WorldWideScience

Sample records for association rule mining

  1. A Collaborative Educational Association Rule Mining Tool

    Science.gov (United States)

    Garcia, Enrique; Romero, Cristobal; Ventura, Sebastian; de Castro, Carlos

    2011-01-01

    This paper describes a collaborative educational data mining tool based on association rule mining for the ongoing improvement of e-learning courses and allowing teachers with similar course profiles to share and score the discovered information. The mining tool is oriented to be used by non-expert instructors in data mining so its internal…

  2. 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...

  3. Mining Hesitation Information by Vague Association Rules

    Science.gov (United States)

    Lu, An; Ng, Wilfred

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

  4. 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 ) .

  5. 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 ...

  6. Class association rules mining from students’ test data (Abstract)

    NARCIS (Netherlands)

    Romero, C.; Ventura, S.; Vasilyeva, E.; Pechenizkiy, M.; Baker, de R.S.J.; Merceron, A.; Pavlik Jr., P.I.

    2010-01-01

    In this paper we propose the use of a special type of association rules mining for discovering interesting relationships from the students’ test data collected in our case with Moodle learning management system (LMS). Particularly, we apply Class Association Rule (CAR) mining to different data

  7. Interestingness of association rules in data mining: Issues relevant ...

    Indian Academy of Sciences (India)

    R. Narasimhan (Krishtel eMaging) 1461 1996 Oct 15 13:05:22

    mental changes in many spheres of our daily life. .... concentrate on association rule mining since it features as one of the main data mining tech- ..... years, a lot of work has been done in defining and quantifying 'interestingness. .... a critical effect on both, selection of interesting events and variation of interestingness thresh-.

  8. 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

  9. COLLABORATIVE NETWORK SECURITY MANAGEMENT SYSTEM BASED ON ASSOCIATION MINING RULE

    Directory of Open Access Journals (Sweden)

    Nisha Mariam Varughese

    2014-07-01

    Full Text Available Security is one of the major challenges in open network. There are so many types of attacks which follow fixed patterns or frequently change their patterns. It is difficult to find the malicious attack which does not have any fixed patterns. The Distributed Denial of Service (DDoS attacks like Botnets are used to slow down the system performance. To address such problems Collaborative Network Security Management System (CNSMS is proposed along with the association mining rule. CNSMS system is consists of collaborative Unified Threat Management (UTM, cloud based security centre and traffic prober. The traffic prober captures the internet traffic and given to the collaborative UTM. Traffic is analysed by the Collaborative UTM, to determine whether it contains any malicious attack or not. If any security event occurs, it will reports to the cloud based security centre. The security centre generates security rules based on association mining rule and distributes to the network. The cloud based security centre is used to store the huge amount of tragic, their logs and the security rule generated. The feedback is evaluated and the invalid rules are eliminated to improve the system efficiency.

  10. 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.

  11. Using fuzzy association rule mining in cancer classification

    International Nuclear Information System (INIS)

    Mahmoodian, Hamid; Marhaban, M.H.; Abdulrahim, Raha; Rosli, Rozita; Saripan, Iqbal

    2011-01-01

    Full text: The classification of the cancer tumors based on gene expression profiles has been extensively studied in numbers of studies. A wide variety of cancer datasets have been implemented by the various methods of gene selec tion and classification to identify the behavior of the genes in tumors and find the relationships between them and outcome of diseases. Interpretability of the model, which is developed by fuzzy rules and linguistic variables in this study, has been rarely considered. In addition, creating a fuzzy classifier with high performance in classification that uses a subset of significant genes which have been selected by different types of gene selection methods is another goal of this study. A new algorithm has been developed to identify the fuzzy rules and significant genes based on fuzzy association rule mining. At first, different subset of genes which have been selected by different methods, were used to generate primary fuzzy classifiers separately and then proposed algorithm was implemented to mix the genes which have been associated in the primary classifiers and generate a new classifier. The results show that fuzzy classifier can classify the tumors with high performance while presenting the relationships between the genes by linguistic variables

  12. 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...

  13. RANWAR: rank-based weighted association rule mining from gene expression and methylation data.

    Science.gov (United States)

    Mallik, Saurav; Mukhopadhyay, Anirban; Maulik, Ujjwal

    2015-01-01

    Ranking of association rules is currently an interesting topic in data mining and bioinformatics. The huge number of evolved rules of items (or, genes) by association rule mining (ARM) algorithms makes confusion to the decision maker. In this article, we propose a weighted rule-mining technique (say, RANWAR or rank-based weighted association rule-mining) to rank the rules using two novel rule-interestingness measures, viz., rank-based weighted condensed support (wcs) and weighted condensed confidence (wcc) measures to bypass the problem. These measures are basically depended on the rank of items (genes). Using the rank, we assign weight to each item. RANWAR generates much less number of frequent itemsets than the state-of-the-art association rule mining algorithms. Thus, it saves time of execution of the algorithm. We run RANWAR on gene expression and methylation datasets. The genes of the top rules are biologically validated by Gene Ontologies (GOs) and KEGG pathway analyses. Many top ranked rules extracted from RANWAR that hold poor ranks in traditional Apriori, are highly biologically significant to the related diseases. Finally, the top rules evolved from RANWAR, that are not in Apriori, are reported.

  14. EOQ estimation for imperfect quality items using association rule mining with clustering

    Directory of Open Access Journals (Sweden)

    Mandeep Mittal

    2015-09-01

    Full Text Available Timely identification of newly emerging trends is needed in business process. Data mining techniques like clustering, association rule mining, classification, etc. are very important for business support and decision making. This paper presents a method for redesigning the ordering policy by including cross-selling effect. Initially, association rules are mined on the transactional database and EOQ is estimated with revenue earned. Then, transactions are clustered to obtain homogeneous clusters and association rules are mined in each cluster to estimate EOQ with revenue earned for each cluster. Further, this paper compares ordering policy for imperfect quality items which is developed by applying rules derived from apriori algorithm viz. a without clustering the transactions, and b after clustering the transactions. A numerical example is illustrated to validate the results.

  15. From Intra-transaction to Generalized Inter-transaction: Landscaping Multidimensional Contexts in Association Rule Mining

    NARCIS (Netherlands)

    Li, Q; Feng, L.; Wong, A.K.Y.

    The problem of mining multidimensional inter-transactional association rules was recently introduced in [ACM Trans. Inform. Syst. 18(4) (2000) 423; Proc. of the ACM SIGMOD Workshop on Research Issues on Data Mining and Knowledge Discovery, Seattle, Washington, June 1998, p. 12:1]. It extends the

  16. 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.

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

    Science.gov (United States)

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

    2015-11-01

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

  18. Analysis of mesenchymal stem cell differentiation in vitro using classification association rule mining.

    Science.gov (United States)

    Wang, Weiqi; Wang, Yanbo Justin; Bañares-Alcántara, René; Coenen, Frans; Cui, Zhanfeng

    2009-12-01

    In this paper, data mining is used to analyze the data on the differentiation of mammalian Mesenchymal Stem Cells (MSCs), aiming at discovering known and hidden rules governing MSC differentiation, following the establishment of a web-based public database containing experimental data on the MSC proliferation and differentiation. To this effect, a web-based public interactive database comprising the key parameters which influence the fate and destiny of mammalian MSCs has been constructed and analyzed using Classification Association Rule Mining (CARM) as a data-mining technique. The results show that the proposed approach is technically feasible and performs well with respect to the accuracy of (classification) prediction. Key rules mined from the constructed MSC database are consistent with experimental observations, indicating the validity of the method developed and the first step in the application of data mining to the study of MSCs.

  19. Association Rule Mining on Five Years of Motor Vehicle Crashes

    Directory of Open Access Journals (Sweden)

    Daher Jean Raymond

    2016-01-01

    Full Text Available Every year, road accidents kill more than a million people and injure more than 20 million worldwide. This paper aims to offer guidance on road safety and create awareness by pinpointing the major causes of traffic accidents. The study investigates motor vehicle crashes in the Genesee Finger Lakes Region of New York State. Frequency Pattern Growth algorithm is utilized to cultivate knowledge and create association rules to highlight the time and environment settings that cause the most catastrophic crashes. This knowledge can be used to warn drivers about the dangers of accidents, and how the consequences are worse given a specific context. For instance, a discovered rule from the data states that ‘most of the crashes occur between 12:00 pm and 6:00pm’; hence, it is suggested to modify existing navigation application to warn drivers about the increase in risk factor.

  20. Spatio-Temporal Rule Mining

    DEFF Research Database (Denmark)

    Gidofalvi, Gyozo; Pedersen, Torben Bach

    2005-01-01

    Recent advances in communication and information technology, such as the increasing accuracy of GPS technology and the miniaturization of wireless communication devices pave the road for Location-Based Services (LBS). To achieve high quality for such services, spatio-temporal data mining techniques...... are needed. In this paper, we describe experiences with spatio-temporal rule mining in a Danish data mining company. First, a number of real world spatio-temporal data sets are described, leading to a taxonomy of spatio-temporal data. Second, the paper describes a general methodology that transforms...... the spatio-temporal rule mining task to the traditional market basket analysis task and applies it to the described data sets, enabling traditional association rule mining methods to discover spatio-temporal rules for LBS. Finally, unique issues in spatio-temporal rule mining are identified and discussed....

  1. 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.

  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. Interesting association rule mining with consistent and inconsistent rule detection from big sales data in distributed environment

    Directory of Open Access Journals (Sweden)

    Dinesh J. Prajapati

    2017-06-01

    Full Text Available Nowadays, there is an increasing demand in mining interesting patterns from the big data. The process of analyzing such a huge amount of data is really computationally complex task when using traditional methods. The overall purpose of this paper is in twofold. First, this paper presents a novel approach to identify consistent and inconsistent association rules from sales data located in distributed environment. Secondly, the paper also overcomes the main memory bottleneck and computing time overhead of single computing system by applying computations to multi node cluster. The proposed method initially extracts frequent itemsets for each zone using existing distributed frequent pattern mining algorithms. The paper also compares the time efficiency of Mapreduce based frequent pattern mining algorithm with Count Distribution Algorithm (CDA and Fast Distributed Mining (FDM algorithms. The association generated from frequent itemsets are too large that it becomes complex to analyze it. Thus, Mapreduce based consistent and inconsistent rule detection (MR-CIRD algorithm is proposed to detect the consistent and inconsistent rules from big data and provide useful and actionable knowledge to the domain experts. These pruned interesting rules also give useful knowledge for better marketing strategy as well. The extracted consistent and inconsistent rules are evaluated and compared based on different interestingness measures presented together with experimental results that lead to the final conclusions.

  4. Object-oriented spatial-temporal association rules mining on ocean remote sensing imagery

    International Nuclear Information System (INIS)

    Xue, C J; Dong, Q; Ma, W X

    2014-01-01

    Using the long term marine remote sensing imagery, we develop an object-oriented spatial-temporal association rules mining framework to explore the association rules mining among marine environmental elements. Within the framework, two key issues are addressed. They are how to effectively deal with the related lattices and how to reduce the related dimensions? To deal with the first key issues, this paper develops an object-oriented method for abstracting marine sensitive objects from raster pixels and for representing them with a quadruple. To deal with the second key issues, by embedding the mutual information theory, we construct the direct association pattern tree to reduce the related elements at the first step, and then the Apriori algorithm is used to discover the spatio-temporal associated rules. Finally, Pacific Ocean is taken as a research area and multi- marine remote sensing imagery in recent three decades is used as a case study. The results show that the object-oriented spatio-temporal association rules mining can acquire the associated relationships not only among marine environmental elements in same region, also among the different regions. In addition, the information from association rules mining is much more expressive and informative in space and time than traditional spatio-temporal analysis

  5. 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.

  6. 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.

  7. 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.

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

    Directory of Open Access Journals (Sweden)

    Nattawat Khamphakdee

    2015-07-01

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

  9. Fuzzy OLAP association rules mining-based modular reinforcement learning approach for multiagent systems.

    Science.gov (United States)

    Kaya, Mehmet; Alhajj, Reda

    2005-04-01

    Multiagent systems and data mining have recently attracted considerable attention in the field of computing. Reinforcement learning is the most commonly used learning process for multiagent systems. However, it still has some drawbacks, including modeling other learning agents present in the domain as part of the state of the environment, and some states are experienced much less than others, or some state-action pairs are never visited during the learning phase. Further, before completing the learning process, an agent cannot exhibit a certain behavior in some states that may be experienced sufficiently. In this study, we propose a novel multiagent learning approach to handle these problems. Our approach is based on utilizing the mining process for modular cooperative learning systems. It incorporates fuzziness and online analytical processing (OLAP) based mining to effectively process the information reported by agents. First, we describe a fuzzy data cube OLAP architecture which facilitates effective storage and processing of the state information reported by agents. This way, the action of the other agent, not even in the visual environment. of the agent under consideration, can simply be predicted by extracting online association rules, a well-known data mining technique, from the constructed data cube. Second, we present a new action selection model, which is also based on association rules mining. Finally, we generalize not sufficiently experienced states, by mining multilevel association rules from the proposed fuzzy data cube. Experimental results obtained on two different versions of a well-known pursuit domain show the robustness and effectiveness of the proposed fuzzy OLAP mining based modular learning approach. Finally, we tested the scalability of the approach presented in this paper and compared it with our previous work on modular-fuzzy Q-learning and ordinary Q-learning.

  10. Association rule mining data for census tract chemical exposure analysis

    Data.gov (United States)

    U.S. Environmental Protection Agency — Chemical concentration, exposure, and health risk data for U.S. census tracts from National Scale Air Toxics Assessment (NATA). This dataset is associated with the...

  11. Privacy Preserving Association Rule Mining Revisited: Privacy Enhancement and Resources Efficiency

    Science.gov (United States)

    Mohaisen, Abedelaziz; Jho, Nam-Su; Hong, Dowon; Nyang, Daehun

    Privacy preserving association rule mining algorithms have been designed for discovering the relations between variables in data while maintaining the data privacy. In this article we revise one of the recently introduced schemes for association rule mining using fake transactions (FS). In particular, our analysis shows that the FS scheme has exhaustive storage and high computation requirements for guaranteeing a reasonable level of privacy. We introduce a realistic definition of privacy that benefits from the average case privacy and motivates the study of a weakness in the structure of FS by fake transactions filtering. In order to overcome this problem, we improve the FS scheme by presenting a hybrid scheme that considers both privacy and resources as two concurrent guidelines. Analytical and empirical results show the efficiency and applicability of our proposed scheme.

  12. 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.

  13. A Novel Method of Interestingness Measures for Association Rules Mining Based on Profit

    Directory of Open Access Journals (Sweden)

    Chunhua Ju

    2015-01-01

    Full Text Available Association rules mining is an important topic in the domain of data mining and knowledge discovering. Some papers have presented several interestingness measure methods; the most typical are Support, Confidence, Lift, Improve, and so forth. But their limitations are obvious, like no objective criterion, lack of statistical base, disability of defining negative relationship, and so forth. This paper proposes three new methods, Bi-lift, Bi-improve, and Bi-confidence, for Lift, Improve, and Confidence, respectively. Then, on the basis of utility function and the executing cost of rules, we propose interestingness function based on profit (IFBP considering subjective preferences and characteristics of specific application object. Finally, a novel measure framework is proposed to improve the traditional one through experimental analysis. In conclusion, the new methods and measure framework are prior to the traditional ones in the aspects of objective criterion, comprehensive definition, and practical application.

  14. Effect of Temporal Relationships in Associative Rule Mining for Web Log Data

    Science.gov (United States)

    Mohd Khairudin, Nazli; Mustapha, Aida

    2014-01-01

    The advent of web-based applications and services has created such diverse and voluminous web log data stored in web servers, proxy servers, client machines, or organizational databases. This paper attempts to investigate the effect of temporal attribute in relational rule mining for web log data. We incorporated the characteristics of time in the rule mining process and analysed the effect of various temporal parameters. The rules generated from temporal relational rule mining are then compared against the rules generated from the classical rule mining approach such as the Apriori and FP-Growth algorithms. The results showed that by incorporating the temporal attribute via time, the number of rules generated is subsequently smaller but is comparable in terms of quality. PMID:24587757

  15. Analysis of correlation between pediatric asthma exacerbation and exposure to pollutant mixtures with association rule mining.

    Science.gov (United States)

    Toti, Giulia; Vilalta, Ricardo; Lindner, Peggy; Lefer, Barry; Macias, Charles; Price, Daniel

    2016-11-01

    Traditional studies on effects of outdoor pollution on asthma have been criticized for questionable statistical validity and inefficacy in exploring the effects of multiple air pollutants, alone and in combination. Association rule mining (ARM), a method easily interpretable and suitable for the analysis of the effects of multiple exposures, could be of use, but the traditional interest metrics of support and confidence need to be substituted with metrics that focus on risk variations caused by different exposures. We present an ARM-based methodology that produces rules associated with relevant odds ratios and limits the number of final rules even at very low support levels (0.5%), thanks to post-pruning criteria that limit rule redundancy and control for statistical significance. The methodology has been applied to a case-crossover study to explore the effects of multiple air pollutants on risk of asthma in pediatric subjects. We identified 27 rules with interesting odds ratio among more than 10,000 having the required support. The only rule including only one chemical is exposure to ozone on the previous day of the reported asthma attack (OR=1.14). 26 combinatory rules highlight the limitations of air quality policies based on single pollutant thresholds and suggest that exposure to mixtures of chemicals is more harmful, with odds ratio as high as 1.54 (associated with the combination day0 SO 2 , day0 NO, day0 NO 2 , day1 PM). The proposed method can be used to analyze risk variations caused by single and multiple exposures. The method is reliable and requires fewer assumptions on the data than parametric approaches. Rules including more than one pollutant highlight interactions that deserve further investigation, while helping to limit the search field. Copyright © 2016 Elsevier B.V. All rights reserved.

  16. Efficient mining of association rules for the early diagnosis of Alzheimer's disease

    International Nuclear Information System (INIS)

    Chaves, R; Gorriz, J M; Ramirez, J; Illan, I A; Salas-Gonzalez, D; Gomez-RIo, M

    2011-01-01

    In this paper, a novel technique based on association rules (ARs) is presented in order to find relations among activated brain areas in single photon emission computed tomography (SPECT) imaging. In this sense, the aim of this work is to discover associations among attributes which characterize the perfusion patterns of normal subjects and to make use of them for the early diagnosis of Alzheimer's disease (AD). Firstly, voxel-as-feature-based activation estimation methods are used to find the tridimensional activated brain regions of interest (ROIs) for each patient. These ROIs serve as input to secondly mine ARs with a minimum support and confidence among activation blocks by using a set of controls. In this context, support and confidence measures are related to the proportion of functional areas which are singularly and mutually activated across the brain. Finally, we perform image classification by comparing the number of ARs verified by each subject under test to a given threshold that depends on the number of previously mined rules. Several classification experiments were carried out in order to evaluate the proposed methods using a SPECT database that consists of 41 controls (NOR) and 56 AD patients labeled by trained physicians. The proposed methods were validated by means of the leave-one-out cross validation strategy, yielding up to 94.87% classification accuracy, thus outperforming recent developed methods for computer aided diagnosis of AD.

  17. Efficient mining of association rules for the early diagnosis of Alzheimer's disease

    Science.gov (United States)

    Chaves, R.; Górriz, J. M.; Ramírez, J.; Illán, I. A.; Salas-Gonzalez, D.; Gómez-Río, M.

    2011-09-01

    In this paper, a novel technique based on association rules (ARs) is presented in order to find relations among activated brain areas in single photon emission computed tomography (SPECT) imaging. In this sense, the aim of this work is to discover associations among attributes which characterize the perfusion patterns of normal subjects and to make use of them for the early diagnosis of Alzheimer's disease (AD). Firstly, voxel-as-feature-based activation estimation methods are used to find the tridimensional activated brain regions of interest (ROIs) for each patient. These ROIs serve as input to secondly mine ARs with a minimum support and confidence among activation blocks by using a set of controls. In this context, support and confidence measures are related to the proportion of functional areas which are singularly and mutually activated across the brain. Finally, we perform image classification by comparing the number of ARs verified by each subject under test to a given threshold that depends on the number of previously mined rules. Several classification experiments were carried out in order to evaluate the proposed methods using a SPECT database that consists of 41 controls (NOR) and 56 AD patients labeled by trained physicians. The proposed methods were validated by means of the leave-one-out cross validation strategy, yielding up to 94.87% classification accuracy, thus outperforming recent developed methods for computer aided diagnosis of AD.

  18. Mining Context-Aware Association Rules Using Grammar-Based Genetic Programming.

    Science.gov (United States)

    Luna, Jose Maria; Pechenizkiy, Mykola; Del Jesus, Maria Jose; Ventura, Sebastian

    2017-09-25

    Real-world data usually comprise features whose interpretation depends on some contextual information. Such contextual-sensitive features and patterns are of high interest to be discovered and analyzed in order to obtain the right meaning. This paper formulates the problem of mining context-aware association rules, which refers to the search for associations between itemsets such that the strength of their implication depends on a contextual feature. For the discovery of this type of associations, a model that restricts the search space and includes syntax constraints by means of a grammar-based genetic programming methodology is proposed. Grammars can be considered as a useful way of introducing subjective knowledge to the pattern mining process as they are highly related to the background knowledge of the user. The performance and usefulness of the proposed approach is examined by considering synthetically generated datasets. A posteriori analysis on different domains is also carried out to demonstrate the utility of this kind of associations. For example, in educational domains, it is essential to identify and understand contextual and context-sensitive factors that affect overall and individual student behavior and performance. The results of the experiments suggest that the approach is feasible and it automatically identifies interesting context-aware associations from real-world datasets.

  19. A Stock Trading Recommender System Based on Temporal Association Rule Mining

    Directory of Open Access Journals (Sweden)

    Binoy B. Nair

    2015-04-01

    Full Text Available Recommender systems capable of discovering patterns in stock price movements and generating stock recommendations based on the patterns thus discovered can significantly supplement the decision-making process of a stock trader. Such recommender systems are of great significance to a layperson who wishes to profit by stock trading even while not possessing the skill or expertise of a seasoned trader. A genetic algorithm optimized Symbolic Aggregate approXimation (SAX–Apriori based stock trading recommender system, which can mine temporal association rules from the stock price data set to generate stock trading recommendations, is presented in this article. The proposed system is validated on 12 different data sets. The results indicate that the proposed system significantly outperforms the passive buy-and-hold strategy, offering scope for a layperson to successfully invest in capital markets.

  20. Leveraging Bibliographic RDF Data for Keyword Prediction with Association Rule Mining (ARM

    Directory of Open Access Journals (Sweden)

    Nidhi Kushwaha

    2014-11-01

    Full Text Available The Semantic Web (Web 3.0 has been proposed as an efficient way to access the increasingly large amounts of data on the internet. The Linked Open Data Cloud project at present is the major effort to implement the concepts of the Seamtic Web, addressing the problems of inhomogeneity and large data volumes. RKBExplorer is one of many repositories implementing Open Data and contains considerable bibliographic information. This paper discusses bibliographic data, an important part of cloud data. Effective searching of bibiographic datasets can be a challenge as many of the papers residing in these databases do not have sufficient or comprehensive keyword information. In these cases however, a search engine based on RKBExplorer is only able to use information to retrieve papers based on author names and title of papers without keywords. In this paper we attempt to address this problem by using the data mining algorithm Association Rule Mining (ARM to develop keywords based on features retrieved from Resource Description Framework (RDF data within a bibliographic citation. We have demonstrate the applicability of this method for predicting missing keywords for bibliographic entries in several typical databases. −−−−− Paper presented at 1st International Symposium on Big Data and Cloud Computing Challenges (ISBCC-2014 March 27-28, 2014. Organized by VIT University, Chennai, India. Sponsored by BRNS.

  1. An association rule mining-based framework for understanding lifestyle risk behaviors.

    Directory of Open Access Journals (Sweden)

    So Hyun Park

    Full Text Available OBJECTIVES: This study investigated the prevalence and patterns of lifestyle risk behaviors in Korean adults. METHODS: We utilized data from the Fourth Korea National Health and Nutrition Examination Survey for 14,833 adults (>20 years of age. We used association rule mining to analyze patterns of lifestyle risk behaviors by characterizing non-adherence to public health recommendations related to the Alameda 7 health behaviors. The study variables were current smoking, heavy drinking, physical inactivity, obesity, inadequate sleep, breakfast skipping, and frequent snacking. RESULTS: Approximately 72% of Korean adults exhibited two or more lifestyle risk behaviors. Among women, current smoking, obesity, and breakfast skipping were associated with inadequate sleep. Among men, breakfast skipping with additional risk behaviors such as physical inactivity, obesity, and inadequate sleep was associated with current smoking. Current smoking with additional risk behaviors such as inadequate sleep or breakfast skipping was associated with physical inactivity. CONCLUSION: Lifestyle risk behaviors are intercorrelated in Korea. Information on patterns of lifestyle risk behaviors could assist in planning interventions targeted at multiple behaviors simultaneously.

  2. The Usage of Association Rule Mining to Identify Influencing Factors on Deafness After Birth.

    Science.gov (United States)

    Shahraki, Azimeh Danesh; Safdari, Reza; Gahfarokhi, Hamid Habibi; Tahmasebian, Shahram

    2015-12-01

    Providing complete and high quality health care services has very important role to enable people to understand the factors related to personal and social health and to make decision regarding choice of suitable healthy behaviors in order to achieve healthy life. For this reason, demographic and clinical data of person are collecting, this huge volume of data can be known as a valuable resource for analyzing, exploring and discovering valuable information and communication. This study using forum rules techniques in the data mining has tried to identify the affecting factors on hearing loss after birth in Iran. The survey is kind of data oriented study. The population of the study is contained questionnaires in several provinces of the country. First, all data of questionnaire was implemented in the form of information table in Software SQL Server and followed by Data Entry using written software of C # .Net, then algorithm Association in SQL Server Data Tools software and Clementine software was implemented to determine the rules and hidden patterns in the gathered data. Two factors of number of deaf brothers and the degree of consanguinity of the parents have a significant impact on severity of deafness of individuals. Also, when the severity of hearing loss is greater than or equal to moderately severe hearing loss, people use hearing aids and Men are also less interested in the use of hearing aids. In fact, it can be said that in families with consanguineous marriage of parents that are from first degree (girl/boy cousins) and 2(nd) degree relatives (girl/boy cousins) and especially from first degree, the number of people with severe hearing loss or deafness are more and in the use of hearing aids, gender of the patient is more important than the severity of the hearing loss.

  3. Quality prediction modeling for multistage manufacturing based on classification and association rule mining

    Directory of Open Access Journals (Sweden)

    Kao Hung-An

    2017-01-01

    Full Text Available For manufacturing enterprises, product quality is a key factor to assess production capability and increase their core competence. To reduce external failure cost, many research and methodology have been introduced in order to improve process yield rate, such as TQC/TQM, Shewhart CycleDeming's 14 Points, etc. Nowadays, impressive progress has been made in process monitoring and industrial data analysis because of the Industry 4.0 trend. Industries start to utilize quality control (QC methodology to lower inspection overhead and internal failure cost. Currently, the focus of QC is mostly in the inspection of single workstation and final product, however, for multistage manufacturing, many factors (like equipment, operators, parameters, etc. can have cumulative and interactive effects to the final quality. When failure occurs, it is difficult to resume the original settings for cause analysis. To address these problems, this research proposes a combination of principal components analysis (PCA with classification and association rule mining algorithms to extract features representing relationship of multiple workstations, predict final product quality, and analyze the root-cause of product defect. The method is demonstrated on a semiconductor data set.

  4. 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...

  5. Olap and data mining technologies' integration in the construction of interdimensional associative rules in multidimensional data

    Directory of Open Access Journals (Sweden)

    Микола Тихонович Фісун

    2015-06-01

    Full Text Available The features of associative rules in multidimensional data searching are presented in the article, specifically theoretical basis of association searching between different dimensions in OLAP cubes and formulas of their significance characteristics (support, confidence, lift, leverage calculation are shown. The method of interdimensional association rules generation is proposed. The implementation of this method as a component of operative and intellectual data analysis information system on database management system Caché platform is described.

  6. Decision Mining Revisited – Discovering Overlapping Rules

    NARCIS (Netherlands)

    Mannhardt, F.; de Leoni, M.; Reijers, H.A.; van der Aalst, W.M.P.

    2016-01-01

    Decision mining enriches process models with rules underlying decisions in processes using historical process execution data. Choices between multiple activities are specified through rules defined over process data. Existing decision mining methods focus on discovering mutually-exclusive rules,

  7. Decision Mining Revisited - Discovering Overlapping Rules

    NARCIS (Netherlands)

    Mannhardt, F.; De Leoni, M.; Reijers, H.A.; van der Aalst, W.M.P.; Nurcan, S.; Soffer, P.; Bajec, M.; Eder, J.

    2016-01-01

    Decision mining enriches process models with rules underlying decisions in processes using historical process execution data. Choices between multiple activities are specified through rules defined over process data. Existing decision mining methods focus on discovering mutually-exclusive rules,

  8. Decision mining revisited - Discovering overlapping rules

    NARCIS (Netherlands)

    Mannhardt, Felix; De Leoni, Massimiliano; Reijers, Hajo A.; Van Der Aalst, Wil M P

    2016-01-01

    Decision mining enriches process models with rules underlying decisions in processes using historical process execution data. Choices between multiple activities are specified through rules defined over process data. Existing decision mining methods focus on discovering mutually-exclusive rules,

  9. Using GO-WAR for mining cross-ontology weighted association rules.

    Science.gov (United States)

    Agapito, Giuseppe; Cannataro, Mario; Guzzi, Pietro Hiram; Milano, Marianna

    2015-07-01

    The Gene Ontology (GO) is a structured repository of concepts (GO terms) that are associated to one or more gene products. The process of association is referred to as annotation. The relevance and the specificity of both GO terms and annotations are evaluated by a measure defined as information content (IC). The analysis of annotated data is thus an important challenge for bioinformatics. There exist different approaches of analysis. From those, the use of association rules (AR) may provide useful knowledge, and it has been used in some applications, e.g. improving the quality of annotations. Nevertheless classical association rules algorithms do not take into account the source of annotation nor the importance yielding to the generation of candidate rules with low IC. This paper presents GO-WAR (Gene Ontology-based Weighted Association Rules) a methodology for extracting weighted association rules. GO-WAR can extract association rules with a high level of IC without loss of support and confidence from a dataset of annotated data. A case study on using of GO-WAR on publicly available GO annotation datasets is used to demonstrate that our method outperforms current state of the art approaches. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  10. A New Approach of Multi-robot Cooperative Pursuit Based on Association Rule Data Mining

    Directory of Open Access Journals (Sweden)

    Jun Li

    2010-02-01

    Full Text Available An approach of cooperative hunting for multiple mobile targets by multi-robot is presented, which divides the pursuit process into forming the pursuit teams and capturing the targets. The data sets of attribute relationship is built by consulting all of factors about capturing evaders, then the interesting rules can be found by data mining from the data sets to build the pursuit teams. Through doping out the positions of targets, the pursuit game can be transformed into multi-robot path planning. Reinforcement learning is used to find the best path. The simulation results show that the mobile evaders can be captured effectively and efficiently, and prove the feasibility and validity of the given algorithm under a dynamic environment.

  11. A New Approach of Multi-Robot Cooperative Pursuit Based on Association Rule Data Mining

    Directory of Open Access Journals (Sweden)

    Jun Li

    2009-12-01

    Full Text Available An approach of cooperative hunting for multiple mobile targets by multi-robot is presented, which divides the pursuit process into forming the pursuit teams and capturing the targets. The data sets of attribute relationship is built by consulting all of factors about capturing evaders, then the interesting rules can be found by data mining from the data sets to build the pursuit teams. Through doping out the positions of targets, the pursuit game can be transformed into multi-robot path planning. Reinforcement learning is used to find the best path. The simulation results show that the mobile evaders can be captured effectively and efficiently, and prove the feasibility and validity of the given algorithm under a dynamic environment.

  12. 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.

  13. Mining association rule based on the diseases population for recommendation of medicine need

    Science.gov (United States)

    Harahap, M.; Husein, A. M.; Aisyah, S.; Lubis, F. R.; Wijaya, B. A.

    2018-04-01

    Selection of medicines that is inappropriate will lead to an empty result at medicines, this has an impact on medical services and economic value in hospital. The importance of an appropriate medicine selection process requires an automated way to select need based on the development of the patient's illness. In this study, we analyzed patient prescriptions to identify the relationship between the disease and the medicine used by the physician in treating the patient's illness. The analytical framework includes: (1) patient prescription data collection, (2) applying k-means clustering to classify the top 10 diseases, (3) applying Apriori algorithm to find association rules based on support, confidence and lift value. The results of the tests of patient prescription datasets in 2015-2016, the application of the k-means algorithm for the clustering of 10 dominant diseases significantly affects the value of trust and support of all association rules on the Apriori algorithm making it more consistent with finding association rules of disease and related medicine. The value of support, confidence and the lift value of disease and related medicine can be used as recommendations for appropriate medicine selection. Based on the conditions of disease progressions of the hospital, there is so more optimal medicine procurement.

  14. Prediction of Metabolic Pathway Involvement in Prokaryotic UniProtKB Data by Association Rule Mining

    KAUST Repository

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

    2016-01-01

    The widening gap between known proteins and their functions has encouraged the development of methods to automatically infer annotations. Automatic functional annotation of proteins is expected to meet the conflicting requirements of maximizing annotation coverage, while minimizing erroneous functional assignments. This trade-off imposes a great challenge in designing intelligent systems to tackle the problem of automatic protein annotation. In this work, we present a system that utilizes rule mining techniques to predict metabolic pathways in prokaryotes. The resulting knowledge represents predictive models that assign pathway involvement to UniProtKB entries. We carried out an evaluation study of our system performance using cross-validation technique. We found that it achieved very promising results in pathway identification with an F1-measure of 0.982 and an AUC of 0.987. Our prediction models were then successfully applied to 6.2 million UniProtKB/TrEMBL reference proteome entries of prokaryotes. As a result, 663,724 entries were covered, where 436,510 of them lacked any previous pathway annotations.

  15. Prediction of Metabolic Pathway Involvement in Prokaryotic UniProtKB Data by Association Rule Mining

    KAUST Repository

    Boudellioua, Imene

    2016-07-08

    The widening gap between known proteins and their functions has encouraged the development of methods to automatically infer annotations. Automatic functional annotation of proteins is expected to meet the conflicting requirements of maximizing annotation coverage, while minimizing erroneous functional assignments. This trade-off imposes a great challenge in designing intelligent systems to tackle the problem of automatic protein annotation. In this work, we present a system that utilizes rule mining techniques to predict metabolic pathways in prokaryotes. The resulting knowledge represents predictive models that assign pathway involvement to UniProtKB entries. We carried out an evaluation study of our system performance using cross-validation technique. We found that it achieved very promising results in pathway identification with an F1-measure of 0.982 and an AUC of 0.987. Our prediction models were then successfully applied to 6.2 million UniProtKB/TrEMBL reference proteome entries of prokaryotes. As a result, 663,724 entries were covered, where 436,510 of them lacked any previous pathway annotations.

  16. Characteristics of cyclist crashes in Italy using latent class analysis and association rule mining.

    Directory of Open Access Journals (Sweden)

    Gabriele Prati

    Full Text Available The factors associated with severity of the bicycle crashes may differ across different bicycle crash patterns. Therefore, it is important to identify distinct bicycle crash patterns with homogeneous attributes. The current study aimed at identifying subgroups of bicycle crashes in Italy and analyzing separately the different bicycle crash types. The present study focused on bicycle crashes that occurred in Italy during the period between 2011 and 2013. We analyzed categorical indicators corresponding to the characteristics of infrastructure (road type, road signage, and location type, road user (i.e., opponent vehicle and cyclist's maneuver, type of collision, age and gender of the cyclist, vehicle (type of opponent vehicle, and the environmental and time period variables (time of the day, day of the week, season, pavement condition, and weather. To identify homogenous subgroups of bicycle crashes, we used latent class analysis. Using latent class analysis, the bicycle crash data set was segmented into 19 classes, which represents 19 different bicycle crash types. Logistic regression analysis was used to identify the association between class membership and severity of the bicycle crashes. Finally, association rules were conducted for each of the latent classes to uncover the factors associated with an increased likelihood of severity. Association rules highlighted different crash characteristics associated with an increased likelihood of severity for each of the 19 bicycle crash types.

  17. In-Depth Analysis of Energy Efficiency Related Factors in Commercial Buildings Using Data Cube and Association Rule Mining

    Directory of Open Access Journals (Sweden)

    Byeongjoon Noh

    2017-11-01

    Full Text Available Significant amounts of energy are consumed in the commercial building sector, resulting in various adverse environmental issues. To reduce energy consumption and improve energy efficiency in commercial buildings, it is necessary to develop effective methods for analyzing building energy use. In this study, we propose a data cube model combined with association rule mining for more flexible and detailed analysis of building energy consumption profiles using the Commercial Buildings Energy Consumption Survey (CBECS dataset, which has accumulated over 6700 existing commercial buildings across the U.S.A. Based on the data cube model, a multidimensional commercial sector building energy analysis was performed based upon on-line analytical processing (OLAP operations to assess the energy efficiency according to building factors with various levels of abstraction. Furthermore, the proposed analysis system provided useful information that represented a set of energy efficient combinations by applying the association rule mining method. We validated the feasibility and applicability of the proposed analysis model by structuring a building energy analysis system and applying it to different building types, weather conditions, composite materials, and heating/cooling systems of the multitude of commercial buildings classified in the CBECS dataset.

  18. Interestingness measures and strategies for mining multi-ontology multi-level association rules from gene ontology annotations for the discovery of new GO relationships.

    Science.gov (United States)

    Manda, Prashanti; McCarthy, Fiona; Bridges, Susan M

    2013-10-01

    The Gene Ontology (GO), a set of three sub-ontologies, is one of the most popular bio-ontologies used for describing gene product characteristics. GO annotation data containing terms from multiple sub-ontologies and at different levels in the ontologies is an important source of implicit relationships between terms from the three sub-ontologies. Data mining techniques such as association rule mining that are tailored to mine from multiple ontologies at multiple levels of abstraction are required for effective knowledge discovery from GO annotation data. We present a data mining approach, Multi-ontology data mining at All Levels (MOAL) that uses the structure and relationships of the GO to mine multi-ontology multi-level association rules. We introduce two interestingness measures: Multi-ontology Support (MOSupport) and Multi-ontology Confidence (MOConfidence) customized to evaluate multi-ontology multi-level association rules. We also describe a variety of post-processing strategies for pruning uninteresting rules. We use publicly available GO annotation data to demonstrate our methods with respect to two applications (1) the discovery of co-annotation suggestions and (2) the discovery of new cross-ontology relationships. Copyright © 2013 The Authors. Published by Elsevier Inc. All rights reserved.

  19. Investigating the Relation Between Prevalence of Asthmatic Allergy with the Characteristics of the Environment Using Association Rule Mining

    Science.gov (United States)

    Kanani Sadat, Y.; Karimipour, F.; Kanani Sadat, A.

    2014-10-01

    The prevalence of allergic diseases has highly increased in recent decades due to contamination of the environment with the allergy stimuli. A common treat is identifying the allergy stimulus and, then, avoiding the patient to be exposed with it. There are, however, many unknown allergic diseases stimuli that are related to the characteristics of the living environment. In this paper, we focus on the effect of air pollution on asthmatic allergies and investigate the association between prevalence of such allergies with those characteristics of the environment that may affect the air pollution. For this, spatial association rule mining has been deployed to mine the association between spatial distribution of allergy prevalence and the air pollution parameters such as CO, SO2, NO2, PM10, PM2.5, and O3 (compiled by the air pollution monitoring stations) as well as living distance to parks and roads. The results for the case study (i.e., Tehran metropolitan area) indicates that distance to parks and roads as well as CO, NO2, PM10, and PM2.5 is related to the allergy prevalence in December (the most polluted month of the year in Tehran), while SO2 and O3 have no effect on that.

  20. Studying Co-evolution of Production and Test Code Using Association Rule Mining

    NARCIS (Netherlands)

    Lubsen, Z.; Zaidman, A.; Pinzger, M.

    2009-01-01

    Long version of the short paper accepted for publication in the proceedings of the 6th International Working Conference on Mining Software Repositories (MSR 2009). Unit tests are generally acknowledged as an important aid to produce high quality code, as they provide quick feedback to developers on

  1. Discovery of novel targets for multi-epitope vaccines: Screening of HIV-1 genomes using association rule mining

    Directory of Open Access Journals (Sweden)

    Piontkivska Helen

    2009-07-01

    Full Text Available Abstract Background Studies have shown that in the genome of human immunodeficiency virus (HIV-1 regions responsible for interactions with the host's immune system, namely, cytotoxic T-lymphocyte (CTL epitopes tend to cluster together in relatively conserved regions. On the other hand, "epitope-less" regions or regions with relatively low density of epitopes tend to be more variable. However, very little is known about relationships among epitopes from different genes, in other words, whether particular epitopes from different genes would occur together in the same viral genome. To identify CTL epitopes in different genes that co-occur in HIV genomes, association rule mining was used. Results Using a set of 189 best-defined HIV-1 CTL/CD8+ epitopes from 9 different protein-coding genes, as described by Frahm, Linde & Brander (2007, we examined the complete genomic sequences of 62 reference HIV sequences (including 13 subtypes and sub-subtypes with approximately 4 representative sequences for each subtype or sub-subtype, and 18 circulating recombinant forms. The results showed that despite inclusion of recombinant sequences that would be expected to break-up associations of epitopes in different genes when two different genomes are recombined, there exist particular combinations of epitopes (epitope associations that occur repeatedly across the world-wide population of HIV-1. For example, Pol epitope LFLDGIDKA is found to be significantly associated with epitopes GHQAAMQML and FLKEKGGL from Gag and Nef, respectively, and this association rule is observed even among circulating recombinant forms. Conclusion We have identified CTL epitope combinations co-occurring in HIV-1 genomes including different subtypes and recombinant forms. Such co-occurrence has important implications for design of complex vaccines (multi-epitope vaccines and/or drugs that would target multiple HIV-1 regions at once and, thus, may be expected to overcome challenges

  2. 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.

  3. Literature mining of protein-residue associations with graph rules learned through distant supervision

    Directory of Open Access Journals (Sweden)

    Ravikumar KE

    2012-10-01

    Full Text Available Abstract Background We propose a method for automatic extraction of protein-specific residue mentions from the biomedical literature. The method searches text for mentions of amino acids at specific sequence positions and attempts to correctly associate each mention with a protein also named in the text. The methods presented in this work will enable improved protein functional site extraction from articles, ultimately supporting protein function prediction. Our method made use of linguistic patterns for identifying the amino acid residue mentions in text. Further, we applied an automated graph-based method to learn syntactic patterns corresponding to protein-residue pairs mentioned in the text. We finally present an approach to automated construction of relevant training and test data using the distant supervision model. Results The performance of the method was assessed by extracting protein-residue relations from a new automatically generated test set of sentences containing high confidence examples found using distant supervision. It achieved a F-measure of 0.84 on automatically created silver corpus and 0.79 on a manually annotated gold data set for this task, outperforming previous methods. Conclusions The primary contributions of this work are to (1 demonstrate the effectiveness of distant supervision for automatic creation of training data for protein-residue relation extraction, substantially reducing the effort and time involved in manual annotation of a data set and (2 show that the graph-based relation extraction approach we used generalizes well to the problem of protein-residue association extraction. This work paves the way towards effective extraction of protein functional residues from the literature.

  4. Literature mining of protein-residue associations with graph rules learned through distant supervision.

    Science.gov (United States)

    Ravikumar, Ke; Liu, Haibin; Cohn, Judith D; Wall, Michael E; Verspoor, Karin

    2012-10-05

    We propose a method for automatic extraction of protein-specific residue mentions from the biomedical literature. The method searches text for mentions of amino acids at specific sequence positions and attempts to correctly associate each mention with a protein also named in the text. The methods presented in this work will enable improved protein functional site extraction from articles, ultimately supporting protein function prediction. Our method made use of linguistic patterns for identifying the amino acid residue mentions in text. Further, we applied an automated graph-based method to learn syntactic patterns corresponding to protein-residue pairs mentioned in the text. We finally present an approach to automated construction of relevant training and test data using the distant supervision model. The performance of the method was assessed by extracting protein-residue relations from a new automatically generated test set of sentences containing high confidence examples found using distant supervision. It achieved a F-measure of 0.84 on automatically created silver corpus and 0.79 on a manually annotated gold data set for this task, outperforming previous methods. The primary contributions of this work are to (1) demonstrate the effectiveness of distant supervision for automatic creation of training data for protein-residue relation extraction, substantially reducing the effort and time involved in manual annotation of a data set and (2) show that the graph-based relation extraction approach we used generalizes well to the problem of protein-residue association extraction. This work paves the way towards effective extraction of protein functional residues from the literature.

  5. New probabilistic interest measures for association rules

    OpenAIRE

    Hahsler, Michael; Hornik, Kurt

    2008-01-01

    Mining association rules is an important technique for discovering meaningful patterns in transaction databases. Many different measures of interestingness have been proposed for association rules. However, these measures fail to take the probabilistic properties of the mined data into account. In this paper, we start with presenting a simple probabilistic framework for transaction data which can be used to simulate transaction data when no associations are present. We use such data and a rea...

  6. Class Association Rule Pada Metode Associative Classification

    Directory of Open Access Journals (Sweden)

    Eka Karyawati

    2011-11-01

    Full Text Available Frequent patterns (itemsets discovery is an important problem in associative classification rule mining.  Differents approaches have been proposed such as the Apriori-like, Frequent Pattern (FP-growth, and Transaction Data Location (Tid-list Intersection algorithm. This paper focuses on surveying and comparing the state of the art associative classification techniques with regards to the rule generation phase of associative classification algorithms.  This phase includes frequent itemsets discovery and rules mining/extracting methods to generate the set of class association rules (CARs.  There are some techniques proposed to improve the rule generation method.  A technique by utilizing the concepts of discriminative power of itemsets can reduce the size of frequent itemset.  It can prune the useless frequent itemsets. The closed frequent itemset concept can be utilized to compress the rules to be compact rules.  This technique may reduce the size of generated rules.  Other technique is in determining the support threshold value of the itemset. Specifying not single but multiple support threshold values with regard to the class label frequencies can give more appropriate support threshold value.  This technique may generate more accurate rules. Alternative technique to generate rule is utilizing the vertical layout to represent dataset.  This method is very effective because it only needs one scan over dataset, compare with other techniques that need multiple scan over dataset.   However, one problem with these approaches is that the initial set of tid-lists may be too large to fit into main memory. It requires more sophisticated techniques to compress the tid-lists.

  7. Rule Mining Techniques to Predict Prokaryotic Metabolic Pathways

    KAUST Repository

    Saidi, Rabie

    2017-08-28

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

  8. Rule Mining Techniques to Predict Prokaryotic Metabolic Pathways

    KAUST Repository

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

    2017-01-01

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

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

    Science.gov (United States)

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

    2017-10-23

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

  10. New game - new rules: mining in the democratic South Africa

    Energy Technology Data Exchange (ETDEWEB)

    Motlatsi, J. [National Union of Mineworkers (South Africa)

    1995-12-31

    Discusses the eight areas identified by the South African Union of Mineworkers as requiring new rules to improve safety and conditions in the South African mining industry. The areas are: improved health and safety; the elimination of racism; fair wages; decent living conditions; proper training; care for workers and areas affected by the downscaling of mining; development of an economically viable mining sector; and a mining sector run on a humane and participatory manner.

  11. Association-rule-based tuberculosis disease diagnosis

    Science.gov (United States)

    Asha, T.; Natarajan, S.; Murthy, K. N. B.

    2010-02-01

    Tuberculosis (TB) is a disease caused by bacteria called Mycobacterium tuberculosis. It usually spreads through the air and attacks low immune bodies such as patients with Human Immunodeficiency Virus (HIV). This work focuses on finding close association rules, a promising technique in Data Mining, within TB data. The proposed method first normalizes of raw data from medical records which includes categorical, nominal and continuous attributes and then determines Association Rules from the normalized data with different support and confidence. Association rules are applied on a real data set containing medical records of patients with TB obtained from a state hospital. The rules determined describes close association between one symptom to another; as an example, likelihood that an occurrence of sputum is closely associated with blood cough and HIV.

  12. Mining rare associations between biological ontologies.

    Science.gov (United States)

    Benites, Fernando; Simon, Svenja; Sapozhnikova, Elena

    2014-01-01

    The constantly increasing volume and complexity of available biological data requires new methods for their management and analysis. An important challenge is the integration of information from different sources in order to discover possible hidden relations between already known data. In this paper we introduce a data mining approach which relates biological ontologies by mining cross and intra-ontology pairwise generalized association rules. Its advantage is sensitivity to rare associations, for these are important for biologists. We propose a new class of interestingness measures designed for hierarchically organized rules. These measures allow one to select the most important rules and to take into account rare cases. They favor rules with an actual interestingness value that exceeds the expected value. The latter is calculated taking into account the parent rule. We demonstrate this approach by applying it to the analysis of data from Gene Ontology and GPCR databases. Our objective is to discover interesting relations between two different ontologies or parts of a single ontology. The association rules that are thus discovered can provide the user with new knowledge about underlying biological processes or help improve annotation consistency. The obtained results show that produced rules represent meaningful and quite reliable associations.

  13. Mining rare associations between biological ontologies.

    Directory of Open Access Journals (Sweden)

    Fernando Benites

    Full Text Available The constantly increasing volume and complexity of available biological data requires new methods for their management and analysis. An important challenge is the integration of information from different sources in order to discover possible hidden relations between already known data. In this paper we introduce a data mining approach which relates biological ontologies by mining cross and intra-ontology pairwise generalized association rules. Its advantage is sensitivity to rare associations, for these are important for biologists. We propose a new class of interestingness measures designed for hierarchically organized rules. These measures allow one to select the most important rules and to take into account rare cases. They favor rules with an actual interestingness value that exceeds the expected value. The latter is calculated taking into account the parent rule. We demonstrate this approach by applying it to the analysis of data from Gene Ontology and GPCR databases. Our objective is to discover interesting relations between two different ontologies or parts of a single ontology. The association rules that are thus discovered can provide the user with new knowledge about underlying biological processes or help improve annotation consistency. The obtained results show that produced rules represent meaningful and quite reliable associations.

  14. Revealing Significant Relations between Chemical/Biological Features and Activity: Associative Classification Mining for Drug Discovery

    Science.gov (United States)

    Yu, Pulan

    2012-01-01

    Classification, clustering and association mining are major tasks of data mining and have been widely used for knowledge discovery. Associative classification mining, the combination of both association rule mining and classification, has emerged as an indispensable way to support decision making and scientific research. In particular, it offers a…

  15. RANCANG BANGUN SISTEM INFORMASI INVENTORI MENGGUNAKAN METODE ASSOCIATION RULES DI CV. DAMAR LANGIT

    Directory of Open Access Journals (Sweden)

    Zainul Fanani

    2012-03-01

    Kata Kunci : Sistem informasi, Inventori, Sistem Pendukung Keputusan (Decisition Support System, Association Rule, Data Mining, OLAP (Online Analitic Processing, Algoritma Apriori, Support, Confidence, Lift Rasio.

  16. Sanitizing sensitive association rules using fuzzy correlation scheme

    International Nuclear Information System (INIS)

    Hameed, S.; Shahzad, F.; Asghar, S.

    2013-01-01

    Data mining is used to extract useful information hidden in the data. Sometimes this extraction of information leads to revealing sensitive information. Privacy preservation in Data Mining is a process of sanitizing sensitive information. This research focuses on sanitizing sensitive rules discovered in quantitative data. The proposed scheme, Privacy Preserving in Fuzzy Association Rules (PPFAR) is based on fuzzy correlation analysis. In this work, fuzzy set concept is integrated with fuzzy correlation analysis and Apriori algorithm to mark interesting fuzzy association rules. The identified rules are called sensitive. For sanitization, we use modification technique where we substitute maximum value of fuzzy items with zero, which occurs most frequently. Experiments demonstrate that PPFAR method hides sensitive rules with minimum modifications. The technique also maintains the modified data's quality. The PPFAR scheme has applications in various domains e.g. temperature control, medical analysis, travel time prediction, genetic behavior prediction etc. We have validated the results on medical dataset. (author)

  17. Using the interestingness measure lift to generate association rules

    OpenAIRE

    Nada Hussein; Abdallah Alashqur; Bilal Sowan

    2015-01-01

    In this digital age, organizations have to deal with huge amounts of data, sometimes called Big Data. In recent years, the volume of data has increased substantially. Consequently, finding efficient and automated techniques for discovering useful patterns and relationships in the data becomes very important. In data mining, patterns and relationships can be represented in the form of association rules. Current techniques for discovering association rules rely on measures such as support for f...

  18. Effective Diagnosis of Alzheimer's Disease by Means of Association Rules

    Science.gov (United States)

    Chaves, R.; Ramírez, J.; Górriz, J. M.; López, M.; Salas-Gonzalez, D.; Illán, I.; Segovia, F.; Padilla, P.

    In this paper we present a novel classification method of SPECT images for the early diagnosis of the Alzheimer's disease (AD). The proposed method is based on Association Rules (ARs) aiming to discover interesting associations between attributes contained in the database. The system uses firstly voxel-as-features (VAF) and Activation Estimation (AE) to find tridimensional activated brain regions of interest (ROIs) for each patient. These ROIs act as inputs to secondly mining ARs between activated blocks for controls, with a specified minimum support and minimum confidence. ARs are mined in supervised mode, using information previously extracted from the most discriminant rules for centering interest in the relevant brain areas, reducing the computational requirement of the system. Finally classification process is performed depending on the number of previously mined rules verified by each subject, yielding an up to 95.87% classification accuracy, thus outperforming recent developed methods for AD diagnosis.

  19. 5 CFR 5201.105 - Additional rules for Mine Safety and Health Administration employees.

    Science.gov (United States)

    2010-01-01

    ... for Mine Safety and Health Administration employees. The rules in this section apply to employees of... Mine Safety and Health Act. Example: A mine inspector who was a former employee of mining company X... Secretary of labor for Mine Safety and Health or the Assistant Secretary's designee may grant an employee a...

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

    OpenAIRE

    Batal, Iyad; Cooper, Gregory; Hauskrecht, Milos

    2012-01-01

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

  1. A study on PubMed search tag usage pattern: association rule mining of a full-day PubMed query log.

    Science.gov (United States)

    Mosa, Abu Saleh Mohammad; Yoo, Illhoi

    2013-01-09

    The practice of evidence-based medicine requires efficient biomedical literature search such as PubMed/MEDLINE. Retrieval performance relies highly on the efficient use of search field tags. The purpose of this study was to analyze PubMed log data in order to understand the usage pattern of search tags by the end user in PubMed/MEDLINE search. A PubMed query log file was obtained from the National Library of Medicine containing anonymous user identification, timestamp, and query text. Inconsistent records were removed from the dataset and the search tags were extracted from the query texts. A total of 2,917,159 queries were selected for this study issued by a total of 613,061 users. The analysis of frequent co-occurrences and usage patterns of the search tags was conducted using an association mining algorithm. The percentage of search tag usage was low (11.38% of the total queries) and only 2.95% of queries contained two or more tags. Three out of four users used no search tag and about two-third of them issued less than four queries. Among the queries containing at least one tagged search term, the average number of search tags was almost half of the number of total search terms. Navigational search tags are more frequently used than informational search tags. While no strong association was observed between informational and navigational tags, six (out of 19) informational tags and six (out of 29) navigational tags showed strong associations in PubMed searches. The low percentage of search tag usage implies that PubMed/MEDLINE users do not utilize the features of PubMed/MEDLINE widely or they are not aware of such features or solely depend on the high recall focused query translation by the PubMed's Automatic Term Mapping. The users need further education and interactive search application for effective use of the search tags in order to fulfill their biomedical information needs from PubMed/MEDLINE.

