Sample records for rule mining arm

  1. CARIBIAM: constrained Association Rules using Interactive Biological IncrementAl Mining.

    PubMed

    Rahal, Imad; Rahhal, Riad; Wang, Baoying; Perrizo, William

    2008-01-01

    This paper analyses annotated genome data by applying a very central data-mining technique known as Association Rule Mining (ARM) with the aim of discovering rules and hypotheses capable of yielding deeper insights into this type of data. In the literature, ARM has been noted for producing an overwhelming number of rules. This work proposes a new technique capable of using domain knowledge in the form of queries in order to efficiently mine only the subset of the associations that are of interest to investigators in an incremental and interactive manner.

  2. Association rule mining in the US Vaccine Adverse Event Reporting System (VAERS).

    PubMed

    Wei, Lai; Scott, John

    2015-09-01

    Spontaneous adverse event reporting systems are critical tools for monitoring the safety of licensed medical products. Commonly used signal detection algorithms identify disproportionate product-adverse event pairs and may not be sensitive to more complex potential signals. We sought to develop a computationally tractable multivariate data-mining approach to identify product-multiple adverse event associations. We describe an application of stepwise association rule mining (Step-ARM) to detect potential vaccine-symptom group associations in the US Vaccine Adverse Event Reporting System. Step-ARM identifies strong associations between one vaccine and one or more adverse events. To reduce the number of redundant association rules found by Step-ARM, we also propose a clustering method for the post-processing of association rules. In sample applications to a trivalent intradermal inactivated influenza virus vaccine and to measles, mumps, rubella, and varicella (MMRV) vaccine and in simulation studies, we find that Step-ARM can detect a variety of medically coherent potential vaccine-symptom group signals efficiently. In the MMRV example, Step-ARM appears to outperform univariate methods in detecting a known safety signal. Our approach is sensitive to potentially complex signals, which may be particularly important when monitoring novel medical countermeasure products such as pandemic influenza vaccines. The post-processing clustering algorithm improves the applicability of the approach as a screening method to identify patterns that may merit further investigation. Copyright © 2015 John Wiley & Sons, Ltd.

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

    PubMed Central

    Mande, Sharmila S.

    2016-01-01

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

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

    PubMed

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

    2016-01-01

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

  5. Quantum algorithm for association rules mining

    NASA Astrophysics Data System (ADS)

    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 ) .

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

    PubMed

    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.

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

    NASA Astrophysics Data System (ADS)

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

    2017-11-01

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

  8. Quantifying Associations between Environmental Stressors and Demographic Factors

    EPA Science Inventory

    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...

  9. Exploration of association rule mining for coding consistency and completeness assessment in inpatient administrative health data.

    PubMed

    Peng, Mingkai; Sundararajan, Vijaya; Williamson, Tyler; Minty, Evan P; Smith, Tony C; Doktorchik, Chelsea T A; Quan, Hude

    2018-03-01

    Data quality assessment is a challenging facet for research using coded administrative health data. Current assessment approaches are time and resource intensive. We explored whether association rule mining (ARM) can be used to develop rules for assessing data quality. We extracted 2013 and 2014 records from the hospital discharge abstract database (DAD) for patients between the ages of 55 and 65 from five acute care hospitals in Alberta, Canada. The ARM was conducted using the 2013 DAD to extract rules with support ≥0.0019 and confidence ≥0.5 using the bootstrap technique, and tested in the 2014 DAD. The rules were compared against the method of coding frequency and assessed for their ability to detect error introduced by two kinds of data manipulation: random permutation and random deletion. The association rules generally had clear clinical meanings. Comparing 2014 data to 2013 data (both original), there were 3 rules with a confidence difference >0.1, while coding frequency difference of codes in the right hand of rules was less than 0.004. After random permutation of 50% of codes in the 2014 data, average rule confidence dropped from 0.72 to 0.27 while coding frequency remained unchanged. Rule confidence decreased with the increase of coding deletion, as expected. Rule confidence was more sensitive to code deletion compared to coding frequency, with slope of change ranging from 1.7 to 184.9 with a median of 9.1. The ARM is a promising technique to assess data quality. It offers a systematic way to derive coding association rules hidden in data, and potentially provides a sensitive and efficient method of assessing data quality compared to standard methods. Copyright © 2018 Elsevier Inc. All rights reserved.

  10. Quantifying Associations between Environmental and Social Stressors

    EPA Science Inventory

    Introduction: Association rule mining (ARM) has been widely used to identify associations between various entities in many fields. Although some studies have utilized it to analyze the relationship between chemicals and human effects, fewer have used this technique to identify an...

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

    PubMed

    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.

  12. Associations between socio-demographic characteristics and chemical concentrations contributing to cumulative exposures in the United States

    EPA Science Inventory

    Association rule mining (ARM) has been widely used to identify associations between various entities in many fields. Although some studies have utilized it to analyze the relationship between chemicals and human health effects, fewer have used this technique to identify and quant...

  13. A novel association rule mining approach using TID intermediate itemset.

    PubMed

    Aqra, Iyad; Herawan, Tutut; Abdul Ghani, Norjihan; Akhunzada, Adnan; Ali, Akhtar; Bin Razali, Ramdan; Ilahi, Manzoor; Raymond Choo, Kim-Kwang

    2018-01-01

    Designing an efficient association rule mining (ARM) algorithm for multilevel knowledge-based transactional databases that is appropriate for real-world deployments is of paramount concern. However, dynamic decision making that needs to modify the threshold either to minimize or maximize the output knowledge certainly necessitates the extant state-of-the-art algorithms to rescan the entire database. Subsequently, the process incurs heavy computation cost and is not feasible for real-time applications. The paper addresses efficiently the problem of threshold dynamic updation for a given purpose. The paper contributes by presenting a novel ARM approach that creates an intermediate itemset and applies a threshold to extract categorical frequent itemsets with diverse threshold values. Thus, improving the overall efficiency as we no longer needs to scan the whole database. After the entire itemset is built, we are able to obtain real support without the need of rebuilding the itemset (e.g. Itemset list is intersected to obtain the actual support). Moreover, the algorithm supports to extract many frequent itemsets according to a pre-determined minimum support with an independent purpose. Additionally, the experimental results of our proposed approach demonstrate the capability to be deployed in any mining system in a fully parallel mode; consequently, increasing the efficiency of the real-time association rules discovery process. The proposed approach outperforms the extant state-of-the-art and shows promising results that reduce computation cost, increase accuracy, and produce all possible itemsets.

  14. A novel association rule mining approach using TID intermediate itemset

    PubMed Central

    Ali, Akhtar; Bin Razali, Ramdan; Ilahi, Manzoor; Raymond Choo, Kim-Kwang

    2018-01-01

    Designing an efficient association rule mining (ARM) algorithm for multilevel knowledge-based transactional databases that is appropriate for real-world deployments is of paramount concern. However, dynamic decision making that needs to modify the threshold either to minimize or maximize the output knowledge certainly necessitates the extant state-of-the-art algorithms to rescan the entire database. Subsequently, the process incurs heavy computation cost and is not feasible for real-time applications. The paper addresses efficiently the problem of threshold dynamic updation for a given purpose. The paper contributes by presenting a novel ARM approach that creates an intermediate itemset and applies a threshold to extract categorical frequent itemsets with diverse threshold values. Thus, improving the overall efficiency as we no longer needs to scan the whole database. After the entire itemset is built, we are able to obtain real support without the need of rebuilding the itemset (e.g. Itemset list is intersected to obtain the actual support). Moreover, the algorithm supports to extract many frequent itemsets according to a pre-determined minimum support with an independent purpose. Additionally, the experimental results of our proposed approach demonstrate the capability to be deployed in any mining system in a fully parallel mode; consequently, increasing the efficiency of the real-time association rules discovery process. The proposed approach outperforms the extant state-of-the-art and shows promising results that reduce computation cost, increase accuracy, and produce all possible itemsets. PMID:29351287

  15. Magnetic signature of overbank sediment in industry impacted floodplains identified by data mining methods

    NASA Astrophysics Data System (ADS)

    Chudaničová, Monika; Hutchinson, Simon M.

    2016-11-01

    Our study attempts to identify a characteristic magnetic signature of overbank sediments exhibiting anthropogenically induced magnetic enhancement and thereby to distinguish them from unenhanced sediments with weak magnetic background values, using a novel approach based on data mining methods, thus providing a mean of rapid pollution determination. Data were obtained from 539 bulk samples from vertical profiles through overbank sediment, collected on seven rivers in the eastern Czech Republic and three rivers in northwest England. k-Means clustering and hierarchical clustering methods, paired group (UPGMA) and Ward's method, were used to divide the samples to natural groups according to their attributes. Interparametric ratios: SIRM/χ; SIRM/ARM; and S-0.1T were chosen as attributes for analyses making the resultant model more widely applicable as magnetic concentration values can differ by two orders. Division into three clusters appeared to be optimal and corresponded to inherent clusters in the data scatter. Clustering managed to separate samples with relatively weak anthropogenically induced enhancement, relatively strong anthropogenically induced enhancement and samples lacking enhancement. To describe the clusters explicitly and thus obtain a discrete magnetic signature, classification rules (JRip method) and decision trees (J4.8 and Simple Cart methods) were used. Samples lacking anthropogenic enhancement typically exhibited an S-0.1T < c. 0.5, SIRM/ARM < c. 150 and SIRM/χ < c. 6000 A m-1. Samples with magnetic enhancement all exhibited an S-0.1T > 0.5. Samples with relatively stronger anthropogenic enhancement were unequivocally distinguished from the samples with weaker enhancement by an SIRM/ARM > c. 150. Samples with SIRM/ARM in a range c. 126-150 were classified as relatively strongly enhanced when their SIRM/χ > 18 000 A m-1 and relatively less enhanced when their SIRM/χ < 18 000 A m-1. An additional rule was arbitrary added to exclude samples with χfd% > 6 per cent from anthropogenically enhanced clusters as samples with natural magnetic enhancement. The characteristics of the clusters resulted mainly from the relationship between SIRM/ARM and the S-0.1T, and SIRM/χ and the S-0.1T. Both SIRM/ARM and SIRM/χ increase with increasing S-0.1T values reflecting a greater level of anthropogenic magnetic particles. Overall, data mining methods demonstrated good potential for utilization in environmental magnetism.

  16. Spatio-Temporal Pattern Mining on Trajectory Data Using Arm

    NASA Astrophysics Data System (ADS)

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

    2017-09-01

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

  17. Cutter-loader apparatus having overhung shearer drum

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

    Groger, H.; Harms, E.E.

    1984-05-01

    A longwall mining machine includes a drum cutter-loader and face conveyor wherein the drum cutter-loader is overhung and is supported by a support arm adjacent to the mine face. Nozzles direct high pressure liquid jets against the forward edge of the support arm to cut away the mining face and permit the face side support arm to advance as the mining machine advances. In one embodiment the nozzles are provided along an inclined cutting edge at the forward end of the support arm. Such nozzles may be fixed or oscillating. In an alternative embodiment the nozzles are provided in themore » cylindrical edge zone of the shearer drum and direct the high pressure fluid jets against the cutter edge at the forward end of the support arm.« less

  18. Safety rules and regulations on mine sites - the problem and a solution.

    PubMed

    Laurence, David

    2005-01-01

    Many accidents and incidents on mine sites have a causal factor in the rules and regulations that supposedly are in place to prevent the incident from occurring. The causes involve a lack of awareness or understanding, ignorance, or deliberate violations. The issue of mine rules, procedures, and regulations is a central focus of this paper, highlighted by this recent comment - "very few people have accidents for which there is no procedure in place..." An attitudinal survey was conducted at 33 mines throughout NSW, Queensland and international mine sites involving almost 500 mineworkers. The survey was in the form of a self-completing questionnaire, consisting of approximately 65 questions. It aimed to seek the opinions of the mining workforce on safety rules and regulations generally, as well as how they apply to their specific jobs on a mine site. The research also aimed to investigate: (a) the level of awareness and understanding of mine rules and procedures such as manager's rules and safe work procedures (SWPs); (b) the level of awareness and understanding of mine safety regulations and legislation; (c) the extent of communication of and commitment to rules and regulations; (d) the extent of compliance with rules and regulations; and (e) attitudes regarding errors, risk-taking, and accidents and their interaction with rules and regulations. The sample consisted of a random selection of underground and open pit mines, extracting coal, metals, or industrial minerals. The insights provided by the mineworkers enabled a set of principles to be developed to guide mine management and regulators in the development of more effective rules and regulations. CONCLUSIONS AND IMPACT ON THE MINING INDUSTRY: (a) Management and regulators should not continue to produce more and more rules and regulations to cover every aspect of mining. (b) Detailed prescriptive regulations, detailed safe work procedures, and voluminous safety management plans will not "connect" with a miner. (c) Achieving more effective rules and regulations is not the only answer to a safer workplace.

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

    PubMed Central

    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

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

    PubMed Central

    Batal, Iyad; Cooper, Gregory; Hauskrecht, Milos

    2015-01-01

    Rule mining is an important class of data mining methods for discovering interesting patterns in data. The success of a rule mining method heavily depends on the evaluation function that is used to assess the quality of the rules. In this work, we propose a new rule evaluation score - the Predictive and Non-Spurious Rules (PNSR) score. This score relies on Bayesian inference to evaluate the quality of the rules and considers the structure of the rules to filter out spurious rules. We present an efficient algorithm for finding rules with high PNSR scores. The experiments demonstrate that our method is able to cover and explain the data with a much smaller rule set than existing methods. PMID:25938136

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

    PubMed

    Batal, Iyad; Cooper, Gregory; Hauskrecht, Milos

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

  2. On Interestingness Measures for Mining Statistically Significant and Novel Clinical Associations from EMRs

    PubMed Central

    Abar, Orhan; Charnigo, Richard J.; Rayapati, Abner

    2017-01-01

    Association rule mining has received significant attention from both the data mining and machine learning communities. While data mining researchers focus more on designing efficient algorithms to mine rules from large datasets, the learning community has explored applications of rule mining to classification. A major problem with rule mining algorithms is the explosion of rules even for moderate sized datasets making it very difficult for end users to identify both statistically significant and potentially novel rules that could lead to interesting new insights and hypotheses. Researchers have proposed many domain independent interestingness measures using which, one can rank the rules and potentially glean useful rules from the top ranked ones. However, these measures have not been fully explored for rule mining in clinical datasets owing to the relatively large sizes of the datasets often encountered in healthcare and also due to limited access to domain experts for review/analysis. In this paper, using an electronic medical record (EMR) dataset of diagnoses and medications from over three million patient visits to the University of Kentucky medical center and affiliated clinics, we conduct a thorough evaluation of dozens of interestingness measures proposed in data mining literature, including some new composite measures. Using cumulative relevance metrics from information retrieval, we compare these interestingness measures against human judgments obtained from a practicing psychiatrist for association rules involving the depressive disorders class as the consequent. Our results not only surface new interesting associations for depressive disorders but also indicate classes of interestingness measures that weight rule novelty and statistical strength in contrasting ways, offering new insights for end users in identifying interesting rules. PMID:28736771

  3. 76 FR 63238 - Proximity Detection Systems for Continuous Mining Machines in Underground Coal Mines

    Federal Register 2010, 2011, 2012, 2013, 2014

    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...

  4. Boosting association rule mining in large datasets via Gibbs sampling.

    PubMed

    Qian, Guoqi; Rao, Calyampudi Radhakrishna; Sun, Xiaoying; Wu, Yuehua

    2016-05-03

    Current algorithms for association rule mining from transaction data are mostly deterministic and enumerative. They can be computationally intractable even for mining a dataset containing just a few hundred transaction items, if no action is taken to constrain the search space. In this paper, we develop a Gibbs-sampling-induced stochastic search procedure to randomly sample association rules from the itemset space, and perform rule mining from the reduced transaction dataset generated by the sample. Also a general rule importance measure is proposed to direct the stochastic search so that, as a result of the randomly generated association rules constituting an ergodic Markov chain, the overall most important rules in the itemset space can be uncovered from the reduced dataset with probability 1 in the limit. In the simulation study and a real genomic data example, we show how to boost association rule mining by an integrated use of the stochastic search and the Apriori algorithm.

  5. 26 CFR 48.4216(b)-3 - Constructive sale price; special rule for arm's-length sales.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... 26 Internal Revenue 16 2011-04-01 2011-04-01 false Constructive sale price; special rule for arm's... Provisions Applicable to Manufacturers Taxes § 48.4216(b)-3 Constructive sale price; special rule for arm's... such articles to one or more wholesale distributors in arm's-length transactions, and the manufacturer...

  6. 27 CFR 53.96 - Constructive sale price; special rule for arm's-length sales.

    Code of Federal Regulations, 2012 CFR

    2012-04-01

    ...; special rule for arm's-length sales. 53.96 Section 53.96 Alcohol, Tobacco Products and Firearms ALCOHOL... sale price; special rule for arm's-length sales. (a) In general. Section 4216(b)(2) of the Code... distributors in arm's-length transactions, and the manufacturer establishes that its prices in such cases are...

  7. 27 CFR 53.96 - Constructive sale price; special rule for arm's-length sales.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ...; special rule for arm's-length sales. 53.96 Section 53.96 Alcohol, Tobacco Products and Firearms ALCOHOL... sale price; special rule for arm's-length sales. (a) In general. Section 4216(b)(2) of the Code... distributors in arm's-length transactions, and the manufacturer establishes that its prices in such cases are...

  8. 27 CFR 53.96 - Constructive sale price; special rule for arm's-length sales.

    Code of Federal Regulations, 2013 CFR

    2013-04-01

    ...; special rule for arm's-length sales. 53.96 Section 53.96 Alcohol, Tobacco Products and Firearms ALCOHOL... sale price; special rule for arm's-length sales. (a) In general. Section 4216(b)(2) of the Code... distributors in arm's-length transactions, and the manufacturer establishes that its prices in such cases are...

  9. 27 CFR 53.96 - Constructive sale price; special rule for arm's-length sales.

    Code of Federal Regulations, 2014 CFR

    2014-04-01

    ...; special rule for arm's-length sales. 53.96 Section 53.96 Alcohol, Tobacco Products and Firearms ALCOHOL... sale price; special rule for arm's-length sales. (a) In general. Section 4216(b)(2) of the Code... distributors in arm's-length transactions, and the manufacturer establishes that its prices in such cases are...

  10. 26 CFR 48.4216(b)-3 - Constructive sale price; special rule for arm's-length sales.

    Code of Federal Regulations, 2013 CFR

    2013-04-01

    ... 26 Internal Revenue 16 2013-04-01 2013-04-01 false Constructive sale price; special rule for arm's... Provisions Applicable to Manufacturers Taxes § 48.4216(b)-3 Constructive sale price; special rule for arm's... such articles to one or more wholesale distributors in arm's-length transactions, and the manufacturer...

  11. 26 CFR 48.4216(b)-3 - Constructive sale price; special rule for arm's-length sales.

    Code of Federal Regulations, 2012 CFR

    2012-04-01

    ... 26 Internal Revenue 16 2012-04-01 2012-04-01 false Constructive sale price; special rule for arm's... Provisions Applicable to Manufacturers Taxes § 48.4216(b)-3 Constructive sale price; special rule for arm's... such articles to one or more wholesale distributors in arm's-length transactions, and the manufacturer...

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

    NASA Astrophysics Data System (ADS)

    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.

  13. 26 CFR 1.611-2 - Rules applicable to mines, oil and gas wells, and other natural deposits.

    Code of Federal Regulations, 2013 CFR

    2013-04-01

    ... 26 Internal Revenue 7 2013-04-01 2013-04-01 false Rules applicable to mines, oil and gas wells....611-2 Rules applicable to mines, oil and gas wells, and other natural deposits. (a) Computation of cost depletion of mines, oil and gas wells, and other natural deposits. (1) The basis upon which cost...

  14. 26 CFR 1.611-2 - Rules applicable to mines, oil and gas wells, and other natural deposits.

    Code of Federal Regulations, 2012 CFR

    2012-04-01

    ... 26 Internal Revenue 7 2012-04-01 2012-04-01 false Rules applicable to mines, oil and gas wells....611-2 Rules applicable to mines, oil and gas wells, and other natural deposits. (a) Computation of cost depletion of mines, oil and gas wells, and other natural deposits. (1) The basis upon which cost...

  15. Pillars of Power: Silver and Steel of the Ottoman Empire.

    NASA Astrophysics Data System (ADS)

    Nerantzis, N.

    The Ottoman Empire was forged over disintegrating Byzantium, stretching across Anatolia and the Balkans and ruled for almost five centuries. One crucial parameter that allowed for its quick expansion has been a combination of economic wealth and superiority of armed forces. The Ottomans succeeded in both sectors by promoting innovative technology in the field of silver and steel production for supplying their monetary system and weapons industry. Rich mines and smelting workshops provided increased output in metals, allowing for quick expansion and economic growth. Some of the major centres for silver and steel production are being discussed in this paper in conjunction with analytical data from smelting residues.

  16. A Collaborative Educational Association Rule Mining Tool

    ERIC Educational Resources Information Center

    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…

  17. Performance of Case-Based Reasoning Retrieval Using Classification Based on Associations versus Jcolibri and FreeCBR: A Further Validation Study

    NASA Astrophysics Data System (ADS)

    Aljuboori, Ahmed S.; Coenen, Frans; Nsaif, Mohammed; Parsons, David J.

    2018-05-01

    Case-Based Reasoning (CBR) plays a major role in expert system research. However, a critical problem can be met when a CBR system retrieves incorrect cases. Class Association Rules (CARs) have been utilized to offer a potential solution in a previous work. The aim of this paper was to perform further validation of Case-Based Reasoning using a Classification based on Association Rules (CBRAR) to enhance the performance of Similarity Based Retrieval (SBR). The CBRAR strategy uses a classed frequent pattern tree algorithm (FP-CAR) in order to disambiguate wrongly retrieved cases in CBR. The research reported in this paper makes contributions to both fields of CBR and Association Rules Mining (ARM) in that full target cases can be extracted from the FP-CAR algorithm without invoking P-trees and union operations. The dataset used in this paper provided more efficient results when the SBR retrieves unrelated answers. The accuracy of the proposed CBRAR system outperforms the results obtained by existing CBR tools such as Jcolibri and FreeCBR.

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

    PubMed

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

    NASA Astrophysics Data System (ADS)

    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.

  20. 76 FR 2617 - Lowering Miners' Exposure to Respirable Coal Mine Dust, Including Continuous Personal Dust Monitors

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-01-14

    ... 1219-AB64 Lowering Miners' Exposure to Respirable Coal Mine Dust, Including Continuous Personal Dust... comment period on the proposed rule addressing Lowering Miners' Exposure to Respirable Coal Mine Dust...), MSHA published a proposed rule, Lowering Miners' Exposure to Respirable Coal Mine Dust, Including...

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

    PubMed

    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.

  2. An Automated Technique to Construct a Knowledge Base of Traditional Chinese Herbal Medicine for Cancers: An Exploratory Study for Breast Cancer.

    PubMed

    Nguyen, Phung Anh; Yang, Hsuan-Chia; Xu, Rong; Li, Yu-Chuan Jack

    2018-01-01

    Traditional Chinese Medicine utilization has rapidly increased worldwide. However, there is limited database provides the information of TCM herbs and diseases. The study aims to identify and evaluate the meaningful associations between TCM herbs and breast cancer by using the association rule mining (ARM) techniques. We employed the ARM techniques for 19.9 million TCM prescriptions by using Taiwan National Health Insurance claim database from 1999 to 2013. 364 TCM herbs-breast cancer associations were derived from those prescriptions and were then filtered by their support of 20. Resulting of 296 associations were evaluated by comparing to a gold-standard that was curated information from Chinese-Wikipedia with the following terms, cancer, tumor, malignant. All 14 TCM herbs-breast cancer associations with their confidence of 1% were valid when compared to gold-standard. For other confidences, the statistical results showed consistently with high precisions. We thus succeed to identify the TCM herbs-breast cancer associations with useful techniques.

  3. 77 FR 34894 - Wyoming Regulatory Program

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-06-12

    ... DEPARTMENT OF THE INTERIOR Office of Surface Mining Reclamation and Enforcement 30 CFR Part 950... Mining Reclamation and Enforcement, Interior. ACTION: Proposed rule; withdrawal. SUMMARY: We, the Office of Surface Mining Reclamation and Enforcement (OSM), are announcing the withdrawal of a proposed rule...

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

    PubMed Central

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

    2015-01-01

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

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

    PubMed

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

    2015-01-01

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

  6. Target-Based Maintenance of Privacy Preserving Association Rules

    ERIC Educational Resources Information Center

    Ahluwalia, Madhu V.

    2011-01-01

    In the context of association rule mining, the state-of-the-art in privacy preserving data mining provides solutions for categorical and Boolean association rules but not for quantitative association rules. This research fills this gap by describing a method based on discrete wavelet transform (DWT) to protect input data privacy while preserving…

  7. A novel approach for incremental uncertainty rule generation from databases with missing values handling: application to dynamic medical databases.

    PubMed

    Konias, Sokratis; Chouvarda, Ioanna; Vlahavas, Ioannis; Maglaveras, Nicos

    2005-09-01

    Current approaches for mining association rules usually assume that the mining is performed in a static database, where the problem of missing attribute values does not practically exist. However, these assumptions are not preserved in some medical databases, like in a home care system. In this paper, a novel uncertainty rule algorithm is illustrated, namely URG-2 (Uncertainty Rule Generator), which addresses the problem of mining dynamic databases containing missing values. This algorithm requires only one pass from the initial dataset in order to generate the item set, while new metrics corresponding to the notion of Support and Confidence are used. URG-2 was evaluated over two medical databases, introducing randomly multiple missing values for each record's attribute (rate: 5-20% by 5% increments) in the initial dataset. Compared with the classical approach (records with missing values are ignored), the proposed algorithm was more robust in mining rules from datasets containing missing values. In all cases, the difference in preserving the initial rules ranged between 30% and 60% in favour of URG-2. Moreover, due to its incremental nature, URG-2 saved over 90% of the time required for thorough re-mining. Thus, the proposed algorithm can offer a preferable solution for mining in dynamic relational databases.

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

    PubMed

    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.

  9. 75 FR 22723 - Stream Protection Rule; Environmental Impact Statement

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-04-30

    ... DEPARTMENT OF THE INTERIOR Office of Surface Mining Reclamation and Enforcement 30 CFR Parts 780... of Surface Mining Reclamation and Enforcement, Interior. ACTION: Proposed rule; notice of intent to prepare an environmental impact statement. SUMMARY: We, the Office of Surface Mining Reclamation and...

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

    PubMed Central

    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

  11. 76 FR 12082 - U.S. Court of Appeals for the Armed Forces Proposed Rules Changes

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-03-04

    ... DEPARTMENT OF DEFENSE Office of the Secretary [Docket ID DOD-2011-OS-0028] U.S. Court of Appeals for the Armed Forces Proposed Rules Changes AGENCY: Department of Defense. ACTION: Notice of Proposed... Federal Liaison Officer, Department of Defense. Rule 9(e) Rule 9(e) currently reads: (e) Hours. The Clerk...

  12. A New Data Mining Scheme Using Artificial Neural Networks

    PubMed Central

    Kamruzzaman, S. M.; Jehad Sarkar, A. M.

    2011-01-01

    Classification is one of the data mining problems receiving enormous attention in the database community. Although artificial neural networks (ANNs) have been successfully applied in a wide range of machine learning applications, they are however often regarded as black boxes, i.e., their predictions cannot be explained. To enhance the explanation of ANNs, a novel algorithm to extract symbolic rules from ANNs has been proposed in this paper. ANN methods have not been effectively utilized for data mining tasks because how the classifications were made is not explicitly stated as symbolic rules that are suitable for verification or interpretation by human experts. With the proposed approach, concise symbolic rules with high accuracy, that are easily explainable, can be extracted from the trained ANNs. Extracted rules are comparable with other methods in terms of number of rules, average number of conditions for a rule, and the accuracy. The effectiveness of the proposed approach is clearly demonstrated by the experimental results on a set of benchmark data mining classification problems. PMID:22163866

  13. Data Mining for Financial Applications

    NASA Astrophysics Data System (ADS)

    Kovalerchuk, Boris; Vityaev, Evgenii

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

  14. Analysis 320 coal mine accidents using structural equation modeling with unsafe conditions of the rules and regulations as exogenous variables.

    PubMed

    Zhang, Yingyu; Shao, Wei; Zhang, Mengjia; Li, Hejun; Yin, Shijiu; Xu, Yingjun

    2016-07-01

    Mining has been historically considered as a naturally high-risk industry worldwide. Deaths caused by coal mine accidents are more than the sum of all other accidents in China. Statistics of 320 coal mine accidents in Shandong province show that all accidents contain indicators of "unsafe conditions of the rules and regulations" with a frequency of 1590, accounting for 74.3% of the total frequency of 2140. "Unsafe behaviors of the operator" is another important contributory factor, which mainly includes "operator error" and "venturing into dangerous places." A systems analysis approach was applied by using structural equation modeling (SEM) to examine the interactions between the contributory factors of coal mine accidents. The analysis of results leads to three conclusions. (i) "Unsafe conditions of the rules and regulations," affect the "unsafe behaviors of the operator," "unsafe conditions of the equipment," and "unsafe conditions of the environment." (ii) The three influencing factors of coal mine accidents (with the frequency of effect relation in descending order) are "lack of safety education and training," "rules and regulations of safety production responsibility," and "rules and regulations of supervision and inspection." (iii) The three influenced factors (with the frequency in descending order) of coal mine accidents are "venturing into dangerous places," "poor workplace environment," and "operator error." Copyright © 2016 Elsevier Ltd. All rights reserved.

  15. Predicting missing values in a home care database using an adaptive uncertainty rule method.

    PubMed

    Konias, S; Gogou, G; Bamidis, P D; Vlahavas, I; Maglaveras, N

    2005-01-01

    Contemporary literature illustrates an abundance of adaptive algorithms for mining association rules. However, most literature is unable to deal with the peculiarities, such as missing values and dynamic data creation, that are frequently encountered in fields like medicine. This paper proposes an uncertainty rule method that uses an adaptive threshold for filling missing values in newly added records. A new approach for mining uncertainty rules and filling missing values is proposed, which is in turn particularly suitable for dynamic databases, like the ones used in home care systems. In this study, a new data mining method named FiMV (Filling Missing Values) is illustrated based on the mined uncertainty rules. Uncertainty rules have quite a similar structure to association rules and are extracted by an algorithm proposed in previous work, namely AURG (Adaptive Uncertainty Rule Generation). The main target was to implement an appropriate method for recovering missing values in a dynamic database, where new records are continuously added, without needing to specify any kind of thresholds beforehand. The method was applied to a home care monitoring system database. Randomly, multiple missing values for each record's attributes (rate 5-20% by 5% increments) were introduced in the initial dataset. FiMV demonstrated 100% completion rates with over 90% success in each case, while usual approaches, where all records with missing values are ignored or thresholds are required, experienced significantly reduced completion and success rates. It is concluded that the proposed method is appropriate for the data-cleaning step of the Knowledge Discovery process in databases. The latter, containing much significance for the output efficiency of any data mining technique, can improve the quality of the mined information.

  16. Highly scalable and robust rule learner: performance evaluation and comparison.

    PubMed

    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.

  17. 5 CFR 5201.105 - Additional rules for Mine Safety and Health Administration employees.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... Health Administration employees. 5201.105 Section 5201.105 Administrative Personnel DEPARTMENT OF LABOR... for Mine Safety and Health Administration employees. The rules in this section apply to employees of the Mine Safety and Health Administration (MSHA) and are in addition to §§ 5201.101, 5201.102, and...

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

    PubMed

    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.

  19. In Brief: Coal mining regulations

    NASA Astrophysics Data System (ADS)

    Showstack, Randy

    2009-12-01

    The U.S. Department of the Interior (DOI) announced on 18 November measures to strengthen the oversight of state surface coal mining programs and to promulgate federal regulations to protect streams affected by surface coal mining operations. DOI's Office of Surface Mining Reclamation and Enforcement (OSM) is publishing an advance notice of a proposed rule about protecting streams from adverse impacts of surface coal mining operations. A rule issued by the Bush administration in December 2008 allows coal mine operators to place excess excavated materials into streams if they can show it is not reasonably possible to avoid doing so. “We are moving as quickly as possible under the law to gather public input for a new rule, based on sound science, that will govern how companies handle fill removed from mountaintop coal seams,” according to Wilma Lewis, assistant secretary for Land and Minerals Management at DOI.

  20. Evaluation of a multi-arm multi-stage Bayesian design for phase II drug selection trials - an example in hemato-oncology.

    PubMed

    Jacob, Louis; Uvarova, Maria; Boulet, Sandrine; Begaj, Inva; Chevret, Sylvie

    2016-06-02

    Multi-Arm Multi-Stage designs aim at comparing several new treatments to a common reference, in order to select or drop any treatment arm to move forward when such evidence already exists based on interim analyses. We redesigned a Bayesian adaptive design initially proposed for dose-finding, focusing our interest in the comparison of multiple experimental drugs to a control on a binary criterion measure. We redesigned a phase II clinical trial that randomly allocates patients across three (one control and two experimental) treatment arms to assess dropping decision rules. We were interested in dropping any arm due to futility, either based on historical control rate (first rule) or comparison across arms (second rule), and in stopping experimental arm due to its ability to reach a sufficient response rate (third rule), using the difference of response probabilities in Bayes binomial trials between the treated and control as a measure of treatment benefit. Simulations were then conducted to investigate the decision operating characteristics under a variety of plausible scenarios, as a function of the decision thresholds. Our findings suggest that one experimental treatment was less efficient than the control and could have been dropped from the trial based on a sample of approximately 20 instead of 40 patients. In the simulation study, stopping decisions were reached sooner for the first rule than for the second rule, with close mean estimates of response rates and small bias. According to the decision threshold, the mean sample size to detect the required 0.15 absolute benefit ranged from 63 to 70 (rule 3) with false negative rates of less than 2 % (rule 1) up to 6 % (rule 2). In contrast, detecting a 0.15 inferiority in response rates required a sample size ranging on average from 23 to 35 (rules 1 and 2, respectively) with a false positive rate ranging from 3.6 to 0.6 % (rule 3). Adaptive trial design is a good way to improve clinical trials. It allows removing ineffective drugs and reducing the trial sample size, while maintaining unbiased estimates. Decision thresholds can be set according to predefined fixed error decision rates. ClinicalTrials.gov Identifier: NCT01342692 .

  1. Soil quality assessment using weighted fuzzy association rules

    USGS Publications Warehouse

    Xue, Yue-Ju; Liu, Shu-Guang; Hu, Yue-Ming; Yang, Jing-Feng

    2010-01-01

    Fuzzy association rules (FARs) can be powerful in assessing regional soil quality, a critical step prior to land planning and utilization; however, traditional FARs mined from soil quality database, ignoring the importance variability of the rules, can be redundant and far from optimal. In this study, we developed a method applying different weights to traditional FARs to improve accuracy of soil quality assessment. After the FARs for soil quality assessment were mined, redundant rules were eliminated according to whether the rules were significant or not in reducing the complexity of the soil quality assessment models and in improving the comprehensibility of FARs. The global weights, each representing the importance of a FAR in soil quality assessment, were then introduced and refined using a gradient descent optimization method. This method was applied to the assessment of soil resources conditions in Guangdong Province, China. The new approach had an accuracy of 87%, when 15 rules were mined, as compared with 76% from the traditional approach. The accuracy increased to 96% when 32 rules were mined, in contrast to 88% from the traditional approach. These results demonstrated an improved comprehensibility of FARs and a high accuracy of the proposed method.

  2. 77 FR 43721 - Examinations of Work Areas in Underground Coal Mines for Violations of Mandatory Health or Safety...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-07-26

    ... Examinations of Work Areas in Underground Coal Mines for Violations of Mandatory Health or Safety Standards... effectiveness of information collection requirements contained in the final rule on Examinations of Work Areas... requirements in MSHA's final rule on Examinations of Work Areas in Underground Coal Mines for Violations of...

  3. 75 FR 28227 - National Emission Standards for Hazardous Air Pollutants: Gold Mine Ore Processing and Production...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-05-20

    ... published a proposed rule for mercury emissions from the gold mine ore processing and production area source... proposed rule (75 FR 22470). Several parties requested that EPA extend the comment period. EPA has granted...-AP48 National Emission Standards for Hazardous Air Pollutants: Gold Mine Ore Processing and Production...

  4. 22 CFR 121.15 - Surface vessels of war.

    Code of Federal Regulations, 2014 CFR

    2014-04-01

    ... (battleships, aircraft carriers, destroyers, frigates, cruisers, corvettes, littoral combat ships, mine sweepers, mine hunters, mine countermeasure ships, dock landing ships, amphibious assault ships), or Coast... support naval nuclear propulsion plants; (5) Are armed or are specially designed to be used as a platform...

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

    PubMed

    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.

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

    PubMed

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

    PubMed Central

    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. PMID:23766683

  8. 75 FR 34666 - Stream Protection Rule; Environmental Impact Statement

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-06-18

    ... DEPARTMENT OF THE INTERIOR Office of Surface Mining Reclamation and Enforcement 30 CFR Chapter VII RIN 1029-AC63 Stream Protection Rule; Environmental Impact Statement AGENCY: Office of Surface Mining... impact statement. [[Page 34667

  9. 26 CFR 1.611-2 - Rules applicable to mines, oil and gas wells, and other natural deposits.

    Code of Federal Regulations, 2014 CFR

    2014-04-01

    ... Rules applicable to mines, oil and gas wells, and other natural deposits. (a) Computation of cost depletion of mines, oil and gas wells, and other natural deposits. (1) The basis upon which cost depletion... for the taxable year, the cost depletion for that year shall be computed by dividing such amount by...

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

    NASA Astrophysics Data System (ADS)

    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.

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

    Federal Register 2010, 2011, 2012, 2013, 2014

    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. Detection of antipersonnel (AP) mines using mechatronics approach

    NASA Astrophysics Data System (ADS)

    Shahri, Ali M.; Naghdy, Fazel

    1998-09-01

    At present there are approximately 110 million land-mines scattered around the world in 64 countries. The clearance of these mines takes place manually. Unfortunately, on average for every 5000 mines cleared one mine clearer is killed. A Mine Detector Arm (MDA) using mechatronics approach is under development in this work. The robot arm imitates manual hand- prodding technique for mine detection. It inserts a bayonet into the soil and models the dynamics of the manipulator and environment parameters, such as stiffness variation in the soil to control the impact caused by contacting a stiff object. An explicit impact control scheme is applied as the main control scheme, while two different intelligent control methods are designed to deal with uncertainties and varying environmental parameters. Firstly, a neuro-fuzzy adaptive gain controller (NFAGC) is designed to adapt the force gain control according to the estimated environment stiffness. Then, an adaptive neuro-fuzzy plus PID controller is employed to switch from a conventional PID controller to neuro-fuzzy impact control (NFIC), when an impact is detected. The developed control schemes are validated through computer simulation and experimental work.

