WorldWideScience

Sample records for stream mining algorithms

  1. 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

  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. 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…

  4. 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).

  5. 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...

  6. Data streams: algorithms and applications

    National Research Council Canada - National Science Library

    Muthukrishnan, S

    2005-01-01

    ... massive data sets in general. Researchers in Theoretical Computer Science, Databases, IP Networking and Computer Systems are working on the data stream challenges. This article is an overview and survey of data stream algorithmics and is an updated version of [175]. S. Muthukrishnan Rutgers University, New Brunswick, NJ, USA, muthu@cs...

  7. Stream Deniable-Encryption Algorithms

    Directory of Open Access Journals (Sweden)

    N.A. Moldovyan

    2016-04-01

    Full Text Available A method for stream deniable encryption of secret message is proposed, which is computationally indistinguishable from the probabilistic encryption of some fake message. The method uses generation of two key streams with some secure block cipher. One of the key streams is generated depending on the secret key and the other one is generated depending on the fake key. The key streams are mixed with the secret and fake data streams so that the output ciphertext looks like the ciphertext produced by some probabilistic encryption algorithm applied to the fake message, while using the fake key. When the receiver or/and sender of the ciphertext are coerced to open the encryption key and the source message, they open the fake key and the fake message. To disclose their lie the coercer should demonstrate possibility of the alternative decryption of the ciphertext, however this is a computationally hard problem.

  8. Streaming Algorithms for Line Simplification

    DEFF Research Database (Denmark)

    Abam, Mohammad; de Berg, Mark; Hachenberger, Peter

    2010-01-01

    this problem in a streaming setting, where we only have a limited amount of storage, so that we cannot store all the points. We analyze the competitive ratio of our algorithms, allowing resource augmentation: we let our algorithm maintain a simplification with 2k (internal) points and compare the error of our...... simplification to the error of the optimal simplification with k points. We obtain the algorithms with O(1) competitive ratio for three cases: convex paths, where the error is measured using the Hausdorff distance (or Fréchet distance), xy-monotone paths, where the error is measured using the Hausdorff distance...... (or Fréchet distance), and general paths, where the error is measured using the Fréchet distance. In the first case the algorithm needs O(k) additional storage, and in the latter two cases the algorithm needs O(k 2) additional storage....

  9. 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

  10. Contrast data mining concepts, algorithms, and applications

    CERN Document Server

    Dong, Guozhu

    2012-01-01

    A Fruitful Field for Researching Data Mining Methodology and for Solving Real-Life Problems Contrast Data Mining: Concepts, Algorithms, and Applications collects recent results from this specialized area of data mining that have previously been scattered in the literature, making them more accessible to researchers and developers in data mining and other fields. The book not only presents concepts and techniques for contrast data mining, but also explores the use of contrast mining to solve challenging problems in various scientific, medical, and business domains. Learn from Real Case Studies

  11. The Top Ten Algorithms in Data Mining

    CERN Document Server

    Wu, Xindong

    2009-01-01

    From classification and clustering to statistical learning, association analysis, and link mining, this book covers the most important topics in data mining research. It presents the ten most influential algorithms used in the data mining community today. Each chapter provides a detailed description of the algorithm, a discussion of available software implementation, advanced topics, and exercises. With a simple data set, examples illustrate how each algorithm works and highlight the overall performance of each algorithm in a real-world application. Featuring contributions from leading researc

  12. Frequent Pattern Mining Algorithms for Data Clustering

    DEFF Research Database (Denmark)

    Zimek, Arthur; Assent, Ira; Vreeken, Jilles

    2014-01-01

    that frequent pattern mining was at the cradle of subspace clustering—yet, it quickly developed into an independent research field. In this chapter, we discuss how frequent pattern mining algorithms have been extended and generalized towards the discovery of local clusters in high-dimensional data......Discovering clusters in subspaces, or subspace clustering and related clustering paradigms, is a research field where we find many frequent pattern mining related influences. In fact, as the first algorithms for subspace clustering were based on frequent pattern mining algorithms, it is fair to say....... In particular, we discuss several example algorithms for subspace clustering or projected clustering as well as point out recent research questions and open topics in this area relevant to researchers in either clustering or pattern mining...

  13. URL Mining Using Agglomerative Clustering Algorithm

    Directory of Open Access Journals (Sweden)

    Chinmay R. Deshmukh

    2015-02-01

    Full Text Available Abstract The tremendous growth of the web world incorporates application of data mining techniques to the web logs. Data Mining and World Wide Web encompasses an important and active area of research. Web log mining is analysis of web log files with web pages sequences. Web mining is broadly classified as web content mining web usage mining and web structure mining. Web usage mining is a technique to discover usage patterns from Web data in order to understand and better serve the needs of Web-based applications. URL mining refers to a subclass of Web mining that helps us to investigate the details of a Uniform Resource Locator. URL mining can be advantageous in the fields of security and protection. The paper introduces a technique for mining a collection of user transactions with an Internet search engine to discover clusters of similar queries and similar URLs. The information we exploit is a clickthrough data each record consist of a users query to a search engine along with the URL which the user selected from among the candidates offered by search engine. By viewing this dataset as a bipartite graph with the vertices on one side corresponding to queries and on the other side to URLs one can apply an agglomerative clustering algorithm to the graphs vertices to identify related queries and URLs.

  14. 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.

  15. PRESEE: an MDL/MML algorithm to time-series stream segmenting.

    Science.gov (United States)

    Xu, Kaikuo; Jiang, Yexi; Tang, Mingjie; Yuan, Changan; Tang, Changjie

    2013-01-01

    Time-series stream is one of the most common data types in data mining field. It is prevalent in fields such as stock market, ecology, and medical care. Segmentation is a key step to accelerate the processing speed of time-series stream mining. Previous algorithms for segmenting mainly focused on the issue of ameliorating precision instead of paying much attention to the efficiency. Moreover, the performance of these algorithms depends heavily on parameters, which are hard for the users to set. In this paper, we propose PRESEE (parameter-free, real-time, and scalable time-series stream segmenting algorithm), which greatly improves the efficiency of time-series stream segmenting. PRESEE is based on both MDL (minimum description length) and MML (minimum message length) methods, which could segment the data automatically. To evaluate the performance of PRESEE, we conduct several experiments on time-series streams of different types and compare it with the state-of-art algorithm. The empirical results show that PRESEE is very efficient for real-time stream datasets by improving segmenting speed nearly ten times. The novelty of this algorithm is further demonstrated by the application of PRESEE in segmenting real-time stream datasets from ChinaFLUX sensor networks data stream.

  16. 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.

  17. Quantum algorithm for association rules mining

    Science.gov (United States)

    Yu, Chao-Hua; Gao, Fei; Wang, Qing-Le; Wen, Qiao-Yan

    2016-10-01

    Association rules mining (ARM) is one of the most important problems in knowledge discovery and data mining. Given a transaction database that has a large number of transactions and items, the task of ARM is to acquire consumption habits of customers by discovering the relationships between itemsets (sets of items). In this paper, we address ARM in the quantum settings and propose a quantum algorithm for the key part of ARM, finding frequent itemsets from the candidate itemsets and acquiring their supports. Specifically, for the case in which there are Mf(k ) frequent k -itemsets in the Mc(k ) candidate k -itemsets (Mf(k )≤Mc(k ) ), our algorithm can efficiently mine these frequent k -itemsets and estimate their supports by using parallel amplitude estimation and amplitude amplification with complexity O (k/√{Mc(k )Mf(k ) } ɛ ) , where ɛ is the error for estimating the supports. Compared with the classical counterpart, i.e., the classical sampling-based algorithm, whose complexity is O (k/Mc(k ) ɛ2) , our quantum algorithm quadratically improves the dependence on both ɛ and Mc(k ) in the best case when Mf(k )≪Mc(k ) and on ɛ alone in the worst case when Mf(k )≈Mc(k ) .

  18. 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)

  19. 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)

  20. 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.

  1. Recommending Learning Activities in Social Network Using Data Mining Algorithms

    Science.gov (United States)

    Mahnane, Lamia

    2017-01-01

    In this paper, we show how data mining algorithms (e.g. Apriori Algorithm (AP) and Collaborative Filtering (CF)) is useful in New Social Network (NSN-AP-CF). "NSN-AP-CF" processes the clusters based on different learning styles. Next, it analyzes the habits and the interests of the users through mining the frequent episodes by the…

  2. Data mining theories, algorithms, and examples

    CERN Document Server

    Ye, Nong

    2013-01-01

    AN OVERVIEW OF DATA MINING METHODOLOGIESIntroduction to data mining methodologiesMETHODOLOGIES FOR MINING CLASSIFICATION AND PREDICTION PATTERNSRegression modelsBayes classifiersDecision treesMulti-layer feedforward artificial neural networksSupport vector machinesSupervised clusteringMETHODOLOGIES FOR MINING CLUSTERING AND ASSOCIATION PATTERNSHierarchical clusteringPartitional clusteringSelf-organized mapProbability distribution estimationAssociation rulesBayesian networksMETHODOLOGIES FOR MINING DATA REDUCTION PATTERNSPrincipal components analysisMulti-dimensional scalingLatent variable anal

  3. STREAMFINDER I: A New Algorithm for detecting Stellar Streams

    Science.gov (United States)

    Malhan, Khyati; Ibata, Rodrigo A.

    2018-04-01

    We have designed a powerful new algorithm to detect stellar streams in an automated and systematic way. The algorithm, which we call the STREAMFINDER, is well suited for finding dynamically cold and thin stream structures that may lie along any simple or complex orbits in Galactic stellar surveys containing any combination of positional and kinematic information. In the present contribution we introduce the algorithm, lay out the ideas behind it, explain the methodology adopted to detect streams and detail its workings by running it on a suite of simulations of mock Galactic survey data of similar quality to that expected from the ESA/Gaia mission. We show that our algorithm is able to detect even ultra-faint stream features lying well below previous detection limits. Tests show that our algorithm will be able to detect distant halo stream structures >10° long containing as few as ˜15 members (ΣG ˜ 33.6 mag arcsec-2) in the Gaia dataset.

  4. 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.

  5. A Mining Algorithm for Extracting Decision Process Data Models

    Directory of Open Access Journals (Sweden)

    Cristina-Claudia DOLEAN

    2011-01-01

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

  6. 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

  7. Image Encryption Using a Lightweight Stream Encryption Algorithm

    Directory of Open Access Journals (Sweden)

    Saeed Bahrami

    2012-01-01

    Full Text Available Security of the multimedia data including image and video is one of the basic requirements for the telecommunications and computer networks. In this paper, we consider a simple and lightweight stream encryption algorithm for image encryption, and a series of tests are performed to confirm suitability of the described encryption algorithm. These tests include visual test, histogram analysis, information entropy, encryption quality, correlation analysis, differential analysis, and performance analysis. Based on this analysis, it can be concluded that the present algorithm in comparison to A5/1 and W7 stream ciphers has the same security level, is better in terms of the speed of performance, and is used for real-time applications.

  8. Continuity-Aware Scheduling Algorithm for Scalable Video Streaming

    Directory of Open Access Journals (Sweden)

    Atinat Palawan

    2016-05-01

    Full Text Available The consumer demand for retrieving and delivering visual content through consumer electronic devices has increased rapidly in recent years. The quality of video in packet networks is susceptible to certain traffic characteristics: average bandwidth availability, loss, delay and delay variation (jitter. This paper presents a scheduling algorithm that modifies the stream of scalable video to combat jitter. The algorithm provides unequal look-ahead by safeguarding the base layer (without the need for overhead of the scalable video. The results of the experiments show that our scheduling algorithm reduces the number of frames with a violated deadline and significantly improves the continuity of the video stream without compromising the average Y Peek Signal-to-Noise Ratio (PSNR.

  9. Towards an evaluation framework for process mining algorithms

    NARCIS (Netherlands)

    Rozinat, A.; Alves De Medeiros, A.K.; Günther, C.W.; Weijters, A.J.M.M.; Aalst, van der W.M.P.

    2007-01-01

    Although there has been a lot of progress in developing process mining algorithms in recent years, no effort has been put in developing a common means of assessing the quality of the models discovered by these algorithms. In this paper, we outline elements of an evaluation framework that is intended

  10. Research on parallel algorithm for sequential pattern mining

    Science.gov (United States)

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

    2008-03-01

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

  11. Randomized algorithms in automatic control and data mining

    CERN Document Server

    Granichin, Oleg; Toledano-Kitai, Dvora

    2015-01-01

    In the fields of data mining and control, the huge amount of unstructured data and the presence of uncertainty in system descriptions have always been critical issues. The book Randomized Algorithms in Automatic Control and Data Mining introduces the readers to the fundamentals of randomized algorithm applications in data mining (especially clustering) and in automatic control synthesis. The methods proposed in this book guarantee that the computational complexity of classical algorithms and the conservativeness of standard robust control techniques will be reduced. It is shown that when a problem requires "brute force" in selecting among options, algorithms based on random selection of alternatives offer good results with certain probability for a restricted time and significantly reduce the volume of operations.

  12. pubmed.mineR: An R package with text-mining algorithms to ...

    Indian Academy of Sciences (India)

    2015-09-29

    Sep 29, 2015 ... using text-mining algorithms for biomedical research pur- poses. ... studies are described to illustrate some potential uses of ... This is the most applied task. ... other alphabets (for example, Greek alphabets) and hyphens.

  13. 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.

  14. An Incremental High-Utility Mining Algorithm with Transaction Insertion

    Science.gov (United States)

    Gan, Wensheng; Zhang, Binbin

    2015-01-01

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

  15. An Incremental High-Utility Mining Algorithm with Transaction Insertion

    Directory of Open Access Journals (Sweden)

    Jerry Chun-Wei Lin

    2015-01-01

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

  16. 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...

  17. An Evolutionary Algorithm to Mine High-Utility Itemsets

    Directory of Open Access Journals (Sweden)

    Jerry Chun-Wei Lin

    2015-01-01

    Full Text Available High-utility itemset mining (HUIM is a critical issue in recent years since it can be used to reveal the profitable products by considering both the quantity and profit factors instead of frequent itemset mining (FIM of association rules (ARs. In this paper, an evolutionary algorithm is presented to efficiently mine high-utility itemsets (HUIs based on the binary particle swarm optimization. A maximal pattern (MP-tree strcutrue is further designed to solve the combinational problem in the evolution process. Substantial experiments on real-life datasets show that the proposed binary PSO-based algorithm has better results compared to the state-of-the-art GA-based algorithm.

  18. 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.

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

    Science.gov (United States)

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

    2017-08-01

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

  20. 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

  1. Analysing Customer Opinions with Text Mining Algorithms

    Science.gov (United States)

    Consoli, Domenico

    2009-08-01

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

  2. An Application of Data Mining Algorithms for Shipbuilding Cost Estimation

    NARCIS (Netherlands)

    Kaluzny, B.L.; Barbici, S.; Berg, G.; Chiomento, R.; Derpanis,D.; Jonsson, U.; Shaw, R.H.A.D.; Smit, M.C.; Ramaroson, F.

    2011-01-01

    This article presents a novel application of known data mining algorithms to the problem of estimating the cost of ship development and construction. The work is a product of North Atlantic Treaty Organization Research and Technology Organization Systems Analysis and Studies 076 Task Group “NATO

  3. An Approximate L p Difference Algorithm for Massive Data Streams

    Directory of Open Access Journals (Sweden)

    Jessica H. Fong

    2001-12-01

    Full Text Available Several recent papers have shown how to approximate the difference ∑ i |a i-b i | or ∑|a i-b i | 2 between two functions, when the function values a i and b i are given in a data stream, and their order is chosen by an adversary. These algorithms use little space (much less than would be needed to store the entire stream and little time to process each item in the stream. They approximate with small relative error. Using different techniques, we show how to approximate the L p-difference ∑ i |a i-b i | p for any rational-valued p∈(0,2], with comparable efficiency and error. We also show how to approximate ∑ i |a i-b i | p for larger values of p but with a worse error guarantee. Our results fill in gaps left by recent work, by providing an algorithm that is precisely tunable for the application at hand. These results can be used to assess the difference between two chronologically or physically separated massive data sets, making one quick pass over each data set, without buffering the data or requiring the data source to pause. For example, one can use our techniques to judge whether the traffic on two remote network routers are similar without requiring either router to transmit a copy of its traffic. A web search engine could use such algorithms to construct a library of small ``sketches,'' one for each distinct page on the web; one can approximate the extent to which new web pages duplicate old ones by comparing the sketches of the web pages. Such techniques will become increasingly important as the enormous scale, distributional nature, and one-pass processing requirements of data sets become more commonplace.

  4. 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

  5. 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

  6. Predicting mining activity with parallel genetic algorithms

    Science.gov (United States)

    Talaie, S.; Leigh, R.; Louis, S.J.; Raines, G.L.; Beyer, H.G.; O'Reilly, U.M.; Banzhaf, Arnold D.; Blum, W.; Bonabeau, C.; Cantu-Paz, E.W.; ,; ,

    2005-01-01

    We explore several different techniques in our quest to improve the overall model performance of a genetic algorithm calibrated probabilistic cellular automata. We use the Kappa statistic to measure correlation between ground truth data and data predicted by the model. Within the genetic algorithm, we introduce a new evaluation function sensitive to spatial correctness and we explore the idea of evolving different rule parameters for different subregions of the land. We reduce the time required to run a simulation from 6 hours to 10 minutes by parallelizing the code and employing a 10-node cluster. Our empirical results suggest that using the spatially sensitive evaluation function does indeed improve the performance of the model and our preliminary results also show that evolving different rule parameters for different regions tends to improve overall model performance. Copyright 2005 ACM.

  7. A partition enhanced mining algorithm for distributed association rule mining systems

    Directory of Open Access Journals (Sweden)

    A.O. Ogunde

    2015-11-01

    Full Text Available The extraction of patterns and rules from large distributed databases through existing Distributed Association Rule Mining (DARM systems is still faced with enormous challenges such as high response times, high communication costs and inability to adapt to the constantly changing databases. In this work, a Partition Enhanced Mining Algorithm (PEMA is presented to address these problems. In PEMA, the Association Rule Mining Coordinating Agent receives a request and decides the appropriate data sites, partitioning strategy and mining agents to use. The mining process is divided into two stages. In the first stage, the data agents horizontally segment the databases with small average transaction length into relatively smaller partitions based on the number of available sites and the available memory. On the other hand, databases with relatively large average transaction length were vertically partitioned. After this, Mobile Agent-Based Association Rule Mining-Agents, which are the mining agents, carry out the discovery of the local frequent itemsets. At the second stage, the local frequent itemsets were incrementally integrated by the from one data site to another to get the global frequent itemsets. This reduced the response time and communication cost in the system. Results from experiments conducted on real datasets showed that the average response time of PEMA showed an improvement over existing algorithms. Similarly, PEMA incurred lower communication costs with average size of messages exchanged lower when compared with benchmark DARM systems. This result showed that PEMA could be efficiently deployed for efficient discovery of valuable knowledge in distributed databases.

  8. 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

  9. 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…

  10. Developing and Implementing the Data Mining Algorithms in RAVEN

    International Nuclear Information System (INIS)

    Sen, Ramazan Sonat; Maljovec, Daniel Patrick; Alfonsi, Andrea; Rabiti, Cristian

    2015-01-01

    The RAVEN code is becoming a comprehensive tool to perform probabilistic risk assessment, uncertainty quantification, and verification and validation. The RAVEN code is being developed to support many programs and to provide a set of methodologies and algorithms for advanced analysis. Scientific computer codes can generate enormous amounts of data. To post-process and analyze such data might, in some cases, take longer than the initial software runtime. Data mining algorithms/methods help in recognizing and understanding patterns in the data, and thus discover knowledge in databases. The methodologies used in the dynamic probabilistic risk assessment or in uncertainty and error quantification analysis couple system/physics codes with simulation controller codes, such as RAVEN. RAVEN introduces both deterministic and stochastic elements into the simulation while the system/physics code model the dynamics deterministically. A typical analysis is performed by sampling values of a set of parameter values. A major challenge in using dynamic probabilistic risk assessment or uncertainty and error quantification analysis for a complex system is to analyze the large number of scenarios generated. Data mining techniques are typically used to better organize and understand data, i.e. recognizing patterns in the data. This report focuses on development and implementation of Application Programming Interfaces (APIs) for different data mining algorithms, and the application of these algorithms to different databases.

  11. Developing and Implementing the Data Mining Algorithms in RAVEN

    Energy Technology Data Exchange (ETDEWEB)

    Sen, Ramazan Sonat [Idaho National Lab. (INL), Idaho Falls, ID (United States); Maljovec, Daniel Patrick [Idaho National Lab. (INL), Idaho Falls, ID (United States); Alfonsi, Andrea [Idaho National Lab. (INL), Idaho Falls, ID (United States); Rabiti, Cristian [Idaho National Lab. (INL), Idaho Falls, ID (United States)

    2015-09-01

    The RAVEN code is becoming a comprehensive tool to perform probabilistic risk assessment, uncertainty quantification, and verification and validation. The RAVEN code is being developed to support many programs and to provide a set of methodologies and algorithms for advanced analysis. Scientific computer codes can generate enormous amounts of data. To post-process and analyze such data might, in some cases, take longer than the initial software runtime. Data mining algorithms/methods help in recognizing and understanding patterns in the data, and thus discover knowledge in databases. The methodologies used in the dynamic probabilistic risk assessment or in uncertainty and error quantification analysis couple system/physics codes with simulation controller codes, such as RAVEN. RAVEN introduces both deterministic and stochastic elements into the simulation while the system/physics code model the dynamics deterministically. A typical analysis is performed by sampling values of a set of parameter values. A major challenge in using dynamic probabilistic risk assessment or uncertainty and error quantification analysis for a complex system is to analyze the large number of scenarios generated. Data mining techniques are typically used to better organize and understand data, i.e. recognizing patterns in the data. This report focuses on development and implementation of Application Programming Interfaces (APIs) for different data mining algorithms, and the application of these algorithms to different databases.

  12. Symmetric Stream Cipher using Triple Transposition Key Method and Base64 Algorithm for Security Improvement

    Science.gov (United States)

    Nurdiyanto, Heri; Rahim, Robbi; Wulan, Nur

    2017-12-01

    Symmetric type cryptography algorithm is known many weaknesses in encryption process compared with asymmetric type algorithm, symmetric stream cipher are algorithm that works on XOR process between plaintext and key, to improve the security of symmetric stream cipher algorithm done improvisation by using Triple Transposition Key which developed from Transposition Cipher and also use Base64 algorithm for encryption ending process, and from experiment the ciphertext that produced good enough and very random.

  13. Classification of Internet banking customers using data mining algorithms

    Directory of Open Access Journals (Sweden)

    Reza Radfar

    2014-03-01

    Full Text Available Classifying customers using data mining algorithms, enables banks to keep old customers loyality while attracting new ones. Using decision tree as a data mining technique, we can optimize customer classification provided that the appropriate decision tree is selected. In this article we have presented an appropriate model to classify customers who use internet banking service. The model is developed based on CRISP-DM standard and we have used real data of Sina bank’s Internet bank. In compare to other decision trees, ours is based on both optimization and accuracy factors that recognizes new potential internet banking customers using a three level classification, which is low/medium and high. This is a practical, documentary-based research. Mining customer rules enables managers to make policies based on found out patterns in order to have a better perception of what customers really desire.

  14. An Optimization Routing Algorithm for Green Communication in Underground Mines

    Directory of Open Access Journals (Sweden)

    Heng Xu

    2018-06-01

    Full Text Available With the long-term dependence of humans on ore-based energy, underground mines are utilized around the world, and underground mining is often dangerous. Therefore, many underground mines have established networks that manage and acquire information from sensor nodes deployed on miners and in other places. Since the power supplies of many mobile sensor nodes are batteries, green communication is an effective approach of reducing the energy consumption of a network and extending its longevity. To reduce the energy consumption of networks, all factors that negatively influence the lifetime should be considered. The degree constraint minimum spanning tree (DCMST is introduced in this study to consider all the heterogeneous factors and assign weights for the next step of the evaluation. Then, a genetic algorithm (GA is introduced to cluster sensor nodes in the network and balance energy consumption according to several heterogeneous factors and routing paths from DCMST. Based on a comparison of the simulation results, the optimization routing algorithm proposed in this study for use in green communication in underground mines can effectively reduce the network energy consumption and extend the lifetimes of networks.

  15. MINING ON CAR DATABASE EMPLOYING LEARNING AND CLUSTERING ALGORITHMS

    OpenAIRE

    Muhammad Rukunuddin Ghalib; Shivam Vohra; Sunish Vohra; Akash Juneja

    2013-01-01

    In data mining, classification is a form of data analysis that can be used to extract models describing important data classes. Two of the known learning algorithms used are Naïve Bayesian (NB) and SMO (Self-Minimal-Optimisation) .Thus the following two learning algorithms are used on a Car review database and thus a model is hence created which predicts the characteristic of a review comment after getting trained. It was found that model successfully predicted correctly about the review comm...

  16. Mining the National Career Assessment Examination Result Using Clustering Algorithm

    Science.gov (United States)

    Pagudpud, M. V.; Palaoag, T. T.; Padirayon, L. M.

    2018-03-01

    Education is an essential process today which elicits authorities to discover and establish innovative strategies for educational improvement. This study applied data mining using clustering technique for knowledge extraction from the National Career Assessment Examination (NCAE) result in the Division of Quirino. The NCAE is an examination given to all grade 9 students in the Philippines to assess their aptitudes in the different domains. Clustering the students is helpful in identifying students’ learning considerations. With the use of the RapidMiner tool, clustering algorithms such as Density-Based Spatial Clustering of Applications with Noise (DBSCAN), k-means, k-medoid, expectation maximization clustering, and support vector clustering algorithms were analyzed. The silhouette indexes of the said clustering algorithms were compared, and the result showed that the k-means algorithm with k = 3 and silhouette index equal to 0.196 is the most appropriate clustering algorithm to group the students. Three groups were formed having 477 students in the determined group (cluster 0), 310 proficient students (cluster 1) and 396 developing students (cluster 2). The data mining technique used in this study is essential in extracting useful information from the NCAE result to better understand the abilities of students which in turn is a good basis for adopting teaching strategies.

  17. RStorm: Developing and Testing Streaming Algorithms in R

    NARCIS (Netherlands)

    Kaptein, M.C.

    2014-01-01

    Streaming data, consisting of indefinitely evolving sequences, are becoming ubiquitous in many branches of science and in various applications. Computer scientists have developed streaming applications such as Storm and the S4 distributed stream computing platform1 to deal with data streams.

  18. RStorm : Developing and testing streaming algorithms in R

    NARCIS (Netherlands)

    Kaptein, M.C.

    2014-01-01

    Streaming data, consisting of indefinitely evolving sequences, are becoming ubiquitous in many branches of science and in various applications. Computer scientists have developed streaming applications such as Storm and the S4 distributed stream computing platform1 to deal with data streams.

  19. 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.

  20. 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.

  1. An algorithm of opinion leaders mining based on signed network

    Science.gov (United States)

    Cao, Linlin; Zheng, Mingchun; Zhang, Yuanyuan; Zhang, Fuming

    2018-04-01

    With the rapid development of mobile Internet, user gradually become the leader of social media, the abruptly rise of new media has changed the traditional information's dissemination pattern and regularity. There is new era significance of opinion leaders, gatekeepers in the classical theory of mass communication, and it has further expansion and extension to a certain extent. In the existing mining of opinion leaders, it is mainly from the research of network structure and user behavior without considering an important attribute: whether the user has a real impact. In this paper, we take the symbolic network as the research tool, by giving symbol which correspondingly represents support or oppose to the link about point of view relationship between users and combining traditional algorithms of mining with symbolism which can describe the change of view between users, we will get the opinion leader who has real impact on users, then the result is more accurate and effective.

  2. 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.

  3. 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.

  4. Comparison of Firefly algorithm and Artificial Immune System algorithm for lot streaming in -machine flow shop scheduling

    Directory of Open Access Journals (Sweden)

    G. Vijay Chakaravarthy

    2012-11-01

    Full Text Available Lot streaming is a technique used to split the processing of lots into several sublots (transfer batches to allow the overlapping of operations in a multistage manufacturing systems thereby shortening the production time (makespan. The objective of this paper is to minimize the makespan and total flow time of -job, -machine lot streaming problem in a flow shop with equal and variable size sublots and also to determine the optimal sublot size. In recent times researchers are concentrating and applying intelligent heuristics to solve flow shop problems with lot streaming. In this research, Firefly Algorithm (FA and Artificial Immune System (AIS algorithms are used to solve the problem. The results obtained by the proposed algorithms are also compared with the performance of other worked out traditional heuristics. The computational results shows that the identified algorithms are more efficient, effective and better than the algorithms already tested for this problem.

  5. 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.

  6. 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

  7. 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...

  8. 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 ...

  9. Using internal evaluation measures to validate the quality of diverse stream clustering algorithms

    NARCIS (Netherlands)

    Hassani, M.; Seidl, T.

    2017-01-01

    Measuring the quality of a clustering algorithm has shown to be as important as the algorithm itself. It is a crucial part of choosing the clustering algorithm that performs best for an input data. Streaming input data have many features that make them much more challenging than static ones. They

  10. 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

  11. 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

  12. Application of Data Mining Algorithm to Recipient of Motorcycle Installment

    Directory of Open Access Journals (Sweden)

    Harry Dhika

    2015-12-01

    Full Text Available The study was conducted in the subsidiaries that provide services of finance related to the purchase of a motorcycle on credit. At the time of applying, consumers enter their personal data. Based on the personal data, it will be known whether the consumer credit data is approved or rejected. From 224 consumer data obtained, it is known that the number of consumers whose applications are approved is 87% or about 217 consumers and consumers whose application is rejected is 16% or as much as 6 consumers. Acceptance of motorcycle financing on credit by using the method of applying the algorithm through CRIS-P DM is the industry standard in the processing of data mining. The algorithm used in the decision making is the algorithm C4.5. The results obtained previously, the level of accuracy is measured with the Confusion Matrix and Receiver Operating characteristic (ROC. Evaluation of the Confusion Matrix is intended to seek the value of accuracy, precision value, and the value of recall data. While the Receiver Operating Characteristic (ROC is used to find data tables and comparison Area Under Curve (AUC.

  13. 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

  14. 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

  15. 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.

  16. 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

  17. AN EFFECTIVE RECOMMENDATIONS BY DIFFUSION ALGORITHM FOR WEB GRAPH MINING

    Directory of Open Access Journals (Sweden)

    S. Vasukipriya

    2013-04-01

    Full Text Available The information on the World Wide Web grows in an explosive rate. Societies are relying more on the Web for their miscellaneous needs of information. Recommendation systems are active information filtering systems that attempt to present the information items like movies, music, images, books recommendations, tags recommendations, query suggestions, etc., to the users. Various kinds of data bases are used for the recommendations; fundamentally these data bases can be molded in the form of many types of graphs. Aiming at provided that a general framework on effective DR (Recommendations by Diffusion algorithm for web graphs mining. First introduce a novel graph diffusion model based on heat diffusion. This method can be applied to both undirected graphs and directed graphs. Then it shows how to convert different Web data sources into correct graphs in our models.

  18. 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

  19. A genetic algorithm approach to recognition and data mining

    Energy Technology Data Exchange (ETDEWEB)

    Punch, W.F.; Goodman, E.D.; Min, Pei [Michigan State Univ., East Lansing, MI (United States)] [and others

    1996-12-31

    We review here our use of genetic algorithm (GA) and genetic programming (GP) techniques to perform {open_quotes}data mining,{close_quotes} the discovery of particular/important data within large datasets, by finding optimal data classifications using known examples. Our first experiments concentrated on the use of a K-nearest neighbor algorithm in combination with a GA. The GA selected weights for each feature so as to optimize knn classification based on a linear combination of features. This combined GA-knn approach was successfully applied to both generated and real-world data. We later extended this work by substituting a GP for the GA. The GP-knn could not only optimize data classification via linear combinations of features but also determine functional relationships among the features. This allowed for improved performance and new information on important relationships among features. We review the effectiveness of the overall approach on examples from biology and compare the effectiveness of the GA and GP.

  20. 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.

  1. 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.

  2. 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:

  3. 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...

  4. Mining algorithm for association rules in big data based on Hadoop

    Science.gov (United States)

    Fu, Chunhua; Wang, Xiaojing; Zhang, Lijun; Qiao, Liying

    2018-04-01

    In order to solve the problem that the traditional association rules mining algorithm has been unable to meet the mining needs of large amount of data in the aspect of efficiency and scalability, take FP-Growth as an example, the algorithm is realized in the parallelization based on Hadoop framework and Map Reduce model. On the basis, it is improved using the transaction reduce method for further enhancement of the algorithm's mining efficiency. The experiment, which consists of verification of parallel mining results, comparison on efficiency between serials and parallel, variable relationship between mining time and node number and between mining time and data amount, is carried out in the mining results and efficiency by Hadoop clustering. Experiments show that the paralleled FP-Growth algorithm implemented is able to accurately mine frequent item sets, with a better performance and scalability. It can be better to meet the requirements of big data mining and efficiently mine frequent item sets and association rules from large dataset.

  5. 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...

  6. 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.

  7. Study on the Method of Association Rules Mining Based on Genetic Algorithm and Application in Analysis of Seawater Samples

    Directory of Open Access Journals (Sweden)

    Qiuhong Sun

    2014-04-01

    Full Text Available Based on the data mining research, the data mining based on genetic algorithm method, the genetic algorithm is briefly introduced, while the genetic algorithm based on two important theories and theoretical templates principle implicit parallelism is also discussed. Focuses on the application of genetic algorithms for association rule mining method based on association rule mining, this paper proposes a genetic algorithm fitness function structure, data encoding, such as the title of the improvement program, in particular through the early issues study, proposed the improved adaptive Pc, Pm algorithm is applied to the genetic algorithm, thereby improving efficiency of the algorithm. Finally, a genetic algorithm based association rule mining algorithm, and be applied in sea water samples database in data mining and prove its effective.

  8. 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.

  9. A real time sorting algorithm to time sort any deterministic time disordered data stream

    Science.gov (United States)

    Saini, J.; Mandal, S.; Chakrabarti, A.; Chattopadhyay, S.