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

    Science.gov (United States)

    Batal, Iyad; Cooper, Gregory; Hauskrecht, Milos

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

  3. 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.

  4. Using Machine Learning Methods Jointly to Find Better Set of Rules in Data Mining

    Directory of Open Access Journals (Sweden)

    SUG Hyontai

    2017-01-01

    Full Text Available Rough set-based data mining algorithms are one of widely accepted machine learning technologies because of their strong mathematical background and capability of finding optimal rules based on given data sets only without room for prejudiced views to be inserted on the data. But, because the algorithms find rules very precisely, we may confront with the overfitting problem. On the other hand, association rule algorithms find rules of association, where the association resides between sets of items in database. The algorithms find itemsets that occur more than given minimum support, so that they can find the itemsets practically in reasonable time even for very large databases by supplying the minimum support appropriately. In order to overcome the problem of the overfitting problem in rough set-based algorithms, first we find large itemsets, after that we select attributes that cover the large itemsets. By using the selected attributes only, we may find better set of rules based on rough set theory. Results from experiments support our suggested method.

  5. Mine-associated wetlands as avian habitat

    International Nuclear Information System (INIS)

    Horstman, A.J.; Nawrot, J.R.; Woolf, A.

    1998-01-01

    Surveys for interior wetland birds at mine-associated emergent wetlands on coal surface mines in southern Illinois detected one state threatened and two state endangered species. Breeding by least bittern (Ixobrychus exilis) and common moorhen (Gallinula chloropus) was confirmed. Regional assessment of potential wetland bird habitat south of Illinois Interstate 64 identified a total of 8,109 ha of emergent stable water wetlands; 10% were associated with mining. Mine-associated wetlands with persistent hydrology and large expanses of emergent vegetation provide habitat that could potentially compensate for loss of natural wetlands in Illinois

  6. Mining Staff Assignment Rules from Event-Based Data

    NARCIS (Netherlands)

    Ly, Linh Thao; Rinderle, Stefanie; Dadam, Peter; Reichert, Manfred; Bussler, Christoph J.; Haller, Armin

    2006-01-01

    Process mining offers methods and techniques for capturing process behaviour from log data of past process executions. Although many promising approaches on mining the control flow have been published, no attempt has been made to mine the staff assignment situation of business processes. In this

  7. Extracting Cross-Ontology Weighted Association Rules from Gene Ontology Annotations.

    Science.gov (United States)

    Agapito, Giuseppe; Milano, Marianna; Guzzi, Pietro Hiram; Cannataro, Mario

    2016-01-01

    Gene Ontology (GO) is a structured repository of concepts (GO Terms) that are associated to one or more gene products through a process referred to as annotation. The analysis of annotated data is an important opportunity for bioinformatics. There are different approaches of analysis, among those, the use of association rules (AR) which provides useful knowledge, discovering biologically relevant associations between terms of GO, not previously known. In a previous work, we introduced GO-WAR (Gene Ontology-based Weighted Association Rules), a methodology for extracting weighted association rules from ontology-based annotated datasets. We here adapt the GO-WAR algorithm to mine cross-ontology association rules, i.e., rules that involve GO terms present in the three sub-ontologies of GO. We conduct a deep performance evaluation of GO-WAR by mining publicly available GO annotated datasets, showing how GO-WAR outperforms current state of the art approaches.

  8. Dynamic association rules for gene expression data analysis.

    Science.gov (United States)

    Chen, Shu-Chuan; Tsai, Tsung-Hsien; Chung, Cheng-Han; Li, Wen-Hsiung

    2015-10-14

    The purpose of gene expression analysis is to look for the association between regulation of gene expression levels and phenotypic variations. This association based on gene expression profile has been used to determine whether the induction/repression of genes correspond to phenotypic variations including cell regulations, clinical diagnoses and drug development. Statistical analyses on microarray data have been developed to resolve gene selection issue. However, these methods do not inform us of causality between genes and phenotypes. In this paper, we propose the dynamic association rule algorithm (DAR algorithm) which helps ones to efficiently select a subset of significant genes for subsequent analysis. The DAR algorithm is based on association rules from market basket analysis in marketing. We first propose a statistical way, based on constructing a one-sided confidence interval and hypothesis testing, to determine if an association rule is meaningful. Based on the proposed statistical method, we then developed the DAR algorithm for gene expression data analysis. The method was applied to analyze four microarray datasets and one Next Generation Sequencing (NGS) dataset: the Mice Apo A1 dataset, the whole genome expression dataset of mouse embryonic stem cells, expression profiling of the bone marrow of Leukemia patients, Microarray Quality Control (MAQC) data set and the RNA-seq dataset of a mouse genomic imprinting study. A comparison of the proposed method with the t-test on the expression profiling of the bone marrow of Leukemia patients was conducted. We developed a statistical way, based on the concept of confidence interval, to determine the minimum support and minimum confidence for mining association relationships among items. With the minimum support and minimum confidence, one can find significant rules in one single step. The DAR algorithm was then developed for gene expression data analysis. Four gene expression datasets showed that the proposed

  9. On construction of partial association rules

    KAUST Repository

    Moshkov, Mikhail; Piliszczuk, Marcin; Zielosko, Beata Marta

    2009-01-01

    This paper is devoted to the study of approximate algorithms for minimization of partial association rule length. It is shown that under some natural assumptions on the class NP, a greedy algorithm is close to the best polynomial approximate

  10. On construction of partial association rules

    KAUST Repository

    Moshkov, Mikhail

    2009-01-01

    This paper is devoted to the study of approximate algorithms for minimization of partial association rule length. It is shown that under some natural assumptions on the class NP, a greedy algorithm is close to the best polynomial approximate algorithms for solving of this NP-hard problem. The paper contains various bounds on precision of the greedy algorithm, bounds on minimal length of rules based on an information obtained during greedy algorithm work, and results of the study of association rules for the most part of binary information systems. © 2009 Springer Berlin Heidelberg.

  11. Hospitalization patterns associated with Appalachian coal mining.

    Science.gov (United States)

    Hendryx, Michael; Ahern, Melissa M; Nurkiewicz, Timothy R

    2007-12-01

    The goal of this study was to test whether the volume of coal mining was related to population hospitalization risk for diseases postulated to be sensitive or insensitive to coal mining by-products. The study was a retrospective analysis of 2001 adult hospitalization data (n = 93,952) for West Virginia, Kentucky, and Pennsylvania, merged with county-level coal production figures. Hospitalization data were obtained from the Health Care Utilization Project National Inpatient Sample. Diagnoses postulated to be sensitive to coal mining by-product exposure were contrasted with diagnoses postulated to be insensitive to exposure. Data were analyzed using hierarchical nonlinear models, controlling for patient age, gender, insurance, comorbidities, hospital teaching status, county poverty, and county social capital. Controlling for covariates, the volume of coal mining was significantly related to hospitalization risk for two conditions postulated to be sensitive to exposure: hypertension and chronic obstructive pulmonary disease (COPD). The odds for a COPD hospitalization increased 1% for each 1462 tons of coal, and the odds for a hypertension hospitalization increased 1% for each 1873 tons of coal. Other conditions were not related to mining volume. Exposure to particulates or other pollutants generated by coal mining activities may be linked to increased risk of COPD and hypertension hospitalizations. Limitations in the data likely result in an underestimate of associations.

  12. From data mining rules to medical logical modules and medical advices.

    Science.gov (United States)

    Gomoi, Valentin; Vida, Mihaela; Robu, Raul; Stoicu-Tivadar, Vasile; Bernad, Elena; Lupşe, Oana

    2013-01-01

    Using data mining in collaboration with Clinical Decision Support Systems adds new knowledge as support for medical diagnosis. The current work presents a tool which translates data mining rules supporting generation of medical advices to Arden Syntax formalism. The developed system was tested with data related to 2326 births that took place in 2010 at the Bega Obstetrics - Gynaecology Hospital, Timişoara. Based on processing these data, 14 medical rules regarding the Apgar score were generated and then translated in Arden Syntax language.

  13. Recommendation System Based On Association Rules For Distributed E-Learning Management Systems

    Science.gov (United States)

    Mihai, Gabroveanu

    2015-09-01

    Traditional Learning Management Systems are installed on a single server where learning materials and user data are kept. To increase its performance, the Learning Management System can be installed on multiple servers; learning materials and user data could be distributed across these servers obtaining a Distributed Learning Management System. In this paper is proposed the prototype of a recommendation system based on association rules for Distributed Learning Management System. Information from LMS databases is analyzed using distributed data mining algorithms in order to extract the association rules. Then the extracted rules are used as inference rules to provide personalized recommendations. The quality of provided recommendations is improved because the rules used to make the inferences are more accurate, since these rules aggregate knowledge from all e-Learning systems included in Distributed Learning Management System.

  14. Hazards associated with stage one-mining

    International Nuclear Information System (INIS)

    Anon.

    1975-01-01

    Radiation hazards in uranium mining arise from the presence of radon-222, a gas which can escape from exposed rock surfaces into the air. Radon daughter products have been associated with an increased incidence of respiratory lung cancer. Other hazards include the tailings which arise from the extraction of uranium ores. The tailings still contain most of the original radium and emit gamma rays and radon gas. The hazards associated with uranium enrichment and fuel manufacture are also discussed. (R.L.)

  15. Induction and pruning of classification rules for prediction of microseismic hazards in coal mines

    Energy Technology Data Exchange (ETDEWEB)

    Sikora, M. [Silesian Technical University, Gliwice (Poland)

    2011-06-15

    The paper presents results of application of a rule induction and pruning algorithm for classification of a microseismic hazard state in coal mines. Due to imbalanced distribution of examples describing states 'hazardous' and 'safe', the special algorithm was used for induction and rule pruning. The algorithm selects optimal parameters' values influencing rule induction and pruning based on training and tuning sets. A rule quality measure which decides about a form and classification abilities of rules that are induced is the basic parameter of the algorithm. The specificity and sensitivity of a classifier were used to evaluate its quality. Conducted tests show that the admitted method of rules induction and classifier's quality evaluation enables to get better results of classification of microseismic hazards than by methods currently used in mining practice. Results obtained by the rules-based classifier were also compared with results got by a decision tree induction algorithm and by a neuro-fuzzy system.

  16. Mining for associations between text and brain activation in a functional neuroimaging database

    DEFF Research Database (Denmark)

    Nielsen, Finn Årup; Hansen, Lars Kai; Balslev, D.

    2004-01-01

    We describe a method for mining a neuroimaging database for associations between text and brain locations. The objective is to discover association rules between words indicative of cognitive function as described in abstracts of neuroscience papers and sets of reported stereotactic Talairach...

  17. Dynamic Programming Approach for Construction of Association Rule Systems

    KAUST Repository

    Alsolami, Fawaz

    2016-11-18

    In the paper, an application of dynamic programming approach for optimization of association rules from the point of view of knowledge representation is considered. The association rule set is optimized in two stages, first for minimum cardinality and then for minimum length of rules. Experimental results present cardinality of the set of association rules constructed for information system and lower bound on minimum possible cardinality of rule set based on the information obtained during algorithm work as well as obtained results for length.

  18. Dynamic Programming Approach for Construction of Association Rule Systems

    KAUST Repository

    Alsolami, Fawaz; Amin, Talha M.; Chikalov, Igor; Moshkov, Mikhail; Zielosko, Beata

    2016-01-01

    In the paper, an application of dynamic programming approach for optimization of association rules from the point of view of knowledge representation is considered. The association rule set is optimized in two stages, first for minimum cardinality and then for minimum length of rules. Experimental results present cardinality of the set of association rules constructed for information system and lower bound on minimum possible cardinality of rule set based on the information obtained during algorithm work as well as obtained results for length.

  19. Integrated Association Rules Complete Hiding Algorithms

    Directory of Open Access Journals (Sweden)

    Mohamed Refaat Abdellah

    2017-01-01

    Full Text Available This paper presents database security approach for complete hiding of sensitive association rules by using six novel algorithms. These algorithms utilize three new weights to reduce the needed database modifications and support complete hiding, as well as they reduce the knowledge distortion and the data distortions. Complete weighted hiding algorithms enhance the hiding failure by 100%; these algorithms have the advantage of performing only a single scan for the database to gather the required information to form the hiding process. These proposed algorithms are built within the database structure which enables the sanitized database to be generated on run time as needed.

  20. Greedy algorithms withweights for construction of partial association rules

    KAUST Repository

    Moshkov, Mikhail; Piliszczu, Marcin; Zielosko, Beata Marta

    2009-01-01

    This paper is devoted to the study of approximate algorithms for minimization of the total weight of attributes occurring in partial association rules. We consider mainly greedy algorithms with weights for construction of rules. The paper contains bounds on precision of these algorithms and bounds on the minimal weight of partial association rules based on an information obtained during the greedy algorithm run.

  1. Greedy algorithms withweights for construction of partial association rules

    KAUST Repository

    Moshkov, Mikhail

    2009-09-10

    This paper is devoted to the study of approximate algorithms for minimization of the total weight of attributes occurring in partial association rules. We consider mainly greedy algorithms with weights for construction of rules. The paper contains bounds on precision of these algorithms and bounds on the minimal weight of partial association rules based on an information obtained during the greedy algorithm run.

  2. 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.

  3. Association and Sequence Mining in Web Usage

    Directory of Open Access Journals (Sweden)

    Claudia Elena DINUCA

    2011-06-01

    Full Text Available Web servers worldwide generate a vast amount of information on web users’ browsing activities. Several researchers have studied these so-called clickstream or web access log data to better understand and characterize web users. Clickstream data can be enriched with information about the content of visited pages and the origin (e.g., geographic, organizational of the requests. The goal of this project is to analyse user behaviour by mining enriched web access log data. With the continued growth and proliferation of e-commerce, Web services, and Web-based information systems, the volumes of click stream and user data collected by Web-based organizations in their daily operations has reached astronomical proportions. This information can be exploited in various ways, such as enhancing the effectiveness of websites or developing directed web marketing campaigns. The discovered patterns are usually represented as collections of pages, objects, or re-sources that are frequently accessed by groups of users with common needs or interests. The focus of this paper is to provide an overview how to use frequent pattern techniques for discovering different types of patterns in a Web log database. In this paper we will focus on finding association as a data mining technique to extract potentially useful knowledge from web usage data. I implemented in Java, using NetBeans IDE, a program for identification of pages’ association from sessions. For exemplification, we used the log files from a commercial web site.

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

    Directory of Open Access Journals (Sweden)

    Ujjwal Maulik

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

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

    Science.gov (United States)

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

    2015-01-01

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

  6. 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.

  7. A Novel Texture Classification Procedure by using Association Rules

    Directory of Open Access Journals (Sweden)

    L. Jaba Sheela

    2008-11-01

    Full Text Available Texture can be defined as a local statistical pattern of texture primitives in observer’s domain of interest. Texture classification aims to assign texture labels to unknown textures, according to training samples and classification rules. Association rules have been used in various applications during the past decades. Association rules capture both structural and statistical information, and automatically identify the structures that occur most frequently and relationships that have significant discriminative power. So, association rules can be adapted to capture frequently occurring local structures in textures. This paper describes the usage of association rules for texture classification problem. The performed experimental studies show the effectiveness of the association rules. The overall success rate is about 98%.

  8. A Template Model for Multidimensional Inter-Transactional Association Rules

    NARCIS (Netherlands)

    Feng, L.; Yu, J.X.; Lu, H.J.; Han, J.W.

    2002-01-01

    Multidimensional inter-transactional association rules extend the traditional association rules to describe more general associations among items with multiple properties across transactions. “After McDonald and Burger King open branches, KFC will open a branch two months later and one mile away��?

  9. Study of the factors associated with substance use in adolescence using Association Rules.

    Science.gov (United States)

    García, Elena Gervilla; Blasco, Berta Cajal; López, Rafael Jiménez; Pol, Alfonso Palmer

    2010-01-01

    The aim of this study is to analyse the factors related to the use of addictive substances in adolescence using association rules, descriptive tools included in Data Mining. Thus, we have a database referring to the consumption of addictive substances in adolescence, and use the free distribution program in the R arules package (version 2.10.0). The sample was made up of 9,300 students between the ages of 14 and 18 (47.1% boys and 52.9% girls) with an average age of 15.6 (SE=1.2). The adolescents answered an anonymous questionnaire on personal, family and environmental risk factors related to substance use. The best rules obtained with regard to substance use relate the consumption of alcohol to perceived parenting style and peer consumption (confidence = 0.8528), the use of tobacco (smoking), cannabis and cocaine to perceived parental action and illegal behaviour (confidence = 0.8032, 0.8718 and 1.0000, respectively), and the use of ecstasy to peer consumption (confidence = 1.0000). In general, the association rules show in a simple manner the relationship between certain patterns of perceived parental action, behaviours that deviate from social behavioural norms, peer consumption and the use of different legal and illegal drugs of abuse in adolescence. The implications of the results obtained are described, together with the usefulness of this new methodology of analysis.

  10. Finding Exception For Association Rules Via SQL Queries

    Directory of Open Access Journals (Sweden)

    Luminita DUMITRIU

    2000-12-01

    Full Text Available Finding association rules is mainly based on generating larger and larger frequent set candidates, starting from frequent attributes in the database. The frequent sets can be organised as a part of a lattice of concepts according to the Formal Concept Analysis approach. Since the lattice construction is database contents-dependent, the pseudo-intents (see Formal Concept Analysis are avoided. Association rules between concept intents (closed sets A=>B are partial implication rules, meaning that there is some data supporting A and (not B; fully explaining the data requires finding exceptions for the association rules. The approach applies to Oracle databases, via SQL queries.

  11. Mining and sustainable development: environmental policies and programmes of mining industry associations

    International Nuclear Information System (INIS)

    Miller, C.G.

    1997-01-01

    Mining industry policies and practices have evolved rapidly in the environmental area, and more recently in the social area as well. Mining industry associations are using a variety of methods to stimulate and assist their member companies as they improve their environmental, social and economic performance. These associations provide opportunities for companies to use collaborative approaches in developing and applying improved technology, systems and practices (author)

  12. Association rule extraction from XML stream data for wireless sensor networks.

    Science.gov (United States)

    Paik, Juryon; Nam, Junghyun; Kim, Ung Mo; Won, Dongho

    2014-07-18

    With the advances of wireless sensor networks, they yield massive volumes of disparate, dynamic and geographically-distributed and heterogeneous data. The data mining community has attempted to extract knowledge from the huge amount of data that they generate. However, previous mining work in WSNs has focused on supporting simple relational data structures, like one table per network, while there is a need for more complex data structures. This deficiency motivates XML, which is the current de facto format for the data exchange and modeling of a wide variety of data sources over the web, to be used in WSNs in order to encourage the interchangeability of heterogeneous types of sensors and systems. However, mining XML data for WSNs has two challenging issues: one is the endless data flow; and the other is the complex tree structure. In this paper, we present several new definitions and techniques related to association rule mining over XML data streams in WSNs. To the best of our knowledge, this work provides the first approach to mining XML stream data that generates frequent tree items without any redundancy.

  13. Association Rule Extraction from XML Stream Data for Wireless Sensor Networks

    Science.gov (United States)

    Paik, Juryon; Nam, Junghyun; Kim, Ung Mo; Won, Dongho

    2014-01-01

    With the advances of wireless sensor networks, they yield massive volumes of disparate, dynamic and geographically-distributed and heterogeneous data. The data mining community has attempted to extract knowledge from the huge amount of data that they generate. However, previous mining work in WSNs has focused on supporting simple relational data structures, like one table per network, while there is a need for more complex data structures. This deficiency motivates XML, which is the current de facto format for the data exchange and modeling of a wide variety of data sources over the web, to be used in WSNs in order to encourage the interchangeability of heterogeneous types of sensors and systems. However, mining XML data for WSNs has two challenging issues: one is the endless data flow; and the other is the complex tree structure. In this paper, we present several new definitions and techniques related to association rule mining over XML data streams in WSNs. To the best of our knowledge, this work provides the first approach to mining XML stream data that generates frequent tree items without any redundancy. PMID:25046017

  14. Utilization of BSS-Safety Series 115 in facilities for mining ore with uranium and thorium associated to it

    International Nuclear Information System (INIS)

    Matta, Luiz Ernesto S. de C.; Ferreira, Paulo R. Rocha; Mouco, Charles D. do C.L.

    1999-01-01

    During the year of 1995, the Brazilian Nuclear Energy Commission, started a investigation program called Mining Project. The main objective of this program was to create a integrated study of environmental and occupational conditions of mining ores with uranium and thorium associated to it. Several technical visits were done at four different types of mines: coal, phosphate, niobium and gold. This work presents the area monitoring results obtained by the occupational radiation protection group. The data found in these inspections were compared to limits established by national rules. A special assessment of the data obtained was done for a future adoption of the BSS-Safety Series 115 recommendations. (author)

  15. ASSOCIATION RULE ANALYSIS FOR TOUR ROUTE RECOMMENDATION AND APPLICATION TO WCTSNOP

    Directory of Open Access Journals (Sweden)

    H. Fang

    2017-09-01

    Full Text Available The increasing E-tourism systems provide intelligent tour recommendation for tourists. In this sense, recommender system can make personalized suggestions and provide satisfied information associated with their tour cycle. Data mining is a proper tool that extracting potential information from large database for making strategic decisions. In the study, association rule analysis based on FP-growth algorithm is applied to find the association relationship among scenic spots in different cities as tour route recommendation. In order to figure out valuable rules, Kulczynski interestingness measure is adopted and imbalance ratio is computed. The proposed scheme was evaluated on Wangluzhe cultural tourism service network operation platform (WCTSNOP, where it could verify that it is able to quick recommend tour route and to rapidly enhance the recommendation quality.

  16. Association Rule Analysis for Tour Route Recommendation and Application to Wctsnop

    Science.gov (United States)

    Fang, H.; Chen, C.; Lin, J.; Liu, X.; Fang, D.

    2017-09-01

    The increasing E-tourism systems provide intelligent tour recommendation for tourists. In this sense, recommender system can make personalized suggestions and provide satisfied information associated with their tour cycle. Data mining is a proper tool that extracting potential information from large database for making strategic decisions. In the study, association rule analysis based on FP-growth algorithm is applied to find the association relationship among scenic spots in different cities as tour route recommendation. In order to figure out valuable rules, Kulczynski interestingness measure is adopted and imbalance ratio is computed. The proposed scheme was evaluated on Wangluzhe cultural tourism service network operation platform (WCTSNOP), where it could verify that it is able to quick recommend tour route and to rapidly enhance the recommendation quality.

  17. A rough set-based association rule approach implemented on a brand trust evaluation model

    Science.gov (United States)

    Liao, Shu-Hsien; Chen, Yin-Ju

    2017-09-01

    In commerce, businesses use branding to differentiate their product and service offerings from those of their competitors. The brand incorporates a set of product or service features that are associated with that particular brand name and identifies the product/service segmentation in the market. This study proposes a new data mining approach, a rough set-based association rule induction, implemented on a brand trust evaluation model. In addition, it presents as one way to deal with data uncertainty to analyse ratio scale data, while creating predictive if-then rules that generalise data values to the retail region. As such, this study uses the analysis of algorithms to find alcoholic beverages brand trust recall. Finally, discussions and conclusion are presented for further managerial implications.

  18. Privacy-preserving distributed mining of association rules using ...

    Indian Academy of Sciences (India)

    Harendra Chahar

    2017-11-17

    Nov 17, 2017 ... cally or vice-versa. For market analysis, business organizations would like to ..... ticipating sites using Elliptic-curve-based digital signature algorithm. ..... nication Technologies, Research, Innovation, and Vision for the Future ...

  19. Interestingness of association rules in data mining: Issues relevant ...

    Indian Academy of Sciences (India)

    2016-08-26

    Aug 26, 2016 ... ... synonymous with the internet has changed the competitive business environment ... Importance of automated methods that address this immensity problem, ... issues that reveal many promising avenues for future research.

  20. Collaborative Data Mining Tool for Education

    Science.gov (United States)

    Garcia, Enrique; Romero, Cristobal; Ventura, Sebastian; Gea, Miguel; de Castro, Carlos

    2009-01-01

    This paper describes a collaborative educational data mining tool based on association rule mining for the continuous improvement of e-learning courses allowing teachers with similar course's profile sharing and scoring the discovered information. This mining tool is oriented to be used by instructors non experts in data mining such that, its…

  1. Mining Views : database views for data mining

    NARCIS (Netherlands)

    Blockeel, H.; Calders, T.; Fromont, É.; Goethals, B.; Prado, A.

    2008-01-01

    We present a system towards the integration of data mining into relational databases. To this end, a relational database model is proposed, based on the so called virtual mining views. We show that several types of patterns and models over the data, such as itemsets, association rules and decision

  2. Mining Views : database views for data mining

    NARCIS (Netherlands)

    Blockeel, H.; Calders, T.; Fromont, É.; Goethals, B.; Prado, A.; Nijssen, S.; De Raedt, L.

    2007-01-01

    We propose a relational database model towards the integration of data mining into relational database systems, based on the so called virtual mining views. We show that several types of patterns and models over the data, such as itemsets, association rules, decision trees and clusterings, can be

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

    CERN Document Server

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

    2012-01-01

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

  4. Process mining : overview and opportunities

    NARCIS (Netherlands)

    Aalst, van der W.M.P.

    2012-01-01

    Over the last decade, process mining emerged as a new research ¿eld that focuses on the analysis of processes using event data. Classical data mining techniques such as classi¿cation, clustering, regression, association rule learning, and sequence/episode mining do not focus on business process

  5. Mining Branching Rules from Past Survey Data with an Illustration Using a Geriatric Assessment Survey for Older Adults with Cancer

    Directory of Open Access Journals (Sweden)

    Daniel R. Jeske

    2016-05-01

    Full Text Available We construct a fast data mining algorithm that can be used to identify high-frequency response patterns in historical surveys. Identification of these patterns leads to the derivation of question branching rules that shorten the time required to complete a survey. The data mining algorithm allows the user to control the error rate that is incurred through the use of implied answers that go along with each branching rule. The context considered is binary response questions, which can be obtained from multi-level response questions through dichotomization. The algorithm is illustrated by the analysis of four sections of a geriatric assessment survey used by oncologists. Reductions in the number of questions that need to be asked in these four sections range from 33% to 54%.

  6. 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

  7. Parental rules and communication: their association with adolescent smoking

    NARCIS (Netherlands)

    Harakeh, Z.; Scholte, R.H.J.; Vries, H. de; Engels, R.C.M.E.

    2005-01-01

    Aims - To examine the association between parental rules and communication (also referred to as antismoking socialization) and adolescents’ smoking. Design and participants - A cross-sectional study including 428 Dutch two-parent families with at least two adolescent children (aged

  8. [Ginseng prescription rules and molecular mechanism in treating coronary heart disease based on data mining and integrative pharmacology].

    Science.gov (United States)

    Li, Sen; Tang, Shi-Huan; Liu, Jin-Ling; Su, Jin; He, Fu-Yuan

    2018-04-01

    The ancient dragon Materia Medica, Compendium of Materia Medica and other works recorded that the main effect of ginseng is tonifying qi. It is reported that the main active ingredient of ginseng is ginsenoside. Modern studies have found that ginseng mono saponins are effective for cardiovascular related diseases. This paper preliminary clarified the efficacy of traditional ginseng-nourishing qi and cardiovascular disease through the traditional Chinese medicine (TCM) inheritance auxiliary platform and integration platform of association of pharmacology. With the help of TCM inheritance auxiliary platform-analysis of "Chinese medicine database", Chinese medicine treatment of modern diseases that ginseng rules, so the traditional effect associated with modern medicine and pharmacology; application integration platform enrichment analysis on the target of drug and gene function, metabolic pathway, to further explore the molecular mechanism of ginseng in the treatment of coronary heart disease, aimed at mining the molecular mechanism of ginseng in the treatment of coronary heart disease. Chinese medicine containing ginseng 307 prescriptions, 87 kinds of disease indications, western medicine disease Chinese medicine therapy for ginseng main coronary heart disease; analysis of molecular mechanism of ginseng pharmacology integration platform for the treatment of coronary heart disease. Ginsenosides(Ra₁, Ra₂, Rb₁, Rb₂, Rg₁, Ro) bind these targets, PRKAA1, PRKAA2, NDUFA4, COX5B, UQCRC1, affect chemokines, non-alcoholic fatty liver, gonadotropin, carbon metabolism, glucose metabolism and other pathways to treat coronary heart disease indirectly. The molecular mechanism of Panax ginseng's multi-component, multi-target and synergistic action is preliminarily elucidated in this paper. Copyright© by the Chinese Pharmaceutical Association.

  9. Generation of Acid Mine Lakes Associated with Abandoned Coal Mines in Northwest Turkey.

    Science.gov (United States)

    Sanliyuksel Yucel, Deniz; Balci, Nurgul; Baba, Alper

    2016-05-01

    A total of five acid mine lakes (AMLs) located in northwest Turkey were investigated using combined isotope, molecular, and geochemical techniques to identify geochemical processes controlling and promoting acid formation. All of the investigated lakes showed typical characteristics of an AML with low pH (2.59-3.79) and high electrical conductivity values (1040-6430 μS/cm), in addition to high sulfate (594-5370 mg/l) and metal (aluminum [Al], iron [Fe], manganese [Mn], nickel [Ni], and zinc [Zn]) concentrations. Geochemical and isotope results showed that the acid-generation mechanism and source of sulfate in the lakes can change and depends on the age of the lakes. In the relatively older lakes (AMLs 1 through 3), biogeochemical Fe cycles seem to be the dominant process controlling metal concentration and pH of the water unlike in the younger lakes (AMLs 4 and 5). Bacterial species determined in an older lake (AML 2) indicate that biological oxidation and reduction of Fe and S are the dominant processes in the lakes. Furthermore, O and S isotopes of sulfate indicate that sulfate in the older mine lakes may be a product of much more complex oxidation/dissolution reactions. However, the major source of sulfate in the younger mine lakes is in situ pyrite oxidation catalyzed by Fe(III) produced by way of oxidation of Fe(II). Consistent with this, insignificant fractionation between δ(34) [Formula: see text] and δ(34) [Formula: see text] values indicated that the oxidation of pyrite, along with dissolution and precipitation reactions of Fe(III) minerals, is the main reason for acid formation in the region. Overall, the results showed that acid generation during early stage formation of an AML associated with pyrite-rich mine waste is primarily controlled by the oxidation of pyrite with Fe cycles becoming the dominant processes regulating pH and metal cycles in the later stages of mine lake development.

  10. Profiling high frequency accident locations using associations rules

    OpenAIRE

    GEURTS, Karolien; WETS, Geert; BRIJS, Tom; VANHOOF, Koen

    2002-01-01

    In Belgium, traffic safety is currently one of the government’s highest priorities. Identifying and profiling black spots and black zones in terms of accident related data and location characteristics must provide new insights into the complexity and causes of road accidents which, in turn, provide valuable input for government actions. In this paper, association rules are used to identify accident circumstances that frequently occur together at high frequency accident locations. Furthermore,...

  11. Profiling high-frequency accident locations using association rules

    OpenAIRE

    GEURTS, Karolien; WETS, Geert; BRIJS, Tom; VANHOOF, Koen

    2003-01-01

    In Belgium, traffic safety is currently one of the government's highest priorities. Identifying and profiling black spots and black zones in terms of accident related data and location characteristics must provide new insights into the complexity and causes of road accidents, which, in ram, provide valuable input for government actions. In this paper, association rules are used to identify accident circumstances that frequently occur together at high frequency accident locations. Furthermore...

  12. Respirable quartz hazard associated with coal mine roof bolter dust

    International Nuclear Information System (INIS)

    Joy, G.J.; Beck, T.W.; Listak, J.M.

    2010-01-01

    Pneumoconiosis has been reported to be increasing among underground coal miners in the Southern Appalachian Region. The National Institute for Occupational Safety and Health conducted a study to examine the particle size distribution and quartz content of dust generated by the installation of roof bolts in mines. Forty-six bulk samples of roof bolting machine pre-cleaner cyclone dump dust and collector box dust were collected from 26 underground coal mines. Real-time and integrated airborne respirable dust concentrations were measured on 3 mining sections in 2 mines. The real-time airborne dust concentrations profiles were examined to identify any concentration changes that might be associated with pre-cleaner cyclone dust discharge events. The study showed that bolter dust is a potential inhalation hazard due to the fraction of dust less than 10 μm in size, and the quartz content of the dust. The pre-cleaner cyclone dust was significantly larger than the collector box dust, indicating that the pre-cleaner functioned properly in removing the larger dust size fraction from the airstream. However, the pre-cleaner dust still contained a substantial amount of respirable dust. It was concluded that in order to maintain the effectiveness of a roof bolter dust collector, periodic removal of dust is required. Appropriate work procedures and equipment are necessary to minimize exposure during this cleaning task. 13 refs., 3 tabs., 2 figs.

  13. 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

  14. Finding Influential Users in Social Media Using Association Rule Learning

    Directory of Open Access Journals (Sweden)

    Fredrik Erlandsson

    2016-04-01

    Full Text Available Influential users play an important role in online social networks since users tend to have an impact on one other. Therefore, the proposed work analyzes users and their behavior in order to identify influential users and predict user participation. Normally, the success of a social media site is dependent on the activity level of the participating users. For both online social networking sites and individual users, it is of interest to find out if a topic will be interesting or not. In this article, we propose association learning to detect relationships between users. In order to verify the findings, several experiments were executed based on social network analysis, in which the most influential users identified from association rule learning were compared to the results from Degree Centrality and Page Rank Centrality. The results clearly indicate that it is possible to identify the most influential users using association rule learning. In addition, the results also indicate a lower execution time compared to state-of-the-art methods.

  15. Parental rules and communication: their association with adolescent smoking.

    Science.gov (United States)

    Harakeh, Zeena; Scholte, Ron H J; de Vries, Hein; Engels, Rutger C M E

    2005-06-01

    To examine the association between parental rules and communication (also referred to as antismoking socialization) and adolescents' smoking. A cross-sectional study including 428 Dutch two-parent families with at least two adolescent children (aged 13-17 years). Parents' and adolescents' reports on an agreement regarding smoking by adolescents, smoking house rules, parental confidence in preventing their child from smoking, frequency and quality of communication about smoking, and parent's reactions to smoking experimentation. Compared with fathers and adolescents, mothers reported being more involved in antismoking socialization. There were robust differences in antismoking socialization efforts between smoking and non-smoking parents. Perceived parental influence and frequency and quality of communication about smoking were associated with adolescents' smoking. The association between antismoking socialization practices and adolescents' smoking was not moderated by birth order, parents' smoking or gender of the adolescent. Encouraging parents, whether or not they themselves smoke, to discuss smoking-related issues with their children in a constructive and respectful manner is worth exploring as an intervention strategy to prevent young people taking up smoking.

  16. Natural radioactivity associated with bituminous coal mining in Nigeria

    International Nuclear Information System (INIS)

    Balogun, F.A.; Mokobia, C.E.; Fasasi, M.K.; Ogundare, F.O.

    2003-01-01

    Gamma spectroscopic method was used to determine the natural radioactivity associated with the mining of Nigerian bituminous coal for the purpose of determining the radiological implications of coal mining in the country. The activity concentrations of the radionuclides detected range from 0.20±0.002 to 48.42±5.32 Bq kg -1 . The overall natural radionuclide contribution to the radioactivity of the environment was found to be 404.16±23.44 Bq kg -1 . Of this, coal waste (tailing) alone contributed 49.5% representing the largest contribution. Coal contributed just 5.5%. A comparison of the concentrations obtained in this work for coal with those from other parts of the world indicates that the radioactivity content of the Nigerian bituminous coal is not significantly different. The outdoor and indoor exposure rates in air 1 m above the ground are estimated to be (6.31±1.20)x10 -8 and (7.57±1.20) x10 -8 Gy h -1 , respectively, for the mining environment. These values compare very well with the global values reported by UNSCEAR: 5x10 -8 and 6x10 -8 Gy h -1 , respectively. The resulting annual effective dose equivalent estimated is (4.49±0.74)x10 -4 Sv yr -1 . This also compares favourably with the global value -4x10 -4 Sv yr -1 , reported by UNSCEAR

  17. Data Mining Rules for Ultrasonic B-Type Detection and Diagnosis for Cholecystolithiasis

    Institute of Scientific and Technical Information of China (English)

    LOU Wei; YAN Li-min; HE Guo-sen

    2004-01-01

    This paper presents realistic data mining based on the data of B-type ultrasonic detection and diagnosis for cholrcystolithiasis (gallbladder stone in biliary tract) recorded by a district central hospital in Shanghai during the past several years. Computer simulation and modeling is described.

  18. Data mining and visualization techniques

    Science.gov (United States)

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

    2004-03-23

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

  19. 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.

  20. Rule-based statistical data mining agents for an e-commerce application

    Science.gov (United States)

    Qin, Yi; Zhang, Yan-Qing; King, K. N.; Sunderraman, Rajshekhar

    2003-03-01

    Intelligent data mining techniques have useful e-Business applications. Because an e-Commerce application is related to multiple domains such as statistical analysis, market competition, price comparison, profit improvement and personal preferences, this paper presents a hybrid knowledge-based e-Commerce system fusing intelligent techniques, statistical data mining, and personal information to enhance QoS (Quality of Service) of e-Commerce. A Web-based e-Commerce application software system, eDVD Web Shopping Center, is successfully implemented uisng Java servlets and an Oracle81 database server. Simulation results have shown that the hybrid intelligent e-Commerce system is able to make smart decisions for different customers.

  1. Associations between rule-based parenting practices and child screen viewing: A cross-sectional study

    Directory of Open Access Journals (Sweden)

    Joanna M. Kesten

    2015-01-01

    Conclusions: Limit setting is associated with greater SV. Collaborative rule setting may be effective for managing boys' game-console use. More research is needed to understand rule-based parenting practices.

  2. ABOUT CLINICAL EXPERT SYSTEM BASED ON RULES USING DATA MINING TECHNOLOGY

    Directory of Open Access Journals (Sweden)

    V. P. Martsenyuk

    2015-05-01

    Full Text Available In the work the topics of software implementation of rule induction method based on sequential covering algorithm are considered. Such approach allows us to develop clinical decision support system. The project is implemented within Netbeans IDE based on Java-classes.

  3. State Identification of Hoisting Motors Based on Association Rules for Quayside Container Crane

    Science.gov (United States)

    Li, Q. Z.; Gang, T.; Pan, H. Y.; Xiong, H.

    2017-07-01

    Quay container crane hoisting motor is a complex system, and the characteristics of long-term evolution and change of running status of there is a rule, and use it. Through association rules analysis, this paper introduced the similarity in association rules, and quay container crane hoisting motor status identification. Finally validated by an example, some rules change amplitude is small, regular monitoring, not easy to find, but it is precisely because of these small changes led to mechanical failure. Therefore, using the association rules change in monitoring the motor status has the very strong practical significance.

  4. Determination of Relations between Systolic Blood Pressure and Heart Attack in Patients with Type 2 Diabetes with Association Rules

    Directory of Open Access Journals (Sweden)

    Seyyed Payam Shariatpanahi

    2018-03-01

    Full Text Available Abstract Background: Today, the high prevalence of diabetes and its complications are one of the most important public health issues worldwide. For this reason, finding relations between diabetes risk factors is very effective in preventing and reducing complications. For discovering these relations, the data mining methods can be used. By extracting association rules, which is one of the data mining techniques, we can discover the relations between a large numbers of variables in a disease. Materials and Methods: The population of this study was 1046 patients with type 2 diabetes, whose data had recorded between 2011 and 2014 at the Special Clinic for Diabetes in Tehran's Imam Khomeini Hospital. After pre-processing step with SPSS19 software, 573 people entered the analysis phase. The FP-Growth algorithm was applied to the data set to discover the relations between heart attack and other risk factors using Rapid miner5 software. Relations, after extraction, were given to the doctor to confirm clinical validation. Results: The obtained results of studying these 573 people (Including 292 (51% women and 281 (49% men, with age range 27 to 82 years showed that the lack of blood pressure, creatinine and diastolic blood pressure at its normal level, despite higher systolic blood pressure level than normal, doesn't increase the probability of heart attack. Conclusion: Using association rules is a good way of identifying relations between the risk factors of a disease. Also, it can provide new hypotheses to do epidemiological studies for researchers.

  5. Formal and Computational Properties of the Confidence Boost of Association Rules

    OpenAIRE

    Balcázar, José L.

    2011-01-01

    Some existing notions of redundancy among association rules allow for a logical-style characterization and lead to irredundant bases of absolutely minimum size. One can push the intuition of redundancy further and find an intuitive notion of interest of an association rule, in terms of its "novelty" with respect to other rules. Namely: an irredundant rule is so because its confidence is higher than what the rest of the rules would suggest; then, one can ask: how much higher? We propose to mea...

  6. Demographic Variables of Corruption in the Chinese Construction Industry: Association Rule Analysis of Conviction Records.

    Science.gov (United States)

    Yu, Yao; Martek, Igor; Hosseini, M Reza; Chen, Chuan

    2018-05-02

    Corruption in the construction industry is a serious problem in China. As such, fighting this corruption has become a priority target of the Chinese government, with the main effort being to discover and prosecute its perpetrators. This study profiles the demographic characteristics of major incidences of corruption in construction. It draws on the database of the 83 complete recorded cases of construction related corruption held by the Chinese National Bureau of Corruption Prevention. Categorical variables were drawn from the database, and 'association rule mining analysis' was used to identify associations between variables as a means of profiling perpetrators. Such profiling may be used as predictors of future incidences of corruption, and consequently to inform policy makers in their fight against corruption. The results signal corruption within the Chinese construction industry to be correlated with age, with incidences rising as managers' approach retirement age. Moreover, a majority of perpetrators operate within government agencies, are department deputies in direct contact with projects, and extort the greatest amounts per case from second tier cities. The relatively lengthy average 6.4-year period before cases come to public attention corroborates the view that current efforts at fighting corruption remain inadequate.

  7. Mine subsidence control projects associated with solid waste disposal facilities

    International Nuclear Information System (INIS)

    Wood, R.M.

    1994-01-01

    Pennsylvania environmental regulations require applicant's for solid waste disposal permits to provide information regarding the extent of deep mining under the proposed site, evaluations of the maximum subsidence potential, and designs of measures to mitigate potential subsidence impact on the facility. This paper presents three case histories of deep mine subsidence control projects at solid waste disposal facilities. Each case history presents site specific mine grouting project data summaries which include evaluations of the subsurface conditions from drilling, mine void volume calculations, grout mix designs, grouting procedures and techniques, as well as grout coverage and extent of mine void filling evaluations. The case studies described utilized basic gravity grouting techniques to fill the mine voids and fractured strata over the collapsed portions of the deep mines. Grout mixtures were designed to achieve compressive strengths suitable for preventing future mine subsidence while maintaining high flow characteristics to penetrate fractured strata. Verification drilling and coring was performed in the grouted areas to determine the extent of grout coverage and obtain samples of the in-place grout for compression testing. The case histories presented in this report demonstrate an efficient and cost effective technique for mine subsidence control projects

  8. Is there an association of circulatory hospitalizations independent of mining employment in coal-mining and non-coal-mining counties in west virginia?

    Science.gov (United States)

    Talbott, Evelyn O; Sharma, Ravi K; Buchanich, Jeanine; Stacy, Shaina L

    2015-04-01

    Exposures associated with coal mining activities, including diesel fuel exhaust, products used in coal processing, and heavy metals and other forms of particulate matter, may impact the health of nearby residents. We investigated the relationships between county-level circulatory hospitalization rates (CHRs) in coal and non-coal-mining communities of West Virginia, coal production, coal employment, and sociodemographic factors. Direct age-adjusted CHRs were calculated using West Virginia hospitalizations from 2005 to 2009. Spatial regressions were conducted to explore associations between CHR and total, underground, and surface coal production. After adjustment, neither total, nor surface, nor underground coal production was significantly related to rate of hospitalization for circulatory disease. Our findings underscore the significant role sociodemographic and behavioral factors play in the health and well-being of coal mining communities.

  9. Legal instruments for controlling exposure of workers to ionizing radiations in mining and its associated industries

    International Nuclear Information System (INIS)

    Yusoff Ismail

    1994-01-01

    Briefly, the existing legal instruments for protection of workers in mining and its associated activities are given. Further, major provisions of the laws relevant to the protection of workers against ionizing radiations in mining and its associated activities are detailed. Finally, practical framework developed by the Atomic Energy Licensing Board, for implementation and enforcement is described

  10. Assessment of pneumoconiosis hazards associated with mining operations in coal mines. [USSR

    Energy Technology Data Exchange (ETDEWEB)

    Sukhanov, V V; Menyailo, N I; Petul' ko, S N

    1984-07-01

    Methods are discussed for evaluating hazards of pneumoconiosis in underground coal mines. Pneumoconiosis hazards are decisively influenced by: content of respirable dusts in mine air at a working place, dust composition, temperature and time of a miner's contact with dusts. The following classification of pneumoconiosis hazards is used in the USSR: low hazards when a miner is endangered by pneumoconiosis after 20 years or more, medium hazards when pneumoconiosis may occur after 10 to 20 years, high pneumoconiosis hazards when a miner is endangered by pneumoconiosis after less than 10 years of contact with dusts. High air temperature in deep coal mines increases pneumoconiosis hazards: when temperature exceeds 26 C a temperature increase of 1 C causes a 10% increase in dust chemical activity. Safety standards which describe the maximum permissible dust level in coal mine air in the USSR, the FRG, France and Poland are compared.

  11. Health concerns associated with unconventional gas mining in rural Australia.

    Science.gov (United States)

    Haswell, Melissa R; Bethmont, Anna

    2016-01-01

    Many governments globally are investigating the benefits and risks associated with unconventional gas mining for shale, tight and coal seam gas (coalbed methane) to determine whether the industry should proceed in their jurisdiction. Most locations likely to be developed are in rural areas, with potential impact on farmers and small communities. Despite significant health concerns, public health knowledge and growing evidence are often overlooked in decision-making. It is difficult to gain a broad but accurate understanding of the health concerns for rural communities because the evidence has grown very recently and rapidly, is complex and largely based in the USA, where the industry is advanced. In 2016, a concerned South Australian beef and lamb farmer in an area targeted for potential unconventional gas development organised visits to homes in developed unconventional gas areas of Pennsylvania and forums with leading researchers and lawyers in Pennsylvania and New York. Guided by priorities identified during this trip, this communication concisely distils the research evidence on these key concerns, highlighting the Australian situation where evidence exists. It summarises key information of particular concern to rural regions, using Australia as an example, to assist rural health professionals to be better prepared to engage in decision-making and address the challenges associated with this new industry. Discussions with communities and experts, supported by the expanding research from the USA and Australia, revealed increasing health concerns in six key areas. These are absence of a safe solution to the toxic wastewater management problems, air pollution, land and water competition, mental health and psychosocial wellbeing risks, fugitive methane emissions and lack of proven regulatory regimes. Emerging epidemiological studies suggesting interference with foetal development and birth outcomes, and exacerbation of asthma conditions, are particularly concerning

  12. Association Rule-based Predictive Model for Machine Failure in Industrial Internet of Things

    Science.gov (United States)

    Kwon, Jung-Hyok; Lee, Sol-Bee; Park, Jaehoon; Kim, Eui-Jik

    2017-09-01

    This paper proposes an association rule-based predictive model for machine failure in industrial Internet of things (IIoT), which can accurately predict the machine failure in real manufacturing environment by investigating the relationship between the cause and type of machine failure. To develop the predictive model, we consider three major steps: 1) binarization, 2) rule creation, 3) visualization. The binarization step translates item values in a dataset into one or zero, then the rule creation step creates association rules as IF-THEN structures using the Lattice model and Apriori algorithm. Finally, the created rules are visualized in various ways for users’ understanding. An experimental implementation was conducted using R Studio version 3.3.2. The results show that the proposed predictive model realistically predicts machine failure based on association rules.

  13. 17 CFR 240.17a-1 - Recordkeeping rule for national securities exchanges, national securities associations...

    Science.gov (United States)

    2010-04-01

    ... national securities exchanges, national securities associations, registered clearing agencies and the... Certain Stabilizing Activities § 240.17a-1 Recordkeeping rule for national securities exchanges, national...) Every national securities exchange, national securities association, registered clearing agency and the...

  14. A study of trends in occupational risks associated with coal mining

    International Nuclear Information System (INIS)

    Amoudru, C.

    1980-01-01

    The coal industry is well known as a major source of specific types of risk and harmful effects including, for instance, harm to the environment, pollution from various surface installations and hazards associated with the actual task of mining. We shall confine our attention to the third group and discuss only the occupational risks facing miners and ex-miners. Unlike the nuclear and oil industries, coal-mines employ very large work-forces, and the risks associated with mining therefore have a considerable impact. Mining is also a highly integrated industry: a mine's own work-force carries out all the underground engineering work (preparatory excavations, installation work, etc.) as well as maintenance. In this narrow field, a distinction should immediately be drawn between two main areas: industrial accidents; and occupational diseases, which include silicosis or, more precisely, coal-miner's pneumoconiosis

  15. Determination of possible radiation hazards associated with tin mining industry in West Malaysia

    International Nuclear Information System (INIS)

    Hu, S.J.

    1979-04-01

    A study was made in Malaysia under an IAEA research contract on the possible radiation hazards associated with tin mining industry in Malaysia. The study comprised of the measurement of external radiation levels in various mines, gamma-ray spectrometric analysis of various samples from mines, and measurements of radon and radon daughters concentrations. For radon daughters modified Tsivoglou and Kusnetz methods were used. The study showed that there is, in general, no radiation hazard associated with the tin mining industry in West Malaysia. However, the only likely source that might pose some external radiation hazard is the amang upgrading plant which invariably concentrates either or both 232 Th and 238 U in the final products of the upgrading process. A quantitative and thorough investigation of radiation levels in the amang upgrading industry is necessary to determine the degree of hazard. No significant radon or radon daughters concentrations were noted in the underground mines

  16. Arsenic and antimony geochemistry of mine wastes, associated waters and sediments at the Giant Mine, Yellowknife, Northwest Territories, Canada

    International Nuclear Information System (INIS)

    Fawcett, Skya E.; Jamieson, Heather E.; Nordstrom, D. Kirk; McCleskey, R. Blaine

    2015-01-01

    Sb were associated with organic material and appeared mobile in the root zone. In the zone below active plant growth, As and Sb were associated primarily with inorganic phases suggesting a release and reprecipitation of these elements upon plant death. The co-existence of reduced and oxidized As and Sb species, instability of some phases under changing redox conditions, and plant uptake and release pose challenges for remediation efforts at the mine.

  17. 9 CFR 201.4 - Bylaws, rules and regulations, and requirements of exchanges, associations, or other...

    Science.gov (United States)

    2010-01-01

    ... 9 Animals and Animal Products 2 2010-01-01 2010-01-01 false Bylaws, rules and regulations, and... 201.4 Animals and Animal Products GRAIN INSPECTION, PACKERS AND STOCKYARDS ADMINISTRATION (PACKERS AND... of any exchange, association, or other organization, or any other valid law, rule or regulation, or...

  18. [Application of association rule in mental health test for employees in a petrochemical enterprise].

    Science.gov (United States)

    Zhang, L F; Zhang, D N; Wang, Z P

    2017-10-20

    Objective: To investigate the occurrence ruleof common psychological abnormalities in petrochemical workers using association rule. Methods: From July to September,2014,the Symptom Checklist-90 (SCL-90)was used for the general survey of mental healthamong all employees in a petrochemical enterprise.The association rule Apriori algorithm was used to analyze the data of SCL-90 and investigate the occurrence rule of psychological abnormalities in petrochemical workers with different sexes,ages,or nationalities. Results: A total of 8 248 usable questionnaires were collected. The SCL-90 analysis showed that 1623 petrochemical workers(19.68%) had positive results,among whom 567(34.94%)had one positive factor and 1056 (65.06%)had two or more positive factors. A total of 7 strong association rules were identified and all of them included obsessive-compulsive symptom and depression. Male({obsessive-compulsive symptom,anxiety}=>{depression}) and female workers ({somatization,depression}=>{obsessive-compulsive symptom}) had their own special association rules. The workers aged 35-44 years had 17 special association rules,and ethnic minorities had 5 special association rules. Conclusion: Employeesin the petrochemical enterprise have multiple positive factors in SCL-90, and employees aged 35-44 years and ethnic minorities have a rich combination of psychological symptoms and need special attention during mental health intervention.

  19. Wetland and waterbody restoration and creation associated with mining

    International Nuclear Information System (INIS)

    Brooks, R.P.

    1990-01-01

    Published and unpublished reports are reviewed and the strategies and techniques used to facilitate the establishment of wetlands and waterbodies during mine reclamation are summarized. Although the emphasis is on coal, phosphate, and sand and gravel operations, the methods are relevant to other types of mining and mitigation activities. The following key points should receive attention during planning and mitigation processes: (1) development of site-specific objectives that are related to regional wetland trends; (2) integration of wetland mitigation plans with mining operations and reclamation at the beginning of any project; (3) wetland designs that mimic natural systems and provide flexibility for unforeseen events; (4) assurance that basin morphometry and control of the hydrologic regime are properly addressed before considering other aspects of a project; and (5) identification of mandatory monitoring as a known cost. Well-designed studies that use comparative approaches are needed to increase the database on wetland restoration technology. Meanwhile, regional success criteria for different classes of wetlands need to be developed by consensus agreement among professionals. The rationale for a particular mitigation strategy must have a sound, scientific basis if the needs of mining industries are to be balanced against the necessity of wetland operation. 93 refs., 3 figs

  20. Association between clean indoor air laws and voluntary smokefree rules in homes and cars.

    Science.gov (United States)

    Cheng, Kai-Wen; Okechukwu, Cassandra A; McMillen, Robert; Glantz, Stanton A

    2015-03-01

    This study examines the influence that smokefree workplaces, restaurants and bars have on the adoption of smokefree rules in homes and cars, and whether there is an association with adopting smokefree rules in homes and cars. Bivariate probit models were used to jointly estimate the likelihood of living in a smokefree home and having a smokefree car as a function of law coverage and other variables. Household data were obtained from the nationally representative Social Climate Survey of Tobacco Control 2001, 2002 and 2004-2009; clean indoor air law data were from the American Nonsmokers' Rights Foundation Tobacco Control Laws Database. 'Full coverage' and 'partial coverage' smokefree legislation is associated with an increased likelihood of having voluntary home and car smokefree rules compared with 'no coverage'. The association between 'full coverage' and smokefree rule in homes and cars is 5% and 4%, respectively, and the association between 'partial coverage' and smokefree rules in homes and cars is 3% and 4%, respectively. There is a positive association between the adoption of smokefree rules in homes and cars. Clean indoor air laws provide the additional benefit of encouraging voluntary adoption of smokefree rules in homes and cars. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

  1. Arsenic and antimony geochemistry of mine wastes, associated waters and sediments at the Giant Mine, Yellowknife, Northwest Territories, Canada

    Science.gov (United States)

    Fawcett, Skya E.; Jamieson, Heather E.; Nordstrom, D. Kirk; McCleskey, R. Blaine

    2015-01-01

    Elevated levels of arsenic (As) and antimony (Sb) in water and sediments are legacy residues found downstream from gold-mining activities at the Giant Mine in Yellowknife, Northwest Territories (NWT), Canada. To track the transport and fate of As and Sb, samples of mine-waste from the mill, and surface water, sediment, pore-water, and vegetation downstream of the mine were collected. Mine waste, pore-water, and sediment samples were analyzed for bulk chemistry, and aqueous and solid-state speciation. Sediment and vegetation chemistry were evaluated using scanning electron microscope imaging, synchrotron-based element mapping and electron microprobe analysis. The distributions of As and Sb in sediments were similar, yet their distributions in the corresponding pore-waters were mostly dissimilar, and the mobility of As was greater than that of Sb. Competition for sorption sites is the most likely cause of elevated Sb concentrations in relatively oxidized pore-water and surface water. The aqueous and solid-state speciation of As and Sb also differed. In pore-water, As(V) dominated in oxidizing environments and As(III) in reducing environments. In contrast, the Sb(V) species dominated in all but one pore-water sample, even under reducing conditions. Antimony(III) appears to preferentially precipitate or adsorb onto sulfides as evidenced by the prevalence of an Sb(III)-S secondary solid-phase and the lack of Sb(III)(aq) in the deeper zones. The As(V)–O solid phase became depleted with depth below the sediment–water interface, and the Sb(V)–O phase persisted under relatively reducing conditions. In the surficial zone at a site populated by Equisetum fluviatile (common horsetail), As and Sb were associated with organic material and appeared mobile in the root zone. In the zone below active plant growth, As and Sb were associated primarily with inorganic phases suggesting a release and reprecipitation of these elements upon plant death. The co-existence of reduced

  2. Mining association patterns of drug-interactions using post marketing FDA's spontaneous reporting data.

    Science.gov (United States)

    Ibrahim, Heba; Saad, Amr; Abdo, Amany; Sharaf Eldin, A

    2016-04-01

    Pharmacovigilance (PhV) is an important clinical activity with strong implications for population health and clinical research. The main goal of PhV is the timely detection of adverse drug events (ADEs) that are novel in their clinical nature, severity and/or frequency. Drug interactions (DI) pose an important problem in the development of new drugs and post marketing PhV that contribute to 6-30% of all unexpected ADEs. Therefore, the early detection of DI is vital. Spontaneous reporting systems (SRS) have served as the core data collection system for post marketing PhV since the 1960s. The main objective of our study was to particularly identify signals of DI from SRS. In addition, we are presenting an optimized tailored mining algorithm called "hybrid Apriori". The proposed algorithm is based on an optimized and modified association rule mining (ARM) approach. A hybrid Apriori algorithm has been applied to the SRS of the United States Food and Drug Administration's (U.S. FDA) adverse events reporting system (FAERS) in order to extract significant association patterns of drug interaction-adverse event (DIAE). We have assessed the resulting DIAEs qualitatively and quantitatively using two different triage features: a three-element taxonomy and three performance metrics. These features were applied on two random samples of 100 interacting and 100 non-interacting DIAE patterns. Additionally, we have employed logistic regression (LR) statistic method to quantify the magnitude and direction of interactions in order to test for confounding by co-medication in unknown interacting DIAE patterns. Hybrid Apriori extracted 2933 interacting DIAE patterns (including 1256 serious ones) and 530 non-interacting DIAE patterns. Referring to the current knowledge using four different reliable resources of DI, the results showed that the proposed method can extract signals of serious interacting DIAEs. Various association patterns could be identified based on the relationships among

  3. Prospectors and Developers Association of Canada Mining Matters: A Model of Effective Outreach

    Science.gov (United States)

    Hymers, L.; Heenan, S.