  13. Big data mining analysis method based on cloud computing

    NASA Astrophysics Data System (ADS)

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

    2017-08-01

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

  14. Taiwan: Major U.S. Arms Sales Since 1990

    DTIC Science & Technology

    2012-05-17

    countermeasure (ECM) systems for F-16s; and 12 MH-53 mine -sweeping helicopters. President Bush approved four decommissioned Kidd-class destroyers for sale as...Section 36(b) of the AECA. See CRS Report RL31675, Arms Sales: Congressional Review Process, by Richard F. Grimmett. 250 Commercial sale. Opall Barbara...340 01/29 (2) Osprey-class mine hunting ships (refurbished and upgraded) $105 2011 09/21 Retrofit of 145 F-16A/B fighters, with 176 AESA radars

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

    DTIC Science & Technology

    2013-12-01

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

  16. Data mining and visualization techniques

    DOEpatents

    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.

  17. 30 CFR 1206.103 - How do I value oil that is not sold under an arm's-length contract?

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... arm's-length contract? 1206.103 Section 1206.103 Mineral Resources OFFICE OF SURFACE MINING... Oil § 1206.103 How do I value oil that is not sold under an arm's-length contract? This section... affiliates' arm's-length contracts for the purchase or sale of production from the field or area during the...

  18. Sensor Technology Assessment for Ordnance and Explosive Waste Detection and Location. Revision B.

    DTIC Science & Technology

    1995-03-01

    5 Figure 1.5 Examples Of Anti-Tank Mines .................... .................... 5 Figure 1.6. Sample Drawing of a Bomb...6 Figure 1.7. Examples of Scatterable Anti-Personnel Mines (top) and Scatterable Anti-Tank Mines (bottom...individuals, and therefore the OEW items must be detected and located. OEW examples are bombs, warheads, guided missiles, mortars, small arms, mines

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

    PubMed Central

    Gan, Wensheng; Zhang, Binbin

    2015-01-01

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

  20. German ’AT’ Mine Units

    DTIC Science & Technology

    1945-09-28

    a fixed - osition by an arm mount- ed on the tail door, and the magnetonhone is released by the blow- ing of a fuse when -the mine becomes armed, it... sensitivity of the unit. The output is condenser-couoled to the second stage. The output of the sec- ond stage is trnnsformer-cou-oled to the third...no orovision for setting sensitivity similar to that u~ed in AT 2. As well, that third rtage is omitted, and the output of the second stage is

  1. Software tool for data mining and its applications

    NASA Astrophysics Data System (ADS)

    Yang, Jie; Ye, Chenzhou; Chen, Nianyi

    2002-03-01

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

  2. Associations between socio-demographic characteristics and chemical concentrations contributing to cumulative exposures in the United States.

    PubMed

    Huang, Hongtai; Tornero-Velez, Rogelio; Barzyk, Timothy M

    2017-11-01

    Association rule mining (ARM) has been widely used to identify associations between various entities in many fields. Although some studies have utilized it to analyze the relationship between chemicals and human health effects, fewer have used this technique to identify and quantify associations between environmental and social stressors. Socio-demographic variables were generated based on U.S. Census tract-level income, race/ethnicity population percentage, education level, and age information from the 2010-2014, 5-Year Summary files in the American Community Survey (ACS) database, and chemical variables were generated by utilizing the 2011 National-Scale Air Toxics Assessment (NATA) census tract-level air pollutant exposure concentration data. Six mobile- and industrial-source pollutants were chosen for analysis, including acetaldehyde, benzene, cyanide, particulate matter components of diesel engine emissions (namely, diesel PM), toluene, and 1,3-butadiene. ARM was then applied to quantify and visualize the associations between the chemical and socio-demographic variables. Census tracts with a high percentage of racial/ethnic minorities and populations with low income tended to have higher estimated chemical exposure concentrations (fourth quartile), especially for diesel PM, 1,3-butadiene, and toluene. In contrast, census tracts with an average population age of 40-50 years, a low percentage of racial/ethnic minorities, and moderate-income levels were more likely to have lower estimated chemical exposure concentrations (first quartile). Unsupervised data mining methods can be used to evaluate potential associations between environmental inequalities and social disparities, while providing support in public health decision-making contexts.

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

    PubMed

    Linden, Ariel; Yarnold, Paul R

    2016-12-01

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

  4. Negative and Positive Association Rules Mining from Text Using Frequent and Infrequent Itemsets

    PubMed Central

    Mahmood, Sajid; Shahbaz, Muhammad; Guergachi, Aziz

    2014-01-01

    Association rule mining research typically focuses on positive association rules (PARs), generated from frequently occurring itemsets. However, in recent years, there has been a significant research focused on finding interesting infrequent itemsets leading to the discovery of negative association rules (NARs). The discovery of infrequent itemsets is far more difficult than their counterparts, that is, frequent itemsets. These problems include infrequent itemsets discovery and generation of accurate NARs, and their huge number as compared with positive association rules. In medical science, for example, one is interested in factors which can either adjudicate the presence of a disease or write-off of its possibility. The vivid positive symptoms are often obvious; however, negative symptoms are subtler and more difficult to recognize and diagnose. In this paper, we propose an algorithm for discovering positive and negative association rules among frequent and infrequent itemsets. We identify associations among medications, symptoms, and laboratory results using state-of-the-art data mining technology. PMID:24955429

  5. Multi-arm group sequential designs with a simultaneous stopping rule.

    PubMed

    Urach, S; Posch, M

    2016-12-30

    Multi-arm group sequential clinical trials are efficient designs to compare multiple treatments to a control. They allow one to test for treatment effects already in interim analyses and can have a lower average sample number than fixed sample designs. Their operating characteristics depend on the stopping rule: We consider simultaneous stopping, where the whole trial is stopped as soon as for any of the arms the null hypothesis of no treatment effect can be rejected, and separate stopping, where only recruitment to arms for which a significant treatment effect could be demonstrated is stopped, but the other arms are continued. For both stopping rules, the family-wise error rate can be controlled by the closed testing procedure applied to group sequential tests of intersection and elementary hypotheses. The group sequential boundaries for the separate stopping rule also control the family-wise error rate if the simultaneous stopping rule is applied. However, we show that for the simultaneous stopping rule, one can apply improved, less conservative stopping boundaries for local tests of elementary hypotheses. We derive corresponding improved Pocock and O'Brien type boundaries as well as optimized boundaries to maximize the power or average sample number and investigate the operating characteristics and small sample properties of the resulting designs. To control the power to reject at least one null hypothesis, the simultaneous stopping rule requires a lower average sample number than the separate stopping rule. This comes at the cost of a lower power to reject all null hypotheses. Some of this loss in power can be regained by applying the improved stopping boundaries for the simultaneous stopping rule. The procedures are illustrated with clinical trials in systemic sclerosis and narcolepsy. © 2016 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd. © 2016 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

  6. 77 FR 5740 - Tennessee Abandoned Mine Land Program

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-02-06

    ... DEPARTMENT OF THE INTERIOR Office of Surface Mining Reclamation and Enforcement 30 CFR Part 942... Mining Reclamation and Enforcement (OSM), Interior. ACTION: Proposed rule; public comment period and... amendment to the Tennessee Abandoned Mine Land (AML) Reclamation Plan under the Surface Mining Control and...

  7. 30 CFR 784.200 - Interpretive rules related to General Performance Standards.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

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

  8. Systematic drug repositioning through mining adverse event data in ClinicalTrials.gov.

    PubMed

    Su, Eric Wen; Sanger, Todd M

    2017-01-01

    Drug repositioning (i.e., drug repurposing) is the process of discovering new uses for marketed drugs. Historically, such discoveries were serendipitous. However, the rapid growth in electronic clinical data and text mining tools makes it feasible to systematically identify drugs with the potential to be repurposed. Described here is a novel method of drug repositioning by mining ClinicalTrials.gov. The text mining tools I2E (Linguamatics) and PolyAnalyst (Megaputer) were utilized. An I2E query extracts "Serious Adverse Events" (SAE) data from randomized trials in ClinicalTrials.gov. Through a statistical algorithm, a PolyAnalyst workflow ranks the drugs where the treatment arm has fewer predefined SAEs than the control arm, indicating that potentially the drug is reducing the level of SAE. Hypotheses could then be generated for the new use of these drugs based on the predefined SAE that is indicative of disease (for example, cancer).

  9. Collaborative Data Mining Tool for Education

    ERIC Educational Resources Information Center

    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…

  10. 77 FR 44155 - Administration of Mining Claims and Sites

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-07-27

    ... 1004-AE27 Administration of Mining Claims and Sites AGENCY: Bureau of Land Management, Interior. ACTION... on locating, recording, and maintaining mining claims or sites. In this rule, the BLM amends its... placer mining claims. The law specifies that the holder of an unpatented placer mining claim must pay the...

  11. 43 CFR 3487.1 - Logical mining units.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... 43 Public Lands: Interior 2 2011-10-01 2011-10-01 false Logical mining units. 3487.1 Section 3487..., DEPARTMENT OF THE INTERIOR MINERALS MANAGEMENT (3000) COAL EXPLORATION AND MINING OPERATIONS RULES Logical Mining Unit § 3487.1 Logical mining units. (a) An LMU shall become effective only upon approval of the...

  12. Health-Mining: a Disease Management Support Service based on Data Mining and Rule Extraction.

    PubMed

    Bei, Andrea; De Luca, Stefano; Ruscitti, Giancarlo; Salamon, Diego

    2005-01-01

    The disease management is the collection of the processes aimed to control the health care and improving the quality at same time reducing the overall cost of the procedures. Our system, Health-Mining, is a Decision Support System with the objective of controlling the adequacy of hospitalization and therapies, determining the effective use of standard guidelines and eventually identifying better ones emerged from the medical practice (Evidence Based Medicine). In realizing the system, we have the aim of creation of a path to admissions- appropriateness criteria construction, valid at an international level. A main goal of the project is rule extraction and the identification of the rules adequate in term of efficacy, quality and cost reduction, especially in the view of fast changing technologies and medicines. We tested Health-Mining in a real test case for an Italian Region, Regione Veneto, on the installation of pacemaker and ICD.

  13. THE HERMAN PIT AND ITS ROLE IN MERCURY TRANSPORT AT THE SULPHUR BANK MERCURY MINE SUPERFUND SITE, CLEAR LAKE, CALIFORNIA

    EPA Science Inventory

    The Sulphur Bank Mercury Mine (SBMM) is an abandoned sulphur and cinnabar mine located on the eastern shore of the Oaks Arm of Clear Lake, Lake County, California. SBMM was one of the largest mercury producers in California and has been described as one of the most productive sh...

  14. Mining Rare Associations between Biological Ontologies

    PubMed Central

    Benites, Fernando; Simon, Svenja; Sapozhnikova, Elena

    2014-01-01

    The constantly increasing volume and complexity of available biological data requires new methods for their management and analysis. An important challenge is the integration of information from different sources in order to discover possible hidden relations between already known data. In this paper we introduce a data mining approach which relates biological ontologies by mining cross and intra-ontology pairwise generalized association rules. Its advantage is sensitivity to rare associations, for these are important for biologists. We propose a new class of interestingness measures designed for hierarchically organized rules. These measures allow one to select the most important rules and to take into account rare cases. They favor rules with an actual interestingness value that exceeds the expected value. The latter is calculated taking into account the parent rule. We demonstrate this approach by applying it to the analysis of data from Gene Ontology and GPCR databases. Our objective is to discover interesting relations between two different ontologies or parts of a single ontology. The association rules that are thus discovered can provide the user with new knowledge about underlying biological processes or help improve annotation consistency. The obtained results show that produced rules represent meaningful and quite reliable associations. PMID:24404165

  15. Mining rare associations between biological ontologies.

    PubMed

    Benites, Fernando; Simon, Svenja; Sapozhnikova, Elena

    2014-01-01

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

  16. Natural Resource Extraction, Armed Violence, and Environmental Degradation

    PubMed Central

    Downey, Liam; Bonds, Eric; Clark, Katherine

    2011-01-01

    The goal of this article is to demonstrate that environmental sociologists cannot fully explain the relationship between humans and the natural world without theorizing a link between natural resource extraction, armed violence, and environmental degradation. The authors begin by arguing that armed violence is one of several overlapping mechanisms that provide powerful actors with the means to (a) prevail over others in conflicts over natural resources and (b) ensure that natural resources critical to industrial production and state power continue to be extracted and sold in sufficient quantities to promote capital accumulation, state power, and ecological unequal exchange. The authors then identify 10 minerals that are critical to the functioning of the U.S. economy and/or military and demonstrate that the extraction of these minerals often involves the use of armed violence. They further demonstrate that armed violence is associated with the activities of the world’s three largest mining companies, with African mines that receive World Bank funding, and with petroleum and rainforest timber extraction. The authors conclude that the natural resource base on which industrial societies stand is constructed in large part through the use and threatened use of armed violence. As a result, armed violence plays a critical role in fostering environmental degradation and ecological unequal exchange. PMID:21909231

  17. 76 FR 35801 - Examinations of Work Areas in Underground Coal Mines and Pattern of Violations

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-06-20

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

  18. 78 FR 48591 - Refuge Alternatives for Underground Coal Mines

    Federal Register 2010, 2011, 2012, 2013, 2014

    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...

  19. 75 FR 20918 - High-Voltage Continuous Mining Machine Standard for Underground Coal Mines

    Federal Register 2010, 2011, 2012, 2013, 2014

    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...

  20. 76 FR 27274 - Defense Federal Acquisition Regulation Supplement; Rules of the Armed Services Board of Contract...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-05-11

    ... 23 Post-Hearing Briefs Rule 24 Transcript of Proceedings Rule 25 Withdrawal of Exhibits... from Court TIME, COMPUTATION, AND EXTENSIONS Rule 33 Time, Computation and Extensions EX PARTE COMMUNICATIONS Rule 34 Ex parte Communications SANCTIONS Rule 35 Sanctions EFFECTIVE DATE AND APPLICABILITY Rule...

  1. 43 CFR 3482.3 - Mining operations maps.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... 43 Public Lands: Interior 2 2011-10-01 2011-10-01 false Mining operations maps. 3482.3 Section... MANAGEMENT, DEPARTMENT OF THE INTERIOR MINERALS MANAGEMENT (3000) COAL EXPLORATION AND MINING OPERATIONS RULES Exploration and Resource Recovery and Protection Plans § 3482.3 Mining operations maps. (a...

  2. Real-time intelligent decision making with data mining

    NASA Astrophysics Data System (ADS)

    Gupta, Deepak P.; Gopalakrishnan, Bhaskaran

    2004-03-01

    Database mining, widely known as knowledge discovery and data mining (KDD), has attracted lot of attention in recent years. With the rapid growth of databases in commercial, industrial, administrative and other applications, it is necessary and interesting to extract knowledge automatically from huge amount of data. Almost all the organizations are generating data and information at an unprecedented rate and they need to get some useful information from this data. Data mining is the extraction of non-trivial, previously unknown and potentially useful patterns, trends, dependence and correlation known as association rules among data values in large databases. In last ten to fifteen years, data mining spread out from one company to the other to help them understand more about customers' aspect of quality and response and also distinguish the customers they want from those they do not. A credit-card company found that customers who complete their applications in pencil rather than pen are more likely to default. There is a program that identifies callers by purchase history. The bigger the spender, the quicker the call will be answered. If you feel your call is being answered in the order in which it was received, think again. Many algorithms assume that data is static in nature and mine the rules and relations in that data. But for a dynamic database e.g. in most of the manufacturing industries, the rules and relations thus developed among the variables/items no longer hold true. A simple approach may be to mine the associations among the variables after every fixed period of time. But again, how much the length of this period should be, is a question to be answered. The next problem with the static data mining is that some of the relationships that might be of interest from one period to the other may be lost after a new set of data is used. To reflect the effect of new data set and current status of the association rules where some of the strong rules might become weak and vice versa, there is a need to develop an efficient algorithm to adapt to the current patterns and associations. Some work has been done in developing the association rules for incremental database but to the best of the author"s knowledge no work has been done to do the same for periodic cause and effect analysis for online association rules in manufacturing industries. The present research attempts to answer these questions and develop an algorithm that can display the association rules online, find the periodic patterns in the data and detect the root cause of the problem.

  3. Evaluation of rational nonsteroidal anti-inflammatory drugs and gastro-protective agents use; association rule data mining using outpatient prescription patterns.

    PubMed

    Pattanaprateep, Oraluck; McEvoy, Mark; Attia, John; Thakkinstian, Ammarin

    2017-07-04

    Nonsteroidal anti-inflammatory drugs (NSAIDs) and gastro-protective agents should be co-prescribed following a standard clinical practice guideline; however, adherence to this guideline in routine practice is unknown. This study applied an association rule model (ARM) to estimate rational NSAIDs and gastro-protective agents use in an outpatient prescriptions dataset. A database of hospital outpatients from October 1st, 2013 to September 30th, 2015 was searched for any of following drugs: oral antacids (A02A), peptic ulcer and gastro-oesophageal reflux disease drugs (GORD, A02B), and anti-inflammatory and anti-rheumatic products, non-steroids or NSAIDs (M01A). Data including patient demographics, diagnoses, and drug utilization were also retrieved. An association rule model was used to analyze co-prescription of the same drug class (i.e., prescriptions within A02A-A02B, M01A) and between drug classes (A02A-A02B & M01A) using the Apriori algorithm in R. The lift value, was calculated by a ratio of confidence to expected confidence, which gave information about the association between drugs in the prescription. We identified a total of 404,273 patients with 2,575,331 outpatient visits in 2 fiscal years. Mean age was 48 years and 34% were male. Among A02A, A02B and M01A drug classes, 12 rules of associations were discovered with support and confidence thresholds of 1% and 50%. The highest lift was between Omeprazole and Ranitidine (340 visits); about one-third of these visits (118) were prescriptions to non-GORD patients, contrary to guidelines. Another finding was the concomitant use of COX-2 inhibitors (Etoricoxib or Celecoxib) and PPIs. 35.6% of these were for patients aged less than 60 years with no GI complication and no Aspirin, inconsistent with guidelines. Around one-third of occasions where these medications were co-prescribed were inconsistent with guidelines. With the rapid growth of health datasets, data mining methods may help assess quality of care and concordance with guidelines and best evidence.

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

    NASA Astrophysics Data System (ADS)

    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.

  5. The association rules search of Indonesian university graduate’s data using FP-growth algorithm

    NASA Astrophysics Data System (ADS)

    Faza, S.; Rahmat, R. F.; Nababan, E. B.; Arisandi, D.; Effendi, S.

    2018-02-01

    The attribute varieties in university graduates data have caused frustrations to the institution in finding the combinations of attributes that often emerge and have high integration between attributes. Association rules mining is a data mining technique to determine the integration of the data or the way of a data set affects another set of data. By way of explanation, there are possibilities in finding the integration of data on a large scale. Frequent Pattern-Growth (FP-Growth) algorithm is one of the association rules mining technique to determine a frequent itemset in an FP-Tree data set. From the research on the search of university graduate’s association rules, it can be concluded that the most common attributes that have high integration between them are in the combination of State-owned High School outside Medan, regular university entrance exam, GPA of 3.00 to 3.49 and over 4-year-long study duration.

  6. 76 FR 12852 - Louisiana Regulatory Program/Abandoned Mine Land Reclamation Plan

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-03-09

    ... DEPARTMENT OF THE INTERIOR Office of Surface Mining Reclamation and Enforcement 30 CFR Part 918... Reclamation Plan AGENCY: Office of Surface Mining Reclamation and Enforcement, Interior. ACTION: Final rule; approval of amendment. SUMMARY: We, the Office of Surface Mining Reclamation and Enforcement (OSM), are...

  7. 75 FR 60373 - Louisiana Regulatory Program/Abandoned Mine Land Reclamation Plan

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-09-30

    ... DEPARTMENT OF THE INTERIOR Office of Surface Mining Reclamation and Enforcement 30 CFR Part 918... Reclamation Plan AGENCY: Office of Surface Mining Reclamation and Enforcement, Interior. ACTION: Proposed rule... of Surface Mining Reclamation and Enforcement (OSM), are announcing receipt of a proposed amendment...

  8. 26 CFR 1.614-3 - Rules relating to separate operating mineral interests in the case of mines.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... 26 Internal Revenue 7 2011-04-01 2009-04-01 true Rules relating to separate operating mineral interests in the case of mines. 1.614-3 Section 1.614-3 Internal Revenue INTERNAL REVENUE SERVICE, DEPARTMENT OF THE TREASURY (CONTINUED) INCOME TAX (CONTINUED) INCOME TAXES (CONTINUED) Natural Resources § 1...

  9. 26 CFR 1.611-2 - Rules applicable to mines, oil and gas wells, and other natural deposits.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... other natural deposits. 1.611-2 Section 1.611-2 Internal Revenue INTERNAL REVENUE SERVICE, DEPARTMENT OF THE TREASURY (CONTINUED) INCOME TAX (CONTINUED) INCOME TAXES (CONTINUED) Natural Resources § 1.611-2 Rules applicable to mines, oil and gas wells, and other natural deposits. (a) Computation of cost...

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

    ERIC Educational Resources Information Center

    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…

  11. 30 CFR 49.60 - Requirements for a local mine rescue contest.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... EDUCATION AND TRAINING MINE RESCUE TEAMS Mine Rescue Teams for Underground Coal Mines § 49.60 Requirements... United States; (2) Uses MSHA-recognized rules; (3) Has a minimum of three mine rescue teams competing; (4) Has one or more problems conducted on one or more days with a determined winner; (5) Includes team...

  12. 30 CFR 49.60 - Requirements for a local mine rescue contest.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... EDUCATION AND TRAINING MINE RESCUE TEAMS Mine Rescue Teams for Underground Coal Mines § 49.60 Requirements... United States; (2) Uses MSHA-recognized rules; (3) Has a minimum of three mine rescue teams competing; (4) Has one or more problems conducted on one or more days with a determined winner; (5) Includes team...

  13. 30 CFR 49.60 - Requirements for a local mine rescue contest.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... EDUCATION AND TRAINING MINE RESCUE TEAMS Mine Rescue Teams for Underground Coal Mines § 49.60 Requirements... United States; (2) Uses MSHA-recognized rules; (3) Has a minimum of three mine rescue teams competing; (4) Has one or more problems conducted on one or more days with a determined winner; (5) Includes team...

  14. 30 CFR 49.60 - Requirements for a local mine rescue contest.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... EDUCATION AND TRAINING MINE RESCUE TEAMS Mine Rescue Teams for Underground Coal Mines § 49.60 Requirements... United States; (2) Uses MSHA-recognized rules; (3) Has a minimum of three mine rescue teams competing; (4) Has one or more problems conducted on one or more days with a determined winner; (5) Includes team...

  15. 30 CFR 49.60 - Requirements for a local mine rescue contest.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... EDUCATION AND TRAINING MINE RESCUE TEAMS Mine Rescue Teams for Underground Coal Mines § 49.60 Requirements... United States; (2) Uses MSHA-recognized rules; (3) Has a minimum of three mine rescue teams competing; (4) Has one or more problems conducted on one or more days with a determined winner; (5) Includes team...

  16. Hard Fighting: Israel in Lebanon and Gaza

    DTIC Science & Technology

    2011-01-01

    mines . Hezbollah itself also proved an unexpectedly formidable adversary. During the years leading up to the Second Lebanon War, Hezbollah forces...hitting Hamas positions and detonating mines and IEDs. IDF engineers used armored D-9 bulldozers to clear paths through the remaining IEDs. Armored...discipline; cellular structure; small formations (squads) • Weapons: small arms; RPGs; mortars; short- range rockets; IEDs/ mines • Command and control

  17. USE OF ENVIRONMENTAL ISOTOPES TO DIFFERENTIATE WATER SOURCES AND CONSTRAIN THE WATER BUDGET AT THE SULPHUR BANK MERCURY MINE, CLEAR LAKE, CALIFORNIA

    EPA Science Inventory

    The Sulphur Bank Mercury Mine (SBMM) is a 65 ha site located on the eastern shore of the Oaks Arm of Clear Lake, Lake County, California. Between 1864 and 1957, SBMM was the site of underground and open pit mining operations for S and Hg, coinciding with past and present hot spr...

  18. 76 FR 76104 - Arkansas Regulatory Program and Abandoned Mine Land Reclamation Plan

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-12-06

    ... DEPARTMENT OF THE INTERIOR Office of Surface Mining Reclamation and Enforcement 30 CFR Part 904... Reclamation Plan AGENCY: Office of Surface Mining Reclamation and Enforcement, Interior. ACTION: Proposed rule; public comment period on proposed amendment. SUMMARY: We, the Office of Surface Mining Reclamation and...

  19. 77 FR 55430 - Arkansas Regulatory Program and Abandoned Mine Land Reclamation Plan

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-09-10

    ... DEPARTMENT OF THE INTERIOR Office of Surface Mining Reclamation and Enforcement 30 CFR Part 904... Reclamation Plan AGENCY: Office of Surface Mining Reclamation and Enforcement, Interior. ACTION: Proposed rule; public comment period on proposed amendment. SUMMARY: We, the Office of Surface Mining Reclamation and...

  20. Association Rule Mining from an Intelligent Tutor

    ERIC Educational Resources Information Center

    Dogan, Buket; Camurcu, A. Yilmaz

    2008-01-01

    Educational data mining is a very novel research area, offering fertile ground for many interesting data mining applications. Educational data mining can extract useful information from educational activities for better understanding and assessment of the student learning process. In this way, it is possible to explore how students learn topics in…

  1. 26 CFR 48.4216(b)-3 - Constructive sale price; special rule for arm's-length sales.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... volume of sales which are at retail or to retailers, or both, is less than half the total industry dollar volume of sales at all levels of distribution by manufacturers, producers, or importers, including sales... 26 Internal Revenue 16 2010-04-01 2010-04-01 true Constructive sale price; special rule for arm's...

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

    PubMed

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

    2017-08-24

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

  3. 76 FR 64047 - Montana Regulatory Program

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-10-17

    ... DEPARTMENT OF THE INTERIOR Office of Surface Mining Reclamation and Enforcement 30 CFR Part 926... Mining Reclamation and Enforcement, Interior. ACTION: Proposed rule; public comment period and... amendment to the Montana regulatory program (hereinafter, the ``Montana program'') under the Surface Mining...

  4. 76 FR 36040 - Wyoming Regulatory Program

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-06-21

    ... DEPARTMENT OF THE INTERIOR Office of Surface Mining Reclamation and Enforcement 30 CFR Part 950... Mining Reclamation and Enforcement, Interior. ACTION: Proposed rule; public comment period and... amendment to the Wyoming regulatory program (hereinafter, the ``Wyoming program'') under the Surface Mining...

  5. 78 FR 16204 - Wyoming Regulatory Program

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-03-14

    ... DEPARTMENT OF THE INTERIOR Office of Surface Mining Reclamation and Enforcement 30 CFR Part 950... Mining Reclamation and Enforcement, Interior. ACTION: Proposed rule; public comment period and... amendment to the Wyoming regulatory program (hereinafter, the ``Wyoming program'') under the Surface Mining...

  6. 76 FR 80310 - Wyoming Regulatory Program

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-12-23

    ... DEPARTMENT OF THE INTERIOR Office of Surface Mining Reclamation and Enforcement 30 CFR Part 950... Mining Reclamation and Enforcement, Interior. ACTION: Proposed rule; public comment period and... amendment to the Wyoming regulatory program (hereinafter, the ``Wyoming program'') under the Surface Mining...

  7. 76 FR 67635 - Alaska Regulatory Program

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-11-02

    ... DEPARTMENT OF THE INTERIOR Office of Surface Mining Reclamation and Enforcement 30 CFR Part 902... Mining Reclamation and Enforcement, Interior. ACTION: Proposed rule; public comment period and... amendment to the Alaska regulatory program (hereinafter, the ``Alaska program'') under the Surface Mining...

  8. 76 FR 64045 - Montana Regulatory Program

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-10-17

    ... DEPARTMENT OF THE INTERIOR Office of Surface Mining Reclamation and Enforcement 30 CFR Part 926... Mining Reclamation and Enforcement, Interior. ACTION: Proposed rule; public comment period and... amendment to the Montana regulatory program (hereinafter, the ``Montana program'') under the Surface Mining...

  9. 76 FR 76111 - Montana Regulatory Program

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-12-06

    ... DEPARTMENT OF THE INTERIOR Office of Surface Mining Reclamation and Enforcement 30 CFR Part 926... Mining Reclamation and Enforcement, Interior. ACTION: Proposed rule; public comment period and... amendment to the Montana regulatory program (hereinafter, the ``Montana program'') under the Surface Mining...

  10. 77 FR 25874 - Pennsylvania Regulatory Program

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-05-02

    ... DEPARTMENT OF THE INTERIOR Office of Surface Mining Reclamation and Enforcement 30 CFR Part 938... Mining Reclamation and Enforcement (OSM), Interior. ACTION: Final rule; removal of required amendment... regulatory program (the ``Pennsylvania program'') regulations under the Surface Mining Control and...

  11. TSCA Chemical Data Reporting Fact Sheet: Reporting Manufactured Chemical Substances from Metal Mining and Related Activities

    EPA Pesticide Factsheets

    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.

  12. 77 FR 1430 - Maryland Regulatory Program

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-01-10

    ... DEPARTMENT OF THE INTERIOR Office of Surface Mining Reclamation and Enforcement 30 CFR Part 920... Mining Reclamation and Enforcement (OSM), Interior. ACTION: Proposed rule; extension of the comment... the Maryland regulatory program (the ``Maryland program'') under the Surface Mining Control and...

  13. Data mining for multiagent rules, strategies, and fuzzy decision tree structure

    NASA Astrophysics Data System (ADS)

    Smith, James F., III; Rhyne, Robert D., II; Fisher, Kristin

    2002-03-01

    A fuzzy logic based resource manager (RM) has been developed that automatically allocates electronic attack resources in real-time over many dissimilar platforms. Two different data mining algorithms have been developed to determine rules, strategies, and fuzzy decision tree structure. The first data mining algorithm uses a genetic algorithm as a data mining function and is called from an electronic game. The game allows a human expert to play against the resource manager in a simulated battlespace with each of the defending platforms being exclusively directed by the fuzzy resource manager and the attacking platforms being controlled by the human expert or operating autonomously under their own logic. This approach automates the data mining problem. The game automatically creates a database reflecting the domain expert's knowledge. It calls a data mining function, a genetic algorithm, for data mining of the database as required and allows easy evaluation of the information mined in the second step. The criterion for re- optimization is discussed as well as experimental results. Then a second data mining algorithm that uses a genetic program as a data mining function is introduced to automatically discover fuzzy decision tree structures. Finally, a fuzzy decision tree generated through this process is discussed.

  14. 49 CFR 236.22 - Semaphore signal arm; clearance to other objects.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... 49 Transportation 4 2010-10-01 2010-10-01 false Semaphore signal arm; clearance to other objects... Rules and Instructions: All Systems Roadway Signals and Cab Signals § 236.22 Semaphore signal arm; clearance to other objects. At least one-half inch clearance shall be provided between semaphore signal arm...

  15. 49 CFR 236.22 - Semaphore signal arm; clearance to other objects.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... 49 Transportation 4 2012-10-01 2012-10-01 false Semaphore signal arm; clearance to other objects... Rules and Instructions: All Systems Roadway Signals and Cab Signals § 236.22 Semaphore signal arm; clearance to other objects. At least one-half inch clearance shall be provided between semaphore signal arm...

  16. 49 CFR 236.22 - Semaphore signal arm; clearance to other objects.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ... 49 Transportation 4 2014-10-01 2014-10-01 false Semaphore signal arm; clearance to other objects... Rules and Instructions: All Systems Roadway Signals and Cab Signals § 236.22 Semaphore signal arm; clearance to other objects. At least one-half inch clearance shall be provided between semaphore signal arm...

  17. 49 CFR 236.22 - Semaphore signal arm; clearance to other objects.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... 49 Transportation 4 2011-10-01 2011-10-01 false Semaphore signal arm; clearance to other objects... Rules and Instructions: All Systems Roadway Signals and Cab Signals § 236.22 Semaphore signal arm; clearance to other objects. At least one-half inch clearance shall be provided between semaphore signal arm...

  18. 49 CFR 236.22 - Semaphore signal arm; clearance to other objects.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... 49 Transportation 4 2013-10-01 2013-10-01 false Semaphore signal arm; clearance to other objects... Rules and Instructions: All Systems Roadway Signals and Cab Signals § 236.22 Semaphore signal arm; clearance to other objects. At least one-half inch clearance shall be provided between semaphore signal arm...

  19. 75 FR 69617 - Lowering Miners' Exposure to Respirable Coal Mine Dust, Including Continuous Personal Dust Monitors

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-11-15

    ... 1219-AB64 Lowering Miners' Exposure to Respirable Coal Mine Dust, Including Continuous Personal Dust... hearings on the proposed rule addressing Lowering Miners' Exposure to Respirable Coal Mine Dust, Including... miners' exposure to respirable coal mine dust by revising the Agency's existing standards on miners...

  20. 76 FR 11187 - Examinations of Work Areas in Underground Coal Mines for Violations of Mandatory Health or Safety...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-03-01

    ... Examinations of Work Areas in Underground Coal Mines for Violations of Mandatory Health or Safety Standards... rule addressing Examinations of Work Areas in Underground Coal Mines for Violations of Mandatory Health..., and weekly examinations of underground coal mines. This extension gives commenters an additional 30...

  1. Validity of association rules extracted by healthcare-data-mining.

    PubMed

    Takeuchi, Hiroshi; Kodama, Naoki

    2014-01-01

    A personal healthcare system used with cloud computing has been developed. It enables a daily time-series of personal health and lifestyle data to be stored in the cloud through mobile devices. The cloud automatically extracts personally useful information, such as rules and patterns concerning the user's lifestyle and health condition embedded in their personal big data, by using healthcare-data-mining. This study has verified that the extracted rules on the basis of a daily time-series data stored during a half- year by volunteer users of this system are valid.

  2. 77 FR 58056 - Mississippi Regulatory Program

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-09-19

    ... DEPARTMENT OF THE INTERIOR Office of Surface Mining Reclamation and Enforcement 30 CFR Part 924... Mining Reclamation and Enforcement, Interior. ACTION: Proposed rule; public comment period and opportunity for public hearing. SUMMARY: We, the Office of Surface Mining Reclamation and Enforcement (OSM...

  3. 76 FR 36039 - Colorado Regulatory Program

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-06-21

    ... DEPARTMENT OF THE INTERIOR Office of Surface Mining Reclamation and Enforcement 30 CFR Part 906... Mining Reclamation and Enforcement, Interior. ACTION: Proposed rule; public comment period and... Mining Control and Reclamation Act of 1977 (``SMCRA'' or ``the Act''). Colorado proposes both additions...

  4. 77 FR 34890 - Oklahoma Regulatory Program

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-06-12

    ... DEPARTMENT OF THE INTERIOR Office of Surface Mining Reclamation and Enforcement 30 CFR Part 936... Mining Reclamation and Enforcement, Interior. ACTION: Proposed rule; public comment period and opportunity for public hearing on proposed amendment. SUMMARY: We, the Office of Surface Mining Reclamation...

  5. 76 FR 50708 - Texas Regulatory Program

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-08-16

    ... DEPARTMENT OF THE INTERIOR Office of Surface Mining Reclamation and Enforcement 30 CFR Part 943... AGENCY: Office of Surface Mining Reclamation and Enforcement, Interior. ACTION: Proposed rule; public comment period and opportunity for public hearing. SUMMARY: We, the Office of Surface Mining Reclamation...

  6. 75 FR 60371 - Alabama Regulatory Program

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-09-30

    ... DEPARTMENT OF THE INTERIOR Office of Surface Mining Reclamation and Enforcement 30 CFR Part 901... Mining Reclamation and Enforcement, Interior. ACTION: Proposed rule; public comment period and opportunity for public hearing on proposed amendment. SUMMARY: We, the Office of Surface Mining Reclamation...

  7. 77 FR 41680 - Indiana Regulatory Program

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-07-16

    ... DEPARTMENT OF THE INTERIOR Office of Surface Mining Reclamation and Enforcement 30 CFR Part 914... Mining Reclamation and Enforcement, Interior. ACTION: Final rule; approval of amendment. SUMMARY: We, the Office of Surface Mining Reclamation and Enforcement (OSM), are approving amendments to the Indiana...

  8. 77 FR 25949 - Texas Regulatory Program

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-05-02

    ... DEPARTMENT OF THE INTERIOR Office of Surface Mining Reclamation and Enforcement 30 CFR Part 943... Mining Reclamation and Enforcement, Interior. ACTION: Proposed rule; public comment period and opportunity for public hearing on proposed amendment. SUMMARY: We, the Office of Surface Mining Reclamation...

  9. 76 FR 76109 - Colorado Regulatory Program

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-12-06

    ... DEPARTMENT OF THE INTERIOR Office of Surface Mining Reclamation and Enforcement 30 CFR Part 906... Mining Reclamation and Enforcement, Interior. ACTION: Proposed rule; reopening and extension of public...'') under the Surface Mining Control and Reclamation Act of 1977 (``SMCRA'' or ``the Act''). Colorado...

  10. 77 FR 66574 - Texas Regulatory Program

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-11-06

    ... DEPARTMENT OF THE INTERIOR Office of Surface Mining Reclamation and Enforcement 30 CFR Part 943... Mining Reclamation and Enforcement, Interior. ACTION: Proposed rule; public comment period and opportunity for public hearing on proposed amendment. SUMMARY: We, the Office of Surface Mining Reclamation...

  11. 77 FR 18149 - Montana Regulatory Program

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-03-27

    ... DEPARTMENT OF THE INTERIOR Office of Surface Mining Reclamation and Enforcement 30 CFR Part 926... Mining Reclamation and Enforcement, Interior. ACTION: Proposed rule; reopening and extension of public... receipt of Montana's response to the Office of Surface Mining Reclamation and Enforcement's (OSM) November...

  12. 77 FR 24661 - North Dakota Regulatory Program

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-04-25

    ... DEPARTMENT OF THE INTERIOR Office of Surface Mining Reclamation and Enforcement 30 CFR Part 934... Mining Reclamation and Enforcement, Interior. ACTION: Proposed rule; public comment period and... Surface Mining Control and Reclamation Act of 1977 (``SMCRA'' or ``the Act''). North Dakota proposes...