    2017-12-01

    In new generation high intensity high energy physics experiments, millions of free streaming high rate data sources are to be readout. Free streaming data with associated time-stamp can only be controlled by thresholds as there is no trigger information available for the readout. Therefore, these readouts are prone to collect large amount of noise and unwanted data. For this reason, these experiments can have output data rate of several orders of magnitude higher than the useful signal data rate. It is therefore necessary to perform online processing of the data to extract useful information from the full data set. Without trigger information, pre-processing on the free streaming data can only be done with time based correlation among the data set. Multiple data sources have different path delays and bandwidth utilizations and therefore the unsorted merged data requires significant computational efforts for real time manifestation of sorting before analysis. Present work reports a new high speed scalable data stream sorting algorithm with its architectural design, verified through Field programmable Gate Array (FPGA) based hardware simulation. Realistic time based simulated data likely to be collected in an high energy physics experiment have been used to study the performance of the algorithm. The proposed algorithm uses parallel read-write blocks with added memory management and zero suppression features to make it efficient for high rate data-streams. This algorithm is best suited for online data streams with deterministic time disorder/unsorting on FPGA like hardware.

  10. STREAM PROCESSING ALGORITHMS FOR DYNAMIC 3D SCENE ANALYSIS

    Science.gov (United States)

    2018-02-15

    PROCESSING ALGORITHMS FOR DYNAMIC 3D SCENE ANALYSIS 5a. CONTRACT NUMBER FA8750-14-2-0072 5b. GRANT NUMBER N/A 5c. PROGRAM ELEMENT NUMBER 62788F 6...of Figures 1 The 3D processing pipeline flowchart showing key modules. . . . . . . . . . . . . . . . . 12 2 Overall view (data flow) of the proposed...pipeline flowchart showing key modules. from motion and bundle adjustment algorithm. By fusion of depth masks of the scene obtained from 3D

  11. Using an improved association rules mining optimization algorithm in web-based mobile-learning system

    Science.gov (United States)

    Huang, Yin; Chen, Jianhua; Xiong, Shaojun

    2009-07-01

    Mobile-Learning (M-learning) makes many learners get the advantages of both traditional learning and E-learning. Currently, Web-based Mobile-Learning Systems have created many new ways and defined new relationships between educators and learners. Association rule mining is one of the most important fields in data mining and knowledge discovery in databases. Rules explosion is a serious problem which causes great concerns, as conventional mining algorithms often produce too many rules for decision makers to digest. Since Web-based Mobile-Learning System collects vast amounts of student profile data, data mining and knowledge discovery techniques can be applied to find interesting relationships between attributes of learners, assessments, the solution strategies adopted by learners and so on. Therefore ,this paper focus on a new data-mining algorithm, combined with the advantages of genetic algorithm and simulated annealing algorithm , called ARGSA(Association rules based on an improved Genetic Simulated Annealing Algorithm), to mine the association rules. This paper first takes advantage of the Parallel Genetic Algorithm and Simulated Algorithm designed specifically for discovering association rules. Moreover, the analysis and experiment are also made to show the proposed method is superior to the Apriori algorithm in this Mobile-Learning system.

  12. Comparison analysis for classification algorithm in data mining and the study of model use

    Science.gov (United States)

    Chen, Junde; Zhang, Defu

    2018-04-01

    As a key technique in data mining, classification algorithm was received extensive attention. Through an experiment of classification algorithm in UCI data set, we gave a comparison analysis method for the different algorithms and the statistical test was used here. Than that, an adaptive diagnosis model for preventive electricity stealing and leakage was given as a specific case in the paper.

  13. 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...

  14. 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 ...

  15. 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

  16. HYBRID CHRIPTOGRAPHY STREAM CIPHER AND RSA ALGORITHM WITH DIGITAL SIGNATURE AS A KEY

    Directory of Open Access Journals (Sweden)

    Grace Lamudur Arta Sihombing

    2017-03-01

    Full Text Available Confidentiality of data is very important in communication. Many cyber crimes that exploit security holes for entry and manipulation. To ensure the security and confidentiality of the data, required a certain technique to encrypt data or information called cryptography. It is one of the components that can not be ignored in building security. And this research aimed to analyze the hybrid cryptography with symmetric key by using a stream cipher algorithm and asymmetric key by using RSA (Rivest Shamir Adleman algorithm. The advantages of hybrid cryptography is the speed in processing data using a symmetric algorithm and easy transfer of key using asymmetric algorithm. This can increase the speed of transaction processing data. Stream Cipher Algorithm using the image digital signature as a keys, that will be secured by the RSA algorithm. So, the key for encryption and decryption are different. Blum Blum Shub methods used to generate keys for the value p, q on the RSA algorithm. It will be very difficult for a cryptanalyst to break the key. Analysis of hybrid cryptography stream cipher and RSA algorithms with digital signatures as a key, indicates that the size of the encrypted file is equal to the size of the plaintext, not to be larger or smaller so that the time required for encryption and decryption process is relatively fast.

  17. A hybrid heuristic algorithm for the open-pit-mining operational planning problem.

    OpenAIRE

    Souza, Marcone Jamilson Freitas; Coelho, Igor Machado; Ribas, Sabir; Santos, Haroldo Gambini; Merschmann, Luiz Henrique de Campos

    2010-01-01

    This paper deals with the Open-Pit-Mining Operational Planning problem with dynamic truck allocation. The objective is to optimize mineral extraction in the mines by minimizing the number of mining trucks used to meet production goals and quality requirements. According to the literature, this problem is NPhard, so a heuristic strategy is justified. We present a hybrid algorithm that combines characteristics of two metaheuristics: Greedy Randomized Adaptive Search Procedures and General Varia...

  18. 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

  19. On the Suitability of Genetic-Based Algorithms for Data Mining

    NARCIS (Netherlands)

    Choenni, R.S.

    1998-01-01

    Data mining has as goal to extract knowledge from large databases. A database may be considered as a search space consisting of an enormous number of elements, and a mining algorithm as a search strategy. In general, an exhaustive search of the space is infeasible. Therefore, efficient search

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

    Science.gov (United States)

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

    2017-11-01

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

  1. A Streaming Distance Transform Algorithm for Neighborhood-Sequence Distances

    Directory of Open Access Journals (Sweden)

    Nicolas Normand

    2014-09-01

    Full Text Available We describe an algorithm that computes a “translated” 2D Neighborhood-Sequence Distance Transform (DT using a look up table approach. It requires a single raster scan of the input image and produces one line of output for every line of input. The neighborhood sequence is specified either by providing one period of some integer periodic sequence or by providing the rate of appearance of neighborhoods. The full algorithm optionally derives the regular (centered DT from the “translated” DT, providing the result image on-the-fly, with a minimal delay, before the input image is fully processed. Its efficiency can benefit all applications that use neighborhood- sequence distances, particularly when pipelined processing architectures are involved, or when the size of objects in the source image is limited.

  2. 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

  3. 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.

  4. pubmed.mineR: an R package with text-mining algorithms to analyse PubMed abstracts.

    Science.gov (United States)

    Rani, Jyoti; Shah, A B Rauf; Ramachandran, Srinivasan

    2015-10-01

    The PubMed literature database is a valuable source of information for scientific research. It is rich in biomedical literature with more than 24 million citations. Data-mining of voluminous literature is a challenging task. Although several text-mining algorithms have been developed in recent years with focus on data visualization, they have limitations such as speed, are rigid and are not available in the open source. We have developed an R package, pubmed.mineR, wherein we have combined the advantages of existing algorithms, overcome their limitations, and offer user flexibility and link with other packages in Bioconductor and the Comprehensive R Network (CRAN) in order to expand the user capabilities for executing multifaceted approaches. Three case studies are presented, namely, 'Evolving role of diabetes educators', 'Cancer risk assessment' and 'Dynamic concepts on disease and comorbidity' to illustrate the use of pubmed.mineR. The package generally runs fast with small elapsed times in regular workstations even on large corpus sizes and with compute intensive functions. The pubmed.mineR is available at http://cran.rproject. org/web/packages/pubmed.mineR.

  5. 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.

  6. 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

  7. A Streaming Algorithm for Online Estimation of Temporal and Spatial Extent of Delays

    Directory of Open Access Journals (Sweden)

    Kittipong Hiriotappa

    2017-01-01

    Full Text Available Knowing traffic congestion and its impact on travel time in advance is vital for proactive travel planning as well as advanced traffic management. This paper proposes a streaming algorithm to estimate temporal and spatial extent of delays online which can be deployed with roadside sensors. First, the proposed algorithm uses streaming input from individual sensors to detect a deviation from normal traffic patterns, referred to as anomalies, which is used as an early indication of delay occurrence. Then, a group of consecutive sensors that detect anomalies are used to temporally and spatially estimate extent of delay associated with the detected anomalies. Performance evaluations are conducted using a real-world data set collected by roadside sensors in Bangkok, Thailand, and the NGSIM data set collected in California, USA. Using NGSIM data, it is shown qualitatively that the proposed algorithm can detect consecutive occurrences of shockwaves and estimate their associated delays. Then, using a data set from Thailand, it is shown quantitatively that the proposed algorithm can detect and estimate delays associated with both recurring congestion and incident-induced nonrecurring congestion. The proposed algorithm also outperforms the previously proposed streaming algorithm.

  8. A Fast Density-Based Clustering Algorithm for Real-Time Internet of Things Stream

    Science.gov (United States)

    Ying Wah, Teh

    2014-01-01

    Data streams are continuously generated over time from Internet of Things (IoT) devices. The faster all of this data is analyzed, its hidden trends and patterns discovered, and new strategies created, the faster action can be taken, creating greater value for organizations. Density-based method is a prominent class in clustering data streams. It has the ability to detect arbitrary shape clusters, to handle outlier, and it does not need the number of clusters in advance. Therefore, density-based clustering algorithm is a proper choice for clustering IoT streams. Recently, several density-based algorithms have been proposed for clustering data streams. However, density-based clustering in limited time is still a challenging issue. In this paper, we propose a density-based clustering algorithm for IoT streams. The method has fast processing time to be applicable in real-time application of IoT devices. Experimental results show that the proposed approach obtains high quality results with low computation time on real and synthetic datasets. PMID:25110753

  9. A fast density-based clustering algorithm for real-time Internet of Things stream.

    Science.gov (United States)

    Amini, Amineh; Saboohi, Hadi; Wah, Teh Ying; Herawan, Tutut

    2014-01-01

    Data streams are continuously generated over time from Internet of Things (IoT) devices. The faster all of this data is analyzed, its hidden trends and patterns discovered, and new strategies created, the faster action can be taken, creating greater value for organizations. Density-based method is a prominent class in clustering data streams. It has the ability to detect arbitrary shape clusters, to handle outlier, and it does not need the number of clusters in advance. Therefore, density-based clustering algorithm is a proper choice for clustering IoT streams. Recently, several density-based algorithms have been proposed for clustering data streams. However, density-based clustering in limited time is still a challenging issue. In this paper, we propose a density-based clustering algorithm for IoT streams. The method has fast processing time to be applicable in real-time application of IoT devices. Experimental results show that the proposed approach obtains high quality results with low computation time on real and synthetic datasets.

  10. Data mining algorithms for land cover change detection: a review

    Indian Academy of Sciences (India)

    Sangram Panigrahi

    2017-11-24

    Nov 24, 2017 ... values, poor quality measurement, high resolution and high dimensional data. The land cover .... These data sets also include quality assurance information, ...... 2012 A new data mining framework for forest fire mapping.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. Transmission Algorithm with QoS Considerations for a Sustainable MPEG Streaming Service

    Directory of Open Access Journals (Sweden)

    Sang-Hyong Kim

    2017-03-01

    Full Text Available With the proliferation of heterogeneous networks, there is a need to provide multimedia stream services in a sustainable manner. It is especially critical to maintain the Quality of Service (QoS standards. Existing multimedia streaming services have been studied to guarantee QoS on the receiving side. QoS has not been ensured due to the fact that the loss of streaming data to be transmitted has not been considered in network conditions. With an algorithm that considers the QoS and can reduce the overhead of the network, it will be possible to reduce the transmission error and wastage of communication network resources. In this paper, we propose a scheme that improves the reliability of multimedia transmissions by using an adaptive algorithm that switches between UDP (User Datagram Protocol and TCP (Transmission Control Protocol based on the size of the data. In addition, we present a method that retransmits essential portions of the multimedia data, thus improving transmission efficiency. We simulate an MPEG (Moving Picture Experts Group stream service and evaluate the performance of the proposed adaptive MPEG stream service.

  18. 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.

  19. 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.

  20. A New Algorithm for Cartographic Simplification of Streams and Lakes Using Deviation Angles and Error Bands

    Directory of Open Access Journals (Sweden)

    Türkay Gökgöz

    2015-10-01

    Full Text Available Multi-representation databases (MRDBs are used in several geographical information system applications for different purposes. MRDBs are mainly obtained through model and cartographic generalizations. Simplification is the essential operator of cartographic generalization, and streams and lakes are essential features in hydrography. In this study, a new algorithm was developed for the simplification of streams and lakes. In this algorithm, deviation angles and error bands are used to determine the characteristic vertices and the planimetric accuracy of the features, respectively. The algorithm was tested using a high-resolution national hydrography dataset of Pomme de Terre, a sub-basin in the USA. To assess the performance of the new algorithm, the Bend Simplify and Douglas-Peucker algorithms, the medium-resolution hydrography dataset of the sub-basin, and Töpfer’s radical law were used. For quantitative analysis, the vertex numbers, the lengths, and the sinuosity values were computed. Consequently, it was shown that the new algorithm was able to meet the main requirements (i.e., accuracy, legibility and aesthetics, and storage.

  1. A backtracking algorithm for the stream AND-parallel execution of logic programs

    Energy Technology Data Exchange (ETDEWEB)

    Somogyi, Z.; Ramamohanarao, K.; Vaghani, J. (Univ. of Melbourne, Parkville (Australia))

    1988-06-01

    The authors present the first backtracking algorithm for stream AND-parallel logic programs. It relies on compile-time knowledge of the data flow graph of each clause to let it figure out efficiently which goals to kill or restart when a goal fails. This crucial information, which they derive from mode declarations, was not available at compile-time in any previous stream AND-parallel system. They show that modes can increase the precision of the backtracking algorithm, though their algorithm allows this precision to be traded off against overhead on a procedure-by-procedure and call-by-call basis. The modes also allow their algorithm to handle efficiently programs that manipulate partially instantiated data structures and an important class of programs with circular dependency graphs. On code that does not need backtracking, the efficiency of their algorithm approaches that of the committed-choice languages; on code that does need backtracking its overhead is comparable to that of the independent AND-parallel backtracking algorithms.

  2. An Efficient Association Rule Hiding Algorithm for Privacy Preserving Data Mining

    OpenAIRE

    Yogendra Kumar Jain,; Vinod Kumar Yadav,; Geetika S. Panday

    2011-01-01

    The security of the large database that contains certain crucial information, it will become a serious issue when sharing data to the network against unauthorized access. Privacy preserving data mining is a new research trend in privacy data for data mining and statistical database. Association analysis is a powerful toolfor discovering relationships which are hidden in large database. Association rules hiding algorithms get strong and efficient performance for protecting confidential and cru...

  3. 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.

  4. 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.

  5. Practical mine ventilation optimization based on genetic algorithms for free splitting networks

    Energy Technology Data Exchange (ETDEWEB)

    Acuna, E.; Maynard, R.; Hall, S. [Laurentian Univ., Sudbury, ON (Canada). Mirarco Mining Innovation; Hardcastle, S.G.; Li, G. [Natural Resources Canada, Sudbury, ON (Canada). CANMET Mining and Mineral Sciences Laboratories; Lowndes, I.S. [Nottingham Univ., Nottingham (United Kingdom). Process and Environmental Research Division; Tonnos, A. [Bestech, Sudbury, ON (Canada)

    2010-07-01

    The method used to optimize the design and operation of mine ventilation has generally been based on case studies and expert knowledge. It has yet to benefit from optimization techniques used and proven in other fields of engineering. Currently, optimization of mine ventilation systems is a manual based decision process performed by an experienced mine ventilation specialist assisted by commercial ventilation distribution solvers. These analysis tools are widely used in the mining industry to evaluate the practical and economic viability of alternative ventilation system configurations. The scenario which is usually selected is the one that reports the lowest energy consumption while delivering the required airflow distribution. Since most commercial solvers do not have an integrated optimization algorithm network, the process of generating a series of potential ventilation solutions using the conventional iterative design strategy can be time consuming. For that reason, a genetic algorithm (GA) optimization routine was developed in combination with a ventilation solver to determine the potential optimal solutions of a primary mine ventilation system based on a free splitting network. The optimization method was used in a small size mine ventilation network. The technique was shown to have the capacity to generate good feasible solutions and improve upon the manual results obtained by mine ventilation specialists. 9 refs., 7 tabs., 3 figs.

  6. Research on Health State Perception Algorithm of Mining Equipment Based on Frequency Closeness

    Directory of Open Access Journals (Sweden)

    Gang Wang

    2014-06-01

    Full Text Available The health state perception of mining equipment is intended to have an online real- time knowledge and analysis of the running conditions of large mining equipments. Due to its unknown failure mode, a challenge was raised to the traditional fault diagnosis of mining equipments. A health state perception algorithm of mining equipment was introduced in this paper, and through continuous sampling of the machine vibration data, the time-series data set was set up; subsequently, the mode set based on the frequency closeness was constructed by the d neighborhood method combined with the TSDM algorithm, thus the forecast method on the basis of the dual mode set was eventually formed. In the calculation of the frequency closeness, the Goertzel algorithm was introduced to effectively decrease the computation amount. It was indicated through the simulation test on the vibration data of the drum shaft base that the health state of the device could be effectively distinguished. The algorithm has been successfully applied to equipment monitoring in the Huoer Xinhe Coal Mine of Shanxi Coal Imp&Exp. Group Co., Ltd.

  7. 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.

  8. 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

  9. 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.

  10. 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.

  11. 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

  12. Genetic Algorithm Calibration of Probabilistic Cellular Automata for Modeling Mining Permit Activity

    Science.gov (United States)

    Louis, S.J.; Raines, G.L.

    2003-01-01

    We use a genetic algorithm to calibrate a spatially and temporally resolved cellular automata to model mining activity on public land in Idaho and western Montana. The genetic algorithm searches through a space of transition rule parameters of a two dimensional cellular automata model to find rule parameters that fit observed mining activity data. Previous work by one of the authors in calibrating the cellular automaton took weeks - the genetic algorithm takes a day and produces rules leading to about the same (or better) fit to observed data. These preliminary results indicate that genetic algorithms are a viable tool in calibrating cellular automata for this application. Experience gained during the calibration of this cellular automata suggests that mineral resource information is a critical factor in the quality of the results. With automated calibration, further refinements of how the mineral-resource information is provided to the cellular automaton will probably improve our model.

  13. 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)

  14. 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.

  15. Formulations and algorithms for problems on rock mass and support deformation during mining

    Science.gov (United States)

    Seryakov, VM

    2018-03-01

    The analysis of problem formulations to calculate stress-strain state of mine support and surrounding rocks mass in rock mechanics shows that such formulations incompletely describe the mechanical features of joint deformation in the rock mass–support system. The present paper proposes an algorithm to take into account the actual conditions of rock mass and support interaction and the algorithm implementation method to ensure efficient calculation of stresses in rocks and support.

  16. A study of the Bienstock-Zuckerberg algorithm, Applications in Mining and Resource Constrained Project Scheduling

    OpenAIRE

    Muñoz, Gonzalo; Espinoza, Daniel; Goycoolea, Marcos; Moreno, Eduardo; Queyranne, Maurice; Rivera, Orlando

    2016-01-01

    We study a Lagrangian decomposition algorithm recently proposed by Dan Bienstock and Mark Zuckerberg for solving the LP relaxation of a class of open pit mine project scheduling problems. In this study we show that the Bienstock-Zuckerberg (BZ) algorithm can be used to solve LP relaxations corresponding to a much broader class of scheduling problems, including the well-known Resource Constrained Project Scheduling Problem (RCPSP), and multi-modal variants of the RCPSP that consider batch proc...

  17. 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.

  18. Effective Application of Improved Profit-Mining Algorithm for the Interday Trading Model

    Directory of Open Access Journals (Sweden)

    Yu-Lung Hsieh

    2014-01-01

    Full Text Available Many real world applications of association rule mining from large databases help users make better decisions. However, they do not work well in financial markets at this time. In addition to a high profit, an investor also looks for a low risk trading with a better rate of winning. The traditional approach of using minimum confidence and support thresholds needs to be changed. Based on an interday model of trading, we proposed effective profit-mining algorithms which provide investors with profit rules including information about profit, risk, and winning rate. Since profit-mining in the financial market is still in its infant stage, it is important to detail the inner working of mining algorithms and illustrate the best way to apply them. In this paper we go into details of our improved profit-mining algorithm and showcase effective applications with experiments using real world trading data. The results show that our approach is practical and effective with good performance for various datasets.

  19. Effective application of improved profit-mining algorithm for the interday trading model.

    Science.gov (United States)

    Hsieh, Yu-Lung; Yang, Don-Lin; Wu, Jungpin

    2014-01-01

    Many real world applications of association rule mining from large databases help users make better decisions. However, they do not work well in financial markets at this time. In addition to a high profit, an investor also looks for a low risk trading with a better rate of winning. The traditional approach of using minimum confidence and support thresholds needs to be changed. Based on an interday model of trading, we proposed effective profit-mining algorithms which provide investors with profit rules including information about profit, risk, and winning rate. Since profit-mining in the financial market is still in its infant stage, it is important to detail the inner working of mining algorithms and illustrate the best way to apply them. In this paper we go into details of our improved profit-mining algorithm and showcase effective applications with experiments using real world trading data. The results show that our approach is practical and effective with good performance for various datasets.

  20. Pattern recognition algorithms for data mining scalability, knowledge discovery and soft granular computing

    CERN Document Server

    Pal, Sankar K

    2004-01-01

    Pattern Recognition Algorithms for Data Mining addresses different pattern recognition (PR) tasks in a unified framework with both theoretical and experimental results. Tasks covered include data condensation, feature selection, case generation, clustering/classification, and rule generation and evaluation. This volume presents various theories, methodologies, and algorithms, using both classical approaches and hybrid paradigms. The authors emphasize large datasets with overlapping, intractable, or nonlinear boundary classes, and datasets that demonstrate granular computing in soft frameworks.Organized into eight chapters, the book begins with an introduction to PR, data mining, and knowledge discovery concepts. The authors analyze the tasks of multi-scale data condensation and dimensionality reduction, then explore the problem of learning with support vector machine (SVM). They conclude by highlighting the significance of granular computing for different mining tasks in a soft paradigm.

  1. An imperialist competitive algorithm for solving the production scheduling problem in open pit mine

    Directory of Open Access Journals (Sweden)

    Mojtaba Mokhtarian Asl

    2016-06-01

    Full Text Available Production scheduling (planning of an open-pit mine is the procedure during which the rock blocks are assigned to different production periods in a way that the highest net present value of the project achieved subject to operational constraints. The paper introduces a new and computationally less expensive meta-heuristic technique known as imperialist competitive algorithm (ICA for long-term production planning of open pit mines. The proposed algorithm modifies the original rules of the assimilation process. The ICA performance for different levels of the control factors has been studied and the results are presented. The result showed that ICA could be efficiently applied on mine production planning problem.

  2. pubmed. mineR: An R package with text-mining algorithms to ...

    Indian Academy of Sciences (India)

    2016-08-26

    Aug 26, 2016 ... Three case studies are presented, namely, `Evolving role of diabetes educators', `Cancer risk assessment' and `Dynamic concepts on disease and comorbidity' to illustrate the use of pubmed.mineR. The package generally runs fast with small elapsed times in regular workstations even on large corpus ...

  3. Background Traffic-Based Retransmission Algorithm for Multimedia Streaming Transfer over Concurrent Multipaths

    Directory of Open Access Journals (Sweden)

    Yuanlong Cao

    2012-01-01

    Full Text Available The content-rich multimedia streaming will be the most attractive services in the next-generation networks. With function of distribute data across multipath end-to-end paths based on SCTP's multihoming feature, concurrent multipath transfer SCTP (CMT-SCTP has been regarded as the most promising technology for the efficient multimedia streaming transmission. However, the current researches on CMT-SCTP mainly focus on the algorithms related to the data delivery performance while they seldom consider the background traffic factors. Actually, background traffic of realistic network environments has an important impact on the performance of CMT-SCTP. In this paper, we firstly investigate the effect of background traffic on the performance of CMT-SCTP based on a close realistic simulation topology with reasonable background traffic in NS2, and then based on the localness nature of background flow, a further improved retransmission algorithm, named RTX_CSI, is proposed to reach more benefits in terms of average throughput and achieve high users' experience of quality for multimedia streaming services.

  4. 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

  5. Parallel field line and stream line tracing algorithms for space physics applications

    Science.gov (United States)

    Toth, G.; de Zeeuw, D.; Monostori, G.

    2004-05-01

    Field line and stream line tracing is required in various space physics applications, such as the coupling of the global magnetosphere and inner magnetosphere models, the coupling of the solar energetic particle and heliosphere models, or the modeling of comets, where the multispecies chemical equations are solved along stream lines of a steady state solution obtained with single fluid MHD model. Tracing a vector field is an inherently serial process, which is difficult to parallelize. This is especially true when the data corresponding to the vector field is distributed over a large number of processors. We designed algorithms for the various applications, which scale well to a large number of processors. In the first algorithm the computational domain is divided into blocks. Each block is on a single processor. The algorithm folows the vector field inside the blocks, and calculates a mapping of the block surfaces. The blocks communicate the values at the coinciding surfaces, and the results are interpolated. Finally all block surfaces are defined and values inside the blocks are obtained. In the second algorithm all processors start integrating along the vector field inside the accessible volume. When the field line leaves the local subdomain, the position and other information is stored in a buffer. Periodically the processors exchange the buffers, and continue integration of the field lines until they reach a boundary. At that point the results are sent back to the originating processor. Efficiency is achieved by a careful phasing of computation and communication. In the third algorithm the results of a steady state simulation are stored on a hard drive. The vector field is contained in blocks. All processors read in all the grid and vector field data and the stream lines are integrated in parallel. If a stream line enters a block, which has already been integrated, the results can be interpolated. By a clever ordering of the blocks the execution speed can be

  6. Rare itemsets mining algorithm based on RP-Tree and spark framework

    Science.gov (United States)

    Liu, Sainan; Pan, Haoan

    2018-05-01

    For the issues of the rare itemsets mining in big data, this paper proposed a rare itemsets mining algorithm based on RP-Tree and Spark framework. Firstly, it arranged the data vertically according to the transaction identifier, in order to solve the defects of scan the entire data set, the vertical datasets are divided into frequent vertical datasets and rare vertical datasets. Then, it adopted the RP-Tree algorithm to construct the frequent pattern tree that contains rare items and generate rare 1-itemsets. After that, it calculated the support of the itemsets by scanning the two vertical data sets, finally, it used the iterative process to generate rare itemsets. The experimental show that the algorithm can effectively excavate rare itemsets and have great superiority in execution time.

  7. 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

  8. 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.)

  9. 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

  10. 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.

  11. 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.

  12. 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

  13. A Survey on Accessing Data over Cloud Environment using Data mining Algorithms

    OpenAIRE

    B.Prasanalakshmi; A.Selvaraj

    2015-01-01

    In today's world to access the large set of data is more complex, because the data may be structured and unstructured like in the form of text, images, videos, etc., it cannot be controlled from the internet users this is known as Big data. Useful data can be accessed through extracting from big data with the help of data mining algorithms. Data mining is a technique for determine the patterns; classify the data, clustering from the large set of data. In this paper we will discuss how large s...

  14. 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.

  15. 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

  16. 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.

  17. Gas Emission Prediction Model of Coal Mine Based on CSBP Algorithm

    Directory of Open Access Journals (Sweden)

    Xiong Yan

    2016-01-01

    Full Text Available In view of the nonlinear characteristics of gas emission in a coal working face, a prediction method is proposed based on cuckoo search algorithm optimized BP neural network (CSBP. In the CSBP algorithm, the cuckoo search is adopted to optimize weight and threshold parameters of BP network, and obtains the global optimal solutions. Furthermore, the twelve main affecting factors of the gas emission in the coal working face are taken as input vectors of CSBP algorithm, the gas emission is acted as output vector, and then the prediction model of BP neural network with optimal parameters is established. The results show that the CSBP algorithm has batter generalization ability and higher prediction accuracy, and can be utilized effectively in the prediction of coal mine gas emission.

  18. Attribute Index and Uniform Design Based Multiobjective Association Rule Mining with Evolutionary Algorithm

    Directory of Open Access Journals (Sweden)

    Jie Zhang

    2013-01-01

    Full Text Available In association rule mining, evaluating an association rule needs to repeatedly scan database to compare the whole database with the antecedent, consequent of a rule and the whole rule. In order to decrease the number of comparisons and time consuming, we present an attribute index strategy. It only needs to scan database once to create the attribute index of each attribute. Then all metrics values to evaluate an association rule do not need to scan database any further, but acquire data only by means of the attribute indices. The paper visualizes association rule mining as a multiobjective problem rather than a single objective one. In order to make the acquired solutions scatter uniformly toward the Pareto frontier in the objective space, elitism policy and uniform design are introduced. The paper presents the algorithm of attribute index and uniform design based multiobjective association rule mining with evolutionary algorithm, abbreviated as IUARMMEA. It does not require the user-specified minimum support and minimum confidence anymore, but uses a simple attribute index. It uses a well-designed real encoding so as to extend its application scope. Experiments performed on several databases demonstrate that the proposed algorithm has excellent performance, and it can significantly reduce the number of comparisons and time consumption.

  19. Attribute index and uniform design based multiobjective association rule mining with evolutionary algorithm.

    Science.gov (United States)

    Zhang, Jie; Wang, Yuping; Feng, Junhong

    2013-01-01

    In association rule mining, evaluating an association rule needs to repeatedly scan database to compare the whole database with the antecedent, consequent of a rule and the whole rule. In order to decrease the number of comparisons and time consuming, we present an attribute index strategy. It only needs to scan database once to create the attribute index of each attribute. Then all metrics values to evaluate an association rule do not need to scan database any further, but acquire data only by means of the attribute indices. The paper visualizes association rule mining as a multiobjective problem rather than a single objective one. In order to make the acquired solutions scatter uniformly toward the Pareto frontier in the objective space, elitism policy and uniform design are introduced. The paper presents the algorithm of attribute index and uniform design based multiobjective association rule mining with evolutionary algorithm, abbreviated as IUARMMEA. It does not require the user-specified minimum support and minimum confidence anymore, but uses a simple attribute index. It uses a well-designed real encoding so as to extend its application scope. Experiments performed on several databases demonstrate that the proposed algorithm has excellent performance, and it can significantly reduce the number of comparisons and time consumption.

  20. Feature Reduction Based on Genetic Algorithm and Hybrid Model for Opinion Mining

    Directory of Open Access Journals (Sweden)

    P. Kalaivani

    2015-01-01

    Full Text Available With the rapid growth of websites and web form the number of product reviews is available on the sites. An opinion mining system is needed to help the people to evaluate emotions, opinions, attitude, and behavior of others, which is used to make decisions based on the user preference. In this paper, we proposed an optimized feature reduction that incorporates an ensemble method of machine learning approaches that uses information gain and genetic algorithm as feature reduction techniques. We conducted comparative study experiments on multidomain review dataset and movie review dataset in opinion mining. The effectiveness of single classifiers Naïve Bayes, logistic regression, support vector machine, and ensemble technique for opinion mining are compared on five datasets. The proposed hybrid method is evaluated and experimental results using information gain and genetic algorithm with ensemble technique perform better in terms of various measures for multidomain review and movie reviews. Classification algorithms are evaluated using McNemar’s test to compare the level of significance of the classifiers.

  1. 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...

  2. A fast calculating two-stream-like multiple scattering algorithm that captures azimuthal and elevation variations

    Science.gov (United States)

    Fiorino, Steven T.; Elmore, Brannon; Schmidt, Jaclyn; Matchefts, Elizabeth; Burley, Jarred L.

    2016-05-01

    Properly accounting for multiple scattering effects can have important implications for remote sensing and possibly directed energy applications. For example, increasing path radiance can affect signal noise. This study describes the implementation of a fast-calculating two-stream-like multiple scattering algorithm that captures azimuthal and elevation variations into the Laser Environmental Effects Definition and Reference (LEEDR) atmospheric characterization and radiative transfer code. The multiple scattering algorithm fully solves for molecular, aerosol, cloud, and precipitation single-scatter layer effects with a Mie algorithm at every calculation point/layer rather than an interpolated value from a pre-calculated look-up-table. This top-down cumulative diffusivity method first considers the incident solar radiance contribution to a given layer accounting for solid angle and elevation, and it then measures the contribution of diffused energy from previous layers based on the transmission of the current level to produce a cumulative radiance that is reflected from a surface and measured at the aperture at the observer. Then a unique set of asymmetry and backscattering phase function parameter calculations are made which account for the radiance loss due to the molecular and aerosol constituent reflectivity within a level and allows for a more accurate characterization of diffuse layers that contribute to multiple scattered radiances in inhomogeneous atmospheres. The code logic is valid for spectral bands between 200 nm and radio wavelengths, and the accuracy is demonstrated by comparing the results from LEEDR to observed sky radiance data.

  3. 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)

  4. 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)

  5. Implementation of a Multichannel Serial Data Streaming Algorithm using the Xilinx Serial RapidIO Solution

    Science.gov (United States)

    Doxley, Charles A.

    2016-01-01

    In the current world of applications that use reconfigurable technology implemented on field programmable gate arrays (FPGAs), there is a need for flexible architectures that can grow as the systems evolve. A project has limited resources and a fixed set of requirements that development efforts are tasked to meet. Designers must develop robust solutions that practically meet the current customer demands and also have the ability to grow for future performance. This paper describes the development of a high speed serial data streaming algorithm that allows for transmission of multiple data channels over a single serial link. The technique has the ability to change to meet new applications developed for future design considerations. This approach uses the Xilinx Serial RapidIO LOGICORE Solution to implement a flexible infrastructure to meet the current project requirements with the ability to adapt future system designs.

