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Sample records for associative flow rule

  1. The study of slip line field and upper bound method based on associated flow and non-associated flow rules

    Institute of Scientific and Technical Information of China (English)

    Zheng Yingren; Deng Chujian; Wang Jinglin

    2010-01-01

    At present,associated flow rule of traditional plastic theory is adopted in the slip line field theory and upper bound method of geotechnical materials.So the stress characteristic line conforms to the velocity line.It is proved that geotechnical materials do not abide by the associated flow rule.It is impossible for the stress characteristic line to conform to the velocity line.Generalized plastic mechanics theoretically proved that plastic potential surface intersects the Mohr-Coulomb yield surface with an angle,so that the velocity line must be studied by non-associated flow rule.According to limit analysis theory,the theory of slip line field is put forward in this paper,and then the ultimate boating capacity of strip footing is obtained based on the associated flow rule and the non-associated flow rule individually.These two results are identical since the ultimate bearing capacity is independent of flow rule.On the contrary,the velocity fields of associated and non-associated flow rules are different which shows the velocity field based on the associated flow rule is incorrect.

  2. Seismic failure mechanisms for loaded slopes with associated and nonassociated flow rules

    Institute of Scientific and Technical Information of China (English)

    YANG Xiao-li; SUI Zhi-rong

    2008-01-01

    Seismic failure mechanisms were investigated for soil slopes subjected to strip load with upper bound method of limit analysis and finite difference method of numerical simulation, considering the influence of associated and nonassociated flow rules. Quasi-static representation of soil inertia effects using a seismic coefficient concept was adopted for seismic failure analysis. Numerical study was conducted to investigate the influences of dilative angle and earthquake on the seismic failure mechanisms for the loaded slope, and the failure mechanisms for different dilation angles were compared. The results show that dilation angle has influences on the seismic failure surfaces, that seismic maximum displacement vector decreases as the dilation angle increases, and that seismic maximum shear strain rate decreases as the dilation angle increases.

  3. Linguistic Valued Association Rules

    Institute of Scientific and Technical Information of China (English)

    LU Jian-jiang; QIAN Zuo-ping

    2002-01-01

    Association rules discovering and prediction with data mining method are two topics in the field of information processing. In this paper, the records in database are divided into many linguistic values expressed with normal fuzzy numbers by fuzzy c-means algorithm, and a series of linguistic valued association rules are generated. Then the records in database are mapped onto the linguistic values according to largest subject principle, and the support and confidence definitions of linguistic valued association rules are also provided. The discovering and prediction methods of the linguistic valued association rules are discussed through a weather example last.

  4. Energy analysis of stability on shallow tunnels based on non-associated flow rule and non-linear failure criterion

    Institute of Scientific and Technical Information of China (English)

    张佳华; 王成洋

    2015-01-01

    On the basis of upper bound theorem, non-associated flow rule and non-linear failure criterion were considered together. The modified shear strength parameters of materials were obtained with the help of the tangent method. Employing the virtual power principle and strength reduction technique, the effects of dilatancy of materials, non-linear failure criterion, pore water pressure, surface loads and buried depth, on the stability of shallow tunnel were studied. In order to validate the effectiveness of the proposed approach, the solutions in the present work agree well with the existing results when the non-associated flow rule is reduced to the associated flow rule and the non-linear failure criterion is degenerated to the linear failure criterion. Compared with dilatancy of materials, the non-linear failure criterion exerts greater impact on the stability of shallow tunnels. The safety factor of shallow tunnels decreases and the failure surface expands outward when the dilatancy coefficient decreases. While the increase of nonlinear coefficient, the pore water pressure coefficient, the surface load and the buried depth results in the small safety factor. Therefore, the dilatancy as well as non-linear failure criterion should be taken into account in the design of shallow tunnel supporting structure. The supporting structure must be reinforced promptly to prevent potential mud from gushing or collapse accident in the areas with abundant pore water, large surface load or buried depth.

  5. Generalized Multidimensional Association Rules

    Institute of Scientific and Technical Information of China (English)

    周傲英; 周水庚; 金文; 田增平

    2000-01-01

    The problem of association rule mining has gained considerable prominence in the data mining community for its use as an important tool of knowl-edge discovery from large-scale databases. And there has been a spurt of research activities around this problem. Traditional association rule mining is limited to intra-transaction. Only recently the concept of N-dimensional inter-transaction as-sociation rule (NDITAR) was proposed by H.J. Lu. This paper modifies and extends Lu's definition of NDITAR based on the analysis of its limitations, and the general-ized multidimensional association rule (GMDAR) is subsequently introduced, which is more general, flexible and reasonable than NDITAR.

  6. DEVELOPMENT OF PLASTICITY MODEL USING NON ASSOCIATED FLOW RULE FOR HCP MATERIALS INCLUDING ZIRCONIUM FOR NUCLEAR APPLICATIONS

    Energy Technology Data Exchange (ETDEWEB)

    Michael V. Glazoff; Jeong-Whan Yoon

    2013-08-01

    In this report (prepared in collaboration with Prof. Jeong Whan Yoon, Deakin University, Melbourne, Australia) a research effort was made to develop a non associated flow rule for zirconium. Since Zr is a hexagonally close packed (hcp) material, it is impossible to describe its plastic response under arbitrary loading conditions with any associated flow rule (e.g. von Mises). As a result of strong tension compression asymmetry of the yield stress and anisotropy, zirconium displays plastic behavior that requires a more sophisticated approach. Consequently, a new general asymmetric yield function has been developed which accommodates mathematically the four directional anisotropies along 0 degrees, 45 degrees, 90 degrees, and biaxial, under tension and compression. Stress anisotropy has been completely decoupled from the r value by using non associated flow plasticity, where yield function and plastic potential have been treated separately to take care of stress and r value directionalities, respectively. This theoretical development has been verified using Zr alloys at room temperature as an example as these materials have very strong SD (Strength Differential) effect. The proposed yield function reasonably well models the evolution of yield surfaces for a zirconium clock rolled plate during in plane and through thickness compression. It has been found that this function can predict both tension and compression asymmetry mathematically without any numerical tolerance and shows the significant improvement compared to any reported functions. Finally, in the end of the report, a program of further research is outlined aimed at constructing tensorial relationships for the temperature and fluence dependent creep surfaces for Zr, Zircaloy 2, and Zircaloy 4.

  7. Pair Triplet Association Rule Generation in Streams

    Directory of Open Access Journals (Sweden)

    Manisha Thool

    2013-08-01

    Full Text Available Many applications involve the generation and analysis of a new kind of data, called stream data, where data flows in and out of an observation platform or window dynamically. Such data streams have the unique features such as huge or possibly infinite volume, dynamically changing, flowing in or out in a fixed order, allowing only one or a small number of scans. An important problem in data stream mining is that of finding frequent items in the stream. This problem finds application across several domains such as financial systems, web traffic monitoring, internet advertising, retail and e-business. This raises new issues that need to be considered when developing association rule mining technique for stream data. The Space-Saving algorithm reports both frequent and top-k elements with tight guarantees on errors. We also develop the notion of association rules in streams of elements. The Streaming-Rules algorithm is integrated with Space-Saving algorithm to report 1-1 association rules with tight guarantees on errors, using minimal space, and limited processing per element and we are using Apriori algorithm for static datasets and generation of association rules and implement Streaming-Rules algorithm for pair, triplet association rules. We compare the top- rules of static datasets with output of stream datasets and find percentage of error.

  8. Pattern Discovery Using Association Rules

    Directory of Open Access Journals (Sweden)

    Ms Kiruthika M,

    2011-12-01

    Full Text Available The explosive growth of Internet has given rise to many websites which maintain large amount of user information. To utilize this information, identifying usage pattern of users is very important. Web usage mining is one of the processes of finding out this usage pattern and has many practical applications. Our paper discusses how association rules can be used to discover patterns in web usage mining. Our discussion starts with preprocessing of the given weblog, followed by clustering them and finding association rules. These rules provide knowledge that helps to improve website design, in advertising, web personalization etc.

  9. Class Association Rule Pada Metode Associative Classification

    Directory of Open Access Journals (Sweden)

    Eka Karyawati

    2011-11-01

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

  10. Research on spatial association rules mining in two-direction

    Institute of Scientific and Technical Information of China (English)

    XUE Li-xia; WANG Zuo-cheng

    2007-01-01

    In data mining from transaction DB, the relationships between the attributes have been focused, but the relationships between the tuples have not been taken into account. In spatial database, there are relationships between the attributes and the tuples, and most of the associations occur between the tuples, such as adjacent, intersection, overlap and other topological relationships. So the tasks of spatial data association rules mining include mining the relationships between attributes of spatial objects, which are called as vertical direction DM, and the relationships between the tuples, which are called as horizontal direction DM. This paper analyzes the storage models of spatial data, uses for reference the technologies of data mining in transaction DB, defines the spatial data association rule, including vertical direction association rule, horizontal direction association rule and two-direction association rule, discusses the measurement of spatial association rule interestingness, and puts forward the work flows of spatial association rule data mining. During two-direction spatial association rules mining, an algorithm is proposed to get non-spatial itemsets. By virtue of spatial analysis, the spatial relations were transferred into non-spatial associations and the non-spatial itemsets were gotten. Based on the non-spatial itemsets, the Apriori algorithm or other algorithms could be used to get the frequent itemsets and then the spatial association rules come into being. Using spatial DB, the spatial association rules were gotten to validate the algorithm, and the test results show that this algorithm is efficient and can mine the interesting spatial rules.

  11. Controlling False Positives in Association Rule Mining

    CERN Document Server

    Liu, Guimei; Wong, Limsoon

    2011-01-01

    Association rule mining is an important problem in the data mining area. It enumerates and tests a large number of rules on a dataset and outputs rules that satisfy user-specified constraints. Due to the large number of rules being tested, rules that do not represent real systematic effect in the data can satisfy the given constraints purely by random chance. Hence association rule mining often suffers from a high risk of false positive errors. There is a lack of comprehensive study on controlling false positives in association rule mining. In this paper, we adopt three multiple testing correction approaches---the direct adjustment approach, the permutation-based approach and the holdout approach---to control false positives in association rule mining, and conduct extensive experiments to study their performance. Our results show that (1) Numerous spurious rules are generated if no correction is made. (2) The three approaches can control false positives effectively. Among the three approaches, the permutation...

  12. Associative Flow Rule Used to Include Hydrostatic Stress Effects in Analysis of Strain-Rate-Dependent Deformation of Polymer Matrix Composites

    Science.gov (United States)

    Goldberg, Robert K.; Roberts, Gary D.

    2004-01-01

    designing reliable composite engine cases that are lighter than the metal cases in current use. The types of polymer matrix composites that are likely to be used in such an application have a deformation response that is nonlinear and that varies with strain rate. The nonlinearity and the strain-rate dependence of the composite response are due primarily to the matrix constituent. Therefore, in developing material models to be used in the design of impact-resistant composite engine cases, the deformation of the polymer matrix must be correctly analyzed. However, unlike in metals, the nonlinear response of polymers depends on the hydrostatic stresses, which must be accounted for within an analytical model. By applying micromechanics techniques along with given fiber properties, one can also determine the effects of the hydrostatic stresses in the polymer on the overall composite deformation response. First efforts to account for the hydrostatic stress effects in the composite deformation applied purely empirical methods that relied on composite-level data. In later efforts, to allow polymer properties to be characterized solely on the basis of polymer data, researchers at the NASA Glenn Research Center developed equations to model the polymers that were based on a non-associative flow rule, and efforts to use these equations to simulate the deformation of representative polymer materials were reasonably successful. However, these equations were found to have difficulty in correctly analyzing the multiaxial stress states found in the polymer matrix constituent of a composite material. To correct these difficulties, and to allow for the accurate simulation of the nonlinear strain-rate-dependent deformation analysis of polymer matrix composites, in the efforts reported here Glenn researchers reformulated the polymer constitutive equations from basic principles using the concept of an associative flow rule. These revised equations were characterized and validated in an

  13. Image segmentation using association rule features.

    Science.gov (United States)

    Rushing, John A; Ranganath, Heggere; Hinke, Thomas H; Graves, Sara J

    2002-01-01

    A new type of texture feature based on association rules is described. Association rules have been used in applications such as market basket analysis to capture relationships present among items in large data sets. It is shown that association rules can be adapted to capture frequently occurring local structures in images. The frequency of occurrence of these structures can be used to characterize texture. Methods for segmentation of textured images based on association rule features are described. Simulation results using images consisting of man made and natural textures show that association rule features perform well compared to other widely used texture features. Association rule features are used to detect cumulus cloud fields in GOES satellite images and are found to achieve higher accuracy than other statistical texture features for this problem.

  14. Association Rules Applied to Intrusion Detection

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    We discuss the basic intrusion detection techniques, and focus on how to apply association rules to intrusion detection. Begin with analyzing some close relations between user's behaviors, we discuss the mining algorithm of association rules and apply to detect anomaly in IDS. Moreover, according to the characteristic of intrusion detection, we optimize the mining algorithm of association rules, and use fuzzy logic to improve the system performance.

  15. Sequential association rules in atonal music

    NARCIS (Netherlands)

    A. Honingh; T. Weyde; D. Conklin

    2009-01-01

    This paper describes a preliminary study on the structure of atonal music. In the same way as sequential association rules of chords can be found in tonal music, sequential association rules of pitch class set categories can be found in atonal music. It has been noted before that certain pitch class

  16. Sequential association rules in atonal music

    NARCIS (Netherlands)

    Honingh, A.; Weyde, T.; Conklin, D.

    2009-01-01

    This paper describes a preliminary study on the structure of atonal music. In the same way as sequential association rules of chords can be found in tonal music, sequential association rules of pitch class set categories can be found in atonal music. It has been noted before that certain pitch class

  17. Association Rule Discovery and Its Applications

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    Data mining, i.e. , mining knowledge from large amounts of data, is a demanding field since huge amounts of data have been collected in various applications. The collected data far exceed peoples ability to analyze it. Thus, some new and efficient methods are needed to discover knowledge from large database. Association rule discovery is an important problem in knowledge discovery and data mining.The association mining task consists of identifying the frequent item sets and then forming conditional implication rule among them. In this paper, we describe and summarize recent work on association rule discovery, offer a new method to association rule mining and point out that association rule discovery can be applied in spatial data mining. It is useful to discover knowledge from remote sensing and geographical information system.``

  18. a Reliability Evaluation System of Association Rules

    Science.gov (United States)

    Chen, Jiangping; Feng, Wanshu; Luo, Minghai

    2016-06-01

    In mining association rules, the evaluation of the rules is a highly important work because it directly affects the usability and applicability of the output results of mining. In this paper, the concept of reliability was imported into the association rule evaluation. The reliability of association rules was defined as the accordance degree that reflects the rules of the mining data set. Such degree contains three levels of measurement, namely, accuracy, completeness, and consistency of rules. To show its effectiveness, the "accuracy-completeness-consistency" reliability evaluation system was applied to two extremely different data sets, namely, a basket simulation data set and a multi-source lightning data fusion. Results show that the reliability evaluation system works well in both simulation data set and the actual problem. The three-dimensional reliability evaluation can effectively detect the useless rules to be screened out and add the missing rules thereby improving the reliability of mining results. Furthermore, the proposed reliability evaluation system is applicable to many research fields; using the system in the analysis can facilitate obtainment of more accurate, complete, and consistent association rules.

  19. Association Rule Mining and Its Application

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    Several algorithms in data mining technique have been studied recently, among which association is one of the most important techniques. In this paper, we introduce theory of association rule in data mining, and analyze the characteristics of postal EMS service. We create a data warehouse model for EMS services and give the procedure of applying association rule mining based on it. In the end, we give an example of the whole mining procedure. This EMS-Data warehouse model and association rule mining technique have been applied in a practical Postal CRM System.

  20. Clustering Association Rules with Fuzzy Concepts

    Science.gov (United States)

    Steinbrecher, Matthias; Kruse, Rudolf

    Association rules constitute a widely accepted technique to identify frequent patterns inside huge volumes of data. Practitioners prefer the straightforward interpretability of rules, however, depending on the nature of the underlying data the number of induced rules can be intractable large. Even reasonably sized result sets may contain a large amount of rules that are uninteresting to the user because they are too general, are already known or do not match other user-related intuitive criteria. We allow the user to model his conception of interestingness by means of linguistic expressions on rule evaluation measures and compound propositions of higher order (i.e., temporal changes of rule properties). Multiple such linguistic concepts can be considered a set of fuzzy patterns (Fuzzy Sets and Systems 28(3):313-331, 1988) and allow for the partition of the initial rule set into fuzzy fragments that contain rules of similar membership to a user’s concept (Höppner et al., Fuzzy Clustering, Wiley, Chichester, 1999; Computational Statistics and Data Analysis 51(1):192-214, 2006; Advances in Fuzzy Clustering and Its Applications, chap. 1, pp. 3-30, Wiley, New York, 2007). With appropriate visualization methods that extent previous rule set visualizations (Foundations of Fuzzy Logic and Soft Computing, Lecture Notes in Computer Science, vol. 4529, pp. 295-303, Springer, Berlin, 2007) we allow the user to instantly assess the matching of his concepts against the rule set.

  1. Effective Discovery of Exception Class Association Rules

    Institute of Scientific and Technical Information of China (English)

    周傲英; 魏藜; 俞舫

    2002-01-01

    In this paper, a new effective method is proposed to find class association rules (CAR), to get useful class association rules (UCAR) by removing the spurious class association rules (SCAR), and to generate exception class association rules (ECAR) for each UCAR. CAR mining, which integrates the techniques of classification and association, is of great interest recently. However, it has two drawbacks: one is that a large part of CARs are spurious and maybe misleading to users; the other is that some important ECARs are difficult to find using traditional data mining techniques. The method introduced in this paper aims to get over these flaws. According to our approach, a user can retrieve correct information from UCARs and know the influence from different conditions by checking corresponding ECARs. Experimental results demonstrate the effectiveness of our proposed approach.

  2. On construction of partial association rules

    KAUST Repository

    Moshkov, Mikhail

    2009-01-01

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

  3. Efficient Mining of Intertransaction Association Rules

    NARCIS (Netherlands)

    Tung, A.K.H.; Lu, H.J.; Han, J.W.; Feng, L.

