Spatial and temporal patterns in trace element deposition to lakes in the Athabasca oil sands region (Alberta, Canada)

NASA Astrophysics Data System (ADS)

Cooke, Colin A.; Kirk, Jane L.; Muir, Derek C. G.; Wiklund, Johan A.; Wang, Xiaowa; Gleason, Amber; Evans, Marlene S.

2017-12-01

The mining and processing of the Athabasca oil sands (Alberta, Canada) has been occurring for decades; however, a lack of consistent regional monitoring has obscured the long-term environmental impact. Here, we present sediment core results to reconstruct spatial and temporal patterns in trace element deposition to lakes in the Athabasca oil sands region. Early mining operations (during the 1970s and 1980s) led to elevated V and Pb inputs to lakes located <50 km from mining operations. Subsequent improvements to mining and upgrading technologies since the 1980s have reduced V and Pb loading to near background levels at many sites. In contrast, Hg deposition increased by a factor of ~3 to all 20 lakes over the 20th century, reflecting global-scale patterns in atmospheric Hg emissions. Base cation deposition (from fugitive dust emissions) has not measurably impacted regional lake sediments. Instead, results from a principal components analysis suggest that the presence of carbonate bedrock underlying lakes located close to development appears to exert a first-order control over lake sediment base cation concentrations and overall lake sediment geochemical composition. Trace element concentrations generally did not exceed Canadian sediment quality guidelines, and no spatial or temporal trends were observed in the frequency of guideline exceedence. Our results demonstrate that early mining efforts had an even greater impact on trace element cycling than has been appreciated previously, placing recent monitoring efforts in a critical long-term context.

Mineralogical controls on mobility of rare earth elements in acid mine drainage environments.

PubMed

Soyol-Erdene, T O; Valente, T; Grande, J A; de la Torre, M L

2018-08-01

Rare earth elements (REE) were analyzed in river waters, acid mine waters, and extracts of secondary precipitates collected in the Iberian Pyrite Belt. The obtained concentrations of the REE in river water and mine waters (acid mine drainage - AMD) were in the range of 0.57 μg/L (Lu) and 2579 μg/L (Ce), which is higher than previously reported in surface waters from the Iberian Pyrite Belt, but are comparable with previous findings from AMD worldwide. Total REE concentrations in river waters were ranged between 297 μg/L (Cobica River) and 7032 μg/L (Trimpancho River) with an average of 2468 μg/L. NASC (North American Shale Composite) normalized REE patterns for river and acid mine waters show clear convex curvatures in middle-REE (MREE) with respect to light- and heavy-REE. During the dissolution experiments of AMD-precipitates, heavy-REE and middle-REE generate the most enriched patterns in the solution. A small number of precipitates did not display MREE enrichment (an index Gd n /Lu n  < 1.0) in NASC normalized pattern and produced relatively lower REE concentrations in extracts. Additionally, very few samples, which mainly contained aluminum sulfates, e.g., pickeringite and alunogen, displayed light-REE enrichment relative to heavy-REE (HREE). In general, the highest retention of REE occurs in samples enriched in magnesium (epsomite or hexahydrite) and aluminum sulfates, mainly pickeringite. Copyright © 2018 Elsevier Ltd. All rights reserved.

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.

Mining of high utility-probability sequential patterns from uncertain databases

PubMed Central

Zhang, Binbin; Fournier-Viger, Philippe; Li, Ting

2017-01-01

High-utility sequential pattern mining (HUSPM) has become an important issue in the field of data mining. Several HUSPM algorithms have been designed to mine high-utility sequential patterns (HUPSPs). They have been applied in several real-life situations such as for consumer behavior analysis and event detection in sensor networks. Nonetheless, most studies on HUSPM have focused on mining HUPSPs in precise data. But in real-life, uncertainty is an important factor as data is collected using various types of sensors that are more or less accurate. Hence, data collected in a real-life database can be annotated with existing probabilities. This paper presents a novel pattern mining framework called high utility-probability sequential pattern mining (HUPSPM) for mining high utility-probability sequential patterns (HUPSPs) in uncertain sequence databases. A baseline algorithm with three optional pruning strategies is presented to mine HUPSPs. Moroever, to speed up the mining process, a projection mechanism is designed to create a database projection for each processed sequence, which is smaller than the original database. Thus, the number of unpromising candidates can be greatly reduced, as well as the execution time for mining HUPSPs. Substantial experiments both on real-life and synthetic datasets show that the designed algorithm performs well in terms of runtime, number of candidates, memory usage, and scalability for different minimum utility and minimum probability thresholds. PMID:28742847

Handling Dynamic Weights in Weighted Frequent Pattern Mining

NASA Astrophysics Data System (ADS)

Ahmed, Chowdhury Farhan; Tanbeer, Syed Khairuzzaman; Jeong, Byeong-Soo; Lee, Young-Koo

Even though weighted frequent pattern (WFP) mining is more effective than traditional frequent pattern mining because it can consider different semantic significances (weights) of items, existing WFP algorithms assume that each item has a fixed weight. But in real world scenarios, the weight (price or significance) of an item can vary with time. Reflecting these changes in item weight is necessary in several mining applications, such as retail market data analysis and web click stream analysis. In this paper, we introduce the concept of a dynamic weight for each item, and propose an algorithm, DWFPM (dynamic weighted frequent pattern mining), that makes use of this concept. Our algorithm can address situations where the weight (price or significance) of an item varies dynamically. It exploits a pattern growth mining technique to avoid the level-wise candidate set generation-and-test methodology. Furthermore, it requires only one database scan, so it is eligible for use in stream data mining. An extensive performance analysis shows that our algorithm is efficient and scalable for WFP mining using dynamic weights.

Design pattern mining using distributed learning automata and DNA sequence alignment.

PubMed

Esmaeilpour, Mansour; Naderifar, Vahideh; Shukur, Zarina

2014-01-01

Over the last decade, design patterns have been used extensively to generate reusable solutions to frequently encountered problems in software engineering and object oriented programming. A design pattern is a repeatable software design solution that provides a template for solving various instances of a general problem. This paper describes a new method for pattern mining, isolating design patterns and relationship between them; and a related tool, DLA-DNA for all implemented pattern and all projects used for evaluation. DLA-DNA achieves acceptable precision and recall instead of other evaluated tools based on distributed learning automata (DLA) and deoxyribonucleic acid (DNA) sequences alignment. The proposed method mines structural design patterns in the object oriented source code and extracts the strong and weak relationships between them, enabling analyzers and programmers to determine the dependency rate of each object, component, and other section of the code for parameter passing and modular programming. The proposed model can detect design patterns better that available other tools those are Pinot, PTIDEJ and DPJF; and the strengths of their relationships. The result demonstrate that whenever the source code is build standard and non-standard, based on the design patterns, then the result of the proposed method is near to DPJF and better that Pinot and PTIDEJ. The proposed model is tested on the several source codes and is compared with other related models and available tools those the results show the precision and recall of the proposed method, averagely 20% and 9.6% are more than Pinot, 27% and 31% are more than PTIDEJ and 3.3% and 2% are more than DPJF respectively. The primary idea of the proposed method is organized in two following steps: the first step, elemental design patterns are identified, while at the second step, is composed to recognize actual design patterns.

A novel water quality data analysis framework based on time-series data mining.

PubMed

Deng, Weihui; Wang, Guoyin

2017-07-01

The rapid development of time-series data mining provides an emerging method for water resource management research. In this paper, based on the time-series data mining methodology, we propose a novel and general analysis framework for water quality time-series data. It consists of two parts: implementation components and common tasks of time-series data mining in water quality data. In the first part, we propose to granulate the time series into several two-dimensional normal clouds and calculate the similarities in the granulated level. On the basis of the similarity matrix, the similarity search, anomaly detection, and pattern discovery tasks in the water quality time-series instance dataset can be easily implemented in the second part. We present a case study of this analysis framework on weekly Dissolve Oxygen time-series data collected from five monitoring stations on the upper reaches of Yangtze River, China. It discovered the relationship of water quality in the mainstream and tributary as well as the main changing patterns of DO. The experimental results show that the proposed analysis framework is a feasible and efficient method to mine the hidden and valuable knowledge from water quality historical time-series data. Copyright © 2017 Elsevier Ltd. All rights reserved.

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)

Large Scale Data Mining to Improve Usability of Data: An Intelligent Archive Testbed

NASA Technical Reports Server (NTRS)

Ramapriyan, Hampapuram; Isaac, David; Yang, Wenli; Morse, Steve

2005-01-01

Research in certain scientific disciplines - including Earth science, particle physics, and astrophysics - continually faces the challenge that the volume of data needed to perform valid scientific research can at times overwhelm even a sizable research community. The desire to improve utilization of this data gave rise to the Intelligent Archives project, which seeks to make data archives active participants in a knowledge building system capable of discovering events or patterns that represent new information or knowledge. Data mining can automatically discover patterns and events, but it is generally viewed as unsuited for large-scale use in disciplines like Earth science that routinely involve very high data volumes. Dozens of research projects have shown promising uses of data mining in Earth science, but all of these are based on experiments with data subsets of a few gigabytes or less, rather than the terabytes or petabytes typically encountered in operational systems. To bridge this gap, the Intelligent Archives project is establishing a testbed with the goal of demonstrating the use of data mining techniques in an operationally-relevant environment. This paper discusses the goals of the testbed and the design choices surrounding critical issues that arose during testbed implementation.

Mining Recent Temporal Patterns for Event Detection in Multivariate Time Series Data

PubMed Central

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

2015-01-01

Improving the performance of classifiers using pattern mining techniques has been an active topic of data mining research. In this work we introduce the recent temporal pattern mining framework for finding predictive patterns for monitoring and event detection problems in complex multivariate time series data. This framework first converts time series into time-interval sequences of temporal abstractions. It then constructs more complex temporal patterns backwards in time using temporal operators. We apply our framework to health care data of 13,558 diabetic patients and show its benefits by efficiently finding useful patterns for detecting and diagnosing adverse medical conditions that are associated with diabetes. PMID:25937993

Percolator: Scalable Pattern Discovery in Dynamic Graphs

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

Choudhury, Sutanay; Purohit, Sumit; Lin, Peng

We demonstrate Percolator, a distributed system for graph pattern discovery in dynamic graphs. In contrast to conventional mining systems, Percolator advocates efficient pattern mining schemes that (1) support pattern detection with keywords; (2) integrate incremental and parallel pattern mining; and (3) support analytical queries such as trend analysis. The core idea of Percolator is to dynamically decide and verify a small fraction of patterns and their in- stances that must be inspected in response to buffered updates in dynamic graphs, with a total mining cost independent of graph size. We demonstrate a) the feasibility of incremental pattern mining by walkingmore » through each component of Percolator, b) the efficiency and scalability of Percolator over the sheer size of real-world dynamic graphs, and c) how the user-friendly GUI of Percolator inter- acts with users to support keyword-based queries that detect, browse and inspect trending patterns. We also demonstrate two user cases of Percolator, in social media trend analysis and academic collaboration analysis, respectively.« less

A Node Linkage Approach for Sequential Pattern Mining

PubMed Central

Navarro, Osvaldo; Cumplido, René; Villaseñor-Pineda, Luis; Feregrino-Uribe, Claudia; Carrasco-Ochoa, Jesús Ariel

2014-01-01

Sequential Pattern Mining is a widely addressed problem in data mining, with applications such as analyzing Web usage, examining purchase behavior, and text mining, among others. Nevertheless, with the dramatic increase in data volume, the current approaches prove inefficient when dealing with large input datasets, a large number of different symbols and low minimum supports. In this paper, we propose a new sequential pattern mining algorithm, which follows a pattern-growth scheme to discover sequential patterns. Unlike most pattern growth algorithms, our approach does not build a data structure to represent the input dataset, but instead accesses the required sequences through pseudo-projection databases, achieving better runtime and reducing memory requirements. Our algorithm traverses the search space in a depth-first fashion and only preserves in memory a pattern node linkage and the pseudo-projections required for the branch being explored at the time. Experimental results show that our new approach, the Node Linkage Depth-First Traversal algorithm (NLDFT), has better performance and scalability in comparison with state of the art algorithms. PMID:24933123

Method of locating underground mines fires

DOEpatents

Laage, Linneas; Pomroy, William

1992-01-01

An improved method of locating an underground mine fire by comparing the pattern of measured combustion product arrival times at detector locations with a real time computer-generated array of simulated patterns. A number of electronic fire detection devices are linked thru telemetry to a control station on the surface. The mine's ventilation is modeled on a digital computer using network analysis software. The time reguired to locate a fire consists of the time required to model the mines' ventilation, generate the arrival time array, scan the array, and to match measured arrival time patterns to the simulated patterns.

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.

Design Pattern Mining Using Distributed Learning Automata and DNA Sequence Alignment

PubMed Central

Esmaeilpour, Mansour; Naderifar, Vahideh; Shukur, Zarina

2014-01-01

Context Over the last decade, design patterns have been used extensively to generate reusable solutions to frequently encountered problems in software engineering and object oriented programming. A design pattern is a repeatable software design solution that provides a template for solving various instances of a general problem. Objective This paper describes a new method for pattern mining, isolating design patterns and relationship between them; and a related tool, DLA-DNA for all implemented pattern and all projects used for evaluation. DLA-DNA achieves acceptable precision and recall instead of other evaluated tools based on distributed learning automata (DLA) and deoxyribonucleic acid (DNA) sequences alignment. Method The proposed method mines structural design patterns in the object oriented source code and extracts the strong and weak relationships between them, enabling analyzers and programmers to determine the dependency rate of each object, component, and other section of the code for parameter passing and modular programming. The proposed model can detect design patterns better that available other tools those are Pinot, PTIDEJ and DPJF; and the strengths of their relationships. Results The result demonstrate that whenever the source code is build standard and non-standard, based on the design patterns, then the result of the proposed method is near to DPJF and better that Pinot and PTIDEJ. The proposed model is tested on the several source codes and is compared with other related models and available tools those the results show the precision and recall of the proposed method, averagely 20% and 9.6% are more than Pinot, 27% and 31% are more than PTIDEJ and 3.3% and 2% are more than DPJF respectively. Conclusion The primary idea of the proposed method is organized in two following steps: the first step, elemental design patterns are identified, while at the second step, is composed to recognize actual design patterns. PMID:25243670

Production and precipitation of rare earth elements in acidic to alkaline coal mine discharges, Appalachian Basin, USA

NASA Astrophysics Data System (ADS)

Stewart, B. W.; Capo, R. C.; Hedin, B. C.; Wallrich, I. L. R.; Hedin, R. S.

2016-12-01

Abandoned coal mine discharges are a serious threat to ground and surface waters due to their high metal content and often high acidity. However, these discharges represent a potential source of rare earth elements (REE), many of which are considered to be critical resources. Trace element data from 18 coal mine drainage (CMD) sites within the Appalachian Basin suggest CMD is enriched in total REE by 1-4 orders of magnitude relative to concentrations expected in unaffected surface or ground waters. When normalized to the North American Shale Composite (NASC), the discharges generally show a pattern of enrichment in the middle REE, including several identified as critical resources (Nd, Eu, Dy, Tb). In contrast, shale, sandstone and coal samples from Appalachian Basin coal-bearing units have concentrations and patterns similar to NASC, indicating that the REE in CMD are fractionated during interaction with rock in the mine pool. The highest total REE contents (up to 2800 mg/L) are found in low-pH discharges (acid mine drainage, or AMD). A precipitous drop in REE concentration in CMD with pH ≥6.6 suggests adsorption or precipitation of REE in the mine pool at circumneutral pH. Precipitated solids from 21 CMD active and passive treatment sites in the Appalachian Basin, including Fe oxy-hydroxides, Ca-Mg lime slurries, and Si- and Al-rich precipitates, are enriched in total REE content relative to the average CMD discharges by about four orders of magnitude. Similar REE trends in the discharges and precipitates, including MREE enrichment, suggest minimal fractionation of REE during precipitation; direct comparisons over multiple seasonal cycles are needed to confirm this. Although the data are limited, Al-rich precipitates generally have high REE concentrations, while those in iron oxy-hydroxides tend to be lower. Based on the area of mined coal in the Appalachian Basin, estimated infiltration rates, and the mean REE flux from discharges analyzed in this study and that of Cravotta and Brady (2015, Appl. Geochem. 62, 108-130), we estimate that coal mine drainage outflows in this region generate approximately 450 metric tons of dissolved REE per year, a portion of which could be targeted for resource recovery during CMD treatment.

Mining and Modeling Real-World Networks: Patterns, Anomalies, and Tools

ERIC Educational Resources Information Center

Akoglu, Leman

2012-01-01

Large real-world graph (a.k.a network, relational) data are omnipresent, in online media, businesses, science, and the government. Analysis of these massive graphs is crucial, in order to extract descriptive and predictive knowledge with many commercial, medical, and environmental applications. In addition to its general structure, knowing what…

Cancer surveillance using data warehousing, data mining, and decision support systems.

PubMed

Forgionne, G A; Gangopadhyay, A; Adya, M

2000-08-01

This article discusses how data warehousing, data mining, and decision support systems can reduce the national cancer burden or the oral complications of cancer therapies, especially as related to oral and pharyngeal cancers. An information system is presented that will deliver the necessary information technology to clinical, administrative, and policy researchers and analysts in an effective and efficient manner. The system will deliver the technology and knowledge that users need to readily: (1) organize relevant claims data, (2) detect cancer patterns in general and special populations, (3) formulate models that explain the patterns, and (4) evaluate the efficacy of specified treatments and interventions with the formulations. Such a system can be developed through a proven adaptive design strategy, and the implemented system can be tested on State of Maryland Medicaid data (which includes women, minorities, and children).

Analysis of Human Mobility Based on Cellular Data

NASA Astrophysics Data System (ADS)

Arifiansyah, F.; Saptawati, G. A. P.

2017-01-01

Nowadays not only adult but even teenager and children have then own mobile phones. This phenomena indicates that the mobile phone becomes an important part of everyday’s life. Based on these indication, the amount of cellular data also increased rapidly. Cellular data defined as the data that records communication among mobile phone users. Cellular data is easy to obtain because the telecommunications company had made a record of the data for the billing system of the company. Billing data keeps a log of the users cellular data usage each time. We can obtained information from the data about communication between users. Through data visualization process, an interesting pattern can be seen in the raw cellular data, so that users can obtain prior knowledge to perform data analysis. Cellular data processing can be done using data mining to find out human mobility patterns and on the existing data. In this paper, we use frequent pattern mining and finding association rules to observe the relation between attributes in cellular data and then visualize them. We used weka tools for finding the rules in stage of data mining. Generally, the utilization of cellular data can provide supporting information for the decision making process and become a data support to provide solutions and information needed by the decision makers.

Research on parallel algorithm for sequential pattern mining

NASA Astrophysics Data System (ADS)

Zhou, Lijuan; Qin, Bai; Wang, Yu; Hao, Zhongxiao

2008-03-01

Sequential pattern mining is the mining of frequent sequences related to time or other orders from the sequence database. Its initial motivation is to discover the laws of customer purchasing in a time section by finding the frequent sequences. In recent years, sequential pattern mining has become an important direction of data mining, and its application field has not been confined to the business database and has extended to new data sources such as Web and advanced science fields such as DNA analysis. The data of sequential pattern mining has characteristics as follows: mass data amount and distributed storage. Most existing sequential pattern mining algorithms haven't considered the above-mentioned characteristics synthetically. According to the traits mentioned above and combining the parallel theory, this paper puts forward a new distributed parallel algorithm SPP(Sequential Pattern Parallel). The algorithm abides by the principal of pattern reduction and utilizes the divide-and-conquer strategy for parallelization. The first parallel task is to construct frequent item sets applying frequent concept and search space partition theory and the second task is to structure frequent sequences using the depth-first search method at each processor. The algorithm only needs to access the database twice and doesn't generate the candidated sequences, which abates the access time and improves the mining efficiency. Based on the random data generation procedure and different information structure designed, this paper simulated the SPP algorithm in a concrete parallel environment and implemented the AprioriAll algorithm. The experiments demonstrate that compared with AprioriAll, the SPP algorithm had excellent speedup factor and efficiency.

Mercury and methylmercury concentrations and loads in the Cache Creek watershed, California

USGS Publications Warehouse

Domagalski, Joseph L.; Alpers, Charles N.; Slotton, D.G.; Suchanek, T.H.; Ayers, S.M.

2004-01-01

Concentrations and loads of total mercury and methylmercury were measured in streams draining abandoned mercury mines and in the proximity of geothermal discharge in the Cache Creek watershed of California during a 17-month period from January 2000 through May 2001. Rainfall and runoff were lower than long-term averages during the study period. The greatest loading of mercury and methylmercury from upstream sources to downstream receiving waters, such as San Francisco Bay, generally occurred during or after winter rainfall events. During the study period, loads of mercury and methylmercury from geothermal sources tended to be greater than those from abandoned mining areas, a pattern attributable to the lack of large precipitation events capable of mobilizing significant amounts of either mercury-laden sediment or dissolved mercury and methylmercury from mine waste. Streambed sediments of Cache Creek are a significant source of mercury and methylmercury to downstream receiving bodies of water. Much of the mercury in these sediments is the result of deposition over the last 100-150 years by either storm-water runoff, from abandoned mines, or continuous discharges from geothermal areas. Several geochemical constituents were useful as natural tracers for mining and geothermal areas, including the aqueous concentrations of boron, chloride, lithium and sulfate, and the stable isotopes of hydrogen and oxygen in water. Stable isotopes of water in areas draining geothermal discharges showed a distinct trend toward enrichment of 18O compared with meteoric waters, whereas much of the runoff from abandoned mines indicated a stable isotopic pattern more consistent with local meteoric water. ?? 2004 Elsevier B.V. All rights reserved.

Association mining of dependency between time series

NASA Astrophysics Data System (ADS)

Hafez, Alaaeldin

2001-03-01

Time series analysis is considered as a crucial component of strategic control over a broad variety of disciplines in business, science and engineering. Time series data is a sequence of observations collected over intervals of time. Each time series describes a phenomenon as a function of time. Analysis on time series data includes discovering trends (or patterns) in a time series sequence. In the last few years, data mining has emerged and been recognized as a new technology for data analysis. Data Mining is the process of discovering potentially valuable patterns, associations, trends, sequences and dependencies in data. Data mining techniques can discover information that many traditional business analysis and statistical techniques fail to deliver. In this paper, we adapt and innovate data mining techniques to analyze time series data. By using data mining techniques, maximal frequent patterns are discovered and used in predicting future sequences or trends, where trends describe the behavior of a sequence. In order to include different types of time series (e.g. irregular and non- systematic), we consider past frequent patterns of the same time sequences (local patterns) and of other dependent time sequences (global patterns). We use the word 'dependent' instead of the word 'similar' for emphasis on real life time series where two time series sequences could be completely different (in values, shapes, etc.), but they still react to the same conditions in a dependent way. In this paper, we propose the Dependence Mining Technique that could be used in predicting time series sequences. The proposed technique consists of three phases: (a) for all time series sequences, generate their trend sequences, (b) discover maximal frequent trend patterns, generate pattern vectors (to keep information of frequent trend patterns), use trend pattern vectors to predict future time series sequences.

76 FR 25277 - Examinations of Work Areas in Underground Coal Mines and Pattern of Violations

Federal Register 2010, 2011, 2012, 2013, 2014

2011-05-04

..., 1219-AB73 Examinations of Work Areas in Underground Coal Mines and Pattern of Violations AGENCY: Mine... four public hearings on the Agency's proposed rules for Examinations of Work Areas in Underground Coal... 1219-AB75'' for Examinations of Work Areas in Underground Coal Mines' submissions, and with ``RIN 1219...

Spatial Point Data Analysis of Geolocated Tweets in the First Day of Eid Al-Fitr 2017 in Java Island

NASA Astrophysics Data System (ADS)

Wibowo, T. W.

2017-12-01

Eid Al-Fitr is a worldwide Muslim feast day, which in Indonesia generally accompanied by tradition of going home (mudik). The demographic patterns at the time of the holiday are generally shifted, in which some urban residents will travel to their hometowns. The impact of this shifting is that there is a quite massive mobility of the population, which is generally accompanied by traffic congestion. The presence of location sensors on smartphone devices, open the opportunity to map the movement of the population in realtime or near-realtime. Especially now that social media applications have been integrated with the capability to include location information. One of the popular social media applications in Indonesia is Twitter, which provides microblogging facilities to its users. This study aims to analyze the pattern of Geolocated Tweets data uploaded by Twitter users on the first day of Eid Al-Fitr (1 Syawal 1438H). Geolocated Tweets data mining is done by using Streaming API (Application Programming Interface) and Python programming language. There are 13,224 Geolocated Tweets points obtained at the location of the study. Various point data analysis techniques applied to the data have been collected, such as density analysis, pattern analysis, and proximity analysis. In general, active Twitter users are dominated by residents in major cities, such as Jakarta, Bandung, Surabaya, Yogyakarta, Surakarta and Semarang. The results of the analysis can be used to determine whether the Geolocated Tweets data mined by the Streaming API method can be used to represent the movement of the population when mudik.

Monitoring coal mine changes and their impact on landscape patterns in an alpine region: a case study of the Muli coal mine in the Qinghai-Tibet Plateau.

PubMed

Qian, Dawen; Yan, Changzhen; Xing, Zanpin; Xiu, Lina

2017-10-14

The Muli coal mine is the largest open-cast coal mine in the Qinghai-Tibet Plateau, and it consists of two independent mining sites named Juhugeng and Jiangcang. It has received much attention due to the ecological problems caused by rapid expansion in recent years. The objective of this paper was to monitor the mining area and its surrounding land cover over the period 1976-2016 utilizing Landsat images, and the network structure of land cover changes was determined to visualize the relationships and pattern of the mining-induced land cover changes. In addition, the responses of the surrounding landscape pattern were analysed by constructing gradient transects. The results show that the mining area was increasing in size, especially after 2000 (increased by 71.68 km 2 ), and this caused shrinkage of the surrounding lands, including alpine meadow wetland (53.44 km 2 ), alpine meadow (6.28 km 2 ) and water (6.24 km 2 ). The network structure of the mining area revealed the changes in lands surrounding the mining area. The impact of mining development on landscape patterns was mainly distributed within a range of 1-6 km. Alpine meadow wetland was most affected in Juhugeng, while alpine meadow was most affected in Jiangcang. The results of this study provide a reference for the ecological assessment and restoration of the Muli coal mine land.

30 CFR 816.81 - Coal mine waste: General requirements.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 30 Mineral Resources 3 2012-07-01 2012-07-01 false Coal mine waste: General requirements. 816.81... ACTIVITIES § 816.81 Coal mine waste: General requirements. (a) General. All coal mine waste disposed of in an... within a permit area, which are approved by the regulatory authority for this purpose. Coal mine waste...

30 CFR 817.81 - Coal mine waste: General requirements.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 30 Mineral Resources 3 2012-07-01 2012-07-01 false Coal mine waste: General requirements. 817.81... ACTIVITIES § 817.81 Coal mine waste: General requirements. (a) General. All coal mine waste disposed of in an... within a permit area, which are approved by the regulatory authority for this purpose. Coal mine waste...

30 CFR 817.81 - Coal mine waste: General requirements.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 3 2011-07-01 2011-07-01 false Coal mine waste: General requirements. 817.81... ACTIVITIES § 817.81 Coal mine waste: General requirements. (a) General. All coal mine waste disposed of in an... within a permit area, which are approved by the regulatory authority for this purpose. Coal mine waste...

30 CFR 816.81 - Coal mine waste: General requirements.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 30 Mineral Resources 3 2013-07-01 2013-07-01 false Coal mine waste: General requirements. 816.81... ACTIVITIES § 816.81 Coal mine waste: General requirements. (a) General. All coal mine waste disposed of in an... within a permit area, which are approved by the regulatory authority for this purpose. Coal mine waste...

30 CFR 817.81 - Coal mine waste: General requirements.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 30 Mineral Resources 3 2013-07-01 2013-07-01 false Coal mine waste: General requirements. 817.81... ACTIVITIES § 817.81 Coal mine waste: General requirements. (a) General. All coal mine waste disposed of in an... within a permit area, which are approved by the regulatory authority for this purpose. Coal mine waste...

30 CFR 816.81 - Coal mine waste: General requirements.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 3 2010-07-01 2010-07-01 false Coal mine waste: General requirements. 816.81... ACTIVITIES § 816.81 Coal mine waste: General requirements. (a) General. All coal mine waste disposed of in an... within a permit area, which are approved by the regulatory authority for this purpose. Coal mine waste...

30 CFR 816.81 - Coal mine waste: General requirements.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 3 2011-07-01 2011-07-01 false Coal mine waste: General requirements. 816.81... ACTIVITIES § 816.81 Coal mine waste: General requirements. (a) General. All coal mine waste disposed of in an... within a permit area, which are approved by the regulatory authority for this purpose. Coal mine waste...

30 CFR 816.81 - Coal mine waste: General requirements.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 30 Mineral Resources 3 2014-07-01 2014-07-01 false Coal mine waste: General requirements. 816.81... ACTIVITIES § 816.81 Coal mine waste: General requirements. (a) General. All coal mine waste disposed of in an... within a permit area, which are approved by the regulatory authority for this purpose. Coal mine waste...

30 CFR 817.81 - Coal mine waste: General requirements.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 30 Mineral Resources 3 2014-07-01 2014-07-01 false Coal mine waste: General requirements. 817.81... ACTIVITIES § 817.81 Coal mine waste: General requirements. (a) General. All coal mine waste disposed of in an... within a permit area, which are approved by the regulatory authority for this purpose. Coal mine waste...

30 CFR 817.81 - Coal mine waste: General requirements.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 3 2010-07-01 2010-07-01 false Coal mine waste: General requirements. 817.81... ACTIVITIES § 817.81 Coal mine waste: General requirements. (a) General. All coal mine waste disposed of in an... within a permit area, which are approved by the regulatory authority for this purpose. Coal mine waste...

Working with Data: Discovering Knowledge through Mining and Analysis; Systematic Knowledge Management and Knowledge Discovery; Text Mining; Methodological Approach in Discovering User Search Patterns through Web Log Analysis; Knowledge Discovery in Databases Using Formal Concept Analysis; Knowledge Discovery with a Little Perspective.

ERIC Educational Resources Information Center

Qin, Jian; Jurisica, Igor; Liddy, Elizabeth D.; Jansen, Bernard J; Spink, Amanda; Priss, Uta; Norton, Melanie J.

2000-01-01

These six articles discuss knowledge discovery in databases (KDD). Topics include data mining; knowledge management systems; applications of knowledge discovery; text and Web mining; text mining and information retrieval; user search patterns through Web log analysis; concept analysis; data collection; and data structure inconsistency. (LRW)

Differential affinities of MinD and MinE to anionic phospholipid influence Min Patterning dynamics in vitro

PubMed Central

Vecchiarelli, Anthony G.; Li, Min; Mizuuchi, Michiyo; Mizuuchi, Kiyoshi

2014-01-01

The E. coli Min system forms a cell-pole-to-cell-pole oscillator that positions the divisome at mid-cell. The MinD ATPase binds the membrane and recruits the cell division inhibitor MinC. MinE interacts with and releases MinD (and MinC) from the membrane. The chase of MinD by MinE creates the in vivo oscillator that maintains a low level of the division inhibitor at mid-cell. In vitro reconstitution and visualization of Min proteins on a supported lipid bilayer has provided significant advances in understanding Min patterns in vivo. Here we studied the effects of flow, lipid composition, and salt concentration on Min patterning. Flow and no-flow conditions both supported Min protein patterns with somewhat different characteristics. Without flow, MinD and MinE formed spiraling waves. MinD and, to a greater extent MinE, have stronger affinities for anionic phospholipid. MinD-independent binding of MinE to anionic lipid resulted in slower and narrower waves. MinE binding to the bilayer was also more susceptible to changes in ionic strength than MinD. We find that modulating protein diffusion with flow, or membrane binding affinities with changes in lipid composition or salt concentration, can differentially affect the retention time of MinD and MinE, leading to spatiotemporal changes in Min patterning. PMID:24930948

String Mining in Bioinformatics

NASA Astrophysics Data System (ADS)

Abouelhoda, Mohamed; Ghanem, Moustafa

Sequence analysis is a major area in bioinformatics encompassing the methods and techniques for studying the biological sequences, DNA, RNA, and proteins, on the linear structure level. The focus of this area is generally on the identification of intra- and inter-molecular similarities. Identifying intra-molecular similarities boils down to detecting repeated segments within a given sequence, while identifying inter-molecular similarities amounts to spotting common segments among two or multiple sequences. From a data mining point of view, sequence analysis is nothing but string- or pattern mining specific to biological strings. For a long time, this point of view, however, has not been explicitly embraced neither in the data mining nor in the sequence analysis text books, which may be attributed to the co-evolution of the two apparently independent fields. In other words, although the word "data-mining" is almost missing in the sequence analysis literature, its basic concepts have been implicitly applied. Interestingly, recent research in biological sequence analysis introduced efficient solutions to many problems in data mining, such as querying and analyzing time series [49,53], extracting information from web pages [20], fighting spam mails [50], detecting plagiarism [22], and spotting duplications in software systems [14].

76 FR 4469 - Privacy Act of 1974; Report of Modified or Altered System of Records

Federal Register 2010, 2011, 2012, 2013, 2014

2011-01-25

... Records, 09-20-0153, ``Mortality Studies in Coal Mining, Metal and Non-metal Mining and General Industry... Coal Mining, Metal and Non-metal Mining and General Industry, HHS/CDC/NIOSH.'' The purpose of this... Occupational Safety and Health (NIOSH) Mortality Studies in Coal Mining, Metal and Non-Metal Mining and General...

Reactive solute transport in acidic streams

USGS Publications Warehouse

Broshears, R.E.

1996-01-01

Spatial and temporal profiles of Ph and concentrations of toxic metals in streams affected by acid mine drainage are the result of the interplay of physical and biogeochemical processes. This paper describes a reactive solute transport model that provides a physically and thermodynamically quantitative interpretation of these profiles. The model combines a transport module that includes advection-dispersion and transient storage with a geochemical speciation module based on MINTEQA2. Input to the model includes stream hydrologic properties derived from tracer-dilution experiments, headwater and lateral inflow concentrations analyzed in field samples, and a thermodynamic database. Simulations reproduced the general features of steady-state patterns of observed pH and concentrations of aluminum and sulfate in St. Kevin Gulch, an acid mine drainage stream near Leadville, Colorado. These patterns were altered temporarily by injection of sodium carbonate into the stream. A transient simulation reproduced the observed effects of the base injection.

The Topological Field Theory of Data: a program towards a novel strategy for data mining through data language

NASA Astrophysics Data System (ADS)

Rasetti, M.; Merelli, E.

2015-07-01

This paper aims to challenge the current thinking in IT for the 'Big Data' question, proposing - almost verbatim, with no formulas - a program aiming to construct an innovative methodology to perform data analytics in a way that returns an automaton as a recognizer of the data language: a Field Theory of Data. We suggest to build, directly out of probing data space, a theoretical framework enabling us to extract the manifold hidden relations (patterns) that exist among data, as correlations depending on the semantics generated by the mining context. The program, that is grounded in the recent innovative ways of integrating data into a topological setting, proposes the realization of a Topological Field Theory of Data, transferring and generalizing to the space of data notions inspired by physical (topological) field theories and harnesses the theory of formal languages to define the potential semantics necessary to understand the emerging patterns.

Exploring patterns of epigenetic information with data mining techniques.

PubMed

Aguiar-Pulido, Vanessa; Seoane, José A; Gestal, Marcos; Dorado, Julián

2013-01-01

Data mining, a part of the Knowledge Discovery in Databases process (KDD), is the process of extracting patterns from large data sets by combining methods from statistics and artificial intelligence with database management. Analyses of epigenetic data have evolved towards genome-wide and high-throughput approaches, thus generating great amounts of data for which data mining is essential. Part of these data may contain patterns of epigenetic information which are mitotically and/or meiotically heritable determining gene expression and cellular differentiation, as well as cellular fate. Epigenetic lesions and genetic mutations are acquired by individuals during their life and accumulate with ageing. Both defects, either together or individually, can result in losing control over cell growth and, thus, causing cancer development. Data mining techniques could be then used to extract the previous patterns. This work reviews some of the most important applications of data mining to epigenetics.

Mining Co-Location Patterns with Clustering Items from Spatial Data Sets

NASA Astrophysics Data System (ADS)

Zhou, G.; Li, Q.; Deng, G.; Yue, T.; Zhou, X.

2018-05-01

The explosive growth of spatial data and widespread use of spatial databases emphasize the need for the spatial data mining. Co-location patterns discovery is an important branch in spatial data mining. Spatial co-locations represent the subsets of features which are frequently located together in geographic space. However, the appearance of a spatial feature C is often not determined by a single spatial feature A or B but by the two spatial features A and B, that is to say where A and B appear together, C often appears. We note that this co-location pattern is different from the traditional co-location pattern. Thus, this paper presents a new concept called clustering terms, and this co-location pattern is called co-location patterns with clustering items. And the traditional algorithm cannot mine this co-location pattern, so we introduce the related concept in detail and propose a novel algorithm. This algorithm is extended by join-based approach proposed by Huang. Finally, we evaluate the performance of this algorithm.

Constraint-based Data Mining

NASA Astrophysics Data System (ADS)

Boulicaut, Jean-Francois; Jeudy, Baptiste

Knowledge Discovery in Databases (KDD) is a complex interactive process. The promising theoretical framework of inductive databases considers this is essentially a querying process. It is enabled by a query language which can deal either with raw data or patterns which hold in the data. Mining patterns turns to be the so-called inductive query evaluation process for which constraint-based Data Mining techniques have to be designed. An inductive query specifies declaratively the desired constraints and algorithms are used to compute the patterns satisfying the constraints in the data. We survey important results of this active research domain. This chapter emphasizes a real breakthrough for hard problems concerning local pattern mining under various constraints and it points out the current directions of research as well.

The Hazards of Data Mining in Healthcare.

PubMed

Househ, Mowafa; Aldosari, Bakheet

2017-01-01

From the mid-1990s, data mining methods have been used to explore and find patterns and relationships in healthcare data. During the 1990s and early 2000's, data mining was a topic of great interest to healthcare researchers, as data mining showed some promise in the use of its predictive techniques to help model the healthcare system and improve the delivery of healthcare services. However, it was soon discovered that mining healthcare data had many challenges relating to the veracity of healthcare data and limitations around predictive modelling leading to failures of data mining projects. As the Big Data movement has gained momentum over the past few years, there has been a reemergence of interest in the use of data mining techniques and methods to analyze healthcare generated Big Data. Much has been written on the positive impacts of data mining on healthcare practice relating to issues of best practice, fraud detection, chronic disease management, and general healthcare decision making. Little has been written about the limitations and challenges of data mining use in healthcare. In this review paper, we explore some of the limitations and challenges in the use of data mining techniques in healthcare. Our results show that the limitations of data mining in healthcare include reliability of medical data, data sharing between healthcare organizations, inappropriate modelling leading to inaccurate predictions. We conclude that there are many pitfalls in the use of data mining in healthcare and more work is needed to show evidence of its utility in facilitating healthcare decision-making for healthcare providers, managers, and policy makers and more evidence is needed on data mining's overall impact on healthcare services and patient care.

Towards comprehensive structural motif mining for better fold annotation in the "twilight zone" of sequence dissimilarity

PubMed Central

Jia, Yi; Huan, Jun; Buhr, Vincent; Zhang, Jintao; Carayannopoulos, Leonidas N

2009-01-01

Background Automatic identification of structure fingerprints from a group of diverse protein structures is challenging, especially for proteins whose divergent amino acid sequences may fall into the "twilight-" or "midnight-" zones where pair-wise sequence identities to known sequences fall below 25% and sequence-based functional annotations often fail. Results Here we report a novel graph database mining method and demonstrate its application to protein structure pattern identification and structure classification. The biologic motivation of our study is to recognize common structure patterns in "immunoevasins", proteins mediating virus evasion of host immune defense. Our experimental study, using both viral and non-viral proteins, demonstrates the efficiency and efficacy of the proposed method. Conclusion We present a theoretic framework, offer a practical software implementation for incorporating prior domain knowledge, such as substitution matrices as studied here, and devise an efficient algorithm to identify approximate matched frequent subgraphs. By doing so, we significantly expanded the analytical power of sophisticated data mining algorithms in dealing with large volume of complicated and noisy protein structure data. And without loss of generality, choice of appropriate compatibility matrices allows our method to be easily employed in domains where subgraph labels have some uncertainty. PMID:19208148

A simple scheme to determine potential aquatic metal toxicity from mining wastes

USGS Publications Warehouse

Wildeman, T.R.; Smith, K.S.; Ranville, J.F.