  6. A hybrid GA-TS algorithm for open vehicle routing optimization of coal mines material

    Energy Technology Data Exchange (ETDEWEB)

    Yu, S.W.; Ding, C.; Zhu, K.J. [China University of Geoscience, Wuhan (China)

    2011-08-15

    In the open vehicle routing problem (OVRP), the objective is to minimize the number of vehicles and the total distance (or time) traveled. This study primarily focuses on solving an open vehicle routing problem (OVRP) by applying a novel hybrid genetic algorithm and the Tabu search (GA-TS), which combines the GA's parallel computing and global optimization with TS's Tabu search skill and fast local search. Firstly, the proposed algorithm uses natural number coding according to the customer demands and the captivity of the vehicle for globe optimization. Secondly, individuals of population do TS local search with a certain degree of probability, namely, do the local routing optimization of all customer sites belong to one vehicle. The mechanism not only improves the ability of global optimization, but also ensures the speed of operation. The algorithm was used in Zhengzhou Coal Mine and Power Supply Co., Ltd.'s transport vehicle routing optimization.

  7. Use of NTRIP for Optimizing the Decoding Algorithm for Real-Time Data Streams

    Directory of Open Access Journals (Sweden)

    Zhanke He

    2014-10-01

    Full Text Available As a network transmission protocol, Networked Transport of RTCM via Internet Protocol (NTRIP is widely used in GPS and Global Orbiting Navigational Satellite System (GLONASS Augmentation systems, such as Continuous Operational Reference System (CORS, Wide Area Augmentation System (WAAS and Satellite Based Augmentation Systems (SBAS. With the deployment of BeiDou Navigation Satellite system(BDS to serve the Asia-Pacific region, there are increasing needs for ground monitoring of the BeiDou Navigation Satellite system and the development of the high-precision real-time BeiDou products. This paper aims to optimize the decoding algorithm of NTRIP Client data streams and the user authentication strategies of the NTRIP Caster based on NTRIP. The proposed method greatly enhances the handling efficiency and significantly reduces the data transmission delay compared with the Federal Agency for Cartography and Geodesy (BKG NTRIP. Meanwhile, a transcoding method is proposed to facilitate the data transformation from the BINary EXchange (BINEX format to the RTCM format. The transformation scheme thus solves the problem of handing real-time data streams from Trimble receivers in the BeiDou Navigation Satellite System indigenously developed by China.

  8. Use of NTRIP for optimizing the decoding algorithm for real-time data streams.

    Science.gov (United States)

    He, Zhanke; Tang, Wenda; Yang, Xuhai; Wang, Liming; Liu, Jihua

    2014-10-10

    As a network transmission protocol, Networked Transport of RTCM via Internet Protocol (NTRIP) is widely used in GPS and Global Orbiting Navigational Satellite System (GLONASS) Augmentation systems, such as Continuous Operational Reference System (CORS), Wide Area Augmentation System (WAAS) and Satellite Based Augmentation Systems (SBAS). With the deployment of BeiDou Navigation Satellite system(BDS) to serve the Asia-Pacific region, there are increasing needs for ground monitoring of the BeiDou Navigation Satellite system and the development of the high-precision real-time BeiDou products. This paper aims to optimize the decoding algorithm of NTRIP Client data streams and the user authentication strategies of the NTRIP Caster based on NTRIP. The proposed method greatly enhances the handling efficiency and significantly reduces the data transmission delay compared with the Federal Agency for Cartography and Geodesy (BKG) NTRIP. Meanwhile, a transcoding method is proposed to facilitate the data transformation from the BINary EXchange (BINEX) format to the RTCM format. The transformation scheme thus solves the problem of handing real-time data streams from Trimble receivers in the BeiDou Navigation Satellite System indigenously developed by China.

  9. 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.

  10. Application of an empiric Bayesian data mining algorithm to reports of pancreatitis associated with atypical antipsychotics.

    Science.gov (United States)

    Hauben, Manfred

    2004-09-01

    To compare the results from one frequently cited data mining algorithm with those from a study, which was published in a peer-reviewed journal, that examined the association of pancreatitis with selected atypical antipsychotics observed by traditional rule-based methods of signal detection. Retrospective pharmacovigilance study. The widely studied data mining algorithm known as the Multi-item Gamma Poisson Shrinker (MGPS) was applied to adverse-event reports from the United States Food and Drug Administration's Adverse Event Reporting System database through the first quarter of 2003 for clozapine, olanzapine, and risperidone to determine if a significant signal of pancreatitis would have been generated by this method in advance of their review or the addition of these events to the respective product labels. Data mining was performed by using nine preferred terms relevant to drug-induced pancreatitis from the Medical Dictionary for Regulatory Activities (MedDRA). Results from a previous study on the antipsychotics were reviewed and analyzed. Physicians' Desk References (PDRs) starting from 1994 were manually reviewed to determine the first year that pancreatitis was listed as an adverse event in the product label for each antipsychotic. This information was used as a surrogate marker of the timing of initial signal detection by traditional criteria. Pancreatitis was listed as an adverse event in a PDR for all three atypical antipsychotics. Despite the presence of up to 88 reports/drug-event combination in the Food and Drug Administration's Adverse Event Reporting System database, the MGPS failed to generate a signal of disproportional reporting of pancreatitis associated with the three antipsychotics despite the signaling of these drug-event combinations by traditional rule-based methods, as reflected in product labeling and/or the literature. These discordant findings illustrate key principles in the application of data mining algorithms to drug safety

  11. 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

  12. Multilevel Association Rule Mining for Bridge Resource Management Based on Immune Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    Yang Ou

    2014-01-01

    Full Text Available This paper is concerned with the problem of multilevel association rule mining for bridge resource management (BRM which is announced by IMO in 2010. The goal of this paper is to mine the association rules among the items of BRM and the vessel accidents. However, due to the indirect data that can be collected, which seems useless for the analysis of the relationship between items of BIM and the accidents, the cross level association rules need to be studied, which builds the relation between the indirect data and items of BRM. In this paper, firstly, a cross level coding scheme for mining the multilevel association rules is proposed. Secondly, we execute the immune genetic algorithm with the coding scheme for analyzing BRM. Thirdly, based on the basic maritime investigation reports, some important association rules of the items of BRM are mined and studied. Finally, according to the results of the analysis, we provide the suggestions for the work of seafarer training, assessment, and management.

  13. Urinary metabolic profiling of asymptomatic acute intermittent porphyria using a rule-mining-based algorithm.

    Science.gov (United States)

    Luck, Margaux; Schmitt, Caroline; Talbi, Neila; Gouya, Laurent; Caradeuc, Cédric; Puy, Hervé; Bertho, Gildas; Pallet, Nicolas

    2018-01-01

    Metabolomic profiling combines Nuclear Magnetic Resonance spectroscopy with supervised statistical analysis that might allow to better understanding the mechanisms of a disease. In this study, the urinary metabolic profiling of individuals with porphyrias was performed to predict different types of disease, and to propose new pathophysiological hypotheses. Urine 1 H-NMR spectra of 73 patients with asymptomatic acute intermittent porphyria (aAIP) and familial or sporadic porphyria cutanea tarda (f/sPCT) were compared using a supervised rule-mining algorithm. NMR spectrum buckets bins, corresponding to rules, were extracted and a logistic regression was trained. Our rule-mining algorithm generated results were consistent with those obtained using partial least square discriminant analysis (PLS-DA) and the predictive performance of the model was significant. Buckets that were identified by the algorithm corresponded to metabolites involved in glycolysis and energy-conversion pathways, notably acetate, citrate, and pyruvate, which were found in higher concentrations in the urines of aAIP compared with PCT patients. Metabolic profiling did not discriminate sPCT from fPCT patients. These results suggest that metabolic reprogramming occurs in aAIP individuals, even in the absence of overt symptoms, and supports the relationship that occur between heme synthesis and mitochondrial energetic metabolism.

  14. 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.

  15. 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

  16. 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.

  17. 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.

  18. Low-complexity transcoding algorithm from H.264/AVC to SVC using data mining

    Science.gov (United States)

    Garrido-Cantos, Rosario; De Cock, Jan; Martínez, Jose Luis; Van Leuven, Sebastian; Cuenca, Pedro; Garrido, Antonio

    2013-12-01

    Nowadays, networks and terminals with diverse characteristics of bandwidth and capabilities coexist. To ensure a good quality of experience, this diverse environment demands adaptability of the video stream. In general, video contents are compressed to save storage capacity and to reduce the bandwidth required for its transmission. Therefore, if these compressed video streams were compressed using scalable video coding schemes, they would be able to adapt to those heterogeneous networks and a wide range of terminals. Since the majority of the multimedia contents are compressed using H.264/AVC, they cannot benefit from that scalability. This paper proposes a low-complexity algorithm to convert an H.264/AVC bitstream without scalability to scalable bitstreams with temporal scalability in baseline and main profiles by accelerating the mode decision task of the scalable video coding encoding stage using machine learning tools. The results show that when our technique is applied, the complexity is reduced by 87% while maintaining coding efficiency.

  19. Mining the multigroup-discrete ordinates algorithm for high quality solutions

    International Nuclear Information System (INIS)

    Ganapol, B.D.; Kornreich, D.E.

    2005-01-01

    A novel approach to the numerical solution of the neutron transport equation via the discrete ordinates (SN) method is presented. The new technique is referred to as 'mining' low order (SN) numerical solutions to obtain high order accuracy. The new numerical method, called the Multigroup Converged SN (MGCSN) algorithm, is a combination of several sequence accelerators: Romberg and Wynn-epsilon. The extreme accuracy obtained by the method is demonstrated through self consistency and comparison to the independent semi-analytical benchmark BLUE. (authors)

  20. Calibration of Mine Ventilation Network Models Using the Non-Linear Optimization Algorithm

    Directory of Open Access Journals (Sweden)

    Guang Xu

    2017-12-01

    Full Text Available Effective ventilation planning is vital to underground mining. To ensure stable operation of the ventilation system and to avoid airflow disorder, mine ventilation network (MVN models have been widely used in simulating and optimizing the mine ventilation system. However, one of the challenges for MVN model simulation is that the simulated airflow distribution results do not match the measured data. To solve this problem, a simple and effective calibration method is proposed based on the non-linear optimization algorithm. The calibrated model not only makes simulated airflow distribution results in accordance with the on-site measured data, but also controls the errors of other parameters within a minimum range. The proposed method was then applied to calibrate an MVN model in a real case, which is built based on ventilation survey results and Ventsim software. Finally, airflow simulation experiments are carried out respectively using data before and after calibration, whose results were compared and analyzed. This showed that the simulated airflows in the calibrated model agreed much better to the ventilation survey data, which verifies the effectiveness of calibrating method.

  1. An overview of data mining algorithms in drug induced toxicity prediction.

    Science.gov (United States)

    Omer, Ankur; Singh, Poonam; Yadav, N K; Singh, R K

    2014-04-01

    The growth in chemical diversity has increased the need to adjudicate the toxicity of different chemical compounds raising the burden on the demand of animal testing. The toxicity evaluation requires time consuming and expensive undertaking, leading to the deprivation of the methods employed for screening chemicals pointing towards the need to develop more efficient toxicity assessment systems. Computational approaches have reduced the time as well as the cost for evaluating the toxicity and kinetic behavior of any chemical. The accessibility of a large amount of data and the intense need of turning this data into useful information have attracted the attention towards data mining. Machine Learning, one of the powerful data mining techniques has evolved as the most effective and potent tool for exploring new insights on combinatorial relationships among various experimental data generated. The article accounts on some sophisticated machine learning algorithms like Artificial Neural Networks (ANN), Support Vector Machine (SVM), k-mean clustering and Self Organizing Maps (SOM) with some of the available tools used for classification, sorting and toxicological evaluation of data, clarifying, how data mining and machine learning interact cooperatively to facilitate knowledge discovery. Addressing the association of some commonly used expert systems, we briefly outline some real world applications to consider the crucial role of data set partitioning.

  2. 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....

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

    Science.gov (United States)

    2014-01-01

    Background Motif mining has always been a hot research topic in bioinformatics. Most of current research on biological networks focuses on exact motif mining. However, due to the inevitable experimental error and noisy data, biological network data represented as the probability model could better reflect the authenticity and biological significance, therefore, it is more biological meaningful to discover probability motif in uncertain biological networks. One of the key steps in probability motif mining is frequent pattern discovery which is usually based on the possible world model having a relatively high computational complexity. Methods In this paper, we present a novel method for detecting frequent probability patterns based on circuit simulation in the uncertain biological networks. First, the partition based efficient search is applied to the non-tree like subgraph mining where the probability of occurrence in random networks is small. Then, an algorithm of probability isomorphic based on circuit simulation is proposed. The probability isomorphic combines the analysis of circuit topology structure with related physical properties of voltage in order to evaluate the probability isomorphism between probability subgraphs. The circuit simulation based probability isomorphic can avoid using traditional possible world model. Finally, based on the algorithm of probability subgraph isomorphism, two-step hierarchical clustering method is used to cluster subgraphs, and discover frequent probability patterns from the clusters. Results The experiment results on data sets of the Protein-Protein Interaction (PPI) networks and the transcriptional regulatory networks of E. coli and S. cerevisiae show that the proposed method can efficiently discover the frequent probability subgraphs. The discovered subgraphs in our study contain all probability motifs reported in the experiments published in other related papers. Conclusions The algorithm of probability graph isomorphism

  4. 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)

  5. 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.

  6. 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

  7. Mining biological information from 3D short time-series gene expression data: the OPTricluster algorithm.

    Science.gov (United States)

    Tchagang, Alain B; Phan, Sieu; Famili, Fazel; Shearer, Heather; Fobert, Pierre; Huang, Yi; Zou, Jitao; Huang, Daiqing; Cutler, Adrian; Liu, Ziying; Pan, Youlian

    2012-04-04

    Nowadays, it is possible to collect expression levels of a set of genes from a set of biological samples during a series of time points. Such data have three dimensions: gene-sample-time (GST). Thus they are called 3D microarray gene expression data. To take advantage of the 3D data collected, and to fully understand the biological knowledge hidden in the GST data, novel subspace clustering algorithms have to be developed to effectively address the biological problem in the corresponding space. We developed a subspace clustering algorithm called Order Preserving Triclustering (OPTricluster), for 3D short time-series data mining. OPTricluster is able to identify 3D clusters with coherent evolution from a given 3D dataset using a combinatorial approach on the sample dimension, and the order preserving (OP) concept on the time dimension. The fusion of the two methodologies allows one to study similarities and differences between samples in terms of their temporal expression profile. OPTricluster has been successfully applied to four case studies: immune response in mice infected by malaria (Plasmodium chabaudi), systemic acquired resistance in Arabidopsis thaliana, similarities and differences between inner and outer cotyledon in Brassica napus during seed development, and to Brassica napus whole seed development. These studies showed that OPTricluster is robust to noise and is able to detect the similarities and differences between biological samples. Our analysis showed that OPTricluster generally outperforms other well known clustering algorithms such as the TRICLUSTER, gTRICLUSTER and K-means; it is robust to noise and can effectively mine the biological knowledge hidden in the 3D short time-series gene expression data.

  8. 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.

  9. Comparison of predictive performance of data mining algorithms in predicting body weight in Mengali rams of Pakistan

    Directory of Open Access Journals (Sweden)

    Senol Celik

    Full Text Available ABSTRACT The present study aimed at comparing predictive performance of some data mining algorithms (CART, CHAID, Exhaustive CHAID, MARS, MLP, and RBF in biometrical data of Mengali rams. To compare the predictive capability of the algorithms, the biometrical data regarding body (body length, withers height, and heart girth and testicular (testicular length, scrotal length, and scrotal circumference measurements of Mengali rams in predicting live body weight were evaluated by most goodness of fit criteria. In addition, age was considered as a continuous independent variable. In this context, MARS data mining algorithm was used for the first time to predict body weight in two forms, without (MARS_1 and with interaction (MARS_2 terms. The superiority order in the predictive accuracy of the algorithms was found as CART > CHAID ≈ Exhaustive CHAID > MARS_2 > MARS_1 > RBF > MLP. Moreover, all tested algorithms provided a strong predictive accuracy for estimating body weight. However, MARS is the only algorithm that generated a prediction equation for body weight. Therefore, it is hoped that the available results might present a valuable contribution in terms of predicting body weight and describing the relationship between the body weight and body and testicular measurements in revealing breed standards and the conservation of indigenous gene sources for Mengali sheep breeding. Therefore, it will be possible to perform more profitable and productive sheep production. Use of data mining algorithms is useful for revealing the relationship between body weight and testicular traits in describing breed standards of Mengali sheep.

  10. 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...

  11. A novel procedure on next generation sequencing data analysis using text mining algorithm.

    Science.gov (United States)

    Zhao, Weizhong; Chen, James J; Perkins, Roger; Wang, Yuping; Liu, Zhichao; Hong, Huixiao; Tong, Weida; Zou, Wen

    2016-05-13

    Next-generation sequencing (NGS) technologies have provided researchers with vast possibilities in various biological and biomedical research areas. Efficient data mining strategies are in high demand for large scale comparative and evolutional studies to be performed on the large amounts of data derived from NGS projects. Topic modeling is an active research field in machine learning and has been mainly used as an analytical tool to structure large textual corpora for data mining. We report a novel procedure to analyse NGS data using topic modeling. It consists of four major procedures: NGS data retrieval, preprocessing, topic modeling, and data mining using Latent Dirichlet Allocation (LDA) topic outputs. The NGS data set of the Salmonella enterica strains were used as a case study to show the workflow of this procedure. The perplexity measurement of the topic numbers and the convergence efficiencies of Gibbs sampling were calculated and discussed for achieving the best result from the proposed procedure. The output topics by LDA algorithms could be treated as features of Salmonella strains to accurately describe the genetic diversity of fliC gene in various serotypes. The results of a two-way hierarchical clustering and data matrix analysis on LDA-derived matrices successfully classified Salmonella serotypes based on the NGS data. The implementation of topic modeling in NGS data analysis procedure provides a new way to elucidate genetic information from NGS data, and identify the gene-phenotype relationships and biomarkers, especially in the era of biological and medical big data. The implementation of topic modeling in NGS data analysis provides a new way to elucidate genetic information from NGS data, and identify the gene-phenotype relationships and biomarkers, especially in the era of biological and medical big data.

  12. A Neural-Network Clustering-Based Algorithm for Privacy Preserving Data Mining

    Science.gov (United States)

    Tsiafoulis, S.; Zorkadis, V. C.; Karras, D. A.

    The increasing use of fast and efficient data mining algorithms in huge collections of personal data, facilitated through the exponential growth of technology, in particular in the field of electronic data storage media and processing power, has raised serious ethical, philosophical and legal issues related to privacy protection. To cope with these concerns, several privacy preserving methodologies have been proposed, classified in two categories, methodologies that aim at protecting the sensitive data and those that aim at protecting the mining results. In our work, we focus on sensitive data protection and compare existing techniques according to their anonymity degree achieved, the information loss suffered and their performance characteristics. The ℓ-diversity principle is combined with k-anonymity concepts, so that background information can not be exploited to successfully attack the privacy of data subjects data refer to. Based on Kohonen Self Organizing Feature Maps (SOMs), we firstly organize data sets in subspaces according to their information theoretical distance to each other, then create the most relevant classes paying special attention to rare sensitive attribute values, and finally generalize attribute values to the minimum extend required so that both the data disclosure probability and the information loss are possibly kept negligible. Furthermore, we propose information theoretical measures for assessing the anonymity degree achieved and empirical tests to demonstrate it.

  13. A data mining approach to optimize pellets manufacturing process based on a decision tree algorithm.

    Science.gov (United States)

    Ronowicz, Joanna; Thommes, Markus; Kleinebudde, Peter; Krysiński, Jerzy

    2015-06-20

    The present study is focused on the thorough analysis of cause-effect relationships between pellet formulation characteristics (pellet composition as well as process parameters) and the selected quality attribute of the final product. The shape using the aspect ratio value expressed the quality of pellets. A data matrix for chemometric analysis consisted of 224 pellet formulations performed by means of eight different active pharmaceutical ingredients and several various excipients, using different extrusion/spheronization process conditions. The data set contained 14 input variables (both formulation and process variables) and one output variable (pellet aspect ratio). A tree regression algorithm consistent with the Quality by Design concept was applied to obtain deeper understanding and knowledge of formulation and process parameters affecting the final pellet sphericity. The clear interpretable set of decision rules were generated. The spehronization speed, spheronization time, number of holes and water content of extrudate have been recognized as the key factors influencing pellet aspect ratio. The most spherical pellets were achieved by using a large number of holes during extrusion, a high spheronizer speed and longer time of spheronization. The described data mining approach enhances knowledge about pelletization process and simultaneously facilitates searching for the optimal process conditions which are necessary to achieve ideal spherical pellets, resulting in good flow characteristics. This data mining approach can be taken into consideration by industrial formulation scientists to support rational decision making in the field of pellets technology. Copyright © 2015 Elsevier B.V. All rights reserved.

  14. 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...

  15. Toward a Progress Indicator for Machine Learning Model Building and Data Mining Algorithm Execution: A Position Paper

    Science.gov (United States)

    Luo, Gang

    2017-01-01

    For user-friendliness, many software systems offer progress indicators for long-duration tasks. A typical progress indicator continuously estimates the remaining task execution time as well as the portion of the task that has been finished. Building a machine learning model often takes a long time, but no existing machine learning software supplies a non-trivial progress indicator. Similarly, running a data mining algorithm often takes a long time, but no existing data mining software provides a nontrivial progress indicator. In this article, we consider the problem of offering progress indicators for machine learning model building and data mining algorithm execution. We discuss the goals and challenges intrinsic to this problem. Then we describe an initial framework for implementing such progress indicators and two advanced, potential uses of them, with the goal of inspiring future research on this topic. PMID:29177022

  16. 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.

  17. 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...

  18. 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.

  19. 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.

  20. A genetic algorithm approach for open-pit mine production scheduling

    Directory of Open Access Journals (Sweden)

    Aref Alipour

    2017-06-01

    Full Text Available In an Open-Pit Production Scheduling (OPPS problem, the goal is to determine the mining sequence of an orebody as a block model. In this article, linear programing formulation is used to aim this goal. OPPS problem is known as an NP-hard problem, so an exact mathematical model cannot be applied to solve in the real state. Genetic Algorithm (GA is a well-known member of evolutionary algorithms that widely are utilized to solve NP-hard problems. Herein, GA is implemented in a hypothetical Two-Dimensional (2D copper orebody model. The orebody is featured as two-dimensional (2D array of blocks. Likewise, counterpart 2D GA array was used to represent the OPPS problem’s solution space. Thereupon, the fitness function is defined according to the OPPS problem’s objective function to assess the solution domain. Also, new normalization method was used for the handling of block sequencing constraint. A numerical study is performed to compare the solutions of the exact and GA-based methods. It is shown that the gap between GA and the optimal solution by the exact method is less than % 5; hereupon GA is found to be efficiently in solving OPPS problem.

  1. Risk of hepatotoxicity associated with the use of telithromycin: a signal detection using data mining algorithms.

    Science.gov (United States)

    Chen, Yan; Guo, Jeff J; Healy, Daniel P; Lin, Xiaodong; Patel, Nick C

    2008-12-01

    With the exception of case reports, limited data are available regarding the risk of hepatotoxicity associated with the use of telithromycin. To detect the safety signal regarding the reporting of hepatotoxicity associated with the use of telithromycin using 4 commonly employed data mining algorithms (DMAs). Based on the Adverse Events Reporting System (AERS) database of the Food and Drug Administration, 4 DMAs, including the reporting odds ratio (ROR), the proportional reporting ratio (PRR), the information component (IC), and the Gamma Poisson Shrinker (GPS), were applied to examine the association between the reporting of hepatotoxicity and the use of telithromycin. The study period was from the first quarter of 2004 to the second quarter of 2006. The reporting of hepatotoxicity was identified using the preferred terms indexed in the Medical Dictionary for Regulatory Activities. The drug name was used to identify reports regarding the use of telithromycin. A total of 226 reports describing hepatotoxicity associated with the use of telithromycin were recorded in the AERS. A safety problem of telithromycin associated with increased reporting of hepatotoxicity was clearly detected by 4 algorithms as early as 2005, signaling the problem in the first quarter by the ROR and the IC, in the second quarter by the PRR, and in the fourth quarter by the GPS. A safety signal was indicated by the 4 DMAs suggesting an association between the reporting of hepatotoxicity and the use of telithromycin. Given the wide use of telithromycin and serious consequences of hepatotoxicity, clinicians should be cautious when selecting telithromycin for treatment of an infection. In addition, further observational studies are required to evaluate the utility of signal detection systems for early recognition of serious, life-threatening, low-frequency drug-induced adverse events.

  2. The Application of Machine Learning Algorithms for Text Mining based on Sentiment Analysis Approach

    Directory of Open Access Journals (Sweden)

    Reza Samizade

    2018-06-01

    Full Text Available Classification of the cyber texts and comments into two categories of positive and negative sentiment among social media users is of high importance in the research are related to text mining. In this research, we applied supervised classification methods to classify Persian texts based on sentiment in cyber space. The result of this research is in a form of a system that can decide whether a comment which is published in cyber space such as social networks is considered positive or negative. The comments that are published in Persian movie and movie review websites from 1392 to 1395 are considered as the data set for this research. A part of these data are considered as training and others are considered as testing data. Prior to implementing the algorithms, pre-processing activities such as tokenizing, removing stop words, and n-germs process were applied on the texts. Naïve Bayes, Neural Networks and support vector machine were used for text classification in this study. Out of sample tests showed that there is no evidence indicating that the accuracy of SVM approach is statistically higher than Naïve Bayes or that the accuracy of Naïve Bayes is not statistically higher than NN approach. However, the researchers can conclude that the accuracy of the classification using SVM approach is statistically higher than the accuracy of NN approach in 5% confidence level.

  3. On the Organization of Parallel Operation of Some Algorithms for Finding the Shortest Path on a Graph on a Computer System with Multiple Instruction Stream and Single Data Stream

    Directory of Open Access Journals (Sweden)

    V. E. Podol'skii

    2015-01-01

    Full Text Available The paper considers the implementing Bellman-Ford and Lee algorithms to find the shortest graph path on a computer system with multiple instruction stream and single data stream (MISD. The MISD computer is a computer that executes commands of arithmetic-logical processing (on the CPU and commands of structures processing (on the structures processor in parallel on a single data stream. Transformation of sequential programs into the MISD programs is a labor intensity process because it requires a stream of the arithmetic-logical processing to be manually separated from that of the structures processing. Algorithms based on the processing of data structures (e.g., algorithms on graphs show high performance on a MISD computer. Bellman-Ford and Lee algorithms for finding the shortest path on a graph are representatives of these algorithms. They are applied to robotics for automatic planning of the robot movement in-situ. Modification of Bellman-Ford and Lee algorithms for finding the shortest graph path in coprocessor MISD mode and the parallel MISD modification of these algorithms were first obtained in this article. Thus, this article continues a series of studies on the transformation of sequential algorithms into MISD ones (Dijkstra and Ford-Fulkerson 's algorithms and has a pronouncedly applied nature. The article also presents the analysis results of Bellman-Ford and Lee algorithms in MISD mode. The paper formulates the basic trends of a technique for parallelization of algorithms into arithmetic-logical processing stream and structures processing stream. Among the key areas for future research, development of the mathematical approach to provide a subsequently formalized and automated process of parallelizing sequential algorithms between the CPU and structures processor is highlighted. Among the mathematical models that can be used in future studies there are graph models of algorithms (e.g., dependency graph of a program. Due to the high

  4. 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.

  5. 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.

  6. 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

  7. 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

  8. 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.

  9. 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.

  10. 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

  11. 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...

  12. 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

  13. 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

  14. 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

  15. Algorithms for Regular Tree Grammar Network Search and Their Application to Mining Human-viral Infection Patterns.

    Science.gov (United States)

    Smoly, Ilan; Carmel, Amir; Shemer-Avni, Yonat; Yeger-Lotem, Esti; Ziv-Ukelson, Michal

    2016-03-01

    Network querying is a powerful approach to mine molecular interaction networks. Most state-of-the-art network querying tools either confine the search to a prespecified topology in the form of some template subnetwork, or do not specify any topological constraints at all. Another approach is grammar-based queries, which are more flexible and expressive as they allow for expressing the topology of the sought pattern according to some grammar-based logic. Previous grammar-based network querying tools were confined to the identification of paths. In this article, we extend the patterns identified by grammar-based query approaches from paths to trees. For this, we adopt a higher order query descriptor in the form of a regular tree grammar (RTG). We introduce a novel problem and propose an algorithm to search a given graph for the k highest scoring subgraphs matching a tree accepted by an RTG. Our algorithm is based on the combination of dynamic programming with color coding, and includes an extension of previous k-best parsing optimization approaches to avoid isomorphic trees in the output. We implement the new algorithm and exemplify its application to mining viral infection patterns within molecular interaction networks. Our code is available online.

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

    NARCIS (Netherlands)

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

    2012-01-01

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

  17. 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.

  18. Grade Distribution Modeling within the Bauxite Seams of the Wachangping Mine, China, Using a Multi-Step Interpolation Algorithm

    Directory of Open Access Journals (Sweden)

    Shaofeng Wang

    2017-05-01

    Full Text Available Mineral reserve estimation and mining design depend on a precise modeling of the mineralized deposit. A multi-step interpolation algorithm, including 1D biharmonic spline estimator for interpolating floor altitudes, 2D nearest neighbor, linear, natural neighbor, cubic, biharmonic spline, inverse distance weighted, simple kriging, and ordinary kriging interpolations for grade distribution on the two vertical sections at roadways, and 3D linear interpolation for grade distribution between sections, was proposed to build a 3D grade distribution model of the mineralized seam in a longwall mining panel with a U-shaped layout having two roadways at both sides. Compared to field data from exploratory boreholes, this multi-step interpolation using a natural neighbor method shows an optimal stability and a minimal difference between interpolation and field data. Using this method, the 97,576 m3 of bauxite, in which the mass fraction of Al2O3 (Wa and the mass ratio of Al2O3 to SiO2 (Wa/s are 61.68% and 27.72, respectively, was delimited from the 189,260 m3 mineralized deposit in the 1102 longwall mining panel in the Wachangping mine, Southwest China. The mean absolute errors, the root mean squared errors and the relative standard deviations of errors between interpolated data and exploratory grade data at six boreholes are 2.544, 2.674, and 32.37% of Wa; and 1.761, 1.974, and 67.37% of Wa/s, respectively. The proposed method can be used for characterizing the grade distribution in a mineralized seam between two roadways at both sides of a longwall mining panel.

  19. Mining Research on Vibration Signal Association Rules of Quayside Container Crane Hoisting Motor Based on Apriori Algorithm

    Science.gov (United States)

    Yang, Chencheng; Tang, Gang; Hu, Xiong

    2017-07-01

    Shore-hoisting motor in the daily work will produce a large number of vibration signal data,in order to analyze the correlation among the data and discover the fault and potential safety hazard of the motor, the data are discretized first, and then Apriori algorithm are used to mine the strong association rules among the data. The results show that the relationship between day 1 and day 16 is the most closely related, which can guide the staff to analyze the work of these two days of motor to find and solve the problem of fault and safety.

  20. 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)

  1. Clustering big data streams : recent challenges and contributions

    NARCIS (Netherlands)

    Hassani, M.; Seidl, T.

    Traditional clustering algorithms merely considered static data. Today's various applications and research issues in big data mining have however to deal with continuous, possibly infinite streams of data, arriving at high velocity. Web traffic data, surveillance data, sensor measurements and stock

  2. An IPSO-SVM algorithm for security state prediction of mine production logistics system

    Science.gov (United States)

    Zhang, Yanliang; Lei, Junhui; Ma, Qiuli; Chen, Xin; Bi, Runfang

    2017-06-01

    A theoretical basis for the regulation of corporate security warning and resources was provided in order to reveal the laws behind the security state in mine production logistics. Considering complex mine production logistics system and the variable is difficult to acquire, a superior security status predicting model of mine production logistics system based on the improved particle swarm optimization and support vector machine (IPSO-SVM) is proposed in this paper. Firstly, through the linear adjustments of inertia weight and learning weights, the convergence speed and search accuracy are enhanced with the aim to deal with situations associated with the changeable complexity and the data acquisition difficulty. The improved particle swarm optimization (IPSO) is then introduced to resolve the problem of parameter settings in traditional support vector machines (SVM). At the same time, security status index system is built to determine the classification standards of safety status. The feasibility and effectiveness of this method is finally verified using the experimental results.

  3. Data Mining Learning Models and Algorithms on a Scada System Data Repository

    Directory of Open Access Journals (Sweden)

    Mircea Rîşteiu

    2010-06-01

    Full Text Available This paper presents three data mining techniques applied
    on a SCADA system data repository: Naijve Bayes, k-Nearest Neighbor and Decision Trees. A conclusion that k-Nearest Neighbor is a suitable method to classify the large amount of data considered is made finally according to the mining result and its reasonable explanation. The experiments are built on the training data set and evaluated using the new test set with machine learning tool WEKA.

  4. Algorithms

    Indian Academy of Sciences (India)

    polynomial) division have been found in Vedic Mathematics which are dated much before Euclid's algorithm. A programming language Is used to describe an algorithm for execution on a computer. An algorithm expressed using a programming.

  5. 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.

  6. Climatic zonation and land suitability determination for saffron in Khorasan-Razavi province using data mining algorithms

    Directory of Open Access Journals (Sweden)

    mehdi Bashiri

    2017-12-01

    Full Text Available Yield prediction for agricultural crops plays an important role in export-import planning, purchase guarantees, pricing, secure profits and increasing in agricultural productivity. Crop yield is affected by several parameters especially climate. In this study, the saffron yield in the Khorasan-Razavi province was evaluated by different classification algorithms including artificial neural networks, regression models, local linear trees, decision trees, discriminant analysis, random forest, support vector machine and nearest neighbor analysis. These algorithms analyzed data for 20 years (1989-2009 including 11 climatological parameters. The results showed that a few numbers of climatological parameters affect the saffron yield. The minimum, mean and maximum of temperature, had the highest positive correlations and the relative humidity of 6.5h, sunny hours, relative humidity of 18.5h, evaporation, relative humidity of 12.5h and absolute humidity had the highest negative correlations with saffron cultivation areas, respectively. In addition, in classification of saffron cultivation areas, the discriminant analysis and support vector machine had higher accuracies. The correlation between saffron cultivation area and saffron yield values was relatively high (r=0.38. The nearest neighbor analysis had the best prediction accuracy for classification of cultivation areas. For this algorithm the coefficients of determination were 1 and 0.944 for training and testing stages, respectively. However, the algorithms accuracy for prediction of crop yield from climatological parameters was low (the average coefficients of determination equal to 0.48 and 0.05 for training and testing stages. The best algorithm i.e. nearest neighbor analysis had coefficients of determination equal to 1 and 0.177 for saffron yield prediction. Results showed that, using climatological parameters and data mining algorithms can classify cultivation areas. By this way it is possible

  7. Data mining scenarios for the discovery of subtypes and the comparison of algorithms

    NARCIS (Netherlands)

    Colas, Fabrice Pierre Robert

    2009-01-01

    A data mining scenario is a logical sequence of steps to infer patterns from data. In this thesis, we present two scenarios. Our first scenario aims to identify homogeneous subtypes in data. It was applied to clinical research on Osteoarthritis (OA) and Parkinson’s disease (PD) and in drug

  8. 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.

