WorldWideScience

Sample records for stream mining techniques

  1. Data Stream Mining

    Science.gov (United States)

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

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

  2. A survey on Big Data Stream Mining

    African Journals Online (AJOL)

    pc

    2018-03-05

    Mar 5, 2018 ... huge amount of stream like telecommunication systems. So, there ... streams have many challenges for data mining algorithm design like using of ..... A. Bifet and R. Gavalda, "Learning from Time-Changing Data with. Adaptive ...

  3. Application for trackless mining technique in Benxi uranium mine

    International Nuclear Information System (INIS)

    Chen Bingguo

    1998-01-01

    The author narrates the circumstances achieving constructional target in Benxi Uranium Mine under relying on advance of science and technology and adopting small trackless mining equipment, presents the application of trackless mining equipment at mining small mine and complex mineral deposit and discusses the unique superiority of trackless mining technique in development work, mining preparation work and backstoping

  4. Mining Building Metadata by Data Stream Comparison

    DEFF Research Database (Denmark)

    Holmegaard, Emil; Kjærgaard, Mikkel Baun

    2016-01-01

    to handle data streams with only slightly similar patterns. We have evaluated Metafier with points and data from one building located in Denmark. We have evaluated Metafier with 903 points, and the overall accuracy, with only 3 known examples, was 94.71%. Furthermore we found that using DTW for mining...... ways to annotate sensor and actuation points. This makes it difficult to create intuitive queries for retrieving data streams from points. Another problem is the amount of insufficient or missing metadata. We introduce Metafier, a tool for extracting metadata from comparing data streams. Metafier...... enables a semi-automatic labeling of metadata to building instrumentation. Metafier annotates points with metadata by comparing the data from a set of validated points with unvalidated points. Metafier has three different algorithms to compare points with based on their data. The three algorithms...

  5. Data mining concepts and techniques

    CERN Document Server

    Han, Jiawei

    2005-01-01

    Our ability to generate and collect data has been increasing rapidly. Not only are all of our business, scientific, and government transactions now computerized, but the widespread use of digital cameras, publication tools, and bar codes also generate data. On the collection side, scanned text and image platforms, satellite remote sensing systems, and the World Wide Web have flooded us with a tremendous amount of data. This explosive growth has generated an even more urgent need for new techniques and automated tools that can help us transform this data into useful information and knowledge.Like the first edition, voted the most popular data mining book by KD Nuggets readers, this book explores concepts and techniques for the discovery of patterns hidden in large data sets, focusing on issues relating to their feasibility, usefulness, effectiveness, and scalability. However, since the publication of the first edition, great progress has been made in the development of new data mining methods, systems, and app...

  6. Data mining and visualization techniques

    Science.gov (United States)

    Wong, Pak Chung [Richland, WA; Whitney, Paul [Richland, WA; Thomas, Jim [Richland, WA

    2004-03-23

    Disclosed are association rule identification and visualization methods, systems, and apparatus. An association rule in data mining is an implication of the form X.fwdarw.Y where X is a set of antecedent items and Y is the consequent item. A unique visualization technique that provides multiple antecedent, consequent, confidence, and support information is disclosed to facilitate better presentation of large quantities of complex association rules.

  7. Recovery of a mining-damaged stream ecosystem

    Science.gov (United States)

    Mebane, Christopher A.; Eakins, Robert J.; Fraser, Brian G.; Adams, William J.

    2015-01-01

    This paper presents a 30+ year record of changes in benthic macroinvertebrate communities and fish populations associated with improving water quality in mining-influenced streams. Panther Creek, a tributary to the Salmon River in central Idaho, USA suffered intensive damage from mining and milling operations at the Blackbird Mine that released copper (Cu), arsenic (As), and cobalt (Co) into tributaries. From the 1960s through the 1980s, no fish and few aquatic invertebrates could be found in 40 km of mine-affected reaches of Panther Creek downstream of the metals contaminated tributaries, Blackbird and Big Deer Creeks.

  8. Mining Frequent Item Sets in Asynchronous Transactional Data Streams over Time Sensitive Sliding Windows Model

    International Nuclear Information System (INIS)

    Javaid, Q.; Memon, F.; Talpur, S.; Arif, M.; Awan, M.D.

    2016-01-01

    EPs (Extracting Frequent Patterns) from the continuous transactional data streams is a challenging and critical task in some of the applications, such as web mining, data analysis and retail market, prediction and network monitoring, or analysis of stock market exchange data. Many algorithms have been developed previously for mining FPs (Frequent Patterns) from a data stream. Such algorithms are currently highly required to develop new solutions and approaches to the precise handling of data streams. New techniques, solutions, or approaches are developed to address unbounded, ordered, and continuous sequences of data and for the generation of data at a rapid speed from data streams. Hence, extracting FPs using fresh or recent data involves the high-level analysis of data streams. We have suggested an efficient technique for the window sliding model; this technique extracts new and fresh FPs from high-speed data streams. In this study, a CPILT (Compacted Tree Compact Pattern Tree) is developed to capture the latest contents in the stream and to efficiently remove outdated contents from the data stream. The main concept introduced in this work on CPILT is the dynamic restructuring of a tree, which is helpful in producing a compacted tree and the frequency descending structure of a tree on runtime. With the help of the mining technique of FP growth, a complete list of new and fresh FPs is obtained from a CPILT using an existing window. The memory usage and time complexity of the latest FPs in high-speed data streams can efficiently be determined through proper experimentation and analysis. (author)

  9. Uranium evaluation and mining techniques

    International Nuclear Information System (INIS)

    1980-01-01

    accurate, comprehensive, and understandable appraisal of the world's potential uranium resources, and the ability to discover, develop and produce these resources within an acceptable time frame are absolutely essential to making meaningful decisions in relation to the future supply of nuclear fuel. Therefore, the methods used to appraise undiscovered uranium resources were examined and compared in the light of the needs of the world nuclear power industry as a whole. Notable among these methods is one based on interactive genetic models. It is currently being developed to reduce the amount of subjectivity inherent in most of the currently used appraisal techniques The goal is to use more geologic data and depend less on the intuition and experience of the estimator. The more esoteric statistical techniques based on past production rates, prices, rates of increase or decrease in reported reserves or resources, etc., while of unknown or unproved value, were not discussed at the symposium. The symposium provided a forum for discussion of closely related subjects as well. One of the major problems in reporting internationally in uranium resources is classification of the resources into various categories and defining those categories. Conceptually, among earth scientists, there is general agreement, but defining these concepts is a difficult task. At least three organizations have undertaken to develop classifications and definitions to satisfy the needs of international reporting. Two of these were described at the symposium. (The third has been used by the joint NEA/IAEA Working Party on Uranium Resources but was not described.) The techniques of winning uranium from its several sources include, besides mining by conventional open pit or underground methods, in situ leaching of low-grade ores in special environments, and from ores left in mines In addition, virtually all marine phosphates contain some uranium that can be recovered as a by-product in the manufacture of

  10. Zips : mining compressing sequential patterns in streams

    NARCIS (Netherlands)

    Hoang, T.L.; Calders, T.G.K.; Yang, J.; Mörchen, F.; Fradkin, D.; Chau, D.H.; Vreeken, J.; Leeuwen, van M.; Faloutsos, C.

    2013-01-01

    We propose a streaming algorithm, based on the minimal description length (MDL) principle, for extracting non-redundant sequential patterns. For static databases, the MDL-based approach that selects patterns based on their capacity to compress data rather than their frequency, was shown to be

  11. Opportunities for membrane technologies in the treatment of mining and mineral process streams and effluents

    International Nuclear Information System (INIS)

    Awadalla, F.T.; Kumar, A.

    1994-01-01

    The membrane separation technologies of microfiltration, ultrafiltration, nanofiltration, and reverse osmosis are suitable for treating many dilute streams and effluents generated in mining and mineral processing. Membrane technologies are capable of treating these dilute streams in order to produce clean permeate water for recycle and a concentrate that can potentially be used for valuable metals recovery. Membrane technologies can be utilized alone, or in combination with other techniques as a polishing step, in these separation processes. A review of potential applications of membranes for the treatment of different process streams and effluents for water recycling and pollution control is given here. Although membranes may not be optimum in all applications, these technologies are recognized in the mining sector for the many potential advantages they can provide. 59 refs

  12. Riffle zoobenthos in streams receiving acid mine drainage

    Energy Technology Data Exchange (ETDEWEB)

    Koryak, M; Shapiro, M A; Sykora, J L

    1972-01-01

    The bottom fauna of a stream polluted by acid mine drainage, was studied, using the standard methods of sample collecting. In localities immediately influenced by mine drainage, where very low pH values and high acidities prevail, the effect of acid mine wastes on the ecology and composition of the benthic fauna is, in general, similar to the effect of organic pollution. In these areas we found high numbers of individuals comprised of a few species. In the zones of active neutralization, where iron hydroxides are deposited, species diversity slightly increases but the biomass is very low. The most numerous invertebrates in the stream sections exhibiting high acidity and low pH are midge larvae, especially Tendipes gr. riparius. The number of insect groups present increases steadily with progressive neutralization until crustacea (amphipoda) and oligochaeta appear, indicating considerable improvement in water quality. The supply of desirable benthic fish food (Tendipes ssp.) is very high in the parts of the stream where low pH, high acidity, and high ferrous iron concentrations prevail. Unfortunately, fish cannot survive under these conditions to utilize this abundant food supply. On the other hand, in the less acidic zones, where fish could possibly survive, the deposition of ferric iron drastically diminishes the total biomass of benthic organisms and therefore severely limits fish populations.

  13. In situ solution mining technique

    International Nuclear Information System (INIS)

    Learmont, R.P.

    1978-01-01

    A method of in situ solution mining is disclosed in which a primary leaching process employing an array of 5-spot leaching patterns of production and injection wells is converted to a different pattern by converting to injection wells all the production wells in alternate rows

  14. Event Streams Clustering Using Machine Learning Techniques

    Directory of Open Access Journals (Sweden)

    Hanen Bouali

    2015-10-01

    Full Text Available Data streams are usually of unbounded lengths which push users to consider only recent observations by focusing on a time window, and ignore past data. However, in many real world applications, past data must be taken in consideration to guarantee the efficiency, the performance of decision making and to handle data streams evolution over time. In order to build a selectively history to track the underlying event streams changes, we opt for the continuously data of the sliding window which increases the time window based on changes over historical data. In this paper, to have the ability to access to historical data without requiring any significant storage or multiple passes over the data. In this paper, we propose a new algorithm for clustering multiple data streams using incremental support vector machine and data representative points’ technique. The algorithm uses a sliding window model for the most recent clustering results and data representative points to model the old data clustering results. Our experimental results on electromyography signal show a better clustering than other present in the literature

  15. Recovery of a mining-damaged stream ecosystem

    Directory of Open Access Journals (Sweden)

    Christopher A. Mebane

    2015-03-01

    Full Text Available Abstract This paper presents a 30+ year record of changes in benthic macroinvertebrate communities and fish populations associated with improving water quality in mining-influenced streams. Panther Creek, a tributary to the Salmon River in central Idaho, USA suffered intensive damage from mining and milling operations at the Blackbird Mine that released copper (Cu, arsenic (As, and cobalt (Co into tributaries. From the 1960s through the 1980s, no fish and few aquatic invertebrates could be found in 40 km of mine-affected reaches of Panther Creek downstream of the metals contaminated tributaries, Blackbird and Big Deer Creeks. Efforts to restore water quality began in 1995, and by 2002 Cu levels had been reduced by about 90%, with incremental declines since. Rainbow Trout (Oncorhynchus mykiss were early colonizers, quickly expanding their range as areas became habitable when Cu concentrations dropped below about 3X the U.S. Environmental Protection Agency’s biotic ligand model (BLM based chronic aquatic life criterion. Anadromous Chinook Salmon (O. tshawytscha and steelhead (O. mykiss have also reoccupied Panther Creek. Full recovery of salmonid populations occurred within about 12-years after the onset of restoration efforts and about 4-years after the Cu chronic criteria had mostly been met, with recovery interpreted as similarity in densities, biomass, year class strength, and condition factors between reference sites and mining-influenced sites. Shorthead Sculpin (Cottus confusus were slower than salmonids to disperse and colonize. While benthic macroinvertebrate biomass has increased, species richness has plateaued at about 70 to 90% of reference despite the Cu criterion having been met for several years. Different invertebrate taxa had distinctly different recovery trajectories. Among the slowest taxa to recover were Ephemerella, Cinygmula and Rhithrogena mayflies, Enchytraeidae oligochaetes, and Heterlimnius aquatic beetles. Potential

  16. Personnel Audit Using a Forensic Mining Technique

    OpenAIRE

    Adesesan B. Adeyemo; Oluwafemi Oriola

    2010-01-01

    This paper applies forensic data mining to determine the true status of employees and thereafter provide useful evidences for proper administration of administrative rules in a Typical Nigerian Teaching Service. The conventional technique of personnel audit was studied and a new technique for personnel audit was modeled using Artificial Neural Networks and Decision Tree algorithms. Atwo-layer classifier architecture was modeled. The outcome of the experiment proved that Radial Basis Function ...

  17. Data Mining Techniques for Customer Relationship Management

    Science.gov (United States)

    Guo, Feng; Qin, Huilin

    2017-10-01

    Data mining have made customer relationship management (CRM) a new area where firms can gain a competitive advantage, and play a key role in the firms’ management decision. In this paper, we first analyze the value and application fields of data mining techniques for CRM, and further explore how data mining applied to Customer churn analysis. A new business culture is developing today. The conventional production centered and sales purposed market strategy is gradually shifting to customer centered and service purposed. Customers’ value orientation is increasingly affecting the firms’. And customer resource has become one of the most important strategic resources. Therefore, understanding customers’ needs and discriminating the most contributed customers has become the driving force of most modern business.

  18. Integrating Data Mining Techniques into Telemedicine Systems

    Directory of Open Access Journals (Sweden)

    Mihaela GHEORGHE

    2014-01-01

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

  19. Effect of Strip Mining on Water Quality in Small Streams in Eastern Kentucky, 1967-1975

    Science.gov (United States)

    Kenneth L. Dyer; Willie R. Curtis

    1977-01-01

    Eight years of streamflow data are analyzed to show the effects of strip mining on chemical quality of water in six first-order streams in Breathitt County, Kentucky. All these watersheds were unmined in August, 1967, but five have since been strip mined. The accumulated data from this case history study indicate that strip mining causes large increases in the...

  20. Influence of acid mine drainage on microbial communities in stream and groundwater samples at Guryong Mine, South Korea

    Science.gov (United States)

    Kim, Jaisoo; Koo, So-Yeon; Kim, Ji-Young; Lee, Eun-Hee; Lee, Sang-Don; Ko, Kyung-Seok; Ko, Dong-Chan; Cho, Kyung-Suk

    2009-10-01

    The effects of acid mine drainage (AMD) in a stream and groundwater near an abandoned copper mine were characterized by physicochemical properties, bacterial community structure using denaturing gel gradient electrophoresis (DGGE), and microbial activity/diversity using Ecoplate technique. Based on DGGE fingerprints, the eubacterial community structures grouped into the stream water (GRS1, GRS2 and GRS3) and groundwater samples (GW1 and GW2), apparently based on differences in water temperature and the concentrations of dissolved oxygen, nitrate and sulfate. The most highly AMD-contaminated sample (GRS1) had additional α-Proteobacteria whereas the groundwater samples included additional β-Proteobacteria, suggesting the development of populations resistant to AMD toxicity under aerobic and anaerobic conditions, respectively. Community level physiological activities on the 31 Ecoplate substrates suggested that the activities decreased with increasing concentrations of sulfate and heavy metals derived from AMD. The Shannon index showed that microbial diversity was greatest in GRS2, and lowest in GRS1, and was probably related to the level of AMD.

  1. Semantic Web Requirements through Web Mining Techniques

    OpenAIRE

    Hassanzadeh, Hamed; Keyvanpour, Mohammad Reza

    2012-01-01

    In recent years, Semantic web has become a topic of active research in several fields of computer science and has applied in a wide range of domains such as bioinformatics, life sciences, and knowledge management. The two fast-developing research areas semantic web and web mining can complement each other and their different techniques can be used jointly or separately to solve the issues in both areas. In addition, since shifting from current web to semantic web mainly depends on the enhance...

  2. A distributed approach for optimizing cascaded classifier topologies in real-time stream mining systems.

    Science.gov (United States)

    Foo, Brian; van der Schaar, Mihaela

    2010-11-01

    In this paper, we discuss distributed optimization techniques for configuring classifiers in a real-time, informationally-distributed stream mining system. Due to the large volume of streaming data, stream mining systems must often cope with overload, which can lead to poor performance and intolerable processing delay for real-time applications. Furthermore, optimizing over an entire system of classifiers is a difficult task since changing the filtering process at one classifier can impact both the feature values of data arriving at classifiers further downstream and thus, the classification performance achieved by an ensemble of classifiers, as well as the end-to-end processing delay. To address this problem, this paper makes three main contributions: 1) Based on classification and queuing theoretic models, we propose a utility metric that captures both the performance and the delay of a binary filtering classifier system. 2) We introduce a low-complexity framework for estimating the system utility by observing, estimating, and/or exchanging parameters between the inter-related classifiers deployed across the system. 3) We provide distributed algorithms to reconfigure the system, and analyze the algorithms based on their convergence properties, optimality, information exchange overhead, and rate of adaptation to non-stationary data sources. We provide results using different video classifier systems.

  3. Impact of potash mining in streams: the Llobregat basin (northeast Spain as a case study

    Directory of Open Access Journals (Sweden)

    Ruben Ladrera

    2016-12-01

    Full Text Available Potash mining is significantly increasing the salt concentration of rivers and streams due to lixiviates coming from the mine tailings. In the present study, we have focused on the middle Llobregat basin (northeast Spain, where an important potash mining activity exists from the beginning of the XX century. Up to 50 million tonnes of saline waste have been disposed in the area, mainly composed of sodium chloride. We assessed the ecological status of streams adjacent to the mines by studying different physicochemical and hydromorphological variables, as well as aquatic macroinvertebrates. We found extraordinary high values of salinity in the studied streams, reaching conductivities up to 132.4 mS/cm. Salt-polluted streams were characterized by a deterioration of the riparian vegetation and the fluvial habitat. Both macroinvertebrate richness and abundance decreased with increasing salinity. In the most polluted stream only two families of macroinvertebrates were found: Ephydridae and Ceratopogonidae. According to the biotic indices IBMWP and IMMi-T, none of the sites met the requirements of the Water Framework Directive (WFD; i.e., good ecological status. Overall, we can conclude that potash-mining activities have the potential to cause severe ecological damage to their surrounding streams. This is mainly related to an inadequate management of the mine tailings, leading to highly saline runoff and percolates entering surface waters. Thus, we urge water managers and policy makers to take action to prevent, detect and remediate salt pollution of rivers and streams in potash mining areas.

  4. Concentration-Discharge Behavior of Contaminants in a Stream Impacted by Acid Mine Drainage

    Science.gov (United States)

    Shaw, M. E.; Klein, M.; Herndon, E.

    2017-12-01

    Acid mine drainage (AMD) has severely degraded streams throughout the Appalachian coal region of the United States. AMD occurs when pyrite contained in coal is exposed to water and air during mining activities and oxidized to release high concentrations of sulfate, metals, and acidity into water bodies. Little is known about the concentration-discharge (CQ) relationships of solutes in AMD-impacted streams due to the complicated nature of acid mine drainage systems. For example, streams may receive inputs from multiple sources that include runoff, constructed treatment systems, and abandoned mines that bypass these systems to continue to contaminate the streams. It is important to understand the CQ relationships of contaminants in AMD-impacted streams in order to elucidate contaminant sources and to predict effects on aquatic ecosystems. Here, we study the CQ behaviors of acid and metals in a contaminated watershed in northeastern Ohio where limestone channels have been installed to remediate water draining from a mine pool into the stream. Stream chemistry was measured in samples collected once per day or once per hour during storm events, and stream flow was measured continuously at the watershed outlet. Increases in stream velocity during storm events resulted in an increase in pH (from 3 to 6) that subsequently decreased back to 3 as flow decreased. Additionally, Fe and Mn concentrations in the stream were high during baseflow (7 and 15 mg/L, respectively) and decreased with increasing discharge during storm events. These results indicate that the treatment system is only effective at neutralizing stream acidity and removing metals when water flow through the limestone channel is continuous. We infer that the acidic and metal-rich baseflow derives from upwelling of contaminated groundwater or subsurface flow from a mine pool. Ongoing studies aim to isolate the source of this baseflow contamination and evaluate the geochemical transformations that occur as it

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2014-02-01

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

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

    International Nuclear Information System (INIS)

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

    2014-01-01

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

  7. The impact of episodic coal mine drainage pollution on benthic macroinvertebrates in streams in the Anthracite region of Pennsylvania

    International Nuclear Information System (INIS)

    MacCausland, A.; McTammany, M.E.

    2007-01-01

    Episodic coal mine drainage, caused by fluctuations in mine discharges relative to stream flow, has devastating effects on aquatic macroinvertebrate communities. Seven stream reaches in the Anthracite region of Pennsylvania were identified as chronically, episodically or not impaired by mine drainage, and sampled seasonally for 1 year to determine the effect of episodic mine drainage on macroinvertebrates. Specific conductance fluctuated seasonally in episodic sites; it was lower in winter when discharge increased and higher in summer when discharges decreased and mine drainage made up a larger proportion of stream flow. Although we hypothesized that episodic streams would have higher macroinvertebrate richness than chronic streams, comparisons showed no differences in richness between treatments. Episodic pollution may result from undersized or poorly maintained passive treatment systems; therefore, intensive macroinvertebrate monitoring may be needed to identify streams being affected by episodic mine drainage because macroinvertebrate richness may be sensitive to water quality fluctuations. - Episodic coal mine pollution decreases benthic macroinvertebrate richness and density

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

    Science.gov (United States)

    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…

  9. DATA MINING TECHNIQUES FOR EDUCATIONAL DATA: A REVIEW

    OpenAIRE

    Pragati Sharma; Dr. Sanjiv Sharma

    2018-01-01

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

  10. Detecting Internet Worms Using Data Mining Techniques

    Directory of Open Access Journals (Sweden)

    Muazzam Siddiqui

    2008-12-01

    Full Text Available Internet worms pose a serious threat to computer security. Traditional approaches using signatures to detect worms pose little danger to the zero day attacks. The focus of malware research is shifting from using signature patterns to identifying the malicious behavior displayed by the malwares. This paper presents a novel idea of extracting variable length instruction sequences that can identify worms from clean programs using data mining techniques. The analysis is facilitated by the program control flow information contained in the instruction sequences. Based upon general statistics gathered from these instruction sequences we formulated the problem as a binary classification problem and built tree based classifiers including decision tree, bagging and random forest. Our approach showed 95.6% detection rate on novel worms whose data was not used in the model building process.

  11. A study of the use of seeded ultrafiltration for the treatment of Thorium-uranium mining waste streams

    International Nuclear Information System (INIS)

    El-Sourougy, M.R.; Hooper, E.W.

    1994-01-01

    The use of seeded ultrafiltration for the treatment of radioactive waste streams arising from the nuclear industry has demonstrated its high potential as an efficient process for the removal of radionuclides present in the radwaste streams. The experimental data on simulated mining streams has given indications on the suitability of this technique for the treatment of mining waste streams. The results also show that the proper choice of absorbers can reduce not only the radioactivity level but also remove most of the products of both the thorium and uranium decay series. Decontamination factor (DF) for the system using manganese dioxide (MnO 2 ) are only slightly affected by the preparation method. On the contrary, the DF achieved using titanium hydroxide (HTiO) absorber was found to be dependent on the preparation method. The experimental data shows that total activity levels can be reduced to below detection limit (3E-3Bq/ml). The extent of decontamination of thorium containing waste streams was found to be dependent on the absorber used; in the order Diuranate > HTiO > Fe(OH) 3 > MnO 2 . The use of HTiO reduced the decay product activity of almost all the thorium daughters to nearly background levels. A DF of the order of 300 can easily be achieved using diuranate floc

  12. Arsenic partitioning among particle-size fractions of mine wastes and stream sediments from cinnabar mining districts.

    Science.gov (United States)

    Silva, Veronica; Loredo, Jorge; Fernández-Martínez, Rodolfo; Larios, Raquel; Ordóñez, Almudena; Gómez, Belén; Rucandio, Isabel

    2014-10-01

    Tailings from abandoned mercury mines represent an important pollution source by metals and metalloids. Mercury mining in Asturias (north-western Spain) has been carried out since Roman times until the 1970s. Specific and non-specific arsenic minerals are present in the paragenesis of the Hg ore deposit. As a result of intensive mining operations, waste materials contain high concentrations of As, which can be geochemically dispersed throughout surrounding areas. Arsenic accumulation, mobility and availability in soils and sediments are strongly affected by the association of As with solid phases and granular size composition. The objective of this study was to examine phase associations of As in the fine grain size subsamples of mine wastes (La Soterraña mine site) and stream sediments heavily affected by acid mine drainage (Los Rueldos mine site). An arsenic-selective sequential procedure, which categorizes As content into seven phase associations, was applied. In spite of a higher As accumulation in the finest particle-size subsamples, As fractionation did not seem to depend on grain size since similar distribution profiles were obtained for the studied granulometric fractions. The presence of As was relatively low in the most mobile forms in both sites. As was predominantly linked to short-range ordered Fe oxyhydroxides, coprecipitated with Fe and partially with Al oxyhydroxides and associated with structural material in mine waste samples. As incorporated into short-range ordered Fe oxyhydroxides was the predominant fraction at sediment samples, representing more than 80% of total As.

  13. Mercury speciation on three European mining districts by XANES techniques

    Science.gov (United States)

    Esbri, J. M.; Garcia-Noguero, E. M.; Guerrero, B.; Kocman, D.; Bernaus, A.; Gaona, X.; Higueras, P.; Alvarez, R.; Loredo, J.; Horvat, M.; Ávila, M.

    2009-04-01

    The mobility, bioavailability and toxicity of mercury in the environment depend on the chemical species in which is present in soil, sediments, water or air. In this work we used synchrotron radiation to determine mercury species in geological samples of three mercury mining districts: Almadén (Spain), Idria (Slovenia) and Asturias (Spain). The aim of this study was to find differences on mobility and bioavailability of mercury on three mining districts with different type of mineralization. For this porpoises we selected samples of ore, calcines, soils and stream sediments from the three sites, completely characterized by the Almadén School of Mines, Josef Stefan Institute of Ljubljana and Oviedo School of Mines. Speciation of mercury was carried out on Synchrotron Laboratories of Hamburg (HASYLAB) by XANES techniques. Spectra of pure compounds [HgCl2, HgSO4, HgO, CH3HgCl, Hg2Cl2 (calomel), HgSred (cinnabar), HgSblack (metacinnabar), Hg2NCl0.5(SO4)0.3(MoO4)0.1(CO3)0.1(H2O) (mosesite), Hg3S2Cl2 (corderoite), Hg3(SO4)O2 (schuetteite) y Hg2ClO (terlinguaite)] were obtained on transmittance mode. The number and type of the compounds required to reconstruct experimental spectra for each sample was obtained by PCA analysis and linear fitting of minimum quadratics of the pure compounds spectra. This offers a semiquantitative approach to the mineralogical constitution of each analyzed sample. The results put forward differences on the efficiency of roasting furnaces from the three studied sites, evidenced by the presence of metacinnabar on the less efficient (Almadén and Asturias) and absence on the most efficient (Idria). For the three studied sites, sulfide species (cinnabar and metacinnabar) were largely more abundant than soluble species (chlorides and sulfates). On the other hand, recent results on the mobility of both Hg and As on the target sites will be presented. These results correlate with the related chemical species found by XANES techniques.

  14. Real-Time Clinical Decision Support System with Data Stream Mining

    Directory of Open Access Journals (Sweden)

    Yang Zhang

    2012-01-01

    Full Text Available This research aims to describe a new design of data stream mining system that can analyze medical data stream and make real-time prediction. The motivation of the research is due to a growing concern of combining software technology and medical functions for the development of software application that can be used in medical field of chronic disease prognosis and diagnosis, children healthcare, diabetes diagnosis, and so forth. Most of the existing software technologies are case-based data mining systems. They only can analyze finite and structured data set and can only work well in their early years and can hardly meet today's medical requirement. In this paper, we describe a clinical-support-system based data stream mining technology; the design has taken into account all the shortcomings of the existing clinical support systems.

  15. Data Mining Practical Machine Learning Tools and Techniques

    CERN Document Server

    Witten, Ian H; Hall, Mark A

    2011-01-01

    Data Mining: Practical Machine Learning Tools and Techniques offers a thorough grounding in machine learning concepts as well as practical advice on applying machine learning tools and techniques in real-world data mining situations. This highly anticipated third edition of the most acclaimed work on data mining and machine learning will teach you everything you need to know about preparing inputs, interpreting outputs, evaluating results, and the algorithmic methods at the heart of successful data mining. Thorough updates reflect the technical changes and modernizations that have taken place

  16. Stream and floodplain restoration in a riparian ecosystem disturbed by placer mining

    Science.gov (United States)

    Karle, Kenneth F.; Densmore, Roseann V.

    1994-01-01

    Techniques for the hydrologic restoration of placer-mined streams and floodplains were developed in Denali National Park and Preserve Alaska, USA. The hydrologic study focused on a design of stream and floodplain geometry using hydraulic capacity and shear stress equations. Slope and sinuosity values were based on regional relationships. Design requirements include a channel capacity for a 1.5-year (bankfull) discharge and a floodplain capacity for a 1.5- to 100-year discharge. Concern for potential damage to the project from annual flooding before natural revegetation occurs led to development of alder (Alnus crispa) brush bars to dissipate floodwater energy and encourage sediment deposition. The brush bars, constructed of alder bundles tied together and anchored laterally adjacent to the channel, were installed on the floodplain in several configurations to test their effectiveness. A moderate flood near the end of the two-year construction phase of the project provided data on channel design, stability, floodplain erosion, and brush bar effectiveness. The brush bars provided substantial protection, but unconsolidated bank material and a lack of bed armour for a new channel segment led to some bank erosion, slope changes and an increase in sinuosity in several reaches of the study area.

  17. Restoration as mitigation: analysis of stream mitigation for coal mining impacts in southern Appalachia.

    Science.gov (United States)

    Palmer, Margaret A; Hondula, Kelly L

    2014-09-16

    Compensatory mitigation is commonly used to replace aquatic natural resources being lost or degraded but little is known about the success of stream mitigation. This article presents a synthesis of information about 434 stream mitigation projects from 117 permits for surface mining in Appalachia. Data from annual monitoring reports indicate that the ratio of lengths of stream impacted to lengths of stream mitigation projects were <1 for many projects, and most mitigation was implemented on perennial streams while most impacts were to ephemeral and intermittent streams. Regulatory requirements for assessing project outcome were minimal; visual assessments were the most common and 97% of the projects reported suboptimal or marginal habitat even after 5 years of monitoring. Less than a third of the projects provided biotic or chemical data; most of these were impaired with biotic indices below state standards and stream conductivity exceeding federal water quality criteria. Levels of selenium known to impair aquatic life were reported in 7 of the 11 projects that provided Se data. Overall, the data show that mitigation efforts being implemented in southern Appalachia for coal mining are not meeting the objectives of the Clean Water Act to replace lost or degraded streams ecosystems and their functions.

  18. Effects of coal mining, forestry, and road construction on southern Appalachian stream invertebrates and habitats.

    Science.gov (United States)

    Gangloff, Michael M; Perkins, Michael; Blum, Peter W; Walker, Craig

    2015-03-01

    Coal has been extracted via surface and sub-surface mining for decades throughout the Appalachian Mountains. New interest in ridge-top mining has raised concerns about possible waterway impacts. We examined effects of forestry, mining, and road construction-based disturbance on physico-chemistry and macroinvertebrate communities in east-central Tennessee headwater streams. Although 11 of 30 sites failed Tennessee's biocriteria scoring system, invertebrate richness was moderately high and we did not find significant differences in any water chemistry or habitat parameters between sites with passing and failing scores. However, conductivity and dissolved solid concentrations appeared elevated in the majority of study streams. Principal components (PCs) analysis indicated that six PCs accounted for ~77 % of among-site habitat variability. One PC associated with dissolved oxygen and specific conductance explained the second highest proportion of among-site variability after catchment area. Specific conductance was not correlated with catchment area but was strongly correlated with mining activity. Composition and success of multivariate models using habitat PCs to predict macroinvertebrate metrics was highly variable. PC scores associated with water chemistry and substrate composition were most frequently included in significant models. These results suggest that impacts of historical and current coal mining remain a source of water quality and macroinvertebrate community impairment in this region, but effects are subtle. Our results suggest that surface mining may have chronic and system-wide effects on habitat conditions and invertebrate communities in Cumberland Plateau streams.

  19. Improved streaming analysis technique: spherical harmonics expansion of albedo data

    International Nuclear Information System (INIS)

    Albert, T.E.; Simmons, G.L.

    1979-01-01

    An improved albedo scattering technique was implemented with a three-dimensional Monte Carlo transport code for use in analyzing radiation streaming problems. The improvement was based on a shifted spherical Harmonics expansion of the doubly differential albedo data base. The result of the improvement was a factor of 3 to 10 reduction in data storage requirements and approximately a factor of 3 to 6 increase in computational speed. Comparisons of results obtained using the technique with measurements are shown for neutron streaming in one- and two-legged square concrete ducts

  20. Simulation of land mine detection processes using nuclear techniques

    International Nuclear Information System (INIS)

    Aziz, M.

    2005-01-01

    A computer models were designed to study the processes of land mine detection using nuclear technique. Parameters that affect the detection were analyzed . Mines of different masses at different depths in the soil are considered using two types of sources , 252 C f and 14 MeV neutron source. The capability to differentiate between mines and other objects such as concrete , iron , wood , Aluminum ,water and polyethylene were analyzed and studied

  1. Uranium exploration, mining and ore enrichment techniques

    International Nuclear Information System (INIS)

    Fuchs, H.D.; Wentzlau, D.

    1985-01-01

    The paper describes the different types of uranium deposits and their importance. It is shown that during the present depressed uranium market situation, mainly high grade deposits such as unconformity-related deposits can be mined economically. The different successive exploration steps are outlined including methods used for uranium. Uranium mining does not greatly differ from normal mining, but the uranium metallurgy needs its own specialized but already classic technology. Only a relative small amount of uranium can be expected from projects where uranium is produced by in situ leach methods or by extraction from phosphoric acid. A short summary of investment costs and operating costs is given for an average uranium mine. The last chapter deals with the definition of different reserve categories and outlines the uranium reserves of the western world including the uranium production (1983) and the expected uranium production capacity for 1985 and 1990. (orig.) [de

  2. Incremental temporal pattern mining using efficient batch-free stream clustering

    NARCIS (Netherlands)

    Lu, Y.; Hassani, M.; Seidl, T.

    2017-01-01

    This paper address the problem of temporal pattern mining from multiple data streams containing temporal events. Temporal events are considered as real world events aligned with comprehensive starting and ending timing information rather than simple integer timestamps. Predefined relations, such as

  3. Arsenic transport in groundwater, surface water, and the hyporheic zone of a mine-influenced stream-aquifer system

    OpenAIRE

    Brown, Brendan

    2005-01-01

    We investigated the transport of dissolved arsenic in groundwater, surface water and the hyporheic zone in a stream-aquifer system influenced by an abandoned arsenopyrite mine. Mine tailing piles consisting of a host of arsenic-bearing minerals including arsenopyrite and scorodite remain adjacent to the stream and represent a continuous source of arsenic. Arsenic loads from the stream, springs, and groundwater were quantified at the study reach on nine dates from January to August 2005 and ...

  4. Effects of acid mine drainage on a headwater stream ecosystem in Colorado

    International Nuclear Information System (INIS)

    Niyogi, D.K.; Lewis, W.M. Jr.; McKnight, D.M.

    1994-01-01

    The ecological effects of acid mine drainage were investigated during the summer of 1993 on St. Kevin Gulch, a headwater stream near Leadville, Colorado. The stream currently receives acidic water from an abandoned mine. The pH downstream of the mine is between 3.5 and 4.5, and several metals exceed concentrations toxic to aquatic organisms. Zinc is present at especially high concentrations (1 to 10 mg/L) Furthermore, the stream bottom is covered with a thick layer of iron hydroxide precipitates. Effects on stream biota have been dramatic. Aquatic flora in the affected reach is limited to a green filamentous alga, Ulothrix subtilissima. Macroinvertebrate densities are significantly lower in the affected reach (mean = 99 indiv/m 2 ; SD = 88 indiv/M 2 ) compared to an upstream (pristine) reference reach (mean = 1,735 indiv/m 2 ; SD = 652 indiv/M 2 ). Functional processes were also studied in the stream. Net primary production (NPP) was measured during midday with recirculating chambers. Production was significantly lower in the affected reach (mean NPP 13.3 MgO 2 hr -1 m -2 ; SD = 87 MgO 2 hr -1 m -2 ) than the upstream reference reach (NPP = 64.1 MgO 2 hr -1 m -2 ; SD = 27.7 MgO 2 hr -1 m -2 ). Decomposition, measured with litter bags, was also lower in the affected reach than the upstream site. In 1994, St. Kevin Gulch is scheduled to undergo remediation that will treat the acidic water from the mine. Further studies on this stream will provide information on the recovery processes in lotic ecosystems

  5. Depauperate macroinvertebrates in a mine affected stream: Clean water may be the key to recovery

    International Nuclear Information System (INIS)

    Battaglia, M.; Hose, G.C.; Turak, E.; Warden, B.

    2005-01-01

    Acid mine drainage (AMD) is frequently linked with changes in macroinvertebrate assemblages, but the relative contribution of water and sediment to toxicity is equivocal. We have shown that the macroinvertebrate fauna of Neubecks Ck, a mine impacted stream in New South Wales, Australia, was much poorer than in two reference streams. Multivariate RELATE analyses indicated that the patterns in the biological data were more strongly correlated with the concentrations of common metals in the surface water than the pore water of these streams. From this we hypothesised that the water was more toxic to the biota than the sediment and we tested this hypothesis with a sediment transplant experiment. Sediment from Neubecks Ck that was placed in reference streams retained high concentrations of metals throughout the experiment, yet supported a macroinvertebrate assemblage similar to that in the reference streams. Sediment from the reference streams that was placed in Neubecks Ck supported few, if any, animals. This indicates that water in Neubecks Ck is toxic to biota, but that sediment is able to support aquatic biota in clean water. Therefore, remediation should focus on improving water quality rather than sediment quality. - Macroinvertebrates colonise contaminated sediment in clean water

  6. Stream-sediment geochemistry in mining-impacted streams: Prichard, Eagle, and Beaver creeks, northern Coeur d'Alene Mining District, northern Idaho

    Science.gov (United States)

    Box, Stephen E.; Wallis, John C.; Briggs, Paul H.; Brown, Zoe Ann

    2005-01-01

    This report presents the results of one aspect of an integrated watershed-characterization study that was undertaken to assess the impacts of historical mining and milling of silver-lead-zinc ores on water and sediment composition and on aquatic biota in streams draining the northern part of the Coeur d?Alene Mining District in northern Idaho. We present the results of chemical analyses of 62 samples of streambed sediment, 19 samples of suspended sediment, 23 samples of streambank soil, and 29 samples of mine- and mill-related artificial- fill material collected from the drainages of Prichard, Eagle, and Beaver Creeks, all tributaries to the North Fork of the Coeur d?Alene River. All samples were sieved into three grain-size fractions (Beaver Creek drainages has resulted in enrichments of lead, zinc, mercury, arsenic, cadmium, silver, copper, cobalt, and, to a lesser extent, iron and manganese in streambed sediment. Using samples collected from the relatively unimpacted West Fork of Eagle Creek as representative of background compositions, streambed sediment in the vicinity of the mines and millsites has Pb and Zn contents of 20 to 100 times background values, decreasing to 2 to 5 times background values at the mouth of the each stream, 15 to 20 km downstream. Lesser enrichments (<10 times background values) of mercury and arsenic also are generally associated with, and decrease downstream from, historical silver-lead-zinc mining in the drainages. However, enrichments of arsenic and, to a lesser extent, mercury also are areally associated with the lode gold deposits along Prichard Creek near Murray, which were not studied here. Metal contents in samples of unfractionated suspended sediment collected during a high-flow event in April 2000 are generally similar to, but slightly higher than, those in the fine (<0.063- mm grain size) fraction of streambed sediment from the same sampling site. Although metal enrichment in streambed sediment typically begins adjacent to

  7. Effects of remediation on the bacterial community of an acid mine drainage impacted stream.

    Science.gov (United States)

    Ghosh, Suchismita; Moitra, Moumita; Woolverton, Christopher J; Leff, Laura G

    2012-11-01

    Acid mine drainage (AMD) represents a global threat to water resources, and as such, remediation of AMD-impacted streams is a common practice. During this study, we examined bacterial community structure and environmental conditions in a low-order AMD-impacted stream before, during, and after remediation. Bacterial community structure was examined via polymerase chain reaction amplification of 16S rRNA genes followed by denaturing gradient gel electrophoresis. Also, bacterial abundance and physicochemical data (including metal concentrations) were collected and relationships to bacterial community structure were determined using BIO-ENV analysis. Remediation of the study stream altered environmental conditions, including pH and concentrations of some metals, and consequently, the bacterial community changed. However, remediation did not necessarily restore the stream to conditions found in the unimpacted reference stream; for example, bacterial abundances and concentrations of some elements, such as sulfur, magnesium, and manganese, were different in the remediated stream than in the reference stream. BIO-ENV analysis revealed that changes in pH and iron concentration, associated with remediation, primarily explained temporal alterations in bacterial community structure. Although the sites sampled in the remediated stream were in relatively close proximity to each other, spatial variation in community composition suggests that differences in local environmental conditions may have large impacts on the microbial assemblage.

  8. Mining Twitter Data Stream to Augment NASA GPM Validation

    Science.gov (United States)

    Teng, W. L.; Albayrak, A.; Huffman, G. J.; Vollmer, B.

    2017-12-01

    The Twitter data stream is an important new source of real-time and historical global information for potentially augmenting the validation program of NASA's Global Precipitation Measurement (GPM) mission. There have been other similar uses of Twitter, though mostly related to natural hazards monitoring and management. The validation of satellite precipitation estimates is challenging, because many regions lack data or access to data, especially outside of the U.S. and in remote and developing areas. The time-varying set of "precipitation" tweets can be thought of as an organic network of rain gauges, potentially providing a widespread view of precipitation occurrence. Twitter provides a large source of crowd for crowdsourcing. During a 24-hour period in the middle of the snow storm this past March in the U.S. Northeast, we collected more than 13,000 relevant precipitation tweets with exact geolocation. The overall objective of our project is to determine the extent to which processed tweets can provide additional information that improves the validation of GPM data. Though our current effort focuses on tweets and precipitation, our approach is general and applicable to other social media and other geophysical measurements. Specifically, we have developed an operational infrastructure for processing tweets, in a format suitable for analysis with GPM data; engaged with potential participants, both passive and active, to "enrich" the Twitter stream; and inter-compared "precipitation" tweet data, ground station data, and GPM retrievals. In this presentation, we detail the technical capabilities of our tweet processing infrastructure, including data abstraction, feature extraction, search engine, context-awareness, real-time processing, and high volume (big) data processing; various means for "enriching" the Twitter stream; and results of inter-comparisons. Our project should bring a new kind of visibility to Twitter and engender a new kind of appreciation of the value

  9. Working with text tools, techniques and approaches for text mining

    CERN Document Server

    Tourte, Gregory J L

    2016-01-01

    Text mining tools and technologies have long been a part of the repository world, where they have been applied to a variety of purposes, from pragmatic aims to support tools. Research areas as diverse as biology, chemistry, sociology and criminology have seen effective use made of text mining technologies. Working With Text collects a subset of the best contributions from the 'Working with text: Tools, techniques and approaches for text mining' workshop, alongside contributions from experts in the area. Text mining tools and technologies in support of academic research include supporting research on the basis of a large body of documents, facilitating access to and reuse of extant work, and bridging between the formal academic world and areas such as traditional and social media. Jisc have funded a number of projects, including NaCTem (the National Centre for Text Mining) and the ResDis programme. Contents are developed from workshop submissions and invited contributions, including: Legal considerations in te...

  10. Application of data mining techniques for nuclear data and instrumentation

    International Nuclear Information System (INIS)

    Toshniwal, Durga

    2013-01-01

    Data mining is defined as the discovery of previously unknown, valid, novel, potentially useful, and understandable patterns in large databases. It encompasses many different techniques and algorithms which differ in the kinds of data that can be analyzed and the form of knowledge representation used to convey the discovered knowledge. Patterns in the data can be represented in many different forms, including classification rules, association rules, clusters, etc. Data mining thus deals with the discovery of hidden trends and patterns from large quantities of data. The field of data mining is emerging as a new, fundamental research area with important applications to science, engineering, medicine, business, and education. It is an interdisciplinary research area and draws upon several roots, including database systems, machine learning, information systems, statistics and expert systems. Data mining, when performed on time series data, is known as time series data mining (TSDM). A time series is a sequence of real numbers, each number representing a value at a point of time. During the past few years, there has been an explosion of research in the area of time series data mining. This includes attempts to model time series data, to design languages to query such data, and to develop access structures to efficiently process queries on such data. Time series data arises naturally in many real-world applications. Efficient discovery of knowledge through time series data mining can be helpful in several domains such as: Stock market analysis, Weather forecasting etc. An important application area of data mining techniques is in nuclear power plant and related data. Nuclear power plant data can be represented in form of time sequences. Often it may be of prime importance to analyze such data to find trends and anomalies. The general goals of data mining include feature extraction, similarity search, clustering and classification, association rule mining and anomaly

  11. Evaluation of Metal Toxicity in Streams Affected by Abandoned Mine Lands, Upper Animas River Watershed, Colorado

    Science.gov (United States)

    Besser, John M.; Allert, Ann L.; Hardesty, Douglas K.; Ingersoll, Christopher G.; May, Thomas W.; Wang, Ning; Leib, Kenneth J.

    2001-01-01

    Acid drainage from abandoned mines and from naturally-acidic rocks and soil in the upper Animas River watershed of Colorado generates elevated concentrations of acidity and dissolved metals in stream waters and deposition of metal-contaminated particulates in streambed sediments, resulting in both toxicity and habitat degradation for stream biota. High concentrations of iron (Fe), aluminum (Al), zinc (Zn), copper (Cu), cadmium (Cd), and lead (Pb) occur in acid streams draining headwaters of the upper Animas River watershed, and high concentrations of some metals, especially Zn, persist in circumneutral reaches of the Animas River and Mineral Creek, downstream of mixing zones of acid tributaries. Seasonal variation of metal concentrations is reflected in variation in toxicity of stream water. Loadings of dissolved metals to the upper Animas River and tributaries are greatest during summer, during periods of high stream discharge from snowmelt and monsoonal rains, but adverse effects on stream biota may be greater during winter low-flow periods, when stream flows are dominated by inputs of groundwater and contain greatest concentrations of dissolved metals. Fine stream-bed sediments of the upper Animas River watershed also contain elevated concentrations of potentially toxic metals. Greatest sediment metal concentrations occur in the Animas River upstream from Silverton, where there are extensive deposits of mine and mill tailings, and in mixing zones in the Animas River and lower Mineral Creek, where precipitates of Fe and Al oxides also contain high concentrations of other metals. This report summarizes the findings of a series of toxicity studies in streams of the upper Animas River watershed, conducted on-site and in the laboratory between 1998 and 2000. The objectives of these studies were: (1) to determine the relative toxicity of stream water and fine stream-bed sediments to fish and invertebrates; (2) to determine the seasonal range of toxicity in stream

  12. Geochemistry of acid mine drainage from a coal mining area and processes controlling metal attenuation in stream waters, southern Brazil

    Directory of Open Access Journals (Sweden)

    VERIDIANA P. CAMPANER

    2014-06-01

    Full Text Available Acid drainage influence on the water and sediment quality was investigated in a coal mining area (southern Brazil. Mine drainage showed pH between 3.2 and 4.6 and elevated concentrations of sulfate, As and metals, of which, Fe, Mn and Zn exceeded the limits for the emission of effluents stated in the Brazilian legislation. Arsenic also exceeded the limit, but only slightly. Groundwater monitoring wells from active mines and tailings piles showed pH interval and chemical concentrations similar to those of mine drainage. However, the river and ground water samples of municipal public water supplies revealed a pH range from 7.2 to 7.5 and low chemical concentrations, although Cd concentration slightly exceeded the limit adopted by Brazilian legislation for groundwater. In general, surface waters showed large pH range (6 to 10.8, and changes caused by acid drainage in the chemical composition of these waters were not very significant. Locally, acid drainage seemed to have dissolved carbonate rocks present in the local stratigraphic sequence, attenuating the dispersion of metals and As. Stream sediments presented anomalies of these elements, which were strongly dependent on the proximity of tailings piles and abandoned mines. We found that precipitation processes in sediments and the dilution of dissolved phases were responsible for the attenuation of the concentrations of the metals and As in the acid drainage and river water mixing zone. In general, a larger influence of mining activities on the chemical composition of the surface waters and sediments was observed when enrichment factors in relation to regional background levels were used.

  13. Geochemistry of acid mine drainage from a coal mining area and processes controlling metal attenuation in stream waters, southern Brazil.

    Science.gov (United States)

    Campaner, Veridiana P; Luiz-Silva, Wanilson; Machado, Wilson

    2014-05-14

    Acid drainage influence on the water and sediment quality was investigated in a coal mining area (southern Brazil). Mine drainage showed pH between 3.2 and 4.6 and elevated concentrations of sulfate, As and metals, of which, Fe, Mn and Zn exceeded the limits for the emission of effluents stated in the Brazilian legislation. Arsenic also exceeded the limit, but only slightly. Groundwater monitoring wells from active mines and tailings piles showed pH interval and chemical concentrations similar to those of mine drainage. However, the river and ground water samples of municipal public water supplies revealed a pH range from 7.2 to 7.5 and low chemical concentrations, although Cd concentration slightly exceeded the limit adopted by Brazilian legislation for groundwater. In general, surface waters showed large pH range (6 to 10.8), and changes caused by acid drainage in the chemical composition of these waters were not very significant. Locally, acid drainage seemed to have dissolved carbonate rocks present in the local stratigraphic sequence, attenuating the dispersion of metals and As. Stream sediments presented anomalies of these elements, which were strongly dependent on the proximity of tailings piles and abandoned mines. We found that precipitation processes in sediments and the dilution of dissolved phases were responsible for the attenuation of the concentrations of the metals and As in the acid drainage and river water mixing zone. In general, a larger influence of mining activities on the chemical composition of the surface waters and sediments was observed when enrichment factors in relation to regional background levels were used.

  14. Comparative analysis of data mining techniques for business data

    Science.gov (United States)

    Jamil, Jastini Mohd; Shaharanee, Izwan Nizal Mohd

    2014-12-01

    Data mining is the process of employing one or more computer learning techniques to automatically analyze and extract knowledge from data contained within a database. Companies are using this tool to further understand their customers, to design targeted sales and marketing campaigns, to predict what product customers will buy and the frequency of purchase, and to spot trends in customer preferences that can lead to new product development. In this paper, we conduct a systematic approach to explore several of data mining techniques in business application. The experimental result reveals that all data mining techniques accomplish their goals perfectly, but each of the technique has its own characteristics and specification that demonstrate their accuracy, proficiency and preference.

  15. A STUDY OF TEXT MINING METHODS, APPLICATIONS,AND TECHNIQUES

    OpenAIRE

    R. Rajamani*1 & S. Saranya2

    2017-01-01

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

  16. Enhanced Landfill Mining case study: Innovative separation techniques

    Science.gov (United States)

    Cuyvers, Lars; Moerenhout, Tim; Helsen, Stefan; Van de Wiele, Katrien; Behets, Tom; Umans, Luk; Wille, Eddy

    2014-05-01

    In 2011, a corporate vision on Enhanced Landfill Mining (ELFM)1 was approved by the OVAM Board of directors, which resulted in an operational programme over the period 2011-2015. OVAM (Public Waste Agency of Flanders) is the competent authority in charge of waste, Sustainable Materials Management (SMM) and contaminated soil management in Flanders. The introduction of the ELFM concept needs to be related with the concept of SMM and the broader shift to a circular economy. Within the concept of ELFM, landfills are no longer considered to be a final and static situation, but a dynamic part of the materials cycle. The main goal of this research programme is to develop a comprehensive policy on resource management to deal with the issue of former landfills. In order to investigate the opportunities of ELFM, the OVAM is applying a three step approach including mapping, surveying and mining of these former landfills. As a result of the mapping part over 2,000 landfill sites, that will need to be dealt with, were revealed. The valorisation potential of ELFM could be assigned to different goals, according to the R³P-concept : Recycling of Materials, Recovery of Energy, Reclamation of Land and Protection of drinking water supply. . On behalf of the OVAM, ECOREM was assigned to follow-up a pilot case executed on a former landfill, located in Zuienkerke, Flanders. Within this case study some technical tests were carried out on the excavated waste material to investigate the possibilities for a waste to resource conversion. The performance of both on site and off site techniques were evaluated. These testings also contribute to the mapping part of OVAM's research programme on ELFM and reveal more information on the composition of former landfills dating from different era's. In order to recover as many materials as possible, five contractors were assigned to perform separation tests on the bulk material from the Zuienkerke landfill. All used techniques were described

  17. Fingerprinting two metal contaminants in streams with Cu isotopes near the Dexing Mine, China

    Energy Technology Data Exchange (ETDEWEB)

    Song, Shiming [Chinese Geological Survey, Nanjing Center, Nanjing (China); Mathur, Ryan, E-mail: mathurr@juniata.edu [Department of Geology, Juniata College, Huntingdon, PA (United States); Ruiz, Joaquin [Department of Geosciences, University of Arizona, Tucson, AZ (United States); Chen, Dandan [Chinese Geological Survey, Nanjing Center, Nanjing (China); Allin, Nicholas [Department of Geology, Juniata College, Huntingdon, PA (United States); Guo, Kunyi; Kang, Wenkai [Chinese Geological Survey, Nanjing Center, Nanjing (China)

    2016-02-15

    Transition metal isotope signatures are becoming useful for fingerprinting sources in surface waters. This study explored the use of Cu isotope values to trace dissolved metal contaminants in stream water throughout a watershed affected by mining by-products of the Dexing Mine, the largest porphyry Cu operation in Asia. Cu isotope values of stream water were compared to potential mineral sources of Cu in the mining operation, and to proximity to the known Cu sources. The first mineral source, chalcopyrite, CuFeS{sub 2} has a ‘tight’ cluster of Cu isotope values (− 0.15‰ to + 1.65‰; + 0.37 ± 0.6‰, 1σ, n = 10), and the second mineral source, pyrite (FeS{sub 2}), has a much larger range of Cu isotope values (− 4‰ to + 11.9‰; 2.7 ± 4.3‰, 1σ, n = 16). Dissolved Cu isotope values of stream water indicated metal derived from either chalcopyrite or pyrite. Above known Cu mineralization, stream waters are approximately + 1.5‰ greater than the average chalcopyrite and are interpreted as derived from weathering of chalcopyrite. In contrast, dissolved Cu isotope values in stream water emanating from tailings piles had Cu isotope values similar to or greater than pyrite (>+6‰, a common mineral in the tailings). These values are interpreted as sourced from the tailings, even in solutions that possess significantly lower concentrations of Cu (< 0.05 ppm). Elevated Cu isotope values were also found in two soil and two tailings samples (δ{sup 65}Cu ranging between + 2 to + 5‰). These data point to the mineral pyrite in tailings as the mineral source for the elevated Cu isotope values. Therefore, Cu isotope values of waters emanating from a clearly contaminated drainage possess different Cu isotope values, permitting the discrimination of Cu derived from chalcopyrite and pyrite in solution. Data demonstrate the utility of Cu isotopic values in waters, minerals, and soils to fingerprint metallic contamination for environmental problems. - Highlights:

  18. Ecology of endangered damselfly Coenagrion ornatum in post-mining streams in relation to their restoration

    OpenAIRE

    TICHÁNEK, Filip

    2016-01-01

    The thesis explores various aspects of ecology of endangered damselfly Coenagrion ornatum, the specialists for lowland headwaters, in post-mining streams of Radovesicka spoil. The first part of thesis is manuscript which has been already submitted in Journal of Insect Conservation. In the first part, we focused on population estimate of the local population using capture-recapture method, and explored its habitat requirements across life stages and spatial scales. In the next part, I assess m...

  19. Estimating benthic secondary production from aquatic insect emergence in streams affected by mountaintop removal coal mining, West Virginia USA

    Science.gov (United States)

    Mountaintop removal and valley fill (MTR/VF) coal mining recountours the Appalachian landscape, buries headwater stream channels, and degrades downstream water quality. The goal of this study was to compare benthic community production estimates, based on seasonal insect emergen...

  20. Mining top-k frequent closed itemsets in data streams using sliding window

    International Nuclear Information System (INIS)

    Rehman, Z.; Shahbaz, M.

    2013-01-01

    Frequent itemset mining has become a popular research area in data mining community since the last few years. T here are two main technical hitches while finding frequent itemsets. First, to provide an appropriate minimum support value to start and user need to tune this minimum support value by running the algorithm again and again. Secondly, generated frequent itemsets are mostly numerous and as a result a number of association rules generated are also very large in numbers. Applications dealing with streaming environment need to process the data received at high rate, therefore, finding frequent itemsets in data streams becomes complex. In this paper, we present an algorithm to mine top-k frequent closed itemsets using sliding window approach from streaming data. We developed a single-pass algorithm to find frequent closed itemsets of length between user's defined minimum and maximum- length. To improve the performance of algorithm and to avoid rescanning of data, we have transformed data into bitmap based tree data structure. (author)

  1. Natural stream flow-rates measurements by tracer techniques

    International Nuclear Information System (INIS)

    Cuellar Mansilla, J.

    1982-01-01

    This paper presents the study of the precision obtained measuring the natural stream flow rates by tracer techniques, especially when the system presents a great slope and a bed constituted by large and extended particle size. The experiences were realized in laboratory pilot channels with flow-rates between 15 and 130 [1/s]; and in natural streams with flow-rates from 1 to 25 m 3 /s. Tracer used were In-133m and Br-82 for laboratory and field measurements respectively. In both cases the tracer was injected as a pulse and its dilution measured collecting samples in the measured section, at constant flow-rates, of 5[1] in laboratory experiences and 60[1] of water in field experiences. Precisions obtained at a 95% confidence level were about 2% for laboratory and 3% for field. (I.V.)

  2. Review of Data Mining Techniques for Churn Prediction in Telecom

    Directory of Open Access Journals (Sweden)

    Vishal Mahajan

    2015-12-01

    service. This data can be usefully mined for churn analysis and prediction. Significant research had been undertaken by researchers worldwide to understand the data mining practices that can be used for predicting customer churn. This paper provides a review of around 100 recent journal articles starting from year 2000 to present the various data mining techniques used in multiple customer based churn models. It then summarizes the existing telecom literature by highlighting the sample size used, churn variables employed and the findings of different DM techniques. Finally, we list the most popular techniques for churn prediction in telecom as decision trees, regression analysis and clustering, thereby providing a roadmap to new researchers to build upon novel churn management models.

  3. Potential toxic elements in stream sediments, soils and waters in an abandoned radium mine (central Portugal).

    Science.gov (United States)

    Antunes, I M H R; Neiva, A M R; Albuquerque, M T D; Carvalho, P C S; Santos, A C T; Cunha, Pedro P

    2018-02-01

    The Alto da Várzea radium mine (AV) exploited ore and U-bearing minerals, such as autunite and torbernite. The mine was exploited underground from 1911 to 1922, closed in 1946 without restoration, and actually a commercial area is deployed. Stream sediments, soils and water samples were collected between 2008 and 2009. Stream sediments are mainly contaminated in As, Th, U and W, which is related to the AV radium mine. The PTEs, As, Co, Cr, Sr, Th, U, W, Zn, and electrical conductivity reached the highest values in soils collected inside the mine influence. Soils are contaminated with As and U and must not be used for any purpose. Most waters have pH values ranging from 4.3 to 6.8 and are poorly mineralized (EC = 41-186 µS/cm; TDS = 33-172 mg/L). Groundwater contains the highest Cu, Cr and Pb contents. Arsenic occurs predominantly as H 2 (AsO 4 ) - and H(AsO 4 ) 2- . Waters are saturated in goethite, haematite and some of them also in lepidocrocite and ferrihydrite, which adsorbs As (V). Lead is divalent in waters collected during the warm season, being mobile in these waters. Thorium occurs mainly as Th(OH) 3 (CO 3 ) - , Th(OH) 2 (CO 3 ) and Th(OH) 2 (CO 3 ) 2 2- , which increase water Th contents. Uranium occurs predominantly as UO 2 CO 3 , but CaUO 2 (CO 3 ) 3 2- and CaUO 2 (CO 3 ) 3 also occur, decreasing its mobility in water. The waters are contaminated in NO 2 - , Mn, Cu, As, Pb and U and must not be used for human consumption and in agricultural activities. The water contamination is mainly associated with the old radium mine and human activities. A restoration of the mining area with PTE monitoring is necessary to avoid a public hazard.

  4. Roles of Benthic Algae in the Structure, Function, and Assessment of Stream Ecosystems Affected by Acid Mine Drainage

    Science.gov (United States)

    Tens of thousands of stream kilometers around the world are degraded by a legacy of environmental impacts and acid mine drainage (AMD) caused by abandoned underground and surface mines, piles of discarded coal wastes, and tailings. Increased acidity, high concentrations of metals...

  5. Export of detritus and invertebrate from headwater streams: linking mountaintop removal and valley fill coal mining to downstream receiving waters

    Science.gov (United States)

    Mountaintop removal and valley fill (MTR/VF) coal mining has resulted in large scale alteration of the topography, reduced forest productivity, and burial of headwater streams in the U.S. Central Appalachians. Although MTR/VF coal mining has occurred for several decades and the ...

  6. Explaining and predicting workplace accidents using data-mining techniques

    International Nuclear Information System (INIS)

    Rivas, T.; Paz, M.; Martin, J.E.; Matias, J.M.; Garcia, J.F.; Taboada, J.

    2011-01-01

    Current research into workplace risk is mainly conducted using conventional descriptive statistics, which, however, fail to properly identify cause-effect relationships and are unable to construct models that could predict accidents. The authors of the present study modelled incidents and accidents in two companies in the mining and construction sectors in order to identify the most important causes of accidents and develop predictive models. Data-mining techniques (decision rules, Bayesian networks, support vector machines and classification trees) were used to model accident and incident data compiled from the mining and construction sectors and obtained in interviews conducted soon after an incident/accident occurred. The results were compared with those for a classical statistical techniques (logistic regression), revealing the superiority of decision rules, classification trees and Bayesian networks in predicting and identifying the factors underlying accidents/incidents.