2007-01-01

A decision tree (mining waste decision tree) that uses simple physical and chemical tests has been developed to determine whether effluent from mine waste material poses a potential toxicity threat to the aquatic environment. For the chemical portion of the tree, leaching tests developed by the United States Geological Survey, the Colorado Division of Minerals and Geology (Denver, CO), and a modified 1311 toxicity characteristic leaching procedure (TCLP) test of the United States Environmental Protection Agency have been extensively used as a surrogate for readily available metals that can be released into the environment from mining wastes. To assist in the assessment, element concentration pattern graphs (ECPG) are produced that compare concentrations of selected groups of elements from the three leachates and any water associated with the mining waste. The MWDT makes a distinction between leachates or waters with pH less than or greater than 5. Generally, when the pH values are below 5, the ECPG of the solutions are quite similar, and potential aquatic toxicity from cationic metals, such as Pb, Cu, Zn, Cd, and Al, is assumed. Below pH 5, these metals are mostly dissolved, generally are not complexed with organic or inorganic ligands, and hence are more bioavailable. Furthermore, there is virtually no carbonate alkalinity at pH less than 5. All of these factors promote metal toxicity to aquatic organisms. On the other hand, when the pH value of the water or the leachates is above 5, the ECPG from the solutions are variable, and inferred aquatic toxicity depends on factors in addition to the metals released from the leaching tests. Hence, leachates and waters with pH above 5 warrant further examination of their chemical composition. Physical ranking criteria provide additional information, particularly in areas where waste piles exhibit similar chemical rankings. Rankings from physical and chemical criteria generally are not correlated. Examples of how this decision tree has been applied in assessing mine sites are discussed. Copyright ?? Taylor & Francis Group, LLC.

Changes in the Extent of Surface Mining and Reclamation in the Central Appalachians Detected Using a 1976-2006 Landsat Time Series

NASA Technical Reports Server (NTRS)

Townsend, Philip A.; Helmers, David P.; Kingdon, Clayton C.; McNeil, Brenden E.; de Beurs, Kirsten M.; Eshleman, Keith N.

2009-01-01

Surface mining and reclamation is the dominant driver of land cover land use change (LCLUC) in the Central Appalachian Mountain region of the Eastern U.S. Accurate quantification of the extent of mining activities is important for assessing how this LCLUC affects ecosystem services such as aesthetics, biodiversity, and mitigation of flooding.We used Landsat imagery from 1976, 1987, 1999 and 2006 to map the extent of surface mines and mine reclamation for eight large watersheds in the Central Appalachian region of West Virginia, Maryland and Pennsylvania. We employed standard image processing techniques in conjunction with a temporal decision tree and GIS maps of mine permits and wetlands to map active and reclaimed mines and track changes through time. For the entire study area, active surface mine extent was highest in 1976, prior to implementation of the Surface Mine Control and Reclamation Act in 1977, with 1.76% of the study area in active mines, declining to 0.44% in 2006. The most extensively mined watershed, Georges Creek in Maryland, was 5.45% active mines in 1976, declining to 1.83% in 2006. For the entire study area, the area of reclaimed mines increased from 1.35% to 4.99% from 1976 to 2006, and from 4.71% to 15.42% in Georges Creek. Land cover conversion to mines and then reclaimed mines after 1976 was almost exclusively from forest. Accuracy levels for mined and reclaimed cover was above 85% for all time periods, and was generally above 80% for mapping active and reclaimed mines separately, especially for the later time periods in which good accuracy assessment data were available. Among other implications, the mapped patterns of LCLUC are likely to significantly affect watershed hydrology, as mined and reclaimed areas have lower infiltration capacity and thus more rapid runoff than unmined forest watersheds, leading to greater potential for extreme flooding during heavy rainfall events.

Multi-Level Sequential Pattern Mining Based on Prime Encoding

NASA Astrophysics Data System (ADS)

Lianglei, Sun; Yun, Li; Jiang, Yin

Encoding is not only to express the hierarchical relationship, but also to facilitate the identification of the relationship between different levels, which will directly affect the efficiency of the algorithm in the area of mining the multi-level sequential pattern. In this paper, we prove that one step of division operation can decide the parent-child relationship between different levels by using prime encoding and present PMSM algorithm and CROSS-PMSM algorithm which are based on prime encoding for mining multi-level sequential pattern and cross-level sequential pattern respectively. Experimental results show that the algorithm can effectively extract multi-level and cross-level sequential pattern from the sequence database.

A Novel Method for Discovering Fuzzy Sequential Patterns Using the Simple Fuzzy Partition Method.

ERIC Educational Resources Information Center

Chen, Ruey-Shun; Hu, Yi-Chung

2003-01-01

Discusses sequential patterns, data mining, knowledge acquisition, and fuzzy sequential patterns described by natural language. Proposes a fuzzy data mining technique to discover fuzzy sequential patterns by using the simple partition method which allows the linguistic interpretation of each fuzzy set to be easily obtained. (Author/LRW)

Data Mining Techniques Applied to Hydrogen Lactose Breath Test.

PubMed

Rubio-Escudero, Cristina; Valverde-Fernández, Justo; Nepomuceno-Chamorro, Isabel; Pontes-Balanza, Beatriz; Hernández-Mendoza, Yoedusvany; Rodríguez-Herrera, Alfonso

2017-01-01

Analyze a set of data of hydrogen breath tests by use of data mining tools. Identify new patterns of H2 production. Hydrogen breath tests data sets as well as k-means clustering as the data mining technique to a dataset of 2571 patients. Six different patterns have been extracted upon analysis of the hydrogen breath test data. We have also shown the relevance of each of the samples taken throughout the test. Analysis of the hydrogen breath test data sets using data mining techniques has identified new patterns of hydrogen generation upon lactose absorption. We can see the potential of application of data mining techniques to clinical data sets. These results offer promising data for future research on the relations between gut microbiota produced hydrogen and its link to clinical symptoms.

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…

78 FR 5055 - Pattern of Violations

Federal Register 2010, 2011, 2012, 2013, 2014

2013-01-23

...The Mine Safety and Health Administration (MSHA) is revising the Agency's existing regulation for pattern of violations (POV). MSHA has determined that the existing regulation does not adequately achieve the intent of the Federal Mine Safety and Health Act of 1977 (Mine Act) that the POV provision be used to address mine operators who have demonstrated a disregard for the health and safety of miners. Congress included the POV provision in the Mine Act so that mine operators would manage health and safety conditions at mines and find and fix the root causes of significant and substantial (S&S) violations, protecting the health and safety of miners. The final rule simplifies the existing POV criteria, improves consistency in applying the POV criteria, and more effectively achieves the Mine Act's statutory intent. It also encourages chronic safety violators to comply with the Mine Act and MSHA's health and safety standards.

Modelling the sensory space of varietal wines: Mining of large, unstructured text data and visualisation of style patterns.

PubMed

Valente, Carlo C; Bauer, Florian F; Venter, Fritz; Watson, Bruce; Nieuwoudt, Hélène H

2018-03-21

The increasingly large volumes of publicly available sensory descriptions of wine raises the question whether this source of data can be mined to extract meaningful domain-specific information about the sensory properties of wine. We introduce a novel application of formal concept lattices, in combination with traditional statistical tests, to visualise the sensory attributes of a big data set of some 7,000 Chenin blanc and Sauvignon blanc wines. Complexity was identified as an important driver of style in hereto uncharacterised Chenin blanc, and the sensory cues for specific styles were identified. This is the first study to apply these methods for the purpose of identifying styles within varietal wines. More generally, our interactive data visualisation and mining driven approach opens up new investigations towards better understanding of the complex field of sensory science.

Dietary patterns analysis using data mining method. An application to data from the CYKIDS study.

PubMed

Lazarou, Chrystalleni; Karaolis, Minas; Matalas, Antonia-Leda; Panagiotakos, Demosthenes B

2012-11-01

Data mining is a computational method that permits the extraction of patterns from large databases. We applied the data mining approach in data from 1140 children (9-13 years), in order to derive dietary habits related to children's obesity status. Rules emerged via data mining approach revealed the detrimental influence of the increased consumption of soft dinks, delicatessen meat, sweets, fried and junk food. For example, frequent (3-5 times/week) consumption of all these foods increases the risk for being obese by 75%, whereas in children who have a similar dietary pattern, but eat >2 times/week fish and seafood the risk for obesity is reduced by 33%. In conclusion patterns revealed from data mining technique refer to specific groups of children and demonstrate the effect on the risk associated with obesity status when a single dietary habit might be modified. Thus, a more individualized approach when translating public health messages could be achieved. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

A prototype system based on visual interactive SDM called VGC

NASA Astrophysics Data System (ADS)

Jia, Zelu; Liu, Yaolin; Liu, Yanfang

2009-10-01

In many application domains, data is collected and referenced by its geo-spatial location. Spatial data mining, or the discovery of interesting patterns in such databases, is an important capability in the development of database systems. Spatial data mining recently emerges from a number of real applications, such as real-estate marketing, urban planning, weather forecasting, medical image analysis, road traffic accident analysis, etc. It demands for efficient solutions for many new, expensive, and complicated problems. For spatial data mining of large data sets to be effective, it is also important to include humans in the data exploration process and combine their flexibility, creativity, and general knowledge with the enormous storage capacity and computational power of today's computers. Visual spatial data mining applies human visual perception to the exploration of large data sets. Presenting data in an interactive, graphical form often fosters new insights, encouraging the information and validation of new hypotheses to the end of better problem-solving and gaining deeper domain knowledge. In this paper a visual interactive spatial data mining prototype system (visual geo-classify) based on VC++6.0 and MapObject2.0 are designed and developed, the basic algorithms of the spatial data mining is used decision tree and Bayesian networks, and data classify are used training and learning and the integration of the two to realize. The result indicates it's a practical and extensible visual interactive spatial data mining tool.

A Novel Higher Order Artificial Neural Networks

NASA Astrophysics Data System (ADS)

Xu, Shuxiang

2010-05-01

In this paper a new Higher Order Neural Network (HONN) model is introduced and applied in several data mining tasks. Data Mining extracts hidden patterns and valuable information from large databases. A hyperbolic tangent function is used as the neuron activation function for the new HONN model. Experiments are conducted to demonstrate the advantages and disadvantages of the new HONN model, when compared with several conventional Artificial Neural Network (ANN) models: Feedforward ANN with the sigmoid activation function; Feedforward ANN with the hyperbolic tangent activation function; and Radial Basis Function (RBF) ANN with the Gaussian activation function. The experimental results seem to suggest that the new HONN holds higher generalization capability as well as abilities in handling missing data.

String Mining in Bioinformatics

NASA Astrophysics Data System (ADS)

Abouelhoda, Mohamed; Ghanem, Moustafa

Sequence analysis is a major area in bioinformatics encompassing the methods and techniques for studying the biological sequences, DNA, RNA, and proteins, on the linear structure level. The focus of this area is generally on the identification of intra- and inter-molecular similarities. Identifying intra-molecular similarities boils down to detecting repeated segments within a given sequence, while identifying inter-molecular similarities amounts to spotting common segments among two or multiple sequences. From a data mining point of view, sequence analysis is nothing but string- or pattern mining specific to biological strings. For a long time, this point of view, however, has not been explicitly embraced neither in the data mining nor in the sequence analysis text books, which may be attributed to the co-evolution of the two apparently independent fields. In other words, although the word “data-mining” is almost missing in the sequence analysis literature, its basic concepts have been implicitly applied. Interestingly, recent research in biological sequence analysis introduced efficient solutions to many problems in data mining, such as querying and analyzing time series [49,53], extracting information from web pages [20], fighting spam mails [50], detecting plagiarism [22], and spotting duplications in software systems [14].

An Incremental High-Utility Mining Algorithm with Transaction Insertion

PubMed Central

Gan, Wensheng; Zhang, Binbin

2015-01-01

Association-rule mining is commonly used to discover useful and meaningful patterns from a very large database. It only considers the occurrence frequencies of items to reveal the relationships among itemsets. Traditional association-rule mining is, however, not suitable in real-world applications since the purchased items from a customer may have various factors, such as profit or quantity. High-utility mining was designed to solve the limitations of association-rule mining by considering both the quantity and profit measures. Most algorithms of high-utility mining are designed to handle the static database. Fewer researches handle the dynamic high-utility mining with transaction insertion, thus requiring the computations of database rescan and combination explosion of pattern-growth mechanism. In this paper, an efficient incremental algorithm with transaction insertion is designed to reduce computations without candidate generation based on the utility-list structures. The enumeration tree and the relationships between 2-itemsets are also adopted in the proposed algorithm to speed up the computations. Several experiments are conducted to show the performance of the proposed algorithm in terms of runtime, memory consumption, and number of generated patterns. PMID:25811038

Software tool for data mining and its applications

NASA Astrophysics Data System (ADS)

Yang, Jie; Ye, Chenzhou; Chen, Nianyi

2002-03-01

A software tool for data mining is introduced, which integrates pattern recognition (PCA, Fisher, clustering, hyperenvelop, regression), artificial intelligence (knowledge representation, decision trees), statistical learning (rough set, support vector machine), computational intelligence (neural network, genetic algorithm, fuzzy systems). It consists of nine function models: pattern recognition, decision trees, association rule, fuzzy rule, neural network, genetic algorithm, Hyper Envelop, support vector machine, visualization. The principle and knowledge representation of some function models of data mining are described. The software tool of data mining is realized by Visual C++ under Windows 2000. Nonmonotony in data mining is dealt with by concept hierarchy and layered mining. The software tool of data mining has satisfactorily applied in the prediction of regularities of the formation of ternary intermetallic compounds in alloy systems, and diagnosis of brain glioma.

Exploiting Sequential Patterns Found in Users' Solutions and Virtual Tutor Behavior to Improve Assistance in ITS

ERIC Educational Resources Information Center

Fournier-Viger, Philippe; Faghihi, Usef; Nkambou, Roger; Nguifo, Engelbert Mephu

2010-01-01

We propose to mine temporal patterns in Intelligent Tutoring Systems (ITSs) to uncover useful knowledge that can enhance their ability to provide assistance. To discover patterns, we suggest using a custom, sequential pattern-mining algorithm. Two ways of applying the algorithm to enhance an ITS's capabilities are addressed. The first is to…

Ecosystem Health Assessment of Mining Cities Based on Landscape Pattern

NASA Astrophysics Data System (ADS)

Yu, W.; Liu, Y.; Lin, M.; Fang, F.; Xiao, R.

2017-09-01

Ecosystem health assessment (EHA) is one of the most important aspects in ecosystem management. Nowadays, ecological environment of mining cities is facing various problems. In this study, through ecosystem health theory and remote sensing images in 2005, 2009 and 2013, landscape pattern analysis and Vigor-Organization-Resilience (VOR) model were applied to set up an evaluation index system of ecosystem health of mining city to assess the healthy level of ecosystem in Panji District Huainan city. Results showed a temporal stable but high spatial heterogeneity landscape pattern during 2005-2013. According to the regional ecosystem health index, it experienced a rapid decline after a slight increase, and finally it maintained at an ordinary level. Among these areas, a significant distinction was presented in different towns. It indicates that the ecosystem health of Tianjijiedao town, the regional administrative centre, descended rapidly during the study period, and turned into the worst level in the study area. While the Hetuan Town, located in the northwestern suburb area of Panji District, stayed on a relatively better level than other towns. The impacts of coal mining collapse area, land reclamation on the landscape pattern and ecosystem health status of mining cities were also discussed. As a result of underground coal mining, land subsidence has become an inevitable problem in the study area. In addition, the coal mining subsidence area has brought about the destruction of the farmland, construction land and water bodies, which causing the change of the regional landscape pattern and making the evaluation of ecosystem health in mining area more difficult. Therefore, this study provided an ecosystem health approach for relevant departments to make scientific decisions.

Mining the SDSS SkyServer SQL queries log

NASA Astrophysics Data System (ADS)

Hirota, Vitor M.; Santos, Rafael; Raddick, Jordan; Thakar, Ani

2016-05-01

SkyServer, the Internet portal for the Sloan Digital Sky Survey (SDSS) astronomic catalog, provides a set of tools that allows data access for astronomers and scientific education. One of SkyServer data access interfaces allows users to enter ad-hoc SQL statements to query the catalog. SkyServer also presents some template queries that can be used as basis for more complex queries. This interface has logged over 330 million queries submitted since 2001. It is expected that analysis of this data can be used to investigate usage patterns, identify potential new classes of queries, find similar queries, etc. and to shed some light on how users interact with the Sloan Digital Sky Survey data and how scientists have adopted the new paradigm of e-Science, which could in turn lead to enhancements on the user interfaces and experience in general. In this paper we review some approaches to SQL query mining, apply the traditional techniques used in the literature and present lessons learned, namely, that the general text mining approach for feature extraction and clustering does not seem to be adequate for this type of data, and, most importantly, we find that this type of analysis can result in very different queries being clustered together.

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

ENVIRONMENTAL IMPACT ON PHYSIOLOGICAL RESPONSES OF UNDERGROUND COAL MINERS IN THE EASTERN PART OF INDIA.

PubMed

Dey, Netai Chandra; Nath, Suva; Sharma, Gourab Dhara; Mallik, Avijit

2014-12-01

Coal in India is extracted generally by semi-mechanized and mechanized underground mining methods. The Bord and Pillar (B & P) mining method still continues to be popular where deployment of manual miners is more than that of other mining methods. The study is conducted at haulage based mine of Eastern Coalfields of West Bengal. Underground miners confront with a lot of hazards like extreme hostile environment, awkward working posture, dust, noise as well as low luminosity. It is difficult to delay the onset of fatigue. In order to study the physiological responses of trammers, various parameters like working heart rates, net cardiac cost and relative cardiac cost including recovery heart rate patterns are recorded during their work at site. Workload classification of trammers has been done following various scales of heaviness. The effect of environment on the physiological responses has been observed and suitable recommendations are made. The work tasks are bound to induce musculoskeletal problems and those problems could be better managed through rationalizing the work-rest scheduling.

Careflow Mining Techniques to Explore Type 2 Diabetes Evolution.

PubMed

Dagliati, Arianna; Tibollo, Valentina; Cogni, Giulia; Chiovato, Luca; Bellazzi, Riccardo; Sacchi, Lucia

2018-03-01

In this work we describe the application of a careflow mining algorithm to detect the most frequent patterns of care in a type 2 diabetes patients cohort. The applied method enriches the detected patterns with clinical data to define temporal phenotypes across the studied population. Novel phenotypes are discovered from heterogeneous data of 424 Italian patients, and compared in terms of metabolic control and complications. Results show that careflow mining can help to summarize the complex evolution of the disease into meaningful patterns, which are also significant from a clinical point of view.

Binary Coded Web Access Pattern Tree in Education Domain

ERIC Educational Resources Information Center

Gomathi, C.; Moorthi, M.; Duraiswamy, K.

2008-01-01

Web Access Pattern (WAP), which is the sequence of accesses pursued by users frequently, is a kind of interesting and useful knowledge in practice. Sequential Pattern mining is the process of applying data mining techniques to a sequential database for the purposes of discovering the correlation relationships that exist among an ordered list of…

Implications of Emerging Data Mining

NASA Astrophysics Data System (ADS)

Kulathuramaiyer, Narayanan; Maurer, Hermann

Data Mining describes a technology that discovers non-trivial hidden patterns in a large collection of data. Although this technology has a tremendous impact on our lives, the invaluable contributions of this invisible technology often go unnoticed. This paper discusses advances in data mining while focusing on the emerging data mining capability. Such data mining applications perform multidimensional mining on a wide variety of heterogeneous data sources, providing solutions to many unresolved problems. This paper also highlights the advantages and disadvantages arising from the ever-expanding scope of data mining. Data Mining augments human intelligence by equipping us with a wealth of knowledge and by empowering us to perform our daily tasks better. As the mining scope and capacity increases, users and organizations become more willing to compromise privacy. The huge data stores of the ‚master miners` allow them to gain deep insights into individual lifestyles and their social and behavioural patterns. Data integration and analysis capability of combining business and financial trends together with the ability to deterministically track market changes will drastically affect our lives.

DMT-TAFM: a data mining tool for technical analysis of futures market

NASA Astrophysics Data System (ADS)

Stepanov, Vladimir; Sathaye, Archana

2002-03-01

Technical analysis of financial markets describes many patterns of market behavior. For practical use, all these descriptions need to be adjusted for each particular trading session. In this paper, we develop a data mining tool for technical analysis of the futures markets (DMT-TAFM), which dynamically generates rules based on the notion of the price pattern similarity. The tool consists of three main components. The first component provides visualization of data series on a chart with different ranges, scales, and chart sizes and types. The second component constructs pattern descriptions using sets of polynomials. The third component specifies the training set for mining, defines the similarity notion, and searches for a set of similar patterns. DMT-TAFM is useful to prepare the data, and then reveal and systemize statistical information about similar patterns found in any type of historical price series. We performed experiments with our tool on three decades of trading data fro hundred types of futures. Our results for this data set shows that, we can prove or disprove many well-known patterns based on real data, as well as reveal new ones, and use the set of relatively consistent patterns found during data mining for developing better futures trading strategies.

Application of Differential InSAR to Mining

NASA Astrophysics Data System (ADS)

Eneva, M.; Baker, E.; Xu, H.

2001-12-01

In a NASA funded project we are applying differential InSAR to measure surface deformation associated with mining at depth. Surface displacement can be caused by rockbursts associated with mine collapse or mining-induced stress released on nearby tectonic features. The latter type of rockbursts are similar to tectonic earthquakes, but generally occur at shallower depths than non-induced events of similar size. Thus significant co-seismic surface changes may accompany them. In addition, subsidence of a more gradual type may result from ongoing soft-rock (e.g., coal, potash, salt) mining. While such subsidence can accidentally occur above abandoned mines, it is most often planned as part of the ongoing ore extraction, especially in so-called long-wall mining. Predicting the amount and spatial extent of this subsidence is an aspect of mining engineering. It is important to compare these predictions with measurements of the actual deformation. Although mines use leveling and GPS measurements to monitor subsidence, these are generally performed with much smaller frequency (e.g., annually) and lower spatial resolution than repeat-pass differential InSAR can provide. We are using ERS-1/2 raw SAR data provided by ESA and Eurimage, and the Gamma software for their processing. At present we are focused on the processing and modeling of data from two representative sites. By the end of the project we will have analyzed several more sites of subsidence and M>4.5 rockbursts. As an example of mining subsidence, we are currently analyzing data from the site of a coal mine in Colorado (USA), operating in a relatively flat and arid area. Numerous adjacent long-wall panels of extraction are used, some exceeding 5 km in length. A 600 to 750-m length of panel may be extracted per month, with a maximum subsidence of 1.5 to 1.8 m expected over each panel. The surface deformation can be monitored especially well during the summers of 1995 and 1996, when nine good-quality ERS-1/2 SAR scenes were gathered. Two of these scenes form a tandem pair to be used for topography. We are also making use of a 30-m DEM from USGS, maps of extraction panels, leveling data and microearthquake locations. As an example of rockbursts, we are presently analyzing ERS-2 SAR data from the site of a M5.1 rockburst that occurred on April 22, 1999, in the gold fields of Welkom, South Africa. The event was induced on a fault transecting the mine and had a normal mechanism. Only two good-quality SAR scenes are available from this site, spanning about a year including the event. Thus the topography effect cannot be removed using interferometry. However, since flat surface and urban environment characterize this site, a clear fringe pattern is observed, apparently associated with the rockburst. This pattern suggests up to 9-cm subsidence. Its center is within 5 km from the seismically determined event location. Thus this rockburst represents an example of the capabilities of InSAR to provide ground truth locations for moderate shallow earthquakes. To model the seismic source, we are using the RNGCHN software (Feigl and Dupré, 1999) based on analytic solutions for a homogeneous half-space. In order to model deformation in realistically complex crust, including layered structure and lateral heterogeneities, we are also developing a 3D finite-difference method of estimating deformation in a volume due to displacement on a fault surface. This method will be also used for the modeling of mining subsidence.

Apriori Versions Based on MapReduce for Mining Frequent Patterns on Big Data.

PubMed

Luna, Jose Maria; Padillo, Francisco; Pechenizkiy, Mykola; Ventura, Sebastian

2017-09-27

Pattern mining is one of the most important tasks to extract meaningful and useful information from raw data. This task aims to extract item-sets that represent any type of homogeneity and regularity in data. Although many efficient algorithms have been developed in this regard, the growing interest in data has caused the performance of existing pattern mining techniques to be dropped. The goal of this paper is to propose new efficient pattern mining algorithms to work in big data. To this aim, a series of algorithms based on the MapReduce framework and the Hadoop open-source implementation have been proposed. The proposed algorithms can be divided into three main groups. First, two algorithms [Apriori MapReduce (AprioriMR) and iterative AprioriMR] with no pruning strategy are proposed, which extract any existing item-set in data. Second, two algorithms (space pruning AprioriMR and top AprioriMR) that prune the search space by means of the well-known anti-monotone property are proposed. Finally, a last algorithm (maximal AprioriMR) is also proposed for mining condensed representations of frequent patterns. To test the performance of the proposed algorithms, a varied collection of big data datasets have been considered, comprising up to 3 · 10#x00B9;⁸ transactions and more than 5 million of distinct single-items. The experimental stage includes comparisons against highly efficient and well-known pattern mining algorithms. Results reveal the interest of applying MapReduce versions when complex problems are considered, and also the unsuitability of this paradigm when dealing with small data.

Trace metal depositional patterns from an open pit mining activity as revealed by archived avian gizzard contents.

PubMed

Bendell, L I

2011-02-15

Archived samples of blue grouse (Dendragapus obscurus) gizzard contents, inclusive of grit, collected yearly between 1959 and 1970 were analyzed for cadmium, lead, zinc, and copper content. Approximately halfway through the 12-year sampling period, an open-pit copper mine began activities, then ceased operations 2 years later. Thus the archived samples provided a unique opportunity to determine if avian gizzard contents, inclusive of grit, could reveal patterns in the anthropogenic deposition of trace metals associated with mining activities. Gizzard concentrations of cadmium and copper strongly coincided with the onset of opening and the closing of the pit mining activity. Gizzard zinc and lead demonstrated significant among year variation; however, maximum concentrations did not correlate to mining activity. The archived gizzard contents did provide a useful tool for documenting trends in metal depositional patterns related to an anthropogenic activity. Further, blue grouse ingesting grit particles during the time of active mining activity would have been exposed to toxicologically significant levels of cadmium. Gizzard lead concentrations were also of toxicological significance but not related to mining activity. This type of "pulse" toxic metal exposure as a consequence of open-pit mining activity would not necessarily have been revealed through a "snap-shot" of soil, plant or avian tissue trace metal analysis post-mining activity. Copyright © 2010 Elsevier B.V. All rights reserved.

Understanding Human Motion Skill with Peak Timing Synergy

NASA Astrophysics Data System (ADS)

Ueno, Ken; Furukawa, Koichi

The careful observation of motion phenomena is important in understanding the skillful human motion. However, this is a difficult task due to the complexities in timing when dealing with the skilful control of anatomical structures. To investigate the dexterity of human motion, we decided to concentrate on timing with respect to motion, and we have proposed a method to extract the peak timing synergy from multivariate motion data. The peak timing synergy is defined as a frequent ordered graph with time stamps, which has nodes consisting of turning points in motion waveforms. A proposed algorithm, PRESTO automatically extracts the peak timing synergy. PRESTO comprises the following 3 processes: (1) detecting peak sequences with polygonal approximation; (2) generating peak-event sequences; and (3) finding frequent peak-event sequences using a sequential pattern mining method, generalized sequential patterns (GSP). Here, we measured right arm motion during the task of cello bowing and prepared a data set of the right shoulder and arm motion. We successfully extracted the peak timing synergy on cello bowing data set using the PRESTO algorithm, which consisted of common skills among cellists and personal skill differences. To evaluate the sequential pattern mining algorithm GSP in PRESTO, we compared the peak timing synergy by using GSP algorithm and the one by using filtering by reciprocal voting (FRV) algorithm as a non time-series method. We found that the support is 95 - 100% in GSP, while 83 - 96% in FRV and that the results by GSP are better than the one by FRV in the reproducibility of human motion. Therefore we show that sequential pattern mining approach is more effective to extract the peak timing synergy than non-time series analysis approach.

Exploration of geo-mineral compounds in granite mining soils using XRD pattern data analysis

NASA Astrophysics Data System (ADS)

Koteswara Reddy, G.; Yarakkula, Kiran

2017-11-01

The purpose of the study was to investigate the major minerals present in granite mining waste and agricultural soils near and away from mining areas. The mineral exploration of representative sub-soil samples are identified by X-Ray Diffractometer (XRD) pattern data analysis. The morphological features and quantitative elementary analysis was performed by Scanning Electron Microscopy-Energy Dispersed Spectroscopy (SEM-EDS).The XRD pattern data revealed that the major minerals are identified as Quartz, Albite, Anorthite, K-Feldspars, Muscovite, Annite, Lepidolite, Illite, Enstatite and Ferrosilite in granite waste. However, in case of agricultural farm soils the major minerals are identified as Gypsum, Calcite, Magnetite, Hematite, Muscovite, K-Feldspars and Quartz. Moreover, the agricultural soils neighbouring mining areas, the minerals are found that, the enriched Mica group minerals (Lepidolite and Illite) the enriched Orthopyroxene group minerals (Ferrosilite and Enstatite). It is observed that the Mica and Orthopyroxene group minerals are present in agricultural farm soils neighbouring mining areas and absent in agricultural farm soils away from mining areas. The study demonstrated that the chemical migration takes place at agricultural farm lands in the vicinity of the granite mining areas.

15 CFR 970.600 - General.

Code of Federal Regulations, 2012 CFR

2012-01-01

... AND ATMOSPHERIC ADMINISTRATION, DEPARTMENT OF COMMERCE GENERAL REGULATIONS OF THE ENVIRONMENTAL DATA SERVICE DEEP SEABED MINING REGULATIONS FOR EXPLORATION LICENSES Resource Development Concepts § 970.600 General. Several provisions in the Act relate to appropriate mining techniques or mining efficiency. These...

15 CFR 970.600 - General.

Code of Federal Regulations, 2014 CFR

2014-01-01

... AND ATMOSPHERIC ADMINISTRATION, DEPARTMENT OF COMMERCE GENERAL REGULATIONS OF THE ENVIRONMENTAL DATA SERVICE DEEP SEABED MINING REGULATIONS FOR EXPLORATION LICENSES Resource Development Concepts § 970.600 General. Several provisions in the Act relate to appropriate mining techniques or mining efficiency. These...

15 CFR 970.600 - General.

Code of Federal Regulations, 2013 CFR

2013-01-01

... AND ATMOSPHERIC ADMINISTRATION, DEPARTMENT OF COMMERCE GENERAL REGULATIONS OF THE ENVIRONMENTAL DATA SERVICE DEEP SEABED MINING REGULATIONS FOR EXPLORATION LICENSES Resource Development Concepts § 970.600 General. Several provisions in the Act relate to appropriate mining techniques or mining efficiency. These...

15 CFR 971.500 - General.

Code of Federal Regulations, 2013 CFR

2013-01-01

... AND ATMOSPHERIC ADMINISTRATION, DEPARTMENT OF COMMERCE GENERAL REGULATIONS OF THE ENVIRONMENTAL DATA SERVICE DEEP SEABED MINING REGULATIONS FOR COMMERCIAL RECOVERY PERMITS Resource Development § 971.500 General. Several provisions in the Act relate to appropriate mining techniques or mining efficiency. These...

15 CFR 971.500 - General.

Code of Federal Regulations, 2010 CFR

2010-01-01

... AND ATMOSPHERIC ADMINISTRATION, DEPARTMENT OF COMMERCE GENERAL REGULATIONS OF THE ENVIRONMENTAL DATA SERVICE DEEP SEABED MINING REGULATIONS FOR COMMERCIAL RECOVERY PERMITS Resource Development § 971.500 General. Several provisions in the Act relate to appropriate mining techniques or mining efficiency. These...

15 CFR 971.500 - General.

Code of Federal Regulations, 2012 CFR

2012-01-01

... AND ATMOSPHERIC ADMINISTRATION, DEPARTMENT OF COMMERCE GENERAL REGULATIONS OF THE ENVIRONMENTAL DATA SERVICE DEEP SEABED MINING REGULATIONS FOR COMMERCIAL RECOVERY PERMITS Resource Development § 971.500 General. Several provisions in the Act relate to appropriate mining techniques or mining efficiency. These...

15 CFR 971.500 - General.

Code of Federal Regulations, 2011 CFR

2011-01-01

... AND ATMOSPHERIC ADMINISTRATION, DEPARTMENT OF COMMERCE GENERAL REGULATIONS OF THE ENVIRONMENTAL DATA SERVICE DEEP SEABED MINING REGULATIONS FOR COMMERCIAL RECOVERY PERMITS Resource Development § 971.500 General. Several provisions in the Act relate to appropriate mining techniques or mining efficiency. These...

15 CFR 971.500 - General.

Code of Federal Regulations, 2014 CFR

2014-01-01

... AND ATMOSPHERIC ADMINISTRATION, DEPARTMENT OF COMMERCE GENERAL REGULATIONS OF THE ENVIRONMENTAL DATA SERVICE DEEP SEABED MINING REGULATIONS FOR COMMERCIAL RECOVERY PERMITS Resource Development § 971.500 General. Several provisions in the Act relate to appropriate mining techniques or mining efficiency. These...

15 CFR 970.600 - General.

Code of Federal Regulations, 2010 CFR

2010-01-01

... AND ATMOSPHERIC ADMINISTRATION, DEPARTMENT OF COMMERCE GENERAL REGULATIONS OF THE ENVIRONMENTAL DATA SERVICE DEEP SEABED MINING REGULATIONS FOR EXPLORATION LICENSES Resource Development Concepts § 970.600 General. Several provisions in the Act relate to appropriate mining techniques or mining efficiency. These...

15 CFR 970.600 - General.

Code of Federal Regulations, 2011 CFR

2011-01-01

... AND ATMOSPHERIC ADMINISTRATION, DEPARTMENT OF COMMERCE GENERAL REGULATIONS OF THE ENVIRONMENTAL DATA SERVICE DEEP SEABED MINING REGULATIONS FOR EXPLORATION LICENSES Resource Development Concepts § 970.600 General. Several provisions in the Act relate to appropriate mining techniques or mining efficiency. These...

Fault Tolerant Frequent Pattern Mining

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

Shohdy, Sameh; Vishnu, Abhinav; Agrawal, Gagan

FP-Growth algorithm is a Frequent Pattern Mining (FPM) algorithm that has been extensively used to study correlations and patterns in large scale datasets. While several researchers have designed distributed memory FP-Growth algorithms, it is pivotal to consider fault tolerant FP-Growth, which can address the increasing fault rates in large scale systems. In this work, we propose a novel parallel, algorithm-level fault-tolerant FP-Growth algorithm. We leverage algorithmic properties and MPI advanced features to guarantee an O(1) space complexity, achieved by using the dataset memory space itself for checkpointing. We also propose a recovery algorithm that can use in-memory and disk-based checkpointing,more » though in many cases the recovery can be completed without any disk access, and incurring no memory overhead for checkpointing. We evaluate our FT algorithm on a large scale InfiniBand cluster with several large datasets using up to 2K cores. Our evaluation demonstrates excellent efficiency for checkpointing and recovery in comparison to the disk-based approach. We have also observed 20x average speed-up in comparison to Spark, establishing that a well designed algorithm can easily outperform a solution based on a general fault-tolerant programming model.« less

76 FR 4466 - Privacy Act of 1974; Report of Modified or Altered System of Records

Federal Register 2010, 2011, 2012, 2013, 2014

2011-01-25

... Records, 09-20-0149, ``Morbidity Studies in Coal Mining, Metal and Non-metal Mining and General Industry... Coal Mining, Metal and Non-metal Mining and General Industry, HHS/CDC/NIOSH.'' The purpose of this... Institute for Occupational Safety And Health (NIOSH) Morbidity Studies in Coal Mining, Metal and Non-Metal...

43 CFR 2650.3-2 - Mining claims.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 43 Public Lands: Interior 2 2011-10-01 2011-10-01 false Mining claims. 2650.3-2 Section 2650.3-2...: Generally § 2650.3-2 Mining claims. (a) Possessory rights. Pursuant to section 22(c) of the Act, on any..., initiated a valid mining claim or location, including millsites, under the general mining laws and recorded...

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.

Quantification of Operational Risk Using A Data Mining

NASA Technical Reports Server (NTRS)

Perera, J. Sebastian

1999-01-01

What is Data Mining? - Data Mining is the process of finding actionable information hidden in raw data. - Data Mining helps find hidden patterns, trends, and important relationships often buried in a sea of data - Typically, automated software tools based on advanced statistical analysis and data modeling technology can be utilized to automate the data mining process

A Temporal Pattern Mining Approach for Classifying Electronic Health Record Data

PubMed Central

Batal, Iyad; Valizadegan, Hamed; Cooper, Gregory F.; Hauskrecht, Milos

2013-01-01

We study the problem of learning classification models from complex multivariate temporal data encountered in electronic health record systems. The challenge is to define a good set of features that are able to represent well the temporal aspect of the data. Our method relies on temporal abstractions and temporal pattern mining to extract the classification features. Temporal pattern mining usually returns a large number of temporal patterns, most of which may be irrelevant to the classification task. To address this problem, we present the Minimal Predictive Temporal Patterns framework to generate a small set of predictive and non-spurious patterns. We apply our approach to the real-world clinical task of predicting patients who are at risk of developing heparin induced thrombocytopenia. The results demonstrate the benefit of our approach in efficiently learning accurate classifiers, which is a key step for developing intelligent clinical monitoring systems. PMID:25309815

An Adaptive Sensor Mining Framework for Pervasive Computing Applications

NASA Astrophysics Data System (ADS)

Rashidi, Parisa; Cook, Diane J.

Analyzing sensor data in pervasive computing applications brings unique challenges to the KDD community. The challenge is heightened when the underlying data source is dynamic and the patterns change. We introduce a new adaptive mining framework that detects patterns in sensor data, and more importantly, adapts to the changes in the underlying model. In our framework, the frequent and periodic patterns of data are first discovered by the Frequent and Periodic Pattern Miner (FPPM) algorithm; and then any changes in the discovered patterns over the lifetime of the system are discovered by the Pattern Adaptation Miner (PAM) algorithm, in order to adapt to the changing environment. This framework also captures vital context information present in pervasive computing applications, such as the startup triggers and temporal information. In this paper, we present a description of our mining framework and validate the approach using data collected in the CASAS smart home testbed.

30 CFR 819.11 - Auger mining: General.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 3 2010-07-01 2010-07-01 false Auger mining: General. 819.11 Section 819.11 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PERMANENT PROGRAM PERFORMANCE STANDARDS SPECIAL PERMANENT PROGRAM PERFORMANCE STANDARDS-AUGER MINING § 819...

30 CFR 819.11 - Auger mining: General.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 3 2011-07-01 2011-07-01 false Auger mining: General. 819.11 Section 819.11 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PERMANENT PROGRAM PERFORMANCE STANDARDS SPECIAL PERMANENT PROGRAM PERFORMANCE STANDARDS-AUGER MINING § 819...

The Determination of Children's Knowledge of Global Lunar Patterns from Online Essays Using Text Mining Analysis

ERIC Educational Resources Information Center

Cheon, Jongpil; Lee, Sangno; Smith, Walter; Song, Jaeki; Kim, Yongjin

2013-01-01

The purpose of this study was to use text mining analysis of early adolescents' online essays to determine their knowledge of global lunar patterns. Australian and American students in grades five to seven wrote about global lunar patterns they had discovered by sharing observations with each other via the Internet. These essays were analyzed for…

Inferring Intra-Community Microbial Interaction Patterns from Metagenomic Datasets Using Associative Rule Mining Techniques

PubMed Central

Mande, Sharmila S.

2016-01-01

The nature of inter-microbial metabolic interactions defines the stability of microbial communities residing in any ecological niche. Deciphering these interaction patterns is crucial for understanding the mode/mechanism(s) through which an individual microbial community transitions from one state to another (e.g. from a healthy to a diseased state). Statistical correlation techniques have been traditionally employed for mining microbial interaction patterns from taxonomic abundance data corresponding to a given microbial community. In spite of their efficiency, these correlation techniques can capture only 'pair-wise interactions'. Moreover, their emphasis on statistical significance can potentially result in missing out on several interactions that are relevant from a biological standpoint. This study explores the applicability of one of the earliest association rule mining algorithm i.e. the 'Apriori algorithm' for deriving 'microbial association rules' from the taxonomic profile of given microbial community. The classical Apriori approach derives association rules by analysing patterns of co-occurrence/co-exclusion between various '(subsets of) features/items' across various samples. Using real-world microbiome data, the efficiency/utility of this rule mining approach in deciphering multiple (biologically meaningful) association patterns between 'subsets/subgroups' of microbes (constituting microbiome samples) is demonstrated. As an example, association rules derived from publicly available gut microbiome datasets indicate an association between a group of microbes (Faecalibacterium, Dorea, and Blautia) that are known to have mutualistic metabolic associations among themselves. Application of the rule mining approach on gut microbiomes (sourced from the Human Microbiome Project) further indicated similar microbial association patterns in gut microbiomes irrespective of the gender of the subjects. A Linux implementation of the Association Rule Mining (ARM) software (customised for deriving 'microbial association rules' from microbiome data) is freely available for download from the following link: http://metagenomics.atc.tcs.com/arm. PMID:27124399

Inferring Intra-Community Microbial Interaction Patterns from Metagenomic Datasets Using Associative Rule Mining Techniques.