    2009-05-01

    Prospectors and Developers Association of Canada Mining Matters is a charitable organization whose mandate is to bring the wonders of Canada's geology and mineral resources to students, educators and industry. The organization provides current information about rocks, minerals, metals, and mining and offers exceptional educational resources, developed by teachers and for teachers that meet Junior, Intermediate and Senior Provincial Earth Science and Geography curriculum expectations. Since 1994, Mining Matters has reached more than 400,000 educators, students, industry representatives, and Aboriginal Youth through Earth Science resources. At the time of the program's inception, members of the Prospectors and Developers Association of Canada (PDAC) realized that their mining and mineral industry expertise could be of help to teachers and students. Consulting experts in education, government, and business, and the PDAC worked together to develop the first Mining Matters Earth Science curriculum kit for Grades 6 and 7 teachers in Ontario. PDAC Mining Matters became the official educational arm of the Association and a charitable organization in 1997. Since then, the organization has partnered with government, industry, and educators to develop bilingual Earth science teaching units for Grades 4 and 7, and senior High School. The teaching units consist of kits that contain curriculum correlated lesson plans, inform bulletins, genuine data sets, rock and mineral samples, equipment and additional instructional resources. Mining Matters offers instructional development workshops for the purposes of training pre-service and in- service educators to use our teaching units in the classroom. The workshops are meant to provide teachers with the knowledge and confidence they need to successfully employ the units in the classroom. Formal mechanisms for resource and workshop evaluations are in place. Overwhelmingly teacher feedback is positive, describing the excellence

  4. A Data Mining and Survey Study on Diseases Associated with Paraesophageal Hernia

    OpenAIRE

    Yang, Jianji; Logan, Judith

    2006-01-01

    Paraesophageal hernia is a severe form of hiatal hernia, characterized by the upward dislocation of the gastric fundus into the thoracic cavity. In this study, the 1999 National Inpatient Sample dataset of the Healthcare Cost and Utilization Project was analyzed using data mining techniques to explore disorders associated with paraesophageal hernia. The result of this data mining process was compared with a subsequent expert knowledge survey of 97 gastrointestinal tract surgeons. This two-ste...

  5. Short-term optimal operation of Three-gorge and Gezhouba cascade hydropower stations in non-flood season with operation rules from data mining

    International Nuclear Information System (INIS)

    Ma Chao; Lian Jijian; Wang Junna

    2013-01-01

    Highlights: ► Short-term optimal operation of Three-gorge and Gezhouba hydropower stations was studied. ► Key state variable and exact constraints were proposed to improve numerical model. ► Operation rules proposed were applied in population initiation step for faster optimization. ► Culture algorithm with difference evolution was selected as optimization method. ► Model and method proposed were verified by case study with feasible operation solutions. - Abstract: Information hidden in the characteristics and relationship data of a cascade hydropower stations can be extracted by data-mining approaches to be operation rules and optimization support information. In this paper, with Three-gorge and Gezhouba cascade hydropower stations as an example, two operation rules are proposed due to different operation efficiency of water turbines and tight water volume and hydraulic relationship between two hydropower stations. The rules are applied to improve optimization model with more exact decision and state variables and constraints. They are also used in the population initiation step to develop better individuals with culture algorithm with differential evolution as an optimization method. In the case study, total feasible population and the best solution based on an initial population with an operation rule can be obtained with a shorter computation time than that of a pure random initiated population. Amount of electricity generation in a dispatch period with an operation rule also increases with an average increase rate of 0.025%. For a fixed water discharge process of Three-gorge hydropower station, there is a better rule to decide an operation plan of Gezhouba hydropower station in which total hydraulic head for electricity generation is optimized and distributed with inner-plant economic operation considered.

  6. Association of rule of law and health outcomes: an ecological study.

    Science.gov (United States)

    Pinzon-Rondon, Angela Maria; Attaran, Amir; Botero, Juan Carlos; Ruiz-Sternberg, Angela Maria

    2015-10-29

    To explore whether the rule of law is a foundational determinant of health that underlies other socioeconomic, political and cultural factors that have been associated with health outcomes. Global project. Data set of 96 countries, comprising 91% of the global population. The following health indicators, infant mortality rate, maternal mortality rate, life expectancy, and cardiovascular disease and diabetes mortality rate, were included to explore their association with the rule of law. We used a novel Rule of Law Index, gathered from survey sources, in a cross-sectional and ecological design. The Index is based on eight subindices: (1) Constraints on Government Powers; (2) Absence of Corruption; (3) Order and Security; (4) Fundamental Rights; (5) Open Government; (6) Regulatory Enforcement, (7) Civil Justice; and (8) Criminal Justice. The rule of law showed an independent association with infant mortality rate, maternal mortality rate, life expectancy, and cardiovascular disease and diabetes mortality rate, after adjusting for the countries' level of per capita income, their expenditures in health, their level of political and civil freedom, their Gini measure of inequality and women's status (plaw remained significant in all the multivariate models, and the following adjustment for potential confounders remained robust for at least one or more of the health outcomes across all eight subindices of the rule of law. Findings show that the higher the country's level of adherence to the rule of law, the better the health of the population. It is necessary to start considering the country's adherence to the rule of law as a foundational determinant of health. Health advocates should consider the improvement of rule of law as a tool to improve population health. Conversely, lack of progress in rule of law may constitute a structural barrier to health improvement. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a

  7. Arsenic associated with historical gold mining in the Sierra Nevada foothills: Case study and field trip guide for Empire Mine State Historic Park, California

    Science.gov (United States)

    Alpers, Charles N.; Myers, Perry A; Millsap, Daniel; Regnier, Tamsen B; Bowell, Robert J.; Alpers, Charles N.; Jamieson, Heather E.; Nordstrom, D. Kirk; Majzlan, Juraj

    2014-01-01

    The Empire Mine, together with other mines in the Grass Valley mining district, produced at least 21.3 million troy ounces (663 tonnes) of gold (Au) during the 1850s through the 1950s, making it the most productive hardrock Au mining district in California history (Clark 1970). The Empire Mine State Historic Park (Empire Mine SHP or EMSHP), established in 1975, provides the public with an opportunity to see many well-preserved features of the historic mining and mineral processing operations (CDPR 2014a).A legacy of Au mining at Empire Mine and elsewhere is contamination of mine wastes and associated soils, surface waters, and groundwaters with arsenic (As), mercury (Hg), lead (Pb), and other metals. At EMSHP, As has been the principal contaminant of concern and the focus of extensive remediation efforts over the past several years by the State of California, Department of Parks and Recreation (DPR) and Newmont USA, Ltd. In addition, the site is the main focus of a multidisciplinary research project on As bioavailability and bioaccessibility led by the California Department of Toxic Substances Control (DTSC) and funded by the U.S. Environmental Protection Agency’s (USEPA’s) Brownfields Program.This chapter was prepared as a guide for a field trip to EMSHP held on June 14, 2014, in conjunction with a short course on “Environmental Geochemistry, Mineralogy, and Microbiology of Arsenic” held in Nevada City, California on June 15–16, 2014. This guide contains background information on geological setting, mining history, and environmental history at EMSHP and other historical Au mining districts in the Sierra Nevada, followed by descriptions of the field trip stops.

  8. 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 ...

  9. 26 CFR 1.614-3 - Rules relating to separate operating mineral interests in the case of mines.

    Science.gov (United States)

    2010-04-01

    ... method of mining the mineral, the location of the excavations or other workings in relation to the mineral deposit or deposits, and the topography of the area. The determination of the taxpayer as to the...

  10. 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.

  11. Exploring interdependencies in students' vacation portfolios using association rules

    NARCIS (Netherlands)

    Grigolon, A.B.; Kemperman, A.D.A.M.; Timmermans, H.J.P.

    2012-01-01

    The transition into adulthood is usually associated with changes and events, accompanied by developments in young people’s social status and consequently, some changes in travel and transport use. This makes the students’ segment highly relevant for both marketing companies and policy-makers. The

  12. Study on structuring the supervision system of coal mine associated with radionuclides in Xinjiang

    International Nuclear Information System (INIS)

    Feng Guangwen; Jia Xiahui

    2012-01-01

    Xinjiang is one of China's rich coal provinces (areas) and it accounts for about 40% national coal reserves. In the long-term radioactive scientific research, monitoring and environmental impact assessment works, we found parts of Yili and Hetian's coal was associated with higher radionuclide, and parts of coal seam even reached nuclear mining level. However the laws and regulations about associated radioactive coal mine supervision were not perfect, and the supervision system is still in the exploration. This article mainly started with the coal mine enterprises' geological prospecting reports, radiation environmental impact assessment and monitoring report preparation for environment acceptance checking and supervisory monitoring, controlled the coal radioactive pollution from the sources, and carried out the research of building Xinjiang associated radioactive coal mine supervision system. The establishment of supervision system will provide technical guidance for the enterprises' coal exploitation and cinders using on the one hand, and on the other hand will provide decision-making basis for strengthening the associated radioactive coal mine supervision for Xinjiang environmental regulators. (authors)

  13. Metal/nonmetal diesel particulate matter rule

    Energy Technology Data Exchange (ETDEWEB)

    Tomko, D.M. [United States Dept. of Labor, Mine Safety and Health Administration, Pittsburgh, PA (United States). Safety and Health Technology Center; Stackpole, R.P. [United States Dept. of Labor, Mine Safety and Health Administration, Triadelphia, WV (United States). Approval and Certification Center; Findlay, C.D. [United States Dept. of Labor, Mine Safety and Health Administration, Arlington, VA (United States). Metal/Nonmetal Safety and Health; Pomroy, W.H. [United States Dept. of Labor, Mine Safety and Health Administration, Duluth, MN (United States). Metal/Nonmetal North Central District

    2010-07-01

    The American Mine Safety and Health Administration (MSHA) issued a health standard in January 2001 designed to reduce exposure to diesel particulate matter (DPM) in underground metal and nonmetal mines. The rule established an interim concentration limit for DPM of 400 {mu}g/m{sup 3} of total carbon, to be followed in 2004 by a final limit of 160 {mu}g/m{sup 3} of total carbon. The 2001 rule was challenged in federal court by various mining trade associations and mining companies. The rule was subsequently amended. This paper highlighted the major provisions of the 2006 final rule and summarized MSHAs current compliance sampling procedures. The concentration limit was changed to a permissible exposure limit and the sampling surrogate was changed from total carbon to elemental carbon. The MSHA published a new rule in 2006 which based the final limit on a miner's personal exposure rather than a concentration limit. The final limit was phased in using 3 steps over 2 years. This paper also discussed engineering controls and a recent MSHA report on organic carbon, elemental carbon and total carbon emissions from a diesel engine fueled with various blends of standard diesel and biodiesel. In May 2008, about two-thirds of all underground metal/nonmetal mines achieved and maintained compliance with the rule. 20 refs.

  14. Applied data mining for business and industry

    CERN Document Server

    Giudici, Paolo

    2009-01-01

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

  15. 76 FR 63238 - Proximity Detection Systems for Continuous Mining Machines in Underground Coal Mines

    Science.gov (United States)

    2011-10-12

    ... Detection Systems for Continuous Mining Machines in Underground Coal Mines AGENCY: Mine Safety and Health... Agency's proposed rule addressing Proximity Detection Systems for Continuous Mining Machines in... proposed rule for Proximity Detection Systems on Continuous Mining Machines in Underground Coal Mines. Due...

  16. A procedure for NEPA assessment of selenium hazards associated with mining.

    Science.gov (United States)

    Lemly, A Dennis

    2007-02-01

    This paper gives step-by-step instructions for assessing aquatic selenium hazards associated with mining. The procedure was developed to provide the U.S. Forest Service with a proactive capability for determining the risk of selenium pollution when it reviews mine permit applications in accordance with the National Environmental Policy Act (NEPA). The procedural framework is constructed in a decision-tree format in order to guide users through the various steps, provide a logical sequence for completing individual tasks, and identify key decision points. There are five major components designed to gather information on operational parameters of the proposed mine as well as key aspects of the physical, chemical, and biological environment surrounding it--geological assessment, mine operation assessment, hydrological assessment, biological assessment, and hazard assessment. Validation tests conducted at three mines where selenium pollution has occurred confirmed that the procedure will accurately predict ecological risks. In each case, it correctly identified and quantified selenium hazard, and indicated the steps needed to reduce this hazard to an acceptable level. By utilizing the procedure, NEPA workers can be confident in their ability to understand the risk of aquatic selenium pollution and take appropriate action. Although the procedure was developed for the Forest Service it should also be useful to other federal land management agencies that conduct NEPA assessments, as well as regulatory agencies responsible for issuing coal mining permits under the authority of the Surface Mining Control and Reclamation Act (SMCRA) and associated Section 401 water quality certification under the Clean Water Act. Mining companies will also benefit from the application of this procedure because priority selenium sources can be identified in relation to specific mine operating parameters. The procedure will reveal the point(s) at which there is a need to modify operating

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

    Directory of Open Access Journals (Sweden)

    Chen Hsin-Hsi

    2008-10-01

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

  18. Ecological and human health risks associated with abandoned gold mine tailings contaminated soil

    DEFF Research Database (Denmark)

    Ngole-Jeme, Veronica Mpode; Fantke, Peter

    2017-01-01

    of arsenic (As), cadmium (Cd), chromium (Cr), cobalt (Co), copper (Cu), lead (Pb), manganese (Mn), nickel (Ni), and zinc (Zn) in soil samples from the area varied with the highest contamination factors (expressed as ratio of metal or metalloid concentration in the tailings contaminated soil......Gold mining is a major source of metal and metalloid emissions into the environment. Studies were carried out in Krugersdorp, South Africa, to evaluate the ecological and human health risks associated with exposure to metals and metalloids in mine tailings contaminated soils. Concentrations......×10−2 for As and Ni respectively among children, and 5×10−3 and 4×10−3 for As and Ni respectively among adults. There is significant potential ecological and human health risk associated with metal and metalloid exposure from contaminated soils around gold mine tailings dumps. This could be a potential contributing...

  19. DISEASES: text mining and data integration of disease-gene associations.

    Science.gov (United States)

    Pletscher-Frankild, Sune; Pallejà, Albert; Tsafou, Kalliopi; Binder, Janos X; Jensen, Lars Juhl

    2015-03-01

    Text mining is a flexible technology that can be applied to numerous different tasks in biology and medicine. We present a system for extracting disease-gene associations from biomedical abstracts. The system consists of a highly efficient dictionary-based tagger for named entity recognition of human genes and diseases, which we combine with a scoring scheme that takes into account co-occurrences both within and between sentences. We show that this approach is able to extract half of all manually curated associations with a false positive rate of only 0.16%. Nonetheless, text mining should not stand alone, but be combined with other types of evidence. For this reason, we have developed the DISEASES resource, which integrates the results from text mining with manually curated disease-gene associations, cancer mutation data, and genome-wide association studies from existing databases. The DISEASES resource is accessible through a web interface at http://diseases.jensenlab.org/, where the text-mining software and all associations are also freely available for download. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

  20. Biomedical Information Extraction: Mining Disease Associated Genes from Literature

    Science.gov (United States)

    Huang, Zhong

    2014-01-01

    Disease associated gene discovery is a critical step to realize the future of personalized medicine. However empirical and clinical validation of disease associated genes are time consuming and expensive. In silico discovery of disease associated genes from literature is therefore becoming the first essential step for biomarker discovery to…

  1. NIOSH (National Institute for Occupational Safety and Health) testimony to Department of Labor on the Mine Safety and Health Administration proposed rule: ionizing radiation standards for metal and nonmetal mines, August 13, 1987 by R. Niemeier

    International Nuclear Information System (INIS)

    1987-01-01

    Recommendations were offered for protecting workers against the health effects of ionizing radiation in metal and nonmetal mines. Available data demonstrating such health effects was reviewed and evidence supporting the technical feasibility of reducing the current Mine Safety and Health Administration (MSHA) standard was presented. Five recent studies indicated a significant increase in lung cancer rates associated with radon progeny exposure in underground mines. Additional studies indicated an exposure/response relationship in uranium miners. The influence of smoking on the association between radon progeny exposure and lung cancer was cited. Evidence has indicated that exposure to radon progeny carries a potential risk of developing occupationally induced lung cancer. Risk-assessment data supported the conclusion that miners with the same characteristics as the United States Public Health Service uranium miners cohort and who accrue a cumulative occupational exposure of 120 working level months, would have a lung cancer excess lifetime risk of about 35 to 40 lung cancer deaths per 1000 exposed miners. Modern mining methods using dilution ventilation as well as bulkheading and backfilling techniques make it possible to achieve substantial reductions in the cumulative exposure to radon progeny. Information was provided on sampling strategy, control technology, ventilation systems, respirators, and medical surveillance programs

  2. Understanding the mobilisation of metal pollution associated with historical mining in a carboniferous upland catchment.

    Science.gov (United States)

    Valencia-Avellan, Magaly; Slack, Rebecca; Stockdale, Anthony; Mortimer, Robert John George

    2017-08-16

    Point and diffuse pollution from metal mining has led to severe environmental damage worldwide. Mine drainage is a significant problem for riverine ecosystems, it is commonly acidic (AMD), but neutral mine drainage (NMD) can also occur. A representative environment for studying metal pollution from NMD is provided by carboniferous catchments characterised by a circumneutral pH and high concentrations of carbonates, supporting the formation of secondary metal-minerals as potential sinks of metals. The present study focuses on understanding the mobility of metal pollution associated with historical mining in a carboniferous upland catchment. In the uplands of the UK, river water, sediments and spoil wastes were collected over a period of fourteen months, samples were chemically analysed to identify the main metal sources and their relationships with geological and hydrological factors. Correlation tests and principal component analysis suggest that the underlying limestone bedrock controls pH and weathering reactions. Significant metal concentrations from mining activities were measured for zinc (4.3 mg l -1 ), and lead (0.3 mg l -1 ), attributed to processes such as oxidation of mined ores (e.g. sphalerite, galena) or dissolution of precipitated secondary metal-minerals (e.g. cerussite, smithsonite). Zinc and lead mobility indicated strong dependence on biogeochemistry and hydrological conditions (e.g. pH and flow) at specific locations in the catchment. Annual loads of zinc and lead (2.9 and 0.2 tonnes per year) demonstrate a significant source of both metals to downstream river reaches. Metal pollution results in a large area of catchment having a depleted chemical status with likely effects on the aquatic ecology. This study provides an improved understanding of geological and hydrological processes controlling water chemistry, which is critical to assessing metal sources and mobilization, especially in neutral mine drainage areas.

  3. Integrated Text Mining and Chemoinformatics Analysis Associates Diet to Health Benefit at Molecular Level

    DEFF Research Database (Denmark)

    Jensen, Kasper; Panagiotou, Gianni; Kouskoumvekaki, Irene

    2014-01-01

    , lipids and nutrients. In this work, we applied text mining and Naïve Bayes classification to assemble the knowledge space of food-phytochemical and food-disease associations, where we distinguish between disease prevention/amelioration and disease progression. We subsequently searched for frequently...

  4. A study of trends in occupational risks associated with coal mining

    Energy Technology Data Exchange (ETDEWEB)

    Amoundru, C.

    1980-10-01

    The occupational risks associated with underground coal mining can be categorized as either industrial accidents or occupational diseases. Since 1957, the number of fatal accidents per million tons of coal produced has dropped by a factor of four. The number of industrial accidents in general decreased by 30% during 1967-75. The main occupational diseases affecting miners are arthrosis, deafness, and pneumoconiosis. To make an objective comparison with the health hazards from other sources of energy, the probable risks facing workers in a modern mine should be compared with those currently confronting workers in other industries.

  5. Improved Personalized Recommendation Based on Causal Association Rule and Collaborative Filtering

    Science.gov (United States)

    Lei, Wu; Qing, Fang; Zhou, Jin

    2016-01-01

    There are usually limited user evaluation of resources on a recommender system, which caused an extremely sparse user rating matrix, and this greatly reduce the accuracy of personalized recommendation, especially for new users or new items. This paper presents a recommendation method based on rating prediction using causal association rules.…

  6. Impact of gold mining associated with mercury contamination in soil, biota sediments and tailings in Kenya.

    Science.gov (United States)

    Odumo, Benjamin Okang'; Carbonell, Gregoria; Angeyo, Hudson Kalambuka; Patel, Jayanti Purshottam; Torrijos, Manuel; Rodríguez Martín, José Antonio

    2014-11-01

    This work considered the environmental impact of artisanal mining gold activity in the Migori-Transmara area (Kenya). From artisanal gold mining, mercury is released to the environment, thus contributing to degradation of soil and water bodies. High mercury contents have been quantified in soil (140 μg kg(-1)), sediment (430 μg kg(-1)) and tailings (8,900 μg kg(-1)), as expected. The results reveal that the mechanism for transporting mercury to the terrestrial ecosystem is associated with wet and dry depositions. Lichens and mosses, used as bioindicators of pollution, are related to the proximity to mining areas. The further the distance from mining areas, the lower the mercury levels. This study also provides risk maps to evaluate potential negative repercussions. We conclude that the Migori-Transmara region can be considered a strongly polluted area with high mercury contents. The technology used to extract gold throughout amalgamation processes causes a high degree of mercury pollution around this gold mining area. Thus, alternative gold extraction methods should be considered to reduce mercury levels that can be released to the environment.

  7. Integrated assessmet of the impacts associated with uranium mining and milling

    International Nuclear Information System (INIS)

    Parzyck, D.C.; Baes, C.F. III; Berry, L.G.

    1979-07-01

    The occupational health and safety impacts are assessed for domestic underground mining, open pit mining, and milling. Public health impacts are calculated for a population of 53,000 located within 88 km (55 miles) of a typical southwestern uranium mill. The collective annual dose would be 6.5 man-lung rem/year, 89% of which is from 222 Rn emitted from mill tailings. The dose to the United States population is estimated to be 6 x 10 4 man-lung rem from combined mining and milling operations. This may be comparedd with 5.7 x 10 5 man-lung rem from domestic use of natural gas and 4.4 x 10 7 man-lung rem from building interiors. Unavoidable adverse environmental impacts appear to be severe in a 250 ha area surrounding a mill site but negligible in the entire potentially impacted area (500,000 ha). The contemporary uranium resource and supply industry and its institutional settings are described in relation to the socio-economic impacts likely to emerge from high levels of uranium mining and milling. Radon and radon daughter monitoring techniques associated with uranium mining and milling are discussed

  8. Integrated assessmet of the impacts associated with uranium mining and milling

    Energy Technology Data Exchange (ETDEWEB)

    Parzyck, D.C.; Baes, C.F. III; Berry, L.G.

    1979-07-01

    The occupational health and safety impacts are assessed for domestic underground mining, open pit mining, and milling. Public health impacts are calculated for a population of 53,000 located within 88 km (55 miles) of a typical southwestern uranium mill. The collective annual dose would be 6.5 man-lung rem/year, 89% of which is from /sup 222/Rn emitted from mill tailings. The dose to the United States population is estimated to be 6 x 10/sup 4/ man-lung rem from combined mining and milling operations. This may be comparedd with 5.7 x 10/sup 5/ man-lung rem from domestic use of natural gas and 4.4 x 10/sup 7/ man-lung rem from building interiors. Unavoidable adverse environmental impacts appear to be severe in a 250 ha area surrounding a mill site but negligible in the entire potentially impacted area (500,000 ha). The contemporary uranium resource and supply industry and its institutional settings are described in relation to the socio-economic impacts likely to emerge from high levels of uranium mining and milling. Radon and radon daughter monitoring techniques associated with uranium mining and milling are discussed.

  9. Environmental impacts associated with an abandoned mine in the Witbank Coalfield, South Africa

    International Nuclear Information System (INIS)

    Bell, F.G.; Bullock, S.E.T.; Haelbich, T.F.J.; Lindsay, P.

    2001-01-01

    Mining at Middelburg Colliery in the Witbank Coalfield commenced at the turn of the last century. Initially, there was little environmental degradation associated with mining activities; however, in the late 1930s, a pillar-robbing programme commenced. This has had a marked effect on the environment. Some of the most notable primary effects include subsidence, the appearance of tension cracks at the surface and crownhole development. Secondary effects include spontaneous combustion of the coal worked, as air has been provided with ready access to the mine, accelerated subsidence due to the strength of many pillars being reduced by burning, and a marked deterioration of groundwater quality in the area due to the seepage of acid mine drainage from the mine. Spoil heaps also form blemishes on the landscape. These contain significant amounts of coal and have undergone spontaneous combustion. The deterioration in the quality of water has led to the decimation of vegetation in some areas and the eradication of aquatic flora and fauna in a nearby stream

  10. Radioactivity in groundwater associated with uranium and phosphate mining and processing

    International Nuclear Information System (INIS)

    Kaufmann, R.F.

    1981-01-01

    From 1975 to 1980 USEPA investigations of the uranium and phosphate mining and milling industries addressed associated changes in the radionuclide content of nearby water resources. Available data for 226 Ra in central Florida aquifers show no significant difference in phosphate mineralized vs. nonmineralized areas. Apparently neither mineralization nor the industry cause significant increase in the Ra content of groundwater. Uranium mining and milling in a number of Western States (e.g. New Mexico, Wyoming, Colorado, Washington) cause locally increased levels of U, Ra and Th in shallow groundwater, but potable water supplies have not been adversely affected. Contamination of deep aquifers does not appear to occur, although elevated levels of Ra and U are present in many mine water discharges as a result of ore body oxidation and leaching. Model underground and surface U mines were used to evaluate chemical loading of 238 U, 226 Ra, 210 Pb and 210 Po to local and regional hydrographic units. Infiltration of mine water to potable groundwater and suspension/solution of contaminants in flood water constitute the principal elements of the aqueous pathway

  11. Element flows associated with marine shore mine tailings deposits.

    Science.gov (United States)

    Dold, Bernhard

    2006-02-01

    From 1938 until 1975, flotation tailings from the Potrerillos--El Salvador mining district (porphyry copper deposits) were discharged into the El Salado valley and transported in suspension to the sea at Chaliaral Bay, Atacama Desert, northern Chile. Over 220 Mt of tailings, averaging 0.8 +/- 0.25 wt % of pyrite, were deposited into the bay, resulting in over a 1 kilometer seaward displacement of the shoreline and an estimated 10-15 m thick tailings accumulation covering a approximately 4 km2 surface area. The Chaniaral case was classified by the United Nations Environmental Programme (UNEP) in 1983 as one of the most serious cases of marine contamination in the Pacific area. Since 1975, the tailings have been exposed to oxidation, resulting in a 70-188 cm thick low-pH (2.6-4) oxidation zone at the top with liberation of divalent metal cations, such as Cu2+, Ni2+, and Zn2+ (up to 2265 mg/L, 18.1 mg/L, and 20.3 mg/ L, respectively). Evaporation-induced transport capillarity led to metal enrichment atthe tailings surface (e.g. up to 2.4% Cu) in the form of secondary chlorides and/or sulfates (dominated by eriochalcite [CuCl.H2O] and halite). These, mainly water-soluble, secondary minerals were exposed to eolian transport in the direction of the Village of Chañaral by the predominant W-SW winds. Two element-flow directions (toward the tailings surface, via capillarity, and toward the sea) and two element groups with different geochemical behaviors (cations such as Cu, Zn, Ni, and oxyanions such as As and Mo) could be distinguished. It can be postulated, that the sea is mainly affected by the following: As, Mo, Cu, and Zn contamination, which were liberated from the oxidation zone from the tailings and mobilized through the tidal cycle, and by Cu and Zn from the subsurface waters flowing in the El Salado valley (up to 19 mg/L and 12 mg/L Zn, respectively), transported as chloro complexes at neutral pH.

  12. DrugQuest - a text mining workflow for drug association discovery.

    Science.gov (United States)

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

    2016-06-06

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

  13. Association of rule of law and health outcomes: an ecological study

    Science.gov (United States)

    Pinzon-Rondon, Angela Maria; Attaran, Amir; Botero, Juan Carlos; Ruiz-Sternberg, Angela Maria

    2015-01-01

    Objectives To explore whether the rule of law is a foundational determinant of health that underlies other socioeconomic, political and cultural factors that have been associated with health outcomes. Setting Global project. Participants Data set of 96 countries, comprising 91% of the global population. Primary and secondary outcome measures The following health indicators, infant mortality rate, maternal mortality rate, life expectancy, and cardiovascular disease and diabetes mortality rate, were included to explore their association with the rule of law. We used a novel Rule of Law Index, gathered from survey sources, in a cross-sectional and ecological design. The Index is based on eight subindices: (1) Constraints on Government Powers; (2) Absence of Corruption; (3) Order and Security; (4) Fundamental Rights; (5) Open Government; (6) Regulatory Enforcement, (7) Civil Justice; and (8) Criminal Justice. Results The rule of law showed an independent association with infant mortality rate, maternal mortality rate, life expectancy, and cardiovascular disease and diabetes mortality rate, after adjusting for the countries’ level of per capita income, their expenditures in health, their level of political and civil freedom, their Gini measure of inequality and women's status (pconstitute a structural barrier to health improvement. PMID:26515684

  14. G2D: a tool for mining genes associated with disease

    OpenAIRE

    Perez-Iratxeta, Carolina; Wjst, Matthias; Bork, Peer; Andrade, Miguel A

    2005-01-01

    Abstract Background Human inherited diseases can be associated by genetic linkage with one or more genomic regions. The availability of the complete sequence of the human genome allows examining those locations for an associated gene. We previously developed an algorithm to prioritize genes on a chromosomal region according to their possible relation to an inherited disease using a combination of data mining on biomedical databases and gene sequence analysis. Results We have implemented this ...

  15. Mining Educational Data to Analyze the Student Motivation Behavior

    OpenAIRE

    Kunyanuth Kularbphettong; Cholticha Tongsiri

    2012-01-01

    The purpose of this research aims to discover the knowledge for analysis student motivation behavior on e-Learning based on Data Mining Techniques, in case of the Information Technology for Communication and Learning Course at Suan Sunandha Rajabhat University. The data mining techniques was applied in this research including association rules, classification techniques. The results showed that using data mining technique can indicate the important variables that influenc...

  16. GWA study data mining and independent replication identify cardiomyopathy-associated 5 (CMYA5) as a risk gene for schizophrenia

    NARCIS (Netherlands)

    Chen, X.; Lee, G.; Maher, B. S.; Fanous, A. H.; Chen, J.; Zhao, Z.; Guo, A.; van den Oord, E.; Sullivan, P. F.; Shi, J.; Levinson, D. F.; Gejman, P. V.; Sanders, A.; Duan, J.; Owen, M. J.; Craddock, N. J.; O'Donovan, M. C.; Blackman, J.; Lewis, D.; Kirov, G. K.; Qin, W.; Schwab, S.; Wildenauer, D.; Chowdari, K.; Nimgaonkar, V.; Straub, R. E.; Weinberger, D. R.; O'Neill, F. A.; Walsh, D.; Bronstein, M.; Darvasi, A.; Lencz, T.; Malhotra, A. K.; Rujescu, D.; Giegling, I.; Werge, T.; Hansen, T.; Ingason, A.; Nöethen, M. M.; Rietschel, M.; Cichon, S.; Djurovic, S.; Andreassen, O. A.; Cantor, R. M.; Ophoff, R.; Corvin, A.; Morris, D. W.; Gill, M.; Pato, C. N.; Pato, M. T.; Macedo, A.; Gurling, H. M. D.; McQuillin, A.; Pimm, J.; Hultman, C.; Lichtenstein, P.; Sklar, P.; Purcell, S. M.; Scolnick, E.; St Clair, D.; Blackwood, D. H. R.; Kendler, K. S.; Kahn, René S.; Linszen, Don H.; van Os, Jim; Wiersma, Durk; Bruggeman, Richard; Cahn, Wiepke; de Haan, Lieuwe; Krabbendam, Lydia; Myin-Germeys, Inez; O'Donovan, Michael C.; Kirov, George K.; Craddock, Nick J.; Holmans, Peter A.; Williams, Nigel M.; Georgieva, Lyudmila; Nikolov, Ivan; Norton, N.; Williams, H.; Toncheva, Draga; Milanova, Vihra; Owen, Michael J.; Hultman, Christina M.; Lichtenstein, Paul; Thelander, Emma F.; Sullivan, Patrick; Morris, Derek W.; O'Dushlaine, Colm T.; Kenny, Elaine; Quinn, Emma M.; Gill, Michael; Corvin, Aiden; McQuillin, Andrew; Choudhury, Khalid; Datta, Susmita; Pimm, Jonathan; Thirumalai, Srinivasa; Puri, Vinay; Krasucki, Robert; Lawrence, Jacob; Quested, Digby; Bass, Nicholas; Gurling, Hugh; Crombie, Caroline; Fraser, Gillian; Kuan, Soh Leh; Walker, Nicholas; St Clair, David; Blackwood, Douglas H. R.; Muir, Walter J.; McGhee, Kevin A.; Pickard, Ben; Malloy, Pat; Maclean, Alan W.; van Beck, Margaret; Wray, Naomi R.; Macgregor, Stuart; Visscher, Peter M.; Pato, Michele T.; Medeiros, Helena; Middleton, Frank; Carvalho, Celia; Morley, Christopher; Fanous, Ayman; Conti, David; Knowles, James A.; Ferreira, Carlos Paz; Macedo, Antonio; Azevedo, M. Helena; Pato, Carlos N.; Stone, Jennifer L.; Ruderfer, Douglas M.; Kirby, Andrew N.; Ferreira, Manuel A. R.; Daly, Mark J.; Purcell, Shaun M.; Sklar, Pamela; Chambert, Kimberly; Kuruvilla, Finny; Gabriel, Stacey B.; Ardlie, Kristin; Moran, Jennifer L.; Scolnick, Edward M.

    2011-01-01

    We conducted data-mining analyses using the Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) and molecular genetics of schizophrenia genome-wide association study supported by the genetic association information network (MGS-GAIN) schizophrenia data sets and performed

  17. 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...

  18. 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.

  19. 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.

  20. Cost efficiency of the non-associative flow rule simulation of an industrial component

    Science.gov (United States)

    Galdos, Lander; de Argandoña, Eneko Saenz; Mendiguren, Joseba

    2017-10-01

    In the last decade, metal forming industry is becoming more and more competitive. In this context, the FEM modeling has become a primary tool of information for the component and process design. Numerous researchers have been focused on improving the accuracy of the material models implemented on the FEM in order to improve the efficiency of the simulations. Aimed at increasing the efficiency of the anisotropic behavior modelling, in the last years the use of non-associative flow rule models (NAFR) has been presented as an alternative to the classic associative flow rule models (AFR). In this work, the cost efficiency of the used flow rule model has been numerically analyzed by simulating an industrial drawing operation with two different models of the same degree of flexibility: one AFR model and one NAFR model. From the present study, it has been concluded that the flow rule has a negligible influence on the final drawing prediction; this is mainly driven by the model parameter identification procedure. Even though the NAFR formulation is complex when compared to the AFR, the present study shows that the total simulation time while using explicit FE solvers has been reduced without loss of accuracy. Furthermore, NAFR formulations have an advantage over AFR formulations in parameter identification because the formulation decouples the yield stress and the Lankford coefficients.

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

    Science.gov (United States)

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

    2014-01-01

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

  2. Quality prediction modeling for multistage manufacturing based on classification and association rule mining

    OpenAIRE

    Kao Hung-An; Hsieh Yan-Shou; Chen Cheng-Hui; Lee Jay

    2017-01-01

    For manufacturing enterprises, product quality is a key factor to assess production capability and increase their core competence. To reduce external failure cost, many research and methodology have been introduced in order to improve process yield rate, such as TQC/TQM, Shewhart CycleDeming's 14 Points, etc. Nowadays, impressive progress has been made in process monitoring and industrial data analysis because of the Industry 4.0 trend. Industries start to utilize quality control (QC) methodo...

  3. A Business Intelligence Model to Predict Bankruptcy using Financial Domain Ontology with Association Rule Mining Algorithm

    OpenAIRE

    Martin, A.; Manjula, M.; Venkatesan, Dr. V. Prasanna

    2011-01-01

    Today in every organization financial analysis provides the basis for understanding and evaluating the results of business operations and delivering how well a business is doing. This means that the organizations can control the operational activities primarily related to corporate finance. One way that doing this is by analysis of bankruptcy prediction. This paper develops an ontological model from financial information of an organization by analyzing the Semantics of the financial statement...

  4. Adverse health effects in Canada geese (Branta canadensis) associated with waste from zinc and lead mines in the Tri-State Mining District (Kansas, Oklahoma, and Missouri, USA).

    Science.gov (United States)

    van der Merwe, Deon; Carpenter, James W; Nietfeld, Jerome C; Miesner, John F

    2011-07-01

    Lead and zinc poisoning have been recorded in a variety of bird species, including migrating waterfowl such as Canada Geese (Branta canadensis), at sites contaminated with mine waste from lead and zinc mines in the Tri-State Mining District, Kansas, Oklahoma, and Missouri, USA. The adverse health impacts from mine waste on these birds may, however, be more extensive than is apparent from incidental reports of clinical disease. To characterize health impacts from mine waste on Canada Geese that do not have observable signs of poisoning, four to eight apparently healthy birds per site were collected from four contaminated sites and an uncontaminated reference site, and examined for physical and physiologic evidence of metals poisoning. Tissue concentrations of silver, aluminum, arsenic, barium, cadmium, cobalt, chromium, copper, iron, magnesium, manganese, molybdenum, nickel, lead, selenium, thallium, vanadium, and zinc were determined by inductively coupled plasma mass spectroscopy. Adverse health effects due to lead were characterized by assessing blood δ-aminolevulinic acid dehydratase (ALAD) enzyme activity. Adverse effects associated with zinc poisoning were determined from histologic examination of pancreas tissues. Elevated tissue lead concentrations and inhibited blood ALAD enzyme activities were consistently found in birds at all contaminated sites. Histopathologic signs of zinc poisoning, including fibrosis and vacuolization, were associated with elevated pancreatic zinc concentrations at one of the study sites. Adverse health effects associated with other analyzed elements, or tissue concentrations indicating potentially toxic exposure levels to these elements, were not observed.

  5. Mineralogic and element association of coals from the Gevra mine, Korba coal field, Madhya Pradesh, India

    International Nuclear Information System (INIS)

    Hart, B.R.; Powell, M.A.; Fyfe, W.S.; Sahu, K.C.; Tripathy, S.

    1991-01-01

    As a part of a project to study the content and distribution of trace elements in coals and coal by-products from coal mining areas of India, the mineral and elemental composition of the whole coal and concentration of the selective elements in the whole coal mined from the Gevra mine of the Korba coal field in Madhya Pradesh are studied. The vertical trend of the selected elements are defined and possible relationships of these elements to the minerals present in or associated with the above coal are examined. The Gevra Coals have ash contact ( 3 times world average) and low sulphur content (1/4 of world average). Most elements are found to be positively correlated with ash indicating an inorganic association. Elements which show organic affinity include S, Cl, I and In. Fe, Cu, Zn and Pb occur in sulfide phases, the dominant Fe phase identified is siderite which also contain Mn and Mg. Th and U along with varying proportions of rare earths, Ce, Dy, La and Y have been identified with discrete phosphate minerals. Most trace elements have been found to be concentrated in the upper and lower portions of the coal seam exposed in Gevra mine and in partings. It is, therefore, suggested that selective mining and removal of high ash/inorganic material, particularly the upper and lower portion of the seam, will greatly reduce the mobilization of Al, As, Co, Fe, Hf, Sc, Si, Ti and to a lesser degree Cr, La, Mn, Th U and V during combustion of coal in power plants and consequently will reduce the influx of trace elements to the environment. (M.G.B.). 23 refs., 5 figs

  6. Chronic respiratory disease among the elderly in South Africa: any association with proximity to mine dumps?

    Science.gov (United States)

    Nkosi, Vusumuzi; Wichmann, Janine; Voyi, Kuku

    2015-04-03

    There is increasing evidence that environmental factors such as air pollution from mine dumps, increase the risk of chronic respiratory symptoms and diseases. The aim of this study was to investigate the association between proximity to mine dumps and prevalence of chronic respiratory disease in people aged 55 years and older. Elderly persons in communities 1-2 km (exposed) and 5 km (unexposed), from five pre-selected mine dumps in Gauteng and North West Province, in South Africa were included in a cross-sectional study. Structured interviews were conducted with 2397 elderly people, using a previously validated ATS-DLD-78 questionnaire from the British Medical Research Council. Exposed elderly persons had a significantly higher prevalence of chronic respiratory symptoms and diseases than those who were unexposed., Results from the multiple logistic regression analysis indicated that living close to mine dumps was significantly associated with asthma (OR = 1.57; 95% CI: 1.20 - 2.05), chronic bronchitis (OR = 1.74; 95 CI: 1.25 - 2.39), chronic cough (OR = 2.02; 95% CI: 1.58 - 2.57), emphysema (OR = 1.75; 95% CI: 1.11 - 2.77), pneumonia (OR = 1.38; 95% CI: 1.07 - 1.77) and wheeze (OR = 2.01; 95% CI: 1.73 - 2.54). Residing in exposed communities, current smoking, ex-smoking, use of paraffin as main residential cooking/heating fuel and low level of education emerged as independent significant risk factors for chronic respiratory symptoms and diseases. This study suggests that there is a high level of chronic respiratory symptoms and diseases among elderly people in communities located near to mine dumps in South Africa.

  7. Mining Long, Sharable Patterns in Trajectories of Moving Objects

    DEFF Research Database (Denmark)

    Gidofalvi, Gyozo; Pedersen, Torben Bach

    2009-01-01

    The efficient analysis of spatio-temporal data, generated by moving objects, is an essential requirement for intelligent location-based services. Spatio-temporal rules can be found by constructing spatio-temporal baskets, from which traditional association rule mining methods can discover spatio...

  8. 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.

  9. Environmental risks associated to wind erosion in a metal mining area from SE Spain

    International Nuclear Information System (INIS)

    Garcia Fernandez, G.; Romero Diaz, A.

    2009-01-01

    Soils and mining wastes from the Mediterranean mining area placed in the Sierra Minera Mountains are highly enriched in heavy metals such as lead and zinc, but also other metals such as cadmium and arsenic. Wind erosion in this area could be considered extremely high and hazards associated to this eroded sediments seems to be high because the huge amount of metals present in this wastes. Therefore, combination of high erosion rates and high metal concentration in this mining waste, make those environmental risks can be considered high for the surrounding ecosystems, but also for public health of the nearby villages and towns. In order, to study these wind erosion processes over these mining materials, some experiments for the evaluation of the transportation of soil particles were carried out. Erosion rates in this realm is particularly important during spring months, when increased activity of the eastern winds brings intense soil dragging, with strong effects on the metals dispersion, including the massive removal of sediments. (Author) 16 refs.

  10. Soil heavy metal contamination and health risks associated with artisanal gold mining in Tongguan, Shaanxi, China.

    Science.gov (United States)

    Xiao, Ran; Wang, Shuang; Li, Ronghua; Wang, Jim J; Zhang, Zengqiang

    2017-07-01

    Soil contamination with heavy metals due to mining activities poses risks to ecological safety and human well-being. Limited studies have investigated heavy metal pollution due to artisanal mining. The present study focused on soil contamination and the health risk in villages in China with historical artisanal mining activities. Heavy metal levels in soils, tailings, cereal and vegetable crops were analyzed and health risk assessed. Additionally, a botany investigation was conducted to identify potential plants for further phytoremediation. The results showed that soils were highly contaminated by residual tailings and previous mining activities. Hg and Cd were the main pollutants in soils. The Hg and Pb concentrations in grains and some vegetables exceeded tolerance limits. Moreover, heavy metal contents in wheat grains were higher than those in maize grains, and leafy vegetables had high concentrations of metals. Ingestion of local grain-based food was the main sources of Hg, Cd, and Pb intake. Local residents had high chronic risks due to the intake of Hg and Pb, while their carcinogenic risk associated with Cd through inhalation was low. Three plants (Erigeron canadensis L., Digitaria ciliaris (Retz.) Koel., and Solanum nigrum L.) were identified as suitable species for phytoremediation. Copyright © 2017. Published by Elsevier Inc.

  11. Environmental risks associated to wind erosion in a metal mining area from SE Spain

    Energy Technology Data Exchange (ETDEWEB)

    Garcia Fernandez, G.; Romero Diaz, A.

    2009-07-01

    Soils and mining wastes from the Mediterranean mining area placed in the Sierra Minera Mountains are highly enriched in heavy metals such as lead and zinc, but also other metals such as cadmium and arsenic. Wind erosion in this area could be considered extremely high and hazards associated to this eroded sediments seems to be high because the huge amount of metals present in this wastes. Therefore, combination of high erosion rates and high metal concentration in this mining waste, make those environmental risks can be considered high for the surrounding ecosystems, but also for public health of the nearby villages and towns. In order, to study these wind erosion processes over these mining materials, some experiments for the evaluation of the transportation of soil particles were carried out. Erosion rates in this realm is particularly important during spring months, when increased activity of the eastern winds brings intense soil dragging, with strong effects on the metals dispersion, including the massive removal of sediments. (Author) 16 refs.

  12. Text mining facilitates database curation - extraction of mutation-disease associations from Bio-medical literature.

    Science.gov (United States)

    Ravikumar, Komandur Elayavilli; Wagholikar, Kavishwar B; Li, Dingcheng; Kocher, Jean-Pierre; Liu, Hongfang

    2015-06-06

    Advances in the next generation sequencing technology has accelerated the pace of individualized medicine (IM), which aims to incorporate genetic/genomic information into medicine. One immediate need in interpreting sequencing data is the assembly of information about genetic variants and their corresponding associations with other entities (e.g., diseases or medications). Even with dedicated effort to capture such information in biological databases, much of this information remains 'locked' in the unstructured text of biomedical publications. There is a substantial lag between the publication and the subsequent abstraction of such information into databases. Multiple text mining systems have been developed, but most of them focus on the sentence level association extraction with performance evaluation based on gold standard text annotations specifically prepared for text mining systems. We developed and evaluated a text mining system, MutD, which extracts protein mutation-disease associations from MEDLINE abstracts by incorporating discourse level analysis, using a benchmark data set extracted from curated database records. MutD achieves an F-measure of 64.3% for reconstructing protein mutation disease associations in curated database records. Discourse level analysis component of MutD contributed to a gain of more than 10% in F-measure when compared against the sentence level association extraction. Our error analysis indicates that 23 of the 64 precision errors are true associations that were not captured by database curators and 68 of the 113 recall errors are caused by the absence of associated disease entities in the abstract. After adjusting for the defects in the curated database, the revised F-measure of MutD in association detection reaches 81.5%. Our quantitative analysis reveals that MutD can effectively extract protein mutation disease associations when benchmarking based on curated database records. The analysis also demonstrates that incorporating

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

    Science.gov (United States)

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

    2018-03-07

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

  14. PENGEMBANGAN SISTEM EVALUASI DESAIN PRODUK BERBASIS ROTAN DENGAN PENDEKATAN REKAYASA KANSEI DAN ASSOCIATION RULES SYSTEM

    OpenAIRE

    Vonny Setiaries Johan; Sapta Rahardja; E Gumbira Said; Taufik Djatna

    2016-01-01

    In product development, it is very important for manufacturers to find out what the customer wants from the product. On the other hand, manufacturers do not know clearly about what the customer wants from the product. This study proposes an evaluation method of product design using Kansei engineering methods and association rules approach. Using rattan dining chair as the object, the chair design divided into five elements, which are backrest, seat, armrest, base and woven. In this study, Kan...

  15. Profiling of high-frequency accident locations by use of association rules

    OpenAIRE

    GEURTS, Karolien; WETS, Geert; BRIJS, Tom; VANHOOF, Koen

    2003-01-01

    In Belgium, traffic safety is one of the government's highest priorities. The identification and profiling of black spots and black zones (geographical locations with high concentrations of traffic accidents) in terms of accident-related data and location characteristics must provide new insights into the complexity and causes of road accidents, which, in turn, provide valuable input for governmental actions. Association rules were used to identify accident-related circumstances that frequent...

  16. Associations of Parental Rules and Socioeconomic Position With Preschool Children's Sedentary Behaviour and Screen Time.

    Science.gov (United States)

    Downing, Katherine L; Hinkley, Trina; Hesketh, Kylie D

    2015-04-01

    There is little current understanding of the influences on sedentary behavior and screen time in preschool children. This study investigated socioeconomic position (SEP) and parental rules as potential correlates of preschool children's sedentary behavior and screen time. Data from the Healthy Active Preschool Years (HAPPY) Study were used. Participating parents reported their child's usual weekly screen time and their rules to regulate their child's screen time. Children wore accelerometers for 8 days to objectively measure sedentary time. Children whose parents limited television viewing spent significantly less time in that behavior and in total screen time; however, overall sedentary behavior was unaffected. An association between parents limiting computer/electronic game use and time spent on the computer was found for girls only. SEP was inversely associated with girls', but not boys', total screen time and television viewing. As parental rules were generally associated with lower levels of screen time, intervention strategies could potentially encourage parents to set limits on, and switch off, screen devices. Intervention strategies should target preschool children across all SEP areas, as there was no difference by SEP in overall sedentary behavior or screen time for boys.

  17. Beating Obesity: Factors Associated with Interest in Workplace Weight Management Assistance in the Mining Industry

    OpenAIRE

    Street, Tamara D.; Thomas, Drew L.

    2016-01-01

    Background: Rates of overweight and obese Australians are high and continue to rise, putting a large proportion of the population at risk of chronic illness. Examining characteristics associated with preference for a work-based weight-loss program will enable employers to better target programs to increase enrolment and benefit employees' health and fitness for work. Methods: A cross-sectional survey was undertaken at two Australian mining sites. The survey collected information on employe...

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

    OpenAIRE

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

    2016-01-01

    Background Atheoretical large-scale data mining techniques using machine learning algorithms have promise in the analysis of large epidemiological datasets. This study illustrates the use of a hybrid methodology for variable selection that took account of missing data and complex survey design to identify key biomarkers associated with depression from a large epidemiological study. Methods The study used a three-step methodology amalgamating multiple imputation, a machine learning boosted reg...

  19. Study on Association between Spatial Distribution of Metal Mines and Disease Mortality: A Case Study in Suxian District, South China

    Science.gov (United States)

    Song, Daping; Jiang, Dong; Wang, Yong; Chen, Wei; Huang, Yaohuan; Zhuang, Dafang

    2013-01-01

    Metal mines release toxic substances into the environment and can therefore negatively impact the health of residents in nearby regions. This paper sought to investigate whether there was excess disease mortality in populations in the vicinity of the mining area in Suxian District, South China. The spatial distribution of metal mining and related activities from 1985 to 2012, which was derived from remote sensing imagery, was overlapped with disease mortality data. Three hotspot areas with high disease mortality were identified around the Shizhuyuan mine sites, i.e., the Dengjiatang metal smelting sites, and the Xianxichong mine sites. Disease mortality decreased with the distance to the mining and smelting areas. Population exposure to pollution was estimated on the basis of distance from town of residence to pollution source. The risk of dying according to disease mortality rates was analyzed within 7–25 km buffers. The results suggested that there was a close relationship between the risk of disease mortality and proximity to the Suxian District mining industries. These associations were dependent on the type and scale of mining activities, the area influenced by mining and so on. PMID:24135822

  20. Mining-induced fault reactivation associated with the main conveyor belt roadway and safety of the Barapukuria Coal Mine in Bangladesh: Constraints from BEM simulations

    Energy Technology Data Exchange (ETDEWEB)

    Islam, Md. Rafiqul; Shinjo, Ryuichi [Department of Physics and Earth Sciences, University of the Ryukyus, Okinawa, 903-0213 (Japan)

    2009-09-01

    Fault reactivation during underground mining is a critical problem in coal mines worldwide. This paper investigates the mining-induced reactivation of faults associated with the main conveyor belt roadway (CBR) of the Barapukuria Coal Mine in Bangladesh. The stress characteristics and deformation around the faults were investigated by boundary element method (BEM) numerical modeling. The model consists of a simple geometry with two faults (Fb and Fb1) near the CBR and the surrounding rock strata. A Mohr-Coulomb failure criterion with bulk rock properties is applied to analyze the stability and safety around the fault zones, as well as for the entire mining operation. The simulation results illustrate that the mining-induced redistribution of stresses causes significant deformation within and around the two faults. The horizontal and vertical stresses influence the faults, and higher stresses are concentrated near the ends of the two faults. Higher vertical tensional stress is prominent at the upper end of fault Fb. High deviatoric stress values that concentrated at the ends of faults Fb and Fb1 indicate the tendency towards block failure around the fault zones. The deviatoric stress patterns imply that the reinforcement strength to support the roof of the roadway should be greater than 55 MPa along the fault core zone, and should be more than 20 MPa adjacent to the damage zone of the fault. Failure trajectories that extend towards the roof and left side of fault Fb indicate that mining-induced reactivation of faults is not sufficient to generate water inflow into the mine. However, if movement of strata occurs along the fault planes due to regional earthquakes, and if the faults intersect the overlying Lower Dupi Tila aquiclude, then liquefaction could occur along the fault zones and enhance water inflow into the mine. The study also reveals that the hydraulic gradient and the general direction of groundwater flow are almost at right angles with the trends of

  1. Mining pathway associations for disease-related pathway activity analysis based on gene expression and methylation data.