    2003-01-01

    Most of the previous studies on mining association rules are on mining intratransaction associations, i.e., the associations among items within the same transaction where the notion of the transaction could be the items bought by the same customer, the events happened on the same day, etc. In this s

  4. A Collaborative Educational Association Rule Mining Tool

    Science.gov (United States)

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

    2011-01-01

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

  5. Discovering Non-Redundant Association Rules using MinMax Approximation Rules

    OpenAIRE

    R. Vijaya Prakash; Dr. A. Govardhan3; Prof. SSVN. Sarma

    2012-01-01

    Frequent pattern mining is an important area of data mining used to generate the Association Rules. The extracted Frequent Patterns quality is a big concern, as it generates huge sets of rules and many of them are redundant. Mining Non-Redundant Frequent patterns is a big concern in the area of Association rule mining. In this paper we proposed a method to eliminate the redundant Frequent patterns using MinMax rule approach, to generate the quality Association Rules.

  6. Exploring Consumer Behavior: Use of Association Rules

    Directory of Open Access Journals (Sweden)

    Pavel Turčínek

    2015-01-01

    Full Text Available This paper focuses on problematic of use of association rules in exploring consumer behavior and presents selected results of applied data analyses on data collected via questionnaire survey on a sample of 1127 Czech respondents with structure close to representative sample of population the Czech Republic. The questionnaire survey deals with problematic of shopping for meat products. The objective was to explore possibilities of less frequently used data-mining techniques in processing of customer preference. For the data analyses, two methods for generating association rules are used: Apriori algorithm and FP-grow algorithm. Both of them were executed in Weka software. The Apriori algorithm seemed to be a better tool, because it has provided finer data, due to the fact that FP-growth algorithm needed reduction of preference scale to only two extreme values, because the input data must be binary. For consumer preferences we also calculated their means. This paper explores the different preferences and expectations of what customers’ favorite outlet should provide, and offer. Customers based on the type of their outlet loyalty were divided into five segments and further explored in more detail. Some of the found best association rules suggest similar patterns across the whole sample, e.g. the results suggest that the respondents for whom a quality of merchandise is a very important factor typically also base their outlet selection on freshness of products. This finding applies to all types of retail loyalty categores. Other rules seem to indicate a behavior more specific for a particular segment of customers. The results suggest that application of association rules in customer research can provide more insight and can be a good supplementary analysis for consumer data exploration when Likert scales were used.

  7. Mining association rule efficiently based on data warehouse

    Institute of Scientific and Technical Information of China (English)

    陈晓红; 赖邦传; 罗铤

    2003-01-01

    The conventional complete association rule set was replaced by the least association rule set in data warehouse association rule mining process. The least association rule set should comply with two requirements: 1) it should be the minimal and the simplest association rule set; 2) its predictive power should in no way be weaker than that of the complete association rule set so that the precision of the association rule set analysis can be guaranteed.By adopting the least association rule set, the pruning of weak rules can be effectively carried out so as to greatly reduce the number of frequent itemset, and therefore improve the mining efficiency. Finally, based on the classical Apriori algorithm, the upward closure property of weak rules is utilized to develop a corresponding efficient algorithm.

  8. Apriori Association Rule Algorithms using VMware Environment

    Directory of Open Access Journals (Sweden)

    R. Sumithra

    2014-07-01

    Full Text Available The aim of this study is to carry out a research in distributed data mining using cloud platform. Distributed Data mining becomes a vital component of big data analytics due to the development of network and distributed technology. Map-reduce hadoop framework is a very familiar concept in big data analytics. Association rule algorithm is one of the popular data mining techniques which finds the relationships between different transactions. A work has been executed using weighted apriori and hash T apriori algorithms for association rule mining on a map reduce hadoop framework using a retail data set of transactions. This study describes the above concepts, explains the experiment carried out with retail data set on a VMW are environment and compares the performances of weighted apriori and hash-T apriori algorithms in terms of memory and time.

  9. A Fast Algorithm for Mining Association Rules

    Institute of Scientific and Technical Information of China (English)

    黄刘生; 陈华平; 王洵; 陈国良

    2000-01-01

    In this paper, the problem of discovering association rules between items in a large database of sales transactions is discussed, and a novel algorithm,BitMatrix, is proposed. The proposed algorithm is fundamentally different from the known algorithms Apriori and AprioriTid. Empirical evaluation shows that the algorithm outperforms the known ones for large databases. Scale-up experiments show that the algorithm scales linearly with the number of transactions.

  10. Association Rule Pruning based on Interestingness Measures with Clustering

    Directory of Open Access Journals (Sweden)

    R. Bhaskaran

    2009-11-01

    Full Text Available Association rule mining plays vital part in knowledge mining. The difficult task is discovering knowledge or useful rules from the large number of rules generated for reduced support. For pruning or grouping rules, several techniques are used such as rule structure cover methods, informative cover methods, rule clustering, etc. Another way of selecting association rules is based on interestingness measures such as support, confidence, correlation, and so on. In this paper, we study how rule clusters of the pattern Xi -> Y are distributed over different interestingness measures.

  11. Dynamic Programming Approach for Construction of Association Rule Systems

    KAUST Repository

    Alsolami, Fawaz

    2016-11-18

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

  12. Integrated Association Rules Complete Hiding Algorithms

    Directory of Open Access Journals (Sweden)

    Mohamed Refaat Abdellah

    2017-01-01

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

  13. Target-Based Maintenance of Privacy Preserving Association Rules

    Science.gov (United States)

    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…

  14. Mining Hesitation Information by Vague Association Rules

    Science.gov (United States)

    Lu, An; Ng, Wilfred

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

  15. An Association Rule Mining Algorithm Based on a Boolean Matrix

    Directory of Open Access Journals (Sweden)

    Hanbing Liu

    2007-09-01

    Full Text Available Association rule mining is a very important research topic in the field of data mining. Discovering frequent itemsets is the key process in association rule mining. Traditional association rule algorithms adopt an iterative method to discovery, which requires very large calculations and a complicated transaction process. Because of this, a new association rule algorithm called ABBM is proposed in this paper. This new algorithm adopts a Boolean vector "relational calculus" method to discovering frequent itemsets. Experimental results show that this algorithm can quickly discover frequent itemsets and effectively mine potential association rules.

  16. Greedy algorithms withweights for construction of partial association rules

    KAUST Repository

    Moshkov, Mikhail

    2009-09-10

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

  17. Mining Association Rules in Students Assessment Data

    Directory of Open Access Journals (Sweden)

    Anupama Chadha

    2012-09-01

    Full Text Available Higher education, throughout the world is delivered through universities, colleges affiliated to various universities and some other recognized academic institutes. Today one of the biggest challenges, the educational institutions face, is the explosive growth of educational data and to use this data to improve the quality of managerial decisions to deliver quality education. In this paper we will perform a case study of a university that hopes to improve the quality of education by analyzing the data and discover the factors that affect the academic results so as to increase success chances of students. In this perspective we use association rules discovery techniques. Also we will show the importance of data preprocessing in data analysis which has a significant impact on the accuracy of the predicted results.

  18. Association Rule Mining for Web Recommendation

    Directory of Open Access Journals (Sweden)

    R. Suguna

    2012-10-01

    Full Text Available Web usage mining is the application of web mining to discover the useful patterns from the web in order to understand and analyze the behavior of the web users and web based applications. It is theemerging research trend for today’s researchers. It entirely deals with web log files which contain the user website access information. It is an interesting thing to analyze and understand the user behaviorabout the web access. Web usage mining normally has three categories: 1. Preprocessing, 2. Pattern Discovery and 3. Pattern Analysis. This paper proposes the association rule mining algorithms for betterWeb Recommendation and Web Personalization. Web recommendation systems are considered as an important role to understand customers’ behavior, interest, improving customer convenience, increasingservice provider profits and future needs.

  19. Efficient mining of association rules based on gravitational search algorithm

    Directory of Open Access Journals (Sweden)

    Fariba Khademolghorani

    2011-07-01

    Full Text Available Association rules mining are one of the most used tools to discover relationships among attributes in a database. A lot of algorithms have been introduced for discovering these rules. These algorithms have to mine association rules in two stages separately. Most of them mine occurrence rules which are easily predictable by the users. Therefore, this paper discusses the application of gravitational search algorithm for discovering interesting association rules. This evolutionary algorithm is based on the Newtonian gravity and the laws of motion. Furthermore, contrary to the previous methods, the proposed method in this study is able to mine the best association rules without generating frequent itemsets and is independent of the minimum support and confidence values. The results of applying this method in comparison with the method of mining association rules based upon the particle swarm optimization show that our method is successful.

  20. Compact Weighted Class Association Rule Mining using Information Gain

    CERN Document Server

    Ibrahim, S P Syed

    2011-01-01

    Weighted association rule mining reflects semantic significance of item by considering its weight. Classification constructs the classifier and predicts the new data instance. This paper proposes compact weighted class association rule mining method, which applies weighted association rule mining in the classification and constructs an efficient weighted associative classifier. This proposed associative classification algorithm chooses one non class informative attribute from dataset and all the weighted class association rules are generated based on that attribute. The weight of the item is considered as one of the parameter in generating the weighted class association rules. This proposed algorithm calculates the weight using the HITS model. Experimental results show that the proposed system generates less number of high quality rules which improves the classification accuracy.

  1. AN ALGORITHM FOR GENERATING SINGLE DIMENSIONAL FUZZY ASSOCIATION RULE MINING

    Directory of Open Access Journals (Sweden)

    Rolly Intan

    2006-01-01

    Full Text Available Association rule mining searches for interesting relationship among items in a large data set. Market basket analysis, a typical example of association rule mining, analyzes buying habit of customers by finding association between the different items that customers put in their shopping cart (basket. Apriori algorithm is an influential algorithm for mining frequent itemset for generating association rules. For some reasons, Apriori algorithm is not based on human intuitive. To provide a more human-based concept, this paper proposes an alternative algorithm for generating the association rule by utilizing fuzzy sets in the market basket analysis.

  2. A Novel Texture Classification Procedure by using Association Rules

    Directory of Open Access Journals (Sweden)

    L. Jaba Sheela

    2008-11-01

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

  3. Time-Saving Approach for Optimal Mining of Association Rules

    Directory of Open Access Journals (Sweden)

    Mouhir Mohammed

    2016-10-01

    Full Text Available Data mining is the process of analyzing data so as to get useful information to be exploited by users. Association rules is one of data mining techniques used to detect different correlations and to reveal relationships among data individual items in huge data bases. These rules usually take the following form: if X then Y as independent attributes. An association rule has become a popular technique used in several vital fields of activity such as insurance, medicine, banks, supermarkets… Association rules are generated in huge numbers by algorithms known as Association Rules Mining algorithms. The generation of huge quantities of Association Rules may be time-and-effort consuming this is the reason behind an urgent necessity of an efficient and scaling approach to mine only the relevant and significant association rules. This paper proposes an innovative approach which mines the optimal rules from a large set of Association Rules in a distributive processing way to improve its efficiency and to decrease the running time.

  4. Discovery of Association Rules from University Admission System Data

    Directory of Open Access Journals (Sweden)

    Abdul Fattah Mashat

    2013-05-01

    Full Text Available Association rules discovery is one of the vital data mining techniques. Currently there is an increasing interest in data mining and educational systems, making educational data mining (EDM as a new growing research community. In this paper, we present a model for association rules discovery from King Abdulaziz University (KAU admission system data. The main objective is to extract the rules and relations between admission system attributes for better analysis. The model utilizes an apriori algorithm for association rule mining. Detailed analysis and interpretation of the experimental results is presented with respect to admission office perspective.

  5. Finding Exception For Association Rules Via SQL Queries

    Directory of Open Access Journals (Sweden)

    Luminita DUMITRIU

    2000-12-01

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

  6. Towards an incremental maintenance of cyclic association rules

    CERN Document Server

    Ahmed, Eya ben

    2010-01-01

    Recently, the cyclic association rules have been introduced in order to discover rules from items characterized by their regular variation over time. In real life situations, temporal databases are often appended or updated. Rescanning the whole database every time is highly expensive while existing incremental mining techniques can efficiently solve such a problem. In this paper, we propose an incremental algorithm for cyclic association rules maintenance. The carried out experiments of our proposal stress on its efficiency and performance.

  7. Detection of Attacks on MAODV Association Rule Mining Optimization

    Directory of Open Access Journals (Sweden)

    A. Fidalcastro

    2015-02-01

    Full Text Available Current mining algorithms can generate large number of rules and very slow to generate rules or generate few results, omitting interesting and valuable information. To address this problem, we propose an algorithm Optimized Featured Top Association Rules (OFTAR algorithm, where every attack have many features and some of the features are more important. The Features are selected by genetic algorithm and processed by the OFTAR algorithm to find the optimized rules. The algorithm utilizes Genetic Algorithm feature selection approach to find optimized features. OFTAR incorporate association rules with several rule optimization techniques and expansion techniques to improve efficiency. Increasing popularity of Mobile ad hoc network users of wireless networks lead to threats and attacks on MANET, due to its features. The main challenge in designing a MANET is protecting from various attacks in the network. Intrusion Detection System is required to monitor the network and to detect the malicious node in the network in multi casting mobility environment. The node features are processed in Association Analysis to generate rules, the generated rules are applied to nodes to detect the attacks. Experimental results show that the algorithm has higher scalability and good performance that is an advantageous to several association rule mining algorithms when the rule generation is controlled and optimized to detect the attacks.

  8. An Optimized Weighted Association Rule Mining On Dynamic Content

    CERN Document Server

    Velvadivu, P

    2010-01-01

    Association rule mining aims to explore large transaction databases for association rules. Classical Association Rule Mining (ARM) model assumes that all items have the same significance without taking their weight into account. It also ignores the difference between the transactions and importance of each and every itemsets. But, the Weighted Association Rule Mining (WARM) does not work on databases with only binary attributes. It makes use of the importance of each itemset and transaction. WARM requires each item to be given weight to reflect their importance to the user. The weights may correspond to special promotions on some products, or the profitability of different items. This research work first focused on a weight assignment based on a directed graph where nodes denote items and links represent association rules. A generalized version of HITS is applied to the graph to rank the items, where all nodes and links are allowed to have weights. This research then uses enhanced HITS algorithm by developing...

  9. a Research on Spatial Topological Association Rules Mining

    Science.gov (United States)

    Chen, J.; Liu, S.; Zhang, P.; Sha, Z.

    2012-07-01

    Spatial association rules mining is a process of acquiring information and knowledge from large databases. Due to the nature of geographic space and the complexity of spatial objects and relations, the classical association rule mining methods are not suitable for the spatial association rule mining. Classical association rule mining treats all input data as independent, while spatial association rules often show high autocorrelation among nearby objects. The contiguous, adjacent and neighboring relations between spatial objects are important topological relations. In this paper a new approach based on topological predictions to discover spatial association rules is presented. First, we develop a fast method to get the topological relationship of spatial data with its algebraic structure. Then the interested spatial objects are selected. To find the interested spatial objects, topological relations combining with distance were used. In this step, the frequent topological predications are gained. Next, the attribute datasets of the selected interested spatial objects are mined with Apriori algorithm. Last, get the spatial topological association rules. The presented approach has been implemented and tested by the data of GDP per capita, railroads and roads in China in the year of 2005 at county level. The results of the experiments show that the approach is effective and valid.

  10. An Object Extraction Model Using Association Rules and Dependence Analysis

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    Extracting objects from legacy systems is a basic step insystem's obje ct-orientation to improve the maintainability and understandability of the syst e ms. A new object extraction model using association rules an d dependence analysis is proposed. In this model data are classified by associat ion rules and the corresponding operations are partitioned by dependence analysis.

  11. Mining multilevel spatial association rules with cloud models

    Institute of Scientific and Technical Information of China (English)

    YANG Bin; ZHU Zhong-ying

    2005-01-01

    The traditional generalization-based knowledge discovery method is introduced. A new kind of multilevel spatial association of the rules mining method based on the cloud model is presented. The cloud model integrates the vague and random use of linguistic terms in a unified way. With these models, spatial and nonspatial attribute values are well generalized at multiple levels, allowing discovery of strong spatial association rules.Combining the cloud model based method with Apriori algorithms for mining association rules from a spatial database shows benefits in being effective and flexible.

  12. Holographic RG flows, entanglement entropy and the sum rule

    CERN Document Server

    Casini, Horacio; Torroba, Gonzalo

    2015-01-01

    We calculate the two-point function of the trace of the stress tensor in holographic renormalization group flows between pairs of conformal field theories. We show that the term proportional to the momentum squared in this correlator gives the change of the central charge between fixed points in d=2 and in d>2 it gives the holographic entanglement entropy for a planar region. This can also be seen as a holographic realization of the Adler-Zee formula for the renormalization of Newton's constant. Holographic regularization is found to provide a perfect match of the finite and divergent terms of the sum rule, and it is analogous to the regularization of the entropy in terms of mutual information. Finally, we provide a general proof of reflection positivity in terms of stability of the dual bulk action, and discuss the relation between unitarity constraints, the null energy condition and regularity in the interior of the gravity solution.

