize breast cancer antibody-drug conjugate targets, and the potential to lead to new and more effective cancer therapeutics. PMID:26700623

Analysis of Mining Terrain Deformation Characteristics with Deformation Information System

NASA Astrophysics Data System (ADS)

Blachowski, Jan; Milczarek, Wojciech; Grzempowski, Piotr

2014-05-01

Mapping and prediction of mining related deformations of the earth surface is an important measure for minimising threat to surface infrastructure, human population, the environment and safety of the mining operation itself arising from underground extraction of useful minerals. The number of methods and techniques used for monitoring and analysis of mining terrain deformations is wide and increasing with the development of geographical information technologies. These include for example: terrestrial geodetic measurements, global positioning systems, remote sensing, spatial interpolation, finite element method modelling, GIS based modelling, geological modelling, empirical modelling using the Knothe theory, artificial neural networks, fuzzy logic calculations and other. The aim of this paper is to introduce the concept of an integrated Deformation Information System (DIS) developed in geographic information systems environment for analysis and modelling of various spatial data related to mining activity and demonstrate its applications for mapping and visualising, as well as identifying possible mining terrain deformation areas with various spatial modelling methods. The DIS concept is based on connected modules that include: the spatial database - the core of the system, the spatial data collection module formed by: terrestrial, satellite and remote sensing measurements of the ground changes, the spatial data mining module for data discovery and extraction, the geological modelling module, the spatial data modeling module with data processing algorithms for spatio-temporal analysis and mapping of mining deformations and their characteristics (e.g. deformation parameters: tilt, curvature and horizontal strain), the multivariate spatial data classification module and the visualization module allowing two-dimensional interactive and static mapping and three-dimensional visualizations of mining ground characteristics. The Systems's functionality has been presented on the case study of a coal mining region in SW Poland where it has been applied to study characteristics and map mining induced ground deformations in a city in the last two decades of underground coal extraction and in the first decade after the end of mining. The mining subsidence area and its deformation parameters (tilt and curvature) have been calculated and the latter classified and mapped according to the Polish regulations. In addition possible areas of ground deformation have been indicated based on multivariate spatial data analysis of geological and mining operation characteristics with the geographically weighted regression method.

Mining Rare Associations between Biological Ontologies

PubMed Central

Benites, Fernando; Simon, Svenja; Sapozhnikova, Elena

2014-01-01

The constantly increasing volume and complexity of available biological data requires new methods for their management and analysis. An important challenge is the integration of information from different sources in order to discover possible hidden relations between already known data. In this paper we introduce a data mining approach which relates biological ontologies by mining cross and intra-ontology pairwise generalized association rules. Its advantage is sensitivity to rare associations, for these are important for biologists. We propose a new class of interestingness measures designed for hierarchically organized rules. These measures allow one to select the most important rules and to take into account rare cases. They favor rules with an actual interestingness value that exceeds the expected value. The latter is calculated taking into account the parent rule. We demonstrate this approach by applying it to the analysis of data from Gene Ontology and GPCR databases. Our objective is to discover interesting relations between two different ontologies or parts of a single ontology. The association rules that are thus discovered can provide the user with new knowledge about underlying biological processes or help improve annotation consistency. The obtained results show that produced rules represent meaningful and quite reliable associations. PMID:24404165

Spatio-Temporal Detection of the Thiomonas Population and the Thiomonas Arsenite Oxidase Involved in Natural Arsenite Attenuation Processes in the Carnoulès Acid Mine Drainage

PubMed Central

Hovasse, Agnès; Bruneel, Odile; Casiot, Corinne; Desoeuvre, Angélique; Farasin, Julien; Hery, Marina; Van Dorsselaer, Alain; Carapito, Christine; Arsène-Ploetze, Florence

2016-01-01

The acid mine drainage (AMD) impacted creek of the Carnoulès mine (Southern France) is characterized by acid waters with a high heavy metal content. The microbial community inhabiting this AMD was extensively studied using isolation, metagenomic and metaproteomic methods, and the results showed that a natural arsenic (and iron) attenuation process involving the arsenite oxidase activity of several Thiomonas strains occurs at this site. A sensitive quantitative Selected Reaction Monitoring (SRM)-based proteomic approach was developed for detecting and quantifying the two subunits of the arsenite oxidase and RpoA of two different Thiomonas groups. Using this approach combined with FISH and pyrosequencing-based 16S rRNA gene sequence analysis, it was established here for the first time that these Thiomonas strains are ubiquitously present in minor proportions in this AMD and that they express the key enzymes involved in natural remediation processes at various locations and time points. In addition to these findings, this study also confirms that targeted proteomics applied at the community level can be used to detect weakly abundant proteins in situ. PMID:26870729

The landscape for epigenetic/epigenomic biomedical resources

PubMed Central

Shakya, Kabita; O'Connell, Mary J.; Ruskin, Heather J.

2012-01-01

Recent advances in molecular biology and computational power have seen the biomedical sector enter a new era, with corresponding development of Bioinformatics as a major discipline. Generation of enormous amounts of data has driven the need for more advanced storage solutions and shared access through a range of public repositories. The number of such biomedical resources is increasing constantly and mining these large and diverse data sets continues to present real challenges. This paper attempts a general overview of currently available resources, together with remarks on their data mining and analysis capabilities. Of interest here is the recent shift in focus from genetic to epigenetic/epigenomic research and the emergence and extension of resource provision to support this both at local and global scale. Biomedical text and numerical data mining are both considered, the first dealing with automated methods for analyzing research content and information extraction, and the second (broadly) with pattern recognition and prediction. Any summary and selection of resources is inherently limited, given the spectrum available, but the aim is to provide a guideline for the assessment and comparison of currently available provision, particularly as this relates to epigenetics/epigenomics. PMID:22874136

Improving Fraud and Abuse Detection in General Physician Claims: A Data Mining Study

PubMed Central

Joudaki, Hossein; Rashidian, Arash; Minaei-Bidgoli, Behrouz; Mahmoodi, Mahmood; Geraili, Bijan; Nasiri, Mahdi; Arab, Mohammad

2016-01-01

Background: We aimed to identify the indicators of healthcare fraud and abuse in general physicians’ drug prescription claims, and to identify a subset of general physicians that were more likely to have committed fraud and abuse. Methods: We applied data mining approach to a major health insurance organization dataset of private sector general physicians’ prescription claims. It involved 5 steps: clarifying the nature of the problem and objectives, data preparation, indicator identification and selection, cluster analysis to identify suspect physicians, and discriminant analysis to assess the validity of the clustering approach. Results: Thirteen indicators were developed in total. Over half of the general physicians (54%) were ‘suspects’ of conducting abusive behavior. The results also identified 2% of physicians as suspects of fraud. Discriminant analysis suggested that the indicators demonstrated adequate performance in the detection of physicians who were suspect of perpetrating fraud (98%) and abuse (85%) in a new sample of data. Conclusion: Our data mining approach will help health insurance organizations in low-and middle-income countries (LMICs) in streamlining auditing approaches towards the suspect groups rather than routine auditing of all physicians. PMID:26927587

Mining rare associations between biological ontologies.