PubMed

Tandon, Disha; Haque, Mohammed Monzoorul; Mande, Sharmila S

2016-01-01

The nature of inter-microbial metabolic interactions defines the stability of microbial communities residing in any ecological niche. Deciphering these interaction patterns is crucial for understanding the mode/mechanism(s) through which an individual microbial community transitions from one state to another (e.g. from a healthy to a diseased state). Statistical correlation techniques have been traditionally employed for mining microbial interaction patterns from taxonomic abundance data corresponding to a given microbial community. In spite of their efficiency, these correlation techniques can capture only 'pair-wise interactions'. Moreover, their emphasis on statistical significance can potentially result in missing out on several interactions that are relevant from a biological standpoint. This study explores the applicability of one of the earliest association rule mining algorithm i.e. the 'Apriori algorithm' for deriving 'microbial association rules' from the taxonomic profile of given microbial community. The classical Apriori approach derives association rules by analysing patterns of co-occurrence/co-exclusion between various '(subsets of) features/items' across various samples. Using real-world microbiome data, the efficiency/utility of this rule mining approach in deciphering multiple (biologically meaningful) association patterns between 'subsets/subgroups' of microbes (constituting microbiome samples) is demonstrated. As an example, association rules derived from publicly available gut microbiome datasets indicate an association between a group of microbes (Faecalibacterium, Dorea, and Blautia) that are known to have mutualistic metabolic associations among themselves. Application of the rule mining approach on gut microbiomes (sourced from the Human Microbiome Project) further indicated similar microbial association patterns in gut microbiomes irrespective of the gender of the subjects. A Linux implementation of the Association Rule Mining (ARM) software (customised for deriving 'microbial association rules' from microbiome data) is freely available for download from the following link: http://metagenomics.atc.tcs.com/arm.

A Framework for Mining Actionable Navigation Patterns from In-Store RFID Datasets via Indoor Mapping

PubMed Central

Shen, Bin; Zheng, Qiuhua; Li, Xingsen; Xu, Libo

2015-01-01

With the quick development of RFID technology and the decreasing prices of RFID devices, RFID is becoming widely used in various intelligent services. Especially in the retail application domain, RFID is increasingly adopted to capture the shopping tracks and behavior of in-store customers. To further enhance the potential of this promising application, in this paper, we propose a unified framework for RFID-based path analytics, which uses both in-store shopping paths and RFID-based purchasing data to mine actionable navigation patterns. Four modules of this framework are discussed, which are: (1) mapping from the physical space to the cyber space, (2) data preprocessing, (3) pattern mining and (4) knowledge understanding and utilization. In the data preprocessing module, the critical problem of how to capture the mainstream shopping path sequences while wiping out unnecessary redundant and repeated details is addressed in detail. To solve this problem, two types of redundant patterns, i.e., loop repeat pattern and palindrome-contained pattern are recognized and the corresponding processing algorithms are proposed. The experimental results show that the redundant pattern filtering functions are effective and scalable. Overall, this work builds a bridge between indoor positioning and advanced data mining technologies, and provides a feasible way to study customers’ shopping behaviors via multi-source RFID data. PMID:25751076

Long Creek Creek Mine Drainage Study: South Fork Reservation: Final Report

EPA Science Inventory

To characterize water quality in streams affected by historical mining it is necessary to determine the seasonal and spatial distribution patterns of trace metals concentrations. Identification of these patterns is used to identify the trace metals that are of ecological concern ...

Anoxia stimulates microbially catalyzed metal release from Animas River sediments.

PubMed

Saup, Casey M; Williams, Kenneth H; Rodríguez-Freire, Lucía; Cerrato, José M; Johnston, Michael D; Wilkins, Michael J

2017-04-19

The Gold King Mine spill in August 2015 released 11 million liters of metal-rich mine waste to the Animas River watershed, an area that has been previously exposed to historical mining activity spanning more than a century. Although adsorption onto fluvial sediments was responsible for rapid immobilization of a significant fraction of the spill-associated metals, patterns of longer-term mobility are poorly constrained. Metals associated with river sediments collected downstream of the Gold King Mine in August 2015 exhibited distinct presence and abundance patterns linked to location and mineralogy. Simulating riverbed burial and development of anoxic conditions, sediment microcosm experiments amended with Animas River dissolved organic carbon revealed the release of specific metal pools coupled to microbial Fe- and SO 4 2- -reduction. Results suggest that future sedimentation and burial of riverbed materials may drive longer-term changes in patterns of metal remobilization linked to anaerobic microbial metabolism, potentially driving decreases in downstream water quality. Such patterns emphasize the need for long-term water monitoring efforts in metal-impacted watersheds.

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.

A Comparative Study of Frequent and Maximal Periodic Pattern Mining Algorithms in Spatiotemporal Databases

NASA Astrophysics Data System (ADS)

Obulesu, O.; Rama Mohan Reddy, A., Dr; Mahendra, M.

2017-08-01

Detecting regular and efficient cyclic models is the demanding activity for data analysts due to unstructured, vigorous and enormous raw information produced from web. Many existing approaches generate large candidate patterns in the occurrence of huge and complex databases. In this work, two novel algorithms are proposed and a comparative examination is performed by considering scalability and performance parameters. The first algorithm is, EFPMA (Extended Regular Model Detection Algorithm) used to find frequent sequential patterns from the spatiotemporal dataset and the second one is, ETMA (Enhanced Tree-based Mining Algorithm) for detecting effective cyclic models with symbolic database representation. EFPMA is an algorithm grows models from both ends (prefixes and suffixes) of detected patterns, which results in faster pattern growth because of less levels of database projection compared to existing approaches such as Prefixspan and SPADE. ETMA uses distinct notions to store and manage transactions data horizontally such as segment, sequence and individual symbols. ETMA exploits a partition-and-conquer method to find maximal patterns by using symbolic notations. Using this algorithm, we can mine cyclic models in full-series sequential patterns including subsection series also. ETMA reduces the memory consumption and makes use of the efficient symbolic operation. Furthermore, ETMA only records time-series instances dynamically, in terms of character, series and section approaches respectively. The extent of the pattern and proving efficiency of the reducing and retrieval techniques from synthetic and actual datasets is a really open & challenging mining problem. These techniques are useful in data streams, traffic risk analysis, medical diagnosis, DNA sequence Mining, Earthquake prediction applications. Extensive investigational outcomes illustrates that the algorithms outperforms well towards efficiency and scalability than ECLAT, STNR and MAFIA approaches.

Tree-based approach for exploring marine spatial patterns with raster datasets.

PubMed

Liao, Xiaohan; Xue, Cunjin; Su, Fenzhen

2017-01-01

From multiple raster datasets to spatial association patterns, the data-mining technique is divided into three subtasks, i.e., raster dataset pretreatment, mining algorithm design, and spatial pattern exploration from the mining results. Comparison with the former two subtasks reveals that the latter remains unresolved. Confronted with the interrelated marine environmental parameters, we propose a Tree-based Approach for eXploring Marine Spatial Patterns with multiple raster datasets called TAXMarSP, which includes two models. One is the Tree-based Cascading Organization Model (TCOM), and the other is the Spatial Neighborhood-based CAlculation Model (SNCAM). TCOM designs the "Spatial node→Pattern node" from top to bottom layers to store the table-formatted frequent patterns. Together with TCOM, SNCAM considers the spatial neighborhood contributions to calculate the pattern-matching degree between the specified marine parameters and the table-formatted frequent patterns and then explores the marine spatial patterns. Using the prevalent quantification Apriori algorithm and a real remote sensing dataset from January 1998 to December 2014, a successful application of TAXMarSP to marine spatial patterns in the Pacific Ocean is described, and the obtained marine spatial patterns present not only the well-known but also new patterns to Earth scientists.

30 CFR 20.6 - General requirements.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false General requirements. 20.6 Section 20.6 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR TESTING, EVALUATION, AND APPROVAL OF MINING PRODUCTS ELECTRIC MINE LAMPS OTHER THAN STANDARD CAP LAMPS § 20.6 General requirements. (a) The...

Environmental consequences of the Retsof Salt Mine roof collapse

USGS Publications Warehouse

Yager, Richard M.

2013-01-01

In 1994, the largest salt mine in North America, which had been in operation for more than 100 years, catastrophically flooded when the mine ceiling collapsed. In addition to causing the loss of the mine and the mineral resources it provided, this event formed sinkholes, caused widespread subsidence to land, caused structures to crack and subside, and changed stream flow and erosion patterns. Subsequent flooding of the mine drained overlying aquifers, changed the groundwater salinity distribution (rendering domestic wells unusable), and allowed locally present natural gas to enter dwellings through water wells. Investigations including exploratory drilling, hydrologic and water-quality monitoring, geologic and geophysical studies, and numerical simulation of groundwater flow, salinity, and subsidence have been effective tools in understanding the environmental consequences of the mine collapse and informing decisions about management of those consequences for the future. Salt mines are generally dry, but are susceptible to leaks and can become flooded if groundwater from overlying aquifers or surface water finds a way downward into the mined cavity through hundreds of feet of rock. With its potential to flood the entire mine cavity, groundwater is a constant source of concern for mine operators. The problem is compounded by the viscous nature of salt and the fact that salt mines commonly lie beneath water-bearing aquifers. Salt (for example halite or potash) deforms and “creeps” into the mined openings over time spans that range from years to centuries. This movement of salt can destabilize the overlying rock layers and lead to their eventual sagging and collapse, creating permeable pathways for leakage of water and depressions or openings at land surface, such as sinkholes. Salt is also highly soluble in water; therefore, whenever water begins to flow into a salt mine, the channels through which it flows increase in diameter as the surrounding salt dissolves. Some mines leak at a slow rate for decades before a section of rock gives way, allowing what initially was a trickle of water to suddenly become a cascade and finally a torrent. Other mines become flooded and are destroyed when an errant drill hole punctures the mine ceiling, allowing water from overlying sources to flow into the mine. Either scenario can cause catastrophic flooding and permanent loss of the mine. Occasionally, a mine that has remained dry for a century will undergo a roof collapse that results in flooding.

Methane Content Estimation in DuongHuy Coal Mine

NASA Astrophysics Data System (ADS)

Nguyen, Van Thinh; Mijał, Waldemar; Dang, Vu Chi; Nguyen, Thi Tuyet Mai

2018-03-01

Methane hazard has always been considered for underground coal mining as it can lead to methane explosion. In Quang Ninh province, several coal mines such as Mạo Khe coal mine, Khe Cham coal mine, especially Duong Huy mine that have high methane content. Experimental data to examine contents of methane bearing coal seams at different depths are not similar in Duong coal mine. In order to ensure safety, this report has been undertaken to determine a pattern of changing methane contents of coal seams at different exploitation depths in Duong Huy underground coal mine.

Physical environment and hydrologic characteristics of coal-mining areas in Missouri

USGS Publications Warehouse

Vaill, J.E.; Barks, James H.

1980-01-01

Hydrologic information for the north-central and western coal-mining regions of Missouri is needed to define the hydrologic system in these areas of major historic and planned coal development. This report describes the physical setting, climate, coal-mining practices, general hydrologic system, and the current (1980) hydrologie data base in these two coal-mining regions. Streamflow in both mining regions is poorly sustained. Stream water quality generally varies with location and the magnitude of coal-mining activity in a watershed. Streams in non coal-mining areas generally have dissolved-solids concentrations less than 400 milligrams per liter. Acid-mine drainage has seriously affected some streams by reducing the pH to less than 4.0 and increasing the dissolved-solids concentrations to greater than 1,000 milligrams per liter. This has resulted in fish kills in some instances. Ground-water movement is impeded both laterally and vertically in both mining regions, especially in western Missouri, because of the low hydraulic conductivity of the rocks of Pennsylvanian age. The quality of ground water varies widely depending on location and depth. Ground water commonly contains high concentrations of iron and sulfate, and dissolved-solids concentrations generally are greater than 1,000 milligrams per liter.

Abandoned Mine Lands Program - Division of Mining, Land, and Water

Science.gov Websites

, safety, general welfare and property from extreme danger resulting from the adverse effects of past coal mining practices. 2. Protection of public health, safety and general welfare from adverse effects of past lands and waters and the environment previously degraded by adverse effects of past coal mining

30 CFR 77.411 - Compressed air and boilers; general.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 1 2011-07-01 2011-07-01 false Compressed air and boilers; general. 77.411 Section 77.411 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE SAFETY AND HEALTH MANDATORY SAFETY STANDARDS, SURFACE COAL MINES AND SURFACE WORK AREAS OF UNDERGROUND COAL MINES Safeguards for Mechanical Equipment ...

30 CFR 77.411 - Compressed air and boilers; general.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 30 Mineral Resources 1 2012-07-01 2012-07-01 false Compressed air and boilers; general. 77.411 Section 77.411 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE SAFETY AND HEALTH MANDATORY SAFETY STANDARDS, SURFACE COAL MINES AND SURFACE WORK AREAS OF UNDERGROUND COAL MINES Safeguards for Mechanical Equipment ...

30 CFR 77.411 - Compressed air and boilers; general.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 30 Mineral Resources 1 2014-07-01 2014-07-01 false Compressed air and boilers; general. 77.411 Section 77.411 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE SAFETY AND HEALTH MANDATORY SAFETY STANDARDS, SURFACE COAL MINES AND SURFACE WORK AREAS OF UNDERGROUND COAL MINES Safeguards for Mechanical Equipment ...

30 CFR 77.411 - Compressed air and boilers; general.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 30 Mineral Resources 1 2013-07-01 2013-07-01 false Compressed air and boilers; general. 77.411 Section 77.411 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE SAFETY AND HEALTH MANDATORY SAFETY STANDARDS, SURFACE COAL MINES AND SURFACE WORK AREAS OF UNDERGROUND COAL MINES Safeguards for Mechanical Equipment ...

30 CFR 77.411 - Compressed air and boilers; general.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Compressed air and boilers; general. 77.411 Section 77.411 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE SAFETY AND HEALTH MANDATORY SAFETY STANDARDS, SURFACE COAL MINES AND SURFACE WORK AREAS OF UNDERGROUND COAL MINES Safeguards for Mechanical Equipment ...

Finding Spatio-Temporal Patterns in Large Sensor Datasets

ERIC Educational Resources Information Center

McGuire, Michael Patrick

2010-01-01

Spatial or temporal data mining tasks are performed in the context of the relevant space, defined by a spatial neighborhood, and the relevant time period, defined by a specific time interval. Furthermore, when mining large spatio-temporal datasets, interesting patterns typically emerge where the dataset is most dynamic. This dissertation is…

Examining Online Learning Patterns with Data Mining Techniques in Peer-Moderated and Teacher-Moderated Courses

ERIC Educational Resources Information Center

Hung, Jui-Long; Crooks, Steven M.

2009-01-01

The student learning process is important in online learning environments. If instructors can "observe" online learning behaviors, they can provide adaptive feedback, adjust instructional strategies, and assist students in establishing patterns of successful learning activities. This study used data mining techniques to examine and…

Pattern Mining for Extraction of mentions of Adverse Drug Reactions from User Comments

PubMed Central

Nikfarjam, Azadeh; Gonzalez, Graciela H.

2011-01-01

Rapid growth of online health social networks has enabled patients to communicate more easily with each other. This way of exchange of opinions and experiences has provided a rich source of information about drugs and their effectiveness and more importantly, their possible adverse reactions. We developed a system to automatically extract mentions of Adverse Drug Reactions (ADRs) from user reviews about drugs in social network websites by mining a set of language patterns. The system applied association rule mining on a set of annotated comments to extract the underlying patterns of colloquial expressions about adverse effects. The patterns were tested on a set of unseen comments to evaluate their performance. We reached to precision of 70.01% and recall of 66.32% and F-measure of 67.96%. PMID:22195162

Privacy Preserving Sequential Pattern Mining in Data Stream

NASA Astrophysics Data System (ADS)

Huang, Qin-Hua

The privacy preserving data mining technique researches have gained much attention in recent years. For data stream systems, wireless networks and mobile devices, the related stream data mining techniques research is still in its' early stage. In this paper, an data mining algorithm dealing with privacy preserving problem in data stream is presented.

The Lure of Statistics in Data Mining

ERIC Educational Resources Information Center

Grover, Lovleen Kumar; Mehra, Rajni

2008-01-01

The field of Data Mining like Statistics concerns itself with "learning from data" or "turning data into information". For statisticians the term "Data mining" has a pejorative meaning. Instead of finding useful patterns in large volumes of data as in the case of Statistics, data mining has the connotation of searching for data to fit preconceived…

Source and path identification of metals pollution in a mining area by PMF and rare earth element patterns in road dust.

PubMed

Tian, Shuhan; Liang, Tao; Li, Kexin; Wang, Lingqing

2018-08-15

To better assess pollution and offer efficient protection for local residents, it is necessary to both conduct an exhaustive investigation into pollution levels and quantify its contributing sources and paths. As it is the biggest light rare earth element (REE) reserve in the world, Bayan Obo deposit releases large amounts of heavy metals into the surrounding environment. In this study, road dust from zones located at different distances to the mining area was collected and sieved using seven sizes. This allowed for subsequent analysis of size-dependent influences of mining activities. A receptor model was used to quantitatively assess mine contributions. REE distribution patterns and other REE parameters were compared with those in airborne particulates and the surrounding soil to analyze pollution paths. Results showed that 27 metals were rated as moderately to extremely polluted (2

Double Mine Building, general view in setting; view northeast ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

Double Mine Building, general view in setting; view northeast - Fort McKinley, Double Mine Building, East side of East Side Drive, approximately 125 feet south of Weymouth Way, Great Diamond Island, Portland, Cumberland County, ME

26 CFR 1.617-4 - Treatment of gain from disposition of certain mining property.

Code of Federal Regulations, 2010 CFR

2010-04-01

... mining property. 1.617-4 Section 1.617-4 Internal Revenue INTERNAL REVENUE SERVICE, DEPARTMENT OF THE... of gain from disposition of certain mining property. (a) In general. (1) In general, section 617(d)(1) provides, that, upon a disposition of mining property, the lower of (i) the adjusted exploration...

Prediction of Human Activity by Discovering Temporal Sequence Patterns.

PubMed

Li, Kang; Fu, Yun

2014-08-01

Early prediction of ongoing human activity has become more valuable in a large variety of time-critical applications. To build an effective representation for prediction, human activities can be characterized by a complex temporal composition of constituent simple actions and interacting objects. Different from early detection on short-duration simple actions, we propose a novel framework for long -duration complex activity prediction by discovering three key aspects of activity: Causality, Context-cue, and Predictability. The major contributions of our work include: (1) a general framework is proposed to systematically address the problem of complex activity prediction by mining temporal sequence patterns; (2) probabilistic suffix tree (PST) is introduced to model causal relationships between constituent actions, where both large and small order Markov dependencies between action units are captured; (3) the context-cue, especially interactive objects information, is modeled through sequential pattern mining (SPM), where a series of action and object co-occurrence are encoded as a complex symbolic sequence; (4) we also present a predictive accumulative function (PAF) to depict the predictability of each kind of activity. The effectiveness of our approach is evaluated on two experimental scenarios with two data sets for each: action-only prediction and context-aware prediction. Our method achieves superior performance for predicting global activity classes and local action units.

Community and job satisfactions: an argument for reciprocal influence based on the principle of stimulus generalization

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

Gavin, J.; Montgomery, J.C.

The principle of stimulus generalization provided the underlying argument for a test of hypotheses regarding the association of community and job satisfactions and a critique of related theory and research. Two-stage least squares (2SLS) analysis made possible the examination of reciprocal causation, a notion inherent in the theoretical argument. Data were obtained from 276 employees of a Western U.S. coal mine as part of a work attitudes survey. The 2SLS analysis indicated a significant impact of community satisfaction on job satisfaction and an effect of borderline significance of job on community satisfaction. Theory-based correlational comparisons were made on groups ofmore » employees residing in four distinct communities, high and low tenure groups, males and females, and different levels in the mine's hierarchy. The pattern of correlations was generally consistent with predictions, but significance tests for differences yielded equivocal support. When considered in the context of previous studies, the data upheld a reciprocal causal model and the explanatory principle of stimulus generalization for understanding the relation of community and job satisfactions. Sample characteristics necessitate cautious interpretation and the model per se might best be viewed as a heuristic framework for more definitive research.« less

Anoxia stimulates microbially catalyzed metal release from Animas River sediments

DOE PAGES

Saup, Casey M.; Williams, Kenneth H.; Rodríguez-Freire, Lucía; ...

2017-03-06

The Gold King Mine spill in August 2015 released 11 million liters of metal-rich mine waste to the Animas River watershed, an area that has been previously exposed to historical mining activity spanning more than a century. Although adsorption onto fluvial sediments was responsible for rapid immobilization of a significant fraction of the spill-associated metals, patterns of longer-term mobility are poorly constrained. Metals associated with river sediments collected downstream of the Gold King Mine in August 2015 exhibited distinct presence and abundance patterns linked to location and mineralogy. Simulating riverbed burial and development of anoxic conditions, sediment microcosm experiments amendedmore » with Animas River dissolved organic carbon revealed the release of specific metal pools coupled to microbial Fe- and SO 4 2-reduction. Results suggest that future sedimentation and burial of riverbed materials may drive longer-term changes in patterns of metal remobilization linked to anaerobic microbial metabolism, potentially driving decreases in downstream water quality. Such patterns emphasize the need for long-term water monitoring efforts in metal-impacted watersheds.« less

Anoxia stimulates microbially catalyzed metal release from Animas River sediments

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

Saup, Casey M.; Williams, Kenneth H.; Rodríguez-Freire, Lucía

The Gold King Mine spill in August 2015 released 11 million liters of metal-rich mine waste to the Animas River watershed, an area that has been previously exposed to historical mining activity spanning more than a century. Although adsorption onto fluvial sediments was responsible for rapid immobilization of a significant fraction of the spill-associated metals, patterns of longer-term mobility are poorly constrained. Metals associated with river sediments collected downstream of the Gold King Mine in August 2015 exhibited distinct presence and abundance patterns linked to location and mineralogy. Simulating riverbed burial and development of anoxic conditions, sediment microcosm experiments amendedmore » with Animas River dissolved organic carbon revealed the release of specific metal pools coupled to microbial Fe- and SO 4 2-reduction. Results suggest that future sedimentation and burial of riverbed materials may drive longer-term changes in patterns of metal remobilization linked to anaerobic microbial metabolism, potentially driving decreases in downstream water quality. Such patterns emphasize the need for long-term water monitoring efforts in metal-impacted watersheds.« less

Mining Temporal Patterns to Improve Agents Behavior: Two Case Studies

NASA Astrophysics Data System (ADS)

Fournier-Viger, Philippe; Nkambou, Roger; Faghihi, Usef; Nguifo, Engelbert Mephu

We propose two mechanisms for agent learning based on the idea of mining temporal patterns from agent behavior. The first one consists of extracting temporal patterns from the perceived behavior of other agents accomplishing a task, to learn the task. The second learning mechanism consists in extracting temporal patterns from an agent's own behavior. In this case, the agent then reuses patterns that brought self-satisfaction. In both cases, no assumption is made on how the observed agents' behavior is internally generated. A case study with a real application is presented to illustrate each learning mechanism.

On mining complex sequential data by means of FCA and pattern structures

NASA Astrophysics Data System (ADS)

Buzmakov, Aleksey; Egho, Elias; Jay, Nicolas; Kuznetsov, Sergei O.; Napoli, Amedeo; Raïssi, Chedy

2016-02-01

Nowadays data-sets are available in very complex and heterogeneous ways. Mining of such data collections is essential to support many real-world applications ranging from healthcare to marketing. In this work, we focus on the analysis of "complex" sequential data by means of interesting sequential patterns. We approach the problem using the elegant mathematical framework of formal concept analysis and its extension based on "pattern structures". Pattern structures are used for mining complex data (such as sequences or graphs) and are based on a subsumption operation, which in our case is defined with respect to the partial order on sequences. We show how pattern structures along with projections (i.e. a data reduction of sequential structures) are able to enumerate more meaningful patterns and increase the computing efficiency of the approach. Finally, we show the applicability of the presented method for discovering and analysing interesting patient patterns from a French healthcare data-set on cancer. The quantitative and qualitative results (with annotations and analysis from a physician) are reported in this use-case which is the main motivation for this work.

Porites corals as recorders of mining and environmental impacts: Misima Island, Papua New Guinea

NASA Astrophysics Data System (ADS)

Fallon, Stewart J.; White, Jamie C.; McCulloch, Malcolm T.

2002-01-01

In 1989 open-cut gold mining commenced on Misima Island in Papua New Guinea (PNG). Open-cut mining by its nature causes a significant increase in sedimentation via the exposure of soils to the erosive forces of rain and runoff. This increased sedimentation affected the nearby fringing coral reef to varying degrees, ranging from coral mortality (smothering) to relatively minor short-term impacts. The sediment associated with the mining operation consists of weathered quartz feldspar, greenstone, and schist. These rocks have distinct chemical characteristics (rare earth element patterns and high abundances of manganese, zinc, and lead) and are entering the near-shore environment in considerably higher than normal concentrations. Using laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS), we analyzed eight colonies (two from high sedimentation, two transitional, two minor, and two unaffected control sites) for Y, La, Ce, Mn, Zn, and Pb. All sites show low steady background levels prior to the commencement of mining in 1988. Subsequently, all sites apart from the control show dramatic increases of Y, La, and Ce associated with the increased sedimentation as well as rapid decreases following the cessation of mining. The elements Zn and Pb exhibit a different behavior, increasing in concentration after 1989 when ore processing began and one year after initial mining operations. Elevated levels of Zn and Pb in corals has continued well after the cessation of mining, indicating ongoing transport into the reef of these metals via sulfate-rich waters. Rare earth element (REE) abundance patterns measured in two corals show significant differences compared to Coral Sea seawater. The corals display enrichments in the light and middle REEs while the heavy REEs are depleted relative to the seawater pattern. This suggests that the nearshore seawater REE pattern is dominated by island sedimentation. Trace element abundances of Misima Island corals clearly record the dramatic changes in the environmental conditions at this site and provide a basis for identifying anthropogenic influences on corals reefs.

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.

30 CFR 57.4200 - General requirements.

Code of Federal Regulations, 2010 CFR

2010-07-01

... Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR METAL AND NONMETAL MINE SAFETY AND HEALTH SAFETY AND HEALTH STANDARDS-UNDERGROUND METAL AND NONMETAL MINES Fire Prevention and Control Firefighting Equipment § 57.4200 General requirements. (a) For fighting fires that could endanger...

30 CFR 56.4200 - General requirements.

Code of Federal Regulations, 2010 CFR

2010-07-01

... Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR METAL AND NONMETAL MINE SAFETY AND HEALTH SAFETY AND HEALTH STANDARDS-SURFACE METAL AND NONMETAL MINES Fire Prevention and Control Firefighting Equipment § 56.4200 General requirements. (a) For fighting fires that could endanger...

A primer to frequent itemset mining for bioinformatics

PubMed Central

Naulaerts, Stefan; Meysman, Pieter; Bittremieux, Wout; Vu, Trung Nghia; Vanden Berghe, Wim; Goethals, Bart

2015-01-01

Over the past two decades, pattern mining techniques have become an integral part of many bioinformatics solutions. Frequent itemset mining is a popular group of pattern mining techniques designed to identify elements that frequently co-occur. An archetypical example is the identification of products that often end up together in the same shopping basket in supermarket transactions. A number of algorithms have been developed to address variations of this computationally non-trivial problem. Frequent itemset mining techniques are able to efficiently capture the characteristics of (complex) data and succinctly summarize it. Owing to these and other interesting properties, these techniques have proven their value in biological data analysis. Nevertheless, information about the bioinformatics applications of these techniques remains scattered. In this primer, we introduce frequent itemset mining and their derived association rules for life scientists. We give an overview of various algorithms, and illustrate how they can be used in several real-life bioinformatics application domains. We end with a discussion of the future potential and open challenges for frequent itemset mining in the life sciences. PMID:24162173

Study of acid mine drainage management with evaluating climate and rainfall in East Pit 3 West Banko coal mine

NASA Astrophysics Data System (ADS)

Rochyani, Neny

2017-11-01

Acid mine drainage is a major problem for the mining environment. The main factor that formed acid mine drainage is the volume of rainfall. Therefore, it is important to know clearly the main climate pattern of rainfall and season on the management of acid mine drainage. This study focuses on the effects of rainfall on acid mine water management. Based on daily rainfall data, monthly and seasonal patterns by using Gumbel approach is known the amount of rainfall that occurred in East Pit 3 West Banko area. The data also obtained the highest maximum daily rainfall on 165 mm/day and the lowest at 76.4 mm/day, where it is known that the rainfall conditions during the period 2007 - 2016 is from November to April so the use of lime is also slightly, While the low rainfall is from May to October and the use of lime will be more and more. Based on calculation of lime requirement for each return period, it can be seen the total of lime and financial requirement for treatment of each return period.

42 CFR 1007.20 - Circumstances in which data mining is permissible and approval by HHS Office of Inspector General.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 42 Public Health 5 2013-10-01 2013-10-01 false Circumstances in which data mining is permissible... CONTROL UNITS § 1007.20 Circumstances in which data mining is permissible and approval by HHS Office of Inspector General. (a) Notwithstanding § 1007.19(e)(2), a MFCU may engage in data mining as defined in this...

42 CFR 1007.20 - Circumstances in which data mining is permissible and approval by HHS Office of Inspector General.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 42 Public Health 5 2014-10-01 2014-10-01 false Circumstances in which data mining is permissible... CONTROL UNITS § 1007.20 Circumstances in which data mining is permissible and approval by HHS Office of Inspector General. (a) Notwithstanding § 1007.19(e)(2), a MFCU may engage in data mining as defined in this...

30 CFR 28.40 - Construction and performance requirements; general.

Code of Federal Regulations, 2012 CFR

2012-07-01

.... Department of Labor, Mine Safety and Health Administration, Approval and Certification Center, 765 Technology...; general. 28.40 Section 28.40 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR...-CIRCUIT PROTECTION FOR TRAILING CABLES IN COAL MINES Construction, Performance, and Testing Requirements...

30 CFR 28.40 - Construction and performance requirements; general.

Code of Federal Regulations, 2014 CFR

2014-07-01

.... Department of Labor, Mine Safety and Health Administration, Approval and Certification Center, 765 Technology...; general. 28.40 Section 28.40 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR...-CIRCUIT PROTECTION FOR TRAILING CABLES IN COAL MINES Construction, Performance, and Testing Requirements...

30 CFR 28.40 - Construction and performance requirements; general.

Code of Federal Regulations, 2011 CFR

2011-07-01

.... Department of Labor, Mine Safety and Health Administration, Approval and Certification Center, 765 Technology...; general. 28.40 Section 28.40 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR...-CIRCUIT PROTECTION FOR TRAILING CABLES IN COAL MINES Construction, Performance, and Testing Requirements...

30 CFR 28.40 - Construction and performance requirements; general.

Code of Federal Regulations, 2013 CFR

2013-07-01

.... Department of Labor, Mine Safety and Health Administration, Approval and Certification Center, 765 Technology...; general. 28.40 Section 28.40 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR...-CIRCUIT PROTECTION FOR TRAILING CABLES IN COAL MINES Construction, Performance, and Testing Requirements...

GENERAL EXTERIOR VIEW, LOOKING NORTHEAST, OF THE SURFACE PLANT WITH ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

GENERAL EXTERIOR VIEW, LOOKING NORTHEAST, OF THE SURFACE PLANT WITH CONVEYORS. JIM WALTER RESOURCES INC. MINING DIVISION OPERATES FOUR UNDERGROUND COAL MINES IN THE BLUE CREEK COAL FIELD OF BIRMINGHAM DISTRICT, THREE IN TUSCALOOSA COUNTY AND ONE IN JEFFERSON COUNTY. TOTAL ANNUAL PRODUCTION IS 8,000,000 TONS. AT 2,300 DEEP, JIM WALTER'S BROOKWOOD MINES ARE THE DEEPEST UNDERGROUND COAL MINES IN NORTH AMERICA. THEY PRODUCE A HIGH-GRADE MEDIUM VOLATILE LOW SULPHUR METALLURGICAL COAL. THE BROOKWOOD NO. 5 MINE (PICTURED IN THIS PHOTOGRAPH) EMPLOYS THE LONGWALL MINING TECHNIQUES WITH BELTS CONVEYING COAL FROM UNDERGROUND OPERATIONS TO THE SURFACE. - JIm Walter Resources, Incorporated, Brookwood No. 5 Mine, 12972 Lock 17 Road, Brookwood, Tuscaloosa County, AL

Data Mining Citizen Science Results

NASA Astrophysics Data System (ADS)

Borne, K. D.

2012-12-01

Scientific discovery from big data is enabled through multiple channels, including data mining (through the application of machine learning algorithms) and human computation (commonly implemented through citizen science tasks). We will describe the results of new data mining experiments on the results from citizen science activities. Discovering patterns, trends, and anomalies in data are among the powerful contributions of citizen science. Establishing scientific algorithms that can subsequently re-discover the same types of patterns, trends, and anomalies in automatic data processing pipelines will ultimately result from the transformation of those human algorithms into computer algorithms, which can then be applied to much larger data collections. Scientific discovery from big data is thus greatly amplified through the marriage of data mining with citizen science.

Data mining in pharma sector: benefits.

PubMed

Ranjan, Jayanthi

2009-01-01

The amount of data getting generated in any sector at present is enormous. The information flow in the pharma industry is huge. Pharma firms are progressing into increased technology-enabled products and services. Data mining, which is knowledge discovery from large sets of data, helps pharma firms to discover patterns in improving the quality of drug discovery and delivery methods. The paper aims to present how data mining is useful in the pharma industry, how its techniques can yield good results in pharma sector, and to show how data mining can really enhance in making decisions using pharmaceutical data. This conceptual paper is written based on secondary study, research and observations from magazines, reports and notes. The author has listed the types of patterns that can be discovered using data mining in pharma data. The paper shows how data mining is useful in the pharma industry and how its techniques can yield good results in pharma sector. Although much work can be produced for discovering knowledge in pharma data using data mining, the paper is limited to conceptualizing the ideas and view points at this stage; future work may include applying data mining techniques to pharma data based on primary research using the available, famous significant data mining tools. Research papers and conceptual papers related to data mining in Pharma industry are rare; this is the motivation for the paper.

Process Mining Online Assessment Data

ERIC Educational Resources Information Center

Pechenizkiy, Mykola; Trcka, Nikola; Vasilyeva, Ekaterina; van der Aalst, Wil; De Bra, Paul

2009-01-01

Traditional data mining techniques have been extensively applied to find interesting patterns, build descriptive and predictive models from large volumes of data accumulated through the use of different information systems. The results of data mining can be used for getting a better understanding of the underlying educational processes, for…

Efficient Mining of Interesting Patterns in Large Biological Sequences

PubMed Central

Rashid, Md. Mamunur; Karim, Md. Rezaul; Jeong, Byeong-Soo

2012-01-01

Pattern discovery in biological sequences (e.g., DNA sequences) is one of the most challenging tasks in computational biology and bioinformatics. So far, in most approaches, the number of occurrences is a major measure of determining whether a pattern is interesting or not. In computational biology, however, a pattern that is not frequent may still be considered very informative if its actual support frequency exceeds the prior expectation by a large margin. In this paper, we propose a new interesting measure that can provide meaningful biological information. We also propose an efficient index-based method for mining such interesting patterns. Experimental results show that our approach can find interesting patterns within an acceptable computation time. PMID:23105928

Efficient mining of interesting patterns in large biological sequences.

PubMed

Rashid, Md Mamunur; Karim, Md Rezaul; Jeong, Byeong-Soo; Choi, Ho-Jin

2012-03-01

Pattern discovery in biological sequences (e.g., DNA sequences) is one of the most challenging tasks in computational biology and bioinformatics. So far, in most approaches, the number of occurrences is a major measure of determining whether a pattern is interesting or not. In computational biology, however, a pattern that is not frequent may still be considered very informative if its actual support frequency exceeds the prior expectation by a large margin. In this paper, we propose a new interesting measure that can provide meaningful biological information. We also propose an efficient index-based method for mining such interesting patterns. Experimental results show that our approach can find interesting patterns within an acceptable computation time.

Mechanistic insights of the Min oscillator via cell-free reconstitution and imaging

NASA Astrophysics Data System (ADS)

Mizuuchi, Kiyoshi; Vecchiarelli, Anthony G.

2018-05-01

The MinD and MinE proteins of Escherichia coli self-organize into a standing-wave oscillator on the membrane to help align division at mid-cell. When unleashed from cellular confines, MinD and MinE form a spectrum of patterns on artificial bilayers—static amoebas, traveling waves, traveling mushrooms, and bursts with standing-wave dynamics. We recently focused our cell-free studies on bursts because their dynamics recapitulate many features of Min oscillation observed in vivo. The data unveiled a patterning mechanism largely governed by MinE regulation of MinD interaction with membrane. We proposed that the MinD to MinE ratio on the membrane acts as a toggle switch between MinE-stimulated recruitment and release of MinD from the membrane. In this review, we summarize cell-free data on the Min system and expand upon a molecular mechanism that provides a biochemical explanation as to how these two ‘simple’ proteins can form the remarkable spectrum of patterns.

Occurrence and Trends of Selected Chemical Constituents in Bottom Sediment, Grand Lake O' the Cherokees, Northeast Oklahoma, 1940-2008

USGS Publications Warehouse

Juracek, Kyle E.; Becker, Mark F.

2009-01-01

After over 100 years of continuous activity, lead and zinc mining in the Tri-State Mining District (hereafter referred to as the TSMD) in parts of southeast Kansas, southwest Missouri, and northeast Oklahoma ended in the 1970s. The mining activity resulted in substantial historical and ongoing input of cadmium, lead, and zinc to the environment including Grand Lake O' the Cherokees (hereafter referred to as Grand Lake), a large reservoir in northeast Oklahoma. To help determine the extent and magnitude of contamination in Grand Lake, a one-year study was conducted by the U.S. Geological Survey in cooperation with the U.S. Fish and Wildlife Service. Bottom-sediment coring at five sites was used to investigate the occurrence of cadmium, lead, zinc, and other selected constituents in the bottom sediment of Grand Lake. Cadmium concentrations in the bottom sediment of Grand Lake ranged from 2.3 to 3.6 mg/kg (milligrams per kilogram) with a median of 3.5 mg/kg (5 samples). Compared to an estimated local background concentration of 0.6 mg/kg, the historical mining activity increased cadmium concentrations by about 280 to 500 percent. Lead concentrations ranged from 35 to 102 mg/kg with a median of 59 mg/kg (50 samples). Compared to an estimated local background concentration of 20 mg/kg, the historical mining activity increased lead concentrations by about 75 to 410 percent. The range in zinc concentrations was 380 to 986 mg/kg with a median of 765 mg/kg (50 samples). Compared to an estimated local background concentration of 100 mg/kg, the historical mining activity increased zinc concentrations by about 280 to 890 percent. With the exception of the most upstream coring site, the lead and zinc depositional profiles generally were similar in terms of the range in concentrations measured and the temporal pattern observed. Depositional profiles for lead and zinc indicated mid-core peaks followed by concentrations that decreased since about the 1980s. The depositional profiles reflect the complex interaction of several factors including historical mining and related activities, mine drainage, remediation, landscape stabilization, precipitation and associated runoff, and the erosion and transport of contaminated and clean sediments within the basin. Compared to sediment-quality guidelines, the Grand Lake samples had cadmium concentrations that were substantially less than the general probable-effects concentration (PEC) (4.98 mg/kg) and a TSMD-specific PEC (11.1 mg/kg). The PECs represent the concentration above which toxic biological effects are likely to occur. Likewise, all sediment samples had lead concentrations that were substantially less than the general PEC (128 mg/kg) and a TSMD-specific PEC (150 mg/kg). Zinc concentrations typically exceeded the general PEC (459 mg/kg), but were substantially less than a TSMD-specific PEC (2,083 mg/kg). Throughout the history of Grand Lake, lead and zinc concentrations in the deposited sediment did not approach or exceed the TSMD-specific PECs. As of 2008, legacy effects of mining still included the delivery of contaminated sediment to Grand Lake by the Spring and Neosho Rivers. The Neosho River, with its larger flows and less-contaminated sediment, likely dilutes the load of contaminated sediment delivered to Grand Lake by the Spring River. The information contained in this report provides a baseline of Grand Lake conditions with which to compare future conditions that may represent a response to changes in mining-related activity in the Grand Lake Basin.

A Contextualized, Differential Sequence Mining Method to Derive Students' Learning Behavior Patterns

ERIC Educational Resources Information Center

Kinnebrew, John S.; Loretz, Kirk M.; Biswas, Gautam

2013-01-01

Computer-based learning environments can produce a wealth of data on student learning interactions. This paper presents an exploratory data mining methodology for assessing and comparing students' learning behaviors from these interaction traces. The core algorithm employs a novel combination of sequence mining techniques to identify deferentially…

36 CFR 5.14 - Prospecting, mining, and mineral leasing.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 36 Parks, Forests, and Public Property 1 2010-07-01 2010-07-01 false Prospecting, mining, and... OF THE INTERIOR COMMERCIAL AND PRIVATE OPERATIONS § 5.14 Prospecting, mining, and mineral leasing. Prospecting, mining, and the location of mining claims under the general mining laws and leasing under the...