  13. Optimizing Mining Association Rules for Artificial Immune System based Classification

    Directory of Open Access Journals (Sweden)

    SAMEER DIXIT

    2011-08-01

    Full Text Available The primary function of a biological immune system is to protect the body from foreign molecules known as antigens. It has great pattern recognition capability that may be used to distinguish between foreigncells entering the body (non-self or antigen and the body cells (self. Immune systems have many characteristics such as uniqueness, autonomous, recognition of foreigners, distributed detection, and noise tolerance . Inspired by biological immune systems, Artificial Immune Systems have emerged during the last decade. They are incited by many researchers to design and build immune-based models for a variety of application domains. Artificial immune systems can be defined as a computational paradigm that is inspired by theoretical immunology, observed immune functions, principles and mechanisms. Association rule mining is one of the most important and well researched techniques of data mining. The goal of association rules is to extract interesting correlations, frequent patterns, associations or casual structures among sets of items in thetransaction databases or other data repositories. Association rules are widely used in various areas such as inventory control, telecommunication networks, intelligent decision making, market analysis and risk management etc. Apriori is the most widely used algorithm for mining the association rules. Other popular association rule mining algorithms are frequent pattern (FP growth, Eclat, dynamic itemset counting (DIC etc. Associative classification uses association rule mining in the rule discovery process to predict the class labels of the data. This technique has shown great promise over many other classification techniques. Associative classification also integrates the process of rule discovery and classification to build the classifier for the purpose of prediction. The main problem with the associative classification approach is the discovery of highquality association rules in a very large space of

  14. A new incremental updating algorithm for association rules

    Institute of Scientific and Technical Information of China (English)

    WANG Zuo-cheng; XUE Li-xia

    2007-01-01

    Incremental data mining is an attractive goal for many kinds of mining in large databases or data warehouses. A new incremental updating algorithm rule growing algorithm (RGA) is presented for efficient maintenance discovered association rules when new transaction data is added to a transaction database. The algorithm RGA makes use of previous association rules as seed rules. By RGA, the seed rules whether are strong or not can be confirmed without scanning all the transaction DB in most cases. If the distributing of item of transaction DB is not uniform, the inflexion of robustness curve comes very quickly, and RGA gets great efficiency, saving lots of time for I/O. Experiments validate the algorithm and the test results showed that this algorithm is efficient.

  15. An Algorithm for Mining Multidimensional Fuzzy Association Rules

    CERN Document Server

    Khare, Neelu; Pardasani, K R

    2009-01-01

    Multidimensional association rule mining searches for interesting relationship among the values from different dimensions or attributes in a relational database. In this method the correlation is among set of dimensions i.e., the items forming a rule come from different dimensions. Therefore each dimension should be partitioned at the fuzzy set level. This paper proposes a new algorithm for generating multidimensional association rules by utilizing fuzzy sets. A database consisting of fuzzy transactions, the Apriory property is employed to prune the useless candidates, itemsets.

  16. Classification approach based on association rules mining for unbalanced data

    CERN Document Server

    Ndour, Cheikh

    2012-01-01

    This paper deals with the supervised classification when the response variable is binary and its class distribution is unbalanced. In such situation, it is not possible to build a powerful classifier by using standard methods such as logistic regression, classification tree, discriminant analysis, etc. To overcome this short-coming of these methods that provide classifiers with low sensibility, we tackled the classification problem here through an approach based on the association rules learning because this approach has the advantage of allowing the identification of the patterns that are well correlated with the target class. Association rules learning is a well known method in the area of data-mining. It is used when dealing with large database for unsupervised discovery of local patterns that expresses hidden relationships between variables. In considering association rules from a supervised learning point of view, a relevant set of weak classifiers is obtained from which one derives a classification rule...

  17. Discovering market basket patterns using hierarchical association rules

    Directory of Open Access Journals (Sweden)

    Marijana Zekić-Sušac

    2015-10-01

    Full Text Available Association rules are a data mining method for discovering patterns of frequent item sets, such as products in a store that are frequently purchased at the same time by a customer (market basket analysis. A number of interestingness measures for association rules have been developed to date, but research has shown that there a dominant measure does not exist. Authors have mostly used objective measures, whereas subjective measures have rarely been investigated. This paper aims to combine objective measures such as support, confidence and lift with a subjective approach based on human expert selection in order to extract interesting rules from a real dataset collected from a large Croatian retail chain. Hierarchical association rules were used to enhance the efficiency of the extraction rule. The results show that rules that are more interesting were extracted using the hierarchical method, and that a hybrid approach of combining objective and subjective measures succeeds in extracting certain unexpected and actionable rules. The research can be useful for retail and marketing managers in planning marketing strategies, as well as for researchers investigating this field.

  18. MAROR: Multi-Level Abstraction of Association Rule Using Ontology and Rule Schema

    Directory of Open Access Journals (Sweden)

    Salim Khiat

    2014-11-01

    Full Text Available Many large organizations have multiple databases distributed over different branches. Number of such organizations is increasing over time. Thus, it is necessary to study data mining on multiple databases. Most multi-databases mining (MDBM algorithms for association rules typically represent input patterns at a single level of abstraction. However, in many applications of association rules – e.g., Industrial discovery, users often need to explore a data set at multiple levels of abstraction, and from different points of view. Each point of view corresponds to set of beliefs (and representational commitments regarding the domain of interest. Using domain ontologies, we strengthen the integration of user knowledge in the mining and post-processing task. Furthermore, an interactive and iterative framework is designed to assist the user along the analyzing task at different levels. This paper formalizes the problem of association rules using ontologies in multi-database mining, describes an ontology-driven association rules algorithm to discoverer rules at multiple levels of abstraction and presents preliminary results in petroleum field to demonstrate the feasibility and applicability of this proposed approach.

  19. Closed-set-based Discovery of Representative Association Rules Revisited

    CERN Document Server

    Balcázar, José L

    2010-01-01

    The output of an association rule miner is often huge in practice. This is why several concise lossless representations have been proposed, such as the "essential" or "representative" rules. We revisit the algorithm given by Kryszkiewicz (Int. Symp. Intelligent Data Analysis 2001, Springer-Verlag LNCS 2189, 350-359) for mining representative rules. We show that its output is sometimes incomplete, due to an oversight in its mathematical validation, and we propose an alternative complete generator that works within only slightly larger running times.

  20. Associative Regressive Decision Rule Mining for Predicting Customer Satisfactory Patterns

    Directory of Open Access Journals (Sweden)

    P. Suresh

    2016-04-01

    Full Text Available Opinion mining also known as sentiment analysis, involves cust omer satisfactory patterns, sentiments and attitudes toward entities, products, service s and their attributes. With the rapid development in the field of Internet, potential customer’s provi des a satisfactory level of product/service reviews. The high volume of customer rev iews were developed for product/review through taxonomy-aware processing but, it was di fficult to identify the best reviews. In this paper, an Associative Regression Decisio n Rule Mining (ARDRM technique is developed to predict the pattern for service provider and to improve customer satisfaction based on the review comments. Associative Regression based Decisi on Rule Mining performs two- steps for improving the customer satisfactory level. Initial ly, the Machine Learning Bayes Sentiment Classifier (MLBSC is used to classify the cla ss labels for each service reviews. After that, Regressive factor of the opinion words and Class labels w ere checked for Association between the words by using various probabilistic rules. Based on t he probabilistic rules, the opinion and sentiments effect on customer reviews, are analyzed to arrive at specific set of service preferred by the customers with their review com ments. The Associative Regressive Decision Rule helps the service provider to take decision on imp roving the customer satisfactory level. The experimental results reveal that the Associ ative Regression Decision Rule Mining (ARDRM technique improved the performance in terms of true positive rate, Associative Regression factor, Regressive Decision Rule Generation time a nd Review Detection Accuracy of similar pattern.

  1. A Survey of Association Rule Mining Using Genetic Algorithm

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    Anubha Sharma

    2012-08-01

    Full Text Available Data mining is the analysis step of the "Knowledge Discovery in Databases" process, or KDD. It is the process that results in the discovery of new patterns in large data sets. It utilizes methods at the intersection of artificial intelligence, machine learning, statistics, and database systems. The overall goal of the data mining process is to extract knowledge from an existing data set and transform it into a human-understandable structure. In data mining, association rule learning is a popular and well researched method for discovering interesting relations between variables in large databases. Association rules are usually required to satisfy a user-specified minimum support and a user-specified minimum confidence at the same time. Genetic algorithm (GA is a search heuristic that mimics the process of natural evolution. This heuristic is routinely used to generate useful solutions to optimization and search problems. Genetic algorithms belong to the larger class of evolutionary algorithms, which generate solutions to optimization problems using techniques inspired by natural evolution, such as inheritance, mutation, selection, and crossover. In previous, many researchers have proposed Genetic Algorithms for mining interesting association rules from quantitative data. In this paper we represent a survey of Association Rule Mining Using Genetic Algorithm. The techniques are categorized based upon different approaches. This paper provides the major advancement in the approaches for association rule mining using genetic algorithms.

  2. A Novel Approach for Association Rule Mining using Pattern Generation

    Directory of Open Access Journals (Sweden)

    Deepa S. Deshpande

    2014-10-01

    Full Text Available Data mining has become a process of significant interest in recent years due to explosive rate of the accumulation of data. It is used to discover potentially valuable implicit knowledge from the large transactional databases. Association rule mining is one of the well known techniques of data mining. It typically aims at discovering associations between attributes in the large databases. The first and the most influential traditional algorithm for association rule discovery is Apriori. Multiple scans of database, generation of large number of candidates item set and discovery of interesting rules are the main challenging issues for the improvement of Apriori algorithm. Therefore in order to decrease the multiple scanning of database, a new method of association rule mining using pattern generation is proposed in this paper. This method involves three steps. First, patterns are generated using items from the transaction database. Second, frequent item set is obtained using these patterns. Finally association rules are derived. The performance of this method is evaluated with the traditional Apriori algorithm. It shows that behavior of the proposed method is much more similar to Apriori algorithm with less memory space and reduction in multiple times scanning of database. Thus it is more efficient than the traditional Apriori algorithm.

  3. Parallel mining and application of fuzzy association rules

    Institute of Scientific and Technical Information of China (English)

    LU Jian-jiang; XU Bao-wen; ZOU Xiao-feng; KANG Da-zhou; LI Yan-hui; ZHOU Jin

    2006-01-01

    Quantitative attributes are partitioned into several fuzzy sets by using fuzzy c-means algorithm.Fuzzy c-means algorithm can embody the actual distribution of the data,and fuzzy sets can soften the partition boundary.Then,we improve the search technology of apriori algorithm and present the algorithm for mining fuzzy association rules.As the database size becomes larger and larger,a better way is to mine fuzzy association rules in parallel.In the parallel mining algorithm,quantitative attributes are partitioned into several fuzzy sets by using parallel fuzzy c-means algorithm.Boolean parallel algorithm is improved to discover frequent fuzzy attribute set,and the fuzzy association rules with at least a minimum confidence are generated on all processors.The experiment results implemented on the distributed linked PC/workstation show that the parallel mining algorithm has fine scaleup,sizeup and speedup.Last,we discuss the application of fuzzy association rules in the classification.The example shows that the accuracy of classification systems of the fuzzy association rules is better than that of the two popular classification methods:C4.5 and CBA.

  4. Plastic flow rule for sands with friction, dilation, density and stress state coupling

    Directory of Open Access Journals (Sweden)

    Wojciechowski Marek

    2015-06-01

    Full Text Available In this paper we propose a flow rule and failure criterion for sands in plane strain conditions based on Drucker-Prager formulation and enhanced with empirical Houlsby formula, which couples friction, dilation, density and stress state in the material. The resulting elasto-plastic, non-associated, shear hardening material model is implemented as a numerical procedure in the frame of finite element method and a simple compression example is presented. Because of the empirical nature of Houlsby formula, it is believed that results of numerical simulations will be more realistic both in deformation and shear strength estimation of sands.

  5. Database Reverse Engineering based on Association Rule Mining

    Directory of Open Access Journals (Sweden)

    Nattapon Pannurat

    2010-03-01

    Full Text Available Maintaining a legacy database is a difficult task especially when system documentation is poor written or even missing. Database reverse engineering is an attempt to recover high-level conceptual design from the existing database instances. In this paper, we propose a technique to discover conceptual schema using the association mining technique. The discovered schema corresponds to the normalization at the third normal form, which is a common practice in many business organizations. Our algorithm also includes the rule filtering heuristic to solve the problem of exponential growth of discovered rules inherited with the association mining technique.

  6. Parametric Rough Sets with Application to Granular Association Rule Mining

    Directory of Open Access Journals (Sweden)

    Xu He

    2013-01-01

    Full Text Available Granular association rules reveal patterns hidden in many-to-many relationships which are common in relational databases. In recommender systems, these rules are appropriate for cold-start recommendation, where a customer or a product has just entered the system. An example of such rules might be “40% men like at least 30% kinds of alcohol; 45% customers are men and 6% products are alcohol.” Mining such rules is a challenging problem due to pattern explosion. In this paper, we build a new type of parametric rough sets on two universes and propose an efficient rule mining algorithm based on the new model. Specifically, the model is deliberately defined such that the parameter corresponds to one threshold of rules. The algorithm benefits from the lower approximation operator in the new model. Experiments on two real-world data sets show that the new algorithm is significantly faster than an existing algorithm, and the performance of recommender systems is stable.

  7. Optimising synaptic learning rules in linear associative memories.

    Science.gov (United States)

    Dayan, P; Willshaw, D J

    1991-01-01

    Associative matrix memories with real-valued synapses have been studied in many incarnations. We consider how the signal/noise ratio for associations depends on the form of the learning rule, and we show that a covariance rule is optimal. Two other rules, which have been suggested in the neurobiology literature, are asymptotically optimal in the limit of sparse coding. The results appear to contradict a line of reasoning particularly prevalent in the physics community. It turns out that the apparent conflict is due to the adoption of different underlying models. Ironically, they perform identically at their co-incident optima. We give details of the mathematical results, and discuss some other possible derivations and definitions of the signal/noise ratio.

  8. Penguins Search Optimisation Algorithm for Association Rules Mining

    Directory of Open Access Journals (Sweden)

    Youcef Gheraibia

    2016-06-01

    Full Text Available Association Rules Mining (ARM is one of the most popular and well-known approaches for the decision-making process. All existing ARM algorithms are time consuming and generate a very large number of association rules with high overlapping. To deal with this issue, we propose a new ARM approach based on penguins search optimization algorithm (Pe-ARM for short. Moreover, an efficient measure is incorporated into the main process to evaluate the amount of overlapping among the generated rules. The proposed approach also ensures a good diversification over the whole solutions space. To demonstrate the effectiveness of the proposed approach, several experiments have been carried out on different datasets and specifically on the biological ones. The results reveal that the proposed approach outperforms the well-known ARM algorithms in both execution time and solution quality.

  9. Rough Set Model for Discovering Hybrid Association Rules

    CERN Document Server

    Pandey, Anjana

    2009-01-01

    In this paper, the mining of hybrid association rules with rough set approach is investigated as the algorithm RSHAR.The RSHAR algorithm is constituted of two steps mainly. At first, to join the participant tables into a general table to generate the rules which is expressing the relationship between two or more domains that belong to several different tables in a database. Then we apply the mapping code on selected dimension, which can be added directly into the information system as one certain attribute. To find the association rules, frequent itemsets are generated in second step where candidate itemsets are generated through equivalence classes and also transforming the mapping code in to real dimensions. The searching method for candidate itemset is similar to apriori algorithm. The analysis of the performance of algorithm has been carried out.

  10. Mining Frequent Generalized Itemsets and Generalized Association Rules Without Redundancy

    Institute of Scientific and Technical Information of China (English)

    Daniel Kunkle; Donghui Zhang; Gene Cooperman

    2008-01-01

    This paper presents some new algorithms to efficiently mine max frequent generalized itemsets (g-itemsets) and essential generalized association rules (g-rules). These are compact and general representations for all frequent patterns and all strong association rules in the generalized environment. Our results fill an important gap among algorithms for frequent patterns and association rules by combining two concepts. First, generalized itemsets employ a taxonomy of items, rather than a fiat list of items. This produces more natural frequent itemsets and associations such as (meat, milk) instead of (beef, milk), (chicken, milk), etc. Second, compact representations of frequent itemsets and strong rules, whose result size is exponentially smaller, can solve a standard dilemma in mining patterns: with small threshold values for support and confidence, the user is overwhelmed by the extraordinary number of identified patterns and associations; but with large threshold values, some interesting patterns and associations fail to be identified. Our algorithms can also expand those max frequent g-itemsets and essential g-rules into the much larger set of ordinary frequent g-itemsets and strong g-rules. While that expansion is not recommended in most practical cases, we do so in order to present a comparison with existing algorithms that only handle ordinary frequent g-itemsets. In this case, the new algorithm is shown to be thousands, and in some cases millions, of the time faster than previous algorithms. Further, the new algorithm succeeds in analyzing deeper taxonomies, with the depths of seven or more. Experimental results for previous algorithms limited themselves to taxonomies with depth at most three or four. In each of the two problems, a straightforward lattice-based approach is briefly discussed and then a classificationbased algorithm is developed. In particular, the two classification-based algorithms are MFGI_class for mining max frequent g-itemsets and EGR

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

    Directory of Open Access Journals (Sweden)

    Nisha Mariam Varughese

    2014-07-01

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

  12. Konstruksi Bayesian Network Dengan Algoritma Bayesian Association Rule Mining Network

    OpenAIRE

    Octavian

    2015-01-01

    Beberapa tahun terakhir, Bayesian Network telah menjadi konsep yang populer digunakan dalam berbagai bidang kehidupan seperti dalam pengambilan sebuah keputusan dan menentukan peluang suatu kejadian dapat terjadi. Sayangnya, pengkonstruksian struktur dari Bayesian Network itu sendiri bukanlah hal yang sederhana. Oleh sebab itu, penelitian ini mencoba memperkenalkan algoritma Bayesian Association Rule Mining Network untuk memudahkan kita dalam mengkonstruksi Bayesian Network berdasarkan data ...

  13. A heuristic algorithm for quick hiding of association rules

    Directory of Open Access Journals (Sweden)

    Maryam Fouladfar

    Full Text Available Increasing use of data mining process and extracting of association rules caused the introduction of privacy preserving in data mining. A complete publication of the database is inconsistent with security policies and it would result in disclosure of some ...

  14. Loss profit estimation using association rule mining with clustering

    Directory of Open Access Journals (Sweden)

    Mandeep Mittal

    2015-02-01

    Full Text Available Data mining is the technique to find hidden patterns from a very large volume of historical data. Association rule is a type of data mining that correlates one set of items or events with another set of items or events. Another data mining strategy is clustering technique. This technique is used to create partitions so that all members of each set are similar according to a specified set of metrics. Both the association rule mining and clustering helps in more effective individual and group decision making for optimal inventory control. Owing to the above facts, association rules are mined from each cluster to find frequent items and then loss profit is calculated for each frequent item. Initially, the clustering algorithm is used to partition the transactional database into different clusters. Apriori, a classic data mining algorithm is utilized for mining association rules from each cluster to find frequent items. Later the loss profit is calculated for each frequent item. The obtained loss profit is used to rank frequent items in each cluster. Thus, the ranking of frequent items in each cluster using the proposed approach greatly facilitate optimal inventory control. An example is illustrated to validate the results.