PubMed

Benites, Fernando; Simon, Svenja; Sapozhnikova, Elena

2014-01-01

The constantly increasing volume and complexity of available biological data requires new methods for their management and analysis. An important challenge is the integration of information from different sources in order to discover possible hidden relations between already known data. In this paper we introduce a data mining approach which relates biological ontologies by mining cross and intra-ontology pairwise generalized association rules. Its advantage is sensitivity to rare associations, for these are important for biologists. We propose a new class of interestingness measures designed for hierarchically organized rules. These measures allow one to select the most important rules and to take into account rare cases. They favor rules with an actual interestingness value that exceeds the expected value. The latter is calculated taking into account the parent rule. We demonstrate this approach by applying it to the analysis of data from Gene Ontology and GPCR databases. Our objective is to discover interesting relations between two different ontologies or parts of a single ontology. The association rules that are thus discovered can provide the user with new knowledge about underlying biological processes or help improve annotation consistency. The obtained results show that produced rules represent meaningful and quite reliable associations.

Data Mining Methods Applied to Flight Operations Quality Assurance Data: A Comparison to Standard Statistical Methods

NASA Technical Reports Server (NTRS)

Stolzer, Alan J.; Halford, Carl

2007-01-01

In a previous study, multiple regression techniques were applied to Flight Operations Quality Assurance-derived data to develop parsimonious model(s) for fuel consumption on the Boeing 757 airplane. The present study examined several data mining algorithms, including neural networks, on the fuel consumption problem and compared them to the multiple regression results obtained earlier. Using regression methods, parsimonious models were obtained that explained approximately 85% of the variation in fuel flow. In general data mining methods were more effective in predicting fuel consumption. Classification and Regression Tree methods reported correlation coefficients of .91 to .92, and General Linear Models and Multilayer Perceptron neural networks reported correlation coefficients of about .99. These data mining models show great promise for use in further examining large FOQA databases for operational and safety improvements.

Adaptive feature selection using v-shaped binary particle swarm optimization.

PubMed

Teng, Xuyang; Dong, Hongbin; Zhou, Xiurong

2017-01-01

Feature selection is an important preprocessing method in machine learning and data mining. This process can be used not only to reduce the amount of data to be analyzed but also to build models with stronger interpretability based on fewer features. Traditional feature selection methods evaluate the dependency and redundancy of features separately, which leads to a lack of measurement of their combined effect. Moreover, a greedy search considers only the optimization of the current round and thus cannot be a global search. To evaluate the combined effect of different subsets in the entire feature space, an adaptive feature selection method based on V-shaped binary particle swarm optimization is proposed. In this method, the fitness function is constructed using the correlation information entropy. Feature subsets are regarded as individuals in a population, and the feature space is searched using V-shaped binary particle swarm optimization. The above procedure overcomes the hard constraint on the number of features, enables the combined evaluation of each subset as a whole, and improves the search ability of conventional binary particle swarm optimization. The proposed algorithm is an adaptive method with respect to the number of feature subsets. The experimental results show the advantages of optimizing the feature subsets using the V-shaped transfer function and confirm the effectiveness and efficiency of the feature subsets obtained under different classifiers.

Adaptive feature selection using v-shaped binary particle swarm optimization

PubMed Central

Dong, Hongbin; Zhou, Xiurong

2017-01-01

Feature selection is an important preprocessing method in machine learning and data mining. This process can be used not only to reduce the amount of data to be analyzed but also to build models with stronger interpretability based on fewer features. Traditional feature selection methods evaluate the dependency and redundancy of features separately, which leads to a lack of measurement of their combined effect. Moreover, a greedy search considers only the optimization of the current round and thus cannot be a global search. To evaluate the combined effect of different subsets in the entire feature space, an adaptive feature selection method based on V-shaped binary particle swarm optimization is proposed. In this method, the fitness function is constructed using the correlation information entropy. Feature subsets are regarded as individuals in a population, and the feature space is searched using V-shaped binary particle swarm optimization. The above procedure overcomes the hard constraint on the number of features, enables the combined evaluation of each subset as a whole, and improves the search ability of conventional binary particle swarm optimization. The proposed algorithm is an adaptive method with respect to the number of feature subsets. The experimental results show the advantages of optimizing the feature subsets using the V-shaped transfer function and confirm the effectiveness and efficiency of the feature subsets obtained under different classifiers. PMID:28358850

ENGINEERING AND ECONOMIC EVALUATION OF GAS RECOVERY AND UTILIZATION TECHNOLOGIES AT SELECTED U.S. MINES

EPA Science Inventory

Methane liberated in underground coal mines is a severe safety hazard to miners. It is also a major contributor to the build-up of greenhouse gases in the global atmosphere. This report presents an engineering and economic evaluation of several methane recovery and end-use techno...

Peptide-functionalized iron oxide magnetic nanoparticle for gold mining

NASA Astrophysics Data System (ADS)

Shen, Wei-Zheng; Cetinel, Sibel; Sharma, Kumakshi; Borujeny, Elham Rafie; Montemagno, Carlo

2017-02-01

Here, we present our work on preparing a novel nanomaterial composed of inorganic binding peptides and magnetic nanoparticles for inorganic mining. Two previously selected and well-characterized gold-binding peptides from cell surface display, AuBP1 and AuBP2, were exploited. This nanomaterial (AuBP-MNP) was designed to fulfill the following two significant functions: the surface conjugated gold-binding peptide will recognize and selectively bind to gold, while the magnetic nano-sized core will respond and migrate according to the applied external magnetic field. This will allow the smart nanomaterial to mine an individual material (gold) from a pool of mixture, without excessive solvent extraction, filtration, and concentration steps. The working efficiency of AuBP-MNP was determined by showing a dramatic reduction of gold nanoparticle colloid concentration, monitored by spectroscopy. The binding kinetics of AuBP-MNP onto the gold surface was determined using surface plasmon resonance (SPR) spectroscopy, which exhibits around 100 times higher binding kinetics than peptides alone. The binding capacity of AuBP-MNP was demonstrated by a bench-top mining test with gold microparticles.

Bio-reduction of Cr(VI) by exopolysaccharides (EPS) from indigenous bacterial species of Sukinda chromite mine, India.

PubMed

Harish, R; Samuel, Jastin; Mishra, R; Chandrasekaran, N; Mukherjee, A

2012-07-01

Chrome mining activity has contributed intensively towards pollution of hexavalent chromium around Sukinda Valley, Orissa, India. In an attempt to study the specific contribution of exopolysaccharides (EPS) extracted from indigenous isolates towards Cr(VI) reduction, three chromium (VI) tolerant strains were isolated from the effluent mining sludge. Based on the tolerance towards Cr(VI) and EPS production capacity, one of them was selected for further work. The taxonomic identity of the selected strain was confirmed to be Enterobacter cloacae (showing 98% similarity in BLAST search to E. cloacae) through 16S rRNA analysis. The EPS production was observed to increase with increasing Cr(VI) concentration in the growth medium, highest being 0.078 at 100 mg/l Cr(VI). The extracted EPS from Enterobacter cloacae SUKCr1D was able to reduce 31.7% of Cr(VI) at 10 mg/l concentration, which was relevant to the prevailing natural concentrations at Sukinda mine effluent sludge. The FT-IR spectral studies confirmed the surface chemical interactions of hexavalent chromium with EPS.

Predicting volume of distribution with decision tree-based regression methods using predicted tissue:plasma partition coefficients.