30 CFR 819.19 - Auger mining: Backfilling and grading.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 3 2011-07-01 2011-07-01 false Auger mining: Backfilling and grading. 819.19 Section 819.19 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE... MINING § 819.19 Auger mining: Backfilling and grading. (a) General. Auger mining shall be conducted in...

Collaborative mining of graph patterns from multiple sources

NASA Astrophysics Data System (ADS)

Levchuk, Georgiy; Colonna-Romanoa, John

2016-05-01

Intelligence analysts require automated tools to mine multi-source data, including answering queries, learning patterns of life, and discovering malicious or anomalous activities. Graph mining algorithms have recently attracted significant attention in intelligence community, because the text-derived knowledge can be efficiently represented as graphs of entities and relationships. However, graph mining models are limited to use-cases involving collocated data, and often make restrictive assumptions about the types of patterns that need to be discovered, the relationships between individual sources, and availability of accurate data segmentation. In this paper we present a model to learn the graph patterns from multiple relational data sources, when each source might have only a fragment (or subgraph) of the knowledge that needs to be discovered, and segmentation of data into training or testing instances is not available. Our model is based on distributed collaborative graph learning, and is effective in situations when the data is kept locally and cannot be moved to a centralized location. Our experiments show that proposed collaborative learning achieves learning quality better than aggregated centralized graph learning, and has learning time comparable to traditional distributed learning in which a knowledge of data segmentation is needed.

Collaborative mining and transfer learning for relational data

NASA Astrophysics Data System (ADS)

Levchuk, Georgiy; Eslami, Mohammed

2015-06-01

Many of the real-world problems, - including human knowledge, communication, biological, and cyber network analysis, - deal with data entities for which the essential information is contained in the relations among those entities. Such data must be modeled and analyzed as graphs, with attributes on both objects and relations encode and differentiate their semantics. Traditional data mining algorithms were originally designed for analyzing discrete objects for which a set of features can be defined, and thus cannot be easily adapted to deal with graph data. This gave rise to the relational data mining field of research, of which graph pattern learning is a key sub-domain [11]. In this paper, we describe a model for learning graph patterns in collaborative distributed manner. Distributed pattern learning is challenging due to dependencies between the nodes and relations in the graph, and variability across graph instances. We present three algorithms that trade-off benefits of parallelization and data aggregation, compare their performance to centralized graph learning, and discuss individual benefits and weaknesses of each model. Presented algorithms are designed for linear speedup in distributed computing environments, and learn graph patterns that are both closer to ground truth and provide higher detection rates than centralized mining algorithm.

SOMA: A Proposed Framework for Trend Mining in Large UK Diabetic Retinopathy Temporal Databases

NASA Astrophysics Data System (ADS)

Somaraki, Vassiliki; Harding, Simon; Broadbent, Deborah; Coenen, Frans

In this paper, we present SOMA, a new trend mining framework; and Aretaeus, the associated trend mining algorithm. The proposed framework is able to detect different kinds of trends within longitudinal datasets. The prototype trends are defined mathematically so that they can be mapped onto the temporal patterns. Trends are defined and generated in terms of the frequency of occurrence of pattern changes over time. To evaluate the proposed framework the process was applied to a large collection of medical records, forming part of the diabetic retinopathy screening programme at the Royal Liverpool University Hospital.

Web usage data mining agent

NASA Astrophysics Data System (ADS)

Madiraju, Praveen; Zhang, Yanqing

2002-03-01

When a user logs in to a website, behind the scenes the user leaves his/her impressions, usage patterns and also access patterns in the web servers log file. A web usage mining agent can analyze these web logs to help web developers to improve the organization and presentation of their websites. They can help system administrators in improving the system performance. Web logs provide invaluable help in creating adaptive web sites and also in analyzing the network traffic analysis. This paper presents the design and implementation of a Web usage mining agent for digging in to the web log files.

Supporting Solar Physics Research via Data Mining

NASA Astrophysics Data System (ADS)

Angryk, Rafal; Banda, J.; Schuh, M.; Ganesan Pillai, K.; Tosun, H.; Martens, P.

2012-05-01

In this talk we will briefly introduce three pillars of data mining (i.e. frequent patterns discovery, classification, and clustering), and discuss some possible applications of known data mining techniques which can directly benefit solar physics research. In particular, we plan to demonstrate applicability of frequent patterns discovery methods for the verification of hypotheses about co-occurrence (in space and time) of filaments and sigmoids. We will also show how classification/machine learning algorithms can be utilized to verify human-created software modules to discover individual types of solar phenomena. Finally, we will discuss applicability of clustering techniques to image data processing.

43 CFR 6304.10 - Mining law administration.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 43 Public Lands: Interior 2 2011-10-01 2011-10-01 false Mining law administration. 6304.10 Section... WILDERNESS AREAS Uses Addressed in Special Provisions of the Wilderness Act Mining Under the General Mining Laws § 6304.10 Mining law administration. ...

Correlation of HIV protease structure with Indinavir resistance: a data mining and neural networks approach

NASA Astrophysics Data System (ADS)

Draghici, Sorin; Cumberland, Lonnie T., Jr.; Kovari, Ladislau C.

2000-04-01

This paper presents some results of data mining HIV genotypic and structural data. Our aim is to try to relate structural features of HIV enzymes essential to its reproductive abilities to the drug resistance phenomenon. This paper concentrates on the HIV protease enzyme and Indinavir which is one of the FDA approved protease inhibitors. Our starting point was the current list of HIV mutations related to drug resistance. We used the fact that some molecular structures determined through high resolution X-ray crystallography were available for the protease-Indinavir complex. Starting with these structures and the known mutations, we modelled the mutant proteases and studied the pattern of atomic contacts between the protease and the drug. After suitable pre- processing, these patterns have been used as the input of our data mining process. We have used both supervised and unsupervised learning techniques with the aim of understanding the relationship between structural features at a molecular level and resistance to Indinavir. The supervised learning was aimed at predicting IC90 values for arbitrary mutants. The SOFM was aimed at identifying those structural features that are important for drug resistance and discovering a classifier based on such features. We have used validation and cross validation to test the generalization abilities of the learning paradigm we have designed. The straightforward supervised learning was able to learn very successfully but validation results are less than satisfactory. This is due to the insufficient number of patterns in the training set which in turn is due to the scarcity of the available data. The data mining using SOFM was very successful. We have managed to distinguish between resistant and non-resistant mutants using structural features. We have been able to divide all reported HIV mutants into several categories based on their 3- dimensional molecular structures and the pattern of contacts between the mutant protease and Indinavir. Our classifier shows reasonably good prediction performance being able to predict the drug resistance of previously unseen mutants with an accuracy of between 60% and 70%. We believe that this performance can be greatly improved once more data becomes available. The results presented here support the hypothesis that structural features of the molecular structure can be used in antiviral drug treatment selection and drug design.

Data Mining for Financial Applications

NASA Astrophysics Data System (ADS)

Kovalerchuk, Boris; Vityaev, Evgenii

This chapter describes Data Mining in finance by discussing financial tasks, specifics of methodologies and techniques in this Data Mining area. It includes time dependence, data selection, forecast horizon, measures of success, quality of patterns, hypothesis evaluation, problem ID, method profile, attribute-based and relational methodologies. The second part of the chapter discusses Data Mining models and practice in finance. It covers use of neural networks in portfolio management, design of interpretable trading rules and discovering money laundering schemes using decision rules and relational Data Mining methodology.

Unravelling associations between unassigned mass spectrometry peaks with frequent itemset mining techniques.

PubMed

Vu, Trung Nghia; Mrzic, Aida; Valkenborg, Dirk; Maes, Evelyne; Lemière, Filip; Goethals, Bart; Laukens, Kris

2014-01-01

Mass spectrometry-based proteomics experiments generate spectra that are rich in information. Often only a fraction of this information is used for peptide/protein identification, whereas a significant proportion of the peaks in a spectrum remain unexplained. In this paper we explore how a specific class of data mining techniques termed "frequent itemset mining" can be employed to discover patterns in the unassigned data, and how such patterns can help us interpret the origin of the unexpected/unexplained peaks. First a model is proposed that describes the origin of the observed peaks in a mass spectrum. For this purpose we use the classical correlative database search algorithm. Peaks that support a positive identification of the spectrum are termed explained peaks. Next, frequent itemset mining techniques are introduced to infer which unexplained peaks are associated in a spectrum. The method is validated on two types of experimental proteomic data. First, peptide mass fingerprint data is analyzed to explain the unassigned peaks in a full scan mass spectrum. Interestingly, a large numbers of experimental spectra reveals several highly frequent unexplained masses, and pattern mining on these frequent masses demonstrates that subsets of these peaks frequently co-occur. Further evaluation shows that several of these co-occurring peaks indeed have a known common origin, and other patterns are promising hypothesis generators for further analysis. Second, the proposed methodology is validated on tandem mass spectrometral data using a public spectral library, where associations within the mass differences of unassigned peaks and peptide modifications are explored. The investigation of the found patterns illustrates that meaningful patterns can be discovered that can be explained by features of the employed technology and found modifications. This simple approach offers opportunities to monitor accumulating unexplained mass spectrometry data for emerging new patterns, with possible applications for the development of mass exclusion lists, for the refinement of quality control strategies and for a further interpretation of unexplained spectral peaks in mass spectrometry and tandem mass spectrometry.

76 FR 5719 - Pattern of Violations

Federal Register 2010, 2011, 2012, 2013, 2014

2011-02-02

... safety and health record of each mine rather than on a strictly quantitative comparison of mines to... several reservations, given the methodological difficulties involved in estimating the compensating wage...

Occupational exposure to diesel engine exhaust: A literature review

PubMed Central

Pronk, Anjoeka; Coble, Joseph; Stewart, Patricia

2010-01-01

Background Diesel exhaust (DE) is classified as a probable human carcinogen. Aims were to describe the major occupational uses of diesel engines and give an overview of personal DE exposure levels and determinants of exposure as reported in the published literature. Methods Measurements representative of personal DE exposure were abstracted from the literature for the following agents: elemental carbon (EC), particulate matter (PM), carbon monoxide (CO), nitrogen oxide (NO), and nitrogen dioxide (NO2). Information on determinants of exposure was abstracted. Results In total, 3528 EC, 4166 PM, 581 CO, 322 NO, and 1404 NO2 measurements were abstracted. From the 10,001 measurements, 32% represented exposure from on-road vehicles, and 68% from off-road vehicles (30% mining, 15% railroad, and 22% other). Highest levels were reported for enclosed underground work sites where heavy equipment is used: mining, mine maintenance, and construction, (EC: 27-658 μg/m3). Intermediate exposure levels were generally reported for above ground (semi-)enclosed areas where smaller equipment was run: mechanics in a shop, emergency workers in fire stations, distribution workers at a dock, and workers loading/unloading inside a ferry (generally: EC< 50 μg/m3). Lowest levels were reported for enclosed areas separated from the source such as drivers and train crew, or outside such as surface mining, parking attendants, vehicle testers, utility service workers, surface construction and airline ground personnel (EC<25 μg/m3). The other agents showed a similar pattern. Determinants of exposure reported for enclosed situations were ventilation and exhaust after treatment devices. Conclusions Reported DE exposure levels were highest for underground mining and construction, intermediate for working in above ground (semi-)enclosed areas and lowest for working outside or separated from the source. The presented data can be used as a basis for assessing occupational exposure in population-based epidemiological studies and guide future exposure assessment efforts for industrial hygiene and epidemiological studies. PMID:19277070

Occupational exposure to diesel engine exhaust: a literature review.

PubMed

Pronk, Anjoeka; Coble, Joseph; Stewart, Patricia A

2009-07-01

Diesel exhaust (DE) is classified as a probable human carcinogen. Aims were to describe the major occupational uses of diesel engines and give an overview of personal DE exposure levels and determinants of exposure as reported in the published literature. Measurements representative of personal DE exposure were abstracted from the literature for the following agents: elemental carbon (EC), particulate matter (PM), carbon monoxide (CO), nitrogen oxide (NO), and nitrogen dioxide (NO(2)). Information on determinants of exposure was abstracted. In total, 3528 EC, 4166 PM, 581 CO, 322 NO, and 1404 NO(2) measurements were abstracted. From the 10,001 measurements, 32% represented exposure from on-road vehicles and 68% from off-road vehicles (30% mining, 15% railroad, and 22% others). Highest levels were reported for enclosed underground work sites in which heavy equipment is used: mining, mine maintenance, and construction (EC: 27-658 microg/m(3)). Intermediate exposure levels were generally reported for above-ground (semi-) enclosed areas in which smaller equipment was run: mechanics in a shop, emergency workers in fire stations, distribution workers at a dock, and workers loading/unloading inside a ferry (generally: EC<50 microg/m(3)). Lowest levels were reported for enclosed areas separated from the source, such as drivers and train crew, or outside, such as surface mining, parking attendants, vehicle testers, utility service workers, surface construction and airline ground personnel (EC<25 microg/m(3)). The other agents showed a similar pattern. Determinants of exposure reported for enclosed situations were ventilation and exhaust after treatment devices. Reported DE exposure levels were highest for underground mining and construction, intermediate for working in above-ground (semi-) enclosed areas and lowest for working outside or separated from the source. The presented data can be used as a basis for assessing occupational exposure in population-based epidemiological studies and guide future exposure assessment efforts for industrial hygiene and epidemiological studies.

Pattern Recognition Using Artificial Neural Network: A Review

NASA Astrophysics Data System (ADS)

Kim, Tai-Hoon

Among the various frameworks in which pattern recognition has been traditionally formulated, the statistical approach has been most intensively studied and used in practice. More recently, artificial neural network techniques theory have been receiving increasing attention. The design of a recognition system requires careful attention to the following issues: definition of pattern classes, sensing environment, pattern representation, feature extraction and selection, cluster analysis, classifier design and learning, selection of training and test samples, and performance evaluation. In spite of almost 50 years of research and development in this field, the general problem of recognizing complex patterns with arbitrary orientation, location, and scale remains unsolved. New and emerging applications, such as data mining, web searching, retrieval of multimedia data, face recognition, and cursive handwriting recognition, require robust and efficient pattern recognition techniques. The objective of this review paper is to summarize and compare some of the well-known methods used in various stages of a pattern recognition system using ANN and identify research topics and applications which are at the forefront of this exciting and challenging field.

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

43 CFR 3830.11 - Which minerals are locatable under the General Mining Law?

Code of Federal Regulations, 2013 CFR

2013-10-01

... 43 Public Lands: Interior 2 2013-10-01 2013-10-01 false Which minerals are locatable under the... (Continued) BUREAU OF LAND MANAGEMENT, DEPARTMENT OF THE INTERIOR MINERALS MANAGEMENT (3000) LOCATING, RECORDING, AND MAINTAINING MINING CLAIMS OR SITES; GENERAL PROVISIONS Mining Law Minerals § 3830.11 Which...

43 CFR 3830.11 - Which minerals are locatable under the General Mining Law?

Code of Federal Regulations, 2011 CFR

2011-10-01

... 43 Public Lands: Interior 2 2011-10-01 2011-10-01 false Which minerals are locatable under the... (Continued) BUREAU OF LAND MANAGEMENT, DEPARTMENT OF THE INTERIOR MINERALS MANAGEMENT (3000) LOCATING, RECORDING, AND MAINTAINING MINING CLAIMS OR SITES; GENERAL PROVISIONS Mining Law Minerals § 3830.11 Which...

43 CFR 3830.11 - Which minerals are locatable under the General Mining Law?

Code of Federal Regulations, 2014 CFR

2014-10-01

... 43 Public Lands: Interior 2 2014-10-01 2014-10-01 false Which minerals are locatable under the... (Continued) BUREAU OF LAND MANAGEMENT, DEPARTMENT OF THE INTERIOR MINERALS MANAGEMENT (3000) LOCATING, RECORDING, AND MAINTAINING MINING CLAIMS OR SITES; GENERAL PROVISIONS Mining Law Minerals § 3830.11 Which...

Geographic applications of ERTS-1 imagery to landscape change. [Mississippi River and Great Smoky Mountains of Tennessee and North Carolina

NASA Technical Reports Server (NTRS)

Rehder, J. B. (Principal Investigator)

1973-01-01

The author has identified the following significant results. ERTS-1 has proven to be an effective earth-orbiting monitor of landscape change. Its regional coverage for large areal monitoring has been effective for the detection and mapping of agricultural plowing regions, for general forest cover mapping, for flood mapping, for strip mine mapping, and for short-lived precipitation mapping patterns. Paramount to the entire study has been the temporal coverage provided by ERTS. Without the cyclic coverage on an 18 day basis, temporal coverage would have been inadequate for the detection and mapping of strip mining landscape change, the analysis of agricultural landscape change based on plowing patterns, the analysis of urban-suburban growth changes, and the mapping of the Mississippi River floods. Cost benefits from ERTS are unquestionably superior to aircraft systems in regard to large regional coverage and cyclic temporal parameters. For the analysis of landscape change in large regions such as statewide areas or even areas of 10,000 square miles, ERTS is of cost benefit consideration. Not only does the cost of imagery favor ERTS but the reduction of man-hours using ERTS has been in the magnitude of 1:10.

Assessing Lightning and Wildfire Hazard by Land Properties and Cloud to Ground Lightning Data with Association Rule Mining in Alberta, Canada.

PubMed

Cha, DongHwan; Wang, Xin; Kim, Jeong Woo

2017-10-23

Hotspot analysis was implemented to find regions in the province of Alberta (Canada) with high frequency Cloud to Ground (CG) lightning strikes clustered together. Generally, hotspot regions are located in the central, central east, and south central regions of the study region. About 94% of annual lightning occurred during warm months (June to August) and the daily lightning frequency was influenced by the diurnal heating cycle. The association rule mining technique was used to investigate frequent CG lightning patterns, which were verified by similarity measurement to check the patterns' consistency. The similarity coefficient values indicated that there were high correlations throughout the entire study period. Most wildfires (about 93%) in Alberta occurred in forests, wetland forests, and wetland shrub areas. It was also found that lightning and wildfires occur in two distinct areas: frequent wildfire regions with a high frequency of lightning, and frequent wild-fire regions with a low frequency of lightning. Further, the preference index (PI) revealed locations where the wildfires occurred more frequently than in other class regions. The wildfire hazard area was estimated with the CG lightning hazard map and specific land use types.

Mercury concentrations in fish from a Sierra Nevada foothill reservoir located downstream from historic gold-mining operations

USGS Publications Warehouse

Saiki, Michael K.; Martin, Barbara A.; May, Thomas W.; Alpers, Charles N.

2010-01-01

This study examined mercury concentrations in whole fish from Camp Far West Reservoir, an 830-ha reservoir in northern California, USA, located downstream from lands mined for gold during and following the Gold Rush of 1848–1864. Total mercury (reported as dry weight concentrations) was highest in spotted bass (mean, 0.93 μg/g; range, 0.16–4.41 μg/g) and lower in bluegill (mean, 0.45 μg/g; range, 0.22–1.96 μg/g) and threadfin shad (0.44 μg/g; range, 0.21–1.34 μg/g). Spatial patterns for mercury in fish indicated high concentrations upstream in the Bear River arm and generally lower concentrations elsewhere, including downstream near the dam. These findings coincided with patterns exhibited by methylmercury in water and sediment, and suggested that mercury-laden inflows from the Bear River were largely responsible for contaminating the reservoir ecosystem. Maximum concentrations of mercury in all three fish species, but especially bass, were high enough to warrant concern about toxic effects in fish and consumers of fish.

Spatial and temporal relationships among watershed mining, water quality, and freshwater mussel status in an eastern USA river.

PubMed

Zipper, Carl E; Donovan, Patricia F; Jones, Jess W; Li, Jing; Price, Jennifer E; Stewart, Roger E

2016-01-15

The Powell River of southwestern Virginia and northeastern Tennessee, USA, drains a watershed with extensive coal surface mining, and it hosts exceptional biological richness, including at-risk species of freshwater mussels, downstream of mining-disturbed watershed areas. We investigated spatial and temporal patterns of watershed mining disturbance; their relationship to water quality change in the section of the river that connects mining areas to mussel habitat; and relationships of mining-related water constituents to measures of recent and past mussel status. Freshwater mussels in the Powell River have experienced significant declines over the past 3.5 decades. Over that same period, surface coal mining has influenced the watershed. Water-monitoring data collected by state and federal agencies demonstrate that dissolved solids and associated constituents that are commonly influenced by Appalachian mining (specific conductance, pH, hardness and sulfates) have experienced increasing temporal trends from the 1960s through ~2008; but, of those constituents, only dissolved solids concentrations are available widely within the Powell River since ~2008. Dissolved solids concentrations have stabilized in recent years. Dissolved solids, specific conductance, pH, and sulfates also exhibited spatial patterns that are consistent with dilution of mining influence with increasing distance from mined areas. Freshwater mussel status indicators are correlated negatively with dissolved solids concentrations, spatially and temporally, but the direct causal mechanisms responsible for mussel declines remain unknown. Copyright © 2015 Elsevier B.V. All rights reserved.

76 FR 51274 - Supplemental Nutrition Assistance Program: Major System Failures

Federal Register 2010, 2011, 2012, 2013, 2014

2011-08-18

... data mining as necessary to determine if losses are occurring in the process of issuing benefits. It is... further by using data mining techniques on States' data or analyzing QC data for error patterns that may... conjunction with an additional sample of cases. Data mining techniques may be employed when QC data cannot...

Exploring the Integration of Data Mining and Data Visualization

ERIC Educational Resources Information Center

Zhang, Yi

2011-01-01

Due to the rapid advances in computing and sensing technologies, enormous amounts of data are being generated everyday in various applications. The integration of data mining and data visualization has been widely used to analyze these massive and complex data sets to discover hidden patterns. For both data mining and visualization to be…

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.

Data Mining in Cyber Operations

DTIC Science & Technology

2014-07-01

information processing units intended to mimic the network of neurons in the human brain for performing pattern recognition  Self- organizing maps (SOM...patterns are mined from in order to influence the learning model . An exploratory attack does not alter the training process , but rather uses other...New Jersey: Prentice Hall. 21) Kohonen, T. (1982). Self- organized formation of topologically correct feature maps. Biological Cybernetics , 43, 59–69

A novel approach for acid mine drainage pollution biomonitoring using rare earth elements bioaccumulated in the freshwater clam Corbicula fluminea.

PubMed

Bonnail, Estefanía; Pérez-López, Rafael; Sarmiento, Aguasanta M; Nieto, José Miguel; DelValls, T Ángel

2017-09-15

Lanthanide series have been used as a record of the water-rock interaction and work as a tool for identifying impacts of acid mine drainage (lixiviate residue derived from sulphide oxidation). The application of North-American Shale Composite-normalized rare earth elements patterns to these minority elements allows determining the origin of the contamination. In the current study, geochemical patterns were applied to rare earth elements bioaccumulated in the soft tissue of the freshwater clam Corbicula fluminea after exposure to different acid mine drainage contaminated environments. Results show significant bioaccumulation of rare earth elements in soft tissue of the clam after 14 days of exposure to acid mine drainage contaminated sediment (ΣREE=1.3-8μg/gdw). Furthermore, it was possible to biomonitor different degrees of contamination based on rare earth elements in tissue. The pattern of this type of contamination describes a particular curve characterized by an enrichment in the middle rare earth elements; a homologous pattern (E MREE =0.90) has also been observed when applied NASC normalization in clam tissues. Results of lanthanides found in clams were contrasted with the paucity of toxicity studies, determining risk caused by light rare earth elements in the Odiel River close to the Estuary. The current study purposes the use of clam as an innovative "bio-tool" for the biogeochemical monitoring of pollution inputs that determines the acid mine drainage networks affection. Copyright © 2017 Elsevier B.V. All rights reserved.

El Paso Natural Gas Mines Fact Sheets

EPA Pesticide Factsheets

These fact sheets contain information about El Paso Natural Gas Mines and the Western Abandoned Uranium Mine Region, 19 abandoned uranium mine claims generally located along the Little Colorado River or Highway 89 near Cameron, AZ.

An efficient, versatile and scalable pattern growth approach to mine frequent patterns in unaligned protein sequences.

PubMed

Ye, Kai; Kosters, Walter A; Ijzerman, Adriaan P

2007-03-15

Pattern discovery in protein sequences is often based on multiple sequence alignments (MSA). The procedure can be computationally intensive and often requires manual adjustment, which may be particularly difficult for a set of deviating sequences. In contrast, two algorithms, PRATT2 (http//www.ebi.ac.uk/pratt/) and TEIRESIAS (http://cbcsrv.watson.ibm.com/) are used to directly identify frequent patterns from unaligned biological sequences without an attempt to align them. Here we propose a new algorithm with more efficiency and more functionality than both PRATT2 and TEIRESIAS, and discuss some of its applications to G protein-coupled receptors, a protein family of important drug targets. In this study, we designed and implemented six algorithms to mine three different pattern types from either one or two datasets using a pattern growth approach. We compared our approach to PRATT2 and TEIRESIAS in efficiency, completeness and the diversity of pattern types. Compared to PRATT2, our approach is faster, capable of processing large datasets and able to identify the so-called type III patterns. Our approach is comparable to TEIRESIAS in the discovery of the so-called type I patterns but has additional functionality such as mining the so-called type II and type III patterns and finding discriminating patterns between two datasets. The source code for pattern growth algorithms and their pseudo-code are available at http://www.liacs.nl/home/kosters/pg/.

Mercury methylation in mine wastes collected from abandoned mercury mines in the USA

USGS Publications Warehouse

Gray, J.E.; Hines, M.E.; Biester, H.; Lasorsa, B.K.; ,

2003-01-01

Speciation and transformation of Hg was studied in mine wastes collected from abandoned Hg mines at McDermitt, Nevada, and Terlingua, Texas, to evaluate formation of methyl-Hg, which is highly toxic. In these mine wastes, we measured total Hg and methyl-Hg contents, identified various Hg compounds using a pyrolysis technique, and determined rates of Hg methylation and methyl-Hg demethylation using isotopic-tracer methods. Mine wastes contain total Hg contents as high as 14000 ??g/g and methyl-Hg concentrations as high as 88 ng/g. Mine wastes were found to contain variable amounts of cinnabar, metacinnabar, Hg salts, Hg0, and Hg0 and Hg2+ sorbed onto matrix particulates. Samples with Hg0 and matrix-sorbed Hg generally contained significant methyl-Hg contents. Similarly, samples containing Hg0 compounds generally produced significant Hg methylation rates, as much as 26%/day. Samples containing mostly cinnabar showed little or no Hg methylation. Mine wastes with high methyl-Hg contents generally showed low methyl-Hg demethylation, suggesting that Hg methylation was dominant. Methyl-Hg demethylation was by both oxidative and microbial pathways. The correspondence of mine wastes containing Hg0 compounds and measured Hg methylation suggests that Hg0 oxidizes to Hg2+, which is subsequently bioavailable for microbial Hg methylation.

15 CFR 970.100 - Purpose.

Code of Federal Regulations, 2012 CFR

2012-01-01

... AND ATMOSPHERIC ADMINISTRATION, DEPARTMENT OF COMMERCE GENERAL REGULATIONS OF THE ENVIRONMENTAL DATA SERVICE DEEP SEABED MINING REGULATIONS FOR EXPLORATION LICENSES General § 970.100 Purpose. (a) General... recognition that the deep seabed mining industry is still evolving and that more information must be developed...

15 CFR 970.100 - Purpose.

Code of Federal Regulations, 2013 CFR

2013-01-01

... AND ATMOSPHERIC ADMINISTRATION, DEPARTMENT OF COMMERCE GENERAL REGULATIONS OF THE ENVIRONMENTAL DATA SERVICE DEEP SEABED MINING REGULATIONS FOR EXPLORATION LICENSES General § 970.100 Purpose. (a) General... recognition that the deep seabed mining industry is still evolving and that more information must be developed...

15 CFR 970.100 - Purpose.

Code of Federal Regulations, 2014 CFR

2014-01-01

... AND ATMOSPHERIC ADMINISTRATION, DEPARTMENT OF COMMERCE GENERAL REGULATIONS OF THE ENVIRONMENTAL DATA SERVICE DEEP SEABED MINING REGULATIONS FOR EXPLORATION LICENSES General § 970.100 Purpose. (a) General... recognition that the deep seabed mining industry is still evolving and that more information must be developed...

15 CFR 970.100 - Purpose.

Code of Federal Regulations, 2010 CFR

2010-01-01

... AND ATMOSPHERIC ADMINISTRATION, DEPARTMENT OF COMMERCE GENERAL REGULATIONS OF THE ENVIRONMENTAL DATA SERVICE DEEP SEABED MINING REGULATIONS FOR EXPLORATION LICENSES General § 970.100 Purpose. (a) General... recognition that the deep seabed mining industry is still evolving and that more information must be developed...

15 CFR 970.100 - Purpose.

Code of Federal Regulations, 2011 CFR

2011-01-01

... AND ATMOSPHERIC ADMINISTRATION, DEPARTMENT OF COMMERCE GENERAL REGULATIONS OF THE ENVIRONMENTAL DATA SERVICE DEEP SEABED MINING REGULATIONS FOR EXPLORATION LICENSES General § 970.100 Purpose. (a) General... recognition that the deep seabed mining industry is still evolving and that more information must be developed...

30 CFR 57.13001 - General requirements for boilers and pressure vessels.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 30 Mineral Resources 1 2014-07-01 2014-07-01 false General requirements for boilers and pressure vessels. 57.13001 Section 57.13001 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR METAL AND NONMETAL MINE SAFETY AND HEALTH SAFETY AND HEALTH STANDARDS-UNDERGROUND METAL AND NONMETAL MINES Compressed Air and Boilers §...

30 CFR 56.13001 - General requirements for boilers and pressure vessels.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false General requirements for boilers and pressure vessels. 56.13001 Section 56.13001 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR METAL AND NONMETAL MINE SAFETY AND HEALTH SAFETY AND HEALTH STANDARDS-SURFACE METAL AND NONMETAL MINES Compressed Air and Boilers §...

30 CFR 57.13001 - General requirements for boilers and pressure vessels.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 30 Mineral Resources 1 2012-07-01 2012-07-01 false General requirements for boilers and pressure vessels. 57.13001 Section 57.13001 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR METAL AND NONMETAL MINE SAFETY AND HEALTH SAFETY AND HEALTH STANDARDS-UNDERGROUND METAL AND NONMETAL MINES Compressed Air and Boilers §...

30 CFR 57.13001 - General requirements for boilers and pressure vessels.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false General requirements for boilers and pressure vessels. 57.13001 Section 57.13001 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR METAL AND NONMETAL MINE SAFETY AND HEALTH SAFETY AND HEALTH STANDARDS-UNDERGROUND METAL AND NONMETAL MINES Compressed Air and Boilers §...

30 CFR 56.13001 - General requirements for boilers and pressure vessels.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 30 Mineral Resources 1 2014-07-01 2014-07-01 false General requirements for boilers and pressure vessels. 56.13001 Section 56.13001 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR METAL AND NONMETAL MINE SAFETY AND HEALTH SAFETY AND HEALTH STANDARDS-SURFACE METAL AND NONMETAL MINES Compressed Air and Boilers §...

30 CFR 56.13001 - General requirements for boilers and pressure vessels.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 30 Mineral Resources 1 2012-07-01 2012-07-01 false General requirements for boilers and pressure vessels. 56.13001 Section 56.13001 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR METAL AND NONMETAL MINE SAFETY AND HEALTH SAFETY AND HEALTH STANDARDS-SURFACE METAL AND NONMETAL MINES Compressed Air and Boilers §...

30 CFR 57.13001 - General requirements for boilers and pressure vessels.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 30 Mineral Resources 1 2013-07-01 2013-07-01 false General requirements for boilers and pressure vessels. 57.13001 Section 57.13001 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR METAL AND NONMETAL MINE SAFETY AND HEALTH SAFETY AND HEALTH STANDARDS-UNDERGROUND METAL AND NONMETAL MINES Compressed Air and Boilers §...

30 CFR 56.13001 - General requirements for boilers and pressure vessels.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 1 2011-07-01 2011-07-01 false General requirements for boilers and pressure vessels. 56.13001 Section 56.13001 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR METAL AND NONMETAL MINE SAFETY AND HEALTH SAFETY AND HEALTH STANDARDS-SURFACE METAL AND NONMETAL MINES Compressed Air and Boilers §...

30 CFR 57.13001 - General requirements for boilers and pressure vessels.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 1 2011-07-01 2011-07-01 false General requirements for boilers and pressure vessels. 57.13001 Section 57.13001 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR METAL AND NONMETAL MINE SAFETY AND HEALTH SAFETY AND HEALTH STANDARDS-UNDERGROUND METAL AND NONMETAL MINES Compressed Air and Boilers §...

30 CFR 56.13001 - General requirements for boilers and pressure vessels.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 30 Mineral Resources 1 2013-07-01 2013-07-01 false General requirements for boilers and pressure vessels. 56.13001 Section 56.13001 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR METAL AND NONMETAL MINE SAFETY AND HEALTH SAFETY AND HEALTH STANDARDS-SURFACE METAL AND NONMETAL MINES Compressed Air and Boilers §...

Mining moving object trajectories in location-based services for spatio-temporal database update

NASA Astrophysics Data System (ADS)

Guo, Danhuai; Cui, Weihong

2008-10-01

Advances in wireless transmission and mobile technology applied to LBS (Location-based Services) flood us with amounts of moving objects data. Vast amounts of gathered data from position sensors of mobile phones, PDAs, or vehicles hide interesting and valuable knowledge and describe the behavior of moving objects. The correlation between temporal moving patterns of moving objects and geo-feature spatio-temporal attribute was ignored, and the value of spatio-temporal trajectory data was not fully exploited too. Urban expanding or frequent town plan change bring about a large amount of outdated or imprecise data in spatial database of LBS, and they cannot be updated timely and efficiently by manual processing. In this paper we introduce a data mining approach to movement pattern extraction of moving objects, build a model to describe the relationship between movement patterns of LBS mobile objects and their environment, and put up with a spatio-temporal database update strategy in LBS database based on trajectories spatiotemporal mining. Experimental evaluation reveals excellent performance of the proposed model and strategy. Our original contribution include formulation of model of interaction between trajectory and its environment, design of spatio-temporal database update strategy based on moving objects data mining, and the experimental application of spatio-temporal database update by mining moving objects trajectories.

36 CFR 1005.14 - Prospecting, mining, and mineral leasing.

Code of Federal Regulations, 2014 CFR

2014-07-01

... mineral leasing. 1005.14 Section 1005.14 Parks, Forests, and Public Property PRESIDIO TRUST COMMERCIAL AND PRIVATE OPERATIONS § 1005.14 Prospecting, mining, and mineral leasing. Prospecting, mining, and the location of mining claims under the general mining laws and leasing under the mineral leasing laws are...

36 CFR 1005.14 - Prospecting, mining, and mineral leasing.

Code of Federal Regulations, 2011 CFR

2011-07-01

... mineral leasing. 1005.14 Section 1005.14 Parks, Forests, and Public Property PRESIDIO TRUST COMMERCIAL AND PRIVATE OPERATIONS § 1005.14 Prospecting, mining, and mineral leasing. Prospecting, mining, and the location of mining claims under the general mining laws and leasing under the mineral leasing laws are...

36 CFR 1005.14 - Prospecting, mining, and mineral leasing.

Code of Federal Regulations, 2012 CFR

2012-07-01

... mineral leasing. 1005.14 Section 1005.14 Parks, Forests, and Public Property PRESIDIO TRUST COMMERCIAL AND PRIVATE OPERATIONS § 1005.14 Prospecting, mining, and mineral leasing. Prospecting, mining, and the location of mining claims under the general mining laws and leasing under the mineral leasing laws are...

43 CFR 3601.40 - Mining and reclamation plans.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 43 Public Lands: Interior 2 2011-10-01 2011-10-01 false Mining and reclamation plans. 3601.40... Materials Disposal; General Provisions Mining and Reclamation Plans § 3601.40 Mining and reclamation plans. BLM may require you to submit mining and reclamation plans before we begin any environmental review or...

Efficient Mining and Detection of Sequential Intrusion Patterns for Network Intrusion Detection Systems

NASA Astrophysics Data System (ADS)

Shyu, Mei-Ling; Huang, Zifang; Luo, Hongli

In recent years, pervasive computing infrastructures have greatly improved the interaction between human and system. As we put more reliance on these computing infrastructures, we also face threats of network intrusion and/or any new forms of undesirable IT-based activities. Hence, network security has become an extremely important issue, which is closely connected with homeland security, business transactions, and people's daily life. Accurate and efficient intrusion detection technologies are required to safeguard the network systems and the critical information transmitted in the network systems. In this chapter, a novel network intrusion detection framework for mining and detecting sequential intrusion patterns is proposed. The proposed framework consists of a Collateral Representative Subspace Projection Modeling (C-RSPM) component for supervised classification, and an inter-transactional association rule mining method based on Layer Divided Modeling (LDM) for temporal pattern analysis. Experiments on the KDD99 data set and the traffic data set generated by a private LAN testbed show promising results with high detection rates, low processing time, and low false alarm rates in mining and detecting sequential intrusion detections.

A gossip based information fusion protocol for distributed frequent itemset mining

NASA Astrophysics Data System (ADS)

Sohrabi, Mohammad Karim

2018-07-01

The computational complexity, huge memory space requirement, and time-consuming nature of frequent pattern mining process are the most important motivations for distribution and parallelization of this mining process. On the other hand, the emergence of distributed computational and operational environments, which causes the production and maintenance of data on different distributed data sources, makes the parallelization and distribution of the knowledge discovery process inevitable. In this paper, a gossip based distributed itemset mining (GDIM) algorithm is proposed to extract frequent itemsets, which are special types of frequent patterns, in a wireless sensor network environment. In this algorithm, local frequent itemsets of each sensor are extracted using a bit-wise horizontal approach (LHPM) from the nodes which are clustered using a leach-based protocol. Heads of clusters exploit a gossip based protocol in order to communicate each other to find the patterns which their global support is equal to or more than the specified support threshold. Experimental results show that the proposed algorithm outperforms the best existing gossip based algorithm in term of execution time.

Data mining: sophisticated forms of managed care modeling through artificial intelligence.

PubMed

Borok, L S

1997-01-01

Data mining is a recent development in computer science that combines artificial intelligence algorithms and relational databases to discover patterns automatically, without the use of traditional statistical methods. Work with data mining tools in health care is in a developmental stage that holds great promise, given the combination of demographic and diagnostic information.

Using Text Mining to Uncover Students' Technology-Related Problems in Live Video Streaming

ERIC Educational Resources Information Center

Abdous, M'hammed; He, Wu

2011-01-01

Because of their capacity to sift through large amounts of data, text mining and data mining are enabling higher education institutions to reveal valuable patterns in students' learning behaviours without having to resort to traditional survey methods. In an effort to uncover live video streaming (LVS) students' technology related-problems and to…

An improved Pearson's correlation proximity-based hierarchical clustering for mining biological association between genes.

PubMed

Booma, P M; Prabhakaran, S; Dhanalakshmi, R

2014-01-01

Microarray gene expression datasets has concerned great awareness among molecular biologist, statisticians, and computer scientists. Data mining that extracts the hidden and usual information from datasets fails to identify the most significant biological associations between genes. A search made with heuristic for standard biological process measures only the gene expression level, threshold, and response time. Heuristic search identifies and mines the best biological solution, but the association process was not efficiently addressed. To monitor higher rate of expression levels between genes, a hierarchical clustering model was proposed, where the biological association between genes is measured simultaneously using proximity measure of improved Pearson's correlation (PCPHC). Additionally, the Seed Augment algorithm adopts average linkage methods on rows and columns in order to expand a seed PCPHC model into a maximal global PCPHC (GL-PCPHC) model and to identify association between the clusters. Moreover, a GL-PCPHC applies pattern growing method to mine the PCPHC patterns. Compared to existing gene expression analysis, the PCPHC model achieves better performance. Experimental evaluations are conducted for GL-PCPHC model with standard benchmark gene expression datasets extracted from UCI repository and GenBank database in terms of execution time, size of pattern, significance level, biological association efficiency, and pattern quality.

An Improved Pearson's Correlation Proximity-Based Hierarchical Clustering for Mining Biological Association between Genes

PubMed Central

Booma, P. M.; Prabhakaran, S.; Dhanalakshmi, R.