    Science.gov (United States)

    Lee, Hyeonjeong; Shin, Miyoung

    2017-01-01

    The problem of discovering genetic markers as disease signatures is of great significance for the successful diagnosis, treatment, and prognosis of complex diseases. Even if many earlier studies worked on identifying disease markers from a variety of biological resources, they mostly focused on the markers of genes or gene-sets (i.e., pathways). However, these markers may not be enough to explain biological interactions between genetic variables that are related to diseases. Thus, in this study, our aim is to investigate distinctive associations among active pathways (i.e., pathway-sets) shown each in case and control samples which can be observed from gene expression and/or methylation data. The pathway-sets are obtained by identifying a set of associated pathways that are often active together over a significant number of class samples. For this purpose, gene expression or methylation profiles are first analyzed to identify significant (active) pathways via gene-set enrichment analysis. Then, regarding these active pathways, an association rule mining approach is applied to examine interesting pathway-sets in each class of samples (case or control). By doing so, the sets of associated pathways often working together in activity profiles are finally chosen as our distinctive signature of each class. The identified pathway-sets are aggregated into a pathway activity network (PAN), which facilitates the visualization of differential pathway associations between case and control samples. From our experiments with two publicly available datasets, we could find interesting PAN structures as the distinctive signatures of breast cancer and uterine leiomyoma cancer, respectively. Our pathway-set markers were shown to be superior or very comparable to other genetic markers (such as genes or gene-sets) in disease classification. Furthermore, the PAN structure, which can be constructed from the identified markers of pathway-sets, could provide deeper insights into

  2. Finding novel relationships with integrated gene-gene association network analysis of Synechocystis sp. PCC 6803 using species-independent text-mining.

    Science.gov (United States)

    Kreula, Sanna M; Kaewphan, Suwisa; Ginter, Filip; Jones, Patrik R

    2018-01-01

    The increasing move towards open access full-text scientific literature enhances our ability to utilize advanced text-mining methods to construct information-rich networks that no human will be able to grasp simply from 'reading the literature'. The utility of text-mining for well-studied species is obvious though the utility for less studied species, or those with no prior track-record at all, is not clear. Here we present a concept for how advanced text-mining can be used to create information-rich networks even for less well studied species and apply it to generate an open-access gene-gene association network resource for Synechocystis sp. PCC 6803, a representative model organism for cyanobacteria and first case-study for the methodology. By merging the text-mining network with networks generated from species-specific experimental data, network integration was used to enhance the accuracy of predicting novel interactions that are biologically relevant. A rule-based algorithm (filter) was constructed in order to automate the search for novel candidate genes with a high degree of likely association to known target genes by (1) ignoring established relationships from the existing literature, as they are already 'known', and (2) demanding multiple independent evidences for every novel and potentially relevant relationship. Using selected case studies, we demonstrate the utility of the network resource and filter to ( i ) discover novel candidate associations between different genes or proteins in the network, and ( ii ) rapidly evaluate the potential role of any one particular gene or protein. The full network is provided as an open-source resource.

  3. An assessment of microbial communities associated with surface mining-disturbed overburden.

    Science.gov (United States)

    Poncelet, Dominique M; Cavender, Nicole; Cutright, Teresa J; Senko, John M

    2014-03-01

    To assess the microbiological changes that occur during the maturation of overburden that has been disturbed by surface mining of coal, a surface mining-disturbed overburden unit in southeastern Ohio, USA was characterized. Overburden from the same unit that had been disturbed for 37 and 16 years were compared to undisturbed soil from the same region. Overburden and soil samples were collected as shallow subsurface cores from each subregion of the mined area (i.e., land 16 years and 37 years post-mining, and unmined land). Chemical and mineralogical characteristics of overburden samples were determined, as were microbial respiration rates. The composition of microbial communities associated with overburden and soil were determined using culture-independent, nucleic acid-based approaches. Chemical and mineralogical evaluation of overburden suggested that weathering of disturbed overburden gave rise to a setting with lower pH and more oxidized chemical constituents. Overburden-associated microbial biomass and respiration rates increased with time after overburden disturbance. Evaluation of 16S rRNA gene libraries that were produced by "next-generation" sequencing technology revealed that recently disturbed overburden contained an abundance of phylotypes attributable to sulfur-oxidizing Limnobacter spp., but with increasing time post-disturbance, overburden-associated microbial communities developed a structure similar to that of undisturbed soil, but retained characteristics of more recently disturbed overburden. Our results indicate that over time, the biogeochemical weathering of disturbed overburden leads to the development of geochemical conditions and microbial communities that approximate those of undisturbed soil, but that this transition is incomplete after 37 years of overburden maturation.

  4. A Case Investigation of Product Structure Complexity in Mass Customization Using a Data Mining Approach

    DEFF Research Database (Denmark)

    Nielsen, Peter; Brunø, Thomas Ditlev; Nielsen, Kjeld

    2014-01-01

    This paper presents a data mining method for analyzing historical configuration data providing a number of opportunities for improving mass customization capabilities. The overall objective of this paper is to investigate how specific quantitative analyses, more specifically the association rule...

  5. Triggered surface slips in the Salton Trough associated with the 1999 Hector Mine, California, earthquake

    Science.gov (United States)

    Rymer, M.J.; Boatwright, J.; Seekins, L.C.; Yule, J.D.; Liu, J.

    2002-01-01

    Surface fracturing occurred along the southern San Andreas, Superstition Hills, and Imperial faults in association with the 16 October 1999 (Mw 7.1) Hector Mine earthquake, making this at least the eighth time in the past 31 years that a regional earthquake has triggered slip along faults in the Salton Trough. Fractures associated with the event formed discontinuous breaks over a 39-km-long stretch of the San Andreas fault, from the Mecca Hills southeastward to Salt Creek and Durmid Hill, a distance from the epicenter of 107 to 139 km. Sense of slip was right lateral; only locally was there a minor (~1 mm) vertical component of slip. Dextral slip ranged from 1 to 13 mm. Maximum slip values in 1999 and earlier triggered slips are most common in the central Mecca Hills. Field evidence indicates a transient opening as the Hector Mine seismic waves passed the southern San Andreas fault. Comparison of nearby strong-motion records indicates several periods of relative opening with passage of the Hector Mine seismic wave-a similar process may have contributed to the field evidence of a transient opening. Slip on the Superstition Hills fault extended at least 9 km, at a distance from the Hector Mine epicenter of about 188 to 196 km. This length of slip is a minimum value, because we saw fresh surface breakage extending farther northwest than our measurement sites. Sense of slip was right lateral; locally there was a minor (~1 mm) vertical component of slip. Dextral slip ranged from 1 to 18 mm, with the largest amounts found distributed (or skewed) away from the Hector Mine earthquake source. Slip triggered on the Superstition Hills fault commonly is skewed away from the earthquake source, most notably in 1968, 1979, and 1999. Surface slip on the Imperial fault and within the Imperial Valley extended about 22 km, representing a distance from the Hector Mine epicenter of about 204 to 226 km. Sense of slip dominantly was right lateral; the right-lateral component of slip

  6. PENGEMBANGAN SISTEM EVALUASI DESAIN PRODUK BERBASIS ROTAN DENGAN PENDEKATAN REKAYASA KANSEI DAN ASSOCIATION RULES SYSTEM

    Directory of Open Access Journals (Sweden)

    Vonny Setiaries Johan

    2016-11-01

    Full Text Available In product development, it is very important for manufacturers to find out what the customer wants from the product. On the other hand, manufacturers do not know clearly about what the customer wants from the product. This study proposes an evaluation method of product design using Kansei engineering methods and association rules approach. Using rattan dining chair as the object, the chair design divided into five elements, which are backrest, seat, armrest, base and woven. In this study, Kansei words from customers such as beautiful, unique, innovative, comfortable, natural, modern, sturdy and simple can be translated in to element design.   Using the support and confidence values, if-then rules can be used as the basis for the assessment of rattan dining chairs

  7. LimTox: a web tool for applied text mining of adverse event and toxicity associations of compounds, drugs and genes.

    Science.gov (United States)

    Cañada, Andres; Capella-Gutierrez, Salvador; Rabal, Obdulia; Oyarzabal, Julen; Valencia, Alfonso; Krallinger, Martin

    2017-07-03

    A considerable effort has been devoted to retrieve systematically information for genes and proteins as well as relationships between them. Despite the importance of chemical compounds and drugs as a central bio-entity in pharmacological and biological research, only a limited number of freely available chemical text-mining/search engine technologies are currently accessible. Here we present LimTox (Literature Mining for Toxicology), a web-based online biomedical search tool with special focus on adverse hepatobiliary reactions. It integrates a range of text mining, named entity recognition and information extraction components. LimTox relies on machine-learning, rule-based, pattern-based and term lookup strategies. This system processes scientific abstracts, a set of full text articles and medical agency assessment reports. Although the main focus of LimTox is on adverse liver events, it enables also basic searches for other organ level toxicity associations (nephrotoxicity, cardiotoxicity, thyrotoxicity and phospholipidosis). This tool supports specialized search queries for: chemical compounds/drugs, genes (with additional emphasis on key enzymes in drug metabolism, namely P450 cytochromes-CYPs) and biochemical liver markers. The LimTox website is free and open to all users and there is no login requirement. LimTox can be accessed at: http://limtox.bioinfo.cnio.es. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

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

    KAUST Repository

    Raies, A. B.

    2014-11-14

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

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

    Science.gov (United States)

    Bin Raies, Arwa; Mansour, Hicham; Incitti, Roberto; Bajic, Vladimir B

    2015-01-01

    Gathering information about associations between methylated genes and diseases is important for diseases diagnosis and treatment decisions. Recent advancements in epigenetics research allow for large-scale discoveries of associations of genes methylated in diseases in different species. Searching manually for such information is not easy, as it is scattered across a large number of electronic publications and repositories. Therefore, we developed DDMGD database (http://www.cbrc.kaust.edu.sa/ddmgd/) to provide a comprehensive repository of information related to genes methylated in diseases that can be found through text mining. DDMGD's scope is not limited to a particular group of genes, diseases or species. Using the text mining system DEMGD we developed earlier and additional post-processing, we extracted associations of genes methylated in different diseases from PubMed Central articles and PubMed abstracts. The accuracy of extracted associations is 82% as estimated on 2500 hand-curated entries. DDMGD provides a user-friendly interface facilitating retrieval of these associations ranked according to confidence scores. Submission of new associations to DDMGD is provided. A comparison analysis of DDMGD with several other databases focused on genes methylated in diseases shows that DDMGD is comprehensive and includes most of the recent information on genes methylated in diseases. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

  10. Human mercury exposure associated with small-scale gold mining in Burkina Faso.

    Science.gov (United States)

    Tomicic, Catherine; Vernez, David; Belem, Tounaba; Berode, Michèle

    2011-06-01

    In Burkina Faso, gold ore is one of the main sources of income for an important part of the active population. Artisan gold miners use mercury in the extraction, a toxic metal whose human health risks are well known. The aim of the present study was to assess mercury exposure as well as to understand the exposure determinants of gold miners in Burkinabe small-scale mines. The examined gold miners' population on the different selected gold mining sites was composed by persons who were directly and indirectly related to gold mining activities. But measurement of urinary mercury was performed on workers most susceptible to be exposed to mercury. Thus, occupational exposure to mercury was evaluated among ninety-three workers belonging to eight different gold mining sites spread in six regions of Burkina Faso. Among others, work-related exposure determinants were taken into account for each person during urine sampling as for example amalgamating or heating mercury. All participants were medically examined by a local medical team in order to identify possible symptoms related to the toxic effect of mercury. Mercury levels were high, showing that 69% of the measurements exceeded the ACGIH (American Conference of Industrial Hygienists) biological exposure indice (BEI) of 35 μg per g of creatinine (μg/g-Cr) (prior to shift) while 16% even exceeded 350 μg/g-Cr. Basically, unspecific but also specific symptoms related to mercury toxicity could be underlined among the persons who were directly related to gold mining activities. Only one-third among the studied subpopulation reported about less than three symptoms possibly associated to mercury exposure and nearly half of them suffered from at least five of these symptoms. Ore washers were more involved in the direct handling of mercury while gold dealers in the final gold recovery activities. These differences may explain the overexposure observed in gold dealers and indicate that the refining process is the major source

  11. 76 FR 70075 - Proximity Detection Systems for Continuous Mining Machines in Underground Coal Mines

    Science.gov (United States)

    2011-11-10

    ... Detection Systems for Continuous Mining Machines in Underground Coal Mines AGENCY: Mine Safety and Health... proposed rule addressing Proximity Detection Systems for Continuous Mining Machines in Underground Coal... Detection Systems for Continuous Mining Machines in Underground Coal Mines. MSHA conducted hearings on...

  12. Associations between parental rules, style of communication and children's screen time.

    Science.gov (United States)

    Bjelland, Mona; Soenens, Bart; Bere, Elling; Kovács, Éva; Lien, Nanna; Maes, Lea; Manios, Yannis; Moschonis, George; te Velde, Saskia J

    2015-10-01

    Research suggests an inverse association between parental rules and screen time in pre-adolescents, and that parents' style of communication with their children is related to the children's time spent watching TV. The aims of this study were to examine associations of parental rules and parental style of communication with children's screen time and perceived excessive screen time in five European countries. UP4FUN was a multi-centre, cluster randomised controlled trial with pre- and post-test measurements in each of five countries; Belgium, Germany, Greece, Hungary and Norway. Questionnaires were completed by the children at school and the parent questionnaire was brought home. Three structural equation models were tested based on measures of screen time and parental style of communication from the pre-test questionnaires. Of the 152 schools invited, 62 (41 %) schools agreed to participate. In total 3325 children (average age 11.2 years and 51 % girls) and 3038 parents (81 % mothers) completed the pre-test questionnaire. The average TV/DVD times across the countries were between 1.5 and 1.8 h/day, while less time was used for computer/games console (0.9-1.4 h/day). The children's perceived parental style of communication was quite consistent for TV/DVD and computer/games console. The presence of rules was significantly associated with less time watching TV/DVD and use of computer/games console time. Moreover, the use of an autonomy-supportive style was negatively related to both time watching TV/DVD and use of computer/games console time. The use of a controlling style was related positively to perceived excessive time used on TV/DVD and excessive time used on computer/games console. With a few exceptions, results were similar across the five countries. This study suggests that an autonomy-supportive style of communicating rules for TV/DVD or computer/ games console use is negatively related to children's time watching TV/DVD and use of computer/games console time

  13. Coseismic and aseismic deformations associated with mining-induced seismic events located in deep level mines in South Africa

    CSIR Research Space (South Africa)

    Milev, A

    2013-10-01

    Full Text Available Two underground sites in a deep level gold mine in South Africa were instrumented by the Council for Scientific and Industrial Research (CSIR) with tilt meters and seismic monitors. One of the sites was also instrumented by Japanese-German...

  14. Injury Profiles Associated with Artisanal and Small-Scale Gold Mining in Tarkwa, Ghana.

    Science.gov (United States)

    Calys-Tagoe, Benedict N L; Ovadje, Lauretta; Clarke, Edith; Basu, Niladri; Robins, Thomas

    2015-07-10

    Artisanal and small-scale gold mining (ASGM) is inherently risky, but little is known about mining-associated hazards and injuries despite the tremendous growth worldwide of ASGM and the benefits it offers. The current study aimed to characterize the physical injuries associated with ASGM in Ghana to guide policy formulation. A cross-sectional survey was carried out in the Tarkwa mining district of the Western Region of Ghana in 2014. A total of 404 small-scale miners were recruited and interviewed regarding their occupational injury experiences over the preceding 10 years using a paper-based structured questionnaire. Nearly one-quarter (23.5%) of the miners interviewed reported getting injured over the previous 10 years, and the overall injury rate was calculated to be 5.39 per 100 person years. The rate was significantly higher for women (11.93 per 100 person years) and those with little mining experience (e.g., 25.31 per 100 person years for those with less than one year of work experience). The most injury-prone mining activities were excavation (58.7%) and crushing (23.1%), and over 70% of the injuries were reported to be due to miners being hit by an object. The majority of the injuries (57%) were lacerations, and nearly 70% of the injuries were to the upper or lower limbs. Approximately one-third (34.7%) of the injuries resulted in miners missing more than two weeks of work. One-quarter of the injured workers believed that abnormal work pressure played a role in their injuries, and nearly two-fifths believed that their injuries could have been prevented, with many citing personal protective equipment as a solution. About one-quarter of the employees reported that their employers never seemed to be interested in the welfare or safety of their employees. These findings greatly advance our understanding of occupational hazards and injuries amongst ASGM workers and help identify several intervention points.

  15. Law 19.126. It dictate Regulatory standards about Mining of great bearing

    International Nuclear Information System (INIS)

    2013-01-01

    It statute rules for regulating mining projects of great size, ownership, location, related mining activities, mine closure plan, exploitation concession contract, taxation regime, canon, infractions and sanctions

  16. Microbial communities associated with uranium in-situ recovery mining process are related to acid mine drainage assemblages.

    Science.gov (United States)

    Coral, Thomas; Descostes, Michaël; De Boissezon, Hélène; Bernier-Latmani, Rizlan; de Alencastro, Luiz Felippe; Rossi, Pierre

    2018-07-01

    A large fraction (47%) of the world's uranium is mined by a technique called "In Situ Recovery" (ISR). This mining technique involves the injection of a leaching fluid (acidic or alkaline) into a uranium-bearing aquifer and the pumping of the resulting solution through cation exchange columns for the recovery of dissolved uranium. The present study reports the in-depth alterations brought to autochthonous microbial communities during acidic ISR activities. Water samples were collected from a uranium roll-front deposit that is part of an ISR mine in operation (Tortkuduk, Kazakhstan). Water samples were obtained at a depth of ca 500 m below ground level from several zones of the Uyuk aquifer following the natural redox zonation inherited from the roll front deposit, including the native mineralized orebody and both upstream and downstream adjacent locations. Samples were collected equally from both the entrance and the exit of the uranium concentration plant. Next-generation sequencing data showed that the redox gradient shaped the community structures, within the anaerobic, reduced, and oligotrophic habitats of the native aquifer zones. Acid injection induced drastic changes in the structures of these communities, with a large decrease in both cell numbers and diversity. Communities present in the acidified (pH values acid mine drainage, with the dominance of Sulfobacillus sp., Leptospirillum sp. and Acidithiobacillus sp., as well as the archaean Ferroplasma sp. Communities located up- and downstream of the mineralized zone under ISR and affected by acidic fluids were blended with additional facultative anaerobic and acidophilic microorganisms. These mixed biomes may be suitable communities for the natural attenuation of ISR mining-affected subsurface through the reduction of metals and sulfate. Assessing the effect of acidification on the microbial community is critical to evaluating the potential for natural attenuation or active bioremediation strategies

  17. Research of the Occupational Psychological Impact Factors Based on the Frequent Item Mining of the Transactional Database

    Directory of Open Access Journals (Sweden)

    Cheng Dongmei

    2015-01-01

    Full Text Available Based on the massive reading of data mining and association rules mining documents, this paper will start from compressing transactional database and propose the frequent complementary item storage structure of the transactional database. According to the previous analysis, this paper will also study the association rules mining algorithm based on the frequent complementary item storage structure of the transactional database. At last, this paper will apply this mining algorithm in the test results analysis module of team psychological health assessment system, and will extract the relationship between each psychological impact factor, so as to provide certain guidance for psychologists in their mental illness treatment.

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

    Directory of Open Access Journals (Sweden)

    Lluís Sanmiquel

    2018-03-01

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

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

    Science.gov (United States)

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

    2018-01-01

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

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

    Science.gov (United States)

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

    2016-01-01

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

  1. Mining PubMed for Biomarker-Disease Associations to Guide Discovery

    OpenAIRE

    Jessen, Walter; Landschulz, Katherine; Turi, Thomas; Reams, Rachel

    2012-01-01

    Biomedical knowledge is growing exponentially; however, meta-knowledge around the data is often lacking. PubMed is a database comprising more than 21 million citations for biomedical literature from MEDLINE and additional life science journals dating back to the 1950s. To explore the use and frequency of biomarkers across human disease, we mined PubMed for biomarker-disease associations. We then ranked the top 100 linked diseases by relevance and mapped them to medical subject headings (MeSH)...

  2. Is outdoor work associated with elevated rates of cerebrovascular disease mortality? : a cohort study based on iron-ore mining

    OpenAIRE

    Björ, Ove; Jonsson, Håkan; Damber, Lena; Burström, Lage; Nilsson, Tohr

    2016-01-01

    BACKGROUND: A cohort study that examined iron ore mining found negative associations between cumulative working time employed underground and several outcomes, including mortality of cerebrovascular diseases. In this cohort study, and using the same group of miners, we examined whether work in an outdoor environment could explain elevated cerebrovascular disease rates. METHODS: This study was based on a Swedish iron ore mining cohort consisting of 13,000 workers. Poisson regression models wer...

  3. Radio-Ecological Situation in the Area of the Priargun Production Mining and Chemical Association - 13522

    International Nuclear Information System (INIS)

    Semenova, M.P.; Seregin, V.A.; Kiselev, S.M.; Titov, A.V.; Zhuravleva, L.A.; Marenny, A.M.

    2013-01-01

    'The Priargun Production Mining and Chemical Association' (hereinafter referred to as PPMCA) is a diversified mining company which, in addition to underground mining of uranium ore, carries out refining of such ores in hydrometallurgical process to produce natural uranium oxide. The PPMCA facilities are sources of radiation and chemical contamination of the environment in the areas of their location. In order to establish the strategy and develop criteria for the site remediation, independent radiation hygienic monitoring is being carried out over some years. In particular, this monitoring includes determination of concentration of the main dose-forming nuclides in the environmental media. The subjects of research include: soil, grass and local foodstuff (milk and potato), as well as media of open ponds (water, bottom sediments, water vegetation). We also measured the radon activity concentration inside surface workshops and auxiliaries. We determined the specific activity of the following natural radionuclides: U-238, Th-232, K-40, Ra-226. The researches performed showed that in soil, vegetation, groundwater and local foods sampled in the vicinity of the uranium mines, there is a significant excess of 226 Ra and 232 Th content compared to areas outside the zone of influence of uranium mining. The ecological and hygienic situation is as follows: - at health protection zone (HPZ) gamma dose rate outdoors varies within 0.11 to 5.4 μSv/h (The mean value in the reference (background) settlement (Soktui-Molozan village) is 0.14 μSv/h); - gamma dose rate in workshops within HPZ varies over the range 0.14 - 4.3 μSv/h. - the specific activity of natural radionuclides in soil at HPZ reaches 12800 Bq/kg and 510 Bq/kg for Ra-226 and Th-232, respectively. - beyond HPZ the elevated values for 226 Ra have been registered near Lantsovo Lake - 430 Bq/kg; - the radon activity concentration in workshops within HPZ varies over the range 22 - 10800 Bq/m 3 . The seasonal dependence

  4. Radio-Ecological Situation in the Area of the Priargun Production Mining and Chemical Association - 13522

    Energy Technology Data Exchange (ETDEWEB)

    Semenova, M.P.; Seregin, V.A.; Kiselev, S.M.; Titov, A.V. [FSBI SRC A.I. Burnasyan Federal Medical Biophysical Center of FMBA of Russia, Zhivopisnaya Street, 46, Moscow (Russian Federation); Zhuravleva, L.A. [FSHE ' Centre of Hygiene and Epidemiology no. 107' under FMBA of Russia (Russian Federation); Marenny, A.M. [Ltd ' Radiation and Environmental Researches' (Russian Federation)

    2013-07-01

    'The Priargun Production Mining and Chemical Association' (hereinafter referred to as PPMCA) is a diversified mining company which, in addition to underground mining of uranium ore, carries out refining of such ores in hydrometallurgical process to produce natural uranium oxide. The PPMCA facilities are sources of radiation and chemical contamination of the environment in the areas of their location. In order to establish the strategy and develop criteria for the site remediation, independent radiation hygienic monitoring is being carried out over some years. In particular, this monitoring includes determination of concentration of the main dose-forming nuclides in the environmental media. The subjects of research include: soil, grass and local foodstuff (milk and potato), as well as media of open ponds (water, bottom sediments, water vegetation). We also measured the radon activity concentration inside surface workshops and auxiliaries. We determined the specific activity of the following natural radionuclides: U-238, Th-232, K-40, Ra-226. The researches performed showed that in soil, vegetation, groundwater and local foods sampled in the vicinity of the uranium mines, there is a significant excess of {sup 226}Ra and {sup 232}Th content compared to areas outside the zone of influence of uranium mining. The ecological and hygienic situation is as follows: - at health protection zone (HPZ) gamma dose rate outdoors varies within 0.11 to 5.4 μSv/h (The mean value in the reference (background) settlement (Soktui-Molozan village) is 0.14 μSv/h); - gamma dose rate in workshops within HPZ varies over the range 0.14 - 4.3 μSv/h. - the specific activity of natural radionuclides in soil at HPZ reaches 12800 Bq/kg and 510 Bq/kg for Ra-226 and Th-232, respectively. - beyond HPZ the elevated values for {sup 226}Ra have been registered near Lantsovo Lake - 430 Bq/kg; - the radon activity concentration in workshops within HPZ varies over the range 22 - 10800 Bq

  5. Radioecological situation in the area of the Priargun Production Mining and Chemical Association in Russian Zabaikalye Territory

    International Nuclear Information System (INIS)

    Shandala, N.K.; Titov, A.V.; Kiselev, S.M.; Akhromeev, S.V.; Semenova, M.P.

    2012-01-01

    'The Priargun Production Mining and Chemical Association' (hereinafter referred to as PPMCA) is a diversified mining company, which, in addition to underground mining of uranium ore, carries out refining of such ores in hydrometallurgical process to produce natural uranium oxide. The PPMCA facilities are sources of radiation and chemical contamination of the environment in the areas of their location. Contamination of local parts of the health protection zone results from discharges and releases, dust transport of radionuclides from the mine rock dumps containing uranium, radium, radon and its decay products, spillage of ore along highways, straits uraniferous pulp and mine water from the pool pump shaft station. The radionuclide migration results in groundwater contamination. In order to establish the strategy and develop criteria for the site remediation, independent radiation hygienic monitoring is being carried out over some years. The subjects of research include: soil, grass and media of open ponds (water, bottom sediments, water vegetation). We also measured the radon activity concentration inside surface workshops and auxiliaries. We determined the specific activity of natural radionuclides. The researches performed showed that in soil, vegetation, groundwater and local foods sampled in the vicinity of the uranium mines, there is a significant excess of 226 Ra and 2 32 Th content compared to areas outside the zone of influence of uranium mining.

  6. Ecological and human health risks associated with abandoned gold mine tailings contaminated soil.

    Directory of Open Access Journals (Sweden)

    Veronica Mpode Ngole-Jeme

    Full Text Available Gold mining is a major source of metal and metalloid emissions into the environment. Studies were carried out in Krugersdorp, South Africa, to evaluate the ecological and human health risks associated with exposure to metals and metalloids in mine tailings contaminated soils. Concentrations of arsenic (As, cadmium (Cd, chromium (Cr, cobalt (Co, copper (Cu, lead (Pb, manganese (Mn, nickel (Ni, and zinc (Zn in soil samples from the area varied with the highest contamination factors (expressed as ratio of metal or metalloid concentration in the tailings contaminated soil to that of the control site observed for As (3.5x102, Co (2.8x102 and Ni (1.1x102. Potential ecological risk index values for metals and metalloids determined from soil metal and metalloid concentrations and their respective risk factors were correspondingly highest for As (3.5x103 and Co (1.4x103, whereas Mn (0.6 presented the lowest ecological risk. Human health risk was assessed using Hazard Quotient (HQ, Chronic Hazard Index (CHI and carcinogenic risk levels, where values of HQ > 1, CHI > 1 and carcinogenic risk values > 1×10-4 represent elevated risks. Values for HQ indicated high exposure-related risk for As (53.7, Cr (14.8, Ni (2.2, Zn (2.64 and Mn (1.67. Children were more at risk from heavy metal and metalloid exposure than adults. Cancer-related risks associated with metal and metalloid exposure among children were also higher than in adults with cancer risk values of 3×10-2 and 4×10-2 for As and Ni respectively among children, and 5×10-3 and 4×10-3 for As and Ni respectively among adults. There is significant potential ecological and human health risk associated with metal and metalloid exposure from contaminated soils around gold mine tailings dumps. This could be a potential contributing factor to a setback in the health of residents in informal settlements dominating this mining area as the immune systems of some of these residents are already compromised by high

  7. A new pattern associative memory model for image recognition based on Hebb rules and dot product

    Science.gov (United States)

    Gao, Mingyue; Deng, Limiao; Wang, Yanjiang

    2018-04-01

    A great number of associative memory models have been proposed to realize information storage and retrieval inspired by human brain in the last few years. However, there is still much room for improvement for those models. In this paper, we extend a binary pattern associative memory model to accomplish real-world image recognition. The learning process is based on the fundamental Hebb rules and the retrieval is implemented by a normalized dot product operation. Our proposed model can not only fulfill rapid memory storage and retrieval for visual information but also have the ability on incremental learning without destroying the previous learned information. Experimental results demonstrate that our model outperforms the existing Self-Organizing Incremental Neural Network (SOINN) and Back Propagation Neuron Network (BPNN) on recognition accuracy and time efficiency.

  8. Data Mining FAERS to Analyze Molecular Targets of Drugs Highly Associated with Stevens-Johnson Syndrome.

    Science.gov (United States)

    Burkhart, Keith K; Abernethy, Darrell; Jackson, David

    2015-06-01

    Drug features that are associated with Stevens-Johnson syndrome (SJS) have not been fully characterized. A molecular target analysis of the drugs associated with SJS in the FDA Adverse Event Reporting System (FAERS) may contribute to mechanistic insights into SJS pathophysiology. The publicly available version of FAERS was analyzed to identify disproportionality among the molecular targets, metabolizing enzymes, and transporters for drugs associated with SJS. The FAERS in-house version was also analyzed for an internal comparison of the drugs most highly associated with SJS. Cyclooxygenases 1 and 2, carbonic anhydrase 2, and sodium channel 2 alpha were identified as disproportionately associated with SJS. Cytochrome P450 (CYPs) 3A4 and 2C9 are disproportionately represented as metabolizing enzymes of the drugs associated with SJS adverse event reports. Multidrug resistance protein 1 (MRP-1), organic anion transporter 1 (OAT1), and PEPT2 were also identified and are highly associated with the transport of these drugs. A detailed review of the molecular targets identifies important roles for these targets in immune response. The association with CYP metabolizing enzymes suggests that reactive metabolites and oxidative stress may have a contributory role. Drug transporters may enhance intracellular tissue concentrations and also have vital physiologic roles that impact keratinocyte proliferation and survival. Data mining FAERS may be used to hypothesize mechanisms for adverse drug events by identifying molecular targets that are highly associated with drug-induced adverse events. The information gained may contribute to systems biology disease models.

  9. HIV preventive behavior and associated factors among mining workers in Sali traditional gold mining site Bench Maji zone, Southwest Ethiopia: a cross sectional study.

    Science.gov (United States)

    Abdissa, Hordofa Gutema; Lemu, Yohannes Kebede; Nigussie, Dejene Tilahun

    2014-09-26

    Prevalence of HIV and other STI is high among migrant mining workers due to factors such as dangerous working conditions, only masculine identities existence, living away from families, desolate and in hospitable place. This makes them known to be HIV and STI vulnerable group in different part of the world. But, in Ethiopia they were not thought as at risk group yet. So the aim of this study is to assess magnitude of HIV preventive behaviours and associated factors among gold miners in Sali traditional gold mining site. A cross sectional study was conducted to assess HIV preventive behavior of the mining worker. The data were collected using interviewer administered structured questionnaire adapted from other related behavioural studies. The data was entered using EPI data version 3.1 and analyzed using SPSS version 17. Multiple logistic regression was used to assess relationship of HIV preventive behavior with constructs of health belief model. A total of 393 respondents with response rate of 93.12% were participated. All of the study participants were male 393(100%), the mean age of the participant was 24.0 (± 5.13SD). Less than half of the respondents 187(47.6%) were engaged in HIV preventive behavior. Less than half (45.3%) of them have high perceived susceptibility to HIV/AIDS; majority (62.8%) of them has high perceived severity to HIV/AIDS. HIV preventive behavior is negatively associated with being in middle, higher and highest income [OR = 0.54, 95% CI: 0.21, 0.74], [OR = 0.40, 95% CI: 0.30, 0.98] and [OR = 0.39, 95% CI: 0.20, 0.77] respectively and positively associated with Completing secondary, tertiary school and self efficacy [OR = 2.66, 95% CI: 1.11, 6.41], [OR = 5.40, 95% CI: 1.54, 19] and [OR = 1.88, 95% CI: 1.18, 2.94] respectively. The HIV preventive behavior of the mining worker was low. Being engaged in sexual intercourse with one sexual partner is very low, Consistent condom use among these mining workers was low. Income, educational status

  10. Identification of Antimony- and Arsenic-Oxidizing Bacteria Associated with Antimony Mine Tailing

    Science.gov (United States)

    Hamamura, Natsuko; Fukushima, Koh; Itai, Takaaki

    2013-01-01

    Antimony (Sb) is a naturally occurring toxic element commonly associated with arsenic (As) in the environment and both elements have similar chemistry and toxicity. Increasing numbers of studies have focused on microbial As transformations, while microbial Sb interactions are still not well understood. To gain insight into microbial roles in the geochemical cycling of Sb and As, soils from Sb mine tailing were examined for the presence of Sb- and As-oxidizing bacteria. After aerobic enrichment culturing with AsIII (10 mM) or SbIII (100 μM), pure cultures of Pseudomonas- and Stenotrophomonas-related isolates with SbIII oxidation activities and a Sinorhizobium-related isolate capable of AsIII oxidation were obtained. The AsIII-oxidizing Sinorhizobium isolate possessed the aerobic arsenite oxidase gene (aioA), the expression of which was induced in the presence of AsIII or SbIII. However, no SbIII oxidation activity was detected from the Sinorhizobium-related isolate, suggesting the involvement of different mechanisms for Sb and As oxidation. These results demonstrate that indigenous microorganisms associated with Sb mine soils are capable of Sb and As oxidation, and potentially contribute to the speciation and mobility of Sb and As in situ. PMID:23666539

  11. Alkemio: association of chemicals with biomedical topics by text and data mining.

    Science.gov (United States)

    Gijón-Correas, José A; Andrade-Navarro, Miguel A; Fontaine, Jean F

    2014-07-01

    The PubMed® database of biomedical citations allows the retrieval of scientific articles studying the function of chemicals in biology and medicine. Mining millions of available citations to search reported associations between chemicals and topics of interest would require substantial human time. We have implemented the Alkemio text mining web tool and SOAP web service to help in this task. The tool uses biomedical articles discussing chemicals (including drugs), predicts their relatedness to the query topic with a naïve Bayesian classifier and ranks all chemicals by P-values computed from random simulations. Benchmarks on seven human pathways showed good retrieval performance (areas under the receiver operating characteristic curves ranged from 73.6 to 94.5%). Comparison with existing tools to retrieve chemicals associated to eight diseases showed the higher precision and recall of Alkemio when considering the top 10 candidate chemicals. Alkemio is a high performing web tool ranking chemicals for any biomedical topics and it is free to non-commercial users. http://cbdm.mdc-berlin.de/∼medlineranker/cms/alkemio. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

  12. Ontology-based literature mining of E. coli vaccine-associated gene interaction networks.

    Science.gov (United States)

    Hur, Junguk; Özgür, Arzucan; He, Yongqun

    2017-03-14

    Pathogenic Escherichia coli infections cause various diseases in humans and many animal species. However, with extensive E. coli vaccine research, we are still unable to fully protect ourselves against E. coli infections. To more rational development of effective and safe E. coli vaccine, it is important to better understand E. coli vaccine-associated gene interaction networks. In this study, we first extended the Vaccine Ontology (VO) to semantically represent various E. coli vaccines and genes used in the vaccine development. We also normalized E. coli gene names compiled from the annotations of various E. coli strains using a pan-genome-based annotation strategy. The Interaction Network Ontology (INO) includes a hierarchy of various interaction-related keywords useful for literature mining. Using VO, INO, and normalized E. coli gene names, we applied an ontology-based SciMiner literature mining strategy to mine all PubMed abstracts and retrieve E. coli vaccine-associated E. coli gene interactions. Four centrality metrics (i.e., degree, eigenvector, closeness, and betweenness) were calculated for identifying highly ranked genes and interaction types. Using vaccine-related PubMed abstracts, our study identified 11,350 sentences that contain 88 unique INO interactions types and 1,781 unique E. coli genes. Each sentence contained at least one interaction type and two unique E. coli genes. An E. coli gene interaction network of genes and INO interaction types was created. From this big network, a sub-network consisting of 5 E. coli vaccine genes, including carA, carB, fimH, fepA, and vat, and 62 other E. coli genes, and 25 INO interaction types was identified. While many interaction types represent direct interactions between two indicated genes, our study has also shown that many of these retrieved interaction types are indirect in that the two genes participated in the specified interaction process in a required but indirect process. Our centrality analysis of

  13. Associations between general parenting, restrictive snacking rules, and adolescent's snack intake. The roles of fathers and mothers and interparental congruence.

    Science.gov (United States)

    Gevers, Dorus W M; van Assema, Patricia; Sleddens, Ester F C; de Vries, Nanne K; Kremers, Stef P J

    2015-04-01

    Little research has been done on the role of fathers and parenting congruence between mothers and fathers. This study aimed to clarify the roles of general parenting and restrictive snacking rules set by fathers and mothers, and to explore parenting congruence in explaining adolescents' snack intake. Adolescents aged 11 to 15 completed a questionnaire assessing their perception of general parenting constructs (i.e. nurturance, structure, behavioral control, coercive control, and overprotection), restrictive snacking rules set by their fathers and mothers, and their own energy-dense snack intakes between meals. Scores for mothers were significantly higher on all constructs than for fathers, except for coercive control. Generally, higher scores on general parenting constructs were associated with higher scores on restrictive snacking rules (most of the associations being significant). Most general parenting constructs were unrelated to the respondents' number of snacks consumed. The use of restrictive snacking rules by both fathers and mothers was significantly and negatively related to respondents' snack intake. Moderation analyses indicated that high levels of incongruence between parents attenuated the favorable impact of fathers' rules and nurturance on their children's snacking, but interactions of congruence with three other paternal scales and all maternal scales were absent. Our findings indicate that both paternal and maternal general parenting and restrictive snacking rules play important roles in adolescents' snacking, and that high parental incongruence regarding restrictive snacking rules and nurturance could be undesirable. Copyright © 2014 Elsevier Ltd. All rights reserved.

  14. Data Mining for Identifying Novel Associations and Temporal Relationships with Charcot Foot

    Directory of Open Access Journals (Sweden)

    Michael E. Munson

    2014-01-01

    Full Text Available Introduction. Charcot foot is a rare and devastating complication of diabetes. While some risk factors are known, debate continues regarding etiology. Elucidating other associated disorders and their temporal occurrence could lead to a better understanding of its pathogenesis. We applied a large data mining approach to Charcot foot for elucidating novel associations. Methods. We conducted an association analysis using ICD-9 diagnosis codes for every patient in our health system (n=1.6 million with 41.2 million time-stamped ICD-9 codes. For the current analysis, we focused on the 388 patients with Charcot foot (ICD-9 713.5. Results. We found 710 associations, 676 (95.2% of which had a P value for the association less than 1.0×10−5 and 603 (84.9% of which had an odds ratio > 5.0. There were 111 (15.6% associations with a significant temporal relationship P<1.0×10−3. The three novel associations with the strongest temporal component were cardiac dysrhythmia, pulmonary eosinophilia, and volume depletion disorder. Conclusion. We identified novel associations with Charcot foot in the context of pathogenesis models that include neurotrophic, neurovascular, and microtraumatic factors mediated through inflammatory cytokines. Future work should focus on confirmatory analyses. These novel areas of investigation could lead to prevention or earlier diagnosis.

  15. Exposure to dust and particle-associated 1-nitropyrene of drivers of diesel-powered equipment in underground mining.

    Science.gov (United States)

    Scheepers, P T J; Micka, V; Muzyka, V; Anzion, R; Dahmann, D; Poole, J; Bos, R P

    2003-07-01

    A field study was conducted in two mines in order to determine the most suitable strategy for ambient exposure assessment in the framework of a European study aimed at validation of biological monitoring approaches for diesel exhaust (BIOMODEM). Exposure to dust and particle-associated 1-nitropyrene (1-NP) was studied in 20 miners of black coal by the long wall method (Czech Republic) and in 20 workers in oil shale mining by the room and pillar method (Estonia). The study in the oil shale mine was extended to include 100 workers in a second phase (main study). In each mine half of the study population worked underground as drivers of diesel-powered trains (black coal) and excavators (oil shale). The other half consisted of workers occupied in various non-diesel production assignments. Exposure to diesel exhaust was studied by measurement of inhalable and respirable dust at fixed locations and by personal air sampling of respirable dust. The ratio of geometric mean inhalable to respirable dust concentration was approximately two to one. The underground/surface ratio of respirable dust concentrations measured at fixed locations and in the breathing zones of the workers was 2-fold or greater. Respirable dust was 2- to 3-fold higher in the breathing zone than at fixed sampling locations. The 1-NP content in these dust fractions was determined by gas chromatography-mass spectrometry/mass spectrometry and ranged from 0.003 to 42.2 ng/m(3) in the breathing zones of the workers. In mine dust no 1-NP was detected. In both mines 1-NP was observed to be primarily associated with respirable particles. The 1-NP concentrations were also higher underground than on the surface (2- to 3-fold in the coal mine and 10-fold or more in the oil shale mine). Concentrations of 1-NP in the breathing zones were also higher than at fixed sites (2.5-fold in the coal mine and 10-fold in the oil shale mine). For individual exposure assessment personal air sampling is preferred over air sampling

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

    Directory of Open Access Journals (Sweden)

    Joanna F Dipnall

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

  17. Study on dose assessment in surrounding environment of the Tono Mine associated with closure activity

    International Nuclear Information System (INIS)

    Sasao, Eiji

    2012-07-01

    Dose assessment associated with closure activity of the Tono Mine has been performed. In this assessment, exposure dose has been calculated on groundwater and surface water migration of radionuclide from 1) waste rock in the waste rock dump facility, 2) mining waste in the mining waste facility, and 3) uranium ore and waste rock backfilled in the shafts and galleries. Direct and skyshine gamma rays and exposure of exhalated radon from the waste rock dump has also been evaluated. An evaluation tool developed for safety assessment for sub-surface disposal of radioactive waste is utilized for this assessment. Localities for dose evaluation are selected at the Higashihoragawa and Hiyoshigawa based on the topography around the Tono Mine and groundwater flow simulation. Evaluation scenarios are classified into 'Scenario for intake of agricultural product' as the base scenario, and 'Scenario for intake of groundwater' as the alternative scenario. Parameters for dose assessment are set-up based on the existing data. But the range and uncertainty of parameters are taken into account in the 'alternative cases'. As the result of dose assessment, maximum exposure dose of the base scenario is 0.08mSv/year, and 0.09mSv/year including direct and skyshine gamma rays and exposure of exhalatedradon at the Higashihoragawa. Maximum exposure dose of the alternative scenario is 0.08mSv/year (0.09mSv/year including direct and skyshine gamma rays and exposure of exhalated radon). On the alternative cases, exposure doses are calculated as 0.05-0.14mSv/year in both of the base and alternative scenarios. At the Hiyoshigawa, maximum exposure dose is less than 0.001mSv/year (1x10 -6 mSv/year) for the base scenario, and 0.001mSv/year for the alternative scenario. On the alternative cases, maximum exposure doses are less than 0.001mSv/year for all cases of the base scenario and 0.0006-0.002mSv/year for the alternative scenario. (author)

  18. Restoring Forests and Associated Ecosystem Services on Appalachian Coal Surface Mines

    Science.gov (United States)

    Zipper, Carl E.; Burger, James A.; Skousen, Jeffrey G.; Angel, Patrick N.; Barton, Christopher D.; Davis, Victor; Franklin, Jennifer A.

    2011-05-01

    Surface coal mining in Appalachia has caused extensive replacement of forest with non-forested land cover, much of which is unmanaged and unproductive. Although forested ecosystems are valued by society for both marketable products and ecosystem services, forests have not been restored on most Appalachian mined lands because traditional reclamation practices, encouraged by regulatory policies, created conditions poorly suited for reforestation. Reclamation scientists have studied productive forests growing on older mine sites, established forest vegetation experimentally on recent mines, and identified mine reclamation practices that encourage forest vegetation re-establishment. Based on these findings, they developed a Forestry Reclamation Approach (FRA) that can be employed by coal mining firms to restore forest vegetation. Scientists and mine regulators, working collaboratively, have communicated the FRA to the coal industry and to regulatory enforcement personnel. Today, the FRA is used routinely by many coal mining firms, and thousands of mined hectares have been reclaimed to restore productive mine soils and planted with native forest trees. Reclamation of coal mines using the FRA is expected to restore these lands' capabilities to provide forest-based ecosystem services, such as wood production, atmospheric carbon sequestration, wildlife habitat, watershed protection, and water quality protection to a greater extent than conventional reclamation practices.

  19. Small scale gold mining in Brazil and Suriname: the troubles of cultural rules, legal regulations and politics of access : In the ENV - Panel Artisanal and small scale mining in Latin America: challenges for reshaping extractive governance

    NARCIS (Netherlands)

    de Theije, Marjo

    2017-01-01

    Suriname and Brazil have very different politics in relation to small scale gold mining. Nevertheless, at the same time we observe a number of similarities in the gold mining practices of both Amazonian countries. In this paper we will identify a number of reasons contributing to the commonalities

  20. Iron oxides in acid mine drainage environments and their association with bacteria

    Energy Technology Data Exchange (ETDEWEB)

    Ferris, F G; Tazaki, K; Fyfe, W S

    1989-01-20

    A variety of iron oxides were identified by X-ray diffraction in sediments receiving acid drainage from mine tailing and coal refuse impoundments. Small amounts of goethite and hematite were found in the sediment samples. However, the major iron oxide species was ferrihydrite which gave diffuse diffraction bands at angles corresponding to d2.5, 2.2 and 1.5 Angstrom. Main core line binding energies in Fe (2p) and O (1s) X-ray photoelectron spectra were consistent with the hydrous nature and predominance of ferrihydrite. Electron microscopy and energy-dispersive X-ray spectroscopy also showed that individual bacterial cells promoted the development of iron oxide mineralization. The bacterial associated iron oxides were similar to those in the bulk sediment samples, and exhibited structures conforming to the presence of chemisorbed sulfate or silicate anions. 23 refs., 3 figs.

  1. Lichens and mosses as monitors of industrial activity associated with uranium mining in northern Ontario, Canada

    International Nuclear Information System (INIS)

    Nieboer, E.; Boileau, L.J.R.; Beckett, P.J.; Lavoie, P.; Padovan, D.

    1982-01-01

    Strong linear regressions (P < 0.001) were observed between background concentrations of iron and titanium in lichens and mosses. For these same samples, the Fe/Ti content ratio was remarkably constant: 8.7 +- 1.8 for fifty-four lichen samples and 10.5 +- 1.5 for thirty-eight mosses. The Fe/Ti concentration ratio for cryptogams collected near uranium mine-exhaust vents accurately reflected the values of this same ratio for the rocks characterising the local ore body. Plant samples exhibiting the largest levels of Fe and Ti also had high mineral ash contents. The various associations and observations reported were interpreted as evidence that particulate trapping is an important elemental accumulation mechanism for lichens and mosses. (author)

  2. Effects of mining-associated lead and zinc soil contamination on native floristic quality.

    Science.gov (United States)

    Struckhoff, Matthew A; Stroh, Esther D; Grabner, Keith W

    2013-04-15

    We assessed the quality of plant communities across a range of lead (Pb) and zinc (Zn) soil concentrations at a variety of sites associated with Pb mining in southeast Missouri, USA. In a novel application, two standard floristic quality measures, Mean Coefficient of Conservatism (Mean C) and Floristic Quality Index (FQI), were examined in relation to concentrations of Pb and Zn, soil nutrients, and other soil characteristics. Nonmetric Multidimensional Scaling and Regression Tree Analyses identified soil Pb and Zn concentrations as primary explanatory variables for plant community composition and indicated negative relationships between soil metals concentrations and both Mean C and FQI. Univariate regression also demonstrated significant negative relationships between metals concentrations and floristic quality. The negative effects of metals in native soils with otherwise relatively undisturbed conditions indicate that elevated soil metals concentrations adversely affect native floristic quality where no other human disturbance is evident. Published by Elsevier Ltd.

  3. Heavy metal pollution associated with an abandoned lead-zinc mine in the Kirki region, NE Greece.

    Science.gov (United States)

    Nikolaidis, Christos; Zafiriadis, Ilias; Mathioudakis, Vasileios; Constantinidis, Theodore

    2010-09-01

    The "Agios Philippos" mine in the Kirki region (NE Greece) has been abandoned in 1998 after half a century of ore exploration without a reclamation or remediation plan. This article aims at elucidating the potential environmental risks associated with this site by quantifying pollution in tailing basins, stream waters, stream sediments and agricultural fields. Concentrations of heavy metals in the abandoned mine tailings reached 12,567 mg/kg for Pb, 22,292 mg/kg for Zn, 174 mg/kg for Cd and 241 mg/kg for As. The geoaccumulation index and enrichment factor for these metals were indicative of extremely high contamination (I(geo) > 5) and extremely high enrichment (EF > 40), respectively. Stream waters in the proximity of the mine had an acidic pH equal to 5.96 and a high sulfate content (SO(4)(-2) = 545.5 mg/L), whereas concentrations of Mn, Zn and Cd reached 2,399 microg/L, 7,681 microg/L and 11.2 microg/L. High I(geo) and EF values for Cd, Zn and As in stream sediments indicates that surface water pollution has a historic background, which is typically associated with acid mine drainage. Agricultural fields in the proximity of the mine exhibited high I(geo) and EF values, which were in decreasing order Cd > Pb > Zn > As. These findings urge for an immediate remediation action of the afflicted area.

  4. Text mining and network analysis to find functional associations of genes in high altitude diseases.

    Science.gov (United States)

    Bhasuran, Balu; Subramanian, Devika; Natarajan, Jeyakumar

    2018-05-02

    Travel to elevations above 2500 m is associated with the risk of developing one or more forms of acute altitude illness such as acute mountain sickness (AMS), high altitude cerebral edema (HACE) or high altitude pulmonary edema (HAPE). Our work aims to identify the functional association of genes involved in high altitude diseases. In this work we identified the gene networks responsible for high altitude diseases by using the principle of gene co-occurrence statistics from literature and network analysis. First, we mined the literature data from PubMed on high-altitude diseases, and extracted the co-occurring gene pairs. Next, based on their co-occurrence frequency, gene pairs were ranked. Finally, a gene association network was created using statistical measures to explore potential relationships. Network analysis results revealed that EPO, ACE, IL6 and TNF are the top five genes that were found to co-occur with 20 or more genes, while the association between EPAS1 and EGLN1 genes is strongly substantiated. The network constructed from this study proposes a large number of genes that work in-toto in high altitude conditions. Overall, the result provides a good reference for further study of the genetic relationships in high altitude diseases. Copyright © 2018 Elsevier Ltd. All rights reserved.

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

    International Nuclear Information System (INIS)

    Toshniwal, Durga

    2013-01-01

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

  6. 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.'

  7. 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

  8. 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.

  9. Beating Obesity: Factors Associated with Interest in Workplace Weight Management Assistance in the Mining Industry.

    Science.gov (United States)

    Street, Tamara D; Thomas, Drew L

    2017-03-01

    Rates of overweight and obese Australians are high and continue to rise, putting a large proportion of the population at risk of chronic illness. Examining characteristics associated with preference for a work-based weight-loss program will enable employers to better target programs to increase enrolment and benefit employees' health and fitness for work. A cross-sectional survey was undertaken at two Australian mining sites. The survey collected information on employee demographics, health characteristics, work characteristics, stages of behavior change, and preference for workplace assistance with reaching a healthy weight. A total of 897 employees participated; 73.7% were male, and 68% had a body mass index in the overweight or obese range. Employees at risk of developing obesity-related chronic illnesses (based on high body mass index) were more likely to report preference for weight management assistance than lower risk employees. This indicates that, even in the absence of workplace promotion for weight management, some at risk employees want workplace assistance. Employees who were not aware of a need to change their current nutrition or physical activity behaviors were less likely to seek assistance. This indicates that practitioners need to communicate the negative effects of excess weight and promote the benefits of a healthy lifestyle to increase the likelihood of weight management. Weight management programs should provide information, motivation. and trouble-shooting assistance to meet the needs of at-risk mining employees, including those who are attempting to change and maintain behaviors to achieve a healthy weight and be suitably fit for work.

  10. Mining Productive-Associated Periodic-Frequent Patterns in Body Sensor Data for Smart Home Care.

    Science.gov (United States)

    Ismail, Walaa N; Hassan, Mohammad Mehedi

    2017-04-26

    The understanding of various health-oriented vital sign data generated from body sensor networks (BSNs) and discovery of the associations between the generated parameters is an important task that may assist and promote important decision making in healthcare. For example, in a smart home scenario where occupants' health status is continuously monitored remotely, it is essential to provide the required assistance when an unusual or critical situation is detected in their vital sign data. In this paper, we present an efficient approach for mining the periodic patterns obtained from BSN data. In addition, we employ a correlation test on the generated patterns and introduce productive-associated periodic-frequent patterns as the set of correlated periodic-frequent items. The combination of these measures has the advantage of empowering healthcare providers and patients to raise the quality of diagnosis as well as improve treatment and smart care, especially for elderly people in smart homes. We develop an efficient algorithm named PPFP-growth (Productive Periodic-Frequent Pattern-growth) to discover all productive-associated periodic frequent patterns using these measures. PPFP-growth is efficient and the productiveness measure removes uncorrelated periodic items. An experimental evaluation on synthetic and real datasets shows the efficiency of the proposed PPFP-growth algorithm, which can filter a huge number of periodic patterns to reveal only the correlated ones.

  11. Mining Productive-Associated Periodic-Frequent Patterns in Body Sensor Data for Smart Home Care

    Directory of Open Access Journals (Sweden)

    Walaa N. Ismail

    2017-04-01

    Full Text Available The understanding of various health-oriented vital sign data generated from body sensor networks (BSNs and discovery of the associations between the generated parameters is an important task that may assist and promote important decision making in healthcare. For example, in a smart home scenario where occupants’ health status is continuously monitored remotely, it is essential to provide the required assistance when an unusual or critical situation is detected in their vital sign data. In this paper, we present an efficient approach for mining the periodic patterns obtained from BSN data. In addition, we employ a correlation test on the generated patterns and introduce productive-associated periodic-frequent patterns as the set of correlated periodic-frequent items. The combination of these measures has the advantage of empowering healthcare providers and patients to raise the quality of diagnosis as well as improve treatment and smart care, especially for elderly people in smart homes. We develop an efficient algorithm named PPFP-growth (Productive Periodic-Frequent Pattern-growth to discover all productive-associated periodic frequent patterns using these measures. PPFP-growth is efficient and the productiveness measure removes uncorrelated periodic items. An experimental evaluation on synthetic and real datasets shows the efficiency of the proposed PPFP-growth algorithm, which can filter a huge number of periodic patterns to reveal only the correlated ones.

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

    Science.gov (United States)

    Dipnall, Joanna F.

    2016-01-01

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

  13. 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.

  14. The N-terminal amphipathic helix of the topological specificity factor MinE is associated with shaping membrane curvature.