  13. 76 FR 23522 - Oklahoma Regulatory Program

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-04-27

    ... DEPARTMENT OF THE INTERIOR Office of Surface Mining Reclamation and Enforcement 30 CFR Part 936... Mining Reclamation and Enforcement, Interior. ACTION: Proposed rule; public comment period and opportunity for public hearing. SUMMARY: We, the Office of Surface Mining Reclamation and Enforcement (OSM...

  14. 75 FR 21534 - Texas Regulatory Program

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-04-26

    ... DEPARTMENT OF THE INTERIOR Office of Surface Mining Reclamation and Enforcement 30 CFR Part 943... Mining Reclamation and Enforcement, Interior. ACTION: Proposed rule; public comment period and opportunity for public hearing on proposed amendment. SUMMARY: We, the Office of Surface Mining Reclamation...

  15. 77 FR 34892 - Utah Regulatory Program

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-06-12

    ... DEPARTMENT OF THE INTERIOR Office of Surface Mining Reclamation and Enforcement 30 CFR Part 944... Mining Reclamation and Enforcement, Interior. ACTION: Proposed rule; public comment period and opportunity for public hearing on proposed amendment. SUMMARY: We, the Office of Surface Mining Reclamation...

  16. 77 FR 18738 - Texas Regulatory Program

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-03-28

    ... DEPARTMENT OF THE INTERIOR Office of Surface Mining Reclamation and Enforcement 30 CFR Part 943... Mining Reclamation and Enforcement, Interior. ACTION: Proposed rule; public comment period and opportunity for public hearing on proposed amendment. SUMMARY: We, the Office of Surface Mining Reclamation...

  17. 76 FR 9700 - Alabama Regulatory Program

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-02-22

    ... DEPARTMENT OF THE INTERIOR Office of Surface Mining Reclamation and Enforcement 30 CFR Part 901... Mining Reclamation and Enforcement, Interior. ACTION: Proposed rule; public comment period and opportunity for public hearing on proposed amendment. SUMMARY: We, the Office of Surface Mining Reclamation...

  18. 77 FR 40796 - Wyoming Regulatory Program

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-07-11

    ... DEPARTMENT OF THE INTERIOR Office of Surface Mining Reclamation and Enforcement 30 CFR Part 950... Mining Reclamation and Enforcement, Interior. ACTION: Final rule. SUMMARY: We, the Office of Surface Mining Reclamation and Enforcement (OSM), are removing a disapproval codified in OSM regulations...

  19. 76 FR 12857 - Montana Regulatory Program

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-03-09

    ... DEPARTMENT OF THE INTERIOR Office of Surface Mining Reclamation and Enforcement 30 CFR Part 926... of Surface Mining Reclamation and Enforcement, Interior. ACTION: Final rule; approval of amendment... the Surface Mining Control and Reclamation Act of 1977 (``SMCRA'' or ``the Act''). Montana proposed...

  20. 78 FR 11617 - Pennsylvania Regulatory Program

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-02-19

    ... DEPARTMENT OF THE INTERIOR Office of Surface Mining Reclamation and Enforcement 30 CFR Part 938... Surface Mining Reclamation and Enforcement (OSM), Interior. ACTION: Proposed rule; reopening of comment... regulatory program (the ``Pennsylvania program'') under the Surface Mining Control and Reclamation Act of...

  1. Empirical evaluation of interest-level criteria

    NASA Astrophysics Data System (ADS)

    Sahar, Sigal; Mansour, Yishay

    1999-02-01

    Efficient association rule mining algorithms already exist, however, as the size of databases increases, the number of patterns mined by the algorithms increases to such an extent that their manual evaluation becomes impractical. Automatic evaluation methods are, therefore, required in order to sift through the initial list of rules, which the datamining algorithm outputs. These evaluation methods, or criteria, rank the association rules mined from the dataset. We empirically examined several such statistical criteria: new criteria, as well as previously known ones. The empirical evaluation was conducted using several databases, including a large real-life dataset, acquired from an order-by-phone grocery store, a dataset composed from www proxy logs, and several datasets from the UCI repository. We were interested in discovering whether the ranking performed by the various criteria is similar or easily distinguishable. Our evaluation detected, when significant differences exist, three patterns of behavior in the eight criteria we examined. There is an obvious dilemma in determining how many association rules to choose (in accordance with support and confidence parameters). The tradeoff is between having stringent parameters and, therefore, few rules, or lenient parameters and, thus, a multitude of rules. In many cases, our empirical evaluation revealed that most of the rules found by the comparably strict parameters ranked highly according to the interestingness criteria, when using lax parameters (producing significantly more association rules). Finally, we discuss the association rules that ranked highest, explain why these results are sound, and how they direct future research.

  2. An Algorithm of Association Rule Mining for Microbial Energy Prospection

    PubMed Central

    Shaheen, Muhammad; Shahbaz, Muhammad

    2017-01-01

    The presence of hydrocarbons beneath earth’s surface produces some microbiological anomalies in soils and sediments. The detection of such microbial populations involves pure bio chemical processes which are specialized, expensive and time consuming. This paper proposes a new algorithm of context based association rule mining on non spatial data. The algorithm is a modified form of already developed algorithm which was for spatial database only. The algorithm is applied to mine context based association rules on microbial database to extract interesting and useful associations of microbial attributes with existence of hydrocarbon reserve. The surface and soil manifestations caused by the presence of hydrocarbon oxidizing microbes are selected from existing literature and stored in a shared database. The algorithm is applied on the said database to generate direct and indirect associations among the stored microbial indicators. These associations are then correlated with the probability of hydrocarbon’s existence. The numerical evaluation shows better accuracy for non-spatial data as compared to conventional algorithms at generating reliable and robust rules. PMID:28393846

  3. The application of data mining to explore association rules between metabolic syndrome and lifestyles.

    PubMed

    Huang, Yi Chao

    This study used an efficient data mining algorithm, called DCIP (the data cutting and inner product method), to explore association rules between the lifestyles of factory workers in Taiwan and the metabolic syndrome. A total of 1,216 workers in four companies completed a lifestyle questionnaire. Results of the questionnaire survey were integrated into the workers' health examination reports to form an attribute database of the metabolic syndrome. Among the association rules derived by DCIP, 80% of those on the list of the top 15 highest support counts are corroborated by medical literature or by healthcare professionals. These findings prove that data mining is a valid and effective research method, and that larger sample sizes will likely produce more accurate associations connecting the metabolic syndrome to specific lifestyles. The rules already verified can serve as a reference guide for the health management of factory workers. The remaining 20%, while still lacking hard evidence, provide fertile ground for future research.

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

    PubMed

    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.

  5. Design of multi-function sensor detection system in coal mine based on ARM

    NASA Astrophysics Data System (ADS)

    Ge, Yan-Xiang; Zhang, Quan-Zhu; Deng, Yong-Hong

    2017-06-01

    The traditional coal mine sensor in the specific measurement points, the number and type of channel will be greater than or less than the number of monitoring points, resulting in a waste of resources or cannot meet the application requirements, in order to enable the sensor to adapt to the needs of different occasions and reduce the cost, a kind of multi-functional intelligent sensor multiple sensors and ARM11 the S3C6410 processor is used to design and realize the dust, gas, temperature and humidity sensor functions together, and has storage, display, voice, pictures, data query, alarm and other new functions.

  6. 78 FR 6062 - North Dakota Regulatory Program

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-01-29

    ... DEPARTMENT OF THE INTERIOR Office of Surface Mining Reclamation and Enforcement 30 CFR Part 934... Mining Reclamation and Enforcement, Interior. ACTION: Proposed rule; public comment period and... Surface Mining Control and Reclamation Act of 1977 (``SMCRA'' or ``the Act''). North Dakota intends to...

  7. 76 FR 4266 - New Mexico Regulatory Program

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-01-25

    ... DEPARTMENT OF THE INTERIOR Office of Surface Mining Reclamation and Enforcement 30 CFR Part 931... Mining Reclamation and Enforcement, Interior. ACTION: Proposed rule; public comment period and... Mining Control and Reclamation Act of 1977 (``SMCRA'' or ``the Act''). New Mexico proposes revisions to...

  8. 76 FR 9642 - Alabama Regulatory Program

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-02-22

    ... DEPARTMENT OF THE INTERIOR Office of Surface Mining Reclamation and Enforcement 30 CFR Part 901... Mining Reclamation and Enforcement, Interior. ACTION: Final rule; approval of amendment. SUMMARY: We, the Office of Surface Mining Reclamation and Enforcement (OSM), are approving an amendment to the Alabama...

  9. 78 FR 13002 - Pennsylvania Regulatory Program

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-02-26

    ... DEPARTMENT OF THE INTERIOR Office of Surface Mining Reclamation and Enforcement 30 CFR Part 938... Mining Reclamation and Enforcement (``OSM''), Interior. ACTION: Proposed rule; public comment period and... regulatory program under the Surface Mining Control and Reclamation Act of 1977 (``SMCRA'' or the ``Act...

  10. 78 FR 11579 - Texas Regulatory Program

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-02-19

    ... DEPARTMENT OF THE INTERIOR Office of Surface Mining Reclamation and Enforcement 30 CFR Part 943... Mining Reclamation and Enforcement, Interior. ACTION: Final rule; approval of amendment. SUMMARY: We, the Office of Surface Mining Reclamation and Enforcement (OSM), are approving an amendment to the Texas...

  11. 76 FR 40649 - Indiana Regulatory Program

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-07-11

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

  12. 78 FR 10512 - Wyoming Regulatory Program

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-02-14

    ... DEPARTMENT OF THE INTERIOR Office of Surface Mining Reclamation and Enforcement 30 CFR Part 950... Mining Reclamation and Enforcement, Interior. ACTION: Final rule; approval of amendment with certain... ``Wyoming program'') under the Surface Mining Control and Reclamation Act of 1977 (``SMCRA'' or ``the Act...

  13. 77 FR 8144 - Texas Regulatory Program

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-02-14

    ... DEPARTMENT OF THE INTERIOR Office of Surface Mining Reclamation and Enforcement 30 CFR Part 943... AGENCY: Office of Surface Mining Reclamation and Enforcement, Interior. ACTION: Final rule; approval of amendment. SUMMARY: We, the Office of Surface Mining Reclamation and Enforcement (OSM), are approving three...

  14. 78 FR 9807 - Utah Regulatory Program

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-02-12

    ... DEPARTMENT OF THE INTERIOR Office of Surface Mining Reclamation and Enforcement 30 CFR Part 944... Mining Reclamation and Enforcement, Interior. ACTION: Final rule; approval of amendment. SUMMARY: We are approving an amendment to the Utah regulatory program (the ``Utah program'') under the Surface Mining...

  15. 76 FR 30008 - Alabama Regulatory Program

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-05-24

    ... DEPARTMENT OF THE INTERIOR Office of Surface Mining Reclamation and Enforcement 30 CFR Part 901... Mining Reclamation and Enforcement, Interior. ACTION: Final rule; approval of amendment. SUMMARY: We, the Office of Surface Mining Reclamation and Enforcement (OSM), are approving an amendment to the Alabama...

  16. 75 FR 43476 - Montana Regulatory Program

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-07-26

    ... DEPARTMENT OF THE INTERIOR Office of Surface Mining Reclamation and Enforcement 30 CFR Part 926... Mining Reclamation and Enforcement, Interior. ACTION: Proposed rule; reopening and extension of public...'') under the Surface Mining Control and Reclamation Act of 1977 (``SMCRA'' or ``the Act''). Montana revised...

  17. 75 FR 81122 - Texas Regulatory Program

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-12-27

    ... DEPARTMENT OF THE INTERIOR Office of Surface Mining Reclamation and Enforcement 30 CFR Part 943... Mining Reclamation and Enforcement, Interior. ACTION: Final rule; approval of amendment. SUMMARY: We, the Office of Surface Mining Reclamation and Enforcement (OSM), are approving an amendment to the Texas...

  18. 77 FR 58025 - Texas Regulatory Program

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-09-19

    ... DEPARTMENT OF THE INTERIOR Office of Surface Mining Reclamation and Enforcement 30 CFR Part 943... Mining Reclamation and Enforcement, Interior. ACTION: Final rule; approval of amendment. SUMMARY: We, the Office of Surface Mining Reclamation and Enforcement (OSM), are approving an amendment to the Texas...

  19. 75 FR 2785 - Naturalization for Certain Persons in the U.S. Armed Forces

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-01-19

    ... 1615-AB85 Naturalization for Certain Persons in the U.S. Armed Forces AGENCY: U.S. Citizenship and... length of time a member of the United States Armed Forces has to serve to qualify for naturalization through service in the Armed Forces. In addition, this rule amends DHS regulations by implementing a...

  20. 49 CFR 236.531 - Trip arm; height and distance from rail.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ... 49 Transportation 4 2014-10-01 2014-10-01 false Trip arm; height and distance from rail. 236.531... Train Stop, Train Control and Cab Signal Systems Rules and Instructions; Roadway § 236.531 Trip arm; height and distance from rail. Trip arm of automatic train stop device when in the stop position shall be...

  1. 49 CFR 236.531 - Trip arm; height and distance from rail.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... 49 Transportation 4 2011-10-01 2011-10-01 false Trip arm; height and distance from rail. 236.531... Train Stop, Train Control and Cab Signal Systems Rules and Instructions; Roadway § 236.531 Trip arm; height and distance from rail. Trip arm of automatic train stop device when in the stop position shall be...

  2. 49 CFR 236.531 - Trip arm; height and distance from rail.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... 49 Transportation 4 2013-10-01 2013-10-01 false Trip arm; height and distance from rail. 236.531... Train Stop, Train Control and Cab Signal Systems Rules and Instructions; Roadway § 236.531 Trip arm; height and distance from rail. Trip arm of automatic train stop device when in the stop position shall be...

  3. 49 CFR 236.531 - Trip arm; height and distance from rail.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... 49 Transportation 4 2010-10-01 2010-10-01 false Trip arm; height and distance from rail. 236.531... Train Stop, Train Control and Cab Signal Systems Rules and Instructions; Roadway § 236.531 Trip arm; height and distance from rail. Trip arm of automatic train stop device when in the stop position shall be...

  4. 49 CFR 236.531 - Trip arm; height and distance from rail.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... 49 Transportation 4 2012-10-01 2012-10-01 false Trip arm; height and distance from rail. 236.531... Train Stop, Train Control and Cab Signal Systems Rules and Instructions; Roadway § 236.531 Trip arm; height and distance from rail. Trip arm of automatic train stop device when in the stop position shall be...

  5. 76 FR 25277 - Examinations of Work Areas in Underground Coal Mines and Pattern of Violations

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-05-04

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

  6. 78 FR 49079 - Lease Modifications, Lease and Logical Mining Unit Diligence, Advance Royalty, Royalty Rates, and...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-08-12

    ... Management 43 CFR Parts 3000, 3400, 3430, et al. Lease Modifications, Lease and Logical Mining Unit Diligence... Lease Modifications, Lease and Logical Mining Unit Diligence, Advance Royalty, Royalty Rates, and Bonds... leases and logical mining units (LMUs). The proposed rule would implement Title IV, Subtitle D of the...

  7. A Swarm Optimization approach for clinical knowledge mining.

    PubMed

    Christopher, J Jabez; Nehemiah, H Khanna; Kannan, A

    2015-10-01

    Rule-based classification is a typical data mining task that is being used in several medical diagnosis and decision support systems. The rules stored in the rule base have an impact on classification efficiency. Rule sets that are extracted with data mining tools and techniques are optimized using heuristic or meta-heuristic approaches in order to improve the quality of the rule base. In this work, a meta-heuristic approach called Wind-driven Swarm Optimization (WSO) is used. The uniqueness of this work lies in the biological inspiration that underlies the algorithm. WSO uses Jval, a new metric, to evaluate the efficiency of a rule-based classifier. Rules are extracted from decision trees. WSO is used to obtain different permutations and combinations of rules whereby the optimal ruleset that satisfies the requirement of the developer is used for predicting the test data. The performance of various extensions of decision trees, namely, RIPPER, PART, FURIA and Decision Tables are analyzed. The efficiency of WSO is also compared with the traditional Particle Swarm Optimization. Experiments were carried out with six benchmark medical datasets. The traditional C4.5 algorithm yields 62.89% accuracy with 43 rules for liver disorders dataset where as WSO yields 64.60% with 19 rules. For Heart disease dataset, C4.5 is 68.64% accurate with 98 rules where as WSO is 77.8% accurate with 34 rules. The normalized standard deviation for accuracy of PSO and WSO are 0.5921 and 0.5846 respectively. WSO provides accurate and concise rulesets. PSO yields results similar to that of WSO but the novelty of WSO lies in its biological motivation and it is customization for rule base optimization. The trade-off between the prediction accuracy and the size of the rule base is optimized during the design and development of rule-based clinical decision support system. The efficiency of a decision support system relies on the content of the rule base and classification accuracy. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  8. Knowledge-guided mutation in classification rules for autism treatment efficacy.

    PubMed

    Engle, Kelley; Rada, Roy

    2017-03-01

    Data mining methods in biomedical research might benefit by combining genetic algorithms with domain-specific knowledge. The objective of this research is to show how the evolution of treatment rules for autism might be guided. The semantic distance between two concepts in the taxonomy is measured by the number of relationships separating the concepts in the taxonomy. The hypothesis is that replacing a concept in a treatment rule will change the accuracy of the rule in direct proportion to the semantic distance between the concepts. The method uses a patient database and autism taxonomies. Treatment rules are developed with an algorithm that exploits the taxonomies. The results support the hypothesis. This research should both advance the understanding of autism data mining in particular and of knowledge-guided evolutionary search in biomedicine in general.

  9. Accelerating clinical development of HIV vaccine strategies: methodological challenges and considerations in constructing an optimised multi-arm phase I/II trial design.

    PubMed

    Richert, Laura; Doussau, Adélaïde; Lelièvre, Jean-Daniel; Arnold, Vincent; Rieux, Véronique; Bouakane, Amel; Lévy, Yves; Chêne, Geneviève; Thiébaut, Rodolphe

    2014-02-26

    Many candidate vaccine strategies against human immunodeficiency virus (HIV) infection are under study, but their clinical development is lengthy and iterative. To accelerate HIV vaccine development optimised trial designs are needed. We propose a randomised multi-arm phase I/II design for early stage development of several vaccine strategies, aiming at rapidly discarding those that are unsafe or non-immunogenic. We explored early stage designs to evaluate both the safety and the immunogenicity of four heterologous prime-boost HIV vaccine strategies in parallel. One of the vaccines used as a prime and boost in the different strategies (vaccine 1) has yet to be tested in humans, thus requiring a phase I safety evaluation. However, its toxicity risk is considered minimal based on data from similar vaccines. We newly adapted a randomised phase II trial by integrating an early safety decision rule, emulating that of a phase I study. We evaluated the operating characteristics of the proposed design in simulation studies with either a fixed-sample frequentist or a continuous Bayesian safety decision rule and projected timelines for the trial. We propose a randomised four-arm phase I/II design with two independent binary endpoints for safety and immunogenicity. Immunogenicity evaluation at trial end is based on a single-stage Fleming design per arm, comparing the observed proportion of responders in an immunogenicity screening assay to an unacceptably low proportion, without direct comparisons between arms. Randomisation limits heterogeneity in volunteer characteristics between arms. To avoid exposure of additional participants to an unsafe vaccine during the vaccine boost phase, an early safety decision rule is imposed on the arm starting with vaccine 1 injections. In simulations of the design with either decision rule, the risks of erroneous conclusions were controlled <15%. Flexibility in trial conduct is greater with the continuous Bayesian rule. A 12-month gain in timelines is expected by this optimised design. Other existing designs such as bivariate or seamless phase I/II designs did not offer a clear-cut alternative. By combining phase I and phase II evaluations in a multi-arm trial, the proposed optimised design allows for accelerating early stage clinical development of HIV vaccine strategies.

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

    NASA Astrophysics Data System (ADS)

    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.

  11. 76 FR 64048 - Pennsylvania Regulatory Program

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-10-17

    ... DEPARTMENT OF THE INTERIOR Office of Surface Mining Reclamation and Enforcement 30 CFR Part 938... Surface Mining Reclamation and Enforcement (OSM), Interior. ACTION: Proposed rule; reopening and extension... Mining Control and Reclamation Act of 1977 (SMCRA or the Act) published on February 7, 2011. In response...

  12. 30 CFR 301.1 - Cross reference.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... within the jurisdiction of administrative law judges and the Interior Board of Surface Mining and... Resources BOARD OF SURFACE MINING AND RECLAMATION APPEALS, DEPARTMENT OF THE INTERIOR PROCEDURES UNDER SURFACE MINING CONTROL AND RECLAMATION ACT OF 1977 § 301.1 Cross reference. For special rules applicable...

  13. 75 FR 60271 - Technical Amendments 2010

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-09-29

    ... Part VI Department of the Interior Office of Surface Mining Reclamation and Enforcement 30 CFR... INTERIOR Office of Surface Mining Reclamation and Enforcement 30 CFR Parts 740, 761, 773, 795, 816, 817...: Office of Surface Mining Reclamation and Enforcement, Interior. ACTION: Final rule. SUMMARY: We, the...

  14. 30 CFR 921.700 - Massachusetts Federal program.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... 921.700 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE MASSACHUSETTS § 921.700 Massachusetts Federal program. (a) This part contains all rules that are applicable to surface coal mining...

  15. 77 FR 58053 - Kentucky Regulatory Program

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-09-19

    ... DEPARTMENT OF THE INTERIOR Office of Surface Mining Reclamation and Enforcement 30 CFR Part 917... Mining Reclamation and Enforcement (OSM), Interior. ACTION: Proposed rule; Removal of Required Amendments... program'') under the Surface Mining Control and Reclamation Act of 1977 (SMCRA or the Act). As a result of...

  16. 30 CFR 937.700 - Oregon Federal program.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... Federal program. (c) The rules in this part apply to all surface coal mining operations in Oregon... more stringent environmental control and regulation of surface coal mining operations than do the... extent they provide for regulation of surface coal mining and reclamation operations which are exempt...

  17. 30 CFR 912.700 - Idaho Federal program.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... seq. and Rules 1 through 20 promulgated thereunder pertaining to regulation of dredge mining. (6... Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE IDAHO § 912.700 Idaho Federal...

  18. 75 FR 64411 - Lowering Miners' Exposure to Respirable Coal Mine Dust, Including Continuous Personal Dust Monitors

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-10-19

    ...The Mine Safety and Health Administration (MSHA) proposes to lower miners' exposure to respirable coal mine dust by revising the Agency's existing standards on miners' occupational exposure to respirable coal mine dust. The major provisions of the proposal would lower the existing exposure limit; provide for full-shift sampling; redefine the term ``normal production shift; '' and add reexamination and decertification requirements for persons certified to sample, and maintain and calibrate sampling devices. In addition, the proposed rule would provide for single shift compliance sampling under the mine operator and MSHA's inspector sampling programs, and would establish sampling requirements for use of the Continuous Personal Dust Monitor (CPDM) and expanded requirements for medical surveillance. The proposed rule would significantly improve health protections for this Nation's coal miners by reducing their occupational exposure to respirable coal mine dust and lowering the risk that they will suffer material impairment of health or functional capacity over their working lives.

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

    PubMed

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

    2014-01-01

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

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

    PubMed Central

    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. PMID:24688442

  1. Special home adaptation grants for members of the Armed Forces and veterans with certain vision impairment. Final rule.

    PubMed

    2014-09-12

    The Department of Veterans Affairs (VA) is issuing a final rule to amend its adjudication regulations regarding special home adaptation grants for members of the Armed Forces and veterans with certain vision impairment. This regulatory amendment is necessary to conform the regulations to changes mandated in the Honoring America's Veterans and Caring for Camp Lejeune Families Act of 2012.

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

    PubMed

    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.

  3. 76 FR 41411 - West Virginia Regulatory Program

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-07-14

    ... of Environmental Protection (WVDEP). The interim rule provided an opportunity for public comment and... 30 CFR Part 948 Intergovernmental relations, Surface mining, Underground mining. Dated: July 5, 2011...

  4. Temporal data mining for the quality assessment of hemodialysis services.

    PubMed

    Bellazzi, Riccardo; Larizza, Cristiana; Magni, Paolo; Bellazzi, Roberto

    2005-05-01

    This paper describes the temporal data mining aspects of a research project that deals with the definition of methods and tools for the assessment of the clinical performance of hemodialysis (HD) services, on the basis of the time series automatically collected during hemodialysis sessions. Intelligent data analysis and temporal data mining techniques are applied to gain insight and to discover knowledge on the causes of unsatisfactory clinical results. In particular, two new methods for association rule discovery and temporal rule discovery are applied to the time series. Such methods exploit several pre-processing techniques, comprising data reduction, multi-scale filtering and temporal abstractions. We have analyzed the data of more than 5800 dialysis sessions coming from 43 different patients monitored for 19 months. The qualitative rules associating the outcome parameters and the measured variables were examined by the domain experts, which were able to distinguish between rules confirming available background knowledge and unexpected but plausible rules. The new methods proposed in the paper are suitable tools for knowledge discovery in clinical time series. Their use in the context of an auditing system for dialysis management helped clinicians to improve their understanding of the patients' behavior.

  5. 30 CFR 912.700 - Idaho Federal program.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE IDAHO § 912.700 Idaho Federal program. (a) This part contains all rules that are applicable to surface coal mining operations in Idaho...

  6. 30 CFR 905.700 - California Federal Program.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ....700 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE CALIFORNIA § 905.700 California Federal Program. (a) This part contains all rules that are applicable to surface coal mining operations in...

  7. 30 CFR 947.700 - Washington Federal program.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ....700 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE WASHINGTON § 947.700 Washington Federal program. (a) This part contains all rules that are applicable to surface coal mining operations in...

  8. 30 CFR 922.700 - Michigan Federal program.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ....700 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE MICHIGAN § 922.700 Michigan Federal program. (a) This part contains all rules that are applicable to surface coal mining operations in...

  9. 30 CFR 910.700 - Georgia Federal program.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ....700 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE GEORGIA § 910.700 Georgia Federal program. (a) This part contains all rules that are applicable to surface coal mining operations in Georgia...

  10. 30 CFR 937.700 - Oregon Federal program.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE OREGON § 937.700 Oregon Federal program. (a) This part contains all rules that are applicable to surface coal mining operations in Oregon...

  11. 30 CFR 942.700 - Tennessee Federal program.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ....700 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE TENNESSEE § 942.700 Tennessee Federal program. (a) This part contains all rules that are applicable to surface coal mining operations in...

  12. Co-evolutionary data mining for fuzzy rules: automatic fitness function creation phase space, and experiments

    NASA Astrophysics Data System (ADS)

    Smith, James F., III; Blank, Joseph A.

    2003-03-01

    An approach is being explored that involves embedding a fuzzy logic based resource manager in an electronic game environment. Game agents can function under their own autonomous logic or human control. This approach automates the data mining problem. The game automatically creates a cleansed database reflecting the domain expert's knowledge, it calls a data mining function, a genetic algorithm, for data mining of the data base as required and allows easy evaluation of the information extracted. The co-evolutionary fitness functions, chromosomes and stopping criteria for ending the game are discussed. Genetic algorithm and genetic program based data mining procedures are discussed that automatically discover new fuzzy rules and strategies. The strategy tree concept and its relationship to co-evolutionary data mining are examined as well as the associated phase space representation of fuzzy concepts. The overlap of fuzzy concepts in phase space reduces the effective strategies available to adversaries. Co-evolutionary data mining alters the geometric properties of the overlap region known as the admissible region of phase space significantly enhancing the performance of the resource manager. Procedures for validation of the information data mined are discussed and significant experimental results provided.

  13. All Glory Is Fleeting: Insights from the Second Lebanon War

    DTIC Science & Technology

    2012-01-01

    Israel border north- ward were heavily mined and covered by antitank weapons by fight- ers well trained in how best to engage Israeli military...in the end, destroy 14 Israeli tanks; mines would ravage another six.14 Even the IDF’s most advanced model, the Merkava 4, proved vulnerable. The...Approximately “50% of Israeli casualties can be attributed to anti-tank missiles, 25% to small arms and mines , around 10% to friendly fire, 10% to

  14. Object-Driven and Temporal Action Rules Mining

    ERIC Educational Resources Information Center

    Hajja, Ayman

    2013-01-01

    In this thesis, I present my complete research work in the field of action rules, more precisely object-driven and temporal action rules. The drive behind the introduction of object-driven and temporally based action rules is to bring forth an adapted approach to extract action rules from a subclass of systems that have a specific nature, in which…

  15. Mining Hesitation Information by Vague Association Rules

    NASA Astrophysics Data System (ADS)

    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.

  16. Intertransaction Class Association Rule Mining Based on Genetic Network Programming and Its Application to Stock Market Prediction

    NASA Astrophysics Data System (ADS)

    Yang, Yuchen; Mabu, Shingo; Shimada, Kaoru; Hirasawa, Kotaro

    Intertransaction association rules have been reported to be useful in many fields such as stock market prediction, but still there are not so many efficient methods to dig them out from large data sets. Furthermore, how to use and measure these more complex rules should be considered carefully. In this paper, we propose a new intertransaction class association rule mining method based on Genetic Network Programming (GNP), which has the ability to overcome some shortages of Apriori-like based intertransaction association methods. Moreover, a general classifier model for intertransaction rules is also introduced. In experiments on the real world application of stock market prediction, the method shows its efficiency and ability to obtain good results and can bring more benefits with a suitable classifier considering larger interval span.

  17. 76 FR 30001 - Amendment to the International Traffic in Arms Regulations: Libya

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-05-24

    ... International Traffic in Arms Regulations: Libya AGENCY: Department of State. ACTION: Final rule. SUMMARY: The... regarding Libya to reflect the United Nations Security Council arms embargoes adopted in February and March...: (202) 261-8199; or e-mail: [email protected] . Attn: Part 126, Libya. SUPPLEMENTARY INFORMATION: On...

  18. Evolutionary Data Mining Approach to Creating Digital Logic

    DTIC Science & Technology

    2010-01-01

    To deal with this problem a genetic program (GP) based data mining ( DM ) procedure has been invented (Smith 2005). A genetic program is an algorithm...that can operate on the variables. When a GP was used as a DM function in the past to automatically create fuzzy decision trees, the Report...rules represents an approach to the determining the effect of linguistic imprecision, i.e., the inability of experts to provide crisp rules. The

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

    USGS Publications Warehouse

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

    2003-01-01

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

  20. Rescue complex for coal mines

    NASA Astrophysics Data System (ADS)

    Yungmeyster, D. A.; Urazbakhtin, R. Yu

    2017-10-01

    The mining industry was potentially dangerous at all times, even with the use of modern equipment in mines, accidents continue to occur, including catastrophic ones. Accidents in mines are due to the presence of specific features in the conduct of mining operations. These include the inconsistency of mining and geological conditions, the contamination of the mine atmosphere due to the release of gases from minerals, the presence of self-igniting coal strata, which creates the danger of underground fires, gas explosions. The main cause of accidents is the irresponsibility of both the manager and the personnel who violate the safety rules during mining operations.

  1. 76 FR 71535 - Taking of Marine Mammals Incidental to Specified Activities; U.S. Marine Corps Training Exercises...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-11-18

    ... small arms, large arms, bombs, rockets, missiles, and pyrotechnics. All munitions used at BT-11 are... shapes each time. Mine simulation shapes include MK76, MK80 series, and BDU practice bombs ranging from... disabling enemy ships or boats. During training, fixed wing or rotary wing aircraft deliver bombs against...

  2. Techniques of Acceleration for Association Rule Induction with Pseudo Artificial Life Algorithm

    NASA Astrophysics Data System (ADS)

    Kanakubo, Masaaki; Hagiwara, Masafumi

    Frequent patterns mining is one of the important problems in data mining. Generally, the number of potential rules grows rapidly as the size of database increases. It is therefore hard for a user to extract the association rules. To avoid such a difficulty, we propose a new method for association rule induction with pseudo artificial life approach. The proposed method is to decide whether there exists an item set which contains N or more items in two transactions. If it exists, a series of item sets which are contained in the part of transactions will be recorded. The iteration of this step contributes to the extraction of association rules. It is not necessary to calculate the huge number of candidate rules. In the evaluation test, we compared the extracted association rules using our method with the rules using other algorithms like Apriori algorithm. As a result of the evaluation using huge retail market basket data, our method is approximately 10 and 20 times faster than the Apriori algorithm and many its variants.

  3. Grants for adaptive sports programs for disabled veterans and disabled members of the Armed Forces. Final rule.

    PubMed

    2015-05-04

    This final rule amends Department of Veterans Affairs (VA) regulations to establish a new program to provide grants to eligible entities to provide adaptive sports activities to disabled veterans and disabled members of the Armed Forces. This rulemaking is necessary to implement a change in the law that authorizes VA to make grants to entities other than the United States Olympic Committee for adaptive sports programs. It establishes procedures for evaluating grant applications under this grant program, and otherwise administering the grant program. This rule implements section 5 of the VA Expiring Authorities Extension Act of 2013.

  4. Java implementation of Class Association Rule algorithms

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

    Tamura, Makio

    2007-08-30

    Java implementation of three Class Association Rule mining algorithms, NETCAR, CARapriori, and clustering based rule mining. NETCAR algorithm is a novel algorithm developed by Makio Tamura. The algorithm is discussed in a paper: UCRL-JRNL-232466-DRAFT, and would be published in a peer review scientific journal. The software is used to extract combinations of genes relevant with a phenotype from a phylogenetic profile and a phenotype profile. The phylogenetic profiles is represented by a binary matrix and a phenotype profile is represented by a binary vector. The present application of this software will be in genome analysis, however, it could be appliedmore » more generally.« less

  5. Handling Data Skew in MapReduce Cluster by Using Partition Tuning

    PubMed

    Gao, Yufei; Zhou, Yanjie; Zhou, Bing; Shi, Lei; Zhang, Jiacai

    2017-01-01

    The healthcare industry has generated large amounts of data, and analyzing these has emerged as an important problem in recent years. The MapReduce programming model has been successfully used for big data analytics. However, data skew invariably occurs in big data analytics and seriously affects efficiency. To overcome the data skew problem in MapReduce, we have in the past proposed a data processing algorithm called Partition Tuning-based Skew Handling (PTSH). In comparison with the one-stage partitioning strategy used in the traditional MapReduce model, PTSH uses a two-stage strategy and the partition tuning method to disperse key-value pairs in virtual partitions and recombines each partition in case of data skew. The robustness and efficiency of the proposed algorithm were tested on a wide variety of simulated datasets and real healthcare datasets. The results showed that PTSH algorithm can handle data skew in MapReduce efficiently and improve the performance of MapReduce jobs in comparison with the native Hadoop, Closer, and locality-aware and fairness-aware key partitioning (LEEN). We also found that the time needed for rule extraction can be reduced significantly by adopting the PTSH algorithm, since it is more suitable for association rule mining (ARM) on healthcare data. © 2017 Yufei Gao et al.

  6. Handling Data Skew in MapReduce Cluster by Using Partition Tuning.

    PubMed

    Gao, Yufei; Zhou, Yanjie; Zhou, Bing; Shi, Lei; Zhang, Jiacai

    2017-01-01

    The healthcare industry has generated large amounts of data, and analyzing these has emerged as an important problem in recent years. The MapReduce programming model has been successfully used for big data analytics. However, data skew invariably occurs in big data analytics and seriously affects efficiency. To overcome the data skew problem in MapReduce, we have in the past proposed a data processing algorithm called Partition Tuning-based Skew Handling (PTSH). In comparison with the one-stage partitioning strategy used in the traditional MapReduce model, PTSH uses a two-stage strategy and the partition tuning method to disperse key-value pairs in virtual partitions and recombines each partition in case of data skew. The robustness and efficiency of the proposed algorithm were tested on a wide variety of simulated datasets and real healthcare datasets. The results showed that PTSH algorithm can handle data skew in MapReduce efficiently and improve the performance of MapReduce jobs in comparison with the native Hadoop, Closer, and locality-aware and fairness-aware key partitioning (LEEN). We also found that the time needed for rule extraction can be reduced significantly by adopting the PTSH algorithm, since it is more suitable for association rule mining (ARM) on healthcare data.

  7. Handling Data Skew in MapReduce Cluster by Using Partition Tuning

    PubMed Central

    Zhou, Yanjie; Zhou, Bing; Shi, Lei

    2017-01-01

    The healthcare industry has generated large amounts of data, and analyzing these has emerged as an important problem in recent years. The MapReduce programming model has been successfully used for big data analytics. However, data skew invariably occurs in big data analytics and seriously affects efficiency. To overcome the data skew problem in MapReduce, we have in the past proposed a data processing algorithm called Partition Tuning-based Skew Handling (PTSH). In comparison with the one-stage partitioning strategy used in the traditional MapReduce model, PTSH uses a two-stage strategy and the partition tuning method to disperse key-value pairs in virtual partitions and recombines each partition in case of data skew. The robustness and efficiency of the proposed algorithm were tested on a wide variety of simulated datasets and real healthcare datasets. The results showed that PTSH algorithm can handle data skew in MapReduce efficiently and improve the performance of MapReduce jobs in comparison with the native Hadoop, Closer, and locality-aware and fairness-aware key partitioning (LEEN). We also found that the time needed for rule extraction can be reduced significantly by adopting the PTSH algorithm, since it is more suitable for association rule mining (ARM) on healthcare data. PMID:29065568

  8. 76 FR 45195 - International Traffic in Arms Regulations: Electronic Payment of Registration Fees

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-07-28

    ... DEPARTMENT OF STATE 22 CFR Parts 120, 122, 123, and 129 RIN 1400-AC74 [Public Notice 7538] International Traffic in Arms Regulations: Electronic Payment of Registration Fees AGENCY: Department of State. ACTION: Final rule. SUMMARY: The Department of State is amending the International Traffic in Arms...