  15. Influences of nonassociated flow rules on seismic bearing capacity factors of strip footing on soil slope by energy dissipation method

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    Seismic bearing capacity factors of a strip footing placed on soil slope were determined with both associated and nonassociated flow rules. Quasi-static representation of earthquake effects using a seismic coefficient concept was adopted for seismic bearing capacity calculations. A multi-wedge translational failure mechanism was used to obtain the seismic bearing capacity factors for different seismic coefficients and various inclined angles. Employing the associated flow rule, numerical results were compared with the published solutions. For bearing capacity factors related to cohesion and equivalent surcharge load, the maximum difference approximates 0.1%. However, the difference of bearing capacity factor related to unit weight is larger. With the two flow rules, the seismic bearing capacity factors were presented in the form of design charts for practical use. The results show that seismic bearing capacity factors related to the cohesion, the equivalent surcharge load and the unit weight increase greatly as the dilatancy angle increases, and that the nonassociated flow rule has important influences on the seismic bearing capacity.

  16. Dynamic association rules for gene expression data analysis.

    Science.gov (United States)

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

    2015-10-14

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

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

    Science.gov (United States)

    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

  18. Fast rule-based bioactivity prediction using associative classification mining

    Directory of Open Access Journals (Sweden)

    Yu Pulan

    2012-11-01

    Full Text Available Abstract Relating chemical features to bioactivities is critical in molecular design and is used extensively in the lead discovery and optimization process. A variety of techniques from statistics, data mining and machine learning have been applied to this process. In this study, we utilize a collection of methods, called associative classification mining (ACM, which are popular in the data mining community, but so far have not been applied widely in cheminformatics. More specifically, classification based on predictive association rules (CPAR, classification based on multiple association rules (CMAR and classification based on association rules (CBA are employed on three datasets using various descriptor sets. Experimental evaluations on anti-tuberculosis (antiTB, mutagenicity and hERG (the human Ether-a-go-go-Related Gene blocker datasets show that these three methods are computationally scalable and appropriate for high speed mining. Additionally, they provide comparable accuracy and efficiency to the commonly used Bayesian and support vector machines (SVM methods, and produce highly interpretable models.

  19. Causal association rule mining methods based on fuzzy state description

    Institute of Scientific and Technical Information of China (English)

    Liang Kaijian; Liang Quan; Yang Bingru

    2006-01-01

    Aiming at the research that using more new knowledge to develope knowledge system with dynamic accordance, and under the background of using Fuzzy language field and Fuzzy language values structure as description framework, the generalized cell Automation that can synthetically process fuzzy indeterminacy and random indeterminacy and generalized inductive logic causal model is brought forward. On this basis, a kind of the new method that can discover causal association rules is provded. According to the causal information of standard sample space and commonly sample space,through constructing its state (abnormality) relation matrix, causal association rules can be gained by using inductive reasoning mechanism. The estimate of this algorithm complexity is given,and its validity is proved through case.

  20. Feasibility study for banking loan using association rule mining classifier

    Directory of Open Access Journals (Sweden)

    Agus Sasmito Aribowo

    2015-03-01

    Full Text Available The problem of bad loans in the koperasi can be reduced if the koperasi can detect whether member can complete the mortgage debt or decline. The method used for identify characteristic patterns of prospective lenders in this study, called Association Rule Mining Classifier. Pattern of credit member will be converted into knowledge and used to classify other creditors. Classification process would separate creditors into two groups: good credit and bad credit groups. Research using prototyping for implementing the design into an application using programming language and development tool. The process of association rule mining using Weighted Itemset Tidset (WIT–tree methods. The results shown that the method can predict the prospective customer credit. Training data set using 120 customers who already know their credit history. Data test used 61 customers who apply for credit. The results concluded that 42 customers will be paying off their loans and 19 clients are decline

  1. A New Parallel Algorithm for Mining Association Rules

    Institute of Scientific and Technical Information of China (English)

    DING Yan-hui; WANG Hong-guo; GAO Ming; GU Jian-jun

    2006-01-01

    Mining association rules from large database is very costly.We develop a parallel algorithm for this task on sharedmemory multiprocessor (SMP). Most proposed parallel algorithms for association rules mining have to scan the database at least two times. In this article, a parallel algorithm Scan Once (SO) has been proposed for SMP,which only scans the database once. And this algorithm is fundamentally different from the known parallel algorithm Count Distribution (CD). It adopts bit matrix to store the database information and gets the support of the frequent itemsets by adopting Vector-And-Operation, which greatly improve the efficiency of generating all frequent itemsets.Empirical evaluation shows that the algorithm outperforms the known one CD algorithm.

  2. Secure Association Rule Mining for Distributed Level Hierarchy in Web

    Directory of Open Access Journals (Sweden)

    Gulshan Shrivastava,

    2011-06-01

    Full Text Available Data mining technology can analyze massive data and it play very important role in many domains, if it used improperly it can also cause some new problem of information security. Thus severalprivacy preserving techniques for association rule mining have also been proposed in the past few years. Various algorithms have been developed for centralized data, while others refer to distributed data scenario. Distributed data Scenarios can also be classified as heterogeneous distributed data and homogenous distributed data and we identify that distributed data could be partitioned as horizontal partition (a.k.a. homogeneous distribution and vertical partition (a.k.a. heterogeneous distribution. In this paper, we propose an algorithm for secure association rule mining for vertical partition.

  3. New scheduling rules for a dynamic flexible flow line problem with sequence-dependent setup times

    Science.gov (United States)

    Kia, Hamidreza; Ghodsypour, Seyed Hassan; Davoudpour, Hamid

    2017-01-01

    In the literature, the application of multi-objective dynamic scheduling problem and simple priority rules are widely studied. Although these rules are not efficient enough due to simplicity and lack of general insight, composite dispatching rules have a very suitable performance because they result from experiments. In this paper, a dynamic flexible flow line problem with sequence-dependent setup times is studied. The objective of the problem is minimization of mean flow time and mean tardiness. A 0-1 mixed integer model of the problem is formulated. Since the problem is NP-hard, four new composite dispatching rules are proposed to solve it by applying genetic programming framework and choosing proper operators. Furthermore, a discrete-event simulation model is made to examine the performances of scheduling rules considering four new heuristic rules and the six adapted heuristic rules from the literature. It is clear from the experimental results that composite dispatching rules that are formed from genetic programming have a better performance in minimization of mean flow time and mean tardiness than others.

  4. New scheduling rules for a dynamic flexible flow line problem with sequence-dependent setup times

    Science.gov (United States)

    Kia, Hamidreza; Ghodsypour, Seyed Hassan; Davoudpour, Hamid

    2017-01-01

    In the literature, the application of multi-objective dynamic scheduling problem and simple priority rules are widely studied. Although these rules are not efficient enough due to simplicity and lack of general insight, composite dispatching rules have a very suitable performance because they result from experiments. In this paper, a dynamic flexible flow line problem with sequence-dependent setup times is studied. The objective of the problem is minimization of mean flow time and mean tardiness. A 0-1 mixed integer model of the problem is formulated. Since the problem is NP-hard, four new composite dispatching rules are proposed to solve it by applying genetic programming framework and choosing proper operators. Furthermore, a discrete-event simulation model is made to examine the performances of scheduling rules considering four new heuristic rules and the six adapted heuristic rules from the literature. It is clear from the experimental results that composite dispatching rules that are formed from genetic programming have a better performance in minimization of mean flow time and mean tardiness than others.

  5. AN INCREMENTAL UPDATING ALGORITHM FOR MINING ASSOCIATION RULES

    Institute of Scientific and Technical Information of China (English)

    Xu Baowen; Yi Tong; Wu Fangjun; Chen Zhenqiang

    2002-01-01

    In this letter, on the basis of Frequent Pattern(FP) tree, the support function to update FP-tree is introduced, then an Incremental FP (IFP) algorithm for mining association rules is proposed. IFP algorithm considers not only adding new data into the database but also reducing old data from the database. Furthermore, it can predigest five cases to three cases.The algorithm proposed in this letter can avoid generating lots of candidate items, and it is high efficient.

  6. Reduction of Negative and Positive Association Rule Mining and Maintain Superiority of Rule Using Modified Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    Nikhil Jain,Vishal Sharma,Mahesh Malviya

    2012-12-01

    Full Text Available Association rule mining play important rule inmarket data analysis and also in medical diagnosisof correlated problem. For the generation ofassociation rule mining various technique are usedsuch as Apriori algorithm, FP-growth and treebased algorithm. Some algorithms are wonderperformance but generate negative association ruleand also suffered from Superiority measureproblem. In this paper we proposed a multi-objectiveassociation rule mining based on genetic algorithmand Euclidean distance formula. In this method wefind the near distance of rule set using Euclideandistance formula and generate two class higherclass and lower class .the validate of class check bydistance weight vector. Basically distance weightvector maintain a threshold value of rule itemsets.In whole process we used genetic algorithm foroptimization of rule set. Here we set population sizeis 1000 and selection process validate by distanceweight vector. Our proposed algorithm distanceweight optimization of association rule mining withgenetic algorithm compared with multi-objectiveassociation rule optimization using geneticalgorithm. Our proposed algorithm is better rule setgeneration instead of MORA method.

  7. Efficient Data Mining in SAMS through Association Rule

    Directory of Open Access Journals (Sweden)

    Mr. Rahul B. Diwate

    2014-05-01

    Full Text Available We propose a protocol for secure mining of association rules in distributed databases. Previous techniques all people deals with different database, now a day’s people also deals with the distributed database. Can we develop a kind of application in which the people can access the distributed data which is already store in remote location in encrypted format? This proposes system technique is used for efficient data mining in SAMS (Student Assessment Management System through association rules in distributed databases. The current leading techniques are that of Kantarcioglu and Clifton. This proposed system is ready to implements two methods, one that computes the union of private subsets that each of the interacting users hold, and another that tests the inclusion of an element held by one user in a subset held by another .We propose a protocol for secure mining through association rule consist a different level of execution process to secure storage of data and access of data. This paper will focus on such process for secure storage plus secure access of data

  8. Efficient Analysis of Pattern and Association Rule Mining Approaches

    Directory of Open Access Journals (Sweden)

    Thabet Slimani

    2014-02-01

    Full Text Available The process of data mining produces various patterns from a given data source. The most recognized data mining tasks are the process of discovering frequent itemsets, frequent sequential patterns, frequent sequential rules and frequent association rules. Numerous efficient algorithms have been proposed to do the above processes. Frequent pattern mining has been a focused topic in data mining research with a good number of references in literature and for that reason an important progress has been made, varying from performant algorithms for frequent itemset mining in transaction databases to complex algorithms, such as sequential pattern mining, structured pattern mining, correlation mining. Association Rule mining (ARM is one of the utmost current data mining techniques designed to group objects together from large databases aiming to extract the interesting correlation and relation among huge amount of data. In this article, we provide a brief review and analysis of the current status of frequent pattern mining and discuss some promising research directions. Additionally, this paper includes a comparative study between the performance of the described approaches.

  9. Effect of violating the traffic light rule in the Biham-Middleton-Levine traffic flow model

    Science.gov (United States)

    Ding, Zhong-Jun; Jiang, Rui; Li, Ming; Li, Qi-Lang; Wang, Bing-Hong

    2012-09-01

    This paper studies the effect of violating the traffic light rule in the Biham-Middleton-Levine (BML) traffic flow model. It is assumed that there are two kinds of drivers: normal drivers obey the traffic light rule and violators disobey it. Simulation results show that although the existence of violators increases the average velocity in the free-flowing phase, it decreases the threshold from free-flowing phase to jam. With the presence of violators, a new kind of configuration with stripe slopes -2 and -1/2 has been found in the free-flowing phase. We have developed an analytical investigation which successfully predicts the average velocity in the free-flowing phase. A phase separation phenomenon, where jams and freely flowing traffic coexist, has been found in the intermediate car density range. The mechanism of the phase separation has been illustrated.

  10. An Efficient Approach to Prune Mined Association Rules in Large Databases

    Directory of Open Access Journals (Sweden)

    D. Narmadha

    2011-01-01

    Full Text Available Association rule mining finds interesting associations and/or correlation relationships among large set of data items. However, when the number of association rules become large, it becomes less interesting to the user. It is crucial to help the decision-maker with an efficient postprocessing step in order to select interesting association rules throughout huge volumes of discovered rules. This motivates the need for association analysis. Thus, this paper presents a novel approach to prune mined association rules in large databases. Further, an analysis of different association rule mining techniques for market basket analysis, highlighting strengths of different association rule mining techniques are also discussed. We want to point out potential pitfalls as well as challenging issues need to be addressed by an association rule mining technique. We believe that the results of this approach will help decision maker for making important decisions.

  11. Cellular Automaton Rule 184++C A Simple Model for the Complex Dynamics of Various Particles Flow

    CERN Document Server

    Awazu, A

    1999-01-01

    A cellular automaton named Rule 184++C is proposed as a meta-model to investigate the flow of various complex particles. In this model, unlike the granular pipe flow and the traffic flow, not only the free-jam phase transition but also the free-intermediate, the intermediate-jam, and the dilute-dense phase transitions appear. Moreover, the freezing phenomena appear if the system contains two types of different particles.

  12. Prediction of users webpage access behaviour using association rule mining

    Indian Academy of Sciences (India)

    R Geetharamani; P Revathy; Shomona G Jacob

    2015-12-01

    Web Usage mining is a technique used to identify the user needs from the web log. Discovering hidden patterns from the logs is an upcoming research area. Association rules play an important role in many web mining applications to detect interesting patterns. However, it generates enormous rules that cause researchers to spend ample time and expertise to discover the really interesting ones. This paper works on the server logs from the MSNBC dataset for the month of September 1999. This research aims at predicting the probable subsequent page in the usage of web pages listed in this data based on their navigating behaviour by using Apriori prefix tree (PT) algorithm. The generated rules were ranked based on the support, confidence and lift evaluation measures. The final predictions revealed that the interestingness of pages mainly depended on the support and lift measure whereas confidence assumed a uniform value among all the pages. It proved that the system guaranteed 100% confidence with the support of 1.3E−05. It revealed that the pages such as Front page, On-air, News, Sports and BBS attracted more interested subsequent users compared to Travel, MSN-News and MSN-Sports which were of less interest.

  13. AN INCREMENTAL UPDATING ALGORITHM FOR MINING ASSOCIATION RULES

    Institute of Scientific and Technical Information of China (English)

    XuBaowen; YiTong; 等

    2002-01-01

    In this letter,on the basis of Frequent Pattern(FP) tree,the support function to update FP-tree is introduced,then an incremental FP(IFP) algorithm for mining association rules is proposed.IFP algorithm considers not only adding new data into the database but also reducing old data from the database.Furthermore,it can predigest five cases to three case .The algorithm proposed in this letter can avoid generating lots of candidate items,and it is high efficient.

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

    Directory of Open Access Journals (Sweden)

    Fredrik Erlandsson

    2016-04-01

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

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

    Science.gov (United States)

    Erlandsson, Fredrik; Bródka, Piotr; Borg, Anton; Johnson, Henric

    2016-04-01

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

  16. Integrated Web Recommendation Model with Improved Weighted Association Rule Mining

    Directory of Open Access Journals (Sweden)

    S.A.Sahaaya Arul Mary

    2013-04-01

    Full Text Available World Wide Web plays a significant role in human life. It requires a technological improvement to satisfy the user needs. Web log data is essential for improving the performance of the web. It contains large,heterogeneous and diverse data. Analyzing g the web log data is a tedious process for Web developers, Web designers, technologists and end users. In this work, a new weighted association mining algorithm is developed to identify the best association rules that are useful for web site restructuring and recommendation that reduces false visit and improve users’ navigation behavior. The algorithm finds the frequent item set from a large uncertain database. Frequent scanning of database in each time is the problem with the existing algorithms which leads to complex output set and time consuming process. Theproposed algorithm scans the database only once at the beginning of the process and the generated frequent item sets, which are stored into the database. The evaluation parameters such as support, confidence, lift and number of rules are considered to analyze the performance of proposed algorithm and traditional association mining algorithm. The new algorithm produced best result that helps the developer to restructure their website in a way to meet the requirements of the end user within short time span.

  17. Using Fuzzy Association Rules to Design E-commerce Personalized Recommendation System

    OpenAIRE

    Guofang Kuang; Yuanchen Li

    2013-01-01

    In order to improve the efficiency of fuzzy association rule mining, the paper defines the redundant fuzzy association rules, and strong fuzzy association rules redundant nature. As much as possible for more information in the e-commerce environment, and in the right form is a prerequisite for personalized recommendation. Personalized recommendation technology is a core issue of e-commerce automated recommendation system. Higher complexity than ordinary association rules algorithm fuzzy assoc...

  18. ASSOCIATION RULE DISCOVERY FOR STUDENT PERFORMANCE PREDICTION USING METAHEURISTIC ALGORITHMS

    Directory of Open Access Journals (Sweden)

    Roghayeh Saneifar

    2015-11-01

    Full Text Available According to the increase of using data mining techniques in improving educational systems operations, Educational Data Mining has been introduced as a new and fast growing research area. Educational Data Mining aims to analyze data in educational environments in order to solve educational research problems. In this paper a new associative classification technique has been proposed to predict students final performance. Despite of several machine learning approaches such as ANNs, SVMs, etc. associative classifiers maintain interpretability along with high accuracy. In this research work, we have employed Honeybee Colony Optimization and Particle Swarm Optimization to extract association rule for student performance prediction as a multi-objective classification problem. Results indicate that the proposed swarm based algorithm outperforms well-known classification techniques on student performance prediction classification problem.

  19. Research on Algorithm for Mining Negative Association Rules Based on Frequent Pattern Tree

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    Typical association rules consider only items enumerated in transactions. Such rules are referred to as positive association rules. Negative association rules also consider the same items, but in addition consider negated items (i.e. absent from transactions). Negative association rules are useful in market-basket analysis to identify products that conflict with each other or products that complement each other. They are also very convenient for associative classifiers, classifiers that build their classification model based on association rules. Indeed, mining for such rules necessitates the examination of an exponentially large search space. Despite their usefulness, very few algorithms to mine them have been proposed to date. In this paper, an algorithm based on FP-tree is presented to discover negative association rules.