PubMed

Freitas, Alex A; Limbu, Kriti; Ghafourian, Taravat

2015-01-01

Volume of distribution is an important pharmacokinetic property that indicates the extent of a drug's distribution in the body tissues. This paper addresses the problem of how to estimate the apparent volume of distribution at steady state (Vss) of chemical compounds in the human body using decision tree-based regression methods from the area of data mining (or machine learning). Hence, the pros and cons of several different types of decision tree-based regression methods have been discussed. The regression methods predict Vss using, as predictive features, both the compounds' molecular descriptors and the compounds' tissue:plasma partition coefficients (Kt:p) - often used in physiologically-based pharmacokinetics. Therefore, this work has assessed whether the data mining-based prediction of Vss can be made more accurate by using as input not only the compounds' molecular descriptors but also (a subset of) their predicted Kt:p values. Comparison of the models that used only molecular descriptors, in particular, the Bagging decision tree (mean fold error of 2.33), with those employing predicted Kt:p values in addition to the molecular descriptors, such as the Bagging decision tree using adipose Kt:p (mean fold error of 2.29), indicated that the use of predicted Kt:p values as descriptors may be beneficial for accurate prediction of Vss using decision trees if prior feature selection is applied. Decision tree based models presented in this work have an accuracy that is reasonable and similar to the accuracy of reported Vss inter-species extrapolations in the literature. The estimation of Vss for new compounds in drug discovery will benefit from methods that are able to integrate large and varied sources of data and flexible non-linear data mining methods such as decision trees, which can produce interpretable models. Graphical AbstractDecision trees for the prediction of tissue partition coefficient and volume of distribution of drugs.

A study on the selection of indigenous leaching-bacteria for effective bioleaching

NASA Astrophysics Data System (ADS)

Oh, S. J.; Cho, K. H.; Kim, B. J.; Choi, N. C.; Park, C. Y.

2012-04-01

Bioleaching technology, which is based on the ability of microorganisms to transform solid compounds into soluble and extractable valuable elements that can be recovered, has been rapidly developed in recent decades for its advantages, which include mild reaction condition, low energy consumption, simple process, low environmental impact and being suitable for low grade mine tailings and residues. The bacteria activities (survival, adaptation of toxically environments etc.) in the bioleaching technology play a key role in the solubilization of metals. The purpose of this study was to selection of optimal leaching-bacteria through changed pH and redox potential on bio-oxidation in batch experiments for successful bioleaching technology. Twenty three indigenous bacteria used throughout this study, leaching-bacteria were obtained from various geochemical conditions; bacteria inhabitation type (acid mine drainage, mine wastes leachate and sulfur hot springs) and base-metal type (sulfur, sulfide, iron and coal). Bio-oxidation experiment result was showed that 9 cycles (1 cycle - 28days) after the leaching-bacteria were inoculated to a leaching medium, pH was observed decreasing and redox potential increased. In the bacteria inhabitation type, bio-oxidation of sulfur hot springs bacteria was greater than other types (acid mine drainage and mine wastes leachate). In addition, bio-oxidation on base-metal type was appeared sulfur was greater than other types (sulfide, iron and coal). This study informs basic knowledge when bacteria apply to eco-/economic resources utilization studies including the biomining and the recycling of mine waste system.

Landfill mining: Development of a cost simulation model.

PubMed

Wolfsberger, Tanja; Pinkel, Michael; Polansek, Stephanie; Sarc, Renato; Hermann, Robert; Pomberger, Roland

2016-04-01

Landfill mining permits recovering secondary raw materials from landfills. Whether this purpose is economically feasible, however, is a matter of various aspects. One is the amount of recoverable secondary raw material (like metals) that can be exploited with a profit. Other influences are the costs for excavation, for processing the waste at the landfill site and for paying charges on the secondary disposal of waste. Depending on the objectives of a landfill mining project (like the recovery of a ferrous and/or a calorific fraction) these expenses and revenues are difficult to assess in advance. This situation complicates any previous assessment of the economic feasibility and is the reason why many landfills that might be suitable for landfill mining are continuingly operated as active landfills, generating aftercare costs and leaving potential hazards to later generations. This article presents a newly developed simulation model for landfill mining projects. It permits identifying the quantities and qualities of output flows that can be recovered by mining and by mobile on-site processing of the waste based on treatment equipment selected by the landfill operator. Thus, charges for disposal and expected revenues from secondary raw materials can be assessed. Furthermore, investment, personnel, operation, servicing and insurance costs are assessed and displayed, based on the selected mobile processing procedure and its throughput, among other things. For clarity, the simulation model is described in this article using the example of a real Austrian sanitary landfill. © The Author(s) 2016.

Guidelines for geophysical investigations of mines under highways mine research project-GUE 70-14.10, PID no. 18459.

DOT National Transportation Integrated Search

2003-06-01

It is estimated that approximately 8,500 abandoned underground mines are present in Ohio and mine-related : subsidence has been a problem dating back to the 1920's. Many investigative methods have been utilized with : varying degrees of success in an...

Application of the Deformation Information System for automated analysis and mapping of mining terrain deformations - case study from SW Poland

NASA Astrophysics Data System (ADS)

Blachowski, Jan; Grzempowski, Piotr; Milczarek, Wojciech; Nowacka, Anna

2015-04-01

Monitoring, mapping and modelling of mining induced terrain deformations are important tasks for quantifying and minimising threats that arise from underground extraction of useful minerals and affect surface infrastructure, human safety, the environment and security of the mining operation itself. The number of methods and techniques used for monitoring and analysis of mining terrain deformations is wide and expanding with the progress in geographical information technologies. These include for example: terrestrial geodetic measurements, Global Navigation Satellite Systems, remote sensing, GIS based modelling and spatial statistics, finite element method modelling, geological modelling, empirical modelling using e.g. the Knothe theory, artificial neural networks, fuzzy logic calculations and other. The presentation shows the results of numerical modelling and mapping of mining terrain deformations for two cases of underground mining sites in SW Poland, hard coal one (abandoned) and copper ore (active) using the functionalities of the Deformation Information System (DIS) (Blachowski et al, 2014 @ http://meetingorganizer.copernicus.org/EGU2014/EGU2014-7949.pdf). The functionalities of the spatial data modelling module of DIS have been presented and its applications in modelling, mapping and visualising mining terrain deformations based on processing of measurement data (geodetic and GNSS) for these two cases have been characterised and compared. These include, self-developed and implemented in DIS, automation procedures for calculating mining terrain subsidence with different interpolation techniques, calculation of other mining deformation parameters (i.e. tilt, horizontal displacement, horizontal strain and curvature), as well as mapping mining terrain categories based on classification of the values of these parameters as used in Poland. Acknowledgments. This work has been financed from the National Science Centre Project "Development of a numerical method of mining ground deformation modelling in complex geological and mining conditions" UMO-2012/07/B/ST10/04297 executed at the Faculty of Geoengineering, Mining and Geology of the Wroclaw University of Technology (Poland).

Method for Determining the Coalbed Methane Content with Determination the Uncertainty of Measurements

NASA Astrophysics Data System (ADS)

Szlązak, Nikodem; Korzec, Marek

2016-06-01

Methane has a bad influence on safety in underground mines as it is emitted to the air during mining works. Appropriate identification of methane hazard is essential to determining methane hazard prevention methods, ventilation systems and methane drainage systems. Methane hazard is identified while roadways are driven and boreholes are drilled. Coalbed methane content is one of the parameters which is used to assess this threat. This is a requirement according to the Decree of the Minister of Economy dated 28 June 2002 on work safety and hygiene, operation and special firefighting protection in underground mines. For this purpose a new method for determining coalbed methane content in underground coal mines has been developed. This method consists of two stages - collecting samples in a mine and testing the sample in the laboratory. The stage of determining methane content in a coal sample in a laboratory is essential. This article presents the estimation of measurement uncertainty of determining methane content in a coal sample according to this methodology.