    Directory of Open Access Journals (Sweden)

    Yu-Ling Shih

    Full Text Available Pole-to-pole oscillations of the Min proteins in Escherichia coli are required for the proper placement of the division septum. Direct interaction of MinE with the cell membrane is critical for the dynamic behavior of the Min system. In vitro, this MinE-membrane interaction led to membrane deformation; however, the underlying mechanism remained unclear. Here we report that MinE-induced membrane deformation involves the formation of an amphipathic helix of MinE(2-9, which, together with the adjacent basic residues, function as membrane anchors. Biochemical evidence suggested that the membrane association induces formation of the helix, with the helical face, consisting of A2, L3, and F6, inserted into the membrane. Insertion of this helix into the cell membrane can influence local membrane curvature and lead to drastic changes in membrane topology. Accordingly, MinE showed characteristic features of protein-induced membrane tubulation and lipid clustering in in vitro reconstituted systems. In conclusion, MinE shares common protein signatures with a group of membrane trafficking proteins in eukaryotic cells. These MinE signatures appear to affect membrane curvature.

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

    KAUST Repository

    Raies, A. B.; Mansour, H.; Incitti, R.; Bajic, Vladimir B.

    2014-01-01

    ://www.cbrc.kaust.edu.sa/ddmgd/) to provide a comprehensive repository of information related to genes methylated in diseases that can be found through text mining. DDMGD's scope is not limited to a particular group of genes, diseases or species. Using the text mining system DEMGD we

  16. Introducing a Simple Equation to Express Oxidation States as an Alternative to Using Rules Associated with Words Alone

    Science.gov (United States)

    Minkiewicz, Piotr; Darewicz, Malgorzata; Iwaniak, Anna

    2018-01-01

    A simple equation to calculate the oxidation states (oxidation numbers) of individual atoms in molecules and ions may be introduced instead of rules associated with words alone. The equation includes two of three categories of bonds, classified as proposed by Goodstein: number of bonds with more electronegative atoms and number of bonds with less…

  17. Costs of abandoned coal mine reclamation and associated recreation benefits in Ohio.

    Science.gov (United States)

    Mishra, Shruti K; Hitzhusen, Frederick J; Sohngen, Brent L; Guldmann, Jean-Michel

    2012-06-15

    Two hundred years of coal mining in Ohio have degraded land and water resources, imposing social costs on its citizens. An interdisciplinary approach employing hydrology, geographic information systems, and a recreation visitation function model, is used to estimate the damages from upstream coal mining to lakes in Ohio. The estimated recreational damages to five of the coal-mining-impacted lakes, using dissolved sulfate as coal-mining-impact indicator, amount to $21 Million per year. Post-reclamation recreational benefits from reducing sulfate concentrations by 6.5% and 15% in the five impacted lakes were estimated to range from $1.89 to $4.92 Million per year, with a net present value ranging from $14.56 Million to $37.79 Million. A benefit costs analysis (BCA) of recreational benefits and coal mine reclamation costs provides some evidence for potential Pareto improvement by investing limited resources in reclamation projects. Copyright © 2012 Elsevier Ltd. All rights reserved.

  18. Development and application of an interaction network ontology for literature mining of vaccine-associated gene-gene interactions.

    Science.gov (United States)

    Hur, Junguk; Özgür, Arzucan; Xiang, Zuoshuang; He, Yongqun

    2015-01-01

    Literature mining of gene-gene interactions has been enhanced by ontology-based name classifications. However, in biomedical literature mining, interaction keywords have not been carefully studied and used beyond a collection of keywords. In this study, we report the development of a new Interaction Network Ontology (INO) that classifies >800 interaction keywords and incorporates interaction terms from the PSI Molecular Interactions (PSI-MI) and Gene Ontology (GO). Using INO-based literature mining results, a modified Fisher's exact test was established to analyze significantly over- and under-represented enriched gene-gene interaction types within a specific area. Such a strategy was applied to study the vaccine-mediated gene-gene interactions using all PubMed abstracts. The Vaccine Ontology (VO) and INO were used to support the retrieval of vaccine terms and interaction keywords from the literature. INO is aligned with the Basic Formal Ontology (BFO) and imports terms from 10 other existing ontologies. Current INO includes 540 terms. In terms of interaction-related terms, INO imports and aligns PSI-MI and GO interaction terms and includes over 100 newly generated ontology terms with 'INO_' prefix. A new annotation property, 'has literature mining keywords', was generated to allow the listing of different keywords mapping to the interaction types in INO. Using all PubMed documents published as of 12/31/2013, approximately 266,000 vaccine-associated documents were identified, and a total of 6,116 gene-pairs were associated with at least one INO term. Out of 78 INO interaction terms associated with at least five gene-pairs of the vaccine-associated sub-network, 14 terms were significantly over-represented (i.e., more frequently used) and 17 under-represented based on our modified Fisher's exact test. These over-represented and under-represented terms share some common top-level terms but are distinct at the bottom levels of the INO hierarchy. The analysis of these

  19. Goal directed worry rules are associated with distinct patterns of amygdala functional connectivity and vagal modulation during perseverative cognition

    OpenAIRE

    Meeten, Frances; Davey, Graham C L; Makovac, Elena; Watson, David R.; Garfinkel, Sarah N.; Critchley, Hugo D.; Ottaviani, Cristina

    2016-01-01

    Excessive and uncontrollable worry is a defining feature of Generalized Anxiety Disorder (GAD). An important endeavor in the treatment of pathological worry is to understand why some people are unable to stop worrying once they have started. Worry perseveration is associated with a tendency to deploy goal-directed worry rules (known as “as many as can” worry rules; AMA). These require attention to the goal of the worry task and continuation of worry until the aims of the “worry bout” are achi...

  20. Central line-associated bloodstream infections and catheter dwell-time: A theoretical foundation for a rule of thumb.

    Science.gov (United States)

    Voets, Philip J G M

    2018-05-14

    Many clinicians know from experience and medical epidemiological literature that the risk of central line-associated bloodstream infections (CLABSI) increases rapidly with a prolonged catheter dwell-time, but how this infection risk increases over time remains obscure. In this manuscript, a clinically useful rule of thumb is derived, stating that the risk of CLABSI increases in a quadratic fashion with the increase in catheter dwell-time. The proposed rule of thumb could be considered a quick and effortless clinical tool to rationally predict the pattern of CLABSI risk with an increasing catheter dwell-time. Copyright © 2018. Published by Elsevier Ltd.

  1. Application of text mining for customer evaluations in commercial banking

    Science.gov (United States)

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

    2015-07-01

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

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

    Science.gov (United States)

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

    2016-01-01

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

  3. Using Association Rules to Study the Co-evolution of Production & Test Code

    NARCIS (Netherlands)

    Lubsen, Z.; Zaidman, A.; Pinzger, M.

    2009-01-01

    Paper accepted for publication in the proceedings of the 6th International Working Conference on Mining Software Repositories (MSR 2009). Unit tests are generally acknowledged as an important aid to produce high quality code, as they provide quick feedback to developers on the correctness of their

  4. Habituation: a non-associative learning rule design for spiking neurons and an autonomous mobile robots implementation

    International Nuclear Information System (INIS)

    Cyr, André; Boukadoum, Mounir

    2013-01-01

    This paper presents a novel bio-inspired habituation function for robots under control by an artificial spiking neural network. This non-associative learning rule is modelled at the synaptic level and validated through robotic behaviours in reaction to different stimuli patterns in a dynamical virtual 3D world. Habituation is minimally represented to show an attenuated response after exposure to and perception of persistent external stimuli. Based on current neurosciences research, the originality of this rule includes modulated response to variable frequencies of the captured stimuli. Filtering out repetitive data from the natural habituation mechanism has been demonstrated to be a key factor in the attention phenomenon, and inserting such a rule operating at multiple temporal dimensions of stimuli increases a robot's adaptive behaviours by ignoring broader contextual irrelevant information. (paper)

  5. Habituation: a non-associative learning rule design for spiking neurons and an autonomous mobile robots implementation.

    Science.gov (United States)

    Cyr, André; Boukadoum, Mounir

    2013-03-01

    This paper presents a novel bio-inspired habituation function for robots under control by an artificial spiking neural network. This non-associative learning rule is modelled at the synaptic level and validated through robotic behaviours in reaction to different stimuli patterns in a dynamical virtual 3D world. Habituation is minimally represented to show an attenuated response after exposure to and perception of persistent external stimuli. Based on current neurosciences research, the originality of this rule includes modulated response to variable frequencies of the captured stimuli. Filtering out repetitive data from the natural habituation mechanism has been demonstrated to be a key factor in the attention phenomenon, and inserting such a rule operating at multiple temporal dimensions of stimuli increases a robot's adaptive behaviours by ignoring broader contextual irrelevant information.

  6. Unstable Malaria Transmission in the Southern Peruvian Amazon and Its Association with Gold Mining, Madre de Dios, 2001–2012

    Science.gov (United States)

    Sanchez, Juan F.; Carnero, Andres M.; Rivera, Esteban; Rosales, Luis A.; Baldeviano, G. Christian; Asencios, Jorge L.; Edgel, Kimberly A.; Vinetz, Joseph M.; Lescano, Andres G.

    2017-01-01

    The reemergence of malaria in the last decade in Madre de Dios, southern Peruvian Amazon basin, was accompanied by ecological, political, and socioeconomic changes related to the proliferation of illegal gold mining. We conducted a secondary analysis of passive malaria surveillance data reported by the health networks in Madre de Dios between 2001 and 2012. We calculated the number of cases of malaria by year, geographic location, intensity of illegal mining activities, and proximity of health facilities to the Peru–Brazil Interoceanic Highway. During 2001–2012, 203,773 febrile cases were identified in Madre de Dios, of which 30,811 (15.1%) were confirmed cases of malaria; all but 10 cases were due to Plasmodium vivax. Cases of malaria rose rapidly between 2004 and 2007, reached 4,469 cases in 2005, and then declined after 2010 to pre-2004 levels. Health facilities located in areas of intense illegal gold mining reported 30-fold more cases than those in non-mining areas (ratio = 31.54, 95% confidence interval [CI] = 19.28, 51.60). Finally, health facilities located > 1 km from the Interoceanic Highway reported significantly more cases than health facilities within this distance (ratio = 16.20, 95% CI = 8.25, 31.80). Transmission of malaria in Madre de Dios is unstable, geographically heterogeneous, and strongly associated with illegal gold mining. These findings highlight the importance of spatially oriented interventions to control malaria in Madre de Dios, as well as the need for research on malaria transmission in illegal gold mining camps. PMID:27879461

  7. The effect of the depth and groundwater on the formation of sinkholes or ground subsidence associated with abandoned room and pillar lignite mines under static and dynamic conditions

    Directory of Open Access Journals (Sweden)

    Ö. Aydan

    2015-11-01

    Full Text Available It is well known that some sinkholes or subsidence take place from time to time in the areas where abandoned room and pillar type mines exist. The author has been involved with the stability of abandoned mines beneath urbanized residential areas in Tokai region and there is a great concern about the stability of these abandoned mines during large earthquakes as well as in the long term. The 2003 Miyagi Hokubu and 2011 Great East Japan earthquakes caused great damage to abandoned mines and resulted in many collapses. The author presents the effect of the depth and groundwater on the formation of sinkholes or ground subsidence associated with abandoned room and pillar lignite mines under static and dynamic conditions and discusses the implications on the areas above abandoned lignite mines in this paper.

  8. Hierarchy-associated semantic-rule inference framework for classifying indoor scenes

    Science.gov (United States)

    Yu, Dan; Liu, Peng; Ye, Zhipeng; Tang, Xianglong; Zhao, Wei

    2016-03-01

    Typically, the initial task of classifying indoor scenes is challenging, because the spatial layout and decoration of a scene can vary considerably. Recent efforts at classifying object relationships commonly depend on the results of scene annotation and predefined rules, making classification inflexible. Furthermore, annotation results are easily affected by external factors. Inspired by human cognition, a scene-classification framework was proposed using the empirically based annotation (EBA) and a match-over rule-based (MRB) inference system. The semantic hierarchy of images is exploited by EBA to construct rules empirically for MRB classification. The problem of scene classification is divided into low-level annotation and high-level inference from a macro perspective. Low-level annotation involves detecting the semantic hierarchy and annotating the scene with a deformable-parts model and a bag-of-visual-words model. In high-level inference, hierarchical rules are extracted to train the decision tree for classification. The categories of testing samples are generated from the parts to the whole. Compared with traditional classification strategies, the proposed semantic hierarchy and corresponding rules reduce the effect of a variable background and improve the classification performance. The proposed framework was evaluated on a popular indoor scene dataset, and the experimental results demonstrate its effectiveness.

  9. Surface structural damage associated with longwall mining near Tuscaloosa, Alabama: a case history

    International Nuclear Information System (INIS)

    Isphording, W.C.

    1992-01-01

    Initially the paper examines the frequency of coal mine subsidence and the influence on surface subsidence of subsurface mining methods, i.e. room and pillar and longwall mining. A case study of the subsidence damage caused to a log house near Tuscaloosa, Alabama (USA), when a longwall panel passed beneath it is presented. The damage resulted in the homeowners suing the mining company for negligence. The article discusses information provided to the plaintiffs attorneys by the author. Aspects covered are: the subsidence and damage to the property; prediction of subsidence; the monitoring of subsidence; and the prevention of subsidence. An out-of-court settlement was agreed by the two parties. 15 refs., 5 figs

  10. Personalized privacy-preserving frequent itemset mining using randomized response.

    Science.gov (United States)

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

    2014-01-01

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

  11. Public exposure to hazards associated with natural radioactivity in open-pit mining in Ghana.

    Science.gov (United States)

    Darko, E O; Faanu, A; Awudu, A R; Emi-Reynolds, G; Yeboah, J; Oppon, O C; Akaho, E H K

    2010-01-01

    The results of studies carried out on public exposure contribution from naturally occurring radioactive materials (NORMS) in two open-pit mines in the Western and Ashanti regions of Ghana are reported. The studies were carried out under International Atomic Energy Agency-supported Technical Co-operation Project GHA/9/005. Measurements were made on samples of water, soil, ore, mine tailings and air using gamma spectrometry. Solid-state nuclear track detectors were used for radon concentration measurements. Survey was also carried out to determine the ambient gamma dose rate in the vicinity of the mines and surrounding areas. The effective doses due to external gamma irradiation, ingestion of water and inhalation of radon and ore dusts were calculated for the two mines. The average annual effective dose was found to be 0.30 +/- 0.06 mSv. The result was found to be within the levels published by other countries. The study provides a useful information and data for establishing a comprehensive framework to investigate other mines and develop guidelines for monitoring and control of NORMS in the mining industry and the environment as a whole in Ghana.

  12. Public health risk assessment associated with heavy metal and arsenic exposure near an abandoned mine (Kirki, Greece).

    Science.gov (United States)

    Nikolaidis, Christos; Orfanidis, Moysis; Hauri, Dimitri; Mylonas, Stratos; Constantinidis, Theodore

    2013-12-01

    The 'Agios Philippos' lead-zinc mine in the Kirki region (NE Greece) is now closed, but its legacy of heavy metal contamination remains at the site. At present, management of the contaminated land is of major concern. The area is in a reclamation process and requires immediate remediation action, whereas human risks need to be carefully evaluated. In order to assess these risks, samples from around the mine were collected and analyzed and a scenario involving the oral, dermal, and inhaled doses of arsenic and heavy metals was formulated. A Monte Carlo approach was undertaken, in order to model the average daily dose and quantify the corresponding hazard index and cancer risk. A toxicological risk was associated with samples collected in the vicinity of the mine (floatation, mine tailings) and a pronounced carcinogenic risk for arsenic was evident at the broader occupational/environmental setting. These findings urge for immediate rehabilitation actions that will mitigate population exposures and promote long-term environmental safety in the area.

  13. The HIPAA privacy rule and HR/benefits outsourcing: does the business associate label belong on your recordkeeper?

    Science.gov (United States)

    Hilger, Denise D

    2004-01-01

    Employers that sponsor group health plans and serve as the plan administrator of those plans are required by the HIPAA Privacy Rule to execute business associate contracts with vendors that provide services on behalf of the plans. The business associate contracts must contain many specific provisions regarding the protection, use and disclosure of health information. This article looks at the implications of imposing business associate contract obligations on an integrated HR and benefits-outsourcing recordkeeper and cautions employers against an overly broad application of the requirements.

  14. 75 FR 1426 - National Futures Association; Notice of Filing and Immediate Effectiveness of Proposed Rule...

    Science.gov (United States)

    2010-01-11

    ...) require that certain audio and video advertisements that appear on the Internet--like similar radio and... CPO/CTA Advisory Committees considered the growing use of social networking groups such as blogs, chat... advertisements, while participating in a chat room is a public appearance subject to FINRA rules. The guidance...

  15. Split-Ring Springback Simulations with the Non-associated Flow Rule and Evolutionary Elastic-Plasticity Models

    Science.gov (United States)

    Lee, K. J.; Choi, Y.; Choi, H. J.; Lee, J. Y.; Lee, M. G.

    2018-06-01

    Finite element simulations and experiments for the split-ring test were conducted to investigate the effect of anisotropic constitutive models on the predictive capability of sheet springback. As an alternative to the commonly employed associated flow rule, a non-associated flow rule for Hill1948 yield function was implemented in the simulations. Moreover, the evolution of anisotropy with plastic deformation was efficiently modeled by identifying equivalent plastic strain-dependent anisotropic coefficients. Comparative study with different yield surfaces and elasticity models showed that the split-ring springback could be best predicted when the anisotropy in both the R value and yield stress, their evolution and variable apparent elastic modulus were taken into account in the simulations. Detailed analyses based on deformation paths superimposed on the anisotropic yield functions predicted by different constitutive models were provided to understand the complex springback response in the split-ring test.

  16. World Nuclear Association (WNA) internationally standardized reporting (checklist) on the sustainable development performance of uranium mining and processing sites

    International Nuclear Information System (INIS)

    Harris, F.

    2014-01-01

    The World Nuclear Association (WNA) has developed internationally standardized reporting (‘Checklist’) for uranium mining and processing sites. This reporting is to achieve widespread utilities/miners agreement on a list of topics/indicators for common use in demonstrating miners’ adherence to strong sustainable development performance. Nuclear utilities are often required to evaluate the sustainable development performance of their suppliers as part of a utility operational management system. In the present case, nuclear utilities are buyers of uranium supplies from uranium miners and such purchases are often achieved through the utility uranium or fuel supply management function. This Checklist is an evaluation tool which has been created to collect information from uranium miners’ available annual reports, data series, and measurable indicators on a wide range of sustainable development topics to verify that best practices in this field are implemented throughout uranium mining and processing sites. The Checklist has been developed to align with the WNA’s policy document Sustaining Global Best Practices in Uranium Mining and Processing: Principles for Managing Radiation, Health and Safety, and Waste and the Environment which encompasses all applicable aspects of sustainable development to uranium mining and processing. The eleven sections of the Checklist are: 1. Adherence to Sustainable Development; 2. Health, Safety and Environmental Protection; 3. Compliance; 4. Social Responsibility and Stakeholder Engagement; 5. Management of Hazardous Materials; 6. Quality Management Systems; 7. Accidents and Emergencies; 8. Transport of Hazardous Materials; 9. Systematic Approach to Training; 10. Security of Sealed Radioactive Sources and Nuclear Substances; 11. Decommissioning and Site Closure. The Checklist benefits from many years of nuclear utility experience in verifying the sustainable development performance of uranium mining and processing sites. This

  17. Regional scale selenium loading associated with surface coal mining, Elk Valley, British Columbia, Canada.

    Science.gov (United States)

    Wellen, Christopher C; Shatilla, Nadine J; Carey, Sean K

    2015-11-01

    Selenium (Se) concentrations in surface water downstream of surface mining operations have been reported at levels in excess of water quality guidelines for the protection of wildlife. Previous research in surface mining environments has focused on downstream water quality impacts, yet little is known about the fundamental controls on Se loading. This study investigated the relationship between mining practices, stream flows and Se concentrations using a SPAtially Referenced Regression On Watershed attributes (SPARROW) model. This work is part of a R&D program examining the influence of surface coal mining on hydrological and water quality responses in the Elk Valley, British Columbia, Canada, aimed at informing effective management responses. Results indicate that waste rock volume, a product of mining activity, accounted for roughly 80% of the Se load from the Elk Valley, while background sources accounted for roughly 13%. Wet years were characterized by more than twice the Se load of dry years. A number of variables regarding placement of waste rock within the catchments, length of buried streams, and the construction of rock drains did not significantly influence the Se load. The age of the waste rock, the proportion of waste rock surface reclaimed, and the ratio of waste rock pile side area to top area all varied inversely with the Se load from watersheds containing waste rock. These results suggest operational practices that are likely to reduce the release of Se to surface waters. Copyright © 2015 Elsevier B.V. All rights reserved.

  18. 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.

  19. An evaluation of trace element release associated with acid mine drainage

    International Nuclear Information System (INIS)

    Sullivan, P.J.; Yelton, J.L.

    1988-01-01

    The determination of trace element release from geologic materials, such as oil shale and coal overburden, is important for proper solid waste management planning. The objective of this study was to determine a correlation between release using the following methods: (1) sequential selective dissolution for determining trace element residencies, (2) toxicity characteristic leaching procedure (TCLP), and (3) humidity cell weathering study simulating maximum trace element release. Two eastern oil shales were used, a New Albany shale that contains 4.6 percent pyrite, and a Chattanooga shale that contains 1.5 percent pyrite. Each shale was analyzed for elemental concentrations by soluble, adsorbed, organic, carbonate, and sulfide phases. The results of the results of the selective dissolution studies show that each trace element has a unique distribution between the various phases. Thus, it is possible to predict trace element release based on trace element residency. The TCLP results show that this method is suitable for assessing soluble trace element release but does not realistically assess potential hazards. The results of the humidity cell studies do demonstrate a more reasonable method for predicting trace element release and potential water quality hazards. The humidity cell methods, however, require months to obtain the required data with a large number of analytical measurements. When the selective dissolution data are compared to the trace element concentrations in the TCLP and humidity cell leachates, it is shown that leachate concentrations are predicted by the selective dissolution data. Therefore, selective dissolution may represent a rapid method to assess trace element release associated with acid mine drainage

  20. Geophysical anomalies associated with uranium mineralization from Beldih mine, South Purulia Shear Zone, India

    International Nuclear Information System (INIS)

    Mandal, Animesh; Biswas, Arkoprovo; Mittal, Saurabh; Mohanty, William K.; Sharma, Shashi Prakash; Sengupta, Debashish; Sen, Joydip; Bhatt, A.K.

    2013-01-01

    Beldih mine at the central part of the South Purulia Shear Zone (SPSZ) has been reported with low grade uranium-bearing formation within quartz-magnetite-apatite host in kaolinized formation. Therefore, the present integrated geophysical study with gravity, magnetic, radiometric, very low frequency electromagnetic (VLF) and gradient resistivity profiling methods around the known mineralized zones aimed at identifying the exact geophysical signatures and lateral extent of these uranium mineralization bands. The closely spaced gravity-magnetic contours over the low to high anomaly transition zones of Bouguer, reduced-to-pole magnetic, and trend surface separated residual gravity-magnetic anomaly maps indicate the possibility of high altered zone(s) along NW-SE direction at the central part of the study area. High current density plots of VLF method and the low resistive zones in gradient resistivity study depict the coincidence with low gravity, moderately high magnetic and low resistivity anomalies at the same locations. Moderate high radioactive zones have also been observed over these locations. This also suggests the existence of radioactive mineralization over this region. Along profile P2, drilled borehole data revealed the presence of uranium mineralization at a depth of ∼100 m. The vertical projection of this mineralization band also identified as low gravity, low resistivity and high magnetic anomaly zone. Thus, the application of integrated geophysical techniques supported by geological information successfully recognized the nature of geophysical signatures associated with the uranium mineralization of this region. This enhances the scope of further integrated geophysical investigations in the unexplored regions of SPSZ. (author)

  1. A fuzzy hill-climbing algorithm for the development of a compact associative classifier

    Science.gov (United States)

    Mitra, Soumyaroop; Lam, Sarah S.

    2012-02-01

    Classification, a data mining technique, has widespread applications including medical diagnosis, targeted marketing, and others. Knowledge discovery from databases in the form of association rules is one of the important data mining tasks. An integrated approach, classification based on association rules, has drawn the attention of the data mining community over the last decade. While attention has been mainly focused on increasing classifier accuracies, not much efforts have been devoted towards building interpretable and less complex models. This paper discusses the development of a compact associative classification model using a hill-climbing approach and fuzzy sets. The proposed methodology builds the rule-base by selecting rules which contribute towards increasing training accuracy, thus balancing classification accuracy with the number of classification association rules. The results indicated that the proposed associative classification model can achieve competitive accuracies on benchmark datasets with continuous attributes and lend better interpretability, when compared with other rule-based systems.

  2. Regulatory issues associated with exclusion, exemption, and clearance related to the mining and minerals processing industries

    International Nuclear Information System (INIS)

    Metcalf, P.; Woude, S. van der; Keenan, N.; Guy, S.

    1997-01-01

    The concepts of exclusion, exemption and clearance have been established in international recommendations and, standards for radiation protection and the management of radioactive waste in recent years. The consistent application of these concepts has given rise to various problems in different spheres of use. This is particularly the case in the mining and minerals processing industries dealing with materials exhibiting elevated concentrations of naturally occurring radionuclides. This paper takes the South African mining industry as an example and highlights some of the issues that have arisen in applying these concepts within a regulatory control regime. (author)

  3. Molecular diversity of the methanotrophic bacteria communities associated with disused tin-mining ponds in Kampar, Perak, Malaysia.

    Science.gov (United States)

    Sow, S L S; Khoo, G; Chong, L K; Smith, T J; Harrison, P L; Ong, H K A

    2014-10-01

    In a previous study, notable differences of several physicochemical properties, as well as the community structure of ammonia oxidizing bacteria as judged by 16S rRNA gene analysis, were observed among several disused tin-mining ponds located in the town of Kampar, Malaysia. These variations were associated with the presence of aquatic vegetation as well as past secondary activities that occurred at the ponds. Here, methane oxidizing bacteria (MOB), which are direct participants in the nutrient cycles of aquatic environments and biological indicators of environmental variations, have been characterised via analysis of pmoA functional genes in the same environments. The MOB communities associated with disused tin-mining ponds that were exposed to varying secondary activities were examined in comparison to those in ponds that were left to nature. Comparing the sequence and phylogenetic analysis of the pmoA clone libraries at the different ponds (idle, lotus-cultivated and post-aquaculture), we found pmoA genes indicating the presence of type I and type II MOB at all study sites, but type Ib sequences affiliated with the Methylococcus/Methylocaldum lineage were most ubiquitous (46.7 % of clones). Based on rarefaction analysis and diversity indices, the disused mining pond with lotus culture was observed to harbor the highest richness of MOB. However, varying secondary activity or sample type did not show a strong variation in community patterns as compared to the ammonia oxidizers in our previous study.

  4. Compass: A hybrid method for clinical and biobank data mining

    DEFF Research Database (Denmark)

    Krysiak-Baltyn, Konrad; Petersen, Thomas Nordahl; Audouze, Karine Marie Laure

    2014-01-01

    We describe a new method for identification of confident associations within large clinical data sets. The method is a hybrid of two existing methods; Self-Organizing Maps and Association Mining. We utilize Self-Organizing Maps as the initial step to reduce the search space, and then apply...... Association Mining in order to find association rules. We demonstrate that this procedure has a number of advantages compared to traditional Association Mining; it allows for handling numerical variables without a priori binning and is able to generate variable groups which act as “hotspots” for statistically...... significant associations. We showcase the method on infertility-related data from Danish military conscripts. The clinical data we analyzed contained both categorical type questionnaire data and continuous variables generated from biological measurements, including missing values. From this data set, we...

  5. The spatial decision-supporting system combination of RBR & CBR based on artificial neural network and association rules

    Science.gov (United States)

    Tian, Yangge; Bian, Fuling

    2007-06-01

    The technology of artificial intelligence should be imported on the basis of the geographic information system to bring up the spatial decision-supporting system (SDSS). The paper discusses the structure of SDSS, after comparing the characteristics of RBR and CBR, the paper brings up the frame of a spatial decisional system that combines RBR and CBR, which has combined the advantages of them both. And the paper discusses the CBR in agriculture spatial decisions, the application of ANN (Artificial Neural Network) in CBR, and enriching the inference rule base based on association rules, etc. And the paper tests and verifies the design of this system with the examples of the evaluation of the crops' adaptability.

  6. Beating Obesity: Factors Associated with Interest in Workplace Weight Management Assistance in the Mining Industry

    Directory of Open Access Journals (Sweden)

    Tamara D. Street

    2017-03-01

    Conclusion: Weight management programs should provide information, motivation. and trouble-shooting assistance to meet the needs of at-risk mining employees, including those who are attempting to change and maintain behaviors to achieve a healthy weight and be suitably fit for work.

  7. Seismic monitoring of ground caving processes associated with longwall mining of coal

    International Nuclear Information System (INIS)

    Hatherly, P.; Luo, X.; Dixon, R.; McKavanagh, B.

    1997-01-01

    At the Gordonstone Coal Mine in Central Queensland, Australia, a microseismic monitoring study was undertaken to investigate the extent of ground failure caused by longwall mining. Twenty seven triaxial geophones were deployed in three vertical boreholes and over a six week period more than 1200 events were recorded. The seismicity correlated with periods of longwall production and occurred mainly within the 250 m wide mining panel. There was an arcuate zone of activity which extended from behind the face, at the sides of the panel and up to 70 m ahead of the face in the middle. There was lesser activity to a depth of about 30 m into the floor. The focal mechanisms show that reverse faulting was dominant. The presence of activity and reverse faulting ahead of the face was an unexpected result. However, piezometer readings at the time of the study and subsequent numerical modelling have supported this finding. This was the first detailed microseismic monitoring study of caving in an Australian underground coal mine. 9 refs., 6 figs

  8. Characterization of iron and manganese minerals and their associated microbiota in different mine sites to reveal the potential interactions of microbiota with mineral formation.

    Science.gov (United States)

    Park, Jin Hee; Kim, Bong-Soo; Chon, Chul-Min

    2018-01-01

    Different environmental conditions such as pH and dissolved elements of mine stream induce precipitation of different minerals and their associated microbial community may vary. Therefore, mine precipitates from various environmental conditions were collected and their associated microbiota were analyzed through metagenomic DNA sequencing. Various Fe and Mn minerals including ferrihydrite, schwertmannite, goethite, birnessite, and Mn-substituted δ-FeOOH (δ-(Fe 1-x , Mn x )OOH) were found in the different environmental conditions. The Fe and Mn minerals were enriched with toxic metal(loid)s including As, Cd, Ni and Zn, indicating they can act as scavengers of toxic metal(loid)s in mine streams. Under acidic conditions, Acidobacteria was dominant phylum and Gallionella (Fe oxidizing bacteria) was the predominant genus in these Fe rich environments. Manganese oxidizing bacteria, Hyphomicrobium, was found in birnessite forming environments. Leptolyngbya within Cyanobacteria was found in Fe and Mn oxidizing environments, and might contribute to Fe and Mn oxidation through the production of molecular oxygen. The potential interaction of microbial community with minerals in mine sites can be traced by analysis of microbial community in different Fe and Mn mineral forming environments. Iron and Mn minerals contribute to the removal of toxic metal(loid)s from mine water. Therefore, the understanding characteristics of mine precipitates and their associated microbes helps to develop strategies for the management of contaminated mine water. Copyright © 2017 Elsevier Ltd. All rights reserved.

  9. Sustainable Mining Environment: Technical Review of Post-mining Plans

    Directory of Open Access Journals (Sweden)

    Restu Juniah

    2017-12-01

    Full Text Available The mining industry exists because humans need mining commodities to meet their daily needs such as motor vehicles, mobile phones, electronic equipment and others. Mining commodities as mentioned in Government Regulation No. 23 of 2010 on Implementation of Mineral and Coal Mining Business Activities are radioactive minerals, metal minerals, nonmetallic minerals, rocks and coal. Mineral and coal mining is conducted to obtain the mining commodities through production operations. Mining and coal mining companies have an obligation to ensure that the mining environment in particular after the post production operation or post mining continues. The survey research aims to examine technically the post-mining plan in coal mining of PT Samantaka Batubara in Indragiri Hulu Regency of Riau Province towards the sustainability of the mining environment. The results indicate that the post-mining plan of PT Samantaka Batubara has met the technical aspects required in post mining planning for a sustainable mining environment. Postponement of post-mining land of PT Samantaka Batubara for garden and forest zone. The results of this study are expected to be useful and can be used by stakeholders, academics, researchers, practitioners and associations of mining, and the environment.

  10. Detection of Independent Associations of Plasma Lipidomic Parameters with Insulin Sensitivity Indices Using Data Mining Methodology.

    Directory of Open Access Journals (Sweden)

    Steffi Kopprasch

    Full Text Available Glucolipotoxicity is a major pathophysiological mechanism in the development of insulin resistance and type 2 diabetes mellitus (T2D. We aimed to detect subtle changes in the circulating lipid profile by shotgun lipidomics analyses and to associate them with four different insulin sensitivity indices.The cross-sectional study comprised 90 men with a broad range of insulin sensitivity including normal glucose tolerance (NGT, n = 33, impaired glucose tolerance (IGT, n = 32 and newly detected T2D (n = 25. Prior to oral glucose challenge plasma was obtained and quantitatively analyzed for 198 lipid molecular species from 13 different lipid classes including triacylglycerls (TAGs, phosphatidylcholine plasmalogen/ether (PC O-s, sphingomyelins (SMs, and lysophosphatidylcholines (LPCs. To identify a lipidomic signature of individual insulin sensitivity we applied three data mining approaches, namely least absolute shrinkage and selection operator (LASSO, Support Vector Regression (SVR and Random Forests (RF for the following insulin sensitivity indices: homeostasis model of insulin resistance (HOMA-IR, glucose insulin sensitivity index (GSI, insulin sensitivity index (ISI, and disposition index (DI. The LASSO procedure offers a high prediction accuracy and and an easier interpretability than SVR and RF.After LASSO selection, the plasma lipidome explained 3% (DI to maximal 53% (HOMA-IR variability of the sensitivity indexes. Among the lipid species with the highest positive LASSO regression coefficient were TAG 54:2 (HOMA-IR, PC O- 32:0 (GSI, and SM 40:3:1 (ISI. The highest negative regression coefficient was obtained for LPC 22:5 (HOMA-IR, TAG 51:1 (GSI, and TAG 58:6 (ISI.Although a substantial part of lipid molecular species showed a significant correlation with insulin sensitivity indices we were able to identify a limited number of lipid metabolites of particular importance based on the LASSO approach. These few selected lipids with the closest

  11. Uncovering Hospitalists' Information Needs from Outside Healthcare Facilities in the Context of Health Information Exchange Using Association Rule Learning.

    Science.gov (United States)

    Martinez, D A; Mora, E; Gemmani, M; Zayas-Castro, J

    2015-01-01

    Important barriers to health information exchange (HIE) adoption are clinical workflow disruptions and troubles with the system interface. Prior research suggests that HIE interfaces providing faster access to useful information may stimulate use and reduce barriers for adoption; however, little is known about informational needs of hospitalists. To study the association between patient health problems and the type of information requested from outside healthcare providers by hospitalists of a tertiary care hospital. We searched operational data associated with fax-based exchange of patient information (previous HIE implementation) between hospitalists of an internal medicine department in a large urban tertiary care hospital in Florida, and any other affiliated and unaffiliated healthcare provider. All hospitalizations from October 2011 to March 2014 were included in the search. Strong association rules between health problems and types of information requested during each hospitalization were discovered using Apriori algorithm, which were then validated by a team of hospitalists of the same department. Only 13.7% (2 089 out of 15 230) of the hospitalizations generated at least one request of patient information to other providers. The transactional data showed 20 strong association rules between specific health problems and types of information exist. Among the 20 rules, for example, abdominal pain, chest pain, and anaemia patients are highly likely to have medical records and outside imaging results requested. Other health conditions, prone to have records requested, were lower urinary tract infection and back pain patients. The presented list of strong co-occurrence of health problems and types of information requested by hospitalists from outside healthcare providers not only informs the implementation and design of HIE, but also helps to target future research on the impact of having access to outside information for specific patient cohorts. Our data

  12. Displaced rocks, strong motion, and the mechanics of shallow faulting associated with the 1999 Hector Mine, California, earthquake

    Science.gov (United States)

    Michael, Andrew J.; Ross, Stephanie L.; Stenner, Heidi D.

    2002-01-01

    The paucity of strong-motion stations near the 1999 Hector Mine earthquake makes it impossible to make instrumental studies of key questions about near-fault strong-motion patterns associated with this event. However, observations of displaced rocks allow a qualitative investigation of these problems. By observing the slope of the desert surface and the frictional coefficient between these rocks and the desert surface, we estimate the minimum horizontal acceleration needed to displace the rocks. Combining this information with observations of how many rocks were displaced in different areas near the fault, we infer the level of shaking. Given current empirical shaking attenuation relationships, the number of rocks that moved is slightly lower than expected; this implies that slightly lower than expected shaking occurred during the Hector Mine earthquake. Perhaps more importantly, stretches of the fault with 4 m of total displacement at the surface displaced few nearby rocks on 15?? slopes, suggesting that the horizontal accelerations were below 0.2g within meters of the fault scarp. This low level of shaking suggests that the shallow parts of this rupture did not produce strong accelerations. Finally, we did not observe an increased incidence of displaced rocks along the fault zone itself. This suggests that, despite observations of fault-zone-trapped waves generated by aftershocks of the Hector Mine earthquake, such waves were not an important factor in controlling peak ground acceleration during the mainshock.

  13. Spatial distribution of environmental risk associated to a uranium abandoned mine (Central Portugal)

    Science.gov (United States)

    Antunes, I. M.; Ribeiro, A. F.

    2012-04-01

    The abandoned uranium mine of Canto do Lagar is located at Arcozelo da Serra, central Portugal. The mine was exploited in an open pit and produced about 12430Kg of uranium oxide (U3O8), between 1987 and 1988. The dominant geological unit is the porphyritic coarse-grained two-mica granite, with biotite>muscovite. The uranium deposit consists of two gaps crushing, parallel to the coarse-grained porphyritic granite, with average direction N30°E, silicified, sericitized and reddish jasperized, with a width of approximately 10 meters. These gaps are accompanied by two thin veins of white quartz, 70°-80° WNW, ferruginous and jasperized with chalcedony, red jasper and opal. These veins are about 6 meters away from each other. They contain secondary U-phosphates phases such as autunite and torbernite. Rejected materials (1000000ton) were deposited on two dumps and a lake was formed in the open pit. To assess the environmental risk of the abandoned uranium mine of Canto do Lagar, were collected and analysed 70 samples on stream sediments, soils and mine tailings materials. The relation between samples composition were tested using the Principal Components Analysis (PCA) (multivariate analysis) and spatial distribution using Kriging Indicator. The spatial distribution of stream sediments shows that the probability of expression for principal component 1 (explaining Y, Zr, Nb, La, Ce, Pr, Nd, Sm, Eu, Gd, Tb, Dy, Ho, Er, Tm, Yb, Hf, Th and U contents), decreases along SE-NW direction. This component is explained by the samples located inside mine influence. The probability of expression for principal component 2 (explaining Be, Na, Al, Si, P, K, Ca, Ti, Mn, Fe, Co, Ni, Cu, As, Rb, Sr, Mo, Cs, Ba, Tl and Bi contents), increases to middle stream line. This component is explained by the samples located outside mine influence. The spatial distribution of soils, shows that the probability of expression for principal component 1 (explaining Mg, P, Ca, Ge, Sr, Y, Zr, La, Ce, Pr

  14. How hard do mineworkers work? An assessment of workplace stress associated with routine mining activities

    CSIR Research Space (South Africa)

    Schutte, PC

    2012-03-01

    Full Text Available . 2 METHODOLOGY 2.1 Physiological strain The Physiological Strain Index (PSI) is a useful tool to determine the impact of environmental tem- peratures and physical work on individuals. The PSI is based on core body temperature and heart rate... of heat built up during muscle contraction, while heart rate re- flects demands placed on the circulatory system in How hard do mineworkers work? An assessment of workplace stress as- sociated with routine mining activities P.C. Schutte CSIR...

  15. Evaluation of the level of norms and associated logical hazards and risks from mining activities of Kenticha Tantalum mines in Ethiopia

    International Nuclear Information System (INIS)

    Dawd, Jemal Edris

    2016-07-01

    In this study radiological hazards to members of the public and workers from exposure to natural radioactivity as a result of mining activities from Kenticha Tantalum Mines in Ethiopia, have been studied through several exposure pathways using direct gamma spectrometry to determine "2"3"8U, "2"3"2Th, "4"0K, "2"2"6Ra and "2"2"2Rn in tantalum ore, soil, waste, waste tailing and water samples. Additionally, cancer risk assessment associated with NORM was estimated. The average activity concentrations of "2"3"8U, "2"3"2Th, "4"0K, "2"2"6Ra and "2"2"2Rn in tantalum ore were 78.653±1.431 Bq/kg, 24.945±0.492 Bq/kg, 603.170±55.013 Bq/kg, 69.478±31.0 Bq/kg and 112.554±50.249 kBq/m"3, respectively. In soil the activity concentrations were 69.354±1.081 Bq/kg, 15.479±0.231 Bq/kg, 718.880±65.531 Bq/kg, 68.923±1.7 Bq/kg and 111.655±2.681 kBq/m"3, respectively and in solid waste samples 110.496±1.907 Bq/kg, 15.009±0.274 Bq/kg, 607.269±55.375 Bq/kg, 98.300±38.6 Bq/kg and 159.246±62.607 kBq/m"3 respectively. The values were generally above the worldwide average activity concentrations in all samples, except thorium-232. This might be due to the high contents of "2"3"8U decay families and "4"0K in the granite – pegmatite rocks of Kenticha area. The corresponding average external dose rate at 1m above the ground in air for tantalum ore, soil and solid waste samples were 76.407 nGy/h, 71.337 nGy/h, 85.408 nGy/h respectively which were above worldwide average value of 60 nGy/h. The annual equivalent doses were also estimated as 0.021±0.003 mSv, 0.020±0.001 mSv and 0.023±0.004 mSv for ore, soil and solid waste samples, respectively and were found to be lower than the worldwide average of 2.42 mSv/y. Likewise, the radon emanation coefficient which is the fraction of radon generated within the grains of materials and escaped to the pore space, varied from 82±2% to 85±2% for ores, from 82±2% to 84±2% for soil, and from 53±15% to 83±15% for solid waste samples. Also

  16. Scattering rules in soliton cellular automata associated with Uq(D(1)n)-crystal Bn,1

    International Nuclear Information System (INIS)

    Mohamad, Mahathir bin

    2012-01-01

    By means of the crystal theory, we study a class of automata associated with U q (D (1) n )-crystal B n,1 . They have a commuting family of time evolutions, and solitons of length l are labeled by U q (A (1) n−1 )-crystal B 2,l A . The scattering rule of two solitons of lengths l 1 and l 2 (l 1 > l 2 ) including the phase shift is identified with the combinatorial R-matrix for the U q (A (1) n −1 )-crystal B 2,l 2 A ⊗B 2,l 1 A . (paper)

  17. Variation in diel activity of ground beetles (Coleoptera: Carabidae) associated with a soybean field and coal mine remnant

    Science.gov (United States)

    Willand, J.E.; McCravy, K.W.

    2006-01-01

    Diel activities of carabids (Coleoptera: Carabidae) associated with a coal mine remnant and surrounding soybean field were studied in west-central Illinois from June through October 2002. A total of 1,402 carabids, representing 29 species and 17 genera, were collected using pitfall traps. Poecilus chalcites (Say) demonstrated roughly equal diurnal and nocturnal activity in June, but greater diurnal activity thereafter. Pterostichus permundus (Say), Cyclotrachelus seximpressus (LeConte), Amara obesa (Say), and Scarites quadriceps Chaudoir showed significant nocturnal activity. Associations between habitat and diel activity were found for three species: P. chalcites associated with the remnant and edge habitats showed greater diurnal activity than those associated with the soybean field; C. seximpressus was most active diurnally in the remnant, and Harpalus pensylvanicus (DeGeer) showed the greatest nocturnal activity in the remnant and edge habitats. We found significant temporal and habitat-related variation in diel activity among carabid species inhabiting agricultural areas in west-central Illinois.

  18. Associate editors' foreword: entrepreneurship in health education and health promotion: five cardinal rules.

    Science.gov (United States)

    Cottrell, Randall R; Cooper, Hanna

    2009-07-01

    A career in health education or health promotion (HE/HP) can be developed in many ways. In past editions of this department, career development has been discussed in relation to distance (Balonna, 2001), consulting (Bookbinder, 2001), certifications (Hayden, 2005), graduate school (Cottrell & Hayden, 2007), and many other topics. This article looks at a less traditional means of career development-entrepreneurship. Health education is a field ripe with opportunities for consulting and for selling health-related products and services. Entrepreneurship can not only create financial rewards but can also provide high visibility and networking contacts that can advance one's career. This article combines both theory and practical applications to assist readers in developing entrepreneurial activities. The authors are experienced in entrepreneurial development and use that expertise to provide relevant examples and develop a framework using "five cardinal rules" for establishing an entrepreneurial enterprise in HE/HP.

  19. Mining the Human Complexome Database Identifies RBM14 as an XPO1-Associated Protein Involved in HIV-1 Rev Function

    OpenAIRE

    Budhiraja, Sona; Liu, Hongbing; Couturier, Jacob; Malovannaya, Anna; Qin, Jun; Lewis, Dorothy E.; Rice, Andrew P.

    2015-01-01

    By recruiting the host protein XPO1 (CRM1), the HIV-1 Rev protein mediates the nuclear export of incompletely spliced viral transcripts. We mined data from the recently described human nuclear complexome to identify a host protein, RBM14, which associates with XPO1 and Rev and is involved in Rev function. Using a Rev-dependent p24 reporter plasmid, we found that RBM14 depletion decreased Rev activity and Rev-mediated enhancement of the cytoplasmic levels of unspliced viral transcripts. RBM14 ...

  20. Mercury Contamination and Biogeochemical Cycling Associated with the Historic Idrija Mining Area of Slovenia

    Science.gov (United States)

    Hines, M. E.; Bonzongo, J. J.; Barkay, T.; Horvat, M.; Faganeli, J.

    2001-12-01

    The Idrija Mine is the second largest Hg mine in the world, which operated for 500 years before recently closing. More than five million tons of ore were mined with only 73% recovered. Hg-laden tailings still line the banks. Exhausts from stacks and mineshafts caused elevated levels of airborne Hg, most of which was deposited in the Idrija basin leading to elevated Hg levels in surficial soils. Hg is continually being transported downstream with approximately 1,500 kg per year entering the northern Adriatic Sea 100 km away. Multidisciplinary studies were conducted on samples collected throughout the Idrija and Soca River systems and waters and sediments in the Gulf of Trieste including Hg speciation, Hg transformation activities in sediments and soils, and the presence and expression of bacterial Hg resistance (mer) genes. Total Hg in the Idrija River increased from 300 ng/L with MeHg accounting for about 0.5%. Concentrations decreased downstream, but increased again in the Soca River and in the estuary with MeHg accounting for nearly 1.5% of the total. However, while bacteria upstream of the mine did not contain mer genes, such genes were detected in bacteria collected downstream for nearly 40 km, and these genes were transcribed. Total Hg levels decreased offshore, but values over 30 ng/L were noted in bottom waters. MeHg concentrations in the Gulf were highest in bottom waters. Sediments near the river mouth contained 40 micro-g/g total Hg with MeHg concentrations of about 3 ng/g. Sediments several km into the Gulf contained 50-fold less total Hg but only 10-fold less MeHg that decreased with depth in the sediment. Hg in sediment pore waters varied between 1 and 8 ng/L, with MeHg accounting for about 30%. Hg methylation and MeHg demethylation were active in Gulf sediments with highest activities near the surface. MeHg was degraded by an oxidative pathway with >97% of the C released from MeHg as carbon dioxide. Hg methylation depth profiles resembled profiles of

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

    Directory of Open Access Journals (Sweden)

    Lam Nina SN

    2006-02-01

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

  2. Genetic Diversity and Elite Allele Mining for Grain Traits in Rice (Oryza sativa L.) by Association Mapping.

    Science.gov (United States)

    Edzesi, Wisdom M; Dang, Xiaojing; Liang, Lijun; Liu, Erbao; Zaid, Imdad U; Hong, Delin

    2016-01-01

    Mining elite alleles for grain size and weight is of importance for the improvement of cultivated rice and selection for market demand. In this study, association mapping for grain traits was performed on a selected sample of 628 rice cultivars using 262 SSRs. Grain traits were evaluated by grain length (GL), grain width (GW), grain thickness (GT), grain length to width ratio (GL/GW), and 1000-grain weight (TGW) in 2013 and 2014. Our result showed abundant phenotypic and genetic diversities found in the studied population. In total, 2953 alleles were detected with an average of 11.3 alleles per locus. The population was divided into seven subpopulations and the levels of linkage disequilibrium (LD) ranged from 34 to 84 cM. Genome-wide association mapping detected 10 marker trait association (MTAs) loci for GL, 1MTAs locus for GW, 7 MTAs loci for GT, 3 MTAs loci for GL/GW, and 1 MTAs locus for TGW. Twenty-nine, 2, 10, 5, and 3 elite alleles were found for the GL, GW, GT, GL/GW, and TGW, respectively. Optimal cross designs were predicted for improving the target traits. The accessions containing elite alleles for grain traits mined in this study could be used for breeding rice cultivars and cloning the candidate genes.

  3. Is outdoor work associated with elevated rates of cerebrovascular disease mortality? A cohort study based on iron-ore mining.

    Science.gov (United States)

    Björ, Ove; Jonsson, Håkan; Damber, Lena; Burström, Lage; Nilsson, Tohr

    2016-01-01

    A cohort study that examined iron ore mining found negative associations between cumulative working time employed underground and several outcomes, including mortality of cerebrovascular diseases. In this cohort study, and using the same group of miners, we examined whether work in an outdoor environment could explain elevated cerebrovascular disease rates. This study was based on a Swedish iron ore mining cohort consisting of 13,000 workers. Poisson regression models were used to generate smoothed estimates of standardized mortality ratios and adjusted rate ratios, both models by cumulative exposure time in outdoor work. The adjusted rate ratio between employment classified as outdoor work ≥25 years and outdoor work 0-4 years was 1.62 (95 % CI 1.07-2.42). The subgroup underground work ≥15 years deviated most in occurrence of cerebrovascular disease mortality compared with the external reference population: SMR (0.70 (95 % CI 0.56-0.85)). Employment in outdoor environments was associated with elevated rates of cerebrovascular disease mortality. In contrast, work in tempered underground employment was associated with a protecting effect.

  4. Quantifying Associations between Environmental Stressors and Demographic Factors

    Science.gov (United States)

    Association rule mining (ARM) [1-3], also known as frequent item set mining [4] or market basket analysis [1], has been widely applied in many different areas, such as business product portfolio planning [5], intrusion detection infrastructure design [6], gene expression analysis...

  5. PM2 : a Process Mining Project Methodology

    NARCIS (Netherlands)

    Eck, van M.L.; Lu, X.; Leemans, S.J.J.; Aalst, van der W.M.P.; Zdravkovic, J.; Kirikova, M.; Johannesson, P.

    2015-01-01

    Process mining aims to transform event data recorded in information systems into knowledge of an organisation’s business processes. The results of process mining analysis can be used to improve process performance or compliance to rules and regulations. However, applying process mining in practice

  6. VICKEY: Mining Conditional Keys on Knowledge Bases

    DEFF Research Database (Denmark)

    Symeonidou, Danai; Prado, Luis Antonio Galarraga Del; Pernelle, Nathalie

    2017-01-01

    A conditional key is a key constraint that is valid in only a part of the data. In this paper, we show how such keys can be mined automatically on large knowledge bases (KBs). For this, we combine techniques from key mining with techniques from rule mining. We show that our method can scale to KBs...

  7. An Association Rule Based Method to Integrate Metro-Public Bicycle Smart Card Data for Trip Chain Analysis

    Directory of Open Access Journals (Sweden)

    De Zhao

    2018-01-01

    Full Text Available Smart card data provide valuable insights and massive samples for enhancing the understanding of transfer behavior between metro and public bicycle. However, smart cards for metro and public bicycle are often issued and managed by independent companies and this results in the same commuter having different identity tags in the metro and public bicycle smart card systems. The primary objective of this study is to develop a data fusion methodology for matching metro and public bicycle smart cards for the same commuter using historical smart card data. A novel method with association rules to match the data derived from the two systems is proposed and validation was performed. The results showed that our proposed method successfully matched 573 pairs of smart cards with an accuracy of 100%. We also validated the association rules method through visualization of individual metro and public bicycle trips. Based on the matched cards, interesting findings of metro-bicycle transfer have been derived, including the spatial pattern of the public bicycle as first/last mile solution as well as the duration of a metro trip chain.

  8. In Situ Generated Colloid Transport of Cu and Zn in Reclaimed Mine Soil Profiles Associated with Bio solids Application

    International Nuclear Information System (INIS)

    Miller, J.O.; Karathanasis, A.D.; Matocha, C.J.

    2011-01-01

    Areas reclaimed for agricultural uses following coal mining often receive bio solids applications to increase organic matter and fertility. Transport of heavy metals within these soils may be enhanced by the additional presence of bio solids colloids. Intact monoliths from reclaimed and undisturbed soils in Virginia and Kentucky were leached to observe Cu and Zn mobility with and without bio solids application. Transport of Cu and Zn was observed in both solution and colloid associated phases in reclaimed and undisturbed forest soils, where the presence of unweathered spoil material and bio solids amendments contributed to higher metal release in solution fractions. Up to 81% of mobile Cu was associated with the colloid fraction, particularly when gabbiest was present, while only up to 18% of mobile Zn was associated with the colloid fraction. The colloid bound Cu was exchangeable by ammonium acetate, suggesting that it will release into groundwater resources.

  9. In Situ Generated Colloid Transport of Cu and Zn in Reclaimed Mine Soil Profiles Associated with Bio solids Application

    International Nuclear Information System (INIS)

    Miller, J.O.; Karathanasis, A.D.; Matocha, C.J.

    2011-01-01

    Areas reclaimed for agricultural uses following coal mining often receive bio solids applications to increase organic matter and fertility. Transport of heavy metals within these soils may be enhanced by the additional presence of bio solids colloids. Intact monoliths from reclaimed and undisturbed soils in Virginia and Kentucky were leached to observe Cu and Zn mobility with and without bio solids application. Transport of Cu and Zn was observed in both solution and colloid associated phases in reclaimed and undisturbed forest soils, where the presence of unweathered spoil material and bio solids amendments contributed to higher metal release in solution fractions. Up to 81% of mobile Cu was associated with the colloid fraction, particularly when gibbsite was present, while only up to 18% of mobile Zn was associated with the colloid fraction. The colloid bound Cu was exchangeable by ammonium acetate, suggesting that it will release into groundwater resources.