  9. 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.

  10. Modeling and clustering users with evolving profiles in usage streams

    KAUST Repository

    Zhang, Chongsheng

    2012-09-01

    Today, there is an increasing need of data stream mining technology to discover important patterns on the fly. Existing data stream models and algorithms commonly assume that users\\' records or profiles in data streams will not be updated or revised once they arrive. Nevertheless, in various applications such asWeb usage, the records/profiles of the users can evolve along time. This kind of streaming data evolves in two forms, the streaming of tuples or transactions as in the case of traditional data streams, and more importantly, the evolving of user records/profiles inside the streams. Such data streams bring difficulties on modeling and clustering for exploring users\\' behaviors. In this paper, we propose three models to summarize this kind of data streams, which are the batch model, the Evolving Objects (EO) model and the Dynamic Data Stream (DDS) model. Through creating, updating and deleting user profiles, these models summarize the behaviors of each user as a profile object. Based upon these models, clustering algorithms are employed to discover interesting user groups from the profile objects. We have evaluated all the proposed models on a large real-world data set, showing that the DDS model summarizes the data streams with evolving tuples more efficiently and effectively, and provides better basis for clustering users than the other two models. © 2012 IEEE.

  11. Modeling and clustering users with evolving profiles in usage streams

    KAUST Repository

    Zhang, Chongsheng; Masseglia, Florent; Zhang, Xiangliang

    2012-01-01

    Today, there is an increasing need of data stream mining technology to discover important patterns on the fly. Existing data stream models and algorithms commonly assume that users' records or profiles in data streams will not be updated or revised once they arrive. Nevertheless, in various applications such asWeb usage, the records/profiles of the users can evolve along time. This kind of streaming data evolves in two forms, the streaming of tuples or transactions as in the case of traditional data streams, and more importantly, the evolving of user records/profiles inside the streams. Such data streams bring difficulties on modeling and clustering for exploring users' behaviors. In this paper, we propose three models to summarize this kind of data streams, which are the batch model, the Evolving Objects (EO) model and the Dynamic Data Stream (DDS) model. Through creating, updating and deleting user profiles, these models summarize the behaviors of each user as a profile object. Based upon these models, clustering algorithms are employed to discover interesting user groups from the profile objects. We have evaluated all the proposed models on a large real-world data set, showing that the DDS model summarizes the data streams with evolving tuples more efficiently and effectively, and provides better basis for clustering users than the other two models. © 2012 IEEE.

  12. hs-CRP is strongly associated with coronary heart disease (CHD): A data mining approach using decision tree algorithm.

    Science.gov (United States)

    Tayefi, Maryam; Tajfard, Mohammad; Saffar, Sara; Hanachi, Parichehr; Amirabadizadeh, Ali Reza; Esmaeily, Habibollah; Taghipour, Ali; Ferns, Gordon A; Moohebati, Mohsen; Ghayour-Mobarhan, Majid

    2017-04-01

    Coronary heart disease (CHD) is an important public health problem globally. Algorithms incorporating the assessment of clinical biomarkers together with several established traditional risk factors can help clinicians to predict CHD and support clinical decision making with respect to interventions. Decision tree (DT) is a data mining model for extracting hidden knowledge from large databases. We aimed to establish a predictive model for coronary heart disease using a decision tree algorithm. Here we used a dataset of 2346 individuals including 1159 healthy participants and 1187 participant who had undergone coronary angiography (405 participants with negative angiography and 782 participants with positive angiography). We entered 10 variables of a total 12 variables into the DT algorithm (including age, sex, FBG, TG, hs-CRP, TC, HDL, LDL, SBP and DBP). Our model could identify the associated risk factors of CHD with sensitivity, specificity, accuracy of 96%, 87%, 94% and respectively. Serum hs-CRP levels was at top of the tree in our model, following by FBG, gender and age. Our model appears to be an accurate, specific and sensitive model for identifying the presence of CHD, but will require validation in prospective studies. Copyright © 2017 Elsevier B.V. All rights reserved.

  13. 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.

  14. On finding similar items in a stream of transactions

    DEFF Research Database (Denmark)

    Campagna, Andrea; Pagh, Rasmus

    2010-01-01

    While there has been a lot of work on finding frequent itemsets in transaction data streams, none of these solve the problem of finding similar pairs according to standard similarity measures. This paper is a first attempt at dealing with this, arguably more important, problem. We start out with ...... in random order, and show that surprisingly, not only is small-space similarity mining possible for the most common similarity measures, but the mining accuracy {\\em improves\\/} with the length of the stream for any fixed support threshold....... with a negative result that also explains the lack of theoretical upper bounds on the space usage of data mining algorithms for finding frequent itemsets: Any algorithm that (even only approximately and with a chance of error) finds the most frequent $k$-itemset must use space $\\Omega...

  15. Analysis Of Data Mining For Car Sales Sparepart Using Apriori Algorithm (Case Study: PT. IDK 1 FIELD

    Directory of Open Access Journals (Sweden)

    Khairul Ummi

    2016-10-01

    Full Text Available PT. IDK 1 is one of the branch offices honda car dealership that sells various types of variants honda matic or manual car and motorcycle parts. Any sales or goods sold will be performed by inputting the database directly connected directly to the central office. But PT. IDK 1 do not know a couple items frequently purchased parts simultaneously. When the stock of spare parts which amount is low, the office is only asking them to send the stock of spare parts from the central office without knowing that the other parts if the parts were purchased then the other parts were also purchased. It was considered difficult when restocking of goods because of the many types of auto parts. Data mining techniques have been widely used to solve the existing problems with the implementation of the algorithm one A-Priori to obtain information about the association between the product of a database transaction. Sales transaction data honda car parts at PT. IDK 1 can be reprocessed using data mining applications resulting association rules is a strong link between itemset sales of spare parts so that it can provide recommendations and facilitate restocking items in the arrangement or placement of goods related to a strong interdependence.

  16. A Tutorial on Nonlinear Time-Series Data Mining in Engineering Asset Health and Reliability Prediction: Concepts, Models, and Algorithms

    Directory of Open Access Journals (Sweden)

    Ming Dong

    2010-01-01

    Full Text Available The primary objective of engineering asset management is to optimize assets service delivery potential and to minimize the related risks and costs over their entire life through the development and application of asset health and usage management in which the health and reliability prediction plays an important role. In real-life situations where an engineering asset operates under dynamic operational and environmental conditions, the lifetime of an engineering asset is generally described as monitored nonlinear time-series data and subject to high levels of uncertainty and unpredictability. It has been proved that application of data mining techniques is very useful for extracting relevant features which can be used as parameters for assets diagnosis and prognosis. In this paper, a tutorial on nonlinear time-series data mining in engineering asset health and reliability prediction is given. Besides that an overview on health and reliability prediction techniques for engineering assets is covered, this tutorial will focus on concepts, models, algorithms, and applications of hidden Markov models (HMMs and hidden semi-Markov models (HSMMs in engineering asset health prognosis, which are representatives of recent engineering asset health prediction techniques.

  17. Algorithms

    Indian Academy of Sciences (India)

    to as 'divide-and-conquer'. Although there has been a large effort in realizing efficient algorithms, there are not many universally accepted algorithm design paradigms. In this article, we illustrate algorithm design techniques such as balancing, greedy strategy, dynamic programming strategy, and backtracking or traversal of ...

  18. Frequent Pairs in Data Streams: Exploiting Parallelism and Skew

    DEFF Research Database (Denmark)

    Campagna, Andrea; Kutzkow, Konstantin; Pagh, Rasmus

    2011-01-01

    We introduce the Pair Streaming Engine (PairSE) that detects frequent pairs in a data stream of transactions. Our algorithm finds the most frequent pairs with high probability, and gives tight bounds on their frequency. It is particularly space efficient for skewed distribution of pair supports...... items mining in data streams. We show how to efficiently scale these approaches to handle large transactions. We report experimental results showcasing precision and recall of our method. In particular, we find that often our method achieves excellent precision, returning identical upper and lower...... bounds on the supports of the most frequent pairs....

  19. 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)

  20. Order Batching in Warehouses by Minimizing Total Tardiness: A Hybrid Approach of Weighted Association Rule Mining and Genetic Algorithms

    Directory of Open Access Journals (Sweden)

    Amir Hossein Azadnia

    2013-01-01

    Full Text Available One of the cost-intensive issues in managing warehouses is the order picking problem which deals with the retrieval of items from their storage locations in order to meet customer requests. Many solution approaches have been proposed in order to minimize traveling distance in the process of order picking. However, in practice, customer orders have to be completed by certain due dates in order to avoid tardiness which is neglected in most of the related scientific papers. Consequently, we proposed a novel solution approach in order to minimize tardiness which consists of four phases. First of all, weighted association rule mining has been used to calculate associations between orders with respect to their due date. Next, a batching model based on binary integer programming has been formulated to maximize the associations between orders within each batch. Subsequently, the order picking phase will come up which used a Genetic Algorithm integrated with the Traveling Salesman Problem in order to identify the most suitable travel path. Finally, the Genetic Algorithm has been applied for sequencing the constructed batches in order to minimize tardiness. Illustrative examples and comparisons are presented to demonstrate the proficiency and solution quality of the proposed approach.

  1. An Unsupervised Opinion Mining Approach for Japanese Weblog Reputation Information Using an Improved SO-PMI Algorithm

    Science.gov (United States)

    Wang, Guangwei; Araki, Kenji

    In this paper, we propose an improved SO-PMI (Semantic Orientation Using Pointwise Mutual Information) algorithm, for use in Japanese Weblog Opinion Mining. SO-PMI is an unsupervised approach proposed by Turney that has been shown to work well for English. When this algorithm was translated into Japanese naively, most phrases, whether positive or negative in meaning, received a negative SO. For dealing with this slanting phenomenon, we propose three improvements: to expand the reference words to sets of words, to introduce a balancing factor and to detect neutral expressions. In our experiments, the proposed improvements obtained a well-balanced result: both positive and negative accuracy exceeded 62%, when evaluated on 1,200 opinion sentences sampled from three different domains (reviews of Electronic Products, Cars and Travels from Kakaku. com). In a comparative experiment on the same corpus, a supervised approach (SA-Demo) achieved a very similar accuracy to our method. This shows that our proposed approach effectively adapted SO-PMI for Japanese, and it also shows the generality of SO-PMI.

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

    Science.gov (United States)

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

    2018-03-01

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

  3. Learning Analytics Through Serious Games: Data Mining Algorithms for Performance Measurement and Improvement Purposes

    Directory of Open Access Journals (Sweden)

    Abdelali Slimani

    2018-01-01

    Full Text Available learning analytics is an emerging discipline focused on the measurement, collection, analysis and reporting of learner interaction data through the E-learning contents. Serious game provides a potential source for relevant educational user data; it can propose an interactive environment for training and offer an effective learning process. This paper presents methods and approaches of educational data mining such as EM and K-Means to discuss the learning analytics through serious games, and then we provide an analysis of the player experience data collected from the educational game “ELISA” used to teach students of biology the immunological technique for determination of ANTI-HIV antibodies. Finally, we propose critically evaluation of our results including the limitations of our study and making suggestions for future research that links learning analytics and serious gaming.

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

    Directory of Open Access Journals (Sweden)

    Schomburg Dietmar

    2010-07-01

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

  5. Study on text mining algorithm for ultrasound examination of chronic liver diseases based on spectral clustering

    Science.gov (United States)

    Chang, Bingguo; Chen, Xiaofei

    2018-05-01

    Ultrasonography is an important examination for the diagnosis of chronic liver disease. The doctor gives the liver indicators and suggests the patient's condition according to the description of ultrasound report. With the rapid increase in the amount of data of ultrasound report, the workload of professional physician to manually distinguish ultrasound results significantly increases. In this paper, we use the spectral clustering method to cluster analysis of the description of the ultrasound report, and automatically generate the ultrasonic diagnostic diagnosis by machine learning. 110 groups ultrasound examination report of chronic liver disease were selected as test samples in this experiment, and the results were validated by spectral clustering and compared with k-means clustering algorithm. The results show that the accuracy of spectral clustering is 92.73%, which is higher than that of k-means clustering algorithm, which provides a powerful ultrasound-assisted diagnosis for patients with chronic liver disease.

  6. PedMine – A simulated annealing algorithm to identify maximally unrelated individuals in population isolates

    OpenAIRE

    Douglas, Julie A.; Sandefur, Conner I.

    2008-01-01

    In family-based genetic studies, it is often useful to identify a subset of unrelated individuals. When such studies are conducted in population isolates, however, most if not all individuals are often detectably related to each other. To identify a set of maximally unrelated (or equivalently, minimally related) individuals, we have implemented simulated annealing, a general-purpose algorithm for solving difficult combinatorial optimization problems. We illustrate our method on data from a ge...

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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...

  12. Algorithms

    Indian Academy of Sciences (India)

    ticians but also forms the foundation of computer science. Two ... with methods of developing algorithms for solving a variety of problems but ... applications of computers in science and engineer- ... numerical calculus are as important. We will ...

  13. An Incremental Classification Algorithm for Mining Data with Feature Space Heterogeneity

    Directory of Open Access Journals (Sweden)

    Yu Wang

    2014-01-01

    Full Text Available Feature space heterogeneity often exists in many real world data sets so that some features are of different importance for classification over different subsets. Moreover, the pattern of feature space heterogeneity might dynamically change over time as more and more data are accumulated. In this paper, we develop an incremental classification algorithm, Supervised Clustering for Classification with Feature Space Heterogeneity (SCCFSH, to address this problem. In our approach, supervised clustering is implemented to obtain a number of clusters such that samples in each cluster are from the same class. After the removal of outliers, relevance of features in each cluster is calculated based on their variations in this cluster. The feature relevance is incorporated into distance calculation for classification. The main advantage of SCCFSH lies in the fact that it is capable of solving a classification problem with feature space heterogeneity in an incremental way, which is favorable for online classification tasks with continuously changing data. Experimental results on a series of data sets and application to a database marketing problem show the efficiency and effectiveness of the proposed approach.

  14. Study on the Detection of Moving Target in the Mining Method Based on Hybrid Algorithm for Sports Video Analysis

    Directory of Open Access Journals (Sweden)

    Huang Tian

    2014-10-01

    Full Text Available Moving object detection and tracking is the computer vision and image processing is a hot research direction, based on the analysis of the moving target detection and tracking algorithm in common use, focus on the sports video target tracking non rigid body. In sports video, non rigid athletes often have physical deformation in the process of movement, and may be associated with the occurrence of moving target under cover. Media data is surging to fast search and query causes more difficulties in data. However, the majority of users want to be able to quickly from the multimedia data to extract the interested content and implicit knowledge (concepts, rules, rules, models and correlation, retrieval and query quickly to take advantage of them, but also can provide the decision support problem solving hierarchy. Based on the motion in sport video object as the object of study, conducts the system research from the theoretical level and technical framework and so on, from the layer by layer mining between low level motion features to high-level semantic motion video, not only provides support for users to find information quickly, but also can provide decision support for the user to solve the problem.

  15. Clustering box office movie with Partition Around Medoids (PAM) Algorithm based on Text Mining of Indonesian subtitle

    Science.gov (United States)

    Alfarizy, A. D.; Indahwati; Sartono, B.

    2017-03-01

    Indonesia is the largest Hollywood movie industry target market in Southeast Asia in 2015. Hollywood movies distributed in Indonesia targeted people in all range of ages including children. Low awareness of guiding children while watching movies make them could watch any rated films even the unsuitable ones for their ages. Even after being translated into Bahasa and passed the censorship phase, words that uncomfortable for children to watch still exist. The purpose of this research is to cluster box office Hollywood movies based on Indonesian subtitle, revenue, IMDb user rating and genres as one of the reference for adults to choose right movies for their children to watch. Text mining is used to extract words from the subtitles and count the frequency for three group of words (bad words, sexual words and terror words), while Partition Around Medoids (PAM) Algorithm with Gower similarity coefficient as proximity matrix is used as clustering method. We clustered 624 movies from 2006 until first half of 2016 from IMDb. Cluster with highest silhouette coefficient value (0.36) is the one with 5 clusters. Animation, Adventure and Comedy movies with high revenue like in cluster 5 is recommended for children to watch, while Comedy movies with high revenue like in cluster 4 should be avoided to watch.

  16. Data Mining at NASA: From Theory to Applications

    Science.gov (United States)

    Srivastava, Ashok N.

    2009-01-01

    This slide presentation demonstrates the data mining/machine learning capabilities of NASA Ames and Intelligent Data Understanding (IDU) group. This will encompass the work done recently in the group by various group members. The IDU group develops novel algorithms to detect, classify, and predict events in large data streams for scientific and engineering systems. This presentation for Knowledge Discovery and Data Mining 2009 is to demonstrate the data mining/machine learning capabilities of NASA Ames and IDU group. This will encompass the work done re cently in the group by various group members.

  17. 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

  18. Algorithms

    Indian Academy of Sciences (India)

    algorithm design technique called 'divide-and-conquer'. One of ... Turtle graphics, September. 1996. 5. ... whole list named 'PO' is a pointer to the first element of the list; ..... Program for computing matrices X and Y and placing the result in C *).

  19. Algorithms

    Indian Academy of Sciences (India)

    algorithm that it is implicitly understood that we know how to generate the next natural ..... Explicit comparisons are made in line (1) where maximum and minimum is ... It can be shown that the function T(n) = 3/2n -2 is the solution to the above ...

  20. Productivity of Stream Definitions

    NARCIS (Netherlands)

    Endrullis, Jörg; Grabmayer, Clemens; Hendriks, Dimitri; Isihara, Ariya; Klop, Jan

    2007-01-01

    We give an algorithm for deciding productivity of a large and natural class of recursive stream definitions. A stream definition is called ‘productive’ if it can be evaluated continuously in such a way that a uniquely determined stream is obtained as the limit. Whereas productivity is undecidable

  1. Productivity of stream definitions

    NARCIS (Netherlands)

    Endrullis, J.; Grabmayer, C.A.; Hendriks, D.; Isihara, A.; Klop, J.W.

    2008-01-01

    We give an algorithm for deciding productivity of a large and natural class of recursive stream definitions. A stream definition is called ‘productive’ if it can be evaluated continually in such a way that a uniquely determined stream in constructor normal form is obtained as the limit. Whereas

  2. Algorithms

    Indian Academy of Sciences (India)

    will become clear in the next article when we discuss a simple logo like programming language. ... Rod B may be used as an auxiliary store. The problem is to find an algorithm which performs this task. ... No disks are moved from A to Busing C as auxiliary rod. • move _disk (A, C);. (No + l)th disk is moved from A to C directly ...

  3. 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

  4. New Splitting Criteria for Decision Trees in Stationary Data Streams.

    Science.gov (United States)

    Jaworski, Maciej; Duda, Piotr; Rutkowski, Leszek; Jaworski, Maciej; Duda, Piotr; Rutkowski, Leszek; Rutkowski, Leszek; Duda, Piotr; Jaworski, Maciej

    2018-06-01

    The most popular tools for stream data mining are based on decision trees. In previous 15 years, all designed methods, headed by the very fast decision tree algorithm, relayed on Hoeffding's inequality and hundreds of researchers followed this scheme. Recently, we have demonstrated that although the Hoeffding decision trees are an effective tool for dealing with stream data, they are a purely heuristic procedure; for example, classical decision trees such as ID3 or CART cannot be adopted to data stream mining using Hoeffding's inequality. Therefore, there is an urgent need to develop new algorithms, which are both mathematically justified and characterized by good performance. In this paper, we address this problem by developing a family of new splitting criteria for classification in stationary data streams and investigating their probabilistic properties. The new criteria, derived using appropriate statistical tools, are based on the misclassification error and the Gini index impurity measures. The general division of splitting criteria into two types is proposed. Attributes chosen based on type- splitting criteria guarantee, with high probability, the highest expected value of split measure. Type- criteria ensure that the chosen attribute is the same, with high probability, as it would be chosen based on the whole infinite data stream. Moreover, in this paper, two hybrid splitting criteria are proposed, which are the combinations of single criteria based on the misclassification error and Gini index.

  5. rEMM: Extensible Markov Model for Data Stream Clustering in R

    Directory of Open Access Journals (Sweden)

    Michael Hahsler

    2010-10-01

    Full Text Available Clustering streams of continuously arriving data has become an important application of data mining in recent years and efficient algorithms have been proposed by several researchers. However, clustering alone neglects the fact that data in a data stream is not only characterized by the proximity of data points which is used by clustering, but also by a temporal component. The extensible Markov model (EMM adds the temporal component to data stream clustering by superimposing a dynamically adapting Markov chain. In this paper we introduce the implementation of the R extension package rEMM which implements EMM and we discuss some examples and applications.

  6. 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...

  7. 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...

  8. The study of Kruskal's and Prim's algorithms on the Multiple Instruction and Single Data stream computer system

    Directory of Open Access Journals (Sweden)

    A. Yu. Popov

    2015-01-01

    Full Text Available Bauman Moscow State Technical University is implementing a project to develop operating principles of computer system having radically new architecture. A developed working model of the system allowed us to evaluate an efficiency of developed hardware and software. The experimental results presented in previous studies, as well as the analysis of operating principles of new computer system permit to draw conclusions regarding its efficiency in solving discrete optimization problems related to processing of sets.The new architecture is based on a direct hardware support of operations of discrete mathematics, which is reflected in using the special facilities for processing of sets and data structures. Within the framework of the project a special device was designed, i.e. a structure processor (SP, which improved the performance, without limiting the scope of applications of such a computer system.The previous works presented the basic principles of the computational process organization in MISD (Multiple Instructions, Single Data system, showed the structure and features of the structure processor and the general principles to solve discrete optimization problems on graphs.This paper examines two search algorithms of the minimum spanning tree, namely Kruskal's and Prim's algorithms. It studies the implementations of algorithms for two SP operation modes: coprocessor mode and MISD one. The paper presents results of experimental comparison of MISD system performance in coprocessor mode with mainframes.

  9. 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...

  10. 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

  11. Improvements in seismic event locations in a deep western U.S. coal mine using tomographic velocity models and an evolutionary search algorithm

    Energy Technology Data Exchange (ETDEWEB)

    Adam Lurka; Peter Swanson [Central Mining Institute, Katowice (Poland)

    2009-09-15

    Methods of improving seismic event locations were investigated as part of a research study aimed at reducing ground control safety hazards. Seismic event waveforms collected with a 23-station three-dimensional sensor array during longwall coal mining provide the data set used in the analyses. A spatially variable seismic velocity model is constructed using seismic event sources in a passive tomographic method. The resulting three-dimensional velocity model is used to relocate seismic event positions. An evolutionary optimization algorithm is implemented and used in both the velocity model development and in seeking improved event location solutions. Results obtained using the different velocity models are compared. The combination of the tomographic velocity model development and evolutionary search algorithm provides improvement to the event locations. 13 refs., 5 figs., 4 tabs.

  12. Final Report: Sampling-Based Algorithms for Estimating Structure in Big Data.

    Energy Technology Data Exchange (ETDEWEB)

    Matulef, Kevin Michael [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2017-02-01

    The purpose of this project was to develop sampling-based algorithms to discover hidden struc- ture in massive data sets. Inferring structure in large data sets is an increasingly common task in many critical national security applications. These data sets come from myriad sources, such as network traffic, sensor data, and data generated by large-scale simulations. They are often so large that traditional data mining techniques are time consuming or even infeasible. To address this problem, we focus on a class of algorithms that do not compute an exact answer, but instead use sampling to compute an approximate answer using fewer resources. The particular class of algorithms that we focus on are streaming algorithms , so called because they are designed to handle high-throughput streams of data. Streaming algorithms have only a small amount of working storage - much less than the size of the full data stream - so they must necessarily use sampling to approximate the correct answer. We present two results: * A streaming algorithm called HyperHeadTail , that estimates the degree distribution of a graph (i.e., the distribution of the number of connections for each node in a network). The degree distribution is a fundamental graph property, but prior work on estimating the degree distribution in a streaming setting was impractical for many real-world application. We improve upon prior work by developing an algorithm that can handle streams with repeated edges, and graph structures that evolve over time. * An algorithm for the task of maintaining a weighted subsample of items in a stream, when the items must be sampled according to their weight, and the weights are dynamically changing. To our knowledge, this is the first such algorithm designed for dynamically evolving weights. We expect it may be useful as a building block for other streaming algorithms on dynamic data sets.

  13. Design of Compressed Sensing Algorithm for Coal Mine IoT Moving Measurement Data Based on a Multi-Hop Network and Total Variation

    Directory of Open Access Journals (Sweden)

    Gang Wang

    2018-05-01

    Full Text Available As the application of a coal mine Internet of Things (IoT, mobile measurement devices, such as intelligent mine lamps, cause moving measurement data to be increased. How to transmit these large amounts of mobile measurement data effectively has become an urgent problem. This paper presents a compressed sensing algorithm for the large amount of coal mine IoT moving measurement data based on a multi-hop network and total variation. By taking gas data in mobile measurement data as an example, two network models for the transmission of gas data flow, namely single-hop and multi-hop transmission modes, are investigated in depth, and a gas data compressed sensing collection model is built based on a multi-hop network. To utilize the sparse characteristics of gas data, the concept of total variation is introduced and a high-efficiency gas data compression and reconstruction method based on Total Variation Sparsity based on Multi-Hop (TVS-MH is proposed. According to the simulation results, by using the proposed method, the moving measurement data flow from an underground distributed mobile network can be acquired and transmitted efficiently.

  14. Design of Compressed Sensing Algorithm for Coal Mine IoT Moving Measurement Data Based on a Multi-Hop Network and Total Variation.

    Science.gov (United States)

    Wang, Gang; Zhao, Zhikai; Ning, Yongjie

    2018-05-28

    As the application of a coal mine Internet of Things (IoT), mobile measurement devices, such as intelligent mine lamps, cause moving measurement data to be increased. How to transmit these large amounts of mobile measurement data effectively has become an urgent problem. This paper presents a compressed sensing algorithm for the large amount of coal mine IoT moving measurement data based on a multi-hop network and total variation. By taking gas data in mobile measurement data as an example, two network models for the transmission of gas data flow, namely single-hop and multi-hop transmission modes, are investigated in depth, and a gas data compressed sensing collection model is built based on a multi-hop network. To utilize the sparse characteristics of gas data, the concept of total variation is introduced and a high-efficiency gas data compression and reconstruction method based on Total Variation Sparsity based on Multi-Hop (TVS-MH) is proposed. According to the simulation results, by using the proposed method, the moving measurement data flow from an underground distributed mobile network can be acquired and transmitted efficiently.

  15. Data mining with SPSS modeler theory, exercises and solutions

    CERN Document Server

    Wendler, Tilo

    2016-01-01

    Introducing the IBM SPSS Modeler, this book guides readers through data mining processes and presents relevant statistical methods. There is a special focus on step-by-step tutorials and well-documented examples that help demystify complex mathematical algorithms and computer programs. The variety of exercises and solutions as well as an accompanying website with data sets and SPSS Modeler streams are particularly valuable. While intended for students, the simplicity of the Modeler makes the book useful for anyone wishing to learn about basic and more advanced data mining, and put this knowledge into practice.

  16. DTFP-Growth: Dynamic Threshold-Based FP-Growth Rule Mining Algorithm Through Integrating Gene Expression, Methylation, and Protein-Protein Interaction Profiles.

    Science.gov (United States)

    Mallik, Saurav; Bhadra, Tapas; Mukherji, Ayan; Mallik, Saurav; Bhadra, Tapas; Mukherji, Ayan; Mallik, Saurav; Bhadra, Tapas; Mukherji, Ayan

    2018-04-01

    Association rule mining is an important technique for identifying interesting relationships between gene pairs in a biological data set. Earlier methods basically work for a single biological data set, and, in maximum cases, a single minimum support cutoff can be applied globally, i.e., across all genesets/itemsets. To overcome this limitation, in this paper, we propose dynamic threshold-based FP-growth rule mining algorithm that integrates gene expression, methylation and protein-protein interaction profiles based on weighted shortest distance to find the novel associations among different pairs of genes in multi-view data sets. For this purpose, we introduce three new thresholds, namely, Distance-based Variable/Dynamic Supports (DVS), Distance-based Variable Confidences (DVC), and Distance-based Variable Lifts (DVL) for each rule by integrating co-expression, co-methylation, and protein-protein interactions existed in the multi-omics data set. We develop the proposed algorithm utilizing these three novel multiple threshold measures. In the proposed algorithm, the values of , , and are computed for each rule separately, and subsequently it is verified whether the support, confidence, and lift of each evolved rule are greater than or equal to the corresponding individual , , and values, respectively, or not. If all these three conditions for a rule are found to be true, the rule is treated as a resultant rule. One of the major advantages of the proposed method compared with other related state-of-the-art methods is that it considers both the quantitative and interactive significance among all pairwise genes belonging to each rule. Moreover, the proposed method generates fewer rules, takes less running time, and provides greater biological significance for the resultant top-ranking rules compared to previous methods.

  17. Efficient constraint-based Sequential Pattern Mining (SPM algorithm to understand customers’ buying behaviour from time stamp-based sequence dataset

    Directory of Open Access Journals (Sweden)

    Niti Ashish Kumar Desai

    2015-12-01

    Full Text Available Business Strategies are formulated based on an understanding of customer needs. This requires development of a strategy to understand customer behaviour and buying patterns, both current and future. This involves understanding, first how an organization currently understands customer needs and second predicting future trends to drive growth. This article focuses on purchase trend of customer, where timing of purchase is more important than association of item to be purchased, and which can be found out with Sequential Pattern Mining (SPM methods. Conventional SPM algorithms worked purely on frequency identifying patterns that were more frequent but suffering from challenges like generation of huge number of uninteresting patterns, lack of user’s interested patterns, rare item problem, etc. Article attempts a solution through development of a SPM algorithm based on various constraints like Gap, Compactness, Item, Recency, Profitability and Length along with Frequency constraint. Incorporation of six additional constraints is as well to ensure that all patterns are recently active (Recency, active for certain time span (Compactness, profitable and indicative of next timeline for purchase (Length―Item―Gap. The article also attempts to throw light on how proposed Constraint-based Prefix Span algorithm is helpful to understand buying behaviour of customer which is in formative stage.

  18. 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...

  19. 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.

  20. Personal continuous route pattern mining

    Institute of Scientific and Technical Information of China (English)

    Qian YE; Ling CHEN; Gen-cai CHEN

    2009-01-01

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

  1. 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

  2. Are Female Applicants Disadvantaged in National Institutes of Health Peer Review? Combining Algorithmic Text Mining and Qualitative Methods to Detect Evaluative Differences in R01 Reviewers' Critiques.

    Science.gov (United States)

    Magua, Wairimu; Zhu, Xiaojin; Bhattacharya, Anupama; Filut, Amarette; Potvien, Aaron; Leatherberry, Renee; Lee, You-Geon; Jens, Madeline; Malikireddy, Dastagiri; Carnes, Molly; Kaatz, Anna

    2017-05-01

    Women are less successful than men in renewing R01 grants from the National Institutes of Health. Continuing to probe text mining as a tool to identify gender bias in peer review, we used algorithmic text mining and qualitative analysis to examine a sample of critiques from men's and women's R01 renewal applications previously analyzed by counting and comparing word categories. We analyzed 241 critiques from 79 Summary Statements for 51 R01 renewals awarded to 45 investigators (64% male, 89% white, 80% PhD) at the University of Wisconsin-Madison between 2010 and 2014. We used latent Dirichlet allocation to discover evaluative "topics" (i.e., words that co-occur with high probability). We then qualitatively examined the context in which evaluative words occurred for male and female investigators. We also examined sex differences in assigned scores controlling for investigator productivity. Text analysis results showed that male investigators were described as "leaders" and "pioneers" in their "fields," with "highly innovative" and "highly significant research." By comparison, female investigators were characterized as having "expertise" and working in "excellent" environments. Applications from men received significantly better priority, approach, and significance scores, which could not be accounted for by differences in productivity. Results confirm our previous analyses suggesting that gender stereotypes operate in R01 grant peer review. Reviewers may more easily view male than female investigators as scientific leaders with significant and innovative research, and score their applications more competitively. Such implicit bias may contribute to sex differences in award rates for R01 renewals.

  3. 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...

  4. LHCb trigger streams optimization

    Science.gov (United States)

    Derkach, D.; Kazeev, N.; Neychev, R.; Panin, A.; Trofimov, I.; Ustyuzhanin, A.; Vesterinen, M.

    2017-10-01

    The LHCb experiment stores around 1011 collision events per year. A typical physics analysis deals with a final sample of up to 107 events. Event preselection algorithms (lines) are used for data reduction. Since the data are stored in a format that requires sequential access, the lines are grouped into several output file streams, in order to increase the efficiency of user analysis jobs that read these data. The scheme efficiency heavily depends on the stream composition. By putting similar lines together and balancing the stream sizes it is possible to reduce the overhead. We present a method for finding an optimal stream composition. The method is applied to a part of the LHCb data (Turbo stream) on the stage where it is prepared for user physics analysis. This results in an expected improvement of 15% in the speed of user analysis jobs, and will be applied on data to be recorded in 2017.

  5. Distributed genetic process mining

    NARCIS (Netherlands)

    Bratosin, C.C.; Sidorova, N.; Aalst, van der W.M.P.

    2010-01-01

    Process mining aims at discovering process models from data logs in order to offer insight into the real use of information systems. Most of the existing process mining algorithms fail to discover complex constructs or have problems dealing with noise and infrequent behavior. The genetic process

  6. 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.

  7. 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.