  9. NIOSH comments to DOL on the Mine Safety and Health Administration's proposed rule on air quality, chemical substances, and respiratory protection standards by J. D. Millar, March 1, 1990

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

    Not Available

    The testimony concerns the views of NIOSH regarding the Mine Safety and Health Administration (MSHA) proposed rule on permissible exposure limits; exposure monitoring, abrasive blasting; drill dust control; dangerous atmospheres; and prohibited areas for food and beverages. NIOSH continues to endorse the recommended exposure limit of 1 part per million (ppm) as a 15 minute short term exposure limit for nitrogen-dioxide (10102440). NIOSH supports MSHA in proposing an 8 hour time weighted average of 25ppm for nitric-oxide (10102439). NIOSH supports MSHA in proposing a limit of 35ppm as an 8 hour time weighted average (TWA) for carbon-monoxide (630080) and recommendsmore » that sulfur-dioxide (7446095) exposure be limited to 0.5ppm as an 8 hour TWA. NIOSH recommends that routine air monitoring be required on a periodic basis. NIOSH recommends that mine operators be required to establish a written exposure monitoring plan for each facility that outlines where area and personal samples should be taken, how many samples should be taken, and the implementation of the remaining portions of the proposed rule change. NIOSH supports the rules for abrasive blasting for both coal and metal/nonmetal mines and has identified several substitutive materials for silica sand that could be used in abrasive blasting.« less

  10. 30 CFR 77.1600 - Loading and haulage; general.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... permitted on haulage roads and at loading or dumping locations. (b) Traffic rules, signals, and warning signs shall be standardized at each mine and posted. (c) Where side or overhead clearances on any haulage road or at any loading or dumping location at the mine are hazardous to mine workers, such areas...

  11. 30 CFR 77.1600 - Loading and haulage; general.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... permitted on haulage roads and at loading or dumping locations. (b) Traffic rules, signals, and warning signs shall be standardized at each mine and posted. (c) Where side or overhead clearances on any haulage road or at any loading or dumping location at the mine are hazardous to mine workers, such areas...

  12. 30 CFR 77.1600 - Loading and haulage; general.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... permitted on haulage roads and at loading or dumping locations. (b) Traffic rules, signals, and warning signs shall be standardized at each mine and posted. (c) Where side or overhead clearances on any haulage road or at any loading or dumping location at the mine are hazardous to mine workers, such areas...

  13. 30 CFR 77.1600 - Loading and haulage; general.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... permitted on haulage roads and at loading or dumping locations. (b) Traffic rules, signals, and warning signs shall be standardized at each mine and posted. (c) Where side or overhead clearances on any haulage road or at any loading or dumping location at the mine are hazardous to mine workers, such areas...

  14. 30 CFR 77.1600 - Loading and haulage; general.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... permitted on haulage roads and at loading or dumping locations. (b) Traffic rules, signals, and warning signs shall be standardized at each mine and posted. (c) Where side or overhead clearances on any haulage road or at any loading or dumping location at the mine are hazardous to mine workers, such areas...

  15. 30 CFR 944.30 - State-Federal Cooperative Agreement.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... Division of Oil, Gas, and Mining (DOGM) will be responsible for administering this Agreement on behalf of..., Final Rules of the Board of Oil, Gas and Mining, UMC/SMC 700 et seq. [52 FR 7850, Mar. 13, 1987] ... INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE UTAH § 944.30 State...

  16. 30 CFR 944.30 - State-Federal Cooperative Agreement.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... Division of Oil, Gas, and Mining (DOGM) will be responsible for administering this Agreement on behalf of..., Final Rules of the Board of Oil, Gas and Mining, UMC/SMC 700 et seq. [52 FR 7850, Mar. 13, 1987] ... INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE UTAH § 944.30 State...

  17. 30 CFR 944.30 - State-Federal Cooperative Agreement.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... Division of Oil, Gas, and Mining (DOGM) will be responsible for administering this Agreement on behalf of..., Final Rules of the Board of Oil, Gas and Mining, UMC/SMC 700 et seq. [52 FR 7850, Mar. 13, 1987] ... INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE UTAH § 944.30 State...

  18. 30 CFR 944.30 - State-Federal Cooperative Agreement.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... Division of Oil, Gas, and Mining (DOGM) will be responsible for administering this Agreement on behalf of..., Final Rules of the Board of Oil, Gas and Mining, UMC/SMC 700 et seq. [52 FR 7850, Mar. 13, 1987] ... INTERIOR PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE UTAH § 944.30 State...

  19. Data Mining and Privacy of Social Network Sites' Users: Implications of the Data Mining Problem.

    PubMed

    Al-Saggaf, Yeslam; Islam, Md Zahidul

    2015-08-01

    This paper explores the potential of data mining as a technique that could be used by malicious data miners to threaten the privacy of social network sites (SNS) users. It applies a data mining algorithm to a real dataset to provide empirically-based evidence of the ease with which characteristics about the SNS users can be discovered and used in a way that could invade their privacy. One major contribution of this article is the use of the decision forest data mining algorithm (SysFor) to the context of SNS, which does not only build a decision tree but rather a forest allowing the exploration of more logic rules from a dataset. One logic rule that SysFor built in this study, for example, revealed that anyone having a profile picture showing just the face or a picture showing a family is less likely to be lonely. Another contribution of this article is the discussion of the implications of the data mining problem for governments, businesses, developers and the SNS users themselves.

  20. Promoter Sequences Prediction Using Relational Association Rule Mining

    PubMed Central

    Czibula, Gabriela; Bocicor, Maria-Iuliana; Czibula, Istvan Gergely

    2012-01-01

    In this paper we are approaching, from a computational perspective, the problem of promoter sequences prediction, an important problem within the field of bioinformatics. As the conditions for a DNA sequence to function as a promoter are not known, machine learning based classification models are still developed to approach the problem of promoter identification in the DNA. We are proposing a classification model based on relational association rules mining. Relational association rules are a particular type of association rules and describe numerical orderings between attributes that commonly occur over a data set. Our classifier is based on the discovery of relational association rules for predicting if a DNA sequence contains or not a promoter region. An experimental evaluation of the proposed model and comparison with similar existing approaches is provided. The obtained results show that our classifier overperforms the existing techniques for identifying promoter sequences, confirming the potential of our proposal. PMID:22563233

  1. Rule Mining Techniques to Predict Prokaryotic Metabolic Pathways.

    PubMed

    Saidi, Rabie; Boudellioua, Imane; 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.

  2. Basic Outline Plan for Blacklist Operations to Occupy Japan Proper and Korea after Surrender or Collapse: Annexes

    DTIC Science & Technology

    1945-08-08

    development, manufacture , importation and exportation of arms, ammunition and. irplements of war. 3. Cause the delivery of all arms in the possession...and equi ment I i i 1 i-’. I -rl - (S) Establish and define safety lanes through all mined areas, both on leand and sea, and subsequently render

  3. 78 FR 19224 - Taking of Marine Mammals Incidental to Specified Activities; U.S. Marine Corps Training Exercises...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-03-29

    ... arms, large arms, bombs, rockets, missiles, and pyrotechnics. All munitions used at BT-11 are inert... shapes each time. Mine simulation shapes include MK76, MK80 series, and BDU practice bombs ranging from... bombs against surface maritime targets at BT-9 or BT-11,day or night, using either unguided or precision...

  4. China and Proliferation of Weapons of Mass Destruction and Missiles: Policy Issues

    DTIC Science & Technology

    2014-01-03

    countries) for secret nuclear weapons facilities, while experts from China worked at a uranium mine at Saghand and a centrifuge facility (for uranium...declaration from North Korea for outside verification. 89 Barbara Opall -Rome and...that the China Guangfa Bank engaged in business with the DPRK’s arms dealer, Global Trading and Technology (a front for Korea Mining Development

  5. 43 CFR 4.1272 - Interlocutory appeals.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... PROCEDURES Special Rules Applicable to Surface Coal Mining Hearings and Appeals Appeals to the Board from... modification of the administrative law judge's interlocutory ruling or order, the jurisdiction of the Board...

  6. Thumb rule of visual angle: a new confirmation.

    PubMed

    Groot, C; Ortega, F; Beltran, F S

    1994-02-01

    The classical thumb rule of visual angle was reexamined. Hence, the visual angle was measured as a function of a thumb's width and the distance between eye and thumb. The measurement of a thumb's width when held at arm's length was taken on 67 second-year students of psychology. The visual angle was about 2 degrees as R. P. O'Shea confirmed in 1991. Also, we confirmed a linear relationship between the size of a thumb's width at arm's length and the visual angle.

  7. A New Framework for Textual Information Mining over Parse Trees. CRESST Report 805

    ERIC Educational Resources Information Center

    Mousavi, Hamid; Kerr, Deirdre; Iseli, Markus R.

    2011-01-01

    Textual information mining is a challenging problem that has resulted in the creation of many different rule-based linguistic query languages. However, these languages generally are not optimized for the purpose of text mining. In other words, they usually consider queries as individuals and only return raw results for each query. Moreover they…

  8. The spiral arms of the Milky Way: The relative location of each different arm tracer within a typical spiral arm width

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

    Vallée, Jacques P., E-mail: jacques.vallee@nrc-cnrc.gc.ca

    2014-07-01

    From the Sun's location in the Galactic disk, different arm tracers (CO, H I, hot dust, etc.) have been employed to locate a tangent to each spiral arm. Using all various and different observed spiral arm tracers (as published elsewhere), we embark on a new goal, namely the statistical analysis of these published data (data mining) to statistically compute the mean location of each spiral arm tracer. We show for a typical arm cross-cut, a separation of 400 pc between the mid-arm and the dust lane (at the inner edge of the arm, toward the Galactic center). Are some armsmore » major and others minor? Separating arms into two sets, as suggested by some, we find the same arm widths between the two sets. Our interpretation is that we live in a multiple (four-arm) spiral (logarithmic) pattern (around a pitch angle of 12°) for the stars and gas in the Milky Way, with a sizable interarm separation (around 3 kpc) at the Sun's location and the same arm width for each arm (near 400 pc from mid-arm to dust lane).« less

  9. Documents for SBAR Panel: CERCLA 108(b) Hard Rock Mining Financial Assurance Rule

    EPA Pesticide Factsheets

    SBAR panel documents for small business advocacy review panel on the financial responsibilities of the hard rock mining industry under Section 108(b) of the Comprehensive Environmental Response, Compensation, and Liability Act

  10. Preference Mining Using Neighborhood Rough Set Model on Two Universes.

    PubMed

    Zeng, Kai

    2016-01-01

    Preference mining plays an important role in e-commerce and video websites for enhancing user satisfaction and loyalty. Some classical methods are not available for the cold-start problem when the user or the item is new. In this paper, we propose a new model, called parametric neighborhood rough set on two universes (NRSTU), to describe the user and item data structures. Furthermore, the neighborhood lower approximation operator is used for defining the preference rules. Then, we provide the means for recommending items to users by using these rules. Finally, we give an experimental example to show the details of NRSTU-based preference mining for cold-start problem. The parameters of the model are also discussed. The experimental results show that the proposed method presents an effective solution for preference mining. In particular, NRSTU improves the recommendation accuracy by about 19% compared to the traditional method.

  11. Analysis of North Atlantic tropical cyclone intensify change using data mining

    NASA Astrophysics Data System (ADS)

    Tang, Jiang

    Tropical cyclones (TC), especially when their intensity reaches hurricane scale, can become a costly natural hazard. Accurate prediction of tropical cyclone intensity is very difficult because of inadequate observations on TC structures, poor understanding of physical processes, coarse model resolution and inaccurate initial conditions, etc. This study aims to tackle two factors that account for the underperformance of current TC intensity forecasts: (1) inadequate observations of TC structures, and (2) deficient understanding of the underlying physical processes governing TC intensification. To tackle the problem of inadequate observations of TC structures, efforts have been made to extract vertical and horizontal structural parameters of latent heat release from Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) data products. A case study of Hurricane Isabel (2003) was conducted first to explore the feasibility of using the 3D TC structure information in predicting TC intensification. Afterwards, several structural parameters were extracted from 53 TRMM PR 2A25 observations on 25 North Atlantic TCs during the period of 1998 to 2003. A new generation of multi-correlation data mining algorithm (Apriori and its variations) was applied to find roles of the latent heat release structure in TC intensification. The results showed that the buildup of TC energy is indicated by the height of the convective tower, and the relative low latent heat release at the core area and around the outer band. Adverse conditions which prevent TC intensification include the following: (1) TC entering a higher latitude area where the underlying sea is relative cold, (2) TC moving too fast to absorb the thermal energy from the underlying sea, or (3) strong energy loss at the outer band. When adverse conditions and amicable conditions reached equilibrium status, tropical cyclone intensity would remain stable. The dataset from Statistical Hurricane Intensity Prediction Scheme (SHIPS) covering the period of 1982-2003 and the Apriori-based association rule mining algorithm were used to study the associations of underlying geophysical characteristics with the intensity change of tropical cyclones. The data have been stratified into 6 TC categories from tropical depression to category 4 hurricanes based on their strength. The result showed that the persistence of intensity change in the past and the strength of vertical shear in the environment are the most prevalent factors for all of the 6 TC categories. Hyper-edge searching had found 3 sets of parameters which showed strong intramural binds. Most of the parameters used in SHIPS model have a consistent "I-W" relation over different TC categories, indicating a consistent function of those parameters in TC development. However, the "I-W" relations of the relative momentum flux and the meridional motion change from tropical storm stage to hurricane stage, indicating a change in the role of those two parameters in TC development. Because rapid intensification (RI) is a major source of errors when predicting hurricane intensity, the association rule mining algorithm was performed on RI versus non-RI tropical cyclone cases using the same SHIPS dataset. The results had been compared with those from the traditional statistical analysis conducted by Kaplan and DeMaria (2003). The rapid intensification rule with 5 RI conditions proposed by the traditional statistical analysis was found by the association rule mining in this study as well. However, further analysis showed that the 5 RI conditions can be replaced by another association rule using fewer conditions but with a higher RI probability (RIP). This means that the rule with all 5 constraints found by Kaplan and DeMaria is not optimal, and the association rule mining technique can find a rule with fewer constraints yet fits more RI cases. The further analysis with the highest RIPs over different numbers of conditions has demonstrated that the interactions among multiple factors are responsible for the RI process of TCs. However, the influence of factors saturates at certain numbers. This study has shown successful data mining examples in studying tropical cyclone intensification using association rules. The higher RI probability with fewer conditions found by association rule technique is significant. This work demonstrated that data mining techniques can be used as an efficient exploration method to generate hypotheses, and that statistical analysis should be performed to confirm the hypotheses, as is generally expected for data mining applications.

  12. Automobile or Other Conveyance and Adaptive Equipment Certificate of Eligibility for Veterans or Members of the Armed Forces With Amyotrophic Lateral Sclerosis Connected to Military Service. Final rule.

    PubMed

    2016-01-13

    The Department of Veterans Affairs (VA) published an Interim Final Rule on February 25, 2015, to amend its adjudication regulations to provide a certificate of eligibility for financial assistance in the purchase of an automobile or other conveyance and adaptive equipment for all veterans with service-connected amyotrophic lateral sclerosis (ALS) and servicemembers serving on active duty with ALS. The amendment authorized automatic issuance of a certificate of eligibility for financial assistance in the purchase of an automobile or other conveyance and adaptive equipment to all veterans with service-connected ALS and members of the Armed Forces serving on active duty with ALS. The intent of this final rule is to confirm the amendment made by the interim final rule without change.

  13. Weighted Association Rule Mining for Item Groups with Different Properties and Risk Assessment for Networked Systems

    NASA Astrophysics Data System (ADS)

    Kim, Jungja; Ceong, Heetaek; Won, Yonggwan

    In market-basket analysis, weighted association rule (WAR) discovery can mine the rules that include more beneficial information by reflecting item importance for special products. In the point-of-sale database, each transaction is composed of items with similar properties, and item weights are pre-defined and fixed by a factor such as the profit. However, when items are divided into more than one group and the item importance must be measured independently for each group, traditional weighted association rule discovery cannot be used. To solve this problem, we propose a new weighted association rule mining methodology. The items should be first divided into subgroups according to their properties, and the item importance, i.e. item weight, is defined or calculated only with the items included in the subgroup. Then, transaction weight is measured by appropriately summing the item weights from each subgroup, and the weighted support is computed as the fraction of the transaction weights that contains the candidate items relative to the weight of all transactions. As an example, our proposed methodology is applied to assess the vulnerability to threats of computer systems that provide networked services. Our algorithm provides both quantitative risk-level values and qualitative risk rules for the security assessment of networked computer systems using WAR discovery. Also, it can be widely used for new applications with many data sets in which the data items are distinctly separated.

  14. Taiwan: Major U.S. Arms Sales Since 1990

    DTIC Science & Technology

    2010-09-28

    howitzers; 54 AAV7A1 amphibious assault vehicles; AN/ALE-50 electronic countermeasure (ECM) systems for F-16s; and 12 MH-53 mine -sweeping helicopters...268 Commercial sale. Opall Barbara and David Silverberg, “Taiwanese May Soon Coproduce...missiles $37 01/29 (60) MIDS (follow-on technical support for Posheng C4ISR systems) $340 01/29 (2) Osprey-class mine hunting ships (refurbished and

  15. Taiwan: Major U.S. Arms Sales Since 1990

    DTIC Science & Technology

    2014-08-29

    amphibious assault vehicles; AN/ALE-50 electronic countermeasure (ECM) systems for F-16s; and 12 MH-53 mine -sweeping helicopters. President Bush...54 243 Commercial sale. Opall Barbara and David Silverberg, “Taiwanese May Soon Coproduce Patriot...systems) $340 01/29 (2) Osprey-class mine hunting ships (refurbished and upgraded) $105 2011 09/21 Retrofit of 145 F-16A/B fighters, with 176 AESA

  16. ARM Operations and Engineering Procedure Mobile Facility Site Startup

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

    Voyles, Jimmy W

    2015-05-01

    This procedure exists to define the key milestones, necessary steps, and process rules required to commission and operate an Atmospheric Radiation Measurement (ARM) Mobile Facility (AMF), with a specific focus toward on-time product delivery to the ARM Data Archive. The overall objective is to have the physical infrastructure, networking and communications, and instrument calibration, grooming, and alignment (CG&A) completed with data products available from the ARM Data Archive by the Operational Start Date milestone.

  17. A comprehensive review on privacy preserving data mining.

    PubMed

    Aldeen, Yousra Abdul Alsahib S; Salleh, Mazleena; Razzaque, Mohammad Abdur

    2015-01-01

    Preservation of privacy in data mining has emerged as an absolute prerequisite for exchanging confidential information in terms of data analysis, validation, and publishing. Ever-escalating internet phishing posed severe threat on widespread propagation of sensitive information over the web. Conversely, the dubious feelings and contentions mediated unwillingness of various information providers towards the reliability protection of data from disclosure often results utter rejection in data sharing or incorrect information sharing. This article provides a panoramic overview on new perspective and systematic interpretation of a list published literatures via their meticulous organization in subcategories. The fundamental notions of the existing privacy preserving data mining methods, their merits, and shortcomings are presented. The current privacy preserving data mining techniques are classified based on distortion, association rule, hide association rule, taxonomy, clustering, associative classification, outsourced data mining, distributed, and k-anonymity, where their notable advantages and disadvantages are emphasized. This careful scrutiny reveals the past development, present research challenges, future trends, the gaps and weaknesses. Further significant enhancements for more robust privacy protection and preservation are affirmed to be mandatory.

  18. [Research of bleeding volume and method in blood-letting acupuncture therapy based on data mining].

    PubMed

    Liu, Xin; Jia, Chun-Sheng; Wang, Jian-Ling; Du, Yu-Zhu; Zhang, Xiao-Xu; Shi, Jing; Li, Xiao-Feng; Sun, Yan-Hui; Zhang, Shen; Zhang, Xuan-Ping; Gang, Wei-Juan

    2014-03-01

    Through computer-based technology and data mining method, with treatment in cases of bloodletting acupuncture therapy in collected literature as sample data, the association rule in data mining was applied. According to self-built database platform, the data was input, arranged and summarized, and eventually required data was acquired to perform the data mining of bleeding volume and method in blood-letting acupuncture therapy, which summarized its application rules and clinical values to provide better guide for clinical practice. There were 9 kinds of blood-letting tools in the literature, in which the frequency of three-edge needle was the highest, accounting for 84.4% (1239/1468). The bleeding volume was classified into six levels, in which less volume (less than 0.1 mL) had the highest frequency (401 times). According to the results of the data mining, blood-letting acupuncture therapy was widely applied in clinical practice of acupuncture, in which use of three-edge needle and less volume (less than 0.1 mL) of blood were the most common, however, there was no central tendency in general.

  19. 20 CFR 410.681 - Change of ruling or legal precedent.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... 20 Employees' Benefits 2 2011-04-01 2011-04-01 false Change of ruling or legal precedent. 410.681 Section 410.681 Employees' Benefits SOCIAL SECURITY ADMINISTRATION FEDERAL COAL MINE HEALTH AND SAFETY ACT..., Administrative Review, Finality of Decisions, and Representation of Parties § 410.681 Change of ruling or legal...

  20. 20 CFR 410.681 - Change of ruling or legal precedent.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... 20 Employees' Benefits 2 2010-04-01 2010-04-01 false Change of ruling or legal precedent. 410.681 Section 410.681 Employees' Benefits SOCIAL SECURITY ADMINISTRATION FEDERAL COAL MINE HEALTH AND SAFETY ACT..., Administrative Review, Finality of Decisions, and Representation of Parties § 410.681 Change of ruling or legal...

  1. Japanese Aggression in Asia (1895-1930). Japan’s Dream of ’Hakko Ichuo’ (Eight Corners of the World under Japanese Rule).

    DTIC Science & Technology

    1980-12-01

    the British Navy was also of significant value, for then Britannia still ruled the waves. The huge indemnity received from the Chinese played an...11 among the sons, the eldest took all and the second and third sons became either factory or mine workers or apprentices of a merchant. When...warehouses, spin- ning, paper and sugar mills, all based on the large profits which came from banking, mining and foreign trade. Mitsubishi had its

  2. Saving Life, Limb, and Eyesight: Assessing the Medical Rules of Eligibility During Armed Conflict.

    PubMed

    Gross, Michael L

    2017-10-01

    Medical rules of eligibility permit severely injured Iraqi and Afghan nationals to receive care in Coalition medical facilities only if bed space is available and their injuries result directly from Coalition fire. The first rule favors Coalition soldiers over host-nation nationals and contradicts the principle of impartial, needs-based medical care. To justify preferential care for compatriots, wartime medicine invokes associative obligations of care that favor friends, family, and comrades-in-arms. Associative obligations have little place in peacetime medical care but significantly affect wartime medicine. The second rule suggests liability for collateral harm that is unsupported by international law and military ethics. Absent liability, there are pragmatic reasons to offer medical care to injured local civilians if it quells resentment and cements support for Coalition forces. In contrast to peacetime medicine, military necessity and associative obligations outweigh distributive principles based on medical need during war.

  3. Taiwan: Major U.S. Arms Sales Since 1990

    DTIC Science & Technology

    2013-07-03

    amphibious assault vehicles; AN/ALE-50 electronic countermeasure (ECM) systems for F-16s; and 12 MH-53 mine -sweeping helicopters. President Bush...235 Commercial sale. Opall Barbara and David Silverberg, “Taiwanese May Soon Coproduce Patriot,” Defense News, February 22-28...systems) $340 01/29 (2) Osprey-class mine hunting ships (refurbished and upgraded) $105 2011 09/21 Retrofit of 145 F-16A/B fighters, with 176 AESA

  4. British Defense Policy: A New Approach?

    DTIC Science & Technology

    1988-12-14

    inherent to their well-being, was also acknowledged by the remainder of the world in its attitude toward Britain. Is not "Rule Britannia , Britannia ...Castle Class 1 1 Island Class 7 43 Mine -Counter Minesweepers 2 2 Mine River Class 12 Ton Class 10 3 Hunt Class 12 1 Patrol Craft Bird Class 5 Coastal 15...submarine warfare carriers, assault ships, and mine -counter mine vessels. British naval aircraft is as depicted in Table 2. Table 2. Aircraft of the Royal

  5. 77 FR 54490 - Alabama Regulatory Program

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-09-05

    ... Mining Reclamation and Enforcement, Interior. ACTION: Proposed rule; public comment period and opportunity for public hearing on proposed amendment. SUMMARY: We, the Office of Surface Mining Reclamation... will follow for the public hearing, if one is requested. DATES: We will accept written comments on this...

  6. Efficient discovery of risk patterns in medical data.

    PubMed

    Li, Jiuyong; Fu, Ada Wai-chee; Fahey, Paul

    2009-01-01

    This paper studies a problem of efficiently discovering risk patterns in medical data. Risk patterns are defined by a statistical metric, relative risk, which has been widely used in epidemiological research. To avoid fruitless search in the complete exploration of risk patterns, we define optimal risk pattern set to exclude superfluous patterns, i.e. complicated patterns with lower relative risk than their corresponding simpler form patterns. We prove that mining optimal risk pattern sets conforms an anti-monotone property that supports an efficient mining algorithm. We propose an efficient algorithm for mining optimal risk pattern sets based on this property. We also propose a hierarchical structure to present discovered patterns for the easy perusal by domain experts. The proposed approach is compared with two well-known rule discovery methods, decision tree and association rule mining approaches on benchmark data sets and applied to a real world application. The proposed method discovers more and better quality risk patterns than a decision tree approach. The decision tree method is not designed for such applications and is inadequate for pattern exploring. The proposed method does not discover a large number of uninteresting superfluous patterns as an association mining approach does. The proposed method is more efficient than an association rule mining method. A real world case study shows that the method reveals some interesting risk patterns to medical practitioners. The proposed method is an efficient approach to explore risk patterns. It quickly identifies cohorts of patients that are vulnerable to a risk outcome from a large data set. The proposed method is useful for exploratory study on large medical data to generate and refine hypotheses. The method is also useful for designing medical surveillance systems.

  7. Bandit strategies evaluated in the context of clinical trials in rare life-threatening diseases.

    PubMed

    Villar, Sofía S

    2018-04-01

    In a rare life-threatening disease setting the number of patients in the trial is a high proportion of all patients with the condition (if not all of them). Further, this number is usually not enough to guarantee the required statistical power to detect a treatment effect of a meaningful size. In such a context, the idea of prioritizing patient benefit over hypothesis testing as the goal of the trial can lead to a trial design that produces useful information to guide treatment, even if it does not do so with the standard levels of statistical confidence. The idealised model to consider such an optimal design of a clinical trial is known as a classic multi-armed bandit problem with a finite patient horizon and a patient benefit objective function. Such a design maximises patient benefit by balancing the learning and earning goals as data accumulates and given the patient horizon. On the other hand, optimally solving such a model has a very high computational cost (many times prohibitive) and more importantly, a cumbersome implementation, even for populations as small as a hundred patients. Several computationally feasible heuristic rules to address this problem have been proposed over the last 40 years in the literature. In this article we study a novel heuristic approach to solve it based on the reformulation of the problem as a Restless bandit problem and the derivation of its corresponding Whittle index rule. Such rule was recently proposed in the context of a clinical trial in Villar et al (2015). We perform extensive computational studies to compare through both exact value calculations and simulated values the performance of this rule, other index rules and simpler heuristics previously proposed in the literature. Our results suggest that for the two and three-armed case and a patient horizon less or equal than a hundred patients, all index rules are a priori practically identical in terms of the expected proportion of success attained when all arms start with a uniform prior. However, we find that a posteriori, for specific values of the parameters of interest, the index policies outperform the simpler rules in every instance and specially so in the case of many arms and a larger, though still relatively small, total number of patients with the diseases. The very good performance of bandit rules in terms of patient benefit (i.e. expected number of successes and mean number of patients allocated to the best arm, if it exists) makes them very appealing in context of the challenge posed by drug development for rare life threatening diseases.

  8. Medication regularity of pulmonary fibrosis treatment by contemporary traditional Chinese medicine experts based on data mining.

    PubMed

    Zhang, Suxian; Wu, Hao; Liu, Jie; Gu, Huihui; Li, Xiujuan; Zhang, Tiansong

    2018-03-01

    Treatment of pulmonary fibrosis by traditional Chinese medicine (TCM) has accumulated important experience. Our interest is in exploring the medication regularity of contemporary Chinese medical specialists treating pulmonary fibrosis. Through literature search, medical records from TCM experts who treat pulmonary fibrosis, which were published in Chinese and English medical journals, were selected for this study. As the object of study, a database was established after analysing the records. After data cleaning, the rules of medicine in the treatment of pulmonary fibrosis in medical records of TCM were explored by using data mining technologies such as frequency analysis, association rule analysis, and link analysis. A total of 124 medical records from 60 doctors were selected in this study; 263 types of medicinals were used a total of 5,455 times; the herbs that were used more than 30 times can be grouped into 53 species and were used a total of 3,681 times. Using main medicinals cluster analysis, medicinals were divided into qi-tonifying, yin-tonifying, blood-activating, phlegm-resolving, cough-suppressing, panting-calming, and ten other major medicinal categories. According to the set conditions, a total of 62 drug compatibility rules have been obtained, involving mainly qi-tonifying, yin-tonifying, blood-activating, phlegm-resolving, qi-descending, and panting-calming medicinals, as well as other medicinals used in combination. The results of data mining are consistent with clinical practice and it is feasible to explore the medical rules applicable to the treatment of pulmonary fibrosis in medical records of TCM by data mining.

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

    NASA Astrophysics Data System (ADS)

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

    2013-06-01

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

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

    PubMed

    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.

  11. 26 CFR 1.614-3 - Rules relating to separate operating mineral interests in the case of mines.

    Code of Federal Regulations, 2010 CFR

    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...

  12. 30 CFR 56.18006 - New employees.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... New employees. New employees shall be indoctrinated in safety rules and safe work procedures. ... 30 Mineral Resources 1 2010-07-01 2010-07-01 false New employees. 56.18006 Section 56.18006 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR METAL AND NONMETAL MINE...

  13. Power System Transient Stability Based on Data Mining Theory

    NASA Astrophysics Data System (ADS)

    Cui, Zhen; Shi, Jia; Wu, Runsheng; Lu, Dan; Cui, Mingde

    2018-01-01

    In order to study the stability of power system, a power system transient stability based on data mining theory is designed. By introducing association rules analysis in data mining theory, an association classification method for transient stability assessment is presented. A mathematical model of transient stability assessment based on data mining technology is established. Meanwhile, combining rule reasoning with classification prediction, the method of association classification is proposed to perform transient stability assessment. The transient stability index is used to identify the samples that cannot be correctly classified in association classification. Then, according to the critical stability of each sample, the time domain simulation method is used to determine the state, so as to ensure the accuracy of the final results. The results show that this stability assessment system can improve the speed of operation under the premise that the analysis result is completely correct, and the improved algorithm can find out the inherent relation between the change of power system operation mode and the change of transient stability degree.

  14. China and Proliferation of Weapons of Mass Destruction and Missiles: Policy Issues

    DTIC Science & Technology

    2012-03-30

    from China worked at a uranium mine at Saghand and a centrifuge facility (for uranium enrichment) near Isfahan, reported the Washington Post (December...Facilities,” China News Agency, September 3, 2007; Xinhua, September 4 and 6, 2007. 99 Barbara Opall -Rome and Vago Muradian, “Bush Privately Lauds...with the DPRK’s arms dealer, Global Trading and Technology (a front for Korea Mining Development Trading Corporation).119 Also, in December 2009

  15. Taiwan: Major U.S. Arms Sales Since 1990

    DTIC Science & Technology

    2013-11-27

    systems for F-16s; and 12 MH-53 mine -sweeping helicopters. President Bush approved four decommissioned Kidd-class destroyers for sale as Excess Defense...239 Commercial sale. Opall Barbara and David Silverberg, “Taiwanese May Soon Coproduce Patriot,” Defense News, February 22-28...340 01/29 (2) Osprey-class mine hunting ships (refurbished and upgraded) $105 2011 09/21 Retrofit of 145 F-16A/B fighters, with 176 AESA radars

  16. 20 CFR 410.703 - Adjudicatory rules for determining entitlement to benefits.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... COAL MINE HEALTH AND SAFETY ACT OF 1969, TITLE IV-BLACK LUNG BENEFITS (1969- ) Rules for the Review of Denied and Pending Claims Under the Black Lung Benefits Reform Act (BLBRA) of 1977 § 410.703 Adjudicatory...

  17. 20 CFR 410.703 - Adjudicatory rules for determining entitlement to benefits.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... COAL MINE HEALTH AND SAFETY ACT OF 1969, TITLE IV-BLACK LUNG BENEFITS (1969- ) Rules for the Review of Denied and Pending Claims Under the Black Lung Benefits Reform Act (BLBRA) of 1977 § 410.703 Adjudicatory...

  18. Shipment of spent nuclear fuel from U.S. Navy ships and submarines to the Idaho National Engineering Laboratory (INEL). Hearing before the Subcommittee on Nuclear Deterrence, Arms Control and Defense Intelligence of the Committee on Armed Services, United States Senate, One Hundred Third Congress, First Session, July 28, 1993

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

    NONE

    1994-12-31

    The purpose of the hearing was to review the impact of the U.S. District Court of Idaho ruling prohibiting receipt of spent nuclear fuel by the Department of Energy (DOE). The court`s ruling enjoined the DOE from receiving spent nuclear fuel, including nuclear fuel from naval surface ships and submarines, at the Idaho National Engineering Laboratory until such time as the DOE completes an environmental impact statement on the transportation, shipment, processing, and storage of spent fuel. Statements of government officials are included. The text of the Court ruling is also included.

  19. 43 CFR 4.1383 - Hearing.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ... 43 Public Lands: Interior 1 2014-10-01 2014-10-01 false Hearing. 4.1383 Section 4.1383 Public Lands: Interior Office of the Secretary of the Interior DEPARTMENT HEARINGS AND APPEALS PROCEDURES Special Rules Applicable to Surface Coal Mining Hearings and Appeals Review of Office of Surface Mining...

  20. 30 CFR 48.6 - Experienced miner training.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    .... (b) Experienced miners must complete the training prescribed in this section before beginning work... to work environment. The course shall include a visit and tour of the mine. The methods of mining... responsibilities of such supervisors and miners' representatives; and an introduction to the operator's rules and...

  1. 43 CFR 3483.6 - Special logical mining unit rules.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... the LMU, of either Federal or non-Federal recoverable coal reserves or a combination thereof, shall be... Section 3483.6 Public Lands: Interior Regulations Relating to Public Lands (Continued) BUREAU OF LAND MANAGEMENT, DEPARTMENT OF THE INTERIOR MINERALS MANAGEMENT (3000) COAL EXPLORATION AND MINING OPERATIONS...

  2. 30 CFR 939.700 - Rhode Island Federal program.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... Rhode Island Federal program. (a) This part contains all rules that are applicable to surface coal... to all surface coal mining and reclamation operations in Rhode Island conducted on non-Federal and... stringent environmental control and regulation of surface coal mining and reclamation operations than do the...

  3. 43 CFR 3483.6 - Special logical mining unit rules.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... the LMU, of either Federal or non-Federal recoverable coal reserves or a combination thereof, shall be... Section 3483.6 Public Lands: Interior Regulations Relating to Public Lands (Continued) BUREAU OF LAND MANAGEMENT, DEPARTMENT OF THE INTERIOR MINERALS MANAGEMENT (3000) COAL EXPLORATION AND MINING OPERATIONS...

  4. 43 CFR 3483.6 - Special logical mining unit rules.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ... the LMU, of either Federal or non-Federal recoverable coal reserves or a combination thereof, shall be... Section 3483.6 Public Lands: Interior Regulations Relating to Public Lands (Continued) BUREAU OF LAND MANAGEMENT, DEPARTMENT OF THE INTERIOR MINERALS MANAGEMENT (3000) COAL EXPLORATION AND MINING OPERATIONS...

  5. 43 CFR 4.1351 - Preliminary finding by OSM.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

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

  6. 43 CFR 3483.6 - Special logical mining unit rules.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... the LMU, of either Federal or non-Federal recoverable coal reserves or a combination thereof, shall be... Section 3483.6 Public Lands: Interior Regulations Relating to Public Lands (Continued) BUREAU OF LAND MANAGEMENT, DEPARTMENT OF THE INTERIOR MINERALS MANAGEMENT (3000) COAL EXPLORATION AND MINING OPERATIONS...

  7. 43 CFR 4.1383 - Hearing.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... 43 Public Lands: Interior 1 2010-10-01 2010-10-01 false Hearing. 4.1383 Section 4.1383 Public Lands: Interior Office of the Secretary of the Interior DEPARTMENT HEARINGS AND APPEALS PROCEDURES Special Rules Applicable to Surface Coal Mining Hearings and Appeals Review of Office of Surface Mining...

  8. Association rule mining on grid monitoring data to detect error sources

    NASA Astrophysics Data System (ADS)

    Maier, Gerhild; Schiffers, Michael; Kranzlmueller, Dieter; Gaidioz, Benjamin

    2010-04-01

    Error handling is a crucial task in an infrastructure as complex as a grid. There are several monitoring tools put in place, which report failing grid jobs including exit codes. However, the exit codes do not always denote the actual fault, which caused the job failure. Human time and knowledge is required to manually trace back errors to the real fault underlying an error. We perform association rule mining on grid job monitoring data to automatically retrieve knowledge about the grid components' behavior by taking dependencies between grid job characteristics into account. Therewith, problematic grid components are located automatically and this information - expressed by association rules - is visualized in a web interface. This work achieves a decrease in time for fault recovery and yields an improvement of a grid's reliability.

  9. Exploration of the association rules mining technique for the signal detection of adverse drug events in spontaneous reporting systems.

    PubMed

    Wang, Chao; Guo, Xiao-Jing; Xu, Jin-Fang; Wu, Cheng; Sun, Ya-Lin; Ye, Xiao-Fei; Qian, Wei; Ma, Xiu-Qiang; Du, Wen-Min; He, Jia

    2012-01-01

    The detection of signals of adverse drug events (ADEs) has increased because of the use of data mining algorithms in spontaneous reporting systems (SRSs). However, different data mining algorithms have different traits and conditions for application. The objective of our study was to explore the application of association rule (AR) mining in ADE signal detection and to compare its performance with that of other algorithms. Monte Carlo simulation was applied to generate drug-ADE reports randomly according to the characteristics of SRS datasets. Thousand simulated datasets were mined by AR and other algorithms. On average, 108,337 reports were generated by the Monte Carlo simulation. Based on the predefined criterion that 10% of the drug-ADE combinations were true signals, with RR equaling to 10, 4.9, 1.5, and 1.2, AR detected, on average, 284 suspected associations with a minimum support of 3 and a minimum lift of 1.2. The area under the receiver operating characteristic (ROC) curve of the AR was 0.788, which was equivalent to that shown for other algorithms. Additionally, AR was applied to reports submitted to the Shanghai SRS in 2009. Five hundred seventy combinations were detected using AR from 24,297 SRS reports, and they were compared with recognized ADEs identified by clinical experts and various other sources. AR appears to be an effective method for ADE signal detection, both in simulated and real SRS datasets. The limitations of this method exposed in our study, i.e., a non-uniform thresholds setting and redundant rules, require further research.