  7. Explaining and predicting workplace accidents using data-mining techniques

    Energy Technology Data Exchange (ETDEWEB)

    Rivas, T., E-mail: trivas@uvigo.e [Dpto. Ingenieria de los Recursos Naturales y Medio Ambiente, E.T.S.I. Minas, University of Vigo, Campus Lagoas, 36310 Vigo (Spain); Paz, M., E-mail: mpaz.minas@gmail.co [Dpto. Ingenieria de los Recursos Naturales y Medio Ambiente, E.T.S.I. Minas, University of Vigo, Campus Lagoas, 36310 Vigo (Spain); Martin, J.E., E-mail: jmartin@cippinternacional.co [CIPP International, S.L. Parque Tecnologico de Asturias, Parcela 43, Oficina 11, 33428 Llanera (Spain); Matias, J.M., E-mail: jmmatias@uvigo.e [Dpto. Estadistica e Investigacion Operativa, E.T.S.I. Minas, University of Vigo, Campus Lagoas, 36310 Vigo (Spain); Garcia, J.F., E-mail: jgarcia@cippinternacional.co [CIPP International, S.L. Parque Tecnologico de Asturias, Parcela 43, Oficina 11, 33428 Llanera (Spain); Taboada, J., E-mail: jtaboada@uvigo.e [Dpto. Ingenieria de los Recursos Naturales y Medio Ambiente, E.T.S.I. Minas, University of Vigo, Campus Lagoas, 36310 Vigo (Spain)

    2011-07-15

    Current research into workplace risk is mainly conducted using conventional descriptive statistics, which, however, fail to properly identify cause-effect relationships and are unable to construct models that could predict accidents. The authors of the present study modelled incidents and accidents in two companies in the mining and construction sectors in order to identify the most important causes of accidents and develop predictive models. Data-mining techniques (decision rules, Bayesian networks, support vector machines and classification trees) were used to model accident and incident data compiled from the mining and construction sectors and obtained in interviews conducted soon after an incident/accident occurred. The results were compared with those for a classical statistical techniques (logistic regression), revealing the superiority of decision rules, classification trees and Bayesian networks in predicting and identifying the factors underlying accidents/incidents.

  8. Geochemical Characterization of Mine Waste, Mine Drainage, and Stream Sediments at the Pike Hill Copper Mine Superfund Site, Orange County, Vermont

    Science.gov (United States)

    Piatak, Nadine M.; Seal, Robert R.; Hammarstrom, Jane M.; Kiah, Richard G.; Deacon, Jeffrey R.; Adams, Monique; Anthony, Michael W.; Briggs, Paul H.; Jackson, John C.

    2006-01-01

    The Pike Hill Copper Mine Superfund Site in the Vermont copper belt consists of the abandoned Smith, Eureka, and Union mines, all of which exploited Besshi-type massive sulfide deposits. The site was listed on the U.S. Environmental Protection Agency (USEPA) National Priorities List in 2004 due to aquatic ecosystem impacts. This study was intended to be a precursor to a formal remedial investigation by the USEPA, and it focused on the characterization of mine waste, mine drainage, and stream sediments. A related study investigated the effects of the mine drainage on downstream surface waters. The potential for mine waste and drainage to have an adverse impact on aquatic ecosystems, on drinking- water supplies, and to human health was assessed on the basis of mineralogy, chemical concentrations, acid generation, and potential for metals to be leached from mine waste and soils. The results were compared to those from analyses of other Vermont copper belt Superfund sites, the Elizabeth Mine and Ely Copper Mine, to evaluate if the waste material at the Pike Hill Copper Mine was sufficiently similar to that of the other mine sites that USEPA can streamline the evaluation of remediation technologies. Mine-waste samples consisted of oxidized and unoxidized sulfidic ore and waste rock, and flotation-mill tailings. These samples contained as much as 16 weight percent sulfides that included chalcopyrite, pyrite, pyrrhotite, and sphalerite. During oxidation, sulfides weather and may release potentially toxic trace elements and may produce acid. In addition, soluble efflorescent sulfate salts were identified at the mines; during rain events, the dissolution of these salts contributes acid and metals to receiving waters. Mine waste contained concentrations of cadmium, copper, and iron that exceeded USEPA Preliminary Remediation Goals. The concentrations of selenium in mine waste were higher than the average composition of eastern United States soils. Most mine waste was

  9. Recommendation in Higher Education Using Data Mining Techniques

    Science.gov (United States)

    Vialardi, Cesar; Bravo, Javier; Shafti, Leila; Ortigosa, Alvaro

    2009-01-01

    One of the main problems faced by university students is to take the right decision in relation to their academic itinerary based on available information (for example courses, schedules, sections, classrooms and professors). In this context, this work proposes the use of a recommendation system based on data mining techniques to help students to…

  10. Assessing mercury exposure and effects to American dippers in headwater streams near mining sites.

    Science.gov (United States)

    Henny, Charles J; Kaiser, James L; Packard, Heidi A; Grove, Robert A; Taft, Michael R

    2005-10-01

    To evaluate mercury (Hg) exposure and possible adverse effects of Hg on American dipper (Cinclus mexicanus) reproduction, we collected eggs and nestling feathers and the larval/nymph form of three Orders of aquatic macroinvertebrates (Ephemeroptera, Plecoptera and Trichoptera = EPT) important in their diet from three major headwater tributaries of the upper Willamette River, Oregon in 2002. The Coast Fork Willamette River is contaminated with Hg due to historical cinnabar (HgS) mining at the Black Butte Mine; the Row River is affected by past gold-mining operations located within the Bohemia Mining District, where Hg was used in the amalgamation process to recover gold; and the Middle Fork Willamette River is the reference area with no known mining. Methyl mercury (MeHg) concentrations (geometric mean) in composite EPT larvae (111.9 ng/g dry weight [dw] or 19.8 ng/g wet weight [ww]), dipper eggs (38.5 ng/g ww) and nestling feathers (1158 ng/g ww) collected from the Coast Fork Willamette were significantly higher than MeHg concentrations in EPT and dipper samples from other streams. Total mercury (THg) concentrations in surface sediments along the same Hg-impacted streams were investigated by others in 1999 (Row River tributaries) and 2002 (Coast Fork). The reported sediment THg concentrations paralleled our biological findings. Dipper breeding territories at higher elevations had fewer second clutches; however, dipper reproductive success along all streams (including the lower elevation and most Hg-contaminated Coast Fork), was judged excellent compared to other studies reviewed. Furthermore, MeHg concentrations in EPT samples from this study were well below dietary concentrations in other aquatic bird species, such as loons and ducks, reported to cause Hg-related reproductive problems. Our data suggest that either dipper feathers or EPT composites used to project MeHg concentrations in dipper feathers (with biomagnification factor of 10-20x) may be used, but with

  11. Applying Supervised Opinion Mining Techniques on Online User Reviews

    Directory of Open Access Journals (Sweden)

    Ion SMEUREANU

    2012-01-01

    Full Text Available In recent years, the spectacular development of web technologies, lead to an enormous quantity of user generated information in online systems. This large amount of information on web platforms make them viable for use as data sources, in applications based on opinion mining and sentiment analysis. The paper proposes an algorithm for detecting sentiments on movie user reviews, based on naive Bayes classifier. We make an analysis of the opinion mining domain, techniques used in sentiment analysis and its applicability. We implemented the proposed algorithm and we tested its performance, and suggested directions of development.

  12. Summarizing of new techniques in uranium mining and metallurgy

    International Nuclear Information System (INIS)

    Wang Delin; Zhang Fei; Su Yanru; Zeng Yijun; Meng Jin

    2010-01-01

    According to character of national resources and uranium mining and metallurgical science and technology members research achievements, new techniques in ten scientific research area of in-situ leaching, heap leaching, multi-metal comprehensive recovery, bio-metallurgy etc. for 10 years is introduced in this paper. The level of innovation ability is shown by technical index, resources recovery and reduction capital cost etc. datum. The application bound of natural uranium resource is enlarged and production ability of national uranium is increased. It is put forward renovation and development ideas for uranium mining and metallurgy. (authors)

  13. Analysis of Occupational Accidents in Underground and Surface Mining in Spain Using Data-Mining Techniques.

    Science.gov (United States)

    Sanmiquel, Lluís; Bascompta, Marc; Rossell, Josep M; Anticoi, Hernán Francisco; Guash, Eduard

    2018-03-07

    An analysis of occupational accidents in the mining sector was conducted using the data from the Spanish Ministry of Employment and Social Safety between 2005 and 2015, and data-mining techniques were applied. Data was processed with the software Weka. Two scenarios were chosen from the accidents database: surface and underground mining. The most important variables involved in occupational accidents and their association rules were determined. These rules are composed of several predictor variables that cause accidents, defining its characteristics and context. This study exposes the 20 most important association rules in the sector-either surface or underground mining-based on the statistical confidence levels of each rule as obtained by Weka. The outcomes display the most typical immediate causes, along with the percentage of accidents with a basis in each association rule. The most important immediate cause is body movement with physical effort or overexertion, and the type of accident is physical effort or overexertion. On the other hand, the second most important immediate cause and type of accident are different between the two scenarios. Data-mining techniques were chosen as a useful tool to find out the root cause of the accidents.

  14. Effects of acid mine drainage on dissolved inorganic carbon and stable carbon isotopes in receiving streams

    International Nuclear Information System (INIS)

    Fonyuy, Ernest W.; Atekwana, Eliot A.

    2008-01-01

    Dissolved inorganic carbon (DIC) constitutes a significant fraction of a stream's carbon budget, yet the role of acid mine drainage (AMD) in DIC dynamics in receiving streams remains poorly understood. The objective of this study was to evaluate spatial and temporal effects of AMD and its chemical evolution on DIC and stable isotope ratio of DIC (δ 13 C DIC ) in receiving streams. We examined spatial and seasonal variations in physical and chemical parameters, DIC, and δ 13 C DIC in a stream receiving AMD. In addition, we mixed different proportions of AMD and tap water in a laboratory experiment to investigate AMD dilution and variable bicarbonate concentrations to simulate downstream and seasonal hydrologic conditions in the stream. Field and laboratory samples showed variable pH, overall decreases in Fe 2+ , alkalinity, and DIC, and variable increase in δ 13 C DIC . We attribute the decrease in alkalinity, DIC loss, and enrichment of 13 C of DIC in stream water to protons produced from oxidation of Fe 2+ followed by Fe 3+ hydrolysis and precipitation of Fe(OH) 3(s) . The extent of DIC decrease and 13 C enrichment of DIC was related to the amount of HCO 3 - dehydrated by protons. The laboratory experiment showed that lower 13 C enrichment occurred in unmixed AMD (2.7 per mille ) when the amount of protons produced was in excess of HCO 3 - or in tap water (3.2 per mille ) where no protons were produced from Fe 3+ hydrolysis for HCO 3 - dehydration. The 13 C enrichment increased and was highest for AMD-tap water mixture (8.0 per mille ) where Fe 2+ was proportional to HCO 3 - concentration. Thus, the variable downstream and seasonal 13 C enrichment in stream water was due in part to: (1) variations in the volume of stream water initially mixed with AMD and (2) to HCO 3 - input from groundwater and seepage in the downstream direction. Protons produced during the chemical evolution of AMD caused seasonal losses of 50 to >98% of stream water DIC. This loss of DIC

  15. Disinfectant properties of acid mine drainage: its effects on enteric bacteria in a sewage-contaminated stream

    Energy Technology Data Exchange (ETDEWEB)

    Keating, S.T.; Celements, C.M.; Ostrowski, D.; Hanlon, T. [St. Francis College, Loretto, PA (United States). Dept. of Biology

    1996-09-01

    Studies conducted in a Cambria County, Pennsylvania, acid mine drainage stream suggest that mine drainage rapidly reduces in situ populations of fecal bacteria associated with inputs of untreated sewage. The density of lactose-fermenting bacteria, mostly coliform species from sewage, declined 1000-fold over a distance of less than 100 m following the input of high acid (pH 3.5 to 4.0), high ferrous iron (45 mg/l) acid mine drainage. Enterobacteriaceae were isolated from the stream, identified, and tested for tolerance to acid mine drainage by exposing cells to drainage for 10 minutes at 0 or 37{degree}C. Populations of all tested isolates were reduced by this treatment, but some isolates were significantly less affected than others. Thus, while mine drainage may act as a disinfectant, it may not reduce all populations of disease-causing intestinal bacteria at an equal, rapid rate.

  16. Aquatic insect deversity and biomass in a stream marginally polluted by acid strip mine drainage

    Energy Technology Data Exchange (ETDEWEB)

    Tomkiewicz, S.M. Jr.; Dunson, W.A.

    1977-01-01

    Upper Three Runs receives a point source of acid mine drainage from a small acid feeder stream and the pH of the main stream falls from above 6 to about 4.5. Over the 1.2 km study section below the introduction of acid drainage, the pH rises to 5.0. This moderate degree of mine acid pollution has severely affected aquatic insect populations. The acid feeder itself (pH near 3.2) was inhabited only by a chironomid, a megalopteran (Sialis), and the caddisfly Ptilostomis. Biomass was very low (140 mg dry weight/m/sup 2/). The drainage of the acid feeder into the stream caused a drop in the Shannon-Weiner diversity index from 3.10 to 1.95, and a drop in biomass from 6.5 g/m/sup 2/ to 2.2 g/m/sup 2/. At the two stations further downstream, the diversity index remained relatively constant and the biomass leveled off at about 1.2 g/m/sup 2/. The number of taxa declined steadily from 30 at the control station to 13 at the lowest site. Populations of Coleoptera, Ephemeroptera and Trichoptera showed little or no recovery as the acid pollution ameliorated slightly. Representatives of the orders Diptera and Plecoptera (especially Nemoura) showed a decided recovery and increase in numbers near pH 5.0. If fish were able to survive in acid mine polluted waters of pH's between 4.5 and 5.0 they should find sufficient insect food for maintenance of a limited population.

  17. Trace metals of an acid mine drainage stream using a chemical model (WATEQ) and sediment analysis

    International Nuclear Information System (INIS)

    West, K.A.; Wilson, T.P.

    1992-01-01

    The high metal contents common to the discharge of acid-mine drainage (AMD) from mines and mine spoils is an environmental concern to both government and industry. This paper reports the results of investigation of the behavior of metals in an AMD system at a former surface coal mine in Tuscarawas County, Oh. AMD discharges from seeps travels, in respective order through a laminar flow stream; a Typha-dominated wetland; a turbulent flow stream; and a sediment retention pond. Dissolved metals (Fe, Mn, Zn, Cr, Cd, Cu, and Al) major and minor components, and other parameters (pH, dissolved oxygen and Eh) were measured in the AMD water at each sample location. A chemical mineral equilibrium model (WATEQ) was used to predict the minerals which should precipitate at each site. Results suggest that the seeps are supersaturated and should be precipitating hematite, goethite and magnetite (iron oxides), and siderite (iron carbonate), whereas water of the other downstream sites were at or below equilibrium conditions for these minerals. The hydrogeochemistry of the AMD was further studied using sequential chemical attacks on the precipitate sediment surface coatings, in order to determine metal concentrations in the exchangeable, carbonate, Fe-Mn oxyhydroxide, and oxidizable fractions. The carbonate and exchangeable fractions of the precipitate are dominated by Ca and Fe, as well as Mg in the carbonate fraction. The Fe-Mn oxyhydroxide fraction contained Fe, Al, Mn, Mg, and trace metals, and also contained the greatest concentration of total elements in the system. The Fe-Mn oxyhydroxide is therefore, the major sink for metals of this AMD system. The decrease in the concentration of metals in the sediment precipitates in the downstream locations, is consistent with WATEQ and water analysis results

  18. Situation and development of uranium open-pit mining techniques in China

    International Nuclear Information System (INIS)

    Li Kaiwen.

    1986-01-01

    The situation of uranium open-pit mining techniques in China is described. The main experiences in production and management are introduced. Meanwhile the suggestions about the further development of uranium open-pit mining techniques are also proposed

  19. Aquifer restoration techniques for in-situ leach uranium mines

    International Nuclear Information System (INIS)

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

    1984-02-01

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

  20. Measurement Techniques for Radon in Mines, Dwellings and the Environment

    International Nuclear Information System (INIS)

    Snihs, J.O.

    1983-06-01

    Definitions and units appropriate for radon and radon daughters are given. The principle methods of detection are ionization chamber, scintillation technique, nuclear track detector, thermoluminescent discs and alpha spectrometry. The activity concentration is determined by grab sampling and subsequent measurement, frequent or continuous grab sampling and measurement and continuous sampling and long time integrated measurement. Sampling and measurement strategies for mines, dwellings and the environment are discussed. (author)

  1. Analysis of Occupational Accidents in Underground and Surface Mining in Spain Using Data-Mining Techniques

    Directory of Open Access Journals (Sweden)

    Lluís Sanmiquel

    2018-03-01

    Full Text Available An analysis of occupational accidents in the mining sector was conducted using the data from the Spanish Ministry of Employment and Social Safety between 2005 and 2015, and data-mining techniques were applied. Data was processed with the software Weka. Two scenarios were chosen from the accidents database: surface and underground mining. The most important variables involved in occupational accidents and their association rules were determined. These rules are composed of several predictor variables that cause accidents, defining its characteristics and context. This study exposes the 20 most important association rules in the sector—either surface or underground mining—based on the statistical confidence levels of each rule as obtained by Weka. The outcomes display the most typical immediate causes, along with the percentage of accidents with a basis in each association rule. The most important immediate cause is body movement with physical effort or overexertion, and the type of accident is physical effort or overexertion. On the other hand, the second most important immediate cause and type of accident are different between the two scenarios. Data-mining techniques were chosen as a useful tool to find out the root cause of the accidents.

  2. Analysis of Occupational Accidents in Underground and Surface Mining in Spain Using Data-Mining Techniques

    Science.gov (United States)

    Sanmiquel, Lluís; Bascompta, Marc; Rossell, Josep M.; Anticoi, Hernán Francisco; Guash, Eduard

    2018-01-01

    An analysis of occupational accidents in the mining sector was conducted using the data from the Spanish Ministry of Employment and Social Safety between 2005 and 2015, and data-mining techniques were applied. Data was processed with the software Weka. Two scenarios were chosen from the accidents database: surface and underground mining. The most important variables involved in occupational accidents and their association rules were determined. These rules are composed of several predictor variables that cause accidents, defining its characteristics and context. This study exposes the 20 most important association rules in the sector—either surface or underground mining—based on the statistical confidence levels of each rule as obtained by Weka. The outcomes display the most typical immediate causes, along with the percentage of accidents with a basis in each association rule. The most important immediate cause is body movement with physical effort or overexertion, and the type of accident is physical effort or overexertion. On the other hand, the second most important immediate cause and type of accident are different between the two scenarios. Data-mining techniques were chosen as a useful tool to find out the root cause of the accidents. PMID:29518921

  3. Uranium solution mining cost estimating technique: means for rapid comparative analysis of deposits

    International Nuclear Information System (INIS)

    Anon.

    1978-01-01

    Twelve graphs provide a technique for determining relative cost ranges for uranium solution mining projects. The use of the technique can provide a consistent framework for rapid comparative analysis of various properties of mining situations. The technique is also useful to determine the sensitivities of cost figures to incremental changes in mining factors or deposit characteristics

  4. Soil Erosion from Agriculture and Mining: A Threat to Tropical Stream Ecosystems

    Directory of Open Access Journals (Sweden)

    Jan H. Mol

    2013-09-01

    Full Text Available In tropical countries soil erosion is often increased due to high erodibility of geologically old and weathered soils; intensive rainfall; inappropriate soil management; removal of forest vegetation cover; and mining activities. Stream ecosystems draining agricultural or mining areas are often severely impacted by the high loads of eroded material entering the stream channel; increasing turbidity; covering instream habitat and affecting the riparian zone; and thereby modifying habitat and food web structures. The biodiversity is severely threatened by these negative effects as the aquatic and riparian fauna and flora are not adapted to cope with excessive rates of erosion and sedimentation. Eroded material may also be polluted by pesticides or heavy metals that have an aggravating effect on functions and ecosystem services. Loss of superficial material and deepening of erosion gullies impoverish the nutrient and carbon contents of the soils; and lower the water tables; causing a “lose-lose” situation for agricultural productivity and environmental integrity. Several examples show how to interrupt this vicious cycle by integrated catchment management and by combining “green” and “hard” engineering for habitat restoration. In this review; we summarize current findings on this issue from tropical countries with a focus on case studies from Suriname and Brazil.

  5. Review of samples of tailings, soils and stream sediment adjacent to and downstream from the Ruth Mine, Inyo County, California

    Science.gov (United States)

    Rytuba, James J.; Kim, Christopher S.; Goldstein, Daniel N.

    2011-01-01

    The Ruth Mine and mill are located in the western Mojave Desert in Inyo County, California (fig. 1). The mill processed gold-silver (Au-Ag) ores mined from the Ruth Au-Ag deposit, which is adjacent to the mill site. The Ruth Au-Ag deposit is hosted in Mesozoic intrusive rocks and is similar to other Au-Ag deposits in the western Mojave Desert that are associated with Miocene volcanic centers that formed on a basement of Mesozoic granitic rocks (Bateman, 1907; Gardner, 1954; Rytuba, 1996). The volcanic rocks consist of silicic domes and associated flows, pyroclastic rocks, and subvolcanic intrusions (fig. 2) that were emplaced into Mesozoic silicic intrusive rocks (Troxel and Morton, 1962). The Ruth Mine is on Federal land managed by the U.S. Bureau of Land Management (BLM). Tailings from the mine have been eroded and transported downstream into Homewood Canyon and then into Searles Valley (figs. 3, 4, 5, and 6). The BLM provided recreational facilities at the mine site for day-use hikers and restored and maintained the original mine buildings in collaboration with local citizen groups for use by visitors (fig. 7). The BLM requested that the U.S. Geological Survey (USGS), in collaboration with Chapman University, measure arsenic (As) and other geochemical constituents in soils and tailings at the mine site and in stream sediments downstream from the mine in Homewood Canyon and in Searles Valley (fig. 3). The request was made because initial sampling of the site by BLM staff indicated high concentrations of As in tailings and soils adjacent to the Ruth Mine. This report summarizes data obtained from field sampling of mine tailings and soils adjacent to the Ruth Mine and stream sediments downstream from the mine on June 7, 2009. Our results permit a preliminary assessment of the sources of As and associated chemical constituents that could potentially impact humans and biota.

  6. Using data mining techniques to characterize participation in observational studies.

    Science.gov (United States)

    Linden, Ariel; Yarnold, Paul R

    2016-12-01

    Data mining techniques are gaining in popularity among health researchers for an array of purposes, such as improving diagnostic accuracy, identifying high-risk patients and extracting concepts from unstructured data. In this paper, we describe how these techniques can be applied to another area in the health research domain: identifying characteristics of individuals who do and do not choose to participate in observational studies. In contrast to randomized studies where individuals have no control over their treatment assignment, participants in observational studies self-select into the treatment arm and therefore have the potential to differ in their characteristics from those who elect not to participate. These differences may explain part, or all, of the difference in the observed outcome, making it crucial to assess whether there is differential participation based on observed characteristics. As compared to traditional approaches to this assessment, data mining offers a more precise understanding of these differences. To describe and illustrate the application of data mining in this domain, we use data from a primary care-based medical home pilot programme and compare the performance of commonly used classification approaches - logistic regression, support vector machines, random forests and classification tree analysis (CTA) - in correctly classifying participants and non-participants. We find that CTA is substantially more accurate than the other models. Moreover, unlike the other models, CTA offers transparency in its computational approach, ease of interpretation via the decision rules produced and provides statistical results familiar to health researchers. Beyond their application to research, data mining techniques could help administrators to identify new candidates for participation who may most benefit from the intervention. © 2016 John Wiley & Sons, Ltd.

  7. Data mining practical machine learning tools and techniques

    CERN Document Server

    Witten, Ian H

    2005-01-01

    As with any burgeoning technology that enjoys commercial attention, the use of data mining is surrounded by a great deal of hype. Exaggerated reports tell of secrets that can be uncovered by setting algorithms loose on oceans of data. But there is no magic in machine learning, no hidden power, no alchemy. Instead there is an identifiable body of practical techniques that can extract useful information from raw data. This book describes these techniques and shows how they work. The book is a major revision of the first edition that appeared in 1999. While the basic core remains the same

  8. Vascular riffle flora of Appalachian streams: the ecology and effects of acid mine drainage on Justificia americana (L. ) Vahl

    Energy Technology Data Exchange (ETDEWEB)

    Koryak, M.; Reilly, R.J.

    1984-06-01

    Justicia americana is a stout-based colonial plant, abundant in most of the larger, low to moderate gradient streams of the upper Ohio River basin. The distribution of J. americana is related to acid drainage from bituminous coal mining operations in the upper Ohio River drainage basin. Possible fluvial and biological consequences of the colonization or absence of Justicia are considered. Luxuriant growths were noted on gravel bars and riffles of larger, unpolluted streams in the basin. Acid mine drainage severely depresses the growth of the plant, leaving gravel shoals and riffles in the acid streams either barren or dominated by other emergent species. Particular among these new species is Elecocharis acicularis. The elimination of J. americana from suitable habitat adversely affects channel morphology, substrate composition, general aesthetic quality and aquatic stream life in the region. 16 references, 2 figures, 3 tables.

  9. Applying data mining techniques to improve diagnosis in neonatal jaundice

    Directory of Open Access Journals (Sweden)

    Ferreira Duarte

    2012-12-01

    Full Text Available Abstract Background Hyperbilirubinemia is emerging as an increasingly common problem in newborns due to a decreasing hospital length of stay after birth. Jaundice is the most common disease of the newborn and although being benign in most cases it can lead to severe neurological consequences if poorly evaluated. In different areas of medicine, data mining has contributed to improve the results obtained with other methodologies. Hence, the aim of this study was to improve the diagnosis of neonatal jaundice with the application of data mining techniques. Methods This study followed the different phases of the Cross Industry Standard Process for Data Mining model as its methodology. This observational study was performed at the Obstetrics Department of a central hospital (Centro Hospitalar Tâmega e Sousa – EPE, from February to March of 2011. A total of 227 healthy newborn infants with 35 or more weeks of gestation were enrolled in the study. Over 70 variables were collected and analyzed. Also, transcutaneous bilirubin levels were measured from birth to hospital discharge with maximum time intervals of 8 hours between measurements, using a noninvasive bilirubinometer. Different attribute subsets were used to train and test classification models using algorithms included in Weka data mining software, such as decision trees (J48 and neural networks (multilayer perceptron. The accuracy results were compared with the traditional methods for prediction of hyperbilirubinemia. Results The application of different classification algorithms to the collected data allowed predicting subsequent hyperbilirubinemia with high accuracy. In particular, at 24 hours of life of newborns, the accuracy for the prediction of hyperbilirubinemia was 89%. The best results were obtained using the following algorithms: naive Bayes, multilayer perceptron and simple logistic. Conclusions The findings of our study sustain that, new approaches, such as data mining, may support

  10. SURVEY ON CRIME ANALYSIS AND PREDICTION USING DATA MINING TECHNIQUES

    Directory of Open Access Journals (Sweden)

    H Benjamin Fredrick David

    2017-04-01

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

  11. Hydrogeochemical characteristics of streams with and without acid mine drainage impacts: A paired catchment study in karst geology, SW China

    Science.gov (United States)

    Sun, Jing; Tang, Changyuan; Wu, Pan; Strosnider, William H. J.; Han, Zhiwei

    2013-11-01

    A paired catchment study was used to assess karst hydrogeochemistry of two streams.Chemistry of streams with and without acid mine drainage (AMD) was very different.The observation was supported by PHREEQC modeling of equilibrium conditions.Ionic fluxes of AMD-impacted water were higher than that of non-AMD-impacted water.The higher ionic fluxes were predominantly controlled by the oxidation of pyrite.

  12. Base Oils Biodegradability Prediction with Data Mining Techniques

    Directory of Open Access Journals (Sweden)

    Malika Trabelsi

    2010-02-01

    Full Text Available In this paper, we apply various data mining techniques including continuous numeric and discrete classification prediction models of base oils biodegradability, with emphasis on improving prediction accuracy. The results show that highly biodegradable oils can be better predicted through numeric models. In contrast, classification models did not uncover a similar dichotomy. With the exception of Memory Based Reasoning and Decision Trees, tested classification techniques achieved high classification prediction. However, the technique of Decision Trees helped uncover the most significant predictors. A simple classification rule derived based on this predictor resulted in good classification accuracy. The application of this rule enables efficient classification of base oils into either low or high biodegradability classes with high accuracy. For the latter, a higher precision biodegradability prediction can be obtained using continuous modeling techniques.

  13. The Effects of Elevated Specific Conductivity on the Chronic Toxicity of Mining Influenced Streams Using Ceriodaphnia dubia.

    Science.gov (United States)

    Armstead, Mindy Yeager; Bitzer-Creathers, Leah; Wilson, Mandee

    2016-01-01

    Salinization of freshwater ecosystems as a result of human activities has markedly increased in recent years. Much attention is currently directed at evaluating the effects of increased salinity on freshwater biota. In the Central Appalachian region of the eastern United States, specific conductance from alkaline discharges associated with mountain top mining practices has been implicated in macroinvertebrate community declines in streams receiving coal mining discharges. Whole effluent toxicity testing of receiving stream water was used to test the hypothesis that mine discharges are toxic to laboratory test organisms and further, that toxicity is related to ionic concentrations as indicated by conductivity. Chronic toxicity testing using Ceriodaphnia dubia was conducted by contract laboratories at 72 sites with a total of 129 tests over a 3.5 year period. The database was evaluated to determine the ionic composition of mine effluent dominated streams and whether discharge constituents were related to toxicity in C. dubia. As expected, sulfate was found to be the dominant anion in streams receiving mining discharges with bicarbonate variable and sometimes a substantial component of the dissolved solids. Overall, the temporal variability in conductance was low at each site which would indicate fairly stable water quality conditions. Results of the toxicity tests show no relationship between conductance and survival of C. dubia in the mining influenced streams with the traditional toxicity test endpoints. However, consideration of the entire dataset revealed a significant inverse relationship between conductivity and neonate production. While conductivity explained very little of the high variability in the offspring production (r2 = 0.1304), the average numbers of offspring were consistently less than 20 neonates at the highest conductivities.

  14. The Effects of Elevated Specific Conductivity on the Chronic Toxicity of Mining Influenced Streams Using Ceriodaphnia dubia.

    Directory of Open Access Journals (Sweden)

    Mindy Yeager Armstead

    Full Text Available Salinization of freshwater ecosystems as a result of human activities has markedly increased in recent years. Much attention is currently directed at evaluating the effects of increased salinity on freshwater biota. In the Central Appalachian region of the eastern United States, specific conductance from alkaline discharges associated with mountain top mining practices has been implicated in macroinvertebrate community declines in streams receiving coal mining discharges. Whole effluent toxicity testing of receiving stream water was used to test the hypothesis that mine discharges are toxic to laboratory test organisms and further, that toxicity is related to ionic concentrations as indicated by conductivity. Chronic toxicity testing using Ceriodaphnia dubia was conducted by contract laboratories at 72 sites with a total of 129 tests over a 3.5 year period. The database was evaluated to determine the ionic composition of mine effluent dominated streams and whether discharge constituents were related to toxicity in C. dubia. As expected, sulfate was found to be the dominant anion in streams receiving mining discharges with bicarbonate variable and sometimes a substantial component of the dissolved solids. Overall, the temporal variability in conductance was low at each site which would indicate fairly stable water quality conditions. Results of the toxicity tests show no relationship between conductance and survival of C. dubia in the mining influenced streams with the traditional toxicity test endpoints. However, consideration of the entire dataset revealed a significant inverse relationship between conductivity and neonate production. While conductivity explained very little of the high variability in the offspring production (r2 = 0.1304, the average numbers of offspring were consistently less than 20 neonates at the highest conductivities.

  15. Process mining techniques: an application to time management

    Science.gov (United States)

    Khowaja, Ali Raza

    2018-04-01

    In an environment people have to make sure that all of their work are completed within a given time in accordance with its quality. In order to achieve the real phenomenon of process mining one needs to understand all of these processes in a detailed manner. Personal Information and communication has always been a highlighting issue on internet but for now information and communication tools within factual life refers to their daily schedule, location analysis, environmental analysis and, more generally, social media applications support these systems which makes data available for data analysis generated through event logs, but also for process analysis which combines environmental and location analysis. Process mining can be used to exploit all these real live processes with the help of the event logs which are already available in those datasets through user censored data or may be user labeled data. These processes could be used to redesign a user's flow and understand all these processes in a bit more detailed manner. In order to increase the quality of each of the processes that we go through our daily lives is to give a closer look to each of the processes and after analyzing them, one should make changes to get better results. On the contrarily, we applied process mining techniques on seven different subjects combined in a single dataset collected from Korea. Above all, the following paper comments on the efficiency of processes in the event logs referring to time management's sphere of influence.

  16. Improving clinical decision support using data mining techniques

    Science.gov (United States)

    Burn-Thornton, Kath E.; Thorpe, Simon I.

    1999-02-01

    Physicians, in their ever-demanding jobs, are looking to decision support systems for aid in clinical diagnosis. However, clinical decision support systems need to be of sufficiently high accuracy that they help, rather than hinder, the physician in his/her diagnosis. Decision support systems with accuracies, of patient state determination, of greater than 80 percent, are generally perceived to be sufficiently accurate to fulfill the role of helping the physician. We have previously shown that data mining techniques have the potential to provide the underpinning technology for clinical decision support systems. In this paper, an extension of the work in reverence 2, we describe how changes in data mining methodologies, for the analysis of 12-lead ECG data, improve the accuracy by which data mining algorithms determine which patients are suffering from heart disease. We show that the accuracy of patient state prediction, for all the algorithms, which we investigated, can be increased by up to 6 percent, using the combination of appropriate test training ratios and 5-fold cross-validation. The use of cross-validation greater than 5-fold, appears to reduce the improvement in algorithm classification accuracy gained by the use of this validation method. The accuracy of 84 percent in patient state predictions, obtained using the algorithm OCI, suggests that this algorithm will be capable of providing the required accuracy for clinical decision support systems.

  17. Mining the IPTV Channel Change Event Stream to Discover Insight and Detect Ads

    Directory of Open Access Journals (Sweden)

    Matej Kren

    2016-01-01

    Full Text Available IPTV has been widely deployed throughout the world, bringing significant advantages to users in terms of the channel offering, video on demand, and interactive applications. One aspect that has been often neglected is the ability of precise and unobtrusive telemetry. TV set-top boxes that are deployed in modern IPTV systems can be thought of as capable sensor nodes that collect vast amounts of data, representing both the user activity and the quality of service delivered by the system itself. In this paper we focus on the user-generated events and analyze how the data stream of channel change events received from the entire IPTV network can be mined to obtain insight about the content. We demonstrate that it is possible to predict the occurrence of TV ads with high probability and show that the approach could be extended to model the user behavior and classify the viewership in multiple dimensions.

  18. Sensitivity analysis of a pulse nutrient addition technique for estimating nutrient uptake in large streams

    Science.gov (United States)

    Laurence Lin; J.R. Webster

    2012-01-01

    The constant nutrient addition technique has been used extensively to measure nutrient uptake in streams. However, this technique is impractical for large streams, and the pulse nutrient addition (PNA) has been suggested as an alternative. We developed a computer model to simulate Monod kinetics nutrient uptake in large rivers and used this model to evaluate the...

  19. Rare Moss-Built Microterraces in a High-Altitude, Acid Mine Drainage-Polluted Stream (Cordillera Negra, Peru)

    NARCIS (Netherlands)

    Sevink, J.; Verstraten, J.M.; Kooijman, A.M.; Loayza-Muro, R.A.; Hoitinga, L.; Palomino, E.J.; Jansen, B.

    2015-01-01

    The Rio Santiago in the Cordillera Negra of Peru is severely contaminated by acid mine drainage in its headwaters. In a strongly acid stream, at about 3800 m above sea level (masl), microterraces were found with terrace walls built up of dead moss, with encrustations and interstitial fine, creamy

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

    Science.gov (United States)

    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.

  1. Building a Classification Model for Enrollment In Higher Educational Courses using Data Mining Techniques

    OpenAIRE

    Saini, Priyanka

    2014-01-01

    Data Mining is the process of extracting useful patterns from the huge amount of database and many data mining techniques are used for mining these patterns. Recently, one of the remarkable facts in higher educational institute is the rapid growth data and this educational data is expanding quickly without any advantage to the educational management. The main aim of the management is to refine the education standard; therefore by applying the various data mining techniques on this data one ca...

  2. Exploration of diffuse and discrete sources of acid mine drainage to a headwater mountain stream in Colorado, USA

    Science.gov (United States)

    Johnston, Allison; Runkel, Robert L.; Navarre-Sitchler, Alexis; Singha, Kamini

    2017-01-01

    We investigated the impact of acid mine drainage (AMD) contamination from the Minnesota Mine, an inactive gold and silver mine, on Lion Creek, a headwater mountain stream near Empire, Colorado. The objective was to map the sources of AMD contamination, including discrete sources visible at the surface and diffuse inputs that were not readily apparent. This was achieved using geochemical sampling, in-stream and in-seep fluid electrical conductivity (EC) logging, and electrical resistivity imaging (ERI) of the subsurface. The low pH of the AMD-impacted water correlated to high fluid EC values that served as a target for the ERI. From ERI, we identified two likely sources of diffuse contamination entering the stream: (1) the subsurface extent of two seepage faces visible on the surface, and (2) rainfall runoff washing salts deposited on the streambank and in a tailings pile on the east bank of Lion Creek. Additionally, rainfall leaching through the tailings pile is a potential diffuse source of contamination if the subsurface beneath the tailings pile is hydraulically connected with the stream. In-stream fluid EC was lowest when stream discharge was highest in early summer and then increased throughout the summer as stream discharge decreased, indicating that the concentration of dissolved solids in the stream is largely controlled by mixing of groundwater and snowmelt. Total dissolved solids (TDS) load is greatest in early summer and displays a large diel signal. Identification of diffuse sources and variability in TDS load through time should allow for more targeted remediation options.

  3. In-stream chemical neutralization: A whole watershed approach to mitigating acid mine drainage

    International Nuclear Information System (INIS)

    Britt, D.L.

    1994-01-01

    The North Branch of the Potomac River is adversely affected by acid mine drainage (AMD) throughout its entire length. As an alternative to mine-mouth treatment methods an in-stream AMD-neutralization demonstration program for an approximately 25-mile segment of the North Branch of the Potomac River was designed and implemented. This river segment was ranked as the highest priority site in Maryland for a demonstration project owing to its combination of very poor water quality and excellent potential for supporting a recreational sport fishery in the absence of toxic metal and acid loadings. A whole-watershed approach employing Scandinavian doser technologies and calcium carbonate neutralizing agents is the basis for the North Branch Potomac River demonstration project. The project involves four phases: feasibility (1), design (2), implementation (3), and monitoring (4). This watershed approach to mitigating AMD is expected to restore circumneutrial water quality and to promote desirable fishery resources throughout the mainstem and selected tributaries of the North Branch of the Potomac River Upstream of Jennings Randolph Dam. This paper summarizes Phases 1--3 of the demonstration project

  4. Determination of total arsenic in streams and sediments from Obuasi gold mines

    International Nuclear Information System (INIS)

    Serfor Armah, Yaw

    1994-03-01

    In this work streams and sediments of Obuasi, a major gold mining town in Ghana were analysed. In addition to the total arsenic the parameters determined included the levels of Pe, Al, Nn and Au and nutrients. Leaching of arsenic from the sediment was also carried out to ascertain the rate at which As will be removed from the sediment to acceptable levels. Results indicate that in spite of the newly installed Arsenic Recovery Plant (ARP) which is able to remove about 90% of the arsenic dusts, the streams in the area remain heavily polluted with arsenic. In the water Total Arsenic values range between 0.13 - 20.00ppm. The sediments are also polluted to a depth of at least 30cm with values ranging from 15.38 - 50.00ppm. Contrary to expectations, the gold concentration in both the water and sediment are too low and may not be suitable for exploration. The leaching results show that very little amount of arsenic was leached from the sediments. Even after 20 weeks of continuous leaching less than 1% of As had been leached. This was attributed to the ability of arsenic to form sparingly soluble compounds with Fe, Al, Mn etc in the sediment environment. (au)

  5. Mining

    Directory of Open Access Journals (Sweden)

    Khairullah Khan

    2014-09-01

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

  6. Marine data users clustering using data mining technique

    Directory of Open Access Journals (Sweden)

    Farnaz Ghiasi

    2015-09-01

    Full Text Available The objective of this research is marine data users clustering using data mining technique. To achieve this objective, marine organizations will enable to know their data and users requirements. In this research, CRISP-DM standard model was used to implement the data mining technique. The required data was extracted from 500 marine data users profile database of Iranian National Institute for Oceanography and Atmospheric Sciences (INIOAS from 1386 to 1393. The TwoStep algorithm was used for clustering. In this research, patterns was discovered between marine data users such as student, organization and scientist and their data request (Data source, Data type, Data set, Parameter and Geographic area using clustering for the first time. The most important clusters are: Student with International data source, Chemistry data type, “World Ocean Database” dataset, Persian Gulf geographic area and Organization with Nitrate parameter. Senior managers of the marine organizations will enable to make correct decisions concerning their existing data. They will direct to planning for better data collection in the future. Also data users will guide with respect to their requests. Finally, the valuable suggestions were offered to improve the performance of marine organizations.

  7. Data mining techniques for thermophysical properties of refrigerants

    International Nuclear Information System (INIS)

    Kuecueksille, Ecir Ugur; Selbas, Resat; Sencan, Arzu

    2009-01-01

    This study presents ten modeling techniques within data mining process for the prediction of thermophysical properties of refrigerants (R134a, R404a, R407c and R410a). These are linear regression (LR), multi layer perception (MLP), pace regression (PR), simple linear regression (SLR), sequential minimal optimization (SMO), KStar, additive regression (AR), M5 model tree, decision table (DT), M5'Rules models. Relations depending on temperature and pressure were carried out for the determination of thermophysical properties as the specific heat capacity, viscosity, heat conduction coefficient, density of the refrigerants. Obtained model results for every refrigerant were compared and the best model was investigated. Results indicate that use of derived formulations from these techniques will facilitate design and optimize of heat exchangers which is component of especially vapor compression refrigeration system

  8. Selected Metals in Sediments and Streams in the Oklahoma Part of the Tri-State Mining District, 2000-2006

    Science.gov (United States)

    Andrews, William J.; Becker, Mark F.; Mashburn, Shana L.; Smith, S. Jerrod

    2009-01-01

    The abandoned Tri-State mining district includes 1,188 square miles in northeastern Oklahoma, southeastern Kansas, and southwestern Missouri. The most productive part of the Tri-State mining district was the 40-square mile part in Oklahoma, commonly referred to as 'the Picher mining district' in north-central Ottawa County, Oklahoma. The Oklahoma part of the Tri-State mining district was a primary producing area of lead and zinc in the United States during the first half of the 20th century. Sulfide minerals of cadmium, iron, lead, and zinc that remained in flooded underground mine workings and in mine tailings on the land surface oxidized and dissolved with time, forming a variety of oxide, hydroxide, and hydroxycarbonate metallic minerals on the land surface and in streams that drain the district. Metals in water and sediments in streams draining the mining district can potentially impair the habitat and health of many forms of aquatic and terrestrial life. Lakebed, streambed and floodplain sediments and/or stream water were sampled at 30 sites in the Oklahoma part of the Tri-State mining district by the U.S. Geological Survey and the Oklahoma Department of Environmental Quality from 2000 to 2006 in cooperation with the U.S. Environmental Protection Agency, and the Quapaw and Seneca-Cayuga Tribes of Oklahoma. Aluminum and iron concentrations of several thousand milligrams per kilogram were measured in sediments collected from the upstream end of Grand Lake O' the Cherokees. Manganese and zinc concentrations in those sediments were several hundred milligrams per kilogram. Lead and cadmium concentrations in those sediments were about 10 percent and 0.1 percent of zinc concentrations, respectively. Sediment cores collected in a transect across the floodplain of Tar Creek near Miami, Oklahoma, in 2004 had similar or greater concentrations of those metals than sediment cores collected at the upstream end of Grand Lake O' the Cherokees. The greatest concentrations of

  9. Examining microbial community response to a strong chemical gradient: the effects of surface coal mining on stream bacteria

    Science.gov (United States)

    Bier, R.; Lindberg, T. T.; Wang, S.; Ellis, J. C.; Di Giulio, R. T.; Bernhardt, E. S.

    2012-12-01

    Surface coal mining is the dominant form of land cover change in northern and central Appalachia. In this process, shallow coal seams are exposed by removing overlying rock with explosives. The resulting fragmented carbonate rock and coal residues are disposed of in stream valleys. These valley fills generate alkaline mine drainage (AlkMD), dramatically increasing alkalinity, ionic strength, substrate supply (esp. SO42-), and trace element (Mn, Li, Se, U) concentrations in downstream rivers as well as significant losses of sensitive fish and macroinvertebrate species. In prior work within the Mud River, which drains the largest surface mine complex in Appalachia, we found that concentrations of AlkMD increase proportionally with the extent of upstream mining. Here we ask "How do stream microbial communities change along this strong chemical gradient?" We collected surface water and benthic biofilms from 25 stream reaches throughout the Mud River spanning the full range of surface mining impacts, with 0-96% of the contributing watershed area converted to surface coal mines. Microbial communities were collected from biofilms grown on a common substrate (red maple veneers) that were incubated in each stream reach for four months prior to collection in April, 2011. 16S rRNA genes from microbial communities at each study site were examined using 454 sequencing and compared with a generalized UniFrac distance matrix (674 sequence eveness) that was used in statistical analyses. Water chemistry at the sites was sampled monthly from July 2010 to December 2010 and again in April 2011. In April, surface water concentrations of SO42-, Ca2+, Mg2+, and Se2- increased linearly with the extent of upstream mining (all regressions R2 >0.43; pPERMANOVA; p=0.029). Bacterial diversity (OTU richness defined at 3% sequence difference) peaked at intermediate conductivities (600 μS cm-1). Environmental data that correlated significantly with the ordination axes were a variety of surface

  10. Rule Mining Techniques to Predict Prokaryotic Metabolic Pathways

    KAUST Repository

    Saidi, Rabie

    2017-08-28

    It is becoming more evident that computational methods are needed for the identification and the mapping of pathways in new genomes. We introduce an automatic annotation system (ARBA4Path Association Rule-Based Annotator for Pathways) that utilizes rule mining techniques to predict metabolic pathways across wide range of prokaryotes. It was demonstrated that specific combinations of protein domains (recorded in our rules) strongly determine pathways in which proteins are involved and thus provide information that let us very accurately assign pathway membership (with precision of 0.999 and recall of 0.966) to proteins of a given prokaryotic taxon. Our system can be used to enhance the quality of automatically generated annotations as well as annotating proteins with unknown function. The prediction models are represented in the form of human-readable rules, and they can be used effectively to add absent pathway information to many proteins in UniProtKB/TrEMBL database.

  11. Rule Mining Techniques to Predict Prokaryotic Metabolic Pathways

    KAUST Repository

    Saidi, Rabie; Boudellioua, Imene; Martin, Maria J.; Solovyev, Victor

    2017-01-01

    It is becoming more evident that computational methods are needed for the identification and the mapping of pathways in new genomes. We introduce an automatic annotation system (ARBA4Path Association Rule-Based Annotator for Pathways) that utilizes rule mining techniques to predict metabolic pathways across wide range of prokaryotes. It was demonstrated that specific combinations of protein domains (recorded in our rules) strongly determine pathways in which proteins are involved and thus provide information that let us very accurately assign pathway membership (with precision of 0.999 and recall of 0.966) to proteins of a given prokaryotic taxon. Our system can be used to enhance the quality of automatically generated annotations as well as annotating proteins with unknown function. The prediction models are represented in the form of human-readable rules, and they can be used effectively to add absent pathway information to many proteins in UniProtKB/TrEMBL database.

  12. Exploring Characterizations of Learning Object Repositories Using Data Mining Techniques

    Science.gov (United States)

    Segura, Alejandra; Vidal, Christian; Menendez, Victor; Zapata, Alfredo; Prieto, Manuel

    Learning object repositories provide a platform for the sharing of Web-based educational resources. As these repositories evolve independently, it is difficult for users to have a clear picture of the kind of contents they give access to. Metadata can be used to automatically extract a characterization of these resources by using machine learning techniques. This paper presents an exploratory study carried out in the contents of four public repositories that uses clustering and association rule mining algorithms to extract characterizations of repository contents. The results of the analysis include potential relationships between different attributes of learning objects that may be useful to gain an understanding of the kind of resources available and eventually develop search mechanisms that consider repository descriptions as a criteria in federated search.

  13. Preservation procedures for arsenic speciation in a stream affected by acid mine drainage in southwestern Spain

    Energy Technology Data Exchange (ETDEWEB)

    Sanchez-Rodas, Daniel; Oliveira, Vanesa; Gomez-Ariza, Jose Luis [University of Huelva, Department of Chemistry and Materials Science, Faculty of Experimental Sciences, Huelva (Spain); Sarmiento, Aguasanta M.; Nieto, Jose Miguel [University of Huelva, Department of Geology, Faculty of Experimental Sciences, Huelva (Spain)

    2006-04-15

    A preservation study has been performed for arsenic speciation in surface freshwaters affected by acid mine drainage (AMD), a pollution source characterized by low pH and high metallic content. Two sample preservation procedures described in the literature were attempted using opaque glass containers and refrigeration: i) addition of 0.25 mol L{sup -1} EDTA to the samples, which maintained the stability of the arsenic species for 3 h; and ii) in situ sample clean-up with a cationic exchange resin, in order to reduce the metallic load, which resulted in a partial co-adsorption of arsenic onto Fe precipitates. A new proposed method was also tried: sample acidification with 6 mol L{sup -1} HCl followed by in situ clean-up with a cationic exchange resin, which allowed a longer preservation time of at least 48 h. The proposed method was successfully applied to water samples with high arsenic content, taken from the Aguas Agrias Stream (Odiel River Basin, SW Spain), which is severely affected by AMD that originates at the nearby polymetallic sulfide mine of Tharsis. The speciation results obtained by liquid chromatography-hydride generation-atomic fluorescence spectrometry (HPLC-HG-AFS) indicated that during the summer the main arsenic species was As(V) at the hundred {mu}g L{sup -1} level, followed by DMA (dimethyl arsenic) and As(III) below the ten {mu}g L{sup -1} level. In winter, As(V) and As(III) increased at least fivefold, whereas the DMA was not detected. (orig.)

  14. Methylmercury degradation and exposure pathways in streams and wetlands impacted by historical mining

    Energy Technology Data Exchange (ETDEWEB)

    Donovan, Patrick M., E-mail: pmdon@umich.edu [University of Michigan, Department of Earth and Environmental Sciences, 1100 N., University Ave., Ann Arbor, MI 48109 (United States); Blum, Joel D. [University of Michigan, Department of Earth and Environmental Sciences, 1100 N., University Ave., Ann Arbor, MI 48109 (United States); Singer, Michael Bliss [University of St Andrews, Department of Earth and Environmental Sciences, North St., St. Andrews, KY16 9AL (United Kingdom); Earth Research Institute, University of California Santa Barbara, Santa Barbara, CA, 91306 (United States); Marvin-DiPasquale, Mark [U.S. Geological Survey, Menlo Park, CA (United States); Tsui, Martin T.K. [Department of Biology, University of North Carolina at Greensboro, Greensboro, NC 27402 (United States)

    2016-10-15

    Monomethyl mercury (MMHg) and total mercury (THg) concentrations and Hg stable isotope ratios (δ{sup 202}Hg and Δ{sup 199}Hg) were measured in sediment and aquatic organisms from Cache Creek (California Coast Range) and Yolo Bypass (Sacramento Valley). Cache Creek sediment had a large range in THg (87 to 3870 ng/g) and δ{sup 202}Hg (− 1.69 to − 0.20‰) reflecting the heterogeneity of Hg mining sources in sediment. The δ{sup 202}Hg of Yolo Bypass wetland sediment suggests a mixture of high and low THg sediment sources. Relationships between %MMHg (the percent ratio of MMHg to THg) and Hg isotope values (δ{sup 202}Hg and Δ{sup 199}Hg) in fish and macroinvertebrates were used to identify and estimate the isotopic composition of MMHg. Deviation from linear relationships was found between %MMHg and Hg isotope values, which is indicative of the bioaccumulation of isotopically distinct pools of MMHg. The isotopic composition of pre-photodegraded MMHg (i.e., subtracting fractionation from photochemical reactions) was estimated and contrasting relationships were observed between the estimated δ{sup 202}Hg of pre-photodegraded MMHg and sediment IHg. Cache Creek had mass dependent fractionation (MDF; δ{sup 202}Hg) of at least − 0.4‰ whereas Yolo Bypass had MDF of + 0.2 to + 0.5‰. This result supports the hypothesis that Hg isotope fractionation between IHg and MMHg observed in rivers (− MDF) is unique compared to + MDF observed in non-flowing water environments such as wetlands, lakes, and the coastal ocean. - Highlights: • Mercury isotope ratios were measured in sediment and biota from Central California. • The isotopic composition of MMHg was estimated in streams and wetlands. • Mercury isotopes suggest multiple exposure pathways in these habitats. • Mass dependent fractionation between IHg and MMHg is different in streams.

  15. Methylmercury degradation and exposure pathways in streams and wetlands impacted by historical mining

    International Nuclear Information System (INIS)

    Donovan, Patrick M.; Blum, Joel D.; Singer, Michael Bliss; Marvin-DiPasquale, Mark; Tsui, Martin T.K.

    2016-01-01

    Monomethyl mercury (MMHg) and total mercury (THg) concentrations and Hg stable isotope ratios (δ"2"0"2Hg and Δ"1"9"9Hg) were measured in sediment and aquatic organisms from Cache Creek (California Coast Range) and Yolo Bypass (Sacramento Valley). Cache Creek sediment had a large range in THg (87 to 3870 ng/g) and δ"2"0"2Hg (− 1.69 to − 0.20‰) reflecting the heterogeneity of Hg mining sources in sediment. The δ"2"0"2Hg of Yolo Bypass wetland sediment suggests a mixture of high and low THg sediment sources. Relationships between %MMHg (the percent ratio of MMHg to THg) and Hg isotope values (δ"2"0"2Hg and Δ"1"9"9Hg) in fish and macroinvertebrates were used to identify and estimate the isotopic composition of MMHg. Deviation from linear relationships was found between %MMHg and Hg isotope values, which is indicative of the bioaccumulation of isotopically distinct pools of MMHg. The isotopic composition of pre-photodegraded MMHg (i.e., subtracting fractionation from photochemical reactions) was estimated and contrasting relationships were observed between the estimated δ"2"0"2Hg of pre-photodegraded MMHg and sediment IHg. Cache Creek had mass dependent fractionation (MDF; δ"2"0"2Hg) of at least − 0.4‰ whereas Yolo Bypass had MDF of + 0.2 to + 0.5‰. This result supports the hypothesis that Hg isotope fractionation between IHg and MMHg observed in rivers (− MDF) is unique compared to + MDF observed in non-flowing water environments such as wetlands, lakes, and the coastal ocean. - Highlights: • Mercury isotope ratios were measured in sediment and biota from Central California. • The isotopic composition of MMHg was estimated in streams and wetlands. • Mercury isotopes suggest multiple exposure pathways in these habitats. • Mass dependent fractionation between IHg and MMHg is different in streams.

  16. Evaluating remedial alternatives for an acid mine drainage stream: Application of a reactive transport model

    Science.gov (United States)

    Runkel, R.L.; Kimball, B.A.

    2002-01-01

    A reactive transport model based on one-dimensional transport and equilibrium chemistry is applied to synoptic data from an acid mine drainage stream. Model inputs include streamflow estimates based on tracer dilution, inflow chemistry based on synoptic sampling, and equilibrium constants describing acid/base, complexation, precipitation/dissolution, and sorption reactions. The dominant features of observed spatial profiles in pH and metal concentration are reproduced along the 3.5-km study reach by simulating the precipitation of Fe(III) and Al solid phases and the sorption of Cu, As, and Pb onto freshly precipitated iron-(III) oxides. Given this quantitative description of existing conditions, additional simulations are conducted to estimate the streamwater quality that could result from two hypothetical remediation plans. Both remediation plans involve the addition of CaCO3 to raise the pH of a small, acidic inflow from ???2.4 to ???7.0. This pH increase results in a reduced metal load that is routed downstream by the reactive transport model, thereby providing an estimate of post-remediation water quality. The first remediation plan assumes a closed system wherein inflow Fe(II) is not oxidized by the treatment system; under the second remediation plan, an open system is assumed, and Fe(II) is oxidized within the treatment system. Both plans increase instream pH and substantially reduce total and dissolved concentrations of Al, As, Cu, and Fe(II+III) at the terminus of the study reach. Dissolved Pb concentrations are reduced by ???18% under the first remediation plan due to sorption onto iron-(III) oxides within the treatment system and stream channel. In contrast, iron(III) oxides are limiting under the second remediation plan, and removal of dissolved Pb occurs primarily within the treatment system. This limitation results in an increase in dissolved Pb concentrations over existing conditions as additional downstream sources of Pb are not attenuated by

  17. Energy-Reduction Offloading Technique for Streaming Media Servers

    Directory of Open Access Journals (Sweden)

    Yeongpil Cho

    2016-01-01

    Full Text Available Recent growth in popularity of mobile video services raises a demand for one of the most popular and convenient methods of delivering multimedia data, video streaming. However, heterogeneity of currently existing mobile devices involves an issue of separate video transcoding for each type of mobile devices such as smartphones, tablet PCs, and smart TVs. As a result additional burden comes to media servers, which pretranscode multimedia data for number of clients. Regarding even higher increase of video data in the Internet in the future, the problem of media servers overload is impending. To struggle against the problem an offloading method is introduced in this paper. By the use of SorTube offloading framework video transcoding process is shifted from the centralized media server to the local offloading server. Thus, clients can receive personally customized video stream; meanwhile the overload of centralized servers is reduced.

  18. Short-term stream flow forecasting at Australian river sites using data-driven regression techniques

    CSIR Research Space (South Africa)

    Steyn, Melise

    2017-09-01

    Full Text Available This study proposes a computationally efficient solution to stream flow forecasting for river basins where historical time series data are available. Two data-driven modeling techniques are investigated, namely support vector regression...

  19. Macroinvertebrate assemblages in agricultural, mining, and urban tropical streams: implications for conservation and management.

    Science.gov (United States)

    Mwedzi, Tongayi; Bere, Taurai; Mangadze, Tinotenda

    2016-06-01

    The study evaluated the response of macroinvertebrate assemblages to changes in water quality in different land-use settings in Manyame catchment, Zimbabwe. Four land-use categories were identified: forested commercial farming, communal farming, Great Dyke mining (GDM) and urban areas. Macroinvertebrate community structure and physicochemical variables data were collected in two seasons from 41 sites following standard methods. Although not environmentally threatening, urban and GDM areas were characterised by higher conductivity, total dissolved solids, salinity, magnesium and hardness. Chlorides, total phosphates, total nitrogen, calcium, potassium and sodium were significantly highest in urban sites whilst dissolved oxygen (DO) was significantly higher in the forested commercial faming and GDM sites. Macroinvertebrate communities followed the observed changes in water quality. Macroinvertebrates in urban sites indicated severe pollution (e.g. Chironomidae) whilst those in forested commercial farming sites and GDM sites indicated relatively clean water (e.g. Notonemouridae). Forested watersheds together with good farm management practices are important in mitigating impacts of urbanisation and agriculture. Strategies that reduce oxygen-depleting substances must be devised to protect the health of Zimbabwean streams. The study affirms the wider applicability of the South African Scoring System in different land uses.

  20. Fast Adapting Ensemble: A New Algorithm for Mining Data Streams with Concept Drift

    Science.gov (United States)

    Ortíz Díaz, Agustín; Ramos-Jiménez, Gonzalo; Frías Blanco, Isvani; Caballero Mota, Yailé; Morales-Bueno, Rafael

    2015-01-01

    The treatment of large data streams in the presence of concept drifts is one of the main challenges in the field of data mining, particularly when the algorithms have to deal with concepts that disappear and then reappear. This paper presents a new algorithm, called Fast Adapting Ensemble (FAE), which adapts very quickly to both abrupt and gradual concept drifts, and has been specifically designed to deal with recurring concepts. FAE processes the learning examples in blocks of the same size, but it does not have to wait for the batch to be complete in order to adapt its base classification mechanism. FAE incorporates a drift detector to improve the handling of abrupt concept drifts and stores a set of inactive classifiers that represent old concepts, which are activated very quickly when these concepts reappear. We compare our new algorithm with various well-known learning algorithms, taking into account, common benchmark datasets. The experiments show promising results from the proposed algorithm (regarding accuracy and runtime), handling different types of concept drifts. PMID:25879051

  1. Comparison of braided-stream depositional environment and uranium deposits at Saint Anthony underground mine

    International Nuclear Information System (INIS)

    Baird, C.W.; Martin, K.W.; Lowry, R.M.

    1980-01-01

    United Nuclear's Saint Anthony mine, located in the Laguna district, produces uranium ore from the Jackpile sandstone unit of the Morrison Formation. The Jackpile sediments were deposited in a fluvial environment characterized by aridity, gentle slope, distant source area, and limited flow volume. Resultant stratigraphy consists of an intricate assemblage of trough and tabular cross-stratification grading to near massive bedding at some locations. Interbedded with the Jackpile sands are green mudstones and siltstones that commonly display irregular thicknesses of less than 2 ft and that are laterally discontinuous. Major penecontemporaneous and postdepositional alteration of originally deposited sands, silts, and clays includes: 1) infiltration and filling of interstices by kaolinitic clays; 2) mobilization and relocation of organic carbonaceous material; and 3) geochemical alteration of mineral constituents and fixation of uranium ions in organic carbonaceous material. Mineralized zones of economic volume display a spatial relationship to bedding features indicative of loosely packed sand deposited in dune and trough foresets. This relationship indicates possible permeability control by initial stratigraphy upon the flow of mineralizing solutions. Additionally, the low-energy foreset environment facilitates the accumulation of low-specific-gravity carbonaceous material necessary for interaction with mineralizing solutions. Large volumes of loosely packed foreset sands accumulate in transverse bars in braided-stream environments. These structures have a great potential for conducting large volumes of mineralizing fluids and hosting economic quantities of uranium ore

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

    Science.gov (United States)

    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 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.