2014-01-01

Microarray gene expression datasets has concerned great awareness among molecular biologist, statisticians, and computer scientists. Data mining that extracts the hidden and usual information from datasets fails to identify the most significant biological associations between genes. A search made with heuristic for standard biological process measures only the gene expression level, threshold, and response time. Heuristic search identifies and mines the best biological solution, but the association process was not efficiently addressed. To monitor higher rate of expression levels between genes, a hierarchical clustering model was proposed, where the biological association between genes is measured simultaneously using proximity measure of improved Pearson's correlation (PCPHC). Additionally, the Seed Augment algorithm adopts average linkage methods on rows and columns in order to expand a seed PCPHC model into a maximal global PCPHC (GL-PCPHC) model and to identify association between the clusters. Moreover, a GL-PCPHC applies pattern growing method to mine the PCPHC patterns. Compared to existing gene expression analysis, the PCPHC model achieves better performance. Experimental evaluations are conducted for GL-PCPHC model with standard benchmark gene expression datasets extracted from UCI repository and GenBank database in terms of execution time, size of pattern, significance level, biological association efficiency, and pattern quality. PMID:25136661

Spatio-Temporal Pattern Mining on Trajectory Data Using Arm

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

Measures to restore metallurgical mine wasteland using ecological restoration technologies: A case study at Longnan Rare Earth Mine

NASA Astrophysics Data System (ADS)

Rao, Yunzhang; Gu, Ruizhi; Guo, Ruikai; Zhang, Xueyan

2017-01-01

Whereas mining activities produce the raw materials that are crucial to economic growth, such activities leave extensive scarring on the land, contributing to the waste of valuable land resources and upsetting the ecological environment. The aim of this study is therefore to investigate various ecological technologies to restore metallurgical mine wastelands. These technologies include measures such as soil amelioration, vegetation restoration, different vegetation planting patterns, and engineering technologies. The Longnan Rare Earth Mine in the Jiangxi Province of China is used as the case study. The ecological restoration process provides a favourable reference for the restoration of a metallurgical mine wasteland.

30 CFR 22.6 - General requirements.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false General requirements. 22.6 Section 22.6 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR TESTING, EVALUATION, AND APPROVAL OF MINING PRODUCTS PORTABLE METHANE DETECTORS § 22.6 General requirements. Methane detectors approved under...

30 CFR 22.6 - General requirements.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 30 Mineral Resources 1 2014-07-01 2014-07-01 false General requirements. 22.6 Section 22.6 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR TESTING, EVALUATION, AND APPROVAL OF MINING PRODUCTS PORTABLE METHANE DETECTORS § 22.6 General requirements. Methane detectors approved under...

30 CFR 22.6 - General requirements.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 30 Mineral Resources 1 2012-07-01 2012-07-01 false General requirements. 22.6 Section 22.6 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR TESTING, EVALUATION, AND APPROVAL OF MINING PRODUCTS PORTABLE METHANE DETECTORS § 22.6 General requirements. Methane detectors approved under...

30 CFR 22.6 - General requirements.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 30 Mineral Resources 1 2013-07-01 2013-07-01 false General requirements. 22.6 Section 22.6 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR TESTING, EVALUATION, AND APPROVAL OF MINING PRODUCTS PORTABLE METHANE DETECTORS § 22.6 General requirements. Methane detectors approved under...

30 CFR 22.6 - General requirements.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 1 2011-07-01 2011-07-01 false General requirements. 22.6 Section 22.6 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR TESTING, EVALUATION, AND APPROVAL OF MINING PRODUCTS PORTABLE METHANE DETECTORS § 22.6 General requirements. Methane detectors approved under...

36 CFR § 1005.14 - Prospecting, mining, and mineral leasing.

Code of Federal Regulations, 2013 CFR

2013-07-01

... mineral leasing. § 1005.14 Section § 1005.14 Parks, Forests, and Public Property PRESIDIO TRUST COMMERCIAL AND PRIVATE OPERATIONS § 1005.14 Prospecting, mining, and mineral leasing. Prospecting, mining, and the location of mining claims under the general mining laws and leasing under the mineral leasing...

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

30 CFR 206.261 - Transportation allowances-general.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 2 2010-07-01 2010-07-01 false Transportation allowances-general. 206.261... MANAGEMENT PRODUCT VALUATION Federal Coal § 206.261 Transportation allowances—general. (a) For ad valorem... mine and, if applicable, from the wash plant to a remote sales point. In-mine transportation costs...

30 CFR 1206.261 - Transportation allowances-general.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 30 Mineral Resources 3 2012-07-01 2012-07-01 false Transportation allowances-general. 1206.261... RESOURCES REVENUE PRODUCT VALUATION Federal Coal § 1206.261 Transportation allowances—general. (a) For ad... mine and, if applicable, from the wash plant to a remote sales point. In-mine transportation costs...

30 CFR 1206.460 - Transportation allowances-general.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 30 Mineral Resources 3 2013-07-01 2013-07-01 false Transportation allowances-general. 1206.460... RESOURCES REVENUE PRODUCT VALUATION Indian Coal § 1206.460 Transportation allowances—general. (a) For ad... mine and, if applicable, from the wash plant to a remote sales point. In-mine transportation costs...

30 CFR 1206.460 - Transportation allowances-general.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 30 Mineral Resources 3 2012-07-01 2012-07-01 false Transportation allowances-general. 1206.460... RESOURCES REVENUE PRODUCT VALUATION Indian Coal § 1206.460 Transportation allowances—general. (a) For ad... mine and, if applicable, from the wash plant to a remote sales point. In-mine transportation costs...

30 CFR 1206.460 - Transportation allowances-general.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 30 Mineral Resources 3 2014-07-01 2014-07-01 false Transportation allowances-general. 1206.460... RESOURCES REVENUE PRODUCT VALUATION Indian Coal § 1206.460 Transportation allowances—general. (a) For ad... mine and, if applicable, from the wash plant to a remote sales point. In-mine transportation costs...

30 CFR 1206.261 - Transportation allowances-general.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 30 Mineral Resources 3 2013-07-01 2013-07-01 false Transportation allowances-general. 1206.261... RESOURCES REVENUE PRODUCT VALUATION Federal Coal § 1206.261 Transportation allowances—general. (a) For ad... mine and, if applicable, from the wash plant to a remote sales point. In-mine transportation costs...

30 CFR 1206.261 - Transportation allowances-general.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 30 Mineral Resources 3 2014-07-01 2014-07-01 false Transportation allowances-general. 1206.261... RESOURCES REVENUE PRODUCT VALUATION Federal Coal § 1206.261 Transportation allowances—general. (a) For ad... mine and, if applicable, from the wash plant to a remote sales point. In-mine transportation costs...

30 CFR 77.1007 - Drilling; general.

Code of Federal Regulations, 2010 CFR

2010-07-01

... Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE SAFETY AND HEALTH MANDATORY SAFETY STANDARDS, SURFACE COAL MINES AND SURFACE WORK AREAS OF UNDERGROUND COAL MINES Ground... each shift by a competent person. Equipment defects affecting safety shall be reported. (b) Equipment...

Study of the crater deformation of the CODELCO/Andina mine using the satellite and ground data

NASA Astrophysics Data System (ADS)

Caverlotti-Silva, M. A.; Arellano-Baeza, A. A.

2011-12-01

The correct monitoring of the subsidence of the craters related to the underground mine exploitation is one of the most important endeavors of the satellite remote sensing. The ASTER and LANDSAT satellite images have been used to study the deformation of the crater of the CODELCO/Andina mine, Valparaiso Region, Chile. The high-resolution satellite images were used to detect changes in the lineament patterns related to the subsidence. These results were compared with the ground deformation extracted from the GPS and topography station networks. It was found that sudden changes in the lineament patterns appear when the ground deformation overcomes a definite threshold.

Protein classification using sequential pattern mining.

PubMed

Exarchos, Themis P; Papaloukas, Costas; Lampros, Christos; Fotiadis, Dimitrios I

2006-01-01

Protein classification in terms of fold recognition can be employed to determine the structural and functional properties of a newly discovered protein. In this work sequential pattern mining (SPM) is utilized for sequence-based fold recognition. One of the most efficient SPM algorithms, cSPADE, is employed for protein primary structure analysis. Then a classifier uses the extracted sequential patterns for classifying proteins of unknown structure in the appropriate fold category. The proposed methodology exhibited an overall accuracy of 36% in a multi-class problem of 17 candidate categories. The classification performance reaches up to 65% when the three most probable protein folds are considered.

Differentiation of closely related isomers: application of data mining techniques in conjunction with variable wavelength infrared multiple photon dissociation mass spectrometry for identification of glucose-containing disaccharide ions.

PubMed

Stefan, Sarah E; Ehsan, Mohammad; Pearson, Wright L; Aksenov, Alexander; Boginski, Vladimir; Bendiak, Brad; Eyler, John R

2011-11-15

Data mining algorithms have been used to analyze the infrared multiple photon dissociation (IRMPD) patterns of gas-phase lithiated disaccharide isomers irradiated with either a line-tunable CO(2) laser or a free electron laser (FEL). The IR fragmentation patterns over the wavelength range of 9.2-10.6 μm have been shown in earlier work to correlate uniquely with the asymmetry at the anomeric carbon in each disaccharide. Application of data mining approaches for data analysis allowed unambiguous determination of the anomeric carbon configurations for each disaccharide isomer pair using fragmentation data at a single wavelength. In addition, the linkage positions were easily assigned. This combination of wavelength-selective IRMPD and data mining offers a powerful and convenient tool for differentiation of structurally closely related isomers, including those of gas-phase carbohydrate complexes.

The design and implementation of web mining in web sites security

NASA Astrophysics Data System (ADS)

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

2003-06-01

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

26 CFR 1.612-2 - Allowable capital additions in case of mines.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 26 Internal Revenue 7 2010-04-01 2010-04-01 true Allowable capital additions in case of mines. 1... in case of mines. (a) In general. Expenditures for improvements and for replacements, not including... the recession of the working faces of the mine and which: (1) Do not increase the value of the mine...

75 FR 71668 - Cibota National Forest, Mount Taylor Ranger District, NM, Roca Honda Mine

Federal Register 2010, 2011, 2012, 2013, 2014

2010-11-24

... develop and conduct underground uranium mining operations on their mining claims on and near Jesus Mesa in... open to mineral entry under the General Mining Law of 1872. Section 16 is State of New Mexico land... statement (EIS) to assess the development of a uranium mining operation on the Mount Taylor Ranger District...

30 CFR 71.600 - Drinking water; general.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 1 2011-07-01 2011-07-01 false Drinking water; general. 71.600 Section 71.600 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE SAFETY AND HEALTH... Water § 71.600 Drinking water; general. An adequate supply of potable water shall be provided for...

30 CFR 71.600 - Drinking water; general.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Drinking water; general. 71.600 Section 71.600 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE SAFETY AND HEALTH... Water § 71.600 Drinking water; general. An adequate supply of potable water shall be provided for...

30 CFR 75.1902 - Underground diesel fuel storage-general requirements.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Underground diesel fuel storage-general... LABOR COAL MINE SAFETY AND HEALTH MANDATORY SAFETY STANDARDS-UNDERGROUND COAL MINES Diesel-Powered Equipment § 75.1902 Underground diesel fuel storage—general requirements. (a) All diesel fuel must be stored...

30 CFR 75.1902 - Underground diesel fuel storage-general requirements.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 1 2011-07-01 2011-07-01 false Underground diesel fuel storage-general... LABOR COAL MINE SAFETY AND HEALTH MANDATORY SAFETY STANDARDS-UNDERGROUND COAL MINES Diesel-Powered Equipment § 75.1902 Underground diesel fuel storage—general requirements. (a) All diesel fuel must be stored...

30 CFR 77.1007 - Drilling; general.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 30 Mineral Resources 1 2014-07-01 2014-07-01 false Drilling; general. 77.1007 Section 77.1007 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE SAFETY AND HEALTH... Control § 77.1007 Drilling; general. (a) Equipment that is to be used during a shift shall be inspected...

30 CFR 77.1007 - Drilling; general.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 30 Mineral Resources 1 2012-07-01 2012-07-01 false Drilling; general. 77.1007 Section 77.1007 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE SAFETY AND HEALTH... Control § 77.1007 Drilling; general. (a) Equipment that is to be used during a shift shall be inspected...

30 CFR 77.1007 - Drilling; general.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 1 2011-07-01 2011-07-01 false Drilling; general. 77.1007 Section 77.1007 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE SAFETY AND HEALTH... Control § 77.1007 Drilling; general. (a) Equipment that is to be used during a shift shall be inspected...

30 CFR 77.1007 - Drilling; general.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 30 Mineral Resources 1 2013-07-01 2013-07-01 false Drilling; general. 77.1007 Section 77.1007 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE SAFETY AND HEALTH... Control § 77.1007 Drilling; general. (a) Equipment that is to be used during a shift shall be inspected...

30 CFR 71.600 - Drinking water; general.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 30 Mineral Resources 1 2013-07-01 2013-07-01 false Drinking water; general. 71.600 Section 71.600 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE SAFETY AND HEALTH... Water § 71.600 Drinking water; general. An adequate supply of potable water shall be provided for...

30 CFR 71.600 - Drinking water; general.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 30 Mineral Resources 1 2012-07-01 2012-07-01 false Drinking water; general. 71.600 Section 71.600 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE SAFETY AND HEALTH... Water § 71.600 Drinking water; general. An adequate supply of potable water shall be provided for...

30 CFR 71.600 - Drinking water; general.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 30 Mineral Resources 1 2014-07-01 2014-07-01 false Drinking water; general. 71.600 Section 71.600 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE SAFETY AND HEALTH... Water § 71.600 Drinking water; general. An adequate supply of potable water shall be provided for...

Natural radiation and its hazard in copper ore mines in Poland

NASA Astrophysics Data System (ADS)

Chau, Nguyen; Jodłowski, Paweł; Kalita, Stefan; Olko, Paweł; Chruściel, Edward; Maksymowicz, Adam; Waligórski, Michał; Bilski, Paweł; Budzanowski, Maciej

2008-06-01

The doses of gamma radiation, concentrations of radium isotopes in water and sediments, radon concentration and concentration of alpha potential energy of radon decay products in the copper ore mine and in the mining region in the vicinity of Lubin town in Poland are presented. These data served as a basis for the assessment of radiological hazard to the mine workers and general public. The results of this assessment indicate that radiological hazard in the region does not differ substantially from typical values associated with natural radiation background. The calculated average annual effective dose for copper miners is 1.48 mSv. In general, copper ore mines can be regarded as radiologically safe workplaces.

Tellurium, a guide to mineral deposits

USGS Publications Warehouse

Watterson, J.R.; Gott, G.B.; Neuerburg, G.J.; Lakin, H.W.; Cathrall, J.B.

1977-01-01

Te dispersion patterns are useful in exploring for different types of mineral deposits and in providing additional information about known ore deposits. The Te content of rocks is given for five mining districts in the western United States: Coeur d'Alene, Idaho; Robinson, near Ely, Nevada; Montezuma, Colorado; Crater Creek area, Colorado; Cripple Creek, Colorado. Many of the analyses were obtained by use of a new analytical method sensitive to 0.001 ppm Te. The principal ore deposits in the Coeur d'Alene district, Idaho, are Pb-Zn-Ag replacement veins in Precambrian rocks of the Belt Supergroup. Te dispersion patterns show the outlines of the original mineral belts, the effects of intrusive events, the location of ore deposits, the displacements caused by post-ore faulting, and the borders of the 780-km2 district. The disseminated porphyry Cu deposits of the Robinson mining district, Nevada, are associated with Cretaceous quartz monzonite stocks that have intruded Palaeozoic carbonate rocks. Te is present in rock samples in concentrations as high as 10,000 ppm and forms a halo around the areas containing the Cu deposits. The alteration zones in the porphyry Mo district near Montezuma, Colorado, are developed around several small Tertiary intrusions occurring along a regional shear zone. Te haloes reflect the locations of porphyry intrusives, individual deposits and their ore shoots, and the pattern and intensity of adjacent alteration. The Te content of soils over the Montezuma stock is higher than, and varies independently from, the Te content of adjacent outcrops. Soils generally contain more Te than adjacent outcropping rocks. Soil may collect gaseous Te compounds from mineral deposits. The Crater Creek area is a northwestern extension of the Summitville mining district, Colorado. Te dispersion patterns radiate out from exposed Cu-Pb-Zn veins, from an outcrop of molybdenite stockwork veins and from associated iron-stained altered rock. Te haloes intensify exponentially with proximity to known ore and suggest the presence of Summitville-type chimney deposits. Most of the gold- and silver-telluride ore in the Cripple Creek district, Colorado, is found in fracture fillings within a volcanic subsidence basin. Haloes of Au, Ag and Te all define the mineralized portions of the fissure veins. ?? 1977.

30 CFR 740.15 - Bonds on Federal lands.

Code of Federal Regulations, 2010 CFR

2010-07-01

... Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR FEDERAL LANDS PROGRAM GENERAL REQUIREMENTS FOR SURFACE COAL MINING AND RECLAMATION OPERATIONS ON FEDERAL LANDS... surface coal mining, the applicant for a mining permit, if unable to obtain the written consent of the...

30 CFR 77.1905 - Hoist safeguards; general.

Code of Federal Regulations, 2010 CFR

2010-07-01

....1905 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE SAFETY AND HEALTH MANDATORY SAFETY STANDARDS, SURFACE COAL MINES AND SURFACE WORK AREAS OF UNDERGROUND COAL MINES... when fully loaded. (b) When persons are transported by a hoist, a second person familiar with and...

30 CFR 75.1 - Scope.

Code of Federal Regulations, 2010 CFR

2010-07-01

... SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE SAFETY AND HEALTH MANDATORY SAFETY STANDARDS-UNDERGROUND COAL MINES General § 75.1 Scope. This part 75 sets forth safety standards compliance with which is mandatory in each underground coal mine subject to the Federal Mine Safety and Health Act...

30 CFR 75.1 - Scope.

Code of Federal Regulations, 2013 CFR

2013-07-01

... SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE SAFETY AND HEALTH MANDATORY SAFETY STANDARDS-UNDERGROUND COAL MINES General § 75.1 Scope. This part 75 sets forth safety standards compliance with which is mandatory in each underground coal mine subject to the Federal Mine Safety and Health Act...

30 CFR 75.1 - Scope.

Code of Federal Regulations, 2012 CFR

2012-07-01

... SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE SAFETY AND HEALTH MANDATORY SAFETY STANDARDS-UNDERGROUND COAL MINES General § 75.1 Scope. This part 75 sets forth safety standards compliance with which is mandatory in each underground coal mine subject to the Federal Mine Safety and Health Act...

30 CFR 75.1 - Scope.

Code of Federal Regulations, 2011 CFR

2011-07-01

... SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE SAFETY AND HEALTH MANDATORY SAFETY STANDARDS-UNDERGROUND COAL MINES General § 75.1 Scope. This part 75 sets forth safety standards compliance with which is mandatory in each underground coal mine subject to the Federal Mine Safety and Health Act...

30 CFR 75.1 - Scope.

Code of Federal Regulations, 2014 CFR

2014-07-01

... SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE SAFETY AND HEALTH MANDATORY SAFETY STANDARDS-UNDERGROUND COAL MINES General § 75.1 Scope. This part 75 sets forth safety standards compliance with which is mandatory in each underground coal mine subject to the Federal Mine Safety and Health Act...

Off-road truck-related accidents in U.S. mines

PubMed Central

Dindarloo, Saeid R.; Pollard, Jonisha P.; Siami-Irdemoosa, Elnaz

2016-01-01

Introduction Off-road trucks are one of the major sources of equipment-related accidents in the U.S. mining industries. A systematic analysis of all off-road truck-related accidents, injuries, and illnesses, which are reported and published by the Mine Safety and Health Administration (MSHA), is expected to provide practical insights for identifying the accident patterns and trends in the available raw database. Therefore, appropriate safety management measures can be administered and implemented based on these accident patterns/trends. Methods A hybrid clustering-classification methodology using K-means clustering and gene expression programming (GEP) is proposed for the analysis of severe and non-severe off-road truck-related injuries at U.S. mines. Using the GEP sub-model, a small subset of the 36 recorded attributes was found to be correlated to the severity level. Results Given the set of specified attributes, the clustering sub-model was able to cluster the accident records into 5 distinct groups. For instance, the first cluster contained accidents related to minerals processing mills and coal preparation plants (91%). More than two-thirds of the victims in this cluster had less than 5 years of job experience. This cluster was associated with the highest percentage of severe injuries (22 severe accidents, 3.4%). Almost 50% of all accidents in this cluster occurred at stone operations. Similarly, the other four clusters were characterized to highlight important patterns that can be used to determine areas of focus for safety initiatives. Conclusions The identified clusters of accidents may play a vital role in the prevention of severe injuries in mining. Further research into the cluster attributes and identified patterns will be necessary to determine how these factors can be mitigated to reduce the risk of severe injuries. Practical application Analyzing injury data using data mining techniques provides some insight into attributes that are associated with high accuracies for predicting injury severity. PMID:27620937

Off-road truck-related accidents in U.S. mines.

PubMed

Dindarloo, Saeid R; Pollard, Jonisha P; Siami-Irdemoosa, Elnaz

2016-09-01

Off-road trucks are one of the major sources of equipment-related accidents in the U.S. mining industries. A systematic analysis of all off-road truck-related accidents, injuries, and illnesses, which are reported and published by the Mine Safety and Health Administration (MSHA), is expected to provide practical insights for identifying the accident patterns and trends in the available raw database. Therefore, appropriate safety management measures can be administered and implemented based on these accident patterns/trends. A hybrid clustering-classification methodology using K-means clustering and gene expression programming (GEP) is proposed for the analysis of severe and non-severe off-road truck-related injuries at U.S. mines. Using the GEP sub-model, a small subset of the 36 recorded attributes was found to be correlated to the severity level. Given the set of specified attributes, the clustering sub-model was able to cluster the accident records into 5 distinct groups. For instance, the first cluster contained accidents related to minerals processing mills and coal preparation plants (91%). More than two-thirds of the victims in this cluster had less than 5years of job experience. This cluster was associated with the highest percentage of severe injuries (22 severe accidents, 3.4%). Almost 50% of all accidents in this cluster occurred at stone operations. Similarly, the other four clusters were characterized to highlight important patterns that can be used to determine areas of focus for safety initiatives. The identified clusters of accidents may play a vital role in the prevention of severe injuries in mining. Further research into the cluster attributes and identified patterns will be necessary to determine how these factors can be mitigated to reduce the risk of severe injuries. Analyzing injury data using data mining techniques provides some insight into attributes that are associated with high accuracies for predicting injury severity. Copyright © 2016 Elsevier Ltd and National Safety Council. All rights reserved.

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

30 CFR 33.1 - Purpose.

Code of Federal Regulations, 2012 CFR

2012-07-01

... PRODUCTS DUST COLLECTORS FOR USE IN CONNECTION WITH ROCK DRILLING IN COAL MINES General Provisions § 33.1... with rock drilling in coal mines to procure their certification as permissible for use in coal mines...

30 CFR 33.1 - Purpose.

Code of Federal Regulations, 2011 CFR

2011-07-01

... PRODUCTS DUST COLLECTORS FOR USE IN CONNECTION WITH ROCK DRILLING IN COAL MINES General Provisions § 33.1... with rock drilling in coal mines to procure their certification as permissible for use in coal mines...

30 CFR 33.1 - Purpose.

Code of Federal Regulations, 2013 CFR

2013-07-01

... PRODUCTS DUST COLLECTORS FOR USE IN CONNECTION WITH ROCK DRILLING IN COAL MINES General Provisions § 33.1... with rock drilling in coal mines to procure their certification as permissible for use in coal mines...

30 CFR 33.1 - Purpose.

Code of Federal Regulations, 2010 CFR

2010-07-01

... PRODUCTS DUST COLLECTORS FOR USE IN CONNECTION WITH ROCK DRILLING IN COAL MINES General Provisions § 33.1... with rock drilling in coal mines to procure their certification as permissible for use in coal mines...

30 CFR 33.1 - Purpose.

Code of Federal Regulations, 2014 CFR

2014-07-01

... PRODUCTS DUST COLLECTORS FOR USE IN CONNECTION WITH ROCK DRILLING IN COAL MINES General Provisions § 33.1... with rock drilling in coal mines to procure their certification as permissible for use in coal mines...

43 CFR 3802.4-3 - Multiple-use conflicts.

Code of Federal Regulations, 2011 CFR

2011-10-01

... MANAGEMENT, DEPARTMENT OF THE INTERIOR MINERALS MANAGEMENT (3000) MINING CLAIMS UNDER THE GENERAL MINING LAWS Exploration and Mining, Wilderness Review Program § 3802.4-3 Multiple-use conflicts. In the event that uses...

40 CFR 434.11 - General definitions.

Code of Federal Regulations, 2013 CFR

2013-07-01

... dispoal or long-term storage (greater than 180 days) of such material, but does not include coal refuse... STANDARDS General Provisions § 434.11 General definitions. (a) The term “acid or ferruginous mine drainage... concentration equal to or greater than 10 mg/l. (b) The term “active mining area” means the area, on and beneath...

40 CFR 434.11 - General definitions.

Code of Federal Regulations, 2011 CFR

2011-07-01

... dispoal or long-term storage (greater than 180 days) of such material, but does not include coal refuse... General Provisions § 434.11 General definitions. (a) The term “acid or ferruginous mine drainage” means... concentration equal to or greater than 10 mg/l. (b) The term “active mining area” means the area, on and beneath...

40 CFR 434.11 - General definitions.

Code of Federal Regulations, 2010 CFR

2010-07-01

... dispoal or long-term storage (greater than 180 days) of such material, but does not include coal refuse... General Provisions § 434.11 General definitions. (a) The term “acid or ferruginous mine drainage” means... concentration equal to or greater than 10 mg/l. (b) The term “active mining area” means the area, on and beneath...

40 CFR 434.11 - General definitions.

Code of Federal Regulations, 2014 CFR

2014-07-01

... dispoal or long-term storage (greater than 180 days) of such material, but does not include coal refuse... STANDARDS General Provisions § 434.11 General definitions. (a) The term “acid or ferruginous mine drainage... concentration equal to or greater than 10 mg/l. (b) The term “active mining area” means the area, on and beneath...

40 CFR 434.11 - General definitions.

Code of Federal Regulations, 2012 CFR

2012-07-01

... dispoal or long-term storage (greater than 180 days) of such material, but does not include coal refuse... STANDARDS General Provisions § 434.11 General definitions. (a) The term “acid or ferruginous mine drainage... concentration equal to or greater than 10 mg/l. (b) The term “active mining area” means the area, on and beneath...

20 CFR 726.1 - Statutory insurance requirements for coal mine operators.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 20 Employees' Benefits 3 2010-04-01 2010-04-01 false Statutory insurance requirements for coal... OF LABOR FEDERAL COAL MINE HEALTH AND SAFETY ACT OF 1969, AS AMENDED BLACK LUNG BENEFITS; REQUIREMENTS FOR COAL MINE OPERATOR'S INSURANCE General § 726.1 Statutory insurance requirements for coal mine...

15 CFR 971.501 - Resource assessment, recovery plan, and logical mining unit.

Code of Federal Regulations, 2010 CFR

2010-01-01

..., and logical mining unit. 971.501 Section 971.501 Commerce and Foreign Trade Regulations Relating to... COMMERCE GENERAL REGULATIONS OF THE ENVIRONMENTAL DATA SERVICE DEEP SEABED MINING REGULATIONS FOR... mining unit. (a) The applicant must submit with the application a resource assessment to provide a basis...

30 CFR 90.220 - Status change reports.

Code of Federal Regulations, 2014 CFR

2014-07-01

... Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE SAFETY AND HEALTH... Procedures § 90.201 Sampling; general and technical requirements. (a) An approved coal mine dust personal sampler unit (CMDPSU) shall be used to take samples of the concentration of respirable coal mine dust in...

A Dictionary of Mining, Mineral and Related Terms.

ERIC Educational Resources Information Center

Thrush, Paul W., Comp.

This dictionary contains about 55,000 terms with approximately 150,000 definitions. These terms are of both a technical and local nature and apply to metal mining, coal mining, quarrying, geology, metallurgy, ceramics and clays, glassmaking, minerals and mineralogy, and general terminology. Petroleum, natural gas, and legal mining terminology,…

43 CFR 3420.1-4 - General requirements for land use planning.

Code of Federal Regulations, 2011 CFR

2011-10-01

... mining by other than underground mining techniques. (ii) For the purposes of this paragraph, any surface... techniques shall be deemed to have expressed a preference in favor of mining. Where a significant number of... underground mining techniques, that area shall be considered acceptable for further consideration only for...

43 CFR 3420.1-4 - General requirements for land use planning.

Code of Federal Regulations, 2013 CFR

2013-10-01

... mining by other than underground mining techniques. (ii) For the purposes of this paragraph, any surface... techniques shall be deemed to have expressed a preference in favor of mining. Where a significant number of... underground mining techniques, that area shall be considered acceptable for further consideration only for...

43 CFR 3420.1-4 - General requirements for land use planning.

Code of Federal Regulations, 2014 CFR

2014-10-01

... mining by other than underground mining techniques. (ii) For the purposes of this paragraph, any surface... techniques shall be deemed to have expressed a preference in favor of mining. Where a significant number of... underground mining techniques, that area shall be considered acceptable for further consideration only for...

43 CFR 3420.1-4 - General requirements for land use planning.

Code of Federal Regulations, 2012 CFR

2012-10-01

... mining by other than underground mining techniques. (ii) For the purposes of this paragraph, any surface... techniques shall be deemed to have expressed a preference in favor of mining. Where a significant number of... underground mining techniques, that area shall be considered acceptable for further consideration only for...

76 FR 14637 - State Medicaid Fraud Control Units; Data Mining

Federal Register 2010, 2011, 2012, 2013, 2014

2011-03-17

...] State Medicaid Fraud Control Units; Data Mining AGENCY: Office of Inspector General (OIG), HHS. ACTION... and analyzing State Medicaid claims data, known as data mining. To support and modernize MFCU efforts... (FFP) in the costs of defined data mining activities under specified conditions. In addition, we...

30 CFR 77.502-2 - Electric equipment; frequency of examination and testing.

Code of Federal Regulations, 2010 CFR

2010-07-01

... and testing. 77.502-2 Section 77.502-2 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE SAFETY AND HEALTH MANDATORY SAFETY STANDARDS, SURFACE COAL MINES AND SURFACE WORK AREAS OF UNDERGROUND COAL MINES Electrical Equipment-General § 77.502-2 Electric equipment...

30 CFR 77.1 - Scope.

Code of Federal Regulations, 2010 CFR

2010-07-01

... SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE SAFETY AND HEALTH MANDATORY SAFETY STANDARDS, SURFACE COAL MINES AND SURFACE WORK AREAS OF UNDERGROUND COAL MINES General § 77.1 Scope. This..., pursuant to section 101(i) of the Federal Mine Safety and Health Act of 1977. [36 FR 9364, May 22, 1971, as...

43 CFR 3830.3 - Who may locate mining claims?

Code of Federal Regulations, 2011 CFR

2011-10-01

... 43 Public Lands: Interior 2 2011-10-01 2011-10-01 false Who may locate mining claims? 3830.3... MANAGEMENT, DEPARTMENT OF THE INTERIOR MINERALS MANAGEMENT (3000) LOCATING, RECORDING, AND MAINTAINING MINING CLAIMS OR SITES; GENERAL PROVISIONS Introduction § 3830.3 Who may locate mining claims? Persons qualified...

Data mining of air traffic control operational errors

DOT National Transportation Integrated Search

2006-01-01

In this paper we present the results of : applying data mining techniques to identify patterns and : anomalies in air traffic control operational errors (OEs). : Reducing the OE rate is of high importance and remains a : challenge in the aviation saf...

Acid-base accounting to predict post-mining drainage quality on surface mines.

PubMed

Skousen, J; Simmons, J; McDonald, L M; Ziemkiewicz, P

2002-01-01

Acid-base accounting (ABA) is an analytical procedure that provides values to help assess the acid-producing and acid-neutralizing potential of overburden rocks prior to coal mining and other large-scale excavations. This procedure was developed by West Virginia University scientists during the 1960s. After the passage of laws requiring an assessment of surface mining on water quality, ABA became a preferred method to predict post-mining water quality, and permitting decisions for surface mines are largely based on the values determined by ABA. To predict the post-mining water quality, the amount of acid-producing rock is compared with the amount of acid-neutralizing rock, and a prediction of the water quality at the site (whether acid or alkaline) is obtained. We gathered geologic and geographic data for 56 mined sites in West Virginia, which allowed us to estimate total overburden amounts, and values were determined for maximum potential acidity (MPA), neutralization potential (NP), net neutralization potential (NNP), and NP to MPA ratios for each site based on ABA. These values were correlated to post-mining water quality from springs or seeps on the mined property. Overburden mass was determined by three methods, with the method used by Pennsylvania researchers showing the most accurate results for overburden mass. A poor relationship existed between MPA and post-mining water quality, NP was intermediate, and NNP and the NP to MPA ratio showed the best prediction accuracy. In this study, NNP and the NP to MPA ratio gave identical water quality prediction results. Therefore, with NP to MPA ratios, values were separated into categories: <1 should produce acid drainage, between 1 and 2 can produce either acid or alkaline water conditions, and >2 should produce alkaline water. On our 56 surface mined sites, NP to MPA ratios varied from 0.1 to 31, and six sites (11%) did not fit the expected pattern using this category approach. Two sites with ratios <1 did not produce acid drainage as predicted (the drainage was neutral), and four sites with a ratio >2 produced acid drainage when they should not have. These latter four sites were either mined very slowly, had nonrepresentative ABA data, received water from an adjacent underground mine, or had a surface mining practice that degraded the water. In general, an NP to MPA ratio of <1 produced mostly acid drainage sites, between 1 and 2 produced mostly alkaline drainage sites, while NP to MPA ratios >2 produced alkaline drainage with a few exceptions. Using these values, ABA is a good tool to assess overburden quality before surface mining and to predict post-mining drainage quality after mining. The interpretation from ABA values was correct in 50 out of 52 cases (96%), excluding the four anomalous sites, which had acid water for reasons other than overburden quality.

Preliminary appraisal of the hydrology of the Red Oak area, Latimer County, Oklahoma

USGS Publications Warehouse

Marcher, M.V.; Bergman, D.L.; Stoner, J.D.; Blumer, S.P.

1983-01-01

Bed rock in the Red Oak area consists of shale, siltstone, and sandstone of the McAlester and Savanna Formations of Pennsylvanian age. Water in bedrock occurs in bedding planes, joints, and fractures and is confined. The potentiometric surface generally is less than 20 feet below the land surface. Wells yield enough water for domestic and stock use, but larger amounts of ground water are not available. Ground water commonly is a sodium or mixed cation carbonate/bicarbonate type with dissolved-solids concentrations ranging from 321 to 714 milligrams per liter. Although variable in quality, ground water generally is suitable for domestic use. No relationship between water chemistry and well depth or location is apparent. Brazil Creek, the principal stream in the area, has no flow 15 percent of the time, and flow is less than 1 cubic foot per second about 25 percent of the time. Water in Brazil Creek is a mixed cation carbonate/bicarbonate type. Dissolved-solids concentrations in Brazil Creek upstream from areas of old and recent mining ranged from 31 to 99 milligrams per liter with a mean of 58 milligrams per liter, whereas concentrations downstream from the mine areas ranged from 49 to 596 milligrams per liter with a mean of 132 milligrams per liter. Water in Brazil and Rock Creeks had concentrations of cadmium, chromium, lead, and mercury that exceeded maximum contaminant levels established by the U.S. Environmental Protection Agency at least once during the 1979-81 water years. Maximum suspended-sediment discharge, in tons per day, was 2,500 for Brazil Creek and 3,318 for Rock Creek. Silt-clay particles (diameters less than 0.062 millimeter) were the dominant sediment size. A significant hydrologic effect of surface mining is creation of additional water storage in mine ponds; one such pond supplies water for the town of Red Oak. Other effects or potential effects of surface mining include changes in rock permeability and ground-water storage, changes in drainage patterns, and changes in the chemical quality and sediment loads of streams.

Mining High-Dimensional Data

NASA Astrophysics Data System (ADS)

Wang, Wei; Yang, Jiong

With the rapid growth of computational biology and e-commerce applications, high-dimensional data becomes very common. Thus, mining high-dimensional data is an urgent problem of great practical importance. However, there are some unique challenges for mining data of high dimensions, including (1) the curse of dimensionality and more crucial (2) the meaningfulness of the similarity measure in the high dimension space. In this chapter, we present several state-of-art techniques for analyzing high-dimensional data, e.g., frequent pattern mining, clustering, and classification. We will discuss how these methods deal with the challenges of high dimensionality.

Water spray ventilator system for continuous mining machines

DOEpatents

Page, Steven J.; Mal, Thomas

1995-01-01

The invention relates to a water spray ventilator system mounted on a continuous mining machine to streamline airflow and provide effective face ventilation of both respirable dust and methane in underground coal mines. This system has two side spray nozzles mounted one on each side of the mining machine and six spray nozzles disposed on a manifold mounted to the underside of the machine boom. The six spray nozzles are angularly and laterally oriented on the manifold so as to provide non-overlapping spray patterns along the length of the cutter drum.

A Data Mining Approach to Identify Sexuality Patterns in a Brazilian University Population.

PubMed

Waleska Simões, Priscyla; Cesconetto, Samuel; Toniazzo de Abreu, Larissa Letieli; Côrtes de Mattos Garcia, Merisandra; Cassettari Junior, José Márcio; Comunello, Eros; Bisognin Ceretta, Luciane; Aparecida Manenti, Sandra

2015-01-01

This paper presents the profile and experience of sexuality generated from a data mining classification task. We used a database about sexuality and gender violence performed on a university population in southern Brazil. The data mining task identified two relationships between the variables, which enabled the distinction of subgroups that better detail the profile and experience of sexuality. The identification of the relationships between the variables define behavioral models and factors of risk that will help define the algorithms being implemented in the data mining classification task.

A generalized method for high throughput in-situ experiment data analysis: An example of battery materials exploration

NASA Astrophysics Data System (ADS)

Aoun, Bachir; Yu, Cun; Fan, Longlong; Chen, Zonghai; Amine, Khalil; Ren, Yang

2015-04-01

A generalized method is introduced to extract critical information from series of ranked correlated data. The method is generally applicable to all types of spectra evolving as a function of any arbitrary parameter. This approach is based on correlation functions and statistical scedasticity formalism. Numerous challenges in analyzing high throughput experimental data can be tackled using the herein proposed method. We applied this method to understand the reactivity pathway and formation mechanism of a Li-ion battery cathode material during high temperature synthesis using in-situ high-energy X-ray diffraction. We demonstrate that Pearson's correlation function can easily unravel all major phase transition and, more importantly, the minor structural changes which cannot be revealed by conventionally inspecting the series of diffraction patterns. Furthermore, a two-dimensional (2D) reactivity pattern calculated as the scedasticity along all measured reciprocal space of all successive diffraction pattern pairs unveils clearly the structural evolution path and the active areas of interest during the synthesis. The methods described here can be readily used for on-the-fly data analysis during various in-situ operando experiments in order to quickly evaluate and optimize experimental conditions, as well as for post data analysis and large data mining where considerable amount of data hinders the feasibility of the investigation through point-by-point inspection.

A generalized method for high throughput in-situ experiment data analysis: An example of battery materials exploration

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

Aoun, Bachir; Yu, Cun; Fan, Longlong

A generalized method is introduced to extract critical information from series of ranked correlated data. The method is generally applicable to all types of spectra evolving as a function of any arbitrary parameter. This approach is based on correlation functions and statistical scedasticity formalism. Numerous challenges in analyzing high throughput experimental data can be tackled using the herein proposed method. We applied this method to understand the reactivity pathway and formation mechanism of a Li-ion battery cathode material during high temperature synthesis using in-situ highenergy X-ray diffraction. We demonstrate that Pearson's correlation function can easily unravel all major phase transitionmore » and, more importantly, the minor structural changes which cannot be revealed by conventionally inspecting the series of diffraction patterns. Furthermore, a two-dimensional (2D) reactivity pattern calculated as the scedasticity along all measured reciprocal space of all successive diffraction pattern pairs unveils clearly the structural evolution path and the active areas of interest during the synthesis. The methods described here can be readily used for on-the-fly data analysis during various in-situ operando experiments in order to quickly evaluate and optimize experimental conditions, as well as for post data analysis and large data mining where considerable amount of data hinders the feasibility of the investigation through point-by-point inspection.« less

Aircraft Mishap Fire Pattern Investigations

DTIC Science & Technology

1985-08-01

AD-AI61 094 AIRC1Arr WSWEA FlREg PATMEN INVESTIGATIONS . Joseph M. Kuchta Mining and industrial Cadre15143 Green latetrutiovalp 𔃻nco 54 Sewickley...ORGANIZATION REPORT NUMSER(S) AFWAL-TR-85-2057 6. NAME OF PERFORMING ORGANIZATION kb. OFFICE SYMBOL 7a. NAME OF MONITORING ORGANIZATION Mining and Industrial...IS OBSOLETE. Unc .assi fied SECURITY CLASSIFICATION OF THIS PAGE ( / FOREWARD This report was prepared by the Mining and Industrial Cadre of Green

Data Stream Mining

NASA Astrophysics Data System (ADS)

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

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

Data mining in radiology

PubMed Central

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

2014-01-01

Data mining facilitates the study of radiology data in various dimensions. It converts large patient image and text datasets into useful information that helps in improving patient care and provides informative reports. Data mining technology analyzes data within the Radiology Information System and Hospital Information System using specialized software which assesses relationships and agreement in available information. By using similar data analysis tools, radiologists can make informed decisions and predict the future outcome of a particular imaging finding. Data, information and knowledge are the components of data mining. Classes, Clusters, Associations, Sequential patterns, Classification, Prediction and Decision tree are the various types of data mining. Data mining has the potential to make delivery of health care affordable and ensure that the best imaging practices are followed. It is a tool for academic research. Data mining is considered to be ethically neutral, however concerns regarding privacy and legality exists which need to be addressed to ensure success of data mining. PMID:25024513

Value, Cost, and Sharing: Open Issues in Constrained Clustering

NASA Technical Reports Server (NTRS)

Wagstaff, Kiri L.