  20. ASSOCIATION RULES IN HORIZONTALLY DISTRIBUTED DATABASES WITH ENHANCED SECURE MINING

    Directory of Open Access Journals (Sweden)

    Sonal Patil

    2015-10-01

    Full Text Available Recent developments in information technology have made possible the collection and analysis of millions of transactions containing personal data. These data include shopping habits, criminal records, medical histories and credit records among others. In the term of distributed database, distributed database is a database in which storage devices are not all attached to a common processing unit such as the CPU controlled by a distributed database management system (together sometimes called a distributed database system. It may be stored in multiple computers located in the same physical location or may be dispersed over a network of interconnected computers. A protocol has been proposed for secure mining of association rules in horizontally distributed databases. This protocol is optimized than the Fast Distributed Mining (FDM algorithm which is an unsecured distributed version of the Apriori algorithm. The main purpose of this protocol is to remove the problem of mining generalized association rules that affects the existing system. This protocol offers more enhanced privacy with respect to previous protocols. In addition it is simpler and is optimized in terms of communication rounds, communication cost and computational cost than other protocols.

  1. Urban association rules: uncovering linked trips for shopping behavior

    CERN Document Server

    Yoshimura, Yuji; Hobin, Juan N Bautista; Ratti, Carlo; Blat, Josep

    2016-01-01

    In this article, we introduce the method of urban association rules and its uses for extracting frequently appearing combinations of stores that are visited together to characterize shoppers' behaviors. The Apriori algorithm is used to extract the association rules (i.e., if -> result) from customer transaction datasets in a market-basket analysis. An application to our large-scale and anonymized bank card transaction dataset enables us to output linked trips for shopping all over the city: the method enables us to predict the other shops most likely to be visited by a customer given a particular shop that was already visited as an input. In addition, our methodology can consider all transaction activities conducted by customers for a whole city in addition to the location of stores dispersed in the city. This approach enables us to uncover not only simple linked trips such as transition movements between stores but also the edge weight for each linked trip in the specific district. Thus, the proposed methodo...

  2. A dual active-restrictive approach to incorporating environmental flow targets into existing reservoir operation rules

    Science.gov (United States)

    Shiau, Jenq-Tzong; Wu, Fu-Chun

    2010-08-01

    Environmental flow schemes may be implemented through active or restrictive strategies. The former may be applied via reservoir releases, and the latter can be executed by reducing water demands. We present a dual active-restrictive approach to devising the optimal reservoir operation rules that aim to secure off-stream water supplies while maximizing environmental benefits. For the active part, a multicomponent environmental flow target (including the minimum and monthly flows) is incorporated in the operation rules. For the restrictive counterpart, we use a novel demands partitioning and prioritizing (DPP) approach to reallocating the demands of various sectors. The DPP approach partitions the existing off-stream demand and newly incorporated environmental demand and reassembles the two as the first- and second-priority demands. Water is reallocated to each demand according to the ratios derived from the prioritized demands. The proposed approach is coupled with a multicriteria optimization framework to seek the optimal operation rules for the existing Feitsui Reservoir system (Taiwan) under various scenarios. The best overall performance is achieved by an optimal dual strategy whose operational parameters are all determined by optimization. The optimal environmental flow target may well be a top-priority constant base flow rather than the variable quantities. The active strategy would outperform the restrictive one. For the former, a top-priority base flow target is essential; for the latter, the off-stream demand can become vanishingly small in compensation for the eliminated base flow target, thus promoting the monthly flow target as nearly the top-priority demand. For either the active or restrictive strategy, a prioritized environmental flow demand would provide a path toward the optimal overall performance. A significantly improved overall performance over the existing operation rules is unlikely if the active and restrictive parameters are both favorable

  3. Integrated analysis of gene expression by association rules discovery

    Directory of Open Access Journals (Sweden)

    Carazo Jose M

    2006-02-01

    Full Text Available Abstract Background Microarray technology is generating huge amounts of data about the expression level of thousands of genes, or even whole genomes, across different experimental conditions. To extract biological knowledge, and to fully understand such datasets, it is essential to include external biological information about genes and gene products to the analysis of expression data. However, most of the current approaches to analyze microarray datasets are mainly focused on the analysis of experimental data, and external biological information is incorporated as a posterior process. Results In this study we present a method for the integrative analysis of microarray data based on the Association Rules Discovery data mining technique. The approach integrates gene annotations and expression data to discover intrinsic associations among both data sources based on co-occurrence patterns. We applied the proposed methodology to the analysis of gene expression datasets in which genes were annotated with metabolic pathways, transcriptional regulators and Gene Ontology categories. Automatically extracted associations revealed significant relationships among these gene attributes and expression patterns, where many of them are clearly supported by recently reported work. Conclusion The integration of external biological information and gene expression data can provide insights about the biological processes associated to gene expression programs. In this paper we show that the proposed methodology is able to integrate multiple gene annotations and expression data in the same analytic framework and extract meaningful associations among heterogeneous sources of data. An implementation of the method is included in the Engene software package.

  4. Improving Leung's bidirectional learning rule for associative memories.

    Science.gov (United States)

    Lenze, B

    2001-01-01

    Leung (1994) introduced a perceptron-like learning rule to enhance the recall performance of bidirectional associative memories (BAMs). He proved that his so-called bidirectional learning scheme always yields a solution within a finite number of learning iterations in case that a solution exists. Unfortunately, in the setting of Leung a solution only exists in case that the training set is strongly linear separable by hyperplanes through the origin. We extend Leung's approach by considering conditionally strong linear separable sets allowing separating hyperplanes not containing the origin. Moreover, we deal with BAMs, which are generalized by defining so-called dilation and translation parameters enlarging their capacity, while leaving their complexity almost unaffected. The whole approach leads to a generalized bidirectional learning rule which generates BAMs with dilation and translation that perform perfectly on the training set in a case that the latter satisfies the conditionally strong linear separability assumption. Therefore, in the sense of Leung, we conclude with an optimal learning strategy which contains Leung's initial idea as a special case.

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

    Directory of Open Access Journals (Sweden)

    Nattawat Khamphakdee

    2015-07-01

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

  6. Using Fuzzy Association Rules to Design E-commerce Personalized Recommendation System

    Directory of Open Access Journals (Sweden)

    Guofang Kuang

    2013-09-01

    Full Text Available In order to improve the efficiency of fuzzy association rule mining, the paper defines the redundant fuzzy association rules, and strong fuzzy association rules redundant nature. As much as possible for more information in the e-commerce environment, and in the right form is a prerequisite for personalized recommendation. Personalized recommendation technology is a core issue of e-commerce automated recommendation system. Higher complexity than ordinary association rules algorithm fuzzy association rules, the low efficiency become a bottleneck in the practical application of fuzzy association rules algorithm. The paper presents using fuzzy association rules to design E-commerce personalized recommendation system. The experimental results show that the new algorithm to improve the efficiency of the implementation.

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

    Directory of Open Access Journals (Sweden)

    Joanna M. Kesten

    2015-01-01

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

  8. Mining Association Rules in Dengue Gene Sequence with Latent Periodicity

    Directory of Open Access Journals (Sweden)

    Marimuthu Thangam

    2015-01-01

    Full Text Available The mining of periodic patterns in dengue database is an interesting research problem that can be used for predicting the future evolution of dengue viruses. In this paper, we propose an algorithm called Recurrence Finder (RECFIN that uses the suffix tree for detecting the periodic patterns of dengue gene sequence. Also, the RECFIN finds the presence of palindrome which indicates the possibilities of formation of proteins. Further, this paper computes the periodicity of nucleic acid and amino acid sequences of any length. The periodicity based association rules are used to diagnose the type of dengue. The time complexity of the proposed algorithm is O(n2. We demonstrate the effectiveness of the proposed approach by comparing the experimental results performed on dengue virus serotypes dataset with NCBI-BLAST algorithm.

  9. A SURVEY ON PRIVACY PRESERVING ASSOCIATION RULE MINING

    Directory of Open Access Journals (Sweden)

    K.Sathiyapriya

    2013-03-01

    Full Text Available Businesses share data, outsourcing for specific business problems. Large companies stake a large part of their business on analysis of private data. Consulting firms often handle sensitive third party data as part of client projects. Organizations face great risks while sharing their data. Most of this sharing takes place with little secrecy. It also increases the legal responsibility of the parties involved in the process. So, it is crucial to reliably protect their data due to legal and customer concerns. In this paper, a review of the state-of-the-art methods for privacy preservation is presented. It also analyzes the techniques for privacy preserving association rule mining and points out their merits and demerits. Finally the challenges and directions for future research are discussed.

  10. Study on the Customer targeting using Association Rule Mining

    Directory of Open Access Journals (Sweden)

    Surendiran.R

    2010-10-01

    Full Text Available Data mining is one of the widest area where many researches takes place to mine desired and hidden data. There are many different approaches to find the hidden data. This paper deals with Frequent Pattern growth algorithm which follows association rule concept togroup the required data items. Using this method of mining time can be reduced to a greater extent. This paper contains implementation of a real time system; the implementation is about making a survey on the group of people and their mobile connection’s service providers.End result contains the set of people from a particular age group with their support and confidence for the service provider they have chosen. Based on which any decisions can be made by service providers to enhance their business and attain many customers.

  11. A NEW ASSOCIATION RULE MINING BASED ON FREQUENT ITEM SET

    Directory of Open Access Journals (Sweden)

    Ms. Sanober Shaikh

    2011-09-01

    Full Text Available In this paper a new mining algorithm is defined based on frequent item set. Apriori Algorithm scans the database every time when it finds the frequent item set so it is very time consuming and at each step it generates candidate item set. So for large databases it takes lots of space to store candidate item set. The defined algorithm scans the database at the start only once and then makes the undirected item set graph. From this graph by considering minimum support it finds the frequent item set and by considering the minimum confidence it generates the association rule. If database and minimum support is changed, the new algorithm finds the new frequent items by scanning undirected item set graph. That is why it’s executing efficiency is improved distinctly compared to traditional algorithm.

  12. An Efficient Algorithm to Automated Discovery of Interesting Positive and Negative Association Rules

    Directory of Open Access Journals (Sweden)

    Ahmed Abdul-WahabAl-Opahi

    2015-06-01

    Full Text Available Association Rule mining is very efficient technique for finding strong relation between correlated data. The correlation of data gives meaning full extraction process. For the discovering frequent items and the mining of positive rules, a variety of algorithms are used such as Apriori algorithm and tree based algorithm. But these algorithms do not consider negation occurrence of the attribute in them and also these rules are not in infrequent form. 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 interest negative association rules, and their huge number as compared with positive association rules. The interesting discovery of association rules is an important and active area within data mining research. In this paper, an efficient algorithm is proposed for discovering interesting positive and negative association rules from frequent and infrequent items. The experimental results show the usefulness and effectiveness of the proposed algorithm.

  13. Analisis Keterkaitan Penyakit Pasien pada Puskesmas Menggunakan Metode Association Rule

    Directory of Open Access Journals (Sweden)

    karina auliasari

    2016-08-01

    The data used in this research is an inpatient medical records of patients Brang Rea Puskesmas from January to June 2015. The system was developed using the programming language Visual Basic and Microsoft SQL Server 2008 as the database. Tests on the analysis modules generate output system of rules "if" "then" or "if" "it", rule or rule illness taken from the rules that exceed the value or the minimum support and minimum confidence. From the results of system testing conducted seen that the rules that can be used by the health center for analysis Brang Rea inpatients disease is a rule that has a value of minimum support and minimum confidence-value equals or exceeds the value specified by the administrator.

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

    OpenAIRE

    Balcázar, José L.

    2011-01-01

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

  15. Deriving Association between Student’s Comprehension and Facial expressions using Class Association Rule Mining

    Directory of Open Access Journals (Sweden)

    M. Mohamed Sathik

    2013-06-01

    Full Text Available The scope of this study was to discover the association between facial expressions of students in an academic lecture and the level of comprehension shown by their expressions. This study focussed onfinding the relationship between the specific elements of learner’s behaviour for the different emotional states and the relevant expression that could be observed from individual students. The experimentation was done through surveying quantitative observations of the lecturers in the classroom in which the behaviour of students are recorded and were statistically analyzed. The main aim of this paper is to derive association rules that represent relationships between input conditions and results of domain experiments. Hence the relationship between the physical behaviors that are linked to emotional state with the student’s comprehension is being formulated in the form of rules. We present Predictive Apriori algorithm that is able to find all valid class association rules with high accuracy. The rules derived by Predictive Apriori are pruned by objective and subjective measures.

  16. A differential equation for the flow rate during silo discharge: Beyond the Beverloo rule

    OpenAIRE

    2016-01-01

    We present a differential equation for the flow rate of granular materials during the discharge of a silo. This is based in the energy balance of the variable mass system in contrast with the traditional derivations based on heuristic postulates such as the free fall arch. We show that this new equation is consistent with the well known Beverloo rule, providing an independent estimate for the universal Beverloo prefactor. We also find an analytic expression for the pressure under discharging ...

  17. Analysis of Electric Power System Using Data Mining Association Rule

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Jun Sub; Kim, Min Soo; Choi, Sang Yule; Kim, Chul Whan; Kim, Ung Mo [Skungkyunkwan University (Korea)

    2001-07-01

    Data Mining is a issue of Database fields. Data mining is discovered optimally interesting rules for user, which are results of specific requirement of user, through past data. Through to analyze and to statical suppose interesting rules, we can prepare future faults of system. In this paper, we present a new way which is discovered and repaired faults of Electric Power system using Data Mining techniques. (author). 15 refs., 4 figs., 1 tab.

  18. Association Rule Hiding Techniques for Privacy Preserving Data Mining: A Study

    Directory of Open Access Journals (Sweden)

    Gayathiri P

    2015-12-01

    Full Text Available Association rule mining is an efficient data mining technique that recognizes the frequent items and associative rule based on a market basket data analysis for large set of transactional databases. The probability of most frequent data item occurrence of the transactional data items are calculated to present the associative rule that represents the habits of buying products of the customers in demand. Identifying associative rules of a transactional database in data mining may expose the confidentiality and privacy of an organization and individual. Privacy Preserving Data Mining (PPDM is a solution for privacy threats in data mining. This issue is solved using Association Rule Hiding (ARH techniques in Privacy Preserving Data Mining (PPDM. This research work on Association Rule Hiding technique in data mining performs the generation of sensitive association rules by the way of hiding based on the transactional data items. The property of hiding rules not the data makes the sensitive rule hiding process is a minimal side effects and higher data utility technique.

  19. 关联规则挖掘研究述评%Association Rule Mining: A Survey

    Institute of Scientific and Technical Information of China (English)

    贾彩燕; 倪现君

    2003-01-01

    Association rule mining has been one of the most popular data mining subejcts and has a wide range of applicability. In this paper, we first investigate the main approaches for the task of association rule mining, and analyzed the essence of the algorithms. Then we review foundations of assocation rule mining based on the several possible theoretical frameworks for data mining. What's more,we show the open problems in field of the association rule mining and figure out the tendency of its development in recent years.

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

    Science.gov (United States)

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

    2017-09-01

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

  1. Design and Realization of user Behaviors Recommendation System Based on Association rules under Cloud Environment

    Directory of Open Access Journals (Sweden)

    Wei Dai

    2013-07-01

    Full Text Available This study introduces the basal principles of association rules, properties and advantages of Map Reduce model and Hbase in Hadoop ecosystem. And giving design steps of the user's actions recommend system in detail, many time experiences proves that the exploration combined association rules theory with cloud computing is successful and effective.

  2. Mining of the quantitative association rules with standard SQL queries and its evaluation

    Institute of Scientific and Technical Information of China (English)

    孙海洪; 唐菁; 蒋洪; 杨炳儒

    2004-01-01

    A new algorithm for mining quantitative association rules with standard SQL is presented. The association rules are evaluated with the sufficiency gene LS of subjectivity Bayes reasoning. This algorithm is proved to be quick and effective with its application in Lujiang insects and pests database.

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

    Science.gov (United States)

    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.

  4. Liquefaction, flow, and associated ground failure

    Science.gov (United States)

    Youd, T. Leslie

    1973-01-01

    Ambiguities in the use of the term liquefaction and in defining the relation between liquefaction and ground failure have led to encumbered communication between workers in various fields and between specialists in the same field, and the possibility that evaluations of liquefaction potential could be misinterpreted or misapplied. Explicit definitions of liquefaction and related concepts are proposed herein. These definitions, based on observed laboratory behavior, are then used to clarify the relation between liquefaction and ground failure. Soil liquefaction is defined as the transformation of a granular material from a solid into a liquefied state as a consequence of increased pore-water pressures. This definition avoids confusion between liquefaction and possible flow-failure conditions after liquefaction. Flow-failure conditions are divided into two types: (1) unlimited flow if pore-pressure reductions caused by dilatancy during flow deformation are not sufficient to solidify the material and thus arrest flow, and (2) limited flow if they are sufficient to solidify the material after a finite deformation. After liquefaction in the field, unlimited flow commonly leads to flow landslides, whereas limited flow leads at most to lateral-spreading landslides. Quick-condition failures such as loss of bearing capacity form a third type of ground failure associated with liquefaction.

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

    Science.gov (United States)

    Mihai, Gabroveanu

    2015-09-01

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

  6. Modified Approach for Hiding Sensitive Association Rules for Preserving Privacy in Database

    Directory of Open Access Journals (Sweden)

    Tania Banerjee

    2014-03-01

    Full Text Available Data mining is the process of analyzing large database to find useful patterns. The term pattern refers to the items which are frequently occurring in set of transaction. The frequent patterns are used to find association between sets of item. The efficiency of mining association rules and confidentiality of association rule is becoming one of important area of knowledge discovery in database. This paper is organized into two sections. In the system Apriori algorithm is being presented that efficiently generates association rules. These reduces unnecessary database scan at time of forming frequent large item sets .We have tried to give contribution to improved Apriori algorithm by hiding sensitive association rules which are generated by applying improved Apriori algorithm on supermarket database. In this paper we have used novel approach that strategically modifies few transactions in transaction database to decrease support and confidence of sensitive rule without producing any side effects. Thus in the paper we have efficiently generated frequent item set sets by applying Improved Apriori algorithm and generated association rules by applying minimum support and minimum confidence and then we went one step further to identify sensitive rules and tried to hide them without any side effects to maintain integrity of data without generating spurious rules.