  8. 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

  9. Diagnosing Breast Cancer with the Aid of Fuzzy Logic Based on Data Mining of a Genetic Algorithm in Infrared Images

    Directory of Open Access Journals (Sweden)

    Hossein Ghayoumi Zadeh

    2012-10-01

    Full Text Available Background: Breast cancer is one of the most prevalent cancers among women today. The importance of breast cancer screening, its role in the timely identification of patients, and the reduction in treatment expenses are considered to be among the highest sanitary priorities of a modern country. Thermal imaging clearly possesses a special role in this stage due to rapid diagnosis and use of harmless rays.Methods: We used a thermal camera for imaging of the patients. Important parameters were derived from the images for their posterior analysis with the aid of a genetic algorithm. The principal components that were entered in a fuzzy neural network for clustering breast cancer were identified.Results: The number of images considered for the test included a database of 200 patients out of whom 15 were diagnosed with breast cancer via mammography. Results of the base method show a sensitivity of 93%. The selection of parameters in the combination module gave rise measured errors, which in training of the fuzzy-neural network were of the order of clustering 1.0923×10-5, which reached 2%.Conclusion: The study indicates that thermal image scanning coupled with the presented method based on artificial intelligence can possess a special status in screening women for breast cancer due to the use of harmless non-radiation rays. There are cases where physicians cannot decisively say that the observed pattern in theimage is benign or malignant. In such cases, the response of the computer model can be a valuable support tool for the physician enabling an accurate diagnosis based on the type of imaging pattern as a response from the computer model.

  10. Data mining methods

    CERN Document Server

    Chattamvelli, Rajan

    2015-01-01

    DATA MINING METHODS, Second Edition discusses both theoretical foundation and practical applications of datamining in a web field including banking, e-commerce, medicine, engineering and management. This book starts byintroducing data and information, basic data type, data category and applications of data mining. The second chapterbriefly reviews data visualization technology and importance in data mining. Fundamentals of probability and statisticsare discussed in chapter 3, and novel algorithm for sample covariants are derived. The next two chapters give an indepthand useful discussion of data warehousing and OLAP. Decision trees are clearly explained and a new tabularmethod for decision tree building is discussed. The chapter on association rules discusses popular algorithms andcompares various algorithms in summary table form. An interesting application of genetic algorithm is introduced inthe next chapter. Foundations of neural networks are built from scratch and the back propagation algorithm is derived...

  11. Development of energy-saving technologies providing comfortable microclimate conditions for mining

    Directory of Open Access Journals (Sweden)

    Б. П. Казаков

    2017-03-01

    Full Text Available The paper contains analysis of natural and technogenic factors influencing properties of mine atmosphere, defining level of mining safety and probability of emergencies. Main trends in development of energy-saving technologies providing comfortable microclimate conditions are highlighted. A complex of methods and mathematical models has been developed to carry out aerologic and thermophysical calculations. Main ways of improvement for existing calculation methods of stationary and non-stationary air distribution have been defined: use of ejection draught sources to organize recirculation ventilation; accounting of depression losses at working intersections; inertance impact of  air streams and mined-out spaces for modeling transitory emergency scenarios. Based on the calculation algorithm of airflow rate distribution in the mine network, processing method has been developed for the results of air-depressive surveys under conditions of data shortage. Processes of dust transfer have been modeled in view of its coagulation and settlement, as well as interaction with water drops in case of wet dust prevention. A method to calculate intensity of water evaporation and condensation has been suggested, which allows to forecast time, duration and quantity of precipitation and its migration inside the mine during winter season. Solving the problem of heat exchange between mine airflow and timbering of the ventilation shaft in a conjugation formulation permits to estimate depression value of natural draught and conditions of convective balance between air streams. Normalization of microclimatic parameters for mine atmosphere is forecasted for the use of heat-exchange units either heating or cooling and dehumidifying ventilation air. Algorithms are presented that permit to minimize ventilation energy demands at the stages of mine design and exploitation.

  12. 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.

  13. 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...

  14. 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.

  15. 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 ...

  16. Parallel sorting algorithms

    CERN Document Server

    Akl, Selim G

    1985-01-01

    Parallel Sorting Algorithms explains how to use parallel algorithms to sort a sequence of items on a variety of parallel computers. The book reviews the sorting problem, the parallel models of computation, parallel algorithms, and the lower bounds on the parallel sorting problems. The text also presents twenty different algorithms, such as linear arrays, mesh-connected computers, cube-connected computers. Another example where algorithm can be applied is on the shared-memory SIMD (single instruction stream multiple data stream) computers in which the whole sequence to be sorted can fit in the

  17. 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 ...

  18. 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.

  19. 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.

  20. 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.

  1. Stream Clustering of Growing Objects

    Science.gov (United States)

    Siddiqui, Zaigham Faraz; Spiliopoulou, Myra

    We study incremental clustering of objects that grow and accumulate over time. The objects come from a multi-table stream e.g. streams of Customer and Transaction. As the Transactions stream accumulates, the Customers’ profiles grow. First, we use an incremental propositionalisation to convert the multi-table stream into a single-table stream upon which we apply clustering. For this purpose, we develop an online version of K-Means algorithm that can handle these swelling objects and any new objects that arrive. The algorithm also monitors the quality of the model and performs re-clustering when it deteriorates. We evaluate our method on the PKDD Challenge 1999 dataset.

  2. A Novel Image Stream Cipher Based On Dynamic Substitution

    OpenAIRE

    Elsharkawi, A.; El-Sagheer, R. M.; Akah, H.; Taha, H.

    2016-01-01

    Recently, many chaos-based stream cipher algorithms have been developed. Traditional chaos stream cipher is based on XORing a generated secure random number sequence based on chaotic maps (e.g. logistic map, Bernoulli Map, Tent Map etc.) with the original image to get the encrypted image, This type of stream cipher seems to be vulnerable to chosen plaintext attacks. This paper introduces a new stream cipher algorithm based on dynamic substitution box. The new algorithm uses one substitution b...

  3. 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.

  4. Applied data mining

    CERN Document Server

    Xu, Guandong

    2013-01-01

    Data mining has witnessed substantial advances in recent decades. New research questions and practical challenges have arisen from emerging areas and applications within the various fields closely related to human daily life, e.g. social media and social networking. This book aims to bridge the gap between traditional data mining and the latest advances in newly emerging information services. It explores the extension of well-studied algorithms and approaches into these new research arenas.

  5. 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. ...

  6. 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...

  7. Signal Processing Algorithms for Down-Stream Traffic in Next Generation 10 Gbit/s Fixed-Grid Passive Optical Networks

    Directory of Open Access Journals (Sweden)

    Rameez Asif

    2014-01-01

    Full Text Available We have analyzed the impact of digital and optical signal processing algorithms, that is, Volterra equalization (VE, digital backpropagation (BP, and optical phase conjugation with nonlinearity module (OPC-NM, in next generation 10 Gbit/s (also referred to as XG DP-QPSK long haul WDM (fixed-grid passive optical network (PON without midspan repeaters over 120 km standard single mode fiber (SMF link for downstream signals. Due to the compensation of optical Kerr effects, the sensitivity penalty is improved by 2 dB by implementing BP algorithm, 1.5 dB by VE algorithm, and 2.69 dB by OPC-NM. Moreover, with the implementation of NL equalization technique, we are able to get the transmission distance of 126.6 km SMF for the 1 : 1024 split ratio at 5 GHz channel spacing in the nonlinear region.

  8. 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.

  9. 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.

  10. 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

  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. Performance of fusion algorithms for computer-aided detection and classification of mines in very shallow water obtained from testing in navy Fleet Battle Exercise-Hotel 2000

    Science.gov (United States)

    Ciany, Charles M.; Zurawski, William; Kerfoot, Ian

    2001-10-01

    The performance of Computer Aided Detection/Computer Aided Classification (CAD/CAC) Fusion algorithms on side-scan sonar images was evaluated using data taken at the Navy's's Fleet Battle Exercise-Hotel held in Panama City, Florida, in August 2000. A 2-of-3 binary fusion algorithm is shown to provide robust performance. The algorithm accepts the classification decisions and associated contact locations form three different CAD/CAC algorithms, clusters the contacts based on Euclidian distance, and then declares a valid target when a clustered contact is declared by at least 2 of the 3 individual algorithms. This simple binary fusion provided a 96 percent probability of correct classification at a false alarm rate of 0.14 false alarms per image per side. The performance represented a 3.8:1 reduction in false alarms over the best performing single CAD/CAC algorithm, with no loss in probability of correct classification.

  13. On-Board Mining in the Sensor Web

    Science.gov (United States)

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

    2004-12-01

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

  14. Evolving temporal association rules with genetic algorithms

    OpenAIRE

    Matthews, Stephen G.; Gongora, Mario A.; Hopgood, Adrian A.

    2010-01-01

    A novel framework for mining temporal association rules by discovering itemsets with a genetic algorithm is introduced. Metaheuristics have been applied to association rule mining, we show the efficacy of extending this to another variant - temporal association rule mining. Our framework is an enhancement to existing temporal association rule mining methods as it employs a genetic algorithm to simultaneously search the rule space and temporal space. A methodology for validating the ability of...

  15. Reacting to different types of concept drift: the Accuracy Updated Ensemble algorithm.

    Science.gov (United States)

    Brzezinski, Dariusz; Stefanowski, Jerzy

    2014-01-01

    Data stream mining has been receiving increased attention due to its presence in a wide range of applications, such as sensor networks, banking, and telecommunication. One of the most important challenges in learning from data streams is reacting to concept drift, i.e., unforeseen changes of the stream's underlying data distribution. Several classification algorithms that cope with concept drift have been put forward, however, most of them specialize in one type of change. In this paper, we propose a new data stream classifier, called the Accuracy Updated Ensemble (AUE2), which aims at reacting equally well to different types of drift. AUE2 combines accuracy-based weighting mechanisms known from block-based ensembles with the incremental nature of Hoeffding Trees. The proposed algorithm is experimentally compared with 11 state-of-the-art stream methods, including single classifiers, block-based and online ensembles, and hybrid approaches in different drift scenarios. Out of all the compared algorithms, AUE2 provided best average classification accuracy while proving to be less memory consuming than other ensemble approaches. Experimental results show that AUE2 can be considered suitable for scenarios, involving many types of drift as well as static environments.

  16. STREAM2016: Streaming Requirements, Experience, Applications and Middleware Workshop

    Energy Technology Data Exchange (ETDEWEB)

    Fox, Geoffrey [Indiana Univ., Bloomington, IN (United States); Jha, Shantenu [Rutgers Univ., New Brunswick, NJ (United States); Ramakrishnan, Lavanya [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

    2016-10-01

    discusses four research directions driven by current and future application requirements reflecting the areas identified as important by STREAM2016. These include (i) Algorithms, (ii) Programming Models, Languages and Runtime Systems (iii) Human-in-the-loop and Steering in Scientific Workflow and (iv) Facilities.

  17. 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...

  18. 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.

  19. Knowledge discovery from data streams

    CERN Document Server

    Gama, Joao

    2010-01-01

    Since the beginning of the Internet age and the increased use of ubiquitous computing devices, the large volume and continuous flow of distributed data have imposed new constraints on the design of learning algorithms. Exploring how to extract knowledge structures from evolving and time-changing data, Knowledge Discovery from Data Streams presents a coherent overview of state-of-the-art research in learning from data streams.The book covers the fundamentals that are imperative to understanding data streams and describes important applications, such as TCP/IP traffic, GPS data, sensor networks,

  20. 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 ...

  1. 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

  2. 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 ...

  3. 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.

  4. A direct mining approach to efficient constrained graph pattern discovery

    DEFF Research Database (Denmark)

    Zhu, Feida; Zhang, Zequn; Qu, Qiang

    2013-01-01

    Despite the wealth of research on frequent graph pattern mining, how to efficiently mine the complete set of those with constraints still poses a huge challenge to the existing algorithms mainly due to the inherent bottleneck in the mining paradigm. In essence, mining requests with explicitly-spe...

  5. 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.

  6. 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.

  7. Uncertainty modeling for data mining a label semantics approach

    CERN Document Server

    Qin, Zengchang

    2014-01-01

    Outlining a new research direction in fuzzy set theory applied to data mining, this volume proposes a number of new data mining algorithms and includes dozens of figures and illustrations that help the reader grasp the complexities of the concepts.

  8. 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.

  9. Towards automatic parameter tuning of stream processing systems

    KAUST Repository

    Bilal, Muhammad; Canini, Marco

    2017-01-01

    for automating parameter tuning for stream-processing systems. Our framework supports standard black-box optimization algorithms as well as a novel gray-box optimization algorithm. We demonstrate the multiple benefits of automated parameter tuning in optimizing

  10. 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.

  11. 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…

  12. 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,...

  13. 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

  14. 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

  15. 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.

  16. An optimization framework for process discovery algorithms

    NARCIS (Netherlands)

    Weijters, A.J.M.M.; Stahlbock, R.

    2011-01-01

    Today there are many process mining techniques that, based on an event log, allow for the automatic induction of a process model. The process mining algorithms that are able to deal with incomplete event logs, exceptions, and noise typically have many parameters to tune the algorithm. Therefore, the

  17. Support-Less Association Rule Mining Using Tuple Count Cube

    OpenAIRE

    Qin Ding; William Perrizo

    2007-01-01

    Association rule mining is one of the important tasks in data mining and knowledge discovery (KDD). The traditional task of association rule mining is to find all the rules with high support and high confidence. In some applications, we are interested in finding high confidence rules even though the support may be low. This type of problem differs from the traditional association rule mining problem; hence, it is called support-less association rule mining. Existing algorithms for association...

  18. 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)

  19. Stream Processing Using Grammars and Regular Expressions

    DEFF Research Database (Denmark)

    Rasmussen, Ulrik Terp

    disambiguation. The first algorithm operates in two passes in a semi-streaming fashion, using a constant amount of working memory and an auxiliary tape storage which is written in the first pass and consumed by the second. The second algorithm is a single-pass and optimally streaming algorithm which outputs...... as much of the parse tree as is semantically possible based on the input prefix read so far, and resorts to buffering as many symbols as is required to resolve the next choice. Optimality is obtained by performing a PSPACE-complete pre-analysis on the regular expression. In the second part we present...... Kleenex, a language for expressing high-performance streaming string processing programs as regular grammars with embedded semantic actions, and its compilation to streaming string transducers with worst-case linear-time performance. Its underlying theory is based on transducer decomposition into oracle...

  20. Applying genetic algorithms to set the optimal combination of forest fire related variables and model forest fire susceptibility based on data mining models. The case of Dayu County, China.

    Science.gov (United States)

    Hong, Haoyuan; Tsangaratos, Paraskevas; Ilia, Ioanna; Liu, Junzhi; Zhu, A-Xing; Xu, Chong

    2018-07-15

    The main objective of the present study was to utilize Genetic Algorithms (GA) in order to obtain the optimal combination of forest fire related variables and apply data mining methods for constructing a forest fire susceptibility map. In the proposed approach, a Random Forest (RF) and a Support Vector Machine (SVM) was used to produce a forest fire susceptibility map for the Dayu County which is located in southwest of Jiangxi Province, China. For this purpose, historic forest fires and thirteen forest fire related variables were analyzed, namely: elevation, slope angle, aspect, curvature, land use, soil cover, heat load index, normalized difference vegetation index, mean annual temperature, mean annual wind speed, mean annual rainfall, distance to river network and distance to road network. The Natural Break and the Certainty Factor method were used to classify and weight the thirteen variables, while a multicollinearity analysis was performed to determine the correlation among the variables and decide about their usability. The optimal set of variables, determined by the GA limited the number of variables into eight excluding from the analysis, aspect, land use, heat load index, distance to river network and mean annual rainfall. The performance of the forest fire models was evaluated by using the area under the Receiver Operating Characteristic curve (ROC-AUC) based on the validation dataset. Overall, the RF models gave higher AUC values. Also the results showed that the proposed optimized models outperform the original models. Specifically, the optimized RF model gave the best results (0.8495), followed by the original RF (0.8169), while the optimized SVM gave lower values (0.7456) than the RF, however higher than the original SVM (0.7148) model. The study highlights the significance of feature selection techniques in forest fire susceptibility, whereas data mining methods could be considered as a valid approach for forest fire susceptibility modeling

  1. Physics Mining of Multi-source Data Sets, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — We propose to implement novel physics mining algorithms with analytical capabilities to derive diagnostic and prognostic numerical models from multi-source...

  2. BLOSTREAM: A HIGH SPEED STREAM CIPHER

    Directory of Open Access Journals (Sweden)

    ALI H. KASHMAR

    2017-04-01

    Full Text Available Although stream ciphers are widely utilized to encrypt sensitive data at fast speeds, security concerns have led to a shift from stream to block ciphers, judging that the current technology in stream cipher is inferior to the technology of block ciphers. This paper presents the design of an improved efficient and secure stream cipher called Blostream, which is more secure than conventional stream ciphers that use XOR for mixing. The proposed cipher comprises two major components: the Pseudo Random Number Generator (PRNG using the Rabbit algorithm and a nonlinear invertible round function (combiner for encryption and decryption. We evaluate its performance in terms of implementation and security, presenting advantages and disadvantages, comparison of the proposed cipher with similar systems and a statistical test for randomness. The analysis shows that the proposed cipher is more efficient, high speed, and secure than current conventional stream ciphers.

  3. Mining a database of single amplified genomes from Red Sea brine pool extremophiles—improving reliability of gene function prediction using a profile and pattern matching algorithm (PPMA)

    Science.gov (United States)

    Grötzinger, Stefan W.; Alam, Intikhab; Ba Alawi, Wail; Bajic, Vladimir B.; Stingl, Ulrich; Eppinger, Jörg

    2014-01-01

    Reliable functional annotation of genomic data is the key-step in the discovery of novel enzymes. Intrinsic sequencing data quality problems of single amplified genomes (SAGs) and poor homology of novel extremophile's genomes pose significant challenges for the attribution of functions to the coding sequences identified. The anoxic deep-sea brine pools of the Red Sea are a promising source of novel enzymes with unique evolutionary adaptation. Sequencing data from Red Sea brine pool cultures and SAGs are annotated and stored in the Integrated Data Warehouse of Microbial Genomes (INDIGO) data warehouse. Low sequence homology of annotated genes (no similarity for 35% of these genes) may translate into false positives when searching for specific functions. The Profile and Pattern Matching (PPM) strategy described here was developed to eliminate false positive annotations of enzyme function before progressing to labor-intensive hyper-saline gene expression and characterization. It utilizes InterPro-derived Gene Ontology (GO)-terms (which represent enzyme function profiles) and annotated relevant PROSITE IDs (which are linked to an amino acid consensus pattern). The PPM algorithm was tested on 15 protein families, which were selected based on scientific and commercial potential. An initial list of 2577 enzyme commission (E.C.) numbers was translated into 171 GO-terms and 49 consensus patterns. A subset of INDIGO-sequences consisting of 58 SAGs from six different taxons of bacteria and archaea were selected from six different brine pool environments. Those SAGs code for 74,516 genes, which were independently scanned for the GO-terms (profile filter) and PROSITE IDs (pattern filter). Following stringent reliability filtering, the non-redundant hits (106 profile hits and 147 pattern hits) are classified as reliable, if at least two relevant descriptors (GO-terms and/or consensus patterns) are present. Scripts for annotation, as well as for the PPM algorithm, are available

  4. Mining a database of single amplified genomes from Red Sea brine pool extremophiles – Improving reliability of gene function prediction using a profile and pattern matching algorithm (PPMA

    Directory of Open Access Journals (Sweden)

    Stefan Wolfgang Grötzinger

    2014-04-01

    Full Text Available Reliable functional annotation of genomic data is the key-step in the discovery of novel enzymes. Intrinsic sequencing data quality problems of single amplified genomes (SAGs and poor homology of novel extremophile’s genomes pose significant challenges for the attribution of functions to the coding sequences identified. The anoxic deep-sea brine pools of the Red Sea are a promising source of novel enzymes with unique evolutionary adaptation. Sequencing data from Red Sea brine pool cultures and SAGs are annotated and stored in the INDIGO data warehouse. Low sequence homology of annotated genes (no similarity for 35% of these genes may translate into false positives when searching for specific functions. The Profile & Pattern Matching (PPM strategy described here was developed to eliminate false positive annotations of enzyme function before progressing to labor-intensive hyper-saline gene expression and characterization. It utilizes InterPro-derived Gene Ontology (GO-terms (which represent enzyme function profiles and annotated relevant PROSITE IDs (which are linked to an amino acid consensus pattern. The PPM algorithm was tested on 15 protein families, which were selected based on scientific and commercial potential. An initial list of 2,577 E.C. numbers was translated into 171 GO-terms and 49 consensus patterns. A subset of INDIGO-sequences consisting of 58 SAGs from six different taxons of bacteria and archaea were selected from 6 different brine pool environments. Those SAGs code for 74,516 genes, which were independently scanned for the GO-terms (profile filter and PROSITE IDs (pattern filter. Following stringent reliability filtering, the non-redundant hits (106 profile hits and 147 pattern hits are classified as reliable, if at least two relevant descriptors (GO-terms and/or consensus patterns are present. Scripts for annotation, as well as for the PPM algorithm, are available through the INDIGO website.

  5. Mining a database of single amplified genomes from Red Sea brine pool extremophiles-improving reliability of gene function prediction using a profile and pattern matching algorithm (PPMA).

    KAUST Repository

    Grötzinger, Stefan W.

    2014-04-07

    Reliable functional annotation of genomic data is the key-step in the discovery of novel enzymes. Intrinsic sequencing data quality problems of single amplified genomes (SAGs) and poor homology of novel extremophile\\'s genomes pose significant challenges for the attribution of functions to the coding sequences identified. The anoxic deep-sea brine pools of the Red Sea are a promising source of novel enzymes with unique evolutionary adaptation. Sequencing data from Red Sea brine pool cultures and SAGs are annotated and stored in the Integrated Data Warehouse of Microbial Genomes (INDIGO) data warehouse. Low sequence homology of annotated genes (no similarity for 35% of these genes) may translate into false positives when searching for specific functions. The Profile and Pattern Matching (PPM) strategy described here was developed to eliminate false positive annotations of enzyme function before progressing to labor-intensive hyper-saline gene expression and characterization. It utilizes InterPro-derived Gene Ontology (GO)-terms (which represent enzyme function profiles) and annotated relevant PROSITE IDs (which are linked to an amino acid consensus pattern). The PPM algorithm was tested on 15 protein families, which were selected based on scientific and commercial potential. An initial list of 2577 enzyme commission (E.C.) numbers was translated into 171 GO-terms and 49 consensus patterns. A subset of INDIGO-sequences consisting of 58 SAGs from six different taxons of bacteria and archaea were selected from six different brine pool environments. Those SAGs code for 74,516 genes, which were independently scanned for the GO-terms (profile filter) and PROSITE IDs (pattern filter). Following stringent reliability filtering, the non-redundant hits (106 profile hits and 147 pattern hits) are classified as reliable, if at least two relevant descriptors (GO-terms and/or consensus patterns) are present. Scripts for annotation, as well as for the PPM algorithm, are available

  6. Stream sediment detailed geochemical survey for Date Creek Basin, Arizona

    International Nuclear Information System (INIS)

    Butz, T.R.; Tieman, D.J.; Grimes, J.G.; Bard, C.S.; Helgerson, R.N.; Pritz, P.M.; Wolf, D.A.

    1981-01-01

    The purpose of the Date Creek Supplement is to characterize the chemistry of sediment samples representing stream basins in which the Anderson Mine (and related prospects) occur. Once characterized, the chemistry is then used to delineate other areas within the Date Creek Basin where stream sediment chemistry resembles that of the Anderson Mine area. This supplementary report examines more closely the data from sediment samples taken in 239 stream basins collected over a total area of approximately 900 km 2 (350 mi 2 ). Cluster and discriminant analyses are used to characterize the geochemistry of the stream sediment samples collected in the Date Creek Basin. Cluster and discriminant analysis plots are used to delineate areas having a potential for uranium mineralization similar to that of the Anderson Mine

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

    Science.gov (United States)

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

    2018-04-01

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

  8. Online Nonparametric Bayesian Activity Mining and Analysis From Surveillance Video.

    Science.gov (United States)

    Bastani, Vahid; Marcenaro, Lucio; Regazzoni, Carlo S

    2016-05-01

    A method for online incremental mining of activity patterns from the surveillance video stream is presented in this paper. The framework consists of a learning block in which Dirichlet process mixture model is employed for the incremental clustering of trajectories. Stochastic trajectory pattern models are formed using the Gaussian process regression of the corresponding flow functions. Moreover, a sequential Monte Carlo method based on Rao-Blackwellized particle filter is proposed for tracking and online classification as well as the detection of abnormality during the observation of an object. Experimental results on real surveillance video data are provided to show the performance of the proposed algorithm in different tasks of trajectory clustering, classification, and abnormality detection.

  9. Prediction of Allogeneic Hematopoietic Stem-Cell Transplantation Mortality 100 Days After Transplantation Using a Machine Learning Algorithm: A European Group for Blood and Marrow Transplantation Acute Leukemia Working Party Retrospective Data Mining Study.

    Science.gov (United States)

    Shouval, Roni; Labopin, Myriam; Bondi, Ori; Mishan-Shamay, Hila; Shimoni, Avichai; Ciceri, Fabio; Esteve, Jordi; Giebel, Sebastian; Gorin, Norbert C; Schmid, Christoph; Polge, Emmanuelle; Aljurf, Mahmoud; Kroger, Nicolaus; Craddock, Charles; Bacigalupo, Andrea; Cornelissen, Jan J; Baron, Frederic; Unger, Ron; Nagler, Arnon; Mohty, Mohamad

    2015-10-01

    Allogeneic hematopoietic stem-cell transplantation (HSCT) is potentially curative for acute leukemia (AL), but carries considerable risk. Machine learning algorithms, which are part of the data mining (DM) approach, may serve for transplantation-related mortality risk prediction. This work is a retrospective DM study on a cohort of 28,236 adult HSCT recipients from the AL registry of the European Group for Blood and Marrow Transplantation. The primary objective was prediction of overall mortality (OM) at 100 days after HSCT. Secondary objectives were estimation of nonrelapse mortality, leukemia-free survival, and overall survival at 2 years. Donor, recipient, and procedural characteristics were analyzed. The alternating decision tree machine learning algorithm was applied for model development on 70% of the data set and validated on the remaining data. OM prevalence at day 100 was 13.9% (n=3,936). Of the 20 variables considered, 10 were selected by the model for OM prediction, and several interactions were discovered. By using a logistic transformation function, the crude score was transformed into individual probabilities for 100-day OM (range, 3% to 68%). The model's discrimination for the primary objective performed better than the European Group for Blood and Marrow Transplantation score (area under the receiver operating characteristics curve, 0.701 v 0.646; Prisk evaluation of patients with AL before HSCT, and is available online (http://bioinfo.lnx.biu.ac.il/∼bondi/web1.html). It is presented as a continuous probabilistic score for the prediction of day 100 OM, extending prediction to 2 years. The DM method has proved useful for clinical prediction in HSCT. © 2015 by American Society of Clinical Oncology.

  10. Examine the criteria for establishing the small span small pillar concept as a safe mining method in deep mines,Volume 1 of 1.

    CSIR Research Space (South Africa)

    De Frey, FSA

    2002-01-01

    Full Text Available with conventional breast panel 38 4.4 Critical evaluation of results 39 4.5 A recommended alternative method 41 4.6 Comparison criteria used as for other layouts 45 4.7 Conclusions and future research needs 47 5 MINE ECONOMICS 48 5.1 Mine economic criteria 48... stream_source_info GAP822.pdf.txt stream_content_type text/plain stream_size 176631 Content-Encoding UTF-8 stream_name GAP822.pdf.txt Content-Type text/plain; charset=UTF-8 Safety in Mines Research Advisory Committee...

  11. Online feature selection with streaming features.

    Science.gov (United States)

    Wu, Xindong; Yu, Kui; Ding, Wei; Wang, Hao; Zhu, Xingquan

    2013-05-01

    We propose a new online feature selection framework for applications with streaming features where the knowledge of the full feature space is unknown in advance. We define streaming features as features that flow in one by one over time whereas the number of training examples remains fixed. This is in contrast with traditional online learning methods that only deal with sequentially added observations, with little attention being paid to streaming features. The critical challenges for Online Streaming Feature Selection (OSFS) include 1) the continuous growth of feature volumes over time, 2) a large feature space, possibly of unknown or infinite size, and 3) the unavailability of the entire feature set before learning starts. In the paper, we present a novel Online Streaming Feature Selection method to select strongly relevant and nonredundant features on the fly. An efficient Fast-OSFS algorithm is proposed to improve feature selection performance. The proposed algorithms are evaluated extensively on high-dimensional datasets and also with a real-world case study on impact crater detection. Experimental results demonstrate that the algorithms achieve better compactness and higher prediction accuracy than existing streaming feature selection algorithms.

  12. Streaming simplification of tetrahedral meshes.

    Science.gov (United States)

    Vo, Huy T; Callahan, Steven P; Lindstrom, Peter; Pascucci, Valerio; Silva, Cláudio T

    2007-01-01

    Unstructured tetrahedral meshes are commonly used in scientific computing to represent scalar, vector, and tensor fields in three dimensions. Visualization of these meshes can be difficult to perform interactively due to their size and complexity. By reducing the size of the data, we can accomplish real-time visualization necessary for scientific analysis. We propose a two-step approach for streaming simplification of large tetrahedral meshes. Our algorithm arranges the data on disk in a streaming, I/O-efficient format that allows coherent access to the tetrahedral cells. A quadric-based simplification is sequentially performed on small portions of the mesh in-core. Our output is a coherent streaming mesh which facilitates future processing. Our technique is fast, produces high quality approximations, and operates out-of-core to process meshes too large for main memory.

  13. 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

  14. Mining Product Data Models: A Case Study

    Directory of Open Access Journals (Sweden)

    Cristina-Claudia DOLEAN

    2014-01-01

    Full Text Available This paper presents two case studies used to prove the validity of some data-flow mining algorithms. We proposed the data-flow mining algorithms because most part of mining algorithms focuses on the control-flow perspective. First case study uses event logs generated by an ERP system (Navision after we set several trackers on the data elements needed in the process analyzed; while the second case study uses the event logs generated by YAWL system. We offered a general solution of data-flow model extraction from different data sources. In order to apply the data-flow mining algorithms the event logs must comply a certain format (using InputOutput extension. But to respect this format, a set of conversion tools is needed. We depicted the conversion tools used and how we got the data-flow models. Moreover, the data-flow model is compared to the control-flow model.

  15. 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 ...

  16. EMiT: a process mining tool

    NARCIS (Netherlands)

    Dongen, van B.F.; Aalst, van der W.M.P.; Cortadella, J.; Reisig, W.

    2004-01-01

    Process mining offers a way to distill process models from event logs originating from transactional systems in logistics, banking, e-business, health-care, etc. The algorithms used for process mining are complex and in practise large logs are needed to derive a high-quality process model. To

  17. Declarative Process Mining for DCR Graphs

    DEFF Research Database (Denmark)

    Debois, Søren; Hildebrandt, Thomas T.; Laursen, Paw Høvsgaard

    2017-01-01

    We investigate process mining for the declarative Dynamic Condition Response (DCR) graphs process modelling language. We contribute (a) a process mining algorithm for DCR graphs, (b) a proposal for a set of metrics quantifying output model quality, and (c) a preliminary example-based comparison...

  18. Interactive collision detection for deformable models using streaming AABBs.

    Science.gov (United States)

    Zhang, Xinyu; Kim, Young J

    2007-01-01

    We present an interactive and accurate collision detection algorithm for deformable, polygonal objects based on the streaming computational model. Our algorithm can detect all possible pairwise primitive-level intersections between two severely deforming models at highly interactive rates. In our streaming computational model, we consider a set of axis aligned bounding boxes (AABBs) that bound each of the given deformable objects as an input stream and perform massively-parallel pairwise, overlapping tests onto the incoming streams. As a result, we are able to prevent performance stalls in the streaming pipeline that can be caused by expensive indexing mechanism required by bounding volume hierarchy-based streaming algorithms. At runtime, as the underlying models deform over time, we employ a novel, streaming algorithm to update the geometric changes in the AABB streams. Moreover, in order to get only the computed result (i.e., collision results between AABBs) without reading back the entire output streams, we propose a streaming en/decoding strategy that can be performed in a hierarchical fashion. After determining overlapped AABBs, we perform a primitive-level (e.g., triangle) intersection checking on a serial computational model such as CPUs. We implemented the entire pipeline of our algorithm using off-the-shelf graphics processors (GPUs), such as nVIDIA GeForce 7800 GTX, for streaming computations, and Intel Dual Core 3.4G processors for serial computations. We benchmarked our algorithm with different models of varying complexities, ranging from 15K up to 50K triangles, under various deformation motions, and the timings were obtained as 30 approximately 100 FPS depending on the complexity of models and their relative configurations. Finally, we made comparisons with a well-known GPU-based collision detection algorithm, CULLIDE [4] and observed about three times performance improvement over the earlier approach. We also made comparisons with a SW-based AABB

  19. 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

  20. Uranium mining

    International Nuclear Information System (INIS)

    2008-01-01

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

  1. Acid mine drainage arising from gold mining activity in Johannesburg, South Africa and environs

    International Nuclear Information System (INIS)

    Naicker, K.; Cukrowska, E.; McCarthy, T.S.

    2003-01-01

    Ground water within the mining district is heavily contaminated and acidified. - The Witwatersrand region of South Africa is famous for its gold production and a major conurbation, centred on Johannesburg, has developed as a result of mining activity. A study was undertaken of surface and ground water in a drainage system in this area. Soils were also analysed from a site within the mining district. This study revealed that the ground water within the mining district is heavily contaminated and acidified as a result of oxidation of pyrite (FeS 2 ) contained within mine tailings dumps, and has elevated concentrations of heavy metals. Where the water table is close to surface, the upper 20 cm of soil profiles are severely contaminated by heavy metals due to capillary rise and evaporation of the ground water. The polluted ground water is discharging into streams in the area and contributes up to 20% of stream discharge, causing a lowering of pH of the stream water. Much of the metal load is precipitated in the stream: Fe and Mn precipitate as a consequence of oxidation, while other heavy metals are being removed by co-precipitation. The oxidation of iron has created a redox buffer which controls the pH of the stream water. The rate of oxidation and of dilution is slow and the deleterious effect of the addition of contaminated water persists for more than 10 km beyond the source

  2. VALUING ACID MINE DRAINAGE REMEDIATION IN WEST VIRGINIA: A HEDONIC MODELING APPROACH INCORPORATING GEOGRAPHIC INFORMATION SYSTEMS

    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). Appalachian states have an especially large number of contaminated streams and rivers, and the USGS places AMD as the primary source...