Scenario-Based Systems Engineering Application to Mine Warfare

DTIC Science & Technology

2015-12-01

hunter- killer capabilities to find, classify, and destroy moored and bottom mines with sonar and video systems, cable cutting devices, and mine...Method: Serial 3 LCS MH-60s LCS: RMS with AN/AQS-20, MH-60s: Archerfish Hunt Method: Serial 1M MK18 MH-60s LCS: MK18 Mod 2, MH-60s...Archerfish Hunt Method: Serial 2M MK18 MH-60s LCS: MK18 Mod 2, MH-60s: Archerfish Hunt Method: Serial 3M MK18 MH-60s LCS: MK18

Study of the distribution patterns of the constituent herbs in classical Chinese medicine prescriptions treating respiratory disease by data mining methods.

PubMed

Fu, Xian-Jun; Song, Xu-Xia; Wei, Lin-Bo; Wang, Zhen-Guo

2013-08-01

To provide the distribution pattern and compatibility laws of the constituent herbs in prescriptions, for doctor's convenience to make decision in choosing correct herbs and prescriptions for treating respiratory disease. Classical prescriptions treating respiratory disease were selected from authoritative prescription books. Data mining methods (frequent itemsets and association rules) were used to analyze the regular patterns and compatibility laws of the constituent herbs in the selected prescriptions. A total of 562 prescriptions were selected to be studied. The result exhibited that, Radix glycyrrhizae was the most frequently used in 47.2% prescriptions, other frequently used were Semen armeniacae amarum, Fructus schisandrae Chinese, Herba ephedrae, and Radix ginseng. Herbal ephedrae was always coupled with Semen armeniacae amarum with the confidence of 73.3%, and many herbs were always accompanied by Radix glycyrrhizae with high confidence. More over, Fructus schisandrae Chinese, Herba ephedrae and Rhizoma pinelliae was most commonly used to treat cough, dyspnoea and associated sputum respectively besides Radix glycyrrhizae and Semen armeniacae amarum. The prescriptions treating dyspnoea often used double herb group of Herba ephedrae & Radix glycyrrhizae, while prescriptions treating sputum often used double herb group of Rhizoma pinelliae & Radix glycyrrhizae and Rhizoma pinelliae & Semen armeniacae amarum, triple herb groups of Rhizoma pinelliae & Semen armeniacae amarum & Radix glycyrrhizae and Pericarpium citri reticulatae & Rhizoma pinelliae & Radix glycyrrhizae. The prescriptions treating respiratory disease showed common compatibility laws in using herbs and special compatibility laws for treating different respiratory symptoms. These principle patterns and special compatibility laws reported here could be useful for doctors to choose correct herbs and prescriptions in treating respiratory disease.

Mercury Pollution from Small-Scale Gold Mining Can Be Stopped by Implementing the Gravity-Borax Method--A Two-Year Follow-Up Study from Two Mining Communities in the Philippines.

PubMed

Køster-Rasmussen, Rasmus; Westergaard, Maria L; Brasholt, Marie; Gutierrez, Richard; Jørs, Erik; Thomsen, Jane F

2016-02-01

Mercury is used globally to extract gold in artisanal and small-scale gold mining. The mercury-free gravity-borax method for gold extraction was introduced in two mining communities using mercury in the provinces Kalinga and Camarines Norte. This article describes project activities and quantitative changes in mercury consumption and analyzes the implementation with diffusion of innovations theory. Activities included miner-to-miner training; seminars for health-care workers, school teachers, and children; and involvement of community leaders. Baseline (2011) and follow-up (2013) data were gathered on mining practices and knowledge about mercury toxicology. Most miners in Kalinga converted to the gravity-borax method, whereas only a few did so in Camarines Norte. Differences in the nature of the social systems impacted the success of the implementation, and involvement of the tribal organization facilitated the shift in Kalinga. In conclusion, the gravity-borax method is a doable alternative to mercury use in artisanal and small-scale gold mining, but support from the civil society is needed. © The Author(s) 2016.

Corrosion of rock anchors in US coal mines

NASA Astrophysics Data System (ADS)

Bylapudi, Gopi

The mining industry is a major consumer of rock bolts in the United States. Due to the high humidity in the underground mining environment, the rock bolts corrode and loose their load bearing capacity which in turn reduces the life expectancy of the ground support and, thus, creates operational difficulties and number of safety concerns[1]. Research on rock anchor corrosion has not been adequately extensive in the past and the effects of several factors in the mine atmosphere and waters are not clearly understood. One of the probable reasons for this lack of research may be attributed to the time required for gathering meaningful data that makes the study of corrosion quite challenging. In this particular work underground water samples from different mines in the Illinois coal basin were collected and the major chemical content was analyzed and used for the laboratory testing. The corrosion performance of the different commercial rock anchors was investigated by techniques such as laboratory immersion tests in five different corrosion chambers, and potentiodynamic polarization tests in simulated ground waters based on the Illinois coal basin. The experiments were conducted with simulate underground mining conditions (corrosive). The tensile strengths were measured for the selected rock anchors taken every 3 months from the salt spray corrosion chambers maintained at different pH values and temperatures. The corrosion potential (Ecorr ), corrosion current (Icorr) and the corresponding corrosion rates (CR) of the selected commercial rock bolts: #5, #6, #6 epoxy coated and #7 forged head rebar steels, #6 and #7 threaded head rebar steels were measured at the solution pH values of 5 and 8 at room temperature. The open circuit potential (OCP) values of the different rock anchors were recorded in 3 selected underground coal mines (A, B & C) in the Illinois coal basin and the data compared with the laboratory electrochemical tests for analyzing the life of the rock anchors installed in the mines with respect to corrosion potential and corrosion current measured. The results of this research were statistically validated. This research will have direct consequence to the rock related safety. The results of this research indicate that certain corrosive conditions are commonly found in mines but uniform corrosion (around 0.01-0.03mm loss per year across the diameter) is generally not considered a serious issue. From this study, longer term research for longterm excavation support is recommended that could quantify the problem depending on the rock anchor used and specific strata conditions.

Lunar vertical-shaft mining system

NASA Technical Reports Server (NTRS)

Introne, Steven D. (Editor); Krause, Roy; Williams, Erik; Baskette, Keith; Martich, Frederick; Weaver, Brad; Meve, Jeff; Alexander, Kyle; Dailey, Ron; White, Matt

1994-01-01

This report proposes a method that will allow lunar vertical-shaft mining. Lunar mining allows the exploitation of mineral resources imbedded within the surface. The proposed lunar vertical-shaft mining system is comprised of five subsystems: structure, materials handling, drilling, mining, and planning. The structure provides support for the exploration and mining equipment in the lunar environment. The materials handling subsystem moves mined material outside the structure and mining and drilling equipment inside the structure. The drilling process bores into the surface for the purpose of collecting soil samples, inserting transducer probes, or locating ore deposits. Once the ore deposits are discovered and pinpointed, mining operations bring the ore to the surface. The final subsystem is planning, which involves the construction of the mining structure.

Coal mine bumps as related to geologic features in the northern part of the Sunnyside District, Carbon County, Utah

USGS Publications Warehouse

Osterwald, Frank W.; Dunrud, C. Richard; Collins, Donley S.