  7. A differential equation for the flow rate during silo discharge: Beyond the Beverloo rule

    Directory of Open Access Journals (Sweden)

    Madrid Marcos A.

    2017-01-01

    Full Text Available We present a differential equation for the flow rate of granular materials during the discharge of a silo. This is based in the energy balance of the variable mass system in contrast with the traditional derivations based on heuristic postulates such as the free fall arch. We show that this new equation is consistent with the well known Beverloo rule, providing an independent estimate for the universal Beverloo prefactor. We also find an analytic expression for the pressure under discharging conditions.

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

    CERN Document Server

    Balcázar, José L

    2011-01-01

    Some existing notions of redundancy among association rules allow for a logical-style characterization and lead to irredundant bases of absolutely minimum size. One can push the intuition of redundancy further and find an intuitive notion of interest of an association rule, in terms of its "novelty" with respect to other rules. Namely: an irredundant rule is so because its confidence is higher than what the rest of the rules would suggest; then, one can ask: how much higher? We propose to measure such a sort of "novelty" through the confidence boost of a rule, which encompasses two previous similar notions (confidence width and rule blocking, of which the latter is closely related to the earlier measure "improvement"). Acting as a complement to confidence and support, the confidence boost helps to obtain small and crisp sets of mined association rules, and solves the well-known problem that, in certain cases, rules of negative correlation may pass the confidence bound. We analyze the properties of two version...

  9. Sum rules and spectral density flow in QCD and in superconformal theories

    Directory of Open Access Journals (Sweden)

    Costantini Antonio

    2014-01-01

    Full Text Available We discuss the signature of the anomalous breaking of the superconformal symmetry in N${\\cal N}$ = 1 super Yang Mills theory and its manifestation in the form of anomaly poles. Moreover, we describe the massive deformations of the N${\\cal N}$ = 1 theory and the spectral densities of the corresponding anomaly form factors. These are characterized by spectral densities which flow with the mass deformation and turn the continuum contributions from the two-particle cuts of the intermediate states into poles, with a single sum rule satisfied by each component. The poles can be interpreted as signaling the exchange of a composite axion/dilaton/dilatino (ADD multiplet in the effective Lagrangian. We conclude that global anomalous currents characterized by a single flow in the perturbative picture always predict the existence of composite interpolating fields.

  10. Mining Interesting Positive and Negative Association Rule Based on Improved Genetic Algorithm (MIPNAR_GA

    Directory of Open Access Journals (Sweden)

    Nikky Suryawanshi Rai

    2014-01-01

    Full Text Available Association Rule mining is very efficient technique for finding strong relation between correlated data. The correlation of data gives meaning full extraction process. For the mining of positive and negative rules, a variety of algorithms are used such as Apriori algorithm and tree based algorithm. A number of algorithms are wonder performance but produce large number of negative association rule and also suffered from multi-scan problem. The idea of this paper is to eliminate these problems and reduce large number of negative rules. Hence we proposed an improved approach to mine interesting positive and negative rules based on genetic and MLMS algorithm. In this method we used a multi-level multiple support of data table as 0 and 1. The divided process reduces the scanning time of database. The proposed algorithm is a combination of MLMS and genetic algorithm. This paper proposed a new algorithm (MIPNAR_GA for mining interesting positive and negative rule from frequent and infrequent pattern sets. The algorithm is accomplished in to three phases: a.Extract frequent and infrequent pattern sets by using apriori method b.Efficiently generate positive and negative rule. c.Prune redundant rule by applying interesting measures. The process of rule optimization is performed by genetic algorithm and for evaluation of algorithm conducted the real world dataset such as heart disease data and some standard data used from UCI machine learning repository.

  11. Analysis of dispatching rules application on scheduling problem in flexible-flow shop production

    Directory of Open Access Journals (Sweden)

    Rakićević Zoran M.

    2014-01-01

    Full Text Available In this paper we analyzed a group of simple heuristic methods, which are used for solving the scheduling problem in manufacturing and services. The analysis was performed on the scheduling problem in a flexible-flow shop production, which is known by the English term - Flexible-Flow Shop (FFS. The task is to determine the schedule of processing multiple products on multiple machines, where all the products have the same sequence of processing and for each process there are multiple machines available. For this FFS problem we present the corresponding mathematical model of mixed integer programming. Among potential methods for solving the set task, we consider simple heuristics because the original scheduling problem is NP-hard and finding the exact optimal solution would require unacceptably long computing time. Heuristic methods are based on priority rules that are performed based on the relations of importance between products and their processing time on individual machines. Heuristic methods are widely used for solving practical problems, which was the motivation for the analysis performed in this paper. The aim of the analysis is to identify those priority rules, from a set of considered, which provide a good solution to a hypothetical scheduling problem example, where the evaluation of solution is performed using different criteria functions. The analysis that is presented in the paper was obtained by using the computer program LEKIN. The main results of the analysis indicated that priority rules give different solutions to the problem of FFS and that each of these solutions is a significantly good result in terms of some of the considered criteria functions.

  12. 77 FR 74449 - Water Quality Standards for the State of Florida's Lakes and Flowing Waters; Proposed Rule; Stay

    Science.gov (United States)

    2012-12-14

    ... AGENCY 40 CFR Part 131 RIN 2040-AF41 Water Quality Standards for the State of Florida's Lakes and Flowing... regulation the ``Water Quality Standards for the State of Florida's Lakes and Flowing Waters; Final Rule... Information Does this action apply to me? Citizens concerned with water quality in Florida may be interested...

  13. Hiding Sensitive Association Rules without Altering the Support of Sensitive Item(s)

    CERN Document Server

    Jain, Dhyanendra

    2012-01-01

    Association rule mining is an important data-mining technique that finds interesting association among a large set of data items. Since it may disclose patterns and various kinds of sensitive knowledge that are difficult to find otherwise, it may pose a threat to the privacy of discovered confidential information. Such information is to be protected against unauthorized access. Many strategies had been proposed to hide the information. Some use distributed databases over several sites, data perturbation, clustering, and data distortion techniques. Hiding sensitive rules problem, and still not sufficiently investigated, is the requirement to balance the confidentiality of the disclosed data with the legitimate needs of the user. The proposed approach uses the data distortion technique where the position of the sensitive items is altered but its support is never changed. The size of the database remains the same. It uses the idea of representative rules to prune the rules first and then hides the sensitive rule...

  14. E-commerce Website Recommender System Based on Dissimilarity and Association Rule

    OpenAIRE

    MingWang Zhang; ShuWen Yang; LiFeng Zhang

    2013-01-01

    By analyzing the current electronic commerce recommendation algorithm analysis, put forward a kind to use dissimilarity clustering and association recommendation algorithm, the algorithm realized web website shopping user data clustering by use of the dissimilarity, and then use the association rules algorithm for clustering results of association recommendation, experiments show that the algorithm compared with traditional clustering association algorithm of iteration times decrease, improve...

  15. Stellar spectra association rule mining method based on the weighted frequent pattern tree

    Institute of Scientific and Technical Information of China (English)

    Jiang-Hui Cai; Xu-Jun Zhao; Shi-Wei Sun; Ji-Fu Zhang; Hai-Feng Yang

    2013-01-01

    Effective extraction of data association rules can provide a reliable basis for classification of stellar spectra.The concept of stellar spectrum weighted itemsets and stellar spectrum weighted association rules are introduced,and the weight of a single property in the stellar spectrum is determined by information entropy.On that basis,a method is presented to mine the association rules of a stellar spectrum based on the weighted frequent pattern tree.Important properties of the spectral line are highlighted using this method.At the same time,the waveform of the whole spectrum is taken into account.The experimental results show that the data association rules of a stellar spectrum mined with this method are consistent with the main features of stellar spectral types.

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

    Science.gov (United States)

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

    2015-01-01

    Objectives To explore whether the rule of law is a foundational determinant of health that underlies other socioeconomic, political and cultural factors that have been associated with health outcomes. Setting Global project. Participants Data set of 96 countries, comprising 91% of the global population. Primary and secondary outcome measures The following health indicators, infant mortality rate, maternal mortality rate, life expectancy, and cardiovascular disease and diabetes mortality rate, were included to explore their association with the rule of law. We used a novel Rule of Law Index, gathered from survey sources, in a cross-sectional and ecological design. The Index is based on eight subindices: (1) Constraints on Government Powers; (2) Absence of Corruption; (3) Order and Security; (4) Fundamental Rights; (5) Open Government; (6) Regulatory Enforcement, (7) Civil Justice; and (8) Criminal Justice. Results The rule of law showed an independent association with infant mortality rate, maternal mortality rate, life expectancy, and cardiovascular disease and diabetes mortality rate, after adjusting for the countries’ level of per capita income, their expenditures in health, their level of political and civil freedom, their Gini measure of inequality and women's status (p<0.05). Rule of law remained significant in all the multivariate models, and the following adjustment for potential confounders remained robust for at least one or more of the health outcomes across all eight subindices of the rule of law. Findings show that the higher the country's level of adherence to the rule of law, the better the health of the population. Conclusions It is necessary to start considering the country's adherence to the rule of law as a foundational determinant of health. Health advocates should consider the improvement of rule of law as a tool to improve population health. Conversely, lack of progress in rule of law may constitute a structural barrier to health improvement

  17. Association Rule Mining for Both Frequent and Infrequent Items Using Particle Swarm Optimization Algorithm

    Directory of Open Access Journals (Sweden)

    MIR MD. JAHANGIR KABIR

    2014-07-01

    Full Text Available In data mining research, generating frequent items from large databases is one of the important issues and the key factor for implementing association rule mining tasks. Mining infrequent items such as relationships among rare but expensive products is another demanding issue which have been shown in some recent studies. Therefore this study considers user assigned threshold values as a constraint which helps users mine those rules which are more interesting for them. In addition, in real world users may prefer to know relationships among frequent items along with infrequent ones. The particle swarm optimization algorithm is an important heuristic technique in recent years and this study uses this technique to mine association rules effectively. If this technique considers user defined threshold values, interesting association rules can be generated more efficiently. Therefore this study proposes a novel approach which includes using particle swarm optimization algorithm to mine association rules from databases. Our implementation of the search strategy includes bitmap representation of nodes in a lexicographic tree and from superset-subset relationship of the nodes it classifies frequent items along with infrequent itemsets. In addition, this approach avoids extra calculation overhead for generating frequent pattern trees and handling large memory which store the support values of candidate item sets. Our experimental results show that this approach efficiently mines association rules. It accesses a database to calculate a support value for fewer numbers of nodes to find frequent itemsets and from that it generates association rules, which dramatically reduces search time. The main aim of this proposed algorithm is to show how heuristic method works on real databases to find all the interesting association rules in an efficient way.

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

    Directory of Open Access Journals (Sweden)

    Mandeep Mittal

    2015-09-01

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

  19. A Frequent Closed Itemsets Lattice-based Approach for Mining Minimal Non-Redundant Association Rules

    CERN Document Server

    Vo, Bay

    2011-01-01

    There are many algorithms developed for improvement the time of mining frequent itemsets (FI) or frequent closed itemsets (FCI). However, the algorithms which deal with the time of generating association rules were not put in deep research. In reality, in case of a database containing many FI/FCI (from ten thousands up to millions), the time of generating association rules is much larger than that of mining FI/FCI. Therefore, this paper presents an application of frequent closed itemsets lattice (FCIL) for mining minimal non-redundant association rules (MNAR) to reduce a lot of time for generating rules. Firstly, we use CHARM-L for building FCIL. After that, based on FCIL, an algorithm for fast generating MNAR will be proposed. Experimental results show that the proposed algorithm is much faster than frequent itemsets lattice-based algorithm in the mining time.

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

    Science.gov (United States)

    Huang, Yin; Chen, Jianhua; Xiong, Shaojun

    2009-07-01

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

  1. A NOVEL SIMILARITY ASSESSMENT FOR REMOTE SENSING IMAGES VIA FAST ASSOCIATION RULE MINING

    Directory of Open Access Journals (Sweden)

    J. Liu

    2016-06-01

    Full Text Available Similarity assessment is the fundamentally important to various remote sensing applications such as image classification, image retrieval and so on. The objective of similarity assessment is to automatically distinguish differences between images and identify the contents of an image. Unlike the existing feature-based or object-based methods, we concern more about the deep level pattern of image content. The association rule mining is capable to find out the potential patterns of image, hence in this paper, a fast association rule mining algorithm is proposed and the similarity is represented by rules. More specifically, the proposed approach consist of the following steps: firstly, the gray level of image is compressed using linear segmentation to avoid interference of details and reduce the computation amount; then the compressed gray values between pixels are collected to generate the transaction sets which are transformed into the proposed multi-dimension data cube structure; the association rules are then fast mined based on multi-dimension data cube; finally the mined rules are represented as a vector and similarity assessment is achieved by vector comparison using first order approximation of Kullback-Leibler divergence. Experimental results indicate that the proposed fast association rule mining algorithm is more effective than the widely used Apriori method. The remote sensing image retrieval experiments using various images for example, QuickBird, WorldView-2, based on the existing and proposed similarity assessment show that the proposed method can provide higher retrieval precision.

  2. a Novel Similarity Assessment for Remote Sensing Images via Fast Association Rule Mining

    Science.gov (United States)

    Liu, Jun; Chen, Kai; Liu, Ping; Qian, Jing; Chen, Huijuan

    2016-06-01

    Similarity assessment is the fundamentally important to various remote sensing applications such as image classification, image retrieval and so on. The objective of similarity assessment is to automatically distinguish differences between images and identify the contents of an image. Unlike the existing feature-based or object-based methods, we concern more about the deep level pattern of image content. The association rule mining is capable to find out the potential patterns of image, hence in this paper, a fast association rule mining algorithm is proposed and the similarity is represented by rules. More specifically, the proposed approach consist of the following steps: firstly, the gray level of image is compressed using linear segmentation to avoid interference of details and reduce the computation amount; then the compressed gray values between pixels are collected to generate the transaction sets which are transformed into the proposed multi-dimension data cube structure; the association rules are then fast mined based on multi-dimension data cube; finally the mined rules are represented as a vector and similarity assessment is achieved by vector comparison using first order approximation of Kullback-Leibler divergence. Experimental results indicate that the proposed fast association rule mining algorithm is more effective than the widely used Apriori method. The remote sensing image retrieval experiments using various images for example, QuickBird, WorldView-2, based on the existing and proposed similarity assessment show that the proposed method can provide higher retrieval precision.

  3. Gain ratio based fuzzy weighted association rule mining classifier for medical diagnostic interface

    Indian Academy of Sciences (India)

    N S Nithya; K Duraiswamy

    2014-02-01

    The health care environment still needs knowledge based discovery for handling wealth of data. Extraction of the potential causes of the diseases is the most important factor for medical data mining. Fuzzy association rule mining is wellperformed better than traditional classifiers but it suffers from the exponential growth of the rules produced. In the past, we have proposed an information gain based fuzzy association rule mining algorithm for extracting both association rules and membership functions of medical data to reduce the rules. It used a ranking based weight value to identify the potential attribute. When we take a large number of distinct values, the computation of information gain value is not feasible. In this paper, an enhanced approach, called gain ratio based fuzzy weighted association rule mining, is thus proposed for distinct diseases and also increase the learning time of the previous one. Experimental results show that there is a marginal improvement in the attribute selection process and also improvement in the classifier accuracy. The system has been implemented in Java platform and verified by using benchmark data from the UCI machine learning repository.

  4. Cross-Ontology multi-level association rule mining in the Gene Ontology.

    Directory of Open Access Journals (Sweden)

    Prashanti Manda

    Full Text Available The Gene Ontology (GO has become the internationally accepted standard for representing function, process, and location aspects of gene products. The wealth of GO annotation data provides a valuable source of implicit knowledge of relationships among these aspects. We describe a new method for association rule mining to discover implicit co-occurrence relationships across the GO sub-ontologies at multiple levels of abstraction. Prior work on association rule mining in the GO has concentrated on mining knowledge at a single level of abstraction and/or between terms from the same sub-ontology. We have developed a bottom-up generalization procedure called Cross-Ontology Data Mining-Level by Level (COLL that takes into account the structure and semantics of the GO, generates generalized transactions from annotation data and mines interesting multi-level cross-ontology association rules. We applied our method on publicly available chicken and mouse GO annotation datasets and mined 5368 and 3959 multi-level cross ontology rules from the two datasets respectively. We show that our approach discovers more and higher quality association rules from the GO as evaluated by biologists in comparison to previously published methods. Biologically interesting rules discovered by our method reveal unknown and surprising knowledge about co-occurring GO terms.

  5. Solution of Strain-Softening Surrounding Rock in Deep Tunnel Incorporating 3D Hoek-Brown Failure Criterion and Flow Rule

    Directory of Open Access Journals (Sweden)

    Jin-feng Zou

    2016-01-01

    Full Text Available In order to investigate the influence of the intermediate principal stress on the stress and displacement of surrounding rock, a novel approach based on 3D Hoek-Brown (H-B failure criterion was proposed. Taking the strain-softening characteristic of rock mass into account, the potential plastic zone is subdivided into a finite number of concentric annulus and a numerical procedure for calculating the stress and displacement of each annulus was presented. Strains were obtained based on the nonassociated and associated flow rule and 3D plastic potential function. Stresses were achieved by the stress equilibrium equation and generalized Hoek-Brown failure criterion. Using the proposed approach, we can get the solutions of the stress and displacement of the surrounding rock considering the intermediate principal stress. Moreover, the proposed approach was validated with the published results. Compared with the results based on generalized Hoek-Brown failure criterion, it is shown that the plastic radius calculated by 3D Hoek-Brown failure criterion is smaller than those solved by generalized H-B failure criterion, and the influences of dilatancy effect on the results based on the generalized H-B failure criterion are greater than those based on 3D H-B failure criterion. The displacements considering the nonassociated flow rule are smaller than those considering associated flow rules.