  3. VALUING ACID MINE DRAINAGE REMEDIATION 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). Appalachian states have an especially large number of contaminated streams and rivers, and the USGS places AMD as the primary source...

  4. Preliminary Results: Release Of Metals From Acid-Mine Drainage Contaminated Streambed Sediments Under Anaerobic Conditions

    Science.gov (United States)

    Many miles of streams in the western U.S. are contaminated with acid-mine drainage (AMD) from abandoned metal mines. Treatment of these streams may include removal of the existing sediments, with subsequent burial (e.g., in a repository). Burial of previously aerobic sediments ma...

  5. Tracking Gendered Streams

    Directory of Open Access Journals (Sweden)

    Maria Eriksson

    2017-10-01

    Full Text Available One of the most prominent features of digital music services is the provision of personalized music recommendations that come about through the profiling of users and audiences. Based on a range of "bot experiments," this article investigates if, and how, gendered patterns in music recommendations are provided by the streaming service Spotify. While our experiments did not give any strong indications that Spotify assigns different taste profiles to male and female users, the study showed that male artists were highly overrepresented in Spotify's music recommendations; an issue which we argue prompts users to cite hegemonic masculine norms within the music industries. Although the results should be approached as historically and contextually contingent, we argue that they point to how gender and gendered tastes may be constituted through the interplay between users and algorithmic knowledge-making processes, and how digital content delivery may maintain and challenge gender relations and gendered power differentials within the music industries. Seen through the lens of critical research on software, music and gender performativity, the experiments thus provide insights into how gender is shaped and attributed meaning as it materializes in contemporary music streams.

  6. Streaming Compression of Hexahedral Meshes

    Energy Technology Data Exchange (ETDEWEB)

    Isenburg, M; Courbet, C

    2010-02-03

    We describe a method for streaming compression of hexahedral meshes. Given an interleaved stream of vertices and hexahedral our coder incrementally compresses the mesh in the presented order. Our coder is extremely memory efficient when the input stream documents when vertices are referenced for the last time (i.e. when it contains topological finalization tags). Our coder then continuously releases and reuses data structures that no longer contribute to compressing the remainder of the stream. This means in practice that our coder has only a small fraction of the whole mesh in memory at any time. We can therefore compress very large meshes - even meshes that do not file in memory. Compared to traditional, non-streaming approaches that load the entire mesh and globally reorder it during compression, our algorithm trades a less compact compressed representation for significant gains in speed, memory, and I/O efficiency. For example, on the 456k hexahedra 'blade' mesh, our coder is twice as fast and uses 88 times less memory (only 3.1 MB) with the compressed file increasing about 3% in size. We also present the first scheme for predictive compression of properties associated with hexahedral cells.

  7. Web Mining and Social Networking

    DEFF Research Database (Denmark)

    Xu, Guandong; Zhang, Yanchun; Li, Lin

    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 ...... sense of individuals or communities. The volume will benefit both academic and industry communities interested in the techniques and applications of web search, web data management, web mining and web knowledge discovery, as well as web community and social network analysis.......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...

  8. 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

  9. MO-A-BRD-09: A Data-Mining Algorithm for Large Scale Analysis of Dose-Outcome Relationships in a Database of Irradiated Head-And-Neck (HN) Cancer Patients

    Energy Technology Data Exchange (ETDEWEB)

    Robertson, SP; Quon, H; Kiess, AP; Moore, JA; Yang, W; Cheng, Z; Sharabi, A; McNutt, TR [Johns Hopkins University, Baltimore, MD (United States)

    2014-06-15

    Purpose: To develop a framework for automatic extraction of clinically meaningful dosimetric-outcome relationships from an in-house, analytic oncology database. Methods: Dose-volume histograms (DVH) and clinical outcome-related structured data elements have been routinely stored to our database for 513 HN cancer patients treated from 2007 to 2014. SQL queries were developed to extract outcomes that had been assessed for at least 100 patients, as well as DVH curves for organs-at-risk (OAR) that were contoured for at least 100 patients. DVH curves for paired OAR (e.g., left and right parotids) were automatically combined and included as additional structures for analysis. For each OAR-outcome combination, DVH dose points, D(V{sub t}), at a series of normalized volume thresholds, V{sub t}=[0.01,0.99], were stratified into two groups based on outcomes after treatment completion. The probability, P[D(V{sub t})], of an outcome was modeled at each V{sub t} by logistic regression. Notable combinations, defined as having P[D(V{sub t})] increase by at least 5% per Gy (p<0.05), were further evaluated for clinical relevance using a custom graphical interface. Results: A total of 57 individual and combined structures and 115 outcomes were queried, resulting in over 6,500 combinations for analysis. Of these, 528 combinations met the 5%/Gy requirement, with further manual inspection revealing a number of reasonable models based on either reported literature or proximity between neighboring OAR. The data mining algorithm confirmed the following well-known toxicity/outcome relationships: dysphagia/larynx, voice changes/larynx, esophagitis/esophagus, xerostomia/combined parotids, and mucositis/oral mucosa. Other notable relationships included dysphagia/pharyngeal constrictors, nausea/brainstem, nausea/spinal cord, weight-loss/mandible, and weight-loss/combined parotids. Conclusion: Our database platform has enabled large-scale analysis of dose-outcome relationships. The current data-mining

  10. StreamMap: Smooth Dynamic Visualization of High-Density Streaming Points.

    Science.gov (United States)

    Li, Chenhui; Baciu, George; Han, Yu

    2018-03-01

    Interactive visualization of streaming points for real-time scatterplots and linear blending of correlation patterns is increasingly becoming the dominant mode of visual analytics for both big data and streaming data from active sensors and broadcasting media. To better visualize and interact with inter-stream patterns, it is generally necessary to smooth out gaps or distortions in the streaming data. Previous approaches either animate the points directly or present a sampled static heat-map. We propose a new approach, called StreamMap, to smoothly blend high-density streaming points and create a visual flow that emphasizes the density pattern distributions. In essence, we present three new contributions for the visualization of high-density streaming points. The first contribution is a density-based method called super kernel density estimation that aggregates streaming points using an adaptive kernel to solve the overlapping problem. The second contribution is a robust density morphing algorithm that generates several smooth intermediate frames for a given pair of frames. The third contribution is a trend representation design that can help convey the flow directions of the streaming points. The experimental results on three datasets demonstrate the effectiveness of StreamMap when dynamic visualization and visual analysis of trend patterns on streaming points are required.

  11. Setup of a testing environment for mission planning in mining

    NARCIS (Netherlands)

    Groenen, J.P.J.; Steinbuch, M.

    2013-01-01

    Mission planning algorithms for surface mining applications are difficult to test as a result of the large scale tasks. To validate these algorithms, a scaled setup is created where the mining excavator is mimicked by an industrial robot. This report discusses the development of a software

  12. Data Stream Clustering With Affinity Propagation

    KAUST Repository

    Zhang, Xiangliang; Furtlehner, Cyril; Germain-Renaud, Cecile; Sebag, Michele

    2014-01-01

    Data stream clustering provides insights into the underlying patterns of data flows. This paper focuses on selecting the best representatives from clusters of streaming data. There are two main challenges: how to cluster with the best representatives and how to handle the evolving patterns that are important characteristics of streaming data with dynamic distributions. We employ the Affinity Propagation (AP) algorithm presented in 2007 by Frey and Dueck for the first challenge, as it offers good guarantees of clustering optimality for selecting exemplars. The second challenging problem is solved by change detection. The presented StrAP algorithm combines AP with a statistical change point detection test; the clustering model is rebuilt whenever the test detects a change in the underlying data distribution. Besides the validation on two benchmark data sets, the presented algorithm is validated on a real-world application, monitoring the data flow of jobs submitted to the EGEE grid.

  13. Data Stream Clustering With Affinity Propagation

    KAUST Repository

    Zhang, Xiangliang

    2014-07-09

    Data stream clustering provides insights into the underlying patterns of data flows. This paper focuses on selecting the best representatives from clusters of streaming data. There are two main challenges: how to cluster with the best representatives and how to handle the evolving patterns that are important characteristics of streaming data with dynamic distributions. We employ the Affinity Propagation (AP) algorithm presented in 2007 by Frey and Dueck for the first challenge, as it offers good guarantees of clustering optimality for selecting exemplars. The second challenging problem is solved by change detection. The presented StrAP algorithm combines AP with a statistical change point detection test; the clustering model is rebuilt whenever the test detects a change in the underlying data distribution. Besides the validation on two benchmark data sets, the presented algorithm is validated on a real-world application, monitoring the data flow of jobs submitted to the EGEE grid.

  14. Data preprocessing in data mining

    CERN Document Server

    García, Salvador; Herrera, Francisco

    2015-01-01

    Data Preprocessing for Data Mining addresses one of the most important issues within the well-known Knowledge Discovery from Data process. Data directly taken from the source will likely have inconsistencies, errors or most importantly, it is not ready to be considered for a data mining process. Furthermore, the increasing amount of data in recent science, industry and business applications, calls to the requirement of more complex tools to analyze it. Thanks to data preprocessing, it is possible to convert the impossible into possible, adapting the data to fulfill the input demands of each data mining algorithm. Data preprocessing includes the data reduction techniques, which aim at reducing the complexity of the data, detecting or removing irrelevant and noisy elements from the data. This book is intended to review the tasks that fill the gap between the data acquisition from the source and the data mining process. A comprehensive look from a practical point of view, including basic concepts and surveying t...

  15. Uranium recovery from mine water

    International Nuclear Information System (INIS)

    Sarkar, K.M.

    1984-01-01

    In many plant trials it has been proven that very small amounts (10 to 20 ppm) of uranium dissolved in mine water can be effectively recovered by the use of ion exchange resins and this uranium recovery has many advantages. In this paper an economic analysis at different levels of uranium contamination and at different market prices of uranium are described. For this study an operating mine-mill complex with a sulphuric acid leach circuit, followed by solvent extraction (SX) process, is considered, where contaminated mine water is available in excess of process requirements. It is further assumed that the sulphuric acid eluant containing uranium would be mixed with the mill pregnant liquor stream that proceeds to the SX plant for final uranium recovery

  16. Set-Oriented Mining for Association Rules in Relational Databases

    NARCIS (Netherlands)

    Houtsma, M.A.W.; Houtsma, M.A.W.; Swami, A.

    1995-01-01

    Describe set-oriented algorithms for mining association rules. Such algorithms imply performing multiple joins and may appear to be inherently less efficient than special-purpose algorithms. We develop new algorithms that can be expressed as SQL queries, and discuss the optimization of these

  17. Social big data mining

    CERN Document Server

    Ishikawa, Hiroshi

    2015-01-01

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

  18. Quick fuzzy backpropagation algorithm.

    Science.gov (United States)

    Nikov, A; Stoeva, S

    2001-03-01

    A modification of the fuzzy backpropagation (FBP) algorithm called QuickFBP algorithm is proposed, where the computation of the net function is significantly quicker. It is proved that the FBP algorithm is of exponential time complexity, while the QuickFBP algorithm is of polynomial time complexity. Convergence conditions of the QuickFBP, resp. the FBP algorithm are defined and proved for: (1) single output neural networks in case of training patterns with different targets; and (2) multiple output neural networks in case of training patterns with equivalued target vector. They support the automation of the weights training process (quasi-unsupervised learning) establishing the target value(s) depending on the network's input values. In these cases the simulation results confirm the convergence of both algorithms. An example with a large-sized neural network illustrates the significantly greater training speed of the QuickFBP rather than the FBP algorithm. The adaptation of an interactive web system to users on the basis of the QuickFBP algorithm is presented. Since the QuickFBP algorithm ensures quasi-unsupervised learning, this implies its broad applicability in areas of adaptive and adaptable interactive systems, data mining, etc. applications.

  19. Action Rules Mining

    CERN Document Server

    Dardzinska, Agnieszka

    2013-01-01

    We are surrounded by data, numerical, categorical and otherwise, which must to be analyzed and processed to convert it into information that instructs, answers or aids understanding and decision making. Data analysts in many disciplines such as business, education or medicine, are frequently asked to analyze new data sets which are often composed of numerous tables possessing different properties. They try to find completely new correlations between attributes and show new possibilities for users.   Action rules mining discusses some of data mining and knowledge discovery principles and then describe representative concepts, methods and algorithms connected with action. The author introduces the formal definition of action rule, notion of a simple association action rule and a representative action rule, the cost of association action rule, and gives a strategy how to construct simple association action rules of a lowest cost. A new approach for generating action rules from datasets with numerical attributes...

  20. A influência das atividades mineradoras na alteração do pH e da alcalinidade em águas fluviais: o exemplo do rio Capivari, região do carste paranaense The consequences of mining activities on pH alteration in fluvial waters: following the example of Capivari stream, Paraná carstic region

    Directory of Open Access Journals (Sweden)

    Elenice Fritzsons

    2009-09-01

    Full Text Available As atividades de mineração causam vários tipos de impactos ao meio ambiente. Este trabalho apresenta um estudo de impacto sobre recursos hídricos superficiais desenvolvidos numa bacia hidrográfica na região metropolitana de Curitiba (PR, onde se observaram modificações no pH e na alcalinidade nas águas do rio Capivari ocorridas num intervalo médio de doze anos. Foram avaliados 387 dias de amostragem da série 1986/1987 e 1.095 dias da série 1998/2000. Comparando-se as duas séries, observou-se que, ao longo deste período (1986-2000, a média do pH elevou-se, em média, 0,5 unidade, enquanto a alcalinidade aumentou em 15%. De 1980 a 2001, as áreas de mineração desta mesma bacia tiveram uma expansão de aproximadamente 47.000 m²/ano. Avaliações ao longo do rio revelaram, nos locais à jusante e mais próximos das pedreiras, que o pH apresenta valores mais altos, tornando-se alcalino, e a condutividade elétrica aumenta. Esses dados confirmam a hipótese de que a expansão das áreas de mineração provocaria alterações nos valores de pH e de alcalinidade das águas do rio Capivari.Mining activities causes many kinds of environmental impacts over environment. In this paper we describe the research developed in the Capivari watershed, in the Curitiba metropolitan region, Paraná, Brazil. Alkalinity and pH changes in Capivari stream over 12 years were observed. The sampling program was performed in 387 sampling day's series at 1986/1987, and another period covering 1,095 days from 1998 to 2000. Comparing these series, the pH average was higher in 0,5 unities and the alkalinity were 15% higher within this period of time. From 1980 to 2001, mining areas of metadolomites spread out to an average rate of 47,000 m²/year. Field evaluations carried out on the Capivari stream showed that in regions close to low water streams and closer to stone-pits, the pH level was higher and it became more alkaline as the electric conductivity

  1. Uranium mining in Australia: dreams--and reality

    International Nuclear Information System (INIS)

    Anon.

    1977-01-01

    By the early 1980's if the current mining projects described are allowed to go on stream, Australia will be able to produce at least 10 900 tons of U$sub 3$O$sub 8$ annually from ores whose grade ranges from a low of 0.150% to a high of 2.300%. The Jabiluka Project of uranium mining is described, and plans for other mines are discussed in Queensland, South and Western Australia. 2 refs

  2. STRIP: stream learning of influence probabilities

    DEFF Research Database (Denmark)

    Kutzkov, Konstantin

    2013-01-01

    cascades, and developing applications such as viral marketing. Motivated by modern microblogging platforms, such as twitter, in this paper we study the problem of learning influence probabilities in a data-stream scenario, in which the network topology is relatively stable and the challenge of a learning...... algorithm is to keep up with a continuous stream of tweets using a small amount of time and memory. Our contribution is a number of randomized approximation algorithms, categorized according to the available space (superlinear, linear, and sublinear in the number of nodes n) and according to dierent models...

  3. 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.

  4. 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.

  5. 77 FR 55430 - Arkansas Regulatory Program and Abandoned Mine Land Reclamation Plan

    Science.gov (United States)

    2012-09-10

    ... of its regulatory program and abandoned mine land reclamation plan, make grammatical changes, correct... portions of its regulatory program and abandoned mine land reclamation plan, make grammatical changes... Streams. PART 785--REQUIREMENTS FOR PERMITS FOR SPECIAL CATEGORIES OF MINING 785.13, 785.14, 785.15...

  6. Modeling N Cycling during Succession after Forest Disturbance: an Analysis of N Mining and Retention Hypothesis

    Science.gov (United States)

    Zhou, Z.; Ollinger, S. V.; Ouimette, A.; Lovett, G. M.; Fuss, C. B.; Goodale, C. L.

    2017-12-01

    Dissolved inorganic nitrogen losses at the Hubbard Brook Experimental Forest (HBEF), New Hampshire, USA, have declined in recent decades, a pattern that counters expectations based on prevailing theory. An unbalanced ecosystem nitrogen (N) budget implies there is a missing component for N sink. Hypotheses to explain this discrepancy include increasing rates of denitrification and accumulation of N in mineral soil pools following N mining by plants. Here, we conducted a modeling analysis fused with field measurements of N cycling, specifically examining the hypothesis relevant to N mining and retention in mineral soils. We included simplified representations of both mechanisms, N mining and retention, in a revised ecosystem process model, PnET-SOM, to evaluate the dynamics of N cycling during succession after forest disturbance at the HBEF. The predicted N mining during the early succession was regulated by a metric representing a potential demand of extra soil N for large wood growth. The accumulation of nitrate in mineral soil pools was a function of the net aboveground biomass accumulation and soil N availability and parameterized based on field 15N tracer incubation data. The predicted patterns of forest N dynamics were consistent with observations. The addition of the new algorithms also improved the predicted DIN export in stream water with an R squared of 0.35 (Ppay back the mined N in mineral soils. Predicted ecosystem N balance showed that N gas loss could account for 14-46% of the total N deposition, the soil mining about 103% during the early succession, and soil retention about 35% at the current forest stage at the HBEF.

  7. StreamQRE: Modular Specification and Efficient Evaluation of Quantitative Queries over Streaming Data.

    Science.gov (United States)

    Mamouras, Konstantinos; Raghothaman, Mukund; Alur, Rajeev; Ives, Zachary G; Khanna, Sanjeev

    2017-06-01

    Real-time decision making in emerging IoT applications typically relies on computing quantitative summaries of large data streams in an efficient and incremental manner. To simplify the task of programming the desired logic, we propose StreamQRE, which provides natural and high-level constructs for processing streaming data. Our language has a novel integration of linguistic constructs from two distinct programming paradigms: streaming extensions of relational query languages and quantitative extensions of regular expressions. The former allows the programmer to employ relational constructs to partition the input data by keys and to integrate data streams from different sources, while the latter can be used to exploit the logical hierarchy in the input stream for modular specifications. We first present the core language with a small set of combinators, formal semantics, and a decidable type system. We then show how to express a number of common patterns with illustrative examples. Our compilation algorithm translates the high-level query into a streaming algorithm with precise complexity bounds on per-item processing time and total memory footprint. We also show how to integrate approximation algorithms into our framework. We report on an implementation in Java, and evaluate it with respect to existing high-performance engines for processing streaming data. Our experimental evaluation shows that (1) StreamQRE allows more natural and succinct specification of queries compared to existing frameworks, (2) the throughput of our implementation is higher than comparable systems (for example, two-to-four times greater than RxJava), and (3) the approximation algorithms supported by our implementation can lead to substantial memory savings.

  8. Bulky goods separation from the stream of conveyed coal. RWE Power - Garzweiler opencast mine - bucket-wheel excavator 261; Sperrgutaushaltung aus dem laufenden Foerderstrom. RWE Power - Tagebau Garzweiler - Schaufelradbagger 261

    Energy Technology Data Exchange (ETDEWEB)

    Borchardt, Guenter; Gums, Bernd; Pyrcik, Jaroslaw [RWE Power AG, Grevenbroich (Germany). Tagebau Garzweiler; Jansen, Klemens [RWE Power AG, Eschweiler (Germany). Tagebau Inden

    2011-01-15

    Bucket-wheel excavator 261 is deployed on the two upper benches of the Garzweiler opencast mine. Large stones and other bulk material, the separation of which caused considerable output losses in the past, are frequently found in the mining horizons in situ. Stones and other bulk material that are not detected cause substantial damage to the machine belts on the excavator, to the downstream transfer substations of the belt conveyors, and to the spreader, and generate associated maintenance costs. In addition, the stone-separation method used so far carries a serious risk of injury for the employees concerned. A sensor-based stone detection system on the one hand and an automatic bulk material discharge system on the other were developed to improve the situation. Within the scope of the static analyses performed prior to installing the new bulk material discharge system, the amount and position of overweight and underweight were checked. Owing to the symmetrical distribution of the weights of the built-in structure, a change of ballast was not necessary. In the main, the new, fully revised bulk material separation system differs from the original design in three points: - considerably more robust design, - hydraulic rake drive, - the stone storage container on the excavator is designed as a self-discharging push-floor conveyor. (orig.)

  9. Unsupervised learning algorithms

    CERN Document Server

    Aydin, Kemal

    2016-01-01

    This book summarizes the state-of-the-art in unsupervised learning. The contributors discuss how with the proliferation of massive amounts of unlabeled data, unsupervised learning algorithms, which can automatically discover interesting and useful patterns in such data, have gained popularity among researchers and practitioners. The authors outline how these algorithms have found numerous applications including pattern recognition, market basket analysis, web mining, social network analysis, information retrieval, recommender systems, market research, intrusion detection, and fraud detection. They present how the difficulty of developing theoretically sound approaches that are amenable to objective evaluation have resulted in the proposal of numerous unsupervised learning algorithms over the past half-century. The intended audience includes researchers and practitioners who are increasingly using unsupervised learning algorithms to analyze their data. Topics of interest include anomaly detection, clustering,...

  10. Coastal mining

    Science.gov (United States)

    Bell, Peter M.

    The Exclusive Economic Zone (EEZ) declared by President Reagan in March 1983 has met with a mixed response from those who would benefit from a guaranteed, 200-nautical-mile (370-km) protected underwater mining zone off the coasts of the United States and its possessions. On the one hand, the U.S. Department of the Interior is looking ahead and has been very successful in safeguarding important natural resources that will be needed in the coming decades. On the other hand, the mining industry is faced with a depressed metals and mining market.A report of the Exclusive Economic Zone Symposium held in November 1983 by the U.S. Geological Survey, the Mineral Management Service, and the Bureau of Mines described the mixed response as: “ … The Department of Interior … raring to go into promotion of deep-seal mining but industrial consortia being very pessimistic about the program, at least for the next 30 or so years.” (Chemical & Engineering News, February 5, 1983).

  11. VALUING ACID MINE DRAINAGE REMEDIATION IN WEST VIRGINIA: BENEFIT TRANSFER WITH PREFERENCE CALIBRATION

    Science.gov (United States)

    Several thousand kilometers of West Virginia streams are degraded by acid mine drainage (AMD), and the estimates for cleanup range in the billions of dollars. Not enough money is available to restore all the affected streams, so some way to prioritize those streams is needed. Ben...

  12. Surface Mines, Other - Longwall Mining Panels

    Data.gov (United States)

    NSGIC Education | GIS Inventory — Coal mining has occurred in Pennsylvania for over a century. A method of coal mining known as Longwall Mining has become more prevalent in recent decades. Longwall...

  13. Stretch-minimising stream surfaces

    KAUST Repository

    Barton, Michael; Kosinka, Jin; Calo, Victor M.

    2015-01-01

    We study the problem of finding stretch-minimising stream surfaces in a divergence-free vector field. These surfaces are generated by motions of seed curves that propagate through the field in a stretch minimising manner, i.e., they move without stretching or shrinking, preserving the length of their arbitrary arc. In general fields, such curves may not exist. How-ever, the divergence-free constraint gives rise to these 'stretch-free' curves that are locally arc-length preserving when infinitesimally propagated. Several families of stretch-free curves are identified and used as initial guesses for stream surface generation. These surfaces are subsequently globally optimised to obtain the best stretch-minimising stream surfaces in a given divergence-free vector field. Our algorithm was tested on benchmark datasets, proving its applicability to incompressible fluid flow simulations, where our stretch-minimising stream surfaces realistically reflect the flow of a flexible univariate object. © 2015 Elsevier Inc. All rights reserved.

  14. Stretch-minimising stream surfaces

    KAUST Repository

    Barton, Michael

    2015-05-01

    We study the problem of finding stretch-minimising stream surfaces in a divergence-free vector field. These surfaces are generated by motions of seed curves that propagate through the field in a stretch minimising manner, i.e., they move without stretching or shrinking, preserving the length of their arbitrary arc. In general fields, such curves may not exist. How-ever, the divergence-free constraint gives rise to these \\'stretch-free\\' curves that are locally arc-length preserving when infinitesimally propagated. Several families of stretch-free curves are identified and used as initial guesses for stream surface generation. These surfaces are subsequently globally optimised to obtain the best stretch-minimising stream surfaces in a given divergence-free vector field. Our algorithm was tested on benchmark datasets, proving its applicability to incompressible fluid flow simulations, where our stretch-minimising stream surfaces realistically reflect the flow of a flexible univariate object. © 2015 Elsevier Inc. All rights reserved.

  15. 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...

  16. Contrast data mining: concepts, algorithms, and applications

    National Research Council Canada - National Science Library

    Dong, Guozhu; Bailey, James

    2013-01-01

    .... Contrasting involves the comparison of one dataset against another. The datasets may represent data of different time periods, spatial locations, or classes, or they may represent data satisfying different conditions...

  17. Data mining

    CERN Document Server

    Gorunescu, Florin

    2011-01-01

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

  18. Mining wastes

    International Nuclear Information System (INIS)

    Pradel, J.

    1981-01-01

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

  19. PROGRAMS WITH DATA MINING CAPABILITIES

    Directory of Open Access Journals (Sweden)

    Ciobanu Dumitru

    2012-03-01

    Full Text Available The fact that the Internet has become a commodity in the world has created a framework for anew economy. Traditional businesses migrate to this new environment that offers many features and options atrelatively low prices. However competitiveness is fierce and successful Internet business is tied to rigorous use of allavailable information. The information is often hidden in data and for their retrieval is necessary to use softwarecapable of applying data mining algorithms and techniques. In this paper we want to review some of the programswith data mining capabilities currently available in this area.We also propose some classifications of this softwareto assist those who wish to use such software.

  20. IoT Stream Processing and Analytics in The Fog

    OpenAIRE

    Yang, Shusen

    2017-01-01

    The emerging Fog paradigm has been attracting increasing interests from both academia and industry, due to the low-latency, resilient, and cost-effective services it can provide. Many Fog applications such as video mining and event monitoring, rely on data stream processing and analytics, which are very popular in the Cloud, but have not been comprehensively investigated in the context of Fog architecture. In this article, we present the general models and architecture of Fog data streaming, ...

  1. Algorithming the Algorithm

    DEFF Research Database (Denmark)

    Mahnke, Martina; Uprichard, Emma

    2014-01-01

    Imagine sailing across the ocean. The sun is shining, vastness all around you. And suddenly [BOOM] you’ve hit an invisible wall. Welcome to the Truman Show! Ever since Eli Pariser published his thoughts on a potential filter bubble, this movie scenario seems to have become reality, just with slight...... changes: it’s not the ocean, it’s the internet we’re talking about, and it’s not a TV show producer, but algorithms that constitute a sort of invisible wall. Building on this assumption, most research is trying to ‘tame the algorithmic tiger’. While this is a valuable and often inspiring approach, we...

  2. Secure remote service execution for web media streaming

    OpenAIRE

    Mikityuk, Alexandra

    2017-01-01

    Through continuous advancements in streaming and Web technologies over the past decade, the Web has become a platform for media delivery. Web standards like HTML5 have been designed accordingly, allowing for the delivery of applications, high-quality streaming video, and hooks for interoperable content protection. Efficient video encoding algorithms such as AVC/HEVC and streaming protocols such as MPEG-DASH have served as additional triggers for this evolution. Users now employ...

  3. Big data mining analysis method based on cloud computing

    Science.gov (United States)

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

    2017-08-01

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

  4. Temporal Segmentation of MPEG Video Streams

    Directory of Open Access Journals (Sweden)

    Janko Calic

    2002-06-01

    Full Text Available Many algorithms for temporal video partitioning rely on the analysis of uncompressed video features. Since the information relevant to the partitioning process can be extracted directly from the MPEG compressed stream, higher efficiency can be achieved utilizing information from the MPEG compressed domain. This paper introduces a real-time algorithm for scene change detection that analyses the statistics of the macroblock features extracted directly from the MPEG stream. A method for extraction of the continuous frame difference that transforms the 3D video stream into a 1D curve is presented. This transform is then further employed to extract temporal units within the analysed video sequence. Results of computer simulations are reported.

  5. AMIDST: Analysis of MassIve Data STreams

    DEFF Research Database (Denmark)

    Masegosa, Andres; Martinez, Ana Maria; Borchani, Hanen

    2015-01-01

    The Analysis of MassIve Data STreams (AMIDST) Java toolbox provides a collection of scalable and parallel algorithms for inference and learning of hybrid Bayesian networks from data streams. The toolbox, available at http://amidst.github.io/toolbox/ under the Apache Software License version 2.......0, also efficiently leverages existing functionalities and algorithms by interfacing to software tools such as HUGIN and MOA....

  6. Preliminary Results: Release Of Metals From Acid-Mine Drainage Contaminated Streambed Sediments Under Anaerobic Conditions (Presentation)

    Science.gov (United States)

    Many miles of streams in the western U.S. are contaminated with acid-mine drainage (AMD) from abandoned metal mines. Treatment of these streams may include removal of the existing sediments, with subsequent burial (e.g., in a repository). Burial of previously aerobic sediments ma...

  7. Mining Method

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Young Shik; Lee, Kyung Woon; Kim, Oak Hwan; Kim, Dae Kyung [Korea Institute of Geology Mining and Materials, Taejon (Korea, Republic of)

    1996-12-01

    The reducing coal market has been enforcing the coal industry to make exceptional rationalization and restructuring efforts since the end of the eighties. To the competition from crude oil and natural gas has been added the growing pressure from rising wages and rising production cost as the workings get deeper. To improve the competitive position of the coal mines against oil and gas through cost reduction, studies to improve mining system have been carried out. To find fields requiring improvements most, the technologies using in Tae Bak Colliery which was selected one of long running mines were investigated and analyzed. The mining method appeared the field needing improvements most to reduce the production cost. The present method, so-called inseam roadway caving method presently is using to extract the steep and thick seam. However, this method has several drawbacks. To solve the problems, two mining methods are suggested for a long term and short term method respectively. Inseam roadway caving method with long-hole blasting method is a variety of the present inseam roadway caving method modified by replacing timber sets with steel arch sets and the shovel loaders with chain conveyors. And long hole blasting is introduced to promote caving. And pillar caving method with chock supports method uses chock supports setting in the cross-cut from the hanging wall to the footwall. Two single chain conveyors are needed. One is installed in front of chock supports to clear coal from the cutting face. The other is installed behind the supports to transport caved coal from behind. This method is superior to the previous one in terms of safety from water-inrushes, production rate and productivity. The only drawback is that it needs more investment. (author). 14 tabs., 34 figs.

  8. StreamCat

    Data.gov (United States)

    U.S. Environmental Protection Agency — The StreamCat Dataset provides summaries of natural and anthropogenic landscape features for ~2.65 million streams, and their associated catchments, within the...

  9. Prioritized Contact Transport Stream

    Science.gov (United States)

    Hunt, Walter Lee, Jr. (Inventor)

    2015-01-01

    A detection process, contact recognition process, classification process, and identification process are applied to raw sensor data to produce an identified contact record set containing one or more identified contact records. A prioritization process is applied to the identified contact record set to assign a contact priority to each contact record in the identified contact record set. Data are removed from the contact records in the identified contact record set based on the contact priorities assigned to those contact records. A first contact stream is produced from the resulting contact records. The first contact stream is streamed in a contact transport stream. The contact transport stream may include and stream additional contact streams. The contact transport stream may be varied dynamically over time based on parameters such as available bandwidth, contact priority, presence/absence of contacts, system state, and configuration parameters.

  10. Overview of mine drainage geochemistry at historical mines, Humboldt River basin and adjacent mining areas, Nevada. Chapter E.

    Science.gov (United States)

    Nash, J. Thomas; Stillings, Lisa L.

    2004-01-01

    Reconnaissance hydrogeochemical studies of the Humboldt River basin and adjacent areas of northern Nevada have identified local sources of acidic waters generated by historical mine workings and mine waste. The mine-related acidic waters are rare and generally flow less than a kilometer before being neutralized by natural processes. Where waters have a pH of less than about 3, particularly in the presence of sulfide minerals, the waters take on high to extremely high concentrations of many potentially toxic metals. The processes that create these acidic, metal-rich waters in Nevada are the same as for other parts of the world, but the scale of transport and the fate of metals are much more localized because of the ubiquitous presence of caliche soils. Acid mine drainage is rare in historical mining districts of northern Nevada, and the volume of drainage rarely exceeds about 20 gpm. My findings are in close agreement with those of Price and others (1995) who estimated that less than 0.05 percent of inactive and abandoned mines in Nevada are likely to be a concern for acid mine drainage. Most historical mining districts have no draining mines. Only in two districts (Hilltop and National) does water affected by mining flow into streams of significant size and length (more than 8 km). Water quality in even the worst cases is naturally attenuated to meet water-quality standards within about 1 km of the source. Only a few historical mines release acidic water with elevated metal concentrations to small streams that reach the Humboldt River, and these contaminants and are not detectable in the Humboldt. These reconnaissance studies offer encouraging evidence that abandoned mines in Nevada create only minimal and local water-quality problems. Natural attenuation processes are sufficient to compensate for these relatively small sources of contamination. These results may provide useful analogs for future mining in the Humboldt River basin, but attention must be given to

  11. Layout Study and Application of Mobile App Recommendation Approach Based On Spark Streaming Framework

    Science.gov (United States)

    Wang, H. T.; Chen, T. T.; Yan, C.; Pan, H.

    2018-05-01

    For App recommended areas of mobile phone software, made while using conduct App application recommended combined weighted Slope One algorithm collaborative filtering algorithm items based on further improvement of the traditional collaborative filtering algorithm in cold start, data matrix sparseness and other issues, will recommend Spark stasis parallel algorithm platform, the introduction of real-time streaming streaming real-time computing framework to improve real-time software applications recommended.