  3. Techniques to correct and prevent acid mine drainage: A review

    OpenAIRE

    Pozo-Antonio, Santiago; Puente-Luna, Iván; Lagüela-López, Susana; Veiga-Ríos, María

    2014-01-01

    Acid mine drainage (AMD) from mining wastes is one of the current environmental problems in the field of mining pollution that requires most action measures. This term describes the drainage generated by natural oxidation of sulfide minerals when they are exposed to the combined action of water and atmospheric oxygen. AMD is characterized by acidic effluents with a high content of sulfate and heavy metal ions in solution, which can contaminate both groundwater and surface water. Minerals resp...

  4. WASTE WATER TREATMENT AND MANAGEMENT TECHNIQUES IN MINES

    OpenAIRE

    Navneet S. Pote*

    2017-01-01

    Mining industries enhance comfort of human life on one hand but this also cause pollution to air and water which are essential for survival of life. Therefore, mining and industrial activity adversely affects the ecosystem including wild life population due to deforestation, fragmentation, to habitat, air and water pollution. Eliminating the mining activities is not the solution to this problem. Hence, it is important to find the most suitable and applicable methods to reduce the pollution ca...

  5. Determination of intensity functions for predicting subsidence from coal mining, potash mining, and groundwater withdrawal using the influence function technique

    Energy Technology Data Exchange (ETDEWEB)

    Triplett, T; Yurchak, D [Twin Cities Research Center, Bureau of Mines, US Dept. of the Interior, Minneapolis, MN (United States)

    1997-12-31

    This paper presents research, conducted by the Bureau of Mines, on modifying the influence function method to predict subsidence. According to theory, this technique must incorporate an intensity function to represent the relative significance of the causes of subsidence. This paper shows that the inclusion of a reasonable intensity function increases the accuracy of the technique, then presents the required functions for case studies of longwall coal mining subsidence in Illinois, USA, potash mining subsidence in new Mexico, USA, and subsidence produced by ground water withdrawal in California, USA. Finally, the paper discusses a method to predict the resultant strain from a simply measured site constant and ground curvatures calculated by the technique. (orig.)

  6. Determination of intensity functions for predicting subsidence from coal mining, potash mining, and groundwater withdrawal using the influence function technique

    Energy Technology Data Exchange (ETDEWEB)

    Triplett, T.; Yurchak, D. [Twin Cities Research Center, Bureau of Mines, US Dept. of the Interior, Minneapolis, MN (United States)

    1996-12-31

    This paper presents research, conducted by the Bureau of Mines, on modifying the influence function method to predict subsidence. According to theory, this technique must incorporate an intensity function to represent the relative significance of the causes of subsidence. This paper shows that the inclusion of a reasonable intensity function increases the accuracy of the technique, then presents the required functions for case studies of longwall coal mining subsidence in Illinois, USA, potash mining subsidence in new Mexico, USA, and subsidence produced by ground water withdrawal in California, USA. Finally, the paper discusses a method to predict the resultant strain from a simply measured site constant and ground curvatures calculated by the technique. (orig.)

  7. A novel Neuro-fuzzy classification technique for data mining

    Directory of Open Access Journals (Sweden)

    Soumadip Ghosh

    2014-11-01

    Full Text Available In our study, we proposed a novel Neuro-fuzzy classification technique for data mining. The inputs to the Neuro-fuzzy classification system were fuzzified by applying generalized bell-shaped membership function. The proposed method utilized a fuzzification matrix in which the input patterns were associated with a degree of membership to different classes. Based on the value of degree of membership a pattern would be attributed to a specific category or class. We applied our method to ten benchmark data sets from the UCI machine learning repository for classification. Our objective was to analyze the proposed method and, therefore compare its performance with two powerful supervised classification algorithms Radial Basis Function Neural Network (RBFNN and Adaptive Neuro-fuzzy Inference System (ANFIS. We assessed the performance of these classification methods in terms of different performance measures such as accuracy, root-mean-square error, kappa statistic, true positive rate, false positive rate, precision, recall, and f-measure. In every aspect the proposed method proved to be superior to RBFNN and ANFIS algorithms.

  8. Construction accident narrative classification: An evaluation of text mining techniques.

    Science.gov (United States)

    Goh, Yang Miang; Ubeynarayana, C U

    2017-11-01

    Learning from past accidents is fundamental to accident prevention. Thus, accident and near miss reporting are encouraged by organizations and regulators. However, for organizations managing large safety databases, the time taken to accurately classify accident and near miss narratives will be very significant. This study aims to evaluate the utility of various text mining classification techniques in classifying 1000 publicly available construction accident narratives obtained from the US OSHA website. The study evaluated six machine learning algorithms, including support vector machine (SVM), linear regression (LR), random forest (RF), k-nearest neighbor (KNN), decision tree (DT) and Naive Bayes (NB), and found that SVM produced the best performance in classifying the test set of 251 cases. Further experimentation with tokenization of the processed text and non-linear SVM were also conducted. In addition, a grid search was conducted on the hyperparameters of the SVM models. It was found that the best performing classifiers were linear SVM with unigram tokenization and radial basis function (RBF) SVM with uni-gram tokenization. In view of its relative simplicity, the linear SVM is recommended. Across the 11 labels of accident causes or types, the precision of the linear SVM ranged from 0.5 to 1, recall ranged from 0.36 to 0.9 and F1 score was between 0.45 and 0.92. The reasons for misclassification were discussed and suggestions on ways to improve the performance were provided. Copyright © 2017 Elsevier Ltd. All rights reserved.

  9. Assessment of corn and banana leaves as potential standardized substrates for leaf decomposition in streams affected by mountaintop removal coal mining, West Virginia, USA

    Science.gov (United States)

    Mountaintop removal and valley filling is a method of coal mining that buries Central Appalachian headwater streams. A 2007 federal court ruling highlighted the need for measurement of both ecosystem structure and function when assessing streams for mitigaton. Rapid functional as...

  10. Assessment of stream bottom sediment quality in the vicinity of the Caldas uranium mine

    Energy Technology Data Exchange (ETDEWEB)

    Oliveira, Priscila E.S. de, E-mail: pge_13@hotmail.com [Universidade Federal de Ouro Preto (ProAmb/UFOP), Ouro Preto, MG (Brazil). Programa de Pos-Graduacao em Engenharia Ambiental; Filho, Carlos A.C.; Moreira, Rubens M.; Ramos, Maria E.A.F.; Dutra, Pedro H.; Ferreira, Vinicius V.M., E-mail: cacf@cdtn.br [Centro de Desenvolvimento da Tecnologia Nuclear (CDTN/CNEN-MG), Belo Horizonte (Brazil); Silva, Nivaldo C., E-mail: ncsilva@cnen.gov.br [Comissao Nacional de Energia Nuclear (LAPOC/CNEN-MG), Pocos de Caldas, MG (Brazil). Laboratorio de Pocos de Caldas

    2015-07-01

    An evaluation of the quality of stream bottom sediments was performed in the surroundings of the Caldas Uranium Mining and Milling Facilities (UMMF), sited on Pocos de Caldas Plateau (southeastern Brazil), to verify whether the sediments in the water bodies downstream the plant, were impacted by effluents from a large waste rock pile, named Waste Rock Pile 4 (WRP4), and from the Tailings Dam (TD). In order to perform the research, twelve sampling stations were established in the watersheds around Caldas UMMF: the Soberbo creek, the Consulta brook, and the Taquari river. One of the stations was located inside the Bacia Nestor Figueiredo, a retention pond that receives effluents from WRP4, and another in a settling tank (D2) for radium, which receives the effluents from TD. A monitoring scheme has been developed, comprising four sampling campaigns in 2010 and 2011, and the samples were analyzed for selected metals-metalloids and radionuclides, using Inductively Coupled Plasma Mass Spectrometry (ICP-MS), Inductively Coupled Plasma Atomic Emission Spectroscopy (ICP-AES), Ultraviolet-Visible (UV-Vis) Spectroscopy and Gamma-ray Spectrometry. The results suggest that effluents discharged from retention ponds to watercourses, causing an increase in the concentration of As, B, Ba, Cr, Mo, Mn, Pb, Zn, {sup 238}U, {sup 232}Th, {sup 226}Ra, {sup 228}Ra and {sup 210}Pb in sediments. Detailed investigation in sub-superficial layers is recommended at these locations to evaluate the need of implementing mitigation actions such as lining and constructing hydraulic barriers downstream the ponds. Actually, the UTM/Caldas operator is already implementing control measures. (author)

  11. Assessment of stream bottom sediment quality in the vicinity of the Caldas uranium mine

    International Nuclear Information System (INIS)

    Oliveira, Priscila E.S. de; Silva, Nivaldo C.

    2015-01-01

    An evaluation of the quality of stream bottom sediments was performed in the surroundings of the Caldas Uranium Mining and Milling Facilities (UMMF), sited on Pocos de Caldas Plateau (southeastern Brazil), to verify whether the sediments in the water bodies downstream the plant, were impacted by effluents from a large waste rock pile, named Waste Rock Pile 4 (WRP4), and from the Tailings Dam (TD). In order to perform the research, twelve sampling stations were established in the watersheds around Caldas UMMF: the Soberbo creek, the Consulta brook, and the Taquari river. One of the stations was located inside the Bacia Nestor Figueiredo, a retention pond that receives effluents from WRP4, and another in a settling tank (D2) for radium, which receives the effluents from TD. A monitoring scheme has been developed, comprising four sampling campaigns in 2010 and 2011, and the samples were analyzed for selected metals-metalloids and radionuclides, using Inductively Coupled Plasma Mass Spectrometry (ICP-MS), Inductively Coupled Plasma Atomic Emission Spectroscopy (ICP-AES), Ultraviolet-Visible (UV-Vis) Spectroscopy and Gamma-ray Spectrometry. The results suggest that effluents discharged from retention ponds to watercourses, causing an increase in the concentration of As, B, Ba, Cr, Mo, Mn, Pb, Zn, 238 U, 232 Th, 226 Ra, 228 Ra and 210 Pb in sediments. Detailed investigation in sub-superficial layers is recommended at these locations to evaluate the need of implementing mitigation actions such as lining and constructing hydraulic barriers downstream the ponds. Actually, the UTM/Caldas operator is already implementing control measures. (author)

  12. Technique for producing a continuous interference-free stream of Argon-41 in air

    International Nuclear Information System (INIS)

    Tseng, T.-T.; Jester, W.A.

    1984-01-01

    A monitoring system was developed for the detection of 131 I in the presence of orders of magnitude higher concentrations of radioactive noble gas. During the course of this work, a technique was developed for producing a continuous air stream of 41 Ar required for testing this concept. The 41 Ar stream is produced by the neutron activation of air using a research reactor. The 41 Ar content of the air stream can be varied by many orders of magnitude by varying the reactor power level and the rate at which the air is pumped through a vertically positioned tube in or in front of the reactor. It was found that the neutrons also activate other air constituents, producing undesirable interference radionuclides. Selective filtering techniques have therefore been developed to remove these interference radionuclides from the 41 Ar air stream

  13. Benthic Communities of Low-Order Streams Affected by Acid Mine Drainages: A Case Study from Central Europe

    Directory of Open Access Journals (Sweden)

    Marek Svitok

    2014-05-01

    Full Text Available Only little attention has been paid to the impact of acid mine drainages (AMD on aquatic ecosystems in Central Europe. In this study, we investigate the physico-chemical properties of low-order streams and the response of benthic invertebrates to AMD pollution in the Banská Štiavnica mining region (Slovakia. The studied streams showed typical signs of mine drainage pollution: higher conductivity, elevated iron, aluminum, zinc and copper loads and accumulations of ferric precipitates. Electric conductivity correlated strongly with most of the investigated elements (weighted mean absolute correlation = 0.95 and, therefore, can be recommended as a good proxy indicator for rapid AMD pollution assessments. The diversity and composition of invertebrate assemblages was related to water chemistry. Taxa richness decreased significantly along an AMD-intensity gradient. While moderately affected sites supported relatively rich assemblages, the harshest environmental conditions (pH < 2.5 were typical for the presence of a limited number of very tolerant taxa, such as Oligochaeta and some Diptera (Limnophyes, Forcipomyiinae. The trophic guild structure correlated significantly with AMD chemistry, whereby predators completely disappeared under the most severe AMD conditions. We also provide a brief review of the AMD literature and outline the needs for future detailed studies involving functional descriptors of the impact of AMD on aquatic ecosystems.

  14. Seasonal and spatial patterns of metals at a restored copper mine site. I. Stream copper and zinc

    International Nuclear Information System (INIS)

    Bambic, Dustin G.; Alpers, Charles N.; Green, Peter G.; Fanelli, Eileen; Silk, Wendy K.

    2006-01-01

    Seasonal and spatial variations in metal concentrations and pH were found in a stream at a restored copper mine site located near a massive sulfide deposit in the Foothill copper-zinc belt of the Sierra Nevada, California. At the mouth of the stream, copper concentrations increased and pH decreased with increased streamflow after the onset of winter rain and, unexpectedly, reached extreme values 1 or 2 months after peaks in the seasonal hydrographs. In contrast, aqueous zinc and sulfate concentrations were highest during low-flow periods. Spatial variation was assessed in 400 m of reach encompassing an acidic, metal-laden seep. At this seep, pH remained low (2-3) throughout the year, and copper concentrations were highest. In contrast, the zinc concentrations increased with downstream distance. These spatial patterns were caused by immobilization of copper by hydrous ferric oxides in benthic sediments, coupled with increasing downstream supply of zinc from groundwater seepage. - Seasonal hydrology and benthic sediments control copper and zinc concentrations in a stream through a restored mine site

  15. Statistical and Machine-Learning Data Mining Techniques for Better Predictive Modeling and Analysis of Big Data

    CERN Document Server

    Ratner, Bruce

    2011-01-01

    The second edition of a bestseller, Statistical and Machine-Learning Data Mining: Techniques for Better Predictive Modeling and Analysis of Big Data is still the only book, to date, to distinguish between statistical data mining and machine-learning data mining. The first edition, titled Statistical Modeling and Analysis for Database Marketing: Effective Techniques for Mining Big Data, contained 17 chapters of innovative and practical statistical data mining techniques. In this second edition, renamed to reflect the increased coverage of machine-learning data mining techniques, the author has

  16. Review of Data Mining Techniques for Churn Prediction in Telecom

    OpenAIRE

    Vishal Mahajan; Richa Misra; Renuka Mahajan

    2015-01-01

    Telecommunication sector generates a huge amount of data due to increasing number of subscribers, rapidly renewable technologies; data based applications and other value added service. This data can be usefully mined for churn analysis and prediction. Significant research had been undertaken by researchers worldwide to understand the data mining practices that can be used for predicting customer churn. This paper provides a review of around 100 recent journal articles starting from year 2000 ...

  17. A look at aerosol formation using data mining techniques

    Directory of Open Access Journals (Sweden)

    S. Hyvönen

    2005-01-01

    Full Text Available Atmospheric aerosol particle formation is frequently observed throughout the atmosphere, but despite various attempts of explanation, the processes behind it remain unclear. In this study data mining techniques were used to find the key parameters needed for atmospheric aerosol particle formation to occur. A dataset of 8 years of 80 variables collected at the boreal forest station (SMEAR II in Southern Finland was used, incorporating variables such as radiation, humidity, SO2, ozone and present aerosol surface area. This data was analyzed using clustering and classification methods. The aim of this approach was to gain new parameters independent of any subjective interpretation. This resulted in two key parameters, relative humidity and preexisting aerosol particle surface (condensation sink, capable in explaining 88% of the nucleation events. The inclusion of any further parameters did not improve the results notably. Using these two variables it was possible to derive a nucleation probability function. Interestingly, the two most important variables are related to mechanisms that prevent the nucleation from starting and particles from growing, while parameters related to initiation of particle formation seemed to be less important. Nucleation occurs only with low relative humidity and condensation sink values. One possible explanation for the effect of high water content is that it prevents biogenic hydrocarbon ozonolysis reactions from producing sufficient amounts of low volatility compounds, which might be able to nucleate. Unfortunately the most important biogenic hydrocarbon compound emissions were not available for this study. Another effect of water vapour may be due to its linkage to cloudiness which may prevent the formation of nucleating and/or condensing vapours. A high number of preexisting particles will act as a sink for condensable vapours that otherwise would have been able to form sufficient supersaturation and initiate the

  18. Application of integrated data mining techniques in stock market forecasting

    Directory of Open Access Journals (Sweden)

    Chin-Yin Huang

    2014-12-01

    Full Text Available Stock market is considered too uncertain to be predictable. Many individuals have developed methodologies or models to increase the probability of making a profit in their stock investment. The overall hit rates of these methodologies and models are generally too low to be practical for real-world application. One of the major reasons is the huge fluctuation of the market. Therefore, the current research focuses in the stock forecasting area is to improve the accuracy of stock trading forecast. This paper introduces a system that addresses the particular need. The system integrates various data mining techniques and supports the decision-making for stock trades. The proposed system embeds the top-down trading theory, artificial neural network theory, technical analysis, dynamic time series theory, and Bayesian probability theory. To experimentally examine the trading return of the presented system, two examples are studied. The first uses the Taiwan Semiconductor Manufacturing Company (TSMC data-set that covers an investment horizon of 240 trading days from 16 February 2011 to 23 January 2013. Eighty four transactions were made using the proposed approach and the investment return of the portfolio was 54% with an 80.4% hit rate during a 12-month period in which the TSMC stock price increased by 25% (from $NT 78.5 to $NT 101.5. The second example examines the stock data of Evergreen Marine Corporation, an international marine shipping company. Sixty four transactions were made and the investment return of the portfolio was 128% in 12 months. Given the remarkable investment returns in trading the example TSMC and Evergreen stocks, the proposed system demonstrates promising potentials as a viable tool for stock market forecasting.

  19. Occurrence and transport of selected constituents in streams near the Stibnite mining area, Central Idaho, 2012–14

    Science.gov (United States)

    Etheridge, Alexandra B.

    2015-12-07

    Mining of stibnite (antimony sulfide), tungsten, gold, silver, and mercury near the town of Stibnite in central Idaho has left a legacy of trace element contamination in local streams. Water-quality and streamflow monitoring data from a network of five streamflow-gaging stations were used to estimate trace-element and suspended-sediment loads and flow-weighted concentrations in the Stibnite mining area between 2012 and 2014. Measured concentrations of arsenic exceeded human health-based water-quality criteria at each streamflow-gaging station, except for Meadow Creek (site 2), which was selected to represent background conditions in the study area. Measured concentrations of antimony exceeded human health-based water-quality criteria at sites 3, 4, and 5.

  20. In situ studies with Asian clams (Carbacula fluminea) detect acid mine drainage and nutrient inputs in low-order streams

    International Nuclear Information System (INIS)

    Soucek, D. J.; Schmidt, T. S.; Cherry, D. S.

    2001-01-01

    This study evaluates the correlation between transplanted Asiatic clam and indigenous community responses to acid mine drainage and nutrient loading in first-to-third-order streams, by comparing the toxicological endpoints of clam survival and growth with benthic macro-invertebrate community indices as community responses to both acid mine drainage and nutrient loading. Clam survival was found to be positively correlated with water column pH and negatively correlated with conductivity and metal concentrations. There was also a positive correlation with the relative abundance of the macro-invertebrate Ephemeroptera, the most sensitive taxonomic group, to acid mine drainage in this watershed. No correlation was found between clam growth and acid mine drainage inputs, but there was evidence of positive correlation with nitrate concentrations and the relative abundance of collector-filterer functional feeding groups. These results suggest that clam growth is related to nutrient levels and accurately reflect benthic macro-invertebrate responses to nutrient loading. 28 refs., 5 tabs., 1 fig

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

    Science.gov (United States)

    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 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.

  2. Relationships among exceedences of metals criteria, the results of ambient bioassays, and community metrics in mining-impacted streams.

    Science.gov (United States)

    Griffith, Michael B; Lazorchak, James M; Herlihy, Alan T

    2004-07-01

    If bioassessments are to help diagnose the specific environmental stressors affecting streams, a better understanding is needed of the relationships between community metrics and ambient criteria or ambient bioassays. However, this relationship is not simple, because metrics assess responses at the community level of biological organization, while ambient criteria and ambient bioassays assess or are based on responses at the individual level. For metals, the relationship is further complicated by the influence of other chemical variables, such as hardness, on their bioavailability and toxicity. In 1993 and 1994, U.S. Environmental Protection Agency (U.S. EPA) conducted a Regional Environmental Monitoring and Assessment Program (REMAP) survey on wadeable streams in Colorado's (USA) Southern Rockies Ecoregion. In this ecoregion, mining over the past century has resulted in metals contamination of streams. The surveys collected data on fish and macroinvertebrate assemblages, physical habitat, and sediment and water chemistry and toxicity. These data provide a framework for assessing diagnostic community metrics for specific environmental stressors. We characterized streams as metals-affected based on exceedence of hardness-adjusted criteria for cadmium, copper, lead, and zinc in water; on water toxicity tests (48-h Pimephales promelas and Ceriodaphnia dubia survival); on exceedence of sediment threshold effect levels (TELs); or on sediment toxicity tests (7-d Hyalella azteca survival and growth). Macroinvertebrate and fish metrics were compared among affected and unaffected sites to identify metrics sensitive to metals. Several macroinvertebrate metrics, particularly richness metrics, were less in affected streams, while other metrics were not. This is a function of the sensitivity of the individual metrics to metals effects. Fish metrics were less sensitive to metals because of the low diversity of fish in these streams.

  3. The ClusTree : indexing micro-clusters for anytime stream mining

    DEFF Research Database (Denmark)

    Kranen, Philipp; Assent, Ira; Baldauf, Corinna

    2011-01-01

    -arrival times of the stream. Likewise, memory is limited, making it impossible to store all data. For clustering, we are faced with the challenge of maintaining a current result that can be presented to the user at any given time. In this work, we propose a parameter-free algorithm that automatically adapts...... introduce the ClusTree, a compact and self-adaptive index structure for maintaining stream summaries. Additionally we present solutions to handle very fast streams through aggregation mechanisms and propose novel descent strategies that improve the clustering result on slower streams as long as time permits...

  4. Managing Multiuser Database Buffers Using Data Mining Techniques

    NARCIS (Netherlands)

    Feng, L.; Lu, H.J.

    2004-01-01

    In this paper, we propose a data-mining-based approach to public buffer management for a multiuser database system, where database buffers are organized into two areas – public and private. While the private buffer areas contain pages to be updated by particular users, the public

  5. High-resolution, short-range, in-mine geophysical techniques for the delineation of South African orebodies

    CSIR Research Space (South Africa)

    Van Schoor, Abraham M

    2006-02-28

    Full Text Available ) • Geophysical techniques Ground penetrating radar (GPR) Borehole radar Electrical resistance tomography (ERT) • Case studies Waterval Mine (GPR) Mponeng Gold Mine (Borehole Radar) Western Platinum Mine (ERT) • Conclusion • Future research... equivalent – e.g. electrical resistance tomography (ERT) is based on medical impedance tomography Gold and platinum mining in South Africa An overview Slide 9 © CSIR 2006 www.csir.co.za Gold and platinum mining in South Africa...

  6. STREAM

    DEFF Research Database (Denmark)

    Godsk, Mikkel

    This paper presents a flexible model, ‘STREAM’, for transforming higher science education into blended and online learning. The model is inspired by ideas of active and collaborative learning and builds on feedback strategies well-known from Just-in-Time Teaching, Flipped Classroom, and Peer...... Instruction. The aim of the model is to provide both a concrete and comprehensible design toolkit for adopting and implementing educational technologies in higher science teaching practice and at the same time comply with diverse ambitions. As opposed to the above-mentioned feedback strategies, the STREAM...... model supports a relatively diverse use of educational technologies and may also be used to transform teaching into completely online learning. So far both teachers and educational developers have positively received the model and the initial design experiences show promise....

  7. Radiation shielding techniques and applications. 3. Analysis of Photon Streaming Through and Around Shield Doors

    International Nuclear Information System (INIS)

    Barnett, Marvin; Hack, Joe; Nathan, Steve; White, Travis

    2001-01-01

    Westinghouse Safety Management Solutions (Westinghouse SMS) has been tasked with providing radiological engineering design support for the new Commercial Light Water Reactor Tritium Extraction Facility (CLWR-TEF) being constructed at the Savannah River Site (SRS). The Remote Handling Building (RHB) of the CLWR-TEF will act as the receiving facility for irradiated targets used in the production of tritium for the U.S. Department of Energy (DOE). Because of the high dose rates, approaching 50 000 rads/h (500 Gy/h) from the irradiated target bundles, significant attention has been made to shielding structures within the facility. One aspect of the design that has undergone intense review is the shield doors. The RHB has six shield doors that needed to be studied with respect to photon streaming. Several aspects had to be examined to ensure that the design meets the radiation dose levels. Both the thickness and streaming issues around the door edges were designed and examined. Photon streaming through and around a shield door is a complicated problem, creating a reliance on computer modeling to perform the analyses. The computer code typically used by the Westinghouse SMS in the evaluation of photon transport through complex geometries is the MCNP Monte Carlo computer code. The complexity of the geometry within the problem can cause problems even with the Monte Carlo codes. Striking a balance between how the code handles transport through the shield door with transport through the streaming paths, particularly with the use of typical variance reduction methods, is difficult when trying to ensure that all important regions of the model are sampled appropriately. The thickness determination used a simple variance reduction technique. In construction, the shield door will not be flush against the wall, so a solid rectangular slab leaves streaming paths around the edges. Administrative controls could be used to control dose to workers; however, 10 CFR 835.1001 states

  8. Adsorption of copper, cadmium and zinc on suspended sediments in a stream contaminated by acid mine drainage: The effect of seasonal changes in dissolved organic carbon

    International Nuclear Information System (INIS)

    Macalady, D.L.; Ranville, J.F.; Smith, K.S.; Daniel, S.R.

    1991-01-01

    The release of metal-rich, acidic waters from abandoned mining operations is a major problem in Colorado and throughout the Western United States. In Colorado, over 600 km of stream reach are estimated to be affected by such releases (Wentz, 1974). The metals released adversely affect stream biota, including fish. It is therefore important to understand the chemical processes which influence metal transport in these waters. The report details studies of the role of suspended sediments with respect to the transport of several important trace metals in a stream impacted by acid mine drainage. The role of streambed sediments was studied in the same system as part of an earlier project (Acid Mine Drainage: streambed sorption of copper, cadmium and zinc, PB--93-118263)

  9. Stable Carbon Isotope Characterization of CO2 Loss in Acid Mine Drainage Impacted Stream Water: Observations from a Laboratory Experiment

    Science.gov (United States)

    Ali, H. N.; Atekwana, E. A.

    2007-05-01

    Water from an acid mine drainage spring, ground water from a mine tailings pile, stream water and tap water were acidified to simulate acid mine drainage (AMD) contamination. The objective was to determine how acidification of stream water by AMD affected DIC loss and carbon isotope fraction. Two 20 L HDP containers (reactors) containing samples from each source were left un-acidified and allowed to evolve under ambient conditions for several weeks in the laboratory and two others were acidified. Acidification was carried out progressively with sulfuric acid to pH <3. For acidified samples, one reactor was acidified open to the atmosphere and the other closed from contact with atmosphere and CO2(g) was collected under vacuum. The un-acidified samples did not show significant alkalinity and DIC loss, and the 13C of DIC was enriched with time. The acidified samples showed decrease in alkalinity and DIC and increase in the 13C of DIC and CO2(g) with progressive acidification. The enrichment of 13C of DIC for un-acidified samples was due to exchange with atmospheric CO2. On the other hand, the 13C enrichment in the acidified samples was due to fractionation during dehydration of HCO3- and diffusive loss of CO2(g) from the aqueous phase. The actual values measured depended on the amount of CO2 lost from the aqueous phase during acidification. Samples with greater CO2 loss (closed acidification) had greater 13C enrichment. Beyond the HCO3- titration end point, the δ13C of DIC and CO2(g) was similar and nearly constant. The result of this study suggests that AMD effects on DIC can be modeled as a first order kinetic reaction and the isotope enrichment modeled using Rayleigh distillation.

  10. Fractionation of chemical elements including the REEs and 226Ra in stream contaminated with coal-mine effluent

    International Nuclear Information System (INIS)

    Centeno, L.M.; Faure, G.; Lee, G.; Talnagi, J.

    2004-01-01

    Water draining from abandoned open-pit coal mines in southeastern Ohio typically has a low pH and high concentrations of Fe, Al and Mn, as well as of trace metals (Pb, Cu, Zn, Ni, Co, etc.) and of the rare earth elements (REEs). The cations of different elements are sorbed selectively by Fe and Al hydroxide precipitates which form with increasing pH. As a result, the trace elements are separated from each other when the hydroxide precipitates are deposited in the channel of a flowing stream. Therefore, the low-energy environment of a stream contaminated by mine effluent is a favorable site for the chemical fractionation of the REEs and of other groups of elements with similar chemical properties. The interpretation of chemical analyses of water collected along a 30-km-stretch of Rush Creek near the town of New Lexington, Perry County, Ohio, indicates that the abundances of the REEs in the water appear to change downstream when they are normalized to the REE concentrations of the mine effluent. In addition, the Ce/La ratios (and those of all REEs) in the water decrease consistently downstream. The evidence indicates that the REEs which remain in solution are enriched La and Ce because the other REEs are sorbed more efficiently. The solid Fe(OH) 3 precipitates in the channel of Rush Creek upstream of New Lexington also contain radioactive 226 Ra that was sorbed from the water. This isotope of Ra is a decay product of 238 U which occurs in the Middle Pennsylvanian (Upper Carboniferous) coal and in the associated shale of southeastern Ohio. The activity of 226 Ra of the Fe(OH) 3 precipitates increases with rising pH, but then declines farther downstream as the concentration of Ra remaining in the water decreases

  11. Real-time analytics techniques to analyze and visualize streaming data

    CERN Document Server

    Ellis, Byron

    2014-01-01

    Construct a robust end-to-end solution for analyzing and visualizing streaming data Real-time analytics is the hottest topic in data analytics today. In Real-Time Analytics: Techniques to Analyze and Visualize Streaming Data, expert Byron Ellis teaches data analysts technologies to build an effective real-time analytics platform. This platform can then be used to make sense of the constantly changing data that is beginning to outpace traditional batch-based analysis platforms. The author is among a very few leading experts in the field. He has a prestigious background in research, development,

  12. Survey of Insurance Fraud Detection Using Data Mining Techniques

    OpenAIRE

    Sithic, H. Lookman; Balasubramanian, T.

    2013-01-01

    With an increase in financial accounting fraud in the current economic scenario experienced, financial accounting fraud detection has become an emerging topics of great importance for academics, research and industries. Financial fraud is a deliberate act that is contrary to law, rule or policy with intent to obtain unauthorized financial benefit and intentional misstatements or omission of amounts by deceiving users of financial statements, especially investors and creditors. Data mining tec...

  13. Stochastic production phase design for an open pit mining complex with multiple processing streams

    Science.gov (United States)

    Asad, Mohammad Waqar Ali; Dimitrakopoulos, Roussos; van Eldert, Jeroen

    2014-08-01

    In a mining complex, the mine is a source of supply of valuable material (ore) to a number of processes that convert the raw ore to a saleable product or a metal concentrate for production of the refined metal. In this context, expected variation in metal content throughout the extent of the orebody defines the inherent uncertainty in the supply of ore, which impacts the subsequent ore and metal production targets. Traditional optimization methods for designing production phases and ultimate pit limit of an open pit mine not only ignore the uncertainty in metal content, but, in addition, commonly assume that the mine delivers ore to a single processing facility. A stochastic network flow approach is proposed that jointly integrates uncertainty in supply of ore and multiple ore destinations into the development of production phase design and ultimate pit limit. An application at a copper mine demonstrates the intricacies of the new approach. The case study shows a 14% higher discounted cash flow when compared to the traditional approach.

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

    DEFF Research Database (Denmark)

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

    2012-01-01

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

  15. Application of schlieren techniques for improved understanding of underground mine ventilation

    International Nuclear Information System (INIS)

    Jong, E.C.; Luxbacher, K.D.

    2010-01-01

    Mine ventilation systems must be maintained in optimal running order in order to suppress dusts and provide fresh air to mine workers. However, it is difficult to gather representative ventilation data because of the dynamic nature of mines, including geologic conditions, equipment operations, personnel movements, advance of mine openings and atmospheric changes. Errors and imprecision in computer codes can be detrimental to mine forecasting. The best way to improve the validity of ventilation models is to increase the quality of survey data. This study examined the feasibility of using the background-oriented schlieren (BOS) flow visualization method to reach this objective. Schlieren techniques involve the use of refractive properties of different air densities to enhance the distortions of light, thereby allowing airflow to be visualized. In this study, the BOS technique was used to image flow with 2 fans, an axivane fan and a custom built axial flow fan. The results showed that the BOS technique can clearly display air flow under the correct conditions. Producing an accurate picture of air flow can improve the industry's overall understanding of air flow and resistance, thus improving mine safety and productivity. 8 refs., 7 figs.

  16. Application of schlieren techniques for improved understanding of underground mine ventilation

    Energy Technology Data Exchange (ETDEWEB)

    Jong, E.C.; Luxbacher, K.D. [Virginia Tech, Blacksburg, VA (United States)

    2010-07-01

    Mine ventilation systems must be maintained in optimal running order in order to suppress dusts and provide fresh air to mine workers. However, it is difficult to gather representative ventilation data because of the dynamic nature of mines, including geologic conditions, equipment operations, personnel movements, advance of mine openings and atmospheric changes. Errors and imprecision in computer codes can be detrimental to mine forecasting. The best way to improve the validity of ventilation models is to increase the quality of survey data. This study examined the feasibility of using the background-oriented schlieren (BOS) flow visualization method to reach this objective. Schlieren techniques involve the use of refractive properties of different air densities to enhance the distortions of light, thereby allowing airflow to be visualized. In this study, the BOS technique was used to image flow with 2 fans, an axivane fan and a custom built axial flow fan. The results showed that the BOS technique can clearly display air flow under the correct conditions. Producing an accurate picture of air flow can improve the industry's overall understanding of air flow and resistance, thus improving mine safety and productivity. 8 refs., 7 figs.

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

    Science.gov (United States)

    Warrer, Pernille; Hansen, Ebba Holme; Juhl-Jensen, Lars; Aagaard, Lise

    2012-05-01

    This literature review included studies that use text-mining techniques in narrative documents stored in electronic patient records (EPRs) to investigate ADRs. We searched PubMed, Embase, Web of Science and International Pharmaceutical Abstracts without restrictions from origin until July 2011. We included empirically based studies on text mining of electronic patient records (EPRs) that focused on detecting ADRs, excluding those that investigated adverse events not related to medicine use. We extracted information on study populations, EPR data sources, frequencies and types of the identified ADRs, medicines associated with ADRs, text-mining algorithms used and their performance. Seven studies, all from the United States, were eligible for inclusion in the review. Studies were published from 2001, the majority between 2009 and 2010. Text-mining techniques varied over time from simple free text searching of outpatient visit notes and inpatient discharge summaries to more advanced techniques involving natural language processing (NLP) of inpatient discharge summaries. Performance appeared to increase with the use of NLP, although many ADRs were still missed. Due to differences in study design and populations, various types of ADRs were identified and thus we could not make comparisons across studies. The review underscores the feasibility and potential of text mining to investigate narrative documents in EPRs for ADRs. However, more empirical studies are needed to evaluate whether text mining of EPRs can be used systematically to collect new information about ADRs. © 2011 The Authors. British Journal of Clinical Pharmacology © 2011 The British Pharmacological Society.

  18. Data mining techniques in sensor networks summarization, interpolation and surveillance

    CERN Document Server

    Appice, Annalisa; Fumarola, Fabio; Malerba, Donato

    2013-01-01

    Sensor networks comprise of a number of sensors installed across a spatially distributed network, which gather information and periodically feed a central server with the measured data. The server monitors the data, issues possible alarms and computes fast aggregates. As data analysis requests may concern both present and past data, the server is forced to store the entire stream. But the limited storage capacity of a server may reduce the amount of data stored on the disk. One solution is to compute summaries of the data as it arrives, and to use these summaries to interpolate the real data.

  19. Development of testing techniques for mine fan performance

    Institute of Scientific and Technical Information of China (English)

    WU Zheng-yan; JIANG Shu-guang; PENG Dan-ren

    2006-01-01

    Three progressive stages of testing techniques are elaborated, which are entirely manual operating, taking separate instruments testing and computer program controlling. The testing method and principle are detailed based on the testing process for meteorological parameters, air pressure, air quality and rotating velocity. And every testing technique is analyzed. Finally, the technique outlook is viewed. All this plays a leading role in development of the testing techniques.

  20. A Review of Financial Accounting Fraud Detection based on Data Mining Techniques

    Science.gov (United States)

    Sharma, Anuj; Kumar Panigrahi, Prabin

    2012-02-01

    With an upsurge in financial accounting fraud in the current economic scenario experienced, financial accounting fraud detection (FAFD) has become an emerging topic of great importance for academic, research and industries. The failure of internal auditing system of the organization in identifying the accounting frauds has lead to use of specialized procedures to detect financial accounting fraud, collective known as forensic accounting. Data mining techniques are providing great aid in financial accounting fraud detection, since dealing with the large data volumes and complexities of financial data are big challenges for forensic accounting. This paper presents a comprehensive review of the literature on the application of data mining techniques for the detection of financial accounting fraud and proposes a framework for data mining techniques based accounting fraud detection. The systematic and comprehensive literature review of the data mining techniques applicable to financial accounting fraud detection may provide a foundation to future research in this field. The findings of this review show that data mining techniques like logistic models, neural networks, Bayesian belief network, and decision trees have been applied most extensively to provide primary solutions to the problems inherent in the detection and classification of fraudulent data.

  1. Data Mining Streams of Social Networks, A Tool to Improve The Library Services

    OpenAIRE

    Jaramillo Valbuena, Sonia; Cardona, Sergio Augusto; Fernández, Alejandro

    2015-01-01

    Los sistemas de soporte al trabajo colaborativo son herramientas valiosas en contextos en los cuales se requiere la participación de un grupo de personas para llevar a cabo una determinada tarea. Uno de estos contextos es la Bibliotecología, Archivística y Documentación. Las interacciones entre los usuarios y profesionales de esta área, mediante el uso de herramientas tales como Twitter, Facebook, fuentes RSS y blogs, generan grandes flujos de datos (streams) no estructurados. Estos streams p...

  2. Financial planning and analysis techniques of mining firms: a note on Canadian practice

    Energy Technology Data Exchange (ETDEWEB)

    Blanco, H.; Zanibbi, L.R. (Laurentian University, Sudbury, ON (Canada). School of Commerce and Administration)

    1992-06-01

    This paper reports on the results of a survey of the financial planning and analysis techniques in use in the mining industry in Canada. The study was undertaken to determine the current status of these practices within mining firms in Canada and to investigate the extent to which the techniques are grouped together within individual firms. In addition, tests were performed on the relationship between these groups of techniques and both organizational size and price volatility of end product. The results show that a few techniques are widely utilized in this industry but that the techniques used most frequently are not as sophisticated as reported in previous, more broadly based surveys. The results also show that firms tend to use 'bundles' of techniques and that the relative use of some of these groups of techniques is weakly associated with both organizational size and type of end product. 19 refs., 7 tabs.

  3. Assessing Lost Ecosystem Service Benefits Due to Mining-Induced Stream Degradation in the Appalachian Region: Economic Approaches to Valuing Recreational Fishing Impacts

    Science.gov (United States)

    Sport fishing is a popular activity for Appalachian residents and visitors. The region’s coldwater streams support a strong regional outdoor tourism industry. We examined the influence of surface coal mining, in the context of other stressors, on freshwater sport fishing in...

  4. Privacy-Preserving Data Mining of Medical Data Using Data Separation-Based Techniques

    Directory of Open Access Journals (Sweden)

    Gang Kou

    2007-08-01

    Full Text Available Data mining is concerned with the extraction of useful knowledge from various types of data. Medical data mining has been a popular data mining topic of late. Compared with other data mining areas, medical data mining has some unique characteristics. Because medical files are related to human subjects, privacy concerns are taken more seriously than other data mining tasks. This paper applied data separation-based techniques to preserve privacy in classification of medical data. We take two approaches to protect privacy: one approach is to vertically partition the medical data and mine these partitioned data at multiple sites; the other approach is to horizontally split data across multiple sites. In the vertical partition approach, each site uses a portion of the attributes to compute its results, and the distributed results are assembled at a central trusted party using a majority-vote ensemble method. In the horizontal partition approach, data are distributed among several sites. Each site computes its own data, and a central trusted party is responsible to integrate these results. We implement these two approaches using medical datasets from UCI KDD archive and report the experimental results.

  5. Exploring the potential of data mining techniques for the analysis of accident patterns

    DEFF Research Database (Denmark)

    Prato, Carlo Giacomo; Bekhor, Shlomo; Galtzur, Ayelet

    2010-01-01

    Research in road safety faces major challenges: individuation of the most significant determinants of traffic accidents, recognition of the most recurrent accident patterns, and allocation of resources necessary to address the most relevant issues. This paper intends to comprehend which data mining...... and association rules) data mining techniques are implemented for the analysis of traffic accidents occurred in Israel between 2001 and 2004. Results show that descriptive techniques are useful to classify the large amount of analyzed accidents, even though introduce problems with respect to the clear...... importance of input and intermediate neurons, and the relative importance of hundreds of association rules. Further research should investigate whether limiting the analysis to fatal accidents would simplify the task of data mining techniques in recognizing accident patterns without the “noise” probably...

  6. A survey of text clustering techniques used for web mining

    Directory of Open Access Journals (Sweden)

    Dan MUNTEANU

    2005-12-01

    Full Text Available This paper contains an overview of basic formulations and approaches to clustering. Then it presents two important clustering paradigms: a bottom-up agglomerative technique, which collects similar documents into larger and larger groups, and a top-down partitioning technique, which divides a corpus into topic-oriented partitions.

  7. Quality and mutagenicity of water and sediment of the streams impacted by the former uranium mine area Olší-Drahonín (Czech Republic).

    Science.gov (United States)

    Hudcová, H; Badurová, J; Rozkošný, M; Sova, J; Funková, R; Svobodová, J

    2013-02-01

    The water quality research performed in the years 2003-2010 demonstrated an impact of the mine water pumped from the closed Olší uranium mine and discharged from the mine water treatment plant (MWTP) and groundwater from springs in the area on the water quality of the Hadůvka stream. The water ecosystems of the lower part of the Hadůvka stream are impacted mainly by water originated from the springs located in the stream valley and drained syenit subsoil, naturally rich in uranium. Those inflows caused a very high concentration of uranium measured in the water of the stream, which exceeds the given limit value. No negative impact on the water ecosystems of the receiving Bobrůvka River was found. This reduction of impact is caused by five times higher average daily flow rate of the Bobrůvka River in comparison with the Hadůvka stream, which results in a sufficient dilution of pollution from the Hadůvka. Copyright © 2012 Elsevier Ltd. All rights reserved.

  8. Variance reduction techniques for 14 MeV neutron streaming problem in rectangular annular bent duct

    Energy Technology Data Exchange (ETDEWEB)

    Ueki, Kotaro [Ship Research Inst., Mitaka, Tokyo (Japan)

    1998-03-01

    Monte Carlo method is the powerful technique for solving wide range of radiation transport problems. Its features are that it can solve the Boltzmann`s transport equation almost without approximation, and that the complexity of the systems to be treated rarely becomes a problem. However, the Monte Carlo calculation is always accompanied by statistical errors called variance. In shielding calculation, standard deviation or fractional standard deviation (FSD) is used frequently. The expression of the FSD is shown. Radiation shielding problems are roughly divided into transmission through deep layer and streaming problem. In the streaming problem, the large difference in the weight depending on the history of particles makes the FSD of Monte Carlo calculation worse. The streaming experiment in the 14 MeV neutron rectangular annular bent duct, which is the typical streaming bench mark experiment carried out of the OKTAVIAN of Osaka University, was analyzed by MCNP 4B, and the reduction of variance or FSD was attempted. The experimental system is shown. The analysis model by MCNP 4B, the input data and the results of analysis are reported, and the comparison with the experimental results was examined. (K.I.)

  9. Restoration Potential of a Mining-Impacted Urban Stream: Horseshoe Branch of Lion Creek, Oakland, CA

    OpenAIRE

    Hackenjos, Bethany; Woelfle-Erskine, Cleo; Wood, Jacob

    2010-01-01

    Horseshoe Creek, located in the Oakland Hills of California, flows through a remnant oak and redwood forests in Horseshoe Canyon. From the 1880s through the 1930s, nearby Leona sulfur mine deposited massive tailings piles in the valleys east of Horseshoe Creek. During that time, clear-cut logging of redwoods denuded and destabilized the surrounding hillsides. Today, most of Horseshoe Creekʼs upper and middle reaches are either culverted or transformed into an engineered channel, and Merritt C...

  10. Reliable cost effective technique for in situ ground stress measurements in deep gold mines.

    CSIR Research Space (South Africa)

    Stacey, TR

    1995-07-01

    Full Text Available on these requirements, an in situ stress measurement technique which will be practically applicable in the deep gold mines, has been developed conceptually. Referring to the figure on the following page, this method involves: • a borehole-based system, using... level mines have not been developed. 2 This is some of the background to the present SIMRAC research project, the title ofwhich is “Reliable cost effective technique for in-situ ground stress measurements in deep gold mines”. A copy of the research...

  11. The precipitation of indium at elevated pH in a stream influenced by acid mine drainage

    Science.gov (United States)

    White, Sarah Jane O.; Hussain, Fatima A.; Hemond, Harold F.; Sacco, Sarah A.; Shine, James P.; Runkel, Robert L.; Walton-Day, Katherine; Kimball, Briant A.

    2017-01-01

    Indium is an increasingly important metal in semiconductors and electronics and has uses in important energy technologies such as photovoltaic cells and light-emitting diodes (LEDs). One significant flux of indium to the environment is from lead, zinc, copper, and tin mining and smelting, but little is known about its aqueous behavior after it is mobilized. In this study, we use Mineral Creek, a headwater stream in southwestern Colorado severely affected by heavy metal contamination as a result of acid mine drainage, as a natural laboratory to study the aqueous behavior of indium. At the existing pH of ~ 3, indium concentrations are 6–29 μg/L (10,000 × those found in natural rivers), and are completely filterable through a 0.45 μm filter. During a pH modification experiment, the pH of the system was raised to > 8, and > 99% of the indium became associated with the suspended solid phase (i.e. does not pass through a 0.45 μm filter). To determine the mechanism of removal of indium from the filterable and likely primarily dissolved phase, we conducted laboratory experiments to determine an upper bound for a sorption constant to iron oxides, and used this, along with other published thermodynamic constants, to model the partitioning of indium in Mineral Creek. Modeling results suggest that the removal of indium from the filterable phase is consistent with precipitation of indium hydroxide from a dissolved phase. This work demonstrates that nonferrous mining processes can be a significant source of indium to the environment, and provides critical information about the aqueous behavior of indium.

  12. Quality and mutagenicity of water and sediment of the streams impacted by the former uranium mine area Olší–Drahonín (Czech Republic)

    International Nuclear Information System (INIS)

    Hudcová, H.; Badurová, J.; Rozkošný, M.; Sova, J.; Funková, R.; Svobodová, J.

    2013-01-01

    The water quality research performed in the years 2003–2010 demonstrated an impact of the mine water pumped from the closed Olší uranium mine and discharged from the mine water treatment plant (MWTP) and groundwater from springs in the area on the water quality of the Hadůvka stream. The water ecosystems of the lower part of the Hadůvka stream are impacted mainly by water originated from the springs located in the stream valley and drained syenit subsoil, naturally rich in uranium. Those inflows caused a very high concentration of uranium measured in the water of the stream, which exceeds the given limit value. No negative impact on the water ecosystems of the receiving Bobrůvka River was found. This reduction of impact is caused by five times higher average daily flow rate of the Bobrůvka River in comparison with the Hadůvka stream, which results in a sufficient dilution of pollution from the Hadůvka. - Highlights: ► No significant impact of former uranium mining in the Olší mine area on the water ecosystems. ► The water ecosystems impacted mainly by natural sources of uranium. ► The occurrence of mutagenic compounds in the surface water was found using Ames fluctuated test. ► The mutagenicity was repeatedly detected in sediments. ► None of the samples showed cytotoxic effects in tests with S. typhimurium or P. phosphoreum organisms.

  13. Techniques to correct and prevent acid mine drainage: A review

    Directory of Open Access Journals (Sweden)

    Santiago Pozo-Antonio

    2014-01-01

    Full Text Available En la actualidad uno de los problemas medioambientales con mayor necesidad de actuación es la contaminación por la formación de drenajes ácidos de mina (AMD: “Acid Mine Drainage” procedentes de estériles de mina. Este es el término utilizado para describir el drenaje generado por la oxidación natural de sulfuros minerales que son expuestos a la acción combinada de agua y oxígeno atmosférico. Los minerales responsables de la generación de AMD son los sulfuros de hierro (pirita, FeS2 y en menor medida la pirrotita, Fe1-XS, los cuales son estables e insolubles mientras no se encuentren en contacto con agua y oxígeno atmosférico. Sin embargo, como consecuencia de la actividad minera, estos dos sulfuros son expuestos a condiciones ambientales oxidantes. La necesidad de prevenir la formación de AMD ha desarrollado numerosas investigaciones sobre los mecanismos de oxidación y su prevención. En el presente trabajo además de realizar una explicación y valoración teórica del proceso de oxidación de la pirita también se realiza un compendio de las medidas preventivas y correctoras más empleadas.

  14. Prediction of Thyroid Disease Using Data Mining Techniques

    Directory of Open Access Journals (Sweden)

    Irina Ioniţă

    2016-08-01

    Full Text Available Recently, thyroid diseases are more and more spread worldwide. In Romania, for example, one of eight women suffer from hypothyroidism, hyperthyroidism or thyroid cancer. Various research studies estimate that about 30% of Romanians are diagnosed with endemic goiter. The factors that affect the thyroid function are: stress, infection, trauma, toxins, low-calorie diet, certain medication etc. It is very important to prevent such diseases rather than cure them, because the majority of treatments consist in long term medication or in chirurgical intervention. The current study refers to the thyroid disease classification in two of the most common thyroid dysfunctions (hyperthyroidism and hypothyroidism among the population. The authors analyzed and compared four classification models: Naive Bayes, Decision Tree, Multilayer Perceptron and Radial Basis Function Network. The results indicate a significant accuracy for all the classification models mentioned above, the best classification rate being that of the Decision Tree model. The data set used to build and to validate the classifier was provided by the UCI machine learning repository and by a website with Romanian data. The framework for building and testing the classification models was KNIME Analytics Platform and Weka, two data mining software.

  15. Effective approach toward Intrusion Detection System using data mining techniques

    Directory of Open Access Journals (Sweden)

    G.V. Nadiammai

    2014-03-01

    Full Text Available With the tremendous growth of the usage of computers over network and development in application running on various platform captures the attention toward network security. This paradigm exploits security vulnerabilities on all computer systems that are technically difficult and expensive to solve. Hence intrusion is used as a key to compromise the integrity, availability and confidentiality of a computer resource. The Intrusion Detection System (IDS plays a vital role in detecting anomalies and attacks in the network. In this work, data mining concept is integrated with an IDS to identify the relevant, hidden data of interest for the user effectively and with less execution time. Four issues such as Classification of Data, High Level of Human Interaction, Lack of Labeled Data, and Effectiveness of Distributed Denial of Service Attack are being solved using the proposed algorithms like EDADT algorithm, Hybrid IDS model, Semi-Supervised Approach and Varying HOPERAA Algorithm respectively. Our proposed algorithm has been tested using KDD Cup dataset. All the proposed algorithm shows better accuracy and reduced false alarm rate when compared with existing algorithms.

  16. Simulation of California's Major Reservoirs Outflow Using Data Mining Technique

    Science.gov (United States)

    Yang, T.; Gao, X.; Sorooshian, S.

    2014-12-01

    The reservoir's outflow is controlled by reservoir operators, which is different from the upstream inflow. The outflow is more important than the reservoir's inflow for the downstream water users. In order to simulate the complicated reservoir operation and extract the outflow decision making patterns for California's 12 major reservoirs, we build a data-driven, computer-based ("artificial intelligent") reservoir decision making tool, using decision regression and classification tree approach. This is a well-developed statistical and graphical modeling methodology in the field of data mining. A shuffled cross validation approach is also employed to extract the outflow decision making patterns and rules based on the selected decision variables (inflow amount, precipitation, timing, water type year etc.). To show the accuracy of the model, a verification study is carried out comparing the model-generated outflow decisions ("artificial intelligent" decisions) with that made by reservoir operators (human decisions). The simulation results show that the machine-generated outflow decisions are very similar to the real reservoir operators' decisions. This conclusion is based on statistical evaluations using the Nash-Sutcliffe test. The proposed model is able to detect the most influential variables and their weights when the reservoir operators make an outflow decision. While the proposed approach was firstly applied and tested on California's 12 major reservoirs, the method is universally adaptable to other reservoir systems.

  17. Sentiment analysis of Arabic tweets using text mining techniques

    Science.gov (United States)

    Al-Horaibi, Lamia; Khan, Muhammad Badruddin

    2016-07-01

    Sentiment analysis has become a flourishing field of text mining and natural language processing. Sentiment analysis aims to determine whether the text is written to express positive, negative, or neutral emotions about a certain domain. Most sentiment analysis researchers focus on English texts, with very limited resources available for other complex languages, such as Arabic. In this study, the target was to develop an initial model that performs satisfactorily and measures Arabic Twitter sentiment by using machine learning approach, Naïve Bayes and Decision Tree for classification algorithms. The datasets used contains more than 2,000 Arabic tweets collected from Twitter. We performed several experiments to check the performance of the two algorithms classifiers using different combinations of text-processing functions. We found that available facilities for Arabic text processing need to be made from scratch or improved to develop accurate classifiers. The small functionalities developed by us in a Python language environment helped improve the results and proved that sentiment analysis in the Arabic domain needs lot of work on the lexicon side.

  18. Basin Visual Estimation Technique (BVET) and Representative Reach Approaches to Wadeable Stream Surveys: Methodological Limitations and Future Directions

    Science.gov (United States)

    Lance R. Williams; Melvin L. Warren; Susan B. Adams; Joseph L. Arvai; Christopher M. Taylor

    2004-01-01

    Basin Visual Estimation Techniques (BVET) are used to estimate abundance for fish populations in small streams. With BVET, independent samples are drawn from natural habitat units in the stream rather than sampling "representative reaches." This sampling protocol provides an alternative to traditional reach-level surveys, which are criticized for their lack...

  19. Computational intelligence techniques for biological data mining: An overview

    Science.gov (United States)

    Faye, Ibrahima; Iqbal, Muhammad Javed; Said, Abas Md; Samir, Brahim Belhaouari

    2014-10-01

    Computational techniques have been successfully utilized for a highly accurate analysis and modeling of multifaceted and raw biological data gathered from various genome sequencing projects. These techniques are proving much more effective to overcome the limitations of the traditional in-vitro experiments on the constantly increasing sequence data. However, most critical problems that caught the attention of the researchers may include, but not limited to these: accurate structure and function prediction of unknown proteins, protein subcellular localization prediction, finding protein-protein interactions, protein fold recognition, analysis of microarray gene expression data, etc. To solve these problems, various classification and clustering techniques using machine learning have been extensively used in the published literature. These techniques include neural network algorithms, genetic algorithms, fuzzy ARTMAP, K-Means, K-NN, SVM, Rough set classifiers, decision tree and HMM based algorithms. Major difficulties in applying the above algorithms include the limitations found in the previous feature encoding and selection methods while extracting the best features, increasing classification accuracy and decreasing the running time overheads of the learning algorithms. The application of this research would be potentially useful in the drug design and in the diagnosis of some diseases. This paper presents a concise overview of the well-known protein classification techniques.

  20. Studies of MHD stability using data mining technique in helical plasmas

    International Nuclear Information System (INIS)

    Yamamoto, Satoshi; Pretty, David; Blackwell, Boyd

    2010-01-01

    Data mining techniques, which automatically extract useful knowledge from large datasets, are applied to multichannel magnetic probe signals of several helical plasmas in order to identify and classify MHD instabilities in helical plasmas. This method is useful to find new MHD instabilities as well as previously identified ones. Moreover, registering the results obtained from data mining in a database allows us to investigate the characteristics of MHD instabilities with parameter studies. We introduce the data mining technique consisted of pre-processing, clustering and visualizations using results from helical plasmas in H-1 and Heliotron J. We were successfully able to classify the MHD instabilities using the criterion of phase differences of each magnetic probe and identify them as energetic-ion-driven MHD instabilities using parameter study in Heliotron J plasmas. (author)

  1. Datafish Multiphase Data Mining Technique to Match Multiple Mutually Inclusive Independent Variables in Large PACS Databases.

    Science.gov (United States)

    Kelley, Brendan P; Klochko, Chad; Halabi, Safwan; Siegal, Daniel

    2016-06-01

    Retrospective data mining has tremendous potential in research but is time and labor intensive. Current data mining software contains many advanced search features but is limited in its ability to identify patients who meet multiple complex independent search criteria. Simple keyword and Boolean search techniques are ineffective when more complex searches are required, or when a search for multiple mutually inclusive variables becomes important. This is particularly true when trying to identify patients with a set of specific radiologic findings or proximity in time across multiple different imaging modalities. Another challenge that arises in retrospective data mining is that much variation still exists in how image findings are described in radiology reports. We present an algorithmic approach to solve this problem and describe a specific use case scenario in which we applied our technique to a real-world data set in order to identify patients who matched several independent variables in our institution's picture archiving and communication systems (PACS) database.

  2. A Multi-Agent Framework for Anomalies Detection on Distributed Firewalls Using Data Mining Techniques

    Science.gov (United States)

    Karoui, Kamel; Ftima, Fakher Ben; Ghezala, Henda Ben

    The Agents and Data Mining integration has emerged as a promising area for disributed problems solving. Applying this integration on distributed firewalls will facilitate the anomalies detection process. In this chapter, we present a set of algorithms and mining techniques to analyse, manage and detect anomalies on distributed firewalls' policy rules using the multi-agent approach; first, for each firewall, a static agent will execute a set of data mining techniques to generate a new set of efficient firewall policy rules. Then, a mobile agent will exploit these sets of optimized rules to detect eventual anomalies on a specific firewall (intra-firewalls anomalies) or between firewalls (inter-firewalls anomalies). An experimental case study will be presented to demonstrate the usefulness of our approach.

  3. Data-Mining Techniques in Detecting Factors Linked to Academic Achievement

    Science.gov (United States)

    Martínez Abad, Fernando; Chaparro Caso López, Alicia A.

    2017-01-01

    In light of the emergence of statistical analysis techniques based on data mining in education sciences, and the potential they offer to detect non-trivial information in large databases, this paper presents a procedure used to detect factors linked to academic achievement in large-scale assessments. The study is based on a non-experimental,…

  4. Combining Data Warehouse and Data Mining Techniques for Web Log Analysis

    DEFF Research Database (Denmark)

    Pedersen, Torben Bach; Jespersen, Søren; Thorhauge, Jesper

    2008-01-01

    a number of approaches thatcombine data warehousing and data mining techniques in order to analyze Web logs.After introducing the well-known click and session data warehouse (DW) schemas,the chapter presents the subsession schema, which allows fast queries on sequences...

  5. An efficient reversible privacy-preserving data mining technology over data streams.

    Science.gov (United States)

    Lin, Chen-Yi; Kao, Yuan-Hung; Lee, Wei-Bin; Chen, Rong-Chang

    2016-01-01

    With the popularity of smart handheld devices and the emergence of cloud computing, users and companies can save various data, which may contain private data, to the cloud. Topics relating to data security have therefore received much attention. This study focuses on data stream environments and uses the concept of a sliding window to design a reversible privacy-preserving technology to process continuous data in real time, known as a continuous reversible privacy-preserving (CRP) algorithm. Data with CRP algorithm protection can be accurately recovered through a data recovery process. In addition, by using an embedded watermark, the integrity of the data can be verified. The results from the experiments show that, compared to existing algorithms, CRP is better at preserving knowledge and is more effective in terms of reducing information loss and privacy disclosure risk. In addition, it takes far less time for CRP to process continuous data than existing algorithms. As a result, CRP is confirmed as suitable for data stream environments and fulfills the requirements of being lightweight and energy-efficient for smart handheld devices.

  6. Evaluation of Stream Mining Classifiers for Real-Time Clinical Decision Support System: A Case Study of Blood Glucose Prediction in Diabetes Therapy

    Directory of Open Access Journals (Sweden)

    Simon Fong

    2013-01-01

    Full Text Available Earlier on, a conceptual design on the real-time clinical decision support system (rt-CDSS with data stream mining was proposed and published. The new system is introduced that can analyze medical data streams and can make real-time prediction. This system is based on a stream mining algorithm called VFDT. The VFDT is extended with the capability of using pointers to allow the decision tree to remember the mapping relationship between leaf nodes and the history records. In this paper, which is a sequel to the rt-CDSS design, several popular machine learning algorithms are investigated for their suitability to be a candidate in the implementation of classifier at the rt-CDSS. A classifier essentially needs to accurately map the events inputted to the system into one of the several predefined classes of assessments, such that the rt-CDSS can follow up with the prescribed remedies being recommended to the clinicians. For a real-time system like rt-CDSS, the major technological challenges lie in the capability of the classifier to process, analyze and classify the dynamic input data, quickly and upmost reliably. An experimental comparison is conducted. This paper contributes to the insight of choosing and embedding a stream mining classifier into rt-CDSS with a case study of diabetes therapy.

  7. Multivariate statistical techniques for the evaluation of surface water quality of the Himalayan foothills streams, Pakistan

    Science.gov (United States)

    Malik, Riffat Naseem; Hashmi, Muhammad Zaffar

    2017-10-01

    Himalayan foothills streams, Pakistan play an important role in living water supply and irrigation of farmlands; thus, the water quality is closely related to public health. Multivariate techniques were applied to check spatial and seasonal trends, and metals contamination sources of the Himalayan foothills streams, Pakistan. Grab surface water samples were collected from different sites (5-15 cm water depth) in pre-washed polyethylene containers. Fast Sequential Atomic Absorption Spectrophotometer (Varian FSAA-240) was used to measure the metals concentration. Concentrations of Ni, Cu, and Mn were high in pre-monsoon season than the post-monsoon season. Cluster analysis identified impaired, moderately impaired and least impaired clusters based on water parameters. Discriminant function analysis indicated spatial variability in water was due to temperature, electrical conductivity, nitrates, iron and lead whereas seasonal variations were correlated with 16 physicochemical parameters. Factor analysis identified municipal and poultry waste, automobile activities, surface runoff, and soil weathering as major sources of contamination. Levels of Mn, Cr, Fe, Pb, Cd, Zn and alkalinity were above the WHO and USEPA standards for surface water. The results of present study will help to higher authorities for the management of the Himalayan foothills streams.