2006-01-01

Clustering is an important tool for data mining, since it can identify major patterns or trends without any supervision (labeled data). Over the past five years, semi-supervised (constrained) clustering methods have become very popular. These methods began with incorporating pairwise constraints and have developed into more general methods that can learn appropriate distance metrics. However, several important open questions have arisen about which constraints are most useful, how they can be actively acquired, and when and how they should be propagated to neighboring points. This position paper describes these open questions and suggests future directions for constrained clustering research.

20 CFR 726.1 - Statutory insurance requirements for coal mine operators.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 20 Employees' Benefits 3 2011-04-01 2011-04-01 false Statutory insurance requirements for coal..., DEPARTMENT OF LABOR FEDERAL COAL MINE HEALTH AND SAFETY ACT OF 1969, AS AMENDED BLACK LUNG BENEFITS; REQUIREMENTS FOR COAL MINE OPERATOR'S INSURANCE General § 726.1 Statutory insurance requirements for coal mine...

42 CFR 37.100 - Coal mine operator plan for medical examinations.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 42 Public Health 1 2014-10-01 2014-10-01 false Coal mine operator plan for medical examinations... MEDICAL CARE AND EXAMINATIONS SPECIFICATIONS FOR MEDICAL EXAMINATIONS OF COAL MINERS General Requirements § 37.100 Coal mine operator plan for medical examinations. (a) Each coal mine operator must submit and...

20 CFR 726.1 - Statutory insurance requirements for coal mine operators.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 20 Employees' Benefits 4 2012-04-01 2012-04-01 false Statutory insurance requirements for coal..., DEPARTMENT OF LABOR FEDERAL COAL MINE HEALTH AND SAFETY ACT OF 1969, AS AMENDED BLACK LUNG BENEFITS; REQUIREMENTS FOR COAL MINE OPERATOR'S INSURANCE General § 726.1 Statutory insurance requirements for coal mine...

20 CFR 726.1 - Statutory insurance requirements for coal mine operators.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 20 Employees' Benefits 4 2013-04-01 2013-04-01 false Statutory insurance requirements for coal..., DEPARTMENT OF LABOR FEDERAL COAL MINE HEALTH AND SAFETY ACT OF 1969, AS AMENDED BLACK LUNG BENEFITS; REQUIREMENTS FOR COAL MINE OPERATOR'S INSURANCE General § 726.1 Statutory insurance requirements for coal mine...

20 CFR 726.1 - Statutory insurance requirements for coal mine operators.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 20 Employees' Benefits 4 2014-04-01 2014-04-01 false Statutory insurance requirements for coal..., DEPARTMENT OF LABOR FEDERAL COAL MINE HEALTH AND SAFETY ACT OF 1969, AS AMENDED BLACK LUNG BENEFITS; REQUIREMENTS FOR COAL MINE OPERATOR'S INSURANCE General § 726.1 Statutory insurance requirements for coal mine...

The Potentials of Educational Data Mining for Researching Metacognition, Motivation and Self-Regulated Learning

ERIC Educational Resources Information Center

Winne, Philip H.; Baker, Ryan S. J. D.

2013-01-01

Our article introduces the "Journal of Educational Data Mining's" Special Issue on Educational Data Mining on Motivation, Metacognition, and Self-Regulated Learning. We outline general research challenges for data mining researchers who conduct investigations in these areas, the potential of EDM to advance research in this area, and…

78 FR 53775 - Renewal of Approved Information Collection

Federal Register 2010, 2011, 2012, 2013, 2014

2013-08-30

... regulations. These regulations pertain to the location, recording, and maintenance of mining claims and sites... Location Notices and Mining Claims; Payment of Fees (43 CFR parts 3832-3838). OMB Control Number: 1004-0114..., recording, and maintenance of mining claims and sites, in accordance with the General Mining Law (30 U.S.C...

43 CFR 3737.1 - Mining claim and millsite use.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 43 Public Lands: Interior 2 2011-10-01 2011-10-01 false Mining claim and millsite use. 3737.1... MANAGEMENT, DEPARTMENT OF THE INTERIOR MINERALS MANAGEMENT (3000) PUBLIC LAW 359; MINING IN POWERSITE WITHDRAWALS: GENERAL Use § 3737.1 Mining claim and millsite use. (a) The Act in section 6 provides as follows...

Western Abandoned Uranium Mine Region Maps

EPA Pesticide Factsheets

Map of the Western Abandoned Uranium Mine (AUM) Region, more than 100 abandoned uranium mine claims generally located along the Little Colorado River and Highway 89 in the Cameron, Coalmine Canyon, Bodaway/Gap, and Leupp Chapters in Northern Arizona.

Biosorption of metal and salt tolerant microbial isolates from a former uranium mining area. Their impact on changes in rare earth element patterns in acid mine drainage.

PubMed

Haferburg, Götz; Merten, Dirk; Büchel, Georg; Kothe, Erika

2007-12-01

The concentration of metals in microbial habitats influenced by mining operations can reach enormous values. Worldwide, much emphasis is placed on the research of resistance and biosorptive capacities of microorganisms suitable for bioremediation purposes. Using a collection of isolates from a former uranium mining area in Eastern Thuringia, Germany, this study presents three Gram-positive bacterial strains with distinct metal tolerances. These strains were identified as members of the genera Bacillus, Micrococcus and Streptomyces. Acid mine drainage (AMD) originating from the same mining area is characterized by high metal concentrations of a broad range of elements and a very low pH. AMD was analyzed and used as incubation solution. The sorption of rare earth elements (REE), aluminum, cobalt, copper, manganese, nickel, strontium, and uranium through selected strains was studied during a time course of four weeks. Biosorption was investigated after one hour, one week and four weeks by analyzing the concentrations of metals in supernatant and biomass. Additionally, dead biomass was investigated after four weeks of incubation. The maximum of metal removal was reached after one week. Up to 80% of both Al and Cu, and more than 60% of U was shown to be removed from the solution. High concentrations of metals could be bound to the biomass, as for example 2.2 mg/g U. The strains could survive four weeks of incubation. Distinct and different patterns of rare earth elements of the inoculated and non-inoculated AMD water were observed. Changes in REE patterns hint at different binding types of heavy metals regarding incubation time and metabolic activity of the cells. (c) 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

VisualUrText: A Text Analytics Tool for Unstructured Textual Data

NASA Astrophysics Data System (ADS)

Zainol, Zuraini; Jaymes, Mohd T. H.; Nohuddin, Puteri N. E.

2018-05-01

The growing amount of unstructured text over Internet is tremendous. Text repositories come from Web 2.0, business intelligence and social networking applications. It is also believed that 80-90% of future growth data is available in the form of unstructured text databases that may potentially contain interesting patterns and trends. Text Mining is well known technique for discovering interesting patterns and trends which are non-trivial knowledge from massive unstructured text data. Text Mining covers multidisciplinary fields involving information retrieval (IR), text analysis, natural language processing (NLP), data mining, machine learning statistics and computational linguistics. This paper discusses the development of text analytics tool that is proficient in extracting, processing, analyzing the unstructured text data and visualizing cleaned text data into multiple forms such as Document Term Matrix (DTM), Frequency Graph, Network Analysis Graph, Word Cloud and Dendogram. This tool, VisualUrText, is developed to assist students and researchers for extracting interesting patterns and trends in document analyses.

FraudMiner: A Novel Credit Card Fraud Detection Model Based on Frequent Itemset Mining

PubMed Central

Seeja, K. R.; Zareapoor, Masoumeh

2014-01-01

This paper proposes an intelligent credit card fraud detection model for detecting fraud from highly imbalanced and anonymous credit card transaction datasets. The class imbalance problem is handled by finding legal as well as fraud transaction patterns for each customer by using frequent itemset mining. A matching algorithm is also proposed to find to which pattern (legal or fraud) the incoming transaction of a particular customer is closer and a decision is made accordingly. In order to handle the anonymous nature of the data, no preference is given to any of the attributes and each attribute is considered equally for finding the patterns. The performance evaluation of the proposed model is done on UCSD Data Mining Contest 2009 Dataset (anonymous and imbalanced) and it is found that the proposed model has very high fraud detection rate, balanced classification rate, Matthews correlation coefficient, and very less false alarm rate than other state-of-the-art classifiers. PMID:25302317

FraudMiner: a novel credit card fraud detection model based on frequent itemset mining.

PubMed

Seeja, K R; Zareapoor, Masoumeh

2014-01-01

This paper proposes an intelligent credit card fraud detection model for detecting fraud from highly imbalanced and anonymous credit card transaction datasets. The class imbalance problem is handled by finding legal as well as fraud transaction patterns for each customer by using frequent itemset mining. A matching algorithm is also proposed to find to which pattern (legal or fraud) the incoming transaction of a particular customer is closer and a decision is made accordingly. In order to handle the anonymous nature of the data, no preference is given to any of the attributes and each attribute is considered equally for finding the patterns. The performance evaluation of the proposed model is done on UCSD Data Mining Contest 2009 Dataset (anonymous and imbalanced) and it is found that the proposed model has very high fraud detection rate, balanced classification rate, Matthews correlation coefficient, and very less false alarm rate than other state-of-the-art classifiers.

A New Approach for Mining Order-Preserving Submatrices Based on All Common Subsequences.

PubMed

Xue, Yun; Liao, Zhengling; Li, Meihang; Luo, Jie; Kuang, Qiuhua; Hu, Xiaohui; Li, Tiechen

2015-01-01

Order-preserving submatrices (OPSMs) have been applied in many fields, such as DNA microarray data analysis, automatic recommendation systems, and target marketing systems, as an important unsupervised learning model. Unfortunately, most existing methods are heuristic algorithms which are unable to reveal OPSMs entirely in NP-complete problem. In particular, deep OPSMs, corresponding to long patterns with few supporting sequences, incur explosive computational costs and are completely pruned by most popular methods. In this paper, we propose an exact method to discover all OPSMs based on frequent sequential pattern mining. First, an existing algorithm was adjusted to disclose all common subsequence (ACS) between every two row sequences, and therefore all deep OPSMs will not be missed. Then, an improved data structure for prefix tree was used to store and traverse ACS, and Apriori principle was employed to efficiently mine the frequent sequential pattern. Finally, experiments were implemented on gene and synthetic datasets. Results demonstrated the effectiveness and efficiency of this method.

Reverse and forward engineering of protein pattern formation.

PubMed

Kretschmer, Simon; Harrington, Leon; Schwille, Petra

2018-05-26

Living systems employ protein pattern formation to regulate important life processes in space and time. Although pattern-forming protein networks have been identified in various prokaryotes and eukaryotes, their systematic experimental characterization is challenging owing to the complex environment of living cells. In turn, cell-free systems are ideally suited for this goal, as they offer defined molecular environments that can be precisely controlled and manipulated. Towards revealing the molecular basis of protein pattern formation, we outline two complementary approaches: the biochemical reverse engineering of reconstituted networks and the de novo design, or forward engineering, of artificial self-organizing systems. We first illustrate the reverse engineering approach by the example of the Escherichia coli Min system, a model system for protein self-organization based on the reversible and energy-dependent interaction of the ATPase MinD and its activating protein MinE with a lipid membrane. By reconstituting MinE mutants impaired in ATPase stimulation, we demonstrate how large-scale Min protein patterns are modulated by MinE activity and concentration. We then provide a perspective on the de novo design of self-organizing protein networks. Tightly integrated reverse and forward engineering approaches will be key to understanding and engineering the intriguing phenomenon of protein pattern formation.This article is part of the theme issue 'Self-organization in cell biology'. © 2018 The Author(s).

Efficient frequent pattern mining algorithm based on node sets in cloud computing environment

NASA Astrophysics Data System (ADS)

Billa, V. N. Vinay Kumar; Lakshmanna, K.; Rajesh, K.; Reddy, M. Praveen Kumar; Nagaraja, G.; Sudheer, K.

2017-11-01

The ultimate goal of Data Mining is to determine the hidden information which is useful in making decisions using the large databases collected by an organization. This Data Mining involves many tasks that are to be performed during the process. Mining frequent itemsets is the one of the most important tasks in case of transactional databases. These transactional databases contain the data in very large scale where the mining of these databases involves the consumption of physical memory and time in proportion to the size of the database. A frequent pattern mining algorithm is said to be efficient only if it consumes less memory and time to mine the frequent itemsets from the given large database. Having these points in mind in this thesis we proposed a system which mines frequent itemsets in an optimized way in terms of memory and time by using cloud computing as an important factor to make the process parallel and the application is provided as a service. A complete framework which uses a proven efficient algorithm called FIN algorithm. FIN algorithm works on Nodesets and POC (pre-order coding) tree. In order to evaluate the performance of the system we conduct the experiments to compare the efficiency of the same algorithm applied in a standalone manner and in cloud computing environment on a real time data set which is traffic accidents data set. The results show that the memory consumption and execution time taken for the process in the proposed system is much lesser than those of standalone system.

Process Mining for Individualized Behavior Modeling Using Wireless Tracking in Nursing Homes

PubMed Central

Fernández-Llatas, Carlos; Benedi, José-Miguel; García-Gómez, Juan M.; Traver, Vicente

2013-01-01

The analysis of human behavior patterns is increasingly used for several research fields. The individualized modeling of behavior using classical techniques requires too much time and resources to be effective. A possible solution would be the use of pattern recognition techniques to automatically infer models to allow experts to understand individual behavior. However, traditional pattern recognition algorithms infer models that are not readily understood by human experts. This limits the capacity to benefit from the inferred models. Process mining technologies can infer models as workflows, specifically designed to be understood by experts, enabling them to detect specific behavior patterns in users. In this paper, the eMotiva process mining algorithms are presented. These algorithms filter, infer and visualize workflows. The workflows are inferred from the samples produced by an indoor location system that stores the location of a resident in a nursing home. The visualization tool is able to compare and highlight behavior patterns in order to facilitate expert understanding of human behavior. This tool was tested with nine real users that were monitored for a 25-week period. The results achieved suggest that the behavior of users is continuously evolving and changing and that this change can be measured, allowing for behavioral change detection. PMID:24225907

Topographic Maps and Coal Mining.

ERIC Educational Resources Information Center

Raitz, Karl B.

1984-01-01

Geography teachers can illustrate the patterns associated with mineral fuel production, especially coal, by using United States Geological Survey topographic maps, which are illustrated by symbols that indicate mine-related features, such as shafts and tailings. Map reading exercises are presented; an interpretative map key that can facilitate…

Report: Gold King Mine Release - Inspector General Response to Congressional Requests

EPA Pesticide Factsheets

Report #17-P-0250, June 12, 2017. Since causing the uncontrolled release of 3 million gallons of contaminated mine water, the EPA has taken steps to minimize the possibility of similar incidents at other mine sites.

30 CFR 701.1 - Scope.

Code of Federal Regulations, 2010 CFR

2010-07-01

... OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR GENERAL PERMANENT... program implementation; (2) Subchapter D on surface coal mining and reclamation operations on Federal lands; (3) Subchapter E on surface coal mining and reclamation operations on Indian lands. (4...

30 CFR 701.4 - Responsibility.

Code of Federal Regulations, 2010 CFR

2010-07-01

... Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR GENERAL PERMANENT... responsibility for regulation of coal exploration and surface coal mining and reclamation operations during the... mining and reclamation operations, approval of coal exploration which substantially disturbs the natural...

Northeast Church Rock Mine

EPA Pesticide Factsheets

Northeast Church Rock Mine, a former uranium mine 17 miles northeast of Gallup, NM in the Pinedale Chapter of the Navajo Nation. EPA is working with NNEPA to oversee cleanup work by United Nuclear Corporation, a company owned by General Electric (GE).

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.

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).

Detecting Malicious Tweets in Twitter Using Runtime Monitoring With Hidden Information

DTIC Science & Technology

2016-06-01

text mining using Twitter streaming API and python [Online]. Available: http://adilmoujahid.com/posts/2014/07/twitter-analytics/ [22] M. Singh, B...sites with 645,750,000 registered users [3] and has open source public tweets for data mining . 2. Malicious Users and Tweets In the modern world...want to data mine in Twitter, and presents the natural language assertions and corresponding rule patterns. It then describes the steps performed using

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.

20 CFR 726.201 - Insurance contracts-generally.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 20 Employees' Benefits 3 2010-04-01 2010-04-01 false Insurance contracts-generally. 726.201 Section 726.201 Employees' Benefits EMPLOYMENT STANDARDS ADMINISTRATION, DEPARTMENT OF LABOR FEDERAL COAL MINE HEALTH AND SAFETY ACT OF 1969, AS AMENDED BLACK LUNG BENEFITS; REQUIREMENTS FOR COAL MINE OPERATOR...

Data Mining and Complex Problems: Case Study in Composite Materials

NASA Technical Reports Server (NTRS)

Rabelo, Luis; Marin, Mario

2009-01-01

Data mining is defined as the discovery of useful, possibly unexpected, patterns and relationships in data using statistical and non-statistical techniques in order to develop schemes for decision and policy making. Data mining can be used to discover the sources and causes of problems in complex systems. In addition, data mining can support simulation strategies by finding the different constants and parameters to be used in the development of simulation models. This paper introduces a framework for data mining and its application to complex problems. To further explain some of the concepts outlined in this paper, the potential application to the NASA Shuttle Reinforced Carbon-Carbon structures and genetic programming is used as an illustration.

Application of EREP imagery to fracture-related mine safety hazards in coal mining and mining-environmental problems in Indiana. [Indiana and Illinois

NASA Technical Reports Server (NTRS)

Wier, C. E. (Principal Investigator); Powell, R. L.; Amato, R. V.; Russell, O. R.; Martin, K. R.

1975-01-01

The author has identified the following significant results. This investigation evaluated the applicability of a variety of sensor types, formats, and resolution capabilities to the study of both fuel and nonfuel mined lands. The image reinforcement provided by stereo viewing of the EREP images proved useful for identifying lineaments and for mined lands mapping. Skylab S190B color and color infrared transparencies were the most useful EREP imagery. New information on lineament and fracture patterns in the bedrock of Indiana and Illinois extracted from analysis of the Skylab imagery has contributed to furthering the geological understanding of this portion of the Illinois basin.

Constructing Patient Specific Clinical Trajectories from Electronic Healthcare Reimbursement Claims using Sequential Pattern Mining

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

Pullum, Laura L; Hobson, Tanner C

We examine the use of electronic healthcare reimbursement claims (EHRC) for analyzing healthcare delivery and practice patterns across the United States (US). By analyzing over 1 billion EHRCs, we track patterns of clinical procedures administered to patients with heart disease (HD) using sequential pattern mining algorithms. Our analyses reveal that the clinical procedures performed on HD patients are highly varied leading up to and after the primary diagnosis. The discovered clinical procedure sequences reveal significant differences in the overall costs incurred across different parts of the US, indicating significant heterogeneity in treating HD patients. We show that a data-driven approachmore » to understand patient specific clinical trajectories constructed from EHRC can provide quantitative insights into how to better manage and treat patients.« less

Educational Data Mining Application for Estimating Students Performance in Weka Environment

NASA Astrophysics Data System (ADS)

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

2017-11-01

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

Heavy Metal Concentrations in Soils and Factors Affecting Metal Uptake by Plants in the Vicinity of a Korean Cu-W Mine.

PubMed

Jung, Myung Chae

2008-04-04

Heavy metal concentrations were measured in soils and plants in and around a copper-tungsten mine in southeast Korea to investigate the influence of past base metal mining on the surface environment. The results of chemical analysis indicate that the heavy metals in soils decreased with distance from the source, controlled mainly by water movement and topography. The metal concentrations measured in plant species generally decreased in the order; spring onions > soybean leaves > perilla leaves » red pepper > corn grains » jujube grains, although this pattern varied moderately between different elements. The results agree with other reports that metal concentrations in leaves are usually much higher than those in grain. Factors influencing the bioavailability of metals and their occurrences in crops were found as soil pH, cation exchange capacity, organic matter content, soil texture, and interaction among the target elements. It is concluded that total metal concentrations in soils are the main controls on their contents in plants. Soil pH was also an important factor. A stepwise linear multiple regression analysis was also conducted to identify the dominant factors influencing metal uptake by plants. Metal concentrations in plants were also estimated by computer-aided statistical methods.

Video mining using combinations of unsupervised and supervised learning techniques

NASA Astrophysics Data System (ADS)

Divakaran, Ajay; Miyahara, Koji; Peker, Kadir A.; Radhakrishnan, Regunathan; Xiong, Ziyou

2003-12-01

We discuss the meaning and significance of the video mining problem, and present our work on some aspects of video mining. A simple definition of video mining is unsupervised discovery of patterns in audio-visual content. Such purely unsupervised discovery is readily applicable to video surveillance as well as to consumer video browsing applications. We interpret video mining as content-adaptive or "blind" content processing, in which the first stage is content characterization and the second stage is event discovery based on the characterization obtained in stage 1. We discuss the target applications and find that using a purely unsupervised approach are too computationally complex to be implemented on our product platform. We then describe various combinations of unsupervised and supervised learning techniques that help discover patterns that are useful to the end-user of the application. We target consumer video browsing applications such as commercial message detection, sports highlights extraction etc. We employ both audio and video features. We find that supervised audio classification combined with unsupervised unusual event discovery enables accurate supervised detection of desired events. Our techniques are computationally simple and robust to common variations in production styles etc.

Content based image retrieval using local binary pattern operator and data mining techniques.

PubMed

Vatamanu, Oana Astrid; Frandeş, Mirela; Lungeanu, Diana; Mihalaş, Gheorghe-Ioan

2015-01-01

Content based image retrieval (CBIR) concerns the retrieval of similar images from image databases, using feature vectors extracted from images. These feature vectors globally define the visual content present in an image, defined by e.g., texture, colour, shape, and spatial relations between vectors. Herein, we propose the definition of feature vectors using the Local Binary Pattern (LBP) operator. A study was performed in order to determine the optimum LBP variant for the general definition of image feature vectors. The chosen LBP variant is then subsequently used to build an ultrasound image database, and a database with images obtained from Wireless Capsule Endoscopy. The image indexing process is optimized using data clustering techniques for images belonging to the same class. Finally, the proposed indexing method is compared to the classical indexing technique, which is nowadays widely used.

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.

Integration of Text- and Data-Mining Technologies for Use in Banking Applications

NASA Astrophysics Data System (ADS)

Maslankowski, Jacek

Unstructured data, most of it in the form of text files, typically accounts for 85% of an organization's knowledge stores, but it's not always easy to find, access, analyze or use (Robb 2004). That is why it is important to use solutions based on text and data mining. This solution is known as duo mining. This leads to improve management based on knowledge owned in organization. The results are interesting. Data mining provides to lead with structuralized data, usually powered from data warehouses. Text mining, sometimes called web mining, looks for patterns in unstructured data — memos, document and www. Integrating text-based information with structured data enriches predictive modeling capabilities and provides new stores of insightful and valuable information for driving business and research initiatives forward.

30 CFR 740.10 - Information collection.

Code of Federal Regulations, 2010 CFR

2010-07-01

... Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR FEDERAL LANDS PROGRAM GENERAL REQUIREMENTS FOR SURFACE COAL MINING AND RECLAMATION OPERATIONS ON FEDERAL LANDS... surface coal mining operations on Federal lands. Persons intending to conduct such operations must respond...

30 CFR 740.10 - Information collection.

Code of Federal Regulations, 2013 CFR

2013-07-01

... Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR FEDERAL LANDS PROGRAM GENERAL REQUIREMENTS FOR SURFACE COAL MINING AND RECLAMATION OPERATIONS ON FEDERAL LANDS... surface coal mining operations on Federal lands. Persons intending to conduct such operations must respond...

43 CFR 4.1351 - Preliminary finding by OSM.

Code of Federal Regulations, 2010 CFR

2010-10-01

... APPEALS PROCEDURES Special Rules Applicable to Surface Coal Mining Hearings and Appeals Request for...(c) of the Act, 30 U.s.c. 1260(c) (federal Program; Federal Lands Program; Federal Program for Indian... or has controlled surface coal mining and reclamation operations with a demonstrated pattern of...

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

Shumway, R.H.; McQuarrie, A.D.

Robust statistical approaches to the problem of discriminating between regional earthquakes and explosions are developed. We compare linear discriminant analysis using descriptive features like amplitude and spectral ratios with signal discrimination techniques using the original signal waveforms and spectral approximations to the log likelihood function. Robust information theoretic techniques are proposed and all methods are applied to 8 earthquakes and 8 mining explosions in Scandinavia and to an event from Novaya Zemlya of unknown origin. It is noted that signal discrimination approaches based on discrimination information and Renyi entropy perform better in the test sample than conventional methods based onmore » spectral ratios involving the P and S phases. Two techniques for identifying the ripple-firing pattern for typical mining explosions are proposed and shown to work well on simulated data and on several Scandinavian earthquakes and explosions. We use both cepstral analysis in the frequency domain and a time domain method based on the autocorrelation and partial autocorrelation functions. The proposed approach strips off underlying smooth spectral and seasonal spectral components corresponding to the echo pattern induced by two simple ripple-fired models. For two mining explosions, a pattern is identified whereas for two earthquakes, no pattern is evident.« less

30 CFR 784.200 - Interpretive rules related to General Performance Standards.

Code of Federal Regulations, 2010 CFR

2010-07-01

... RECLAMATION AND OPERATION PLAN § 784.200 Interpretive rules related to General Performance Standards. The... ENFORCEMENT, DEPARTMENT OF THE INTERIOR SURFACE COAL MINING AND RECLAMATION OPERATIONS PERMITS AND COAL... Surface Mining Reclamation and Enforcement. (a) Interpretation of § 784.15: Reclamation plan: Postmining...

30 CFR 50.20-1 - General instructions for completing MSHA Form 7000-1.

Code of Federal Regulations, 2010 CFR

2010-07-01

... LABOR ACCIDENTS, INJURIES, ILLNESSES, EMPLOYMENT, AND PRODUCTION IN MINES NOTIFICATION, INVESTIGATION, REPORTS AND RECORDS OF ACCIDENTS, INJURIES, ILLNESSES, EMPLOYMENT, AND COAL PRODUCTION IN MINES Reporting of Accidents, Injuries, and Illnesses § 50.20-1 General instructions for completing MSHA Form 7000-1...

30 CFR 50.20-1 - General instructions for completing MSHA Form 7000-1.

Code of Federal Regulations, 2014 CFR

2014-07-01

... LABOR ACCIDENTS, INJURIES, ILLNESSES, EMPLOYMENT, AND PRODUCTION IN MINES NOTIFICATION, INVESTIGATION, REPORTS AND RECORDS OF ACCIDENTS, INJURIES, ILLNESSES, EMPLOYMENT, AND COAL PRODUCTION IN MINES Reporting of Accidents, Injuries, and Illnesses § 50.20-1 General instructions for completing MSHA Form 7000-1...

30 CFR 50.20-1 - General instructions for completing MSHA Form 7000-1.

Code of Federal Regulations, 2013 CFR

2013-07-01

... LABOR ACCIDENTS, INJURIES, ILLNESSES, EMPLOYMENT, AND PRODUCTION IN MINES NOTIFICATION, INVESTIGATION, REPORTS AND RECORDS OF ACCIDENTS, INJURIES, ILLNESSES, EMPLOYMENT, AND COAL PRODUCTION IN MINES Reporting of Accidents, Injuries, and Illnesses § 50.20-1 General instructions for completing MSHA Form 7000-1...

30 CFR 50.20-1 - General instructions for completing MSHA Form 7000-1.

Code of Federal Regulations, 2012 CFR

2012-07-01

... LABOR ACCIDENTS, INJURIES, ILLNESSES, EMPLOYMENT, AND PRODUCTION IN MINES NOTIFICATION, INVESTIGATION, REPORTS AND RECORDS OF ACCIDENTS, INJURIES, ILLNESSES, EMPLOYMENT, AND COAL PRODUCTION IN MINES Reporting of Accidents, Injuries, and Illnesses § 50.20-1 General instructions for completing MSHA Form 7000-1...

30 CFR 50.20-1 - General instructions for completing MSHA Form 7000-1.

Code of Federal Regulations, 2011 CFR

2011-07-01

... LABOR ACCIDENTS, INJURIES, ILLNESSES, EMPLOYMENT, AND PRODUCTION IN MINES NOTIFICATION, INVESTIGATION, REPORTS AND RECORDS OF ACCIDENTS, INJURIES, ILLNESSES, EMPLOYMENT, AND COAL PRODUCTION IN MINES Reporting of Accidents, Injuries, and Illnesses § 50.20-1 General instructions for completing MSHA Form 7000-1...

Multifunctional greenway approach for landscape planning and reclamation of a post-mining district: Cartagena-La Unión, SE Spain

NASA Astrophysics Data System (ADS)

Acosta, Jose A.; Faz, Ángel; Zornoza, Raúl; Martínez-Martínez, Silvia; Kabas, Sebla; Bech, Jaume

2015-04-01

Fragmented structures create metaphorical wounds in the landscape altering the ecological and cultural processes associated with it, as it can be seen in many mine areas. Therefore it is advisable to organize the reclamation plan in the beginning of mine operating to provide spatial and functional integration of the landscape based on scientific arguments and with all possible legal and administrative means, which is generally the case of the Strategic Environmental Assessment. However, there are many abandon mine areas where no reclamation plan has been carried out, such as the case of Mining District of Sierra Minera Cartagena-La Unión, SE Spain. In these cases it is vital to respond in a sustainable manner for healing the landscape wounds of post-mining activities. Reclamation activities of a post-mining district includes not only the mine soils also all land uses around them, for this reason on necessary create practical solutions for returning the functions of ecologic and cultural processes of the area. Greenway approach shows the main veins which are crucial for keeping alive and sustaining the mentioned processes of the area. Therefore the main objectives of this study are to 1) develop an integrated local greenway network to be able to preserve significant resources and values of the district, and to 2) develop this greenway network as a part of reclamation process for degraded areas. Landscape assessments revealed the most valuable and potential connectivity resources of the area. These clustering and linear patterns of resource concentrations include mountain range and valleys, natural drainage network, legally protected areas and cultural-historical resources. Conservation areas, cultural-educational resources of post-mining activities and the riverbeds have been the main building stones for the greenway corridor. The multifunctional greenway approach serves as landscape reclamation and planning tool in a degraded area by showing the priority zones for reclamation and having the landscape planners to be more decent in these vital veins that help to return the ecological and social functions and interrelations back. Conservation and benefitting of significant resources can be provided simultaneously and this guides to land managers for making land use decisions and implementing the linkage designs. Protection of the corridors has to be provided through a combination of land acquisition, land-use regulation and policies to avoid inappropriate land use developments in the corridors.

Land use-based landscape planning and restoration in mine closure areas.

PubMed

Zhang, Jianjun; Fu, Meichen; Hassani, Ferri P; Zeng, Hui; Geng, Yuhuan; Bai, Zhongke

2011-05-01

Landscape planning and restoration in mine closure areas is not only an inevitable choice to sustain mining areas but also an important path to maximize landscape resources and to improve ecological function in mine closure areas. The analysis of the present mine development shows that many mines are unavoidably facing closures in China. This paper analyzes the periodic impact of mining activities on landscapes and then proposes planning concepts and principles. According to the landscape characteristics in mine closure areas, this paper classifies available landscape resources in mine closure areas into the landscape for restoration, for limited restoration and for protection, and then summarizes directions for their uses. This paper establishes the framework of spatial control planning and design of landscape elements from "macro control, medium allocation and micro optimization" for the purpose of managing and using this kind of special landscape resources. Finally, this paper applies the theories and methods to a case study in Wu'an from two aspects: the construction of a sustainable land-use pattern on a large scale and the optimized allocation of typical mine landscape resources on a small scale.

NDVI (Normalized Difference Vegetation Index) signatures of transient ecohydrological systems: The case of post-mining landscapes

NASA Astrophysics Data System (ADS)

Brück, Yasemine; Schulte Overberg, Philipp; Pohle, Ina; Hinz, Christoph

2017-04-01

Assessing ecohydrological systems that undergo state transitions due to environmental change is becoming increasingly important. One system that can be used to study severe disturbances are post-mining landscapes as they usually are associated with complete removal of vegetation and afterwards subsequent ecosystem restoration or spontaneous rehabilitation in line with natural succession. Within this context it is of interest, whether and how (fast) the land cover in these areas returns to conditions comparable to those in the undisturbed surrounding or those prior mining. Many aspects of mine site rehabilitation depend on climatic, geomorphic and ecological settings, which determine at which rate vegetation may be re-established. In order to identify general patterns of vegetation establishment, we propose to use NDVI (Normalized Difference Vegetation Index) time series for mine affected land to estimate rate of recovery across climate regions and ecoregions. In this study we analysed the MODIS Terra Satellite 8 day-composite NDVI for areas influenced by surface mining in different climates from 2001 to 2015. The locations have been chosen based on their extent and the data availability of mining and rehabilitation activities. We selected coal extraction as a case study as strip mining generates well-defined chronosequences of disturbance. The selected mining areas are located in equatorial, arid, warm temperate or snow climates with different precipitation and temperature conditions according to the Köppen-Geiger classification. We analysed the NDVI time series regarding significant characteristics of the re-vegetation phase. We applied hierarchical cluster analysis to capture the spatial heterogeneity between different pixels (ca. 250 * 250 m2 each) in and around each open cast mine. We disentangled seasonality, trend and residual components in the NDVI time series by Seasonal and Trend decomposition using LOESS. As expected the time of the removal of vegetation can be clearly identified from the NDVI time series and provides the starting point of disturbance. The cluster analysis allowed us to distinguish between the non-mining land, the mine and the restored land of different ages. Based on these clusters, the time series decomposition revealed the dominance of the trend of increasing NDVI in areas undergoing the restoration process as well as the prevailing seasonality of the oldest restored sites. The determined phase of a dominant trend component, lasting until the NDVI is in the range of the surrounding landscape or the pre-mining conditions, is in the scale of a decade. The impacts of different hydroclimatic regimes and different rehabilitation strategies on long term NDVI development are currently being investigated. Furthermore, coherence analysis will be applied to quantify short term influences of hydrometeorological variables on vegetation development.

Determination of Abutment Pressure in Coal Mines with Extremely Thick Alluvium Stratum: A Typical Kind of Rockburst Mines in China

NASA Astrophysics Data System (ADS)

Zhu, Sitao; Feng, Yu; Jiang, Fuxing

2016-05-01

This paper investigates the abutment pressure distribution in coal mines with extremely thick alluvium stratum (ETAS), which is a typical kind of mines encountering frequent intense rockbursts in China. This occurs due to poor understanding to abutment pressure distribution pattern and the consequent inappropriate mine design. In this study, a theoretical computational model of abutment pressure for ETAS longwall panels is proposed based on the analysis of load transfer mechanisms of key stratum (KS) and ETAS. The model was applied to determine the abutment pressure distribution of LW2302S in Xinjulong Coal Mine; the results of stress and microseismic monitoring verified the rationality of this model. The calculated abutment pressure of LW2302S was also used in the terminal mining line design of LW2301N for rockburst prevention, successfully protecting the main roadway from the adverse influence of the abutment pressure.

30 CFR 740.4 - Responsibilities.

Code of Federal Regulations, 2010 CFR

2010-07-01

... Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR FEDERAL LANDS PROGRAM GENERAL REQUIREMENTS FOR SURFACE COAL MINING AND RECLAMATION OPERATIONS ON FEDERAL LANDS § 740.4 Responsibilities. (a) The Secretary is responsible for: (1) Approval, disapproval or conditional approval of mining...

30 CFR 740.11 - Applicability.

Code of Federal Regulations, 2010 CFR

2010-07-01

... jurisdiction. (e) This subchapter shall not apply to surface coal mining and reclamation operations within a... Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR FEDERAL LANDS PROGRAM GENERAL REQUIREMENTS FOR SURFACE COAL MINING AND RECLAMATION OPERATIONS ON FEDERAL LANDS § 740.11...

30 CFR 705.5 - Definitions.

Code of Federal Regulations, 2010 CFR

2010-07-01

... Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR GENERAL RESTRICTION ON FINANCIAL INTERESTS OF STATE EMPLOYEES § 705.5 Definitions. Act. Means the Surface Mining Control and Reclamation Act of 1977, Pub. L. 95-87. Coal mining operation. Means the business of...

76 FR 40649 - Indiana Regulatory Program

Federal Register 2010, 2011, 2012, 2013, 2014

2011-07-11

... at 312 IAC 25-6-30 Surface mining; explosives; general requirements. The full text of the program... DEPARTMENT OF THE INTERIOR Office of Surface Mining Reclamation and Enforcement 30 CFR Part 914... Mining Reclamation and Enforcement, Interior. ACTION: Proposed rule; public comment period on proposed...

Reclaimed surface mine terrestrial pools: Integrating remote sensing, spatial data and field work

NASA Astrophysics Data System (ADS)

Kazar, Sheila A.

This study investigated the remote sensing of aboveground biomass in reclaimed surface mine reclamation sites and the carbon (C) storage potential of these sites. The research is structured in three sections. In the first study, the potential for utilizing the tasseled cap (TC) spectral transformation to characterize multi-temporal changes of vegetation growth was investigated within nine reclaimed coal surface mines in Monongalia and Preston Counties, West Virginia. The spectral patterns of TC greenness, brightness and wetness values associated with the minesites were investigated for a multi-temporal series of Landsat Thematic Mapper (TM) images, from 1992 to 2007. In general, most of the minesites at the time of mining showed increased brightness, and decreased greenness and wetness, with a reverse of this pattern during reclamation. However, rainfall appears to be a confounding variable, at least for relatively recently reclaimed sites. Spectral change vector analysis (CVA) was found to be effective for summarizing the patterns of change in TC values before and after reclamation. In the second study, field samples were collected from reclaimed grassland minesites and used to estimate biomass and C accumulation. In general, biomass and C increased in the six years following reclamation, and then slowly declined. Three Landsat Thematic Mapper (TM) images, from April, May and September of 2007, were used to assess four vegetation indices (VIs), TC, and red and near infrared radiance for potential for mapping biomass. For the April 3 Landsat image, the vegetation indices were not statistically correlated with field-measured biomass, and nor were the regression models significant. For the May 13 image, TC greenness and EVI were most strongly correlated with biomass, with TC wetness, NDVI, TVI and SAVI all significant at the 0.05 level. A number of regression models that included age since reclamation and spectral indices for May 13 were statistically significant, with the strongest prediction obtained from EVI. For the September 18 image, the correlation of biomass and TC brightness, TM4 and TVI were all statistically significant at the 0.05 level, although regression models that included age since reclamation as a dummy variable were not significant. In the third and final study, the biophysical potential for terrestrial aboveground C storage in minelands reclaimed to grasslands was investigated at the regional and state scale. Although above-ground annual accumulation of C is low in grasslands, if the aboveground biomass were harvested annually, and stored permanently C storage over 20 years on the grasslands of reclaimed minelands in West Virginia could be 3.60-7.32 Tg C, compared to 1.60 -9.80 Tg C if those same sites were reclaimed to forests. Although there is currently only limited usage of harvested hay for purposes that would result in its long-term storage, this study points to the benefits that would accrue if such mechanisms could be developed.

75 FR 30055 - Notice of Availability of the Final Environmental Impact Statement for the Graymont Western U.S...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-05-28

... mining claims located in accordance with the General Mining Law of 1872, as amended. DATES: The Final EIS... operation, which is located on unpatented mining claims on public lands west of Townsend, Montana. This proposal is a continuation of mining along a prominent limestone ridge which forms the crest of the...

Response of transplanted aspen to irrigation and weeding on a Colorado reclaimed surface coal mine

Treesearch

Robert C. Musselman; Wayne D. Shepperd; Frederick W. Smith; Lance A. Asherin; Brian W. Gee

2012-01-01

Successful re-establishment of aspen (Populus tremuloides Michx.) on surface-mined lands in the western United States is problematic because the species generally regenerates vegetatively by sprouting from parent roots in the soil; however, topsoil is removed in the mining process. Previous attempts to plant aspen on reclaimed mine sites have failed because...

Factors defining value and direction of thermal pressure between the mine shafts and impact of the general mine natural draught on ventilation process of underground mining companies

NASA Astrophysics Data System (ADS)

Nikolaev, A. V.; Alymenko, N. I.; Kamenskikh, A. A.; Alymenko, D. N.; Nikolaev, V. A.; Petrov, A. I.

2017-10-01

The article specifies measuring data of air parameters and its volume flow in the shafts and on the surface, collected in BKPRU-2 (Berezniki potash plant and mine 2) («Uralkali» PJSC) in normal operation mode, after shutdown of the main mine fan (GVU) and within several hours. As a result of the test it has been established that thermal pressure between the mine shafts is active continuously regardless of the GVU operation mode or other draught sources. Also it has been discovered that depth of the mine shafts has no impact on thermal pressure value. By the same difference of shaft elevation marks and parameters of outer air between the shafts, by their different depth, thermal pressure of the same value will be active. Value of the general mine natural draught defined as an algebraic sum of thermal pressure values between the shafts depends only on the difference of temperature and pressure of outer air and air in the shaft bottoms on condition of shutdown of the air handling system (unit-heaters, air conditioning systems).