  10. Preliminary results on variations of radon concentration associated with rock deformation in a uranium mine

    Science.gov (United States)

    Verdoya, Massimo; Bochiolo, Massimo; Chiozzi, Paolo; Pasquale, Vincenzo; Armadillo, Egidio; Rizzello, Daniele; Chiaberto, Enrico

    2013-04-01

    Time-series of radon concentration and environmental parameters were recently recorded in a uranium mine gallery, located in the Maritime Alps (NW Italy). The mine was bored in metarhyolites and porphyric schists mainly composed by quartz, feldspar, sericite and fluorite. U-bearing minerals are generally concentrated in veins heterogeneously spaced and made of crystals of metaautunite and metatorbernite. Radon air concentration monitoring was performed with an ionization chamber which was placed at the bottom of the gallery. Hourly mean values of temperature, pressure, and relative humidity were also measured. External data of atmospheric temperature, pressure and rainfall were also available from a meteorological station located nearby, at a similar altitude of the mine. The analysis of the time series recorded showed variation of radon concentration, of large amplitude, exhibiting daily and half-daily periods, which do not seem correlated with meteorological records. Searching for the origin of radon concentration changes and monitoring their amplitude as a function of time can provide important clues on the complex emanation process. During this process, radon reaches the air- and water-filled interstices by recoil and diffusion, where its migration is directed towards lower concentration regions, following the local gradient. The radon emanation from the rock matrix could also be controlled by stress changes acting on the rate of migration of radon into fissures, and fractures. This may yield emanation boosts due to rock extension and the consequent crack broadening, and emanation decrease when joints between cracks close. Thus, besides interaction and mass transfer with the external atmospheric environment, one possible explanation for the periodic changes in radon concentrations in the investigated mine, could be the variation of rock deformation related to lunar-solar tides. The large variation of concentration could be also due to the fact that the mine is

  11. Data mining in radiology

    International Nuclear Information System (INIS)

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

    2014-01-01

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

  12. Assessing radiological impacts (exposures and doses) associated with the mining and milling of radioactive ores

    International Nuclear Information System (INIS)

    Williams, G.A.

    1990-01-01

    The basic units and concepts applicable to radiological assessment are presented. Data relevant to the assessment of radiological exposures from the mining and milling phases of uranium and thorium ores are discussed. As a guide to the assessment of environmental exposures to members of the public, concepts such as the critical group are defined. Environmental transport and exposure pathways are presented in general terms, together with a discussion of the use of mathematical models. The dose assessment procedures defined in the 1987 Code of Practice are described. 13 refs., 2 tabs., 1 fig

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

    Science.gov (United States)

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

    2017-11-01

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

  14. Arsenic toxicosis in cattle associated with soil and water contamination from mining operations

    Energy Technology Data Exchange (ETDEWEB)

    Bergeland, M.E.; Ruth, G.R.; Stack, R.L.; Emerick, R.J.

    1976-01-01

    Arsenic toxicosis occurred in cattle from 2 herds located along rivers in western South Dakota that have been contaminated by effluence of mine tailings during many years of gold mining in the area. Clinical signs in cattle of various ages from herd A included aberrant behavior, progressive weakness, abscess formation, emaciation, and agonal convulsions. Cows from herd B exhibited posterior ataxia and recurrent epileptiform convulsions. Hepatic lipidosis was found in 2 cows, and cerebral edema plus necrosis of cerebrocortical neurons was seen in the brain of 1 cow. Soil from the cattle yard of premise A, which is on the floodplain of a contaminated creek, contained 2200 ppM arsenic. Corn silage that has been contaminated with soil during silo-filling contained 140 ppM arsenic. The arsenic content of hair from herd A cattle ranged from 2.4 to 22.0 ppM and the arsenic content of the liver and kidney of 1 cow from herd B was 3.0 and 7.0 ppM, respectively.

  15. Examining health and well-being outcomes associated with mining activity in rural communities of high-income countries: A systematic review.

    Science.gov (United States)

    Mactaggart, Fiona; McDermott, Liane; Tynan, Anna; Gericke, Christian

    2016-08-01

    It is recognised internationally that rural communities often experience greater barriers to accessing services and have poorer health outcomes compared to urban communities. In some settings, health disparities may be further exacerbated by mining activity, which can affect the social, physical and economic environment in which rural communities reside. Direct environmental health impacts are often associated with mining activity and are frequently investigated. However, there is evidence of broader, indirect health and well-being implications emerging in the literature. This systematic review examines these health and well-being outcomes in communities living in proximity to mining in high-income countries, and, in doing so, discusses their possible determinants. Four databases were systematically searched. Articles were selected if adult residents in mining communities were studied and outcomes were related to health or individual or community-level well-being. A narrative synthesis was conducted. Sixteen publications were included. Evidence of increased prevalence of chronic diseases and poor self-reported health status was reported in the mining communities. Relationship breakdown and poor family health, lack of social connectedness and decreased access to health services were also reported. Changes to the physical landscape; risky health behaviours; shift work of partners in the mine industry; social isolation and cyclical nature of 'boom and bust' activity contributed to poorer outcomes in the communities. This review highlights the broader health and well-being outcomes associated with mining activity that should be monitored and addressed in addition to environmental health impacts to support co-existence of mining activities and rural communities. © 2016 National Rural Health Alliance Inc.

  16. Longitudinal associations in adolescence between cortisol and persistent aggressive or rule-breaking behavior

    NARCIS (Netherlands)

    Platje, E.; Jansen, L.M.C.; Raine, A.; Branje, S.T.J.; Doreleijers, Th.A.H.; de Vries-Bouw, M.; Popma, A.; van Lier, P.A.C.; Koot, H.M.; Meeus, W.H.J.; Vermeiren, R.

    2013-01-01

    Although several studies have associated antisocial behavior with decreased cortisol awakening responses (CAR), studies in adolescent samples yielded inconsistent results. In adolescence however, the CAR develops and antisocial behavior is heterogeneous in type and persistence. Therefore this

  17. 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.

  18. GWA study data mining and independent replication identify cardiomyopathy-associated 5 (CMYA5) as a risk gene for schizophrenia

    DEFF Research Database (Denmark)

    Chen, X; Lee, G; Maher, B S

    2011-01-01

    We conducted data-mining analyses using the Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) and molecular genetics of schizophrenia genome-wide association study supported by the genetic association information network (MGS-GAIN) schizophrenia data sets and performed...... bioinformatic prioritization for all the markers with P-values ¿0.05 in both data sets. In this process, we found that in the CMYA5 gene, there were two non-synonymous markers, rs3828611 and rs10043986, showing nominal significance in both the CATIE and MGS-GAIN samples. In a combined analysis of both the CATIE...... in our Irish samples and was dropped out without further investigation. The other two markers were verified in 23 other independent data sets. In a meta-analysis of all 23 replication samples (family samples, 912 families with 4160 subjects; case-control samples, 11¿380 cases and 15¿021 controls), we...

  19. 78 FR 48591 - Refuge Alternatives for Underground Coal Mines

    Science.gov (United States)

    2013-08-08

    ... Administration 30 CFR Parts 7 and 75 Refuge Alternatives for Underground Coal Mines; Proposed Rules #0;#0;Federal... Underground Coal Mines AGENCY: Mine Safety and Health Administration, Labor. ACTION: Limited reopening of the... for miners to deploy and use refuge alternatives in underground coal mines. The U.S. Court of Appeals...

  20. Lack of parental rule-setting on eating is associated with a wide range of adolescent unhealthy eating behaviour both for boys and girls

    OpenAIRE

    Holubcikova, Jana; Kolarcik, Peter; Madarasova Geckova, Andrea; van Dijk, Jitse P.; Reijneveld, Sijmen A.

    2016-01-01

    Abstract Background Unhealthy eating habits in adolescence lead to a wide variety of health problems and disorders. The aim of this study was to assess the prevalence of absence of parental rules on eating and unhealthy eating behaviour and to explore the relationships between parental rules on eating and a wide range of unhealthy eating habits of boys and girls. We also explored the association of sociodemographic characteristics such as gender, family affluence or parental education with ea...

  1. The 59. conference of Canada's energy and mines ministers : A submission by the Coal Association of Canada

    International Nuclear Information System (INIS)

    2002-01-01

    The most abundant fossil fuel in Canada is coal, and almost 20 per cent of all electricity generated in Canada uses coal as its energy source. About 75 per cent of all electricity generated in Alberta and 67 per cent of that generated in Saskatchewan is derived from domestic coal resources. Coal plays an important role in regional economies. This paper was prepared with the intent of providing a status report on the coal industry to the Energy and Mines Ministers while also identifying the challenges facing the industry. Productivity has been increased and emissions have been reduced, but the industry is facing risks. Cooperation between industry players and governments is required to ensure the long-term viability of the coal industry in Canada. Some recommendations were made by the Coal Association of Canada (CAC) as follows: (1) that the 21 per cent tax-rate to the mining sector be extended by the federal government, while continuing deductibility of the existing resource allowance, (2) that the Corporate Capital Tax be eliminated entirely by the federal government, or that at least for all assets located in rural areas, and (3) the CAC believes better solutions than the Kyoto Protocol exist (CAC does not support Kyoto). The CAC is of the opinion that continental approach should be favored for the reduction of greenhouse gas emissions. The CAC also believes that financial and technical resources should be allocated for the improvement of existing infrastructure and the development of new technologies in terms of reductions of emissions. refs

  2. Effects of acid mine drainage on water, sediment and associated benthic macroinvertebrate communities

    International Nuclear Information System (INIS)

    Rutherford, L.G.; Cherry, D.S.; Dobbs, M.G.; Cairns, J. Jr.; Zipper, C.E.

    1995-01-01

    The toxic constituents of abandoned mined land (AML) discharges (acidic pH, heavy metals, total suspended solids) are extremely toxic to aquatic life . Studies were undertaken to ascertain environmental impacts to the upper Powell River, Lee and Wise Counties, Va. These impacts included disruptions in physical water quality, sediment quality, altered benthic macroinvertebrate assemblages, and toxicity of the water column and sediments from short-term impairment bioassays, and the potential to bioaccumulate selected metals (Al, Fe, Mn, P, Zn, Cu, Mg, S, Ni, Cd) by periphyton and resident bivalves. Water chemistry and macroinvertebrate assemblages were collected at upstream control, just below acid mine drainage and other downstream sites. Selected trace metal concentrations (Al, Fe, Mn, P, Zn, Cu, Mg, S, Ni, Cd) were determined for water, sediment and resident bivalves using ICP-AES. Acidic pH ranged from 2.15--3.3 at three AML-influenced seeps and varied from 6.4--8.0 at reference stations. At one AML-influenced creek, acidic pH conditions worsened from summer to fall and eradicated aquatic life throughout a 1.5 km stretch of that creek as it flowed into another creek. An additional dilution of 3.4 km in the second creek was needed to nearly neutralize the acidic pH problem. Conductivity (umhos/cm) ranged from 32--278 at reference sites and from 245--4,180 at AML-impact sites. Benthic macroinvertebrate abundance and taxon richness were essentially eliminated in the seeps or reached numbers of 1 -3 taxa totaling < 10 organisms relative to reference areas where richness values were 12--17 and comprised 300--977 organisms. Concentrations of Fe, Al, Mg and Cu and Zn were highest in the environmentally stressed stations of low pH and high conductivity relative to the reference stations. Iron was, by far, the element in highest concentration followed by Al and Mg

  3. Mine soils associated with open-cast coal mining in Spain: a review; Suelos mineros asociados a la mineria de carbon a cielo abierto en Espana: una revision

    Energy Technology Data Exchange (ETDEWEB)

    Arranz-Gonzalez, J. C.

    2011-07-01

    The different situations that may be found after the closure of coal mines range from the simple abandonment of pits and spoil tips to areas where reclamation work has led to the creation of artificial soils on a reconstituted surface composed of layers of rock and soil or both types of material. Soils of this type are known as mine soils, amongst which those generated by coal mining have been studied most extensively, both to assess their potential for reclamation and to learn more about their pedogenetic evolution. We present here a review of some of the more important works devoted to this subject. We have found evidence to show that in Spain, just as in other countries, the physical and chemical properties of these anthropogenic soils are changing rapidly and so the mine-soil profiles described can be considered as belonging to very young soils still undergoing incipient but rapid development. We have also found that an analysis of information obtained from the soil parameters of surface samples and its interpretation is of great practical use in restoration processes. Nevertheless, the sampling and description of soil profiles has proved to be of much greater interest, allowing us to reach a clearer understanding of the internal processes and properties that are unique to these types of anthropogenic soil. (Author) 64 refs.

  4. Use of Six Sigma Worksheets for assessment of internal and external failure costs associated with candidate quality control rules for an ADVIA 120 hematology analyzer.

    Science.gov (United States)

    Cian, Francesco; Villiers, Elisabeth; Archer, Joy; Pitorri, Francesca; Freeman, Kathleen

    2014-06-01

    Quality control (QC) validation is an essential tool in total quality management of a veterinary clinical pathology laboratory. Cost-analysis can be a valuable technique to help identify an appropriate QC procedure for the laboratory, although this has never been reported in veterinary medicine. The aim of this study was to determine the applicability of the Six Sigma Quality Cost Worksheets in the evaluation of possible candidate QC rules identified by QC validation. Three months of internal QC records were analyzed. EZ Rules 3 software was used to evaluate candidate QC procedures, and the costs associated with the application of different QC rules were calculated using the Six Sigma Quality Cost Worksheets. The costs associated with the current and the candidate QC rules were compared, and the amount of cost savings was calculated. There was a significant saving when the candidate 1-2.5s, n = 3 rule was applied instead of the currently utilized 1-2s, n = 3 rule. The savings were 75% per year (£ 8232.5) based on re-evaluating all of the patient samples in addition to the controls, and 72% per year (£ 822.4) based on re-analyzing only the control materials. The savings were also shown to change accordingly with the number of samples analyzed and with the number of daily QC procedures performed. These calculations demonstrated the importance of the selection of an appropriate QC procedure, and the usefulness of the Six Sigma Costs Worksheet in determining the most cost-effective rule(s) when several candidate rules are identified by QC validation. © 2014 American Society for Veterinary Clinical Pathology and European Society for Veterinary Clinical Pathology.

  5. Factors Associated With Healthcare-Acquired Catheter-Associated Urinary Tract Infections: Analysis Using Multiple Data Sources and Data Mining Techniques.

    Science.gov (United States)

    Park, Jung In; Bliss, Donna Z; Chi, Chih-Lin; Delaney, Connie W; Westra, Bonnie L

    The purpose of this study was to identify factors associated with healthcare-acquired catheter-associated urinary tract infections (HA-CAUTIs) using multiple data sources and data mining techniques. Three data sets were integrated for analysis: electronic health record data from a university hospital in the Midwestern United States was combined with staffing and environmental data from the hospital's National Database of Nursing Quality Indicators and a list of patients with HA-CAUTIs. Three data mining techniques were used for identification of factors associated with HA-CAUTI: decision trees, logistic regression, and support vector machines. Fewer total nursing hours per patient-day, lower percentage of direct care RNs with specialty nursing certification, higher percentage of direct care RNs with associate's degree in nursing, and higher percentage of direct care RNs with BSN, MSN, or doctoral degree are associated with HA-CAUTI occurrence. The results also support the association of the following factors with HA-CAUTI identified by previous studies: female gender; older age (>50 years); longer length of stay; severe underlying disease; glucose lab results (>200 mg/dL); longer use of the catheter; and RN staffing. Additional findings from this study demonstrated that the presence of more nurses with specialty nursing certifications can reduce HA-CAUTI occurrence. While there may be valid reasons for leaving in a urinary catheter, findings show that having a catheter in for more than 48 hours contributes to HA-CAUTI occurrence. Finally, the findings suggest that more nursing hours per patient-day are related to better patient outcomes.

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

    Science.gov (United States)

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

    2016-01-01

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

  7. 75 FR 20918 - High-Voltage Continuous Mining Machine Standard for Underground Coal Mines

    Science.gov (United States)

    2010-04-22

    ... DEPARTMENT OF LABOR Mine Safety and Health Administration 30 CFR Parts 18 and 75 RIN 1219-AB34 High-Voltage Continuous Mining Machine Standard for Underground Coal Mines Correction In rule document 2010-7309 beginning on page 17529 in the issue of Tuesday, April 6, 2010, make the following correction...

  8. Metals in agricultural produce associated with acid-mine drainage in Mount Morgan (Queensland, Australia).

    Science.gov (United States)

    Vicente-Beckett, Victoria A; McCauley, Gaylene J Taylor; Duivenvoorden, Leo J

    2016-01-01

    Acid-mine drainage (AMD) into the Dee River from the historic gold and copper mine in Mount Morgan, Queensland (Australia) has been of concern to farmers in the area since 1925. This study sought to determine the levels of AMD-related metals and sulfur in agricultural produce grown near the mine-impacted Dee River, compare these with similar produce grown in reference fields (which had no known AMD influence), and assess any potential health risk using relevant Australian or US guidelines. Analyses of lucerne (Medicago sativa; also known as alfalfa) from five Dee fields showed the following average concentrations (mg/kg dry basis): Cd < 1, Cu 11, Fe 106, Mn 52, Pb < 5, Zn 25 and S 3934; similar levels were found in lucerne hay (used as cattle feed) from two Dee fields. All lucerne and lucerne hay data were generally comparable with levels found in the lucerne reference fields, suggesting no AMD influence; the levels were within the US National Research Council (US NRC) guidelines for maximum tolerable cattle dietary intake. Pasture grass (also cattle feed) from two fields in the Dee River floodplains gave mean concentrations (mg/kg dry) of Cd 0.14, Cu 12, Fe 313, Mn 111, Pb 1.4, Zn 86 and S 2450. All metal levels from the Dee and from reference sites were below the US NRC guidelines for maximum tolerable cattle dietary intake; however, the average Cd, Cu and Fe levels in Dee samples were significantly greater than the corresponding levels in the pasture grass reference sites, suggesting AMD influence in the Dee samples. The average levels in the edible portions of mandarin oranges (Citrus reticulata) from Dee sites (mg/kg wet weight) were Cd 0.011, Cu 0.59, Fe 2.2, Mn 0.56, Pb 0.18, S 91 and Zn 0.96. Cd and Zn were less than or close to, average Fe and Mn levels were at most twice, Cd 1.8 or 6.5 times, and Pb 8.5 or 72 times the maximum levels in raw oranges reported in the US total diet study (TDS) or the Australian TDS, respectively. Average Cd, Fe, Mn, Pb and

  9. miRiaD: A Text Mining Tool for Detecting Associations of microRNAs with Diseases.

    Science.gov (United States)

    Gupta, Samir; Ross, Karen E; Tudor, Catalina O; Wu, Cathy H; Schmidt, Carl J; Vijay-Shanker, K

    2016-04-29

    MicroRNAs are increasingly being appreciated as critical players in human diseases, and questions concerning the role of microRNAs arise in many areas of biomedical research. There are several manually curated databases of microRNA-disease associations gathered from the biomedical literature; however, it is difficult for curators of these databases to keep up with the explosion of publications in the microRNA-disease field. Moreover, automated literature mining tools that assist manual curation of microRNA-disease associations currently capture only one microRNA property (expression) in the context of one disease (cancer). Thus, there is a clear need to develop more sophisticated automated literature mining tools that capture a variety of microRNA properties and relations in the context of multiple diseases to provide researchers with fast access to the most recent published information and to streamline and accelerate manual curation. We have developed miRiaD (microRNAs in association with Disease), a text-mining tool that automatically extracts associations between microRNAs and diseases from the literature. These associations are often not directly linked, and the intermediate relations are often highly informative for the biomedical researcher. Thus, miRiaD extracts the miR-disease pairs together with an explanation for their association. We also developed a procedure that assigns scores to sentences, marking their informativeness, based on the microRNA-disease relation observed within the sentence. miRiaD was applied to the entire Medline corpus, identifying 8301 PMIDs with miR-disease associations. These abstracts and the miR-disease associations are available for browsing at http://biotm.cis.udel.edu/miRiaD . We evaluated the recall and precision of miRiaD with respect to information of high interest to public microRNA-disease database curators (expression and target gene associations), obtaining a recall of 88.46-90.78. When we expanded the evaluation to

  10. Decolonisation of fractional calculus rules: Breaking commutativity and associativity to capture more natural phenomena

    Science.gov (United States)

    Atangana, Abdon; Gómez-Aguilar, J. F.

    2018-04-01

    To answer some issues raised about the concept of fractional differentiation and integration based on the exponential and Mittag-Leffler laws, we present, in this paper, fundamental differences between the power law, exponential decay, Mittag-Leffler law and their possible applications in nature. We demonstrate the failure of the semi-group principle in modeling real-world problems. We use natural phenomena to illustrate the importance of non-commutative and non-associative operators under which the Caputo-Fabrizio and Atangana-Baleanu fractional operators fall. We present statistical properties of generator for each fractional derivative, including Riemann-Liouville, Caputo-Fabrizio and Atangana-Baleanu ones. The Atangana-Baleanu and Caputo-Fabrizio fractional derivatives show crossover properties for the mean-square displacement, while the Riemann-Liouville is scale invariant. Their probability distributions are also a Gaussian to non-Gaussian crossover, with the difference that the Caputo Fabrizio kernel has a steady state between the transition. Only the Atangana-Baleanu kernel is a crossover for the waiting time distribution from stretched exponential to power law. A new criterion was suggested, namely the Atangana-Gómez fractional bracket, that helps describe the energy needed by a fractional derivative to characterize a 2-pletic manifold. Based on these properties, we classified fractional derivatives in three categories: weak, mild and strong fractional differential and integral operators. We presented some applications of fractional differential operators to describe real-world problems and we proved, with numerical simulations, that the Riemann-Liouville power-law derivative provides a description of real-world problems with much additional information, that can be seen as noise or error due to specific memory properties of its power-law kernel. The Caputo-Fabrizio derivative is less noisy while the Atangana-Baleanu fractional derivative provides an

  11. Assessment of radiation hazards associated with tailing and sediment from an abandoned gold mine in Ilesa and an active tantalite mine in Ijero, southwest Nigeria

    Energy Technology Data Exchange (ETDEWEB)

    Isinkaye, O. [Ekiti State University (Nigeria)

    2014-07-01

    The implication of indiscriminate or unregulated mining activities has been pointed out as a major risk to human health and the environment. In order to assess the potential radiological hazards pose to the environment due to mining activities in southwest Nigeria, the activity concentrations of {sup 40}K, {sup 226}Ra and {sup 232}Th was determined in tailing and sediment from two mines within the study area. The samples were analysed by gamma spectrometry with low background NaI(Tl) detector. The activity concentrations of {sup 40}K, {sup 226}Ra and {sup 232}Th in all the measured samples ranged from 249.66-1459.25 BqKg{sup -1}, 7.62-50.31 Bqkg{sup -1} and 12.68-234.18 Bqkg{sup -1}, respectively in soil while in sediment samples, the values ranged from 241.86-1590.40 Bqkg{sup -1}, 9.86-74.8 Bqkg{sup -1} and 15.47-145.46 Bqkg{sup -1} for {sup 40}K, {sup 226}Ra and {sup 232}Th, respectively. In order to evaluate the radiological hazards due to the concentrations of natural radionuclides in the samples, the radium equivalent activity, external hazard index, absorbed gamma dose rates and the annual effective dose rates were determined. All these hazard indexes have mean values which are higher than the world average values but are all within their acceptable limits. Document available in abstract form only. (authors)

  12. Associations of dominant plant species with arbuscular mycorrhizal fungi during vegetation development on coal mine spoil banks

    Energy Technology Data Exchange (ETDEWEB)

    Rydlova, J.; Vosatka, M. [Academy of Science. Pruhonice (Czech Republic). Inst. of Botany

    2001-07-01

    Among plants colonizing mine spoil banks in Northern Bohemia the first colonizers, mainly ruderal annuals from Chenopodiaceae and Brassicaceae were found not to be associated with arbuscular mycorrhizal fungi (AMF). These species cultivated in pots with soil from four sites in different succession stages of the spoil bank did not respond to the presence of native or non-native AMF. All grass species studied (Elytrigia repens, Calamagrostis epigejos and Arrhenatherum elatius) were found moderately colonized in the field. Carduus acanthoides was found to be highly colonized in the field; however, it did not show growth response to AMF in the pot experiment. The AMF native in four sites on the spoil banks showed high infectivity but low effectiveness in association with colonizing plants compared to the non-native isolate G. fistulosum BEG23. In general, dependence on AMF in the cultivation experiment was rather low, regardless of the fact that plants were found to be associated with AMF either in the field or in pots. Occurrence and effectiveness of mycorrhizal associations might relate primarily to the mycotrophic status of each plant species rather than to the age of the spoil bank sites studied.

  13. AN EFFICIENT DATA MINING METHOD TO FIND FREQUENT ITEM SETS IN LARGE DATABASE USING TR- FCTM

    Directory of Open Access Journals (Sweden)

    Saravanan Suba

    2016-01-01

    Full Text Available Mining association rules in large database is one of most popular data mining techniques for business decision makers. Discovering frequent item set is the core process in association rule mining. Numerous algorithms are available in the literature to find frequent patterns. Apriori and FP-tree are the most common methods for finding frequent items. Apriori finds significant frequent items using candidate generation with more number of data base scans. FP-tree uses two database scans to find significant frequent items without using candidate generation. This proposed TR-FCTM (Transaction Reduction- Frequency Count Table Method discovers significant frequent items by generating full candidates once to form frequency count table with one database scan. Experimental results of TR-FCTM shows that this algorithm outperforms than Apriori and FP-tree.

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

    DEFF Research Database (Denmark)

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

    2010-01-01

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

  15. Lack of parental rule-setting on eating is associated with a wide range of adolescent unhealthy eating behaviour both for boys and girls.

    Science.gov (United States)

    Holubcikova, Jana; Kolarcik, Peter; Madarasova Geckova, Andrea; van Dijk, Jitse P; Reijneveld, Sijmen A

    2016-04-27

    Unhealthy eating habits in adolescence lead to a wide variety of health problems and disorders. The aim of this study was to assess the prevalence of absence of parental rules on eating and unhealthy eating behaviour and to explore the relationships between parental rules on eating and a wide range of unhealthy eating habits of boys and girls. We also explored the association of sociodemographic characteristics such as gender, family affluence or parental education with eating related parental rules and eating habits of adolescents. The data on 2765 adolescents aged 13-15 years (mean age: 14.4; 50.7 % boys) from the Slovak part of the Health Behaviour in School-Aged Children (HBSC) study 2014 were assessed. The associations between eating-related parental rules and unhealthy eating patterns using logistic regression were assessed using logistic regression. Unhealthy eating habits occurred frequently among adolescents (range: 18.0 % reported skipping breakfast during weekends vs. 75.8 % for low vegetables intake). Of all adolescents, 20.5 % reported a lack of any parental rules on eating (breakfast not mandatory, meal in front of TV allowed, no rules about sweets and soft drinks). These adolescents were more likely to eat unhealthily, i.e. to skip breakfast on weekdays (odds ratio/95 % confidence interval: 5.33/4.15-6.84) and on weekends (2.66/2.12-3.34), to report low consumption of fruits (1.63/1.30-2.04) and vegetables (1.32/1.04-1.68), and the frequent consumption of sweets (1.59/1.30-1.94), soft drinks (1.93/1.56-2.38) and energy drinks (2.15/1.72-2.70). Parental rule-setting on eating is associated with eating behaviours of adolescents. Further research is needed to disentangle causality in this relationship. If causal, parents may be targeted to modify the eating habits of adolescents.

  16. Decoding Metal Associations in an Arid Urban Environment with Active and Legacy Mining: the Case of Copiapó, Chile

    Science.gov (United States)

    Pasten, P.; Moya, P.; Coquery, M.; Bonilla, C. A.; Vega, A.; Carkovic, A.; Calcagni, M.

    2015-12-01

    The urban and periurban area of Copiapó in the arid Atacama desert has more than 30 abandoned mine tailings, one active copper smelter, and 150,000 inhabitants. Fast development of the mining industry during the 19th century and unplanned growth has led to public concern about the presence of metals in soils and street dust. Recent floods and mud currents in the Copiapó watershed have introduced new solid material in about 40% of the urban area. We conducted a geochemical screening before and after the disaster in March 2015. We found concentrations as high as 1000 mg/kg of copper and 180 mg/kg of arsenic in urban soils. Since effective control measures require connecting sites of metal enrichment with the possible sources, we have performed a statistical analysis of metal association and complemented it with other analyses like x-ray diffraction. Cluster analyses of elemental compositions suggest that mud and tailing have different origins from the rest of the matrices, while soils and street dust have a similar one. Some clusters have a mix of matrices that suggest anthropogenic enrichment of some areas of Copiapó. Our initial results indicate that a correlation between observed enrichment and the copper smelter can be hypothesized for Cu, Pb, and Zn. Further spatial, statistical, and chemical analyses are needed to further confirm such findings, complemented with a thorough analysis of the baseline values that could be considered representative of the area. Future work include Principal Component Analysis (PCA) and Positive matrix factorization (PMF) to test the link contaminant sources and metal occurrence, while scanning electron microscopy can be used to identify the presence of smelter-related particles. The information generated by this research will be a necessary input for defining urban planning strategies and land use guidelines, defining health risk assessment studies, and for future evaluation of intervention priorities. Acknowledgements: Proyecto

  17. Mining Genotype-Phenotype Associations from Public Knowledge Sources via Semantic Web Querying.

    Science.gov (United States)

    Kiefer, Richard C; Freimuth, Robert R; Chute, Christopher G; Pathak, Jyotishman

    2013-01-01

    Gene Wiki Plus (GeneWiki+) and the Online Mendelian Inheritance in Man (OMIM) are publicly available resources for sharing information about disease-gene and gene-SNP associations in humans. While immensely useful to the scientific community, both resources are manually curated, thereby making the data entry and publication process time-consuming, and to some degree, error-prone. To this end, this study investigates Semantic Web technologies to validate existing and potentially discover new genotype-phenotype associations in GWP and OMIM. In particular, we demonstrate the applicability of SPARQL queries for identifying associations not explicitly stated for commonly occurring chronic diseases in GWP and OMIM, and report our preliminary findings for coverage, completeness, and validity of the associations. Our results highlight the benefits of Semantic Web querying technology to validate existing disease-gene associations as well as identify novel associations although further evaluation and analysis is required before such information can be applied and used effectively.

  18. Data Mining FAERS to Analyze Molecular Targets of Drugs Highly Associated with Stevens-Johnson Syndrome

    OpenAIRE

    Burkhart, Keith K.; Abernethy, Darrell; Jackson, David

    2015-01-01

    Drug features that are associated with Stevens-Johnson syndrome (SJS) have not been fully characterized. A molecular target analysis of the drugs associated with SJS in the FDA Adverse Event Reporting System (FAERS) may contribute to mechanistic insights into SJS pathophysiology. The publicly available version of FAERS was analyzed to identify disproportionality among the molecular targets, metabolizing enzymes, and transporters for drugs associated with SJS. The FAERS in-house version was al...

  19. SNPranker 2.0: a gene-centric data mining tool for diseases associated SNP prioritization in GWAS.

    Science.gov (United States)

    Merelli, Ivan; Calabria, Andrea; Cozzi, Paolo; Viti, Federica; Mosca, Ettore; Milanesi, Luciano

    2013-01-01

    The capability of correlating specific genotypes with human diseases is a complex issue in spite of all advantages arisen from high-throughput technologies, such as Genome Wide Association Studies (GWAS). New tools for genetic variants interpretation and for Single Nucleotide Polymorphisms (SNPs) prioritization are actually needed. Given a list of the most relevant SNPs statistically associated to a specific pathology as result of a genotype study, a critical issue is the identification of genes that are effectively related to the disease by re-scoring the importance of the identified genetic variations. Vice versa, given a list of genes, it can be of great importance to predict which SNPs can be involved in the onset of a particular disease, in order to focus the research on their effects. We propose a new bioinformatics approach to support biological data mining in the analysis and interpretation of SNPs associated to pathologies. This system can be employed to design custom genotyping chips for disease-oriented studies and to re-score GWAS results. The proposed method relies (1) on the data integration of public resources using a gene-centric database design, (2) on the evaluation of a set of static biomolecular annotations, defined as features, and (3) on the SNP scoring function, which computes SNP scores using parameters and weights set by users. We employed a machine learning classifier to set default feature weights and an ontological annotation layer to enable the enrichment of the input gene set. We implemented our method as a web tool called SNPranker 2.0 (http://www.itb.cnr.it/snpranker), improving our first published release of this system. A user-friendly interface allows the input of a list of genes, SNPs or a biological process, and to customize the features set with relative weights. As result, SNPranker 2.0 returns a list of SNPs, localized within input and ontologically enriched genes, combined with their prioritization scores. Different

  20. Data Mining Methods for Recommender Systems

    Science.gov (United States)

    Amatriain, Xavier; Jaimes*, Alejandro; Oliver, Nuria; Pujol, Josep M.

    In this chapter, we give an overview of the main Data Mining techniques used in the context of Recommender Systems. We first describe common preprocessing methods such as sampling or dimensionality reduction. Next, we review the most important classification techniques, including Bayesian Networks and Support Vector Machines. We describe the k-means clustering algorithm and discuss several alternatives. We also present association rules and related algorithms for an efficient training process. In addition to introducing these techniques, we survey their uses in Recommender Systems and present cases where they have been successfully applied.

  1. Mechanisms of rule acquisition and rule following in inductive reasoning.

    Science.gov (United States)

    Crescentini, Cristiano; Seyed-Allaei, Shima; De Pisapia, Nicola; Jovicich, Jorge; Amati, Daniele; Shallice, Tim

    2011-05-25

    Despite the recent interest in the neuroanatomy of inductive reasoning processes, the regional specificity within prefrontal cortex (PFC) for the different mechanisms involved in induction tasks remains to be determined. In this study, we used fMRI to investigate the contribution of PFC regions to rule acquisition (rule search and rule discovery) and rule following. Twenty-six healthy young adult participants were presented with a series of images of cards, each consisting of a set of circles numbered in sequence with one colored blue. Participants had to predict the position of the blue circle on the next card. The rules that had to be acquired pertained to the relationship among succeeding stimuli. Responses given by subjects were categorized in a series of phases either tapping rule acquisition (responses given up to and including rule discovery) or rule following (correct responses after rule acquisition). Mid-dorsolateral PFC (mid-DLPFC) was active during rule search and remained active until successful rule acquisition. By contrast, rule following was associated with activation in temporal, motor, and medial/anterior prefrontal cortex. Moreover, frontopolar cortex (FPC) was active throughout the rule acquisition and rule following phases before a rule became familiar. We attributed activation in mid-DLPFC to hypothesis generation and in FPC to integration of multiple separate inferences. The present study provides evidence that brain activation during inductive reasoning involves a complex network of frontal processes and that different subregions respond during rule acquisition and rule following phases.

  2. Groundwater-quality data associated with abandoned underground coal mine aquifers in West Virginia, 1973-2016: Compilation of existing data from multiple sources

    Science.gov (United States)

    McAdoo, Mitchell A.; Kozar, Mark D.

    2017-11-14

    This report describes a compilation of existing water-quality data associated with groundwater resources originating from abandoned underground coal mines in West Virginia. Data were compiled from multiple sources for the purpose of understanding the suitability of groundwater from abandoned underground coal mines for public supply, industrial, agricultural, and other uses. This compilation includes data collected for multiple individual studies conducted from July 13, 1973 through September 7, 2016. Analytical methods varied by the time period of data collection and requirements of the independent studies.This project identified 770 water-quality samples from 294 sites that could be attributed to abandoned underground coal mine aquifers originating from multiple coal seams in West Virginia.

  3. Acid mine drainage: mining and water pollution issues in British Columbia

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1998-12-31

    The importance of protecting water quality and some of the problems associated with mineral development are described. Negative impacts of mining operations such as sedimentation, water disturbances, and water pollution from waste rock and tailings are considered. Mining wastes, types of water pollution from mining, the legacy of acid mine drainage, predicting acid mine drainage, preventing and mitigating acid mine drainage, examples from the past, and cyanide heap-leaching are discussed. The real costs of mining at the Telkwa open pit coal mine are assessed. British Columbia mines that are known for or are potentially acid generating are shown on a map. 32 refs., 10 figs.

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

    International Nuclear Information System (INIS)

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

    2005-01-01

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

  5. Locating previously unknown patterns in data-mining results: a dual data- and knowledge-mining method

    Directory of Open Access Journals (Sweden)

    Knaus William A

    2006-03-01

    Full Text Available Abstract Background Data mining can be utilized to automate analysis of substantial amounts of data produced in many organizations. However, data mining produces large numbers of rules and patterns, many of which are not useful. Existing methods for pruning uninteresting patterns have only begun to automate the knowledge acquisition step (which is required for subjective measures of interestingness, hence leaving a serious bottleneck. In this paper we propose a method for automatically acquiring knowledge to shorten the pattern list by locating the novel and interesting ones. Methods The dual-mining method is based on automatically comparing the strength of patterns mined from a database with the strength of equivalent patterns mined from a relevant knowledgebase. When these two estimates of pattern strength do not match, a high "surprise score" is assigned to the pattern, identifying the pattern as potentially interesting. The surprise score captures the degree of novelty or interestingness of the mined pattern. In addition, we show how to compute p values for each surprise score, thus filtering out noise and attaching statistical significance. Results We have implemented the dual-mining method using scripts written in Perl and R. We applied the method to a large patient database and a biomedical literature citation knowledgebase. The system estimated association scores for 50,000 patterns, composed of disease entities and lab results, by querying the database and the knowledgebase. It then computed the surprise scores by comparing the pairs of association scores. Finally, the system estimated statistical significance of the scores. Conclusion The dual-mining method eliminates more than 90% of patterns with strong associations, thus identifying them as uninteresting. We found that the pruning of patterns using the surprise score matched the biomedical evidence in the 100 cases that were examined by hand. The method automates the acquisition of

  6. 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...

  7. Detecting a Weak Association by Testing its Multiple Perturbations: a Data Mining Approach

    Science.gov (United States)

    Lo, Min-Tzu; Lee, Wen-Chung

    2014-05-01

    Many risk factors/interventions in epidemiologic/biomedical studies are of minuscule effects. To detect such weak associations, one needs a study with a very large sample size (the number of subjects, n). The n of a study can be increased but unfortunately only to an extent. Here, we propose a novel method which hinges on increasing sample size in a different direction-the total number of variables (p). We construct a p-based `multiple perturbation test', and conduct power calculations and computer simulations to show that it can achieve a very high power to detect weak associations when p can be made very large. As a demonstration, we apply the method to analyze a genome-wide association study on age-related macular degeneration and identify two novel genetic variants that are significantly associated with the disease. The p-based method may set a stage for a new paradigm of statistical tests.

  8. High resolution microgravity investigations for the detection and characterisation of subsidence associated with abandoned, coal, chalk and salt mines

    Energy Technology Data Exchange (ETDEWEB)

    Styles, P.; Toon, S.; Branston, M.; England, R. [Keele Univ., Applied And Environmental Geophysics Group, School of Physical and Geographical Sciences (United Kingdom); Thomas, E.; Mcgrath, R. [Geotechnology, Neath (United Kingdom)

    2005-07-01

    The closure and decay of industrial activity involving mining has scarred the landscape of urban areas and geo-hazards posed by subsurface cavities are ubiquitous throughout Europe. Features of concern consist of natural solution cavities (e.g. swallow holes and sinkholes in limestone gypsum and chalk) and man-made cavities (mine workings, shafts) in a great variety of post mining environments, including coal, salt, gypsum, anhydrite, tin and chalk. These problems restrict land utilisation, hinder regeneration, pose a threat to life, seriously damage property and services and blight property values. This paper outlines the application of microgravity techniques to characterise abandoned mining hazard in case studies from Coal, Chalk and Salt Mining environments in the UK. (authors)

  9. High resolution microgravity investigations for the detection and characterisation of subsidence associated with abandoned, coal, chalk and salt mines

    International Nuclear Information System (INIS)

    Styles, P.; Toon, S.; Branston, M.; England, R.; Thomas, E.; Mcgrath, R.

    2005-01-01

    The closure and decay of industrial activity involving mining has scarred the landscape of urban areas and geo-hazards posed by subsurface cavities are ubiquitous throughout Europe. Features of concern consist of natural solution cavities (e.g. swallow holes and sinkholes in limestone gypsum and chalk) and man-made cavities (mine workings, shafts) in a great variety of post mining environments, including coal, salt, gypsum, anhydrite, tin and chalk. These problems restrict land utilisation, hinder regeneration, pose a threat to life, seriously damage property and services and blight property values. This paper outlines the application of microgravity techniques to characterise abandoned mining hazard in case studies from Coal, Chalk and Salt Mining environments in the UK. (authors)

  10. Mining Genotype-Phenotype Associations from Public Knowledge Sources via Semantic Web Querying

    Science.gov (United States)

    Kiefer, Richard C.; Freimuth, Robert R.; Chute, Christopher G; Pathak, Jyotishman

    Gene Wiki Plus (GeneWiki+) and the Online Mendelian Inheritance in Man (OMIM) are publicly available resources for sharing information about disease-gene and gene-SNP associations in humans. While immensely useful to the scientific community, both resources are manually curated, thereby making the data entry and publication process time-consuming, and to some degree, error-prone. To this end, this study investigates Semantic Web technologies to validate existing and potentially discover new genotype-phenotype associations in GWP and OMIM. In particular, we demonstrate the applicability of SPARQL queries for identifying associations not explicitly stated for commonly occurring chronic diseases in GWP and OMIM, and report our preliminary findings for coverage, completeness, and validity of the associations. Our results highlight the benefits of Semantic Web querying technology to validate existing disease-gene associations as well as identify novel associations although further evaluation and analysis is required before such information can be applied and used effectively. PMID:24303249

  11. Mining potential biomarkers associated with space flight in Caenorhabditis elegans experienced Shenzhou-8 mission with multiple feature selection techniques

    International Nuclear Information System (INIS)

    Zhao, Lei; Gao, Ying; Mi, Dong; Sun, Yeqing

    2016-01-01

    Highlights: • A combined algorithm is proposed to mine biomarkers of spaceflight in C. elegans. • This algorithm makes the feature selection more reliable and robust. • Apply this algorithm to predict 17 positive biomarkers to space environment stress. • The strategy can be used as a general method to select important features. - Abstract: To identify the potential biomarkers associated with space flight, a combined algorithm, which integrates the feature selection techniques, was used to deal with the microarray datasets of Caenorhabditis elegans obtained in the Shenzhou-8 mission. Compared with the ground control treatment, a total of 86 differentially expressed (DE) genes in responses to space synthetic environment or space radiation environment were identified by two filter methods. And then the top 30 ranking genes were selected by the random forest algorithm. Gene Ontology annotation and functional enrichment analyses showed that these genes were mainly associated with metabolism process. Furthermore, clustering analysis showed that 17 genes among these are positive, including 9 for space synthetic environment and 8 for space radiation environment only. These genes could be used as the biomarkers to reflect the space environment stresses. In addition, we also found that microgravity is the main stress factor to change the expression patterns of biomarkers for the short-duration spaceflight.

  12. Mining potential biomarkers associated with space flight in Caenorhabditis elegans experienced Shenzhou-8 mission with multiple feature selection techniques

    Energy Technology Data Exchange (ETDEWEB)

    Zhao, Lei [Institute of Environmental Systems Biology, College of Environmental Science and Engineering, Dalian Maritime University, Dalian 116026 (China); Gao, Ying [Center of Medical Physics and Technology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Shushanhu Road 350, Hefei 230031 (China); Mi, Dong, E-mail: mid@dlmu.edu.cn [Department of Physics, Dalian Maritime University, Dalian 116026 (China); Sun, Yeqing, E-mail: yqsun@dlmu.edu.cn [Institute of Environmental Systems Biology, College of Environmental Science and Engineering, Dalian Maritime University, Dalian 116026 (China)

    2016-09-15

    Highlights: • A combined algorithm is proposed to mine biomarkers of spaceflight in C. elegans. • This algorithm makes the feature selection more reliable and robust. • Apply this algorithm to predict 17 positive biomarkers to space environment stress. • The strategy can be used as a general method to select important features. - Abstract: To identify the potential biomarkers associated with space flight, a combined algorithm, which integrates the feature selection techniques, was used to deal with the microarray datasets of Caenorhabditis elegans obtained in the Shenzhou-8 mission. Compared with the ground control treatment, a total of 86 differentially expressed (DE) genes in responses to space synthetic environment or space radiation environment were identified by two filter methods. And then the top 30 ranking genes were selected by the random forest algorithm. Gene Ontology annotation and functional enrichment analyses showed that these genes were mainly associated with metabolism process. Furthermore, clustering analysis showed that 17 genes among these are positive, including 9 for space synthetic environment and 8 for space radiation environment only. These genes could be used as the biomarkers to reflect the space environment stresses. In addition, we also found that microgravity is the main stress factor to change the expression patterns of biomarkers for the short-duration spaceflight.

  13. FLEXOWELL vertical lift systems in underground mining and construction industries

    Energy Technology Data Exchange (ETDEWEB)

    Paelke, J.W.

    1988-06-01

    Mining and quarrying companies are seeking improved and more continuous transport methods to reduce their costs. Frequently in the past the use of conveyors has been ruled out in steep mining applications but now the Scholtz FLEXOWELL belting which can be used at angles up to the vertical will enable many mines to consider complete belt conveyor systems for the first time. Applications will include steep conveyors for surface mines and quarries in order to eliminate the need for expensive and noisy fleets of trucks and the associated requirements to maintain haul roads. A further field is in the use of steep or vertical conveyors in underground mines to ensure improved continuity of output in existing shaft systems or reduced development costs in new mines. The Scholtz company, a member of the Nokia Group which had sales of about 3.5 billion U.S. Dollars in 1987, has more than 20 years experience with their FLEXOWELL belts. Over 40,000 units are operating around the world. These are already fully proven for vertical lifts of over 100 m (328ft) and up to 500 m (1,640 ft) is possible. Tonnage ratings of up to 4,000 t/h are achievable. Widespread acceptance of this technology has resulted in unique and major installations over the past few years. This paper reviews various applications - from the viewpoint of successfully proven vertical lift systems as well as the maintenance and downtime aspects. 3 refs., 9 figs.

  14. Human exposure and risk assessment associated with mercury contamination in artisanal gold mining areas in the Brazilian Amazon.

    Science.gov (United States)

    Castilhos, Zuleica; Rodrigues-Filho, Saulo; Cesar, Ricardo; Rodrigues, Ana Paula; Villas-Bôas, Roberto; de Jesus, Iracina; Lima, Marcelo; Faial, Kleber; Miranda, Antônio; Brabo, Edilson; Beinhoff, Christian; Santos, Elisabeth

    2015-08-01

    Mercury (Hg) contamination is an issue of concern in the Amazon region due to potential health effects associated with Hg exposure in artisanal gold mining areas. The study presents a human health risk assessment associated with Hg vapor inhalation and MeHg-contaminated fish ingestion, as well as Hg determination in urine, blood, and hair, of human populations (about 325 miners and 321 non-miners) from two gold mining areas in the Brazilian Amazon (São Chico and Creporizinho, Pará State). In São Chico and Creporizinho, 73 fish specimens of 13 freshwater species, and 161 specimens of 11 species, were collected for total Hg determination, respectively. The hazard quotient (HQ) is a risk indicator which defines the ratio of the exposure level and the toxicological reference dose and was applied to determine the threat of MeHg exposure. The mean Hg concentrations in fish from São Chico and Creporizinho were 0.83 ± 0.43 and 0.36 ± 0.33 μg/g, respectively. More than 60 and 22 % of fish collected in São Chico and Creporizinho, respectively, were above the Hg limit (0.5 μg/g) recommended by WHO for human consumption. For all sampling sites, HQ resulted from 1.5 to 28.5, except for the reference area. In Creporizinho, the values of HQ are close to 2 for most sites, whereas in São Chico, there is a hot spot of MeHg contamination in fish (A2-São Chico Reservoir) with the highest risk level (HQ = 28) associated with its human consumption. Mean Hg concentrations in urine, blood, and hair samples indicated that the miners group (in São Chico: urine = 17.37 μg/L; blood = 27.74 μg/L; hair = 4.50 μg/g and in Creporizinho: urine = 13.75 μg/L; blood = 25.23 μg/L; hair: 4.58 μg/g) was more exposed to mercury compared to non-miners (in São Chico: urine = 5.73 μg/L; blood = 16.50 μg/L; hair = 3.16 μg/g and in Creporizinho: urine = 3.91 μg/L; blood = 21.04 μg/L, hair = 1.88 μg/g). These high Hg levels (found

  15. Modeling and mining term association for improving biomedical information retrieval performance.

    Science.gov (United States)

    Hu, Qinmin; Huang, Jimmy Xiangji; Hu, Xiaohua

    2012-06-11

    The growth of the biomedical information requires most information retrieval systems to provide short and specific answers in response to complex user queries. Semantic information in the form of free text that is structured in a way makes it straightforward for humans to read but more difficult for computers to interpret automatically and search efficiently. One of the reasons is that most traditional information retrieval models assume terms are conditionally independent given a document/passage. Therefore, we are motivated to consider term associations within different contexts to help the models understand semantic information and use it for improving biomedical information retrieval performance. We propose a term association approach to discover term associations among the keywords from a query. The experiments are conducted on the TREC 2004-2007 Genomics data sets and the TREC 2004 HARD data set. The proposed approach is promising and achieves superiority over the baselines and the GSP results. The parameter settings and different indices are investigated that the sentence-based index produces the best results in terms of the document-level, the word-based index for the best results in terms of the passage-level and the paragraph-based index for the best results in terms of the passage2-level. Furthermore, the best term association results always come from the best baseline. The tuning number k in the proposed recursive re-ranking algorithm is discussed and locally optimized to be 10. First, modelling term association for improving biomedical information retrieval using factor analysis, is one of the major contributions in our work. Second, the experiments confirm that term association considering co-occurrence and dependency among the keywords can produce better results than the baselines treating the keywords independently. Third, the baselines are re-ranked according to the importance and reliance of latent factors behind term associations. These latent

  16. 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.

  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. Analysis on Medication Rules of Gastric Cancer Treatment Prescription Based on Association Analysis and Composition Network%基于关联分析和配伍网络的胃癌方剂用药规律分析

    Institute of Scientific and Technical Information of China (English)

    蒋志滨; 樊巧玲

    2015-01-01

    目的:总结分析现代临床实践中胃癌中医药治疗组方配伍规律,探索数据挖掘技术在方剂配伍规律研究中的合理应用.方法:本研究以CNKI及万方文献引擎为数据源搜集整理现代文献资料,综合运用频次统计、关联分析以及配伍网络等技术方法,分析了目标方剂集上中药使用频次及配伍特点等规律.结果:经筛选与标准化处理后,共纳入方剂116首,含中药1 269味次,涉及17类212个中药.结论:中医治疗胃癌重视以扶正为本,随证常配伍活血化瘀、清热解毒、消痰散结、理气行滞之品.%This study was aimed to analyze the current prescription combination rules on traditional Chinese medicine (TCM) in gastric cancer treatment, in order to explore reasonable application of data mining technology in the study of prescription combination rules. Modern literatures were searched in CNKI and WanFang database. Frequency analysis, association analysis and composition network were used comprehensively. Rules such as herb application frequency and combination rules of the target prescription set were analyzed. The results showed that after screening and standardization, 116 prescriptions were included in the set which including 1 269 herbs and involving 17 types of 212 herbs. It was concluded that TCM paid attention to strengthen body resistance in gastric cancer treatment. It can also be combined with drugs for invigorating blood circulation and stasis, heat-clearing and detoxification, dispersing phlegm and stasis, as well as regulatingqi stagnation depending on the syndrome.

  19. AprioriGWAS, a new pattern mining strategy for detecting genetic variants associated with disease through interaction effects.

    Science.gov (United States)

    Zhang, Qingrun; Long, Quan; Ott, Jurg

    2014-06-01

    Identifying gene-gene interaction is a hot topic in genome wide association studies. Two fundamental challenges are: (1) how to smartly identify combinations of variants that may be associated with the trait from astronomical number of all possible combinations; and (2) how to test epistatic interaction when all potential combinations are available. We developed AprioriGWAS, which brings two innovations. (1) Based on Apriori, a successful method in field of Frequent Itemset Mining (FIM) in which a pattern growth strategy is leveraged to effectively and accurately reduce search space, AprioriGWAS can efficiently identify genetically associated genotype patterns. (2) To test the hypotheses of epistasis, we adopt a new conditional permutation procedure to obtain reliable statistical inference of Pearson's chi-square test for the [Formula: see text] contingency table generated by associated variants. By applying AprioriGWAS to age-related macular degeneration (AMD) data, we found that: (1) angiopoietin 1 (ANGPT1) and four retinal genes interact with Complement Factor H (CFH). (2) GO term "glycosaminoglycan biosynthetic process" was enriched in AMD interacting genes. The epistatic interactions newly found by AprioriGWAS on AMD data are likely true interactions, since genes interacting with CFH are retinal genes, and GO term enrichment also verified that interaction between glycosaminoglycans (GAGs) and CFH plays an important role in disease pathology of AMD. By applying AprioriGWAS on Bipolar disorder in WTCCC data, we found variants without marginal effect show significant interactions. For example, multiple-SNP genotype patterns inside gene GABRB2 and GRIA1 (AMPA subunit 1 receptor gene). AMPARs are found in many parts of the brain and are the most commonly found receptor in the nervous system. The GABRB2 mediates the fastest inhibitory synaptic transmission in the central nervous system. GRIA1 and GABRB2 are relevant to mental disorders supported by multiple

  20. The South African mining industry

    International Nuclear Information System (INIS)

    Langton, G.

    1982-01-01

    This paper covers six of the many mining and associated developments in South Africa. These are: (1) Deep level gold mining at Western Deep Levels Limited - (2) Palabora Mining Company Limited - SA's unique copper mine - (3) Production of steel and vanadium-rich slag at Highveld Steel and Vanadium Corporation - (4) Coal mining at Kriel and Kleinkopje Collieries - (5) A mass mining system for use below the Gabbro Sill at Premier Diamond Mine - (6) Uranium production - joint metallurgical scheme- Orange Free State Gold Mines. - For publication in this journal the original paper has been summarised. Should any reader wish to have the full text in English he should write to the author at the address below. (orig.) [de

  1. Two non-synonymous markers in PTPN21, identified by genome-wide association study data-mining and replication, are associated with schizophrenia.

    LENUS (Irish Health Repository)

    Chen, Jingchun

    2011-09-01

    We conducted data-mining analyses of genome wide association (GWA) studies of the CATIE and MGS-GAIN datasets, and found 13 markers in the two physically linked genes, PTPN21 and EML5, showing nominally significant association with schizophrenia. Linkage disequilibrium (LD) analysis indicated that all 7 markers from PTPN21 shared high LD (r(2)>0.8), including rs2274736 and rs2401751, the two non-synonymous markers with the most significant association signals (rs2401751, P=1.10 × 10(-3) and rs2274736, P=1.21 × 10(-3)). In a meta-analysis of all 13 replication datasets with a total of 13,940 subjects, we found that the two non-synonymous markers are significantly associated with schizophrenia (rs2274736, OR=0.92, 95% CI: 0.86-0.97, P=5.45 × 10(-3) and rs2401751, OR=0.92, 95% CI: 0.86-0.97, P=5.29 × 10(-3)). One SNP (rs7147796) in EML5 is also significantly associated with the disease (OR=1.08, 95% CI: 1.02-1.14, P=6.43 × 10(-3)). These 3 markers remain significant after Bonferroni correction. Furthermore, haplotype conditioned analyses indicated that the association signals observed between rs2274736\\/rs2401751 and rs7147796 are statistically independent. Given the results that 2 non-synonymous markers in PTPN21 are associated with schizophrenia, further investigation of this locus is warranted.

  2. Towards a database for genotype-phenotype association research: mining data from encyclopaedia

    NARCIS (Netherlands)

    Pajić, V.S.; Pavlović-Lažetić, G.M.; Beljanski, M.V.; Brandt, B.W.; Pajić, M.B.

    2013-01-01

    To associate phenotypic characteristics of an organism to molecules encoded by its genome, there is a need for well-structured genotype and phenotype data. We use a novel method for extracting data on phenotype and genotype characteristics of microorganisms from text. As a resource, we use an

  3. Canadian Nuclear Association brief to the standing committee on Energy, Mines and Resources

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1991-10-01

    The Canadian Nuclear Association outlines points on electricity demand, environmental impact of electricity production, Canada`s nuclear technology and uranium deposits. Several recommendations are discussed that promote the Canadian nuclear industry and outline issues related to greenhouse gas emmisions, nuclear waste containment, funding of R and D and outlines the need for improving the environmental assessment approval processes.