  8. Survey of Analysis of Crime Detection Techniques Using Data Mining and Machine Learning

    Science.gov (United States)

    Prabakaran, S.; Mitra, Shilpa

    2018-04-01

    Data mining is the field containing procedures for finding designs or patterns in a huge dataset, it includes strategies at the convergence of machine learning and database framework. It can be applied to various fields like future healthcare, market basket analysis, education, manufacturing engineering, crime investigation etc. Among these, crime investigation is an interesting application to process crime characteristics to help the society for a better living. This paper survey various data mining techniques used in this domain. This study may be helpful in designing new strategies for crime prediction and analysis.

  9. Automatic detection of adverse events to predict drug label changes using text and data mining techniques.

    Science.gov (United States)

    Gurulingappa, Harsha; Toldo, Luca; Rajput, Abdul Mateen; Kors, Jan A; Taweel, Adel; Tayrouz, Yorki

    2013-11-01

    The aim of this study was to assess the impact of automatically detected adverse event signals from text and open-source data on the prediction of drug label changes. Open-source adverse effect data were collected from FAERS, Yellow Cards and SIDER databases. A shallow linguistic relation extraction system (JSRE) was applied for extraction of adverse effects from MEDLINE case reports. Statistical approach was applied on the extracted datasets for signal detection and subsequent prediction of label changes issued for 29 drugs by the UK Regulatory Authority in 2009. 76% of drug label changes were automatically predicted. Out of these, 6% of drug label changes were detected only by text mining. JSRE enabled precise identification of four adverse drug events from MEDLINE that were undetectable otherwise. Changes in drug labels can be predicted automatically using data and text mining techniques. Text mining technology is mature and well-placed to support the pharmacovigilance tasks. Copyright © 2013 John Wiley & Sons, Ltd.

  10. Skills and Vacancy Analysis with Data Mining Techniques

    Directory of Open Access Journals (Sweden)

    Izabela A. Wowczko

    2015-11-01

    Full Text Available Through recognizing the importance of a qualified workforce, skills research has become one of the focal points in economics, sociology, and education. Great effort is dedicated to analyzing labor demand and supply, and actions are taken at many levels to match one with the other. In this work we concentrate on skills needs, a dynamic variable dependent on many aspects such as geography, time, or the type of industry. Historically, skills in demand were easy to evaluate since transitions in that area were fairly slow, gradual, and easy to adjust to. In contrast, current changes are occurring rapidly and might take an unexpected turn. Therefore, we introduce a relatively simple yet effective method of monitoring skills needs straight from the source—as expressed by potential employers in their job advertisements. We employ open source tools such as RapidMiner and R as well as easily accessible online vacancy data. We demonstrate selected techniques, namely classification with k-NN and information extraction from a textual dataset, to determine effective ways of discovering knowledge from a given collection of vacancies.

  11. Financial Distress Prediction of Iranian Companies Using Data Mining Techniques

    Directory of Open Access Journals (Sweden)

    Moradi Mahdi

    2013-01-01

    Full Text Available Decision-making problems in the area of financial status evaluation are considered very important. Making incorrect decisions in firms is very likely to cause financial crises and distress. Predicting financial distress of factories and manufacturing companies is the desire of managers and investors, auditors, financial analysts, governmental officials, employees. Therefore, the current study aims to predict financial distress of Iranian Companies. The current study applies support vector data description (SVDD to the financial distress prediction problem in an attempt to suggest a new model with better explanatory power and stability. To serve this purpose, we use a grid-search technique using 3-fold cross-validation to find out the optimal parameter values of kernel function of SVDD. To evaluate the prediction accuracy of SVDD, we compare its performance with fuzzy c-means (FCM.The experiment results show that SVDD outperforms the other method in years before financial distress occurrence. The data used in this research were obtained from Iran Stock Market and Accounting Research Database. According to the data between 2000 and 2009, 70 pairs of companies listed in Tehran Stock Exchange are selected as initial data set.

  12. Evaluating remedial alternatives for an acid mine drainage stream: A model post audit

    Science.gov (United States)

    Runkel, Robert L.; Kimball, Briant A.; Walton-Day, Katherine; Verplanck, Philip L.; Broshears, Robert E.

    2012-01-01

    A post audit for a reactive transport model used to evaluate acid mine drainage treatment systems is presented herein. The post audit is based on a paired synoptic approach in which hydrogeochemical data are collected at low (existing conditions) and elevated (following treatment) pH. Data obtained under existing, low-pH conditions are used for calibration, and the resultant model is used to predict metal concentrations observed following treatment. Predictions for Al, As, Fe, H+, and Pb accurately reproduce the observed reduction in dissolved concentrations afforded by the treatment system, and the information provided in regard to standard attainment is also accurate (predictions correctly indicate attainment or nonattainment of water quality standards for 19 of 25 cases). Errors associated with Cd, Cu, and Zn are attributed to misspecification of sorbent mass (precipitated Fe). In addition to these specific results, the post audit provides insight in regard to calibration and sensitivity analysis that is contrary to conventional wisdom. Steps taken during the calibration process to improve simulations of As sorption were ultimately detrimental to the predictive results, for example, and the sensitivity analysis failed to bracket observed metal concentrations.

  13. Evaluating remedial alternatives for an acid mine drainage stream: a model post audit.

    Science.gov (United States)

    Runkel, Robert L; Kimball, Briant A; Walton-Day, Katherine; Verplanck, Philip L; Broshears, Robert E

    2012-01-03

    A post audit for a reactive transport model used to evaluate acid mine drainage treatment systems is presented herein. The post audit is based on a paired synoptic approach in which hydrogeochemical data are collected at low (existing conditions) and elevated (following treatment) pH. Data obtained under existing, low-pH conditions are used for calibration, and the resultant model is used to predict metal concentrations observed following treatment. Predictions for Al, As, Fe, H(+), and Pb accurately reproduce the observed reduction in dissolved concentrations afforded by the treatment system, and the information provided in regard to standard attainment is also accurate (predictions correctly indicate attainment or nonattainment of water quality standards for 19 of 25 cases). Errors associated with Cd, Cu, and Zn are attributed to misspecification of sorbent mass (precipitated Fe). In addition to these specific results, the post audit provides insight in regard to calibration and sensitivity analysis that is contrary to conventional wisdom. Steps taken during the calibration process to improve simulations of As sorption were ultimately detrimental to the predictive results, for example, and the sensitivity analysis failed to bracket observed metal concentrations.

  14. Rapid Automated Dissolution and Analysis Techniques for Radionuclides in Recycle Process Streams

    International Nuclear Information System (INIS)

    Sudowe, Ralf; Roman, Audrey; Dailey, Ashlee; Go, Elaine

    2013-01-01

    The analysis of process samples for radionuclide content is an important part of current procedures for material balance and accountancy in the different process streams of a recycling plant. The destructive sample analysis techniques currently available necessitate a significant amount of time. It is therefore desirable to develop new sample analysis procedures that allow for a quick turnaround time and increased sample throughput with a minimum of deviation between samples. In particular, new capabilities for rapid sample dissolution and radiochemical separation are required. Most of the radioanalytical techniques currently employed for sample analysis are based on manual laboratory procedures. Such procedures are time- and labor-intensive, and not well suited for situations in which a rapid sample analysis is required and/or large number of samples need to be analyzed. To address this issue we are currently investigating radiochemical separation methods based on extraction chromatography that have been specifically optimized for the analysis of process stream samples. The influence of potential interferences present in the process samples as well as mass loading, flow rate and resin performance is being studied. In addition, the potential to automate these procedures utilizing a robotic platform is evaluated. Initial studies have been carried out using the commercially available DGA resin. This resin shows an affinity for Am, Pu, U, and Th and is also exhibiting signs of a possible synergistic effects in the presence of iron.

  15. Cross-Layer Techniques for Adaptive Video Streaming over Wireless Networks

    Directory of Open Access Journals (Sweden)

    Yufeng Shan

    2005-02-01

    Full Text Available Real-time streaming media over wireless networks is a challenging proposition due to the characteristics of video data and wireless channels. In this paper, we propose a set of cross-layer techniques for adaptive real-time video streaming over wireless networks. The adaptation is done with respect to both channel and data. The proposed novel packetization scheme constructs the application layer packet in such a way that it is decomposed exactly into an integer number of equal-sized radio link protocol (RLP packets. FEC codes are applied within an application packet at the RLP packet level rather than across different application packets and thus reduce delay at the receiver. A priority-based ARQ, together with a scheduling algorithm, is applied at the application layer to retransmit only the corrupted RLP packets within an application layer packet. Our approach combines the flexibility and programmability of application layer adaptations, with low delay and bandwidth efficiency of link layer techniques. Socket-level simulations are presented to verify the effectiveness of our approach.

  16. Determination of free acidity in nuclear fuel reprocessing streams by fiber optic aided spectrophotometric technique

    International Nuclear Information System (INIS)

    Ganesh, S.; Velavendan, P.; Pandey, N.K.; Kamachi Mudali, U.; Natarajan, R.

    2014-01-01

    A fiber optic aided spectrophotometric technique has been developed for the determination of free acidity in nuclear fuel reprocessing streams. The developed method is simple, accurate and applicable to all ranges of nitric acid and heavy metal concentrations relevant to the purex process. The method is based on the formation of yellow colour with an acid-sensitive indicator such as chrome azurol s, the intensity of yellow colour is proportional to the acid concentration. The system obeys Lambert-Beer's law at 455 nm in the range of acidity 1-10 M of nitric acid. The results obtained are reproducible with standard deviation 2% and relative error is less than 3%. The results obtained by the developed technique are in good agreement with those obtained by the standard procedure. This method is adaptable for remote operation and on-line monitoring. (author)

  17. On the classification techniques in data mining for microarray data classification

    Science.gov (United States)

    Aydadenta, Husna; Adiwijaya

    2018-03-01

    Cancer is one of the deadly diseases, according to data from WHO by 2015 there are 8.8 million more deaths caused by cancer, and this will increase every year if not resolved earlier. Microarray data has become one of the most popular cancer-identification studies in the field of health, since microarray data can be used to look at levels of gene expression in certain cell samples that serve to analyze thousands of genes simultaneously. By using data mining technique, we can classify the sample of microarray data thus it can be identified with cancer or not. In this paper we will discuss some research using some data mining techniques using microarray data, such as Support Vector Machine (SVM), Artificial Neural Network (ANN), Naive Bayes, k-Nearest Neighbor (kNN), and C4.5, and simulation of Random Forest algorithm with technique of reduction dimension using Relief. The result of this paper show performance measure (accuracy) from classification algorithm (SVM, ANN, Naive Bayes, kNN, C4.5, and Random Forets).The results in this paper show the accuracy of Random Forest algorithm higher than other classification algorithms (Support Vector Machine (SVM), Artificial Neural Network (ANN), Naive Bayes, k-Nearest Neighbor (kNN), and C4.5). It is hoped that this paper can provide some information about the speed, accuracy, performance and computational cost generated from each Data Mining Classification Technique based on microarray data.

  18. Geochemical and Pb isotopic evidence for sources and dispersal of metal contamination in stream sediments from the mining and smelting district of Pribram, Czech Republic

    International Nuclear Information System (INIS)

    Ettler, Vojtech; Mihaljevic, Martin; Sebek, Ondrej; Molek, Michael; Grygar, Tomas; Zeman, Josef

    2006-01-01

    Stream sediments from the mining and smelting district of Pribram, Czech Republic, were studied to determine the degree, sources and dispersal of metal contamination using a combination of bulk metal and mineralogical determinations, sequential extractions and Pb isotopic analyses. The highest metal concentrations were found 3-4 km downstream from the main polymetallic mining site (9800 mg Pb kg -1 , 26 039 mg Zn kg -1 , 316.4 mg Cd kg -1 , 256.9 mg Cu kg -1 ). The calculated enrichment factors (EFs) confirmed the extreme degree of contamination by Pb, Zn and Cd (EF > 40). Lead, Zn and Cd are bound mainly to Fe oxides and hydroxides. In the most contaminated samples Pb is also present as Pb carbonates and litharge (PbO). Lead isotopic analysis indicates that the predominant source of stream sediment contamination is historic Pb-Ag mining and primary Pb smelting ( 206 Pb/ 207 Pb = 1.16), while the role of secondary smelting (car battery processing) is negligible. - Pb isotopes properly complete traditional investigations of metal sources and dispersal in contaminated stream sediments

  19. Fungi in a heavy metal precipitating stream in the Mansfeld mining district, Germany

    International Nuclear Information System (INIS)

    Ehrman, James M.; Baerlocher, Felix; Wennrich, Rainer; Krauss, Gerd-Joachim; Krauss, Gudrun

    2008-01-01

    Fungal growth on alder leaves was studied in two heavy metal polluted streams in central Germany. The aim of the study was to examine previously observed differences in leaf decomposition rates, heavy metal precipitation and fungal involvement in these processes at the microscopic level. Ergosterol analyses indicated that neither habitat was optimal for fungi, but leaves exposed at the less polluted site (H8) decomposed rapidly and were colonized externally and internally by fungi and other microorganisms. Leaves exposed at the more polluted site (H4) decomposed very slowly and fungal colonization was restricted to external surfaces. An amorphous organic layer, deposited within 24 h of exposure, quickly became covered with a pale blue-green crystalline deposit (zincowoodwardite) with significant amounts of Al, S, Cu and Zn, determined by energy dispersive X-ray spectroscopy (EDS). Scanning electron microscopy (SEM) analysis of the precipitate revealed a branching arrangement of the precipitated particles caused by the presence of fungal hyphae growing on the surface. Hyphae that were not disturbed by handling were usually completely encased in the precipitate, but hyphae did not contain EDS-detectable amounts of precipitate metals. Elemental analysis using inductively coupled plasma (ICP) atomic emission spectrometry and ICP mass spectrometry revealed continuing accumulation of Zn, Cu and several other metals/metalloids on and in leaves. The formation of metal precipitates on various artificial substrates at site H4 was much reduced compared to leaves, which we attribute to the absence of fungal colonization on the artificial substrates. We could not determine whether fungi accelerate the precipitation of heavy metals at site H4, but mycelial growth on leaves continues to create new surfaces and therefore thicker layers of precipitate on leaves compared to artificial substrates

  20. Fungi in a heavy metal precipitating stream in the Mansfeld mining district, Germany

    Energy Technology Data Exchange (ETDEWEB)

    Ehrman, James M. [Department of Biology, Mount Allison University, 63B York St., Sackville, NB, E4L 1G7 (Canada)], E-mail: jehrman@mta.ca; Baerlocher, Felix [Department of Biology, Mount Allison University, 63B York St., Sackville, NB, E4L 1G7 (Canada); Wennrich, Rainer [Helmholtz Centre for Environmental Research- UFZ, Department of Analytical Chemistry, Permoserstr. 15, 04318 Leipzig (Germany); Krauss, Gerd-Joachim [Martin-Luther-University, Halle-Wittenberg, Institute of Biochemistry and Biotechnology, Div. Ecological and Plant Biochemistry, Kurt-Mothes-Str. 3, 06120 Halle/Saale (Germany); Krauss, Gudrun [Helmholtz Centre for Environmental Research- UFZ, Department of Environmental Microbiology, Theodor-Lieser-Str. 4, 06120 Halle/Saale (Germany)

    2008-01-25

    Fungal growth on alder leaves was studied in two heavy metal polluted streams in central Germany. The aim of the study was to examine previously observed differences in leaf decomposition rates, heavy metal precipitation and fungal involvement in these processes at the microscopic level. Ergosterol analyses indicated that neither habitat was optimal for fungi, but leaves exposed at the less polluted site (H8) decomposed rapidly and were colonized externally and internally by fungi and other microorganisms. Leaves exposed at the more polluted site (H4) decomposed very slowly and fungal colonization was restricted to external surfaces. An amorphous organic layer, deposited within 24 h of exposure, quickly became covered with a pale blue-green crystalline deposit (zincowoodwardite) with significant amounts of Al, S, Cu and Zn, determined by energy dispersive X-ray spectroscopy (EDS). Scanning electron microscopy (SEM) analysis of the precipitate revealed a branching arrangement of the precipitated particles caused by the presence of fungal hyphae growing on the surface. Hyphae that were not disturbed by handling were usually completely encased in the precipitate, but hyphae did not contain EDS-detectable amounts of precipitate metals. Elemental analysis using inductively coupled plasma (ICP) atomic emission spectrometry and ICP mass spectrometry revealed continuing accumulation of Zn, Cu and several other metals/metalloids on and in leaves. The formation of metal precipitates on various artificial substrates at site H4 was much reduced compared to leaves, which we attribute to the absence of fungal colonization on the artificial substrates. We could not determine whether fungi accelerate the precipitation of heavy metals at site H4, but mycelial growth on leaves continues to create new surfaces and therefore thicker layers of precipitate on leaves compared to artificial substrates.

  1. Image/Time Series Mining Algorithms: Applications to Developmental Biology, Document Processing and Data Streams

    Science.gov (United States)

    Tataw, Oben Moses

    2013-01-01

    Interdisciplinary research in computer science requires the development of computational techniques for practical application in different domains. This usually requires careful integration of different areas of technical expertise. This dissertation presents image and time series analysis algorithms, with practical interdisciplinary applications…

  2. DATA MINING WORKSPACE AS AN OPTIMIZATION PREDICTION TECHNIQUE FOR SOLVING TRANSPORT PROBLEMS

    Directory of Open Access Journals (Sweden)

    Anastasiia KUPTCOVA

    2016-09-01

    Full Text Available This article addresses the study related to forecasting with an actual high-speed decision making under careful modelling of time series data. The study uses data-mining modelling for algorithmic optimization of transport goals. Our finding brings to the future adequate techniques for the fitting of a prediction model. This model is going to be used for analyses of the future transaction costs in the frontiers of the Czech Republic. Time series prediction methods for the performance of prediction models in the package of Statistics are Exponential, ARIMA and Neural Network approaches. The primary target for a predictive scenario in the data mining workspace is to provide modelling data faster and with more versatility than the other management techniques.

  3. Evaluation of a fluorescent lectin-based staining technique for some acidophilic mining bacteria

    International Nuclear Information System (INIS)

    Fife, D.J.; Bruhn, D.F.; Miller, K.S.; Stoner, D.L.

    2000-01-01

    A fluorescence-labeled wheat germ agglutinin staining technique was modified and found to be effective for staining gram-positive, acidophilic mining bacteria. Bacteria identified by others as being gram positive through 16S rRNA sequence analyses, yet clustering near the divergence of that group, stained weakly. Gram-negative bacteria did not stain. Background staining of environmental samples was negligible, and pyrite and soil particles in the samples did not interfere with the staining procedure

  4. Application of Artificial Intelligence and Data Mining Techniques to Financial Markets

    OpenAIRE

    Katarína Hilovska; Peter Koncz

    2012-01-01

    The aim of artificial intelligence is to discover mechanisms of adaptation in a changing environment with utilisation of intelligence, for instance in the ability to exclude unlikely solutions. Artificial intelligence methods have extensive application in different fields such as medicine, games, transportation, or heavy industry. This paper deals with interdisciplinary issues – interconnection of artificial intelligence and finance. The paper briefly describes techniques of data mining, expe...

  5. Selenium and other trace elements in aquatic insects in coal mine-affected streams in the Rocky Mountains of Alberta, Canada

    Energy Technology Data Exchange (ETDEWEB)

    Wayland, M.; Crosley, R. [Environmental Canada, Saskatoon, SK (Canada)

    2006-05-15

    We determined levels of Se, As, Cd, Pb, and Zn in aquatic insects at coal mine-impacted and reference sites in streams in the Rocky Mountain foothills of west central Alberta from 2001-2003. Selenium levels were greater at coal mine-impacted sites than at reference sites in caddisflies but not in mayflies or stoneflies. Arsenic levels were greater at coal mine-impacted sites than at reference sites in caddisflies and stoneflies but not in mayflies. Zn levels were higher at coal mine-impacted sites than at reference sites in all three groups of insects. At coal mine-impacted sites, Se levels in mayflies and caddisflies were greater than those in stoneflies while at reference sites mayflies contained greater concentrations of Se than either caddisflies or stoneflies. Arsenic levels in mayflies were greater than those in caddisflies at reference and coal mine-impacted sites and were greater than those in stoneflies at reference sites. At both types of sites Cd differed amongst insect taxa in the order of mayflies < caddisflies < stoneflies. The same was true of Zn at coal mine-affected sites. At reference sites, stoneflies had greater concentrations of Zn than both mayflies and caddisflies. At both types of sites, Pb levels were greater in mayflies and caddisflies than they were in stoneflies. Of the five trace elements considered in this study, only Se was sufficiently elevated in aquatic invertebrates to be of potential concern for consumers such as fish and aquatic birds. Such was the case at both coal mine-impacted and reference sites.

  6. Extending mine life

    International Nuclear Information System (INIS)

    Anon.

    1984-01-01

    Mine layouts, new machines and techniques, research into problem areas of ground control and so on, are highlighted in this report on extending mine life. The main resources taken into account are coal mining, uranium mining, molybdenum and gold mining

  7. Applying Data-mining techniques to study drought periods in Spain

    Science.gov (United States)

    Belda, F.; Penades, M. C.

    2010-09-01

    Data-mining is a technique that it can be used to interact with large databases and to help in the discovery relations between parameters by extracting information from massive and multiple data archives. Drought affects many economic and social sectors, from agricultural to transportation, going through urban water deficit and the development of modern industries. With these problems and drought geographical and temporal distribution it's difficult to find a single definition of drought. Improving the understanding of the knowledge of climatic index is necessary to reduce the impacts of drought and to facilitate quick decisions regarding this problem. The main objective is to analyze drought periods from 1950 to 2009 in Spain. We use several kinds of information, different formats, sources and transmission mode. We use satellite-based Vegetation Index, dryness index for several temporal periods. We use daily and monthly precipitation and temperature data and soil moisture data from numerical weather model. We calculate mainly Standardized Precipitation Index (SPI) that it has been used amply in the bibliography. We use OLAP-Mining techniques to discovery of association rules between remote-sensing, numerical weather model and climatic index. Time series Data- Mining techniques organize data as a sequence of events, with each event having a time of recurrence, to cluster the data into groups of records or cluster with similar characteristics. Prior climatological classification is necessary if we want to study drought periods over all Spain.

  8. Application of indirect stress measurement techniques (non strain gauge based technology) to quantify stress environments in mines

    CSIR Research Space (South Africa)

    Stacey, TR

    2002-03-01

    Full Text Available Reliable values of in situ stress are essential for the valid modelling of mine layouts. Available non-strain gauge methods are reviewed as potential practical techniques for South African mines. From this review it is concluded that the most...

  9. Occurrence, distribution, and volume of metals-contaminated sediment of selected streams draining the Tri-State Mining District, Missouri, Oklahoma, and Kansas, 2011–12

    Science.gov (United States)

    Smith, D. Charlie

    2016-12-14

    Lead and zinc were mined in the Tri-State Mining District (TSMD) of southwest Missouri, northeast Oklahoma, and southeast Kansas for more than 100 years. The effects of mining on the landscape are still evident, nearly 50 years after the last mine ceased operation. The legacies of mining are the mine waste and discharge of groundwater from underground mines. The mine-waste piles and underground mines are continuous sources of trace metals (primarily lead, zinc, and cadmium) to the streams that drain the TSMD. Many previous studies characterized the horizontal extent of mine-waste contamination in streams but little information exists on the depth of mine-waste contamination in these streams. Characterizing the vertical extent of contamination is difficult because of the large amount of coarse-grained material, ranging from coarse gravel to boulders, within channel sediment. The U.S. Geological Survey, in cooperation with U.S. Fish and Wildlife service, collected channel-sediment samples at depth for subsequent analyses that would allow attainment of the following goals: (1) determination of the relation between concentration and depth for lead, zinc and cadmium in channel sediments and flood-plain sediments, and (2) determination of the volume of gravel-bar sediment from the surface to the maximum depth with concentrations of these metals that exceeded sediment-quality guidelines. For the purpose of this report, volume of gravel-bar sediment is considered to be distributed in two forms, gravel bars and the wetted channel, and this study focused on gravel bars. Concentrations of lead, zinc, and cadmium in samples were compared to the consensus probable effects concentration (CPEC) and Tri-State Mining District specific probable effects concentration (TPEC) sediment-quality guidelines.During the study, more than 700 sediment samples were collected from borings at multiple sites, including gravel bars and flood plains, along Center Creek, Turkey Creek, Shoal Creek

  10. Knowledge-driven GIS modeling technique for gold exploration, Bulghah gold mine area, Saudi Arabia

    Directory of Open Access Journals (Sweden)

    Ahmed A. Madani

    2011-12-01

    Full Text Available This research aims to generate a favorability map for gold exploration at the Bulghah gold mine area using integration of geo-datasets within a GIS environment. Spatial data analyses and integration of different geo-datasets are carried out based on knowledge-driven and weighting technique. The integration process involves the weighting and scoring of different layers affecting the gold mineralization at the study area using the index overlay method within PCI Geomatica environment. Generation of the binary predictor maps for lithology, lineaments, faults and favorable contacts precede the construction of the favorability map. About 100 m buffer zones are generated for favorable contacts, lineaments and major faults layers. Internal weighting is assigned to each layer based on favorability for gold mineralization. The scores for lithology, major faults, lineaments and favorable contacts layers in the constructed favorability map are 50%, 25%, 10% and 15%, respectively. Final favorability map for the Bulghah gold mine area shows the recording of two new sites for gold mineralization located at the northern and southern extensions of tonalite–diorite intrusions. The northern new site is now exploited for gold from the Bulghah North mine. The southern new site is narrow and small; its rocks resemble those of the Bulghah gold mine.

  11. Sensitivity Analysis Techniques Applied in Video Streaming Service on Eucalyptus Cloud Environments

    Directory of Open Access Journals (Sweden)

    Rosangela Melo

    2018-01-01

    Full Text Available Nowdays, several streaming servers are available to provide a variety of multimedia applications such as Video on Demand in cloud computing environments. These environments have the business potential because of the pay-per-use model, as well as the advantages of easy scalability and, up-to-date of the packages and programs. This paper uses hierarchical modeling and different sensitivity analysis techniques to determine the parameters that cause the greatest impact on the availability of a Video on Demand. The results show that distinct approaches provide similar results regarding the sensitivity ranking, with specific exceptions. A combined evaluation indicates that system availability may be improved effectively by focusing on a reduced set of factors that produce large variation on the measure of interest.

  12. Minería de datos sobre streams de redes sociales, una herramienta al servicio de la Bibliotecología = Data Mining Streams of Social Networks, A Tool to Improve The Library Services

    Directory of Open Access Journals (Sweden)

    Sonia Jaramillo Valbuena

    2015-12-01

    , Facebook, RSS feeds and blogs, generate a large amount of unstructured data streams. They can be used to the problem of mining topic-specific influence, graph mining, opinion mining and recommender systems, thus achieving that libraries can obtain maximum benefit from the use of Information and Communication Technologies. From the perspective of data stream mining, the processing of these streams poses significant challenges. The algorithms must be adapted to problems such as: high arrival rate, memory requirements without restrictions, diverse sources of data and concept-drift. In this work, we explore the current state-of-the-art solutions of data stream mining originating from social networks, specifically, Facebook and Twitter. We present a review of the most representative algorithms and how they contribute to knowledge discovery in the area of librarianship. We conclude by presenting some of the problems that are the subject of active research.

  13. pH in streams draining small mined and unmined watersheds in the coal region of Appalachia

    Science.gov (United States)

    Kenneth L. Dyer; Willie R. Curtis

    1983-01-01

    To better evaluate the effects of surface mining for coal in first-order watersheds in Appalachia, a network of 421 water-quality sampling stations was established in 136 counties in nine states in 1977 and sampled on approximately a monthly basis until August 1979. Three categories of watersheds were sampled: (1) unmined, (2) mined after January 1972, and (3) mined...

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

    Directory of Open Access Journals (Sweden)

    Julián Martínez

    2017-12-01

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

  15. Gaining Insights on Nasopharyngeal Carcinoma Treatment Outcome Using Clinical Data Mining Techniques.

    Science.gov (United States)

    Ghaibeh, A Ammar; Kasem, Asem; Ng, Xun Jin; Nair, Hema Latha Krishna; Hirose, Jun; Thiruchelvam, Vinesh

    2018-01-01

    The analysis of Electronic Health Records (EHRs) is attracting a lot of research attention in the medical informatics domain. Hospitals and medical institutes started to use data mining techniques to gain new insights from the massive amounts of data that can be made available through EHRs. Researchers in the medical field have often used descriptive statistics and classical statistical methods to prove assumed medical hypotheses. However, discovering new insights from large amounts of data solely based on experts' observations is difficult. Using data mining techniques and visualizations, practitioners can find hidden knowledge, identify interesting patterns, or formulate new hypotheses to be further investigated. This paper describes a work in progress on using data mining methods to analyze clinical data of Nasopharyngeal Carcinoma (NPC) cancer patients. NPC is the fifth most common cancer among Malaysians, and the data analyzed in this study was collected from three states in Malaysia (Kuala Lumpur, Sabah and Sarawak), and is considered to be the largest up-to-date dataset of its kind. This research is addressing the issue of cancer recurrence after the completion of radiotherapy and chemotherapy treatment. We describe the procedure, problems, and insights gained during the process.

  16. Develop and implement preconditioning techniques to control face ejection rockbursts for safer mining in seismically hazardous areas

    CSIR Research Space (South Africa)

    Toper, AZ

    1998-01-01

    Full Text Available This research report discusses the development of preconditioning techniques to control face bursts, for safer mining in seismically hazardous areas. Preconditioning involves regularly setting off carefully tailored blasts in the fractured rock...

  17. Quality of water and sediment in streams affected by historical mining, and quality of Mine Tailings, in the Rio Grande/Rio Bravo Basin, Big Bend Area of the United States and Mexico, August 2002

    Science.gov (United States)

    Lambert, Rebecca B.; Kolbe, Christine M.; Belzer, Wayne

    2008-01-01

    The U.S. Geological Survey, in cooperation with the International Boundary and Water Commission - U.S. and Mexican Sections, the National Park Service, the Texas Commission on Environmental Quality, the Secretaria de Medio Ambiente y Recursos Naturales in Mexico, the Area de Proteccion de Flora y Fauna Canon de Santa Elena in Mexico, and the Area de Proteccion de Flora y Fauna Maderas del Carmen in Mexico, collected samples of stream water, streambed sediment, and mine tailings during August 2002 for a study to determine whether trace elements from abandoned mines in the area in and around Big Bend National Park have affected the water and sediment quality in the Rio Grande/Rio Bravo Basin of the United States and Mexico. Samples were collected from eight sites on the main stem of the Rio Grande/Rio Bravo, four Rio Grande/Rio Bravo tributary sites downstream from abandoned mines or mine-tailing sites, and 11 mine-tailing sites. Mines in the area were operated to produce fluorite, germanium, iron, lead, mercury, silver, and zinc during the late 1800s through at least the late 1970s. Moderate (relatively neutral) pHs in stream-water samples collected at the 12 Rio Grande/Rio Bravo main-stem and tributary sites indicate that water is well mixed, diluted, and buffered with respect to the solubility of trace elements. The highest sulfate concentrations were in water samples from tributaries draining the Terlingua mining district. Only the sample from the Rough Run Draw site exceeded the Texas Surface Water Quality Standards general-use protection criterion for sulfate. All chloride and dissolved solids concentrations in water samples were less than the general-use protection criteria. Aluminum, copper, mercury, nickel, selenium, and zinc were detected in all water samples for which each element was analyzed. Cadmium, chromium, and lead were detected in samples less frequently, and silver was not detected in any of the samples. None of the sample concentrations of

  18. Reduce of adherence problems in galvanised processes through data mining techniques

    International Nuclear Information System (INIS)

    Martinez de Pison, F. J.; Ordieres, J.; Pernia, A.; Alba, F.; Torre, V.

    2007-01-01

    This paper presents an example of the application of data mining techniques to obtain hidden knowledge from the historical data of a hot dip galvanizing process and to establish rules to improve quality in the final product and to reduce errors in the process. For this purpose, the tuning records of a hot dip galvanizing line where coils with adherence problems in the zinc coating had been identified were used as starting point. From the database of the process, the classical data mining approach was applied to obtain and analyze a number of decision trees hat classified two types of coils, i.e. those with the right adherence and those with irregular adherence. The variables and values that might have influenced the quality of the coating were extracted from these tress. Several rules that may be applied to reduce the number of faulty coils with adherence problems were also established. (Author) 24 refs

  19. Analysis of value added services on GDP Growth Rate using Data Mining Techniques

    Directory of Open Access Journals (Sweden)

    Douglas KUNDA

    2017-08-01

    Full Text Available The growth of Information Technology has spawned large amount of databases and huge data in numerous areas. The research in databases and information technology has given rise to an approach to store and manipulate this data for further decision making. In this paper certain data mining techniques were adopted to analyze the data that shows relevance with desired attributes. Regression technique was adopted to help us find out the influence of Agriculture, Service and Manufacturing on the performance of gross domestic product (GDP. Trend and time series technique was applied to the data to help us find out what trend of GDP with respect to service, agriculture and manufacturing sector for the past decade has been. Finally Correlation was also used to help us analyze the relationship among the variables (service, agriculture and manufacturing sector. From the three techniques analyzed, service value added variable was the most prominent variable which showed the strong influence on GDP growth rate.

  20. Stream water quality in coal mined areas of the lower Cheat River Basin, West Virginia and Pennsylvania, during low-flow conditions, July 1997

    Science.gov (United States)

    Williams, Donald R.; Clark, Mary E.; Brown, Juliane B.

    1999-01-01

    IntroductionThe Cheat River Basin is in the Allegheny Plateau and Allegheny Mountain Sections of the Appalachian Plateau Physiographic Province (Fenneman, 1946) and is almost entirely within the state of West Virginia. The Cheat River drains an area of 1,422 square miles in Randolph, Tucker, Preston, and Monongalia Counties in West Virginia and Fayette County in Pennsylvania. From its headwaters in Randolph County, W.Va., the Cheat River flows 157 miles north to the Pennsylvania state line, where it enters the Monongahela River. The Cheat River drainage comprises approximately 19 percent of the total Monongahela River Basin. The Cheat River and streams within the Cheat River Basin are characterized by steep gradients, rock channels, and high flow velocities that have created a thriving white-water rafting industry for the area. The headwaters of the Cheat River contain some of the most pristine and aesthetic streams in West Virginia. The attraction to the area, particularly the lower part of the Cheat River Basin (the lower 412 square miles of the basin), has been suppressed because of poor water quality. The economy of the Lower Cheat River Basin has been dominated by coal mining over many decades. As a result, many abandoned deep and surface mines discharge untreated acid mine drainage (AMD), which degrades water quality, into the Cheat River and many of its tributary streams. Approximately 60 regulated mine-related discharges (West Virginia Department of Environmental Protection, 1996) and 185 abandoned mine sites (U.S. Office of Surface Mining, 1998) discharge treated and untreated AMD into the Cheat River and its tributaries.The West Virginia Department of Environmental Protection (WVDEP) Office of Abandoned Mine Lands and Reclamation (AML&R) has recently completed several AMD reclamation projects throughout the Cheat River Basin that have collectively improved the mainstem water quality. The AML&R office is currently involved in acquiring grant funds and

  1. Abandoned mine drainage in the Swatara Creek Basin, southern anthracite coalfield, Pennsylvania, USA: 1. stream quality trends coinciding with the return of fish

    Science.gov (United States)

    Cravotta, Charles A.; Brightbill, Robin A.; Langland, Michael J.

    2010-01-01

    Acidic mine drainage (AMD) from legacy anthracite mines has contaminated Swatara Creek in eastern Pennsylvania. Intermittently collected base-flow data for 1959–1986 indicate that fish were absent immediately downstream from the mined area where pH ranged from 3.5 to 7.2 and concentrations of sulfate, dissolved iron, and dissolved aluminum were as high as 250, 2.0, and 4.7 mg/L, respectively. However, in the 1990s, fish returned to upper Swatara Creek, coinciding with the implementation of AMD treatment (limestone drains, limestone diversion wells, limestone sand, constructed wetlands) in the watershed. During 1996–2006, as many as 25 species of fish were identified in the reach downstream from the mined area, with base-flow pH from 5.8 to 7.6 and concentrations of sulfate, dissolved iron, and dissolved aluminum as high as 120, 1.2, and 0.43 mg/L, respectively. Several of the fish taxa are intolerant of pollution and low pH, such as river chub (Nocomis icropogon) and longnose dace (Rhinichthys cataractae). Cold-water species such as brook trout (Salvelinus fontinalis) and warm-water species such as rock bass (Ambloplites rupestris) varied in predominance depending on stream flow and stream temperature. Storm flow data for 1996–2007 indicated pH, alkalinity, and sulfate concentrations decreased as the stream flow and associated storm-runoff component increased, whereas iron and other metal concentrations were poorly correlated with stream flow because of hysteresis effects (greater metal concentrations during rising stage than falling stage). Prior to 1999, pH\\5.0 was recorded during several storm events; however, since the implementation of AMD treatments, pH has been maintained near neutral. Flow-adjusted trends for1997–2006 indicated significant increases in calcium; decreases in hydrogen ion, dissolved aluminum, dissolved and total manganese, and total iron; and no change in sulfate or dissolved iron in Swatara Creek immediately downstream from the

  2. Detection of breast cancer using advanced techniques of data mining with neural networks

    International Nuclear Information System (INIS)

    Ortiz M, J. A.; Celaya P, J. M.; Martinez B, M. R.; Solis S, L. O.; Castaneda M, R.; Garza V, I.; Martinez F, M.; Lopez H, Y.; Ortiz R, J. M.

    2016-10-01

    The breast cancer is one of the biggest health problems worldwide, is the most diagnosed cancer in women and prevention seems impossible since its cause is unknown, due to this; the early detection has a key role in the patient prognosis. In developing countries such as Mexico, where access to specialized health services is minimal, the regular clinical review is infrequent and there are not enough radiologists; the most common form of detection of breast cancer is through self-exploration, but this is only detected in later stages, when is already palpable. For these reasons, the objective of the present work is the creation of a system of computer assisted diagnosis (CAD x) using information analysis techniques such as data mining and advanced techniques of artificial intelligence, seeking to offer a previous medical diagnosis or a second opinion, as if it was a second radiologist in order to reduce the rate of mortality from breast cancer. In this paper, advances in the design of computational algorithms using computer vision techniques for the extraction of features derived from mammograms are presented. Using data mining techniques of data mining is possible to identify patients with a high risk of breast cancer. With the information obtained from the mammography analysis, the objective in the next stage will be to establish a methodology for the generation of imaging bio-markers to establish a breast cancer risk index for Mexican patients. In this first stage we present results of the classification of patients with high and low risk of suffering from breast cancer using neural networks. (Author)

  3. Error Control Techniques for Efficient Multicast Streaming in UMTS Networks: Proposals andPerformance Evaluation

    Directory of Open Access Journals (Sweden)

    Michele Rossi

    2004-06-01

    Full Text Available In this paper we introduce techniques for efficient multicast video streaming in UMTS networks where a video content has to be conveyed to multiple users in the same cell. Efficient multicast data delivery in UMTS is still an open issue. In particular, suitable solutions have to be found to cope with wireless channel errors, while maintaining both an acceptable channel utilization and a controlled delivery delay over the wireless link between the serving base station and the mobile terminals. Here, we first highlight that standard solutions such as unequal error protection (UEP of the video flow are ineffective in the UMTS systems due to its inherent large feedback delay at the link layer (Radio Link Control, RLC. Subsequently, we propose a local approach to solve errors directly at the UMTS link layer while keeping a reasonably high channel efficiency and saving, as much as possible, system resources. The solution that we propose in this paper is based on the usage of the common channel to serve all the interested users in a cell. In this way, we can save resources with respect to the case where multiple dedicated channels are allocated for every user. In addition to that, we present a hybrid ARQ (HARQ proactive protocol that, at the cost of some redundancy (added to the link layer flow, is able to consistently improve the channel efficiency with respect to the plain ARQ case, by therefore making the use of a single common channel for multicast data delivery feasible. In the last part of the paper we give some hints for future research, by envisioning the usage of the aforementioned error control protocols with suitably encoded video streams.

  4. Geochemistry of stream sediments, water and U-Th radiation anomaly around Neyshabour Fyrouzeh mine and its environmental impact on people living nearby villages

    International Nuclear Information System (INIS)

    Karimpour, M. H.; Malekzadeh Shafaroudi, A.

    2013-01-01

    Fyrouzeh mine is located about 55 km northwest of Neyshabour in the Province of Khorasan Razavi. The exposed rocks are mainly volcanic and intrusive with intermediate composition and all of them are altered. This mine is the first type of IOCG recognized in Iran with Cu-Au-LREE-U. Besides Cu-Au-U, this area shows As, Mo, Zn and Th anomalies. Geochemical evaluation of stream sediment with regard to environmental concern revealed high Cu anomalies. Rocks show high uranium anomalies (up to 35 ppm) higher than the standard values (1 ppm). Airborne radiometric maps show high U and Th anomalies in a broad area. Ag, Hg and Mn show anomalies within the stream sediments. Cu, Pb, Zn, Ag, Ni, Mn, Sb, Hg, and U content of both drinking and agricultural water are fortunately within the range of standard, only two samples have higher As content (more than 10 ppb). High level of U-Th radiation and contamination of stream sediment with respect to Cu, Hg, Ag, Mn and agricultural water to As are important environmental issues and people health therefore they need to be study.

  5. A study of natural recovery in an aquatic ecosystem affected by mining: the Rodrigatos stream (El Bierzo, Leon, Spain)

    International Nuclear Information System (INIS)

    Lacal, M.; Herrero, T.; Rodriguez, V.; Alberruche, E.; Vadillo, L.

    2009-01-01

    This work takes place into the Bierzo Region, located in northeast of the province of Leon (Spain). In this area numerous open-pit and underground coal mines exist. Some of them are still in activity but almost have been abandoned. In any case, mining implies the presence of coal adits, spoil dumps, tailing dams, and coal-washing plants at the river bank. Most of them persist when mining have finished. (Author)

  6. The Application of Data Mining Techniques to Create Promotion Strategy for Mobile Phone Shop

    Science.gov (United States)

    Khasanah, A. U.; Wibowo, K. S.; Dewantoro, H. F.

    2017-12-01

    The number of mobile shop is growing very fast in various regions in Indonesia including in Yogyakarta due to the increasing demand of mobile phone. This fact leads high competition among the mobile phone shops. In these conditions the mobile phone shop should have a good promotion strategy in order to survive in competition, especially for a small mobile phone shop. To create attractive promotion strategy, the companies/shops should know their customer segmentation and the buying pattern of their target market. These kind of analysis can be done using Data mining technique. This study aims to segment customer using Agglomerative Hierarchical Clustering and know customer buying pattern using Association Rule Mining. This result conducted in a mobile shop in Sleman Yogyakarta. The clustering result shows that the biggest customer segment of the shop was male university student who come on weekend and from association rule mining, it can be concluded that tempered glass and smart phone “x” as well as action camera and waterproof monopod and power bank have strong relationship. This results that used to create promotion strategies which are presented in the end of the study.

  7. Review on Malware and Malware Detection ‎Using Data Mining Techniques

    Directory of Open Access Journals (Sweden)

    Wesam S Bhaya

    2017-11-01

    Full Text Available Malicious software is any type of software or codes which hooks some: private information, data from the computer system, computer operations or(and merely just to do malicious goals of the author on the computer system, without permission of the computer users. (The short abbreviation of malicious software is Malware. However, the detection of malware has become one of biggest issues in the computer security field because of the current communication infrastructures are vulnerable to penetration from many types of malware infection strategies and attacks.  Moreover, malwares are variant and diverse in volume and types and that strictly explode the effectiveness of traditional defense methods like signature approach, which is unable to detect a new malware. However, this vulnerability will lead to a successful computer system penetration (and attack as well as success of more advanced attacks like distributed denial of service (DDoS attack. Data mining methods can be used to overcome limitation of signature-based techniques to detect the zero-day malware. This paper provides an overview of malware and malware detection system using modern techniques such as techniques of data mining approach to detect known and unknown malware samples.

  8. Brand Switching Pattern Discovery by Data Mining Techniques for the Telecommunication Industry in Australia

    Directory of Open Access Journals (Sweden)

    Md Zahidul Islam

    2016-11-01

    Full Text Available There is more than one mobile-phone subscription per member of the Australian population. The number of complaints against the mobile-phone-service providers is also high. Therefore, the mobile service providers are facing a huge challenge in retaining their customers. There are a number of existing models to analyse customer behaviour and switching patterns. A number of switching models may also exist within a large market. These models are often not useful due to the heterogeneous nature of the market. Therefore, in this study we use data mining techniques to let the data talk to help us discover switching patterns without requiring us to use any models and domain knowledge. We use a variety of decision tree and decision forest techniques on a real mobile-phone-usage dataset in order to demonstrate the effectiveness of data mining techniques in knowledge discovery. We report many interesting patterns, and discuss them from a brand-switching and marketing perspective, through which they are found to be very sensible and interesting.

  9. A Data mining Technique for Analyzing and Predicting the success of Movie

    Science.gov (United States)

    Meenakshi, K.; Maragatham, G.; Agarwal, Neha; Ghosh, Ishitha

    2018-04-01

    In real world prediction models and mechanisms can be used to predict the success of a movie. The proposed work aims to develop a system based upon data mining techniques that may help in predicting the success of a movie in advance thereby reducing certain level of uncertainty. An attempt is made to predict the past as well as the future of movie for the purpose of business certainty or simply a theoretical condition in which decision making [the success of the movie] is without risk, because the decision maker [movie makers and stake holders] has all the information about the exact outcome of the decision, before he or she makes the decision [release of the movie]. With over two million spectators a day and films exported to over 100 countries, the impact of Bollywood film industry is formidable We gather a series of interesting facts and relationships using a variety of data mining techniques. In particular, we concentrate on attributes relevant to the success prediction of movies, such as whether any particular actors or actresses are likely to help a movie to succeed. The paper additionally reports on the techniques used, giving their implementation and utility. Additionally, we found some attention-grabbing facts, such as the budget of a movie isn't any indication of how well-rated it'll be, there's a downward trend within the quality of films over time, and also the director and actors/actresses involved in the movie.

  10. Case study: how to apply data mining techniques in a healthcare data warehouse.

    Science.gov (United States)

    Silver, M; Sakata, T; Su, H C; Herman, C; Dolins, S B; O'Shea, M J

    2001-01-01

    Healthcare provider organizations are faced with a rising number of financial pressures. Both administrators and physicians need help analyzing large numbers of clinical and financial data when making decisions. To assist them, Rush-Presbyterian-St. Luke's Medical Center and Hitachi America, Ltd. (HAL), Inc., have partnered to build an enterprise data warehouse and perform a series of case study analyses. This article focuses on one analysis, which was performed by a team of physicians and computer science researchers, using a commercially available on-line analytical processing (OLAP) tool in conjunction with proprietary data mining techniques developed by HAL researchers. The initial objective of the analysis was to discover how to use data mining techniques to make business decisions that can influence cost, revenue, and operational efficiency while maintaining a high level of care. Another objective was to understand how to apply these techniques appropriately and to find a repeatable method for analyzing data and finding business insights. The process used to identify opportunities and effect changes is described.

  11. Applying Data Mining Techniques to Improve Information Security in the Cloud: A Single Cache System Approach

    OpenAIRE

    Amany AlShawi

    2016-01-01

    Presently, the popularity of cloud computing is gradually increasing day by day. The purpose of this research was to enhance the security of the cloud using techniques such as data mining with specific reference to the single cache system. From the findings of the research, it was observed that the security in the cloud could be enhanced with the single cache system. For future purposes, an Apriori algorithm can be applied to the single cache system. This can be applied by all cloud providers...

  12. Does leaf chemistry differentially affect breakdown in tropical vs temperate streams? Importance of standardized analytical techniques to measure leaf chemistry

    Science.gov (United States)

    Marcelo Ard& #243; n; Catherine M. Pringle; Susan L. Eggert

    2009-01-01

    Comparisons of the effects of leaf litter chemistry on leaf breakdown rates in tropical vs temperate streams are hindered by incompatibility among studies and across sites of analytical methods used to measure leaf chemistry. We used standardized analytical techniques to measure chemistry and breakdown rate of leaves from common riparian tree species at 2 sites, 1...

  13. Techniques for Minimizing and Monitoring the Impact of Pipeline Construction on Coastal Streams

    Science.gov (United States)

    Thomas W. Mulroy; John R. Storrer; Vincent J. Semonsen; Michael L. Dungan

    1989-01-01

    This paper describes specific measures recently employed for protection of riparian resources during construction of an oil and gas pipeline that crossed coastal reaches of 23 perennial and intermittent streams between Point Conception and Gaviota in Santa Barbara County, California. Flumes were constructed to maintain stream flow; anchored straw bales and silt fences...

  14. Application of remote-sensing techniques to hydrologic studies in selected coal-mine areas of southeastern Kansas

    Science.gov (United States)

    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)

  15. A case-based reasoning tool for breast cancer knowledge management with data mining concepts and techniques

    Science.gov (United States)

    Demigha, Souâd.

    2016-03-01

    The paper presents a Case-Based Reasoning Tool for Breast Cancer Knowledge Management to improve breast cancer screening. To develop this tool, we combine both concepts and techniques of Case-Based Reasoning (CBR) and Data Mining (DM). Physicians and radiologists ground their diagnosis on their expertise (past experience) based on clinical cases. Case-Based Reasoning is the process of solving new problems based on the solutions of similar past problems and structured as cases. CBR is suitable for medical use. On the other hand, existing traditional hospital information systems (HIS), Radiological Information Systems (RIS) and Picture Archiving Information Systems (PACS) don't allow managing efficiently medical information because of its complexity and heterogeneity. Data Mining is the process of mining information from a data set and transform it into an understandable structure for further use. Combining CBR to Data Mining techniques will facilitate diagnosis and decision-making of medical experts.

  16. Hydrogeochemical and mineralogical characteristics related to heavy metal attenuation in a stream polluted by acid mine drainage:A case study in Dabaoshan Mine, China

    Institute of Scientific and Technical Information of China (English)

    Huarong Zhao; Beicheng Xia; Jianqiao Qin; Jiaying Zhang

    2012-01-01

    Dabaoshan Mine,the largest mine in south China,has been developed since the 1970s.Acid mine drainage (AMD) discharged from the mine has caused severe environmental pollution and human health problems.In this article,chemical characteristics,mineralogy of ocher precipitations and heavy metal attenuation in the AMD are discussed based on physicochemical analysis,mineral analysis,sequential extraction experiments and hydrogeochemistry.The AMD chemical characteristics were determined from the initial water composition,water-rock interactions and dissolved sulfide minerals in the mine tailings.The waters,affected and unaffected by AMD,were Ca-SO4 and Ca-HCO3 types,respectively.The affected water had a low pH,high SO42- and high heavy metal content and oxidation as determined by the Fe2+/Fe3+ couple.Heavy metal and SO42- contents of Hengshi River water decreased,while pH increased,downstream.Schwertmannite was the major mineral at the waste dump,while goethite and quartz were dominant at the tailings dam and streambed.Schwertmannite was transformed into goethite at the tailings dam and streambed.The sulfate ions of the secondary minerals changed from bidentate- to monodentate-complexes downstream.Fe-Mn oxide phases of Zn,Cd and Pb in sediments increased downstream.However,organic matter complexes of Cu in sediments increased further away from the tailings.Fe3+ mineral precipitates and transformations controlled the AMD water chemistry.

  17. Examining students' graduation issues using data mining techniques - The case of TEI of Athens

    Science.gov (United States)

    Chalaris, Manolis; Gritzalis, Stefanos; Maragoudakis, Manolis; Sgouropoulou, Cleo; Lykeridou, Katerina

    2015-02-01

    One of the major issues that Greek Higher Education Institutes face is the delayed completion of studies of their students. For example, in the case of the Technological Educational Institute of Athens, in the academic year 2012-2013, the percentage of graduates with a length of studies of more than 6 years was 53%. This "problem" becomes harder if we consider that according to the new legislation, the Greek Higher Education Institutes (HEI) must cut off access to the students who "linger" too long. This means that many of these graduates wouldn't be able to complete their studies. While many institutes have systems to quantify and report the length of studies of all graduates, far less attention is typically paid to each student's reason(s) for delayed graduation. In this paper, we focus on examining the question of why students delay in the completion of their studies using several data mining techniques. Through the application of data mining techniques new knowledge will be provided to the administration of a HEI that could be used for solving this problem. The data used in our case study come from a questionnaire distributed to graduates of the institute but also from educational data stored in the Institute's student database.

  18. THE NOVELS ULYSSES AND TUTUNAMAYANLAR IN POINT OF STREAM OF CONSCIOUSNESS TECHNIQUE / ULYSSES ve TUTUNAMAYANLAR’DA BİLİNÇ AKISI TEKNİĞİ

    Directory of Open Access Journals (Sweden)

    Dr. Serdar ODACI

    2009-01-01

    Full Text Available By the modernism in novel, to introduce the innerworld of characters, stream of consciousness is used as anew narration technique. James Joyce has used identicalexamples of stream of consciousness technique inUlysses. The novel Tutunamayanlar written by Oğuz Atayhas an important position for Turkish novel. This novelbelonged to the writer who had followed the way modernism in Turkish literature. In this study these twonovels are examined in point of stream of consciousnesstechnique.

  19. Data Mining Techniques to Estimate Plutonium, Initial Enrichment, Burnup, and Cooling Time in Spent Fuel Assemblies

    Energy Technology Data Exchange (ETDEWEB)

    Trellue, Holly Renee [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Fugate, Michael Lynn [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Tobin, Stephen Joesph [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2015-03-19

    The Next Generation Safeguards Initiative (NGSI), Office of Nonproliferation and Arms Control (NPAC), National Nuclear Security Administration (NNSA) of the U.S. Department of Energy (DOE) has sponsored a multi-laboratory, university, international partner collaboration to (1) detect replaced or missing pins from spent fuel assemblies (SFA) to confirm item integrity and deter diversion, (2) determine plutonium mass and related plutonium and uranium fissile mass parameters in SFAs, and (3) verify initial enrichment (IE), burnup (BU), and cooling time (CT) of facility declaration for SFAs. A wide variety of nondestructive assay (NDA) techniques were researched to achieve these goals [Veal, 2010 and Humphrey, 2012]. In addition, the project includes two related activities with facility-specific benefits: (1) determination of heat content and (2) determination of reactivity (multiplication). In this research, a subset of 11 integrated NDA techniques was researched using data mining solutions at Los Alamos National Laboratory (LANL) for their ability to achieve the above goals.

  20. REVIEW OF HEART DISEASE PREDICTION SYSTEM USING DATA MINING AND HYBRID INTELLIGENT TECHNIQUES

    Directory of Open Access Journals (Sweden)

    R. Chitra

    2013-07-01

    Full Text Available The Healthcare industry generally clinical diagnosis is done mostly by doctor’s expertise and experience. Computer Aided Decision Support System plays a major role in medical field. With the growing research on heart disease predicting system, it has become important to categories the research outcomes and provides readers with an overview of the existing heart disease prediction techniques in each category. Neural Networks are one of many data mining analytical tools that can be utilized to make predictions for medical data. From the study it is observed that Hybrid Intelligent Algorithm improves the accuracy of the heart disease prediction system. The commonly used techniques for Heart Disease Prediction and their complexities are summarized in this paper.

  1. Optimization long hole blast fragmentation techniques and detonating circuit underground uranium mine stope

    International Nuclear Information System (INIS)

    Li Qin; Yang Lizhi; Song Lixia; Qin De'en; Xue Yongshe; Wang Zhipeng

    2012-01-01

    Aim at high rate of large blast fragmentation, a big difficulty in long hole drilling and blasting underground uranium mine stope, it is pointed out at the same time of taking integrated technical management measures, the key is to optimize the drilling and blasting parameters and insure safety the act of one that primes, adopt 'minimum burden' blasting technique, renew the stope fragmentation process, and use new process of hole bottom indirect initiation fragmentation; optimize the detonating circuit and use safe, reliable and economically rational duplex non-electric detonating circuit. The production practice shows that under the guarantee of strictly controlled construction quality, the application of optimized blast fragmentation technique has enhanced the reliability of safety detonation and preferably solved the problem of high rate of large blast fragments. (authors)

  2. Detecting the effects of coal mining, acid rain, and natural gas extraction in Appalachian basin streams in Pennsylvania (USA) through analysis of barium and sulfate concentrations.

    Science.gov (United States)

    Niu, Xianzeng; Wendt, Anna; Li, Zhenhui; Agarwal, Amal; Xue, Lingzhou; Gonzales, Matthew; Brantley, Susan L

    2018-04-01

    To understand how extraction of different energy sources impacts water resources requires assessment of how water chemistry has changed in comparison with the background values of pristine streams. With such understanding, we can develop better water quality standards and ecological interpretations. However, determination of pristine background chemistry is difficult in areas with heavy human impact. To learn to do this, we compiled a master dataset of sulfate and barium concentrations ([SO 4 ], [Ba]) in Pennsylvania (PA, USA) streams from publically available sources. These elements were chosen because they can represent contamination related to oil/gas and coal, respectively. We applied changepoint analysis (i.e., likelihood ratio test) to identify pristine streams, which we defined as streams with a low variability in concentrations as measured over years. From these pristine streams, we estimated the baseline concentrations for major bedrock types in PA. Overall, we found that 48,471 data values are available for [SO 4 ] from 1904 to 2014 and 3243 data for [Ba] from 1963 to 2014. Statewide [SO 4 ] baseline was estimated to be 15.8 ± 9.6 mg/L, but values range from 12.4 to 26.7 mg/L for different bedrock types. The statewide [Ba] baseline is 27.7 ± 10.6 µg/L and values range from 25.8 to 38.7 µg/L. Results show that most increases in [SO 4 ] from the baseline occurred in areas with intensive coal mining activities, confirming previous studies. Sulfate inputs from acid rain were also documented. Slight increases in [Ba] since 2007 and higher [Ba] in areas with higher densities of gas wells when compared to other areas could document impacts from shale gas development, the prevalence of basin brines, or decreases in acid rain and its coupled effects on [Ba] related to barite solubility. The largest impacts on PA stream [Ba] and [SO 4 ] are related to releases from coal mining or burning rather than oil and gas development.

  3. An approach to quantify sources, seasonal change, and biogeochemical processes affecting metal loading in streams: Facilitating decisions for remediation of mine drainage

    Science.gov (United States)

    Kimball, B.A.; Runkel, R.L.; Walton-Day, K.

    2010-01-01

    Historical mining has left complex problems in catchments throughout the world. Land managers are faced with making cost-effective plans to remediate mine influences. Remediation plans are facilitated by spatial mass-loading profiles that indicate the locations of metal mass-loading, seasonal changes, and the extent of biogeochemical processes. Field-scale experiments during both low- and high-flow conditions and time-series data over diel cycles illustrate how this can be accomplished. A low-flow experiment provided spatially detailed loading profiles to indicate where loading occurred. For example, SO42 - was principally derived from sources upstream from the study reach, but three principal locations also were important for SO42 - loading within the reach. During high-flow conditions, Lagrangian sampling provided data to interpret seasonal changes and indicated locations where snowmelt runoff flushed metals to the stream. Comparison of metal concentrations between the low- and high-flow experiments indicated substantial increases in metal loading at high flow, but little change in metal concentrations, showing that toxicity at the most downstream sampling site was not substantially greater during snowmelt runoff. During high-flow conditions, a detailed temporal sampling at fixed sites indicated that Zn concentration more than doubled during the diel cycle. Monitoring programs must account for diel variation to provide meaningful results. Mass-loading studies during different flow conditions and detailed time-series over diel cycles provide useful scientific support for stream management decisions.

  4. Development and Application of Blast Casting Technique in Large-Scale Surface Mines: A Case Study of Heidaigou Surface Coal Mine in China

    Directory of Open Access Journals (Sweden)

    Li Ma

    2016-01-01

    Full Text Available Blast casting is a high-efficiency technique applied in surface mines for overburden removal and results in stripping cost savings. According to ballistic theory and center-of-mass frame basic movement principles, key factors influencing blast casting effect were analyzed, which include bench height and mining panel width, inclined angle of blast holes, explosive unit consumption (EUC, delay-time interval, presplitting, and blast hole pattern parameters. An intelligent design software was developed for obtaining better breaking and casting effect, and the error rates predicted with actual result can be controlled with 10%. Blast casting technique was successfully applied in Heidaigou Surface Coal Mine (HSCM with more than 34% of material casted into the inner dump. A ramp ditch was set within the middle inner dump for coal transportation. The procedure of stripping and excavating was implemented separately and alternately in the two sections around the middle ramp ditch. An unconstrained-nonlinear model was deduced for optimizing the shift distance of the middle ramp. The calculation results show that optimum shift distance of HSCM is 480 m, and the middle ditch should be shifted after 6 blast casting mining panels being stripped.