  10. 75 FR 26828 - Self-Regulatory Organizations; Chicago Board Options Exchange, Incorporated; Notice of Filing and...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-05-12

    ... amend [sic] its rules relating to the Penny Pilot Program. The text of the rule proposal is available on... proposed rule change. The text of those statements may be examined at the places specified in Item IV below... Technology Select Sector XME SPDR S&P Metals & Mining SPDR Fund. ETF. AKS AK Steel Holding Corp... KGC...

  11. Federal Register Notice for the Mining Waste Exclusion Final Rule, September 1, 1989

    EPA Pesticide Factsheets

    Final rule responding to a federal Appeals Court directive to narrow the exclusion of solid waste from the extraction, beneficiation, and processing of ores and minerals from regulation as hazardous waste as it applies to mineral processing wastes.

  12. 76 FR 13928 - Amendment to the International Traffic in Arms Regulations: Replacement Parts/Components and...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-03-15

    ... International Traffic in Arms Regulations: Replacement Parts/Components and Incorporated Articles AGENCY... incorporated articles. DATES: The Department of State will accept comments on this proposed rule until April 14... Controls Policy, Attn: Regulatory Changes--Replacement Parts/Components and Incorporated Articles, Bureau...

  13. 43 CFR 4.1109 - Service.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... Special Rules Applicable to Surface Coal Mining Hearings and Appeals General Provisions § 4.1109 Service.... Department of the Interior, representing OSMRE in the state in which the mining operation at issue is located, and on any other statutory parties specified under § 4.1105 of this part. (2) The jurisdictions...

  14. 78 FR 37404 - Small Business Size Standards: Support Activities for Mining

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-06-20

    ... SMALL BUSINESS ADMINISTRATION 13 CFR Part 121 RIN 3245-AG44 Small Business Size Standards: Support Activities for Mining AGENCY: U.S. Small Business Administration. ACTION: Final rule. SUMMARY: The United States Small Business Administration (SBA) is increasing the small business size standards for three of...

  15. 26 CFR 1.611-5 - Depreciation of improvements.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... (CONTINUED) INCOME TAXES (CONTINUED) Natural Resources § 1.611-5 Depreciation of improvements. (a) In general. Section 611 provides in the case of mines, oil and gas wells, other natural deposits, and timber that...). (b) Special rules for mines, oil and gas wells, other natural deposits and timber. (1) For principles...

  16. 75 FR 21987 - Penalty Settlement Procedure

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-04-27

    ... and Health Act of 1977, or Mine Act. Hearings are held before the Commission's Administrative Law... settling civil penalties assessed under the Mine Act. DATES: The interim rule takes effect on May 27, 2010... Commission has explored is to simplify how it processes civil penalty settlements. Under section 110(k) of...

  17. 30 CFR 906.1 - Scope.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... 30 Mineral Resources 3 2010-07-01 2010-07-01 false Scope. 906.1 Section 906.1 Mineral Resources... OF SURFACE MINING OPERATIONS WITHIN EACH STATE COLORADO § 906.1 Scope. This part contains all rules applicable only within Colorado that have been adopted under the Surface Mining Control and Reclamation Act...

  18. 75 FR 52980 - Submission for OMB Review; Comment Request

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-08-30

    .../maintaining): $303,512. Description: The Safety Standards for Underground Coal Mine Ventilation Belt Entry rule provides safety requirements for the use of the conveyor belt entry as a ventilation intake to... Underground Coal Mine Ventilation--Belt Entry Used as an Intake Air Course to Ventilate Working Sections and...

  19. Data Mining in Health and Medical Information.

    ERIC Educational Resources Information Center

    Bath, Peter A.

    2004-01-01

    Presents a literature review that covers the following topics related to data mining (DM) in health and medical information: the potential of DM in health and medicine; statistical methods; evaluation of methods; DM tools for health and medicine; inductive learning of symbolic rules; application of DM tools in diagnosis and prognosis; and…

  20. Army Needs to Identify Government Purchase Card High-Risk Transactions

    DTIC Science & Technology

    2012-01-20

    Purchase Card Program Data Mining Process Needs Improvement 11...Mining Process Needs Improvement The 17 transactions that were noncompliant occurred because cardholders ignored the GPC business rules so the...Scope and Methodology 16 Use of Computer- Processed Data 16 Use of Technical Assistance 17 Prior Coverage

  1. Epidemiological and entomological studies of a malaria outbreak among French armed forces deployed at illegal gold mining sites reveal new aspects of the disease's transmission in French Guiana.

    PubMed

    Pommier de Santi, Vincent; Girod, Romain; Mura, Marie; Dia, Aissata; Briolant, Sébastien; Djossou, Félix; Dusfour, Isabelle; Mendibil, Alexandre; Simon, Fabrice; Deparis, Xavier; Pagès, Frédéric

    2016-01-22

    In December 2010, a Plasmodium vivax malaria outbreak occurred among French forces involved in a mission to control illegal gold mining in French Guiana. The findings of epidemiological and entomological investigations conducted after this outbreak are presented here. Data related to malaria cases reported to the French armed forces epidemiological surveillance system were collected during the epidemic period from December 2010 to April 2011. A retrospective cohort study was conducted to identify presumed contamination sites. Anopheles mosquitoes were sampled at the identified sites using Mosquito Magnet and CDC light traps. Specimens were identified morphologically and confirmed using molecular methods (sequencing of ITS2 gene and/or barcoding). Anopheles infections with Plasmodium falciparum and P. vivax were tested by both enzyme-linked immunosorbent assay and real-time PCR. Seventy-two P. vivax malaria cases were reported (three were mixed P. falciparum/P. vivax infections), leading to a global attack rate of 26.5% (72/272). Lack of compliance with vector control measures and doxycycline chemoprophylaxis was reported by patients. Two illegal gold mining sites located in remote areas in the primary forest were identified as places of contamination. In all, 595 Anopheles females were caught and 528 specimens were formally identified: 305 Anopheles darlingi, 145 Anopheles nuneztovari s.l., 63 Anopheles marajoara and 15 Anopheles triannulatus s.l. Three An. darlingi were infected by P. falciparum (infection rate: 1.1%) and four An. marajoara by P. vivax (infection rate: 6.4%). The main drivers of the outbreak were the lack of adherence by military personnel to malaria prevention measures and the high level of malaria transmission at illegal gold mining sites. Anopheles marajoara was clearly implicated in malaria transmission for the first time in French Guiana. The high infection rates observed confirm that illegal gold mining sites must be considered as high level malaria transmission areas in the territory. Illegal gold mining activities are challenging the control of malaria in French Guiana. Collaboration with neighbouring countries is necessary to take into account mobile populations such as gold miners. Malaria control strategies in the French armed forces must be adapted to P. vivax malaria and sylvatic Anopheles species.

  2. Iran Sanctions

    DTIC Science & Technology

    2016-11-16

    Iran); Korea Mining and Development Corp. ( N . Korea). October 21, 2007 Islamic Revolutionary Guard Corps (IRGC); Ministry of Defense and Armed...Maritime (Philippines); Ferland Company Limited (previously designated under other E.O.); Vitaly Sokolenko (general manager of Ferland) April 29

  3. A Study of Pattern Prediction in the Monitoring Data of Earthen Ruins with the Internet of Things.

    PubMed

    Xiao, Yun; Wang, Xin; Eshragh, Faezeh; Wang, Xuanhong; Chen, Xiaojiang; Fang, Dingyi

    2017-05-11

    An understanding of the changes of the rammed earth temperature of earthen ruins is important for protection of such ruins. To predict the rammed earth temperature pattern using the air temperature pattern of the monitoring data of earthen ruins, a pattern prediction method based on interesting pattern mining and correlation, called PPER, is proposed in this paper. PPER first finds the interesting patterns in the air temperature sequence and the rammed earth temperature sequence. To reduce the processing time, two pruning rules and a new data structure based on an R-tree are also proposed. Correlation rules between the air temperature patterns and the rammed earth temperature patterns are then mined. The correlation rules are merged into predictive rules for the rammed earth temperature pattern. Experiments were conducted to show the accuracy of the presented method and the power of the pruning rules. Moreover, the Ming Dynasty Great Wall dataset was used to examine the algorithm, and six predictive rules from the air temperature to rammed earth temperature based on the interesting patterns were obtained, with the average hit rate reaching 89.8%. The PPER and predictive rules will be useful for rammed earth temperature prediction in protection of earthen ruins.

  4. Detecting Malicious Tweets in Twitter Using Runtime Monitoring With Hidden Information

    DTIC Science & Technology

    2016-06-01

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

  5. Taiwan: Major U.S. Arms Sales Since 1990

    DTIC Science & Technology

    2010-08-31

    howitzers; 54 AAV7A1 amphibious assault vehicles; AN/ALE-50 electronic countermeasure (ECM) systems for F-16s; and 12 MH-53 mine -sweeping helicopters...268 Commercial sale. Opall Barbara and David Silverberg, “Taiwanese May Soon Coproduce Patriot,” Defense News, February 22-28, 1993; Military...29 (2) Osprey-class mine hunting ships (refurbished and upgraded) $105 Author Contact Information Shirley A. Kan Specialist in Asian Security Affairs skan@crs.loc.gov, 7-7606

  6. Taiwan: Major U.S. Arms Sales Since 1990

    DTIC Science & Technology

    2012-11-29

    vehicles; AN/ALE-50 electronic countermeasure (ECM) systems for F-16s; and 12 MH-53 mine -sweeping helicopters. President Bush approved four...Review Process, by Richard F. Grimmett. 256 Commercial sale. Opall Barbara and David Silverberg, “Taiwanese May Soon Coproduce Patriot,” Defense News...Sheng C4 systems) $340 01/29 (2) Osprey-class mine hunting ships (refurbished and upgraded) $105 2011 09/21 Retrofit of 145 F-16A/B fighters, with 176

  7. Taiwan: Major U.S. Arms Sales Since 1990

    DTIC Science & Technology

    2012-02-24

    howitzers; 54 AAV7A1 amphibious assault vehicles; AN/ALE-50 electronic countermeasure (ECM) systems for F-16s; and 12 MH-53 mine -sweeping helicopters...Grimmett. 279 Commercial sale. Opall Barbara and David Silverberg, “Taiwanese May Soon Coproduce Patriot,” Defense News, February 22-28, 1993...Sheng C4 systems) $340 01/29 (2) Osprey-class mine hunting ships (refurbished and upgraded) $105 2011 09/21 Retrofit of 145 F-16A/B fighters, with

  8. Taiwan: Major U.S. Arms Sales Since 1990

    DTIC Science & Technology

    2014-03-03

    vehicles; AN/ALE-50 electronic countermeasure (ECM) systems for F-16s; and 12 MH-53 mine -sweeping helicopters. President Bush approved four...resolution of disapproval) as stipulated under Section 36(b) of the AECA. 239 Commercial sale. Opall Barbara and David Silverberg, “Taiwanese May Soon...Sheng C4 systems) $340 01/29 (2) Osprey-class mine hunting ships (refurbished and upgraded) $105 2011 09/21 Retrofit of 145 F-16A/B fighters, with

  9. Federal employees health benefits acquisition regulation: Board of Contract Appeals. Final rule.

    PubMed

    2008-10-08

    The Office of Personnel Management (OPM) is adopting as final,without change, the proposed rule published April 7, 2008 to remove the designation of the Armed Services Board of Contract Appeals (ASBCA)from the Federal Employees Health Benefits Acquisition Regulation(FEHBAR).

  10. 75 FR 73995 - Lowering Miners' Exposure to Respirable Coal Mine Dust, Including Continuous Personal Dust Monitors

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-11-30

    ... http://www.msha.gov/REGS/FEDREG/PROPOSED/2010PROP/2010-25249.pdf . The proposed rule would revise the.../PROPOSED/2010PROP/2010-25249.pdf . The following error in the preamble to the proposed rule is corrected to...

  11. Integrated mined-area reclamation and land-use planning. Volume 3C. A case study of surface mining and reclamation planning: Georgia Kaolin Company Clay Mines, Washington County, Georgia

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

    Guernsey, J L; Brown, L A; Perry, A O

    1978-02-01

    This case study examines the reclamation practices of the Georgia Kaolin's American Industrial Clay Company Division, a kaolin producer centered in Twiggs, Washington, and Wilkinson Counties, Georgia. The State of Georgia accounts for more than one-fourth of the world's kaolin production and about three-fourths of U.S. kaolin output. The mining of kaolin in Georgia illustrates the effects of mining and reclaiming lands disturbed by area surface mining. The disturbed areas are reclaimed under the rules and regulations of the Georgia Surface Mining Act of 1968. The natural conditions influencing the reclamation methodologies and techniques are markedly unique from those ofmore » other mining operations. The environmental disturbances and procedures used in reclaiming the kaolin mined lands are reviewed and implications for planners are noted.« less

  12. 78 FR 5055 - Pattern of Violations

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-01-23

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

  13. The effect of mining on the sediment - trace element geochemistry of cores from the Cheyenne River arm of Lake Oahe, South Dakota, U.S.A.

    USGS Publications Warehouse

    Horowitz, A.J.; Elrick, K.A.; Callender, E.

    1988-01-01

    Six cores, ranging in length from 1 to 2 m, were collected in the Cheyenne River arm of Lake Oahe, South Dakota, to investigate potential impacts from gold-mining operations around Lead, South Dakota. Sedimentation rates in the river arm appear to be event-dominated and rapid, on the order of 6-7 cm yr.-1. All the chemical concentrations in the core samples fall within the wide ranges previously reported for the Pierre Shale of Cretaceous age and with the exception of As, generally are similar to bed sediment levels in the Cheyenne River, Lake Oahe and Foster Bay. Based on the downcore distribution of Mn, it appears that reducing conditions exist in the sediment column of the river arm below 2-3 cm. The reducing conditions do not appear to be severe enough to produce differentiation of Fe and Mn throughout the sediment column in the river arm. Cross-correlations for high-level metal-bearing strata within the sediment column can be made for several strata and for several cores; however, cross-correlations for all the high-level metal-bearing strata are not feasible. As is the only element which appears enriched in the core samples compared to surface sediment levels. Well-crystallized arsenopyrite was found in high-As bearing strata from two cores and probably was transported in that form from reducing sediment-storage sites in the banks or floodplains of Whitewood Creek and the Belle Fourche River. It has not oxidized due to the reducing conditions in the sediment column of the Cheyenne River arm. Some As may also be transported in association with Fe- and Mn-oxides and -hydroxides, remobilized under the reducing conditions in the river arm, and then reprecipitated in authigenic sulfide phases. In either case, the As appears to be relatively immobile in the sediment column. ?? 1988.

  14. Rules of meridians and acupoints selection in treatment of Parkinson's disease based on data mining techniques.

    PubMed

    Li, Zhe; Hu, Ying-Yu; Zheng, Chun-Ye; Su, Qiao-Zhen; An, Chang; Luo, Xiao-Dong; Liu, Mao-Cai

    2018-01-15

    To help selecting appropriate meridians and acupoints in clinical practice and experimental study for Parkinson's disease (PD), the rules of meridians and acupoints selection of acupuncture and moxibustion were analyzed in domestic and foreign clinical treatment for PD based on data mining techniques. Literature about PD treated by acupuncture and moxibustion in China and abroad was searched and selected from China National Knowledge Infrastructure and MEDLINE. Then the data from all eligible articles were extracted to establish the database of acupuncture-moxibustion for PD. The association rules of data mining techniques were used to analyze the rules of meridians and acupoints selection. Totally, 168 eligible articles were included and 184 acupoints were applied. The total frequency of acupoints application was 1,090 times. Those acupoints were mainly distributed in head and neck and extremities. Among all, Taichong (LR 3), Baihui (DU 20), Fengchi (GB 20), Hegu (LI 4) and Chorea-tremor Controlled Zone were the top five acupoints that had been used. Superior-inferior acupoints matching was utilized the most. As to involved meridians, Du Meridian, Dan (Gallbladder) Meridian, Dachang (Large Intestine) Meridian, and Gan (Liver) Meridian were the most popular meridians. The application of meridians and acupoints for PD treatment lay emphasis on the acupoints on the head, attach importance to extinguishing Gan wind, tonifying qi and blood, and nourishing sinews, and make good use of superior-inferior acupoints matching.

  15. Mining machine with adjustable jib

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

    Hart, D.

    1987-05-26

    A mining machine is described having a pair of crawler tracks, a means for individually driving each of the crawler tracks, a frame mounted on the crawler tracks, an elongated jib carrying a sprocket at each end, an endless cutting chain supported on the sprockets, cutters and loading flights mounted on the endless cutting chain, and means on the frame supporting the elongated jib. The means support the elongated jib consisting of a bridge on the frame, at least one scissors linkage pivotally mounted on the bridge, and arm having a first end attached to the scissors linkage, a frontmore » plate mounted on the second end of the arm and means adjustably mounting the elongated jib on the front plate. The means adjustably mount the elongated jib on the front plate including a first means for rotating the elongated jib between a vertical position and a horizontal position.« less

  16. Association Rule Based Feature Extraction for Character Recognition

    NASA Astrophysics Data System (ADS)

    Dua, Sumeet; Singh, Harpreet

    Association rules that represent isomorphisms among data have gained importance in exploratory data analysis because they can find inherent, implicit, and interesting relationships among data. They are also commonly used in data mining to extract the conditions among attribute values that occur together frequently in a dataset [1]. These rules have wide range of applications, namely in the financial and retail sectors of marketing, sales, and medicine.

  17. Stream biological surveys - self-defense for coal mine operators

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

    Hampton, E.L.; Pennington, W.L.; Lackey, J.L.

    1979-12-01

    According to Section 779.20 of the Permanent Regulatory Program Regulations, Surface Coal Mining and Reclamation Operations, Department of the Interior, office of Surface Mining Reclamation and Enforcement, coal mine operators must provide information on fish and wildlife resources in order to obtain mining permits. Although considered to be a liability by many mine operators, stream biological surveys can, in reality, become a significant asset. When combined with appropriate water quality measurements, stream biological surveys can adequately assess a stream's health. Although initially adding cost, stream biological surveys can actually save money and potential litigation during the mining period. However, streammore » biological surveys must be conducted before any mining activity is initiated and should continue on a periodic basis thereafter. Only in this manner can mine operators be assured that biological measurements made on streams affected by their operation are accurate reflections of pre- and post-mining conditions. Armed with this vital information, mine operators have a basis to defend against any unjustified claims that their operations are having deleterious effects on the stream in question. This paper addresses the purpose, scope, methodology, and interpretation of results of stream biological surveys. Additionally, methods for utilizing information from stream biological surveys will be stressed.« less

  18. Association algorithm to mine the rules that govern enzyme definition and to classify protein sequences.

    PubMed

    Chiu, Shih-Hau; Chen, Chien-Chi; Yuan, Gwo-Fang; Lin, Thy-Hou

    2006-06-15

    The number of sequences compiled in many genome projects is growing exponentially, but most of them have not been characterized experimentally. An automatic annotation scheme must be in an urgent need to reduce the gap between the amount of new sequences produced and reliable functional annotation. This work proposes rules for automatically classifying the fungus genes. The approach involves elucidating the enzyme classifying rule that is hidden in UniProt protein knowledgebase and then applying it for classification. The association algorithm, Apriori, is utilized to mine the relationship between the enzyme class and significant InterPro entries. The candidate rules are evaluated for their classificatory capacity. There were five datasets collected from the Swiss-Prot for establishing the annotation rules. These were treated as the training sets. The TrEMBL entries were treated as the testing set. A correct enzyme classification rate of 70% was obtained for the prokaryote datasets and a similar rate of about 80% was obtained for the eukaryote datasets. The fungus training dataset which lacks an enzyme class description was also used to evaluate the fungus candidate rules. A total of 88 out of 5085 test entries were matched with the fungus rule set. These were otherwise poorly annotated using their functional descriptions. The feasibility of using the method presented here to classify enzyme classes based on the enzyme domain rules is evident. The rules may be also employed by the protein annotators in manual annotation or implemented in an automatic annotation flowchart.

  19. Application of data mining in science and technology management information system based on WebGIS

    NASA Astrophysics Data System (ADS)

    Wu, Xiaofang; Xu, Zhiyong; Bao, Shitai; Chen, Feixiang

    2009-10-01

    With the rapid development of science and technology and the quick increase of information, a great deal of data is accumulated in the management department of science and technology. Usually, many knowledge and rules are contained and concealed in the data. Therefore, how to excavate and use the knowledge fully is very important in the management of science and technology. It will help to examine and approve the project of science and technology more scientifically and make the achievement transformed as the realistic productive forces easier. Therefore, the data mine technology will be researched and applied to the science and technology management information system to find and excavate the knowledge in the paper. According to analyzing the disadvantages of traditional science and technology management information system, the database technology, data mining and web geographic information systems (WebGIS) technology will be introduced to develop and construct the science and technology management information system based on WebGIS. The key problems are researched in detail such as data mining and statistical analysis. What's more, the prototype system is developed and validated based on the project data of National Natural Science Foundation Committee. The spatial data mining is done from the axis of time, space and other factors. Then the variety of knowledge and rules will be excavated by using data mining technology, which helps to provide an effective support for decisionmaking.

  20. 77 FR 16670 - Amendment to the International Traffic in Arms Regulations: Sri Lanka

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-03-22

    ... International Traffic in Arms Regulations: Sri Lanka AGENCY: Department of State. ACTION: Final rule. SUMMARY... exception to the license denial policy toward Sri Lanka. This change allows for exports to Sri Lanka for... . ATTN: Regulatory Change, Part 126, Sri Lanka. SUPPLEMENTARY INFORMATION: Section 126.1(n) is amended to...

  1. 76 FR 6110 - Mine Safety Disclosure

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-02-03

    ... Comments Use the Commission's Internet comment form ( http://www.sec.gov/rules/proposed.shtml ); Send an e... all comments on the Commission's Internet Web site ( http://www.sec.gov/rules/proposed.shtml... on the proposal to, among other things, allow for the collection of information and improve the...

  2. 30 CFR 937.700 - Oregon Federal program.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... 30 Mineral Resources 3 2012-07-01 2012-07-01 false Oregon Federal program. 937.700 Section 937.700... PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE OREGON § 937.700 Oregon Federal program. (a) This part contains all rules that are applicable to surface coal mining operations in Oregon...

  3. 30 CFR 937.700 - Oregon Federal program.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... 30 Mineral Resources 3 2011-07-01 2011-07-01 false Oregon Federal program. 937.700 Section 937.700... PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE OREGON § 937.700 Oregon Federal program. (a) This part contains all rules that are applicable to surface coal mining operations in Oregon...

  4. 30 CFR 937.700 - Oregon Federal program.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... 30 Mineral Resources 3 2014-07-01 2014-07-01 false Oregon Federal program. 937.700 Section 937.700... PROGRAMS FOR THE CONDUCT OF SURFACE MINING OPERATIONS WITHIN EACH STATE OREGON § 937.700 Oregon Federal program. (a) This part contains all rules that are applicable to surface coal mining operations in Oregon...

  5. Frequent Itemset Hiding Algorithm Using Frequent Pattern Tree Approach

    ERIC Educational Resources Information Center

    Alnatsheh, Rami

    2012-01-01

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

  6. 76 FR 12648 - Lowering Miners' Exposure to Respirable Coal Mine Dust, Including Continuous Personal Dust Monitors

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-03-08

    ... be appropriate to use on a short-term basis. 13. The proposed rule addresses (1) which occupations... for respirable coal mine dust, provide for full- shift sampling, redefine the term ``normal production... respect to their availability. If shorter or longer timeframes are recommended, please provide the...

  7. A Novel Biclustering Approach to Association Rule Mining for Predicting HIV-1–Human Protein Interactions

    PubMed Central

    Mukhopadhyay, Anirban; Maulik, Ujjwal; Bandyopadhyay, Sanghamitra

    2012-01-01

    Identification of potential viral-host protein interactions is a vital and useful approach towards development of new drugs targeting those interactions. In recent days, computational tools are being utilized for predicting viral-host interactions. Recently a database containing records of experimentally validated interactions between a set of HIV-1 proteins and a set of human proteins has been published. The problem of predicting new interactions based on this database is usually posed as a classification problem. However, posing the problem as a classification one suffers from the lack of biologically validated negative interactions. Therefore it will be beneficial to use the existing database for predicting new viral-host interactions without the need of negative samples. Motivated by this, in this article, the HIV-1–human protein interaction database has been analyzed using association rule mining. The main objective is to identify a set of association rules both among the HIV-1 proteins and among the human proteins, and use these rules for predicting new interactions. In this regard, a novel association rule mining technique based on biclustering has been proposed for discovering frequent closed itemsets followed by the association rules from the adjacency matrix of the HIV-1–human interaction network. Novel HIV-1–human interactions have been predicted based on the discovered association rules and tested for biological significance. For validation of the predicted new interactions, gene ontology-based and pathway-based studies have been performed. These studies show that the human proteins which are predicted to interact with a particular viral protein share many common biological activities. Moreover, literature survey has been used for validation purpose to identify some predicted interactions that are already validated experimentally but not present in the database. Comparison with other prediction methods is also discussed. PMID:22539940

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

    NASA Astrophysics Data System (ADS)

    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.

  9. [Analysis of the characteristics of the older adults with depression using data mining decision tree analysis].

    PubMed

    Park, Myonghwa; Choi, Sora; Shin, A Mi; Koo, Chul Hoi

    2013-02-01

    The purpose of this study was to develop a prediction model for the characteristics of older adults with depression using the decision tree method. A large dataset from the 2008 Korean Elderly Survey was used and data of 14,970 elderly people were analyzed. Target variable was depression and 53 input variables were general characteristics, family & social relationship, economic status, health status, health behavior, functional status, leisure & social activity, quality of life, and living environment. Data were analyzed by decision tree analysis, a data mining technique using SPSS Window 19.0 and Clementine 12.0 programs. The decision trees were classified into five different rules to define the characteristics of older adults with depression. Classification & Regression Tree (C&RT) showed the best prediction with an accuracy of 80.81% among data mining models. Factors in the rules were life satisfaction, nutritional status, daily activity difficulty due to pain, functional limitation for basic or instrumental daily activities, number of chronic diseases and daily activity difficulty due to disease. The different rules classified by the decision tree model in this study should contribute as baseline data for discovering informative knowledge and developing interventions tailored to these individual characteristics.

  10. Iran Sanctions

    DTIC Science & Technology

    2016-09-21

    Iran); Korea Mining and Development Corp. ( N . Korea). October 21, 2007 Islamic Revolutionary Guard Corps (IRGC); Ministry of Defense and Armed...designated under other E.O.); Vitaly Sokolenko (general manager of Ferland) April 29, 2014 (for connections to deceptive oil dealings for Iran) Saeed Al

  11. 76 FR 7782 - Defense Federal Acquisition Regulation Supplement; Rules of the Armed Services Board of Contract...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-02-11

    ...--Depositions Rule 15 Interrogatories to Parties, Admission of Facts, and Production and Inspection of Documents.... Affidavits, depositions, admissions, answers to interrogatories, and stipulations may be employed to... items, if any: pleadings, prehearing conference memoranda or orders, prehearing briefs, depositions or...

  12. 30 CFR 910.817 - Performance standards-underground mining activities.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... with the Georgia Safe Dams Act and Rules for Safety of the Natural Resources, Environmental Protection Division; the Solid Waste Management Rules of the Georgia Department of Natural Resources, Environmental Protection Division, Chapter 391-3-4; and the Georgia Seed Laws and Regulation 4. [47 FR 36399, Aug. 19, 1982...

  13. 30 CFR 910.816 - Performance standards-surface mining activities.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... except in compliance with the Georgia Safe Dams Act and Rules for Safety of the Natural Resources, Environmental Protection Division; the Solid Waste Management Rules of the Georgia Department of Natural Resources, Environmental Protection Division, Chapter 391-3-4; and the Georgia Seed Laws and Regulation 4...

  14. 30 CFR 910.817 - Performance standards-underground mining activities.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... with the Georgia Safe Dams Act and Rules for Safety of the Natural Resources, Environmental Protection Division; the Solid Waste Management Rules of the Georgia Department of Natural Resources, Environmental Protection Division, Chapter 391-3-4; and the Georgia Seed Laws and Regulation 4. [47 FR 36399, Aug. 19, 1982...

  15. 30 CFR 910.817 - Performance standards-underground mining activities.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... with the Georgia Safe Dams Act and Rules for Safety of the Natural Resources, Environmental Protection Division; the Solid Waste Management Rules of the Georgia Department of Natural Resources, Environmental Protection Division, Chapter 391-3-4; and the Georgia Seed Laws and Regulation 4. [47 FR 36399, Aug. 19, 1982...

  16. 30 CFR 910.816 - Performance standards-surface mining activities.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... except in compliance with the Georgia Safe Dams Act and Rules for Safety of the Natural Resources, Environmental Protection Division; the Solid Waste Management Rules of the Georgia Department of Natural Resources, Environmental Protection Division, Chapter 391-3-4; and the Georgia Seed Laws and Regulation 4...

  17. 30 CFR 910.816 - Performance standards-surface mining activities.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... except in compliance with the Georgia Safe Dams Act and Rules for Safety of the Natural Resources, Environmental Protection Division; the Solid Waste Management Rules of the Georgia Department of Natural Resources, Environmental Protection Division, Chapter 391-3-4; and the Georgia Seed Laws and Regulation 4...

  18. Sustainability Activities In The Mining Sector: Current Status And Challenges Ahead Limestone Mining In Nusakambangan

    NASA Astrophysics Data System (ADS)

    Ayuningrum, Theresia Vika; Purnaweni, Hartuti

    2018-02-01

    Potential Karst area in Nusakambangan has an important role in maintaining the balance of nature. But with the existence of mining activities, will automatically change the environmental conditions there. In order for the utilization of resources to meet the rules of optimization between the interests of mining and sustainability of the environment so in every mining sector activities required a variety of environmental studies. The purpose of this study is to find out how the analysis of environmental management due to limestone mining activities in Nusakambangan so that it can be known the management of mining areas are optimal, wise based on ecological principles, and sustainability. In qualitative research methods, data analysis using description percentage, with the type of data collected in the form of primary data and secondary data.

  19. Clustering and Dimensionality Reduction to Discover Interesting Patterns in Binary Data

    NASA Astrophysics Data System (ADS)

    Palumbo, Francesco; D'Enza, Alfonso Iodice

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

  20. Personalized Privacy-Preserving Frequent Itemset Mining Using Randomized Response

    PubMed Central

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

    2014-01-01

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

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

    PubMed

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

    2014-01-01

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

  2. 76 FR 40237 - Approval and Disapproval and Promulgation of Air Quality Implementation Plans; Montana; Revisions...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-07-08

    ... before permit issuance. The rule only allows installing concrete foundations work, below ground plumbing...)), submitted on May 28, 2003; 17.8.743 (except the phrases ``asphalt concrete plants, mineral crushers'' in 17... following provisions in Subchapter 7: ARM 17.8.743(1)(c) and ARM 17.8.770, the phrase ``asphalt concrete...

  3. 26 CFR 1.61-2 - Compensation for services, including fees, commissions, and similar items.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... contributions received by a clergyman for services, pay of persons in the military or naval forces of the United... excluded by law. Several special rules apply to members of the Armed Forces, National Oceanic and... regulations thereunder; (v) Miscellaneous items, see section 122. (b) Members of the Armed Forces, National...

  4. 26 CFR 1.61-2 - Compensation for services, including fees, commissions, and similar items.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... contributions received by a clergyman for services, pay of persons in the military or naval forces of the United... excluded by law. Several special rules apply to members of the Armed Forces, National Oceanic and... regulations thereunder; (v) Miscellaneous items, see section 122. (b) Members of the Armed Forces, National...

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

    EPA Science Inventory

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

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

    ERIC Educational Resources Information Center

    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. Association algorithm to mine the rules that govern enzyme definition and to classify protein sequences

    PubMed Central

    Chiu, Shih-Hau; Chen, Chien-Chi; Yuan, Gwo-Fang; Lin, Thy-Hou

    2006-01-01

    Background The number of sequences compiled in many genome projects is growing exponentially, but most of them have not been characterized experimentally. An automatic annotation scheme must be in an urgent need to reduce the gap between the amount of new sequences produced and reliable functional annotation. This work proposes rules for automatically classifying the fungus genes. The approach involves elucidating the enzyme classifying rule that is hidden in UniProt protein knowledgebase and then applying it for classification. The association algorithm, Apriori, is utilized to mine the relationship between the enzyme class and significant InterPro entries. The candidate rules are evaluated for their classificatory capacity. Results There were five datasets collected from the Swiss-Prot for establishing the annotation rules. These were treated as the training sets. The TrEMBL entries were treated as the testing set. A correct enzyme classification rate of 70% was obtained for the prokaryote datasets and a similar rate of about 80% was obtained for the eukaryote datasets. The fungus training dataset which lacks an enzyme class description was also used to evaluate the fungus candidate rules. A total of 88 out of 5085 test entries were matched with the fungus rule set. These were otherwise poorly annotated using their functional descriptions. Conclusion The feasibility of using the method presented here to classify enzyme classes based on the enzyme domain rules is evident. The rules may be also employed by the protein annotators in manual annotation or implemented in an automatic annotation flowchart. PMID:16776838

  8. The Royal Navy and British Security Policy.

    DTIC Science & Technology

    1983-12-01

    supremacy were embodied in that fleet. Britannia ruled the waves around the world. -~ Sixty-six years later Rear Admiral Sandy Woodward went *into battle off...already sold to Australia and just over a dozen destroyers and frigates. Britannia ruled the waves around those remote islands only with great difficulty...with the Americans, vulnerability to mining and the costs in manpower and money that a larger force would require, ruled out the non-nuclear-powered

  9. 78 FR 52680 - Amendment to the International Traffic in Arms Regulations: Registration and Licensing of Brokers...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-08-26

    ...The Department of State is issuing this interim final rule amending the International Traffic in Arms Regulations (ITAR) relating to brokers and brokering activities and to related provisions of the ITAR. These amendments clarify registration requirements, the scope of brokering activities, prior approval requirements and exemptions, procedures for obtaining prior approval and guidance, and reporting and recordkeeping of such activities. Conforming and technical changes are made to other parts of the ITAR that affect export as well as brokering activities. The revisions contained in this rule are part of the Department of State's retrospective plan under E.O. 13563 completed on August 17, 2011.

  10. 48 CFR Appendix A to Chapter 2 - Armed Services Board of Contract Appeals

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... EXTENSIONS Rule 33Time, Computation and Extensions EX PARTE COMMUNICATIONS Rule 34Ex parte Communications..., taking into account such factors as the size and complexity of the claim, the contractor may file a... exhibits, post-hearing briefs, and documents which the Board has specifically designated to be made a part...

  11. 48 CFR Appendix A to Chapter 2 - Armed Services Board of Contract Appeals

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... EXTENSIONS Rule 33Time, Computation and Extensions EX PARTE COMMUNICATIONS Rule 34Ex parte Communications..., taking into account such factors as the size and complexity of the claim, the contractor may file a... exhibits, post-hearing briefs, and documents which the Board has specifically designated to be made a part...

  12. 48 CFR Appendix A to Chapter 2 - Armed Services Board of Contract Appeals

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... EXTENSIONS Rule 33Time, Computation and Extensions EX PARTE COMMUNICATIONS Rule 34Ex parte Communications..., taking into account such factors as the size and complexity of the claim, the contractor may file a... exhibits, post-hearing briefs, and documents which the Board has specifically designated to be made a part...

  13. 76 FR 49650 - Private Security Contractors (PSCs) Operating in Contingency Operations, Combat Operations or...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-08-11

    ...] Private Security Contractors (PSCs) Operating in Contingency Operations, Combat Operations or Other..., ``Contractor Personnel Authorized to Accompany the U.S. Armed Forces,'' which provides guidance for all DoD contractors operating in contingency operations. This Rule was published as an Interim Final Rule on July 17...

  14. 2012 Alabama Lunabotics Systems Engineering Paper

    NASA Technical Reports Server (NTRS)

    Baker, Justin; Ricks, Kenneth; Hull, Bethanne J.

    2012-01-01

    Excavation will hold a key role for future lunar missions. NASA has stated that "advances in lunar regolith mining have the potential to significantly contribute to our nation's space vision and NASA space exploration operations." [1]. The Lunabotics Mining Competition is an event hosted by NASA that is meant to encourage "the development of innovative lunar excavation concepts from universities which may result in clever ideas and solutions which could be applied to an actual lunar excavation device or payload." [2]. Teams entering the competition must "design and build a remote controlled or autonomous excavator, called a lunabot, that can collect and deposit a minimum of 10 kilograms of lunar simulant within 10 minutes." [2]. While excavation will play an important part in lunar missions, there will still be many other tasks that would benefit from robotic assistance. An excavator might not be as well suited for these tasks as other types of robots might be. For example a lightweight rover would do well with reconnaissance, and a mobile gripper arm would be fit for manipulation, while an excavator would be comparatively clumsy and slow in both cases. Even within the realm of excavation it would be beneficial to have different types of excavators for different tasks, as there are on Earth. The Alabama Lunabotics Team at the University of Alabama has made it their goal to not only design and build a robot that could compete in the Lunabotics Mining Competition, but would also be a multipurpose tool for future NASA missions. The 2010-2011 resulting robot was named the Modular Omnidirectional Lunar Excavator (MOLE). Using the Systems Engineering process and building off of two years of Lunabotics experience, the 20ll-2012 Alabama Lunabotics team (Team NASACAR) has improved the MOLE 1.0 design and optimized it for the 2012 Lunabotics Competition rules [I]. A CAD model of MOLE 2.0 can be seen below in Fig. 1.

  15. 75 FR 17803 - Self-Regulatory Organizations; NASDAQ OMX PHLX, Inc.; Notice of Filing and Immediate...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-04-07

    .... The text of the proposed rule change is available on the Exchange's Web site at http://nasdaqtrader... and discussed any comments it received on the proposed rule change. The text of these statements may... Mining Corporation (``NEM''); Palm, Inc. (``PALM''); Pfizer, Inc. (``PFE''); ''); Potash Corp...

  16. 29 CFR 2700.55 - Powers of Judges.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... 29 Labor 9 2013-07-01 2013-07-01 false Powers of Judges. 2700.55 Section 2700.55 Labor Regulations Relating to Labor (Continued) FEDERAL MINE SAFETY AND HEALTH REVIEW COMMISSION PROCEDURAL RULES Hearings § 2700.55 Powers of Judges. Subject to these rules, a Judge is empowered to: (a) Administer oaths and...

  17. 29 CFR 2700.55 - Powers of Judges.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... 29 Labor 9 2012-07-01 2012-07-01 false Powers of Judges. 2700.55 Section 2700.55 Labor Regulations Relating to Labor (Continued) FEDERAL MINE SAFETY AND HEALTH REVIEW COMMISSION PROCEDURAL RULES Hearings § 2700.55 Powers of Judges. Subject to these rules, a Judge is empowered to: (a) Administer oaths and...