  6. SQL Based Association Rule Mining%基于SQL的关联规则挖掘

    Institute of Scientific and Technical Information of China (English)

    2004-01-01

    Data mining is becoming increasingly important since the size of database grows even larger and the need to explore hidden rules from the database becomes widely recognized. Currently database systems are dominated by relational database and the ability to perform data mining using standard SQL queries will definitely ease implementation of data mining. In this paper ,we introduce an association rule mining algorithm based on Apriori and the implementation using SQL. At the end of the paper ,we summarize the paper.

  7. A Novel Approach for Discovery Quantitative Fuzzy Multi-Level Association Rules Mining Using Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    Saad M. Darwish

    2016-10-01

    Full Text Available Quantitative multilevel association rules mining is a central field to realize motivating associations among data components with multiple levels abstractions. The problem of expanding procedures to handle quantitative data has been attracting the attention of many researchers. The algorithms regularly discretize the attribute fields into sharp intervals, and then implement uncomplicated algorithms established for Boolean attributes. Fuzzy association rules mining approaches are intended to defeat such shortcomings based on the fuzzy set theory. Furthermore, most of the current algorithms in the direction of this topic are based on very tiring search methods to govern the ideal support and confidence thresholds that agonize from risky computational cost in searching association rules. To accelerate quantitative multilevel association rules searching and escape the extreme computation, in this paper, we propose a new genetic-based method with significant innovation to determine threshold values for frequent item sets. In this approach, a sophisticated coding method is settled, and the qualified confidence is employed as the fitness function. With the genetic algorithm, a comprehensive search can be achieved and system automation is applied, because our model does not need the user-specified threshold of minimum support. Experiment results indicate that the recommended algorithm can powerfully generate non-redundant fuzzy multilevel association rules.

  8. Temperature-flow regulation rule in indirect connection heating system and its energy-saving contrast analysis

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    Primary and secondary networks are treated as a whole in indirect heating systems, and an advanced new temperature-flow regulation method is presented whose flow ratio is greater than 60% in a secondary network and 30% in a primary network when under a partial load. Through deducing and optimizing an exponential function flow regulation rule, the formulae of flow regulation and the supply and return water temperatures are obtained, and their relevant curves are plotted. After comparison, it is found that this control method has a huge energy conservation space, and it should therefore be generalized soon.

  9. Mining Association Rules to Evade Network Intrusion in Network Audit Data

    Directory of Open Access Journals (Sweden)

    Kamini Nalavade

    2014-06-01

    Full Text Available With the growth of hacking and exploiting tools and invention of new ways of intrusion, intrusion detection and prevention is becoming the major challenge in the world of network security. The increasing network traffic and data on Internet is making this task more demanding. There are various approaches being utilized in intrusion detections, but unfortunately any of the systems so far is not completely flawless. The false positive rates make it extremely hard to analyse and react to attacks. Intrusion detection systems using data mining approaches make it possible to search patterns and rules in large amount of audit data. In this paper, we represent a model to integrate association rules to intrusion detection to design and implement a network intrusion detection system. Our technique is used to generate attack rules that will detect the attacks in network audit data using anomaly detection. This shows that the modified association rules algorithm is capable of detecting network intrusions. The KDD dataset which is freely available online is used for our experimentation and results are compared. Our intrusion detection system using association rule mining is able to generate attack rules that will detect the attacks in network audit data using anomaly detection, while maintaining a low false positive rate.

  10. 加权模糊关联规则的研究%Research on Weighted Fuzzy Association Rules

    Institute of Scientific and Technical Information of China (English)

    陆建江

    2003-01-01

    Algorithms for mining quantitative association rules consider each attribute equally, but the attributes usu-ally have different importance. Two kinds of algorithms for mining the weighted fuzzy association rules are providedwith respect to two kinds of database. The first algorithm can effectively consider the importance of quantitative at-tributes, and considers that the importance of association rule is not increased with the amount of attributes in therule. The second algorithm not only considers the importance of quantitative attributes, but also considers that theimportance of association rule is increased with the amount of attributes in the rule.

  11. DoS detections based on association rules and frequent itemsets

    Institute of Scientific and Technical Information of China (English)

    George S Oreku; LI Jian-zhong; Fredrick J Mtenzi

    2008-01-01

    To detect the DoS in networks by applying association rules mining techniques, we propose that asso-ciation rules and frequent itemsets can be employed to find DoS pattern in packet streams which describe trafficand user behaviors. The method extracts information from the log analysis of submitted packets using the algo-rithm which depends on the definition of the intrusion. Large itemsets were extracted to represent the super facts to build the association analysis for the intrusion. Network data files were analysed for experiments. The analy-sis and experimental results are encouraging with better performance as packet frequency number increases.

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

    Directory of Open Access Journals (Sweden)

    Yang Ou

    2014-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Juryon Paik

    2014-07-01

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

  14. Design a Weight Based sorting distortion algorithm using Association rule Hiding for Privacy Preserving Data mining

    Directory of Open Access Journals (Sweden)

    R.Sugumar

    2011-12-01

    Full Text Available The security of the large database that contains certain crucial information, it will become a serious issue when sharing data to the network against unauthorized access. Privacy preserving data mining is a new research trend in privacy data for data mining and statistical database. Association analysis is a powerful tool for discovering relationships which are hidden in large database. Association rules hiding algorithms get strong an efficient performance for protecting confidential and crucial data. Data modification and rule hiding is one of the most important approaches for secure data. The objective of the proposed Weight Based Sorting Distortion (WBSD algorithm is to distort certain data which satisfies a particular sensitive rule. Then hide those transactions which support a sensitive rule and assigns them a priority and sorts them in ascending order according to the priority value of each rule. Then it uses these weights to compute the priority value for each transaction according to how weak the rule is that a transaction supports. Data distortion is one of the important methods to avoid this kind of scalability issues

  15. Objective novelty of association rules: measuring the confidence boost

    OpenAIRE

    Balcázar Navarro, José Luis

    2010-01-01

    On sait bien que la confiance des régles d’association n’est pas vraiment satisfaisant comme mésure d’interêt. Nous proposons, au lieu de la substituer par des autres mésures (soit, en l’employant de façon conjointe a des autres mésures), évaluer la nouveauté de chaque régle par comparaison de sa confiance par rapport á des régles plus fortes qu’on trouve au même ensemble de données. C’est á dire, on considère un seuil “relative” de confiance au lieu du seuil absolute habituel. Cette idée se ...

  16. A comparative study of applying Mason’s Rule in the case of flow-graphs and bond-graphs

    Directory of Open Access Journals (Sweden)

    Adriana Grava

    2009-05-01

    Full Text Available The paper presents two methods to analyzethe electric circuits using the flow-graphs and thebond-graphs studying the differences between thesemethods.As it can be noticed, the two methods are totallydifferent; their common point being Mason’s rule thatis applied in both cases but it is applied differently foreach type of graphs.

  17. Generalization-based discovery of spatial association rules with linguistic cloud models

    Institute of Scientific and Technical Information of China (English)

    杨斌; 田永青; 朱仲英

    2004-01-01

    Extraction of interesting and general spatial association rules from large spatial databases is an important task in the development of spatial database systems. In this paper, we investigate the generalization-based knowledge discovery mechanism that integrates attribute-oriented induction on nonspatial data and spatial merging and generalization on spatial data. Furthermore, we present linguistic cloud models for knowledge representation and uncertainty handling to enhance current generalization-based method. With these models, spatial and nonspatial attribute values are well generalized at higher-concept levels, allowing discovery of strong spatial association rules. Combining the cloud model based generalization method with Apriori algorithm for mining association rules from a spatial database shows the benefits in effectiveness and flexibility.

  18. Patterns Exploration on Patterns of Empirical Herbal Formula of Chinese Medicine by Association Rules.

    Science.gov (United States)

    Huang, Li; Yuan, Jiamin; Yang, Zhimin; Xu, Fuping; Huang, Chunhua

    2015-01-01

    In this study, we use association rules to explore the latent rules and patterns of prescribing and adjusting the ingredients of herbal decoctions based on empirical herbal formula of Chinese Medicine (CM). The consideration and development of CM prescriptions based on the knowledge of CM doctors are analyzed. The study contained three stages. The first stage is to identify the chief symptoms to a specific empirical herbal formula, which can serve as the key indication for herb addition and cancellation. The second stage is to conduct a case study on the empirical CM herbal formula for insomnia. Doctors will add extra ingredients or cancel some of them by CM syndrome diagnosis. The last stage of the study is to divide the observed cases into the effective group and ineffective group based on the assessed clinical effect by doctors. The patterns during the diagnosis and treatment are selected by the applied algorithm and the relations between clinical symptoms or indications and herb choosing principles will be selected by the association rules algorithm. Totally 40 patients were observed in this study: 28 patients were considered effective after treatment and the remaining 12 were ineffective. 206 patterns related to clinical indications of Chinese Medicine were checked and screened with each observed case. In the analysis of the effective group, we used the algorithm of association rules to select combinations between 28 herbal adjustment strategies of the empirical herbal formula and the 190 patterns of individual clinical manifestations. During this stage, 11 common patterns were eliminated and 5 major symptoms for insomnia remained. 12 association rules were identified which included 5 herbal adjustment strategies. The association rules method is an effective algorithm to explore the latent relations between clinical indications and herbal adjustment strategies for the study on empirical herbal formulas.

  19. Efficiency and acceptance of new water allocation rules - The case of an agricultural water users association.

    Science.gov (United States)

    Goetz, Renan U; Martínez, Yolanda; Xabadia, Àngels

    2017-12-01

    Water scarcity is one of the major environmental problems in Southern Europe. High levels of water stress and increasing frequency of droughts, along with a greater environmental protection, make it necessary to design water management strategies that are allocative efficient and balance supply and demand. When functioning markets cannot be developed, the allocation rules proposed in the literature of social choice have been recognized as a suitable alternative. However, the application of new water allocation rules can be impaired by a lack of acceptance and implementation problems. This paper examines these obstacles for the case of an agricultural water users association (WUA), situated in the basin of the River Ebro, in relation to the governance structure and collective decision rule of the WUA. It analyzes the extent to which the gains and losses of the farmers affect their acceptance, and examines conditions for building agreements with side payments that provide incentives for the majority of the farmers to form part of a possible agreement. The results show that the uniform and sequential rules improve the allocative efficiency under normal conditions compared to the status quo and the sequential rule even in the case of droughts. In the presence of side payments this rule is likely to be accepted and has only an insignificant impact on distributional inequality. Copyright © 2017 Elsevier B.V. All rights reserved.

  20. A New Approach of Using Association Rule Mining in Customer Complaint Management

    Directory of Open Access Journals (Sweden)

    Behrouz Minaei-Bidgoli

    2010-09-01

    Full Text Available A new approach of using data mining tools for customer complaint management is presented in this paper. The association rule mining technique is applied to discover the relationship between different groups of citizens and different kinds of complainers. The data refers to citizens' complaints from the performance of municipality of Tehran, the capital of Iran. Analyzing these rules, make it possible for the municipality managers to find out the causes of complaints, so, it leads to facilitate engineering changes accordingly. The idea of contrast association rules is also applied to identify the attributes characterizing patterns of complaints occurrence among various groups of citizens. The results would enable the municipality to optimize its services.

  1. A Method for Hiding Association rules with Minimum Changes in Database

    Directory of Open Access Journals (Sweden)

    Zahra Sheykhinezhad

    Full Text Available Privacy preserving data mining is a continues way for to use data mining, without disclosing private information. To prevent disclosure of sensitive information by data mining techniques, it is necessary to make changes to the data base. Association rules ...

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

    Science.gov (United States)

    Lei, Wu; Qing, Fang; Zhou, Jin

    2016-01-01

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

  3. The Books Recommend Service System Based on Improved Algorithm for Mining Association Rules

    Institute of Scientific and Technical Information of China (English)

    王萍

    2009-01-01

    The Apriori algorithm is a classical method of association rules mining. Based on analysis of this theory, the paper provides an improved Apriori algorithm. The paper puts foward with algorithm combines HASH table technique and reduction of candidate item sets to en-hance the usage efficiency of resources as well as the individualized service of the data library.

  4. An Associate Rules Mining Algorithm Based on Artificial Immune Network for SAR Image Segmentation

    Directory of Open Access Journals (Sweden)

    Mengling Zhao

    2015-01-01

    Full Text Available As a computational intelligence method, artificial immune network (AIN algorithm has been widely applied to pattern recognition and data classification. In the existing artificial immune network algorithms, the calculating affinity for classifying is based on calculating a certain distance, which may lead to some unsatisfactory results in dealing with data with nominal attributes. To overcome the shortcoming, the association rules are introduced into AIN algorithm, and we propose a new classification algorithm an associate rules mining algorithm based on artificial immune network (ARM-AIN. The new method uses the association rules to represent immune cells and mine the best association rules rather than searching optimal clustering centers. The proposed algorithm has been extensively compared with artificial immune network classification (AINC algorithm, artificial immune network classification algorithm based on self-adaptive PSO (SPSO-AINC, and PSO-AINC over several large-scale data sets, target recognition of remote sensing image, and segmentation of three different SAR images. The result of experiment indicates the superiority of ARM-AIN in classification accuracy and running time.

  5. MIDClass: microarray data classification by association rules and gene expression intervals.

    Directory of Open Access Journals (Sweden)

    Rosalba Giugno

    Full Text Available We present a new classification method for expression profiling data, called MIDClass (Microarray Interval Discriminant CLASSifier, based on association rules. It classifies expressions profiles exploiting the idea that the transcript expression intervals better discriminate subtypes in the same class. A wide experimental analysis shows the effectiveness of MIDClass compared to the most prominent classification approaches.

  6. Challenges associated with privacy in health care industry: implementation of HIPAA and the security rules.

    Science.gov (United States)

    Choi, Young B; Capitan, Kathleen E; Krause, Joshua S; Streeper, Meredith M

    2006-02-01

    This paper discusses the challenges associated with privacy in health care in the electronic information age based on the Health Insurance Portability and Accountability Act (HIPAA) and the Security Rules. We examine the storing and transmission of sensitive patient data in the modem health care system and discuss current security practices that health care providers institute to comply with HIPAA Security Rule regulations. Based on our research results, we address current outstanding issues that act as impediments to the successful implementation of security measures and conclude the discussion and offer possible avenues of future research.

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

    Directory of Open Access Journals (Sweden)

    A.O. Ogunde

    2015-11-01

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

  8. Multidimensional Data Mining to Determine Association Rules in an Assortment of Granularities

    Directory of Open Access Journals (Sweden)

    C. Usha Rani

    2013-09-01

    Full Text Available Data Mining is one of the most significant tools for discovering association patterns that are useful for many knowledge domains. Yet, there are some drawbacks in existing mining techniques. The three main weaknesses of current data- mining techniques are: 1 rescanning of the entire database must be done whenever new attributes are added because current methods are based on flat mining using predefined schemata. 2 An association rule may be true on a certain granularity but fail on a smaller ones and vise verse. This may result in loss of important association rules. 3 Current methods can only be used to find either frequent rules or infrequent rules, but not both at the same time. This research proposes a novel data schema and an algorithm that solves the above weaknesses while improving on the efficiency and effectiveness of data mining strategies. Crucial mechanisms in each step will be clarified in this paper. This paper also presents a benchmark which is used to compare the level of efficiency and effectiveness of the proposed algorithm against other known methods. Finally, this paper presents experimental results regarding efficiency, scalability, information loss, etc. of the proposed approach to prove its advantages.

  9. Impact of polymer film thickness and cavity size on polymer flow during embossing : towards process design rules for nanoimprint lithography.

    Energy Technology Data Exchange (ETDEWEB)

    Schunk, Peter Randall; King, William P. (Georgia Institute of Technology, Atlanta, GA); Sun, Amy Cha-Tien; Rowland, Harry D. (Georgia Institute of Technology, Atlanta, GA)

    2006-08-01

    This paper presents continuum simulations of polymer flow during nanoimprint lithography (NIL). The simulations capture the underlying physics of polymer flow from the nanometer to millimeter length scale and examine geometry and thermophysical process quantities affecting cavity filling. Variations in embossing tool geometry and polymer film thickness during viscous flow distinguish different flow driving mechanisms. Three parameters can predict polymer deformation mode: cavity width to polymer thickness ratio, polymer supply ratio, and Capillary number. The ratio of cavity width to initial polymer film thickness determines vertically or laterally dominant deformation. The ratio of indenter width to residual film thickness measures polymer supply beneath the indenter which determines Stokes or squeeze flow. The local geometry ratios can predict a fill time based on laminar flow between plates, Stokes flow, or squeeze flow. Characteristic NIL capillary number based on geometry-dependent fill time distinguishes between capillary or viscous driven flows. The three parameters predict filling modes observed in published studies of NIL deformation over nanometer to millimeter length scales. The work seeks to establish process design rules for NIL and to provide tools for the rational design of NIL master templates, resist polymers, and process parameters.

  10. E-commerce Website Recommender System Based on Dissimilarity and Association Rule

    Directory of Open Access Journals (Sweden)

    MingWang Zhang

    2013-07-01

    Full Text Available By analyzing the current electronic commerce recommendation algorithm analysis, put forward a kind to use dissimilarity clustering and association recommendation algorithm, the algorithm realized web website shopping user data clustering by use of the dissimilarity, and then use the association rules algorithm for clustering results of association recommendation, experiments show that the algorithm compared with traditional clustering association algorithm of iteration times decrease, improve operational efficiency, to prove the method by use of the actual users purchase the recommended, and evidence of the effectiveness of the algorithm in recommendation.  