1993-01-01

Coal mine bumps, which are violent, spontaneous, and often catastrophic disruptions of coal and rock, were common in the Sunnyside coal mining district, Utah, before the introduction of protective-engineering methods, modern room-and-pillar retreat mining with continuous mining machines, and particularly modern longwall mining. The coal at Sunnyside, when stressed during mining, fails continuously with many popping, snapping, and banging noises. Although most of the bumps are beneficial because they make mining easier, many of the large ones are dangerous and in the past caused injuries and fatalities, particularly with room- and-pillar mining methods used in the early mining operations. Geologic mapping of underground mine openings revealed many types of deformational features, some pre-mine and some post-mine in age. Stresses resulting from mining are concentrated near the mine openings; if openings are driven at large angles to small pre-mine deformational features, particularly shatter zones in coal, abnormal stress buildups may occur and violent bumps may result. Other geologic features, such as ripple marks, oriented sand grains, intertongued rock contacts, trace fossils, and load casts, also influence the occurrence of bumps by impeding slip of coal and rocks along bedding planes. The stress field in the coal also varies markedly because of the rough ridge and canyon topography. These features may allow excessively large stress components to accumulate. At many places, the stresses that contribute to deformation and failures of mine openings are oriented horizontally. The stratigraphy of the rocks immediately above and below the mined coal bed strongly influences the deformation of the mine openings in response to stress accumulations. Triaxial compressive testing of coal from the Sunnyside No.1 and No.3 Mines indicates that the strength of the coal increases several times as the confining (lateral) stress is increased. Strengths of cores cut from single large blocks of coal vary widely. Although the strengths of coal cores increase slowly at high levels of confining stress, the coal in Sunnyside No. 1 Mine is slightly stronger in laboratory tests than coal in Sunnyside No.3 Mine. The coal in No.1 Mine probably can store larger amounts of stress than coal in the No.3 Mine, which may account for the apparently greater number of violent bumps in No.1 Mine. The strength of coal, and its ability to store stress before failure, may correlate in part with chemical composition, particularly with the amounts of benzene ring compounds in vitrain; coal with relatively large amounts of benzene ring compounds is stronger than coal with lesser amounts of these compounds. Alternatively, the chemical composition of coal may affect its response to stress. Increasing contents of kaolinite in coal appear to reduce its compressive strength at low confining stresses, resulting in easy failures of pillars and ribs in mine openings. Applications of the geologic factors outlined in this report, carefully coupled with advanced modern engineering methods, have markedly reduced the hazards from coal mine bumps and related failures of mine openings at Sunnyside. Similar studies probably could aid in reducing bump-related hazards in other coal mining areas.

Heat acclimation: Gold mines and genes

PubMed Central

Schneider, Suzanne M.

2016-01-01

ABSTRACT The underground gold mines of South Africa offer a unique historical setting to study heat acclimation. The early heat stress research was conducted and described by a young medical officer, Dr. Aldo Dreosti. He developed practical and specific protocols to first assess the heat tolerance of thousands of new mining recruits, and then used the screening results as the basis for assigning a heat acclimation protocol. The mines provide an interesting paradigm where the prevention of heat stroke evolved from genetic selection, where only Black natives were recruited due to a false assumption of their intrinsic tolerance to heat, to our current appreciation of the epigenetic and other molecular adaptations that occur with exposure to heat. PMID:28090556

[Hyperspectral remote sensing in monitoring the vegetation heavy metal pollution].

PubMed

Li, Na; Lü, Jian-sheng; Altemann, W

2010-09-01

Mine exploitation aggravates the environment pollution. The large amount of heavy metal element in the drainage of slag from the mine pollutes the soil seriously, doing harm to the vegetation growing and human health. The investigation of mining environment pollution is urgent, in which remote sensing, as a new technique, helps a lot. In the present paper, copper mine in Dexing was selected as the study area and China sumac as the study plant. Samples and spectral data in field were gathered and analyzed in lab. The regression model from spectral characteristics for heavy metal content was built, and the feasibility of hyperspectral remote sensing in environment pollution monitoring was testified.

Chemical composition of samples collected from waste rock dumps and other mining-related features at selected phosphate mines in southeastern Idaho, western Wyoming, and northern Utah

USGS Publications Warehouse

Moyle, Phillip R.; Causey, J. Douglas

2001-01-01

This report provides chemical analyses for 31 samples collected from various phosphate mine sites in southeastern Idaho (25), northern Utah (2), and western Wyoming (4). The sampling effort was undertaken as a reconnaissance and does not constitute a characterization of mine wastes. Twenty-five samples were collected from waste rock dumps, 2 from stockpiles, and 1 each from slag, tailings, mill shale, and an outcrop. All samples were analyzed for a suite of major, minor, and trace elements. Although the analytical data set for the 31 samples is too small for detailed statistical analysis, a summary of general observations is made.

Evaluation of the long-term performance of six alternative disposal methods for LLRW

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kossik, R.; Sharp, G.; Chau, T.

1995-12-31

The State of New York has carried out a comparison of six alternative disposal methods for low-level radioactive waste (LLRW). An important part of these evaluations involved quantitatively analyzing the long-term (10,000 yr) performance of the methods with respect to dose to humans, radionuclide concentrations in the environment, and cumulative release from the facility. Four near-surface methods (covered above-grade vault, uncovered above-grade vault, below-grade vault, augered holes) and two mine methods (vertical shaft mine and drift mine) were evaluated. Each method was analyzed for several generic site conditions applicable for the state. The evaluations were carried out using RIP (Repositorymore » Integration Program), an integrated, total system performance assessment computer code which has been applied to radioactive waste disposal facilities both in the U.S. (Yucca Mountain, WIPP) and worldwide. The evaluations indicate that mines in intact low-permeability rock and near-surface facilities with engineered covers generally have a high potential to perform well (within regulatory limits). Uncovered above-grade vaults and mines in highly fractured crystalline rock, however, have a high potential to perform poorly, exceeding regulatory limits.« less

Hydrologic data and instrumentation, and methods of collecting the data to small watersheds in the coal-mining region of west-central Indiana, October 1980 to June 1983

USGS Publications Warehouse

Renn, D.E.; Duwelius, R.F.; Keeton, C.R.; Tyler, J.W.

1985-01-01

Methods and instrumentation used in collecting samples and measuring concentrations and properties of the following types of data are described in the text: streamflow in seven watersheds; ground-water levels in 46 wells in unconsolidated material and 12 wells in bedrock in or near the watersheds; precipitation in seven watersheds; solar radiation, relative humidity, wind speed, and temperature of air and soil at one location; and pH, specific conductance, temperature of water, and concentrations of selected chemical constituents and suspended sediment in two watersheds.

Slope Stability Analysis of Waste Dump in Sandstone Open Pit Osielec

NASA Astrophysics Data System (ADS)

Adamczyk, Justyna; Cała, Marek; Flisiak, Jerzy; Kolano, Malwina; Kowalski, Michał

2013-03-01

This paper presents the slope stability analysis for the current as well as projected (final) geometry of waste dump Sandstone Open Pit "Osielec". For the stability analysis six sections were selected. Then, the final geometry of the waste dump was designed and the stability analysis was conducted. On the basis of the analysis results the opportunities to improve the stability of the object were identified. The next issue addressed in the paper was to determine the proportion of the mixture containing mining and processing wastes, for which the waste dump remains stable. Stability calculations were carried out using Janbu method, which belongs to the limit equilibrium methods.