  18. 29 CFR 2700.55 - Powers of Judges.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... 29 Labor 9 2014-07-01 2014-07-01 false Powers of Judges. 2700.55 Section 2700.55 Labor Regulations Relating to Labor (Continued) FEDERAL MINE SAFETY AND HEALTH REVIEW COMMISSION PROCEDURAL RULES Hearings § 2700.55 Powers of Judges. Subject to these rules, a Judge is empowered to: (a) Administer oaths and...

  19. 20 CFR 410.687 - Rules governing the representation and advising of claimants and parties.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... 20 Employees' Benefits 2 2010-04-01 2010-04-01 false Rules governing the representation and advising of claimants and parties. 410.687 Section 410.687 Employees' Benefits SOCIAL SECURITY ADMINISTRATION FEDERAL COAL MINE HEALTH AND SAFETY ACT OF 1969, TITLE IV-BLACK LUNG BENEFITS (1969...

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

    NASA Astrophysics Data System (ADS)

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

    2015-07-01

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

  1. The Law of Force or The Force of Law: Does Following The Rule of Law Assist Security Forces in Defeating an Armed Insurgency?

    DTIC Science & Technology

    2012-06-08

    and Policy in International Relations (Spring): 40-79 Arendt , Hannah . 1963. On revolution. New York: Viking Cohen, Eliot A., John Horvath, and...conditions, where the armed forces can be trusted to obey the civil authorities” ( Arendt 1965, 40). This is especially the case in countries where

  2. Mining Student Data Captured from a Web-Based Tutoring Tool: Initial Exploration and Results

    ERIC Educational Resources Information Center

    Merceron, Agathe; Yacef, Kalina

    2004-01-01

    In this article we describe the initial investigations that we have conducted on student data collected from a web-based tutoring tool. We have used some data mining techniques such as association rule and symbolic data analysis, as well as traditional SQL queries to gain further insight on the students' learning and deduce information to improve…

  3. Compass: a hybrid method for clinical and biobank data mining.

    PubMed

    Krysiak-Baltyn, K; Nordahl Petersen, T; Audouze, K; Jørgensen, Niels; Angquist, L; Brunak, S

    2014-02-01

    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 successfully generated a number of interesting association rules, which relate an observation with a specific consequence and the p-value for that finding. Additionally, we demonstrate that the method can be used on non-clinical data containing chemical-disease associations in order to find associations between different phenotypes, such as prostate cancer and breast cancer. Copyright © 2013 Elsevier Inc. All rights reserved.

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

    NASA Astrophysics Data System (ADS)

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

    2017-12-01

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

  5. Occupancy schedules learning process through a data mining framework

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

    D'Oca, Simona; Hong, Tianzhen

    Building occupancy is a paramount factor in building energy simulations. Specifically, lighting, plug loads, HVAC equipment utilization, fresh air requirements and internal heat gain or loss greatly depends on the level of occupancy within a building. Developing the appropriate methodologies to describe and reproduce the intricate network responsible for human-building interactions are needed. Extrapolation of patterns from big data streams is a powerful analysis technique which will allow for a better understanding of energy usage in buildings. A three-step data mining framework is applied to discover occupancy patterns in office spaces. First, a data set of 16 offices with 10more » minute interval occupancy data, over a two year period is mined through a decision tree model which predicts the occupancy presence. Then a rule induction algorithm is used to learn a pruned set of rules on the results from the decision tree model. Finally, a cluster analysis is employed in order to obtain consistent patterns of occupancy schedules. Furthermore, the identified occupancy rules and schedules are representative as four archetypal working profiles that can be used as input to current building energy modeling programs, such as EnergyPlus or IDA-ICE, to investigate impact of occupant presence on design, operation and energy use in office buildings.« less

  6. Validation of an association rule mining-based method to infer associations between medications and problems.

    PubMed

    Wright, A; McCoy, A; Henkin, S; Flaherty, M; Sittig, D

    2013-01-01

    In a prior study, we developed methods for automatically identifying associations between medications and problems using association rule mining on a large clinical data warehouse and validated these methods at a single site which used a self-developed electronic health record. To demonstrate the generalizability of these methods by validating them at an external site. We received data on medications and problems for 263,597 patients from the University of Texas Health Science Center at Houston Faculty Practice, an ambulatory practice that uses the Allscripts Enterprise commercial electronic health record product. We then conducted association rule mining to identify associated pairs of medications and problems and characterized these associations with five measures of interestingness: support, confidence, chi-square, interest and conviction and compared the top-ranked pairs to a gold standard. 25,088 medication-problem pairs were identified that exceeded our confidence and support thresholds. An analysis of the top 500 pairs according to each measure of interestingness showed a high degree of accuracy for highly-ranked pairs. The same technique was successfully employed at the University of Texas and accuracy was comparable to our previous results. Top associations included many medications that are highly specific for a particular problem as well as a large number of common, accurate medication-problem pairs that reflect practice patterns.

  7. Occupancy schedules learning process through a data mining framework

    DOE PAGES

    D'Oca, Simona; Hong, Tianzhen

    2014-12-17

    Building occupancy is a paramount factor in building energy simulations. Specifically, lighting, plug loads, HVAC equipment utilization, fresh air requirements and internal heat gain or loss greatly depends on the level of occupancy within a building. Developing the appropriate methodologies to describe and reproduce the intricate network responsible for human-building interactions are needed. Extrapolation of patterns from big data streams is a powerful analysis technique which will allow for a better understanding of energy usage in buildings. A three-step data mining framework is applied to discover occupancy patterns in office spaces. First, a data set of 16 offices with 10more » minute interval occupancy data, over a two year period is mined through a decision tree model which predicts the occupancy presence. Then a rule induction algorithm is used to learn a pruned set of rules on the results from the decision tree model. Finally, a cluster analysis is employed in order to obtain consistent patterns of occupancy schedules. Furthermore, the identified occupancy rules and schedules are representative as four archetypal working profiles that can be used as input to current building energy modeling programs, such as EnergyPlus or IDA-ICE, to investigate impact of occupant presence on design, operation and energy use in office buildings.« less

  8. Decision Tree based Prediction and Rule Induction for Groundwater Trichloroethene (TCE) Pollution Vulnerability

    NASA Astrophysics Data System (ADS)

    Park, J.; Yoo, K.

    2013-12-01

    For groundwater resource conservation, it is important to accurately assess groundwater pollution sensitivity or vulnerability. In this work, we attempted to use data mining approach to assess groundwater pollution vulnerability in a TCE (trichloroethylene) contaminated Korean industrial site. The conventional DRASTIC method failed to describe TCE sensitivity data with a poor correlation with hydrogeological properties. Among the different data mining methods such as Artificial Neural Network (ANN), Multiple Logistic Regression (MLR), Case Base Reasoning (CBR), and Decision Tree (DT), the accuracy and consistency of Decision Tree (DT) was the best. According to the following tree analyses with the optimal DT model, the failure of the conventional DRASTIC method in fitting with TCE sensitivity data may be due to the use of inaccurate weight values of hydrogeological parameters for the study site. These findings provide a proof of concept that DT based data mining approach can be used in predicting and rule induction of groundwater TCE sensitivity without pre-existing information on weights of hydrogeological properties.

  9. Biogeochemical behaviour and bioremediation of uranium in waters of abandoned mines.

    PubMed

    Mkandawire, Martin

    2013-11-01

    The discharges of uranium and associated radionuclides as well as heavy metals and metalloids from waste and tailing dumps in abandoned uranium mining and processing sites pose contamination risks to surface and groundwater. Although many more are being planned for nuclear energy purposes, most of the abandoned uranium mines are a legacy of uranium production that fuelled arms race during the cold war of the last century. Since the end of cold war, there have been efforts to rehabilitate the mining sites, initially, using classical remediation techniques based on high chemical and civil engineering. Recently, bioremediation technology has been sought as alternatives to the classical approach due to reasons, which include: (a) high demand of sites requiring remediation; (b) the economic implication of running and maintaining the facilities due to high energy and work force demand; and (c) the pattern and characteristics of contaminant discharges in most of the former uranium mining and processing sites prevents the use of classical methods. This review discusses risks of uranium contamination from abandoned uranium mines from the biogeochemical point of view and the potential and limitation of uranium bioremediation technique as alternative to classical approach in abandoned uranium mining and processing sites.

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

    PubMed

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

    2017-07-12

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

  11. 14 CFR 65.117 - Military riggers or former military riggers: Special certification rule.

    Code of Federal Regulations, 2013 CFR

    2013-01-01

    ... 14 Aeronautics and Space 2 2013-01-01 2013-01-01 false Military riggers or former military riggers: Special certification rule. 65.117 Section 65.117 Aeronautics and Space FEDERAL AVIATION ADMINISTRATION... that he— (a) Is a member or civilian employee of an Armed Force of the United States, is a civilian...

  12. 14 CFR 65.117 - Military riggers or former military riggers: Special certification rule.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 14 Aeronautics and Space 2 2010-01-01 2010-01-01 false Military riggers or former military riggers: Special certification rule. 65.117 Section 65.117 Aeronautics and Space FEDERAL AVIATION ADMINISTRATION... that he— (a) Is a member or civilian employee of an Armed Force of the United States, is a civilian...

  13. 14 CFR 65.117 - Military riggers or former military riggers: Special certification rule.

    Code of Federal Regulations, 2014 CFR

    2014-01-01

    ... 14 Aeronautics and Space 2 2014-01-01 2014-01-01 false Military riggers or former military riggers: Special certification rule. 65.117 Section 65.117 Aeronautics and Space FEDERAL AVIATION ADMINISTRATION... that he— (a) Is a member or civilian employee of an Armed Force of the United States, is a civilian...

  14. 14 CFR 65.117 - Military riggers or former military riggers: Special certification rule.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... 14 Aeronautics and Space 2 2011-01-01 2011-01-01 false Military riggers or former military riggers: Special certification rule. 65.117 Section 65.117 Aeronautics and Space FEDERAL AVIATION ADMINISTRATION... that he— (a) Is a member or civilian employee of an Armed Force of the United States, is a civilian...

  15. 14 CFR 65.117 - Military riggers or former military riggers: Special certification rule.

    Code of Federal Regulations, 2012 CFR

    2012-01-01

    ... 14 Aeronautics and Space 2 2012-01-01 2012-01-01 false Military riggers or former military riggers: Special certification rule. 65.117 Section 65.117 Aeronautics and Space FEDERAL AVIATION ADMINISTRATION... that he— (a) Is a member or civilian employee of an Armed Force of the United States, is a civilian...

  16. 77 FR 35317 - Amendment to the International Traffic in Arms Regulations: Revision of U.S. Munitions List...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-06-13

    ... State. ACTION: Proposed rule. SUMMARY: As part of the President's Export Control Reform effort, the... materials warranting control on the USML. The revisions to this rule are part of the Department of State's... Directorate of Defense Trade Controls Web site at www.pmddtc.state.gov . Parties who wish to comment...

  17. An Analysis Pipeline with Statistical and Visualization-Guided Knowledge Discovery for Michigan-Style Learning Classifier Systems

    PubMed Central

    Urbanowicz, Ryan J.; Granizo-Mackenzie, Ambrose; Moore, Jason H.

    2014-01-01

    Michigan-style learning classifier systems (M-LCSs) represent an adaptive and powerful class of evolutionary algorithms which distribute the learned solution over a sizable population of rules. However their application to complex real world data mining problems, such as genetic association studies, has been limited. Traditional knowledge discovery strategies for M-LCS rule populations involve sorting and manual rule inspection. While this approach may be sufficient for simpler problems, the confounding influence of noise and the need to discriminate between predictive and non-predictive attributes calls for additional strategies. Additionally, tests of significance must be adapted to M-LCS analyses in order to make them a viable option within fields that require such analyses to assess confidence. In this work we introduce an M-LCS analysis pipeline that combines uniquely applied visualizations with objective statistical evaluation for the identification of predictive attributes, and reliable rule generalizations in noisy single-step data mining problems. This work considers an alternative paradigm for knowledge discovery in M-LCSs, shifting the focus from individual rules to a global, population-wide perspective. We demonstrate the efficacy of this pipeline applied to the identification of epistasis (i.e., attribute interaction) and heterogeneity in noisy simulated genetic association data. PMID:25431544

  18. Study on the Rule of Super Strata Movement and Subsidence

    NASA Astrophysics Data System (ADS)

    Yao, Shunli; Yuan, Hongyong; Jiang, Fuxing; Chen, Tao; Wu, Peng

    2018-01-01

    The movement of key strata is related to the safety of the whole earth’s surface for coal mining under super strata. Based on the key strata theory, the paper comprehensively analyzes the characteristics of the subsidence before and after the instability of the super strata by studing through FLAC3D and microseismic dynamic monitoring of the surface rock movement observation. The stability of the super strata movement is analyzed according to the characteristic value of the subsidence. The subsidence law and quantitative indexes under the control of the super rock strata that provides basis for the prevention and control of surface risk, optimize mining area and face layout and reasonably set mining boundary around mining area. It provides basis for the even growth of mine safety production and regional public safety.

  19. The Weather Forecast Using Data Mining Research Based on Cloud Computing.

    NASA Astrophysics Data System (ADS)

    Wang, ZhanJie; Mazharul Mujib, A. B. M.

    2017-10-01

    Weather forecasting has been an important application in meteorology and one of the most scientifically and technologically challenging problem around the world. In my study, we have analyzed the use of data mining techniques in forecasting weather. This paper proposes a modern method to develop a service oriented architecture for the weather information systems which forecast weather using these data mining techniques. This can be carried out by using Artificial Neural Network and Decision tree Algorithms and meteorological data collected in Specific time. Algorithm has presented the best results to generate classification rules for the mean weather variables. The results showed that these data mining techniques can be enough for weather forecasting.

  20. The Value of Data Mining in Music Education Research and Some Findings from Its Application to a Study of Instrumental Learning during Childhood

    ERIC Educational Resources Information Center

    Faulkner, Robert; Davidson, Jane W.; McPherson, Gary E.

    2010-01-01

    The use of data mining for the analysis of data collected in natural settings is increasingly recognized as a legitimate mode of enquiry. This rule-inductive paradigm is an effective means of discovering relationships within large datasets--especially in research that has limited experimental design--and for the subsequent formulation of…

  1. MINEs: Open access databases of computationally predicted enzyme promiscuity products for untargeted metabolomics

    DOE PAGES

    Jeffryes, James G.; Colastani, Ricardo L.; Elbadawi-Sidhu, Mona; ...

    2015-08-28

    Metabolomics have proven difficult to execute in an untargeted and generalizable manner. Liquid chromatography–mass spectrometry (LC–MS) has made it possible to gather data on thousands of cellular metabolites. However, matching metabolites to their spectral features continues to be a bottleneck, meaning that much of the collected information remains uninterpreted and that new metabolites are seldom discovered in untargeted studies. These challenges require new approaches that consider compounds beyond those available in curated biochemistry databases. Here we present Metabolic In silico Network Expansions (MINEs), an extension of known metabolite databases to include molecules that have not been observed, but are likelymore » to occur based on known metabolites and common biochemical reactions. We utilize an algorithm called the Biochemical Network Integrated Computational Explorer (BNICE) and expert-curated reaction rules based on the Enzyme Commission classification system to propose the novel chemical structures and reactions that comprise MINE databases. Starting from the Kyoto Encyclopedia of Genes and Genomes (KEGG) COMPOUND database, the MINE contains over 571,000 compounds, of which 93% are not present in the PubChem database. However, these MINE compounds have on average higher structural similarity to natural products than compounds from KEGG or PubChem. MINE databases were able to propose annotations for 98.6% of a set of 667 MassBank spectra, 14% more than KEGG alone and equivalent to PubChem while returning far fewer candidates per spectra than PubChem (46 vs. 1715 median candidates). Application of MINEs to LC–MS accurate mass data enabled the identity of an unknown peak to be confidently predicted. MINE databases are freely accessible for non-commercial use via user-friendly web-tools at http://minedatabase.mcs.anl.gov and developer-friendly APIs. MINEs improve metabolomics peak identification as compared to general chemical databases whose results include irrelevant synthetic compounds. MINEs complement and expand on previous in silico generated compound databases that focus on human metabolism. We are actively developing the database; future versions of this resource will incorporate transformation rules for spontaneous chemical reactions and more advanced filtering and prioritization of candidate structures.« less

  2. Is self-reported height or arm span a more accurate alternative measure of height?

    PubMed

    Brown, Jean K; Feng, Jui-Ying; Knapp, Thomas R

    2002-11-01

    The purpose of this study was to determine whether self-reported height or arm span is the more accurate alternative measure of height. A sample of 409 people between the ages of 19 and 67 (M = 35.0) participated in this anthropometric study. Height, self-reported height, and arm span were measured by 82 nursing research students. Mean differences from criterion measures were 0.17 cm for the measuring rules, 0.47 cm for arm span, and 0.85 cm and 0.87 cm for heights. Test-retest reliability was r = .997 for both height and arm span. The relationships of height to self-reported height and arm span were r = .97 and .90, respectively. Mean absolute differences were 1.80 cm and 4.29 cm, respectively. These findings support the practice of using self-reported height as an alternative measure of measured height in clinical settings, but arm span is an accurate alternative when neither measured height nor self-reported height is obtainable.

  3. A novel on-line spatial-temporal k-anonymity method for location privacy protection from sequence rules-based inference attacks.

    PubMed

    Zhang, Haitao; Wu, Chenxue; Chen, Zewei; Liu, Zhao; Zhu, Yunhong

    2017-01-01

    Analyzing large-scale spatial-temporal k-anonymity datasets recorded in location-based service (LBS) application servers can benefit some LBS applications. However, such analyses can allow adversaries to make inference attacks that cannot be handled by spatial-temporal k-anonymity methods or other methods for protecting sensitive knowledge. In response to this challenge, first we defined a destination location prediction attack model based on privacy-sensitive sequence rules mined from large scale anonymity datasets. Then we proposed a novel on-line spatial-temporal k-anonymity method that can resist such inference attacks. Our anti-attack technique generates new anonymity datasets with awareness of privacy-sensitive sequence rules. The new datasets extend the original sequence database of anonymity datasets to hide the privacy-sensitive rules progressively. The process includes two phases: off-line analysis and on-line application. In the off-line phase, sequence rules are mined from an original sequence database of anonymity datasets, and privacy-sensitive sequence rules are developed by correlating privacy-sensitive spatial regions with spatial grid cells among the sequence rules. In the on-line phase, new anonymity datasets are generated upon LBS requests by adopting specific generalization and avoidance principles to hide the privacy-sensitive sequence rules progressively from the extended sequence anonymity datasets database. We conducted extensive experiments to test the performance of the proposed method, and to explore the influence of the parameter K value. The results demonstrated that our proposed approach is faster and more effective for hiding privacy-sensitive sequence rules in terms of hiding sensitive rules ratios to eliminate inference attacks. Our method also had fewer side effects in terms of generating new sensitive rules ratios than the traditional spatial-temporal k-anonymity method, and had basically the same side effects in terms of non-sensitive rules variation ratios with the traditional spatial-temporal k-anonymity method. Furthermore, we also found the performance variation tendency from the parameter K value, which can help achieve the goal of hiding the maximum number of original sensitive rules while generating a minimum of new sensitive rules and affecting a minimum number of non-sensitive rules.

  4. A novel on-line spatial-temporal k-anonymity method for location privacy protection from sequence rules-based inference attacks

    PubMed Central

    Wu, Chenxue; Liu, Zhao; Zhu, Yunhong

    2017-01-01

    Analyzing large-scale spatial-temporal k-anonymity datasets recorded in location-based service (LBS) application servers can benefit some LBS applications. However, such analyses can allow adversaries to make inference attacks that cannot be handled by spatial-temporal k-anonymity methods or other methods for protecting sensitive knowledge. In response to this challenge, first we defined a destination location prediction attack model based on privacy-sensitive sequence rules mined from large scale anonymity datasets. Then we proposed a novel on-line spatial-temporal k-anonymity method that can resist such inference attacks. Our anti-attack technique generates new anonymity datasets with awareness of privacy-sensitive sequence rules. The new datasets extend the original sequence database of anonymity datasets to hide the privacy-sensitive rules progressively. The process includes two phases: off-line analysis and on-line application. In the off-line phase, sequence rules are mined from an original sequence database of anonymity datasets, and privacy-sensitive sequence rules are developed by correlating privacy-sensitive spatial regions with spatial grid cells among the sequence rules. In the on-line phase, new anonymity datasets are generated upon LBS requests by adopting specific generalization and avoidance principles to hide the privacy-sensitive sequence rules progressively from the extended sequence anonymity datasets database. We conducted extensive experiments to test the performance of the proposed method, and to explore the influence of the parameter K value. The results demonstrated that our proposed approach is faster and more effective for hiding privacy-sensitive sequence rules in terms of hiding sensitive rules ratios to eliminate inference attacks. Our method also had fewer side effects in terms of generating new sensitive rules ratios than the traditional spatial-temporal k-anonymity method, and had basically the same side effects in terms of non-sensitive rules variation ratios with the traditional spatial-temporal k-anonymity method. Furthermore, we also found the performance variation tendency from the parameter K value, which can help achieve the goal of hiding the maximum number of original sensitive rules while generating a minimum of new sensitive rules and affecting a minimum number of non-sensitive rules. PMID:28767687

  5. 26 CFR 1.367(a)-4T - Special rules applicable to specified transfers of property (temporary).

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... property (as defined in paragraph (b)(2) of this section) to a foreign corporation in an exchange described... subject to the rules of this paragraph (b) is any property that— (i) Is either mining property (as defined in section 617(f)(2)), section 1245 property (as defined in section 1245(a)(3)), section 1250...

  6. 40 CFR 52.1222 - Original Identification of plan section.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... between the State Pollution Control Agency and Erie Mining Company submitted by the State on February 20... 19, 1983, at 8 S.R. 1419 (text of rule starting at 8 S.R. 1420) and adopted as modified on April 16... Permits—Proposed and Published on December 19, 1983, at 8 S.R. 1419 (text of rule starting at 8 S.R. 1470...

  7. MINEs: open access databases of computationally predicted enzyme promiscuity products for untargeted metabolomics.

    PubMed

    Jeffryes, James G; Colastani, Ricardo L; Elbadawi-Sidhu, Mona; Kind, Tobias; Niehaus, Thomas D; Broadbelt, Linda J; Hanson, Andrew D; Fiehn, Oliver; Tyo, Keith E J; Henry, Christopher S

    2015-01-01

    In spite of its great promise, metabolomics has proven difficult to execute in an untargeted and generalizable manner. Liquid chromatography-mass spectrometry (LC-MS) has made it possible to gather data on thousands of cellular metabolites. However, matching metabolites to their spectral features continues to be a bottleneck, meaning that much of the collected information remains uninterpreted and that new metabolites are seldom discovered in untargeted studies. These challenges require new approaches that consider compounds beyond those available in curated biochemistry databases. Here we present Metabolic In silico Network Expansions (MINEs), an extension of known metabolite databases to include molecules that have not been observed, but are likely to occur based on known metabolites and common biochemical reactions. We utilize an algorithm called the Biochemical Network Integrated Computational Explorer (BNICE) and expert-curated reaction rules based on the Enzyme Commission classification system to propose the novel chemical structures and reactions that comprise MINE databases. Starting from the Kyoto Encyclopedia of Genes and Genomes (KEGG) COMPOUND database, the MINE contains over 571,000 compounds, of which 93% are not present in the PubChem database. However, these MINE compounds have on average higher structural similarity to natural products than compounds from KEGG or PubChem. MINE databases were able to propose annotations for 98.6% of a set of 667 MassBank spectra, 14% more than KEGG alone and equivalent to PubChem while returning far fewer candidates per spectra than PubChem (46 vs. 1715 median candidates). Application of MINEs to LC-MS accurate mass data enabled the identity of an unknown peak to be confidently predicted. MINE databases are freely accessible for non-commercial use via user-friendly web-tools at http://minedatabase.mcs.anl.gov and developer-friendly APIs. MINEs improve metabolomics peak identification as compared to general chemical databases whose results include irrelevant synthetic compounds. Furthermore, MINEs complement and expand on previous in silico generated compound databases that focus on human metabolism. We are actively developing the database; future versions of this resource will incorporate transformation rules for spontaneous chemical reactions and more advanced filtering and prioritization of candidate structures. Graphical abstractMINE database construction and access methods. The process of constructing a MINE database from the curated source databases is depicted on the left. The methods for accessing the database are shown on the right.

  8. 78 FR 6765 - Amendment to the International Traffic in Arms Regulations: Revision of U.S. Munitions List...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-01-31

    ... revise Category IV (launch vehicles, guided missiles, ballistic missiles, rockets, torpedoes, bombs, and... revises USML Category IV (launch vehicles, guided missiles, ballistic missiles, rockets, torpedoes, bombs... missiles, rockets, torpedoes, bombs, and mines whose jurisdiction would be in doubt based on this revision...

  9. Mining knowledge from corpora: an application to retrieval and indexing.

    PubMed

    Soualmia, Lina F; Dahamna, Badisse; Darmoni, Stéfan

    2008-01-01

    The present work aims at discovering new associations between medical concepts to be exploited as input in retrieval and indexing. Association rules method is applied to documents. The process is carried out on three major document categories referring to e-health information consumers: health professionals, students and lay people. Association rules evaluation is founded on statistical measures combined with domain knowledge. Association rules represent existing relations between medical concepts (60.62%) and new knowledge (54.21%). Based on observations, 463 expert rules are defined by medical librarians for retrieval and indexing. Association rules bear out existing relations, produce new knowledge and support users and indexers in document retrieval and indexing.

  10. Bayesian selective response-adaptive design using the historical control.

    PubMed

    Kim, Mi-Ok; Harun, Nusrat; Liu, Chunyan; Khoury, Jane C; Broderick, Joseph P

    2018-06-13

    High quality historical control data, if incorporated, may reduce sample size, trial cost, and duration. A too optimistic use of the data, however, may result in bias under prior-data conflict. Motivated by well-publicized two-arm comparative trials in stroke, we propose a Bayesian design that both adaptively incorporates historical control data and selectively adapt the treatment allocation ratios within an ongoing trial responsively to the relative treatment effects. The proposed design differs from existing designs that borrow from historical controls. As opposed to reducing the number of subjects assigned to the control arm blindly, this design does so adaptively to the relative treatment effects only if evaluation of cumulated current trial data combined with the historical control suggests the superiority of the intervention arm. We used the effective historical sample size approach to quantify borrowed information on the control arm and modified the treatment allocation rules of the doubly adaptive biased coin design to incorporate the quantity. The modified allocation rules were then implemented under the Bayesian framework with commensurate priors addressing prior-data conflict. Trials were also more frequently concluded earlier in line with the underlying truth, reducing trial cost, and duration and yielded parameter estimates with smaller standard errors. © 2018 The Authors. Statistics in Medicine Published by John Wiley & Sons, Ltd.

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

    NASA Astrophysics Data System (ADS)

    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.

  12. Microbial genotype-phenotype mapping by class association rule mining.

    PubMed

    Tamura, Makio; D'haeseleer, Patrik

    2008-07-01

    Microbial phenotypes are typically due to the concerted action of multiple gene functions, yet the presence of each gene may have only a weak correlation with the observed phenotype. Hence, it may be more appropriate to examine co-occurrence between sets of genes and a phenotype (multiple-to-one) instead of pairwise relations between a single gene and the phenotype. Here, we propose an efficient class association rule mining algorithm, netCAR, in order to extract sets of COGs (clusters of orthologous groups of proteins) associated with a phenotype from COG phylogenetic profiles and a phenotype profile. netCAR takes into account the phylogenetic co-occurrence graph between COGs to restrict hypothesis space, and uses mutual information to evaluate the biconditional relation. We examined the mining capability of pairwise and multiple-to-one association by using netCAR to extract COGs relevant to six microbial phenotypes (aerobic, anaerobic, facultative, endospore, motility and Gram negative) from 11,969 unique COG profiles across 155 prokaryotic organisms. With the same level of false discovery rate, multiple-to-one association can extract about 10 times more relevant COGs than one-to-one association. We also reveal various topologies of association networks among COGs (modules) from extracted multiple-to-one correlation rules relevant with the six phenotypes; including a well-connected network for motility, a star-shaped network for aerobic and intermediate topologies for the other phenotypes. netCAR outperforms a standard CAR mining algorithm, CARapriori, while requiring several orders of magnitude less computational time for extracting 3-COG sets. Source code of the Java implementation is available as Supplementary Material at the Bioinformatics online website, or upon request to the author. Supplementary data are available at Bioinformatics online.

  13. Jackson Mills and Mine Falls Dams, Nashua, New Hampshire. Reconnaissance Report, Hydroelectric Feasibility. Volume 2. Mine Falls Dam.

    DTIC Science & Technology

    1980-01-01

    producers under a state law of 1978. Until the regulations under PURPA Title II (the National Energy Act of 1978) are promulgated and the PUC reviews this...hour (rWi); end it is FURTr.R ORDERMD, that the Corumission will re-examine th4 PURPA issues in this proceedirg upon the issuance of rules by the F-RC

  14. Mining and Exploitation of Rare Earth Elements in Africa as an Engagement Strategy in US Africa Command

    DTIC Science & Technology

    2011-06-17

    rechargeable batteries, cell phones, catalytic converters, fluorescent lights, hybrid vehicle batteries, and other pollution control devices.21 Figure...79 Lee Yong-tim, “South China Villagers Slam Pollution from Rare Earth Mine,” February 22, 2008, http://www.rfa.org/english...writing and implementing new environmental standards. “The rules will limit pollutants allowed in waste water and emissions of radioactive elements

  15. iADRs: towards online adverse drug reaction analysis.

    PubMed

    Lin, Wen-Yang; Li, He-Yi; Du, Jhih-Wei; Feng, Wen-Yu; Lo, Chiao-Feng; Soo, Von-Wun

    2012-12-01

    Adverse Drug Reaction (ADR) is one of the most important issues in the assessment of drug safety. In fact, many adverse drug reactions are not discovered during limited pre-marketing clinical trials; instead, they are only observed after long term post-marketing surveillance of drug usage. In light of this, the detection of adverse drug reactions, as early as possible, is an important topic of research for the pharmaceutical industry. Recently, large numbers of adverse events and the development of data mining technology have motivated the development of statistical and data mining methods for the detection of ADRs. These stand-alone methods, with no integration into knowledge discovery systems, are tedious and inconvenient for users and the processes for exploration are time-consuming. This paper proposes an interactive system platform for the detection of ADRs. By integrating an ADR data warehouse and innovative data mining techniques, the proposed system not only supports OLAP style multidimensional analysis of ADRs, but also allows the interactive discovery of associations between drugs and symptoms, called a drug-ADR association rule, which can be further developed using other factors of interest to the user, such as demographic information. The experiments indicate that interesting and valuable drug-ADR association rules can be efficiently mined.

  16. A Visual Analytics Approach to Structured Data Analysis to Enhance Nonproliferation and Arms Control Verification Activities

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

    Gillen, David S.

    Analysis activities for Nonproliferation and Arms Control verification require the use of many types of data. Tabular structured data, such as Excel spreadsheets and relational databases, have traditionally been used for data mining activities, where specific queries are issued against data to look for matching results. The application of visual analytics tools to structured data enables further exploration of datasets to promote discovery of previously unknown results. This paper discusses the application of a specific visual analytics tool to datasets related to the field of Arms Control and Nonproliferation to promote the use of visual analytics more broadly in thismore » domain. Visual analytics focuses on analytical reasoning facilitated by interactive visual interfaces (Wong and Thomas 2004). It promotes exploratory analysis of data, and complements data mining technologies where known patterns can be mined for. Also with a human in the loop, they can bring in domain knowledge and subject matter expertise. Visual analytics has not widely been applied to this domain. In this paper, we will focus on one type of data: structured data, and show the results of applying a specific visual analytics tool to answer questions in the Arms Control and Nonproliferation domain. We chose to use the T.Rex tool, a visual analytics tool developed at PNNL, which uses a variety of visual exploration patterns to discover relationships in structured datasets, including a facet view, graph view, matrix view, and timeline view. The facet view enables discovery of relationships between categorical information, such as countries and locations. The graph tool visualizes node-link relationship patterns, such as the flow of materials being shipped between parties. The matrix visualization shows highly correlated categories of information. The timeline view shows temporal patterns in data. In this paper, we will use T.Rex with two different datasets to demonstrate how interactive exploration of the data can aid an analyst with arms control and nonproliferation verification activities. Using a dataset from PIERS (PIERS 2014), we will show how container shipment imports and exports can aid an analyst in understanding the shipping patterns between two countries. We will also use T.Rex to examine a collection of research publications from the IAEA International Nuclear Information System (IAEA 2014) to discover collaborations of concern. We hope this paper will encourage the use of visual analytics structured data analytics in the field of nonproliferation and arms control verification. Our paper outlines some of the challenges that exist before broad adoption of these kinds of tools can occur and offers next steps to overcome these challenges.« less

  17. Example Building Damage Caused by Mining Exploitation in Disturbed Rock Mass

    NASA Astrophysics Data System (ADS)

    Florkowska, Lucyna

    2013-06-01

    Issues concerning protection of buildings against the impact of underground coal mining pose significant scientific and engineering challenges. In Poland, where mining is a potent and prominent industry assuring domestic energy security, regions within reach of mining influences are plenty. Moreover, due to their industrial character they are also densely built-up areas. Because minerals have been extracted on an industrial scale in majority of those areas for many years, the rock mass structure has been significantly disturbed. Hence, exploitation of successive layers of multi-seam deposits might cause considerable damage - both in terms of surface and existing infrastructure networks. In the light of those facts, the means of mining and building prevention have to be improved on a regular basis. Moreover, they have to be underpinned by reliable analyses holistically capturing the comprehensive picture of the mining, geotechnical and constructional situation of structures. Scientific research conducted based on observations and measurements of mining-induced strain in buildings is deployed to do just that. Presented in this paper examples of damage sustained by buildings armed with protection against mining influences give an account of impact the mining exploitation in disturbed rock mass can have. This paper is based on analyses of mining damage to church and Nursing Home owned by Evangelical Augsburg Parish in Bytom-Miechowice. Neighbouring buildings differ in the date they were built, construction, building technology, geometry of the building body and fitted protection against mining damage. Both the buildings, however, have sustained lately significant deformation and damage caused by repeated mining exploitation. Selected damage has been discussed hereunder. The structures have been characterised, their current situation and mining history have been outlined, which have taken their toll on character and magnitude of damage. Description has been supplemented with photographic documentation.

  18. International Humanitarian Law: The legal framework for humanitarian forensic action.

    PubMed

    Gaggioli, Gloria

    2018-01-01

    In armed conflicts, death is not an exceptional occurrence, but becomes the rule and occurs on a daily basis. Dead bodies are sometimes despoiled, mutilated, abandoned without any funeral rite and without a decent burial. Unidentified remains may be counted by hundreds or thousands. As a result, families look for years for missing relatives, ignorant of the fate of their loved ones. International Humanitarian Law, also called the laws of war or the law of armed conflict, is an international law branch, which has been developed to regulate and, as far as possible, to humanize armed conflicts. It contains a number of clear and concrete obligations incumbent to belligerent parties on the management of dead bodies, which provide the legal framework for humanitarian forensic action. The purpose of this article is to present, in a simple and concise manner, these rules with a view to extrapolate some key legal principles, such as the obligation to respect the dignity of the dead or the right to know the fate of relatives, which shall guide anyone dealing with human remains. Copyright © 2017 Elsevier B.V. All rights reserved.

  19. Integrated approach using data mining-based decision tree and object-based image analysis for high-resolution urban mapping of WorldView-2 satellite sensor data

    NASA Astrophysics Data System (ADS)

    Hamedianfar, Alireza; Shafri, Helmi Zulhaidi Mohd

    2016-04-01

    This paper integrates decision tree-based data mining (DM) and object-based image analysis (OBIA) to provide a transferable model for the detailed characterization of urban land-cover classes using WorldView-2 (WV-2) satellite images. Many articles have been published on OBIA in recent years based on DM for different applications. However, less attention has been paid to the generation of a transferable model for characterizing detailed urban land cover features. Three subsets of WV-2 images were used in this paper to generate transferable OBIA rule-sets. Many features were explored by using a DM algorithm, which created the classification rules as a decision tree (DT) structure from the first study area. The developed DT algorithm was applied to object-based classifications in the first study area. After this process, we validated the capability and transferability of the classification rules into second and third subsets. Detailed ground truth samples were collected to assess the classification results. The first, second, and third study areas achieved 88%, 85%, and 85% overall accuracies, respectively. Results from the investigation indicate that DM was an efficient method to provide the optimal and transferable classification rules for OBIA, which accelerates the rule-sets creation stage in the OBIA classification domain.

  20. Rules of co-occurring mutations characterize the antigenic evolution of human influenza A/H3N2, A/H1N1 and B viruses.

    PubMed

    Chen, Haifen; Zhou, Xinrui; Zheng, Jie; Kwoh, Chee-Keong

    2016-12-05

    The human influenza viruses undergo rapid evolution (especially in hemagglutinin (HA), a glycoprotein on the surface of the virus), which enables the virus population to constantly evade the human immune system. Therefore, the vaccine has to be updated every year to stay effective. There is a need to characterize the evolution of influenza viruses for better selection of vaccine candidates and the prediction of pandemic strains. Studies have shown that the influenza hemagglutinin evolution is driven by the simultaneous mutations at antigenic sites. Here, we analyze simultaneous or co-occurring mutations in the HA protein of human influenza A/H3N2, A/H1N1 and B viruses to predict potential mutations, characterizing the antigenic evolution. We obtain the rules of mutation co-occurrence using association rule mining after extracting HA1 sequences and detect co-mutation sites under strong selective pressure. Then we predict the potential drifts with specific mutations of the viruses based on the rules and compare the results with the "observed" mutations in different years. The sites under frequent mutations are in antigenic regions (epitopes) or receptor binding sites. Our study demonstrates the co-occurring site mutations obtained by rule mining can capture the evolution of influenza viruses, and confirms that cooperative interactions among sites of HA1 protein drive the influenza antigenic evolution.

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

    PubMed

    Galvão, Noemi Dreyer; de Fátima Marin, Heimar

    2010-01-01

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

  2. An Analysis of Mao Tse-Tung's Three Main Rules of Discipline and Eight Points for Attention. Occasional Paper No. 77-3.