  12. Anthropogenic and natural sources of acidity and metals and their influence on the structure of stream food webs.

    Science.gov (United States)

    Hogsden, Kristy L; Harding, Jon S

    2012-03-01

    We compared food web structure in 20 streams with either anthropogenic or natural sources of acidity and metals or circumneutral water chemistry in New Zealand. Community and diet analysis indicated that mining streams receiving anthropogenic inputs of acidic and metal-rich drainage had much simpler food webs (fewer species, shorter food chains, less links) than those in naturally acidic, naturally high metal, and circumneutral streams. Food webs of naturally high metal streams were structurally similar to those in mining streams, lacking fish predators and having few species. Whereas, webs in naturally acidic streams differed very little from those in circumneutral streams due to strong similarities in community composition and diets of secondary and top consumers. The combined negative effects of acidity and metals on stream food webs are clear. However, elevated metal concentrations, regardless of source, appear to play a more important role than acidity in driving food web structure. Copyright © 2011 Elsevier Ltd. All rights reserved.

  13. Red River Stream Improvement Final Design Nez Perce National Forest.

    Energy Technology Data Exchange (ETDEWEB)

    Watershed Consulting, LLC

    2007-03-15

    This report details the final stream improvement design along the reach of Red River between the bridge below Dawson Creek, upstream for approximately 2 miles, Idaho County, Idaho. Geomorphic mapping, hydrologic profiles and cross-sections were presented along with existing fish habitat maps in the conceptual design report. This information is used to develop a stream improvement design intended to improve aquatic habitat and restore riparian health in the reach. The area was placer mined using large bucket dredges between 1938 and 1957. This activity removed most of the riparian vegetation in the stream corridor and obliterated the channel bed and banks. The reach was also cut-off from most valley margin tributaries. In the 50 years since large-scale dredging ceased, the channel has been re-established and parts of the riparian zone have grown in. However, the recruitment of large woody debris to the stream has been extremely low and overhead cover is poor. Pool habitat makes up more than 37% of the reach, and habitat diversity is much better than the project reach on Crooked River. There is little large woody debris in the stream to provide cover for spawning and juvenile rearing, because the majority of the woody debris does not span a significant part of the channel, but is mainly on the side slopes of the stream. Most of the riparian zone has very little soil or subsoil left after the mining and so now consists primarily of unconsolidated cobble tailings or heavily compacted gravel tailings. Knapweed and lodgepole pine are the most successful colonizers of these post mining landforms. Tributary fans which add complexity to many other streams in the region, have been isolated from the main reach due to placer mining and road building.

  14. The online performance estimation framework: heterogeneous ensemble learning for data streams

    NARCIS (Netherlands)

    van Rijn, J.N.; Holmes, G.; Pfahringer, B.; Vanschoren, J.

    2018-01-01

    Ensembles of classifiers are among the best performing classifiers available in many data mining applications, including the mining of data streams. Rather than training one classifier, multiple classifiers are trained, and their predictions are combined according to a given voting schedule. An

  15. Mine games

    Energy Technology Data Exchange (ETDEWEB)

    Patchett, A. [Hitachi Construction Equipment (United Kingdom)

    2006-09-15

    The article describes various excavators used in the UK by Hall Construction for coal mining and reclamation projects. They include machines from Hitachi Construction Machinery that have been modified with a coal shovel at the front end. The ZX350LC-3, for example incorporates a coal shovel, manufactured by Kocurek, to allow it to work at the rock face and lift coal into road wagons or dump trucks. 5 figs.

  16. Graph Mining Meets the Semantic Web

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Sangkeun (Matt) [ORNL; Sukumar, Sreenivas R [ORNL; Lim, Seung-Hwan [ORNL

    2015-01-01

    The Resource Description Framework (RDF) and SPARQL Protocol and RDF Query Language (SPARQL) were introduced about a decade ago to enable flexible schema-free data interchange on the Semantic Web. Today, data scientists use the framework as a scalable graph representation for integrating, querying, exploring and analyzing data sets hosted at different sources. With increasing adoption, the need for graph mining capabilities for the Semantic Web has emerged. We address that need through implementation of three popular iterative Graph Mining algorithms (Triangle count, Connected component analysis, and PageRank). We implement these algorithms as SPARQL queries, wrapped within Python scripts. We evaluate the performance of our implementation on 6 real world data sets and show graph mining algorithms (that have a linear-algebra formulation) can indeed be unleashed on data represented as RDF graphs using the SPARQL query interface.

  17. Tracing disturbance impacts on water quantity and quality through a stream network

    Science.gov (United States)

    Ross, Matthew; Nippgen, Fabian; McGlynn, Brian; Bernhardt, Emily

    2017-04-01

    By dismantling and redistributing 100s of meters of bedrock to mine coal from the surface, mountaintop mining with valley fills has dramatically changed catchment hydrology and biogeochemistry over more than 5,000 km2 in Central Appalachia. Throughout this expansive coal region, mining operators deposit tens of millions of m3 of crushed bedrock into headwater valleys, creating valley fills, which have substantial subsurface water storage potential. Streams draining mines have reduced peakflows, elevated baseflows, and lower event runoff ratios on average. The water stored in and percolating through valley fills drives the dissolution and oxidation of pyrite into sulfuric acid which reacts with carbonate-rich materials to rapidly weather out a suite of elements including Ca2+, Mg2+, K+, SO42-, HCO3-, and the pollutant Selenium. Together these ions increase the average specific conductance of mined streams from 60 to 1,500 µS/cm, 25-times higher than unmined streams, exporting 45-times more total dissolved solids. Together, the increased catchment storage, consequent elevated baseflow, and elevated weathering rates from mining have the potential to lower water quality throughout river networks in Central Appalachia, especially during the summer low flow period. To better understand the water quality impacts of mining at the river network scale, we used the paired catchment approach. Working in the Mud River, West Virginia, we instrumented a 4th order catchment 35 km2, that was 46% mined. Within the large catchment we instrumented 8 additional 1st-3rd order sub-catchments that varied in catchment size, mining cover, mine size, and mine age. At each site we measured stream discharge and specific conductance (SC). Using SC as a trace for mining we did simple hydrograph separations at our largest catchments, partitioning the hydrograph between mined and unmined water. Our results suggest that on an annual scale, mine water contributes a disproportionate percentage of

  18. Predictive analytics on evolving data streams anticipating and adapting to changes in known and unknown contexts

    NARCIS (Netherlands)

    Pechenizkiy, M.

    2015-01-01

    Ever increasing volumes of sensor readings, transactional records, web data and event logs call for next generation of big data mining technology providing effective and efficient tools for making use of the streaming data. Predictive analytics on data streams is actively studied in research

  19. Evaluation of Heavy Metals in Stream Sediments from Abakaliki Pb ...

    African Journals Online (AJOL)

    PROF HORSFALL

    Evaluation of Heavy Metals in Stream Sediments from Abakaliki Pb – Zn Ore Mining. Areas of Ebonyi ... produced both for local consumption and also for food supplies to other .... of deionised water using a pH-meter (Aqualytica. Model pH 17).

  20. Heavy metal contamination in stream water and sediments of gold ...

    African Journals Online (AJOL)

    I.O.OLABANJI

    3D) with 0.457 ± 0.061 and 0.364 ± 0.056 mg/L in dry and wet seasons. The mean .... safe limit clearly indicating that Cd contamination of the stream water might be ... of lead contaminant in the study area is the formation of acid mine drainage.

  1. Benthic invertebrate fauna, small streams

    Science.gov (United States)

    J. Bruce Wallace; S.L. Eggert

    2009-01-01

    Small streams (first- through third-order streams) make up >98% of the total number of stream segments and >86% of stream length in many drainage networks. Small streams occur over a wide array of climates, geology, and biomes, which influence temperature, hydrologic regimes, water chemistry, light, substrate, stream permanence, a basin's terrestrial plant...

  2. Sound algorithms

    OpenAIRE

    De Götzen , Amalia; Mion , Luca; Tache , Olivier

    2007-01-01

    International audience; We call sound algorithms the categories of algorithms that deal with digital sound signal. Sound algorithms appeared in the very infancy of computer. Sound algorithms present strong specificities that are the consequence of two dual considerations: the properties of the digital sound signal itself and its uses, and the properties of auditory perception.

  3. Genetic algorithms

    Science.gov (United States)

    Wang, Lui; Bayer, Steven E.

    1991-01-01

    Genetic algorithms are mathematical, highly parallel, adaptive search procedures (i.e., problem solving methods) based loosely on the processes of natural genetics and Darwinian survival of the fittest. Basic genetic algorithms concepts are introduced, genetic algorithm applications are introduced, and results are presented from a project to develop a software tool that will enable the widespread use of genetic algorithm technology.

  4. Seasonal factors controlling mineral precipitation in the acid mine drainage at Donghae coal mine, Korea

    International Nuclear Information System (INIS)

    Kim, J.J.; Kim, S.J.

    2004-01-01

    Monitoring over a 12 month period in the Sanae creek flow in acid mine drainage, Donghae coal mine area, demonstrates that the concentrations of dissolved metals and sulphate are highest during autumn when water flow in the creek is at its lowest. The highest pH values of the stream were measured in April and May, whereas the lowest pH was recorded in October. The Fe concentration of stream water rapidly decreased downstream due to the precipitation of Fe oxyhydroxide and/or oxyhydroxysulfate phases in the stream. Mineral precipitates in the creek in the Donghae mine area show various colours such as brownish yellow (Munsell colour 9.5 YR hues), reddish brown (Munsell colour 3.5 YR hues) and white depending on seasons and distance from the pollution source in the creek. Such phenomena are attributed to the variation in pH and chemical composition of stream water caused by seasonal factors. The measured pH ranges in stream water of the brownish yellow, white and reddish brown precipitates are pH 3.2-4.5, 4.5-6.0 and 5.3-6.9, respectively

  5. Earth Science Mining Web Services

    Science.gov (United States)

    Pham, Long; Lynnes, Christopher; Hegde, Mahabaleshwa; Graves, Sara; Ramachandran, Rahul; Maskey, Manil; Keiser, Ken

    2008-01-01

    To allow scientists further capabilities in the area of data mining and web services, the Goddard Earth Sciences Data and Information Services Center (GES DISC) and researchers at the University of Alabama in Huntsville (UAH) have developed a system to mine data at the source without the need of network transfers. The system has been constructed by linking together several pre-existing technologies: the Simple Scalable Script-based Science Processor for Measurements (S4PM), a processing engine at he GES DISC; the Algorithm Development and Mining (ADaM) system, a data mining toolkit from UAH that can be configured in a variety of ways to create customized mining processes; ActiveBPEL, a workflow execution engine based on BPEL (Business Process Execution Language); XBaya, a graphical workflow composer; and the EOS Clearinghouse (ECHO). XBaya is used to construct an analysis workflow at UAH using ADam components, which are also installed remotely at the GES DISC, wrapped as Web Services. The S4PM processing engine searches ECHO for data using space-time criteria, staging them to cache, allowing the ActiveBPEL engine to remotely orchestras the processing workflow within S4PM. As mining is completed, the output is placed in an FTP holding area for the end user. The goals are to give users control over the data they want to process, while mining data at the data source using the server's resources rather than transferring the full volume over the internet. These diverse technologies have been infused into a functioning, distributed system with only minor changes to the underlying technologies. The key to the infusion is the loosely coupled, Web-Services based architecture: All of the participating components are accessible (one way or another) through (Simple Object Access Protocol) SOAP-based Web Services.

  6. Data Mining and Machine Learning in Astronomy

    Science.gov (United States)

    Ball, Nicholas M.; Brunner, Robert J.

    We review the current state of data mining and machine learning in astronomy. Data Mining can have a somewhat mixed connotation from the point of view of a researcher in this field. If used correctly, it can be a powerful approach, holding the potential to fully exploit the exponentially increasing amount of available data, promising great scientific advance. However, if misused, it can be little more than the black box application of complex computing algorithms that may give little physical insight, and provide questionable results. Here, we give an overview of the entire data mining process, from data collection through to the interpretation of results. We cover common machine learning algorithms, such as artificial neural networks and support vector machines, applications from a broad range of astronomy, emphasizing those in which data mining techniques directly contributed to improving science, and important current and future directions, including probability density functions, parallel algorithms, Peta-Scale computing, and the time domain. We conclude that, so long as one carefully selects an appropriate algorithm and is guided by the astronomical problem at hand, data mining can be very much the powerful tool, and not the questionable black box.

  7. TSC mobile mining and extraction technology

    Energy Technology Data Exchange (ETDEWEB)

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

    2001-11-01

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

  8. Integration of vertical and in-seam horizontal well production analyses with stochastic geostatistical algorithms to estimate pre-mining methane drainage efficiency from coal seams: Blue Creek seam, Alabama.

    Science.gov (United States)

    Karacan, C Özgen

    2013-07-30

    Coal seam degasification and its efficiency are directly related to the safety of coal mining. Degasification activities in the Black Warrior basin started in the early 1980s by using vertical boreholes. Although the Blue Creek seam, which is part of the Mary Lee coal group, has been the main seam of interest for coal mining, vertical wellbores have also been completed in the Pratt, Mary Lee, and Black Creek coal groups of the Upper Pottsville formation to degasify multiple seams. Currently, the Blue Creek seam is further degasified 2-3 years in advance of mining using in-seam horizontal boreholes to ensure safe mining. The studied location in this work is located between Tuscaloosa and Jefferson counties in Alabama and was degasified using 81 vertical boreholes, some of which are still active. When the current long mine expanded its operation into this area in 2009, horizontal boreholes were also drilled in advance of mining for further degasification of only the Blue Creek seam to ensure a safe and a productive operation. This paper presents an integrated study and a methodology to combine history matching results from vertical boreholes with production modeling of horizontal boreholes using geostatistical simulation to evaluate spatial effectiveness of in-seam boreholes in reducing gas-in-place (GIP). Results in this study showed that in-seam wells' boreholes had an estimated effective drainage area of 2050 acres with cumulative production of 604 MMscf methane during ~2 years of operation. With horizontal borehole production, GIP in the Blue Creek seam decreased from an average of 1.52 MMscf to 1.23 MMscf per acre. It was also shown that effective gas flow capacity, which was independently modeled using vertical borehole data, affected horizontal borehole production. GIP and effective gas flow capacity of coal seam gas were also used to predict remaining gas potential for the Blue Creek seam.

  9. Anthropogenic and natural sources of acidity and metals and their influence on the structure of stream food webs

    International Nuclear Information System (INIS)

    Hogsden, Kristy L.; Harding, Jon S.

    2012-01-01

    We compared food web structure in 20 streams with either anthropogenic or natural sources of acidity and metals or circumneutral water chemistry in New Zealand. Community and diet analysis indicated that mining streams receiving anthropogenic inputs of acidic and metal-rich drainage had much simpler food webs (fewer species, shorter food chains, less links) than those in naturally acidic, naturally high metal, and circumneutral streams. Food webs of naturally high metal streams were structurally similar to those in mining streams, lacking fish predators and having few species. Whereas, webs in naturally acidic streams differed very little from those in circumneutral streams due to strong similarities in community composition and diets of secondary and top consumers. The combined negative effects of acidity and metals on stream food webs are clear. However, elevated metal concentrations, regardless of source, appear to play a more important role than acidity in driving food web structure. - Highlights: ► Food webs in acid mine drainage impacted streams are small and extremely simplified. ► Conductivity explained differences in food web properties between streams. ► Number of links and web size accounted for much dissimilarity between food webs. ► Food web structure was comparable in naturally acidic and circumneutral streams. - Food web structure differs in streams with anthropogenic and natural sources of acidity and metals.

  10. Solar wind stream interfaces

    International Nuclear Information System (INIS)

    Gosling, J.T.; Asbridge, J.R.; Bame, S.J.; Feldman, W.C.

    1978-01-01

    Measurements aboard Imp 6, 7, and 8 reveal that approximately one third of all high-speed solar wind streams observed at 1 AU contain a sharp boundary (of thickness less than approx.4 x 10 4 km) near their leading edge, called a stream interface, which separates plasma of distinctly different properties and origins. Identified as discontinuities across which the density drops abruptly, the proton temperature increases abruptly, and the speed rises, stream interfaces are remarkably similar in character from one stream to the next. A superposed epoch analysis of plasma data has been performed for 23 discontinuous stream interfaces observed during the interval March 1971 through August 1974. Among the results of this analysis are the following: (1) a stream interface separates what was originally thick (i.e., dense) slow gas from what was originally thin (i.e., rare) fast gas; (2) the interface is the site of a discontinuous shear in the solar wind flow in a frame of reference corotating with the sun; (3) stream interfaces occur at speeds less than 450 km s - 1 and close to or at the maximum of the pressure ridge at the leading edges of high-speed streams; (4) a discontinuous rise by approx.40% in electron temperature occurs at the interface; and (5) discontinuous changes (usually rises) in alpha particle abundance and flow speed relative to the protons occur at the interface. Stream interfaces do not generally recur on successive solar rotations, even though the streams in which they are embedded often do. At distances beyond several astronomical units, stream interfaces should be bounded by forward-reverse shock pairs; three of four reverse shocks observed at 1 AU during 1971--1974 were preceded within approx.1 day by stream interfaces. Our observations suggest that many streams close to the sun are bounded on all sides by large radial velocity shears separating rapidly expanding plasma from more slowly expanding plasma

  11. The role of scientists in acid mine drainage policy response in Gauteng, South Africa: Presentation

    CSIR Research Space (South Africa)

    Funke, Nicola S

    2012-10-01

    Full Text Available . This government response came after considerable publicity in the media and threats of legal action by NGOs. • Complexity: historical link between government and mines, lack of inter-departmental coordination, scientific uncertainty, many actors involved... stream_source_info Funke3_2012.pdf.txt stream_content_type text/plain stream_size 6180 Content-Encoding UTF-8 stream_name Funke3_2012.pdf.txt Content-Type text/plain; charset=UTF-8 The role of scientists in Acid Mine...

  12. Stream chemistry in the eastern United States. 2. Current sources of acidity in acidic and low acid-neutralizing-capacity streams

    International Nuclear Information System (INIS)

    Herlihy, A.T.; Kaufmann, P.R.; Mitch, M.E.

    1991-01-01

    The authors examined anion composition in National Stream Survey (NSS) data in order to evaluate the most probable sources of current acidity in acidic and low acid neutralizing capacity (ANC) streams in the eastern United States. Acidic streams that had almost no organic influence (less than 10% of total anions) and sulfate and nitrate concentrations indicative of evaporative concentration of atmospheric deposition were classified as acidic due to acidic deposition. These acidic streams were located in small forested watersheds in the Mid-Atlantic Highlands (an estimated 1950 km of stream length) and in the Mid-Atlantic Coastal Plain (1250 km). Acidic streams affected primarily by acidic deposition but also influenced by naturally occurring organic anions accounted for another 1180 km of acidic stream length and were located in the New Jersey Pine Barrens, plateau tops in the Mid-Atlantic and Southeast Highlands, and the Florida Panhandle. The total length of streams acidic due to acid mine drainage in the NSS (4590 km) was about the same as the total length of acidic streams likely affected by acidic deposition (4380 km). Acidic streams whose acid anion composition was dominated by organics were located in Florida and the Mid-Atlantic Coastal Plain. In Florida, most of the acidic streams were organic dominated, whereas about half of the streams in the Mid-Atlantic Coastal Plain were organic dominated. Organic-dominated acidic streams were not observed in the Mid-Atlantic and Southeast Highlands

  13. Software tool for data mining and its applications

    Science.gov (United States)

    Yang, Jie; Ye, Chenzhou; Chen, Nianyi

    2002-03-01

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

  14. Exploration and Mining Roadmap

    Energy Technology Data Exchange (ETDEWEB)

    none,

    2002-09-01

    This Exploration and Mining Technology Roadmap represents the third roadmap for the Mining Industry of the Future. It is based upon the results of the Exploration and Mining Roadmap Workshop held May 10 ñ 11, 2001.

  15. Ghana Mining Journal

    African Journals Online (AJOL)

    ... in the Ghana mining journal: Geology and Mineral Exploration, Mining, Quarrying, Geomechanics, Groundwater Studies, Hydrocarbon Development, Mineral Processing, Metallurgy, Material Science, Mineral Management Policies, Mineral Economics, Environmental Aspects, Computer Applications and Mining Education.

  16. Coal Mine Permit Boundaries

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — ESRI ArcView shapefile depicting New Mexico coal mines permitted under the Surface Mining Control and Reclamation Act of 1977 (SMCRA), by either the NM Mining these...

  17. Uranium mining in Australia

    International Nuclear Information System (INIS)

    Anon.

    1984-01-01

    The mining of uranium in Australia is criticised in relation to it's environmental impact, economics and effects on mine workers and Aborigines. A brief report is given on each of the operating and proposed uranium mines in Australia

  18. Algorithms for Academic Search and Recommendation Systems

    DEFF Research Database (Denmark)

    Amolochitis, Emmanouil

    2014-01-01

    are part of a developed Movie Recommendation system, the first such system to be commercially deployed in Greece by a major Triple Play services provider. In the third part of the work we present the design of a quantitative association rule mining algorithm. The introduced mining algorithm processes......In this work we present novel algorithms for academic search, recommendation and association rules mining. In the first part of the work we introduce a novel hierarchical heuristic scheme for re-ranking academic publications. The scheme is based on the hierarchical combination of a custom...... implementation of the term frequency heuristic, a time-depreciated citation score and a graph-theoretic computed score that relates the paper’s index terms with each other. On the second part we describe the design of hybrid recommender ensemble (user, item and content based). The newly introduced algorithms...

  19. Mining royalties

    Directory of Open Access Journals (Sweden)

    Jelenković Rade J.

    2014-01-01

    Full Text Available Mineral resources are finite and nonrenewable in the sense that their extraction permanently depletes a country's resource inventory. The role of governments should be to manage the exploitation of these resources to maximize the economic benefits to their community, consistent with the need to attract and retain the exploration and development capital necessary to continue to realize these benefits for as long as possible. In designing mineral sector taxation systems, policy makers must carefully seek to balance tax types, rates, and incentives that satisfy the needs of both the nation and the mining investor.

  20. WEKA-G: Parallel data mining on computational grids

    Directory of Open Access Journals (Sweden)

    PIMENTA, A.

    2009-12-01

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

  1. Survival of mayfly larvae under mine acid conditions

    Energy Technology Data Exchange (ETDEWEB)

    Napier, S. Jr.; Hummon, W.D.

    1976-01-01

    Mayfly larvae were abundant and diverse in riffle zones of three control streams in southeastern Ohio. But none were found in such zones of three streams having current or past histories of mine acid pollution, despite vegetative recovery of reclaimed land bordering two of the streams. Laboratory studies showed stepwise increases in non-predatory mortality of mayfly larvae with increased mine acidity. Dragonfly larvae predation on mayfly larvae was constant at pH 8.1 to 4.1, but decreased at pH 3.1 despite tolerance of dragonfly larvae to low pH conditions. Extensive acid mine pollution thus may threaten aquatic biota through removal of food sources or reduced feeding rates as well as through direct mortality.

  2. Gain ratio based fuzzy weighted association rule mining classifier for ...

    Indian Academy of Sciences (India)

    association rule mining algorithm for extracting both association rules and member- .... The disadvantage of this work is in considering the generalization at each ... If the new attribute is entered, the generalization process does not consider the ...

  3. Inventory of miscellaneous streams

    International Nuclear Information System (INIS)

    Lueck, K.J.

    1995-09-01

    On December 23, 1991, the US Department of Energy, Richland Operations Office (RL) and the Washington State Department of Ecology (Ecology) agreed to adhere to the provisions of the Department of Ecology Consent Order. The Consent Order lists the regulatory milestones for liquid effluent streams at the Hanford Site to comply with the permitting requirements of Washington Administrative Code. The RL provided the US Congress a Plan and Schedule to discontinue disposal of contaminated liquid effluent into the soil column on the Hanford Site. The plan and schedule document contained a strategy for the implementation of alternative treatment and disposal systems. This strategy included prioritizing the streams into two phases. The Phase 1 streams were considered to be higher priority than the Phase 2 streams. The actions recommended for the Phase 1 and 2 streams in the two reports were incorporated in the Hanford Federal Facility Agreement and Consent Order. Miscellaneous Streams are those liquid effluents streams identified within the Consent Order that are discharged to the ground but are not categorized as Phase 1 or Phase 2 Streams. This document consists of an inventory of the liquid effluent streams being discharged into the Hanford soil column

  4. Hydrography - Streams and Shorelines

    Data.gov (United States)

    California Natural Resource Agency — The hydrography layer consists of flowing waters (rivers and streams), standing waters (lakes and ponds), and wetlands -- both natural and manmade. Two separate...

  5. Algorithmic cryptanalysis

    CERN Document Server

    Joux, Antoine

    2009-01-01

    Illustrating the power of algorithms, Algorithmic Cryptanalysis describes algorithmic methods with cryptographically relevant examples. Focusing on both private- and public-key cryptographic algorithms, it presents each algorithm either as a textual description, in pseudo-code, or in a C code program.Divided into three parts, the book begins with a short introduction to cryptography and a background chapter on elementary number theory and algebra. It then moves on to algorithms, with each chapter in this section dedicated to a single topic and often illustrated with simple cryptographic applic

  6. Expressive power of an algebra for data mining

    NARCIS (Netherlands)

    Calders, T.; Lakshmanan, L.V.S.; Ng, R.T.; Paredaens, J.

    2006-01-01

    The relational data model has simple and clear foundations on which significant theoretical and systems research has flourished. By contrast, most research on data mining has focused on algorithmic issues. A major open question is: what's an appropriate foundation for data mining, which can

  7. Numerical modelling of suspended radioactive sediment transport in a stream using matlab

    International Nuclear Information System (INIS)

    Sarpong, Linda

    2017-07-01

    The use of materials that contain radioactive substances has gained grounds in Ghana due to numerous benefits derived from them. These radioactive materials can be found in the areas of medicine, agriculture and industries such as mining. Though there are strict measures to ensure such material do not find its way into the environment, improper management of the waste poses a threat to the environment. To be able to understand the impact the radioactive material has on the environment, mathematical models play a very relevant role in tracking the level of pollution in any medium. This thesis was concerned with the numerical modelling for the transport of the radioactive solute material that suspends in a stream using Matlab at different velocities as a result of flooding or an accident for research purposes. The modelling was done by using partial differential equations describing relevant physical processes evolution which includes water level, dissolved and suspended substances concentration and velocities. The equation system basis are the mass conservation and momentum laws, state equation and state transport equations. The implicit finite difference scheme was used to evaluate the transport equation, Advection-Dispersion Equation (ADE) with respect to time and space. Solution algorithms for Matlab programming were developed and implemented for generating results for analysis. The results obtained showed that the model was able to simulate accurately the various levels of suspended radioactive sediment concentration changes in the flowing stream longitudinally. (au)

  8. Application of MIKE SHE to study the impact of coal mining on river runoff in Gujiao mining area, Shanxi, China.

    Directory of Open Access Journals (Sweden)

    Jianhua Ping

    Full Text Available Coal mining is one of the core industries that contribute to the economic development of a country but deteriorate the environment. Being the primary source of energy, coal has become essential to meet the energy demand of a country. It is excavated by both opencast and underground mining methods and affects the environment, especially hydrological cycle, by discharging huge amounts of mine water. Natural hydrological processes have been well known to be vulnerable to human activities, especially large scale mining activities, which inevitably generate surface cracks and subsidence. It is therefore valuable to assess the impact of mining on river runoff for the sustainable development of regional economy. In this paper, the impact of coal mining on river runoff is assessed in one of the national key coal mining sites, Gujiao mining area, Shanxi Province, China. The characteristics of water cycle are described, the similarities and differences of runoff formation are analyzed in both coal mining and pre-mining periods. The integrated distributed hydrological model named MIKE SHE is employed to simulate and evaluate the influence of coal mining on river runoff. The study shows that mining one ton of raw coal leads to the reduction of river runoff by 2.87 m3 between 1981 and 2008, of which the surface runoff decreases by 0.24 m3 and the baseflow by 2.63 m3. The reduction degree of river runoff for mining one ton of raw coal shows an increasing trend over years. The current study also reveals that large scale coal mining initiates the formation of surface cracks and subsidence, which intercepts overland flow and enhances precipitation infiltration. Together with mine drainage, the natural hydrological processes and the stream flows have been altered and the river run off has been greatly reduced.

  9. Application of MIKE SHE to study the impact of coal mining on river runoff in Gujiao mining area, Shanxi, China.

    Science.gov (United States)

    Ping, Jianhua; Yan, Shiyan; Gu, Pan; Wu, Zening; Hu, Caihong

    2017-01-01

    Coal mining is one of the core industries that contribute to the economic development of a country but deteriorate the environment. Being the primary source of energy, coal has become essential to meet the energy demand of a country. It is excavated by both opencast and underground mining methods and affects the environment, especially hydrological cycle, by discharging huge amounts of mine water. Natural hydrological processes have been well known to be vulnerable to human activities, especially large scale mining activities, which inevitably generate surface cracks and subsidence. It is therefore valuable to assess the impact of mining on river runoff for the sustainable development of regional economy. In this paper, the impact of coal mining on river runoff is assessed in one of the national key coal mining sites, Gujiao mining area, Shanxi Province, China. The characteristics of water cycle are described, the similarities and differences of runoff formation are analyzed in both coal mining and pre-mining periods. The integrated distributed hydrological model named MIKE SHE is employed to simulate and evaluate the influence of coal mining on river runoff. The study shows that mining one ton of raw coal leads to the reduction of river runoff by 2.87 m3 between 1981 and 2008, of which the surface runoff decreases by 0.24 m3 and the baseflow by 2.63 m3. The reduction degree of river runoff for mining one ton of raw coal shows an increasing trend over years. The current study also reveals that large scale coal mining initiates the formation of surface cracks and subsidence, which intercepts overland flow and enhances precipitation infiltration. Together with mine drainage, the natural hydrological processes and the stream flows have been altered and the river run off has been greatly reduced.

  10. Algorithmic mathematics

    CERN Document Server

    Hougardy, Stefan

    2016-01-01

    Algorithms play an increasingly important role in nearly all fields of mathematics. This book allows readers to develop basic mathematical abilities, in particular those concerning the design and analysis of algorithms as well as their implementation. It presents not only fundamental algorithms like the sieve of Eratosthenes, the Euclidean algorithm, sorting algorithms, algorithms on graphs, and Gaussian elimination, but also discusses elementary data structures, basic graph theory, and numerical questions. In addition, it provides an introduction to programming and demonstrates in detail how to implement algorithms in C++. This textbook is suitable for students who are new to the subject and covers a basic mathematical lecture course, complementing traditional courses on analysis and linear algebra. Both authors have given this "Algorithmic Mathematics" course at the University of Bonn several times in recent years.

  11. A study into the treatability of ochreous mine water discharges

    Energy Technology Data Exchange (ETDEWEB)

    Clark, C J; Crawshaw, D H

    1979-01-01

    The oxidation of ferrous salts in solution from waste-water discharges from 3 abandoned and flooded mines near Bromley, Lancs, (UK) has since 1968 caused discoloration in the Calder River. Deposition and dilution decreases the ochreous effect, but the iron oxide is harmful to the benthos by producing a low dissolved-oxygen environment. The Calder River is only a Class 4 river below the confluence with the stream which carried the mine waters, and pilot-plant studies and field trials are described to determine the feasibility of full- scale treatment of the stream waters, resulting in the recommendation of lagoon treatment followed by neutralization.

  12. Mercury pollution in Wuchuan mercury mining area, Guizhou, Southwestern China: the impacts from large scale and artisanal mercury mining.

    Science.gov (United States)

    Li, Ping; Feng, Xinbin; Qiu, Guangle; Shang, Lihai; Wang, Shaofeng

    2012-07-01

    To evaluate the environmental impacts from large scale mercury mining (LSMM) and artisanal mercury mining (AMM), total mercury (THg) and methyl mercury (MeHg) were determined in mine waste, ambient air, stream water and soil samples collected from Wuchuan mercury (Hg) mining area, Guizhou, Southwestern China. Mine wastes from both LSMM and AMM contained high THg concentrations, which are important Hg contamination sources to the local environment. Total gaseous mercury (TGM) concentrations in the ambient air near AMM furnaces were highly elevated, which indicated that AMM retorting is a major source of Hg emission. THg concentrations in the stream water varied from 43 to 2100 ng/L, where the elevated values were mainly found in the vicinity of AMM and mine waste heaps of LSMM. Surface soils were seriously contaminated with Hg, and land using types and organic matter played an important role in accumulation and transportation of Hg in soil. The results indicated heavy Hg contaminations in the study area, which were resulted from both LSMM and AMM. The areas impacted by LSMM were concentrated in the historical mining and smelting facilities, while Hg pollution resulted from AMM can be distributed anywhere in the Hg mining area. Copyright © 2011 Elsevier Ltd. All rights reserved.

  13. Total algorithms

    NARCIS (Netherlands)

    Tel, G.