Measuring mine roof bolt strains

DOEpatents

Steblay, Bernard J.

1986-01-01

A mine roof bolt and a method of measuring the strain in mine roof bolts of this type are disclosed. According to the method, a flat portion on the head of the mine roof bolt is first machined. Next, a hole is drilled radially through the bolt at a predetermined distance from the bolt head. After installation of the mine roof bolt and loading, the strain of the mine roof bolt is measured by generating an ultrasonic pulse at the flat portion. The time of travel of the ultrasonic pulse reflected from the hole is measured. This time of travel is a function of the distance from the flat portion to the hole and increases as the bolt is loaded. Consequently, the time measurement is correlated to the strain in the bolt. Compensation for various factors affecting the travel time are also provided.

Industrial chimney monitoring - contemporary methods

NASA Astrophysics Data System (ADS)

Kaszowska, Olga; Gruchlik, Piotr; Mika, Wiesław

2018-04-01

The paper presents knowledge acquired during the monitoring of a flue-gas stack, performed as part of technical and scientific surveillance of mining activity and its impact on industrial objects. The chimney is located in an area impacted by mining activity since the 1970s, from a coal mine which is no longer in existence. In the period of 2013-16, this area was subject to mining carried out by a mining entrepreneur who currently holds a license to excavate hard coal. Periodic measurements of the deflection of the 113-meter chimney are performed using conventional geodetic methods. The GIG used 3 methods to observe the stack: landbased 3D laser scanning, continuous deflection monitoring with a laser sensor, and drone-based visual inspections. The drone offered the possibility to closely inspect the upper sections of the flue-gas stack, which are difficult to see from the ground level.

Efficient discovery of risk patterns in medical data.

PubMed

Li, Jiuyong; Fu, Ada Wai-chee; Fahey, Paul

2009-01-01

This paper studies a problem of efficiently discovering risk patterns in medical data. Risk patterns are defined by a statistical metric, relative risk, which has been widely used in epidemiological research. To avoid fruitless search in the complete exploration of risk patterns, we define optimal risk pattern set to exclude superfluous patterns, i.e. complicated patterns with lower relative risk than their corresponding simpler form patterns. We prove that mining optimal risk pattern sets conforms an anti-monotone property that supports an efficient mining algorithm. We propose an efficient algorithm for mining optimal risk pattern sets based on this property. We also propose a hierarchical structure to present discovered patterns for the easy perusal by domain experts. The proposed approach is compared with two well-known rule discovery methods, decision tree and association rule mining approaches on benchmark data sets and applied to a real world application. The proposed method discovers more and better quality risk patterns than a decision tree approach. The decision tree method is not designed for such applications and is inadequate for pattern exploring. The proposed method does not discover a large number of uninteresting superfluous patterns as an association mining approach does. The proposed method is more efficient than an association rule mining method. A real world case study shows that the method reveals some interesting risk patterns to medical practitioners. The proposed method is an efficient approach to explore risk patterns. It quickly identifies cohorts of patients that are vulnerable to a risk outcome from a large data set. The proposed method is useful for exploratory study on large medical data to generate and refine hypotheses. The method is also useful for designing medical surveillance systems.

Water budgets and groundwater volumes for abandoned underground mines in the Western Middle Anthracite Coalfield, Schuylkill, Columbia, and Northumberland Counties, Pennsylvania-Preliminary estimates with identification of data needs

USGS Publications Warehouse

Goode, Daniel J.; Cravotta, Charles A.; Hornberger, Roger J.; Hewitt, Michael A.; Hughes, Robert E.; Koury, Daniel J.; Eicholtz, Lee W.

2011-01-01

This report, prepared in cooperation with the Pennsylvania Department of Environmental Protection (PaDEP), the Eastern Pennsylvania Coalition for Abandoned Mine Reclamation, and the Dauphin County Conservation District, provides estimates of water budgets and groundwater volumes stored in abandoned underground mines in the Western Middle Anthracite Coalfield, which encompasses an area of 120 square miles in eastern Pennsylvania. The estimates are based on preliminary simulations using a groundwater-flow model and an associated geographic information system that integrates data on the mining features, hydrogeology, and streamflow in the study area. The Mahanoy and Shamokin Creek Basins were the focus of the study because these basins exhibit extensive hydrologic effects and water-quality degradation from the abandoned mines in their headwaters in the Western Middle Anthracite Coalfield. Proposed groundwater withdrawals from the flooded parts of the mines and stream-channel modifications in selected areas have the potential for altering the distribution of groundwater and the interaction between the groundwater and streams in the area. Preliminary three-dimensional, steady-state simulations of groundwater flow by the use of MODFLOW are presented to summarize information on the exchange of groundwater among adjacent mines and to help guide the management of ongoing data collection, reclamation activities, and water-use planning. The conceptual model includes high-permeability mine voids that are connected vertically and horizontally within multicolliery units (MCUs). MCUs were identified on the basis of mine maps, locations of mine discharges, and groundwater levels in the mines measured by PaDEP. The locations and integrity of mine barriers were determined from mine maps and groundwater levels. The permeability of intact barriers is low, reflecting the hydraulic characteristics of unmined host rock and coal. A steady-state model was calibrated to measured groundwater levels and stream base flow, the latter at many locations composed primarily of discharge from mines. Automatic parameter estimation used MODFLOW-2000 with manual adjustments to constrain parameter values to realistic ranges. The calibrated model supports the conceptual model of high-permeability MCUs separated by low-permeability barriers and streamflow losses and gains associated with mine infiltration and discharge. The simulated groundwater levels illustrate low groundwater gradients within an MCU and abrupt changes in water levels between MCUs. The preliminary model results indicate that the primary result of increased pumping from the mine would be reduced discharge from the mine to streams near the pumping wells. The intact barriers limit the spatial extent of mine dewatering. Considering the simulated groundwater levels, depth of mining, and assumed bulk porosity of 11 or 40 percent for the mined seams, the water volume in storage in the mines of the Western Middle Anthracite Coalfield was estimated to range from 60 to 220 billion gallons, respectively. Details of the groundwater-level distribution and the rates of some mine discharges are not simulated well using the preliminary model. Use of the model results should be limited to evaluation of the conceptual model and its simulation using porous-media flow methods, overall water budgets for the Western Middle Anthracite Coalfield, and approximate storage volumes. Model results should not be considered accurate for detailed simulation of flow within a single MCU or individual flooded mine. Although improvements in the model calibration were possible by introducing spatial variability in permeability parameters and adjusting barrier properties, more detailed parameterizations have increased uncertainty because of the limited data set. The preliminary identification of data needs includes continuous streamflow, mine discharge rate, and groundwater levels in the mines and adjacent areas. Data collected whe

Causes and Consequences of Water Flux on the Example of Transverse Heading Mina in the Salt Mine "Wieliczka" / Przyczyny i Skutki Dopływu Wody na Przykładzie Poprzeczni Mina w Kopalni Soli "Wieliczka"

NASA Astrophysics Data System (ADS)

Gonet, Andrzej; Stryczek, Stanisław; Brudnik, Krzysztof

2012-11-01

The causes of disastrous water flux in the historical Salt Mine "Wieliczka" have been presented on the example of transverse heading Mina at the IV level at a depth of 175 m bsl. The complex geological setting of direct environment of the transverse heading Mina has been described paying attention to unfavorable hydrogeological conditions in the northern part of the salt deposit. The main activities oriented to limiting the water hazard in the Salt Mine "Wieliczka" and the reconstruction of inner safety pillar, which had been seriously damaged by mining activities, have been analyzed. A selection of objects inside the mine, saved from flooding thanks to protection works has been visualized in photos.