  5. Geospatial Image Stream Processing: Models, techniques, and applications in remote sensing change detection

    Science.gov (United States)

    Rueda-Velasquez, Carlos Alberto

    Detection of changes in environmental phenomena using remotely sensed data is a major requirement in the Earth sciences, especially in natural disaster related scenarios where real-time detection plays a crucial role in the saving of human lives and the preservation of natural resources. Although various approaches formulated to model multidimensional data can in principle be applied to the inherent complexity of remotely sensed geospatial data, there are still challenging peculiarities that demand a precise characterization in the context of change detection, particularly in scenarios of fast changes. In the same vein, geospatial image streams do not fit appropriately in the standard Data Stream Management System (DSMS) approach because these systems mainly deal with tuple-based streams. Recognizing the necessity for a systematic effort to address the above issues, the work presented in this thesis is a concrete step toward the foundation and construction of an integrated Geospatial Image Stream Processing framework, GISP. First, we present a data and metadata model for remotely sensed image streams. We introduce a precise characterization of images and image streams in the context of remotely sensed geospatial data. On this foundation, we define spatially-aware temporal operators with a consistent semantics for change analysis tasks. We address the change detection problem in settings where multiple image stream sources are available, and thus we introduce an architectural design for the processing of geospatial image streams from multiple sources. With the aim of targeting collaborative scientific environments, we construct a realization of our architecture based on Kepler, a robust and widely used scientific workflow management system, as the underlying computational support; and open data and Web interface standards, as a means to facilitate the interoperability of GISP instances with other processing infrastructures and client applications. We demonstrate our

  6. Mine Water Treatment in Hongai Coal Mines

    OpenAIRE

    Dang Phuong Thao; Dang Vu Chi

    2018-01-01

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

  7. Estimation of Crop Coefficient of Corn (Kccorn under Climate Change Scenarios Using Data Mining Technique

    Directory of Open Access Journals (Sweden)

    Kampanad Bhaktikul

    2012-01-01

    Full Text Available The main objectives of this study are to determine the crop coefficient of corn (Kccorn using data mining technique under climate change scenarios, and to develop the guidelines for future water management based on climate change scenarios. Variables including date, maximum temperature, minimum temperature, precipitation, humidity, wind speed, and solar radiation from seven meteorological stations during 1991 to 2000 were used. Cross-Industry Standard Process for Data Mining (CRISP-DM was applied for data collection and analyses. The procedures compose of investigation of input data, model set up using Artificial Neural Networks (ANNs, model evaluation, and finally estimation of the Kccorn. Three climate change scenarios of carbon dioxide (CO2 concentration level: 360 ppm, 540 ppm, and 720 ppm were set. The results indicated that the best number of node of input layer - hidden layer - output layer was 7-13-1. The correlation coefficient of model was 0.99. The predicted Kccorn revealed that evapotranspiration (ETcorn pattern will be changed significantly upon CO2 concentration level. From the model predictions, ETcorn will be decreased 3.34% when CO2 increased from 360 ppm to 540 ppm. For the double CO2 concentration from 360 ppm to 720 ppm, ETcorn will be increased 16.13%. The future water management guidelines to cope with the climate change are suggested.

  8. Detection of underground mined voids using line electrode resistivity technique - case study

    Energy Technology Data Exchange (ETDEWEB)

    Peng, S.S.; Ziaie, F. (West Virginia University, Morgantown, WV (USA))

    1991-06-01

    A new resistivity method was developed and tested in three phases; simulated model, similitude model, and field survey. This resistivity method was a combination of the Bristow arrangement and line electrode method. Three line electrodes were chosen so that the sinkhole electrode was emplaced at a far distance from the other two electrodes. Any of the two electrodes and the sinkhole electrode were activated and several resistivity profiles perpendicular to the line electrode prepared for different electrodes activation. Subsurface cavities caused resistivity anomalies which were interpreted to locate their sources (cavities) and estimate the depths and dimension of the cavities. A coal mine site employing the room and pillar mining system was selected to confirm the results of the laboratory. The results of the interpretation indicated that the entry with a dimension of 135 cm high and 5.40 m wide at a depth of 25.50 m can be detected by this method. The resolution of the detectability of this method proved a great success when compared to other resistivity techniques. 6 refs., 6 figs.

  9. An application of data mining techniques in designing catalogue for a laundry service

    Directory of Open Access Journals (Sweden)

    Khasanah Annisa Uswatun

    2018-01-01

    Full Text Available Catalogues are the media that companies use to promote their products or services. Since catalogue is one of marketing media, the first essential step before designing product catalogue is determining the market target. Besides, it is also important to put some information that appeal to the target market, such as discount or promos by analysing customer pattern preferences in using services or buying product. This study conduct two data mining technique. The first is clustering analysis to segment customer and the second one is association rule mining to discover an interesting pattern about the services that commonly used by the customer at the same service time. Thus, the results will be used as a recommendation to make an attractive marketing strategy to be put in the service catalogue promo for a laundry in Sleman Yogyakarta. The clustering result showed that the biggest customer segment is university student who come 3 until 5 times in a month on weekends, while the association rule result showed that clothes, shoes, and bed sheet have strong relationship. The catalogue design is presented in the end of the paper.

  10. The Study of Mining Activities and their Influences in the Almaden Region Applying Remote Sensing Techniques

    International Nuclear Information System (INIS)

    Rico, C.; Schmid, T.; Millan, R.; Gumuzzio, J.

    2010-01-01

    This scientific-technical report is a part of an ongoing research work carried out by Celia Rico Fraile in order to obtain the Diploma of Advanced Studies as part of her PhD studies. This work has been developed in collaboration with the Faculty of Science at The Universidad Autonoma de Madrid and the Department of Environment at CIEMAT. The main objective of this work was the characterization and classification of land use in Almaden (Ciudad Real) during cinnabar mineral exploitation and after mining activities ceased in 2002, developing a methodology focused on the integration of remote sensing techniques applying multispectral and hyper spectral satellite data. By means of preprocessing and processing of data from the satellite images as well as data obtained from field campaigns, a spectral library was compiled in order to obtain representative land surfaces within the study area. Monitoring results show that the distribution of areas affected by mining activities is rapidly diminishing in recent years. (Author) 130 refs

  11. Application of Modern Tools and Techniques for Mine Safety & Disaster Management

    Science.gov (United States)

    Kumar, Dheeraj

    2016-04-01

    The implementation of novel systems and adoption of improvised equipment in mines help mining companies in two important ways: enhanced mine productivity and improved worker safety. There is a substantial need for adoption of state-of-the-art automation technologies in the mines to ensure the safety and to protect health of mine workers. With the advent of new autonomous equipment used in the mine, the inefficiencies are reduced by limiting human inconsistencies and error. The desired increase in productivity at a mine can sometimes be achieved by changing only a few simple variables. Significant developments have been made in the areas of surface and underground communication, robotics, smart sensors, tracking systems, mine gas monitoring systems and ground movements etc. Advancement in information technology in the form of internet, GIS, remote sensing, satellite communication, etc. have proved to be important tools for hazard reduction and disaster management. This paper is mainly focused on issues pertaining to mine safety and disaster management and some of the recent innovations in the mine automations that could be deployed in mines for safe mining operations and for avoiding any unforeseen mine disaster.

  12. Applying Data Mining Techniques to Improve Information Security in the Cloud: A Single Cache System Approach

    Directory of Open Access Journals (Sweden)

    Amany AlShawi

    2016-01-01

    Full Text Available Presently, the popularity of cloud computing is gradually increasing day by day. The purpose of this research was to enhance the security of the cloud using techniques such as data mining with specific reference to the single cache system. From the findings of the research, it was observed that the security in the cloud could be enhanced with the single cache system. For future purposes, an Apriori algorithm can be applied to the single cache system. This can be applied by all cloud providers, vendors, data distributors, and others. Further, data objects entered into the single cache system can be extended into 12 components. Database and SPSS modelers can be used to implement the same.

  13. Effective search for stable segregation configurations at grain boundaries with data-mining techniques

    Science.gov (United States)

    Kiyohara, Shin; Mizoguchi, Teruyasu

    2018-03-01

    Grain boundary segregation of dopants plays a crucial role in materials properties. To investigate the dopant segregation behavior at the grain boundary, an enormous number of combinations have to be considered in the segregation of multiple dopants at the complex grain boundary structures. Here, two data mining techniques, the random-forests regression and the genetic algorithm, were applied to determine stable segregation sites at grain boundaries efficiently. Using the random-forests method, a predictive model was constructed from 2% of the segregation configurations and it has been shown that this model could determine the stable segregation configurations. Furthermore, the genetic algorithm also successfully determined the most stable segregation configuration with great efficiency. We demonstrate that these approaches are quite effective to investigate the dopant segregation behaviors at grain boundaries.

  14. Geomechanical characterization of volcanic rocks using empirical systems and data mining techniques

    Directory of Open Access Journals (Sweden)

    T. Miranda

    2018-02-01

    Full Text Available This paper tries to characterize volcanic rocks through the development and application of an empirical geomechanical system. Geotechnical information was collected from the samples from several Atlantic Ocean islands including Madeira, Azores and Canarias archipelagos. An empirical rock classification system termed as the volcanic rock system (VRS is developed and presented in detail. Results using the VRS are compared with those obtained using the traditional rock mass rating (RMR system. Data mining (DM techniques are applied to a database of volcanic rock geomechanical information from the islands. Different algorithms were developed and consequently approaches were followed for predicting rock mass classes using the VRS and RMR classification systems. Finally, some conclusions are drawn with emphasis on the fact that a better performance was achieved using attributes from VRS.

  15. Ground-based thermal imaging of stream surface temperatures: Technique and evaluation

    Science.gov (United States)

    Bonar, Scott A.; Petre, Sally J.

    2015-01-01

    We evaluated a ground-based handheld thermal imaging system for measuring water temperatures using data from eight southwestern USA streams and rivers. We found handheld thermal imagers could provide considerably more spatial information on water temperature (for our unit one image = 19,600 individual temperature measurements) than traditional methods could supply without a prohibitive amount of effort. Furthermore, they could provide measurements of stream surface temperature almost instantaneously compared with most traditional handheld thermometers (e.g., >20 s/reading). Spatial temperature analysis is important for measurement of subtle temperature differences across waterways, and identification of warm and cold groundwater inputs. Handheld thermal imaging is less expensive and equipment intensive than airborne thermal imaging methods and is useful under riparian canopies. Disadvantages of handheld thermal imagers include their current higher expense than thermometers, their susceptibility to interference when used incorrectly, and their slightly lower accuracy than traditional temperature measurement methods. Thermal imagers can only measure surface temperature, but this usually corresponds to subsurface temperatures in well-mixed streams and rivers. Using thermal imaging in select applications, such as where spatial investigations of water temperature are needed, or in conjunction with stationary temperature data loggers or handheld electronic or liquid-in-glass thermometers to characterize stream temperatures by both time and space, could provide valuable information on stream temperature dynamics. These tools will become increasingly important to fisheries biologists as costs continue to decline.

  16. Web Mining

    Science.gov (United States)

    Fürnkranz, Johannes

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

  17. Mining for diagnostic information in body surface potential maps: A comparison of feature selection techniques

    Directory of Open Access Journals (Sweden)

    McCullagh Paul J

    2005-09-01

    Full Text Available Abstract Background In body surface potential mapping, increased spatial sampling is used to allow more accurate detection of a cardiac abnormality. Although diagnostically superior to more conventional electrocardiographic techniques, the perceived complexity of the Body Surface Potential Map (BSPM acquisition process has prohibited its acceptance in clinical practice. For this reason there is an interest in striking a compromise between the minimum number of electrocardiographic recording sites required to sample the maximum electrocardiographic information. Methods In the current study, several techniques widely used in the domains of data mining and knowledge discovery have been employed to mine for diagnostic information in 192 lead BSPMs. In particular, the Single Variable Classifier (SVC based filter and Sequential Forward Selection (SFS based wrapper approaches to feature selection have been implemented and evaluated. Using a set of recordings from 116 subjects, the diagnostic ability of subsets of 3, 6, 9, 12, 24 and 32 electrocardiographic recording sites have been evaluated based on their ability to correctly asses the presence or absence of Myocardial Infarction (MI. Results It was observed that the wrapper approach, using sequential forward selection and a 5 nearest neighbour classifier, was capable of choosing a set of 24 recording sites that could correctly classify 82.8% of BSPMs. Although the filter method performed slightly less favourably, the performance was comparable with a classification accuracy of 79.3%. In addition, experiments were conducted to show how (a features chosen using the wrapper approach were specific to the classifier used in the selection model, and (b lead subsets chosen were not necessarily unique. Conclusion It was concluded that both the filter and wrapper approaches adopted were suitable for guiding the choice of recording sites useful for determining the presence of MI. It should be noted however

  18. A Framework for Prediction of Response to HCV Therapy Using Different Data Mining Techniques

    Directory of Open Access Journals (Sweden)

    Enas M. F. El Houby

    2014-01-01

    Full Text Available Hepatitis C which is a widely spread disease all over the world is a fatal liver disease caused by Hepatitis C Virus (HCV. The only approved therapy is interferon plus ribavirin. The number of responders to this treatment is low, while its cost is high and side effects are undesirable. Treatment response prediction will help in reducing the patients who suffer from the side effects and high costs without achieving recovery. The aim of this research is to develop a framework which can select the best model to predict HCV patients’ response to the treatment of HCV from clinical information. The framework contains three phases which are preprocessing phase to prepare the data for applying Data Mining (DM techniques, DM phase to apply different DM techniques, and evaluation phase to evaluate and compare the performance of the built models and select the best model as the recommended one. Different DM techniques had been applied which are associative classification, artificial neural network, and decision tree to evaluate the framework. The experimental results showed the effectiveness of the framework in selecting the best model which is the model built by associative classification using histology activity index, fibrosis stage, and alanine amino transferase.

  19. Classification of the financial sustainability of health insurance beneficiaries through data mining techniques

    Directory of Open Access Journals (Sweden)

    Sílvia Maria Dias Pedro Rebouças

    2016-09-01

    Full Text Available Advances in information technologies have led to the storage of large amounts of data by organizations. An analysis of this data through data mining techniques is important support for decision-making. This article aims to apply techniques for the classification of the beneficiaries of an operator of health insurance in Brazil, according to their financial sustainability, via their sociodemographic characteristics and their healthcare cost history. Beneficiaries with a loss ratio greater than 0.75 are considered unsustainable. The sample consists of 38875 beneficiaries, active between the years 2011 and 2013. The techniques used were logistic regression and classification trees. The performance of the models was compared to accuracy rates and receiver operating Characteristic curves (ROC curves, by determining the area under the curves (AUC. The results showed that most of the sample is composed of sustainable beneficiaries. The logistic regression model had a 68.43% accuracy rate with AUC of 0.7501, and the classification tree obtained 67.76% accuracy and an AUC of 0.6855. Age and the type of plan were the most important variables related to the profile of the beneficiaries in the classification. The highlights with regard to healthcare costs were annual spending on consultation and on dental insurance.

  20. On the sensitivity evaluation for on-stream elemental analysis using neutron and photoactivation techniques

    International Nuclear Information System (INIS)

    Ivanov, I.N.; Zakharov, E.A.; Kasatkin, V.A.; Kartashev, E.R.; Mashinin, V.A.; Feoktistov, Yu.V.; Tchulkin, V.L.

    1984-01-01

    The paper discusses the data of calculations of neutron and photonactivation effects of moving substances, in particular, bulk materials moving on a conveyor belt and solution streams. The calculated data on minimum detectable concentrations of the various elements are given. The calculation data satisfactorily agree with the experimental data obtained as a result of on-stream neutron activation analysis of solutions containing indium, selenium, aluminium, fluorine and also bulk materials containing aluminium and silicon. The opportunity of applying the bremsstrahlung generated by the electron accelerator for photon activation analysis and sorting gold-bearing ores on the conveyor belt has been analysed

  1. Agricultural Soil Spectral Response and Properties Assessment: Effects of Measurement Protocol and Data Mining Technique

    Directory of Open Access Journals (Sweden)

    Asa Gholizadeh

    2017-10-01

    Full Text Available Soil spectroscopy has shown to be a fast, cost-effective, environmentally friendly, non-destructive, reproducible and repeatable analytical technique. Soil components, as well as types of instruments, protocols, sampling methods, sample preparation, spectral acquisition techniques and analytical algorithms have a combined influence on the final performance. Therefore, it is important to characterize these differences and to introduce an effective approach in order to minimize the technical factors that alter reflectance spectra and consequent prediction. To quantify this alteration, a joint project between Czech University of Life Sciences Prague (CULS and Tel-Aviv University (TAU was conducted to estimate Cox, pH-H2O, pH-KCl and selected forms of Fe and Mn. Two different soil spectral measurement protocols and two data mining techniques were used to examine seventy-eight soil samples from five agricultural areas in different parts of the Czech Republic. Spectral measurements at both laboratories were made using different ASD spectroradiometers. The CULS protocol was based on employing a contact probe (CP spectral measurement scheme, while the TAU protocol was carried out using a CP measurement method, accompanied with the internal soil standard (ISS procedure. Two spectral datasets, acquired from different protocols, were both analyzed using partial least square regression (PLSR technique as well as the PARACUDA II®, a new data mining engine for optimizing PLSR models. The results showed that spectra based on the CULS setup (non-ISS demonstrated significantly higher albedo intensity and reflectance values relative to the TAU setup with ISS. However, the majority of statistics using the TAU protocol was not noticeably better than the CULS spectra. The paper also highlighted that under both measurement protocols, the PARACUDA II® engine proved to be a powerful tool for providing better results than PLSR. Such initiative is not only a way to

  2. Post-acquisition data mining techniques for LC-MS/MS-acquired data in drug metabolite identification.

    Science.gov (United States)

    Dhurjad, Pooja Sukhdev; Marothu, Vamsi Krishna; Rathod, Rajeshwari

    2017-08-01

    Metabolite identification is a crucial part of the drug discovery process. LC-MS/MS-based metabolite identification has gained widespread use, but the data acquired by the LC-MS/MS instrument is complex, and thus the interpretation of data becomes troublesome. Fortunately, advancements in data mining techniques have simplified the process of data interpretation with improved mass accuracy and provide a potentially selective, sensitive, accurate and comprehensive way for metabolite identification. In this review, we have discussed the targeted (extracted ion chromatogram, mass defect filter, product ion filter, neutral loss filter and isotope pattern filter) and untargeted (control sample comparison, background subtraction and metabolomic approaches) post-acquisition data mining techniques, which facilitate the drug metabolite identification. We have also discussed the importance of integrated data mining strategy.

  3. Some physiochemical and heavy metal concentration in surface water streams of Tutuka in the Kenyasi mining catchment area

    Energy Technology Data Exchange (ETDEWEB)

    Boateng, Louis [University of Education, Winneba Ghana, P. O. Box 40, Mampong (Ghana)

    2013-07-01

    This research was conducted in the Akantansu stream of Tutuka in Kenyasi in the Brong Ahafo Region of Ghana in the months of October and November 2010 and January 2011. The major objectives of the study were to measure levels of pH, BOD (biochemical oxygen demand), lead, chromium, and arsenic in the Akantansu stream of Tutuka and to find ways that the community could ensure safe water use. To achieve the objectives of the study, sampling was done over a period of three months and data was collected and analyzed into graphs and ANOVA tables. The research revealed that the levels of arsenic and BOD were high as compared to the standards of WHO and EPA. If the people of Tutuka continue to use the stream, they may experience negative health effects (e.g., nausea, vomiting, diarrhea, etc.). The level of pH, chromium and lead was acceptable as compared to the standard of WHO and EPA. (authors)

  4. Analysis and optimization techniques for real-time streaming image processing software on general purpose systems

    NARCIS (Netherlands)

    Westmijze, Mark

    2018-01-01

    Commercial Off The Shelf (COTS) Chip Multi-Processor (CMP) systems are for cost reasons often used in industry for soft real-time stream processing. COTS CMP systems typically have a low timing predictability, which makes it difficult to develop software applications for these systems with tight

  5. Examining Mobile Learning Trends 2003-2008: A Categorical Meta-Trend Analysis Using Text Mining Techniques

    Science.gov (United States)

    Hung, Jui-Long; Zhang, Ke

    2012-01-01

    This study investigated the longitudinal trends of academic articles in Mobile Learning (ML) using text mining techniques. One hundred and nineteen (119) refereed journal articles and proceedings papers from the SCI/SSCI database were retrieved and analyzed. The taxonomies of ML publications were grouped into twelve clusters (topics) and four…

  6. Application of rule-based data mining techniques to real time ATLAS Grid job monitoring data

    CERN Document Server

    Ahrens, R; The ATLAS collaboration; Kalinin, S; Maettig, P; Sandhoff, M; dos Santos, T; Volkmer, F

    2012-01-01

    The Job Execution Monitor (JEM) is a job-centric grid job monitoring software developed at the University of Wuppertal and integrated into the pilot-based “PanDA” job brokerage system leveraging physics analysis and Monte Carlo event production for the ATLAS experiment on the Worldwide LHC Computing Grid (WLCG). With JEM, job progress and grid worker node health can be supervised in real time by users, site admins and shift personnel. Imminent error conditions can be detected early and countermeasures can be initiated by the Job’s owner immideatly. Grid site admins can access aggregated data of all monitored jobs to infer the site status and to detect job and Grid worker node misbehaviour. Shifters can use the same aggregated data to quickly react to site error conditions and broken production tasks. In this work, the application of novel data-centric rule based methods and data-mining techniques to the real time monitoring data is discussed. The usage of such automatic inference techniques on monitorin...

  7. A methodology for semiautomatic taxonomy of concepts extraction from nuclear scientific documents using text mining techniques

    International Nuclear Information System (INIS)

    Braga, Fabiane dos Reis

    2013-01-01

    This thesis presents a text mining method for semi-automatic extraction of taxonomy of concepts, from a textual corpus composed of scientific papers related to nuclear area. The text classification is a natural human practice and a crucial task for work with large repositories. The document clustering technique provides a logical and understandable framework that facilitates the organization, browsing and searching. Most clustering algorithms using the bag of words model to represent the content of a document. This model generates a high dimensionality of the data, ignores the fact that different words can have the same meaning and does not consider the relationship between them, assuming that words are independent of each other. The methodology presents a combination of a model for document representation by concepts with a hierarchical document clustering method using frequency of co-occurrence concepts and a technique for clusters labeling more representatives, with the objective of producing a taxonomy of concepts which may reflect a structure of the knowledge domain. It is hoped that this work will contribute to the conceptual mapping of scientific production of nuclear area and thus support the management of research activities in this area. (author)

  8. Towards an increase of flash flood geomorphic effects due to gravel mining and ground subsidence in Nogalte stream (Murcia, SE Spain

    Directory of Open Access Journals (Sweden)

    J. A. Ortega-Becerril

    2016-10-01

    Full Text Available Transition from endorheic alluvial fan environments to well-channelized fluvial systems in natural conditions may occur in response to base-level fluctuations. However, human-induced changes in semi-arid regions can also be responsible for similar unforeseen modifications. Our results confirm that in-channel gravel mining and aquifer overexploitation over the last 50 years in the case study area have changed the natural stability of the Nogalte stream and, as a result, its geomorphic parameters including channel depth and longitudinal profile have begun to adapt to the new situation. Using interferometric synthetic aperture radar (InSAR data we obtain maximum values for ground subsidence in the Upper Guadalentín Basin of  ∼ 10 cm yr−1 for the period 2003–2010. In this context of a lowered base level, the river is changing its natural flood model to a more powerful one. A comparison of the 1973 flood event, the most dramatic flood event ever recorded in the area, with the 2012 event, where there was a similar discharge but a sediment load deficit, reveals greater changes and a new flooding pattern and extension. In-channel gravel mining may be responsible for significant local changes in channel incision and profile. This, together with the collateral effects of aquifer overexploitation, can favour increased river velocity and stream power, which intensify the consequences of the flooding. The results obtained here clearly demonstrate an existing transition from the former alluvial pattern to a confined fluvial trend, which may become more pronounced in the future due to the time lag between the drop in aquifer level and ground subsidence, and introduce a new scenario to be taken into consideration in future natural hazard planning in this area.

  9. Some physiochemical and heavy metal concentration in surface water stream of Tutuka in the Kenyasi mining catchment area

    Directory of Open Access Journals (Sweden)

    B.M. Tiimub

    2012-09-01

    Full Text Available The research was conducted in the Akantansu stream of Tutuka in Kenyasi in the Brong Ahafo Region of Ghana from October 2010 to January 2011. The objectives of the study were to find out the contamination levels of pH, BOD5, Lead, Chromium, and Arsenic in the Akantansu stream of Tutuka to promote public health safety of people patronizing the stream for bathing and cooking. Determination of pH was achieved using Etech instrument (PC 300 series where as BOD5 level was assessed by means of empirical standard laboratory test which determined the relative oxygen requirements of waste water, effluents and polluted water using the standard procedure as per America Public Health Association (2006. An AAS 220 atomic absorption spectrometer was used for the analyses of heavy metals (lead, chromium and arsenic. The Research revealed that, the geometric mean levels of (0.01- 0.02, 0.03 – 0.26, 0 - 0.01, 3.99 – 7.06 mg/L and 5.64 – 6.40 for Arsenic, Lead, Chromium, BOD5 and pH compared to the EPA Maximum Permissible Limits of ( 0.5, 0.1, 0.1, 50 mg/L and 6-9 were respectively within the acceptable standards. However, due to slightly higher concentration of chromium (0.26 mg/L up the stream, the people of Tutuka may develop health effects such as nausea, vomiting, diarrhea, hallucinations, headaches, depression, sleeping disorders, skin cancers, tumours in lungs, bladder, kidney and liver if they continue to use water from the stream for bathing and cooking.

  10. Deriving preference order of post-mining land-uses through MLSA framework: application of an outranking technique

    Science.gov (United States)

    Soltanmohammadi, Hossein; Osanloo, Morteza; Aghajani Bazzazi, Abbas

    2009-08-01

    This study intends to take advantage of a previously developed framework for mined land suitability analysis (MLSA) consisted of economical, social, technical and mine site factors to achieve a partial and also a complete pre-order of feasible post-mining land-uses. Analysis by an outranking multi-attribute decision-making (MADM) technique, called PROMETHEE (preference ranking organization method for enrichment evaluation), was taken into consideration because of its clear advantages on the field of MLSA as compared with MADM ranking techniques. Application of the proposed approach on a mined land can be completed through some successive steps. First, performance of the MLSA attributes is scored locally by each individual decision maker (DM). Then the assigned performance scores are normalized and the deviation amplitudes of non-dominated alternatives are calculated. Weights of the attributes are calculated by another MADM technique namely, analytical hierarchy process (AHP) in a separate procedure. Using the Gaussian preference function beside the weights, the preference indexes of the land-use alternatives are obtained. Calculation of the outgoing and entering flows of the alternatives and one by one comparison of these values will lead to partial pre-order of them and calculation of the net flows, will lead to a ranked preference for each land-use. At the final step, utilizing the PROMETHEE group decision support system which incorporates judgments of all the DMs, a consensual ranking can be derived. In this paper, preference order of post-mining land-uses for a hypothetical mined land has been derived according to judgments of one DM to reveal applicability of the proposed approach.

  11. Mercury Concentrations in Fish and Sediment within Streams are Influenced by Watershed and Landscape Variables including Historical Gold Mining in the Sierra Nevada, California

    Science.gov (United States)

    Alpers, C. N.; Yee, J. L.; Ackerman, J. T.; Orlando, J. L.; Slotton, D. G.; Marvin-DiPasquale, M. C.

    2015-12-01

    We compiled available data on total mercury (THg) and methylmercury (MeHg) concentrations in fish tissue and streambed sediment from stream sites in the Sierra Nevada, California, to assess whether spatial data, including information on historical mining, can be used to make robust predictions of fish fillet tissue THg concentrations. A total of 1,271 fish from five species collected at 103 sites during 1980-2012 were used for the modeling effort: 210 brown trout, 710 rainbow trout, 79 Sacramento pikeminnow, 93 Sacramento sucker, and 179 smallmouth bass. Sediment data were used from 73 sites, including 106 analyses of THg and 77 analyses of MeHg. The dataset included 391 fish (mostly rainbow trout) and 28 sediment samples collected explicitly for this study during 2011-12. Spatial data on historical mining included the USGS Mineral Resources Data System and publicly available maps and satellite photos showing the areas of hydraulic mine pits and other placer mines. Modeling was done using multivariate linear regression and multi-model inference using Akaike Information Criteria. Results indicate that fish THg, accounting for species and length, can be predicted using geospatial data on mining history together with other landscape characteristics including land use/land cover. A model requiring only geospatial data, with an R2 value of 0.61, predicted fish THg correctly with respect to over-or-under 0.2 μg/g wet weight (a California regulatory threshold) for 108 of 121 (89 %) size-species combinations tested. Data for THg in streambed sediment did not improve the geospatial-only model. However, data for sediment MeHg, loss on ignition (organic content), and percent of sediment less than 0.063 mm resulted in a slightly improved model, with an R2 value of 0.63. It is anticipated that these models will be useful to the State of California and others to predict areas where mercury concentrations in fish are likely to exceed regulatory criteria.

  12. Assessing effects of a mining and municipal sewage effluent mixture on fathead minnow (Pimephales promelas) reproduction using a novel, field-based trophic-transfer artificial stream.

    Science.gov (United States)

    Rickwood, Carrie J; Dubé, Monique G; Weber, Lynn P; Lux, Sarah; Janz, David M

    2008-01-31

    The Junction Creek watershed, located in Sudbury, ON, Canada receives effluent from three metal mine wastewater treatment plants, as well as a municipal wastewater (MWW) discharge. Effects on fish have been documented within the creek (decreased egg size and increased metal body burdens). It has been difficult to identify the cause of the effects observed due to the confounded nature of the creek. The objectives of this investigation were to assess the: (1) effects of a mine effluent and municipal wastewater (CCMWW) mixture on fathead minnow (FHM; Pimephales promelas) reproduction in an on-site artificial stream and (2) importance of food (Chironomus tentans) as a source of exposure using a trophic-transfer system. Exposures to CCMWW through the water significantly decreased egg production and spawning events. Exposure through food and water using the trophic-transfer system significantly increased egg production and spawning events. Embryos produced in the trophic-transfer system showed similar hatching success but increased incidence and severity of deformities after CCMWW exposure. We concluded that effects of CCMWW on FHM were more apparent when exposed through the water. Exposure through food and water may have reduced effluent toxicity, possibly due to increased nutrients and organic matter, which may have reduced metal bioavailability. More detailed examination of metal concentrations in the sediment, water column, prey (C. tentans) and FHM tissues is recommended to better understand the toxicokinetics of potential causative compounds within the different aquatic compartments when conducting exposures through different pathways.

  13. Data Mining for Business Intelligence Concepts, Techniques, and Applications in Microsoft Office Excel(r) with XLMiner(r)

    CERN Document Server

    Shmueli, Galit; Bruce, Peter C

    2011-01-01

    Data Mining for Business Intelligence, Second Edition uses real data and actual cases to illustrate the applicability of data mining (DM) intelligence in the development of successful business models. Featuring complimentary access to XLMiner, the Microsoft Office Excel add-in, this book allows readers to follow along and implement algorithms at their own speed, with a minimal learning curve. In addition, students and practitioners of DM techniques are presented with hands-on, business-oriented applications. An abundant amount of exercises and examples, now doubled in number in the second edit

  14. Surface mining

    Science.gov (United States)

    Robert Leopold; Bruce Rowland; Reed Stalder

    1979-01-01

    The surface mining process consists of four phases: (1) exploration; (2) development; (3) production; and (4) reclamation. A variety of surface mining methods has been developed, including strip mining, auger, area strip, open pit, dredging, and hydraulic. Sound planning and design techniques are essential to implement alternatives to meet the myriad of laws,...

  15. Uranium mining

    International Nuclear Information System (INIS)

    Lange, G.

    1975-01-01

    The winning of uranium ore is the first stage of the fuel cycle. The whole complex of questions to be considered when evaluating the profitability of an ore mine is shortly outlined, and the possible mining techniques are described. Some data on uranium mining in the western world are also given. (RB) [de

  16. Low-dimensional and Data Fusion Techniques Applied to a Rectangular Supersonic Multi-stream Jet

    Science.gov (United States)

    Berry, Matthew; Stack, Cory; Magstadt, Andrew; Ali, Mohd; Gaitonde, Datta; Glauser, Mark

    2017-11-01

    Low-dimensional models of experimental and simulation data for a complex supersonic jet were fused to reconstruct time-dependent proper orthogonal decomposition (POD) coefficients. The jet consists of a multi-stream rectangular single expansion ramp nozzle, containing a core stream operating at Mj , 1 = 1.6 , and bypass stream at Mj , 3 = 1.0 with an underlying deck. POD was applied to schlieren and PIV data to acquire the spatial basis functions. These eigenfunctions were projected onto their corresponding time-dependent large eddy simulation (LES) fields to reconstruct the temporal POD coefficients. This reconstruction was able to resolve spectral peaks that were previously aliased due to the slower sampling rates of the experiments. Additionally, dynamic mode decomposition (DMD) was applied to the experimental and LES datasets, and the spatio-temporal characteristics were compared to POD. The authors would like to acknowledge AFOSR, program manager Dr. Doug Smith, for funding this research, Grant No. FA9550-15-1-0435.

  17. Detection of solvent losses (entrainment) in gas streams of process vessels using radioisotope tracing techniques

    International Nuclear Information System (INIS)

    Wan Zakaria Wan Muhamad Tahir; Juhari Mohd Yusof

    2002-01-01

    Liquid droplets (MDEA aqueous solution) entrained in the gas streams can cause severe problems on chemical plants. On-line detection of liquid entrainment (carry over) into gas streams from process vessel is investigated using radioisotope iodine ( 131 I). In order to obtain information on whether there is any carry-over of MDEA in the vapour space leaving from the process system, a number of test and calibration injections involving the released of certain amount of tracer activity (mCi) at the inlet and overhead lines of the process vessels were made using a special injection device. MDEA solvent- tagged tracer in the overhead line of the designated process vessels was monitored using radiation scintillation detectors mounted externally at specified locations of the vessels. Output pulses (response curves) with respect to time of measurements from all detectors were plotted and analysed for the finger prints of solvent losses leaving the vessels. From this study, no distinguishable peaks were detected at the outlet vessels of the overhead lines. Thus, no significant MDEA solvent losses in the form of vapour being discovered along the gas streams due to the process taking place in the system. (Author)

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

    OpenAIRE

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

    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 str...

  19. Comparison between energy dispersive X-ray fluorescence and other nuclear analytical techniques in mineral exploration and mining

    International Nuclear Information System (INIS)

    Clayton, C.G.; Packer, T.W.; Wormald, M.R.

    1979-01-01

    At the present time there is an increasing awareness of the value and need for in-situ analytical methods throughout the general area of mineral exploration and mining. Of the alternative techniques, the measurement of natural gamma radiation is well established for uranium exploration and it is now being developed for sea-bed and lake-bed surveying. Energy dispersive X-ray fluorescence equipment is becoming more generally accepted, especially for mine control. Neutron techniques, for so long used routinely in oil well logging, are now being developed for a wide range of applications in all aspects of exploration and mining. It is believed that these techniques will result in major applications in the future. The present paper compares the principal characteristics of energy dispersive X-ray fluorescence and neutron techniques in particular, with special emphasis being given to those factors which affect the accuracy of analytical content; such as elemental resolution, matrix effects, material heterogeneity and neutron transport. A generalised comparison between the techniques is difficult to achieve because of the different nature of radiation interactions, but a range of applications is described and these show the complementary nature of the methods and point to the areas for more active development in the future. (author)

  20. IBM SPSS modeler essentials effective techniques for building powerful data mining and predictive analytics solutions

    CERN Document Server

    McCormick, Keith; Wei, Bowen

    2017-01-01

    IBM SPSS Modeler allows quick, efficient predictive analytics and insight building from your data, and is a popularly used data mining tool. This book will guide you through the data mining process, and presents relevant statistical methods which are used to build predictive models and conduct other analytic tasks using IBM SPSS Modeler. From ...

  1. In-situ performance evaluation of radon measurement techniques in Uranium mine exhausts of Jaduguda

    International Nuclear Information System (INIS)

    Patnaik, R.L.; Jha, V.N.; Singh, M.K.; Meena, J.S.; Rajesh Kumar; Srivastava, V.S.; Sethy, N.K.; Ravi, P.M.; Tripathi, R.M.

    2014-01-01

    Several techniques are used for the measurement of the activity concentration of radon in the work place and the environment. Devices like Scintillation cell, Alpha guard and Low Level Radon Detection System (LLRDS) are widely used for the estimation of radon. Some of the devices like scintillation cell is normally used in high activity concentration, whereas, device like LLRDS is used in low activity concentration range. All these above devices are used in ambient mode in which air sample is either collected in a cell or in a chamber and the alpha counts are recorded after a definite delay. In some device, air is allowed to be diffused through a filter and alpha activity is estimated using proper detection system. Passive radon dosimeters can effectively be used both in low and high activity concentration range. The cumulative radon exposure can be assessed using passive radon dosimeters. For in situ performance evaluation an area is required where both high and low level activity concentration of radon is anticipated. Uranium mines exhaust area is presumed to be an area where both these conditions can be found by mere variation in the placement of the device. Inter comparison exercise can also be done effectively at this location using various devices of radon estimation

  2. Nuclear techniques to search for buried land mines and hidden materials

    International Nuclear Information System (INIS)

    Cinausero, M.

    2001-01-01

    Full text: In the last few years, the so called land mine crisis has gained the attention of the general public. This crisis is caused not only by the large number of and lines spread over a few countries around the world, but also by the low efficiency, intrinsic danger and high cost of the present humanitarian demining operations. After the Ottawa treaty, there is a general political consensus to spur technological development in providing new tools for humanitarian demining operations, with the goal of decreasing at least by one order of magnitude the actual cost for the neutralization of a single explosive device. In this respect, two different tools are needed: anomaly detectors and bulk explosive sensors. The first device should be able to perform a fast scan of the suspected area marking all target places which exhibit discontinuities in their physical properties with respect to the surrounding soil. The bulk detector is needed to confirm the presence of the explosive in the target places, thus lowering the false alarm rate. The I.N.F.N. has started since 1998 a research program (EXPLODET) aimed at pushing the use of nuclear techniques in sensors designed for humanitarian demining, once the state of the art technical developments have been taken into consideration. In 2001 an U.E. project called DIAMINE has also started in collaboration with various European industries and academic institutions. The results achieved in these years using thermal and fast neutron irradiation methods will be illustrated and discussed in the presentation. Future development which extends the nuclear techniques to other fields such as environmental investigations will be briefly discussed. (Author)

  3. Techniques for estimating flood-depth frequency relations for streams in West Virginia

    Science.gov (United States)

    Wiley, J.B.

    1987-01-01

    Multiple regression analyses are applied to data from 119 U.S. Geological Survey streamflow stations to develop equations that estimate baseline depth (depth of 50% flow duration) and 100-yr flood depth on unregulated streams in West Virginia. Drainage basin characteristics determined from the 100-yr flood depth analysis were used to develop 2-, 10-, 25-, 50-, and 500-yr regional flood depth equations. Two regions with distinct baseline depth equations and three regions with distinct flood depth equations are delineated. Drainage area is the most significant independent variable found in the central and northern areas of the state where mean basin elevation also is significant. The equations are applicable to any unregulated site in West Virginia where values of independent variables are within the range evaluated for the region. Examples of inapplicable sites include those in reaches below dams, within and directly upstream from bridge or culvert constrictions, within encroached reaches, in karst areas, and where streams flow through lakes or swamps. (Author 's abstract)

  4. Comparison of electrofishing techniques to detect larval lampreys in wadeable streams in the Pacific Northwest

    Science.gov (United States)

    Dunham, Jason B.; Chelgren, Nathan D.; Heck, Michael P.; Clark, Steven M.

    2013-01-01

    We evaluated the probability of detecting larval lampreys using different methods of backpack electrofishing in wadeable streams in the U.S. Pacific Northwest. Our primary objective was to compare capture of lampreys using electrofishing with standard settings for salmon and trout to settings specifically adapted for capture of lampreys. Field work consisted of removal sampling by means of backpack electrofishing in 19 sites in streams representing a broad range of conditions in the region. Captures of lampreys at these sites were analyzed with a modified removal-sampling model and Bayesian estimation to measure the relative odds of capture using the lamprey-specific settings compared with the standard salmonid settings. We found that the odds of capture were 2.66 (95% credible interval, 0.87–78.18) times greater for the lamprey-specific settings relative to standard salmonid settings. When estimates of capture probability were applied to estimating the probabilities of detection, we found high (>0.80) detectability when the actual number of lampreys in a site was greater than 10 individuals and effort was at least two passes of electrofishing, regardless of the settings used. Further work is needed to evaluate key assumptions in our approach, including the evaluation of individual-specific capture probabilities and population closure. For now our results suggest comparable results are possible for detection of lampreys by using backpack electrofishing with salmonid- or lamprey-specific settings.

  5. 21 Recipes for Mining Twitter

    CERN Document Server

    Russell, Matthew

    2011-01-01

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

  6. Sentiment Analysis in Geo Social Streams by using Machine Learning Techniques

    OpenAIRE

    Twanabasu, Bikesh

    2018-01-01

    Treball de Final de Màster Universitari Erasmus Mundus en Tecnologia Geoespacial (Pla de 2013). Codi: SIW013. Curs acadèmic 2017-2018 Massive amounts of sentiment rich data are generated on social media in the form of Tweets, status updates, blog post, reviews, etc. Different people and organizations are using these user generated content for decision making. Symbolic techniques or Knowledge base approaches and Machine learning techniques are two main techniques used for analysis sentiment...

  7. A Bayesian Scoring Technique for Mining Predictive and Non-Spurious Rules

    OpenAIRE

    Batal, Iyad; Cooper, Gregory; Hauskrecht, Milos

    2012-01-01

    Rule mining is an important class of data mining methods for discovering interesting patterns in data. The success of a rule mining method heavily depends on the evaluation function that is used to assess the quality of the rules. In this work, we propose a new rule evaluation score - the Predictive and Non-Spurious Rules (PNSR) score. This score relies on Bayesian inference to evaluate the quality of the rules and considers the structure of the rules to filter out spurious rules. We present ...

  8. Influence of the old mining loads on the contamination of streams, flows in the Water-work Reservoir “Ružín I” in 2004 year by the selected elements

    Directory of Open Access Journals (Sweden)

    Tomislav Špaldon

    2005-11-01

    Full Text Available This article presents results of the research concentrated on the content of selected elements, mostly heavy metals, in samples of stream waters and stream deposits from selected profiles of streams in the drainage basins of the Hnilec and Hornád river, which flow in the water-work Reservoir “Ružín I”. The sampling was carried out from the winter to the summer months, 2004. The major part of the drainage basins of these two rivers is located in the territory of the central Spiš, which is well-known from the historic times until these days by its intensive mining, mineral processing and metallurgical activities. The wastes generated by such activities are sources of metals, which penetrate into the surface waters and consequently into the stream deposits. From the point of view of the transfer and the transformation of these metal elements, their monitoring deserves a continuous attention

  9. Machine Learning Techniques for Characterizing IEEE 802.11b Encrypted Data Streams

    National Research Council Canada - National Science Library

    Henson, Michael

    2004-01-01

    .... Even though there have been major advancements in encryption technology, security protocols and packet header obfuscation techniques, other distinguishing characteristics do exist in wireless network traffic...

  10. Mine Water Treatment in Hongai Coal Mines

    Science.gov (United States)

    Dang, Phuong Thao; Dang, Vu Chi

    2018-03-01

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

  11. Mine Water Treatment in Hongai Coal Mines

    Directory of Open Access Journals (Sweden)

    Dang Phuong Thao

    2018-01-01

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

  12. Preliminary state-of-the-art survey: mining techniques for salt and other rock types

    Energy Technology Data Exchange (ETDEWEB)

    1976-12-01

    This is a systematic review of the state-of-the-art of underground mining and excavation technology in the U.S. as applied to salt, limestone, shale, and granite. Chapter 2 covers the basic characteristics of these rock types, the most frequently used underground mining methods, shaft and slope entry construction, equipment, and safety and productivity data. Chapters 3 and 4 summarize underground salt and limestone mining in the U.S. Chapter 5 shows that large amounts of thick shale exist in the U.S., but little is mined. Chapter 6 discusses underground excavations into granite-type rocks. Suggestions are given in the last chapter for further study. (DLC)

  13. Reliable practical technique for in-situ rock stress measurements in deep gold mines.

    CSIR Research Space (South Africa)

    Stacey, TR

    1998-03-01

    Full Text Available The proposed primary output of this research project is the development of a set of equipment and method of in situ stress measurements in a high stress environment typical of the deep level gold mines....

  14. ENVIRONMENTAL IMPACT ASSESSMENT OF LAND USE PLANING AROUND THE LEASED LIMESTONE MINE USING REMOTE SENSING TECHNIQUES

    Directory of Open Access Journals (Sweden)

    P. Ranade

    2007-01-01

    Full Text Available Mining activities and the waste products produced can have significant impact on the surrounding environment - ranging from localized surface and ground water contamination to the damaging effects of airborne pollutants on the regional ecosystem. The long term monitoring of environmental impacts requires a cost effective method to characterize land cover and land cover changes over time. As per the guidelines of Ministry of Environment and Forest, Govt. of India, it is mandatory to study and analyze the impacts of mining on its surroundings. The use of remote sensing technology to generate reliable land cover maps is a valuable asset to completing environmental assessments over mining affected areas. In this paper, a case study has been discussed to study the land use – land cover status around 10 Km radius of open cast limestone mine area and the subsequent impacts on environmental as well as social surroundings.

  15. The stream flow rate measurement using tracer techniques at the Kemubu Agricultural Development Authority (KADA), Kelantan

    International Nuclear Information System (INIS)

    Daud Mohammad; Abd Razak Hamzah; Wan Abd Aziz Wan Mohamad; Juhari Yusoff; Wan Zakaria Wan Mohd Tahir

    1985-01-01

    Measuring the flow rate of a water course is one of the basic operations in hydrology, being of general relevance to water problems and of particular importance in the planning of water control schemes. The techniques commonly used in streamflow gauging are either by a current meter of tracer dilution method. This paper describes the latter technique in which radioisotope Tc-99m was used as a tracer in streamflow measurements performed in 1983 in a few selected irrigation canals and pump house under the Kemubu Agriculture Development Authority (KADA), Kelantan. Total count technique and peak-to-peak method were adopted in this study. (author)

  16. Psychovisual masks and intelligent streaming RTP techniques for the MPEG-4 standard

    Science.gov (United States)

    Mecocci, Alessandro; Falconi, Francesco

    2003-06-01

    In today multimedia audio-video communication systems, data compression plays a fundamental role by reducing the bandwidth waste and the costs of the infrastructures and equipments. Among the different compression standards, the MPEG-4 is becoming more and more accepted and widespread. Even if one of the fundamental aspects of this standard is the possibility of separately coding video objects (i.e. to separate moving objects from the background and adapt the coding strategy to the video content), currently implemented codecs work only at the full-frame level. In this way, many advantages of the flexible MPEG-4 syntax are missed. This lack is due both to the difficulties in properly segmenting moving objects in real scenes (featuring an arbitrary motion of the objects and of the acquisition sensor), and to the current use of these codecs, that are mainly oriented towards the market of DVD backups (a full-frame approach is enough for these applications). In this paper we propose a codec for MPEG-4 real-time object streaming, that codes separately the moving objects and the scene background. The proposed codec is capable of adapting its strategy during the transmission, by analysing the video currently transmitted and setting the coder parameters and modalities accordingly. For example, the background can be transmitted as a whole or by dividing it into "slightly-detailed" and "highly detailed" zones that are coded in different ways to reduce the bit-rate while preserving the perceived quality. The coder can automatically switch in real-time, from one modality to the other during the transmission, depending on the current video content. Psychovisual masks and other video-content based measurements have been used as inputs for a Self Learning Intelligent Controller (SLIC) that changes the parameters and the transmission modalities. The current implementation is based on the ISO 14496 standard code that allows Video Objects (VO) transmission (other Open Source Codes

  17. Applying Value Stream Mapping Technique for Production Improvement in a Manufacturing Company: A Case Study

    Science.gov (United States)

    Jeyaraj, K. L.; Muralidharan, C.; Mahalingam, R.; Deshmukh, S. G.

    2013-01-01

    The purpose of this paper is to explain how value stream mapping (VSM) is helpful in lean implementation and to develop the road map to tackle improvement areas to bridge the gap between the existing state and the proposed state of a manufacturing firm. Through this case study, the existing stage of manufacturing is mapped with the help of VSM process symbols and the biggest improvement areas like excessive TAKT time, production, and lead time are identified. Some modifications in current state map are suggested and with these modifications future state map is prepared. Further TAKT time is calculated to set the pace of production processes. This paper compares the current state and future state of a manufacturing firm and witnessed 20 % reduction in TAKT time, 22.5 % reduction in processing time, 4.8 % reduction in lead time, 20 % improvement in production, 9 % improvement in machine utilization, 7 % improvement in man power utilization, objective improvement in workers skill level, and no change in the product and semi finished product inventory level. The findings are limited due to the focused nature of the case study. This case study shows that VSM is a powerful tool for lean implementation and allows the industry to understand and continuously improve towards lean manufacturing.

  18. Soil decontamination at the Montevecchio-Levante mine site with experimental washing and leaching techniques

    Energy Technology Data Exchange (ETDEWEB)

    Dessi, R. [Progemisa SpA, Cagliari (Italy); Fadda, S.; Peretti, R.; Zucca, A. [CSGM, Centro Studi Germinerari e Mineralurgici del CNR, Cagliari (Italy); Serci, A. [Digita, Dipt. di Geoingegneria e Tecnologie Ambientali, Cagliari (Italy)

    2000-12-01

    The soils in the neighbourhood of the Rio Montevecchio-Sitzerri, a stream that flows in the valley below the tailings pond of the Montevecchio-Levante mineral processing plant (SW Sardinia, Italy) are severely contaminated by heavy metals, to the extent that traditional land uses are compromised. Consequently urgent measures are needed both to abate the pollution at source and rehabilitate the contaminated land. This paper is concerned with the problem of soil decontamination using washing and leaching techniques. Laboratory experiments have been conducted in mechanically agitated reactors, using citric acid and acetic acid solutions and brine of hydrochloric acid and calcium chloride. The influence of both reagent concentration and solid-to-liquid ratio has been assessed, and in the most significant cases, the attack kinetics has been determined. The tests showed the brine to be the most effective for removing metals from the soils. Based on the findings of the investigations, the possibility of decontamination by heap leaching has been simulated in the laboratory using the column technique. [Italian] I suoi circostanti il Rio Montevecchio-Sitzerri, che scorre a valle del bacino di decantazione degli sterili dell'impianto di trattamento dei minerali di Montevecchio-Levante (Sardegna Centro-Occidentale), sono caratterizzati da un elevato contenuto di metalli pesanti, che ne pregiudicano gli usi tradizionali. Si rende percio' improrogabile sia la necessita' di intervenire sulle cause all'origine della contaminazione, sia di bonificare i suoli in questione al fine di recuperarli a nuovi usi. La memoria intende portare un contributo alle relative problematiche affrontando la possibilita' di decontaminazione mediante tecniche di lavaggio e lisciviazione. La sperimentazione di laboratorio e' stata condotta in reattori ad agitazione meccanica, utilizzando soluzioni con acido citrico, acido acetico ed una salamoia costituita da acido

  19. Annual Report on Scientific Activities in 1997 of Department of Physics and Nuclear Techniques, Academy of Mining and Metallurgy, Cracow

    International Nuclear Information System (INIS)

    Wolny, J.; Olszynska, E.

    1998-01-01

    The Annual Report 1997 is the review of scientific activities of the Department of Nuclear Physics and Techniques (DNPT) of the Academy of Mining and Metallurgy, Cracow. The studies connected with: radiometric analysis, nuclear electronics, solid state physics, elementary particle and detectors, medical physics, physics of environment, theoretical physics, nuclear geophysics, energetic problems, industrial radiometry and tracer techniques have been broadly presented. The fill list of works being published and presented at scientific conferences in 1997 by the staff of DNPT are also included

  20. Applying value stream mapping techniques to eliminate non-value-added waste for the procurement of endovascular stents

    International Nuclear Information System (INIS)

    Teichgräber, Ulf K.; Bucourt, Maximilian de

    2012-01-01

    Objectives: To eliminate non-value-adding (NVA) waste for the procurement of endovascular stents in interventional radiology services by applying value stream mapping (VSM). Materials and methods: The Lean manufacturing technique was used to analyze the process of material and information flow currently required to direct endovascular stents from external suppliers to patients. Based on a decision point analysis for the procurement of stents in the hospital, a present state VSM was drawn. After assessment of the current status VSM and progressive elimination of unnecessary NVA waste, a future state VSM was drawn. Results: The current state VSM demonstrated that out of 13 processes for the procurement of stents only 2 processes were value-adding. Out of the NVA processes 5 processes were unnecessary NVA activities, which could be eliminated. The decision point analysis demonstrated that the procurement of stents was mainly a forecast driven push system. The future state VSM applies a pull inventory control system to trigger the movement of a unit after withdrawal by using a consignment stock. Conclusion: VSM is a visualization tool for the supply chain and value stream, based on the Toyota Production System and greatly assists in successfully implementing a Lean system.

  1. Applying value stream mapping techniques to eliminate non-value-added waste for the procurement of endovascular stents.

    Science.gov (United States)

    Teichgräber, Ulf K; de Bucourt, Maximilian

    2012-01-01

    OJECTIVES: To eliminate non-value-adding (NVA) waste for the procurement of endovascular stents in interventional radiology services by applying value stream mapping (VSM). The Lean manufacturing technique was used to analyze the process of material and information flow currently required to direct endovascular stents from external suppliers to patients. Based on a decision point analysis for the procurement of stents in the hospital, a present state VSM was drawn. After assessment of the current status VSM and progressive elimination of unnecessary NVA waste, a future state VSM was drawn. The current state VSM demonstrated that out of 13 processes for the procurement of stents only 2 processes were value-adding. Out of the NVA processes 5 processes were unnecessary NVA activities, which could be eliminated. The decision point analysis demonstrated that the procurement of stents was mainly a forecast driven push system. The future state VSM applies a pull inventory control system to trigger the movement of a unit after withdrawal by using a consignment stock. VSM is a visualization tool for the supply chain and value stream, based on the Toyota Production System and greatly assists in successfully implementing a Lean system. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

  2. Use of Data Mining Techniques to Detect Medical Fraud in Health Insurance

    Directory of Open Access Journals (Sweden)

    Kuo-Chung Lin

    2012-04-01

    Full Text Available The health insurance claims application case the inspection usually relies on experts’ experience for verification and experienced personnel in charge for checking. However, due to the heavy work load and the insufficiency of manpower and experience, the ratio of miscarriages of justice is high, leading to improper settlement of claims and the waste of social resources. This paper takes advantage of data-mining technology to design models and find out cases requiring for manual inspection so as to save time and manpower. Six models are designed in this paper. By the analysis of the 20/80 principle and the coverage and accuracy ratio, a great number of periodic data (over 2 million records are fed back to the data-mining models after repetitive verification. Also, it is discovered that to integrate the data-mining technology and feed back to different business stages so as to establish early warning system will be an important topic for the health insurance system in hospital’s EMR in the future. Meanwhile, as the information acquired by data-mining needs to be stored and the traditional database technology has limitations. Next time, this paper explores the ontology framework to be set up by semantic network technology in the future in order to assist the storage of knowledge gained by data-mining.

  3. The Stream-Catchment (StreamCat) and Lake-Catchment ...

    Science.gov (United States)

    Background/Question/MethodsLake and stream conditions respond to both natural and human-related landscape features. Characterizing these features within contributing areas (i.e., delineated watersheds) of streams and lakes could improve our understanding of how biological conditions vary spatially and improve the use, management, and restoration of these aquatic resources. However, the specialized geospatial techniques required to define and characterize stream and lake watersheds has limited their widespread use in both scientific and management efforts at large spatial scales. We developed the StreamCat and LakeCat Datasets to model, predict, and map the probable biological conditions of streams and lakes across the conterminous US (CONUS). Both StreamCat and LakeCat contain watershed-level characterizations of several hundred natural (e.g., soils, geology, climate, and land cover) and anthropogenic (e.g., urbanization, agriculture, mining, and forest management) landscape features for ca. 2.6 million stream segments and 376,000 lakes across the CONUS, respectively. These datasets can be paired with field samples to provide independent variables for modeling and other analyses. We paired 1,380 stream and 1,073 lake samples from the USEPAs National Aquatic Resource Surveys with StreamCat and LakeCat and used random forest (RF) to model and then map an invertebrate condition index and chlorophyll a concentration, respectively. Results/ConclusionsThe invertebrate

  4. A Bayesian Scoring Technique for Mining Predictive and Non-Spurious Rules.

    Science.gov (United States)

    Batal, Iyad; Cooper, Gregory; Hauskrecht, Milos

    Rule mining is an important class of data mining methods for discovering interesting patterns in data. The success of a rule mining method heavily depends on the evaluation function that is used to assess the quality of the rules. In this work, we propose a new rule evaluation score - the Predictive and Non-Spurious Rules (PNSR) score. This score relies on Bayesian inference to evaluate the quality of the rules and considers the structure of the rules to filter out spurious rules. We present an efficient algorithm for finding rules with high PNSR scores. The experiments demonstrate that our method is able to cover and explain the data with a much smaller rule set than existing methods.

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

    Science.gov (United States)

    Uswatun Khasanah, Annisa; Harwati

    2017-06-01

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

  6. An injection technique for in-situ remediation of abandoned underground coal mines

    International Nuclear Information System (INIS)

    Canty, G.A.; Everett, J.W.

    1998-01-01

    Remediation of underground mines can prove to be a difficult task, given the physical constraints associated with introducing amendments to a subterranean environment. An acid mine abatement project involving in-situ chemical treatment method was conducted by the University of Oklahoma. The treatment method involved the injection of an alkaline coal combustion by-product (CCB) slurry into a flooded mine void (pH 4.4) to create a buffered zone. Injection of the CCB slurry was possible through the use of equipment developed by the petroleum industry for grouting recovery wells. This technology was selected because the CCB slurry could be injected under significant pressure and at a high rate. With higher pressure and rates of injection, a large quantity of slurry can be introduced into the mine within a limited amount of time. Theoretically, the high pressure and rate would improve dispersal of the slurry within the void. In addition, the high pressure is advantageous in fracturing or breaking-down obstructions to injection. During the injection process, a total of 418 tons of CCB was introduced within 15 hours. The mine did not refuse any of the material, and it is likely that a much larger mass could have been added. One injection well was drilled into a pillar of coal. Normally this would pose a problem when introducing a slurry; however, the coal pillar was easily fractured during the injection process. Currently, the pH of the mine discharge is above 6.5 and the alkalinity is approximately 100 mg/L as CACO 3

  7. Using text mining techniques to extract phenotypic information from the PhenoCHF corpus.

    Science.gov (United States)

    Alnazzawi, Noha; Thompson, Paul; Batista-Navarro, Riza; Ananiadou, Sophia

    2015-01-01

    Phenotypic information locked away in unstructured narrative text presents significant barriers to information accessibility, both for clinical practitioners and for computerised applications used for clinical research purposes. Text mining (TM) techniques have previously been applied successfully to extract different types of information from text in the biomedical domain. They have the potential to be extended to allow the extraction of information relating to phenotypes from free text. To stimulate the development of TM systems that are able to extract phenotypic information from text, we have created a new corpus (PhenoCHF) that is annotated by domain experts with several types of phenotypic information relating to congestive heart failure. To ensure that systems developed using the corpus are robust to multiple text types, it integrates text from heterogeneous sources, i.e., electronic health records (EHRs) and scientific articles from the literature. We have developed several different phenotype extraction methods to demonstrate the utility of the corpus, and tested these methods on a further corpus, i.e., ShARe/CLEF 2013. Evaluation of our automated methods showed that PhenoCHF can facilitate the training of reliable phenotype extraction systems, which are robust to variations in text type. These results have been reinforced by evaluating our trained systems on the ShARe/CLEF corpus, which contains clinical records of various types. Like other studies within the biomedical domain, we found that solutions based on conditional random fields produced the best results, when coupled with a rich feature set. PhenoCHF is the first annotated corpus aimed at encoding detailed phenotypic information. The unique heterogeneous composition of the corpus has been shown to be advantageous in the training of systems that can accurately extract phenotypic information from a range of different text types. Although the scope of our annotation is currently limited to a single

  8. Applying aerial digital photography as a spectral remote sensing technique for macrophytic cover assessment in small rural streams

    Science.gov (United States)

    Anker, Y.; Hershkovitz, Y.; Gasith, A.; Ben-Dor, E.

    2011-12-01

    Although remote sensing of fluvial ecosystems is well developed, the tradeoff between spectral and spatial resolutions prevents its application in small streams (habitat scales classifications, acquisition of aerial digital RGB datasets. B. For section scale classification, hyperspectral (HSR) dataset acquisition. C. For calibration, HSR reflectance measurements of specific ground targets, in close proximity to each dataset acquisition swath. D. For habitat scale classification, manual, in-stream flora grid transects classification. The digital RGB datasets were converted to reflectance units by spectral calibration against colored reference plates. These red, green, blue, white, and black EVA foam reference plates were measured by an ASD field spectrometer and each was given a spectral value. Each spectral value was later applied to the spectral calibration and radiometric correction of spectral RGB (SRGB) cube. Spectral calibration of the HSR dataset was done using the empirical line method, based on reference values of progressive grey scale targets. Differentiation between the vegetation species was done by supervised classification both for the HSR and for the SRGB datasets. This procedure was done using the Spectral Angle Mapper function with the spectral pattern of each vegetation species as a spectral end member. Comparison between the two remote sensing techniques and between the SRGB classification and the in-situ transects indicates that: A. Stream vegetation classification resolution is about 4 cm by the SRGB method compared to about 1 m by HSR. Moreover, this resolution is also higher than of the manual grid transect classification. B. The SRGB method is by far the most cost-efficient. The combination of spectral information (rather than the cognitive color) and high spatial resolution of aerial photography provides noise filtration and better sub-water detection capabilities than the HSR technique. C. Only the SRGB method applies for habitat and

  9. Using Data-Driven and Process Mining Techniques for Identifying and Characterizing Problem Gamblers in New Zealand

    Directory of Open Access Journals (Sweden)

    Suriadi Suriadi

    2016-12-01

    Full Text Available This article uses data-driven techniques combined with established theory in order to analyse gambling behavioural patterns of 91 thousand individuals on a real-world fixed-odds gambling dataset in New Zealand. This research uniquely integrates a mixture of process mining, data mining and confirmatory statistical techniques in order to categorise different sub-groups of gamblers, with the explicit motivation of identifying problem gambling behaviours and reporting on the challenges and lessons learned from our case study.We demonstrate how techniques from various disciplines can be combined in order to gain insight into the behavioural patterns exhibited by different types of gamblers, as well as provide assurances of the correctness of our approach and findings. A highlight of this case study is both the methodology which demonstrates how such a combination of techniques provides a rich set of effective tools to undertake an exploratory and open-ended data analysis project that is guided by the process cube concept, as well as the findings themselves which indicate that the contribution that problem gamblers make to the total volume, expenditure, and revenue is higher than previous studies have maintained.

  10. Use of the freshwater mussel, Velesunio angasi, in the monitoring and assessment of mining impact in top and streams

    International Nuclear Information System (INIS)

    Humphrey, C.L.; Martin, P.; LeGras, C.