  4. Canadian Nuclear Association brief to the standing committee on Energy, Mines and Resources

    International Nuclear Information System (INIS)

    1991-10-01

    The Canadian Nuclear Association outlines points on electricity demand, environmental impact of electricity production, Canada's nuclear technology and uranium deposits. Several recommendations are discussed that promote the Canadian nuclear industry and outline issues related to greenhouse gas emmisions, nuclear waste containment, funding of R and D and outlines the need for improving the environmental assessment approval processes

  5. 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.

  6. Assessment of radioactivity associated with a low ore grade open cast mine at Banduhurang, Jharkhand, India and estimation of occupational exposure to the miners

    International Nuclear Information System (INIS)

    Rana, B.K.; Shukla, A.K.; Topno, R.; Tripathi, R.M.; Puranik, V.D.

    2010-01-01

    The study summarizes radiological characteristics of Banduhurang open cast mine which includes qualitative and quantitative behavior of 222 Rn concentration, external gamma radiation level over the mine pit as well as in its adjoining environment, long-lived alpha (LLα) activity concentration associated with the respirable size of ore dust and assessment of dose to the mine workers in 2006-2008. The investigations reveal that geometric means (χg) of measured radon concentration were 36.39, 38.69, 26.64 and 24 Bq m -3 with respective geometric standard deviations (σg) were 1.52, 1.55, 1.36 and 1.68 Bq m -3 and χg of gamma absorbed dose rates were 0.54, 0.64, 0. 45 and 0.15 μGy h -1 with respective σg were 1.63, 1.53, 1.52 and 1.72 μGy h -1 over the mine pit, ore yard, waste yard and in the surrounding environment within a 10 km radius to the mine, respectively. The χg of LLα activity was observed to be 16 mBq m-3 with σg of 1.9 mBq m -3 . The annual mean effective dose equivalent received by the member radiation workers of Banduhurang mine was estimated to 1.41 mSv y -1 , which is about 7% of the prescribed dose limits of 20 mSv y -1 . (author)

  7. 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…

  8. 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,...

  9. 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

  10. DESTAF: A database of text-mined associations for reproductive toxins potentially affecting human fertility

    KAUST Repository

    Dawe, Adam Sean; Radovanovic, Aleksandar; Kaur, Mandeep; Sagar, Sunil; Seshadri, Sundararajan Vijayaraghava; Schaefer, Ulf; Kamau, Allan; Christoffels, Alan G.; Bajic, Vladimir B.

    2012-01-01

    The Dragon Exploration System for Toxicants and Fertility (DESTAF) is a publicly available resource which enables researchers to efficiently explore both known and potentially novel information and associations in the field of reproductive toxicology. To create DESTAF we used data from the literature (including over 10. 500 PubMed abstracts), several publicly available biomedical repositories, and specialized, curated dictionaries. DESTAF has an interface designed to facilitate rapid assessment of the key associations between relevant concepts, allowing for a more in-depth exploration of information based on different gene/protein-, enzyme/metabolite-, toxin/chemical-, disease- or anatomically centric perspectives. As a special feature, DESTAF allows for the creation and initial testing of potentially new association hypotheses that suggest links between biological entities identified through the database.DESTAF, along with a PDF manual, can be found at http://cbrc.kaust.edu.sa/destaf. It is free to academic and non-commercial users and will be updated quarterly. © 2011 Elsevier Inc.

  11. Rules of acupoint compatibility in acupuncture treatment of nasosinusitis based on data mining%基于数据挖掘技术针灸治疗鼻渊临床选穴配伍规律

    Institute of Scientific and Technical Information of China (English)

    曹方; 李铁; 哈丽娟; 王富春

    2016-01-01

    目的:运用数据挖掘技术,分析现代针灸文献治疗鼻渊临床选穴配伍规律。方法采用计算机检索的方式,对1959—2016年中国期刊全文数据库(CNKI)、万方数据知识服务平台(WF)和维普数据库中针灸治疗鼻渊的相关文献进行检索及梳理,得到相关文献38篇,分析现代针灸治疗鼻渊临床选穴配伍规律。结果分析发现,现代文献针灸治疗鼻渊有着以本经配穴法、局部配穴法、前后配穴法和三部配穴法为主的规律。结论针灸治疗鼻渊,应在中医整体观念、辨证论治原则指导下,将辨证选穴与对症选穴有机结合起来,选取以位于鼻部周围,属于手阳明大肠经的腧穴为主进行配伍,起到协同增效作用,增强针灸治疗鼻渊的临床疗效。%Objective To analyze the rules of acupoint compatibility for modern literature of acupuncture treat-ment of nasosinusitis based on data mining. Methods Through retrieved CNKI,Wanfang,and Weipu Database on ac-upuncture treatment of nasosinusitis from 1959 to 2016,get related with 38 papers,to analyze the rules of acupoint compatibility for modern literature of acupuncture treatment of nasosinusitis. Results According to analysis,acupunc-ture in the treatment of nasosinusitis acupoints compatibility rules mainly include:the same meridians points combina-tion,the local points combination,the front and back points combination,and the three part points combination. Con-clusion Acupuncture treatment of nasosinusitis,should be under the guidance of holistic concept of TCM,syndrome differentiation and treatment principles,the selection of the syndrome differentiation,on the basis of the organic combi-nation of acupuncture point to suit the chosen point selection with are located around the nose,the compatibility mainly belong to Large Intestine Meridian of hand-Yangming. through acupuncture points,a synergistic effect,and enhance the clinical curative effect

  12. Evaluating the role of vegetation on the transport of contaminants associated with a mine tailing using the Phyto-DSS

    International Nuclear Information System (INIS)

    Cano-Resendiz, Omar; Rosa, Guadalupe de la; Cruz-Jimenez, Gustavo; Gardea-Torresdey, Jorge L.; Robinson, Brett H.

    2011-01-01

    We identified contaminants associated with the Cata mine tailing depot located in the outskirts of the city of Guanajuato, Mexico. We also investigated strategies for their phytomanagement. Silver and antimony were present at 39 and 31 mg kg -1 , respectively, some twofold higher than the Dutch Intervention Values. Total and extractable boron (B) occurred at concentrations of 301 and 6.3 mg L -1 , respectively. Concentrations of B in soil solution above 1.9 mg L -1 have been shown to be toxic to plants. Plant growth may also be inhibited by the low concentrations of extractable plant nutrients. Analysis of the aerial portions of Aloe vera (L. Burm.f.) revealed that this plant accumulates negligible concentrations of the identified contaminants. Calculations using a whole system model (Phyto-DSS) showed that establishing a crop of A. vera would have little effect on the drainage or leaching from the site. However, this plant would reduce wind and water erosion and potentially produce valuable cosmetic products. In contrast, crops of poplar, a species that is tolerant to high soil B concentrations, would mitigate leaching from this site. Alternate rows of trees could be periodically harvested and be used for timber or bioenergy.

  13. 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.

  14. Evaluating the role of vegetation on the transport of contaminants associated with a mine tailing using the Phyto-DSS

    Energy Technology Data Exchange (ETDEWEB)

    Cano-Resendiz, Omar [Departamento de Ingenieria Quimica, Universidad de Guanajuato, Noria Alta s/n, CP 36050 Guanajuato (Mexico); Rosa, Guadalupe de la, E-mail: delarosa@quijote.ugto.mx [Departamento de Ingenieria Quimica, Universidad de Guanajuato, Noria Alta s/n, CP 36050 Guanajuato (Mexico); Cruz-Jimenez, Gustavo [Departamento de Farmacia, Universidad de Guanajuato, Noria Alta s/n, CP 36050 Guanajuato (Mexico); Gardea-Torresdey, Jorge L. [Chemistry Department and Environmental Science and Engineering, Ph.D. Program, The University of Texas at El Paso, 500 W. University Ave., 79968 El Paso, TX (United States); Robinson, Brett H. [Agriculture and Life Sciences, Lincoln University, P.O. Box 84 Lincoln, Canterbury 7646 (New Zealand)

    2011-05-15

    We identified contaminants associated with the Cata mine tailing depot located in the outskirts of the city of Guanajuato, Mexico. We also investigated strategies for their phytomanagement. Silver and antimony were present at 39 and 31 mg kg{sup -1}, respectively, some twofold higher than the Dutch Intervention Values. Total and extractable boron (B) occurred at concentrations of 301 and 6.3 mg L{sup -1}, respectively. Concentrations of B in soil solution above 1.9 mg L{sup -1} have been shown to be toxic to plants. Plant growth may also be inhibited by the low concentrations of extractable plant nutrients. Analysis of the aerial portions of Aloe vera (L. Burm.f.) revealed that this plant accumulates negligible concentrations of the identified contaminants. Calculations using a whole system model (Phyto-DSS) showed that establishing a crop of A. vera would have little effect on the drainage or leaching from the site. However, this plant would reduce wind and water erosion and potentially produce valuable cosmetic products. In contrast, crops of poplar, a species that is tolerant to high soil B concentrations, would mitigate leaching from this site. Alternate rows of trees could be periodically harvested and be used for timber or bioenergy.

  15. Submission to Energy and Mines Ministers Conference by the Canadian Energy Pipeline Association

    International Nuclear Information System (INIS)

    2002-01-01

    Almost all of the oil and natural gas in Canada is transported from supply basins to customers across the country through the critical network operated by the members of the Canadian Energy Pipeline Association (CEPA). More than 50 per cent of the liquid hydrocarbons transported last year were exported to the United States. The issues discussed in this paper are pipeline safety and integrity, landowner relations, climate change, Aboriginal consultation, and economic regulation and taxation. Each of these topics is discussed in detail. CEPA members are working closely with industry partners and their associations in both the United States and Canada, especially so since the events of September 11, as well as with federal and provincial governments in the field of critical infrastructure protection. Landowners agree to the tune of 87 per cent with the statement to the effect that Canadians can trust pipelines to safely transport oil and natural gas products across the country. CEPA members continue to strive to meet the communication and information needs of stakeholders. Climate change poses significant challenges to the industry, which is committed to doing its part to reduce the emissions of greenhouse gases. Consultation with Aboriginals is taking place in the eight provinces and two territories where CEPA members operate. The issues discussed are environmental protection, preservation of cultural and heritage resources, education and training, employment, contracting, and business opportunities. A vital component of the Canadian economy, the pipeline industry improves the quality of life for all Canadians, but the regulators are awarding low rates of return, creating a disadvantage for Canadians in the marketplace. Adjustments in this field are required, in the opinion of CEPA members. The current Capital Cost Allowance (CCA) rate for pipeline compressor assets is an issue that is being defended by CEPA members along with the Canadian Gas Association and

  16. Deep mining heterogeneous networks of biomedical linked data to predict novel drug-target associations.

    Science.gov (United States)

    Zong, Nansu; Kim, Hyeoneui; Ngo, Victoria; Harismendy, Olivier

    2017-08-01

    A heterogeneous network topology possessing abundant interactions between biomedical entities has yet to be utilized in similarity-based methods for predicting drug-target associations based on the array of varying features of drugs and their targets. Deep learning reveals features of vertices of a large network that can be adapted in accommodating the similarity-based solutions to provide a flexible method of drug-target prediction. We propose a similarity-based drug-target prediction method that enhances existing association discovery methods by using a topology-based similarity measure. DeepWalk, a deep learning method, is adopted in this study to calculate the similarities within Linked Tripartite Network (LTN), a heterogeneous network generated from biomedical linked datasets. This proposed method shows promising results for drug-target association prediction: 98.96% AUC ROC score with a 10-fold cross-validation and 99.25% AUC ROC score with a Monte Carlo cross-validation with LTN. By utilizing DeepWalk, we demonstrate that: (i) this method outperforms other existing topology-based similarity computation methods, (ii) the performance is better for tripartite than with bipartite networks and (iii) the measure of similarity using network topology outperforms the ones derived from chemical structure (drugs) or genomic sequence (targets). Our proposed methodology proves to be capable of providing a promising solution for drug-target prediction based on topological similarity with a heterogeneous network, and may be readily re-purposed and adapted in the existing of similarity-based methodologies. The proposed method has been developed in JAVA and it is available, along with the data at the following URL: https://github.com/zongnansu1982/drug-target-prediction . nazong@ucsd.edu. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

  17. The Association between Noise, Cortisol and Heart Rate in a Small-Scale Gold Mining Community—A Pilot Study

    Directory of Open Access Journals (Sweden)

    Allyson Green

    2015-08-01

    Full Text Available We performed a cross-sectional pilot study on salivary cortisol, heart rate, and personal noise exposures in a small-scale gold mining village in northeastern Ghana in 2013. Cortisol level changes between morning and evening among participants showed a relatively low decline in cortisol through the day (−1.44 ± 4.27 nmol/L, n = 18, a pattern consistent with chronic stress. A multiple linear regression, adjusting for age, sex, smoking status, and time between samples indicated a significant increase of 0.25 nmol/L cortisol from afternoon to evening per 1 dBA increase in equivalent continuous noise exposure (Leq over that period (95% CI: 0.08–0.42, Adj R2 = 0.502, n = 17. A mixed effect linear regression model adjusting for age and sex indicated a significant increase of 0.29 heart beats per minute (BPM for every 1 dB increase in Leq. Using standard deviations (SDs as measures of variation, and adjusting for age and sex over the sampling period, we found that a 1 dBA increase in noise variation over time (Leq SD was associated with a 0.5 BPM increase in heart rate SD (95% CI: 0.04–−0.9, Adj. R2 = 0.229, n = 16. Noise levels were consistently high, with 24-hour average Leq exposures ranging from 56.9 to 92.0 dBA, with a mean daily Leq of 82.2 ± 7.3 dBA (mean monitoring duration 22.1 ± 1.9 hours, n = 22. Ninety-five percent of participants had 24-hour average Leq noise levels over the 70 dBA World health Organization (WHO guideline level for prevention of hearing loss. These findings suggest that small-scale mining communities may face multiple, potentially additive health risks that are not yet well documented, including hearing loss and cardiovascular effects of stress and noise.

  18. Optimization of cultural conditions for growth associated chromate reduction by Arthrobacter sp. SUK 1201 isolated from chromite mine overburden

    Energy Technology Data Exchange (ETDEWEB)

    Dey, Satarupa, E-mail: dey1919@gmail.com [Microbiology Laboratory, Department of Botany, University of Calcutta, Kolkata 700019 (India); Paul, A.K., E-mail: amalk_paul@yahoo.co.in [Microbiology Laboratory, Department of Botany, University of Calcutta, Kolkata 700019 (India)

    2012-04-30

    Highlights: Black-Right-Pointing-Pointer Isolation of a potent Cr(VI) resistant and reducing Arthrobacter SUK 1201 from chromite mine overburdens of Orissa, India. Black-Right-Pointing-Pointer Phylogenetically (16S rDNA analysis), Arthrobacter SUK 1201 showed 99% nucleotide base pair similarity with Arthrobacter GZK-1. Black-Right-Pointing-Pointer Production of insoluble chromium precipitates during chromate reduction under batch culture by the isolate SUK 1201. Black-Right-Pointing-Pointer Confirmation of formation of insoluble chromium precipitate during reduction studies by EDX analysis. Black-Right-Pointing-Pointer Optimization of cultural conditions for Cr(VI) reduction under batch culture leading to complete reduction of 2 mM of Cr(VI). - Abstract: Arthrobacter sp. SUK 1201, a chromium resistant and reducing bacterium having 99% sequence homology of 16S rDNA with Arthrobacter sp. GZK-1 was isolated from chromite mine overburden dumps of Orissa, India. The objective of the present study was to optimize the cultural conditions for chromate reduction by Arthrobacter sp. SUK 1201. The strain showed 67% reduction of 2 mM chromate in 7 days and was associated with the formation of green insoluble precipitate, which showed characteristic peak of chromium in to energy dispersive X-ray analysis. However, Fourier transform infrared spectra have failed to detect any complexation of end products of Cr(VI) reduction with the cell mass. Reduction of chromate increased with increased cell density and was maximum at 10{sup 10} cells/ml, but the reduction potential decreased with increase in Cr(VI) concentration. Chromate reducing efficiency was promoted when glycerol and glucose was used as electron donors. Optimum pH and temperature of Cr(VI) reduction was 7.0 and 35 Degree-Sign C respectively. The reduction process was inhibited by several metal ions and metabolic inhibitors but not by Cu(II) and DNP. These findings suggest that Arthrobacter sp. SUK 1201 has great promise

  19. The Association between Noise, Cortisol and Heart Rate in a Small-Scale Gold Mining Community-A Pilot Study.

    Science.gov (United States)

    Green, Allyson; Jones, Andrew D; Sun, Kan; Neitzel, Richard L

    2015-08-21

    We performed a cross-sectional pilot study on salivary cortisol, heart rate, and personal noise exposures in a small-scale gold mining village in northeastern Ghana in 2013. Cortisol level changes between morning and evening among participants showed a relatively low decline in cortisol through the day (-1.44 ± 4.27 nmol/L, n = 18), a pattern consistent with chronic stress. A multiple linear regression, adjusting for age, sex, smoking status, and time between samples indicated a significant increase of 0.25 nmol/L cortisol from afternoon to evening per 1 dBA increase in equivalent continuous noise exposure (Leq) over that period (95% CI: 0.08-0.42, Adj R(2) = 0.502, n = 17). A mixed effect linear regression model adjusting for age and sex indicated a significant increase of 0.29 heart beats per minute (BPM) for every 1 dB increase in Leq. Using standard deviations (SDs) as measures of variation, and adjusting for age and sex over the sampling period, we found that a 1 dBA increase in noise variation over time (Leq SD) was associated with a 0.5 BPM increase in heart rate SD (95% CI: 0.04--0.9, Adj. R(2) = 0.229, n = 16). Noise levels were consistently high, with 24-hour average Leq exposures ranging from 56.9 to 92.0 dBA, with a mean daily Leq of 82.2 ± 7.3 dBA (mean monitoring duration 22.1 ± 1.9 hours, n = 22). Ninety-five percent of participants had 24-hour average Leq noise levels over the 70 dBA World health Organization (WHO) guideline level for prevention of hearing loss. These findings suggest that small-scale mining communities may face multiple, potentially additive health risks that are not yet well documented, including hearing loss and cardiovascular effects of stress and noise.

  20. Dissolved metals and associated constituents in abandoned coal-mine discharges, Pennsylvania, USA. Part 1: Constituent quantities and correlations

    International Nuclear Information System (INIS)

    Cravotta, Charles A.

    2008-01-01

    Complete hydrochemical data are rarely reported for coal-mine discharges (CMD). This report summarizes major and trace-element concentrations and loadings for CMD at 140 abandoned mines in the Anthracite and Bituminous Coalfields of Pennsylvania. Clean-sampling and low-level analytical methods were used in 1999 to collect data that could be useful to determine potential environmental effects, remediation strategies, and quantities of valuable constituents. A subset of 10 sites was resampled in 2003 to analyze both the CMD and associated ochreous precipitates; the hydrochemical data were similar in 2003 and 1999. In 1999, the flow at the 140 CMD sites ranged from 0.028 to 2210 L s -1 , with a median of 18.4 L s -1 . The pH ranged from 2.7 to 7.3; concentrations (range in mg/L) of dissolved (0.45-μm pore-size filter) SO 4 (34-2000), Fe (0.046-512), Mn (0.019-74), and Al (0.007-108) varied widely. Predominant metalloid elements were Si (2.7-31.3 mg L -1 ), B ( -1 ), Ge ( -1 ), and As ( -1 ). The most abundant trace metals, in order of median concentrations (range in μg/L), were Zn (0.6-10,000), Ni (2.6-3200), Co (0.27-3100), Ti (0.65-28), Cu (0.4-190), Cr ( -1 in 97% of the samples, with a maximum of 0.0175 μg L -1 . No samples had detectable concentrations of Hg, Os or Pt, and less than half of the samples had detectable Pd, Ag, Ru, Ta, Nb, Re or Sn. Predominant rare-earth elements, in order of median concentrations (range in μg/L), were Y (0.11-530), Ce (0.01-370), Sc (1.0-36), Nd (0.006-260), La (0.005-140), Gd (0.005-110), Dy (0.002-99) and Sm ( C > P = N = Se) were not elevated in the CMD samples compared to average river water or seawater. Compared to seawater, the CMD samples also were poor in halogens (Cl > Br > I > F), alkalies (Na > K > Li > Rb > Cs), most alkaline earths (Ca > Mg > Sr), and most metalloids but were enriched by two to four orders of magnitude with Fe, Al, Mn, Co, Be, Sc, Y and the lanthanide rare-earth elements, and one order of

  1. Priority pollutants and associated constituents in untreated and treated discharges from coal mining or processing facilities in Pennsylvania, USA

    Science.gov (United States)

    Cravotta, III, Charles A.; Brady, Keith B.C.

    2015-01-01

    Clean sampling and analysis procedures were used to quantify more than 70 inorganic constituents, including 35 potentially toxic or hazardous constituents, organic carbon, and other characteristics of untreated (influent) and treated (effluent) coal-mine discharges (CMD) at 38 permitted coal-mining or coal-processing facilities in the bituminous coalfield and 4 facilities in the anthracite coalfield of Pennsylvania. Of the 42 facilities sampled during 2011, 26 were surface mines, 11 were underground mines, and 5 were coal refuse disposal operations. Treatment of CMD with caustic soda (NaOH), lime (CaO or Ca(OH)2), flocculent, or limestone was ongoing at 21%, 40%, 6%, and 4% of the facilities, respectively; no chemicals were added at the remaining facilities. All facilities with CMD treatment incorporated structures for active or passive aeration and settling of metal-rich precipitate.

  2. 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.

  3. 76 FR 81761 - Mine Safety Disclosure

    Science.gov (United States)

    2011-12-28

    ... or other mine to file a current report on Form 8-K with the Commission reporting receipt of certain....\\24\\ Issuers have been providing disclosure in their periodic and current reports filed with the... Release, that to the extent mine safety issues are material, under our current rules disclosure could be...

  4. Granitoid-associated gold mineralization in Egypt: a case study from the Atalla mine

    Science.gov (United States)

    Zoheir, Basem; Deshesh, Fatma; Broman, Curt; Pitcairn, Iain; El-Metwally, Ahmed; Mashaal, Shabaan

    2018-06-01

    Gold-bearing sulfide-quartz veins cutting mainly through the Atalla monzogranite intrusion in the Eastern Desert of Egypt are controlled by subparallel NE-trending brittle shear zones. These veins are associated with pervasive sericite-altered, silicified, and ferruginated rocks. The hosting shear zones are presumed as high-order structures of the Najd-style faults in the Central Eastern Desert ( 615-585 Ma). Ore minerals include an early pyrite-arsenopyrite (±pyrrhotite) mineralization, partly replaced by a late pyrite-galena-sphalerite-chalcopyrite (±gold/electrum ± tetrahedrite ± hessite) assemblage. Gold occurs as small inclusions in pyrite and arsenopyrite, or more commonly as intergrowths with galena and sphalerite/tetrahedrite in microfractures. Arsenopyrite geothermometry suggests formation of the early Fe-As-sulfide mineralization at 380-340 °C, while conditions of deposition of the late base metal-gold assemblage are assumed to be below 300 °C. Rare hessite, electrum, and Bi-galena are associated with sphalerite and gold in the late assemblage. The early and late sulfide minerals show consistently a narrow range of δ34S ‰ (3.4-6.5) that overlaps with sulfur isotopic values in ophiolitic rocks. The Au-quartz veins are characterized by abundant CO2 and H2O ± CO2 ± NaCl inclusions, where three-dimensional clusters of inclusions show variable aqueous/carbonic proportions and broad range of total (bimodal) homogenization temperatures. Heterogeneous entrapment of immiscible fluids is interpreted to be caused by unmixing of an originally homogenous, low salinity ( 2 eq. mass % NaCl) aqueous-carbonic fluid, during transition from lithostatic to hydrostatic conditions. Gold deposition occurred generally under mesothermal conditions, i.e., 1.3 kbar and 280 °C, and continued during system cooling to chemistry of the ore fluids.

  5. A review of mortality associated with elongate mineral particle (EMP) exposure in occupational epidemiology studies of gold, talc, and taconite mining.

    Science.gov (United States)

    Mandel, Jeffrey H; Alexander, Bruce H; Ramachandran, Gurumurthy

    2016-12-01

    Mining of gold, taconite, and talc may involve exposure to elongate mineral particles (EMP). The involved EMPs are typically non-asbestiform, include dimensions that regulatory definitions exclude, and have been less studied. A review of the literature was undertaken for this exposure and occupational epidemiological studies that occur in gold, talc, and taconite mining. Quantitative EMP exposure information in these industries is incomplete. However, there are consistent findings of pneumoconiosis in each of these types of mining. A recent case-control study suggests a possible association between this exposure and mesothelioma. Lung cancer is inconsistently reported in these industries and is an unlikely outcome of non-asbestiform EMP exposure. There is evidence of cardiovascular mortality excess across all of these types of mining. Non-malignant respiratory disease and cardiovascular mortality have been consistently increased in these industries. Further investigation, including additional insights for the role of non-asbestiform EMP, is warranted. Am. J. Ind. Med. 59:1047-1060, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

  6. GWA study data mining and independent replication identify cardiomyopathy-associated 5 (CMYA5) as a risk gene for schizophrenia.

    LENUS (Irish Health Repository)

    Chen, X

    2011-11-01

    We conducted data-mining analyses using the Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) and molecular genetics of schizophrenia genome-wide association study supported by the genetic association information network (MGS-GAIN) schizophrenia data sets and performed bioinformatic prioritization for all the markers with P-values ≤0.05 in both data sets. In this process, we found that in the CMYA5 gene, there were two non-synonymous markers, rs3828611 and rs10043986, showing nominal significance in both the CATIE and MGS-GAIN samples. In a combined analysis of both the CATIE and MGS-GAIN samples, rs4704591 was identified as the most significant marker in the gene. Linkage disequilibrium analyses indicated that these markers were in low LD (3 828 611-rs10043986, r(2)=0.008; rs10043986-rs4704591, r(2)=0.204). In addition, CMYA5 was reported to be physically interacting with the DTNBP1 gene, a promising candidate for schizophrenia, suggesting that CMYA5 may be involved in the same biological pathway and process. On the basis of this information, we performed replication studies for these three single-nucleotide polymorphisms. The rs3828611 was found to have conflicting results in our Irish samples and was dropped out without further investigation. The other two markers were verified in 23 other independent data sets. In a meta-analysis of all 23 replication samples (family samples, 912 families with 4160 subjects; case-control samples, 11 380 cases and 15 021 controls), we found that both markers are significantly associated with schizophrenia (rs10043986, odds ratio (OR)=1.11, 95% confidence interval (CI)=1.04-1.18, P=8.2 × 10(-4) and rs4704591, OR=1.07, 95% CI=1.03-1.11, P=3.0 × 10(-4)). The results were also significant for the 22 Caucasian replication samples (rs10043986, OR=1.11, 95% CI=1.03-1.17, P=0.0026 and rs4704591, OR=1.07, 95% CI=1.02-1.11, P=0.0015). Furthermore, haplotype conditioned analyses indicated that the association

  7. Mining, Validation, and Clinical Significance of Colorectal Cancer (CRC)-Associated lncRNAs.

    Science.gov (United States)

    Sun, Xiangwei; Hu, Yingying; Zhang, Liang; Hu, Changyuan; Guo, Gangqiang; Mao, Chenchen; Xu, Jianfeng; Ye, Sisi; Huang, Guanli; Xue, Xiangyang; Guo, Aizhen; Shen, Xian

    2016-01-01

    Colorectal cancer (CRC) is one of the deadliest tumours, but its pathogenesis remains unclear. The involvement of differentially expressed long non-coding RNAs (lncRNAs) in CRC tumorigenesis makes them suitable tumour biomarkers. Here, we screened 150 cases of CRC and 85 cases of paracancerous tissues in the GEO database for differentially expressed lncRNAs. The levels of lncRNA candidates in 84 CRC and paracancerous tissue samples were validated by qRT-PCR and their clinical significance was analyzed. We identified 15 lncRNAs with differential expression in CRC tumours; among them, AK098081 was significantly up-regulated, whereas AK025209, BC040303, BC037331, AK026659, and CR749831 were down-regulated in CRC. In a receiver operating characteristic curve analysis, the area under the curve for the six lncRNAs was 0.914. High expression of AK098081 and low expression of BC040303, CR749831, and BC037331 indicated poor CRC differentiation. CRC patients with lymph node metastasis had lower expression of BC037331. In addition, the group with high AK098081 expression presented significantly lower overall survival and disease-free survival rates than the low-expression group, confirming AK098081 as an independent risk factor for CRC patients. In conclusion, we have identified multiple CRC-associated lncRNAs from microarray expression profiles that can serve as novel biomarkers for the diagnosis and prognosis of CRC.

  8. Fish gill responses to pollutants from oil sands mining-associated waters

    International Nuclear Information System (INIS)

    Lee, L.E.J.; Willfang, S.; Lamb, M.P.; Nero, V.; Farwell, A.J.; Dixon, D.G.

    2002-01-01

    The processing of Athabasca Deposit oil sands results in large amounts of liquid wastes associated with oil sand tailings. In addition to containing polycyclic aromatic hydrocarbons (PAHs), these waste waters are high in salinity and naphthenic acids which may be toxic to aquatic biota and their effects must be clarified. This study presents a suite of tests for in-depth and quick analysis of tailings water toxicity and contributes to the assessment of environmental risk. Yellow perch, fathead minnows, and rainbow trout were exposed to reclamation ponds where both in vivo and in vitro evaluation of crude and individual naphthenic acids and salts were conducted to examine their effect on fish gills which are very susceptible to contaminants. The fish exposed to the reclamation ponds showed higher incidence of gill pathological changes than control fish in Mildred Lake, a reservoir lake whose waters are diverted for use in oil sands extraction. Notable gill histopathological changes were observed when fish were exposed in vivo to sulfate/chloride salts and to abietic acid. Changes in membrane integrity, lysosomal activity and general morphology were observed when fished were exposed in vitro to salts, commercial napthenic acids or crude naphthenic extracts from the reclamation ponds

  9. QTL detection and elite alleles mining for stigma traits in Oryza sativa by association mapping

    Directory of Open Access Journals (Sweden)

    Xiaojing Dang

    2016-08-01

    Full Text Available Stigma traits are very important for hybrid seed production in Oryza sativa, which is a self-pollinated crop; however, the genetic mechanism controlling the traits is poorly understood. In this study, we investigated the phenotypic data of 227 accessions across two years and assessed their genotypic variation with 249 simple sequence repeat (SSR markers. By combining phenotypic and genotypic data, a genome-wide association (GWA map was generated. Large phenotypic variations in stigma length (STL, stigma brush-shaped part length (SBPL and stigma non-brush-shaped part length (SNBPL were found. Significant positive correlations were identified among stigma traits. In total, 2,072 alleles were detected among 227 accessions, with an average of 8.3 alleles per SSR locus. GWA mapping detected 6 quantitative trait loci (QTLs for the STL, 2 QTLs for the SBPL and 7 QTLs for the SNBPL. Eleven, 5, and 12 elite alleles were found for the STL, SBPL and SNBPL, respectively. Optimal cross designs were predicted for improving the target traits. The detected genetic variation in stigma traits and QTLs provides helpful information for cloning candidate STL genes and breeding rice cultivars with longer STLs in the future.

  10. Empirical approach for designing of support system in mechanized coal pillar mining

    Energy Technology Data Exchange (ETDEWEB)

    Kushwaha, A.; Singh, S.K.; Tewari, S.; Sinha, A. [Central Institute of Mining & Fuel Research, Dhanbad (India)

    2010-10-15

    Mechanized room-and-pillar system of coal pillar mining using side dump loading machine or load haul dumper machine, or by continuous miner, is the presently most dominant under ground method of extraction in India. Under this method of extraction, strata control is a major problem affecting safety and productivity of the mine. As per existing Director General of Mine Safety guidelines, systematic support rules must be followed at the depillaring faces irrespective of immediate roof rock type and competency. Therefore, there is a high chance that sometimes these systematic support rules give unnecessarily high support, or sometimes inadequate support, which may lead to roof failure at the face. As a result, there is a big loss of life and material including coal in terms of left-outribs/stooks and other associated mining equipment deployed at the faces. Therefore, in the present paper, authors attempted to develop generalized empirical equations for estimating the required support load density at different places of the face based on geotechnical parameters of the mine and physico-mechanical properties of the immediate roof rocks for designing of support system during mechanized coal pillar mining.

  11. An improved association-mining research for exploring Chinese herbal property theory: based on data of the Shennong's Classic of Materia Medica.

    Science.gov (United States)

    Jin, Rui; Lin, Zhi-jian; Xue, Chun-miao; Zhang, Bing

    2013-09-01

    Knowledge Discovery in Databases is gaining attention and raising new hopes for traditional Chinese medicine (TCM) researchers. It is a useful tool in understanding and deciphering TCM theories. Aiming for a better understanding of Chinese herbal property theory (CHPT), this paper performed an improved association rule learning to analyze semistructured text in the book entitled Shennong's Classic of Materia Medica. The text was firstly annotated and transformed to well-structured multidimensional data. Subsequently, an Apriori algorithm was employed for producing association rules after the sensitivity analysis of parameters. From the confirmed 120 resulting rules that described the intrinsic relationships between herbal property (qi, flavor and their combinations) and herbal efficacy, two novel fundamental principles underlying CHPT were acquired and further elucidated: (1) the many-to-one mapping of herbal efficacy to herbal property; (2) the nonrandom overlap between the related efficacy of qi and flavor. This work provided an innovative knowledge about CHPT, which would be helpful for its modern research.

  12. Lack of parental rule-setting on eating is associated with a wide range of adolescent unhealthy eating behaviour both for boys and girls

    Directory of Open Access Journals (Sweden)

    Jana Holubcikova

    2016-04-01

    Full Text Available Abstract Background Unhealthy eating habits in adolescence lead to a wide variety of health problems and disorders. The aim of this study was to assess the prevalence of absence of parental rules on eating and unhealthy eating behaviour and to explore the relationships between parental rules on eating and a wide range of unhealthy eating habits of boys and girls. We also explored the association of sociodemographic characteristics such as gender, family affluence or parental education with eating related parental rules and eating habits of adolescents. Methods The data on 2765 adolescents aged 13–15 years (mean age: 14.4; 50.7 % boys from the Slovak part of the Health Behaviour in School-Aged Children (HBSC study 2014 were assessed. The associations between eating-related parental rules and unhealthy eating patterns using logistic regression were assessed using logistic regression. Results Unhealthy eating habits occurred frequently among adolescents (range: 18.0 % reported skipping breakfast during weekends vs. 75.8 % for low vegetables intake. Of all adolescents, 20.5 % reported a lack of any parental rules on eating (breakfast not mandatory, meal in front of TV allowed, no rules about sweets and soft drinks. These adolescents were more likely to eat unhealthily, i.e. to skip breakfast on weekdays (odds ratio/95 % confidence interval: 5.33/4.15–6.84 and on weekends (2.66/2.12–3.34, to report low consumption of fruits (1.63/1.30–2.04 and vegetables (1.32/1.04–1.68, and the frequent consumption of sweets (1.59/1.30–1.94, soft drinks (1.93/1.56–2.38 and energy drinks (2.15/1.72–2.70. Conclusions Parental rule-setting on eating is associated with eating behaviours of adolescents. Further research is needed to disentangle causality in this relationship. If causal, parents may be targeted to modify the eating habits of adolescents.

  13. Structuring osteosarcoma knowledge: an osteosarcoma-gene association database based on literature mining and manual annotation.

    Science.gov (United States)

    Poos, Kathrin; Smida, Jan; Nathrath, Michaela; Maugg, Doris; Baumhoer, Daniel; Neumann, Anna; Korsching, Eberhard

    2014-01-01

    Osteosarcoma (OS) is the most common primary bone cancer exhibiting high genomic instability. This genomic instability affects multiple genes and microRNAs to a varying extent depending on patient and tumor subtype. Massive research is ongoing to identify genes including their gene products and microRNAs that correlate with disease progression and might be used as biomarkers for OS. However, the genomic complexity hampers the identification of reliable biomarkers. Up to now, clinico-pathological factors are the key determinants to guide prognosis and therapeutic treatments. Each day, new studies about OS are published and complicate the acquisition of information to support biomarker discovery and therapeutic improvements. Thus, it is necessary to provide a structured and annotated view on the current OS knowledge that is quick and easily accessible to researchers of the field. Therefore, we developed a publicly available database and Web interface that serves as resource for OS-associated genes and microRNAs. Genes and microRNAs were collected using an automated dictionary-based gene recognition procedure followed by manual review and annotation by experts of the field. In total, 911 genes and 81 microRNAs related to 1331 PubMed abstracts were collected (last update: 29 October 2013). Users can evaluate genes and microRNAs according to their potential prognostic and therapeutic impact, the experimental procedures, the sample types, the biological contexts and microRNA target gene interactions. Additionally, a pathway enrichment analysis of the collected genes highlights different aspects of OS progression. OS requires pathways commonly deregulated in cancer but also features OS-specific alterations like deregulated osteoclast differentiation. To our knowledge, this is the first effort of an OS database containing manual reviewed and annotated up-to-date OS knowledge. It might be a useful resource especially for the bone tumor research community, as specific

  14. Legal aspects of search and mining of nuclear ores under Brazilian law

    International Nuclear Information System (INIS)

    Godinho, T.M.

    1980-06-01

    The legal aspects of mining in the Brazilian law its general principles, the basic concepts and rules established in the constitution of Brazil, in the mining code and in special laws are analysed. The rules for mining and usage of nuclear ores and other ores of interest to the nuclear field are emphasized. (A.L.) [pt

  15. A cross-sectional survey on knowledge and perceptions of health risks associated with arsenic and mercury contamination from artisanal gold mining in Tanzania

    Directory of Open Access Journals (Sweden)

    Charles Elias

    2013-01-01

    Full Text Available Abstract Background An estimated 0.5 to 1.5 million informal miners, of whom 30-50% are women, rely on artisanal mining for their livelihood in Tanzania. Mercury, used in the processing gold ore, and arsenic, which is a constituent of some ores, are common occupational exposures that frequently result in widespread environmental contamination. Frequently, the mining activities are conducted haphazardly without regard for environmental, occupational, or community exposure. The primary objective of this study was to assess community risk knowledge and perception of potential mercury and arsenic toxicity and/or exposure from artisanal gold mining in Rwamagasa in northwestern Tanzania. Methods A cross-sectional survey of respondents in five sub-villages in the Rwamagasa Village located in Geita District in northwestern Tanzania near Lake Victoria was conducted. This area has a history of artisanal gold mining and many of the population continue to work as miners. Using a clustered random selection approach for recruitment, a total of 160 individuals over 18 years of age completed a structured interview. Results The interviews revealed wide variations in knowledge and risk perceptions concerning mercury and arsenic exposure, with 40.6% (n=65 and 89.4% (n=143 not aware of the health effects of mercury and arsenic exposure respectively. Males were significantly more knowledgeable (n=59, 36.9% than females (n=36, 22.5% with regard to mercury (x2=3.99, px2=22.82, p= Conclusions The knowledge of individuals living in Rwamagasa, Tanzania, an area with a history of artisanal gold mining, varied widely with regard to the health hazards of mercury and arsenic. In these communities there was limited awareness of the threats to health associated with exposure to mercury and arsenic. This lack of knowledge, combined with minimal environmental monitoring and controlled waste management practices, highlights the need for health education, surveillance, and policy

  16. Mining with Rare Cases

    Science.gov (United States)

    Weiss, Gary M.

    Rare cases are often the most interesting cases. For example, in medical diagnosis one is typically interested in identifying relatively rare diseases, such as cancer, rather than more frequently occurring ones, such as the common cold. In this chapter we discuss the role of rare cases in Data Mining. Specific problems associated with mining rare cases are discussed, followed by a description of methods for addressing these problems.

  17. Exploring the challenges associated with the greening of supply chains in the South African manganese and phosphate mining industry

    Directory of Open Access Journals (Sweden)

    R.I. David Pooe

    2014-11-01

    Full Text Available As with most mining activities, the mining of manganese and phosphate has serious consequences for the environment. Despite a largely adequate and progressive framework for environmental governance developed since 1994, few mines have integrated systems into their supply chain processes to minimise environmental risks and ensure the achievement of acceptable standards. Indeed, few mines have been able to implement green supply chain management (GrSCM. The purpose of this article was to explore challenges related to the implementation of GrSCM and to provide insight into how GrSCM can be implemented in the South African manganese and phosphate industry. This article reported findings of a qualitative study involving interviews with 12 participants from the manganese and phosphate industry in South Africa. Purposive sampling techniques were used. Emerging from the study were six themes, all of which were identified as key challenges in the implementation of GrSCM in the manganese and phosphate mining industry. From the findings, these challenges include the operationalisation of environmental issues, lack of collaboration and knowledge sharing, proper application of monitoring and control systems,lack of clear policy and legislative direction, the cost of implementing GrSCM practices, and the need for strong leadership and management of change. On the basis of the literature reviewed and empirical findings, conclusions were drawn and policy and management recommendations were accordingly made.

  18. An association between dietary habits and traffic accidents in patients with chronic liver disease: A data-mining analysis.

    Science.gov (United States)

    Kawaguchi, Takumi; Suetsugu, Takuro; Ogata, Shyou; Imanaga, Minami; Ishii, Kumiko; Esaki, Nao; Sugimoto, Masako; Otsuyama, Jyuri; Nagamatsu, Ayu; Taniguchi, Eitaro; Itou, Minoru; Oriishi, Tetsuharu; Iwasaki, Shoko; Miura, Hiroko; Torimura, Takuji

    2016-05-01

    The incidence of traffic accidents in patients with chronic liver disease (CLD) is high in the USA. However, the characteristics of patients, including dietary habits, differ between Japan and the USA. The present study investigated the incidence of traffic accidents in CLD patients and the clinical profiles associated with traffic accidents in Japan using a data-mining analysis. A cross-sectional study was performed and 256 subjects [148 CLD patients (CLD group) and 106 patients with other digestive diseases (disease control group)] were enrolled; 2 patients were excluded. The incidence of traffic accidents was compared between the two groups. Independent factors for traffic accidents were analyzed using logistic regression and decision-tree analyses. The incidence of traffic accidents did not differ between the CLD and disease control groups (8.8 vs. 11.3%). The results of the logistic regression analysis showed that yoghurt consumption was the only independent risk factor for traffic accidents (odds ratio, 0.37; 95% confidence interval, 0.16-0.85; P=0.0197). Similarly, the results of the decision-tree analysis showed that yoghurt consumption was the initial divergence variable. In patients who consumed yoghurt habitually, the incidence of traffic accidents was 6.6%, while that in patients who did not consume yoghurt was 16.0%. CLD was not identified as an independent factor in the logistic regression and decision-tree analyses. In conclusion, the difference in the incidence of traffic accidents in Japan between the CLD and disease control groups was insignificant. Furthermore, yoghurt consumption was an independent negative risk factor for traffic accidents in patients with digestive diseases, including CLD.

  19. An association between dietary habits and traffic accidents in patients with chronic liver disease: A data-mining analysis

    Science.gov (United States)

    KAWAGUCHI, TAKUMI; SUETSUGU, TAKURO; OGATA, SHYOU; IMANAGA, MINAMI; ISHII, KUMIKO; ESAKI, NAO; SUGIMOTO, MASAKO; OTSUYAMA, JYURI; NAGAMATSU, AYU; TANIGUCHI, EITARO; ITOU, MINORU; ORIISHI, TETSUHARU; IWASAKI, SHOKO; MIURA, HIROKO; TORIMURA, TAKUJI

    2016-01-01

    The incidence of traffic accidents in patients with chronic liver disease (CLD) is high in the USA. However, the characteristics of patients, including dietary habits, differ between Japan and the USA. The present study investigated the incidence of traffic accidents in CLD patients and the clinical profiles associated with traffic accidents in Japan using a data-mining analysis. A cross-sectional study was performed and 256 subjects [148 CLD patients (CLD group) and 106 patients with other digestive diseases (disease control group)] were enrolled; 2 patients were excluded. The incidence of traffic accidents was compared between the two groups. Independent factors for traffic accidents were analyzed using logistic regression and decision-tree analyses. The incidence of traffic accidents did not differ between the CLD and disease control groups (8.8 vs. 11.3%). The results of the logistic regression analysis showed that yoghurt consumption was the only independent risk factor for traffic accidents (odds ratio, 0.37; 95% confidence interval, 0.16–0.85; P=0.0197). Similarly, the results of the decision-tree analysis showed that yoghurt consumption was the initial divergence variable. In patients who consumed yoghurt habitually, the incidence of traffic accidents was 6.6%, while that in patients who did not consume yoghurt was 16.0%. CLD was not identified as an independent factor in the logistic regression and decision-tree analyses. In conclusion, the difference in the incidence of traffic accidents in Japan between the CLD and disease control groups was insignificant. Furthermore, yoghurt consumption was an independent negative risk factor for traffic accidents in patients with digestive diseases, including CLD. PMID:27123257

  20. Heavy metal pollution in soil associated with a large-scale cyanidation gold mining region in southeast of Jilin, China.

    Science.gov (United States)

    Chen, Mo; Lu, Wenxi; Hou, Zeyu; Zhang, Yu; Jiang, Xue; Wu, Jichun

    2017-01-01

    Different gold mining and smelting processes can lead to distinctive heavy metal contamination patterns and results. This work examined heavy metal pollution from a large-scale cyanidation gold mining operation, which is distinguished from artisanal and small-scale amalgamation gold mining, in Jilin Province, China. A total of 20 samples including one background sample were collected from the surface of the mining area and the tailings pond in June 2013. These samples were analyzed for heavy metal concentrations and degree of pollution as well as sources of Cr, Cu, Zn, Pb, Ni, Cd, As, and Hg. The mean concentrations of Pb, Hg, and Cu (819.67, 0.12, and 46.92 mg kg -1 , respectively) in soil samples from the gold mine area exceeded local background values. The mean Hg content was less than the first-class standard of the Environmental Quality for Soils, which suggested that the cyanidation method is helpful for reducing Hg pollution. The geochemical accumulation index and enrichment factor results indicated clear signs that enrichment was present for Pb, Cu, and Hg, with the presence of serious Pb pollution and moderate presence to none of Hg and Cu pollution. Multivariate statistical analysis showed that there were three metal sources: (1) Pb, Cd, Cu, and As came from anthropogenic sources; (2) Cr and Zn were naturally occurring; whereas (3) Hg and Ni had a mix of anthropogenic and natural sources. Moreover, the tailings dam plays an important role in intercepting the tailings. Furthermore, the potential ecological risk assessment results showed that the study area poses a potentially strong risk to the ecological health. Furthermore, Pb and Hg (due to high concentration and high toxicity, respectively) are major pollutants on the risk index, and both Pb and Hg pollution should be of great concern at the Haigou gold mines in Jilin, China.

  1. Economic impact of world mining

    International Nuclear Information System (INIS)

    Walser, G.

    2002-01-01

    Mining plays a vital role in the economic development of many countries. The emerging economies are now major players in the production and availability of key commodities such as copper (70%), bauxite (40%), iron ore and precious metals. Mining also has a positive impact on the economy of many countries. Another impact of mining can be measured in terms of employment opportunities and income generation. Commercial scale mining provides employment and skills transfer to more than 2 million workers. The multiplier effect increases this benefit by a factor of between 2 and 5. The World Bank Mining Department has carried out an in-depth study on economic and social impact of mining at the community level in Chile, Peru, Bolivia, Papua New Guinea and Mali. This study demonstrates that there are substantial social and economic benefits to the community. The most positive cases are related to the growth of local small- and micro-enterprise activities. However, mining remains controversial, as true sustainable development is not only a matter of financial flows. Mining has also been associated with a number of economic and social problems. As a result there are questions about the sustainability of the economic outcome of mining. The contribution of mining to sustainable development needs to be considered in terms of economic and technical viability, ecological sustainability and social equity. To achieve this, governments, mining companies and local communities must work together to address these issues. (author)

  2. Neutralization and attenuation of metal species in acid mine drainage and mine leachates using magnesite: a batch experimental approach

    CSIR Research Space (South Africa)

    Masindi, Vhahangwele

    2014-08-01

    Full Text Available International Mine Water Association Conference – An Interdisciplinary Response to Mine Water Challenges, China University of Mining and Technogy, China, China, 18-22 August 2014 Neutralization and Attenuation of Metal Species in Acid Mine Drainage and Mine...

  3. SPATIO-TEMPORAL PATTERN MINING ON TRAJECTORY DATA USING ARM

    Directory of Open Access Journals (Sweden)

    S. Khoshahval

    2017-09-01

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

  4. Spatio-Temporal Pattern Mining on Trajectory Data Using Arm

    Science.gov (United States)

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

    2017-09-01

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

  5. Radiation in mines

    International Nuclear Information System (INIS)

    Rose, H.J.M.

    1982-01-01

    Radiation in mines is primarily associated with, but not restricted to, the exploitation of uranium bearing orebodies. The intent of this chapter is to convey some aspects of radiation control in the mining industry, the behaviour of the parent radon and its daughter products. An attempt was made to demonstrate that anything less than complete diligence by the ventilation personnel could result in rapid deterioration of the mine environment, and consequently high exposure rates. When the maximum annual exposure limit is 4,0 WLM (Working level month exposure) the ventilation official is not allowed the privilege of making an error. Ventilation planning in uranium mines is of prime importance and is very much a group involvement

  6. Mercury and trace element contents of Donbas coals and associated mine water in the vicinity of Donetsk, Ukraine

    Science.gov (United States)

    Kolker, A.; Panov, B.S.; Panov, Y.B.; Landa, E.R.; Conko, K.M.; Korchemagin, V.A.; Shendrik, T.; McCord, J.D.

    2009-01-01

    Mercury-rich coals in the Donets Basin (Donbas region) of Ukraine were sampled in active underground mines to assess the levels of potentially harmful elements and the potential for dispersion of metals through use of this coal. For 29 samples representing c11 to m3 Carboniferous coals, mercury contents range from 0.02 to 3.5 ppm (whole-coal dry basis). Mercury is well correlated with pyritic sulfur (0.01 to 3.2 wt.%), with an r2 of 0.614 (one outlier excluded). Sulfides in these samples show enrichment of minor constituents in late-stage pyrite formed as a result of interaction of coal with hydrothermal fluids. Mine water sampled at depth and at surface collection points does not show enrichment of trace metals at harmful levels, indicating pyrite stability at subsurface conditions. Four samples of coal exposed in the defunct open-cast Nikitovka mercury mines in Gorlovka have extreme mercury contents of 12.8 to 25.5 ppm. This coal was formerly produced as a byproduct of extracting sandstone-hosted cinnabar ore. Access to these workings is unrestricted and small amounts of extreme mercury-rich coal are collected for domestic use, posing a limited human health hazard. More widespread hazards are posed by the abandoned Nikitovka mercury processing plant, the extensive mercury mine tailings, and mercury enrichment of soils extending into residential areas of Gorlovka.

  7. Reduction of the safety and health risk associated with the generation of dust on strip coal mine haul roads.

    CSIR Research Space (South Africa)

    Thompson, RJ

    2000-01-01

    Full Text Available mine haul roads. This would be used to identify suitable spray-on or mix-in surface treatments to reduce the generation of dust, within the constraints of cost effectiveness and maintainability, through consideration of wearing course material type...

  8. Data mining for the identification of metabolic syndrome status.

    Science.gov (United States)

    Worachartcheewan, Apilak; Schaduangrat, Nalini; Prachayasittikul, Virapong; Nantasenamat, Chanin

    2018-01-01

    Metabolic syndrome (MS) is a condition associated with metabolic abnormalities that are characterized by central obesity (e.g. waist circumference or body mass index), hypertension (e.g. systolic or diastolic blood pressure), hyperglycemia (e.g. fasting plasma glucose) and dyslipidemia (e.g. triglyceride and high-density lipoprotein cholesterol). It is also associated with the development of diabetes mellitus (DM) type 2 and cardiovascular disease (CVD). Therefore, the rapid identification of MS is required to prevent the occurrence of such diseases. Herein, we review the utilization of data mining approaches for MS identification. Furthermore, the concept of quantitative population-health relationship (QPHR) is also presented, which can be defined as the elucidation/understanding of the relationship that exists between health parameters and health status. The QPHR modeling uses data mining techniques such as artificial neural network (ANN), support vector machine (SVM), principal component analysis (PCA), decision tree (DT), random forest (RF) and association analysis (AA) for modeling and construction of predictive models for MS characterization. The DT method has been found to outperform other data mining techniques in the identification of MS status. Moreover, the AA technique has proved useful in the discovery of in-depth as well as frequently occurring health parameters that can be used for revealing the rules of MS development. This review presents the potential benefits on the applications of data mining as a rapid identification tool for classifying MS.

  9. Data mining for the identification of metabolic syndrome status

    Science.gov (United States)

    Worachartcheewan, Apilak; Schaduangrat, Nalini; Prachayasittikul, Virapong; Nantasenamat, Chanin

    2018-01-01

    Metabolic syndrome (MS) is a condition associated with metabolic abnormalities that are characterized by central obesity (e.g. waist circumference or body mass index), hypertension (e.g. systolic or diastolic blood pressure), hyperglycemia (e.g. fasting plasma glucose) and dyslipidemia (e.g. triglyceride and high-density lipoprotein cholesterol). It is also associated with the development of diabetes mellitus (DM) type 2 and cardiovascular disease (CVD). Therefore, the rapid identification of MS is required to prevent the occurrence of such diseases. Herein, we review the utilization of data mining approaches for MS identification. Furthermore, the concept of quantitative population-health relationship (QPHR) is also presented, which can be defined as the elucidation/understanding of the relationship that exists between health parameters and health status. The QPHR modeling uses data mining techniques such as artificial neural network (ANN), support vector machine (SVM), principal component analysis (PCA), decision tree (DT), random forest (RF) and association analysis (AA) for modeling and construction of predictive models for MS characterization. The DT method has been found to outperform other data mining techniques in the identification of MS status. Moreover, the AA technique has proved useful in the discovery of in-depth as well as frequently occurring health parameters that can be used for revealing the rules of MS development. This review presents the potential benefits on the applications of data mining as a rapid identification tool for classifying MS. PMID:29383020

  10. VICKEY: Mining Conditional Keys on Knowledge Bases

    OpenAIRE

    Symeonidou , Danai; Galárraga , Luis; Pernelle , Nathalie; Saïs , Fatiha; Suchanek , Fabian

    2017-01-01

    International audience; A conditional key is a key constraint that is valid in only a part of the data. In this paper, we show how such keys can be mined automatically on large knowledge bases (KBs). For this, we combine techniques from key mining with techniques from rule mining. We show that our method can scale to KBs of millions of facts. We also show that the conditional keys we mine can improve the quality of entity linking by up to 47 percentage points.

  11. Bioremediation of mine water.

    Science.gov (United States)

    Klein, Robert; Tischler, Judith S; Mühling, Martin; Schlömann, Michael

    2014-01-01

    Caused by the oxidative dissolution of sulfide minerals, mine waters are often acidic and contaminated with high concentrations of sulfates, metals, and metalloids. Because the so-called acid mine drainage (AMD) affects the environment or poses severe problems for later use, treatment of these waters is required. Therefore, various remediation strategies have been developed to remove soluble metals and sulfates through immobilization using physical, chemical, and biological approaches. Conventionally, iron and sulfate-the main pollutants in mine waters-are removed by addition of neutralization reagents and subsequent chemical iron oxidation and sulfate mineral precipitation. Biological treatment strategies take advantage of the ability of microorganisms that occur in mine waters to metabolize iron and sulfate. As a rule, these can be grouped into oxidative and reductive processes, reflecting the redox state of mobilized iron (reduced form) and sulfur (oxidized form) in AMD. Changing the redox states of iron and sulfur results in iron and sulfur compounds with low solubility, thus leading to their precipitation and removal. Various techniques have been developed to enhance the efficacy of these microbial processes, as outlined in this review.

  12. Environmental effects of uranium exploration and mining

    International Nuclear Information System (INIS)

    Tibbs, N.H.; Rath, D.L.; Donovan, T.K.