    ERIC Educational Resources Information Center

    Massie, Michael

    The document analyzes Mao Tse-Tung's "Three Main Rules of Discipline" and "Eight Points For Attention" and presents, by way of comparison, the text of the "Code of Conduct" issued by the President of the United States for members of the armed forces during the Vietnam War. Mao's regulations were revised by the General…

  3. Finding the Density of a Liquid Using a Metre Rule

    ERIC Educational Resources Information Center

    Chattopadhyay, K. N.

    2008-01-01

    A simple method, which is based on the principle of moment of forces only, is described for the determination of the density of liquids without measuring the mass and volume. At first, an empty test tube and a solid substance, which are hung on each side of a metre rule, are balanced and the moment arm of the test tube is measured. Keeping the…

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

    NASA Astrophysics Data System (ADS)

    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.

  5. Visualization of usability and functionality of a professional website through web-mining.

    PubMed

    Jones, Josette F; Mahoui, Malika; Gopa, Venkata Devi Pragna

    2007-10-11

    Functional interface design requires understanding of the information system structure and the user. Web logs record user interactions with the interface, and thus provide some insight into user search behavior and efficiency of the search process. The present study uses a data-mining approach with techniques such as association rules, clustering and classification, to visualize the usability and functionality of a digital library through in depth analyses of web logs.

  6. Implementing the Seapower Strategy

    DTIC Science & Technology

    2008-01-01

    between the two ends. Here is an example. When Britannia ruled the waves with a global navy to pro- tect the empire, Sir Julian Corbett specified three...because torpedo boats, submarines, and mines threatened cheap kills.7 Upon the rise of the German High Seas Fleet in the decades before World War I...face swarms of small combatants are being developed with accompanying search and attack systems. We have reawakened to the threats from mines and quiet

  7. A//r//m//s AND SEISMIC SOURCE STUDIES.

    USGS Publications Warehouse

    Hanks, T.C.; ,

    1984-01-01

    This paper briefly summarizes some recent developments in studies of seismic source parameter estimation, emphasizing the essential similarities between mining-induced seismogenic-failure and naturally occurring, tectonically driven earthquakes. The root-mean-square acceleration, a//r//m//s, shows much promise as an observational measure of high-frequency ground motion; it is very stable observationally, is insensitive to radiation pattern, and can be related linearly to the dynamic stress differences arising in the faulting process. To interpret a//r//m//s correctly, however, requires knowledge of f//m//a//x, the high-frequency band-limitation of the radiated field of earthquakes. As a practical matter, f//m//a//x can be due to any number of causes, but an essential ambiguity is whether or not f//m//a//x can arise from source properties alone. The interaction of the aftershocks of the Oroville, California, earthquake illustrates how a//r//m//s stress drops may be connected to detailed seismicity patterns.

  8. The People’s Liberation Army Navy, A Modern Navy With Chinese Characteristics

    DTIC Science & Technology

    2009-04-01

    strategy that does not advocate replicating U.S. or Soviet " blue -water" naval capabilities. Instead, it calls for naval capabilities suited for...strength in 2009 consists of approximately 26 destroyers, 48 fugates , more than 80 missile-armed patrol craft, 58 amphibious ships, 40 mine warfare

  9. 76 FR 67637 - West Virginia Regulatory Program

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-11-02

    ... Surface Mining Reclamation and Enforcement (OSM), Interior. ACTION: Proposed rule with public comment period and opportunity for public hearing on proposed amendment. SUMMARY: We are announcing receipt of a... [[Page 67638

  10. Evaluation of corrosion fatigue and life prediction of lower arm for automotive suspension component

    NASA Astrophysics Data System (ADS)

    Kim, Yong-Sang; Kim, Jung-Gu

    2017-01-01

    Lower arm is one of the suspension components of automobile. It is suffered from driving vibration and corrosive environment, namely corrosion fatigue. In this study, corrosion fatigue property of lower arm was investigated, and a modified model based on Palmgren-Miner rule was developed to predict the lifetimes of corrosion fatigue. The corrosion fatigue life of lower arm was about 1/6 times shorter than fatigue life. Based on the results of corrosion fatigue tests and meteorological data in Seoul and Halifax, the corrosion fatigue life of lower arm was predicted. The satisfaction of 10-year and 300,000 km warranty was dominated by the climate of automobile driving. This prediction indicates that the weather condition or driving condition influences the life of automotive parts. Therefore, to determine the warranty of automotive parts, the driving condition has to be carefully considered.

  11. Association-rule-based tuberculosis disease diagnosis

    NASA Astrophysics Data System (ADS)

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

    NASA Astrophysics Data System (ADS)

    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.

  13. A primer to frequent itemset mining for bioinformatics

    PubMed Central

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

    2015-01-01

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

  14. Biclustering Learning of Trading Rules.

    PubMed

    Huang, Qinghua; Wang, Ting; Tao, Dacheng; Li, Xuelong

    2015-10-01

    Technical analysis with numerous indicators and patterns has been regarded as important evidence for making trading decisions in financial markets. However, it is extremely difficult for investors to find useful trading rules based on numerous technical indicators. This paper innovatively proposes the use of biclustering mining to discover effective technical trading patterns that contain a combination of indicators from historical financial data series. This is the first attempt to use biclustering algorithm on trading data. The mined patterns are regarded as trading rules and can be classified as three trading actions (i.e., the buy, the sell, and no-action signals) with respect to the maximum support. A modified K nearest neighborhood ( K -NN) method is applied to classification of trading days in the testing period. The proposed method [called biclustering algorithm and the K nearest neighbor (BIC- K -NN)] was implemented on four historical datasets and the average performance was compared with the conventional buy-and-hold strategy and three previously reported intelligent trading systems. Experimental results demonstrate that the proposed trading system outperforms its counterparts and will be useful for investment in various financial markets.

  15. Two-sample binary phase 2 trials with low type I error and low sample size

    PubMed Central

    Litwin, Samuel; Basickes, Stanley; Ross, Eric A.

    2017-01-01

    Summary We address design of two-stage clinical trials comparing experimental and control patients. Our end-point is success or failure, however measured, with null hypothesis that the chance of success in both arms is p0 and alternative that it is p0 among controls and p1 > p0 among experimental patients. Standard rules will have the null hypothesis rejected when the number of successes in the (E)xperimental arm, E, sufficiently exceeds C, that among (C)ontrols. Here, we combine one-sample rejection decision rules, E ≥ m, with two-sample rules of the form E – C > r to achieve two-sample tests with low sample number and low type I error. We find designs with sample numbers not far from the minimum possible using standard two-sample rules, but with type I error of 5% rather than 15% or 20% associated with them, and of equal power. This level of type I error is achieved locally, near the stated null, and increases to 15% or 20% when the null is significantly higher than specified. We increase the attractiveness of these designs to patients by using 2:1 randomization. Examples of the application of this new design covering both high and low success rates under the null hypothesis are provided. PMID:28118686

  16. Entity Bases: Large-Scale Knowledgebases for Intelligence Data

    DTIC Science & Technology

    2009-02-01

    declaratively expressed as Datalog rules . The EntityBase supports two query scenarios: • Free-Form Querying: A human analyst or a client program can pose...integration, Prometheus follows the Inverse Rules algo- rithm (Duschka 1997) with additional optimizations (Thakkar et al. 2005). We use the mediator...Discovery and Data Mining (PAKDD󈧈), Sydney, Australia. Crammer , K., Dekel, O., Keshet, J., Shalev-Shwartz, S., and Singer, Y. (2006). Online passive

  17. Analyzing Divisia Rules Extracted from a Feedforward Neural Network

    DTIC Science & Technology

    2006-03-01

    assumptions. (Barnett and work, Data Mining, Rule Generation Serletis give a detailed treatment of the the- ory of monetary aggregation [1].) However, 1... Serletis , A. (Eds.) (2000), The The- Swizerland, 1995. ory of Monetary Aggregation, North-H ollandeAmsterdam, Chgaptero , pp.- [11] Vincent A. Schmidt and...gas, Nevada, 2002. sets. Macroeconomic Dynamics, 1:485-512, 1997. Reprinted in Barnett, WA. [12] Vincent A. Schmidt and Jane M. Binner. and Serletis

  18. SCADA-based Operator Support System for Power Plant Equipment Fault Forecasting

    NASA Astrophysics Data System (ADS)

    Mayadevi, N.; Ushakumari, S. S.; Vinodchandra, S. S.

    2014-12-01

    Power plant equipment must be monitored closely to prevent failures from disrupting plant availability. Online monitoring technology integrated with hybrid forecasting techniques can be used to prevent plant equipment faults. A self learning rule-based expert system is proposed in this paper for fault forecasting in power plants controlled by supervisory control and data acquisition (SCADA) system. Self-learning utilizes associative data mining algorithms on the SCADA history database to form new rules that can dynamically update the knowledge base of the rule-based expert system. In this study, a number of popular associative learning algorithms are considered for rule formation. Data mining results show that the Tertius algorithm is best suited for developing a learning engine for power plants. For real-time monitoring of the plant condition, graphical models are constructed by K-means clustering. To build a time-series forecasting model, a multi layer preceptron (MLP) is used. Once created, the models are updated in the model library to provide an adaptive environment for the proposed system. Graphical user interface (GUI) illustrates the variation of all sensor values affecting a particular alarm/fault, as well as the step-by-step procedure for avoiding critical situations and consequent plant shutdown. The forecasting performance is evaluated by computing the mean absolute error and root mean square error of the predictions.

  19. INDEXABILITY AND OPTIMAL INDEX POLICIES FOR A CLASS OF REINITIALISING RESTLESS BANDITS.

    PubMed

    Villar, Sofía S

    2016-01-01

    Motivated by a class of Partially Observable Markov Decision Processes with application in surveillance systems in which a set of imperfectly observed state processes is to be inferred from a subset of available observations through a Bayesian approach, we formulate and analyze a special family of multi-armed restless bandit problems. We consider the problem of finding an optimal policy for observing the processes that maximizes the total expected net rewards over an infinite time horizon subject to the resource availability. From the Lagrangian relaxation of the original problem, an index policy can be derived, as long as the existence of the Whittle index is ensured. We demonstrate that such a class of reinitializing bandits in which the projects' state deteriorates while active and resets to its initial state when passive until its completion possesses the structural property of indexability and we further show how to compute the index in closed form. In general, the Whittle index rule for restless bandit problems does not achieve optimality. However, we show that the proposed Whittle index rule is optimal for the problem under study in the case of stochastically heterogenous arms under the expected total criterion, and it is further recovered by a simple tractable rule referred to as the 1-limited Round Robin rule. Moreover, we illustrate the significant suboptimality of other widely used heuristic: the Myopic index rule, by computing in closed form its suboptimality gap. We present numerical studies which illustrate for the more general instances the performance advantages of the Whittle index rule over other simple heuristics.

  20. INDEXABILITY AND OPTIMAL INDEX POLICIES FOR A CLASS OF REINITIALISING RESTLESS BANDITS

    PubMed Central

    Villar, Sofía S.

    2016-01-01

    Motivated by a class of Partially Observable Markov Decision Processes with application in surveillance systems in which a set of imperfectly observed state processes is to be inferred from a subset of available observations through a Bayesian approach, we formulate and analyze a special family of multi-armed restless bandit problems. We consider the problem of finding an optimal policy for observing the processes that maximizes the total expected net rewards over an infinite time horizon subject to the resource availability. From the Lagrangian relaxation of the original problem, an index policy can be derived, as long as the existence of the Whittle index is ensured. We demonstrate that such a class of reinitializing bandits in which the projects’ state deteriorates while active and resets to its initial state when passive until its completion possesses the structural property of indexability and we further show how to compute the index in closed form. In general, the Whittle index rule for restless bandit problems does not achieve optimality. However, we show that the proposed Whittle index rule is optimal for the problem under study in the case of stochastically heterogenous arms under the expected total criterion, and it is further recovered by a simple tractable rule referred to as the 1-limited Round Robin rule. Moreover, we illustrate the significant suboptimality of other widely used heuristic: the Myopic index rule, by computing in closed form its suboptimality gap. We present numerical studies which illustrate for the more general instances the performance advantages of the Whittle index rule over other simple heuristics. PMID:27212781

  1. [Rule of Clinical Application of Auricular Acupuncture Based on Data Mining].

    PubMed

    Bao, Na; Wang, Qiong; Sun, Yan-Hui; Shi, Jing; Li, Xiao-Feng; Xu, Jing; Xing, Hai-Jiao; Zhang, Xuan-Ping; Zhang, Xin; Du, Yu-Zhu; Li, Jun-Lei; Yang, Qing-Qing; Feng, Xin-Xin; Jia, Chun-Sheng; Wang, Jian-Ling

    2017-02-25

    To explore the rule of clinical application of auricular acupuncture therapy by data mining in order to guide clinical practice. The data base about single auricular acupuncture therapy for different clinical diseases was established by collection, sorting, screening, recording, collation, data extraction, statistic analysis on data samples from journals, academic theses dissertations published in near 60 years. The application rules of auricular therapy including its predominant diseases, stimulus modality, therapeutic effect, and angle of needling were summarized by data mining technique. Auricular acupuncture therapy has been widely and mostly used in the internal medicine department, accounting for 48.56%. Of stimulus modalities, auricular point paste and pressure is applied with the highest frequency, accounting for 64%. The highest effective rate is found in the surgery department diseases(81.41%). Pressure is the most effective stimulus in the internal medi-cine department, and bloodletting combined with paste and pressure in the surgery department, auricular point injection in the gynecology and pediatrics departments, bloodletting in the ophthalmology and otorhinolaryngology department, and auricular point incision in the dermatology department. Auricular point injection has remarkable effect. Bloodletting combined with paste and pressure has nearly the same effect as bloodletting in the same medical department except dematology department. Otherwise, angle of needling is rarely studied. Auricular therapy is widely used and has remarkable effect in treating diseases by using different stimulus modalities. Whereas the angle of needling is rarely studied and future investigation is needed.

  2. An Examination of the Effect of External Influences on the Soviet Negotiation Position in Post 1962 Arms Control Agreements

    DTIC Science & Technology

    1978-06-09

    Bolsheviks inherited not only the geography and • natural resources of Russia, but also the people and the his- tory and the culture. While Marxism ...international disarmament, but rather the arming of the proletariat for the purpose of disarming and defeating the bourgeoisie . <hough Maxim Litvinov, the...Drachkovitch, Milorad M, Marxism in the Modern World, Stanford, CA: Stanford University Press, 1965. Fainsod, Merle. How Russia-is Ruled, Cambridges

  3. Non-Lethal Weapons in Noncombatant Evacuation Operations

    DTIC Science & Technology

    1999-12-01

    against your small squad of peacekeepers. If any of the three men decides to shoot, your rules of engagement unambiguously allow you to shoot back in...personnel (Siegel, pp. 7-8). By 30 December, Mogadishu resembled a war zone, with shells being fired into tribal neighborhoods, and uncontrolled small arms...his sentiments changed during his New Year’s Day jog in the compound; the constant small arms fire outside the walls forced him to reconsider the

  4. Implementation of hospital examination reservation system using data mining technique.

    PubMed

    Cha, Hyo Soung; Yoon, Tae Sik; Ryu, Ki Chung; Shin, Il Won; Choe, Yang Hyo; Lee, Kyoung Yong; Lee, Jae Dong; Ryu, Keun Ho; Chung, Seung Hyun

    2015-04-01

    New methods for obtaining appropriate information for users have been attempted with the development of information technology and the Internet. Among such methods, the demand for systems and services that can improve patient satisfaction has increased in hospital care environments. In this paper, we proposed the Hospital Exam Reservation System (HERS), which uses the data mining method. First, we focused on carrying clinical exam data and finding the optimal schedule for generating rules using the multi-examination pattern-mining algorithm. Then, HERS was applied by a rule master and recommending system with an exam log. Finally, HERS was designed as a user-friendly interface. HERS has been applied at the National Cancer Center in Korea since June 2014. As the number of scheduled exams increased, the time required to schedule more than a single condition decreased (from 398.67% to 168.67% and from 448.49% to 188.49%; p < 0.0001). As the number of tests increased, the difference between HERS and non-HERS increased (from 0.18 days to 0.81 days). It was possible to expand the efficiency of HERS studies using mining technology in not only exam reservations, but also the medical environment. The proposed system based on doctor prescription removes exams that were not executed in order to improve recommendation accuracy. In addition, we expect HERS to become an effective system in various medical environments.

  5. Classification Based on Pruning and Double Covered Rule Sets for the Internet of Things Applications

    PubMed Central

    Zhou, Zhongmei; Wang, Weiping

    2014-01-01

    The Internet of things (IOT) is a hot issue in recent years. It accumulates large amounts of data by IOT users, which is a great challenge to mining useful knowledge from IOT. Classification is an effective strategy which can predict the need of users in IOT. However, many traditional rule-based classifiers cannot guarantee that all instances can be covered by at least two classification rules. Thus, these algorithms cannot achieve high accuracy in some datasets. In this paper, we propose a new rule-based classification, CDCR-P (Classification based on the Pruning and Double Covered Rule sets). CDCR-P can induce two different rule sets A and B. Every instance in training set can be covered by at least one rule not only in rule set A, but also in rule set B. In order to improve the quality of rule set B, we take measure to prune the length of rules in rule set B. Our experimental results indicate that, CDCR-P not only is feasible, but also it can achieve high accuracy. PMID:24511304

  6. Classification based on pruning and double covered rule sets for the internet of things applications.

    PubMed

    Li, Shasha; Zhou, Zhongmei; Wang, Weiping

    2014-01-01

    The Internet of things (IOT) is a hot issue in recent years. It accumulates large amounts of data by IOT users, which is a great challenge to mining useful knowledge from IOT. Classification is an effective strategy which can predict the need of users in IOT. However, many traditional rule-based classifiers cannot guarantee that all instances can be covered by at least two classification rules. Thus, these algorithms cannot achieve high accuracy in some datasets. In this paper, we propose a new rule-based classification, CDCR-P (Classification based on the Pruning and Double Covered Rule sets). CDCR-P can induce two different rule sets A and B. Every instance in training set can be covered by at least one rule not only in rule set A, but also in rule set B. In order to improve the quality of rule set B, we take measure to prune the length of rules in rule set B. Our experimental results indicate that, CDCR-P not only is feasible, but also it can achieve high accuracy.

  7. Discovering Sentinel Rules for Business Intelligence

    NASA Astrophysics Data System (ADS)

    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.

  8. An overview of mining-related environmental and human health issues, Marinduque Island, Philippines: observations from a joint U.S. Geological Survey - Armed Forces Institute of Pathology reconnaissance field evaluation, May 12-19, 2000

    USGS Publications Warehouse

    Plumlee, Geoffrey S.; Morton, Robert A.; Boyle, Terence P.; Medlin, Jack H.; Centeno, Jose A.

    2000-01-01

    This report summarizes results of a visit by the report authors to Marinduque Island, Philippines, in May 2000. The purpose of the visit was to conduct a preliminary examination of environmental problems created by a 1996 tailings spill from the Marcopper open-pit copper mine. The mine was operated from 1969-1996 by Macropper Mining Corperation, under 39.9% ownership, and design and management control of Placer Dome, Inc. Our trip expenses to and from the Philippines were funded by the USGS. In-country expenses were paid by the offices of Congressman Reyes and the Governor of Marinduque, Carmencita O. Reyes. This report includes observations we made based on our relatively short visit to the island, and observations based upon a preliminary review of the literature available on the islanda??s mining-environmental issues. In addition, we have included preliminary interpretations and analytical results of some water, sediment, and mine waste samples collected during our trip. We also highlight the environmental and human health issues we fell are in need of further study and consideration for mitigation or remediation. This report is preliminary and is not intended to be a comprehensive or final review of the islanda??s mining-environmental issues; many areas of further study are clearly neededa?|

  9. The role of conflict minerals, artisanal mining, and informal trading networks in African intrastate and regional conflicts

    USGS Publications Warehouse

    Chirico, Peter G.; Malpeli, Katherine C.

    2014-01-01

    The relationship between natural resources and armed conflict gained public and political attention in the 1990s, when it became evident that the mining and trading of diamonds were connected with brutal rebellions in several African nations. Easily extracted resources such as alluvial diamonds and gold have been and continue to be exploited by rebel groups to fund their activities. Artisanal and small-scale miners operating under a quasi-legal status often mine these mineral deposits. While many African countries have legalized artisanal mining and established flow chains through which production is intended to travel, informal trading networks frequently emerge in which miners seek to evade taxes and fees by selling to unauthorized buyers. These networks have the potential to become international in scope, with actors operating in multiple countries. The lack of government control over the artisanal mining sector and the prominence of informal trade networks can have severe social, political, and economic consequences. In the past, mineral extraction fuelled violent civil wars in Sierra Leone, Liberia, and Angola, and it continues to do so today in several other countries. The significant influence of the informal network that surrounds artisanal mining is therefore an important security concern that can extend across borders and have far-reaching impacts.

  10. Research of Litchi Diseases Diagnosis Expertsystem Based on Rbr and Cbr

    NASA Astrophysics Data System (ADS)

    Xu, Bing; Liu, Liqun

    To conquer the bottleneck problems existing in the traditional rule-based reasoning diseases diagnosis system, such as low reasoning efficiency and lack of flexibility, etc.. It researched the integrated case-based reasoning (CBR) and rule-based reasoning (RBR) technology, and put forward a litchi diseases diagnosis expert system (LDDES) with integrated reasoning method. The method use data mining and knowledge obtaining technology to establish knowledge base and case library. It adopt rules to instruct the retrieval and matching for CBR, and use association rule and decision trees algorithm to calculate case similarity.The experiment shows that the method can increase the system's flexibility and reasoning ability, and improve the accuracy of litchi diseases diagnosis.

  11. 78 FR 45017 - Amendment to the International Traffic in Arms Regulations: Revision of U.S. Munitions List...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-07-25

    ...)(i)(A) through (D), on the basis that commercial articles would otherwise be covered. The Department notes that the criteria in (A) through (D) are modified by the criteria of paragraph (a)(1)(i). However..., submarines, other undersea vehicles, torpedoes, or mines, having any of the following: (A) Multi-static...

  12. Hand-arm vibration syndrome in South African gold miners.

    PubMed

    Nyantumbu, Busi; Barber, Chris M; Ross, Mary; Curran, Andrew D; Fishwick, David; Dias, Belinda; Kgalamono, Spo; Phillips, James I

    2007-01-01

    Hand-arm vibration syndrome (HAVS) is associated with the use of hand-held vibrating tools. Affected workers may experience symptoms of tingling, numbness, loss of grip strength and pain. Loss of dexterity may impair everyday activities, and potentially increase the risk of occupational accidents. Although high vibration levels (up to 31 m/s(2)) have been measured in association with rock drills, HAVS has not been scientifically evaluated in the South African mining industry. The aim of this study was to determine the prevalence and severity of HAVS in South African gold miners, and to identify the tools responsible. A cross-sectional study was conducted in a single South African gold-mine. Participants were randomly selected from mineworkers returning from annual leave, comprising 156 subjects with occupational exposure to vibration, and 140 workers with no exposure. Miners who consented to participate underwent a clinical HAVS assessment following the UK Health and Safety Laboratory protocol. The prevalence of HAVS in vibration-exposed gold miners was 15%, with a mean latent period of 5.6 years. Among the non-exposed comparison group, 5% had signs and symptoms indistinguishable from HAVS. This difference was statistically significant (P < 0.05). All the cases of HAVS gave a history of exposure to rock drills. The study has diagnosed the first cases of HAVS in the South African mining industry. The prevalence of HAVS was lower than expected, and possible explanations for this may include a survivor population, and lack of vascular symptom reporting due to warm-ambient temperatures.

  13. Research on PM2.5 time series characteristics based on data mining technology

    NASA Astrophysics Data System (ADS)

    Zhao, Lifang; Jia, Jin

    2018-02-01

    With the development of data mining technology and the establishment of environmental air quality database, it is necessary to discover the potential correlations and rules by digging the massive environmental air quality information and analyzing the air pollution process. In this paper, we have presented a sequential pattern mining method based on the air quality data and pattern association technology to analyze the PM2.5 time series characteristics. Utilizing the real-time monitoring data of urban air quality in China, the time series rule and variation properties of PM2.5 under different pollution levels are extracted and analyzed. The analysis results show that the time sequence features of the PM2.5 concentration is directly affected by the alteration of the pollution degree. The longest time that PM2.5 remained stable is about 24 hours. As the pollution degree gets severer, the instability time and step ascending time gradually changes from 12-24 hours to 3 hours. The presented method is helpful for the controlling and forecasting of the air quality while saving the measuring costs, which is of great significance for the government regulation and public prevention of the air pollution.

  14. Cardiac data mining (CDM); organization and predictive analytics on biomedical (cardiac) data

    NASA Astrophysics Data System (ADS)

    Bilal, M. Musa; Hussain, Masood; Basharat, Iqra; Fatima, Mamuna

    2013-10-01

    Data mining and data analytics has been of immense importance to many different fields as we witness the evolution of data sciences over recent years. Biostatistics and Medical Informatics has proved to be the foundation of many modern biological theories and analysis techniques. These are the fields which applies data mining practices along with statistical models to discover hidden trends from data that comprises of biological experiments or procedures on different entities. The objective of this research study is to develop a system for the efficient extraction, transformation and loading of such data from cardiologic procedure reports given by Armed Forces Institute of Cardiology. It also aims to devise a model for the predictive analysis and classification of this data to some important classes as required by cardiologists all around the world. This includes predicting patient impressions and other important features.

  15. A fuzzy classifier system for process control

    NASA Technical Reports Server (NTRS)

    Karr, C. L.; Phillips, J. C.

    1994-01-01

    A fuzzy classifier system that discovers rules for controlling a mathematical model of a pH titration system was developed by researchers at the U.S. Bureau of Mines (USBM). Fuzzy classifier systems successfully combine the strengths of learning classifier systems and fuzzy logic controllers. Learning classifier systems resemble familiar production rule-based systems, but they represent their IF-THEN rules by strings of characters rather than in the traditional linguistic terms. Fuzzy logic is a tool that allows for the incorporation of abstract concepts into rule based-systems, thereby allowing the rules to resemble the familiar 'rules-of-thumb' commonly used by humans when solving difficult process control and reasoning problems. Like learning classifier systems, fuzzy classifier systems employ a genetic algorithm to explore and sample new rules for manipulating the problem environment. Like fuzzy logic controllers, fuzzy classifier systems encapsulate knowledge in the form of production rules. The results presented in this paper demonstrate the ability of fuzzy classifier systems to generate a fuzzy logic-based process control system.

  16. Managing the Big Data Avalanche in Astronomy - Data Mining the Galaxy Zoo Classification Database

    NASA Astrophysics Data System (ADS)

    Borne, Kirk D.

    2014-01-01

    We will summarize a variety of data mining experiments that have been applied to the Galaxy Zoo database of galaxy classifications, which were provided by the volunteer citizen scientists. The goal of these exercises is to learn new and improved classification rules for diverse populations of galaxies, which can then be applied to much larger sky surveys of the future, such as the LSST (Large Synoptic Sky Survey), which is proposed to obtain detailed photometric data for approximately 20 billion galaxies. The massive Big Data that astronomy projects will generate in the future demand greater application of data mining and data science algorithms, as well as greater training of astronomy students in the skills of data mining and data science. The project described here has involved several graduate and undergraduate research assistants at George Mason University.

  17. Ion Channel ElectroPhysiology Ontology (ICEPO) - a case study of text mining assisted ontology development.

    PubMed

    Elayavilli, Ravikumar Komandur; Liu, Hongfang

    2016-01-01

    Computational modeling of biological cascades is of great interest to quantitative biologists. Biomedical text has been a rich source for quantitative information. Gathering quantitative parameters and values from biomedical text is one significant challenge in the early steps of computational modeling as it involves huge manual effort. While automatically extracting such quantitative information from bio-medical text may offer some relief, lack of ontological representation for a subdomain serves as impedance in normalizing textual extractions to a standard representation. This may render textual extractions less meaningful to the domain experts. In this work, we propose a rule-based approach to automatically extract relations involving quantitative data from biomedical text describing ion channel electrophysiology. We further translated the quantitative assertions extracted through text mining to a formal representation that may help in constructing ontology for ion channel events using a rule based approach. We have developed Ion Channel ElectroPhysiology Ontology (ICEPO) by integrating the information represented in closely related ontologies such as, Cell Physiology Ontology (CPO), and Cardiac Electro Physiology Ontology (CPEO) and the knowledge provided by domain experts. The rule-based system achieved an overall F-measure of 68.93% in extracting the quantitative data assertions system on an independently annotated blind data set. We further made an initial attempt in formalizing the quantitative data assertions extracted from the biomedical text into a formal representation that offers potential to facilitate the integration of text mining into ontological workflow, a novel aspect of this study. This work is a case study where we created a platform that provides formal interaction between ontology development and text mining. We have achieved partial success in extracting quantitative assertions from the biomedical text and formalizing them in ontological framework. The ICEPO ontology is available for download at http://openbionlp.org/mutd/supplementarydata/ICEPO/ICEPO.owl.

  18. Fact Sheet - Final Air Toxics Rule for Gold Mine Ore Processing and Production

    EPA Pesticide Factsheets

    Fact sheet summarizing main points of National Emissions Standards for Hazardous Air Pollutants for gold ore processing and production facilities, the seventh largest source of mercury air emission in the United States.

  19. Chromite Ore from the Transvaal Region of South Africa

    EPA Pesticide Factsheets

    In 2001, EPA finalized a rule to to delete both chromite ore mined in the Transvaal Region of South Africa and the unreacted ore component of the chromite ore processing residue (COPR) from TRI reporting requirements.

  20. 78 FR 77024 - Telemarketing Sales Rule; Notice of Termination of Caller ID Rulemaking

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-12-20

    ..., data mining and anomaly detection, and call-blocking technology). \\19\\ AT&T Servs., Inc., No. 00040, at... technically feasible, by looking at the signaling data . . . to distinguish between a CPN [calling party...

  1. An intelligent knowledge mining model for kidney cancer using rough set theory.

    PubMed

    Durai, M A Saleem; Acharjya, D P; Kannan, A; Iyengar, N Ch Sriman Narayana

    2012-01-01

    Medical diagnosis processes vary in the degree to which they attempt to deal with different complicating aspects of diagnosis such as relative importance of symptoms, varied symptom pattern and the relation between diseases themselves. Rough set approach has two major advantages over the other methods. First, it can handle different types of data such as categorical, numerical etc. Secondly, it does not make any assumption like probability distribution function in stochastic modeling or membership grade function in fuzzy set theory. It involves pattern recognition through logical computational rules rather than approximating them through smooth mathematical functional forms. In this paper we use rough set theory as a data mining tool to derive useful patterns and rules for kidney cancer faulty diagnosis. In particular, the historical data of twenty five research hospitals and medical college is used for validation and the results show the practical viability of the proposed approach.

  2. The expert explorer: a tool for hospital data visualization and adverse drug event rules validation.

    PubMed

    Băceanu, Adrian; Atasiei, Ionuţ; Chazard, Emmanuel; Leroy, Nicolas

    2009-01-01

    An important part of adverse drug events (ADEs) detection is the validation of the clinical cases and the assessment of the decision rules to detect ADEs. For that purpose, a software called "Expert Explorer" has been designed by Ideea Advertising. Anonymized datasets have been extracted from hospitals into a common repository. The tool has 3 main features. (1) It can display hospital stays in a visual and comprehensive way (diagnoses, drugs, lab results, etc.) using tables and pretty charts. (2) It allows designing and executing dashboards in order to generate knowledge about ADEs. (3) It finally allows uploading decision rules obtained from data mining. Experts can then review the rules, the hospital stays that match the rules, and finally give their advice thanks to specialized forms. Then the rules can be validated, invalidated, or improved (knowledge elicitation phase).

  3. Statistical methods of estimating mining costs

    USGS Publications Warehouse

    Long, K.R.

    2011-01-01

    Until it was defunded in 1995, the U.S. Bureau of Mines maintained a Cost Estimating System (CES) for prefeasibility-type economic evaluations of mineral deposits and estimating costs at producing and non-producing mines. This system had a significant role in mineral resource assessments to estimate costs of developing and operating known mineral deposits and predicted undiscovered deposits. For legal reasons, the U.S. Geological Survey cannot update and maintain CES. Instead, statistical tools are under development to estimate mining costs from basic properties of mineral deposits such as tonnage, grade, mineralogy, depth, strip ratio, distance from infrastructure, rock strength, and work index. The first step was to reestimate "Taylor's Rule" which relates operating rate to available ore tonnage. The second step was to estimate statistical models of capital and operating costs for open pit porphyry copper mines with flotation concentrators. For a sample of 27 proposed porphyry copper projects, capital costs can be estimated from three variables: mineral processing rate, strip ratio, and distance from nearest railroad before mine construction began. Of all the variables tested, operating costs were found to be significantly correlated only with strip ratio.

  4. Ensuring the Environmental and Industrial Safety in Solid Mineral Deposit Surface Mining

    NASA Astrophysics Data System (ADS)

    Trubetskoy, Kliment; Rylnikova, Marina; Esina, Ekaterina

    2017-11-01

    The growing environmental pressure of mineral deposit surface mining and severization of industrial safety requirements dictate the necessity of refining the regulatory framework governing safe and efficient development of underground resources. The applicable regulatory documentation governing the procedure of ore open-pit wall and bench stability design for the stage of pit reaching its final boundary was issued several decades ago. Over recent decades, mining and geomechanical conditions have changed significantly in surface mining operations, numerous new software packages and computer developments have appeared, opportunities of experimental methods of source data collection and processing, grounding of the permissible parameters of open pit walls have changed dramatically, and, thus, methods of risk assessment have been perfected [10-13]. IPKON RAS, with the support of the Federal Service for Environmental Supervision, assumed the role of the initiator of the project for the development of Federal norms and regulations of industrial safety "Rules for ensuring the stability of walls and benches of open pits, open-cast mines and spoil banks", which contribute to the improvement of economic efficiency and safety of mineral deposit surface mining and enhancement of the competitiveness of Russian mines at the international level that is very important in the current situation.

  5. Methodological issues with adaptation of clinical trial design.

    PubMed

    Hung, H M James; Wang, Sue-Jane; O'Neill, Robert T

    2006-01-01

    Adaptation of clinical trial design generates many issues that have not been resolved for practical applications, though statistical methodology has advanced greatly. This paper focuses on some methodological issues. In one type of adaptation such as sample size re-estimation, only the postulated value of a parameter for planning the trial size may be altered. In another type, the originally intended hypothesis for testing may be modified using the internal data accumulated at an interim time of the trial, such as changing the primary endpoint and dropping a treatment arm. For sample size re-estimation, we make a contrast between an adaptive test weighting the two-stage test statistics with the statistical information given by the original design and the original sample mean test with a properly corrected critical value. We point out the difficulty in planning a confirmatory trial based on the crude information generated by exploratory trials. In regards to selecting a primary endpoint, we argue that the selection process that allows switching from one endpoint to the other with the internal data of the trial is not very likely to gain a power advantage over the simple process of selecting one from the two endpoints by testing them with an equal split of alpha (Bonferroni adjustment). For dropping a treatment arm, distributing the remaining sample size of the discontinued arm to other treatment arms can substantially improve the statistical power of identifying a superior treatment arm in the design. A common difficult methodological issue is that of how to select an adaptation rule in the trial planning stage. Pre-specification of the adaptation rule is important for the practicality consideration. Changing the originally intended hypothesis for testing with the internal data generates great concerns to clinical trial researchers.

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

    PubMed

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

    2012-11-01

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

  7. Two-sample binary phase 2 trials with low type I error and low sample size.

    PubMed

    Litwin, Samuel; Basickes, Stanley; Ross, Eric A

    2017-04-30

    We address design of two-stage clinical trials comparing experimental and control patients. Our end point is success or failure, however measured, with null hypothesis that the chance of success in both arms is p 0 and alternative that it is p 0 among controls and p 1  > p 0 among experimental patients. Standard rules will have the null hypothesis rejected when the number of successes in the (E)xperimental arm, E, sufficiently exceeds C, that among (C)ontrols. Here, we combine one-sample rejection decision rules, E⩾m, with two-sample rules of the form E - C > r to achieve two-sample tests with low sample number and low type I error. We find designs with sample numbers not far from the minimum possible using standard two-sample rules, but with type I error of 5% rather than 15% or 20% associated with them, and of equal power. This level of type I error is achieved locally, near the stated null, and increases to 15% or 20% when the null is significantly higher than specified. We increase the attractiveness of these designs to patients by using 2:1 randomization. Examples of the application of this new design covering both high and low success rates under the null hypothesis are provided. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

  8. Dynamic association rules for gene expression data analysis.

    PubMed

    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 DAR algorithm not only was able to identify a set of differentially expressed genes that largely agreed with that of other methods, but also provided an efficient and accurate way to find influential genes of a disease. In the paper, the well-established association rule mining technique from marketing has been successfully modified to determine the minimum support and minimum confidence based on the concept of confidence interval and hypothesis testing. It can be applied to gene expression data to mine significant association rules between gene regulation and phenotype. The proposed DAR algorithm provides an efficient way to find influential genes that underlie the phenotypic variance.

  9. [Analysis of on medication rules for Qi-deficiency and blood-stasis syndrome of chronic heart failure based on data mining technology].

    PubMed

    Wang, Qian; Yao, Geng-Zhen; Pan, Guang-Ming; Huang, Jing-Yi; An, Yi-Pei; Zou, Xu

    2017-01-01

    To analyze the medication features and the regularity of prescriptions of traditional Chinese medicine in treating patients with Qi-deficiency and blood-stasis syndrome of chronic heart failure based on modern literature. In this article, CNKI Chinese academic journal database, Wanfang Chinese academic journal database and VIP Chinese periodical database were all searched from January 2000 to December 2015 for the relevant literature on traditional Chinese medicine treatment for Qi-deficiency and blood-stasis syndrome of chronic heart failure. Then a normalized database was established for further data mining and analysis. Subsequently, the medication features and the regularity of prescriptions were mined by using traditional Chinese medicine inheritance support system(V2.5), association rules, improved mutual information algorithm, complex system entropy clustering and other mining methods. Finally, a total of 171 articles were included, involving 171 prescriptions, 140 kinds of herbs, with a total frequency of 1 772 for the herbs. As a result, 19 core prescriptions and 7 new prescriptions were mined. The most frequently used herbs included Huangqi(Astragali Radix), Danshen(Salviae Miltiorrhizae Radix et Rhizoma), Fuling(Poria), Renshen(Ginseng Radix et Rhizoma), Tinglizi(Semen Lepidii), Baizhu(Atractylodis Macrocephalae Rhizoma), and Guizhi(Cinnamomum Ramulus). The core prescriptions were composed of Huangqi(Astragali Radix), Danshen(Salviae Miltiorrhizae Radix et Rhizoma) and Fuling(Poria), etc. The high frequent herbs and core prescriptions not only highlight the medication features of Qi-invigorating and blood-circulating therapy, but also reflect the regularity of prescriptions of blood-circulating, Yang-warming, and urination-promoting therapy based on syndrome differentiation. Moreover, the mining of the new prescriptions provide new reference and inspiration for clinical treatment of various accompanying symptoms of chronic heart failure. In conclusion, this article provides new reference for traditional Chinese medicine in the treatment of chronic heart failure. Copyright© by the Chinese Pharmaceutical Association.