    2002-01-01

    A number of features of freshwater mussels make them well suited as indicators of past environments and present-day environmental health. Radium and thorium isotope loads, and activity ratios such as Ra-228/Ra-226 and Th-228/Ra-228, are strongly age-dependent (ARRRI, 1985, 1987a). Determination of this dependency for a site can give information on pollution events even several years later. For this type of investigation, radioisotope activity ratios are more sensitive and reliable indicators than concentrations or loads of individual radionuclides. An example of the archival potential of the Ra-228/Ra-226 ratio in mussels for demonstrating downstream effects in Magela Creek of hypothetical releases of process water from the Ranger uranium mine is shown. The Ra-228/Ra-226 activity ratio decreases with age due to the disproportionate decay of the two isotopes: 6 year half-life for Ra-228 vs 1600 year half-life for Ra- 226. Hence, the ratio is lower in older mussels as the Ra-228 activity incorporated early in life has partially decayed. If there had been an event several years ago, this would be observed in the age-dependence of the ratio. Uranium provides an unusual example of metal absorption and bioaccumulation. The overall evidence suggests that, although U has a short half-life in mussel protoplasm, the transport mechanism to extracellular granules is impeded in a way that does not occur with many other divalent ions. This may be because U 2 2+ is mainly only nominally divalent at physiological and most naturally-occurring pH values. The transport of metals from an intracellular environment to an extracellular phosphate granule probably involves a decomplexation step. For most divalent metals, extracellular pH is unlikely to be sufficiently high to cause significant hydrolysis. For U, however, extensive hydrolysis occurs at pH > 4 (Moulin et al., 1995), lowering the effective charge on the U species, and restricting its incorporation (as an unhydrolysed UO 2 2

  11. Identifying Engineering Students' English Sentence Reading Comprehension Errors: Applying a Data Mining Technique

    Science.gov (United States)

    Tsai, Yea-Ru; Ouyang, Chen-Sen; Chang, Yukon

    2016-01-01

    The purpose of this study is to propose a diagnostic approach to identify engineering students' English reading comprehension errors. Student data were collected during the process of reading texts of English for science and technology on a web-based cumulative sentence analysis system. For the analysis, the association-rule, data mining technique…

  12. Study of the effect of environmental impact on land mine detection using nuclear techniques

    International Nuclear Information System (INIS)

    Aziz, M.; Massoud, E.

    2005-01-01

    Parameters that affect the accuracy of landmine detection using nuclear methods were analyzed. The influence of the soil type and water content on the detection processes were studied by calculating the backscattered neutron and gamma - rays at the detector. The difference at the detector between mines and several organic objects were calculated and analyzed

  13. Analysis of Nature of Science Included in Recent Popular Writing Using Text Mining Techniques

    Science.gov (United States)

    Jiang, Feng; McComas, William F.

    2014-01-01

    This study examined the inclusion of nature of science (NOS) in popular science writing to determine whether it could serve supplementary resource for teaching NOS and to evaluate the accuracy of text mining and classification as a viable research tool in science education research. Four groups of documents published from 2001 to 2010 were…

  14. Technique of complex slime water treatment of coal-mining branch

    OpenAIRE

    Solodov, G. А.; Zhbyr, Е. V.; Papin, А. V.; Nevedrov, А. V.

    2007-01-01

    The possibility of complex slime water treatment at coal-mining and coal-treating plants producing marketable products: power-generating concentrate, coal-water fuel, magnetic fraction, industrial water is shown. A basic process flowsheet of slime water treatment presenting a united technological complex is suggested.

  15. Placing Music Artists and Songs in Time Using Editorial Metadata and Web Mining Techniques

    NARCIS (Netherlands)

    Bountouridis, D.; Veltkamp, R.C.; Balen, J.M.H. van

    2013-01-01

    This paper investigates the novel task of situating music artists and songs in time, thereby adding contextual information that typically correlates with an artist’s similarities, collaborations and influences. The proposed method makes use of editorial metadata in conjunction with web mining

  16. Issues in the analyze of low content gold mining samples by fire assay technique

    Science.gov (United States)

    Cetean, Valentina

    2016-04-01

    during oxidation stage. The better metal recovery and the decreasing of the amount of errors for low gold content samples are controlled in this case by: - the management of the quantity of one or more components of the flux, depending on the chemical composition of the sample (sometimes just by observing the behavior and the visual characteristics of lead Au + Ag button/bead and the resulted slag); - addition of gold-free silver, which will be removed by chemical reduction with aqua regia after the fire assay stage. Regarding the instrumental analyze stage of the samples with less than 100 ppb gold content, there were obtained similar values by both techniques: atomic absorption and inductively coupled mass spectrometry, taking into account each of them has different detection limit. It is mandatory the quality control with a certified reference material with known content, both in the fire assay stage and the reading instrumental stage. This abstract are written in the frame of the SUSMIN project: "Tools for sustainable gold mining in EU".

  17. Validation of an Improved Computer-Assisted Technique for Mining Free-Text Electronic Medical Records.

    Science.gov (United States)

    Duz, Marco; Marshall, John F; Parkin, Tim

    2017-06-29

    The use of electronic medical records (EMRs) offers opportunity for clinical epidemiological research. With large EMR databases, automated analysis processes are necessary but require thorough validation before they can be routinely used. The aim of this study was to validate a computer-assisted technique using commercially available content analysis software (SimStat-WordStat v.6 (SS/WS), Provalis Research) for mining free-text EMRs. The dataset used for the validation process included life-long EMRs from 335 patients (17,563 rows of data), selected at random from a larger dataset (141,543 patients, ~2.6 million rows of data) and obtained from 10 equine veterinary practices in the United Kingdom. The ability of the computer-assisted technique to detect rows of data (cases) of colic, renal failure, right dorsal colitis, and non-steroidal anti-inflammatory drug (NSAID) use in the population was compared with manual classification. The first step of the computer-assisted analysis process was the definition of inclusion dictionaries to identify cases, including terms identifying a condition of interest. Words in inclusion dictionaries were selected from the list of all words in the dataset obtained in SS/WS. The second step consisted of defining an exclusion dictionary, including combinations of words to remove cases erroneously classified by the inclusion dictionary alone. The third step was the definition of a reinclusion dictionary to reinclude cases that had been erroneously classified by the exclusion dictionary. Finally, cases obtained by the exclusion dictionary were removed from cases obtained by the inclusion dictionary, and cases from the reinclusion dictionary were subsequently reincluded using Rv3.0.2 (R Foundation for Statistical Computing, Vienna, Austria). Manual analysis was performed as a separate process by a single experienced clinician reading through the dataset once and classifying each row of data based on the interpretation of the free

  18. STEEP STREAMS - Solid Transport Evaluation and Efficiency in Prevention: Sustainable Techniques of Rational Engineering and Advanced MethodS

    Science.gov (United States)

    Armanini, Aronne; Cardoso, Antonio H.; Di Baldassarre, Giuliano; Bellin, Alberto; Breinl, Korbinian; Canelas, Ricardo B.; Larcher, Michele; Majone, Bruno; Matos, Jorges; Meninno, Sabrina; Nucci, Elena; Rigon, Riccardo; Rosatti, Giorgio; Zardi, Dino

    2017-04-01

    The STEEP STREAMS (Solid Transport Evaluation and Efficiency in Prevention: Sustainable Techniques of Rational Engineering and Advanced MethodS) project consists of a collaboration among the Universities of Trento, Uppsala and Lisbon, who joined in a consortium within the ERANET Water JPI call WaterWorks2014. The aim of the project is to produce new rational criteria for the design of protection works against debris flows, a phenomenon consisting in hyper-concentrated flows of water and sediments, classified as catastrophic events typical of small mountainous basins (area triggered by intense rainstorms. Such events are non-stationary phenomena that arise in a very short time, and their recurrence is rather difficult to determine. Compared to flash floods, they are more difficult to anticipate, mostly since they are triggered by convective precipitation events, posing a higher risk of damage and even loss of human lives. These extreme events occur almost annually across Europe, though the formal return period in an exposed site is much larger. Recently, an increase in intensity and frequency of small-scale storm events, leading to extreme solid transport in steep channels, are recognized as one of the effects of climate change. In this context, one of the key challenges of this project is the use of comparatively coarse RCM projections to the small catchments examined in STEEP STREAMS. Given these changes, conventional protection works and their design criteria may not suffice to provide adequate levels of protection to human life and urban settlements. These structures create a storage area upstream the alluvial fans and the settlements, thereby reducing the need of channelization in areas often constrained by urban regulations. To optimize the lamination, and in particular to reduce the peak of solid mass flux, it is necessary that the deposition basin is controlled by a slit check dam, capable of inducing a controlled sedimentation of the solid mas flux. In

  19. The use of Data Mining techniques to Automated Detection of Beneficiaries With Indicative of Diabetes Mellitus 2

    Directory of Open Access Journals (Sweden)

    Deborah Ribeiro Carvalho

    2015-09-01

    Full Text Available Introduction: The Health Industry companies store a vast amount of data in order to support administrative tasks like payment of medical bills, but filling out epidemiological data (International Classification of Diseases - ICD is not mandatory. This makes it difficult to identify the persons’ illness using standard data extraction techniques as well as implementing preventive programs. Objective: This paper proposes a data mining model that identifies automatically the patients with chronic illnesses. Method: The proposed method is comprised of the following steps: initial identification of the variables and their analysis; variable selection; data mining and rule validation by experts. An experiment, for identifying the patients with propensity for diabetes type 2, was designed to validate the methodology. Results: For the data mining process, 12 variables were selected, targeting 43.375 patients: 843 rules were discovered, with a 88,9% success rate. Conclusion: From the 843 rules, six were selected to be evaluated by four experts: they considered the model efficient, with an 89.6% rate of positive results.

  20. Optimization of mining design of Hongwei uranium mine

    International Nuclear Information System (INIS)

    Wu Sanmao; Yuan Baixiang

    2012-01-01

    Combined with the mining conditions of Hongwei uranium mine, optimization schemes for hoisting cage, mine drainge,ore transport, mine wastewater treatment, power-supply system,etc are put forward in the mining design of the mine. Optimized effects are analyzed from the aspects of technique, economy, and energy saving and reducing emissions. (authors)

  1. Application Of Data Mining Techniques For Student Success And Failure Prediction The Case Of DebreMarkos University

    Directory of Open Access Journals (Sweden)

    Muluken Alemu Yehuala

    2015-04-01

    Full Text Available Abstract This research work has investigated the potential applicability of data mining technology to predict student success and failure cases on University students datasets. CRISP-DM Cross Industry Standard Process for Data mining is a data mining methodology to be used by the research. Classification and prediction data mining functionalities are used to extract hidden patterns from students data. These patterns can be seen in relation to different variables in the students records. The classification rule generation process is based on the decision tree and Bayes as a classification technique and the generated rules were studied and evaluated. Data collected from MSEXCEL files and it has been preprocessed for model building. Models were built and tested by using a sample dataset of 11873 regular undergraduate students. Analysis is done by using WEKA 3.7 application software. The research results offer a helpful and constructive recommendations to the academic planners in universities of learning to enhance their decision making process. This will also aid in the curriculum structure and modification in order to improve students academic performance. Students able to decide about their field of study before they are enrolled in specific field of study based on the previous experience taken from the research-findings. The research findings indicated that EHEECE Ethiopian Higher Education Entrance Certificate Examination result Sex Number of students in a class number of courses given in a semester and field of study are the major factors affecting the student performances. So on the bases of the research findings the level of student success will increase and it is possible to prevent educational institutions from serious financial strains.

  2. Use of rope guides in uranium mining and their innovations in techniques

    International Nuclear Information System (INIS)

    Hu Erlian.

    1984-01-01

    Thanks to some innovations and effective measures, the rope guides have been successfully used in multi-level operation in some uranium mines since the year of 1968. These innovations and measures are as follows: (1) by the use of the intermediate fixing grips of guide ropes, etc., to increase the rigidity of the guides and restrain swaying of the hoisting conveyance. (2) by the use of modified screw tensioning device to replace the weight tensioning one to cut down operation cost apparently. (3) By the use of mobile platform in the form of arc plate, or the shiftable guides as the cage stabilizer for intermediate levels to firm the cage horizontally and prevent it from vertical tilting owing to impulsive force from the motion of mine cars, etc. (Author)

  3. Image restoration techniques using Compton backscatter imaging for the detection of buried land mines

    Science.gov (United States)

    Wehlburg, Joseph C.; Keshavmurthy, Shyam P.; Watanabe, Yoichi; Dugan, Edward T.; Jacobs, Alan M.

    1995-06-01

    Earlier landmine imaging systems used two collimated detectors to image objects. These systems had difficulty in distinguishing between surface features and buried features. Using a combination of collimated and uncollimated detectors in a Compton backscatter imaging (CBI) system, allows the identification of surface and buried features. Images created from the collimated detectors contain information about the surface and the buried features, while the uncollimated detectors respond (approximately 80%) to features on the surface. The analysis of surface features are performed first, then these features can be removed and the buried features can be identified. Separation of the surface and buried features permits the use of a globbing algorithm to define regions of interest that can then be quantified [area, Y dimension, X dimension, and center location (xo, yo)]. Mine composition analysis is also possible because of the properties of the four detector system. Distinguishing between a pothole and a mine, that was previously very difficult, can now be easily accomplished.

  4. The StreamCat Dataset: Accumulated Attributes for NHDPlusV2 (Version 2.1) Catchments Riparian Buffer for the Conterminous United States: Mine Density Active Mines and Mineral Plants in the US

    Data.gov (United States)

    U.S. Environmental Protection Agency — This dataset represents the mine density within individual, local NHDPlusV2 catchments and upstream, contributing watersheds riparian buffers based on mine plants...

  5. The StreamCat Dataset: Accumulated Attributes for NHDPlusV2 (Version 2.1) Catchments for the Conterminous United States: Mine Density Active Mines and Mineral Plants in the US

    Data.gov (United States)

    U.S. Environmental Protection Agency — This dataset represents the mine density within individual, local NHDPlusV2 catchments and upstream, contributing watersheds based on mine plants and operations...

  6. Using data mining techniques for diagnosis and prognosis of cancer disease

    OpenAIRE

    Kharya, Shweta

    2012-01-01

    Breast cancer is one of the leading cancers for women in developed countries including India. It is the second most common cause of cancer death in women. The high incidence of breast cancer in women has increased significantly in the last years. In this paper we have discussed various data mining approaches that have been utilized for breast cancer diagnosis and prognosis. Breast Cancer Diagnosis is distinguishing of benign from malignant breast lumps and Breast Cancer Prognosis predicts whe...

  7. A study on gold detection in Wenyu gold mine with XRF techniques

    International Nuclear Information System (INIS)

    Liu Liuchun

    1988-01-01

    A portable X ray fluorescence analyzer was used for detecting fluorcescent X rays from the elements associated with gold ores. Fe, As and Ni were chosen to be the indicator elements to analyse rock samples in Wenyu gold mine. Optimum indicators were determined, and it had proved to be successful to detect gold indirectly by measuring the yields of characteristic X rays of the elements. The method provided also valuable information on geology mapping and deposits forming environment

  8. Looking for the perfect tweet. The use of data mining techniques to find influencers on twitter

    OpenAIRE

    Lahuerta Otero, Eva; Cordero Gutiérrez, Rebeca

    2017-01-01

    The purpose of this study is to investigate influencers on Twitter to discover the characteristics of their tweets through PIAR, a unique data mining research tool developed by the University of Salamanca that combines graph theory and social influence theory. An analysis of 3853 users posting about two automotive Japanese car firms, Toyota and Nissan, reveals the characteristics influencers have on this social network. The findings suggest that influencers use more hashtags and mentions on a...

  9. Mineral resources accounting: A technique formonitoring the Philippine mining industry for sustainable development

    Science.gov (United States)

    Santos, Teodoro M.; Zaratan, May L.

    Mining which extracts exhaustible mineral resources has been condemned by certain sectors as promoting social inequity and underdevelopment. This is so because once a tonne of copper, say, is mined it is forever lost to the future generation. Such perception translates into policies that are usually disadvantageous or even hostile to the industry. Despite this adverse criticism, recent developments in natural resources accounting indicate that mining can truly contribute to the sustainable economic development of a society. True worth of mining in economic development can be assessed and monitored on a continuing basis through an appropriate system of natural accounts (SNA). If the industry is found deficient, such SNA can also point out how the industry can be made to constribute to sustainable growth. The prevailing SNA is criticized as having failed to capture the adverse effects on the welfare of society of producing a nonrenewable resource such as minerals. For instance, the production of copper for a particular year registers an increase in gross national product equivalent to its monetary value. However, the concomitant depletion of the country's natural wealth due to such production is nowhere recorded in the SNA. This faulty accounting gives rise to policies that result in nonsustainable economic growth. In order to address the preceding problem, this paper presents an accounting formula applicable to any nonrenewable resource whereby revenue is decomposed into income and capital components. To achieve sustainable economic growth, it states that the capital component must be invested to generate future incomes. However, investments need not be confined to the same sector. Application of the accounting scheme to the Philippine copper and gold sectors during the 1980-1990 period leads to the following conclusions: (a) by and large, gold and copper mining operations have indeed contributed positively to national income, contrary to allegations of certain

  10. Novel mining methods

    CSIR Research Space (South Africa)

    Monchusi, B

    2012-10-01

    Full Text Available stream_source_info Monchusi_2012.pdf.txt stream_content_type text/plain stream_size 1953 Content-Encoding ISO-8859-1 stream_name Monchusi_2012.pdf.txt Content-Type text/plain; charset=ISO-8859-1 Novel Mining Methods 4th... 2012 Slide 12 CSIR mine safety platform AR Drone Differential time-of-flight beacon Sampling ? CSIR 2012 Slide 13 Reef Laser-Induced Breakdown Spectroscopy (LIBS) head Scan X-Y Laser/Spectrometer/Computer Rock Breaking ? CSIR 2012 Slide...

  11. Monitoring, field experiments, and geochemical modeling of Fe(II) oxidation kinetics in a stream dominated by net-alkaline coal-mine drainage, Pennsylvania, USA

    Science.gov (United States)

    Cravotta,, Charles A.

    2015-01-01

    Watershed-scale monitoring, field aeration experiments, and geochemical equilibrium and kinetic modeling were conducted to evaluate interdependent changes in pH, dissolved CO2, O2, and Fe(II) concentrations that typically take place downstream of net-alkaline, circumneutral coal-mine drainage (CMD) outfalls and during aerobic treatment of such CMD. The kinetic modeling approach, using PHREEQC, accurately simulates observed variations in pH, Fe(II) oxidation, alkalinity consumption, and associated dissolved gas concentrations during transport downstream of the CMD outfalls (natural attenuation) and during 6-h batch aeration tests on the CMD using bubble diffusers (enhanced attenuation). The batch aeration experiments demonstrated that aeration promoted CO2 outgassing, thereby increasing pH and the rate of Fe(II) oxidation. The rate of Fe(II) oxidation was accurately estimated by the abiotic homogeneous oxidation rate law −d[Fe(II)]/dt = k1·[O2]·[H+]−2·[Fe(II)] that indicates an increase in pH by 1 unit at pH 5–8 and at constant dissolved O2 (DO) concentration results in a 100-fold increase in the rate of Fe(II) oxidation. Adjusting for sample temperature, a narrow range of values for the apparent homogeneous Fe(II) oxidation rate constant (k1′) of 0.5–1.7 times the reference value of k1 = 3 × 10−12 mol/L/min (for pH 5–8 and 20 °C), reported by Stumm and Morgan (1996), was indicated by the calibrated models for the 5-km stream reach below the CMD outfalls and the aerated CMD. The rates of CO2 outgassing and O2ingassing in the model were estimated with first-order asymptotic functions, whereby the driving force is the gradient of the dissolved gas concentration relative to equilibrium with the ambient atmosphere. Although the progressive increase in DO concentration to saturation could be accurately modeled as a kinetic function for the conditions evaluated, the simulation of DO as an instantaneous equilibrium process did not affect the

  12. Mapping Of The Hydrothermal Alteration Zones At Haimur Gold Mine Area, South Eastern Desert, Egypt, Using Remote Sensing Techniques

    International Nuclear Information System (INIS)

    Madani, A.A.; Abdel Rahman, E.M.; FA WZY, Kh.M.; EMAM, A.

    2003-01-01

    The utilization of the Landsat-7 ETM+ imagery and scanned aerial photograph for mapping hydrothermal alteration zones at the Haimur gold mine area, south Eastern Desert, Egypt and the production of large scale geologic image map, scale 1 :20 000, using fusion technique are the main tasks of this article. The study area lies at the conjunction of two shear zones, namely the Allaqi shear zone (NW-SE) and the Haimur shear zone (NE-SW). The basement rocks covering Haimur gold mine area include ophiolitic blocks and sheets that were tectonically thrusted over and mixed within a matrix of island arc rocks. Principal Component Analysis, band ratios and data fusion are the main remote sensing techniques applied in the present work. The eigenvalue of the first principal component (PCl) includes 95.9% of the information content of the image whereas PC2 and PC5 mark 3.03% and 0.10%, respectively. The PC5 image was found to represent the highly altered rocks in the study area (serpentinites and carbonates), which display dark image signatures. The metagabbros and metapyroclastics can be easily discriminated on the PC1:R, PC2:G and PC5:B false color composite image in which they have dark red and blue image signatures, respectively. The talc carbonates and the serpentinites have bright image signatures on 5/7 band ratio image whereas metapyroxenites have dark image signatures. The talc carbonates are composed mainly of talc, magnesite and calcite with subordinate amounts of fibrous antigorite. These minerals have absorption features near 2.35 m which lead to increase 5/7 band ratio value. The false color composite ratio image 5/7:R, 4/5:G and 3/1:B was merged with scanned high spatial resolution aerial photograph using IHS transformation method. The resultant fused image was then used to delineate the hydrothermal alteration zones as well as listwaenite ridges exposed at the Haimur gold mine area

  13. Development of effective means of propaganda of safety techniques for coal mines

    Energy Technology Data Exchange (ETDEWEB)

    Galushko, A.L.; Brusilovskiy, V.I.; Popov, I.I.

    1979-01-01

    Information letters about accidents in coal mines are systematically developed and sent to enterprises and organizations of the branch for practical use in preventive work on work protection and work safety. Information materials on advanced experience in prevention of accidents and traumatism are published in large quantities. Principal measures which have dramatically affected the reduction of the level of production traumatism are listed which merit dissemination in the branch. It is noted that the use of these means of propaganda of work safety makes it possible to improve preventive work on work safety and production sanitation in enterprises of the coal industry.

  14. Effect of lithological variations of mine roof on chock shield support using numerical modeling technique

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2006-09-15

    Interaction between chock shield supports, the most popular powered supports in Indian longwall mines, and surrounding coal measure strata is analyzed using finite element models. Thickness and material properties of the main roof, the immediate roof and the coal seam are varied to simulate various geological conditions of Indian coal measure strata. Contact/gap elements are inserted in between the main roof and overburden layer to allow strata separation. Nonlinear material properties are applied with plastic corrections based on Drucker-Prager yield criterion. This paper illustrates effects of lithological variations on shield load, abutment stress, yield zone and longwall face convergence.

  15. Mining techniques and some aspects of high-level waste disposal

    International Nuclear Information System (INIS)

    Hoefnagels, J.A.R.

    1980-01-01

    The solutions to many problems of underground waste disposal involve mine engineering. This article attempts to highlight chosen issues and thereby create an overall impression, avoiding emphasis on single-aspect calculation. High level waste (H.L.W.) dominates current radioactive waste studies because of its specific characteristics and is therefore dealt with in this paper. However, depending on the method of disposal the other categories of radio active waste might become problems by themselves because of the relatively large quantities involved. (Auth.)

  16. Environmental monitoring of uranium mining wastes using geophysical techniques-Phase 1

    International Nuclear Information System (INIS)

    Koch, R.R.

    1996-08-01

    Monitoring of contaminants, from uranium mine waste management facilities, is primarily done by drilling test holes and installing piezometers to sample the subsurface soil and the groundwater. Protocols using geophysical methods of monitoring the migration of acidic leachate from uranium mine waste rock piles and tailings facilities need to be developed. Shallow surface geophysics that include methods such as Electromagnetic (conductivity) and DC Resistivity surveys are less expensive, can locate contaminant plumes both laterally and with depth, providing an areal 'snapshot' of the site at any given time. Cluff Lake Mine, a wholly owned Cogema Resources Inc. of Sakatoon was selected as the research demonstration site. To study the effects of acidic mine drainage a multi-year program is envisioned. The first phase, the subject of this report, involved the testing of various off-the-shelf elctromagnetic and restivity equipment over several site locations. Additional phases are required to monitor temporal changes by carrying out repeat surveys to verify the first phase results. Other methods such as ground penetrating radar may be used to supplement the conductivity and restivity surveys. Electromagnetic surveys identified three conductive zones in the vicinity of the Claude waste rock pile. These anomalies appear to be confined to within 100-150 meters of the pile. A significant area of high conductivity was identified adjacent to the liquid tailings pond on the ED-TDAM-1 grid. Conductivity zones were not detected on grids in the vicinity of the OP waste rock pile and the STS ponds site. The imaged pseudosections of apparent resistivity not only correlate well with the apparent conductivity data at the same locations, but supply information with the anomalies in the third (depth) dimension. On Line 25W of EV-TDAM-1 site the restivity survey indicates that the main anomaly A (450N) has a depth of > 6 metres. Computer assisted inversion and interpretation of sounding

  17. Comparison of hot hydroxylamine hydrochloride and oxalic acid leaching of stream sediment and coated rock samples as anomaly enhancement techniques

    Science.gov (United States)

    Filipek, L.H.; Chao, T.T.; Theobald, P.K.

    1982-01-01

    A hot hydroxylamine hydrochloride (H-Hxl) extraction in 25% acetic acid is compared with the commonly used oxalic acid extraction as a method of anomaly enhancement for Cu and Zn in samples from two very different metal deposits and climatic environments. Results obtained on minus-80-mesh stream sediments from an area near the Magruder massive sulfide deposit in Lincoln County, Georgia, where the climate is humid subtropical, indicate that H-Hxl enhances the anomaly for Cu by a factor of 2 and for Zn by a factor of 1.5, compared to the oxalic method. Analyses of Fe oxide-coated rock samples from outcrops overlying the North Silver Bell porphyry copper deposit near Tucson, Arizona, where the climate is semi-arid to arid, indicate that both techniques effectively outline the zones of hydrothermal alteration. The H-Hxl extraction can also perform well in high-carbonate or high-clay environments, where other workers have suggested that oxalic acid is not very effective. Therefore, the H-Hxl method is recommended for general exploration use. ?? 1982.

  18. Validation of abundance estimates from mark-recapture and removal techniques for rainbow trout captured by electrofishing in small streams

    Science.gov (United States)

    Amanda E. Rosenberger; Jason B. Dunham

    2005-01-01

    Estimation of fish abundance in streams using the removal model or the Lincoln–Peterson mark–recapture model is a common practice in fisheries. These models produce misleading results if their assumptions are violated. We evaluated the assumptions of these two models via electrofishing of rainbow trout Oncorhynchus mykiss in central Idaho streams....

  19. Using Data Mining Techniques to Predict the Detriment Level of Car Insurance Customers

    Directory of Open Access Journals (Sweden)

    Seyyed Mahmood Izadparast

    2012-07-01

    Full Text Available Nowadays customers’ role is changed from just accepting the producers, to leading investors, producers, and even researchers and inventors. Therefore, it is necessary for organizations to identify their customers well and to make plans for them. Some statistical and machine-based learning methods are used so far. However these methods alone are not without limitations. Using various methods of data mining, this research was to eliminate those restrictions as far as possible, so that a framework for identification of car insurance customers could be provided. In fact, the purpose was to categorize the most similar customers and to estimate the amount of risk in each category, according to their characteristics. Now, using this scale (i.e. amount of risk in each category and considering the type of customer’s policy, the level of recompense could be estimated. This criterion can be helpful to identify customers and for making insurance tariff policies. For this purpose, in insurance industry the two data mining methods were been used to estimate customers’ detriment: the decision tree and clustering. Nevertheless, the decision tree method appears to give better results, although at the same, the clustering method generates a good categorization.

  20. Application of risk management techniques for the remediation of an old mining site in Greece.

    Science.gov (United States)

    Panagopoulos, I; Karayannis, A; Adam, K; Aravossis, K

    2009-05-01

    This article summarizes the project and risk management of a remediation/reclamation project in Lavrion, Greece. In Thoricos the disposal of mining and metallurgical wastes in the past resulted in the contamination with heavy metals and acid mine drainage. The objective of this reclamation project was to transform this coastal zone from a contaminated site to an area suitable for recreation purposes. A separate risk assessment study was performed to provide the basis of determining the relevant environmental contamination and to rate the alternative remedial schemes involved. The study used both existing data available from comprehensive studies, as well as newly collected field data. For considering environmental risk, the isolation and minimization of risk option was selected, and a reclamation scheme, based on environmental criteria, was applied which was comprised of in situ neutralization, stabilization and cover of the potentially acid generating wastes and contaminated soils with a low permeability geochemical barrier. Additional measures were specifically applied in the areas where highly sulphidic wastes existed constituting active acid generation sources, which included the encapsulation of wastes in HDPE liners installed on clay layers.

  1. Predicting CD4 count changes among patients on antiretroviral treatment: Application of data mining techniques.

    Science.gov (United States)

    Kebede, Mihiretu; Zegeye, Desalegn Tigabu; Zeleke, Berihun Megabiaw

    2017-12-01

    To monitor the progress of therapy and disease progression, periodic CD4 counts are required throughout the course of HIV/AIDS care and support. The demand for CD4 count measurement is increasing as ART programs expand over the last decade. This study aimed to predict CD4 count changes and to identify the predictors of CD4 count changes among patients on ART. A cross-sectional study was conducted at the University of Gondar Hospital from 3,104 adult patients on ART with CD4 counts measured at least twice (baseline and most recent). Data were retrieved from the HIV care clinic electronic database and patients` charts. Descriptive data were analyzed by SPSS version 20. Cross-Industry Standard Process for Data Mining (CRISP-DM) methodology was followed to undertake the study. WEKA version 3.8 was used to conduct a predictive data mining. Before building the predictive data mining models, information gain values and correlation-based Feature Selection methods were used for attribute selection. Variables were ranked according to their relevance based on their information gain values. J48, Neural Network, and Random Forest algorithms were experimented to assess model accuracies. The median duration of ART was 191.5 weeks. The mean CD4 count change was 243 (SD 191.14) cells per microliter. Overall, 2427 (78.2%) patients had their CD4 counts increased by at least 100 cells per microliter, while 4% had a decline from the baseline CD4 value. Baseline variables including age, educational status, CD8 count, ART regimen, and hemoglobin levels predicted CD4 count changes with predictive accuracies of J48, Neural Network, and Random Forest being 87.1%, 83.5%, and 99.8%, respectively. Random Forest algorithm had a superior performance accuracy level than both J48 and Artificial Neural Network. The precision, sensitivity and recall values of Random Forest were also more than 99%. Nearly accurate prediction results were obtained using Random Forest algorithm. This algorithm could be

  2. Predicting the Location and Time of Mobile Phone Users by Using Sequential Pattern Mining Techniques

    DEFF Research Database (Denmark)

    Ozer, Mert; Keles, Ilkcan; Toroslu, Hakki

    2016-01-01

    In recent years, using cell phone log data to model human mobility patterns became an active research area. This problem is a challenging data mining problem due to huge size and non-uniformity of the log data, which introduces several granularity levels for the specification of temporal...... and spatial dimensions. This paper focuses on the prediction of the location of the next activity of the mobile phone users. There are several versions of this problem. In this work, we have concentrated on the following three problems: predicting the location and the time of the next user activity...... the success of these methods with real data obtained from one of the largest mobile phone operators in Turkey. Our results are very encouraging, since we were able to obtain quite high accuracy results under small prediction sets....

  3. Applying Fuzzy Logic and Data Mining Techniques in Wireless Sensor Network for Determination Residential Fire Confidence

    Directory of Open Access Journals (Sweden)

    Mirjana Maksimović

    2014-09-01

    Full Text Available The main goal of soft computing technologies (fuzzy logic, neural networks, fuzzy rule-based systems, data mining techniques… is to find and describe the structural patterns in the data in order to try to explain connections between data and on their basis create predictive or descriptive models. Integration of these technologies in sensor nodes seems to be a good idea because it can significantly lead to network performances improvements, above all to reduce the energy consumption and enhance the lifetime of the network. The purpose of this paper is to analyze different algorithms in the case of fire confidence determination in order to see which of the methods and parameter values work best for the given problem. Hence, an analysis between different classification algorithms in a case of nominal and numerical d

  4. Applying data mining techniques to explore factors contributing to occupational injuries in Taiwan's construction industry.

    Science.gov (United States)

    Cheng, Ching-Wu; Leu, Sou-Sen; Cheng, Ying-Mei; Wu, Tsung-Chih; Lin, Chen-Chung

    2012-09-01

    Construction accident research involves the systematic sorting, classification, and encoding of comprehensive databases of injuries and fatalities. The present study explores the causes and distribution of occupational accidents in the Taiwan construction industry by analyzing such a database using the data mining method known as classification and regression tree (CART). Utilizing a database of 1542 accident cases during the period 2000-2009, the study seeks to establish potential cause-and-effect relationships regarding serious occupational accidents in the industry. The results of this study show that the occurrence rules for falls and collapses in both public and private project construction industries serve as key factors to predict the occurrence of occupational injuries. The results of the study provide a framework for improving the safety practices and training programs that are essential to protecting construction workers from occasional or unexpected accidents. Copyright © 2011 Elsevier Ltd. All rights reserved.

  5. Development of a photogrammetry technique for large-area deformation monitoring in coal mining areas

    International Nuclear Information System (INIS)

    Redweik, P.M.

    1993-01-01

    The investigations of ground movements in coal mining areas during the past 10 years have been performed by methods of aerial photogrammetry. The ground points used for the determination of the movement in urban areas are manhole covers. The measurements must be repeated every three or four years. These facts have motivated the development of a new automatic method for measuring photo coordinates. This method is implemented on the Rollei RS1 (Reseau-Scanner Monocomparator. The approximate photo coordinates that are needed for this instrument can be computed from the old ground coordinates of each point. The manhole cover will be first recognised with a sort of template matching. Its central point will then be computed by using an ellipse operator. (orig.) [de

  6. Applying data mining techniques to medical time series: an empirical case study in electroencephalography and stabilometry

    Directory of Open Access Journals (Sweden)

    A. Anguera

    2016-01-01

    This paper illustrates the application of different knowledge discovery techniques for the purposes of classification within the above domains. The accuracy of this application for the two classes considered in each case is 99.86% and 98.11% for epilepsy diagnosis in the electroencephalography (EEG domain and 99.4% and 99.1% for early-age sports talent classification in the stabilometry domain. The KDD techniques achieve better results than other traditional neural network-based classification techniques.

  7. What Online Communities Can Tell Us About Electronic Cigarettes and Hookah Use: A Study Using Text Mining and Visualization Techniques.

    Science.gov (United States)

    Chen, Annie T; Zhu, Shu-Hong; Conway, Mike

    2015-09-29

    The rise in popularity of electronic cigarettes (e-cigarettes) and hookah over recent years has been accompanied by some confusion and uncertainty regarding the development of an appropriate regulatory response towards these emerging products. Mining online discussion content can lead to insights into people's experiences, which can in turn further our knowledge of how to address potential health implications. In this work, we take a novel approach to understanding the use and appeal of these emerging products by applying text mining techniques to compare consumer experiences across discussion forums. This study examined content from the websites Vapor Talk, Hookah Forum, and Reddit to understand people's experiences with different tobacco products. Our investigation involves three parts. First, we identified contextual factors that inform our understanding of tobacco use behaviors, such as setting, time, social relationships, and sensory experience, and compared the forums to identify the ones where content on these factors is most common. Second, we compared how the tobacco use experience differs with combustible cigarettes and e-cigarettes. Third, we investigated differences between e-cigarette and hookah use. In the first part of our study, we employed a lexicon-based extraction approach to estimate prevalence of contextual factors, and then we generated a heat map based on these estimates to compare the forums. In the second and third parts of the study, we employed a text mining technique called topic modeling to identify important topics and then developed a visualization, Topic Bars, to compare topic coverage across forums. In the first part of the study, we identified two forums, Vapor Talk Health & Safety and the Stopsmoking subreddit, where discussion concerning contextual factors was particularly common. The second part showed that the discussion in Vapor Talk Health & Safety focused on symptoms and comparisons of combustible cigarettes and e

  8. Improving Intrusion Detection System Based on Snort Rules for Network Probe Attacks Detection with Association Rules Technique of Data Mining

    Directory of Open Access Journals (Sweden)

    Nattawat Khamphakdee

    2015-07-01

    Full Text Available The intrusion detection system (IDS is an important network security tool for securing computer and network systems. It is able to detect and monitor network traffic data. Snort IDS is an open-source network security tool. It can search and match rules with network traffic data in order to detect attacks, and generate an alert. However, the Snort IDS  can detect only known attacks. Therefore, we have proposed a procedure for improving Snort IDS rules, based on the association rules data mining technique for detection of network probe attacks.  We employed the MIT-DARPA 1999 data set for the experimental evaluation. Since behavior pattern traffic data are both normal and abnormal, the abnormal behavior data is detected by way of the Snort IDS. The experimental results showed that the proposed Snort IDS rules, based on data mining detection of network probe attacks, proved more efficient than the original Snort IDS rules, as well as icmp.rules and icmp-info.rules of Snort IDS.  The suitable parameters for the proposed Snort IDS rules are defined as follows: Min_sup set to 10%, and Min_conf set to 100%, and through the application of eight variable attributes. As more suitable parameters are applied, higher accuracy is achieved.

  9. Combining QSAR Modeling and Text-Mining Techniques to Link Chemical Structures and Carcinogenic Modes of Action.

    Science.gov (United States)

    Papamokos, George; Silins, Ilona

    2016-01-01

    There is an increasing need for new reliable non-animal based methods to predict and test toxicity of chemicals. Quantitative structure-activity relationship (QSAR), a computer-based method linking chemical structures with biological activities, is used in predictive toxicology. In this study, we tested the approach to combine QSAR data with literature profiles of carcinogenic modes of action automatically generated by a text-mining tool. The aim was to generate data patterns to identify associations between chemical structures and biological mechanisms related to carcinogenesis. Using these two methods, individually and combined, we evaluated 96 rat carcinogens of the hematopoietic system, liver, lung, and skin. We found that skin and lung rat carcinogens were mainly mutagenic, while the group of carcinogens affecting the hematopoietic system and the liver also included a large proportion of non-mutagens. The automatic literature analysis showed that mutagenicity was a frequently reported endpoint in the literature of these carcinogens, however, less common endpoints such as immunosuppression and hormonal receptor-mediated effects were also found in connection with some of the carcinogens, results of potential importance for certain target organs. The combined approach, using QSAR and text-mining techniques, could be useful for identifying more detailed information on biological mechanisms and the relation with chemical structures. The method can be particularly useful in increasing the understanding of structure and activity relationships for non-mutagens.

  10. Combining QSAR Modeling and Text-Mining Techniques to Link Chemical Structures and Carcinogenic Modes of Action

    Science.gov (United States)

    Papamokos, George; Silins, Ilona

    2016-01-01

    There is an increasing need for new reliable non-animal based methods to predict and test toxicity of chemicals. Quantitative structure-activity relationship (QSAR), a computer-based method linking chemical structures with biological activities, is used in predictive toxicology. In this study, we tested the approach to combine QSAR data with literature profiles of carcinogenic modes of action automatically generated by a text-mining tool. The aim was to generate data patterns to identify associations between chemical structures and biological mechanisms related to carcinogenesis. Using these two methods, individually and combined, we evaluated 96 rat carcinogens of the hematopoietic system, liver, lung, and skin. We found that skin and lung rat carcinogens were mainly mutagenic, while the group of carcinogens affecting the hematopoietic system and the liver also included a large proportion of non-mutagens. The automatic literature analysis showed that mutagenicity was a frequently reported endpoint in the literature of these carcinogens, however, less common endpoints such as immunosuppression and hormonal receptor-mediated effects were also found in connection with some of the carcinogens, results of potential importance for certain target organs. The combined approach, using QSAR and text-mining techniques, could be useful for identifying more detailed information on biological mechanisms and the relation with chemical structures. The method can be particularly useful in increasing the understanding of structure and activity relationships for non-mutagens. PMID:27625608

  11. Does leaf chemistry differentially affect breakdown in tropical versus temperate streams? Importance of standardized analytical techniques to measure leaf chemistry

    Science.gov (United States)

    Marcelo Ardon; Catherine M. Pringle; Susan L. Eggert

    2009-01-01

    Comparisons of the effects of leaf litter chemistry on leaf breakdown rates in tropical vs temperate streams are hindered by incompatibility among studies and across sites of analytical methods used to...

  12. Application Of Data Mining Techniques For Student Success And Failure Prediction The Case Of DebreMarkos University

    OpenAIRE

    Muluken Alemu Yehuala

    2015-01-01

    Abstract This research work has investigated the potential applicability of data mining technology to predict student success and failure cases on University students datasets. CRISP-DM Cross Industry Standard Process for Data mining is a data mining methodology to be used by the research. Classification and prediction data mining functionalities are used to extract hidden patterns from students data. These patterns can be seen in relation to different variables in the students records. The ...

  13. A comparison of machine learning techniques for predicting downstream acid mine drainage

    CSIR Research Space (South Africa)

    van Zyl, TL

    2014-07-01

    Full Text Available windowing approach over historical values to generate a prediction for the current value. We evaluate a number of Machine Learning techniques as regressors including Support Vector Regression, Random Forests, Stochastic Gradient Decent Regression, Linear...

  14. Use of nuclear techniques for coal analysis in exploration, mining and processing

    International Nuclear Information System (INIS)

    Clayton, C.G.; Wormald, M.R.

    1982-01-01

    Nuclear techniques have a long history of application in the coal industry, during exploration and especially during coal preparation, for the measurement of ash content. The preferred techniques are based on X- and gamma-ray scattering and borehole logging, and on-line equipment incorporating these techniques are now in world-wide routine use. However, gamma-ray techniques are mainly restricted to density measurement and X-ray techniques are principally used for ash determinations. They have a limited range and when used on-line some size reduction of the coal is usually required and a full elemental analysis is not possible. In particular, X- and gamma-ray techniques are insensitive to the principal elements in the combustible component and to many of the important elements in the mineral fraction. Neutron techniques on the other hand have a range which is compatible with on-line requirements and all elements in the combustible component and virtually all elements in the mineral component can be observed. A complete elemental analysis of coal then allows the ash content and the calorific value to be determined on-line. This paper surveys the various nuclear techniques now in use and gives particular attention to the present state of development of neutron methods and to their advantages and limitations. Although it is shown that considerable further development and operational experience are still required, equipment now being introduced has a performance which matches many of the identified requirements and an early improvement in specification can be anticipated

  15. Application of fuzzy weight of evidence and data mining techniques in construction of flood susceptibility map of Poyang County, China.

    Science.gov (United States)

    Hong, Haoyuan; Tsangaratos, Paraskevas; Ilia, Ioanna; Liu, Junzhi; Zhu, A-Xing; Chen, Wei

    2018-06-01

    In China, floods are considered as the most frequent natural disaster responsible for severe economic losses and serious damages recorded in agriculture and urban infrastructure. Based on the international experience prevention of flood events may not be completely possible, however identifying susceptible and vulnerable areas through prediction models is considered as a more visible task with flood susceptibility mapping being an essential tool for flood mitigation strategies and disaster preparedness. In this context, the present study proposes a novel approach to construct a flood susceptibility map in the Poyang County, JiangXi Province, China by implementing fuzzy weight of evidence (fuzzy-WofE) and data mining methods. The novelty of the presented approach is the usage of fuzzy-WofE that had a twofold purpose. Firstly, to create an initial flood susceptibility map in order to identify non-flood areas and secondly to weight the importance of flood related variables which influence flooding. Logistic Regression (LR), Random Forest (RF) and Support Vector Machines (SVM) were implemented considering eleven flood related variables, namely: lithology, soil cover, elevation, slope angle, aspect, topographic wetness index, stream power index, sediment transport index, plan curvature, profile curvature and distance from river network. The efficiency of this new approach was evaluated using area under curve (AUC) which measured the prediction and success rates. According to the outcomes of the performed analysis, the fuzzy WofE-SVM model was the model with the highest predictive performance (AUC value, 0.9865) which also appeared to be statistical significant different from the other predictive models, fuzzy WofE-RF (AUC value, 0.9756) and fuzzy WofE-LR (AUC value, 0.9652). The proposed methodology and the produced flood susceptibility map could assist researchers and local governments in flood mitigation strategies. Copyright © 2017 Elsevier B.V. All rights reserved.

  16. On the advantage of using dedicated data mining techniques to predict colorectal cancer

    NARCIS (Netherlands)

    Kop, Reinier; Hoogendoorn, Mark; Moons, Leon M G; Numans, Mattijs E.; ten Teije, Annette

    2015-01-01

    Electronic Medical Records (EMRs) provide a wealth of data that can be used to generate predictive models for diseases. Quite some studies have been performed that use EMRs to generate such models for specific diseases, but most of them are based on more traditional techniques used in medical

  17. Propensity Score Estimation with Data Mining Techniques: Alternatives to Logistic Regression

    Science.gov (United States)

    Keller, Bryan S. B.; Kim, Jee-Seon; Steiner, Peter M.

    2013-01-01

    Propensity score analysis (PSA) is a methodological technique which may correct for selection bias in a quasi-experiment by modeling the selection process using observed covariates. Because logistic regression is well understood by researchers in a variety of fields and easy to implement in a number of popular software packages, it has…

  18. Mining FDA drug labels using an unsupervised learning technique--topic modeling.

    Science.gov (United States)

    Bisgin, Halil; Liu, Zhichao; Fang, Hong; Xu, Xiaowei; Tong, Weida

    2011-10-18

    The Food and Drug Administration (FDA) approved drug labels contain a broad array of information, ranging from adverse drug reactions (ADRs) to drug efficacy, risk-benefit consideration, and more. However, the labeling language used to describe these information is free text often containing ambiguous semantic descriptions, which poses a great challenge in retrieving useful information from the labeling text in a consistent and accurate fashion for comparative analysis across drugs. Consequently, this task has largely relied on the manual reading of the full text by experts, which is time consuming and labor intensive. In this study, a novel text mining method with unsupervised learning in nature, called topic modeling, was applied to the drug labeling with a goal of discovering "topics" that group drugs with similar safety concerns and/or therapeutic uses together. A total of 794 FDA-approved drug labels were used in this study. First, the three labeling sections (i.e., Boxed Warning, Warnings and Precautions, Adverse Reactions) of each drug label were processed by the Medical Dictionary for Regulatory Activities (MedDRA) to convert the free text of each label to the standard ADR terms. Next, the topic modeling approach with latent Dirichlet allocation (LDA) was applied to generate 100 topics, each associated with a set of drugs grouped together based on the probability analysis. Lastly, the efficacy of the topic modeling was evaluated based on known information about the therapeutic uses and safety data of drugs. The results demonstrate that drugs grouped by topics are associated with the same safety concerns and/or therapeutic uses with statistical significance (P<0.05). The identified topics have distinct context that can be directly linked to specific adverse events (e.g., liver injury or kidney injury) or therapeutic application (e.g., antiinfectives for systemic use). We were also able to identify potential adverse events that might arise from specific

  19. Mining FDA drug labels using an unsupervised learning technique - topic modeling

    Science.gov (United States)

    2011-01-01

    Background The Food and Drug Administration (FDA) approved drug labels contain a broad array of information, ranging from adverse drug reactions (ADRs) to drug efficacy, risk-benefit consideration, and more. However, the labeling language used to describe these information is free text often containing ambiguous semantic descriptions, which poses a great challenge in retrieving useful information from the labeling text in a consistent and accurate fashion for comparative analysis across drugs. Consequently, this task has largely relied on the manual reading of the full text by experts, which is time consuming and labor intensive. Method In this study, a novel text mining method with unsupervised learning in nature, called topic modeling, was applied to the drug labeling with a goal of discovering “topics” that group drugs with similar safety concerns and/or therapeutic uses together. A total of 794 FDA-approved drug labels were used in this study. First, the three labeling sections (i.e., Boxed Warning, Warnings and Precautions, Adverse Reactions) of each drug label were processed by the Medical Dictionary for Regulatory Activities (MedDRA) to convert the free text of each label to the standard ADR terms. Next, the topic modeling approach with latent Dirichlet allocation (LDA) was applied to generate 100 topics, each associated with a set of drugs grouped together based on the probability analysis. Lastly, the efficacy of the topic modeling was evaluated based on known information about the therapeutic uses and safety data of drugs. Results The results demonstrate that drugs grouped by topics are associated with the same safety concerns and/or therapeutic uses with statistical significance (P<0.05). The identified topics have distinct context that can be directly linked to specific adverse events (e.g., liver injury or kidney injury) or therapeutic application (e.g., antiinfectives for systemic use). We were also able to identify potential adverse events that

  20. Development of data enhancement and display techniques for stream-sediment data collected in the national uranium resource evaluation program of the United States Department of Energy

    International Nuclear Information System (INIS)

    Koch, G.S. Jr.; Howarth, R.J.; Carpenter, R.H.; Schuenemeyer, J.H.

    1979-08-01

    The objective of this study was to combine statistical, mapping, and geological techniques in order to evaluate and appropriately display geochemical data for the identification of uranium associated halos utilizing the NURE hydrogeochemical and stream sediment reconnaissance data base. A set of computer-based procedures implemented in a time-sharing interactive mode on a Control Data Corporation Cyber 70 and 174 computer was developed. Techniques of data analysis are developed. Results of the data analysis for the Southeastern area, Seguin quadrangle, and Pueblo quadrangle are presented. Conclusions are drawn and recommendations are stated

  1. Melodic pattern extraction in large collections of music recordings using time series mining techniques

    OpenAIRE

    Gulati, Sankalp; Serrà, Joan; Ishwar, Vignesh; Serra, Xavier

    2014-01-01

    We demonstrate a data-driven unsupervised approach for the discovery of melodic patterns in large collections of Indian art music recordings. The approach first works on single recordings and subsequently searches in the entire music collection. Melodic similarity is based on dynamic time warping. The task being computationally intensive, lower bounding and early abandoning techniques are applied during distance computation. Our dataset comprises 365 hours of music, containing 1,764 audio rec...

  2. Data mining technique for a secure electronic payment transaction using MJk-RSA in mobile computing

    Science.gov (United States)

    G. V., Ramesh Babu; Narayana, G.; Sulaiman, A.; Padmavathamma, M.

    2012-04-01

    Due to the evolution of the Electronic Learning (E-Learning), one can easily get desired information on computer or mobile system connected through Internet. Currently E-Learning materials are easily accessible on the desktop computer system, but in future, most of the information shall also be available on small digital devices like Mobile, PDA, etc. Most of the E-Learning materials are paid and customer has to pay entire amount through credit/debit card system. Therefore, it is very important to study about the security of the credit/debit card numbers. The present paper is an attempt in this direction and a security technique is presented to secure the credit/debit card numbers supplied over the Internet to access the E-Learning materials or any kind of purchase through Internet. A well known method i.e. Data Cube Technique is used to design the security model of the credit/debit card system. The major objective of this paper is to design a practical electronic payment protocol which is the safest and most secured mode of transaction. This technique may reduce fake transactions which are above 20% at the global level.

  3. Handling Dynamic Weights in Weighted Frequent Pattern Mining

    Science.gov (United States)

    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.

  4. Uranium aqueous speciation in the vicinity of the former uranium mining sites using the diffusive gradients in thin films and ultrafiltration techniques.

    Science.gov (United States)

    Drozdzak, Jagoda; Leermakers, Martine; Gao, Yue; Elskens, Marc; Phrommavanh, Vannapha; Descostes, Michael

    2016-03-24

    The performance of the Diffusive Gradients in Thin films (DGT) technique with Chelex(®)-100, Metsorb™ and Diphonix(®) as binding phases was evaluated in the vicinity of the former uranium mining sites of Chardon and L'Ecarpière (Loire-Atlantique department in western France). This is the first time that the DGT technique with three different binding agents was employed for the aqueous U determination in the context of uranium mining environments. The fractionation and speciation of uranium were investigated using a multi-methodological approach using filtration (0.45 μm, 0.2 μm), ultrafiltration (500 kDa, 100 kDa and 10 kDa) coupled to geochemical speciation modelling (PhreeQC) and the DGT technique. The ultrafiltration data showed that at each sampling point uranium was present mostly in the 10 kDa truly dissolved fraction and the geochemical modelling speciation calculations indicated that U speciation was markedly predominated by CaUO2(CO3)3(2-). In natural waters, no significant difference was observed in terms of U uptake between Chelex(®)-100 and Metsorb™, while similar or inferior U uptake was observed on Diphonix(®) resin. In turn, at mining influenced sampling spots, the U accumulation on DGT-Diphonix(®) was higher than on DGT-Chelex(®)-100 and DGT-Metsorb™, probably because their performance was disturbed by the extreme composition of the mining waters. The use of Diphonix(®) resin leads to a significant advance in the application and development of the DGT technique for determination of U in mining influenced environments. This investigation demonstrated that such multi-technique approach provides a better picture of U speciation and enables to assess more accurately the potentially bioavailable U pool. Copyright © 2016 Elsevier B.V. All rights reserved.

  5. The application of Double-difference technique to improve localization of induced microseismic events at Pyhäsalmi copper mine, Pyhäjärvi, Finland.

    Science.gov (United States)

    Nevalainen, Jouni; Usoltseva, Olga; Kozlovskaya, Elena; Mäki, Timo

    2017-04-01

    Pyhäsalmi mine, an underground copper mine at Pyhäjärvi, Finland, have been known to have induced seismicity due ore excavation for over half of a century. In 2002, the excavation depth increased as mining activity focused to Pyhäsalmi deep ore body, a potato shaped ore concentration that lies roughly from 1000 meter to 1425 meters below the surface. The stress level in the rock was detected to be very high with clear main direction and due to this microseismicity started occurring immediately when the construction of "new mine" section began. Thus a microseismic monitoring system was installed to trace this frequently occurring induced seismicity as seismic observations are one of the quickest ways to map mines state-of-health. The system consist over 25 geophones that are mainly around the excavation site. Since the installation, over 250000 events have been observed. Currently the automated (triggered) and afterwards manually verified seismic events localization routine is applied by absolute location method that minimizes the penalty function of calculated location and origin time to match as good as possibly for corresponding events observed arrivaltimes. However with this method the best location accuracy is around 20 meters at center of the excavation, since it uses homogenous velocity model that have been applied to whole mine but in reality the seismic velocity structure is very complex with tunnels, fill material and ore. For mines seismic alarm purposes this suits well, but for more advanced source analysis this accuracy is not enough. We apply Double-difference technique to relocate microseismic scale events at Pyhäsalmi mine. This iterative least-squares procedure method utilizes pairs of events with common receiver. The basic principle of the technique is that it relates the residual between the observed and the predicted phase traveltime difference for pairs of earthquakes observed at common station to adjustments in the vector that connects

  6. [A comparative study of maintenance services using the data-mining technique].

    Science.gov (United States)

    Cruz, Antonio M; Aguilera-Huertas, Wilmer A; Días-Mora, Darío A

    2009-08-01

    The main goal in this research was comparing two hospitals' maintenance service quality. One of them had a contract service; the other one had an in-house maintenance service. The authors followed the next stages when conducting this research: domain understanding, data characterisation and sample reduction, insight characterisation and building the TAT predictor. Multiple linear regression and clustering techniques were used for improving the efficiency of corrective maintenance tasks in a clinical engineering department (CED). The indicator being studied was turnaround time (TAT). The institution having an in-house maintenance service had better quality indicators than the contract maintenance service. There was lineal dependence between availability and service productivity.

  7. 75 FR 22723 - Stream Protection Rule; Environmental Impact Statement

    Science.gov (United States)

    2010-04-30

    ..., 784, 816, and 817 RIN 1029-AC63 Stream Protection Rule; Environmental Impact Statement AGENCY: Office... streams from the adverse impacts of surface coal mining operations. We are requesting comments for the... mining activities may be conducted in or near perennial or intermittent streams. That rule, which this...

  8. Introduction to stream: An Extensible Framework for Data Stream Clustering Research with R

    Directory of Open Access Journals (Sweden)

    Michael Hahsler

    2017-02-01

    Full Text Available In recent years, data streams have become an increasingly important area of research for the computer science, database and statistics communities. Data streams are ordered and potentially unbounded sequences of data points created by a typically non-stationary data generating process. Common data mining tasks associated with data streams include clustering, classification and frequent pattern mining. New algorithms for these types of data are proposed regularly and it is important to evaluate them thoroughly under standardized conditions. In this paper we introduce stream, a research tool that includes modeling and simulating data streams as well as an extensible framework for implementing, interfacing and experimenting with algorithms for various data stream mining tasks. The main advantage of stream is that it seamlessly integrates with the large existing infrastructure provided by R. In addition to data handling, plotting and easy scripting capabilities, R also provides many existing algorithms and enables users to interface code written in many programming languages popular among data mining researchers (e.g., C/C++, Java and Python. In this paper we describe the architecture of stream and focus on its use for data stream clustering research. stream was implemented with extensibility in mind and will be extended in the future to cover additional data stream mining tasks like classification and frequent pattern mining.

  9. An Application of Data Mining Techniques for Flood Forecasting: Application in Rivers Daya and Bhargavi, India

    Science.gov (United States)

    Panigrahi, Binay Kumar; Das, Soumya; Nath, Tushar Kumar; Senapati, Manas Ranjan

    2018-05-01

    In the present study, with a view to speculate the water flow of two rivers in eastern India namely river Daya and river Bhargavi, the focus was on developing Cascaded Functional Link Artificial Neural Network (C-FLANN) model. Parameters of C-FLANN architecture were updated using Harmony Search (HS) and Differential Evolution (DE). As the numbers of samples are very low, there is a risk of over fitting. To avoid this Map reduce based ANOVA technique is used to select important features. These features were used and provided to the architecture which is used to predict the water flow in both the rivers, one day, one week and two weeks ahead. The results of both the techniques were compared with Radial Basis Functional Neural Network (RBFNN) and Multilayer Perceptron (MLP), two widely used artificial neural network for prediction. From the result it was confirmed that C-FLANN trained through HS gives better prediction result than being trained through DE or RBFNN or MLP and can be used for predicting water flow in different rivers.

  10. Data mining technique for fast retrieval of similar waveforms in Fusion massive databases

    International Nuclear Information System (INIS)

    Vega, J.; Pereira, A.; Portas, A.; Dormido-Canto, S.; Farias, G.; Dormido, R.; Sanchez, J.; Duro, N.; Santos, M.; Sanchez, E.; Pajares, G.

    2008-01-01

    Fusion measurement systems generate similar waveforms for reproducible behavior. A major difficulty related to data analysis is the identification, in a rapid and automated way, of a set of discharges with comparable behaviour, i.e. discharges with 'similar' waveforms. Here we introduce a new technique for rapid searching and retrieval of 'similar' signals. The approach consists of building a classification system that avoids traversing the whole database looking for similarities. The classification system diminishes the problem dimensionality (by means of waveform feature extraction) and reduces the searching space to just the most probable 'similar' waveforms (clustering techniques). In the searching procedure, the input waveform is classified in any of the existing clusters. Then, a similarity measure is computed between the input signal and all cluster elements in order to identify the most similar waveforms. The inner product of normalized vectors is used as the similarity measure as it allows the searching process to be independent of signal gain and polarity. This development has been applied recently to TJ-II stellarator databases and has been integrated into its remote participation system

  11. Data mining technique for fast retrieval of similar waveforms in Fusion massive databases

    Energy Technology Data Exchange (ETDEWEB)

    Vega, J. [Asociacion EURATOM/CIEMAT Para Fusion, Madrid (Spain)], E-mail: jesus.vega@ciemat.es; Pereira, A.; Portas, A. [Asociacion EURATOM/CIEMAT Para Fusion, Madrid (Spain); Dormido-Canto, S.; Farias, G.; Dormido, R.; Sanchez, J.; Duro, N. [Departamento de Informatica y Automatica, UNED, Madrid (Spain); Santos, M. [Departamento de Arquitectura de Computadores y Automatica, UCM, Madrid (Spain); Sanchez, E. [Asociacion EURATOM/CIEMAT Para Fusion, Madrid (Spain); Pajares, G. [Departamento de Arquitectura de Computadores y Automatica, UCM, Madrid (Spain)

    2008-01-15

    Fusion measurement systems generate similar waveforms for reproducible behavior. A major difficulty related to data analysis is the identification, in a rapid and automated way, of a set of discharges with comparable behaviour, i.e. discharges with 'similar' waveforms. Here we introduce a new technique for rapid searching and retrieval of 'similar' signals. The approach consists of building a classification system that avoids traversing the whole database looking for similarities. The classification system diminishes the problem dimensionality (by means of waveform feature extraction) and reduces the searching space to just the most probable 'similar' waveforms (clustering techniques). In the searching procedure, the input waveform is classified in any of the existing clusters. Then, a similarity measure is computed between the input signal and all cluster elements in order to identify the most similar waveforms. The inner product of normalized vectors is used as the similarity measure as it allows the searching process to be independent of signal gain and polarity. This development has been applied recently to TJ-II stellarator databases and has been integrated into its remote participation system.

  12. The use of data mining techniques for analysing factors affecting cow reactivity during milking

    Directory of Open Access Journals (Sweden)

    Wojciech NEJA

    2017-06-01

    Full Text Available Motor activity of 158 Polish Holstein-Friesian cows was evaluated 5 times (before and during milking in a DeLaval 2*10 milking parlour for both the morning and evening milking, on a 5-point scale, according to the method of Budzyńska et al. (2007. The statistical analysis used multiple logistic regression and classification trees (Enterprise Miner 7.1 software which comes in with SAS package. In the evaluation of motor activity, cows that were among the first ten to enter the milking parlour were more often given a score of 3 points before (11.5% and during milking (23.5% compared to the other cows. Cows’ activity tended to decrease (both before and during milking with advancing lactation. The cows’ reduced activity was accompanied by shorter teat cup attachment times and lower milk yields. The criteria calculated for the quality of models based on classification tree technique as well as logistic regression showed that similar variables were responsible for the reactivity of cows before milking (teat cup attachment time, day of lactation, number of lactation, side of the milking parlour and during milking (day of lactation, side of the milking parlour, morning or evening milking, milk yield, number of lactation. At the same time, the applied methods showed that the determinants of the cow reactivity trait are highly complex. This complexity may be well explained using the classification tree technique.

  13. Process mining

    DEFF Research Database (Denmark)

    van der Aalst, W.M.P.; Rubin, V.; Verbeek, H.M.W.

    2010-01-01

    Process mining includes the automated discovery of processes from event logs. Based on observed events (e.g., activities being executed or messages being exchanged) a process model is constructed. One of the essential problems in process mining is that one cannot assume to have seen all possible...... behavior. At best, one has seen a representative subset. Therefore, classical synthesis techniques are not suitable as they aim at finding a model that is able to exactly reproduce the log. Existing process mining techniques try to avoid such “overfitting” by generalizing the model to allow for more...... support for it). None of the existing techniques enables the user to control the balance between “overfitting” and “underfitting”. To address this, we propose a two-step approach. First, using a configurable approach, a transition system is constructed. Then, using the “theory of regions”, the model...