    1977-01-01

    Uranium exploration and mining is increasing as the Nation's demand for energy grows. The environmental impacts associated with this exploration and mining are not severe and compare favorably with impacts from the production of other energy resources

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

    Science.gov (United States)

    Sridhar, S

    2013-09-01

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

  14. 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

  15. TSCA Chemical Data Reporting Fact Sheet: Reporting Manufactured Chemical Substances from Metal Mining and Related Activities

    Science.gov (United States)

    This fact sheet provides guidance on the Chemical Data Reporting (CDR) rule requirements related to the reporting of mined metals, intermediates, and byproducts manufactured during metal mining and related activities.

  16. Potential use of Pseudomonas koreensis AGB-1 in association with Miscanthus sinensis to remediate heavy metal(loid)-contaminated mining site soil.

    Science.gov (United States)

    Babu, A Giridhar; Shea, Patrick J; Sudhakar, D; Jung, Ik-Boo; Oh, Byung-Taek

    2015-03-15

    Endophytic bacteria have the potential to promote plant growth and heavy metal(loid) (HM) removal from contaminated soil. Pseudomonas koreensis AGB-1, isolated from roots of Miscanthus sinensis growing in mine-tailing soil, exhibited high tolerance to HMs and plant growth promoting traits. Transmission electron microscope (TEM) analysis revealed that AGB-1 sequestered HMs extracellularly and their accumulation was visible as dark metal complexes on bacterial surfaces and outside of the cells. DNA sequencing of HM resistance marker genes indicated high homology to the appropriate regions of the arsB, ACR3(1), aoxB, and bmtA determinants. Inoculating mining site soil with AGB-1 increased M. sinensis biomass by 54%, chlorophyll by 27%, and protein content by 28%. High superoxide dismutase and catalase activities, and the lower malondialdehyde content of plants growing in AGB-1-inoculated soil indicate reduced oxidative stress. Metal(loid) concentrations in roots and shoots of plants grown in inoculated soil were higher than those of the controls in pot trials with mine tailing soil. Results suggest that AGB-1 can be used in association with M. sinensis to promote phytostabilization and remediation of HM-contaminated sites. Copyright © 2015 Elsevier Ltd. All rights reserved.

  17. Characterization of bacterial diversity associated with calcareous deposits and drip-waters, and isolation of calcifying bacteria from two Colombian mines.

    Science.gov (United States)

    García G, Mariandrea; Márquez G, Marco Antonio; Moreno H, Claudia Ximena

    2016-01-01

    Bacterial carbonate precipitation has implications in geological processes and important biotechnological applications. Bacteria capable of precipitating carbonates have been isolated from different calcium carbonate deposits (speleothems) in caves, soil, freshwater and seawater around the world. However, the diversity of bacteria from calcareous deposits in Colombia, and their ability to precipitate carbonates, remains unknown. In this study, conventional microbiological methods and molecular tools, such as temporal temperature gradient electrophoresis (TTGE), were used to assess the composition of bacterial communities associated with carbonate deposits and drip-waters from two Colombian mines. A genetic analysis of these bacterial communities revealed a similar level of diversity, based on the number of bands detected using TTGE. The dominant phylogenetic affiliations of the bacteria, determined using 16S rRNA gene sequencing, were grouped into two phyla: Proteobacteria and Firmicutes. Within these phyla, seven genera were capable of precipitating calcium carbonates: Lysinibacillus, Bacillus, Strenotophomonas, Brevibacillus, Methylobacterium, Aeromicrobium and Acinetobacter. FTIR and SEM/EDX were used to analyze calcium carbonate crystals produced by isolated Acinetobacter gyllenbergii. The results showed that rhombohedral and angular calcite crystals with sizes of 90μm were precipitated. This research provides information regarding the presence of complex bacterial communities in secondary carbonate deposits from mines and their ability to precipitate calcium carbonate from calcareous deposits of Colombian mines. Copyright © 2015 Elsevier GmbH. All rights reserved.

  18. Alleviation of environmental risks associated with severely contaminated mine tailings using amendments: Modeling of trace element speciation, solubility, and plant accumulation.

    Science.gov (United States)

    Pardo, Tania; Bes, Cleménce; Bernal, Maria Pilar; Clemente, Rafael

    2016-11-01

    Tailings are considered one of the most relevant sources of contamination associated with mining activities. Phytostabilization of mine spoils may need the application of the adequate combination of amendments to facilitate plant establishment and reduce their environmental impact. Two pot experiments were set up to assess the capability of 2 inorganic materials (calcium carbonate and a red mud derivate, ViroBind TM ), alone or in combination with organic amendments, for the stabilization of highly acidic trace element-contaminated mine tailings using Atriplex halimus. The effects of the treatments on tailings and porewater physico-chemical properties and trace-element accumulation by the plants, as well as the processes governing trace elements speciation and solubility in soil solution and their bioavailability were modeled. The application of the amendments increased tailings pH and decreased (>99%) trace elements solubility in porewater, but also changed the speciation of soluble Cd, Cu, and Pb. All the treatments made A. halimus growth in the tailings possible; organic amendments increased plant biomass and nutritional status, and reduced trace-element accumulation in the plants. Tailings amendments modified trace-element speciation in porewater (favoring the formation of chlorides and/or organo-metallic forms) and their solubility and plant uptake, which were found to be mainly governed by tailing/porewater pH, electrical conductivity, and organic carbon content, as well as soluble/available trace-element concentrations. Environ Toxicol Chem 2016;35:2874-2884. © 2016 SETAC. © 2016 SETAC.

  19. Textual Data Mining Applications in the Service Chain Knowledge Management of e-Government

    Directory of Open Access Journals (Sweden)

    Jalal Rezaeenour

    2017-03-01

    Full Text Available Systems related to knowledge management can improve quality and efficiency of knowledge used for decision making process. Approximately 80 percent of corporate information are in textual data formats. That is why text mining is useful and important in service chain knowledge management. For example, one of the most important applications of text mining is in managing on-line source of digital documents and the analysis of internal documents. This research is based on text-based documents and textual information and interviews processed by Grounded theory. In this research clustering techniques were applied at first step. In the second step, Apriori association rules techniques for discovering and extracting the most useful association rules were applied. In other words, integration of datamining techniques was emphasized to improve the accuracy and precision of classification. Using decision tree technique for classification may result in reducing classification precision. But, the proposed method showed a significant improvement in classification precision.

  20. Multielement determination in orange juice by ICP-MS associated with data mining for the classification of organic samples

    Directory of Open Access Journals (Sweden)

    Christian Turra

    2017-09-01

    Full Text Available The aim of this study was to discriminate organic from conventional orange juice based on chemical elements and data mining applications. A comprehensive sampling of organic and conventional oranges was carried out in Borborema, state of São Paulo, Brazil. The fruits of the variety Valencia (Citrus sinensis (L. Osbeck budded on Rangpur lime (Citrus limonia Osbeck were analyzed. Eleven chemical elements were determined in 57 orange samples grown in organic and conventional systems. In order to classify these samples, data mining techniques (Support Vector Machine (SVM and Multilayer Perceptron (MLP were combined with feature selection (F-score and chi-squared. SVM with chi-squared had a better performance compared with the other techniques because it reached 93.00% accuracy using only seven chemical components (Cu, Cs, Zn, Al, Mn, Rb and Sr, and correctly classified 96.73% of the samples grown in an organic system.

  1. Habitat use and food habits of snowshoe hares associated with a reclaimed strip mine in interior Alaska

    International Nuclear Information System (INIS)

    Elliott, C.L.

    1998-01-01

    The value of reclaimed coal stripmine spoils as snowshoe hare (Lepus americanus) habitat in interior Alaska was examined. Hare density in 3 cover types (tall shrub, conifer forest, revegetated lands) was determined using the pellet plot method. Hare food habits were determined via microhistological examination of fecal material. Snowshoe hares used the tall shrub cover type more than any other habitat examined. Hare density in the shrub zone was 10/ha in winter and 18/ha in summer. Shrubs (mainly willow species) comprised the major portion of the summer diet (69%), while spruce made up 51% of the winter diet. Based on dietary data and habitat use, the long-term loss of coniferous forests and tall shrubs due to mining, and the lack of emphasis on the re-establishment of woody vegetation in present reclamation procedures; will greatly reduce and possibly eliminate snowshoe hare populations on large-scale surface coal mines in the northern boreal regions

  2. Radioactivity and metal concentrations in marine sediments associated with mining activities in Ierissos Gulf, North Aegean Sea, Greece

    International Nuclear Information System (INIS)

    Pappa, F.K.; Tsabaris, C.; Ioannidou, A.; Patiris, D.L.; Kaberi, H.; Pashalidis, I.; Eleftheriou, G.; Androulakaki, E.G.; Vlastou, R.

    2016-01-01

    Marine sediment samples were collected from Ierissos Gulf, N Aegean Sea, close to the coastal mining facilities. Measurements of radionuclide and metal concentrations, mineral composition and grain size distribution were performed. The concentrations of "2"2"6Ra, "2"3"5U and trace metals showed enhanced values in the port of Stratoni compared with those obtained near to Ierissos port. The dose rates received by marine biota were also calculated by the ERICA Assessment Tool and the results indicated no significant radiological risk. - Highlights: • Baseline information of radionuclides in a coastal area near a mining site. • Trace metals measurements in marine sediment. • Dose rates assessment for marine biota using ERICA Assessment Tool.

  3. Uranium and Associated Heavy Metals in Ovis aries in a Mining Impacted Area in Northwestern New Mexico.

    Science.gov (United States)

    Samuel-Nakamura, Christine; Robbins, Wendie A; Hodge, Felicia S

    2017-07-28

    The objective of this study was to determine uranium (U) and other heavy metal (HM) concentrations (As, Cd, Pb, Mo, and Se) in tissue samples collected from sheep ( Ovis aries ), the primary meat staple on the Navajo reservation in northwestern New Mexico. The study setting was a prime target of U mining, where more than 1100 unreclaimed abandoned U mines and structures remain. The forage and water sources for the sheep in this study were located within 3.2 km of abandoned U mines and structures. Tissue samples from sheep ( n = 3), their local forage grasses ( n = 24), soil ( n = 24), and drinking water ( n = 14) sources were collected. The samples were analyzed using Inductively Coupled Plasma-Mass Spectrometry. Results: In general, HMs concentrated more in the roots of forage compared to the above ground parts. The sheep forage samples fell below the National Research Council maximum tolerable concentration (5 mg/kg). The bioaccumulation factor ratio was >1 in several forage samples, ranging from 1.12 to 16.86 for Mo, Cd, and Se. The study findings showed that the concentrations of HMs were greatest in the liver and kidneys. Of the calculated human intake, Se Reference Dietary Intake and Mo Recommended Dietary Allowance were exceeded, but the tolerable upper limits for both were not exceeded. Food intake recommendations informed by research are needed for individuals especially those that may be more sensitive to HMs. Further study with larger sample sizes is needed to explore other impacted communities across the reservation.

  4. On Intensive Late Holocene Iron Mining and Production in the Northern Congo Basin and the Environmental Consequences Associated with Metallurgy in Central Africa

    Science.gov (United States)

    Lupo, Karen D.; Schmitt, Dave N.; Kiahtipes, Christopher A.; Ndanga, Jean-Paul; Young, D. Craig; Simiti, Bernard

    2015-01-01

    An ongoing question in paleoenvironmental reconstructions of the central African rainforest concerns the role that prehistoric metallurgy played in shaping forest vegetation. Here we report evidence of intensive iron-ore mining and smelting in forested regions of the northern Congo Basin dating to the late Holocene. Volumetric estimates on extracted iron-ore and associated slag mounds from prehistoric sites in the southern Central African Republic suggest large-scale iron production on par with other archaeological and historically-known iron fabrication areas. These data document the first evidence of intensive iron mining and production spanning approximately 90 years prior to colonial occupation (circa AD 1889) and during an interval of time that is poorly represented in the archaeological record. Additional site areas pre-dating these remains by 3-4 centuries reflect an earlier period of iron production on a smaller scale. Microbotanical evidence from a sediment core collected from an adjacent riparian trap shows a reduction in shade-demanding trees in concert with an increase in light-demanding species spanning the time interval associated with iron intensification. This shift occurs during the same time interval when many portions of the Central African witnessed forest transgressions associated with a return to moister and more humid conditions beginning 500-100 years ago. Although data presented here do not demonstrate that iron smelting activities caused widespread vegetation change in Central Africa, we argue that intense mining and smelting can have localized and potentially regional impacts on vegetation communities. These data further demonstrate the high value of pairing archeological and paleoenvironmental analyses to reconstruct regional-scale forest histories. PMID:26161540

  5. On Intensive Late Holocene Iron Mining and Production in the Northern Congo Basin and the Environmental Consequences Associated with Metallurgy in Central Africa.

    Science.gov (United States)

    Lupo, Karen D; Schmitt, Dave N; Kiahtipes, Christopher A; Ndanga, Jean-Paul; Young, D Craig; Simiti, Bernard

    2015-01-01

    An ongoing question in paleoenvironmental reconstructions of the central African rainforest concerns the role that prehistoric metallurgy played in shaping forest vegetation. Here we report evidence of intensive iron-ore mining and smelting in forested regions of the northern Congo Basin dating to the late Holocene. Volumetric estimates on extracted iron-ore and associated slag mounds from prehistoric sites in the southern Central African Republic suggest large-scale iron production on par with other archaeological and historically-known iron fabrication areas. These data document the first evidence of intensive iron mining and production spanning approximately 90 years prior to colonial occupation (circa AD 1889) and during an interval of time that is poorly represented in the archaeological record. Additional site areas pre-dating these remains by 3-4 centuries reflect an earlier period of iron production on a smaller scale. Microbotanical evidence from a sediment core collected from an adjacent riparian trap shows a reduction in shade-demanding trees in concert with an increase in light-demanding species spanning the time interval associated with iron intensification. This shift occurs during the same time interval when many portions of the Central African witnessed forest transgressions associated with a return to moister and more humid conditions beginning 500-100 years ago. Although data presented here do not demonstrate that iron smelting activities caused widespread vegetation change in Central Africa, we argue that intense mining and smelting can have localized and potentially regional impacts on vegetation communities. These data further demonstrate the high value of pairing archeological and paleoenvironmental analyses to reconstruct regional-scale forest histories.

  6. 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.

  7. 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.

  8. Reclamation of slopes left after surface mining

    Energy Technology Data Exchange (ETDEWEB)

    Zmitko, J [Banske Projekty, Teplice (Czech Republic)

    1993-03-01

    Discusses land reclamation of abandoned slopes from brown coal surface mining in the North Bohemian brown coal basin in the Czech Republic. Problems associated with reclamation of landslide areas in two former coal mines are evaluated: the Otokar mine in Kostany (mining from 1956 to 1966) and the CSM mine in Pozorka (mining from 1955 to 1967). Land reclamation was introduced 25 years after damage occurred. The following aspects are analyzed: hydrogeologic conditions, range of landslides, types of rocks in landslide areas, water conditions, methods for stabilizing slopes, safety aspects.

  9. Comparison of Heuristics for Inhibitory Rule Optimization

    KAUST Repository

    Alsolami, Fawaz

    2014-09-13

    Knowledge representation and extraction are very important tasks in data mining. In this work, we proposed a variety of rule-based greedy algorithms that able to obtain knowledge contained in a given dataset as a series of inhibitory rules containing an expression “attribute ≠ value” on the right-hand side. The main goal of this paper is to determine based on rule characteristics, rule length and coverage, whether the proposed rule heuristics are statistically significantly different or not; if so, we aim to identify the best performing rule heuristics for minimization of rule length and maximization of rule coverage. Friedman test with Nemenyi post-hoc are used to compare the greedy algorithms statistically against each other for length and coverage. The experiments are carried out on real datasets from UCI Machine Learning Repository. For leading heuristics, the constructed rules are compared with optimal ones obtained based on dynamic programming approach. The results seem to be promising for the best heuristics: the average relative difference between length (coverage) of constructed and optimal rules is at most 2.27% (7%, respectively). Furthermore, the quality of classifiers based on sets of inhibitory rules constructed by the considered heuristics are compared against each other, and the results show that the three best heuristics from the point of view classification accuracy coincides with the three well-performed heuristics from the point of view of rule length minimization.

  10. Education Roadmap for Mining Professionals

    Energy Technology Data Exchange (ETDEWEB)

    none,

    2002-12-01

    This document represents the roadmap for education in the U.S. mining industry. It was developed based on the results of an Education Roadmap Workshop sponsored by the National Mining Association in conjunction with the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Office of Industrial Technologies. The Workshop was held February 23, 2002 in Phoenix, Arizona.

  11. A cross-sectional survey on knowledge and perceptions of health risks associated with arsenic and mercury contamination from artisanal gold mining in Tanzania.

    Science.gov (United States)

    Charles, Elias; Thomas, Deborah S K; Dewey, Deborah; Davey, Mark; Ngallaba, Sospatro E; Konje, Eveline

    2013-01-25

    An estimated 0.5 to 1.5 million informal miners, of whom 30-50% are women, rely on artisanal mining for their livelihood in Tanzania. Mercury, used in the processing gold ore, and arsenic, which is a constituent of some ores, are common occupational exposures that frequently result in widespread environmental contamination. Frequently, the mining activities are conducted haphazardly without regard for environmental, occupational, or community exposure. The primary objective of this study was to assess community risk knowledge and perception of potential mercury and arsenic toxicity and/or exposure from artisanal gold mining in Rwamagasa in northwestern Tanzania. A cross-sectional survey of respondents in five sub-villages in the Rwamagasa Village located in Geita District in northwestern Tanzania near Lake Victoria was conducted. This area has a history of artisanal gold mining and many of the population continue to work as miners. Using a clustered random selection approach for recruitment, a total of 160 individuals over 18 years of age completed a structured interview. The interviews revealed wide variations in knowledge and risk perceptions concerning mercury and arsenic exposure, with 40.6% (n=65) and 89.4% (n=143) not aware of the health effects of mercury and arsenic exposure respectively. Males were significantly more knowledgeable (n=59, 36.9%) than females (n=36, 22.5%) with regard to mercury (x²=3.99, pmining (n=63, 73.2%) were more knowledgeable about the negative health effects of mercury than individuals in other occupations. Of the few individuals (n=17, 10.6%) who knew about arsenic toxicity, the majority (n=10, 58.8%) were miners. The knowledge of individuals living in Rwamagasa, Tanzania, an area with a history of artisanal gold mining, varied widely with regard to the health hazards of mercury and arsenic. In these communities there was limited awareness of the threats to health associated with exposure to mercury and arsenic. This lack of

  12. Mining the bulk positron lifetime

    International Nuclear Information System (INIS)

    Aourag, H.; Guittom, A.

    2009-01-01

    We introduce a new approach to investigate the bulk positron lifetimes of new systems based on data-mining techniques. Through data mining of bulk positron lifetimes, we demonstrate the ability to predict the positron lifetimes of new semiconductors on the basis of available semiconductor data already studied. Informatics techniques have been applied to bulk positron lifetimes for different tetrahedrally bounded semiconductors in order to discover computational design rules. (copyright 2009 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim) (orig.)

  13. Mathematical tools for data mining set theory, partial orders, combinatorics

    CERN Document Server

    Simovici, Dan A

    2014-01-01

    Data mining essentially relies on several mathematical disciplines, many of which are presented in this second edition of this book. Topics include partially ordered sets, combinatorics, general topology, metric spaces, linear spaces, graph theory. To motivate the reader a significant number of applications of these mathematical tools are included ranging from association rules, clustering algorithms, classification, data constraints, logical data analysis, etc. The book is intended as a reference for researchers and graduate students. The current edition is a significant expansion of the firs

  14. DATA MINING IN EDUCATION: CURRENT STATE AND PERSPECTIVES OF DEVELOPMENT

    Directory of Open Access Journals (Sweden)

    Yurii O. Kovalchuk

    2016-01-01

    Full Text Available The main tasks (classification and regression, association rules, clustering and the basic principles of the Data Mining algorithms in the context of their use for a variety of research in the field of education which are the subject of a relatively new independent direction Educational Data Mining are considered. The findings about the most popular topics of research within this area as well as the perspectives of its development are presented. Presentation of the material is illustrated by simple examples. This article is intended for readers who are engaged in research in the field of education at various levels, especially those involved in the use of e-learning systems, but little familiar with this area of data analysis.

  15. Uranium and Associated Heavy Metals in Ovis aries in a Mining Impacted Area in Northwestern New Mexico

    Directory of Open Access Journals (Sweden)

    Christine Samuel-Nakamura

    2017-07-01

    Full Text Available The objective of this study was to determine uranium (U and other heavy metal (HM concentrations (As, Cd, Pb, Mo, and Se in tissue samples collected from sheep (Ovis aries, the primary meat staple on the Navajo reservation in northwestern New Mexico. The study setting was a prime target of U mining, where more than 1100 unreclaimed abandoned U mines and structures remain. The forage and water sources for the sheep in this study were located within 3.2 km of abandoned U mines and structures. Tissue samples from sheep (n = 3, their local forage grasses (n = 24, soil (n = 24, and drinking water (n = 14 sources were collected. The samples were analyzed using Inductively Coupled Plasma-Mass Spectrometry. Results: In general, HMs concentrated more in the roots of forage compared to the above ground parts. The sheep forage samples fell below the National Research Council maximum tolerable concentration (5 mg/kg. The bioaccumulation factor ratio was >1 in several forage samples, ranging from 1.12 to 16.86 for Mo, Cd, and Se. The study findings showed that the concentrations of HMs were greatest in the liver and kidneys. Of the calculated human intake, Se Reference Dietary Intake and Mo Recommended Dietary Allowance were exceeded, but the tolerable upper limits for both were not exceeded. Food intake recommendations informed by research are needed for individuals especially those that may be more sensitive to HMs. Further study with larger sample sizes is needed to explore other impacted communities across the reservation.

  16. Radioactivity and metal concentrations in marine sediments associated with mining activities in Ierissos Gulf, North Aegean Sea, Greece.

    Science.gov (United States)

    Pappa, F K; Tsabaris, C; Ioannidou, A; Patiris, D L; Kaberi, H; Pashalidis, I; Eleftheriou, G; Androulakaki, E G; Vlastou, R

    2016-10-01

    Marine sediment samples were collected from Ierissos Gulf, N Aegean Sea, close to the coastal mining facilities. Measurements of radionuclide and metal concentrations, mineral composition and grain size distribution were performed. The concentrations of (226)Ra, (235)U and trace metals showed enhanced values in the port of Stratoni compared with those obtained near to Ierissos port. The dose rates received by marine biota were also calculated by the ERICA Assessment Tool and the results indicated no significant radiological risk. Copyright © 2016 Elsevier Ltd. All rights reserved.

  17. Environmental problems associated with blasting in mines: public apprehensions of damage due to blast vibrations - case studies

    Energy Technology Data Exchange (ETDEWEB)

    Padhi, S.N. [DGMS, Bhubaneswar (India)

    1994-12-31

    Blast vibrations may be felt in intensities as small as 1/100 of that required to cause any damage to structures. Therefore, the public response and thus complaints regarding damages are often imaginary. The paper deals with three case studies, involving alleged damage from blasting in surface and underground coal mines where public litigations and agitations resulted due to such apprehensions. The paper is written in simple technical language as the situations warranted that the blast vibration studies should be understood by the general public. 7 tabs.

  18. Data mining applications in healthcare.

    Science.gov (United States)

    Koh, Hian Chye; Tan, Gerald

    2005-01-01

    Data mining has been used intensively and extensively by many organizations. In healthcare, data mining is becoming increasingly popular, if not increasingly essential. Data mining applications can greatly benefit all parties involved in the healthcare industry. For example, data mining can help healthcare insurers detect fraud and abuse, healthcare organizations make customer relationship management decisions, physicians identify effective treatments and best practices, and patients receive better and more affordable healthcare services. The huge amounts of data generated by healthcare transactions are too complex and voluminous to be processed and analyzed by traditional methods. Data mining provides the methodology and technology to transform these mounds of data into useful information for decision making. This article explores data mining applications in healthcare. In particular, it discusses data mining and its applications within healthcare in major areas such as the evaluation of treatment effectiveness, management of healthcare, customer relationship management, and the detection of fraud and abuse. It also gives an illustrative example of a healthcare data mining application involving the identification of risk factors associated with the onset of diabetes. Finally, the article highlights the limitations of data mining and discusses some future directions.

  19. Survey of wildlife, including aquatic mammals, associated with riparian habitat on the Syncrude Canada Ltd. Aurora Mine environmental impact assessment local study area

    Energy Technology Data Exchange (ETDEWEB)

    Surrendi, D.C.

    1996-12-31

    A general overview of the wildlife associated with riparian habitats at Syncrude`s proposed Aurora Mine, located 70 km northeast of Fort McMurray, Alberta on the east side of the Athabasca River, was presented. The area is underlain by bitumen and is being considered for bitumen extraction and production of synthetic crude oil. Two surveys were conducted with the help of experienced trappers from the community at Fort McKay. One was an aerial survey on November 3, 1995, the other a ground survey on November 29-30, 1995. The two surveys yielded 248 observed tracks on four 500 metre transects. The study area was comprised of boreal forest with natural drainage via Stanley Creek into the Muskeg River and via Fort Creek into the Athabasca River. Beavers, fox, weasel, mink, rabbit, wolf, moose, deer, ptarmigan, sharp-tailed grouse and ruffed grouse, lynx, coyote, river otter and mice were associated with riparian habitat on the study area. There was no sign of muskrat in the study area. It was concluded that in order to develop an understanding of reclamation alternatives for mined areas in the region, future detailed examination of the site should be approached through the integration of traditional ecological knowledge and conventional scientific methodology. 26 refs., 12 tabs., 2 figs.

  20. Survey of wildlife, including aquatic mammals, associated with riparian habitat on the Syncrude Canada Ltd. Aurora Mine environmental impact assessment local study area

    International Nuclear Information System (INIS)

    Surrendi, D.C.

    1996-01-01

    A general overview of the wildlife associated with riparian habitats at Syncrude's proposed Aurora Mine, located 70 km northeast of Fort McMurray, Alberta on the east side of the Athabasca River, was presented. The area is underlain by bitumen and is being considered for bitumen extraction and production of synthetic crude oil. Two surveys were conducted with the help of experienced trappers from the community at Fort McKay. One was an aerial survey on November 3, 1995, the other a ground survey on November 29-30, 1995. The two surveys yielded 248 observed tracks on four 500 metre transects. The study area was comprised of boreal forest with natural drainage via Stanley Creek into the Muskeg River and via Fort Creek into the Athabasca River. Beavers, fox, weasel, mink, rabbit, wolf, moose, deer, ptarmigan, sharp-tailed grouse and ruffed grouse, lynx, coyote, river otter and mice were associated with riparian habitat on the study area. There was no sign of muskrat in the study area. It was concluded that in order to develop an understanding of reclamation alternatives for mined areas in the region, future detailed examination of the site should be approached through the integration of traditional ecological knowledge and conventional scientific methodology. 26 refs., 12 tabs., 2 figs

  1. Contextual Text Mining

    Science.gov (United States)

    Mei, Qiaozhu

    2009-01-01

    With the dramatic growth of text information, there is an increasing need for powerful text mining systems that can automatically discover useful knowledge from text. Text is generally associated with all kinds of contextual information. Those contexts can be explicit, such as the time and the location where a blog article is written, and the…

  2. The association between social stressors and home smoking rules among women with infants in the United States.

    Science.gov (United States)

    Saint Onge, Jarron M; Gurley-Calvez, Tami; Orth, Teresa A; Okah, Felix A

    2014-12-01

    We examined the role of social stressors on home-smoking rules (HSRs) among women with infants in the United States, with attention on the moderating role of smoking status and depression. We analyzed data for 118 062 women with recent births in the United States who participated in the Pregnancy Risk Assessment Monitoring System (2004-2010), which is a population-based surveillance data set. We fit multinomial logistic models to predict the odds of partial or no HSRs by a cumulative index of prenatal social stressors. Compared with those with no stressors, mothers with high levels of social stressors had 2.5 times higher odds of partial or no HSRs. Smokers in the 1-2, 3-5, and ≥ 6 stressor categories were 9.0%, 9.6%, and 10.8% more likely to have partial or no HSRs, respectively. Under the highest levels of stress (≥ 6), nonsmokers were almost as likely as smokers to have partial or no HSRs. In addition, the effects of stress on HSRs were more pronounced for nonsmoker, nondepressed mothers. Increases in social stressors represented an important risk factor for partial or no HSRs and might have potential negative implications for infants.

  3. Soil heavy metal pollution and risk assessment associated with the Zn-Pb mining region in Yunnan, Southwest China.

    Science.gov (United States)

    Cheng, Xianfeng; Danek, Tomas; Drozdova, Jarmila; Huang, Qianrui; Qi, Wufu; Zou, Liling; Yang, Shuran; Zhao, Xinliang; Xiang, Yungang

    2018-03-07

    The environmental assessment and identification of sources of heavy metals in Zn-Pb ore deposits are important steps for the effective prevention of subsequent contamination and for the development of corrective measures. The concentrations of eight heavy metals (As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn) in soils from 40 sampling points around the Jinding Zn-Pb mine in Yunnan, China, were analyzed. An environmental quality assessment of the obtained data was performed using five different contamination and pollution indexes. Statistical analyses were performed to identify the relations among the heavy metals and the pH in soils and possible sources of pollution. The concentrations of As, Cd, Pb, and Zn were extremely high, and 23, 95, 25, and 35% of the samples, respectively, exceeded the heavy metal limits set in the Chinese Environmental Quality Standard for Soils (GB15618-1995, grade III). According to the contamination and pollution indexes, environmental risks in the area are high or extremely high. The highest risk is represented by Cd contamination, the median concentration of which exceeds the GB15618-1995 limit. Based on the combination of statistical analyses and geostatistical mapping, we identified three groups of heavy metals that originate from different sources. The main sources of As, Cd, Pb, Zn, and Cu are mining activities, airborne particulates from smelters, and the weathering of tailings. The main sources of Hg are dust fallout and gaseous emissions from smelters and tailing dams. Cr and Ni originate from lithogenic sources.

  4. Mine-induced seismicity at East-Rand proprietary mines

    CSIR Research Space (South Africa)

    Milev, AM

    1995-09-01

    Full Text Available Mining results in seismic activity of varying intensity, from small micro seismic events to larger seismic events, often associated with significant seismic induced damages. This work deals with the understanding of the present seismicity...

  5. Mining Association Rules Between Credits in the Leadership in Energy and Environmental Design for New Construction (LEED-NC) Green Building Assessment System

    National Research Council Canada - National Science Library

    Thomas, Benjamin J

    2008-01-01

    The Leadership in Energy and Environmental Design (LEED) Building Assessment System is a performance-based tool for determining the environmental impact of a facility from the whole-building perspective...

  6. Mining Association Rules Between Credits in the Leadership in Energy and Environmental Design for New Construction (LEED-NC) Green Building Assessment System

    National Research Council Canada - National Science Library

    Thomas, Benjamin J

    2008-01-01

    .... Taking this vision into account, the individual credits that comprise LEED are designed to reward design teams for employing sustainable design strategies that reduce the total environmental impact...

  7. 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).

  8. Employee motivation and work performance: A comparative study of mining companies in Ghana

    Energy Technology Data Exchange (ETDEWEB)

    Kuranchie-Mensah, E.; Amponsah-Tawiah, K.

    2016-07-01

    The paper empirically compares employee motivation and its impact on performance in Ghanaian Mining Companies, where in measuring performance, the job satisfaction model is used. The study employed exploratory research design in gathering data from four large-scale Gold mining companies in Ghana with regards to their policies and structures in the effectiveness of motivational tools and strategies used by these companies. The study observed that, due to the risk factors associated with the mining industry, management has to ensure that employees are well motivated to curb the rate at which employees embark on industrial unrest which affect performance, and employees are to comply with health and safety rules because the industry contribute hugely to the Gross Domestic Product (GDP) of the country. Limitation to the present study include the researcher’s inability to contact other mining companies. However, the study suggests possibilities for future research including contacting other mining companies, expanding the sample size, managers ensuring that the safety and health needs of staff are addressed particularly those exposed to toxic and harmful chemicals. A lot of studies have been done on mining companies in the past. This paper fills a gap perceived that employees in this sector are highly motivated in spite of the challenges being faced by them, and knowing more about what keeps employees moving is still of national interest. (Author)

  9. Employee motivation and work performance: A comparative study of mining companies in Ghana

    Directory of Open Access Journals (Sweden)

    Elizabeth Boye Kuranchie-Mensah

    2016-04-01

    Full Text Available Purpose: The paper empirically compares employee motivation and its impact on performance in Ghanaian Mining Companies, where in measuring performance, the job satisfaction model is used. Design/methodology/approach: The study employed exploratory research design in gathering data from four large-scale Gold mining companies in Ghana with regards to their policies and structures in the effectiveness of motivational tools and strategies used by these companies. Findings: The study observed that, due to the risk factors associated with the mining industry, management has to ensure that employees are well motivated to curb the rate at which employees embark on industrial unrest which affect performance, and employees are to comply with health and safety rules because the industry contribute hugely to the Gross Domestic Product (GDP of the country. Research Limitations/Implications: Limitation to the present study include the researcher’s inability to contact other mining companies. However, the study suggests possibilities for future research including contacting other mining companies, expanding the sample size, managers ensuring that the safety and health needs of staff are addressed particularly those exposed to toxic and harmful chemicals. Originality/Value: A lot of studies have been done on mining companies in the past. This paper fills a gap perceived that employees in this sector are highly motivated in spite of the challenges being faced by them, and knowing more about what keeps employees moving is still of national interest.

  10. Educational Data Mining Application for Estimating Students Performance in Weka Environment

    Science.gov (United States)

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

    2017-11-01

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

  11. Employee motivation and work performance: A comparative study of mining companies in Ghana

    International Nuclear Information System (INIS)

    Kuranchie-Mensah, E.; Amponsah-Tawiah, K.

    2016-01-01

    The paper empirically compares employee motivation and its impact on performance in Ghanaian Mining Companies, where in measuring performance, the job satisfaction model is used. The study employed exploratory research design in gathering data from four large-scale Gold mining companies in Ghana with regards to their policies and structures in the effectiveness of motivational tools and strategies used by these companies. The study observed that, due to the risk factors associated with the mining industry, management has to ensure that employees are well motivated to curb the rate at which employees embark on industrial unrest which affect performance, and employees are to comply with health and safety rules because the industry contribute hugely to the Gross Domestic Product (GDP) of the country. Limitation to the present study include the researcher’s inability to contact other mining companies. However, the study suggests possibilities for future research including contacting other mining companies, expanding the sample size, managers ensuring that the safety and health needs of staff are addressed particularly those exposed to toxic and harmful chemicals. A lot of studies have been done on mining companies in the past. This paper fills a gap perceived that employees in this sector are highly motivated in spite of the challenges being faced by them, and knowing more about what keeps employees moving is still of national interest. (Author)

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

    Science.gov (United States)

    Zhou, Lijuan; Wu, Minhua; Li, Shuang

    2009-04-01

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

  13. 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...

  14. Implementasi Data Warehouse dan Data Mining: Studi Kasus Analisis Peminatan Studi Siswa

    Directory of Open Access Journals (Sweden)

    Eka Miranda

    2011-06-01

    Full Text Available This paper discusses the implementation of data mining and their role in helping decision-making related to students’ specialization program selection. Currently, the university uses a database to store records of transactions which can not directly be used to assist analysis and decision making. Based on these issues then made the data warehouse design used to store large amounts of data and also has the potential to gain new data distribution perspectives and allows to answer the ad hoc question as well as to perform data analysis. The method used consists of: record analysis related to students’ academic achievement, designing data warehouse and data mining. The paper’s results are in a form of data warehouse and data mining design and its implementation with the classification techniques and association rules. From these results can be seen the students’ tendency and pattern background in choosing the specialization, to help them make decisions. 

  15. 77 FR 20700 - Examinations of Work Areas in Underground Coal Mines for Violations of Mandatory Health or Safety...

    Science.gov (United States)

    2012-04-06

    ... DEPARTMENT OF LABOR Mine Safety and Health Administration 30 CFR Part 75 RIN 1219-AB75 Examinations of Work Areas in Underground Coal Mines for Violations of Mandatory Health or Safety Standards AGENCY: Mine Safety and Health Administration, Labor. ACTION: Final rule. SUMMARY: The Mine Safety and...

  16. 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...

  17. When process mining meets bioinformatics

    NARCIS (Netherlands)

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

    2011-01-01

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

  18. Prediction of users webpage access behaviour using association ...

    Indian Academy of Sciences (India)

    pages mainly depended on the support and lift measure whereas confidence assumed ... Apriori algorithm; association rules; data mining; MSNBC; web usage .... clustering was used in finding the user access patterns from web access log. .... satisfied the minimum support and confidence of 0.6% and 100% respectively.

  19. 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

  20. 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

  1. Ectoparasites associated to two species of Corynorhinus (Chiroptera: Vespertilionidae) from the Guanaceví mining region, Durango, Mexico.

    Science.gov (United States)

    Villegas-Guzman, Gabriel A; López-González, Celia; Vargas, Margarita

    2005-03-01

    As a part of an inventory of bats in abandoned mines at the municipality of Guanaceví, Durango, Mexico, a sample of long-eared bats (genus Corynorhinus) was collected and ectoparasites were taken. Twenty-three specimens of Corynorhinus mexicanus Allen, 1916, and 18 of Corynorhinus townsendii (Cooper, 1937) were collected in four sampling periods coincident with the seasons. In total, 98 ectoparasites of 10 species and seven families were examined. Five species are recorded for the first time on C. mexicanus and four on C. townsendii. Macronyssus cyclaspis and Trichobius corynorhini had the highest frequency of infestation in both bats. Differences in number of arthropods per bat among seasons were nonsignificant for both species.

  2. Community structure of arbuscular mycorrhizal fungi associated to Veronica rechingeri at the Anguran zinc and lead mining region

    International Nuclear Information System (INIS)

    Zarei, M.; Koenig, S.; Hempel, S.; Nekouei, M. Khayam; Savaghebi, Gh.; Buscot, F.

    2008-01-01

    Root colonization and diversity of arbuscular mycorrhizal fungi (AMF) were analyzed in Veronica rechingeri growing in heavy metal (HM) and non-polluted soils of the Anguran Zn and Pb mining region (Iran). Three species could be separated morphologically, while phylogenetic analyses after PCR amplification of the ITS region followed by RFLP and sequencing revealed seven different AMF sequence types all within the genus Glomus. Rarefaction analysis confirmed exhaustive molecular characterization of the AMF diversity present within root samples. Increasing heavy metal contamination between the sites studied was accompanied by a decrease in AMF spore numbers, mycorrhizal colonization parameters and the number of AMF sequence types colonizing the roots. Some AMF sequence types were only found at sites with the highest and lowest soil HM contents, respectively. - The increase in soil heavy metal content between sites was accompanied by a decrease in mycorrhization parameters, spore numbers and AMF molecular diversity

  3. Community structure of arbuscular mycorrhizal fungi associated to Veronica rechingeri at the Anguran zinc and lead mining region

    Energy Technology Data Exchange (ETDEWEB)

    Zarei, M. [Department of Soil Science Engineering, Soil and Water Engineering Faculty, University College of Agriculture and Natural Resources, University of Tehran, Karaj (Iran, Islamic Republic of)], E-mail: mehdizarei20@yahoo.ca; Koenig, S. [UFZ Helmholtz Center for Environmental Research Leipzig-Halle Ltd, Department of Soil Ecology, Theodor-Lieser-Strasse 4, D-06120 Halle (Germany)], E-mail: stephan.koenig@ufz.de; Hempel, S. [UFZ Helmholtz Center for Environmental Research Leipzig-Halle Ltd, Department of Soil Ecology, Theodor-Lieser-Strasse 4, D-06120 Halle (Germany)], E-mail: hempel.stefan@gmail.com; Nekouei, M. Khayam [Agricultural Biotechnology Research Institute of Iran (ABRII), P.O. Box 31535-1897, Karaj (Iran, Islamic Republic of)], E-mail: Khayam@abrii.ac.ir; Savaghebi, Gh. [Department of Soil Science Engineering, Soil and Water Engineering Faculty, University College of Agriculture and Natural Resources, University of Tehran, Karaj (Iran, Islamic Republic of)], E-mail: Savagheb@ut.ac.ir; Buscot, F. [UFZ Helmholtz Center for Environmental Research Leipzig-Halle Ltd, Department of Soil Ecology, Theodor-Lieser-Strasse 4, D-06120 Halle (Germany)], E-mail: francois.buscot@ufz.de

    2008-12-15

    Root colonization and diversity of arbuscular mycorrhizal fungi (AMF) were analyzed in Veronica rechingeri growing in heavy metal (HM) and non-polluted soils of the Anguran Zn and Pb mining region (Iran). Three species could be separated morphologically, while phylogenetic analyses after PCR amplification of the ITS region followed by RFLP and sequencing revealed seven different AMF sequence types all within the genus Glomus. Rarefaction analysis confirmed exhaustive molecular characterization of the AMF diversity present within root samples. Increasing heavy metal contamination between the sites studied was accompanied by a decrease in AMF spore numbers, mycorrhizal colonization parameters and the number of AMF sequence types colonizing the roots. Some AMF sequence types were only found at sites with the highest and lowest soil HM contents, respectively. - The increase in soil heavy metal content between sites was accompanied by a decrease in mycorrhization parameters, spore numbers and AMF molecular diversity.

  4. Qualitative evaluation of environmental radiological impact in a phosphate associated uranium conventional mine: Santa Quiteria Project, CE, Brazil

    International Nuclear Information System (INIS)

    Reis, Rocio G. dos; Santo, Aline Sa E.

    2013-01-01

    The aim of this study is to identify and evaluate qualitatively the main potential sources of mineral and installation terms of Santa Quiteria, CE, Brazil, evaluating their possible impacts on the environment. The key terms sources in the production of phosphoric acid are usually: the dig of the mines, tailings dams and phospho plaster stack. Thus, this work intends to inform the academic community about this issue, as well as the population in general and also, acting proactively in order to warn about the possible environmental impacts, so that actions to compensate, minimize or avoid these radiological impacts on the environment, can be included in the planning of the industrial mineral project of Santa Quiteria (author)

  5. Collaboration rules.

    Science.gov (United States)

    Evans, Philip; Wolf, Bob

    2005-01-01

    Corporate leaders seeking to boost growth, learning, and innovation may find the answer in a surprising place: the Linux open-source software community. Linux is developed by an essentially volunteer, self-organizing community of thousands of programmers. Most leaders would sell their grandmothers for workforces that collaborate as efficiently, frictionlessly, and creatively as the self-styled Linux hackers. But Linux is software, and software is hardly a model for mainstream business. The authors have, nonetheless, found surprising parallels between the anarchistic, caffeinated, hirsute world of Linux hackers and the disciplined, tea-sipping, clean-cut world of Toyota engineering. Specifically, Toyota and Linux operate by rules that blend the self-organizing advantages of markets with the low transaction costs of hierarchies. In place of markets' cash and contracts and hierarchies' authority are rules about how individuals and groups work together (with rigorous discipline); how they communicate (widely and with granularity); and how leaders guide them toward a common goal (through example). Those rules, augmented by simple communication technologies and a lack of legal barriers to sharing information, create rich common knowledge, the ability to organize teams modularly, extraordinary motivation, and high levels of trust, which radically lowers transaction costs. Low transaction costs, in turn, make it profitable for organizations to perform more and smaller transactions--and so increase the pace and flexibility typical of high-performance organizations. Once the system achieves critical mass, it feeds on itself. The larger the system, the more broadly shared the knowledge, language, and work style. The greater individuals' reputational capital, the louder the applause and the stronger the motivation. The success of Linux is evidence of the power of that virtuous circle. Toyota's success is evidence that it is also powerful in conventional companies.

  6. Robert's rules of order

    CERN Document Server

    Robert, Henry M; Balch, Thomas J; Seabold, Daniel E; Gerber, Shmuel

    2011-01-01

    The only authorized edition of the classic work on parliamentary procedure, with new and enhanced features, including how to conduct electronic meetings. Robert's Rules of Order is the book on parliamentary procedure for parliamentarians and anyone involved in an organization, association, club, or group and the authoritative guide to smooth, orderly, and fairly conducted meetings and assemblies. This newly revised edition is the only book on parliamentary procedure to have been updated since 1876 under the continuing program of review established by General Henry M. Robert himself, in cooperation with the official publisher of Robert's Rules. The eleventh edition has been thoroughly revised to address common inquiries and incorporate new rules, interpretations, and procedures made necessary by the evolution of parliamentary procedure, including new material relating to electronic communication and "electronic meetings."

  7. artery disease guidelines with extracted knowledge from data mining

    Directory of Open Access Journals (Sweden)

    Peyman Rezaei-Hachesu

    2017-06-01

    Conclusion: Guidelines confirm the achieved results from data mining (DM techniques and help to rank important risk factors based on national and local information. Evaluation of extracted rules determined new patterns for CAD patients.

  8. The hydrogen mine introduction initiative

    Energy Technology Data Exchange (ETDEWEB)

    Betournay, M.C.; Howell, B. [Natural Resources Canada, Ottawa, ON (Canada). CANMET Mining and Mineral Sciences Laboratories

    2009-07-01

    In an effort to address air quality concerns in underground mines, the mining industry is considering the use fuel cells instead of diesel to power mine production vehicles. The immediate issues and opportunities associated with fuel cells use include a reduction in harmful greenhouse gas emissions; reduction in ventilation operating costs; reduction in energy consumption; improved health benefits; automation; and high productivity. The objective of the hydrogen mine introduction initiative (HMII) is to develop and test the range of fundamental and needed operational technology, specifications and best practices for underground hydrogen power applications. Although proof of concept studies have shown high potential for fuel cell use, safety considerations must be addressed, including hydrogen behaviour in confined conditions. This presentation highlighted the issues to meet operational requirements, notably hydrogen production; delivery and storage; mine regulations; and hydrogen behaviour underground. tabs., figs.

  9. Highly scalable and robust rule learner: performance evaluation and comparison.

    Science.gov (United States)

    Kurgan, Lukasz A; Cios, Krzysztof J; Dick, Scott

    2006-02-01

    Business intelligence and bioinformatics applications increasingly require the mining of datasets consisting of millions of data points, or crafting real-time enterprise-level decision support systems for large corporations and drug companies. In all cases, there needs to be an underlying data mining system, and this mining system must be highly scalable. To this end, we describe a new rule learner called DataSqueezer. The learner belongs to the family of inductive supervised rule extraction algorithms. DataSqueezer is a simple, greedy, rule builder that generates a set of production rules from labeled input data. In spite of its relative simplicity, DataSqueezer is a very effective learner. The rules generated by the algorithm are compact, comprehensible, and have accuracy comparable to rules generated by other state-of-the-art rule extraction algorithms. The main advantages of DataSqueezer are very high efficiency, and missing data resistance. DataSqueezer exhibits log-linear asymptotic complexity with the number of training examples, and it is faster than other state-of-the-art rule learners. The learner is also robust to large quantities of missing data, as verified by extensive experimental comparison with the other learners. DataSqueezer is thus well suited to modern data mining and business intelligence tasks, which commonly involve huge datasets with a large fraction of missing data.

  10. Relative importance of plant uptake and plant associated denitrification for removal of nitrogen from mine drainage in sub-arctic wetlands.

    Science.gov (United States)

    Hallin, Sara; Hellman, Maria; Choudhury, Maidul I; Ecke, Frauke

    2015-11-15

    Reactive nitrogen (N) species released from undetonated ammonium-nitrate based explosives used in mining or other blasting operations are an emerging environmental problem. Wetlands are frequently used to treat N-contaminated water in temperate climate, but knowledge on plant-microbial interactions and treatment potential in sub-arctic wetlands is limited. Here, we compare the relative importance of plant uptake and denitrification among five plant species commonly occurring in sub-arctic wetlands for removal of N in nitrate-rich mine drainage in northern Sweden. Nitrogen uptake and plant associated potential denitrification activity and genetic potential for denitrification based on quantitative PCR of the denitrification genes nirS, nirK, nosZI and nosZII were determined in plants growing both in situ and cultivated in a growth chamber. The growth chamber and in situ studies generated similar results, suggesting high relevance and applicability of results from growth chamber experiments. We identified denitrification as the dominating pathway for N-removal and abundances of denitrification genes were strong indicators of plant associated denitrification activity. The magnitude and direction of the effect differed among the plant species, with the aquatic moss Drepanocladus fluitans showing exceptionally high ratios between denitrification and uptake rates, compared to the other species. However, to acquire realistic estimates of N-removal potential of specific wetlands and their associated plant species, the total plant biomass needs to be considered. The species-specific plant N-uptake and abundance of denitrification genes on the root or plant surfaces were affected by the presence of other plant species, which show that both multi- and inter-trophic interactions are occurring. Future studies on N-removal potential of wetland plant species should consider how to best exploit these interactions in sub-arctic wetlands. Copyright © 2015 Elsevier Ltd. All rights

  11. Critical analysis of the Colombian mining legislation

    International Nuclear Information System (INIS)

    Vargas P, Elkin; Gonzalez S, Carmen Lucia

    2003-01-01

    The document analyses the Colombian mining legislation, Act 685 of 2001, based on the reasons expressed by the government and the miners for its conceit and approval. The document tries to determine the developments achieved by this new Mining Code considering international mining competitiveness and its adaptation to the constitutional rules about environment, indigenous communities, decentralization and sustainable development. The analysis formulates general and specific hypothesis about the proposed objectives of the reform, which are confronted with the arguments and critical evaluations of the results. Most hypothesis are not verified, thus demonstrating that the Colombian mining legislation is far from being the necessary instrument to promote mining activities, making it competitive according to international standards and adapted to the principles of sustainable development, healthy environment, community participation, ethnic minorities and regional autonomy

  12. Discovering Sentinel Rules for Business Intelligence

    Science.gov (United States)

    Middelfart, Morten; Pedersen, Torben Bach

    This paper proposes the concept of sentinel rules for multi-dimensional data that warns users when measure data concerning the external environment changes. For instance, a surge in negative blogging about a company could trigger a sentinel rule warning that revenue will decrease within two months, so a new course of action can be taken. Hereby, we expand the window of opportunity for organizations and facilitate successful navigation even though the world behaves chaotically. Since sentinel rules are at the schema level as opposed to the data level, and operate on data changes as opposed to absolute data values, we are able to discover strong and useful sentinel rules that would otherwise be hidden when using sequential pattern mining or correlation techniques. We present a method for sentinel rule discovery and an implementation of this method that scales linearly on large data volumes.

  13. Australian road rules

    Science.gov (United States)

    2009-02-01

    *These are national-level rules. Australian Road Rules - 2009 Version, Part 18, Division 1, Rule 300 "Use of Mobile Phones" describes restrictions of mobile phone use while driving. The rule basically states that drivers cannot make or receive calls ...

  14. 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.

  15. An inductive database prototype based on virtual mining views

    NARCIS (Netherlands)

    Blockeel, H.; Calders, T.; Fromont, É.; Goethals, B.; Prado, A.; Robardet, C.

    2008-01-01

    We present a prototype of an inductive database. Our system enables the user to query not only the data stored in the database but also generalizations (e.g. rules or trees) over these data through the use of virtual mining views. The mining views are relational tables that virtually contain the

  16. The Brazilian approach to dealing with problems associated to contaminated sites at conventional mining areas. A study case on the niobium industry

    International Nuclear Information System (INIS)

    Fernandes, H.M.; Pires do Rio, M.A.; Amaral, E.C.S.

    1996-01-01

    This work addresses the evaluation of the radiological environmental impacts associated to non-nuclear mining activities in Brazil. A study case on a niobium industry located at Minas Gerais State - south east region of the country - was carried out. It has been pointed out that the desliming, flotation and metallurgical operations were the main phases in radioactive wastes generation. However, the acid leaching of the ore removed large amounts of radionuclides from the host minerals (especially 226 Ra and 228 Ra) turning them out be in a more labile conditions and more available for remobilization processes. An estimated value of 0.26 mSv/y was obtained for the equivalent effective dose for an adult ingesting irrigated vegetables as a consequence of the radionuclides released with the liquid effluents. (author) 9 refs, 3 figs, 4 tabs

  17. Method of assessment of the environmental risk associated with releases of radioactive substances. Adaptation to the case of mining sites in Haute-Vienne

    International Nuclear Information System (INIS)

    Beaugelin-Seiller, K.; Garnier-Laplace, J.

    2007-01-01

    This report presents methods which aim at proposing a first quantification (screening) of the potential impact and risk of releases from mining installations at the scale of a drainage basin for a given period, and at refining the characterization of the radiological and/or chemical risk when a potential risk is revealed by the screening step. The screening method allows a parallel assessment of the radio-ecological risk (for the whole set of radionuclides belonging to the uranium family) and of the chemical risk associated with uranium. The refinement is based on the use of probabilistic methods. These approaches lead to the calculation of a deterministic risk index by comparing Predicted Environmental Concentrations (PECs) with Predicted No-Effect Concentrations (PNECs) in the same media

  18. Multiagent data warehousing and multiagent data mining for cerebrum/cerebellum modeling

    Science.gov (United States)

    Zhang, Wen-Ran

    2002-03-01

    An algorithm named Neighbor-Miner is outlined for multiagent data warehousing and multiagent data mining. The algorithm is defined in an evolving dynamic environment with autonomous or semiautonomous agents. Instead of mining frequent itemsets from customer transactions, the new algorithm discovers new agents and mining agent associations in first-order logic from agent attributes and actions. While the Apriori algorithm uses frequency as a priory threshold, the new algorithm uses agent similarity as priory knowledge. The concept of agent similarity leads to the notions of agent cuboid, orthogonal multiagent data warehousing (MADWH), and multiagent data mining (MADM). Based on agent similarities and action similarities, Neighbor-Miner is proposed and illustrated in a MADWH/MADM approach to cerebrum/cerebellum modeling. It is shown that (1) semiautonomous neurofuzzy agents can be identified for uniped locomotion and gymnastic training based on attribute relevance analysis; (2) new agents can be discovered and agent cuboids can be dynamically constructed in an orthogonal MADWH, which resembles an evolving cerebrum/cerebellum system; and (3) dynamic motion laws can be discovered as association rules in first order logic. Although examples in legged robot gymnastics are used to illustrate the basic ideas, the new approach is generally suitable for a broad category of data mining tasks where knowledge can be discovered collectively by a set of agents from a geographically or geometrically distributed but relevant environment, especially in scientific and engineering data environments.

  19. Uranium mining sites - Thematic sheets

    International Nuclear Information System (INIS)

    2009-01-01

    A first sheet proposes comments, data and key numbers about uranium extraction in France: general overview of uranium mining sites, status of waste rock and tailings after exploitation, site rehabilitation. The second sheet addresses the sources of exposure to ionizing radiations due to ancient uranium mining sites: discussion on the identification of these sources associated with these sites, properly due to mining activities or to tailings, or due to the transfer of radioactive substances towards water and to the contamination of sediments, description of the practice and assessment of radiological control of mining sites. A third sheet addresses the radiological exposure of public to waste rocks, and the dose assessment according to exposure scenarios: main exposure ways to be considered, studied exposure scenarios (passage on backfilled path and grounds, stay in buildings built on waste rocks, keeping mineralogical samples at home). The fourth sheet addresses research programmes of the IRSN on uranium and radon: epidemiological studies (performed on mine workers; on French and on European cohorts, French and European studies on the risk of lung cancer associated with radon in housing), study of the biological effects of chronic exposures. The last sheet addresses studies and expertises performed by the IRSN on ancient uranium mining sites in France: studies commissioned by public authorities, radioactivity control studies performed by the IRSN about mining sites, participation of the IRSN to actions to promote openness to civil society

  20. Improve Data Mining and Knowledge Discovery through the use of MatLab

    Science.gov (United States)

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

    2011-01-01

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