  10. Knowledge discovery with classification rules in a cardiovascular dataset.

    PubMed

    Podgorelec, Vili; Kokol, Peter; Stiglic, Milojka Molan; Hericko, Marjan; Rozman, Ivan

    2005-12-01

    In this paper we study an evolutionary machine learning approach to data mining and knowledge discovery based on the induction of classification rules. A method for automatic rules induction called AREX using evolutionary induction of decision trees and automatic programming is introduced. The proposed algorithm is applied to a cardiovascular dataset consisting of different groups of attributes which should possibly reveal the presence of some specific cardiovascular problems in young patients. A case study is presented that shows the use of AREX for the classification of patients and for discovering possible new medical knowledge from the dataset. The defined knowledge discovery loop comprises a medical expert's assessment of induced rules to drive the evolution of rule sets towards more appropriate solutions. The final result is the discovery of a possible new medical knowledge in the field of pediatric cardiology.

  11. 20 CFR 410.687 - Rules governing the representation and advising of claimants and parties.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... ADMINISTRATION FEDERAL COAL MINE HEALTH AND SAFETY ACT OF 1969, TITLE IV-BLACK LUNG BENEFITS (1969... attorney or other representative shall: (a) With intent to defraud, in any matter willfully and knowingly...

  12. Using knowledge rules for pharmacy mapping.

    PubMed

    Shakib, Shaun C; Che, Chengjian; Lau, Lee Min

    2006-01-01

    The 3M Health Information Systems (HIS) Healthcare Data Dictionary (HDD) is used to encode and structure patient medication data for the Electronic Health Record (EHR) of the Department of Defense's (DoD's) Armed Forces Health Longitudinal Technology Application (AHLTA). HDD Subject Matter Experts (SMEs) are responsible for initial and maintenance mapping of disparate, standalone medication master files from all 100 DoD host sites worldwide to a single concept-based vocabulary, to accomplish semantic interoperability. To achieve higher levels of automation, SMEs began defining a growing set of knowledge rules. These knowledge rules were implemented in a pharmacy mapping tool, which enhanced consistency through automation and increased mapping rate by 29%.

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

    NASA Astrophysics Data System (ADS)

    Vathsala, H.; Koolagudi, Shashidhar G.

    2017-01-01

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

  14. PubMedMiner: Mining and Visualizing MeSH-based Associations in PubMed.

    PubMed

    Zhang, Yucan; Sarkar, Indra Neil; Chen, Elizabeth S

    2014-01-01

    The exponential growth of biomedical literature provides the opportunity to develop approaches for facilitating the identification of possible relationships between biomedical concepts. Indexing by Medical Subject Headings (MeSH) represent high-quality summaries of much of this literature that can be used to support hypothesis generation and knowledge discovery tasks using techniques such as association rule mining. Based on a survey of literature mining tools, a tool implemented using Ruby and R - PubMedMiner - was developed in this study for mining and visualizing MeSH-based associations for a set of MEDLINE articles. To demonstrate PubMedMiner's functionality, a case study was conducted that focused on identifying and comparing comorbidities for asthma in children and adults. Relative to the tools surveyed, the initial results suggest that PubMedMiner provides complementary functionality for summarizing and comparing topics as well as identifying potentially new knowledge.

  15. Identification of water-quality trends using sediment cores from Dillon Reservoir, Summit County, Colorado

    USGS Publications Warehouse

    Greve, Adrienne I.; Spahr, Norman E.; Van Metre, Peter C.; Wilson, Jennifer T.

    2001-01-01

    Since the construction of Dillon Reservoir, in Summit County, Colorado, in 1963, its drainage area has been the site of rapid urban development and the continued influence of historical mining. In an effort to assess changes in water quality within the drainage area, sediment cores were collected from Dillon Reservoir in 1997. The sediment cores were analyzed for pesticides, polychlorinated biphenyls (PCBs), polycyclic aromatic hydrocarbons (PAHs), and trace elements. Pesticides, PCBs, and PAHs were used to determine the effects of urban development, and trace elements were used to identify mining contributions. Water-quality and streambed-sediment samples, collected at the mouth of three streams that drain into Dillon Reservoir, were analyzed for trace elements. Of the 14 pesticides and 3 PCBs for which the sediment samples were analyzed, only 2 pesticides were detected. Low amounts of dichloro-diphenyldichloroethylene (DDE) and dichloro-diphenyldichloroethane (DDD), metabolites of dichlorodiphenyltrichloroethane (DDT), were found at core depths of 5 centimeters and below 15 centimeters in a core collected near the dam. The longest core, which was collected near the dam, spanned the entire sedimentation history of the reservoir. Concentrations of total combustion PAH and the ratio of fluoranthene to pyrene in the core sample decreased with core depth and increased over time. This relation is likely due to growth in residential and tourist populations in the region. Comparisons between core samples gathered in each arm of the reservoir showed the highest PAH concentrations were found in the Tenmile Creek arm, the only arm that has an urban area on its shores, the town of Frisco. All PAH concentrations, except the pyrene concentration in one segment in the core near the dam and acenaphthylene concentrations in the tops of three cores taken in the reservoir arms, were below Canadian interim freshwater sediment-quality guidelines. Concentrations of arsenic, cadmium, chromium, copper, lead, and zinc in sediment samples from Dillon Reservoir exceeded the Canadian interim freshwater sediment-quality guidelines. Copper, iron, lithium, nickel, scandium, titanium, and vanadium concentrations in sediment samples decreased over time. Other elements, while no trend was evident, displayed concentration spikes in the down-core profiles, indicating loads entering the reservoir may have been larger than they were in 1997. The highest concentrations of copper, lead, manganese, mercury, and zinc were detected during the late 1970's and early 1980's. Elevated concentrations of trace elements in sediment in Dillon Reservoir likely resulted from historical mining in the drainage area. The downward trend identified for copper, iron, lithium, nickel, scandium, titanium, and vanadium may be due in part to restoration efforts in mining-affected areas and a decrease in active mining in the Dillon Reservoir watershed. Although many trace-element core-sediment concentrations exceeded the Canadian probable effect level for freshwater lakes, under current limnological conditions, the high core-sediment concentrations do not adversely affect water quality in Dillon Reservoir. The trace-element concentrations in the reservoir water column meet the standards established by the Colorado Water Quality Control Commission. Although many trace-element core-sediment concentrations exceeded the Canadian probable effect level for freshwater lakes, under current limnological conditions, the high core-sediment concentrations do not adversely affect water quality in Dillon Reservoir. The trace-element concentrations in the reservoir water column meet the standards established by the Colorado Water Quality Control Commission.

  16. Noise-induced hearing loss and combined noise and vibration exposure.

    PubMed

    Turcot, A; Girard, S A; Courteau, M; Baril, J; Larocque, R

    2015-04-01

    While there is a wide body of literature addressing noise-induced hearing loss (NIHL) and hand-arm vibration syndrome (HAVS) independently, relatively few studies have considered the combined effects of noise and vibration. These studies have suggested an increased risk of NIHL in workers with vibration white finger (VWF), though the relationship remains poorly understood. To determine whether hearing impairment is worse in noise-exposed workers with VWF than in workers with similar noise exposures but without VWF. The Quebec National Institute of Public Health audiometric database was used in conjunction with work-related accident and occupational diseases data from the Quebec workers' compensation board to analyse differences in audiometry results between vibration-exposed workers in the mining and forestry industries and the overall source population, and between mining and forestry workers with documented VWF and those without VWF. The International Organization for Standardization (ISO) 7029 standards were used to calculate hearing loss not attributable to age. 15751 vibration-exposed workers were identified in an overall source population of 59339. Workers with VWF (n = 96) had significantly worse hearing at every frequency studied (500, 1000, 2000 4000 Hz) compared with other mining and forestry workers without VWF. This study confirms previous findings of greater hearing loss at higher frequencies in workers with VWF, but also found a significant difference in hearing loss at low frequencies. It therefore supports the association between combined noise and hand-arm vibration (HAV) exposure and NIHL. © The Author 2015. Published by Oxford University Press on behalf of the Society of Occupational Medicine. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  17. A Common Set of Core Values - The Foundation for a More Effective Joint Force

    DTIC Science & Technology

    2015-05-18

    these codes stopped short of codifying a set of core values and instead focused on right and wrong behaviors. This adherence to sets of rules and...Armed Forces independently recognized the limitations of compliance-based rules and the criticality of establishing a strong foundation with core...institutional values vice core values? The knee -jerk reaction of the 1990s and a subsequent lack of a formal effort to institute a single set of core

  18. Automobile or other conveyance and adaptive equipment certificate of eligibility for veterans or members of the armed forces with amyotrophic lateral sclerosis. Interim final rule.

    PubMed

    2015-02-25

    The Department of Veterans Affairs (VA) is amending its adjudication regulation regarding certificates of eligibility for financial assistance in the purchase of an automobile or other conveyance and adaptive equipment. The amendment authorizes automatic issuance of a certificate of eligibility for financial assistance in the purchase of an automobile or other conveyance and adaptive equipment to all veterans with service-connected amyotrophic lateral sclerosis (ALS) and members of the Armed Forces serving on active duty with ALS.

  19. Long-range prediction of Indian summer monsoon rainfall using data mining and statistical approaches

    NASA Astrophysics Data System (ADS)

    H, Vathsala; Koolagudi, Shashidhar G.

    2017-10-01

    This paper presents a hybrid model to better predict Indian summer monsoon rainfall. The algorithm considers suitable techniques for processing dense datasets. The proposed three-step algorithm comprises closed itemset generation-based association rule mining for feature selection, cluster membership for dimensionality reduction, and simple logistic function for prediction. The application of predicting rainfall into flood, excess, normal, deficit, and drought based on 36 predictors consisting of land and ocean variables is presented. Results show good accuracy in the considered study period of 37years (1969-2005).

  20. Data Mining Methods for Recommender Systems

    NASA Astrophysics Data System (ADS)

    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. Remote Manipulator

    NASA Technical Reports Server (NTRS)

    1986-01-01

    SPAR Aerospace Limited's "Canadarm," Canada's contribution to the space shuttle. It is a crane which can operate as a 50 foot extension of an astronaut's arm. It can lift 65,000 pounds in space and retrieve satellites for repair, etc. Redesigned versions have energy and mining applications. Some of its hardware has been redeveloped for use as a Hydro manipulator in a nuclear reactor where it is expected to be extremely cost effective.

  2. Comparison of rule induction, decision trees and formal concept analysis approaches for classification

    NASA Astrophysics Data System (ADS)

    Kotelnikov, E. V.; Milov, V. R.

    2018-05-01

    Rule-based learning algorithms have higher transparency and easiness to interpret in comparison with neural networks and deep learning algorithms. These properties make it possible to effectively use such algorithms to solve descriptive tasks of data mining. The choice of an algorithm depends also on its ability to solve predictive tasks. The article compares the quality of the solution of the problems with binary and multiclass classification based on the experiments with six datasets from the UCI Machine Learning Repository. The authors investigate three algorithms: Ripper (rule induction), C4.5 (decision trees), In-Close (formal concept analysis). The results of the experiments show that In-Close demonstrates the best quality of classification in comparison with Ripper and C4.5, however the latter two generate more compact rule sets.

  3. Analysis of Human Mobility Based on Cellular Data

    NASA Astrophysics Data System (ADS)

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

    2017-01-01

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

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

    NASA Astrophysics Data System (ADS)

    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.

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

    PubMed

    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.

  6. 78 FR 61411 - Self-Regulatory Organizations; NYSE Arca, Inc.; Notice of Filing and Immediate Effectiveness of...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-10-03

    ... systems failure, natural or man- made disaster, act of God, armed conflict, act of terrorism, riot or... communications relating to the proposed rule change between the Commission and any person, other than those that...

  7. 43 CFR 3481.4 - Temporary interruption in coal severance.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... 43 Public Lands: Interior 2 2013-10-01 2013-10-01 false Temporary interruption in coal severance... LAND MANAGEMENT, DEPARTMENT OF THE INTERIOR MINERALS MANAGEMENT (3000) COAL EXPLORATION AND MINING OPERATIONS RULES General Provisions § 3481.4 Temporary interruption in coal severance. ...

  8. 43 CFR 3481.4 - Temporary interruption in coal severance.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... 43 Public Lands: Interior 2 2012-10-01 2012-10-01 false Temporary interruption in coal severance... LAND MANAGEMENT, DEPARTMENT OF THE INTERIOR MINERALS MANAGEMENT (3000) COAL EXPLORATION AND MINING OPERATIONS RULES General Provisions § 3481.4 Temporary interruption in coal severance. ...

  9. 43 CFR 3481.4 - Temporary interruption in coal severance.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ... 43 Public Lands: Interior 2 2014-10-01 2014-10-01 false Temporary interruption in coal severance... LAND MANAGEMENT, DEPARTMENT OF THE INTERIOR MINERALS MANAGEMENT (3000) COAL EXPLORATION AND MINING OPERATIONS RULES General Provisions § 3481.4 Temporary interruption in coal severance. ...

  10. 43 CFR 3481.4 - Temporary interruption in coal severance.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... 43 Public Lands: Interior 2 2011-10-01 2011-10-01 false Temporary interruption in coal severance... LAND MANAGEMENT, DEPARTMENT OF THE INTERIOR MINERALS MANAGEMENT (3000) COAL EXPLORATION AND MINING OPERATIONS RULES General Provisions § 3481.4 Temporary interruption in coal severance. ...

  11. 75 FR 61366 - Montana Regulatory Program

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-10-05

    ... Mining Reclamation and Enforcement, Interior. ACTION: Proposed rule; public comment period and opportunity for public hearing on proposed amendment. SUMMARY: We are announcing receipt of a proposed... that we will follow for the public hearing, if one is requested. DATES: We will accept written comments...

  12. 78 FR 13004 - Wyoming Regulatory Program

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-02-26

    ... Mining Reclamation and Enforcement, Interior. ACTION: Proposed rule; public comment period and opportunity for public hearing on proposed amendment. SUMMARY: We are announcing receipt of a proposed... will follow for the public hearing, if one is requested. DATES: We will accept written comments on this...

  13. 75 FR 81459 - Simplified Proceedings

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-12-28

    ... FEDERAL MINE SAFETY AND HEALTH REVIEW COMMISSION 29 CFR Part 2700 Simplified Proceedings AGENCY... Commission is publishing a final rule to simplify the procedures for handling certain civil penalty.... Electronic comments should state ``Comments on Simplified Proceedings'' in the subject line and be sent to...

  14. 78 FR 11796 - Kentucky Regulatory Program

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-02-20

    ... personal identifying information from public review, we cannot guarantee that we will be able to do so... our review of the proposed amendment after the close of the public comment period and determine... Mining Reclamation and Enforcement, Interior. ACTION: Proposed rule; public comment period and...

  15. 76 FR 73885 - Mandatory Reporting of Greenhouse Gases

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-11-29

    .... 211112 Natural gas liquid extraction facilities. Underground Coal Mines........ 212113 Underground... natural gas liquids in addition to suppliers of petroleum products. 2. Summary of Comments and Responses... Mandatory Reporting of Greenhouse Gases; Final Rule #0;#0;Federal Register / Vol. 76, No. 229 / Tuesday...

  16. Human Systems Integration (HSI) Associated Development Activities in Japan

    DTIC Science & Technology

    2008-06-12

    machine learning and data mining methods. The continuous effort ( KAIZEN ) to improve the analysis phases are illustrated in Figure 14. Although there...model Extraction of a workflow Extraction of a control rule Variation analysis and improvement Plant operation KAIZEN Fig. 14

  17. Chapter 16: text mining for translational bioinformatics.

    PubMed

    Cohen, K Bretonnel; Hunter, Lawrence E

    2013-04-01

    Text mining for translational bioinformatics is a new field with tremendous research potential. It is a subfield of biomedical natural language processing that concerns itself directly with the problem of relating basic biomedical research to clinical practice, and vice versa. Applications of text mining fall both into the category of T1 translational research-translating basic science results into new interventions-and T2 translational research, or translational research for public health. Potential use cases include better phenotyping of research subjects, and pharmacogenomic research. A variety of methods for evaluating text mining applications exist, including corpora, structured test suites, and post hoc judging. Two basic principles of linguistic structure are relevant for building text mining applications. One is that linguistic structure consists of multiple levels. The other is that every level of linguistic structure is characterized by ambiguity. There are two basic approaches to text mining: rule-based, also known as knowledge-based; and machine-learning-based, also known as statistical. Many systems are hybrids of the two approaches. Shared tasks have had a strong effect on the direction of the field. Like all translational bioinformatics software, text mining software for translational bioinformatics can be considered health-critical and should be subject to the strictest standards of quality assurance and software testing.

  18. Frequent associations between CTL and T-Helper epitopes in HIV-1 genomes and implications for multi-epitope vaccine designs

    PubMed Central

    2010-01-01

    Background Epitope vaccines have been suggested as a strategy to counteract viral escape and development of drug resistance. Multiple studies have shown that Cytotoxic T-Lymphocyte (CTL) and T-Helper (Th) epitopes can generate strong immune responses in Human Immunodeficiency Virus (HIV-1). However, not much is known about the relationship among different types of HIV epitopes, particularly those epitopes that can be considered potential candidates for inclusion in the multi-epitope vaccines. Results In this study we used association rule mining to examine relationship between different types of epitopes (CTL, Th and antibody epitopes) from nine protein-coding HIV-1 genes to identify strong associations as potent multi-epitope vaccine candidates. Our results revealed 137 association rules that were consistently present in the majority of reference and non-reference HIV-1 genomes and included epitopes of two different types (CTL and Th) from three different genes (Gag, Pol and Nef). These rules involved 14 non-overlapping epitope regions that frequently co-occurred despite high mutation and recombination rates, including in genomes of circulating recombinant forms. These epitope regions were also highly conserved at both the amino acid and nucleotide levels indicating strong purifying selection driven by functional and/or structural constraints and hence, the diminished likelihood of successful escape mutations. Conclusions Our results provide a comprehensive systematic survey of CTL, Th and Ab epitopes that are both highly conserved and co-occur together among all subtypes of HIV-1, including circulating recombinant forms. Several co-occurring epitope combinations were identified as potent candidates for inclusion in multi-epitope vaccines, including epitopes that are immuno-responsive to different arms of the host immune machinery and can enable stronger and more efficient immune responses, similar to responses achieved with adjuvant therapies. Signature of strong purifying selection acting at the nucleotide level of the associated epitopes indicates that these regions are functionally critical, although the exact reasons behind such sequence conservation remain to be elucidated. PMID:20696039

  19. Statistical physics of nucleosome positioning and chromatin structure

    NASA Astrophysics Data System (ADS)

    Morozov, Alexandre

    2012-02-01

    Genomic DNA is packaged into chromatin in eukaryotic cells. The fundamental building block of chromatin is the nucleosome, a 147 bp-long DNA molecule wrapped around the surface of a histone octamer. Arrays of nucleosomes are positioned along DNA according to their sequence preferences and folded into higher-order chromatin fibers whose structure is poorly understood. We have developed a framework for predicting sequence-specific histone-DNA interactions and the effective two-body potential responsible for ordering nucleosomes into regular higher-order structures. Our approach is based on the analogy between nucleosomal arrays and a one-dimensional fluid of finite-size particles with nearest-neighbor interactions. We derive simple rules which allow us to predict nucleosome occupancy solely from the dinucleotide content of the underlying DNA sequences.Dinucleotide content determines the degree of stiffness of the DNA polymer and thus defines its ability to bend into the nucleosomal superhelix. As expected, the nucleosome positioning rules are universal for chromatin assembled in vitro on genomic DNA from baker's yeast and from the nematode worm C.elegans, where nucleosome placement follows intrinsic sequence preferences and steric exclusion. However, the positioning rules inferred from in vivo C.elegans chromatin are affected by global nucleosome depletion from chromosome arms relative to central domains, likely caused by the attachment of the chromosome arms to the nuclear membrane. Furthermore, intrinsic nucleosome positioning rules are overwritten in transcribed regions, indicating that chromatin organization is actively managed by the transcriptional and splicing machinery.

  20. Application of a hybrid association rules/decision tree model for drought monitoring

    NASA Astrophysics Data System (ADS)

    Nourani, Vahid; Molajou, Amir

    2017-12-01

    The previous researches have shown that the incorporation of the oceanic-atmospheric climate phenomena such as Sea Surface Temperature (SST) into hydro-climatic models could provide important predictive information about hydro-climatic variability. In this paper, the hybrid application of two data mining techniques (decision tree and association rules) was offered to discover affiliation between drought of Tabriz and Kermanshah synoptic stations (located in Iran) and de-trend SSTs of the Black, Mediterranean and Red Seas. Two major steps of the proposed model were the classification of de-trend SST data and selecting the most effective groups and extracting hidden information involved in the data. The techniques of decision tree which can identify the good traits from a data set for the classification purpose were used for classification and selecting the most effective groups and association rules were employed to extract the hidden predictive information from the large observed data. To examine the accuracy of the rules, confidence and Heidke Skill Score (HSS) measures were calculated and compared for different considering lag times. The computed measures confirm reliable performance of the proposed hybrid data mining method to forecast drought and the results show a relative correlation between the Mediterranean, Black and Red Sea de-trend SSTs and drought of Tabriz and Kermanshah synoptic stations so that the confidence between the monthly Standardized Precipitation Index (SPI) values and the de-trend SST of seas is higher than 70 and 80% respectively for Tabriz and Kermanshah synoptic stations.

  1. Location Prediction Based on Transition Probability Matrices Constructing from Sequential Rules for Spatial-Temporal K-Anonymity Dataset

    PubMed Central

    Liu, Zhao; Zhu, Yunhong; Wu, Chenxue

    2016-01-01

    Spatial-temporal k-anonymity has become a mainstream approach among techniques for protection of users’ privacy in location-based services (LBS) applications, and has been applied to several variants such as LBS snapshot queries and continuous queries. Analyzing large-scale spatial-temporal anonymity sets may benefit several LBS applications. In this paper, we propose two location prediction methods based on transition probability matrices constructing from sequential rules for spatial-temporal k-anonymity dataset. First, we define single-step sequential rules mined from sequential spatial-temporal k-anonymity datasets generated from continuous LBS queries for multiple users. We then construct transition probability matrices from mined single-step sequential rules, and normalize the transition probabilities in the transition matrices. Next, we regard a mobility model for an LBS requester as a stationary stochastic process and compute the n-step transition probability matrices by raising the normalized transition probability matrices to the power n. Furthermore, we propose two location prediction methods: rough prediction and accurate prediction. The former achieves the probabilities of arriving at target locations along simple paths those include only current locations, target locations and transition steps. By iteratively combining the probabilities for simple paths with n steps and the probabilities for detailed paths with n-1 steps, the latter method calculates transition probabilities for detailed paths with n steps from current locations to target locations. Finally, we conduct extensive experiments, and correctness and flexibility of our proposed algorithm have been verified. PMID:27508502

  2. Properties of intermodal transfer after dual visuo- and auditory-motor adaptation.

    PubMed

    Schmitz, Gerd; Bock, Otmar L

    2017-10-01

    Previous work documented that sensorimotor adaptation transfers between sensory modalities: When subjects adapt with one arm to a visuomotor distortion while responding to visual targets, they also appear to be adapted when they are subsequently tested with auditory targets. Vice versa, when they adapt to an auditory-motor distortion while pointing to auditory targets, they appear to be adapted when they are subsequently tested with visual targets. Therefore, it was concluded that visuomotor as well as auditory-motor adaptation use the same adaptation mechanism. Furthermore, it has been proposed that sensory information from the trained modality is weighted larger than sensory information from an untrained one, because transfer between sensory modalities is incomplete. The present study tested these hypotheses for dual arm adaptation. One arm adapted to an auditory-motor distortion and the other either to an opposite directed auditory-motor or visuomotor distortion. We found that both arms adapted significantly. However, compared to reference data on single arm adaptation, adaptation in the dominant arm was reduced indicating interference from the non-dominant to the dominant arm. We further found that arm-specific aftereffects of adaptation, which reflect recalibration of sensorimotor transformation rules, were stronger or equally strong when targets were presented in the previously adapted compared to the non-adapted sensory modality, even when one arm adapted visually and the other auditorily. The findings are discussed with respect to a recently published schematic model on sensorimotor adaptation. Copyright © 2017 Elsevier B.V. All rights reserved.

  3. Stratified sampling design based on data mining.

    PubMed

    Kim, Yeonkook J; Oh, Yoonhwan; Park, Sunghoon; Cho, Sungzoon; Park, Hayoung

    2013-09-01

    To explore classification rules based on data mining methodologies which are to be used in defining strata in stratified sampling of healthcare providers with improved sampling efficiency. We performed k-means clustering to group providers with similar characteristics, then, constructed decision trees on cluster labels to generate stratification rules. We assessed the variance explained by the stratification proposed in this study and by conventional stratification to evaluate the performance of the sampling design. We constructed a study database from health insurance claims data and providers' profile data made available to this study by the Health Insurance Review and Assessment Service of South Korea, and population data from Statistics Korea. From our database, we used the data for single specialty clinics or hospitals in two specialties, general surgery and ophthalmology, for the year 2011 in this study. Data mining resulted in five strata in general surgery with two stratification variables, the number of inpatients per specialist and population density of provider location, and five strata in ophthalmology with two stratification variables, the number of inpatients per specialist and number of beds. The percentages of variance in annual changes in the productivity of specialists explained by the stratification in general surgery and ophthalmology were 22% and 8%, respectively, whereas conventional stratification by the type of provider location and number of beds explained 2% and 0.2% of variance, respectively. This study demonstrated that data mining methods can be used in designing efficient stratified sampling with variables readily available to the insurer and government; it offers an alternative to the existing stratification method that is widely used in healthcare provider surveys in South Korea.

  4. Design of foundations with sliding joint at areas affected with underground mining

    NASA Astrophysics Data System (ADS)

    Matečková, P.; Šmiřáková, M.; Maňásek, P.

    2018-04-01

    Underground mining always influences also landscape on surface. If there are buildings on the surface they are affected with terrain deformation which comprises terrain inclination, curvature, shift and horizontal deformation. Ostrava – Karvina region is specific with underground mining very close to densely inhabited area. About 25 years ago there were mines even in the city of Ostrava. Recommendations and rules for design of building structures at areas affected with underground mining have been therefore analysed in long term. This paper is focused on deformation action caused by terrain horizontal deformation - expansion or compression. Through the friction between foundation structure and subsoil in footing bottom the foundation structure has to resist significant normal forces. The idea of sliding joint which eliminates the friction and decreases internal forces comes from the last century. Sliding joint made of asphalt belt has been analysed at Faculty of Civil Engineering, VSB – Technical University of Ostrava in long term. The influence of vertical and horizontal load and the effect of temperature in temperature controlled room have been examined. Testing, design and utilization of sliding joint is presented.

  5. Radiation and ionization energy loss simulation for the GDH sum rule experiment in Hall-A at Jefferson Lab

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

    Yan, Xin -Hu; Ye, Yun -Xiu; Chen, Jian -Ping

    2015-07-17

    The radiation and ionization energy loss are presented for single arm Monte Carlo simulation for the GDH sum rule experiment in Hall-A at Jefferson Lab. Radiation and ionization energy loss are discussed formore » $$^{12}C$$ elastic scattering simulation. The relative momentum ratio $$\\frac{\\Delta p}{p}$$ and $$^{12}C$$ elastic cross section are compared without and with radiation energy loss and a reasonable shape is obtained by the simulation. The total energy loss distribution is obtained, showing a Landau shape for $$^{12}C$$ elastic scattering. This simulation work will give good support for radiation correction analysis of the GDH sum rule experiment.« less

  6. Using Knowledge Rules for Pharmacy Mapping

    PubMed Central

    Shakib, Shaun C.; Che, Chengjian; Lau, Lee Min

    2006-01-01

    The 3M Health Information Systems (HIS) Healthcare Data Dictionary (HDD) is used to encode and structure patient medication data for the Electronic Health Record (EHR) of the Department of Defense’s (DoD’s) Armed Forces Health Longitudinal Technology Application (AHLTA). HDD Subject Matter Experts (SMEs) are responsible for initial and maintenance mapping of disparate, standalone medication master files from all 100 DoD host sites worldwide to a single concept-based vocabulary, to accomplish semantic interoperability. To achieve higher levels of automation, SMEs began defining a growing set of knowledge rules. These knowledge rules were implemented in a pharmacy mapping tool, which enhanced consistency through automation and increased mapping rate by 29%. PMID:17238709

  7. 14 CFR 13.21 - Military personnel.

    Code of Federal Regulations, 2014 CFR

    2014-01-01

    ... 14 Aeronautics and Space 1 2014-01-01 2014-01-01 false Military personnel. 13.21 Section 13.21 Aeronautics and Space FEDERAL AVIATION ADMINISTRATION, DEPARTMENT OF TRANSPORTATION PROCEDURAL RULES... under this part indicates that, while performing official duties, a member of the Armed Forces, or a...

  8. Development of design specifications, details and design criteria for traffic light poles

    DOT National Transportation Integrated Search

    2006-09-01

    Current rules and fabrication methods employed in the design of traffic light poles do not adequately address fatigue and fracture issues associated with the connection of mast arms to the vertical poles and the connection of the poles to the foundat...

  9. Korean Affairs Report, Number 294

    DTIC Science & Technology

    1983-07-18

    felt skepticism about whether the ruling and opposition parties possess the public will of public parties and are loyal to the professional ethics ...be prepared as revolutionized communist women is to completely eliminate egoism from their minds and to arm them with the communist idea and with the

  10. Unbiased estimation in seamless phase II/III trials with unequal treatment effect variances and hypothesis-driven selection rules.

    PubMed

    Robertson, David S; Prevost, A Toby; Bowden, Jack

    2016-09-30

    Seamless phase II/III clinical trials offer an efficient way to select an experimental treatment and perform confirmatory analysis within a single trial. However, combining the data from both stages in the final analysis can induce bias into the estimates of treatment effects. Methods for bias adjustment developed thus far have made restrictive assumptions about the design and selection rules followed. In order to address these shortcomings, we apply recent methodological advances to derive the uniformly minimum variance conditionally unbiased estimator for two-stage seamless phase II/III trials. Our framework allows for the precision of the treatment arm estimates to take arbitrary values, can be utilised for all treatments that are taken forward to phase III and is applicable when the decision to select or drop treatment arms is driven by a multiplicity-adjusted hypothesis testing procedure. © 2016 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd. © 2016 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

  11. A New Approach for Resolving Conflicts in Actionable Behavioral Rules

    PubMed Central

    Zhu, Dan; Zeng, Daniel

    2014-01-01

    Knowledge is considered actionable if users can take direct actions based on such knowledge to their advantage. Among the most important and distinctive actionable knowledge are actionable behavioral rules that can directly and explicitly suggest specific actions to take to influence (restrain or encourage) the behavior in the users' best interest. However, in mining such rules, it often occurs that different rules may suggest the same actions with different expected utilities, which we call conflicting rules. To resolve the conflicts, a previous valid method was proposed. However, inconsistency of the measure for rule evaluating may hinder its performance. To overcome this problem, we develop a new method that utilizes rule ranking procedure as the basis for selecting the rule with the highest utility prediction accuracy. More specifically, we propose an integrative measure, which combines the measures of the support and antecedent length, to evaluate the utility prediction accuracies of conflicting rules. We also introduce a tunable weight parameter to allow the flexibility of integration. We conduct several experiments to test our proposed approach and evaluate the sensitivity of the weight parameter. Empirical results indicate that our approach outperforms those from previous research. PMID:25162054

  12. 75 FR 6330 - North Dakota Regulatory Program

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-02-09

    ... Surface Mining Reclamation and Enforcement, Interior. ACTION: Proposed rule; public comment period and opportunity for public hearing on proposed amendment. SUMMARY: We are announcing receipt of a proposed... the amendment, and the procedures that we will follow for the public hearing, if one is requested...

  13. 77 FR 48429 - Commission Address Change

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-08-14

    ....C. 804(3)(C), this rule ``does not substantially affect the rights or obligations of non-agency... Administrative practice and procedure, Civil rights, Equal employment opportunity, Federal buildings and... ON THE BASIS OF HANDICAP IN PROGRAMS OR ACTIVITIES CONDUCTED BY THE FEDERAL MINE SAFETY AND HEALTH...

  14. 75 FR 73955 - Penalty Settlement Procedure

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-11-30

    ... 1977, or Mine Act. Hearings are held before the Commission's Administrative Law Judges, and appellate... Senate. The Commission is publishing a final rule to streamline the process for settling civil penalties... Commission's civil penalty settlement procedures. 75 FR 21987. The Commission explained that since 2006, the...

  15. 43 CFR 4.1361 - Who may file.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... Special Rules Applicable to Surface Coal Mining Hearings and Appeals Request for Review of Approval Or... Sale of Rights Granted Under Permit (federal Program; Federal Lands Program; Federal Program for Indian... forth in § 4.1360 may file a request for review of that decision. ...

  16. A Hybrid Data Mining Approach for Credit Card Usage Behavior Analysis

    NASA Astrophysics Data System (ADS)

    Tsai, Chieh-Yuan

    Credit card is one of the most popular e-payment approaches in current online e-commerce. To consolidate valuable customers, card issuers invest a lot of money to maintain good relationship with their customers. Although several efforts have been done in studying card usage motivation, few researches emphasize on credit card usage behavior analysis when time periods change from t to t+1. To address this issue, an integrated data mining approach is proposed in this paper. First, the customer profile and their transaction data at time period t are retrieved from databases. Second, a LabelSOM neural network groups customers into segments and identify critical characteristics for each group. Third, a fuzzy decision tree algorithm is used to construct usage behavior rules of interesting customer groups. Finally, these rules are used to analysis the behavior changes between time periods t and t+1. An implementation case using a practical credit card database provided by a commercial bank in Taiwan is illustrated to show the benefits of the proposed framework.

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

    PubMed Central

    Nikfarjam, Azadeh; Gonzalez, Graciela H.

    2011-01-01

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

  18. Agile Text Mining for the 2014 i2b2/UTHealth Cardiac Risk Factors Challenge

    PubMed Central

    Cormack, James; Nath, Chinmoy; Milward, David; Raja, Kalpana; Jonnalagadda, Siddhartha R

    2016-01-01

    This paper describes the use of an agile text mining platform (Linguamatics’ Interactive Information Extraction Platform, I2E) to extract document-level cardiac risk factors in patient records as defined in the i2b2/UTHealth 2014 Challenge. The approach uses a data-driven rule-based methodology with the addition of a simple supervised classifier. We demonstrate that agile text mining allows for rapid optimization of extraction strategies, while post-processing can leverage annotation guidelines, corpus statistics and logic inferred from the gold standard data. We also show how data imbalance in a training set affects performance. Evaluation of this approach on the test data gave an F-Score of 91.7%, one percent behind the top performing system. PMID:26209007

  19. A Bayesian pick-the-winner design in a randomized phase II clinical trial.

    PubMed

    Chen, Dung-Tsa; Huang, Po-Yu; Lin, Hui-Yi; Chiappori, Alberto A; Gabrilovich, Dmitry I; Haura, Eric B; Antonia, Scott J; Gray, Jhanelle E

    2017-10-24

    Many phase II clinical trials evaluate unique experimental drugs/combinations through multi-arm design to expedite the screening process (early termination of ineffective drugs) and to identify the most effective drug (pick the winner) to warrant a phase III trial. Various statistical approaches have been developed for the pick-the-winner design but have been criticized for lack of objective comparison among the drug agents. We developed a Bayesian pick-the-winner design by integrating a Bayesian posterior probability with Simon two-stage design in a randomized two-arm clinical trial. The Bayesian posterior probability, as the rule to pick the winner, is defined as probability of the response rate in one arm higher than in the other arm. The posterior probability aims to determine the winner when both arms pass the second stage of the Simon two-stage design. When both arms are competitive (i.e., both passing the second stage), the Bayesian posterior probability performs better to correctly identify the winner compared with the Fisher exact test in the simulation study. In comparison to a standard two-arm randomized design, the Bayesian pick-the-winner design has a higher power to determine a clear winner. In application to two studies, the approach is able to perform statistical comparison of two treatment arms and provides a winner probability (Bayesian posterior probability) to statistically justify the winning arm. We developed an integrated design that utilizes Bayesian posterior probability, Simon two-stage design, and randomization into a unique setting. It gives objective comparisons between the arms to determine the winner.

  20. Frac Sand Mines Are Preferentially Sited in Unzoned Rural Areas.

    PubMed

    Locke, Christina

    2015-01-01

    Shifting markets can cause unexpected, stochastic changes in rural landscapes that may take local communities by surprise. Preferential siting of new industrial facilities in poor areas or in areas with few regulatory restrictions can have implications for environmental sustainability, human health, and social justice. This study focuses on frac sand mining-the mining of high-quality silica sand used in hydraulic fracturing processes for gas and oil extraction. Frac sand mining gained prominence in the 2000s in the upper midwestern United States where nonmetallic mining is regulated primarily by local zoning. I asked whether frac sand mines were more commonly sited in rural townships without formal zoning regulations or planning processes than in those that undertook zoning and planning before the frac sand boom. I also asked if mine prevalence was correlated with socioeconomic differences across townships. After creating a probability surface to map areas most suitable for frac sand mine occurrence, I developed neutral landscape models from which to compare actual mine distributions in zoned and unzoned areas at three different spatial extents. Mines were significantly clustered in unzoned jurisdictions at the statewide level and in 7 of the 8 counties with at least three frac sand mines and some unzoned land. Subsequent regression analyses showed mine prevalence to be uncorrelated with land value, tax rate, or per capita income, but correlated with remoteness and zoning. The predicted mine count in unzoned townships was over two times higher than that in zoned townships. However, the county with the most mines by far was under a county zoning ordinance, perhaps indicating industry preferences for locations with clear, homogenous rules over patchwork regulation. Rural communities can use the case of frac sand mining as motivation to discuss and plan for sudden land-use predicaments, rather than wait to grapple with unfamiliar legal processes during a period of intense conflict.

Some links on this page may take you to non-federal websites. Their policies may differ from this site.
Top