    We define the notion of total algorithms for networks of processes. A total algorithm enforces that a "decision" is taken by a subset of the processes, and that participation of all processes is required to reach this decision. Total algorithms are an important building block in the design of

  14. Alignment data streams for the ATLAS inner detector

    International Nuclear Information System (INIS)

    Pinto, B; Amorim, A; Pereira, P; Elsing, M; Hawkings, R; Schieck, J; Garcia, S; Schaffer, A; Ma, H; Anjos, A

    2008-01-01

    The ATLAS experiment uses a complex trigger strategy to be able to reduce the Event Filter rate output, down to a level that allows the storage and processing of these data. These concepts are described in the ATLAS Computing Model which embraces Grid paradigm. The output coming from the Event Filter consists of four main streams: physical stream, express stream, calibration stream, and diagnostic stream. The calibration stream will be transferred to the Tier-0 facilities that will provide the prompt reconstruction of this stream with a minimum latency of 8 hours, producing calibration constants of sufficient quality to allow a first-pass processing. The Inner Detector community is developing and testing an independent common calibration stream selected at the Event Filter after track reconstruction. It is composed of raw data, in byte-stream format, contained in Readout Buffers (ROBs) with hit information of the selected tracks, and it will be used to derive and update a set of calibration and alignment constants. This option was selected because it makes use of the Byte Stream Converter infrastructure and possibly gives better bandwidth usage and storage optimization. Processing is done using specialized algorithms running in the Athena framework in dedicated Tier-0 resources, and the alignment constants will be stored and distributed using the COOL conditions database infrastructure. This work is addressing in particular the alignment requirements, the needs for track and hit selection, and the performance issues

  15. Alignment data stream for the ATLAS inner detector

    International Nuclear Information System (INIS)

    Pinto, B

    2010-01-01

    The ATLAS experiment uses a complex trigger strategy to be able to achieve the necessary Event Filter rate output, making possible to optimize the storage and processing needs of these data. These needs are described in the ATLAS Computing Model, which embraces Grid concepts. The output coming from the Event Filter will consist of three main streams: a primary stream, the express stream and the calibration stream. The calibration stream will be transferred to the Tier-0 facilities which will allow the prompt reconstruction of this stream with an admissible latency of 8 hours, producing calibration constants of sufficient quality to permit a first-pass processing. An independent calibration stream is developed and tested, which selects tracks at the level-2 trigger (LVL2) after the reconstruction. The stream is composed of raw data, in byte-stream format, and contains only information of the relevant parts of the detector, in particular the hit information of the selected tracks. This leads to a significantly improved bandwidth usage and storage capability. The stream will be used to derive and update the calibration and alignment constants if necessary every 24h. Processing is done using specialized algorithms running in Athena framework in dedicated Tier-0 resources, and the alignment constants will be stored and distributed using the COOL conditions database infrastructure. The work is addressing in particular the alignment requirements, the needs for track and hit selection, timing and bandwidth issues.

  16. Ambient groundwater flow diminishes nitrogen cycling in streams

    Science.gov (United States)

    Azizian, M.; Grant, S. B.; Rippy, M.; Detwiler, R. L.; Boano, F.; Cook, P. L. M.

    2017-12-01

    Modeling and experimental studies demonstrate that ambient groundwater reduces hyporheic exchange, but the implications of this observation for stream N-cycling is not yet clear. We utilized a simple process-based model (the Pumping and Streamline Segregation or PASS model) to evaluate N- cycling over two scales of hyporheic exchange (fluvial ripples and riffle-pool sequences), ten ambient groundwater and stream flow scenarios (five gaining and losing conditions and two stream discharges), and three biogeochemical settings (identified based on a principal component analysis of previously published measurements in streams throughout the United States). Model-data comparisons indicate that our model provides realistic estimates for direct denitrification of stream nitrate, but overpredicts nitrification and coupled nitrification-denitrification. Riffle-pool sequences are responsible for most of the N-processing, despite the fact that fluvial ripples generate 3-11 times more hyporheic exchange flux. Across all scenarios, hyporheic exchange flux and the Damkohler Number emerge as primary controls on stream N-cycling; the former regulates trafficking of nutrients and oxygen across the sediment-water interface, while the latter quantifies the relative rates of organic carbon mineralization and advective transport in streambed sediments. Vertical groundwater flux modulates both of these master variables in ways that tend to diminish stream N-cycling. Thus, anthropogenic perturbations of ambient groundwater flows (e.g., by urbanization, agricultural activities, groundwater mining, and/or climate change) may compromise some of the key ecosystem services provided by streams.

  17. Algorithm for Compressing Time-Series Data

    Science.gov (United States)

    Hawkins, S. Edward, III; Darlington, Edward Hugo

    2012-01-01

    An algorithm based on Chebyshev polynomials effects lossy compression of time-series data or other one-dimensional data streams (e.g., spectral data) that are arranged in blocks for sequential transmission. The algorithm was developed for use in transmitting data from spacecraft scientific instruments to Earth stations. In spite of its lossy nature, the algorithm preserves the information needed for scientific analysis. The algorithm is computationally simple, yet compresses data streams by factors much greater than two. The algorithm is not restricted to spacecraft or scientific uses: it is applicable to time-series data in general. The algorithm can also be applied to general multidimensional data that have been converted to time-series data, a typical example being image data acquired by raster scanning. However, unlike most prior image-data-compression algorithms, this algorithm neither depends on nor exploits the two-dimensional spatial correlations that are generally present in images. In order to understand the essence of this compression algorithm, it is necessary to understand that the net effect of this algorithm and the associated decompression algorithm is to approximate the original stream of data as a sequence of finite series of Chebyshev polynomials. For the purpose of this algorithm, a block of data or interval of time for which a Chebyshev polynomial series is fitted to the original data is denoted a fitting interval. Chebyshev approximation has two properties that make it particularly effective for compressing serial data streams with minimal loss of scientific information: The errors associated with a Chebyshev approximation are nearly uniformly distributed over the fitting interval (this is known in the art as the "equal error property"); and the maximum deviations of the fitted Chebyshev polynomial from the original data have the smallest possible values (this is known in the art as the "min-max property").

  18. Uranium mining

    International Nuclear Information System (INIS)

    Cheeseman, E.W.

    1980-01-01

    The international uranium market appears to be currently over-supplied with a resultant softening in prices. Buyers on the international market are unhappy about some of the restrictions placed on sales by the government, and Canadian sales may suffer as a result. About 64 percent of Canada's shipments come from five operating Ontario mines, with the balance from Saskatchewan. Several other properties will be producing within the next few years. In spite of the adverse effects of the Three Mile Island incident and the default by the T.V.A. of their contract, some 3 600 tonnes of new uranium sales were completed during the year. The price for uranium had stabilized at US $42 - $44 by mid 1979, but by early 1980 had softened somewhat. The year 1979 saw the completion of major environmental hearings in Ontario and Newfoundland and the start of the B.C. inquiry. Two more hearings are scheduled for Saskatchewan in 1980. The Elliot Lake uranium mining expansion hearings are reviewed, as are other recent hearings. In the production of uranium for nuclear fuel cycle, environmental matters are of major concern to the industry, the public and to governments. Research is being conducted to determine the most effective method for removing radium from tailings area effluents. Very stringent criteria are being drawn up by the regulatory agencies that must be met by the industry in order to obtain an operating licence from the AECB. These criteria cover seepages from the tailings basin and through the tailings retention dam, seismic stability, and both short and long term management of the tailings waste management area. (auth)

  19. Asteroid/meteorite streams

    Science.gov (United States)

    Drummond, J.

    The independent discovery of the same three streams (named alpha, beta, and gamma) among 139 Earth approaching asteroids and among 89 meteorite producing fireballs presents the possibility of matching specific meteorites to specific asteroids, or at least to asteroids in the same stream and, therefore, presumably of the same composition. Although perhaps of limited practical value, the three meteorites with known orbits are all ordinary chondrites. To identify, in general, the taxonomic type of the parent asteroid, however, would be of great scientific interest since these most abundant meteorite types cannot be unambiguously spectrally matched to an asteroid type. The H5 Pribram meteorite and asteroid 4486 (unclassified) are not part of a stream, but travel in fairly similar orbits. The LL5 Innisfree meteorite is orbitally similar to asteroid 1989DA (unclassified), and both are members of a fourth stream (delta) defined by five meteorite-dropping fireballs and this one asteroid. The H5 Lost City meteorite is orbitally similar to 1980AA (S type), which is a member of stream gamma defined by four asteroids and four fireballs. Another asteroid in this stream is classified as an S type, another is QU, and the fourth is unclassified. This stream suggests that ordinary chondrites should be associated with S (and/or Q) asteroids. Two of the known four V type asteroids belong to another stream, beta, defined by five asteroids and four meteorite-dropping (but unrecovered) fireballs, making it the most probable source of the eucrites. The final stream, alpha, defined by five asteroids and three fireballs is of unknown composition since no meteorites have been recovered and only one asteroid has an ambiguous classification of QRS. If this stream, or any other as yet undiscovered ones, were found to be composed of a more practical material (e.g., water or metalrich), then recovery of the associated meteorites would provide an opportunity for in-hand analysis of a potential

  20. An environmental evaluation of the effects of the Eldor Mines

    International Nuclear Information System (INIS)

    1985-11-01

    In 1968, Gulf Minerals Ltd. discovered uranium mineralization around a small body of water referred to as Rabbit Lake. Subsequent drilling at the site discovered sufficient uranium to justify development, and by 1974 the mining and milling processes were in operation and routine monitoring of the release of effluents to Wollaston Lake began, and has been carried out since. Collins, Pow and Hidden Bays of Wollaston Lake are adjacent to the uranium mining operations and the latter two have received drainage and treated process waters. In addition to the Umpherville River, 13 smaller streams of various sizes enter Hidden Bay. Of these, the small stream draining Park's Lake is affected, to a small degree, by the mining operation, while the second stream draining the tailings management area is affected to a significant degree by the facility. With the exception of those discharges to the Pow Bay watershed, virtually all of the mine water, process water and site runoff that may be potentially contaminated by the mining and milling operation is discharged after treatment and routine monitoring to Hidden Bay, the location of Hidden Bay Lodge which is the closest permanent population to the mine site. For these reasons, data from Hidden Bay were reviewed in detail. Both monitoring data and present and future site plans would suggest that if any environmental concerns were to raise related to water discharges, Hidden Bay would be the first place where they would become apparent

  1. Kiruna research mine

    Energy Technology Data Exchange (ETDEWEB)

    Oestensen, A

    1983-12-01

    The research mine at Kiruna is the first large-scale mining research project sponsored by the Swedish government. Under the leadership of the Swedish Mining Research Foundation, a five-year project involving development of new mining systems and machinery will be carried out in cooperation with the Lulea Institute of Technology and a number of Swedish industrial companies.

  2. 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

  3. 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

  4. Surface-water and groundwater interactions in an extensively mined watershed, upper Schuylkill River, Pennsylvania, USA

    Science.gov (United States)

    Cravotta,, Charles A.; Goode, Daniel J.; Bartles, Michael D.; Risser, Dennis W.; Galeone, Daniel G.

    2014-01-01

    Streams crossing underground coal mines may lose flow, while abandoned mine drainage (AMD) restores flow downstream. During 2005-12, discharge from the Pine Knot Mine Tunnel, the largest AMD source in the upper Schuylkill River Basin, had near-neutral pH and elevated concentrations of iron, manganese, and sulfate. Discharge from the tunnel responded rapidly to recharge but exhibited a prolonged recession compared to nearby streams, consistent with rapid infiltration and slow release of groundwater from the mine. Downstream of the AMD, dissolved iron was attenuated by oxidation and precipitation while dissolved CO2 degassed and pH increased. During high-flow conditions, the AMD and downstream waters exhibited decreased pH, iron, and sulfate with increased acidity that were modeled by mixing net-alkaline AMD with recharge or runoff having low ionic strength and low pH. Attenuation of dissolved iron within the river was least effective during high-flow conditions because of decreased transport time coupled with inhibitory effects of low pH on oxidation kinetics. A numerical model of groundwater flow was calibrated using groundwater levels in the Pine Knot Mine and discharge data for the Pine Knot Mine Tunnel and the West Branch Schuylkill River during a snowmelt event in January 2012. Although the calibrated model indicated substantial recharge to the mine complex took place away from streams, simulation of rapid changes in mine pool level and tunnel discharge during a high flow event in May 2012 required a source of direct recharge to the Pine Knot Mine. Such recharge produced small changes in mine pool level and rapid changes in tunnel flow rate because of extensive unsaturated storage capacity and high transmissivity within the mine complex. Thus, elimination of stream leakage could have a small effect on the annual discharge from the tunnel, but a large effect on peak discharge and associated water quality in streams.

  5. Percent Forest Adjacent to Streams

    Data.gov (United States)

    U.S. Environmental Protection Agency — The type of vegetation along a stream influences the water quality in the stream. Intact buffer strips of natural vegetation along streams tend to intercept...

  6. Percent Agriculture Adjacent to Streams

    Data.gov (United States)

    U.S. Environmental Protection Agency — The type of vegetation along a stream influences the water quality in the stream. Intact buffer strips of natural vegetation along streams tend to intercept...

  7. 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.

  8. Streaming Multiframe Deconvolutions on GPUs

    Science.gov (United States)

    Lee, M. A.; Budavári, T.

    2015-09-01

    Atmospheric turbulence distorts all ground-based observations, which is especially detrimental to faint detections. The point spread function (PSF) defining this blur is unknown for each exposure and varies significantly over time, making image analysis difficult. Lucky imaging and traditional co-adding throws away lots of information. We developed blind deconvolution algorithms that can simultaneously obtain robust solutions for the background image and all the PSFs. It is done in a streaming setting, which makes it practical for large number of big images. We implemented a new tool that runs of GPUs and achieves exceptional running times that can scale to the new time-domain surveys. Our code can quickly and effectively recover high-resolution images exceeding the quality of traditional co-adds. We demonstrate the power of the method on the repeated exposures in the Sloan Digital Sky Survey's Stripe 82.

  9. Effect Of Imposed Anaerobic Conditions On Metals Release From Acid-Mine Drainage Contaminated Streambed Sediments

    Science.gov (United States)

    Remediation of streams influenced by mine-drainage may require removal and burial of metal-containing bed sediments. Burial of aerobic sediments into an anaerobic environment may release metals, such as through reductive dissolution of metal oxyhydroxides. Mining-impacted aerob...

  10. Appalachian Stream Mitigation Workshop

    Science.gov (United States)

    A 5 day workshop in 2011 developed for state and federal regulatory and resource agencies, who review, comment on and/or approve compensatory mitigation plans for surface coal mining projects in Appalachia

  11. 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

  12. Innovative use of a mist eliminator in mine ventilation

    International Nuclear Information System (INIS)

    Boyko, K.; Smith, T.

    2010-01-01

    The McArthur River Operation recently installed an upcast mine ventilation system to increase its total mine ventilation capacity. During commissioning, the amount of water discharged by the new system exceeded that which is normally observed in similar installations. Operation of the system was suspended, and a study was conducted to determine to most effective technology to significantly reduce or remove this water from the saturated air stream. A chevron-type mist eliminator was designed and installed to strip the water from the air, such that the condensate could be appropriately managed in the mine effluent treatment system. (author)

  13. UST-IDRC national symposium on the mining industry and the environment: programme and abstracts

    International Nuclear Information System (INIS)

    1997-04-01

    The National Symposium on the mining industry and the environment was organized by the UST/IDRC Environmental Research Group in the Department of Chemistry of the University of Science and Technology, Kumasi, Ghana. The symposium generally covered strategies for the development of the mining industry as well as solutions to the environmental problems associated with the industry in Ghana. The publication contains the programme and abstracts of scientific sessions of the Symposium. The abstracts covered the following topics among others: multi-element analysis of mineral ores samples, review of environmental studies related to gold mining in Ghana, local sulphooxidizing bacteria for environmentally friendly gold mining, arsenic pollution in streams and sediments, rainfall erositivity and soil loss from degraded lands and mine spoils, the impact of surface mining on forest structure and environment, current environmental practices in the mining industry, and the role of the mining industry in the economy of Ghana

  14. A Streaming Language Implementation of the Discontinuous Galerkin Method

    Science.gov (United States)

    Barth, Timothy; Knight, Timothy

    2005-01-01

    We present a Brook streaming language implementation of the 3-D discontinuous Galerkin method for compressible fluid flow on tetrahedral meshes. Efficient implementation of the discontinuous Galerkin method using the streaming model of computation introduces several algorithmic design challenges. Using a cycle-accurate simulator, performance characteristics have been obtained for the Stanford Merrimac stream processor. The current Merrimac design achieves 128 Gflops per chip and the desktop board is populated with 16 chips yielding a peak performance of 2 Teraflops. Total parts cost for the desktop board is less than $20K. Current cycle-accurate simulations for discretizations of the 3-D compressible flow equations yield approximately 40-50% of the peak performance of the Merrimac streaming processor chip. Ongoing work includes the assessment of the performance of the same algorithm on the 2 Teraflop desktop board with a target goal of achieving 1 Teraflop performance.

  15. Wadeable Streams Assessment Data

    Science.gov (United States)

    The Wadeable Streams Assessment (WSA) is a first-ever statistically-valid survey of the biological condition of small streams throughout the U.S. The U.S. Environmental Protection Agency (EPA) worked with the states to conduct the assessment in 2004-2005. Data for each parameter sampled in the Wadeable Streams Assessment (WSA) are available for downloading in a series of files as comma separated values (*.csv). Each *.csv data file has a companion text file (*.txt) that lists a dataset label and individual descriptions for each variable. Users should view the *.txt files first to help guide their understanding and use of the data.

  16. Advanced land mine detection using a synthesis of conventional technologies

    International Nuclear Information System (INIS)

    Rappaport, C.M.

    1998-01-01

    A team at Northeastern University develops and optimizes land mine detection based on ground-penetrating radar, infrared thermography, electromagnetic induction (EM), and high frequency acoustic sensors. It implements sophisticated, physics-based mathematical models to describe the interaction of EM or acoustic waves with mines buried in realistic (electromagnetically loose, inhomogeneous) soil and as a result develops signal processing algorithms to identify and classify mines. These mathematical models are derived from actual soil and land mine measurements, and include detection statistics of the sensors. The novel aspects of Northeastern University's approach are: (1) to combine multiple sensors synergistically, yielding more information than would be available to any single sencor technology operating alone, and (2) to use signal-processing algorithms derived from physics-based models which take into account the actual sensor parameters as well as material and electrical characteristics of the soil and land mines

  17. Performance of the air2stream model that relates air and stream water temperatures depends on the calibration method

    Science.gov (United States)

    Piotrowski, Adam P.; Napiorkowski, Jaroslaw J.

    2018-06-01

    A number of physical or data-driven models have been proposed to evaluate stream water temperatures based on hydrological and meteorological observations. However, physical models require a large amount of information that is frequently unavailable, while data-based models ignore the physical processes. Recently the air2stream model has been proposed as an intermediate alternative that is based on physical heat budget processes, but it is so simplified that the model may be applied like data-driven ones. However, the price for simplicity is the need to calibrate eight parameters that, although have some physical meaning, cannot be measured or evaluated a priori. As a result, applicability and performance of the air2stream model for a particular stream relies on the efficiency of the calibration method. The original air2stream model uses an inefficient 20-year old approach called Particle Swarm Optimization with inertia weight. This study aims at finding an effective and robust calibration method for the air2stream model. Twelve different optimization algorithms are examined on six different streams from northern USA (states of Washington, Oregon and New York), Poland and Switzerland, located in both high mountains, hilly and lowland areas. It is found that the performance of the air2stream model depends significantly on the calibration method. Two algorithms lead to the best results for each considered stream. The air2stream model, calibrated with the chosen optimization methods, performs favorably against classical streamwater temperature models. The MATLAB code of the air2stream model and the chosen calibration procedure (CoBiDE) are available as Supplementary Material on the Journal of Hydrology web page.

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

    Science.gov (United States)

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

    2017-10-01

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

  19. Statistically significant relational data mining :

    Energy Technology Data Exchange (ETDEWEB)

    Berry, Jonathan W.; Leung, Vitus Joseph; Phillips, Cynthia Ann; Pinar, Ali; Robinson, David Gerald; Berger-Wolf, Tanya; Bhowmick, Sanjukta; Casleton, Emily; Kaiser, Mark; Nordman, Daniel J.; Wilson, Alyson G.

    2014-02-01

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

  20. Impacts of groundwater metal loads from bedrock fractures on water quality of a mountain stream.

    Science.gov (United States)

    Caruso, Brian S; Dawson, Helen E

    2009-06-01

    Acid mine drainage and metal loads from hardrock mines to surface waters is a significant problem in the western USA and many parts of the world. Mines often occur in mountain environments with fractured bedrock aquifers that serve as pathways for metals transport to streams. This study evaluates impacts from current and potential future groundwater metal (Cd, Cu, and Zn) loads from fractures underlying the Gilt Edge Mine, South Dakota, on concentrations in Strawberry Creek using existing flow and water quality data and simple mixing/dilution mass balance models. Results showed that metal loads from bedrock fractures to the creek currently contribute water quality is achieved upstream in Strawberry Creek, fracture metal loads would be water quality standards exceedances once groundwater with elevated metals concentrations in the aquifer matrix migrates to the fractures and discharges to the stream. Potential future metal loads from an upstream fracture would contribute a small proportion of the total load relative to current loads in the stream. Cd has the highest stream concentrations relative to standards. Even if all stream water was treated to remove 90% of the Cd, the standard would still not be achieved. At a fracture farther downstream, the Cd standard can only be met if the upstream water is treated achieving a 90% reduction in Cd concentrations and the median stream flow is maintained.

  1. PGG: An Online Pattern Based Approach for Stream Variation Management

    Institute of Scientific and Technical Information of China (English)

    Lu-An Tang; Bin Cui; Hong-Yan Li; Gao-Shan Miao; Dong-Qing Yang; Xin-Biao Zhou

    2008-01-01

    Many database applications require efficient processing of data streams with value variations and fiuctuant sampling frequency. The variations typically imply fundamental features of the stream and important domain knowledge of underlying objects. In some data streams, successive events seem to recur in a certain time interval, but the data indeed evolves with tiny differences as time elapses. This feature, so called pseudo periodicity, poses a new challenge to stream variation management. This study focuses on the online management for variations over such streams. The idea can be applied to many scenarios such as patient vital signal monitoring in medical applications. This paper proposes a new method named Pattern Growth Graph (PGG) to detect and manage variations over evolving streams with following features: 1) adopts the wave-pattern to capture the major information of data evolution and represent them compactly;2) detects the variations in a single pass over the stream with the help of wave-pattern matching algorithm; 3) only stores different segments of the pattern for incoming stream, and hence substantially compresses the data without losing important information; 4) distinguishes meaningful data changes from noise and reconstructs the stream with acceptable accuracy.Extensive experiments on real datasets containing millions of data items, as well as a prototype system, are carried out to demonstrate the feasibility and effectiveness of the proposed scheme.

  2. Future Roads Near Streams

    Data.gov (United States)

    U.S. Environmental Protection Agency — Roads are a source of auto related pollutants (e.g. gasoline, oil and other engine fluids). When roads are near streams, rain can wash these pollutants directly into...

  3. Channelized Streams in Iowa

    Data.gov (United States)

    Iowa State University GIS Support and Research Facility — This draft dataset consists of all ditches or channelized pieces of stream that could be identified using three input datasets; namely the1:24,000 National...

  4. Stochastic ice stream dynamics.

    Science.gov (United States)

    Mantelli, Elisa; Bertagni, Matteo Bernard; Ridolfi, Luca

    2016-08-09

    Ice streams are narrow corridors of fast-flowing ice that constitute the arterial drainage network of ice sheets. Therefore, changes in ice stream flow are key to understanding paleoclimate, sea level changes, and rapid disintegration of ice sheets during deglaciation. The dynamics of ice flow are tightly coupled to the climate system through atmospheric temperature and snow recharge, which are known exhibit stochastic variability. Here we focus on the interplay between stochastic climate forcing and ice stream temporal dynamics. Our work demonstrates that realistic climate fluctuations are able to (i) induce the coexistence of dynamic behaviors that would be incompatible in a purely deterministic system and (ii) drive ice stream flow away from the regime expected in a steady climate. We conclude that environmental noise appears to be crucial to interpreting the past behavior of ice sheets, as well as to predicting their future evolution.

  5. Roads Near Streams

    Data.gov (United States)

    U.S. Environmental Protection Agency — Roads are a source of auto related pollutants (e.g. gasoline, oil and other engine fluids). When roads are near streams, rain can wash these pollutants directly into...

  6. Streaming tearing mode

    Science.gov (United States)

    Shigeta, M.; Sato, T.; Dasgupta, B.

    1985-01-01

    The magnetohydrodynamic stability of streaming tearing mode is investigated numerically. A bulk plasma flow parallel to the antiparallel magnetic field lines and localized in the neutral sheet excites a streaming tearing mode more strongly than the usual tearing mode, particularly for the wavelength of the order of the neutral sheet width (or smaller), which is stable for the usual tearing mode. Interestingly, examination of the eigenfunctions of the velocity perturbation and the magnetic field perturbation indicates that the streaming tearing mode carries more energy in terms of the kinetic energy rather than the magnetic energy. This suggests that the streaming tearing mode instability can be a more feasible mechanism of plasma acceleration than the usual tearing mode instability.

  7. DNR 24K Streams

    Data.gov (United States)

    Minnesota Department of Natural Resources — 1:24,000 scale streams captured from USGS seven and one-half minute quadrangle maps, with perennial vs. intermittent classification, and connectivity through lakes,...

  8. Trout Stream Special Regulations

    Data.gov (United States)

    Minnesota Department of Natural Resources — This layer shows Minnesota trout streams that have a special regulation as described in the 2006 Minnesota Fishing Regulations. Road crossings were determined using...

  9. Scientific stream pollution analysis

    National Research Council Canada - National Science Library

    Nemerow, Nelson Leonard

    1974-01-01

    A comprehensive description of the analysis of water pollution that presents a careful balance of the biological,hydrological, chemical and mathematical concepts involved in the evaluation of stream...

  10. Methylation of Hg downstream from the Bonanza Hg mine, Oregon

    Science.gov (United States)

    Gray, John E.; Hines, Mark E.; Krabbenhoft, David P.; Thoms, Bryn

    2012-01-01

    Speciation of Hg and conversion to methyl-Hg were evaluated in stream sediment, stream water, and aquatic snails collected downstream from the Bonanza Hg mine, Oregon. Total production from the Bonanza mine was >1360t of Hg, during mining from the late 1800s to 1960, ranking it as an intermediate sized Hg mine on an international scale. The primary objective of this study was to evaluate the distribution, transport, and methylation of Hg downstream from a Hg mine in a coastal temperate climatic zone. Data shown here for methyl-Hg, a neurotoxin hazardous to humans, are the first reported for sediment and water from this area. Stream sediment collected from Foster Creek flowing downstream from the Bonanza mine contained elevated Hg concentrations that ranged from 590 to 71,000ng/g, all of which (except the most distal sample) exceeded the probable effect concentration (PEC) of 1060ng/g, the Hg concentration above which harmful effects are likely to be observed in sediment-dwelling organisms. Concentrations of methyl-Hg in stream sediment collected from Foster Creek varied from 11 to 62ng/g and were highly elevated compared to regional baseline concentrations (0.11-0.82ng/g) established in this study. Methyl-Hg concentrations in stream sediment collected in this study showed a significant correlation with total organic C (TOC, R2=0.62), generally indicating increased methyl-Hg formation with increasing TOC in sediment. Isotopic-tracer methods indicated that several samples of Foster Creek sediment exhibited high rates of Hg-methylation. Concentrations of Hg in water collected downstream from the mine varied from 17 to 270ng/L and were also elevated compared to baselines, but all were below the 770ng/L Hg standard recommended by the USEPA to protect against chronic effects to aquatic wildlife. Concentrations of methyl-Hg in the water collected from Foster Creek ranged from 0.17 to 1.8ng/L, which were elevated compared to regional baseline sites upstream and downstream

  11. Mining with communities

    International Nuclear Information System (INIS)

    Veiga, Marcello M.; Scoble, Malcolm; McAllister, Mary Louise

    2001-01-01

    To be considered as sustainable, a mining community needs to adhere to the principles of ecological sustainability, economic vitality and social equity. These principles apply over a long time span, covering both the life of the mine and post-mining closure. The legacy left by a mine to the community after its closure is emerging as a significant aspect of its planning. Progress towards sustainability is made when value is added to a community with respect to these principles by the mining operation during its life cycle. This article presents a series of cases to demonstrate the diverse potential challenges to achieving a sustainable mining community. These case studies of both new and old mining communities are drawn mainly from Canada and from locations abroad where Canadian companies are now building mines. The article concludes by considering various approaches that can foster sustainable mining communities and the role of community consultation and capacity building. (author)

  12. The current environmental impact of base-metal mining at the Tui Mine, Te Aroha, New Zealand

    International Nuclear Information System (INIS)

    Sabti, H.; Hossain, M.M.; Brooks, R.R.; Stewart, R.B.

    2000-01-01

    The current environmental impact of base metal mining at the Tui Mine, Te Aroha and gold mining near Waihi, was investigated by analysis of local waters, stream sediments and aquatic vegetation. X-ray diffraction analysis of heavy metal fractions in stream sediments showed the presence of pyrite in the upper reaches of the Tunakohoia and Tui streams that drain the mineralised reefs and Tui tailings dam. Relatively immobile lead (galena) was retained close to the source, whereas copper and zinc minerals were more mobile and distributed further downstream from the areas of mineralisation. Gold was determined in sediments from the Ohinemuri and Waitekauri Rivers along with other heavy metals derived from sulphide mineralisation at Waihi and Waitekauri. Analysis of waters from the Tui and Tunakohoia streams showed concentrations of arsenic, cadmium, lead and zinc above recommended levels for potable water in the upper parts of these waterways. The discharge of these streams into the Waihou River (sampled upstream from Te Aroha and downstream past Paeroa) did not have any significant effect on heavy-metal concentrations in this river. Aquatic macrophytes sampled in the Waihou, Ohinemuri and Waitekauri Rivers had very high heavy-metal concentrations compared with the ambient water and should be considered as potentially useful for assessing the impact of low-metal fluxes into the waters. Gold was detected in aquatic marcophytes from streams draining both the Martha Mine at Waihi and the Golden Cross Mine at Waitekauri and indicated the possibility of prospecting for gold by analysis of these plants. (author). 17 refs., 3 figs., 6 tabs

  13. Collaborative Media Streaming

    OpenAIRE

    Kahmann, Verena

    2008-01-01

    Mit Hilfe der IP-Technologie erbrachte Multimedia-Dienste wie IPTV oder Video-on-Demand sind zur Zeit ein gefragtes Thema. Technisch werden solche Dienste unter dem Begriff "Streaming" eingeordnet. Ein Server sendet Mediendaten kontinuierlich an Empfänger, welche die Daten sofort weiterverarbeiten und anzeigen. Über einen Rückkanal hat der Kunde die Möglichkeit der Einflussnahme auf die Wiedergabe. Eine Weiterentwicklung dieser Streaming-Dienste ist die Möglichkeit, gemeinsam mit anderen dens...

  14. A Comparison of the Effects of K-Anonymity on Machine Learning Algorithms

    OpenAIRE

    Hayden Wimmer; Loreen Powell

    2014-01-01

    While research has been conducted in machine learning algorithms and in privacy preserving in data mining (PPDM), a gap in the literature exists which combines the aforementioned areas to determine how PPDM affects common machine learning algorithms. The aim of this research is to narrow this literature gap by investigating how a common PPDM algorithm, K-Anonymity, affects common machine learning and data mining algorithms, namely neural networks, logistic regression, decision trees, and Baye...

  15. Prediction and Analysis of students Behavior using BARC Algorithm

    OpenAIRE

    M.Sindhuja; Dr.S.Rajalakshmi; S.M.Nandagopal

    2013-01-01

    Educational Data mining is a recent trends where data mining methods are experimented for the improvement of student performance in academics. The work describes the mining of higher education students’ related attributes such as behavior, attitude and relationship. The data were collected from a higher education institution in terms of the mentioned attributes. The proposed work explored Behavior Attitude Relationship Clustering (BARC) Algorithm, which showed the improvement in students’ per...

  16. A framework for query optimization to support data mining

    NARCIS (Netherlands)

    S.R. Choenni (Sunil); A.P.J.M. Siebes (Arno)

    1996-01-01

    textabstractIn order to extract knowledge from databases, data mining algorithms heavily query the databases. Inefficient processing of these queries will inevitably have its impact on the performance of these algorithms, making them less valuable. In this paper, we describe an optimization

  17. Streaming Pool: reuse, combine and create reactive streams with pleasure

    CERN Multimedia

    CERN. Geneva

    2017-01-01

    When connecting together heterogeneous and complex systems, it is not easy to exchange data between components. Streams of data are successfully used in industry in order to overcome this problem, especially in the case of "live" data. Streams are a specialization of the Observer design pattern and they provide asynchronous and non-blocking data flow. The ongoing effort of the ReactiveX initiative is one example that demonstrates how demanding this technology is even for big companies. Bridging the discrepancies of different technologies with common interfaces is already done by the Reactive Streams initiative and, in the JVM world, via reactive-streams-jvm interfaces. Streaming Pool is a framework for providing and discovering reactive streams. Through the mechanism of dependency injection provided by the Spring Framework, Streaming Pool provides a so called Discovery Service. This object can discover and chain streams of data that are technologically agnostic, through the use of Stream IDs. The stream to ...

  18. Report on the laboratory examination of the effect of fungal invasion on the durability of untreated mine support timbers

    CSIR Research Space (South Africa)

    Hall, PJ

    1967-02-01

    Full Text Available stream_source_info RR 12_67 The laboratory examination of the effect of fungal invasion on the durability of untreated mine support timber COMRO 1967.pdf.txt stream_content_type text/plain stream_size 8 Content-Encoding ISO-8859...-1 stream_name RR 12_67 The laboratory examination of the effect of fungal invasion on the durability of untreated mine support timber COMRO 1967.pdf.txt Content-Type text/plain; charset=ISO-8859-1 ...

  19. A Distributed Flocking Approach for Information Stream Clustering Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Cui, Xiaohui [ORNL; Potok, Thomas E [ORNL

    2006-01-01

    Intelligence analysts are currently overwhelmed with the amount of information streams generated everyday. There is a lack of comprehensive tool that can real-time analyze the information streams. Document clustering analysis plays an important role in improving the accuracy of information retrieval. However, most clustering technologies can only be applied for analyzing the static document collection because they normally require a large amount of computation resource and long time to get accurate result. It is very difficult to cluster a dynamic changed text information streams on an individual computer. Our early research has resulted in a dynamic reactive flock clustering algorithm which can continually refine the clustering result and quickly react to the change of document contents. This character makes the algorithm suitable for cluster analyzing dynamic changed document information, such as text information stream. Because of the decentralized character of this algorithm, a distributed approach is a very natural way to increase the clustering speed of the algorithm. In this paper, we present a distributed multi-agent flocking approach for the text information stream clustering and discuss the decentralized architectures and communication schemes for load balance and status information synchronization in this approach.

  20. South African mine valuation

    Energy Technology Data Exchange (ETDEWEB)

    Storrar, C D

    1977-01-01

    This article sets out the basic concepts of mine valuation, with gold mining receiving more space than base minerals and coal. Sampling practice is given special attention. Chapter headings are methods of investigation, sampling, underground sampling, averaging of underground sampling, diamond-drill sampling, mass and mineral content of ore, organization of a sample office, working costs, mining pay limits, ore reserves, ore accounting, maintenance of grade, forecasting operations and life of mine, statistical mine valuation, state's share of profits and taxation, and financial valuation of mining ventures.