Machine Learning and Data Mining Methods in Diabetes Research.

PubMed

Kavakiotis, Ioannis; Tsave, Olga; Salifoglou, Athanasios; Maglaveras, Nicos; Vlahavas, Ioannis; Chouvarda, Ioanna

2017-01-01

The remarkable advances in biotechnology and health sciences have led to a significant production of data, such as high throughput genetic data and clinical information, generated from large Electronic Health Records (EHRs). To this end, application of machine learning and data mining methods in biosciences is presently, more than ever before, vital and indispensable in efforts to transform intelligently all available information into valuable knowledge. Diabetes mellitus (DM) is defined as a group of metabolic disorders exerting significant pressure on human health worldwide. Extensive research in all aspects of diabetes (diagnosis, etiopathophysiology, therapy, etc.) has led to the generation of huge amounts of data. The aim of the present study is to conduct a systematic review of the applications of machine learning, data mining techniques and tools in the field of diabetes research with respect to a) Prediction and Diagnosis, b) Diabetic Complications, c) Genetic Background and Environment, and e) Health Care and Management with the first category appearing to be the most popular. A wide range of machine learning algorithms were employed. In general, 85% of those used were characterized by supervised learning approaches and 15% by unsupervised ones, and more specifically, association rules. Support vector machines (SVM) arise as the most successful and widely used algorithm. Concerning the type of data, clinical datasets were mainly used. The title applications in the selected articles project the usefulness of extracting valuable knowledge leading to new hypotheses targeting deeper understanding and further investigation in DM.

SPMBR: a scalable algorithm for mining sequential patterns based on bitmaps

NASA Astrophysics Data System (ADS)

Xu, Xiwei; Zhang, Changhai

2013-12-01

Now some sequential patterns mining algorithms generate too many candidate sequences, and increase the processing cost of support counting. Therefore, we present an effective and scalable algorithm called SPMBR (Sequential Patterns Mining based on Bitmap Representation) to solve the problem of mining the sequential patterns for large databases. Our method differs from previous related works of mining sequential patterns. The main difference is that the database of sequential patterns is represented by bitmaps, and a simplified bitmap structure is presented firstly. In this paper, First the algorithm generate candidate sequences by SE(Sequence Extension) and IE(Item Extension), and then obtain all frequent sequences by comparing the original bitmap and the extended item bitmap .This method could simplify the problem of mining the sequential patterns and avoid the high processing cost of support counting. Both theories and experiments indicate that the performance of SPMBR is predominant for large transaction databases, the required memory size for storing temporal data is much less during mining process, and all sequential patterns can be mined with feasibility.

Method of underground mining by pillar extraction

DOEpatents

Bowen, Ray J.; Bowen, William R.

1980-08-12

A method of sublevel caving and pillar and top coal extraction for mining thick coal seams includes the advance mining of rooms and crosscuts along the bottom of a seam to a height of about eight feet, and the retreat mining of the top coal from the rooms, crosscuts and portions of the pillars remaining from formation of the rooms and cross-cuts. In the retreat mining, a pocket is formed in a pillar, the top coal above the pocket is drilled, charged and shot, and then the fallen coal is loaded by a continuous miner so that the operator remains under a roof which has not been shot. The top coal from that portion of the room adjacent the pocket is then mined, and another pocket is formed in the pillar. The top coal above the second pocket is mined followed by the mining of the top coal of that portion of the room adjacent the second pocket, all by use of a continuous miner which allows the operator to remain under a roof portion which has not been shot.

The human factor in mining reclamation

USGS Publications Warehouse

Arbogast, Belinda F.; Knepper, Daniel H.; Langer, William H.

2000-01-01

Rapid urbanization of the landscape results in less space available for wildlife habitat, agriculture, and recreation. Mineral resources (especially nonmetallic construction materials) become unrecoverable due to inaccessibility caused by development. This report both describes mine sites with serious problems and draws attention to thoughtful reclamation projects for better future management. It presents information from selected sites in terms of their history, landform, design approach, and visual discernment. Examples from Colorado are included to introduce the broader issue of regions soundly developing mining sites, permitting the best utilization of natural resources, and respecting the landscape.

Maps showing mines, quarries, and prospects, with analyses of samples, Gee Creek Wilderness, Polk and Monroe counties, Tennessee

USGS Publications Warehouse

Gazdik, Gertrude C.; Behum, Paul T.

1983-01-01

During the recent U.S. Bureau of Mines field investigation, 21 samples were collected (fig. 2) and were submitted to the Bureau's Reno Metallurgy Research Center, Reno, Nev., for analysis. All samples were tested for 40 elements by semiquantitative spectrographic analyses. Additional testing by atomic absorption, neutron activation, and wet chemical techniques was performed for selected elements on some samples. Two shale samples were submitted to the Bureau of Mines, Tuscaloosa Metallurgy Research Center, Tuscaloosa, Ala., for the evaluation of ceramic properties. 

Rules of meridians and acupoints selection in treatment of Parkinson's disease based on data mining techniques.

PubMed

Li, Zhe; Hu, Ying-Yu; Zheng, Chun-Ye; Su, Qiao-Zhen; An, Chang; Luo, Xiao-Dong; Liu, Mao-Cai

2018-01-15

To help selecting appropriate meridians and acupoints in clinical practice and experimental study for Parkinson's disease (PD), the rules of meridians and acupoints selection of acupuncture and moxibustion were analyzed in domestic and foreign clinical treatment for PD based on data mining techniques. Literature about PD treated by acupuncture and moxibustion in China and abroad was searched and selected from China National Knowledge Infrastructure and MEDLINE. Then the data from all eligible articles were extracted to establish the database of acupuncture-moxibustion for PD. The association rules of data mining techniques were used to analyze the rules of meridians and acupoints selection. Totally, 168 eligible articles were included and 184 acupoints were applied. The total frequency of acupoints application was 1,090 times. Those acupoints were mainly distributed in head and neck and extremities. Among all, Taichong (LR 3), Baihui (DU 20), Fengchi (GB 20), Hegu (LI 4) and Chorea-tremor Controlled Zone were the top five acupoints that had been used. Superior-inferior acupoints matching was utilized the most. As to involved meridians, Du Meridian, Dan (Gallbladder) Meridian, Dachang (Large Intestine) Meridian, and Gan (Liver) Meridian were the most popular meridians. The application of meridians and acupoints for PD treatment lay emphasis on the acupoints on the head, attach importance to extinguishing Gan wind, tonifying qi and blood, and nourishing sinews, and make good use of superior-inferior acupoints matching.

Streamflow characteristics related to channel geometry of streams in western United States

USGS Publications Warehouse

Hedman, E.R.; Osterkamp, W.R.

1982-01-01

Assessment of surface-mining and reclamation activities generally requires extensive hydrologic data. Adequate streamflow data from instrumented gaging stations rarely are available, and estimates of surface- water discharge based on rainfall-runoff models, drainage area, and basin characteristics sometimes have proven unreliable. Channel-geometry measurements offer an alternative method of quickly and inexpensively estimating stream-flow characteristics for ungaged streams. The method uses the empirical development of equations to yield a discharge value from channel-geometry and channel-material data. The equations are developed by collecting data at numerous streamflow-gaging sites and statistically relating those data to selected discharge characteristics. Mean annual runoff and flood discharges with selected recurrence intervals can be estimated for perennial, intermittent, and ephemeral streams. The equations were developed from data collected in the western one-half of the conterminous United States. The effect of the channel-material and runoff characteristics are accounted for with the equations.