Solar Data Mining at Georgia State University

NASA Astrophysics Data System (ADS)

Angryk, R.; Martens, P. C.; Schuh, M.; Aydin, B.; Kempton, D.; Banda, J.; Ma, R.; Naduvil-Vadukootu, S.; Akkineni, V.; Küçük, A.; Filali Boubrahimi, S.; Hamdi, S. M.

2016-12-01

In this talk we give an overview of research projects related to solar data analysis that are conducted at Georgia State University. We will provide update on multiple advances made by our research team on the analysis of image parameters, spatio-temporal patterns mining, temporal data analysis and our experiences with big, heterogeneous solar data visualization, analysis, processing and storage. We will talk about up-to-date data mining methodologies, and their importance for big data-driven solar physics research.

Mining Longitudinal Web Queries: Trends and Patterns.

ERIC Educational Resources Information Center

Wang, Peiling; Berry, Michael W.; Yang, Yiheng

2003-01-01

Analyzed user queries submitted to an academic Web site during a four-year period, using a relational database, to examine users' query behavior, to identify problems they encounter, and to develop techniques for optimizing query analysis and mining. Linguistic analyses focus on query structures, lexicon, and word associations using statistical…

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

Kargupta, H.; Stafford, B.; Hamzaoglu, I.

This paper describes an experimental parallel/distributed data mining system PADMA (PArallel Data Mining Agents) that uses software agents for local data accessing and analysis and a web based interface for interactive data visualization. It also presents the results of applying PADMA for detecting patterns in unstructured texts of postmortem reports and laboratory test data for Hepatitis C patients.

Restoring tropical forests on bauxite mined lands: lessons from the Brazilian Amazon

Treesearch

John A. Parrotta; Oliver H. Knowles

2001-01-01

Restoring self-sustaining tropical forest ecosystems on surface mined sites is a formidable challenge that requires the integration of proven reclamation techniques and reforestation strategies appropriate to specific site conditions, including landscape biodiversity patterns. Restorationists working in most tropical settings are usually hampered by lack of basic...

30 CFR 70.201 - Sampling; general requirements.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Sampling; general requirements. 70.201 Section... AND HEALTH MANDATORY HEALTH STANDARDS-UNDERGROUND COAL MINES Sampling Procedures § 70.201 Sampling... respirable dust in the active workings of the mine as required by this part with a sampling device approved...

30 CFR 70.201 - Sampling; general requirements.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 1 2011-07-01 2011-07-01 false Sampling; general requirements. 70.201 Section... AND HEALTH MANDATORY HEALTH STANDARDS-UNDERGROUND COAL MINES Sampling Procedures § 70.201 Sampling... respirable dust in the active workings of the mine as required by this part with a sampling device approved...

30 CFR 937.777 - General content requirements for permit applications.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 30 Mineral Resources 3 2013-07-01 2013-07-01 false General content requirements for permit applications. 937.777 Section 937.777 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE OREGON...

30 CFR 937.777 - General content requirements for permit applications.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 30 Mineral Resources 3 2014-07-01 2014-07-01 false General content requirements for permit applications. 937.777 Section 937.777 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE OREGON...

29 CFR 570.122 - General.

Code of Federal Regulations, 2010 CFR

2010-07-01

... other than the following: (1) Manufacturing, (2) Mining, (3) An occupation found by the Secretary to be..., the revised text is set forth as follows: § 570.122 General. (a) Specific exemptions from the child... sixteen years in any occupation other than manufacturing, mining, or an occupation found by the Secretary...

30 CFR 77.211 - Draw-off tunnels; stockpiling and reclaiming operations; general.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Draw-off tunnels; stockpiling and reclaiming operations; general. 77.211 Section 77.211 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION... WORK AREAS OF UNDERGROUND COAL MINES Surface Installations § 77.211 Draw-off tunnels; stockpiling and...

30 CFR 20.6 - General requirements.

Code of Federal Regulations, 2012 CFR

2012-07-01

... MINING PRODUCTS ELECTRIC MINE LAMPS OTHER THAN STANDARD CAP LAMPS § 20.6 General requirements. (a) The lamps shall be durable in construction, practical in operation, and suitable for the service for which... shall be adequate for the use for which the lamp is intended. (c) Battery terminals and leads therefrom...

30 CFR 20.6 - General requirements.

Code of Federal Regulations, 2013 CFR

2013-07-01

... MINING PRODUCTS ELECTRIC MINE LAMPS OTHER THAN STANDARD CAP LAMPS § 20.6 General requirements. (a) The lamps shall be durable in construction, practical in operation, and suitable for the service for which... shall be adequate for the use for which the lamp is intended. (c) Battery terminals and leads therefrom...

30 CFR 20.6 - General requirements.

Code of Federal Regulations, 2014 CFR

2014-07-01

... MINING PRODUCTS ELECTRIC MINE LAMPS OTHER THAN STANDARD CAP LAMPS § 20.6 General requirements. (a) The lamps shall be durable in construction, practical in operation, and suitable for the service for which... shall be adequate for the use for which the lamp is intended. (c) Battery terminals and leads therefrom...

30 CFR 20.6 - General requirements.

Code of Federal Regulations, 2011 CFR

2011-07-01

... MINING PRODUCTS ELECTRIC MINE LAMPS OTHER THAN STANDARD CAP LAMPS § 20.6 General requirements. (a) The lamps shall be durable in construction, practical in operation, and suitable for the service for which... shall be adequate for the use for which the lamp is intended. (c) Battery terminals and leads therefrom...

30 CFR 282.21 - Plans, general.

Code of Federal Regulations, 2011 CFR

2011-07-01

... Resources BUREAU OF OCEAN ENERGY MANAGEMENT, REGULATION, AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR... provide comments on proposed Delineation, Testing, and Mining Plans and any proposal for a significant... Mining Plan if the lessee has sufficient data and information on which to base a Testing or Mining Plan...

30 CFR 715.11 - General obligations.

Code of Federal Regulations, 2010 CFR

2010-07-01

... Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR INITIAL... surface coal mining and reclamation operations conducted on lands where any element of the operations is... are established by part 716 of this chapter for— (1) Surface coal mining operations on steep slopes...

15 CFR 971.202 - Statement of technological experience and capabilities.

Code of Federal Regulations, 2012 CFR

2012-01-01

... GENERAL REGULATIONS OF THE ENVIRONMENTAL DATA SERVICE DEEP SEABED MINING REGULATIONS FOR COMMERCIAL... results to commercial mining. The more test data offered with the application the less analysis will be... step in the mining process, including nodule collection, retrieval, transfer to ship, environmental...

30 CFR 33.3 - Consultation.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 30 Mineral Resources 1 2013-07-01 2013-07-01 false Consultation. 33.3 Section 33.3 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR TESTING, EVALUATION, AND APPROVAL OF MINING PRODUCTS DUST COLLECTORS FOR USE IN CONNECTION WITH ROCK DRILLING IN COAL MINES General Provisions...

30 CFR 33.3 - Consultation.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 30 Mineral Resources 1 2014-07-01 2014-07-01 false Consultation. 33.3 Section 33.3 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR TESTING, EVALUATION, AND APPROVAL OF MINING PRODUCTS DUST COLLECTORS FOR USE IN CONNECTION WITH ROCK DRILLING IN COAL MINES General Provisions...

30 CFR 33.3 - Consultation.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 1 2011-07-01 2011-07-01 false Consultation. 33.3 Section 33.3 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR TESTING, EVALUATION, AND APPROVAL OF MINING PRODUCTS DUST COLLECTORS FOR USE IN CONNECTION WITH ROCK DRILLING IN COAL MINES General Provisions...

30 CFR 33.3 - Consultation.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 30 Mineral Resources 1 2012-07-01 2012-07-01 false Consultation. 33.3 Section 33.3 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR TESTING, EVALUATION, AND APPROVAL OF MINING PRODUCTS DUST COLLECTORS FOR USE IN CONNECTION WITH ROCK DRILLING IN COAL MINES General Provisions...

30 CFR 33.3 - Consultation.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Consultation. 33.3 Section 33.3 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR TESTING, EVALUATION, AND APPROVAL OF MINING PRODUCTS DUST COLLECTORS FOR USE IN CONNECTION WITH ROCK DRILLING IN COAL MINES General Provisions...

30 CFR 740.1 - Scope and purpose.

Code of Federal Regulations, 2012 CFR

2012-07-01

... Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR FEDERAL LANDS PROGRAM GENERAL REQUIREMENTS FOR SURFACE COAL MINING AND RECLAMATION OPERATIONS ON FEDERAL LANDS § 740.1 Scope and purpose. This part provides for the regulation of surface coal mining and reclamation...

30 CFR 740.1 - Scope and purpose.

Code of Federal Regulations, 2010 CFR

2010-07-01

... Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR FEDERAL LANDS PROGRAM GENERAL REQUIREMENTS FOR SURFACE COAL MINING AND RECLAMATION OPERATIONS ON FEDERAL LANDS § 740.1 Scope and purpose. This part provides for the regulation of surface coal mining and reclamation...

30 CFR 740.1 - Scope and purpose.

Code of Federal Regulations, 2011 CFR

2011-07-01

... Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR FEDERAL LANDS PROGRAM GENERAL REQUIREMENTS FOR SURFACE COAL MINING AND RECLAMATION OPERATIONS ON FEDERAL LANDS § 740.1 Scope and purpose. This part provides for the regulation of surface coal mining and reclamation...

30 CFR 740.1 - Scope and purpose.

Code of Federal Regulations, 2014 CFR

2014-07-01

... Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR FEDERAL LANDS PROGRAM GENERAL REQUIREMENTS FOR SURFACE COAL MINING AND RECLAMATION OPERATIONS ON FEDERAL LANDS § 740.1 Scope and purpose. This part provides for the regulation of surface coal mining and reclamation...

30 CFR 740.1 - Scope and purpose.

Code of Federal Regulations, 2013 CFR

2013-07-01

... Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR FEDERAL LANDS PROGRAM GENERAL REQUIREMENTS FOR SURFACE COAL MINING AND RECLAMATION OPERATIONS ON FEDERAL LANDS § 740.1 Scope and purpose. This part provides for the regulation of surface coal mining and reclamation...

30 CFR 18.7 - [Reserved

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false [Reserved] 18.7 Section 18.7 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR TESTING, EVALUATION, AND APPROVAL OF MINING PRODUCTS ELECTRIC MOTOR-DRIVEN MINE EQUIPMENT AND ACCESSORIES General Provisions § 18.7 [Reserved] ...

30 CFR 18.13 - Certification plate.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Certification plate. 18.13 Section 18.13 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR TESTING, EVALUATION, AND APPROVAL OF MINING PRODUCTS ELECTRIC MOTOR-DRIVEN MINE EQUIPMENT AND ACCESSORIES General Provisions § 18.13...

15 CFR 971.202 - Statement of technological experience and capabilities.

Code of Federal Regulations, 2011 CFR

2011-01-01

... GENERAL REGULATIONS OF THE ENVIRONMENTAL DATA SERVICE DEEP SEABED MINING REGULATIONS FOR COMMERCIAL... results to commercial mining. The more test data offered with the application the less analysis will be... step in the mining process, including nodule collection, retrieval, transfer to ship, environmental...

15 CFR 971.202 - Statement of technological experience and capabilities.

Code of Federal Regulations, 2010 CFR

2010-01-01

... GENERAL REGULATIONS OF THE ENVIRONMENTAL DATA SERVICE DEEP SEABED MINING REGULATIONS FOR COMMERCIAL... results to commercial mining. The more test data offered with the application the less analysis will be... step in the mining process, including nodule collection, retrieval, transfer to ship, environmental...

Modeling Patterns of Total Dissolved Solids Release from Central Appalachia, USA, Mine Spoils.

PubMed

Clark, Elyse V; Zipper, Carl E; Daniels, W Lee; Orndorff, Zenah W; Keefe, Matthew J

2017-01-01

Surface mining in the central Appalachian coalfields (USA) influences water quality because the interaction of infiltrated waters and O with freshly exposed mine spoils releases elevated levels of total dissolved solids (TDS) to streams. Modeling and predicting the short- and long-term TDS release potentials of mine spoils can aid in the management of current and future mining-influenced watersheds and landscapes. In this study, the specific conductance (SC, a proxy variable for TDS) patterns of 39 mine spoils during a sequence of 40 leaching events were modeled using a five-parameter nonlinear regression. Estimated parameter values were compared to six rapid spoil assessment techniques (RSATs) to assess predictive relationships between model parameters and RSATs. Spoil leachates reached maximum values, 1108 ± 161 μS cm on average, within the first three leaching events, then declined exponentially to a breakpoint at the 16th leaching event on average. After the breakpoint, SC release remained linear, with most spoil samples exhibiting declines in SC release with successive leaching events. The SC asymptote averaged 276 ± 25 μS cm. Only three samples had SCs >500 μS cm at the end of the 40 leaching events. Model parameters varied with mine spoil rock and weathering type, and RSATs were predictive of four model parameters. Unweathered samples released higher SCs throughout the leaching period relative to weathered samples, and rock type influenced the rate of SC release. The RSATs for SC, total S, and neutralization potential may best predict certain phases of mine spoil TDS release. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

Quality Assurance of NCI Thesaurus by Mining Structural-Lexical Patterns

PubMed Central

Abeysinghe, Rashmie; Brooks, Michael A.; Talbert, Jeffery; Licong, Cui

2017-01-01

Quality assurance of biomedical terminologies such as the National Cancer Institute (NCI) Thesaurus is an essential part of the terminology management lifecycle. We investigate a structural-lexical approach based on non-lattice subgraphs to automatically identify missing hierarchical relations and missing concepts in the NCI Thesaurus. We mine six structural-lexical patterns exhibiting in non-lattice subgraphs: containment, union, intersection, union-intersection, inference-contradiction, and inference union. Each pattern indicates a potential specific type of error and suggests a potential type of remediation. We found 809 non-lattice subgraphs with these patterns in the NCI Thesaurus (version 16.12d). Domain experts evaluated a random sample of 50 small non-lattice subgraphs, of which 33 were confirmed to contain errors and make correct suggestions (33/50 = 66%). Of the 25 evaluated subgraphs revealing multiple patterns, 22 were verified correct (22/25 = 88%). This shows the effectiveness of our structurallexical-pattern-based approach in detecting errors and suggesting remediations in the NCI Thesaurus. PMID:29854100

The impact of gold mining on the Witwatersrand on the rivers and karst system of Gauteng and North West Province, South Africa

NASA Astrophysics Data System (ADS)

Durand, J. F.

2012-06-01

The Witwatersrand has been subjected to geological exploration, mining activities, parallel industrial development and associated settlement patterns over the past century. The gold mines brought with them not only development, employment and wealth, but also the most devastating war in the history of South Africa, civil unrest, economical inequality, social uprooting, pollution, negative health impacts and ecological destruction. One of the most consistent and pressing problems caused by mining has been its impact on the water bodies in and adjacent to the Witwatersrand. The dewatering and rewatering of the karstic aquifer overlying and adjacent to the Witwatersrand Supergroup and the pollution caused by Acid Mine Drainage (AMD) are some of the most serious consequences of gold mining in South Africa and will affect the lives of many South Africans.

Discovering amino acid patterns on binding sites in protein complexes

PubMed Central

Kuo, Huang-Cheng; Ong, Ping-Lin; Lin, Jung-Chang; Huang, Jen-Peng

2011-01-01

Discovering amino acid (AA) patterns on protein binding sites has recently become popular. We propose a method to discover the association relationship among AAs on binding sites. Such knowledge of binding sites is very helpful in predicting protein-protein interactions. In this paper, we focus on protein complexes which have protein-protein recognition. The association rule mining technique is used to discover geographically adjacent amino acids on a binding site of a protein complex. When mining, instead of treating all AAs of binding sites as a transaction, we geographically partition AAs of binding sites in a protein complex. AAs in a partition are treated as a transaction. For the partition process, AAs on a binding site are projected from three-dimensional to two-dimensional. And then, assisted with a circular grid, AAs on the binding site are placed into grid cells. A circular grid has ten rings: a central ring, the second ring with 6 sectors, the third ring with 12 sectors, and later rings are added to four sectors in order. As for the radius of each ring, we examined the complexes and found that 10Å is a suitable range, which can be set by the user. After placing these recognition complexes on the circular grid, we obtain mining records (i.e. transactions) from each sector. A sector is regarded as a record. Finally, we use the association rule to mine these records for frequent AA patterns. If the support of an AA pattern is larger than the predetermined minimum support (i.e. threshold), it is called a frequent pattern. With these discovered patterns, we offer the biologists a novel point of view, which will improve the prediction accuracy of protein-protein recognition. In our experiments, we produced the AA patterns by data mining. As a result, we found that arginine (arg) most frequently appears on the binding sites of two proteins in the recognition protein complexes, while cysteine (cys) appears the fewest. In addition, if we discriminate the shape of binding sites between concave and convex further, we discover that patterns {arg, glu, asp} and {arg, ser, asp} on the concave shape of binding sites in a protein more frequently (i.e. higher probability) make contact with {lys} or {arg} on the convex shape of binding sites in another protein. Thus, we can confidently achieve a rate of at least 78%. On the other hand {val, gly, lys} on the convex surface of binding sites in proteins is more frequently in contact with {asp} on the concave site of another protein, and the confidence achieved is over 81%. Applying data mining in biology can reveal more facts that may otherwise be ignored or not easily discovered by the naked eye. Furthermore, we can discover more relationships among AAs on binding sites by appropriately rotating these residues on binding sites from a three-dimension to two-dimension perspective. We designed a circular grid to deposit the data, which total to 463 records consisting of AAs. Then we used the association rules to mine these records for discovering relationships. The proposed method in this paper provides an insight into the characteristics of binding sites for recognition complexes. PMID:21464838

Assessment of surface-water quantity and quality, Eagle River watershed, Colorado, 1947-2007

USGS Publications Warehouse

Williams, Cory A.; Moore, Jennifer L.; Richards, Rodney J.

2011-01-01

The spatial patterns for concentrations of trace metals (aluminum, cadmium, copper, iron, manganese, and zinc) indicate an increase in dissolved concentrations of these metals near historical mining areas in the Eagle River and several tributaries near Belden. In general, concentrations decrease downstream from mining areas. Concentrations typically are near or below reporting limits in Gore Creek and other tributaries within the watershed. Concentrations for trace elements (arsenic, selenium, and uranium) in the watershed usually are below the reporting limit, and no prevailing spatial patterns were observed in the data. Step-trend analysis and temporal-trend analysis provide evidence that remediation of historical mining areas in the upper Eagle River have led to observed decreases in metals concentrations in many surface-waters. Comparison of pre- and post-remediation concentrations for many metals indicates significant decreases in metals concentrations for cadmium, manganese, and zinc at sites downstream from the Eagle Mine Superfund Site. Some sites show order of magnitude reductions in median concentrations between these two periods. Evaluation of monotonic trends for dissolved metals concentrations show downward trends at numerous sites in, and downstream from, historic mining areas. The spatial pattern of nutrients shows lower concentrations on many tributaries and on the Eagle River upstream from Red Cliff with increases in nutrients downstream of major urban areas. Seasonal variations show that for many nutrient species, concentrations tend to be lowest May-June and highest January-March. The gradual changes in concentrations between seasons may be related to dilution effects from increases and decreases in streamflow. Upward trends in nutrients between the towns of Gypsum and Avon were detected for nitrate, orthophosphate, and total phosphorus. An upward trend in nitrite was detected in Gore Creek. No trends were detected in un-ionized ammonia within the ERW. Exceedances of State water-quality standards (nitrite, nitrate, and un-ionized ammonia) and levels higher than U.S. Environmental Protection Agency recommendations (total phosphorus) occur in several areas within the ERW. The majority of the exceedances are from comparisons to the U.S. Environmental Protection Agency total phosphorus recommendations. A positive correlation was observed between suspended sediment and total phosphorus. An upward trend in total dissolved solids in Gore Creek may be the result of increases in chloride salts. Highly significant trends were detected in sodium, potassium, and chloride with a significant upward trend in magnesium and a weakly significant upward trend in calcium. A quantitative analysis of the relative abundance of calcium, magnesium, sodium, and potassium to the available anions suggests that chloride salts likely are the source for the detected upward trends because chloride is the only commonly occurring anion with a trend in Gore Greek. A potential source for the observed chloride salts may be the chemical anti-icing and deicing products used during winter road maintenance in municipal areas and on Interstate-70. A downward trend in dissolved solids in the Eagle River between Gypsum and Avon may be contributing to the detected trend on the Eagle River at Gypsum. Significant downward trends were detected in specific ions such as calcium, magnesium, sulfate, and silica. Measures of total dissolved solids as well as comparisons to specific ions show that in water-quality samples within the ERW concentrations generally are lower in the headwaters, with increases downstream from Wolcott. Differences in concentrations likely result from increased abundance of salt-bearing geologic units downstream from Avon. Few sites had measured concentrations that exceeded the State standards for chloride.

An novel frequent probability pattern mining algorithm based on circuit simulation method in uncertain biological networks.

PubMed

He, Jieyue; Wang, Chunyan; Qiu, Kunpu; Zhong, Wei

2014-01-01

Motif mining has always been a hot research topic in bioinformatics. Most of current research on biological networks focuses on exact motif mining. However, due to the inevitable experimental error and noisy data, biological network data represented as the probability model could better reflect the authenticity and biological significance, therefore, it is more biological meaningful to discover probability motif in uncertain biological networks. One of the key steps in probability motif mining is frequent pattern discovery which is usually based on the possible world model having a relatively high computational complexity. In this paper, we present a novel method for detecting frequent probability patterns based on circuit simulation in the uncertain biological networks. First, the partition based efficient search is applied to the non-tree like subgraph mining where the probability of occurrence in random networks is small. Then, an algorithm of probability isomorphic based on circuit simulation is proposed. The probability isomorphic combines the analysis of circuit topology structure with related physical properties of voltage in order to evaluate the probability isomorphism between probability subgraphs. The circuit simulation based probability isomorphic can avoid using traditional possible world model. Finally, based on the algorithm of probability subgraph isomorphism, two-step hierarchical clustering method is used to cluster subgraphs, and discover frequent probability patterns from the clusters. The experiment results on data sets of the Protein-Protein Interaction (PPI) networks and the transcriptional regulatory networks of E. coli and S. cerevisiae show that the proposed method can efficiently discover the frequent probability subgraphs. The discovered subgraphs in our study contain all probability motifs reported in the experiments published in other related papers. The algorithm of probability graph isomorphism evaluation based on circuit simulation method excludes most of subgraphs which are not probability isomorphism and reduces the search space of the probability isomorphism subgraphs using the mismatch values in the node voltage set. It is an innovative way to find the frequent probability patterns, which can be efficiently applied to probability motif discovery problems in the further studies.

An novel frequent probability pattern mining algorithm based on circuit simulation method in uncertain biological networks

PubMed Central

2014-01-01

Background Motif mining has always been a hot research topic in bioinformatics. Most of current research on biological networks focuses on exact motif mining. However, due to the inevitable experimental error and noisy data, biological network data represented as the probability model could better reflect the authenticity and biological significance, therefore, it is more biological meaningful to discover probability motif in uncertain biological networks. One of the key steps in probability motif mining is frequent pattern discovery which is usually based on the possible world model having a relatively high computational complexity. Methods In this paper, we present a novel method for detecting frequent probability patterns based on circuit simulation in the uncertain biological networks. First, the partition based efficient search is applied to the non-tree like subgraph mining where the probability of occurrence in random networks is small. Then, an algorithm of probability isomorphic based on circuit simulation is proposed. The probability isomorphic combines the analysis of circuit topology structure with related physical properties of voltage in order to evaluate the probability isomorphism between probability subgraphs. The circuit simulation based probability isomorphic can avoid using traditional possible world model. Finally, based on the algorithm of probability subgraph isomorphism, two-step hierarchical clustering method is used to cluster subgraphs, and discover frequent probability patterns from the clusters. Results The experiment results on data sets of the Protein-Protein Interaction (PPI) networks and the transcriptional regulatory networks of E. coli and S. cerevisiae show that the proposed method can efficiently discover the frequent probability subgraphs. The discovered subgraphs in our study contain all probability motifs reported in the experiments published in other related papers. Conclusions The algorithm of probability graph isomorphism evaluation based on circuit simulation method excludes most of subgraphs which are not probability isomorphism and reduces the search space of the probability isomorphism subgraphs using the mismatch values in the node voltage set. It is an innovative way to find the frequent probability patterns, which can be efficiently applied to probability motif discovery problems in the further studies. PMID:25350277

The Interaction Network Ontology-supported modeling and mining of complex interactions represented with multiple keywords in biomedical literature.

PubMed

Özgür, Arzucan; Hur, Junguk; He, Yongqun

2016-01-01

The Interaction Network Ontology (INO) logically represents biological interactions, pathways, and networks. INO has been demonstrated to be valuable in providing a set of structured ontological terms and associated keywords to support literature mining of gene-gene interactions from biomedical literature. However, previous work using INO focused on single keyword matching, while many interactions are represented with two or more interaction keywords used in combination. This paper reports our extension of INO to include combinatory patterns of two or more literature mining keywords co-existing in one sentence to represent specific INO interaction classes. Such keyword combinations and related INO interaction type information could be automatically obtained via SPARQL queries, formatted in Excel format, and used in an INO-supported SciMiner, an in-house literature mining program. We studied the gene interaction sentences from the commonly used benchmark Learning Logic in Language (LLL) dataset and one internally generated vaccine-related dataset to identify and analyze interaction types containing multiple keywords. Patterns obtained from the dependency parse trees of the sentences were used to identify the interaction keywords that are related to each other and collectively represent an interaction type. The INO ontology currently has 575 terms including 202 terms under the interaction branch. The relations between the INO interaction types and associated keywords are represented using the INO annotation relations: 'has literature mining keywords' and 'has keyword dependency pattern'. The keyword dependency patterns were generated via running the Stanford Parser to obtain dependency relation types. Out of the 107 interactions in the LLL dataset represented with two-keyword interaction types, 86 were identified by using the direct dependency relations. The LLL dataset contained 34 gene regulation interaction types, each of which associated with multiple keywords. A hierarchical display of these 34 interaction types and their ancestor terms in INO resulted in the identification of specific gene-gene interaction patterns from the LLL dataset. The phenomenon of having multi-keyword interaction types was also frequently observed in the vaccine dataset. By modeling and representing multiple textual keywords for interaction types, the extended INO enabled the identification of complex biological gene-gene interactions represented with multiple keywords.

30 CFR 717.14 - Backfilling and grading of road cuts, mine entry area cuts, and other surface work areas.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 3 2011-07-01 2011-07-01 false Backfilling and grading of road cuts, mine entry area cuts, and other surface work areas. 717.14 Section 717.14 Mineral Resources OFFICE OF SURFACE... MINING GENERAL PERFORMANCE STANDARDS § 717.14 Backfilling and grading of road cuts, mine entry area cuts...

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.

Discovering significant evolution patterns from satellite image time series.

PubMed

Petitjean, François; Masseglia, Florent; Gançarski, Pierre; Forestier, Germain

2011-12-01

Satellite Image Time Series (SITS) provide us with precious information on land cover evolution. By studying these series of images we can both understand the changes of specific areas and discover global phenomena that spread over larger areas. Changes that can occur throughout the sensing time can spread over very long periods and may have different start time and end time depending on the location, which complicates the mining and the analysis of series of images. This work focuses on frequent sequential pattern mining (FSPM) methods, since this family of methods fits the above-mentioned issues. This family of methods consists of finding the most frequent evolution behaviors, and is actually able to extract long-term changes as well as short term ones, whenever the change may start and end. However, applying FSPM methods to SITS implies confronting two main challenges, related to the characteristics of SITS and the domain's constraints. First, satellite images associate multiple measures with a single pixel (the radiometric levels of different wavelengths corresponding to infra-red, red, etc.), which makes the search space multi-dimensional and thus requires specific mining algorithms. Furthermore, the non evolving regions, which are the vast majority and overwhelm the evolving ones, challenge the discovery of these patterns. We propose a SITS mining framework that enables discovery of these patterns despite these constraints and characteristics. Our proposal is inspired from FSPM and provides a relevant visualization principle. Experiments carried out on 35 images sensed over 20 years show the proposed approach makes it possible to extract relevant evolution behaviors.

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

30 CFR 33.11 - Approval plates.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 1 2011-07-01 2011-07-01 false Approval plates. 33.11 Section 33.11 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR TESTING, EVALUATION, AND APPROVAL OF MINING PRODUCTS DUST COLLECTORS FOR USE IN CONNECTION WITH ROCK DRILLING IN COAL MINES General Provisions...

30 CFR 33.2 - Definitions.

Code of Federal Regulations, 2013 CFR

2013-07-01

... MINING PRODUCTS DUST COLLECTORS FOR USE IN CONNECTION WITH ROCK DRILLING IN COAL MINES General Provisions... apparatus for collecting the dust that results from drilling in rock in coal mines, and is independent of the drilling equipment. (f) Combination unit means a rock-drilling device with an integral dust...

30 CFR 33.2 - Definitions.

Code of Federal Regulations, 2014 CFR

2014-07-01

... MINING PRODUCTS DUST COLLECTORS FOR USE IN CONNECTION WITH ROCK DRILLING IN COAL MINES General Provisions... apparatus for collecting the dust that results from drilling in rock in coal mines, and is independent of the drilling equipment. (f) Combination unit means a rock-drilling device with an integral dust...

30 CFR 33.11 - Approval plates.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Approval plates. 33.11 Section 33.11 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR TESTING, EVALUATION, AND APPROVAL OF MINING PRODUCTS DUST COLLECTORS FOR USE IN CONNECTION WITH ROCK DRILLING IN COAL MINES General Provisions...

30 CFR 33.11 - Approval plates.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 30 Mineral Resources 1 2014-07-01 2014-07-01 false Approval plates. 33.11 Section 33.11 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR TESTING, EVALUATION, AND APPROVAL OF MINING PRODUCTS DUST COLLECTORS FOR USE IN CONNECTION WITH ROCK DRILLING IN COAL MINES General Provisions...

30 CFR 33.11 - Approval plates.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 30 Mineral Resources 1 2013-07-01 2013-07-01 false Approval plates. 33.11 Section 33.11 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR TESTING, EVALUATION, AND APPROVAL OF MINING PRODUCTS DUST COLLECTORS FOR USE IN CONNECTION WITH ROCK DRILLING IN COAL MINES General Provisions...

30 CFR 33.11 - Approval plates.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 30 Mineral Resources 1 2012-07-01 2012-07-01 false Approval plates. 33.11 Section 33.11 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR TESTING, EVALUATION, AND APPROVAL OF MINING PRODUCTS DUST COLLECTORS FOR USE IN CONNECTION WITH ROCK DRILLING IN COAL MINES General Provisions...

30 CFR 33.2 - Definitions.

Code of Federal Regulations, 2012 CFR

2012-07-01

... MINING PRODUCTS DUST COLLECTORS FOR USE IN CONNECTION WITH ROCK DRILLING IN COAL MINES General Provisions... apparatus for collecting the dust that results from drilling in rock in coal mines, and is independent of the drilling equipment. (f) Combination unit means a rock-drilling device with an integral dust...

30 CFR 33.2 - Definitions.

Code of Federal Regulations, 2011 CFR

2011-07-01

... MINING PRODUCTS DUST COLLECTORS FOR USE IN CONNECTION WITH ROCK DRILLING IN COAL MINES General Provisions... apparatus for collecting the dust that results from drilling in rock in coal mines, and is independent of the drilling equipment. (f) Combination unit means a rock-drilling device with an integral dust...

30 CFR 33.2 - Definitions.

Code of Federal Regulations, 2010 CFR

2010-07-01

... MINING PRODUCTS DUST COLLECTORS FOR USE IN CONNECTION WITH ROCK DRILLING IN COAL MINES General Provisions... apparatus for collecting the dust that results from drilling in rock in coal mines, and is independent of the drilling equipment. (f) Combination unit means a rock-drilling device with an integral dust...

30 CFR 875.15 - Reclamation priorities for noncoal program.

Code of Federal Regulations, 2011 CFR

2011-07-01

... from the extreme danger of adverse effects of mineral mining and processing practices; (2) The protection of public health, safety, and general welfare from the adverse effects of mineral mining and... degraded by the adverse effects of mineral mining and processing practices. (c) Enhancement of facilities...

30 CFR 875.15 - Reclamation priorities for noncoal program.

Code of Federal Regulations, 2010 CFR

2010-07-01

... from the extreme danger of adverse effects of mineral mining and processing practices; (2) The protection of public health, safety, and general welfare from the adverse effects of mineral mining and... degraded by the adverse effects of mineral mining and processing practices. (c) Enhancement of facilities...

30 CFR 875.15 - Reclamation priorities for noncoal program.

Code of Federal Regulations, 2012 CFR

2012-07-01

... from the extreme danger of adverse effects of mineral mining and processing practices; (2) The protection of public health, safety, and general welfare from the adverse effects of mineral mining and... degraded by the adverse effects of mineral mining and processing practices. (c) Enhancement of facilities...

30 CFR 875.15 - Reclamation priorities for noncoal program.

Code of Federal Regulations, 2014 CFR

2014-07-01

... from the extreme danger of adverse effects of mineral mining and processing practices; (2) The protection of public health, safety, and general welfare from the adverse effects of mineral mining and... degraded by the adverse effects of mineral mining and processing practices. (c) Enhancement of facilities...

30 CFR 18.12 - Letter of certification.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Letter of certification. 18.12 Section 18.12 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR TESTING, EVALUATION, AND APPROVAL OF MINING PRODUCTS ELECTRIC MOTOR-DRIVEN MINE EQUIPMENT AND ACCESSORIES General Provisions § 18.12...

30 CFR 18.11 - Approval plate.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Approval plate. 18.11 Section 18.11 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR TESTING, EVALUATION, AND APPROVAL OF MINING PRODUCTS ELECTRIC MOTOR-DRIVEN MINE EQUIPMENT AND ACCESSORIES General Provisions § 18.11 Approval...

30 CFR 18.15 - Changes after approval or certification.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Changes after approval or certification. 18.15 Section 18.15 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR TESTING, EVALUATION, AND APPROVAL OF MINING PRODUCTS ELECTRIC MOTOR-DRIVEN MINE EQUIPMENT AND ACCESSORIES General...

30 CFR 18.9 - Conduct of investigations and tests.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Conduct of investigations and tests. 18.9 Section 18.9 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR TESTING, EVALUATION, AND APPROVAL OF MINING PRODUCTS ELECTRIC MOTOR-DRIVEN MINE EQUIPMENT AND ACCESSORIES General...

30 CFR 77.510 - Resistors; location and guarding.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Resistors; location and guarding. 77.510 Section 77.510 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE... COAL MINES Electrical Equipment-General § 77.510 Resistors; location and guarding. Resistors, heaters...

Mining local climate data to assess spatiotemporal dengue fever epidemic patterns in French Guiana

PubMed Central

Flamand, Claude; Fabregue, Mickael; Bringay, Sandra; Ardillon, Vanessa; Quénel, Philippe; Desenclos, Jean-Claude; Teisseire, Maguelonne

2014-01-01

Objective To identify local meteorological drivers of dengue fever in French Guiana, we applied an original data mining method to the available epidemiological and climatic data. Through this work, we also assessed the contribution of the data mining method to the understanding of factors associated with the dissemination of infectious diseases and their spatiotemporal spread. Methods We applied contextual sequential pattern extraction techniques to epidemiological and meteorological data to identify the most significant climatic factors for dengue fever, and we investigated the relevance of the extracted patterns for the early warning of dengue outbreaks in French Guiana. Results The maximum temperature, minimum relative humidity, global brilliance, and cumulative rainfall were identified as determinants of dengue outbreaks, and the precise intervals of their values and variations were quantified according to the epidemiologic context. The strongest significant correlations were observed between dengue incidence and meteorological drivers after a 4–6-week lag. Discussion We demonstrated the use of contextual sequential patterns to better understand the determinants of the spatiotemporal spread of dengue fever in French Guiana. Future work should integrate additional variables and explore the notion of neighborhood for extracting sequential patterns. Conclusions Dengue fever remains a major public health issue in French Guiana. The development of new methods to identify such specific characteristics becomes crucial in order to better understand and control spatiotemporal transmission. PMID:24549761

Clustering and Dimensionality Reduction to Discover Interesting Patterns in Binary Data

NASA Astrophysics Data System (ADS)

Palumbo, Francesco; D'Enza, Alfonso Iodice

The attention towards binary data coding increased consistently in the last decade due to several reasons. The analysis of binary data characterizes several fields of application, such as market basket analysis, DNA microarray data, image mining, text mining and web-clickstream mining. The paper illustrates two different approaches exploiting a profitable combination of clustering and dimensionality reduction for the identification of non-trivial association structures in binary data. An application in the Association Rules framework supports the theory with the empirical evidence.

Source Analysis of the Crandall Canyon, Utah, Mine Collapse

DOE PAGES

Dreger, D. S.; Ford, S. R.; Walter, W. R.

2008-07-11

Analysis of seismograms from a magnitude 3.9 seismic event on August 6, 2007 in central Utah reveals an anomalous radiation pattern that is contrary to that expected for a tectonic earthquake, and which is dominated by an implosive component. The results show the seismic event is best modeled as a shallow underground collapse. Interestingly, large transverse surface waves require a smaller additional non-collapse source component that represents either faulting in the rocks above the mine workings or deformation of the medium surrounding the mine.

Water quality of streams draining abandoned and reclaimed mined lands in the Kantishna Hills area, Denali National Park and Preserve, Alaska, 2008–11

USGS Publications Warehouse

Brabets, Timothy P.; Ourso, Robert T.

2013-01-01

The Kantishna Hills are an area of low elevation mountains in the northwest part of Denali National Park and Preserve, Alaska. Streams draining the Kantishna Hills are clearwater streams that support several species of fish and are derived from rain, snowmelt, and subsurface aquifers. However, the water quality of many of these streams has been degraded by mining. Past mining practices generated acid mine drainage and excessive sediment loads that affected water quality and aquatic habitat. Because recovery through natural processes is limited owing to a short growing season, several reclamation projects have been implemented on several streams in the Kantishna Hills region. To assess the current water quality of streams in the Kantishna Hills area and to determine if reclamation efforts have improved water quality, a cooperative study between the U.S. Geological Survey and the National Park Service was undertaken during 2008-11. High levels of turbidity, an indicator of high concentrations of suspended sediment, were documented in water-quality data collected in the mid-1980s when mining was active. Mining ceased in 1985 and water-quality data collected during this study indicate that levels of turbidity have declined significantly. Turbidity levels generally were less than 2 Formazin Nephelometric Units and suspended sediment concentrations generally were less than 1 milligram per liter during the current study. Daily turbidity data at Rock Creek, an unmined stream, and at Caribou Creek, a mined stream, documented nearly identical patterns of turbidity in 2009, indicating that reclamation as well as natural revegetation in mined streams has improved water quality. Specific conductance and concentrations of dissolved solids and major ions were highest from streams that had been mined. Most of these streams flow into Moose Creek, which functions as an integrator stream, and dilutes the specific conductance and ion concentrations. Calcium and magnesium are the dominant cations, and bicarbonate and sulfate are the dominant anions. Water samples indicate that the water from Rock Creek, Moose Creek, Slate Creek, and Eldorado Creek is a calcium bicarbonate-type water. The remaining sites are a calcium sulfate type water. U.S. Environmental Protection Agency guidelines for arsenic and antimony in drinking water were exceeded in water at Slate Creek and Eureka Creek. Concentrations of arsenic, cadmium, chromium, copper, lead, nickel, and zinc in streambed sediments at many sites exceed sediment quality guideline thresholds that could be toxic to aquatic life. However, assessment of these concentrations, along with the level of organic carbon detected in the sediment, indicate that only concentrations of arsenic and chromium may be toxic to aquatic life at many sites. In 2008 and 2009, 104 macroinvertebrate taxa and 164 algae taxa were identified from samples collected from seven sites. Of the macroinvertebrates, 86 percent were insects and most of the algae consisted of diatoms. Based on the National Community Index, Rock Creek, a reference site, and Caribou Creek, and a mined stream that had undergone some reclamation, exhibited the best overall stream conditions; whereas Slate Creek and Friday Creek, two small streams that were mined extensively, exhibited the worst stream conditions. A non-metric multi-dimensional scaling analysis of the macroinvertebrate and algae data showed a distinct grouping between the 2008 and 2009 samples, likely because of differences between a wet, cool summer in 2008 and a dry, warm summer in 2009.

Injection of coal combustion byproducts into the Omega Mine for the reduction of acid mine drainage

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

Gray, T.A.; Moran, T.C.; Broschart, D.W.