  14. Uranium aqueous speciation in the vicinity of the former uranium mining sites using the diffusive gradients in thin films and ultrafiltration techniques

    Energy Technology Data Exchange (ETDEWEB)

    Drozdzak, Jagoda, E-mail: jdrozdza@vub.ac.be [Analytical, Environmental and Geochemistry (AMGC), Vrije Universiteit Brussels (VUB), Pleinlaan 2, 1050 Brussels (Belgium); Leermakers, Martine; Gao, Yue; Elskens, Marc [Analytical, Environmental and Geochemistry (AMGC), Vrije Universiteit Brussels (VUB), Pleinlaan 2, 1050 Brussels (Belgium); Phrommavanh, Vannapha; Descostes, Michael [AREVA Mines – R& D Dpt., Tour AREVA, 1 Place Jean Millier, 92084 Paris La Défense (France)

    2016-03-24

    The performance of the Diffusive Gradients in Thin films (DGT) technique with Chelex{sup ®}-100, Metsorb™ and Diphonix{sup ®} as binding phases was evaluated in the vicinity of the former uranium mining sites of Chardon and L'Ecarpière (Loire-Atlantique department in western France). This is the first time that the DGT technique with three different binding agents was employed for the aqueous U determination in the context of uranium mining environments. The fractionation and speciation of uranium were investigated using a multi-methodological approach using filtration (0.45 μm, 0.2 μm), ultrafiltration (500 kDa, 100 kDa and 10 kDa) coupled to geochemical speciation modelling (PhreeQC) and the DGT technique. The ultrafiltration data showed that at each sampling point uranium was present mostly in the 10 kDa truly dissolved fraction and the geochemical modelling speciation calculations indicated that U speciation was markedly predominated by CaUO{sub 2}(CO{sub 3}){sub 3}{sup 2−}. In natural waters, no significant difference was observed in terms of U uptake between Chelex{sup ®}-100 and Metsorb™, while similar or inferior U uptake was observed on Diphonix{sup ®} resin. In turn, at mining influenced sampling spots, the U accumulation on DGT-Diphonix{sup ®} was higher than on DGT-Chelex{sup ®}-100 and DGT-Metsorb™, probably because their performance was disturbed by the extreme composition of the mining waters. The use of Diphonix{sup ®} resin leads to a significant advance in the application and development of the DGT technique for determination of U in mining influenced environments. This investigation demonstrated that such multi-technique approach provides a better picture of U speciation and enables to assess more accurately the potentially bioavailable U pool. - Highlights: • The applicability of the DGT technique in the vicinity of former uranium mining sites was evaluated. • The binding selectivity order of the binding phase is

  15. Data Mining Techniques for Detecting Household Characteristics Based on Smart Meter Data

    Directory of Open Access Journals (Sweden)

    Krzysztof Gajowniczek

    2015-07-01

    Full Text Available The main goal of this research is to discover the structure of home appliances usage patterns, hence providing more intelligence in smart metering systems by taking into account the usage of selected home appliances and the time of their usage. In particular, we present and apply a set of unsupervised machine learning techniques to reveal specific usage patterns observed at an individual household. The work delivers the solutions applicable in smart metering systems that might: (1 contribute to higher energy awareness; (2 support accurate usage forecasting; and (3 provide the input for demand response systems in homes with timely energy saving recommendations for users. The results provided in this paper show that determining household characteristics from smart meter data is feasible and allows for quickly grasping general trends in data.

  16. Application of electromagnetic techniques in survey of contaminated groundwater at an abandoned mine complex in southwestern Indiana, U.S.A

    International Nuclear Information System (INIS)

    Brooks, G.A.; Olyphant, G.A.; Harper, D.

    1991-01-01

    In part of a large abandoned mining complex, electromagnetic geophysical surveys were used along with data derived from cores and monitoring wells to infer sources of contamination and subsurface hydrologic connections between acidic refuse deposits and adjacent undistributed geologic materials. Electrical resistivity increases sharply along the boundary of an elevated deposit of pyritic coarse refuse, which is highly contaminated and electrically conductive, indicating poor subsurface hydrologic connections with surrounding deposits of fine refuse and undisturbed glacial material. Groundwater chemistry, as reflected in values of specific conductance, also differs markedly across the deposit's boundary, indicating that a widespread contaminant plume has not developed around the coarse refuse in more than 40 yr since the deposit was created. Most acidic drainage from the coarse refuse is by surface and is concentrated around stream channels. Although most of the contaminated groundwater within the study area is concentrated within the surficial refuse deposits, transects of apparent resistivity and phase angle indicate the existence of an anomalous conductive layer at depth (> 4 m) in thick alluvial sediments along the northern boundary of the mining complex. Based on knowledge of local geology, the anomaly is interpreted to represent a subsurface connection between the alluvium and a flooded abandoned underground mine

  17. State and performance of on-stream ash content determination in lignite and black coal using 2-energy transmission technique

    International Nuclear Information System (INIS)

    Thuemmel, H.W.; Koerner, G.; Leonhardt, J.

    1986-01-01

    The total r.m.s. ash error of the 2-energy transmission on-stream ash gauges KRAS-2 (CIIRR, GDR) and SIROASH (Australia) are 4 weight percentage for raw lignite and 0.5 weight percentage for black coal, respectively. A detailed error analysis shows that this difference is due to the high water content and to strong variations in the ash composition of raw lignite. Both gauges show essentially the same radiometric performance. (author)

  18. Validation of abundance estimates from mark–recapture and removal techniques for rainbow trout captured by electrofishing in small streams

    Science.gov (United States)

    Rosenberger, Amanda E.; Dunham, Jason B.

    2005-01-01

    Estimation of fish abundance in streams using the removal model or the Lincoln - Peterson mark - recapture model is a common practice in fisheries. These models produce misleading results if their assumptions are violated. We evaluated the assumptions of these two models via electrofishing of rainbow trout Oncorhynchus mykiss in central Idaho streams. For one-, two-, three-, and four-pass sampling effort in closed sites, we evaluated the influences of fish size and habitat characteristics on sampling efficiency and the accuracy of removal abundance estimates. We also examined the use of models to generate unbiased estimates of fish abundance through adjustment of total catch or biased removal estimates. Our results suggested that the assumptions of the mark - recapture model were satisfied and that abundance estimates based on this approach were unbiased. In contrast, the removal model assumptions were not met. Decreasing sampling efficiencies over removal passes resulted in underestimated population sizes and overestimates of sampling efficiency. This bias decreased, but was not eliminated, with increased sampling effort. Biased removal estimates based on different levels of effort were highly correlated with each other but were less correlated with unbiased mark - recapture estimates. Stream size decreased sampling efficiency, and stream size and instream wood increased the negative bias of removal estimates. We found that reliable estimates of population abundance could be obtained from models of sampling efficiency for different levels of effort. Validation of abundance estimates requires extra attention to routine sampling considerations but can help fisheries biologists avoid pitfalls associated with biased data and facilitate standardized comparisons among studies that employ different sampling methods.

  19. Abandoned Smolník mine (Slovakia – a catchment area affected by mining activities

    Directory of Open Access Journals (Sweden)

    Lintnerová, Otília

    2008-06-01

    Full Text Available Smolník is a historical Cu-mining area that was exploited from the 14th century to 1990. The Smolník mine was definitively closed and flooded in 1990–1994. Acid mine drainage discharging from the flooded mine (pH = 3.83, Fe = 542 mg/l, SO42– = 3642 mg/l, Cu = 1880 µg/l, Zn = 9599 µg/l, As = 108 mg/l acidified and contaminated the Smolník Creek water, which transported pollution into the Hnilec River catchment. The Smolník mine waste area has been used as a model area to document pollution of waters, stream sediments, and soils by metals and other toxic elements. Major goals of this complex study were to document creek water transport of the main pollutants (Fe, sulphates, Cu, Al, As, etc. in the form of suspended solids, to investigate elements mobility in common mine waste (rock and processing waste heaps and tailing impoundment and in the soil on the basis of neutralization and leach experiments. Different methodologies and techniques for sampling and chemical and mineralogical characterization of samples were used and checked to evaluate environmental risk of this abandoned mine area.

  20. Applying data mining techniques to determine important parameters in chronic kidney disease and the relations of these parameters to each other.

    Science.gov (United States)

    Tahmasebian, Shahram; Ghazisaeedi, Marjan; Langarizadeh, Mostafa; Mokhtaran, Mehrshad; Mahdavi-Mazdeh, Mitra; Javadian, Parisa

    2017-01-01

    Introduction: Chronic kidney disease (CKD) includes a wide range of pathophysiological processes which will be observed along with abnormal function of kidneys and progressive decrease in glomerular filtration rate (GFR). According to the definition decreasing GFR must have been present for at least three months. CKD will eventually result in end-stage kidney disease. In this process different factors play role and finding the relations between effective parameters in this regard can help to prevent or slow progression of this disease. There are always a lot of data being collected from the patients' medical records. This huge array of data can be considered a valuable source for analyzing, exploring and discovering information. Objectives: Using the data mining techniques, the present study tries to specify the effective parameters and also aims to determine their relations with each other in Iranian patients with CKD. Material and Methods: The study population includes 31996 patients with CKD. First, all of the data is registered in the database. Then data mining tools were used to find the hidden rules and relationships between parameters in collected data. Results: After data cleaning based on CRISP-DM (Cross Industry Standard Process for Data Mining) methodology and running mining algorithms on the data in the database the relationships between the effective parameters was specified. Conclusion: This study was done using the data mining method pertaining to the effective factors on patients with CKD.

  1. Sedimentation rate and chronology of As and Zn in sediment of a recent former tin mining lake estimated using Pb-210 dating technique

    International Nuclear Information System (INIS)

    Zaharidah Abu Bakar; Ahmad Saat; Zaini Hamzah; Abdul Khalik Wood; Zaharudin Ahmad

    2011-01-01

    Sedimentation in lake occurred through run-off from the land surface and settles on the bottom lake. Past mining activities might enhance sedimentation process in the former tin mining lakes either through natural or human activities. Former tin mining lakes were suspected to have high sedimentation rate due undisturbed environment for almost 50 years. To estimate sedimentation rate and metals contamination in this lake, Pb-210 dating technique was used. Two sediments cores were sampled using gravity corer from a former tin mining lake then analyzed using alpha-spectrometry and Neutron Activation Analysis (NAA). From this study, the results showed the sedimentation rate for sediment cores S1 and S2 are 0.26 cm y -1 and 0.23 cmy -1 respectively. According to sediment chronological sequences, high concentrations of As and Zn in the upper layer indicated that human activities contributed to these metals contamination in the lake sediment. Sedimentation rate and metals contamination possibly due to recent anthropogenic activities around the lake such as human settlement, farming and agricultures activities since the ceased of mining activities a few decades ago. (author)

  2. Education of mining engineers with the specialization in Rescue, fire and safety technique at the BERG Faculty of the Technical University of Košice

    Directory of Open Access Journals (Sweden)

    Sedlatý Václav

    2002-12-01

    Full Text Available After the separation of Czechoslovakia, in 1993, the Mining Faculty (now BERG Faculty of the Technical University of Košice started a teaching program with the specialization in mining rescue, fire guard and safety technique at the Detachment in Prievidza, because of all the needs and conditions related to the education of engineers in the mentioned areas. During the last 10 years, the Detachment in Prievidza has been growing in terms of number of students. From the beginning of this period to present days 75 students graduated. The full-time studies last five years and the academic years are divided into two semesters of 15 weeks each. The semesters are finished by examination sessions. The first 2 years, in principle, include basic studies in mathematics, scientific subjects and some subjects related to earth sciences. The third and fourth year are generally devoted to basic technical subjects of mining and underground works, and then to rescue, fire and safety subjects. A practical work experience has to be gained by students in a mine or fire and safety stations. The practical training term is scheduled after the third academic year. During the last two semesters the students are preparing their Master’s degree thesis using a stay in the mine company or other firms to receive the necessary information and data.

  3. Mining MaNGA for Merging Galaxies: A New Imaging and Kinematic Technique from Hydrodynamical Simulations

    Science.gov (United States)

    Nevin, Becky; Comerford, Julia M.; Blecha, Laura

    2018-06-01

    Merging galaxies play a key role in galaxy evolution, and progress in our understanding of galaxy evolution is slowed by the difficulty of making accurate galaxy merger identifications. Mergers are typically identified using imaging alone, which has its limitations and biases. With the growing popularity of integral field spectroscopy (IFS), it is now possible to use kinematic signatures to improve galaxy merger identifications. I use GADGET-3 hydrodynamical simulations of merging galaxies with the radiative transfer code SUNRISE, the later of which enables me to apply the same analysis to simulations and observations. From the simulated galaxies, I have developed the first merging galaxy classification scheme that is based on kinematics and imaging. Utilizing a Linear Discriminant Analysis tool, I have determined which kinematic and imaging predictors are most useful for identifying mergers of various merger parameters (such as orientation, mass ratio, gas fraction, and merger stage). I will discuss the strengths and limitations of the classification technique and then my initial results for applying the classification to the >10,000 observed galaxies in the MaNGA (Mapping Nearby Galaxies at Apache Point) IFS survey. Through accurate identification of merging galaxies in the MaNGA survey, I will advance our understanding of supermassive black hole growth in galaxy mergers and other open questions related to galaxy evolution.

  4. Application of a Novel Liquid Nitrogen Control Technique for Heat Stress and Fire Prevention in Underground Mines.

    Science.gov (United States)

    Shi, Bobo; Ma, Lingjun; Dong, Wei; Zhou, Fubao

    2015-01-01

    With the continually increasing mining depths, heat stress and spontaneous combustion hazards in high-temperature mines are becoming increasingly severe. Mining production risks from natural hazards and exposures to hot and humid environments can cause occupational diseases and other work-related injuries. Liquid nitrogen injection, an engineering control developed to reduce heat stress and spontaneous combustion hazards in mines, was successfully utilized for environmental cooling and combustion prevention in an underground mining site named "Y120205 Working Face" (Y120205 mine) of Yangchangwan colliery. Both localized humidities and temperatures within the Y120205 mine decreased significantly with liquid nitrogen injection. The maximum percentage drop in temperature and humidity of the Y120205 mine were 21.9% and 10.8%, respectively. The liquid nitrogen injection system has the advantages of economical price, process simplicity, energy savings and emission reduction. The optimized heat exchanger used in the liquid nitrogen injection process achieved superior air-cooling results, resulting in considerable economic benefits.

  5. High-resolution, short-range, in-mine geophysical techniques for the delineation of South African orebodies

    CSIR Research Space (South Africa)

    Van Schoor, Abraham M

    2006-07-01

    Full Text Available of the respective planar orebodies is relatively easy to predict ahead of mining. On a local, in-mine scale, however, the geometry of these orebodies is far less predictable because of the presence of disruptive geological features such as faults, rolls, terraces...

  6. Mining potential biomarkers associated with space flight in Caenorhabditis elegans experienced Shenzhou-8 mission with multiple feature selection techniques

    International Nuclear Information System (INIS)

    Zhao, Lei; Gao, Ying; Mi, Dong; Sun, Yeqing

    2016-01-01

    Highlights: • A combined algorithm is proposed to mine biomarkers of spaceflight in C. elegans. • This algorithm makes the feature selection more reliable and robust. • Apply this algorithm to predict 17 positive biomarkers to space environment stress. • The strategy can be used as a general method to select important features. - Abstract: To identify the potential biomarkers associated with space flight, a combined algorithm, which integrates the feature selection techniques, was used to deal with the microarray datasets of Caenorhabditis elegans obtained in the Shenzhou-8 mission. Compared with the ground control treatment, a total of 86 differentially expressed (DE) genes in responses to space synthetic environment or space radiation environment were identified by two filter methods. And then the top 30 ranking genes were selected by the random forest algorithm. Gene Ontology annotation and functional enrichment analyses showed that these genes were mainly associated with metabolism process. Furthermore, clustering analysis showed that 17 genes among these are positive, including 9 for space synthetic environment and 8 for space radiation environment only. These genes could be used as the biomarkers to reflect the space environment stresses. In addition, we also found that microgravity is the main stress factor to change the expression patterns of biomarkers for the short-duration spaceflight.

  7. Investigation of karst collapse based on 3-D seismic technique and DDA method at Xieqiao coal mine, China

    Energy Technology Data Exchange (ETDEWEB)

    Zuo, Jian-Ping; Chen, Zhong-Hui [State Key Laboratory of Coal Resources and Safe Mining, China University of Mining and Technology, Beijing 100083 (China); Institute of Rock Mechanical and Fractals, China University of Mining and Technology, Beijing 100083 (China); Peng, Su-Ping; Li, Yong-Jun [State Key Laboratory of Coal Resources and Safe Mining, China University of Mining and Technology, Beijing 100083 (China); Xie, He-Ping [Institute of Rock Mechanical and Fractals, China University of Mining and Technology, Beijing 100083 (China)

    2009-06-01

    Karst collapse is a serious geological problem in most of the coal mines in the north of China, but recently it has been found in the south as well. The present study is aimed at investigating subsidence mechanism and deformation field of a karst collapse column at Xieqiao, in the south of China. A method of three-dimensional (3-D) seismic technique has been successful in exploring the spatial morphology of the karst collapse at Xieqiao, and the discontinuous deformation analysis (DDA) method is used to calculate the deformation field and analyze the subsidence mechanism. The results indicated that DDA could approximately simulate and back analyze the subsidence process and strata deformation fields. The subsidence processes of the collapse column depend on the sizes of the karst caves. With the continuous expansion of the karst caves, a semi-elliptic stress field, local separation strata and fracture zone will be formed around the karst cave. Moreover, they will gradually expand upwards along the vertical direction. The paper also indicates that the subsidence failure stage may trigger a sudden collapse of the karst column because of the sudden energy release. Also, it will make a great impact on the vicinity working face so as to cause a rock burst. The effects of the friction angle of rock strata on the subsidence mechanism were reported firstly based on DDA. (author)

  8. Improving the prediction of going concern of Taiwanese listed companies using a hybrid of LASSO with data mining techniques.

    Science.gov (United States)

    Goo, Yeung-Ja James; Chi, Der-Jang; Shen, Zong-De

    2016-01-01

    The purpose of this study is to establish rigorous and reliable going concern doubt (GCD) prediction models. This study first uses the least absolute shrinkage and selection operator (LASSO) to select variables and then applies data mining techniques to establish prediction models, such as neural network (NN), classification and regression tree (CART), and support vector machine (SVM). The samples of this study include 48 GCD listed companies and 124 NGCD (non-GCD) listed companies from 2002 to 2013 in the TEJ database. We conduct fivefold cross validation in order to identify the prediction accuracy. According to the empirical results, the prediction accuracy of the LASSO-NN model is 88.96 % (Type I error rate is 12.22 %; Type II error rate is 7.50 %), the prediction accuracy of the LASSO-CART model is 88.75 % (Type I error rate is 13.61 %; Type II error rate is 14.17 %), and the prediction accuracy of the LASSO-SVM model is 89.79 % (Type I error rate is 10.00 %; Type II error rate is 15.83 %).

  9. Mining potential biomarkers associated with space flight in Caenorhabditis elegans experienced Shenzhou-8 mission with multiple feature selection techniques

    Energy Technology Data Exchange (ETDEWEB)

    Zhao, Lei [Institute of Environmental Systems Biology, College of Environmental Science and Engineering, Dalian Maritime University, Dalian 116026 (China); Gao, Ying [Center of Medical Physics and Technology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Shushanhu Road 350, Hefei 230031 (China); Mi, Dong, E-mail: mid@dlmu.edu.cn [Department of Physics, Dalian Maritime University, Dalian 116026 (China); Sun, Yeqing, E-mail: yqsun@dlmu.edu.cn [Institute of Environmental Systems Biology, College of Environmental Science and Engineering, Dalian Maritime University, Dalian 116026 (China)

    2016-09-15

    Highlights: • A combined algorithm is proposed to mine biomarkers of spaceflight in C. elegans. • This algorithm makes the feature selection more reliable and robust. • Apply this algorithm to predict 17 positive biomarkers to space environment stress. • The strategy can be used as a general method to select important features. - Abstract: To identify the potential biomarkers associated with space flight, a combined algorithm, which integrates the feature selection techniques, was used to deal with the microarray datasets of Caenorhabditis elegans obtained in the Shenzhou-8 mission. Compared with the ground control treatment, a total of 86 differentially expressed (DE) genes in responses to space synthetic environment or space radiation environment were identified by two filter methods. And then the top 30 ranking genes were selected by the random forest algorithm. Gene Ontology annotation and functional enrichment analyses showed that these genes were mainly associated with metabolism process. Furthermore, clustering analysis showed that 17 genes among these are positive, including 9 for space synthetic environment and 8 for space radiation environment only. These genes could be used as the biomarkers to reflect the space environment stresses. In addition, we also found that microgravity is the main stress factor to change the expression patterns of biomarkers for the short-duration spaceflight.

  10. Adulteration detection in olive oil using dielectric technique and data mining

    Directory of Open Access Journals (Sweden)

    Mahdi Rashvand

    2016-12-01

    Full Text Available Olive oil is one of the most important agricultural crops due to its digestive properties and economic status. However, olive oil production is a costly process which causes an expensive price of the final product. The most jobbery ways during olive oil production consist of mixing other oils such as maize, sunflower and soya oil into the olive oil. So, the aim of this study was to develop a dielectric-based system to detect adulteration in olive oil using cylindrical capacitive sensor. For categorizing of fake olive oil by using frequency specification, Linear Discriminant Analysis (LDA was developed. A set of 15 samples of olive oil, sunflower oil and canola oil which mixed with different ratio of adulteration, were used for calibration and evaluation of developed system. For each sample, 25 iterations were performed. Regarding results, the highest error rate was for a sample containing 60% olive oil-40% canola oil. In general, 7 iterations failed to be properly recognized. Regarding to accuracy indexes, specificity and sensitivity, the system had the minimum error for a mixed sample (60% olive oil-40% canola oil, specificity and sensitivity were obtained as 98% and 100%, respectively and accuracy was obtained as 72%, which was the weakest value. Finally, regarding mean value table for all sample, accuracy reached to 97%. Results showed the developed technique has a good capability of detecting impurities in olive oil. It is concluded from obtained results that the developed system revealed an acceptable adulterated detection in oil production. Keywords: Olive oil, Adulteration, Dielectric properties, LDA

  11. Predicting Implantation Outcome of In Vitro Fertilization and Intracytoplasmic Sperm Injection Using Data Mining Techniques

    Directory of Open Access Journals (Sweden)

    Pegah Hafiz

    2017-09-01

    Full Text Available Background In vitro fertilization (IVF and intracytoplasmic sperm injection (ICSI are two important subsets of the assisted reproductive techniques, used for the treatment of infertility. Predicting implantation outcome of IVF/ICSI or the chance of pregnancy is essential for infertile couples, since these treatments are complex and expensive with a low probability of conception. Materials and Methods In this cross-sectional study, the data of 486 patients were collected using census method. The IVF/ICSI dataset contains 29 variables along with an identifier for each patient that is either negative or positive. Mean accuracy and mean area under the receiver operating characteristic (ROC curve are calculated for the classifiers. Sensitivity, specificity, positive and negative predictive values, and likelihood ratios of classifiers are employed as indicators of performance. The state-of-art classifiers which are candidates for this study include support vector machines, recursive partitioning (RPART, random forest (RF, adaptive boosting, and one-nearest neighbor. Results RF and RPART outperform the other comparable methods. The results revealed the areas under the ROC curve (AUC as 84.23 and 82.05%, respectively. The importance of IVF/ICSI features was extracted from the output of RPART. Our findings demonstrate that the probability of pregnancy is low for women aged above 38. Conclusion Classifiers RF and RPART are better at predicting IVF/ICSI cases compared to other decision makers that were tested in our study. Elicited decision rules of RPART determine useful predictive features of IVF/ICSI. Out of 20 factors, the age of woman, number of developed embryos, and serum estradiol level on the day of human chorionic gonadotropin administration are the three best features for such prediction.

  12. Effects of a small-scale, abandoned gold mine on the geochemistry of fine stream-bed and floodplain sediments in the Horsefly River watershed, British Columbia, Canada

    NARCIS (Netherlands)

    Clark, Deirdre E.; Vogels, Marjolein; van der Perk, Marcel; Owens, Philip N.; Petticrew, Ellen L.

    2014-01-01

    Mining is known to be a major source of metal contamination for fluvial systems worldwide. Monitoring and understanding the effects on downstream water and sediment quality is essential for its management and to mitigate against detrimental environmental impacts. This study aimed to examine the

  13. Techniques for detecting effects of urban and rural land-use practices on stream-water chemistry in selected watersheds in Texas, Minnesota,and Illinois

    Science.gov (United States)

    Walker, J.F.

    1993-01-01

    Although considerable effort has been expended during the past two decades to control nonpoint-source contamination of streams and lakes in urban and rural watersheds, little has been published on the effectiveness of various management practices at the watershed scale. This report presents a discussion of several parametric and nonparametric statistical techniques for detecting changes in water-chemistry data. The need for reducing the influence of natural variability was recognized and accomplished through the use of regression equations. Traditional analyses have focused on fixed-frequency instantaneous concentration data; this report describes the use of storm load data as an alternative.

  14. Methods for assessing mine site rehabilitation design for erosion impact

    International Nuclear Information System (INIS)

    Evans, K. G.

    2000-01-01

    Erosion of rehabilitated mines may result in landform instability, which in turn may result in exposure of encapsulated contaminants, elevated sediment delivery at catchment outlets, and subsequent degradation of downstream water quality. Rehabilitation design can be assessed using erosion and hydrology models calibrated to mine site conditions. Incision rates in containment structures can be quantified using 3-dimensional landform evolution simulation techniques. Sediment delivery at catchment outlets for various landform amelioration techniques can be predicted using process-based and empirical erosion-prediction models and sediment delivery ratios. The predicted sediment delivery can be used to estimate an average annual stream sediment load that can, in turn, be used to assess water quality impacts. Application of these techniques is demonstrated through a case study applied to a proposed rehabilitation design option for the Energy Resources of Australia Ltd (ERA) Ranger Mine in the Northern Territory of Australia. Copyright (2000) CSIRO Australia

  15. Streams with Strahler Stream Order

    Data.gov (United States)

    Minnesota Department of Natural Resources — Stream segments with Strahler stream order values assigned. As of 01/08/08 the linework is from the DNR24K stream coverages and will not match the updated...

  16. Comparison of groundwater recharge estimation techniques in an alluvial aquifer system with an intermittent/ephemeral stream (Queensland, Australia)

    Science.gov (United States)

    King, Adam C.; Raiber, Matthias; Cox, Malcolm E.; Cendón, Dioni I.

    2017-09-01

    This study demonstrates the importance of the conceptual hydrogeological model for the estimation of groundwater recharge rates in an alluvial system interconnected with an ephemeral or intermittent stream in south-east Queensland, Australia. The losing/gaining condition of these streams is typically subject to temporal and spatial variability, and knowledge of these hydrological processes is critical for the interpretation of recharge estimates. Recharge rate estimates of 76-182 mm/year were determined using the water budget method. The water budget method provides useful broad approximations of recharge and discharge fluxes. The chloride mass balance (CMB) method and the tritium method were used on 17 and 13 sites respectively, yielding recharge rates of 1-43 mm/year (CMB) and 4-553 mm/year (tritium method). However, the conceptual hydrogeological model confirms that the results from the CMB method at some sites are not applicable in this setting because of overland flow and channel leakage. The tritium method was appropriate here and could be applied to other alluvial systems, provided that channel leakage and diffuse infiltration of rainfall can be accurately estimated. The water-table fluctuation (WTF) method was also applied to data from 16 bores; recharge estimates ranged from 0 to 721 mm/year. The WTF method was not suitable where bank storage processes occurred.

  17. Process for integrating surface drainage constraints on mine planning

    Energy Technology Data Exchange (ETDEWEB)

    Sawatsky, L.F; Ade, F.L.; McDonald, D.M.; Pullman, B.J. [Golder Associates Ltd., Calgary, AB (Canada)

    2009-07-01

    Surface drainage for mine closures must be considered during all phases of mine planning and design in order to minimize environmental impacts and reduce costs. This paper discussed methods of integrating mine drainage criteria and associated mine planning constraints into the mine planning process. Drainage constraints included stream diversions; fish compensation channels; collection receptacles for the re-use of process water; separation of closed circuit water from fresh water; and the provision of storage ponds. The geomorphic approach replicated the ability of natural channels to respond to local and regional changes in hydrology as well as channel disturbances from extreme flood events, sedimentation, debris, ice jams, and beaver activity. The approach was designed to enable a sustainable system and provide conveyance capacity for extreme floods without spillage to adjacent watersheds. Channel dimensions, bank and bed materials, sediment loads, bed material supplies and the hydrologic conditions of the analogue stream were considered. Hydrologic analyses were conducted to determine design flood flow. Channel routes, valley slopes, sinuosity, width, and depth were established. It was concluded that by incorporating the geomorphic technique, mine operators and designers can construct self-sustaining drainage systems that require little or no maintenance in the long-term. 7 refs.

  18. Pocket data mining big data on small devices

    CERN Document Server

    Gaber, Mohamed Medhat; Gomes, Joao Bartolo

    2014-01-01

    Owing to continuous advances in the computational power of handheld devices like smartphones and tablet computers, it has become possible to perform Big Data operations including modern data mining processes onboard these small devices. A decade of research has proved the feasibility of what has been termed as Mobile Data Mining, with a focus on one mobile device running data mining processes. However, it is not before 2010 until the authors of this book initiated the Pocket Data Mining (PDM) project exploiting the seamless communication among handheld devices performing data analysis tasks that were infeasible until recently. PDM is the process of collaboratively extracting knowledge from distributed data streams in a mobile computing environment. This book provides the reader with an in-depth treatment on this emerging area of research. Details of techniques used and thorough experimental studies are given. More importantly and exclusive to this book, the authors provide detailed practical guide on the depl...

  19. Data mining in Cloud Computing

    Directory of Open Access Journals (Sweden)

    Ruxandra-Ştefania PETRE

    2012-10-01

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

  20. An in vitro comparison of irrigation using photon-initiated photoacoustic streaming, ultrasonic, sonic and needle techniques in removing calcium hydroxide.

    Science.gov (United States)

    Arslan, H; Akcay, M; Capar, I D; Saygili, G; Gok, T; Ertas, H

    2015-03-01

    To evaluate the effect of various techniques including photon-initiated photoacoustic streaming (PIPS), ultrasonic, sonic and needle irrigation on the removal of calcium hydroxide [Ca(OH)2 ] from artificial grooves created in root canals. The root canals of 48 extracted single-rooted teeth with straight canals were prepared using ProTaper rotary instruments up to size 40. After the specimens had been split longitudinally, a standardized groove was prepared in the apical part of one segment that was filled with Ca(OH)2 powder mixed with distilled water. Each tooth was reassembled and the apices closed with wax. The specimens were irrigated for 60 s with one of the following techniques: needle irrigation using 17% EDTA, PIPS with 17% EDTA, ultrasonic irrigation using 17% EDTA and sonic irrigation (EndoActivator) using 17% EDTA. The root segments were then disassembled, and the amount of remaining Ca(OH)2 evaluated under a stereomicroscope at 25× magnification. A pixel count of Ca(OH)2 remaining on the artificially created grooves was recorded as a percentage of the overall groove surface. The data were evaluated statistically using one-way analysis of variance and the least significant difference post hoc tests at 95% confidence level (P = 0.05). Photon-initiated photoacoustic streaming was superior in removing Ca(OH)2 as compared to needle irrigation (P streaming provided complete removal of Ca(OH)2 from artificial grooves in straight root canals. Ultrasonic irrigation enhanced the Ca(OH)2 removal capacity of irrigating solution but did not provide complete removal from artificial grooves. © 2014 International Endodontic Journal. Published by John Wiley & Sons Ltd.

  1. Mining Upgrades to Reduce Pollution

    Science.gov (United States)

    Settlement with Southern Coal Corporation and 26 affiliates requires the companies to comprehensively upgrade their coal mining and processing operations to prevent polluted wastewater from threatening rivers and streams and communities across Appalachia.

  2. Distribution of chemical elements in soils and stream sediments in the area of abandoned Sb–As–Tl Allchar mine, Republic of Macedonia

    Energy Technology Data Exchange (ETDEWEB)

    Bačeva, Katerina [Institute of Chemistry, Faculty of Natural Sciences and Mathematics, Ss. Cyril and Methodius University, POB 162, 1000 Skopje (Macedonia, The Former Yugoslav Republic of); Stafilov, Trajče, E-mail: trajcest@pmf.ukim.mk [Institute of Chemistry, Faculty of Natural Sciences and Mathematics, Ss. Cyril and Methodius University, POB 162, 1000 Skopje (Macedonia, The Former Yugoslav Republic of); Šajn, Robert [Geological Survey of Slovenia, Ljubljana (Slovenia); Tănăselia, Claudiu [INCDO-INOE 2000 Research Institute for Analytical Instrumentation (ICIA), Cluj-Napoca (Romania); Makreski, Petre [Institute of Chemistry, Faculty of Natural Sciences and Mathematics, Ss. Cyril and Methodius University, POB 162, 1000 Skopje (Macedonia, The Former Yugoslav Republic of)

    2014-08-15

    The aim of this study was to investigate the distribution of some toxic elements in topsoil and subsoil, focusing on the identification of natural and anthropogenic element sources in the small region of rare As–Sb–Tl mineralization outcrop and abandoned mine Allchar known for the highest natural concentration of Tl in soil worldwide. The samples of soil and sediments after total digestion were analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and inductively coupled plasma–atomic emission spectrometry (ICP–AES). Factor analysis (FA) was used to identify and characterize element associations. Six associations of elements were determined by the method of multivariate statistics: Rb–Ta–K–Nb–Ga–Sn–Ba–Bi–Li–Be–(La–Eu)–Hf–Zr–Zn–In–Pd–Ag–Pt–Mg; Tl–As–Sb–Hg; Te–S–Ag–Pt–Al–Sc–(Gd–Lu)–Y; Fe–Cu–V–Ge–Co–In; Pd–Zr–Hf–W–Be and Ni–Mn–Co–Cr–Mg. The purpose of the assessment was to determine the nature and extent of potential contamination as well as to broadly assess possible impacts to human health and the environment. The results from the analysis of the collected samples in the vicinity of the mine revealed that As and Tl elements have the highest median values. Higher median values for Sb are obviously as a result of the past mining activities and as a result of area surface phenomena in the past. - Highlights: • Soil and river sediments were analyzed from Sb–As–Tl Allchar locality. • An increased content of certain toxic elements for environment was determined. • Highest As and Tl contents are obtained in the close vicinity of Allchar mine. • River sediments portray 160 times higher content of Sb than EU values. • The results classify Allchar as probably the highest natural Tl-deposit worldwide.

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

    Science.gov (United States)

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

    2018-01-01

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

  4. Using value stream mapping technique through the lean production transformation process: An implementation in a large-scaled tractor company

    Directory of Open Access Journals (Sweden)

    Mehmet Rıza Adalı

    2017-04-01

    Full Text Available Today’s world, manufacturing industries have to continue their development and continuity in more competitive environment via decreasing their costs. As a first step in the lean production process transformation is to analyze the value added activities and non-value adding activities. This study aims at applying the concepts of Value Stream Mapping (VSM in a large-scaled tractor company in Sakarya. Waste and process time are identified by mapping the current state in the production line of platform. The future state was suggested with improvements for elimination of waste and reduction of lead time, which went from 13,08 to 4,35 days. Analysis are made using current and future states to support the suggested improvements and cycle time of the production line of platform is improved 8%. Results showed that VSM is a good alternative in the decision-making for change in production process.

  5. Concentrations of cadmium, Cobalt, Lead, Nickel, and Zinc in Blood and Fillets of Northern Hog Sucker (Hypentelium nigricans) from streams contaminated by lead-Zinc mining: Implications for monitoring

    Science.gov (United States)

    Schmitt, C.J.; Brumbaugh, W.G.; May, T.W.

    2009-01-01

    Lead (Pb) and other metals can accumulate in northern hog sucker (Hypentelium nigricans) and other suckers (Catostomidae), which are harvested in large numbers from Ozark streams by recreational fishers. Suckers are also important in the diets of piscivorous wildlife and fishes. Suckers from streams contaminated by historic Pb-zinc (Zn) mining in southeastern Missouri are presently identified in a consumption advisory because of Pb concentrations. We evaluated blood sampling as a potentially nonlethal alternative to fillet sampling for Pb and other metals in northern hog sucker. Scaled, skin-on, bone-in "fillet" and blood samples were obtained from northern hog suckers (n = 75) collected at nine sites representing a wide range of conditions relative to Pb-Zn mining in southeastern Missouri. All samples were analyzed for cadmium (Cd), cobalt (Co), Pb, nickel (Ni), and Zn. Fillets were also analyzed for calcium as an indicator of the amount of bone, skin, and mucus included in the samples. Pb, Cd, Co, and Ni concentrations were typically higher in blood than in fillets, but Zn concentrations were similar in both sample types. Concentrations of all metals except Zn were typically higher at sites located downstream from active and historic Pb-Zn mines and related facilities than at nonmining sites. Blood concentrations of Pb, Cd, and Co were highly correlated with corresponding fillet concentrations; log-log linear regressions between concentrations in the two sample types explained 94% of the variation for Pb, 73-83% of the variation for Co, and 61% of the variation for Cd. In contrast, relations for Ni and Zn explained Fillet Pb and calcium concentrations were correlated (r = 0.83), but only in the 12 fish from the most contaminated site; concentrations were not significantly correlated across all sites. Conversely, fillet Cd and calcium were correlated across the range of sites (r = 0.78), and the inclusion of calcium in the fillet-to-blood relation explained an

  6. Simulation techniques of medium or small sized coal mining; Sistema de simulacion de labores de minas subterraneas de carbon de tamano mediano o pequeno

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1998-12-01

    Usually an underground mining company designs new production systems in order to reach higher productivity levels, but there is always some uncertainty about reaching the planned figures. This research project, so called Project SimCAR, applies to medium or small sized coal mining companies and tries to become a powerful tool in helping technical staff to answer questions about how future systems will behave. The project`s paradigm is to use computer simulation techniques in order to diminish the implicit uncertainty associated to coal mining activities. As a result, this implies to obtain the best possible scenarios for real economic investments in mine planning. The final programs we have built help technical staff to: 1. Study existing systems in depth. The precision of the resulting model exclusively depends on the correctness of input data and a perfect understanding of the system`s logic processes. 2. Perform several changes on the input system variables over the simulated models in order to allow the technical staff to know the system will react under several conditions. 3. Introduce new strategies on the model construction in order to get a complete optimization under productive and economic viewpoints. (Author)

  7. The Application of Borehole Seismic Techniques in Mine Development at the Millennium Uranium Deposit, Northern Saskatchewan, Canada

    Energy Technology Data Exchange (ETDEWEB)

    Wood, G.; O’Dowd, C., E-mail: garnet_wood@cameco.com [Cameco Corporation, Saskatoon, Saskatchewan (Canada); Cosma, C.; Enescu, N. [Vibrometric Canada Ltd., Toronto, Ontario (Canada)

    2014-05-15

    The Millennium uranium deposit is located within the Athabasca Basin of northern Saskatchewan, Canada. The deposit is situated in metasedimentary rocks, is controlled by multiple sub-vertical faults, and crossfaults and is overlain by over 500 m of intensely altered, porous Manitou Falls group sandstones. The rock quality directly surrounding the deposit is greatly reduced because of alteration and post-Athabasca sandstone structures, which provide conduits for the migration of basinal and meteoric fluids. This leads to significant risk for mine development and shaft sinking, because of the increased potential for water inflow into mine workings. To mitigate the risk involved with mining in such complex geology several projects were proposed as part of a pre-feasibility study. Of these, seismic methods were identified as the best tool to potentially identify alteration and structurally compromised zones. Subsequently, a comprehensive surface and borehole seismic program was completed in an attempt to delineate these engineering hazards and to provide assurance of success of the shaft sinking and mine development. This was the first time a seismic program of this scale was undertaken for geotechnical studies during mine development in the Athabasca Basin. (author)

  8. 3D RECONSTRUCTION AND MODELING OF SUBTERRANEAN LANDSCAPES IN COLLABORATIVE MINING ARCHEOLOGY PROJECTS: TECHNIQUES, APPLICATIONS AND EXPERIENCES

    Directory of Open Access Journals (Sweden)

    A. Arles

    2013-07-01

    Full Text Available Mining and underground archaeology are two domains of expertise where three-dimensional data take an important part in the associated researches. Up to now, archaeologists study mines and underground networks from line-plot surveys, cross-section of galleries, and from tool marks surveys. All this kind of information can be clearly recorded back from the field from threedimensional models with a more cautious and extensive approach. Besides, the volumes of the underground structures that are very important data to explain the mining activities are difficult to evaluate from "traditional" hand-made recordings. They can now be calculated more accurately from a 3D model. Finally, reconstructed scenes are a powerful tool as thinking aid to look back again to a structure in the office or in future times. And the recorded models, rendered photo-realistically, can also be used for cultural heritage documentation presenting inaccessible and sometimes dangerous places to the public. Nowadays, thanks to modern computer technologies and highly developed software tools paired with sophisticated digital camera equipment, complex photogrammetric processes are available for moderate costs for research teams. Recognizing these advantages the authors develop and utilize image-based workflows in order to document ancient mining monuments and underground sites as a basis for further historical and archaeological researches, performed in collaborative partnership during recent projects on medieval silver mines and preventive excavations of undergrounds in France.

  9. Non-destructive analysis of sensory traits of dry-cured loins by MRI-computer vision techniques and data mining.

    Science.gov (United States)

    Caballero, Daniel; Antequera, Teresa; Caro, Andrés; Ávila, María Del Mar; G Rodríguez, Pablo; Perez-Palacios, Trinidad

    2017-07-01

    Magnetic resonance imaging (MRI) combined with computer vision techniques have been proposed as an alternative or complementary technique to determine the quality parameters of food in a non-destructive way. The aim of this work was to analyze the sensory attributes of dry-cured loins using this technique. For that, different MRI acquisition sequences (spin echo, gradient echo and turbo 3D), algorithms for MRI analysis (GLCM, NGLDM, GLRLM and GLCM-NGLDM-GLRLM) and predictive data mining techniques (multiple linear regression and isotonic regression) were tested. The correlation coefficient (R) and mean absolute error (MAE) were used to validate the prediction results. The combination of spin echo, GLCM and isotonic regression produced the most accurate results. In addition, the MRI data from dry-cured loins seems to be more suitable than the data from fresh loins. The application of predictive data mining techniques on computational texture features from the MRI data of loins enables the determination of the sensory traits of dry-cured loins in a non-destructive way. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

  10. KDE-Track: An Efficient Dynamic Density Estimator for Data Streams

    KAUST Repository

    Qahtan, Abdulhakim Ali Ali; Wang, Suojin; Zhang, Xiangliang

    2016-01-01

    Recent developments in sensors, global positioning system devices and smart phones have increased the availability of spatiotemporal data streams. Developing models for mining such streams is challenged by the huge amount of data that cannot be stored in the memory, the high arrival speed and the dynamic changes in the data distribution. Density estimation is an important technique in stream mining for a wide variety of applications. The construction of kernel density estimators is well studied and documented. However, existing techniques are either expensive or inaccurate and unable to capture the changes in the data distribution. In this paper, we present a method called KDE-Track to estimate the density of spatiotemporal data streams. KDE-Track can efficiently estimate the density function with linear time complexity using interpolation on a kernel model, which is incrementally updated upon the arrival of new samples from the stream. We also propose an accurate and efficient method for selecting the bandwidth value for the kernel density estimator, which increases its accuracy significantly. Both theoretical analysis and experimental validation show that KDE-Track outperforms a set of baseline methods on the estimation accuracy and computing time of complex density structures in data streams.

  11. KDE-Track: An Efficient Dynamic Density Estimator for Data Streams

    KAUST Repository

    Qahtan, Abdulhakim Ali Ali

    2016-11-08

    Recent developments in sensors, global positioning system devices and smart phones have increased the availability of spatiotemporal data streams. Developing models for mining such streams is challenged by the huge amount of data that cannot be stored in the memory, the high arrival speed and the dynamic changes in the data distribution. Density estimation is an important technique in stream mining for a wide variety of applications. The construction of kernel density estimators is well studied and documented. However, existing techniques are either expensive or inaccurate and unable to capture the changes in the data distribution. In this paper, we present a method called KDE-Track to estimate the density of spatiotemporal data streams. KDE-Track can efficiently estimate the density function with linear time complexity using interpolation on a kernel model, which is incrementally updated upon the arrival of new samples from the stream. We also propose an accurate and efficient method for selecting the bandwidth value for the kernel density estimator, which increases its accuracy significantly. Both theoretical analysis and experimental validation show that KDE-Track outperforms a set of baseline methods on the estimation accuracy and computing time of complex density structures in data streams.

  12. Innovations in uranium exploration, mining and processing techniques, and new exploration target areas. Proceedings of a technical committee meeting held in Vienna, 5-8 December 1994

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1996-03-01

    In 1994 there were 432 nuclear power plants in operation with a combined electricity generating capacity of 340 347 MWe. To achieve this, 58,000 tonnes of uranium were required as nuclear fuel. In view of its economic importance, the International Atomic Energy Agency has had a long-standing interest in uranium exploration, resources, production and demand. This is reflected in numerous publications covering different aspects of this field. Particularly worth mentioning is the periodical ``Uranium Resources, Production and Demand``, published jointly with the Nuclear Energy Agency of the OECD. Its fourteenth edition was published in early 1994. It was the objective of this Technical Committee meeting, the proceedings of which are presented in this TECDOC, to bring together specialists in the field and to collect information on new developments in exploration, mining techniques and innovative methods of processing that are more environmentally friendly. The meeting was attended by a total of 22 participants from 14 countries. Eleven papers were presented describing new exploration areas, improvements in processing methods, new mining techniques for the extraction of high grade ore, and innovative approaches for site reclamation. Two working groups were organized and dealt with the analysis of world uranium resources and the new direction of research in mining and ore processing. Refs, figs, tabs.

  13. Atmospheric pollution with copper around the copper mine and flotation, 'Buchim', Republic of Macedonia, using biomonitoring moss and lichen technique

    International Nuclear Information System (INIS)

    Balabanova, Biljana; Bacheva, Katerina; Shajn, Robert; Stafilov, Trajche

    2009-01-01

    This paper has studied the atmospheric pollution with copper due to copper mining and flotation 'Buchim' near Radovish, Republic of Macedonia. The copper ore and ore tailings continually are exposed to open air, which occur winds carry out the fine particles in to atmosphere. Moss (Hyloconium splendens and Pleurozium schrebery) and lichen (Hypogymnia physodes and Parmelia sulcata) samples were used for biomonitoring the possible atmospheric pollution with copper in the mine vicinity. Moss and lichen samples were digested by using of microwave digestion system and copper was analyzed by atomic emission spectrometry with inductively coupled plasma (ICPAES). The obtained values for the content of copper in moss and lichen samples were statistically processed using the nonparametric and parametric analysis. Maps of areal deposition of copper show an increase content of copper in the vicinity of mine, but long distance distribution of this element is not established yet.

  14. Isolation and identification of Salmonella spp. in drinking water, streams, and swine wastewater by molecular techniques in Taiwan

    Science.gov (United States)

    Kuo, C.; Hsu, B.; Shen, T.; Tseng, S.; Tsai, J.; Huang, K.; Kao, P.; Chen, J.

    2013-12-01

    Salmonella spp. is a common water-borne pathogens and its genus comprises more than 2,500 serotypes. Major pathogenic genotypes which cause typhoid fever, enteritis and other intestinal-type diseases are S. Typhimurium, S. Enteritidis, S. Stanley, S. Agona, S.Albany, S. Schwarzengrund, S. Newport, S. Choleraesuis, and S. Derby. Hence, the identification of the serotypes of Salmonella spp. is important. In the present study, the analytical procedures include direct concentration method, non-selective pre-enrichment method and selective enrichment method of Salmonella spp.. Both selective enrichment method and cultured bacteria were detected with specific primers of Salmonella spp. by polymerase chain reaction (PCR). At last, the serotypes of Salmonella were confirmed by using MLST (multilocus sequence typing) with aroC, dnaN, hemD, hisD, purE, sucA, thrA housekeeping genes to identify the strains of positive samples. This study contains 121 samples from three different types of water sources including the drinking water (51), streams (45), and swine wastewater (25). Thirteen samples with positive invA gene are separated from culture method. The strains of these positive samples which identified from MLST method are S. Albany, S. Typhimurium, S. Newport, S. Bareilly, and S. Derby. Some of the serotypes, S. Albany, S. Typhimurium and S. Newport, are highly pathogenic which correlated to human diarrhea. In our results, MLST is a useful method to identify the strains of Salmonella spp.. Keywords: Salmonella, PCR, MLST.

  15. Reduce of adherence problems in galvanised processes through data mining techniques; Reducciond e problemas de adherencia en procesos de galvanizado mediante tecnicas de mineria de datos

    Energy Technology Data Exchange (ETDEWEB)

    Martinez de Pison, F. J.; Ordieres, J.; Pernia, A.; Alba, F.; Torre, V.

    2007-07-01

    This paper presents an example of the application of data mining techniques to obtain hidden knowledge from the historical data of a hot dip galvanizing process and to establish rules to improve quality in the final product and to reduce errors in the process. For this purpose, the tuning records of a hot dip galvanizing line where coils with adherence problems in the zinc coating had been identified were used as starting point. From the database of the process, the classical data mining approach was applied to obtain and analyze a number of decision trees hat classified two types of coils, i.e. those with the right adherence and those with irregular adherence. The variables and values that might have influenced the quality of the coating were extracted from these tress. Several rules that may be applied to reduce the number of faulty coils with adherence problems were also established. (Author) 24 refs.

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

    Science.gov (United States)

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

    2018-01-01

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

  17. Radiation shielding techniques and applications. 4. Two-Phase Monte Carlo Approach to Photon Streaming Through Three-Legged Penetrations

    International Nuclear Information System (INIS)

    White, Travis; Hack, Joe; Nathan, Steve; Barnett, Marvin

    2001-01-01

    Westinghouse Safety Management Solutions (Westinghouse SMS) has been tasked with providing radiological engineering design support for the new Commercial Light Water Reactor Tritium Extraction Facility (CLWR-TEF) being constructed at the Savannah River Site. The Remote Handling Building (RHB) of the CLWR-TEF will act as the receiving facility for irradiated targets used in the production of tritium for the U.S. Department of Energy (DOE). Because of the high dose rates, approaching 50 000 rads/h (500 Gy/h) from the irradiated target bundles, significant attention has been made to shielding structures within the facility. One aspect of the design that has undergone intense review is the issue of the penetrations through the shield walls of the RHB, which includes heating, ventilation, and air-conditioning ductwork; cylindrical piping penetrations; floor drains; and conduit penetrations. The 'DOE Design Considerations Handbook' suggests that 'straight-line penetration of shield walls should be avoided to prevent radiation streaming', which is a prudent suggestion in this case considering the strength of the source. Therefore, a three-legged penetration approach was adopted for each type of penetration. To incorporate the three-legged penetration approach into the design, certain parameters had to be determined and confirmed as adequate. The main parameter to be determined was a minimum required offset length of the middle leg of the penetration. Additional parameters to be determined were supplemental photon shielding to be added to the interior of the wall to compensate for the void in the concrete created by the penetration, and the minimum necessary overlap dimensions of the supplemental shielding. Further, in cases where the minimum middle-leg offset was not practical, additional shielding requirements were determined for supplemental shielding added to the entrance or exit of the penetration to attenuate radiation scattering down the penetration. Analytical

  18. Detection of breast cancer using advanced techniques of data mining with neural networks; Deteccion de cancer de mama usando tecnicas avanzadas de mineria de datos con redes neuronales

    Energy Technology Data Exchange (ETDEWEB)

    Ortiz M, J. A.; Celaya P, J. M.; Martinez B, M. R.; Solis S, L. O.; Castaneda M, R.; Garza V, I.; Martinez F, M.; Lopez H, Y.; Ortiz R, J. M. [Universidad Autonoma de Zacatecas, Av. Ramon Lopez Velarde 801, Col. Centro, 98000 Zacatecas, Zac. (Mexico)

    2016-10-15

    The breast cancer is one of the biggest health problems worldwide, is the most diagnosed cancer in women and prevention seems impossible since its cause is unknown, due to this; the early detection has a key role in the patient prognosis. In developing countries such as Mexico, where access to specialized health services is minimal, the regular clinical review is infrequent and there are not enough radiologists; the most common form of detection of breast cancer is through self-exploration, but this is only detected in later stages, when is already palpable. For these reasons, the objective of the present work is the creation of a system of computer assisted diagnosis (CAD x) using information analysis techniques such as data mining and advanced techniques of artificial intelligence, seeking to offer a previous medical diagnosis or a second opinion, as if it was a second radiologist in order to reduce the rate of mortality from breast cancer. In this paper, advances in the design of computational algorithms using computer vision techniques for the extraction of features derived from mammograms are presented. Using data mining techniques of data mining is possible to identify patients with a high risk of breast cancer. With the information obtained from the mammography analysis, the objective in the next stage will be to establish a methodology for the generation of imaging bio-markers to establish a breast cancer risk index for Mexican patients. In this first stage we present results of the classification of patients with high and low risk of suffering from breast cancer using neural networks. (Author)

  19. CAMS: OLAPing Multidimensional Data Streams Efficiently

    Science.gov (United States)

    Cuzzocrea, Alfredo

    In the context of data stream research, taming the multidimensionality of real-life data streams in order to efficiently support OLAP analysis/mining tasks is a critical challenge. Inspired by this fundamental motivation, in this paper we introduce CAMS (C ube-based A cquisition model for M ultidimensional S treams), a model for efficiently OLAPing multidimensional data streams. CAMS combines a set of data stream processing methodologies, namely (i) the OLAP dimension flattening process, which allows us to obtain dimensionality reduction of multidimensional data streams, and (ii) the OLAP stream aggregation scheme, which aggregates data stream readings according to an OLAP-hierarchy-based membership approach. We complete our analytical contribution by means of experimental assessment and analysis of both the efficiency and the scalability of OLAPing capabilities of CAMS on synthetic multidimensional data streams. Both analytical and experimental results clearly connote CAMS as an enabling component for next-generation Data Stream Management Systems.

  20. Using Data Mining Techniques Examination of the Middle School Students' Attitude towards Mathematics in the Context of Some Variables

    Science.gov (United States)

    Idil, Feriha Hande; Narli, Serkan; Aksoy, Esra

    2016-01-01

    The aim of this study is to examine middle school students' attitude towards mathematics in the context of their mathematic learning preferences using data mining which is data analysis methodology that has been successfully used in different areas including educational domains. "How do I actually learn?" questionnaire and attitude scale…

  1. Delineation of large localized damage structures forming ahead of an active mining front by using advanced acoustic emission mapping techniques

    CSIR Research Space (South Africa)

    Moriya, H

    2015-10-01

    Full Text Available northward at 1 km depth in the Cooke 4 Gold Mine in South Africa. They first applied joint hypocenter determination (JHD) to improve absolute locations, and then applied the double-difference relative location algorithm to the JHD output. These steps...

  2. Stream Crossings

    Data.gov (United States)

    Vermont Center for Geographic Information — Physical measurements and attributes of stream crossing structures and adjacent stream reaches which are used to provide a relative rating of aquatic organism...

  3. Security Measures in Data Mining

    OpenAIRE

    Anish Gupta; Vimal Bibhu; Rashid Hussain

    2012-01-01

    Data mining is a technique to dig the data from the large databases for analysis and executive decision making. Security aspect is one of the measure requirement for data mining applications. In this paper we present security requirement measures for the data mining. We summarize the requirements of security for data mining in tabular format. The summarization is performed by the requirements with different aspects of security measure of data mining. The performances and outcomes are determin...

  4. Studies in frequent tree mining

    NARCIS (Netherlands)

    Knijf, De J.

    2008-01-01

    Employing Data mining techniques for structured data is particularly challenging, because it is commonly assumed that the structure of the data encodes part of its semantics. As a result are classical data mining techniques insufficient to analyze and mine these data. In this thesis we develop

  5. Sampling and monitoring for the mine life cycle

    Science.gov (United States)

    McLemore, Virginia T.; Smith, Kathleen S.; Russell, Carol C.

    2014-01-01

    Sampling and Monitoring for the Mine Life Cycle provides an overview of sampling for environmental purposes and monitoring of environmentally relevant variables at mining sites. It focuses on environmental sampling and monitoring of surface water, and also considers groundwater, process water streams, rock, soil, and other media including air and biological organisms. The handbook includes an appendix of technical summaries written by subject-matter experts that describe field measurements, collection methods, and analytical techniques and procedures relevant to environmental sampling and monitoring.The sixth of a series of handbooks on technologies for management of metal mine and metallurgical process drainage, this handbook supplements and enhances current literature and provides an awareness of the critical components and complexities involved in environmental sampling and monitoring at the mine site. It differs from most information sources by providing an approach to address all types of mining influenced water and other sampling media throughout the mine life cycle.Sampling and Monitoring for the Mine Life Cycle is organized into a main text and six appendices that are an integral part of the handbook. Sidebars and illustrations are included to provide additional detail about important concepts, to present examples and brief case studies, and to suggest resources for further information. Extensive references are included.

  6. Event metadata records as a testbed for scalable data mining

    International Nuclear Information System (INIS)

    Gemmeren, P van; Malon, D

    2010-01-01

    At a data rate of 200 hertz, event metadata records ('TAGs,' in ATLAS parlance) provide fertile grounds for development and evaluation of tools for scalable data mining. It is easy, of course, to apply HEP-specific selection or classification rules to event records and to label such an exercise 'data mining,' but our interest is different. Advanced statistical methods and tools such as classification, association rule mining, and cluster analysis are common outside the high energy physics community. These tools can prove useful, not for discovery physics, but for learning about our data, our detector, and our software. A fixed and relatively simple schema makes TAG export to other storage technologies such as HDF5 straightforward. This simplifies the task of exploiting very-large-scale parallel platforms such as Argonne National Laboratory's BlueGene/P, currently the largest supercomputer in the world for open science, in the development of scalable tools for data mining. Using a domain-neutral scientific data format may also enable us to take advantage of existing data mining components from other communities. There is, further, a substantial literature on the topic of one-pass algorithms and stream mining techniques, and such tools may be inserted naturally at various points in the event data processing and distribution chain. This paper describes early experience with event metadata records from ATLAS simulation and commissioning as a testbed for scalable data mining tool development and evaluation.

  7. Akamai Streaming

    OpenAIRE

    ECT Team, Purdue

    2007-01-01

    Akamai offers world-class streaming media services that enable Internet content providers and enterprises to succeed in today's Web-centric marketplace. They deliver live event Webcasts (complete with video production, encoding, and signal acquisition services), streaming media on demand, 24/7 Webcasts and a variety of streaming application services based upon their EdgeAdvantage.

  8. VALUING ACID MINE DRAINAGE REMEDIATION OF IMPAIRED WATERWAYS IN WEST VIRGINIA: A HEDONIC MODELING APPROACH

    Science.gov (United States)

    States with active and abandoned mines face large private and public costs to remediate damage to streams and rivers from acid mine drainage (AMD), the metal rich runoff flowing primarily from abandoned mines and surface deposits of mine waste. AMD can lower stream and river pH ...

  9. Heavy metal contamination in stream water and sediments of gold ...

    African Journals Online (AJOL)

    This study assessed the seasonal variation in heavy metal contamination of stream water and sediments in the gold mining area of Atakunmosa West local Government, Osun State, Nigeria. Twelve villages of prominence in illegal gold mining were selected for the study covering dry and wet seasons of 2012. Stream water ...

  10. Inertisation and mine fire simulation using computer software

    Energy Technology Data Exchange (ETDEWEB)

    Stewart Gillies; Hsin Wei Wu [Gillies Wu Mining Technology (Australia)

    2007-05-15

    Inertisation is a technique used to enhance the safety of underground coal mine areas either to avoid the potential for a combustion event or to stabilise a situation after an ignition, fire or heating. The primary objective of the study was to review coal mine inertisation in Australia, in particular, to focus on the use of the Polish mine fire simulation software 'VENTGRAPH' to gain better understanding of how inertisation (GAG, Mineshield, Nitrogen Pressure Swing Adsorption (Floxal) and Tomlinson Boiler) units interact with the complex ventilation behaviour underground during a substantial fire. Most emphasis has been given to understanding the behaviour of the GAG unit because of its high capacity output. Critical aspects targeted for examination include location of the unit for high priority fire positions, size of borehole or pipe range required, time required for inertisation output to interact with and extinguish a fire, effects of seam gases on fire behaviour with inertisation present and main fan management. The project aims to increase understanding of behaviour of mine fires in modern mine ventilation networks with the addition of inert gas streams. A second aim of the project has been to take findings from the simulation exercises and develop inertisation related modifications to the program in conjunction with the Polish program authors. Exercises based on Oaky North and Oaky No 1 mines have involved 'evaluation or auditing' of ability to deliver inert gases generated from GAG units to high priority underground fire locations. These exercises have been built around modelling of fire scenarios across the mine layouts. The fire simulation exercises at Oaky North and Oaky No 1 mines demonstrated that it is possible to efficiently evaluate possible inertisation strategies appropriate to a complex mine layout extracting a gassy seam and determine which approach strategy (if any) can be used to stabilise a mine in a timely fashion.

  11. Control technique of spontaneous combustion in fully mechan ized stope during period of end caving under complex mining influence

    Science.gov (United States)

    Yuan, Benqing

    2018-01-01

    In view of the phenomenon of spontaneous combustion of coal seam occurring during the period of end caving under complex mining conditions, taking the 1116 (3) stope of Guqiao mine as the object of study, the causes of spontaneous combustion during the period of end caving are analyzed, according to the specific geological conditions of the stope to develop corresponding fire prevention measures, including the reduction of air supply and air leakage in goaf, reduce the amount of coal left, reasonable drainage, nitrogen injection for spontaneous combustion prevention, grouting for spontaneous combustion prevention and permanent closure, fundamentally eliminates the potential for spontaneous combustion during the period of 1116(3) stope end caving. The engineering practice shows that this kind of measure has reference value for the prevention and control of spontaneous combustion during the period of stope end caving.

  12. New technique for quantification of elemental hg in mine wastes and its implications for mercury evasion into the atmosphere

    Science.gov (United States)

    Jew, A.D.; Kim, C.S.; Rytuba, J.J.; Gustin, M.S.; Brown, Gordon E.