Seedling growth and heavy metal accumulation of candidate woody species for revegetating Korean mine spoils

Treesearch

Kyung Won Seo; Yowhan Son; Charles C. Rhoades; Nam Jin Noh; Jin Woo Koo; Jeong-Gyu Kim

2008-01-01

Selecting plant species that can overcome harsh soil and microclimatic conditions and speed the recovery of degraded minelands remains a worldwide restoration challenge. This study evaluated the potential of three woody species and various organic and inorganic fertilization treatments for revegetating abandoned metalliferous mines in Korea. We compared survival,...

What's Mine Is Mine: Twelve-Month-Olds Use Possessive Pronouns to Identify Referents

ERIC Educational Resources Information Center

Saylor, Megan M.; Ganea, Patricia A.; Vazquez, Maria D.

2011-01-01

This research investigated 12-month-olds' ability to use person-specific language to determine to which of several absent things a person is referring. Infants were introduced to two experimenters who played separately with a different ball. One researcher asked infants to retrieve her object when both balls were hidden. Infants selected the…

Environmental impacts of mercury related to artisanal gold mining in Ghana

NASA Astrophysics Data System (ADS)

Bonzongo, J. C.; Donkor, A. K.; Nartey, V. K.

2003-05-01

In this study, we investigated the extent of contamination of Hg in selected mine-impacted Ghanaian watersheds. Our results are suggestive of a major environmental problem with Hg in Ghana, with total-Hg concentrations ranging from 17 to 2000ng L^{-1} in surface water samples, and in hundreds of ppm for both soils and sediments.

A Predictive Model of Daily Seismic Activity Induced by Mining, Developed with Data Mining Methods

NASA Astrophysics Data System (ADS)

Jakubowski, Jacek

2014-12-01

The article presents the development and evaluation of a predictive classification model of daily seismic energy emissions induced by longwall mining in sector XVI of the Piast coal mine in Poland. The model uses data on tremor energy, basic characteristics of the longwall face and mined output in this sector over the period from July 1987 to March 2011. The predicted binary variable is the occurrence of a daily sum of tremor seismic energies in a longwall that is greater than or equal to the threshold value of 105 J. Three data mining analytical methods were applied: logistic regression,neural networks, and stochastic gradient boosted trees. The boosted trees model was chosen as the best for the purposes of the prediction. The validation sample results showed its good predictive capability, taking the complex nature of the phenomenon into account. This may indicate the applied model's suitability for a sequential, short-term prediction of mining induced seismic activity.

Theoretical approaches to creation of robotic coal mines based on the synthesis of simulation technologies

NASA Astrophysics Data System (ADS)

Fryanov, V. N.; Pavlova, L. D.; Temlyantsev, M. V.

2017-09-01

Methodological approaches to theoretical substantiation of the structure and parameters of robotic coal mines are outlined. The results of mathematical and numerical modeling revealed the features of manifestation of geomechanical and gas dynamic processes in the conditions of robotic mines. Technological solutions for the design and manufacture of technical means for robotic mine are adopted using the method of economic and mathematical modeling and in accordance with the current regulatory documents. For a comparative performance evaluation of technological schemes of traditional and robotic mines, methods of cognitive modeling and matrix search for subsystem elements in the synthesis of a complex geotechnological system are applied. It is substantiated that the process of technical re-equipment of a traditional mine with a phased transition to a robotic mine will reduce unit costs by almost 1.5 times with a significant social effect due to a reduction in the number of personnel engaged in hazardous work.

Method of operator safety assessment for underground mobile mining equipment

NASA Astrophysics Data System (ADS)

Działak, Paulina; Karliński, Jacek; Rusiński, Eugeniusz

2018-01-01

The paper presents a method of assessing the safety of operators of mobile mining equipment (MME), which is adapted to current and future geological and mining conditions. The authors focused on underground mines, with special consideration of copper mines (KGHM). As extraction reaches into deeper layers of the deposit it can activate natural hazards, which, thus far, have been considered unusual and whose range and intensity are different depending on the field of operation. One of the main hazards that affect work safety and can become the main barrier in the exploitation of deposits at greater depths is climate threat. The authors have analysed the phenomena which may impact the safety of MME operators, with consideration of accidents that have not yet been studied and are not covered by the current safety standards for this group of miners. An attempt was made to develop a method for assessing the safety of MME operators, which takes into account the mentioned natural hazards and which is adapted to current and future environmental conditions in underground mines.

Selected hydrologic data, 1931-77, Wasatch Plateau-Book Cliffs coal-fields area, Utah

USGS Publications Warehouse

Waddell, K.M.; Vickers, H.L.; Upton, Robbin T.; Contratto, P. Kay

1978-01-01

The Wasatch Plateau-Book Cliffs coal-fields area in east-central Utah includes a significant part of the State's coal resources and is currently (1977) the most active coal-mining area in the State.This report presents data gathered by the U.S. Geological Survey as part of a hydrologic reconnaissance carried out during the period July 1975-September 1977 in cooperation with the U.S. Bureau of Land Management, as well as selected information for water-years 1931-75. The data were obtained in the field or from private, State, and other Federal agencies. The purpose of this report is to make the data available to those engaged in coal mining, to those assessing water resources that may possibly be affected by coal mining, and to supplement an interpretive report that will be published at a later date.

Application of fuel cell for pyrite and heavy metal containing mining waste

NASA Astrophysics Data System (ADS)

Keum, H.; Ju, W. J.; Jho, E. H.; Nam, K.

2015-12-01

Once pyrite and heavy metal containing mining waste reacts with water and air it produces acid mine drainage (AMD) and leads to the other environmental problems such as contamination of surrounding soils. Pyrite is the major source of AMD and it can be controlled using a biological-electrochemical dissolution method. By enhancing the dissolution of pyrite using fuel cell technology, not only mining waste be beneficially utilized but also be treated at the same time by. As pyrite-containing mining waste is oxidized in the anode of the fuel cell, electrons and protons are generated, and electrons moves through an external load to cathode reducing oxygen to water while protons migrate to cathode through a proton exchange membrane. Iron-oxidizing bacteria such as Acidithiobacillus ferrooxidans, which can utilize Fe as an electron donor promotes pyrite dissolution and hence enhances electrochemical dissolution of pyrite from mining waste. In this study mining waste from a zinc mine in Korea containing 17 wt% pyrite and 9% As was utilized as a fuel for the fuel cell inoculated with A. ferrooxidans. Electrochemically dissolved As content and chemically dissolved As content was compared. With the initial pH of 3.5 at 23℃, the dissolved As concentration increased (from 4.0 to 13 mg/L after 20 d) in the fuel cell, while it kept decreased in the chemical reactor (from 12 to 0.43 mg/L after 20 d). The fuel cell produced 0.09 V of open circuit voltage with the maximum power density of 0.84 mW/m2. Dissolution of As from mining waste was enhanced through electrochemical reaction. Application of fuel cell technology is a novel treatment method for pyrite and heavy metals containing mining waste, and this method is beneficial for mining environment as well as local community of mining areas.