1998-12-31

The Omega Mine Complex is located outside of Morgantown, West Virginia. The mine is in the Upper Freeport Coal, an acid-producing coal seam. The coal was mined in a manner that has resulted in acid mine drainage (AMD) discharges at multiple points. During the 1990`s, the West Virginia Division of Environmental Protection (WVDEP) assumed responsibility for operating a collection and treatment system for the AMD. Collection and treatment costs are approximately $300,000 per year. An innovative procedure of injecting grout into the mine workings to reduce AMD and the resulting treatment costs is proposed. The procedure involves injecting grout mixesmore » composed primarily of coal combustion byproducts (CCB`s) and water, with a small quantity of cement. The intention of the injection program is to fill the mine voids in the north lobe of the Omega Mine (an area where most of the acidity is believed to be generated) with the grout, thus reducing the contact of air and water with potentially acidic material. The grout mix design consists of an approximate 1:1 ratio of fly ash to byproducts from fluidized bed combustion. Approximately 100 gallons of water per cubic yard of grout is used to help achieve flowability. Observation of the mine workings via subsurface borings and downhole video camera operation confirmed that first-mined areas were generally open while second-mined areas were generally partially collapsed. Closer injection hole spacing was used in second-mined areas to account for collapsed workings. The construction documents have been prepared with the project being bid in late 1997. The engineer`s cost estimate was approximately $2,500,000, with the low bid of approximately $2,300,000 being submitted by Howard Concrete Pumping of Bridgeville, PA.« less

Mining and Modeling Real-world Networks: Patterns, Anomalies, and Tools

DTIC Science & Technology

2012-08-01

3 x 10 4 0 1 2 3 4 5 6 7 x 10 4 Youtube groups Yo ut ub e us er s porn general interest animemusic A1 A2 A3 A4 A3 Figure 10.1: PICS on YOUTUBE finds...groups in major feature clusters; notice that these clusters can be human-labeled as ‘ porn ’, ‘music’, ‘anime’, and ‘special interest’. With respect to...groups 140 labeled as ‘A2’. The node clusters in the blue square labeled as ‘4’ mostly belong to YouTube groups associated with ‘ porn and music’ labeled

16. GENERAL VIEW OF THE DIAMOND MINEYARD. ON THE LEFT ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

16. GENERAL VIEW OF THE DIAMOND MINEYARD. ON THE LEFT IS THE CHIPPY HOIST HOUSE, THE MAIN HOIST HOUSE IS IN THE CENTER, AND THE SUPER HEATER, WHICH WAS USED FOR HEATING COMPRESSED AIR, IS ON THE RIGHT. THE SMALL BUILDING WAS USED FOR CLEANING ROPE CLIPS, AND FOR TOILET FACILITIES. THERE IS ALSO A TAR HOUSE, WHERE TAR WAS STORED AND KEPT WARM. ORIGINALLY EACH MINE HAD ITS OWN TAR STORAGE, BUT IT WAS EVENTUALLY CONSOLIDATED AT THE DIAMOND MINE - Butte Mineyards, Diamond Mine, Butte, Silver Bow County, MT

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.

30 CFR 18.3 - Consultation.

Code of Federal Regulations, 2010 CFR

2010-07-01

... MINING PRODUCTS ELECTRIC MOTOR-DRIVEN MINE EQUIPMENT AND ACCESSORIES General Provisions § 18.3... Safety and Health Administration, Approval and Certification Center, 765 Technology Drive, Triadelphia...

30 CFR 18.3 - Consultation.

Code of Federal Regulations, 2011 CFR

2011-07-01

... MINING PRODUCTS ELECTRIC MOTOR-DRIVEN MINE EQUIPMENT AND ACCESSORIES General Provisions § 18.3... Safety and Health Administration, Approval and Certification Center, 765 Technology Drive, Triadelphia...

30 CFR 18.3 - Consultation.

Code of Federal Regulations, 2014 CFR

2014-07-01

... MINING PRODUCTS ELECTRIC MOTOR-DRIVEN MINE EQUIPMENT AND ACCESSORIES General Provisions § 18.3... Safety and Health Administration, Approval and Certification Center, 765 Technology Drive, Triadelphia...

30 CFR 18.3 - Consultation.

Code of Federal Regulations, 2012 CFR

2012-07-01

... MINING PRODUCTS ELECTRIC MOTOR-DRIVEN MINE EQUIPMENT AND ACCESSORIES General Provisions § 18.3... Safety and Health Administration, Approval and Certification Center, 765 Technology Drive, Triadelphia...

30 CFR 18.3 - Consultation.

Code of Federal Regulations, 2013 CFR

2013-07-01

... MINING PRODUCTS ELECTRIC MOTOR-DRIVEN MINE EQUIPMENT AND ACCESSORIES General Provisions § 18.3... Safety and Health Administration, Approval and Certification Center, 765 Technology Drive, Triadelphia...

Geovisualization of Local and Regional Migration Using Web-mined Demographics

NASA Astrophysics Data System (ADS)

Schuermann, R. T.; Chow, T. E.

2014-11-01

The intent of this research was to augment and facilitate analyses, which gauges the feasibility of web-mined demographics to study spatio-temporal dynamics of migration. As a case study, we explored the spatio-temporal dynamics of Vietnamese Americans (VA) in Texas through geovisualization of mined demographic microdata from the World Wide Web. Based on string matching across all demographic attributes, including full name, address, date of birth, age and phone number, multiple records of the same entity (i.e. person) over time were resolved and reconciled into a database. Migration trajectories were geovisualized through animated sprites by connecting the different addresses associated with the same person and segmenting the trajectory into small fragments. Intra-metropolitan migration patterns appeared at the local scale within many metropolitan areas. At the scale of metropolitan area, varying degrees of immigration and emigration manifest different types of migration clusters. This paper presents a methodology incorporating GIS methods and cartographic design to produce geovisualization animation, enabling the cognitive identification of migration patterns at multiple scales. Identification of spatio-temporal patterns often stimulates further research to better understand the phenomenon and enhance subsequent modeling.

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. (Principal Investigator); Russell, O. R.; Amato, R. V.

1973-01-01

The author has identified the following significant results. The 70mm black and white infrared photography acquired in March 1973 at an approximate scale of 1:115,000 permits the identification of areas of mine subsidence not readily evident on other films. This is largely due to the high contrast rendition of water and land by this film and the excessive surface moisture conditions prevalent in the area at the time of photography. Subsided areas consist of shallow depressions which have impounded water. Patterns with a regularity indicative of the room and pillar configuration used in subsurface coal mining are evident.

Kinetics of bed fracturing around mine workings

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

Veksler, Yu.A.

1988-03-01

A failure of the bed near the walls of the workings of a mine away from the face occurs gradually over time and in this paper the authors take a kinetic approach to evaluating its development. The influence of certain mine engineering factors on the pattern of bed fracturing is discussed. The effect of the depth of mining is shown. Cracking occurs in the portion of the seam at the face near the ground at some distance from it on the interface between soft and hard coal. The density of the fractured rocks and their response affect the bed fracturingmore » near the stope face.« less

Pattern Discovery and Change Detection of Online Music Query Streams

NASA Astrophysics Data System (ADS)

Li, Hua-Fu

In this paper, an efficient stream mining algorithm, called FTP-stream (Frequent Temporal Pattern mining of streams), is proposed to find the frequent temporal patterns over melody sequence streams. In the framework of our proposed algorithm, an effective bit-sequence representation is used to reduce the time and memory needed to slide the windows. The FTP-stream algorithm can calculate the support threshold in only a single pass based on the concept of bit-sequence representation. It takes the advantage of "left" and "and" operations of the representation. Experiments show that the proposed algorithm only scans the music query stream once, and runs significant faster and consumes less memory than existing algorithms, such as SWFI-stream and Moment.

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.

Frequent Itemset Hiding Algorithm Using Frequent Pattern Tree Approach

ERIC Educational Resources Information Center

Alnatsheh, Rami

2012-01-01

A problem that has been the focus of much recent research in privacy preserving data-mining is the frequent itemset hiding (FIH) problem. Identifying itemsets that appear together frequently in customer transactions is a common task in association rule mining. Organizations that share data with business partners may consider some of the frequent…

Using Syntactic Patterns to Enhance Text Analytics

ERIC Educational Resources Information Center

Meyer, Bradley B.

2017-01-01

Large scale product and service reviews proliferate and are commonly found across the web. The ability to harvest, digest and analyze a large corpus of reviews from online websites is still however a difficult problem. This problem is referred to as "opinion mining." Opinion mining is an important area of research as advances in the…

Data mining application in customer relationship management for hospital inpatients.

PubMed

Lee, Eun Whan

2012-09-01

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. 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. 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%. 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.

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

30 CFR 33.7 - Date for conducting tests.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Date for conducting tests. 33.7 Section 33.7 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR TESTING, EVALUATION, AND APPROVAL OF MINING PRODUCTS DUST COLLECTORS FOR USE IN CONNECTION WITH ROCK DRILLING IN COAL MINES General...

30 CFR 33.5 - [Reserved

Code of Federal Regulations, 2014 CFR

2014-07-01

... 30 Mineral Resources 1 2014-07-01 2014-07-01 false [Reserved] 33.5 Section 33.5 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR TESTING, EVALUATION, AND APPROVAL OF MINING PRODUCTS DUST COLLECTORS FOR USE IN CONNECTION WITH ROCK DRILLING IN COAL MINES General Provisions § 33.5...

30 CFR 33.5 - [Reserved

Code of Federal Regulations, 2013 CFR

2013-07-01

... 30 Mineral Resources 1 2013-07-01 2013-07-01 false [Reserved] 33.5 Section 33.5 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR TESTING, EVALUATION, AND APPROVAL OF MINING PRODUCTS DUST COLLECTORS FOR USE IN CONNECTION WITH ROCK DRILLING IN COAL MINES General Provisions § 33.5...

30 CFR 33.7 - Date for conducting tests.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 30 Mineral Resources 1 2014-07-01 2014-07-01 false Date for conducting tests. 33.7 Section 33.7 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR TESTING, EVALUATION, AND APPROVAL OF MINING PRODUCTS DUST COLLECTORS FOR USE IN CONNECTION WITH ROCK DRILLING IN COAL MINES General...

30 CFR 33.5 - [Reserved

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 1 2011-07-01 2011-07-01 false [Reserved] 33.5 Section 33.5 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR TESTING, EVALUATION, AND APPROVAL OF MINING PRODUCTS DUST COLLECTORS FOR USE IN CONNECTION WITH ROCK DRILLING IN COAL MINES General Provisions § 33.5...

30 CFR 33.7 - Date for conducting tests.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 30 Mineral Resources 1 2012-07-01 2012-07-01 false Date for conducting tests. 33.7 Section 33.7 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR TESTING, EVALUATION, AND APPROVAL OF MINING PRODUCTS DUST COLLECTORS FOR USE IN CONNECTION WITH ROCK DRILLING IN COAL MINES General...

30 CFR 33.5 - [Reserved

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false [Reserved] 33.5 Section 33.5 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR TESTING, EVALUATION, AND APPROVAL OF MINING PRODUCTS DUST COLLECTORS FOR USE IN CONNECTION WITH ROCK DRILLING IN COAL MINES General Provisions § 33.5...

30 CFR 33.7 - Date for conducting tests.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 1 2011-07-01 2011-07-01 false Date for conducting tests. 33.7 Section 33.7 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR TESTING, EVALUATION, AND APPROVAL OF MINING PRODUCTS DUST COLLECTORS FOR USE IN CONNECTION WITH ROCK DRILLING IN COAL MINES General...

30 CFR 33.7 - Date for conducting tests.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 30 Mineral Resources 1 2013-07-01 2013-07-01 false Date for conducting tests. 33.7 Section 33.7 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR TESTING, EVALUATION, AND APPROVAL OF MINING PRODUCTS DUST COLLECTORS FOR USE IN CONNECTION WITH ROCK DRILLING IN COAL MINES General...

30 CFR 33.5 - [Reserved

Code of Federal Regulations, 2012 CFR

2012-07-01

... 30 Mineral Resources 1 2012-07-01 2012-07-01 false [Reserved] 33.5 Section 33.5 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR TESTING, EVALUATION, AND APPROVAL OF MINING PRODUCTS DUST COLLECTORS FOR USE IN CONNECTION WITH ROCK DRILLING IN COAL MINES General Provisions § 33.5...

36 CFR 1005.14 - Prospecting, mining, and mineral leasing.

Code of Federal Regulations, 2010 CFR

2010-07-01

... location of mining claims under the general mining laws and leasing under the mineral leasing laws are prohibited in the area administered by the Presidio Trust except as authorized by law. ... mineral leasing. 1005.14 Section 1005.14 Parks, Forests, and Public Property PRESIDIO TRUST COMMERCIAL AND...

78 FR 15040 - Renewal of Approved Information Collection

Federal Register 2010, 2011, 2012, 2013, 2014

2013-03-08

... authorized by the mining laws, and in obtaining financial guarantees for the reclamation of public lands. The... the General Mining Law (43 CFR subpart 3809). Forms: Form 3809-1, Surface Management Surety Bond; Form... whether operators and mining claimants are meeting their responsibility to prevent unnecessary or undue...

30 CFR 77.1108 - Firefighting equipment; requirements; general.

Code of Federal Regulations, 2010 CFR

2010-07-01

.... 77.1108 Section 77.1108 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE SAFETY AND HEALTH MANDATORY SAFETY STANDARDS, SURFACE COAL MINES AND SURFACE WORK AREAS OF... which is adapted to the size and suitable for use under the conditions present on the surface at the...

30 CFR 57.1 - Purpose and scope.

Code of Federal Regulations, 2010 CFR

2010-07-01

.... The purpose of these standards is the protection of life, the promotion of health and safety, and the... Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR METAL AND NONMETAL MINE SAFETY AND HEALTH SAFETY AND HEALTH STANDARDS-UNDERGROUND METAL AND NONMETAL MINES General § 57.1 Purpose and scope...

30 CFR 56.1 - Purpose and scope.

Code of Federal Regulations, 2010 CFR

2010-07-01

... standards is the protection of life, the promotion of health and safety, and the prevention of accidents. ... Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR METAL AND NONMETAL MINE SAFETY AND HEALTH SAFETY AND HEALTH STANDARDS-SURFACE METAL AND NONMETAL MINES General § 56.1 Purpose and scope...

Mining the Temporal Dimension of the Information Propagation

NASA Astrophysics Data System (ADS)

Berlingerio, Michele; Coscia, Michele; Giannotti, Fosca

In the last decade, Social Network Analysis has been a field in which the effort devoted from several researchers in the Data Mining area has increased very fast. Among the possible related topics, the study of the information propagation in a network attracted the interest of many researchers, also from the industrial world. However, only a few answers to the questions “How does the information propagates over a network, why and how fast?” have been discovered so far. On the other hand, these answers are of large interest, since they help in the tasks of finding experts in a network, assessing viral marketing strategies, identifying fast or slow paths of the information inside a collaborative network. In this paper we study the problem of finding frequent patterns in a network with the help of two different techniques: TAS (Temporally Annotated Sequences) mining, aimed at extracting sequential patterns where each transition between two events is annotated with a typical transition time that emerges from input data, and Graph Mining, which is helpful for locally analyzing the nodes of the networks with their properties. Finally we show preliminary results done in the direction of mining the information propagation over a network, performed on two well known email datasets, that show the power of the combination of these two approaches.

High contents of rare earth elements (REEs) in stream waters of a Cu-Pb-Zn mining area.

PubMed

Protano, G; Riccobono, F

2002-01-01

Stream waters draining an old mining area present very high rare earth element (REE) contents, reaching 928 microg/l as the maximum total value (sigmaREE). The middle rare earth elements (MREEs) are usually enriched with respect to both the light (LREEs) and heavy (HREEs) elements of this group, producing a characteristic "roof-shaped" pattern of the shale Post-Archean Australian Shales-normalized concentrations. At the Fenice Capanne Mine (FCM), the most important base metal mine of the study area, the REE source coincides with the mine tailings, mostly the oldest ones composed of iron-rich materials. The geochemical history of the REEs released into Noni stream from wastes in the FCM area is strictly determined by the pH, which controls the REE speciation and in-stream processes. The formation of Al-rich and mainly Fe-rich flocs effectively scavenges the REEs, which are readily and drastically removed from the solution when the pH approaches neutrality. Leaching experiments performed on flocs and waste materials demonstrate that Fe-oxides/oxyhydroxides play a key role in the release of lanthanide elements into stream waters. The origin of the "roof-shaped" REE distribution pattern as well as the peculiar geochemical behavior of some lanthanide elements in the aqueous system are discussed.

Expert systems in clinical microbiology.

PubMed

Winstanley, Trevor; Courvalin, Patrice

2011-07-01

This review aims to discuss expert systems in general and how they may be used in medicine as a whole and clinical microbiology in particular (with the aid of interpretive reading). It considers rule-based systems, pattern-based systems, and data mining and introduces neural nets. A variety of noncommercial systems is described, and the central role played by the EUCAST is stressed. The need for expert rules in the environment of reset EUCAST breakpoints is also questioned. Commercial automated systems with on-board expert systems are considered, with emphasis being placed on the "big three": Vitek 2, BD Phoenix, and MicroScan. By necessity and in places, the review becomes a general review of automated system performances for the detection of specific resistance mechanisms rather than focusing solely on expert systems. Published performance evaluations of each system are drawn together and commented on critically.

A Graph Approach to Mining Biological Patterns in the Binding Interfaces.

PubMed

Cheng, Wen; Yan, Changhui

2017-01-01

Protein-RNA interactions play important roles in the biological systems. Searching for regular patterns in the Protein-RNA binding interfaces is important for understanding how protein and RNA recognize each other and bind to form a complex. Herein, we present a graph-mining method for discovering biological patterns in the protein-RNA interfaces. We represented known protein-RNA interfaces using graphs and then discovered graph patterns enriched in the interfaces. Comparison of the discovered graph patterns with UniProt annotations showed that the graph patterns had a significant overlap with residue sites that had been proven crucial for the RNA binding by experimental methods. Using 200 patterns as input features, a support vector machine method was able to classify protein surface patches into RNA-binding sites and non-RNA-binding sites with 84.0% accuracy and 88.9% precision. We built a simple scoring function that calculated the total number of the graph patterns that occurred in a protein-RNA interface. That scoring function was able to discriminate near-native protein-RNA complexes from docking decoys with a performance comparable with that of a state-of-the-art complex scoring function. Our work also revealed possible patterns that might be important for binding affinity.

Mine blast injuries: ocular and social aspects

PubMed Central

Muzaffar, W.; Khan, M. D.; Akbar, M; Khan, M. D.; Malik, A. M.; Durrani, O.

2000-01-01

BACKGROUND/AIMS—Landmines have long been used in conventional warfare. These are antipersonnel mines which continue to injure people long after a ceasefire without differentiating between friend or foe, soldier or civilian, women or children. This study focuses on Afghan non-combatants engaged in mine clearing operations in Afghanistan in the aftermath of the Russo-Afghan war. The patterns and types of injuries seen are described and experiences in their management, ways, and means to prevent them, and recommendations for the rehabilitation of the affected individuals are given.
METHODS—It is a retrospective and analytical study of 84 patients aged 19-56 years who sustained mine blast injuries during mine clearing operations in Afghanistan from November 1992 to January 1996. The study was carried out at a military hospital with tertiary care facilities. The patients were divided into three groups on the basis of their injuries. Group 1 required only general surgical attention, group 2 sustained only ocular injuries, while group 3 had combined ocular and general injuries. Patients in groups 2 and 3 were treated in two phases. The first phase aimed at immediate restoration of the anatomy, while restoration of function wherever possible was done in subsequent surgical procedures in the second phase.
RESULTS—It was observed that 51 out of 84 patients (60.7%) had sustained ocular trauma of a variable degree as a result of the blasts. The mean age of the victims was 29 years and they were all male. A total of 91 eyes of 51 patients (89.2%) had been damaged. Bilaterality of damage was seen in 40 (78.4%) patients. Most, 34 (37.3%), eyes became totally blind (NPL). Only a few escaped with injury mild enough not to impair vision. Foreign bodies, small and multiple, were found in the majority of eyes; most, however, were found in the anterior segment, and posterior segment injuries were proportionally less.
CONCLUSIONS—The prevalence of blindness caused by mine blast injuries is quite high. The resulting psychosocial trauma to the patients and their families is tremendous and has not been adequately highlighted. These injuries are a great drain on the country's resources. Enforcement of preventive measures and the use of protective gear and sophisticated equipment by the mine clearing personnel would prove to be far more economical in terms of human life as well as medical and economic resources. There is also need for greater attention towards the establishment of support groups and rehabilitation programmes for these individuals.

 PMID:10837390

Statistically significant relational data mining :

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

Berry, Jonathan W.; Leung, Vitus Joseph; Phillips, Cynthia Ann

This report summarizes the work performed under the project (3z(BStatitically significant relational data mining.(3y (BThe goal of the project was to add more statistical rigor to the fairly ad hoc area of data mining on graphs. Our goal was to develop better algorithms and better ways to evaluate algorithm quality. We concetrated on algorithms for community detection, approximate pattern matching, and graph similarity measures. Approximate pattern matching involves finding an instance of a relatively small pattern, expressed with tolerance, in a large graph of data observed with uncertainty. This report gathers the abstracts and references for the eight refereed publicationsmore » that have appeared as part of this work. We then archive three pieces of research that have not yet been published. The first is theoretical and experimental evidence that a popular statistical measure for comparison of community assignments favors over-resolved communities over approximations to a ground truth. The second are statistically motivated methods for measuring the quality of an approximate match of a small pattern in a large graph. The third is a new probabilistic random graph model. Statisticians favor these models for graph analysis. The new local structure graph model overcomes some of the issues with popular models such as exponential random graph models and latent variable models.« less

Modeling of the Nano- and Picoseismicity Rate Changes Resulting from Static Stress Triggering due to Small (MW2.2) Event Recorded at Mponeng Deep Gold Mine, South Africa

NASA Astrophysics Data System (ADS)

Kozlowska, M.; Orlecka-Sikora, B.; Kwiatek, G.; Boettcher, M. S.; Dresen, G. H.

2014-12-01

Static stress changes following large earthquakes are known to affect the rate and spatio-temporal distribution of the aftershocks. Here we utilize a unique dataset of M ≥ -3.4 earthquakes following a MW 2.2 earthquake in Mponeng gold mine, South Africa, to investigate this process for nano- and pico- scale seismicity at centimeter length scales in shallow, mining conditions. The aftershock sequence was recorded during a quiet interval in the mine and thus enabled us to perform the analysis using Dietrich's (1994) rate and state dependent friction law. The formulation for earthquake productivity requires estimation of Coulomb stress changes due to the mainshock, the reference seismicity rate, frictional resistance parameter, and the duration of aftershock relaxation time. We divided the area into six depth intervals and for each we estimated the parameters and modeled the spatio-temporal patterns of seismicity rates after the stress perturbation. Comparing the modeled patterns of seismicity with the observed distribution we found that while the spatial patterns match well, the rate of modeled aftershocks is lower than the observed rate. To test our model, we used four metrics of the goodness-of-fit evaluation. Testing procedure allowed rejecting the null hypothesis of no significant difference between seismicity rates only for one depth interval containing the mainshock, for the other, no significant differences have been found. Results show that mining-induced earthquakes may be followed by a stress relaxation expressed through aftershocks located on the rupture plane and in regions of positive Coulomb stress change. Furthermore, we demonstrate that the main features of the temporal and spatial distribution of very small, mining-induced earthquakes at shallow depths can be successfully determined using rate- and state-based stress modeling.

Evaluation of the environmental contamination at an abandoned mining site using multivariate statistical techniques--the Rodalquilar (Southern Spain) mining district.

PubMed

Bagur, M G; Morales, S; López-Chicano, M

2009-11-15

Unsupervised and supervised pattern recognition techniques such as hierarchical cluster analysis, principal component analysis, factor analysis and linear discriminant analysis have been applied to water samples recollected in Rodalquilar mining district (Southern Spain) in order to identify different sources of environmental pollution caused by the abandoned mining industry. The effect of the mining activity on waters was monitored determining the concentration of eleven elements (Mn, Ba, Co, Cu, Zn, As, Cd, Sb, Hg, Au and Pb) by inductively coupled plasma mass spectrometry (ICP-MS). The Box-Cox transformation has been used to transform the data set in normal form in order to minimize the non-normal distribution of the geochemical data. The environmental impact is affected mainly by the mining activity developed in the zone, the acid drainage and finally by the chemical treatment used for the benefit of gold.

A text-based data mining and toxicity prediction modeling system for a clinical decision support in radiation oncology: A preliminary study

NASA Astrophysics Data System (ADS)

Kim, Kwang Hyeon; Lee, Suk; Shim, Jang Bo; Chang, Kyung Hwan; Yang, Dae Sik; Yoon, Won Sup; Park, Young Je; Kim, Chul Yong; Cao, Yuan Jie

2017-08-01

The aim of this study is an integrated research for text-based data mining and toxicity prediction modeling system for clinical decision support system based on big data in radiation oncology as a preliminary research. The structured and unstructured data were prepared by treatment plans and the unstructured data were extracted by dose-volume data image pattern recognition of prostate cancer for research articles crawling through the internet. We modeled an artificial neural network to build a predictor model system for toxicity prediction of organs at risk. We used a text-based data mining approach to build the artificial neural network model for bladder and rectum complication predictions. The pattern recognition method was used to mine the unstructured toxicity data for dose-volume at the detection accuracy of 97.9%. The confusion matrix and training model of the neural network were achieved with 50 modeled plans (n = 50) for validation. The toxicity level was analyzed and the risk factors for 25% bladder, 50% bladder, 20% rectum, and 50% rectum were calculated by the artificial neural network algorithm. As a result, 32 plans could cause complication but 18 plans were designed as non-complication among 50 modeled plans. We integrated data mining and a toxicity modeling method for toxicity prediction using prostate cancer cases. It is shown that a preprocessing analysis using text-based data mining and prediction modeling can be expanded to personalized patient treatment decision support based on big data.

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.

Spatiotemporal analysis of changes in lode mining claims around the McDermitt Caldera, northern Nevada and southern Oregon

USGS Publications Warehouse

Coyan, Joshua; Zientek, Michael L.; Mihalasky, Mark J.

2017-01-01

Resource managers and agencies involved with planning for future federal land needs are required to complete an assessment of and forecast for future land use every ten years. Predicting mining activities on federal lands is difficult as current regulations do not require disclosure of exploration results. In these cases, historic mining claims may serve as a useful proxy for determining where mining-related activities may occur. We assess the utility of using a space–time cube (STC) and associated analyses to evaluate and characterize mining claim activities around the McDermitt Caldera in northern Nevada and southern Oregon. The most significant advantage of arranging the mining claim data into a STC is the ability to visualize and compare the data, which allows scientists to better understand patterns and results. Additional analyses of the STC (i.e., Trend, Emerging Hot Spot, Hot Spot, and Cluster and Outlier Analyses) provide extra insights into the data and may aid in predicting future mining claim activities.

Geological survey of Maryland using EREP flight data. [mining, mapping, Chesapeake Bay islands, coastal water features

NASA Technical Reports Server (NTRS)

Weaver, K. N. (Principal Investigator)

1973-01-01

The author has identified the following significant results. Underflight photography has been used in the Baltimore County mined land inventory to determine areas of disturbed land where surface mining of sand and ground clay, or stone has taken place. Both active and abandoned pits and quarries were located. Aircraft data has been used to update cultural features of Calvert, Caroline, St. Mary's, Somerset, Talbot, and Wicomico Counties. Islands have been located and catalogued for comparison with older film and map data for erosion data. Strip mined areas are being mapped to obtain total area disturbed to aid in future mining and reclamation problems. Coastal estuarine and Atlantic Coast features are being studied to determine nearshore bedforms, sedimentary, and erosional patterns, and manmade influence on natural systems.

15 CFR 971.103 - Prohibited activities and restrictions.

Code of Federal Regulations, 2014 CFR

2014-01-01

... THE ENVIRONMENTAL DATA SERVICE DEEP SEABED MINING REGULATIONS FOR COMMERCIAL RECOVERY PERMITS General... the effect of harassing, persons conducting deep seabed mining activities authorized by law...

15 CFR 971.103 - Prohibited activities and restrictions.

Code of Federal Regulations, 2012 CFR

2012-01-01

... THE ENVIRONMENTAL DATA SERVICE DEEP SEABED MINING REGULATIONS FOR COMMERCIAL RECOVERY PERMITS General... the effect of harassing, persons conducting deep seabed mining activities authorized by law...

15 CFR 971.103 - Prohibited activities and restrictions.

Code of Federal Regulations, 2013 CFR

2013-01-01

... THE ENVIRONMENTAL DATA SERVICE DEEP SEABED MINING REGULATIONS FOR COMMERCIAL RECOVERY PERMITS General... the effect of harassing, persons conducting deep seabed mining activities authorized by law...

43 CFR 3802.4-2 - Access.

Code of Federal Regulations, 2012 CFR

2012-10-01

... OF THE INTERIOR MINERALS MANAGEMENT (3000) MINING CLAIMS UNDER THE GENERAL MINING LAWS Exploration... specify the location of the access route, the design, construction, operation and maintenance standards...

43 CFR 3802.4-2 - Access.

Code of Federal Regulations, 2013 CFR

2013-10-01

... OF THE INTERIOR MINERALS MANAGEMENT (3000) MINING CLAIMS UNDER THE GENERAL MINING LAWS Exploration... specify the location of the access route, the design, construction, operation and maintenance standards...

15 CFR 971.103 - Prohibited activities and restrictions.

Code of Federal Regulations, 2010 CFR

2010-01-01

... THE ENVIRONMENTAL DATA SERVICE DEEP SEABED MINING REGULATIONS FOR COMMERCIAL RECOVERY PERMITS General... the effect of harassing, persons conducting deep seabed mining activities authorized by law...

15 CFR 971.103 - Prohibited activities and restrictions.

Code of Federal Regulations, 2011 CFR

2011-01-01

... THE ENVIRONMENTAL DATA SERVICE DEEP SEABED MINING REGULATIONS FOR COMMERCIAL RECOVERY PERMITS General... the effect of harassing, persons conducting deep seabed mining activities authorized by law...

Soft Computing Approach to Evaluate and Predict Blast-Induced Ground Vibration

NASA Astrophysics Data System (ADS)

Khandelwal, Manoj

2010-05-01

Drilling and blasting is still one of the major economical operations to excavate a rock mass. The consumption of explosive has been increased many folds in recent years. These explosives are mainly used for the exploitation of minerals in mining industry or the removal of undesirable rockmass for community development. The amount of chemical energy converted into mechanical energy to fragment and displace the rockmass is minimal. Only 20 to 30% of this explosive energy is utilized for the actual fragmentation and displacement of rockmass and rest of the energy is wasted in undesirable ill effects, like, ground vibration, air over pressure, fly rock, back break, noise, etc. Ground vibration induced due to blasting is very crucial and critical as compared to other ill effects due to involvement of public residing in the close vicinity of mining sites, regulating and ground vibration standards setting agencies together with mine owners and environmentalists and ecologists. Also, with the emphasis shifting towards eco-friendly, sustainable and geo-environmental activities, the field of ground vibration have now become an important and imperative parameter for safe and smooth running of any mining and civil project. The ground vibration is a wave motion, spreading outward from the blast like ripples spreading outwards due to impact of a stone dropped into a pond of water. As the vibration passes through the surface structures, it induces vibrations in those structures also. Sometimes, due to high ground vibration level, dwellings may get damaged and there is always confrontation between mine management and the people residing in the surroundings of the mine area. There is number of vibration predictors available suggested by different researchers. All the predictors estimate the PPV based on mainly two parameters (maximum charge used per delay and distance between blast face to monitoring point). However, few predictors considered attenuation/damping factor too. For the same excavation site, different predictors give different values of safe PPV vis-à-vis safe charge per delay. There is no uniformity in the predicted result by different predictors. All vibration predictor equations have their site specific constants. Therefore, they cannot be used in a generalized way with confidence and zero level of risk. To overcome on this aspect new soft computing tools like artificial neural network (ANN) has attracted because of its ability to learn from the pattern acquainted before. ANN has the ability to learn from patterns acquainted before. It is a highly interconnected network of a large number of processing elements called neurons in an architecture inspired by the brain. ANN can be massively parallel and hence said to exhibit parallel distributed processing. Once, the network has been trained, with sufficient number of sample data sets, it can make reliable and trustworthy predictions on the basis of its previous learning, about the output related to new input data set of similar pattern. This paper deals the application of ANN for the prediction of ground vibration by taking into consideration of maximum charge per delay and distance between blast face to monitoring point. To investigate the appropriateness of this approach, the predictions by ANN have been also compared with other vibration predictor equations.

Mining sequential patterns for protein fold recognition.

PubMed

Exarchos, Themis P; Papaloukas, Costas; Lampros, Christos; Fotiadis, Dimitrios I

2008-02-01

Protein data contain discriminative patterns that can be used in many beneficial applications if they are defined correctly. In this work sequential pattern mining (SPM) is utilized for sequence-based fold recognition. Protein classification in terms of fold recognition plays an important role in computational protein analysis, since it can contribute to the determination of the function of a protein whose structure is unknown. Specifically, one of the most efficient SPM algorithms, cSPADE, is employed for the analysis of protein sequence. A classifier uses the extracted sequential patterns to classify proteins in the appropriate fold category. For training and evaluating the proposed method we used the protein sequences from the Protein Data Bank and the annotation of the SCOP database. The method exhibited an overall accuracy of 25% in a classification problem with 36 candidate categories. The classification performance reaches up to 56% when the five most probable protein folds are considered.

78 FR 3913 - Public Land Order No. 7807: Withdrawal of Public Lands for the Camp Michael Monsoor Mountain...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-01-17

..., location, and entry under the general land laws, including the United States mining laws, for a period of... Training Facility. This withdrawal also transfers administrative jurisdiction of the lands to the... entry under the general land laws, including the United States mining laws, but not from leasing under...

30 CFR 75.1103-3 - Automatic fire sensor and warning device systems; minimum requirements; general.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 30 Mineral Resources 1 2014-07-01 2014-07-01 false Automatic fire sensor and warning device systems; minimum requirements; general. 75.1103-3 Section 75.1103-3 Mineral Resources MINE SAFETY AND...-UNDERGROUND COAL MINES Fire Protection § 75.1103-3 Automatic fire sensor and warning device systems; minimum...

Synoptic sampling and principal components analysis to identify sources of water and metals to an acid mine drainage stream.

PubMed

Byrne, Patrick; Runkel, Robert L; Walton-Day, Katherine

2017-07-01

Combining the synoptic mass balance approach with principal components analysis (PCA) can be an effective method for discretising the chemistry of inflows and source areas in watersheds where contamination is diffuse in nature and/or complicated by groundwater interactions. This paper presents a field-scale study in which synoptic sampling and PCA are employed in a mineralized watershed (Lion Creek, Colorado, USA) under low flow conditions to (i) quantify the impacts of mining activity on stream water quality; (ii) quantify the spatial pattern of constituent loading; and (iii) identify inflow sources most responsible for observed changes in stream chemistry and constituent loading. Several of the constituents investigated (Al, Cd, Cu, Fe, Mn, Zn) fail to meet chronic aquatic life standards along most of the study reach. The spatial pattern of constituent loading suggests four primary sources of contamination under low flow conditions. Three of these sources are associated with acidic (pH <3.1) seeps that enter along the left bank of Lion Creek. Investigation of inflow water (trace metal and major ion) chemistry using PCA suggests a hydraulic connection between many of the left bank inflows and mine water in the Minnesota Mine shaft located to the north-east of the river channel. In addition, water chemistry data during a rainfall-runoff event suggests the spatial pattern of constituent loading may be modified during rainfall due to dissolution of efflorescent salts or erosion of streamside tailings. These data point to the complexity of contaminant mobilisation processes and constituent loading in mining-affected watersheds but the combined synoptic sampling and PCA approach enables a conceptual model of contaminant dynamics to be developed to inform remediation.

Synoptic sampling and principal components analysis to identify sources of water and metals to an acid mine drainage stream

USGS Publications Warehouse

Byrne, Patrick; Runkel, Robert L.; Walton-Day, Katie

2017-01-01

Combining the synoptic mass balance approach with principal components analysis (PCA) can be an effective method for discretising the chemistry of inflows and source areas in watersheds where contamination is diffuse in nature and/or complicated by groundwater interactions. This paper presents a field-scale study in which synoptic sampling and PCA are employed in a mineralized watershed (Lion Creek, Colorado, USA) under low flow conditions to (i) quantify the impacts of mining activity on stream water quality; (ii) quantify the spatial pattern of constituent loading; and (iii) identify inflow sources most responsible for observed changes in stream chemistry and constituent loading. Several of the constituents investigated (Al, Cd, Cu, Fe, Mn, Zn) fail to meet chronic aquatic life standards along most of the study reach. The spatial pattern of constituent loading suggests four primary sources of contamination under low flow conditions. Three of these sources are associated with acidic (pH <3.1) seeps that enter along the left bank of Lion Creek. Investigation of inflow water (trace metal and major ion) chemistry using PCA suggests a hydraulic connection between many of the left bank inflows and mine water in the Minnesota Mine shaft located to the north-east of the river channel. In addition, water chemistry data during a rainfall-runoff event suggests the spatial pattern of constituent loading may be modified during rainfall due to dissolution of efflorescent salts or erosion of streamside tailings. These data point to the complexity of contaminant mobilisation processes and constituent loading in mining-affected watersheds but the combined synoptic sampling and PCA approach enables a conceptual model of contaminant dynamics to be developed to inform remediation.

30 CFR 75.501-1 - Coal seams above the water table.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 1 2011-07-01 2011-07-01 false Coal seams above the water table. 75.501-1 Section 75.501-1 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE SAFETY AND HEALTH MANDATORY SAFETY STANDARDS-UNDERGROUND COAL MINES Electrical Equipment-General § 75.501...

30 CFR 75.501-1 - Coal seams above the water table.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 30 Mineral Resources 1 2012-07-01 2012-07-01 false Coal seams above the water table. 75.501-1 Section 75.501-1 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE SAFETY AND HEALTH MANDATORY SAFETY STANDARDS-UNDERGROUND COAL MINES Electrical Equipment-General § 75.501...

30 CFR 75.501-1 - Coal seams above the water table.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 30 Mineral Resources 1 2014-07-01 2014-07-01 false Coal seams above the water table. 75.501-1 Section 75.501-1 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE SAFETY AND HEALTH MANDATORY SAFETY STANDARDS-UNDERGROUND COAL MINES Electrical Equipment-General § 75.501...

30 CFR 75.501-1 - Coal seams above the water table.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Coal seams above the water table. 75.501-1 Section 75.501-1 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE SAFETY AND HEALTH MANDATORY SAFETY STANDARDS-UNDERGROUND COAL MINES Electrical Equipment-General § 75.501...

30 CFR 75.501-1 - Coal seams above the water table.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 30 Mineral Resources 1 2013-07-01 2013-07-01 false Coal seams above the water table. 75.501-1 Section 75.501-1 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE SAFETY AND HEALTH MANDATORY SAFETY STANDARDS-UNDERGROUND COAL MINES Electrical Equipment-General § 75.501...

30 CFR 57.2 - Definitions.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 30 Mineral Resources 1 2012-07-01 2012-07-01 false Definitions. 57.2 Section 57.2 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR METAL AND NONMETAL MINE SAFETY AND HEALTH SAFETY AND HEALTH STANDARDS-UNDERGROUND METAL AND NONMETAL MINES General § 57.2 Definitions. The following definitions apply to this part. In...

30 CFR 57.2 - Definitions.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 30 Mineral Resources 1 2014-07-01 2014-07-01 false Definitions. 57.2 Section 57.2 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR METAL AND NONMETAL MINE SAFETY AND HEALTH SAFETY AND HEALTH STANDARDS-UNDERGROUND METAL AND NONMETAL MINES General § 57.2 Definitions. The following definitions apply to this part. In...

43 CFR 3809.2 - What is the scope of this subpart?

Code of Federal Regulations, 2012 CFR

2012-10-01

... inform the public. (b) This subpart does not apply to lands in the National Park System, National Forest... MANAGEMENT, DEPARTMENT OF THE INTERIOR MINERALS MANAGEMENT (3000) MINING CLAIMS UNDER THE GENERAL MINING LAWS... applies to all operations authorized by the mining laws on public lands where the mineral interest is...

43 CFR 3809.2 - What is the scope of this subpart?

Code of Federal Regulations, 2013 CFR

2013-10-01

... inform the public. (b) This subpart does not apply to lands in the National Park System, National Forest... MANAGEMENT, DEPARTMENT OF THE INTERIOR MINERALS MANAGEMENT (3000) MINING CLAIMS UNDER THE GENERAL MINING LAWS... applies to all operations authorized by the mining laws on public lands where the mineral interest is...

43 CFR 3809.2 - What is the scope of this subpart?

Code of Federal Regulations, 2014 CFR

2014-10-01

... inform the public. (b) This subpart does not apply to lands in the National Park System, National Forest... MANAGEMENT, DEPARTMENT OF THE INTERIOR MINERALS MANAGEMENT (3000) MINING CLAIMS UNDER THE GENERAL MINING LAWS... applies to all operations authorized by the mining laws on public lands where the mineral interest is...

43 CFR 3809.2 - What is the scope of this subpart?

Code of Federal Regulations, 2011 CFR

2011-10-01

... inform the public. (b) This subpart does not apply to lands in the National Park System, National Forest... MANAGEMENT, DEPARTMENT OF THE INTERIOR MINERALS MANAGEMENT (3000) MINING CLAIMS UNDER THE GENERAL MINING LAWS... applies to all operations authorized by the mining laws on public lands where the mineral interest is...