    2011-01-01

    Mercury in the environment is of prime concern to both ecosystem and human health. Determination of the molecular-level speciation of Hg in soils and mine wastes is important for understanding its sequestration, mobility, and availability for methylation. Extended X-ray absorption fine structure (EXAFS) spectroscopy carried out under ambient P-T conditions has been used in a number of past studies to determine Hg speciation in complex mine wastes and associated soils. However, this approach cannot detect elemental (liquid) mercury in Hg-polluted soils and sediments due to the significant structural disorder of liquid Hg at ambient-temperature. A new sample preparation protocol involving slow cooling through the crystallization temperature of Hg(0) (234 K) results in its transformation to crystalline ??-Hg(0). The presence and proportion of Hg(0), relative to other crystalline Hg-bearing phases, in samples prepared in this way can be quantified by low-temperature (77 K) EXAFS spectroscopy. Using this approach, we have determined the relative concentrations of liquid Hg(0) in Hg mine wastes from several sites in the California Coast Range and have found that they correlate well with measured fluxes of gaseous Hg released during light and dark exposure of the same samples, with higher evasion ratios from samples containing higher concentrations of liquid Hg(0). Two different linear relationships are observed in plots of the ratio of Hg emission under light and dark conditions vs % Hg(0), corresponding to silica-carbonate- and hot springs-type Hg deposits, with the hot springs-type samples exhibiting higher evasion fluxes than silica-carbonate type samples at similar Hg(0) concentrations. Our findings help explain significant differences in Hg evasion data for different mine sites in the California Coast Range. ?? 2011 American Chemical Society.

  13. What Online Communities Can Tell Us About Electronic Cigarettes and Hookah Use: A Study Using Text Mining and Visualization Techniques

    OpenAIRE

    Chen, Annie T; Zhu, Shu-Hong; Conway, Mike

    2015-01-01

    © 2015 Journal of Medical Internet Research. Background: The rise in popularity of electronic cigarettes (e-cigarettes) and hookah over recent years has been accompanied by some confusion and uncertainty regarding the development of an appropriate regulatory response towards these emerging products. Mining online discussion content can lead to insights into people's experiences, which can in turn further our knowledge of how to address potential health implications. In this work, we take a no...

  14. Using Data Mining Techniques Examination of the Middle School Students’ Attitude towards Mathematics in the Context of Some Variables

    OpenAIRE

    Aksoy, Esra; Narli, Serkan; Idil, Feriha Hande

    2016-01-01

    The aim of this study is to examine middle school students’ attitude towards mathematics in the context of their mathematic learning preferences using data mining which is data analysis methodology that has been successfully used in different areas including educational domains. ‘How do I actually learn?’ questionnaire and attitude scale were applied to 702 middle school students studying in three different cities of Turkey. Demographic data (gender, grade level, parents’ education level, pre...

  15. Concentration trends for lead and calcium-normalized lead in fish fillets from the Big River, a mining-contaminated stream in southeastern Missouri USA

    Science.gov (United States)

    Schmitt, Christopher J.; McKee, Michael J.

    2016-01-01

    Lead (Pb) and calcium (Ca) concentrations were measured in fillet samples of longear sunfish (Lepomis megalotis) and redhorse suckers (Moxostoma spp.) collected in 2005–2012 from the Big River, which drains a historical mining area in southeastern Missouri and where a consumption advisory is in effect due to elevated Pb concentrations in fish. Lead tends to accumulated in Ca-rich tissues such as bone and scale. Concentrations of Pb in fish muscle are typically low, but can become elevated in fillets from Pb-contaminated sites depending in part on how much bone, scale, and skin is included in the sample. We used analysis-of-covariance to normalize Pb concentration to the geometric mean Ca concentration (415 ug/g wet weight, ww), which reduced variation between taxa, sites, and years, as was the number of samples that exceeded Missouri consumption advisory threshold (300 ng/g ww). Concentrations of Pb in 2005–2012 were lower than in the past, especially after Ca-normalization, but the consumption advisory is still warranted because concentrations were >300 ng/g ww in samples of both taxa from contaminated sites. For monitoring purposes, a simple linear regression model is proposed for estimating Ca-normalized Pb concentrations in fillets from Pb:Ca molar ratios as a way of reducing the effects of differing preparation methods on fillet Pb variation.

  16. Concentration Trends for Lead and Calcium-Normalized Lead in Fish Fillets from the Big River, a Mining-Contaminated Stream in Southeastern Missouri USA.

    Science.gov (United States)

    Schmitt, Christopher J; McKee, Michael J

    2016-11-01

    Lead (Pb) and calcium (Ca) concentrations were measured in fillet samples of longear sunfish (Lepomis megalotis) and redhorse suckers (Moxostoma spp.) collected in 2005-2012 from the Big River, which drains a historical mining area in southeastern Missouri and where a consumption advisory is in effect due to elevated Pb concentrations in fish. Lead tends to accumulated in Ca-rich tissues such as bone and scale. Concentrations of Pb in fish muscle are typically low, but can become elevated in fillets from Pb-contaminated sites depending in part on how much bone, scale, and skin is included in the sample. We used analysis-of-covariance to normalize Pb concentration to the geometric mean Ca concentration (415 ug/g wet weight, ww), which reduced variation between taxa, sites, and years, as was the number of samples that exceeded Missouri consumption advisory threshold (300 ng/g ww). Concentrations of Pb in 2005-2012 were lower than in the past, especially after Ca-normalization, but the consumption advisory is still warranted because concentrations were >300 ng/g ww in samples of both taxa from contaminated sites. For monitoring purposes, a simple linear regression model is proposed for estimating Ca-normalized Pb concentrations in fillets from Pb:Ca molar ratios as a way of reducing the effects of differing preparation methods on fillet Pb variation.

  17. The physiological stress response and oxidative stress biomarkers in rainbow trout and brook trout from selenium-impacted streams in a coal mining region

    Energy Technology Data Exchange (ETDEWEB)

    Miller, L.L.; Rasmussen, J.B.; Palace, V.P.; Hontela, A. [University of Lethbridge, Lethbridge, AB (Canada). Dept. of Biological Science

    2009-11-15

    Selenium (Se) is an essential element that can be toxic at concentrations slightly greater than those required for homeostasis. The main chronic toxic effects of Se in fish are teratogenic deformities, but Se can also activate the physiological stress response and redox cycle with reduced glutathione causing oxidative damage. Rainbow trout, Oncorhynchus mykiss, appear to be more sensitive to Se than brook trout, Salvelinus fontinalis. The objective of this study was to compare the physiological stress response (plasma cortisol, glucose, triiodothyronine, thyroxine, gill Na+/K+ ATPase, cortisol secretory capacity, K and liver somatic index) and oxidative stress biomarkers (liver GSH, GPx, lipid peroxidation, vitamin A and vitamin E) in rainbow trout (RNTR) and brook trout (BKTR) collected from reference and Se-exposed streams. The physiological stress response was not impaired (cortisol secretory capacity unchanged); although there were species differences in plasma cortisol and plasma glucose levels. Liver GSH, GPx and vitamin levels were higher in RNTR than BKTR, but lipid peroxidation levels were not different. The elevated GSH reserves may make RNTR more sensitive to Se-induced lipid peroxidation, but this may be offset by the RNTR's higher antioxidant (GPx and vitamin) levels. Species-specific biochemical differences may mediate differences in Se sensitivity and be used in aquatic Se risk assessments.

  18. Matisse: A Visual Analytics System for Exploring Emotion Trends in Social Media Text Streams

    Energy Technology Data Exchange (ETDEWEB)

    Steed, Chad A [ORNL; Drouhard, Margaret MEG G [ORNL; Beaver, Justin M [ORNL; Pyle, Joshua M [ORNL; BogenII, Paul L. [Google Inc.

    2015-01-01

    Dynamically mining textual information streams to gain real-time situational awareness is especially challenging with social media systems where throughput and velocity properties push the limits of a static analytical approach. In this paper, we describe an interactive visual analytics system, called Matisse, that aids with the discovery and investigation of trends in streaming text. Matisse addresses the challenges inherent to text stream mining through the following technical contributions: (1) robust stream data management, (2) automated sentiment/emotion analytics, (3) interactive coordinated visualizations, and (4) a flexible drill-down interaction scheme that accesses multiple levels of detail. In addition to positive/negative sentiment prediction, Matisse provides fine-grained emotion classification based on Valence, Arousal, and Dominance dimensions and a novel machine learning process. Information from the sentiment/emotion analytics are fused with raw data and summary information to feed temporal, geospatial, term frequency, and scatterplot visualizations using a multi-scale, coordinated interaction model. After describing these techniques, we conclude with a practical case study focused on analyzing the Twitter sample stream during the week of the 2013 Boston Marathon bombings. The case study demonstrates the effectiveness of Matisse at providing guided situational awareness of significant trends in social media streams by orchestrating computational power and human cognition.

  19. StreamAR: incremental and active learning with evolving sensory data for activity recognition

    OpenAIRE

    Abdallah, Z.; Gaber, M.; Srinivasan, B.; Krishnaswamy, S.

    2012-01-01

    Activity recognition focuses on inferring current user activities by leveraging sensory data available on today’s sensor rich environment. Supervised learning has been applied pervasively for activity recognition. Typical activity recognition techniques process sensory data based on point-by-point approaches. In this paper, we propose a novel cluster-based classification for activity recognition Systems, termed StreamAR. The system incorporates incremental and active learning for mining user ...

  20. Research on and Design of a Self-Propelled Nozzle for the Tree-Type Drilling Technique in Underground Coal Mines

    Directory of Open Access Journals (Sweden)

    Yiyu Lu

    2015-12-01

    Full Text Available Due to the increasing depths of coal mines and the low permeability of some coal seams, conventional methods of gas drainage in underground mines are facing many problems. To improve gas extraction, a new technique using water jets to drill tree-type boreholes in coal seams is proposed. A self-propelled water-jet drilling nozzle was designed to drill these boreholes. The configuration of the self-propelled nozzle was optimized by conducting drilling experiments and self-propelling force measurements. Experimental results show that the optimal self-propelled nozzle has a forward orifice axial angle at 25°, a radial angle at 90°, a center distance of 1.5 mm, and backward pointing orifices with an axial angle of 25°. The self-propelling force generated by the jets of the nozzle with 30 MPa pump pressure can reach 29.8 N, enough to pull the hose and the nozzle forward without any external forces. The nozzle can drill at speeds up to 41.5 m/h with pump pressures at 30 MPa. The radial angles of the forward orifices improve the rock breaking performance of the nozzle and, with the correct angle, the rock breaking area of the orifices overlap to produce a connecting hole. The diameter of boreholes drilled by this nozzle can reach 35.2 mm. The nozzle design can be used as the basis for designing other self-propelled nozzles. The drilling experiments demonstrate the feasibility of using the tree-type drilling technique in underground mines.

  1. Evaluation of particle dispersal from mining and milling operations using lead isotopic fingerprinting techniques, Rio Pilcomayo Basin, Bolivia

    International Nuclear Information System (INIS)

    Miller, Jerry R.; Lechler, Paul J.; Mackin, Gail; Germanoski, Dru; Villarroel, Lionel F.

    2007-01-01

    Mining and milling of ores from the Cerro Rico de Potosi precious metal-polymetallic tin deposits of Bolivia have led to severe contamination of water and sediments of the Rio Pilcomayo drainage system. Lead (Pb) isotopic data were used in this study to first document downstream dispersal patterns of Pb contaminated sediment within the channel of the Rio Pilcomayo, and then to determine the relative contribution of Pb from Cerro Rico within alluvial terrace soils that are used for agriculture. The concentration and isotopic composition of Pb within channel bed sediments differed significantly between 2000, 2002, and 2004. These differences presumably reflect changes in the type of ore mined and milled at Cerro Rico, and alterations in dispersal and grain-size dilution mechanisms associated with interannual variations in rainfall and runoff. Within agricultural terrace soils, both Pb concentrations and the percentage of Pb from Cerro Rico: (1) semi-systematically decrease downstream, (2) were found to decrease with terrace height above the channel, and (3) reflect the use of contaminated irrigation water. In upstream reaches (within 30 km of the mills), Pb from mining represents the most significant Pb source, accounting for more than 80% of Pb in the examined agricultural fields. At Sotomayor, located approximately 170 km from the mills, the relative contribution of Pb from Cerro Rico is highly variable between fields, but can be significant, ranging from approximately 15% to 35%. The analysis demonstrates that Pb isotopic ratios can be used to effectively trace contaminated particles through river systems and into adjacent alluvial soils, even where multiple Pb sources exist and Pb concentrations are similar to background values

  2. Application of data mining techniques to explore predictors of HCC in Egyptian patients with HCV-related chronic liver disease.

    Science.gov (United States)

    Omran, Dalia Abd El Hamid; Awad, AbuBakr Hussein; Mabrouk, Mahasen Abd El Rahman; Soliman, Ahmad Fouad; Aziz, Ashraf Omar Abdel

    2015-01-01

    Hepatocellular carcinoma (HCC) is the second most common malignancy in Egypt. Data mining is a method of predictive analysis which can explore tremendous volumes of information to discover hidden patterns and relationships. Our aim here was to develop a non-invasive algorithm for prediction of HCC. Such an algorithm should be economical, reliable, easy to apply and acceptable by domain experts. This cross-sectional study enrolled 315 patients with hepatitis C virus (HCV) related chronic liver disease (CLD); 135 HCC, 116 cirrhotic patients without HCC and 64 patients with chronic hepatitis C. Using data mining analysis, we constructed a decision tree learning algorithm to predict HCC. The decision tree algorithm was able to predict HCC with recall (sensitivity) of 83.5% and precession (specificity) of 83.3% using only routine data. The correctly classified instances were 259 (82.2%), and the incorrectly classified instances were 56 (17.8%). Out of 29 attributes, serum alpha fetoprotein (AFP), with an optimal cutoff value of ≥50.3 ng/ml was selected as the best predictor of HCC. To a lesser extent, male sex, presence of cirrhosis, AST>64U/L, and ascites were variables associated with HCC. Data mining analysis allows discovery of hidden patterns and enables the development of models to predict HCC, utilizing routine data as an alternative to CT and liver biopsy. This study has highlighted a new cutoff for AFP (≥50.3 ng/ml). Presence of a score of >2 risk variables (out of 5) can successfully predict HCC with a sensitivity of 96% and specificity of 82%.

  3. Use of Natural and Applied Tracers to Guide Targeted Remediation Efforts in an Acid Mine Drainage System, Colorado Rockies, USA

    OpenAIRE

    Cowie, Rory; Williams, Mark; Wireman, Mike; Runkel, Robert

    2014-01-01

    Stream water quality in areas of the western United States continues to be degraded by acid mine drainage (AMD), a legacy of hard-rock mining. The Rico-Argentine Mine in southwestern Colorado consists of complex multiple-level mine workings connected to a drainage tunnel discharging AMD to passive treatment ponds that discharge to the Dolores River. The mine workings are excavated into the hillslope on either side of a tributary stream with workings passing directly under the stream channel. ...

  4. Integrating data mining technique and AHP in market analysis to propose new product development in real estate

    Science.gov (United States)

    Yunita; Galinium, M.; Lukas

    2017-01-01

    New product development in real estate industry is a challenging process since it is related to long term concept and high cost. A newly proposed product development should meet customer need and their preferences which appropriate with customer buying power and company value. This research use data mining for profiling customer transaction and Analytic Hierarchy Process (AHP) method for product selection in new product development. This research utilizes Weka as data mining open source software to profiling data customers. The analysis correlated product preferences and profiling demography such as city, age, gender and occupation. Demography profiles gives description buying power and product preferences. The products proposed are based on customer profiles and rank of the product by AHP method. The product with the highest score will be proposed as new product development. Case studies of this research are real estate projects in Serang, Makassar, and Balikpapan. Makassar and Balikpapan are the project that already gained success and Serang is new project which new products development will be proposed to launch. Based on profiling and product preference of customer in Balikpapan, Makassar, and prospectus of Serang markets, new products development that will be proposed are house type of 120/200 m2 with price around Rp1.300.000.000 and house type of 71/120 m2 with price around Rp800.000.000. The markets of Serang and Balikpapan have similarities in profiles as urban city so the new products development will adopt the succeed story of Balikpapan project.

  5. Evaluation of radionuclide contamination in the vicinity of the cunha baixa and quinta do bispo old uranium mines

    International Nuclear Information System (INIS)

    Pereira, A.J.S.C.; Neves, L.J.P.F.; Dias, J.M.M.; Barbosa, S.V.T.

    2004-01-01

    The Cunha Baixa and Quinta do Bispo uranium mines were some of the most important exploitations in Portugal and shared a common geological setting, composed of metasedimentary enclaves in hercynian porphyritic granites. The exploitation of Cunha Baixa began as an underground mine and later evolved to an open-pit; Quinta do Bispo was exclusively exploited as an open-pit. Heap leaching techniques were used in both mines to recover uranium from low-grade ores (300-500 ppm). The mining activities produced large amounts of waste, currently deposited in several tailings. To evaluate the degree and extension of the contamination of the environment, the radionuclides of the U-chain, as well as other chemical elements, were measure in samples of water (116), stream sediments (8) and soils (26), collected in the mining area and its vicinity. The activity of the radionuclides in the different environmental compartments is highly variable, and the modelling by multivariate techniques based on discriminant analysis, allow to separate the samples with chemical signature changed by the mine workings from those that only contain the variability imposed by geology or other anthropogenic activities. Mining contamination is mainly restricted to the surroundings of the studied mines and the worst environmental situation occurs in soils close to Cunha Baixa mine, as a result of the illegal use for irrigation of water collected in the wastewater treatment plant, as well as from resurgences in the tailings. (author)

  6. Ghana - Mining and Development

    OpenAIRE

    Mohan, P.C.

    2004-01-01

    The objectives of the project ($9.37 million, 1996-2001) were to (a) enhance the capacity of the mining sector institutions to carry out their functions of encouraging and regulating investments in the mining sector in an environmentally sound manner and (b) support the use of techniques and mechanisms that will improve productivity, financial viability and reduce the environmental impact of ...

  7. Gesture Recognition from Data Streams of Human Motion Sensor Using Accelerated PSO Swarm Search Feature Selection Algorithm

    Directory of Open Access Journals (Sweden)

    Simon Fong

    2015-01-01

    Full Text Available Human motion sensing technology gains tremendous popularity nowadays with practical applications such as video surveillance for security, hand signing, and smart-home and gaming. These applications capture human motions in real-time from video sensors, the data patterns are nonstationary and ever changing. While the hardware technology of such motion sensing devices as well as their data collection process become relatively mature, the computational challenge lies in the real-time analysis of these live feeds. In this paper we argue that traditional data mining methods run short of accurately analyzing the human activity patterns from the sensor data stream. The shortcoming is due to the algorithmic design which is not adaptive to the dynamic changes in the dynamic gesture motions. The successor of these algorithms which is known as data stream mining is evaluated versus traditional data mining, through a case of gesture recognition over motion data by using Microsoft Kinect sensors. Three different subjects were asked to read three comic strips and to tell the stories in front of the sensor. The data stream contains coordinates of articulation points and various positions of the parts of the human body corresponding to the actions that the user performs. In particular, a novel technique of feature selection using swarm search and accelerated PSO is proposed for enabling fast preprocessing for inducing an improved classification model in real-time. Superior result is shown in the experiment that runs on this empirical data stream. The contribution of this paper is on a comparative study between using traditional and data stream mining algorithms and incorporation of the novel improved feature selection technique with a scenario where different gesture patterns are to be recognized from streaming sensor data.

  8. Stream systems.

    Science.gov (United States)

    Jack E. Williams; Gordon H. Reeves

    2006-01-01

    Restored, high-quality streams provide innumerable benefits to society. In the Pacific Northwest, high-quality stream habitat often is associated with an abundance of salmonid fishes such as chinook salmon (Oncorhynchus tshawytscha), coho salmon (O. kisutch), and steelhead (O. mykiss). Many other native...

  9. Standardization of radiochemical techniques aiming the study of Hg volatilization and methylation in water and sediment of gold mining areas in the Amazon region

    International Nuclear Information System (INIS)

    Guimaraes, Jean Remy Davee

    1992-09-01

    Methylation of inorganic Hg in aquatic systems is a key process in the environmental cycling of this metal, not yet studied in tropical conditions. Radiochemical techniques were adapted and simplified, aiming at the study of Hg volatilization and methylation in water and sediment of gold mining areas in the Amazon region. Preliminary experiments showed, in 35 days volatilization of up to 32 % of 203 Hg 2+ added to aqueous solutions. Acid K 2 Cr 2 0 7 0.1 M solutions were not effective in 203 Hg 0 trapping and the latter was highly and irreversibly absorbed by a variety of synthetic materials commonly used in laboratory work. Considerably simplified versions of the Furutani and Rudd (1980) radiochemical technique for the determination of methylation rates in environmental samples were developed and showed efficiencies close to 90 % in tests with methyl- 2 0 3 H g standards. In-situ incubations of surface sediments were performed in the Madeira River gold mining region, Rondonia State, Brazil, and potential net Hg methylation rates (MR) of up to 1 %.g-1.h-1 were found in black-water affluent like the Mutum-Parana and Jamari rivers and in the Samuel reservoir. MRs in the Madeira River sediments were lower, ranging 10-5 to 10-3 %.g-1.h-1 . MRs obtained in incubations of samples some weeks after collection were one or two orders of magnitude lower than those resulting from in-situ incubations. Methylation in autoclaved samples was close to minimum detectable rates. MRs in surface water samples was in all cases < 7.10-7 %.ml-1.h-1. The determination of the predominant methylation sites will allow a better standardization of the technique described herein, suitable for MR determinations even under the unfavorable conditions prevailing in the Amazon region. (author)

  10. Process mining : overview and opportunities

    NARCIS (Netherlands)

    Aalst, van der W.M.P.

    2012-01-01

    Over the last decade, process mining emerged as a new research ¿eld that focuses on the analysis of processes using event data. Classical data mining techniques such as classi¿cation, clustering, regression, association rule learning, and sequence/episode mining do not focus on business process

  11. Measurement of impulse generated by the detonation of anti-tank mines by using the VLIP technique

    CSIR Research Space (South Africa)

    De Koker, PM

    2009-09-01

    Full Text Available -120 mm Mortar. Artillery rounds up to 155mm MTL-06 A/T HC AT-4 MTL-07 A/T SFF TMRP-6, TMRP-7, TMK-2, UKA-63 MTL-08 UXO heavy size 250-500 kg a/c bombs, sea mines 1 Landwards Sciences is a....8000 1.0000 0 0.01 0.02 0.03 0.04 0.05 0.06 0.07 Time [s] D is pl ac em en t [ m [ Displacement Linear (Displacement) Displacement TMA3 #2 y = 14.026x + 0.0086 0.0000 0.2000 0.4000 0.6000 0.8000 1.0000 1.2000 1.4000 1.6000 0 0...

  12. Trust Mines

    Science.gov (United States)

    The United States and the Navajo Nation entered into settlement agreements that provide funds to conduct investigations and any needed cleanup at 16 of the 46 priority mines, including six mines in the Northern Abandoned Uranium Mine Region.

  13. Construction over abandoned mine workings

    Energy Technology Data Exchange (ETDEWEB)

    Healy, P R; Head, J M

    1984-01-01

    Guidance is given for engineers involved with the planning and development of sites previously undermined for coal and other minerals. Past methods of mining employed in Britain are described, and their short- and long-term effects on surface stability are assessed. Where modern methods of mining are relevant, or where structural design techniques for the surface effects of mining can be applied, these are included for illustration and completeness. Additional objectives over and above those for conventional site investigations are identified, and details are provided for the planning and execution of a mining investigation. Techniques for consolidation of old mine workings and remedial measures for mine shafts are described. Foundation design options are included for cases where expected ground movements can be accommodated. A comprehensive guide to sources of information on previous mining is presented, together with an example of a specification suitable for the consolidation of old shallow mine workings. (50 refs.)

  14. Swedish mines. Underground exploitation methods

    International Nuclear Information System (INIS)

    Paucard, A.

    1960-01-01

    Between 1949 and 1957, 10 engineers of the Mining research and exploitation department of the CEA visited 17 Swedish mines during 5 field trips. This paper presents a compilation of the information gathered during these field trips concerning the different underground mining techniques used in Swedish iron mines: mining with backfilling (Central Sweden and Boliden mines); mining without backfilling (mines of the polar circle area). The following techniques are described successively: pillar drawing and backfilled slices (Ammeberg, Falun, Garpenberg, Boliden group), sub-level pillar drawing (Grangesberg, Bloettberget, Haeksberg), empty room and sub-level pillar drawing (Bodas, Haksberg, Stripa, Bastkarn), storage chamber pillar drawing (Bodas, Haeksberg, Bastkarn), and pillar drawing by block caving (ldkerberget). Reprint of a paper published in Revue de l'Industrie Minerale, vol. 41, no. 12, 1959 [fr

  15. Mine waters: Acidic to circumneutral

    Science.gov (United States)

    Nordstrom, D. Kirk

    2011-01-01

    Acid mine waters, often containing toxic concentrations of Fe, Al, Cu, Zn, Cd, Pb, Ni, Co, and Cr, can be produced from the mining of coal and metallic deposits. Values of pH for acid mine waters can range from –3.5 to 5, but even circumneutral (pH ≈ 7) mine waters can have high concentrations of As, Sb, Mo, U, and F. When mine waters are discharged into streams, lakes, and the oceans, serious degradation of water quality and injury to aquatic life can ensue, especially when tailings impoundments break suddenly. The main acid-producing process is the exposure of pyrite to air and water, which promotes oxidative dissolution, a reaction catalyzed by microbes. Current and future mining should plan for the prevention and remediation of these contaminant discharges by the application of hydrogeochemical principles and available technologies, which might include remining and recycling of waste materials.

  16. Applied Geochemistry Special Issue on Environmental geochemistry of modern mining

    Science.gov (United States)

    Seal, Robert R.; Nordstrom, D. Kirk

    2015-01-01

    challenges of current and future mines share similarities with abandoned mines, but differences also exist. Mining and ore processing techniques have changed; the environmental footprint of waste materials has changed; environmental protection has become a more integral part of the mine planning process; and most historical mining was done with limited regard for the environment. The 17 papers in this special issue evolved from the Society of Economic Geologists’ short course.The relevant geochemical processes encompass the source, transport, and fate of contaminants related to the life cycle of a mine. Contaminants include metals and other inorganic species derived from geologic sources such as ore and solid mine waste, and substances brought to the site for ore processing, such as cyanide to leach gold. Factors, such as mine-waste mineralogy, hydrologic setting, mine-drainage chemistry, and microbial activity, that affect the hydrochemical risks from mining are reviewed by Nordstrom et al. In another paper, Nordstrom discusses baseline characterization at mine sites in a regulatory framework, and emphasizes the influence of mineral deposits in producing naturally elevated concentrations of many trace elements in surface water and groundwater. Surface water quality in mineralized watersheds is influenced by a number of processes that act on daily (diel) cycles and can produce dramatic variations in trace element concentrations as described by Gammons et al. Pre-mining baseline characterization studies should strive to capture the magnitude of these diel variations. Desbarats et al., using a case study of mine drainage from a gold mine, illustrate how elements that commonly occur as negatively charged species (anions) in solution, such as arsenic as arsenate, behave in an opposite fashion than most metals, which occur as positively charged species (cations). Significant improvement in the understanding of factors that influence the toxicity of metals to aquatic organisms

  17. Human impacts to mountain streams

    Science.gov (United States)

    Wohl, Ellen

    2006-09-01

    Mountain streams are here defined as channel networks within mountainous regions of the world. This definition encompasses tremendous diversity of physical and biological conditions, as well as history of land use. Human effects on mountain streams may result from activities undertaken within the stream channel that directly alter channel geometry, the dynamics of water and sediment movement, contaminants in the stream, or aquatic and riparian communities. Examples include channelization, construction of grade-control structures or check dams, removal of beavers, and placer mining. Human effects can also result from activities within the watershed that indirectly affect streams by altering the movement of water, sediment, and contaminants into the channel. Deforestation, cropping, grazing, land drainage, and urbanization are among the land uses that indirectly alter stream processes. An overview of the relative intensity of human impacts to mountain streams is provided by a table summarizing human effects on each of the major mountainous regions with respect to five categories: flow regulation, biotic integrity, water pollution, channel alteration, and land use. This table indicates that very few mountains have streams not at least moderately affected by land use. The least affected mountainous regions are those at very high or very low latitudes, although our scientific ignorance of conditions in low-latitude mountains in particular means that streams in these mountains might be more altered than is widely recognized. Four case studies from northern Sweden (arctic region), Colorado Front Range (semiarid temperate region), Swiss Alps (humid temperate region), and Papua New Guinea (humid tropics) are also used to explore in detail the history and effects on rivers of human activities in mountainous regions. The overview and case studies indicate that mountain streams must be managed with particular attention to upstream/downstream connections, hillslope

  18. Association rule extraction from XML stream data for wireless sensor networks.

    Science.gov (United States)

    Paik, Juryon; Nam, Junghyun; Kim, Ung Mo; Won, Dongho

    2014-07-18

    With the advances of wireless sensor networks, they yield massive volumes of disparate, dynamic and geographically-distributed and heterogeneous data. The data mining community has attempted to extract knowledge from the huge amount of data that they generate. However, previous mining work in WSNs has focused on supporting simple relational data structures, like one table per network, while there is a need for more complex data structures. This deficiency motivates XML, which is the current de facto format for the data exchange and modeling of a wide variety of data sources over the web, to be used in WSNs in order to encourage the interchangeability of heterogeneous types of sensors and systems. However, mining XML data for WSNs has two challenging issues: one is the endless data flow; and the other is the complex tree structure. In this paper, we present several new definitions and techniques related to association rule mining over XML data streams in WSNs. To the best of our knowledge, this work provides the first approach to mining XML stream data that generates frequent tree items without any redundancy.

  19. Association Rule Extraction from XML Stream Data for Wireless Sensor Networks

    Science.gov (United States)

    Paik, Juryon; Nam, Junghyun; Kim, Ung Mo; Won, Dongho

    2014-01-01

    With the advances of wireless sensor networks, they yield massive volumes of disparate, dynamic and geographically-distributed and heterogeneous data. The data mining community has attempted to extract knowledge from the huge amount of data that they generate. However, previous mining work in WSNs has focused on supporting simple relational data structures, like one table per network, while there is a need for more complex data structures. This deficiency motivates XML, which is the current de facto format for the data exchange and modeling of a wide variety of data sources over the web, to be used in WSNs in order to encourage the interchangeability of heterogeneous types of sensors and systems. However, mining XML data for WSNs has two challenging issues: one is the endless data flow; and the other is the complex tree structure. In this paper, we present several new definitions and techniques related to association rule mining over XML data streams in WSNs. To the best of our knowledge, this work provides the first approach to mining XML stream data that generates frequent tree items without any redundancy. PMID:25046017

  20. Route survey periodicity for mine warfare

    OpenAIRE

    Coke, Hartwell F.

    2009-01-01

    Approved for public release, distribution unlimited One of the Navy's most long standing challenges has been conquering the mine warfare threat. As mines and mine warfare techniques evolve and become more sophisticated, so does the United States' ability to counter the threat. The United States newest technique for countering a potential mined harbor, or route, is a process known as "change detection." This concept uses previous side scan sonar images of the area prior to a mining event an...

  1. Factors Associated With Healthcare-Acquired Catheter-Associated Urinary Tract Infections: Analysis Using Multiple Data Sources and Data Mining Techniques.

    Science.gov (United States)

    Park, Jung In; Bliss, Donna Z; Chi, Chih-Lin; Delaney, Connie W; Westra, Bonnie L

    The purpose of this study was to identify factors associated with healthcare-acquired catheter-associated urinary tract infections (HA-CAUTIs) using multiple data sources and data mining techniques. Three data sets were integrated for analysis: electronic health record data from a university hospital in the Midwestern United States was combined with staffing and environmental data from the hospital's National Database of Nursing Quality Indicators and a list of patients with HA-CAUTIs. Three data mining techniques were used for identification of factors associated with HA-CAUTI: decision trees, logistic regression, and support vector machines. Fewer total nursing hours per patient-day, lower percentage of direct care RNs with specialty nursing certification, higher percentage of direct care RNs with associate's degree in nursing, and higher percentage of direct care RNs with BSN, MSN, or doctoral degree are associated with HA-CAUTI occurrence. The results also support the association of the following factors with HA-CAUTI identified by previous studies: female gender; older age (>50 years); longer length of stay; severe underlying disease; glucose lab results (>200 mg/dL); longer use of the catheter; and RN staffing. Additional findings from this study demonstrated that the presence of more nurses with specialty nursing certifications can reduce HA-CAUTI occurrence. While there may be valid reasons for leaving in a urinary catheter, findings show that having a catheter in for more than 48 hours contributes to HA-CAUTI occurrence. Finally, the findings suggest that more nursing hours per patient-day are related to better patient outcomes.

  2. Stream Evaluation

    Data.gov (United States)

    Kansas Data Access and Support Center — Digital representation of the map accompanying the "Kansas stream and river fishery resource evaluation" (R.E. Moss and K. Brunson, 1981.U.S. Fish and Wildlife...

  3. Assessment of levels and 'health-effects' of airborne particulate matter in mining, metal refining and metal working industries using nuclear and related analytical techniques

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2008-01-15

    The International Atomic Energy Agency (IAEA) has been supporting, over the years, several coordinated research programmes (CRPs) on various research topics related to environmental issues impacting human health. A variety of industrial environments such as: galvanisation, iron and steel production, steel construction, coal fired thermal power plants, mining and mineral beneficiation of monazite, zinc smelters, and phosphate fertilizer production plants were included in this CRP. Toxic elements specific for particular industries as potential pollutants were monitored within individual projects. The CRP focussed on the use of nuclear and related analytical techniques for studies of exposure to inorganic constituents and radionuclides from naturally occurring radioactive materials (NORMs), in the workplaces and their impacts on the health of the workers. The objectives were to: develop strategies and techniques for sampling of workplace airborne particulate matter (APM) and of bio-markers (e.g. hair, blood, nails, teeth, urine, breath) of exposed and non-exposed individuals; develop reliable analytical procedures for the analysis of such samples, using nuclear and related analytical techniques; carry out workplace and personal monitoring surveys, and assess workers' exposure to toxic elements on the basis of measurements results. This document provides an overview of the activities performed under the CRP by the participants. The overall achievements are summarized and those aspects that require a further deeper look are also pointed out. The individual country reports include details on the progress made by the respective participants during the CRP period.

  4. Data mining in agriculture

    CERN Document Server

    Mucherino, Antonio; Pardalos, Panos M

    2009-01-01

    Data Mining in Agriculture represents a comprehensive effort to provide graduate students and researchers with an analytical text on data mining techniques applied to agriculture and environmental related fields. This book presents both theoretical and practical insights with a focus on presenting the context of each data mining technique rather intuitively with ample concrete examples represented graphically and with algorithms written in MATLAB®. Examples and exercises with solutions are provided at the end of each chapter to facilitate the comprehension of the material. For each data mining technique described in the book variants and improvements of the basic algorithm are also given. Also by P.J. Papajorgji and P.M. Pardalos: Advances in Modeling Agricultural Systems, 'Springer Optimization and its Applications' vol. 25, ©2009.

  5. Improving the technique of water infusion to control dust in the mines of the central district of the Donetz coalfield

    Energy Technology Data Exchange (ETDEWEB)

    Aleksandrov, S N

    1974-03-01

    A study of the results obtained with different methods of water infusion is followed by an account of a new ''pinpoint'' infusion technique utilizing rising infusion holes of limited depth (20-25 m). This new technique enhances safety of work at the coal face, since it avoids deterioraon of the face due to erosion of surrounding walls and accumulation of gas in the infusion holes; it also renders the arduous job of guided drilling and sealing of the holes unnecessary, and facilitates coal-getting and development work.

  6. A survey of temporal data mining

    Indian Academy of Sciences (India)

    Data mining is concerned with analysing large volumes of (often unstructured) data to automatically discover interesting regularities or relationships which in turn lead to better understanding of the underlying processes. The field of temporal data mining is concerned with such analysis in the case of ordered data streams ...

  7. Factores de éxito de un emprendimiento: Un estudio exploratorio con base en técnicas de data mining (Entrepreneurial success factors: An exploratory study based on Data Mining Techniques

    Directory of Open Access Journals (Sweden)

    María Messina

    2015-04-01

    Full Text Available El Centro de Emprendedurismo CCEEmprende de- sarrolla, desde 2007, un programa de apoyo a emprende- dores. Para mejorar su gestión, resulta de gran importancia analizar, en forma preliminar, los emprendimientos en una de dos categorías: éxito o fracaso. En este artículo se identifican los principales factores asociados al éxito de un emprendimiento y cómo se vincu- lan para anticipar el futuro del emprendimiento. Se presenta un caso de estudio con base en los datos de una encuesta realizada a emprendedores participantes del programa, aplicando técnicas de clasificación. Las dos técnicas utilizadas de data mining son árbol de decisión y regresión logística, en ambas se obtuvieron resultados coincidentes. Los hallazgos muestran que los dos elementos más relevantes para anticipar el éxito de un emprendimiento son contar con financiamiento y que, anteriormente, la situa- ción laboral del emprendedor sea trabajador independiente. Estos primeros resultados obtenidos en el estudio de caso revelan información útil acerca de las mejores formas de apoyo al emprendedor, cómo generar incentivos al em- prendedor y la definición de herramientas o actividades que incidan favorablemente en el éxito de los emprendimientos. Si bien desde la teoría o para otras realidades existe infor- mación sobre los factores que colaboran en la determina- ción del éxito, para la realidad del Uruguay no se identifican estudios similares.   Abstract  Since 2007, the CCEE Entrepreneurship Centre has developed a supporting program for entrepreneurs. A preliminary analysis to determine if the venture was successful or a failure is made to improve the program’s management . In this article, the authors identify the main factors associated with entrepreneurship’s success, and how they can anticipate entrepreneurship’s performance. The case study is based on a survey data applied to the Entrepreneurship Program participants. The two data mining

  8. EU-FP7-iMARS: analysis of Mars multi-resolution images using auto-coregistration, data mining and crowd source techniques

    Science.gov (United States)

    Ivanov, Anton; Muller, Jan-Peter; Tao, Yu; Kim, Jung-Rack; Gwinner, Klaus; Van Gasselt, Stephan; Morley, Jeremy; Houghton, Robert; Bamford, Steven; Sidiropoulos, Panagiotis; Fanara, Lida; Waenlish, Marita; Walter, Sebastian; Steinkert, Ralf; Schreiner, Bjorn; Cantini, Federico; Wardlaw, Jessica; Sprinks, James; Giordano, Michele; Marsh, Stuart

    2016-07-01

    Understanding planetary atmosphere-surface and extra-terrestrial-surface formation processes within our Solar System is one of the fundamental goals of planetary science research. There has been a revolution in planetary surface observations over the last 15 years, especially in 3D imaging of surface shape. This has led to the ability to be able to overlay different epochs back in time to the mid 1970s, to examine time-varying changes, such as the recent discovery of mass movement, tracking inter-year seasonal changes and looking for occurrences of fresh craters. Within the EU FP-7 iMars project, UCL have developed a fully automated multi-resolution DTM processing chain, called the Co-registration ASP-Gotcha Optimised (CASP-GO), based on the open source NASA Ames Stereo Pipeline (ASP), which is being applied to the production of planetwide DTMs and ORIs (OrthoRectified Images) from CTX and HiRISE. Alongside the production of individual strip CTX & HiRISE DTMs & ORIs, DLR have processed HRSC mosaics of ORIs and DTMs for complete areas in a consistent manner using photogrammetric bundle block adjustment techniques. A novel automated co-registration and orthorectification chain has been developed and is being applied to level-1 EDR images taken by the 4 NASA orbital cameras since 1976 using the HRSC map products (both mosaics and orbital strips) as a map-base. The project has also included Mars Radar profiles from Mars Express and Mars Reconnaissance Orbiter missions. A webGIS has been developed for displaying this time sequence of imagery and a demonstration will be shown applied to one of the map-sheets. Automated quality control techniques are applied to screen for suitable images and these are extended to detect temporal changes in features on the surface such as mass movements, streaks, spiders, impact craters, CO2 geysers and Swiss Cheese terrain. These data mining techniques are then being employed within a citizen science project within the Zooniverse family

  9. A survey on Big Data Stream Mining

    African Journals Online (AJOL)

    pc

    2018-03-05

    Mar 5, 2018 ... Big Data can be static on one machine or distributed ... decision making, and process automation. Big data .... Concept Drifting: concept drifting mean the classifier .... transactions generated by a prefix tree structure. EstDec ...

  10. Calibration of the maximum carboxylation velocity (Vcmax using data mining techniques and ecophysiological data from the Brazilian semiarid region, for use in Dynamic Global Vegetation Models

    Directory of Open Access Journals (Sweden)

    L. F. C. Rezende

    Full Text Available Abstract The semiarid region of northeastern Brazil, the Caatinga, is extremely important due to its biodiversity and endemism. Measurements of plant physiology are crucial to the calibration of Dynamic Global Vegetation Models (DGVMs that are currently used to simulate the responses of vegetation in face of global changes. In a field work realized in an area of preserved Caatinga forest located in Petrolina, Pernambuco, measurements of carbon assimilation (in response to light and CO2 were performed on 11 individuals of Poincianella microphylla, a native species that is abundant in this region. These data were used to calibrate the maximum carboxylation velocity (Vcmax used in the INLAND model. The calibration techniques used were Multiple Linear Regression (MLR, and data mining techniques as the Classification And Regression Tree (CART and K-MEANS. The results were compared to the UNCALIBRATED model. It was found that simulated Gross Primary Productivity (GPP reached 72% of observed GPP when using the calibrated Vcmax values, whereas the UNCALIBRATED approach accounted for 42% of observed GPP. Thus, this work shows the benefits of calibrating DGVMs using field ecophysiological measurements, especially in areas where field data is scarce or non-existent, such as in the Caatinga.

  11. Data Mining for Intrusion Detection

    Science.gov (United States)

    Singhal, Anoop; Jajodia, Sushil

    Data Mining Techniques have been successfully applied in many different fields including marketing, manufacturing, fraud detection and network management. Over the past years there is a lot of interest in security technologies such as intrusion detection, cryptography, authentication and firewalls. This chapter discusses the application of Data Mining techniques to computer security. Conclusions are drawn and directions for future research are suggested.

  12. The role of remediation, natural alkalinity sources and physical stream parameters in stream recovery.

    Science.gov (United States)

    Kruse, Natalie A; DeRose, Lisa; Korenowsky, Rebekah; Bowman, Jennifer R; Lopez, Dina; Johnson, Kelly; Rankin, Edward

    2013-10-15

    Acid mine drainage (AMD) negatively impacts not only stream chemistry, but also aquatic biology. The ultimate goal of AMD treatment is restoration of the biological community, but that goal is rarely explicit in treatment system design. Hewett Fork in Raccoon Creek Watershed, Ohio, has been impacted by historic coal mining and has been treated with a calcium oxide doser in the headwaters of the watershed since 2004. All of the acidic inputs are isolated to a 1.5 km stretch of stream in the headwaters of the Hewett Fork watershed. The macroinvertebrate and fish communities have begun to recover and it is possible to distinguish three zones downstream of the doser: an impaired zone, a transition zone and a recovered zone. Alkalinity from both the doser and natural sources and physical stream parameters play a role in stream restoration. In Hewett Fork, natural alkaline additions downstream are higher than those from the doser. Both, alkaline additions and stream velocity drive sediment and metal deposition. Metal deposition occurs in several patterns; aluminum tends to deposit in regions of low stream velocity, while iron tends to deposit once sufficient alkalinity is added to the system downstream of mining inputs. The majority of metal deposition occurs upstream of the recovered zone. Both the physical stream parameters and natural alkalinity sources influence biological recovery in treated AMD streams and should be considered in remediation plans. Copyright © 2013 Elsevier Ltd. All rights reserved.

  13. Reactive solute transport in acidic streams

    Science.gov (United States)

    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.

  14. Pattern Discovery and Change Detection of Online Music Query Streams

    Science.gov (United States)

    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.

  15. THE OPTIMIZATION OF TECHNOLOGICAL MINING PARAMETERS IN QUARRY FOR DIMENSION STONE BLOCKS QUALITY IMPROVEMENT BASED ON PHOTOGRAMMETRIC TECHNIQUES OF MEASUREMENT

    Directory of Open Access Journals (Sweden)

    Ruslan Sobolevskyi

    2018-01-01

    Full Text Available This research focuses on patterns of change in the dimension stone commodity blocks quality production on previously identifi ed and measured geometrical parameters of natural cracks, modelling and planning out the fi nal dimension of stone products and fi nished products based on the proposed digital photogrammetric techniques. The optimal parameters of surveying are investigated and the infl uence of surveying distance to length and crack area is estimated. Rational technological parameters of dimension stone blocks production are taken into account.

  16. Analyzing indicators of stream health for Minnesota streams

    Science.gov (United States)

    Singh, U.; Kocian, M.; Wilson, B.; Bolton, A.; Nieber, J.; Vondracek, B.; Perry, J.; Magner, J.

    2005-01-01

    Recent research has emphasized the importance of using physical, chemical, and biological indicators of stream health for diagnosing impaired watersheds and their receiving water bodies. A multidisciplinary team at the University of Minnesota is carrying out research to develop a stream classification system for Total Maximum Daily Load (TMDL) assessment. Funding for this research is provided by the United States Environmental Protection Agency and the Minnesota Pollution Control Agency. One objective of the research study involves investigating the relationships between indicators of stream health and localized stream characteristics. Measured data from Minnesota streams collected by various government and non-government agencies and research institutions have been obtained for the research study. Innovative Geographic Information Systems tools developed by the Environmental Science Research Institute and the University of Texas are being utilized to combine and organize the data. Simple linear relationships between index of biological integrity (IBI) and channel slope, two-year stream flow, and drainage area are presented for the Redwood River and the Snake River Basins. Results suggest that more rigorous techniques are needed to successfully capture trends in IBI scores. Additional analyses will be done using multiple regression, principal component analysis, and clustering techniques. Uncovering key independent variables and understanding how they fit together to influence stream health are critical in the development of a stream classification for TMDL assessment.

  17. VICKEY: Mining Conditional Keys on Knowledge Bases

    DEFF Research Database (Denmark)

    Symeonidou, Danai; Prado, Luis Antonio Galarraga Del; Pernelle, Nathalie

    2017-01-01

    A conditional key is a key constraint that is valid in only a part of the data. In this paper, we show how such keys can be mined automatically on large knowledge bases (KBs). For this, we combine techniques from key mining with techniques from rule mining. We show that our method can scale to KBs...

  18. Mine drivage in hydraulic mines

    Energy Technology Data Exchange (ETDEWEB)

    Ehkber, B Ya

    1983-09-01

    From 20 to 25% of labor cost in hydraulic coal mines falls on mine drivage. Range of mine drivage is high due to the large number of shortwalls mined by hydraulic monitors. Reducing mining cost in hydraulic mines depends on lowering drivage cost by use of new drivage systems or by increasing efficiency of drivage systems used at present. The following drivage methods used in hydraulic mines are compared: heading machines with hydraulic haulage of cut rocks and coal, hydraulic monitors with hydraulic haulage, drilling and blasting with hydraulic haulage of blasted rocks. Mining and geologic conditions which influence selection of the optimum mine drivage system are analyzed. Standardized cross sections of mine roadways driven by the 3 methods are shown in schemes. Support systems used in mine roadways are compared: timber supports, roof bolts, roof bolts with steel elements, and roadways driven in rocks without a support system. Heading machines (K-56MG, GPKG, 4PU, PK-3M) and hydraulic monitors (GMDTs-3M, 12GD-2) used for mine drivage are described. Data on mine drivage in hydraulic coal mines in the Kuzbass are discussed. From 40 to 46% of roadways are driven by heading machines with hydraulic haulage and from 12 to 15% by hydraulic monitors with hydraulic haulage.

  19. A Stream Function Theory Based Calculation of Wave Kinematics for Very Steep Waves Using a Novel Non-linear Stretching Technique

    DEFF Research Database (Denmark)

    Stroescu, Ionut Emanuel; Sørensen, Lasse; Frigaard, Peter Bak

    2016-01-01

    A non-linear stretching method was implemented for stream function theory to solve wave kinematics for physical conditions close to breaking waves in shallow waters, with wave heights limited by the water depth. The non-linear stretching method proves itself robust, efficient and fast, showing good...

  20. Data mining, mining data : energy consumption modelling

    Energy Technology Data Exchange (ETDEWEB)

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

    2007-09-15

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

  1. Estimation of water quality parameters applying satellite data fusion and mining techniques in the lake Albufera de Valencia (Spain)

    Science.gov (United States)

    Doña, Carolina; Chang, Ni-Bin; Vannah, Benjamin W.; Sánchez, Juan Manuel; Delegido, Jesús; Camacho, Antonio; Caselles, Vicente

    2014-05-01

    Linked to the enforcement of the European Water Framework Directive (2000) (WFD), which establishes that all countries of the European Union have to avoid deterioration, improve and retrieve the status of the water bodies, and maintain their good ecological status, several remote sensing studies have been carried out to monitor and understand the water quality variables trend. Lake Albufera de Valencia (Spain) is a hypereutrophic system that can present chrorophyll a concentrations over 200 mg·m-3 and transparency (Secchi disk) values below 20 cm, needing to retrieve and improve its water quality. The principal aim of our work was to develop algorithms to estimate water quality parameters such as chlorophyll a concentration and water transparency, which are informative of the eutrophication and ecological status, using remote sensing data. Remote sensing data from Terra/MODIS, Landsat 5-TM and Landsat 7-ETM+ images were used to carry out this study. Landsat images are useful to analyze the spatial variability of the water quality variables, as well as to monitor small to medium size water bodies due to its 30-m spatial resolution. But, the poor temporal resolution of Landsat, with a 16-day revisit time, is an issue. In this work we tried to solve this data gap by applying fusion techniques between Landsat and MODIS images. Although the lower spatial resolution of MODIS is 250/500-m, one image per day is available. Thus, synthetic Landsat images were created using data fusion for no data acquisition dates. Good correlation values were obtained when comparing original and synthetic Landsat images. Genetic programming was used to develop models for predicting water quality. Using the reflectance bands of the synthetic Landsat images as inputs to the model, values of R2 = 0.94 and RMSE = 8 mg·m-3 were obtained when comparing modeled and observed values of chlorophyll a, and values of R2= 0.91 and RMSE = 4 cm for the transparency (Secchi disk). Finally, concentration

  2. A survey of temporal data mining

    Indian Academy of Sciences (India)

    other subtle relationships in the data using a combination of techniques from ... stamped list of items bought by customers lends itself to data mining analysis that ...... Frequent episode mining can be used here as part of an alarm management.

  3. Fast algorithm for automatically computing Strahler stream order

    Science.gov (United States)

    Lanfear, Kenneth J.

    1990-01-01

    An efficient algorithm was developed to determine Strahler stream order for segments of stream networks represented in a Geographic Information System (GIS). The algorithm correctly assigns Strahler stream order in topologically complex situations such as braided streams and multiple drainage outlets. Execution time varies nearly linearly with the number of stream segments in the network. This technique is expected to be particularly useful for studying the topology of dense stream networks derived from digital elevation model data.

  4. Methylmercury and dissolved organic carbon relationships in a wetland-rich watershed impacted by elevated sulfate from mining

    International Nuclear Information System (INIS)

    Berndt, Michael E.; Bavin, Travis K.

    2012-01-01

    Methylmercury (MeHg), dissolved organic carbon (DOC), and sulfate (SO 4 = ) relationships were investigated in the mining-influenced St. Louis River watershed in northeast Minnesota. Fewer wetlands and higher SO 4 = in the mining region lead to generally lower availability and solubility of DOC in mining streams compared to non-mining streams. MeHg concentrations, however, are similarly low in mining and non-mining streams during low flow periods, implying that the extra DOC found in non-mining streams carries little MeHg with it during these periods. High water levels elevated MeHg concentrations in both stream types owing to release from wetlands of DOC species that contain MeHg and remain relatively soluble in streams with elevated ionic strength. In-river methylation appeared to be a negligible component of the MeHg budget for the St. Louis River during this study as MeHg and DOC concentrations were intermediate to those observed in its mining-influenced and wetland-dominated tributaries. - Highlights: ► St. Louis River tributaries were sampled for MeHg, SO 4 = , and DOC. ► Mine land tributaries had elevated SO 4 = and low DOC compared to other streams. ► MeHg concentration ranges overlapped for mining and non-mining streams. ► MeHg is carried by a DOC component found in both types of streams. ► Mining streams lack the low-MeHg DOC type common in non-mining streams. - Methylmercury concentrations in mining and non-mining streams are controlled by quantity and quality of DOC.

  5. Text Mining.

    Science.gov (United States)

    Trybula, Walter J.

    1999-01-01

    Reviews the state of research in text mining, focusing on newer developments. The intent is to describe the disparate investigations currently included under the term text mining and provide a cohesive structure for these efforts. A summary of research identifies key organizations responsible for pushing the development of text mining. A section…

  6. Origin of acid mine drainage in Enugu

    International Nuclear Information System (INIS)

    Uma, K.O.

    1992-01-01

    Mine flooding is a serious problem in the Enugu Coal Mines and has led to the abandonment of two of the four mines. About 1800 m 3 of water is pumped out daily from the mines into the nearby streams. The source of this enormous volume of water has been established based on the hydrodynamics and hydrology of the area. Two prolific aquifers - an unconfined and a confined system - overlie the mines, but the mine water is derived principally from the unconfined aquifer. The pathway of flow is, provided by the numerous fractures connecting the two aquifers and the mine tunnel. The major hydrochemical activity resulting in pollution of the mine water occurs within the sumps in the floor of the longwalls. These sumps act as oxidation chambers where groundwater from the fractures mixes and subsequently reacts with sulfur-rich solutes released by coal mining. Contrary to general belief, the mine drainage has not seriously degraded the chemistry of receiving streams. The pH and electric conductivity, representing, the dissolved ions, were increased less than 10% of the values in the unaffected region

  7. Using remote sensing techniques and field-based structural analysis to explore new gold and associated mineral sites around Al-Hajar mine, Asir terrane, Arabian Shield

    Science.gov (United States)

    Sonbul, Abdullah R.; El-Shafei, Mohamed K.; Bishta, Adel Z.

    2016-05-01

    Modern earth resource satellites provide huge amounts of digital imagery at different resolutions. These satellite imageries are considered one of the most significant sources of data for mineral exploration. Image processing techniques were applied to the exposed rocks around the Al-Aqiq area of the Asir terrane in the southern part of the Arabian Shield. The area under study has two sub-parallel N-S trending metamorphic belts of green-schist facies. The first belt is located southeast of Al-Aqiq, where the Al-Hajar Gold Mine is situated. It is essentially composed of metavolcanics and metasedimentary rocks, and it is intruded by different plutonic rocks of primarily diorite, syenite and porphyritic granite. The second belt is located northwest of Al-Aqiq, and it is composed of metavolcanics and metasedimentary rocks and is intruded by granite bodies. The current study aimed to distinguish the lithological units, detect and map the alteration zones, and extract the major fault lineaments around the Al-Hajar gold prospect. Digital satellite imageries, including Landsat 7 ETM + multispectral and panchromatic and SPOT-5 were used in addition to field verification. Areas with similar spectral signatures to the prospect were identified in the nearby metamorphic belt; it was considered as a target area and was inspected in the field. The relationships between the alteration zones, the mineral deposits and the structural elements were used to locate the ore-bearing zones in the subsurface. The metasedimentary units of the target area showed a dextral-ductile shearing top-to-the-north and the presence of dominant mineralized quartz vein-system. The area to the north of the Al-Hajar prospect showed also sub-parallel shear zones along which different types of alterations were detected. Field-based criteria such as hydrothermal breccia, jasper, iron gossans and porphyritic granite strongly indicate the presence of porphyry-type ore deposits in Al-Hajar metamorphic belt that

  8. Data mining for bioinformatics applications

    CERN Document Server

    Zengyou, He

    2015-01-01

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

  9. Data Mining Aplications in Livestock

    Directory of Open Access Journals (Sweden)

    Feyza ALEV ÇETİN

    2016-03-01

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

  10. Contract Mining versus Owner Mining

    African Journals Online (AJOL)

    Owner

    mining companies can concentrate on their core businesses while using specialists for ... 2 Definition of Contract and Owner. Mining ... equipment maintenance, scheduling and budgeting ..... No. Region. Amount Spent on. Contract Mining. ($ billion). Percent of. Total. 1 ... cost and productivity data based on a large range.

  11. Text Mining Applications and Theory

    CERN Document Server

    Berry, Michael W

    2010-01-01

    Text Mining: Applications and Theory presents the state-of-the-art algorithms for text mining from both the academic and industrial perspectives.  The contributors span several countries and scientific domains: universities, industrial corporations, and government laboratories, and demonstrate the use of techniques from machine learning, knowledge discovery, natural language processing and information retrieval to design computational models for automated text analysis and mining. This volume demonstrates how advancements in the fields of applied mathematics, computer science, machine learning

  12. Association and Sequence Mining in Web Usage

    Directory of Open Access Journals (Sweden)

    Claudia Elena DINUCA

    2011-06-01

    Full Text Available Web servers worldwide generate a vast amount of information on web users’ browsing activities. Several researchers have studied these so-called clickstream or web access log data to better understand and characterize web users. Clickstream data can be enriched with information about the content of visited pages and the origin (e.g., geographic, organizational of the requests. The goal of this project is to analyse user behaviour by mining enriched web access log data. With the continued growth and proliferation of e-commerce, Web services, and Web-based information systems, the volumes of click stream and user data collected by Web-based organizations in their daily operations has reached astronomical proportions. This information can be exploited in various ways, such as enhancing the effectiveness of websites or developing directed web marketing campaigns. The discovered patterns are usually represented as collections of pages, objects, or re-sources that are frequently accessed by groups of users with common needs or interests. The focus of this paper is to provide an overview how to use frequent pattern techniques for discovering different types of patterns in a Web log database. In this paper we will focus on finding association as a data mining technique to extract potentially useful knowledge from web usage data. I implemented in Java, using NetBeans IDE, a program for identification of pages’ association from sessions. For exemplification, we used the log files from a commercial web site.

  13. History of ventilation and of air conditioning in Dolni Rozinka uranium mines

    International Nuclear Information System (INIS)

    Voltr, S.

    1987-01-01

    At a time of the start of mining operations in the Dolni Rozinka uranium mine, ventilation had been provided using the underpressure technique with diagonal winding shafts. From 1967 the overpressure system had been used. The system is described in detail and its constraints are listed. In 1983, on the basis of an analysis and model tests, the ventilation system was replaced by a underpressure system which satisfied the current hygiene specifications, was costsaving and reliable. Since 1985, an air conditioning system has been in operation featuring mobile cooling units and a closed-circuit air conditioning water system that is separated from the mining water pumping system. In view of the favourable temperature factors of the deposit, the mobile air conditioning units are only installed in blind headings. When the through-flow wind stream is achieved, air conditioning is abandoned. (J.B.). 2 figs., 5 refs

  14. Assessment of levels and 'health-effects' of airborne particulate matter in mining, metal refining and metal working industries using nuclear and related analytical techniques

    International Nuclear Information System (INIS)

    2008-01-01

    The International Atomic Energy Agency (IAEA) has been supporting, over the years, several coordinated research programmes (CRPs) on various research topics related to environmental issues impacting human health. The primary aim of these CRPs has been to help enhance the research and development capabilities in the Member States, particularly among developing countries; to identify the sources of various environmental contaminants and evaluate their fate; and to provide for the basis of improved health among human populations by the use of nuclear and related analytical techniques. The CRP on Assessment of Levels and Health-Effects of Airborne Particulate Matter in Mining, Metal Refining and Metal Working Industries using nuclear and related analytical techniques focused on improving the competence for research on workplace monitoring in a variety of industrial environments. The personal monitoring of the APM (airborne particulate matter) of the exposed workforce was carried out for the first time by many participants. Nuclear and related analytical techniques, including the application of proton micro-beam, were used to generate the trace element concentration profiles in various biomarkers tissues of the exposed workers. The quality assurance/quality control (QA/QC) aspects related to the CRP were addressed through intercomparison analyses of APM on filter paper samples and freeze dried human urine samples to generate validated data. These data have helped to generate correlations between the occupational exposure measured and the magnitude of the biological response. Such new information is essential to evolve procedures to considerably reduce/eliminate the pollutants in the workplace environment and to make informed decisions on the evolution of standards in working environments aimed at preserving the health of workers. The purpose of this TECDOC is to provide an overview of the activities performed under the CRP by the participants. The overall achievements

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

    Science.gov (United States)

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

    1978-01-01

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

  16. Evaluation of the streaming-matrix method for discrete-ordinates duct-streaming calculations

    International Nuclear Information System (INIS)

    Clark, B.A.; Urban, W.T.; Dudziak, D.J.

    1983-01-01

    A new deterministic streaming technique called the Streaming Matrix Hybrid Method (SMHM) is applied to two realistic duct-shielding problems. The results are compared to standard discrete-ordinates and Monte Carlo calculations. The SMHM shows promise as an alternative deterministic streaming method to standard discrete-ordinates

  17. Process Mining Online Assessment Data

    Science.gov (United States)

    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…

  18. Process mining online assessment data

    NARCIS (Netherlands)

    Pechenizkiy, M.; Trcka, N.; Vasilyeva, E.; Aalst, van der W.M.P.; De Bra, P.M.E.; Barnes, T.; Desmarais, M.; Romero, C.; Ventura, S.

    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

  19. ANALYSIS OF WEB MINING APPLICATIONS AND BENEFICIAL AREAS

    Directory of Open Access Journals (Sweden)

    Khaleel Ahmad

    2011-10-01

    Full Text Available The main purpose of this paper is to study the process of Web mining techniques, features, application ( e-commerce and e-business and its beneficial areas. Web mining has become more popular and its widely used in varies application areas (such as business intelligent system, e-commerce and e-business. The e-commerce or e-business results are bettered by the application of the mining techniques such as data mining and text mining, among all the mining techniques web mining is better.

  20. Web Mining and Social Networking

    CERN Document Server

    Xu, Guandong; Li, Lin

    2011-01-01

    This book examines the techniques and applications involved in the Web Mining, Web Personalization and Recommendation and Web Community Analysis domains, including a detailed presentation of the principles, developed algorithms, and systems of the research in these areas. The applications of web mining, and the issue of how to incorporate web mining into web personalization and recommendation systems are also reviewed. Additionally, the volume explores web community mining and analysis to find the structural, organizational and temporal developments of web communities and reveal the societal s