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

    Science.gov (United States)

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

    2017-09-01

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

  12. The effects of age on associative and rule-based causal learning and generalization.

    Science.gov (United States)

    Mutter, Sharon A; Plumlee, Leslie F

    2014-06-01

    We assessed how age influences associative and rule-based processes in causal learning using the Shanks and Darby (1998) concurrent patterning discrimination task. In Experiment 1, participants were divided into groups based on their learning performance after 6 blocks of training trials. High discrimination mastery young adults learned the patterning discrimination more rapidly and accurately than moderate mastery young adults. They were also more likely to induce the patterning rule and use this rule to generate predictions for novel cues, whereas moderate mastery young adults were more likely to use cue similarity as the basis for their predictions. Like moderate mastery young adults, older adults used similarity-based generalization for novel cues, but they did not achieve the same level of patterning discrimination. In Experiment 2, young and older adults were trained to the same learning criterion. Older adults again showed deficits in patterning discrimination and, in contrast to young adults, even when they reported awareness of the patterning rule, they used only similarity-based generalization in their predictions for novel cues. These findings suggest that it is important to consider how the ability to code or use cue representations interacts with the requirements of the causal learning task. In particular, age differences in causal learning seem to be greatest for tasks that require rapid coding of configural representations to control associative interference between similar cues. Configural coding may also be related to the success of rule-based processes in these types of learning tasks. PsycINFO Database Record (c) 2014 APA, all rights reserved.

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

    CERN Document Server

    Maier, G; Kranzlmueller, D; Gaidioz, B

    2010-01-01

    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

  14. Data Mining Framework for Generating Sales Decision Making Information Using Association Rules

    OpenAIRE

    Md. Humayun Kabir

    2016-01-01

    The rapid technological development in the field of information and communication technology (ICT) has enabled the databases of super shops to be organized under a countrywide sales decision making network to develop intelligent business systems by generating enriched business policies. This paper presents a data mining framework for generating sales decision making information from sales data using association rules generated from valid user input item set with respect to the sales data unde...

  15. Efficient Mining of Association Rules by Reducing the Number of Passes over the Database

    Institute of Scientific and Technical Information of China (English)

    李庆忠; 王海洋; 闫中敏; 马绍汉

    2001-01-01

    This paper introduces a new algorithm of mining association rules.The algorithm RP counts the itemsets with different sizes in the same pass of scanning over the database by dividing the database into m partitions. The total number of passes over the database is only (k+2m-2)/m, where k is the longest size in the itemsets. It is much less than k.

  16. Identification of the Patterns Behavior Consumptions by Using Chosen Tools of Data Mining - Association Rules

    OpenAIRE

    R. Benda Prokeinová; J. Paluchová

    2014-01-01

    The research and development in sustainable environment, that is a subject of research goal of many various countries and food producers, now, it has a long tradition. The research aim of this paper allows for an identification of the patterns behaviour consumptions by using of association rules, because of knowledge ́s importance of segmentation differences between consumers and their opinions on current sustainable tendencies. The research area of sustainability will be in Slovakia stil...

  17. An Associate Rules Mining Algorithm Based on Artificial Immune Network for SAR Image Segmentation

    OpenAIRE

    Mengling Zhao; Hongwei Liu

    2015-01-01

    As a computational intelligence method, artificial immune network (AIN) algorithm has been widely applied to pattern recognition and data classification. In the existing artificial immune network algorithms, the calculating affinity for classifying is based on calculating a certain distance, which may lead to some unsatisfactory results in dealing with data with nominal attributes. To overcome the shortcoming, the association rules are introduced into AIN algorithm, and we propose a new class...

  18. Hybrid Medical Image Classification Using Association Rule Mining with Decision Tree Algorithm

    OpenAIRE

    Rajendran, P.; M.Madheswaran

    2010-01-01

    The main focus of image mining in the proposed method is concerned with the classification of brain tumor in the CT scan brain images. The major steps involved in the system are: pre-processing, feature extraction, association rule mining and hybrid classifier. The pre-processing step has been done using the median filtering process and edge features have been extracted using canny edge detection technique. The two image mining approaches with a hybrid manner have been proposed in this paper....

  19. Studies on Application of Mining Association Rules algorithm in Storage Location Configuration

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    How to reduce in and out motion distance and improve work efficiency is not only the key question of logistics storage & distribution center, but also a primary factor in improving competitive power of enterprise . In view of this question, the method of using mining association rules to resolve the problem of storage location configuration was put forward in this article with the purpose of improving work efficiency.

  20. A LFP-tree based method for association rules mining in telecommunication alarm correlation analysis

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    The mining of association rules is one of the primary methods used in telecommunication alarm correlation analysis,of which the alarm databases are very large.The efficiency of the algorithms plays an important role in tackling with large datasets. The classical frequent pattern growth(FP-growth) algorithm can produce a large number of conditional pattern trees which made it difficult to mine association rules in are telecommunication environment.In this paper,an algorithm based on layered frequent pattern tree(LFP-tree) is proposed for mining frequent patterns. Efficiency of this alagorithm is achieved with following techniques:1) All the frequent patterns are condensed into a layered structure,which can save memory time but also be very useful for updating the alarm databases.2) Each alarm item can be viewed as a triple,in which t is a Boolean vaviable that shows the item frequent or not.3) Deleting infrequent items with dynamic pruning can avoid produce conditional pattern sets. Simulation and analysis of algorithm show that it is a valid method with better time and space efficiency,which is adapted to mine association rules in telecommunication alarm correlation analysis.

  1. Investigate the Performance of Document Clustering Approach Based on Association Rules Mining

    Directory of Open Access Journals (Sweden)

    Noha Negm

    2013-09-01

    Full Text Available The challenges of the standard clustering methods and the weaknesses of Apriori algorithm in frequent termset clustering formulate the goal of our research. Based on Association Rules Mining, an efficient approach for Web Document Clustering (ARWDC has been devised. An efficient Multi-Tire Hashing Frequent Termsets algorithm (MTHFT has been used to improve the efficiency of mining association rules by targeting improvement in mining of frequent termset. Then, the documents are initially partitioned based on association rules. Since a document usually contains more than one frequent termset, the same document may appear in multiple initial partitions, i.e., initial partitions are overlapping. After making partitions disjoint, the documents are grouped within the partition using descriptive keywords, the resultant clusters are obtained effectively. In this paper, we have presented an extensive analysis of the ARWDC approach for different sizes of Reuters datasets. Furthermore the performance of our approach is evaluated with the help of evaluation measures such as, Precision, Recall and F-measure compared to the existing clustering algorithms like Bisecting K-means and FIHC. The experimental results show that the efficiency, scalability and accuracy of the ARWDC approach has been improved significantly for Reuters datasets.

  2. Multi-Scaling Sampling: An Adaptive Sampling Method for Discovering Approximate Association Rules

    Institute of Scientific and Technical Information of China (English)

    Cai-Yan Jia; Xie-Ping Gao

    2005-01-01

    One of the obstacles of the efficient association rule mining is the explosive expansion of data sets since it is costly or impossible to scan large databases, esp., for multiple times. A popular solution to improve the speed and scalability of the association rule mining is to do the algorithm on a random sample instead of the entire database. But how to effectively define and efficiently estimate the degree of error with respect to the outcome of the algorithm, and how to determine the sample size needed are entangling researches until now. In this paper, an effective and efficient algorithm is given based on the PAC (Probably Approximate Correct) learning theory to measure and estimate sample error. Then, a new adaptive, on-line, fast sampling strategy - multi-scaling sampling - is presented inspired by MRA (Multi-Resolution Analysis) and Shannon sampling theorem, for quickly obtaining acceptably approximate association rules at appropriate sample size. Both theoretical analysis and empirical study have showed that the sampling strategy can achieve a very good speed-accuracy trade-off.

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

    Science.gov (United States)

    De Angelis, Marco; Marín Puchades, Víctor; Fraboni, Federico; Pietrantoni, Luca

    2017-01-01

    The factors associated with severity of the bicycle crashes may differ across different bicycle crash patterns. Therefore, it is important to identify distinct bicycle crash patterns with homogeneous attributes. The current study aimed at identifying subgroups of bicycle crashes in Italy and analyzing separately the different bicycle crash types. The present study focused on bicycle crashes that occurred in Italy during the period between 2011 and 2013. We analyzed categorical indicators corresponding to the characteristics of infrastructure (road type, road signage, and location type), road user (i.e., opponent vehicle and cyclist’s maneuver, type of collision, age and gender of the cyclist), vehicle (type of opponent vehicle), and the environmental and time period variables (time of the day, day of the week, season, pavement condition, and weather). To identify homogenous subgroups of bicycle crashes, we used latent class analysis. Using latent class analysis, the bicycle crash data set was segmented into 19 classes, which represents 19 different bicycle crash types. Logistic regression analysis was used to identify the association between class membership and severity of the bicycle crashes. Finally, association rules were conducted for each of the latent classes to uncover the factors associated with an increased likelihood of severity. Association rules highlighted different crash characteristics associated with an increased likelihood of severity for each of the 19 bicycle crash types. PMID:28158296

  4. A Review of Protein-DNA Binding Motif using Association Rule Mining

    Directory of Open Access Journals (Sweden)

    Virendra Kumar Tripathi

    2013-03-01

    Full Text Available The survival of gene regulation and life mechanisms is pre-request of finding unknown pattern of transcription factor binding sites. The discovery motif of gene regulation in bioinformatics is challenging jobs for getting relation between transcription factors and transcription factor binding sites. The increasing size and length of string pattern of motif is issued a problem related to modeling and optimization of gene selection process. In this paper we give a survey of protein-DNA binding using association rule mining. Association rule mining well known data mining technique for pattern analysis. The capability of negative and positive pattern generation help full for discovering of new pattern in DNA binding bioinformatics data. The other data mining approach such as clustering and classification also applied the process of gene selection grouping for known and unknown pattern. But faced a problem of valid string of DNA data, the rule mining principle find a better relation between transcription factors and transcription factor binding sites.

  5. Multi-objective Genetic Algorithm for Association Rule Mining Using a Homogeneous Dedicated Cluster of Workstations

    Directory of Open Access Journals (Sweden)

    S. Dehuri

    2006-01-01

    Full Text Available This study presents a fast and scalable multi-objective association rule mining technique using genetic algorithm from large database. The objective functions such as confidence factor, comprehensibility and interestingness can be thought of as different objectives of our association rule-mining problem and is treated as the basic input to the genetic algorithm. The outcomes of our algorithm are the set of non-dominated solutions. However, in data mining the quantity of data is growing rapidly both in size and dimensions. Furthermore, the multi-objective genetic algorithm (MOGA tends to be slow in comparison with most classical rule mining methods. Hence, to overcome these difficulties we propose a fast and scalability technique using the inherent parallel processing nature of genetic algorithm and a homogeneous dedicated network of workstations (NOWs. Our algorithm exploit both data and control parallelism by distributing the data being mined and the population of individuals across all available processors. The experimental result shows that the algorithm has been found suitable for large database with an encouraging speed up.

  6. Violations of exhibiting and FDA rules at an American Psychiatric Association annual meeting.

    Science.gov (United States)

    Lurie, Peter; Tran, Tung; Wolfe, Sidney Manuel; Goodman, Robert

    2005-12-01

    We conducted a cross-sectional study of all exhibit booths for the 24 pharmaceutical companies at the 2002 American Psychiatric Association (APA) convention. We collected and categorized one of each item distributed by the companies at each booth. A total of 268 items were collected from 24 companies (median=8). The most common categories of items were "reprints or pamphlets" (37%) and "noneducational gifts" (27%), including music CDs and invitations to dinners and museums. There were a total of 16 violations of the APA's own exhibit rules: eight companies had one violation and two companies had four violations. Four companies engaged in FDA-prohibited off-label promotion; one also violated the APA code. Over half of all companies (54%) were in violation of either APA rules or FDA regulations. The APA's voluntary code has failed to adequately reduce inappropriate promotional activity at the annual APA meeting.

  7. The Stability of Memory Rules Associative with the Mathematical Thinking Core

    Directory of Open Access Journals (Sweden)

    Xiuzhen Wang

    2011-02-01

    Full Text Available Activation of how and where arithmetic operations are displayed in the brain has been observed in various number-processing tasks. However, it remains poorly understood whether stabilized memory of Boolean rules are associated with background knowledge. The present study reviewed behavioral and imaging evidence demonstrating that Boolean problem-solving abilities depend on the core systems of number-processing. The core systems account for a mathematical cultural background, and serve as the foundation for sophisticated mathematical knowledge. The Ebbinghaus paradigm was used to investigate learning-induced changes by functional magnetic resonance imaging (fMRI in a retrieval task of Boolean rules. Functional imaging data revealed a common activation pattern in the left inferior parietal lobule and left inferior frontal gyrus during all Boolean tasks, which has been used for number-processing processing in former studies. All other regional activations were tasks-specific and prominently distributed in the left thalamus, bilateral parahippocampal gyrus, bilateral occipital lobe, and other subcortices during contrasting stabilized memory retrieval of Boolean tasks and number-processing tasks. The present results largely verified previous studies suggesting that activation patterns due to number-processing appear to reflect a basic anatomical substrate of stability of Boolean rules memory, which are derived from a network originally related to the core systems of number-processing.

  8. Flow Structure Associated with Hemodialysis Catheters

    Science.gov (United States)

    Foust, Jason

    2005-11-01

    Insertion of a hemodialysis catheter into the superior vena cava (SVC) gives rise to complex flow patterns, which arise from the simultaneous injection and extraction of blood through different holes (ports) of the catheter. Techniques of high-image-density particle image velocimetry are employed in a scaled-up water facility. This approach allows characterization of both the instantaneous and time-averaged flow structure due to generic classes of side hole geometries. The trajectory of the injection jet is related to the ratio of the initial jet velocity to the mainstream velocity through the SVC, and to the type of distortion of the jet cross-section. Furthermore, the mean and fluctuating velocity and vorticity fields are determined. Significant turbulent stresses develop rapidly in the injection jet, which can impinge upon the wall of the simulated SVC. Immediately downstream of the injection hole, a recirculation cell of low velocity exists adjacent to the catheter surface. These and other representations of the flow structure are first evaluated for a steady throughflow, then for the case of a pulsatile waveform in the SVC, which matches that of a normal adult.

  9. 一种新的关联规则挖掘的模型%A New Model of Mining Association Rules

    Institute of Scientific and Technical Information of China (English)

    苏毅娟; 严小卫

    2001-01-01

    A new algorithm for mining positive and negative association rules is presented. A new confi-dence is constructed to measure the uncertainty of an association rule based on the probability theory and Piatetsky-Shapiro′s model.

  10. Could parental rules play a role in the association between short sleep and obesity in young children?

    Science.gov (United States)

    Jones, Caroline H D; Pollard, Tessa M; Summerbell, Carolyn D; Ball, Helen

    2014-05-01

    Short sleep duration is associated with obesity in young children. This study develops the hypothesis that parental rules play a role in this association. Participants were 3-year-old children and their parents, recruited at nursery schools in socioeconomically deprived and non-deprived areas of a North-East England town. Parents were interviewed to assess their use of sleep, television-viewing and dietary rules, and given diaries to document their child's sleep for 4 days/5 nights. Children were measured for height, weight, waist circumference and triceps and subscapular skinfold thicknesses. One-hundred and eight families participated (84 with complete sleep data and 96 with complete body composition data). Parental rules were significantly associated together, were associated with longer night-time sleep and were more prevalent in the non-deprived-area compared with the deprived-area group. Television-viewing and dietary rules were associated with leaner body composition. Parental rules may in part confound the association between night-time sleep duration and obesity in young children, as rules cluster together across behavioural domains and are associated with both sleep duration and body composition. This hypothesis should be tested rigorously in large representative samples.

  11. ADAPTIVE ASSOCIATION RULE MINING BASED CROSS LAYER INTRUSION DETECTION SYSTEM FOR MANET

    Directory of Open Access Journals (Sweden)

    V. Anjana Devi

    2011-10-01

    Full Text Available Mobile ad-hoc wireless networks (MANET are a significant area of research with many applications.MANETs are more vulnerable to malicious attack. Authentication and encryption techniques can be usedas the first line of defense for reducing the possibilities of attacks. Alternatively, these approaches haveseveral demerits and designed for a set of well known attacks. This paper proposes a cross layer intrusiondetection architecture to discover the malicious nodes and different types of DoS attacks by exploiting theinformation available across different layers of protocol stack in order to improve the accuracy ofdetection. This approach uses a fixed width clustering algorithm for efficient detection of the anomalies inthe MANET traffic and also for detecting newer attacks generated . In the association process, theAdaptive Association Rule mining algorithm is utilized. This helps to overcome the more time taken forperforming the association process.

  12. Multi-agent-based modeling for extracting relevant association rules using a multi-criteria analysis approach

    Directory of Open Access Journals (Sweden)

    Addi Ait-Mlouk

    2016-06-01

    Full Text Available Abstract Recently, association rule mining plays a vital role in knowledge discovery in database. In fact, in most cases, the real datasets lead to a very large number of rules, which do not allow users to make their own selection of the most relevant. The difficult task is mining useful and non-redundant rules. Several approaches have been proposed, such as rule clustering, informative cover method and quality measurements. Another way to selecting relevant association rules, we believe that it is necessary to integrate a decisional approach within the knowledge discovery process. Therefore, in this paper, we propose an approach to discover a category of relevant association rules based on multi-criteria analysis. In other side, the general process of association rules extraction becomes more and more complex, to solve such problem, we also proposed a multi-agent system for modeling the different process of our proposed approach. Therefore, we conclude our work by an empirical study applied to a set of banking data to illustrate the performance of our approach.

  13. An Optimized Distributed Association Rule Mining Algorithm in Parallel and Distributed Data Mining with XML Data for Improved Response Time

    OpenAIRE

    Sujni Paul

    2010-01-01

    Many current data mining tasks can be accomplished successfully only in a distributed setting. The field of distributed data mining has therefore gained increasing importance in the last decade. The Apriori algorithm by Rakesh Agarwal has emerged as one of the best Association Rule mining algorithms. Ii also serves as the base algorithm for most parallel algorithms. The enormity and high dimensionality of datasets typically available as input to problem of association rule discovery, makes it...

  14. A Study of Frequent Cyclic Association Rule%经常性周期关联规则的研究

    Institute of Scientific and Technical Information of China (English)

    黄益民

    2000-01-01

    One of the most intportant data mining problems is mining association rules. In this paper,we considered the problem of founding frequent cyclic association rules. By exploiting the relationship between cycles and large itemsets,we identified optimization techniques that allow us to minimize the unnecessary amount of work performed during the data mining process. Furthermore,we demonstrated the effectiveness of these methods through a series of experiments.

  15. Rule-Based Multidisciplinary Tool for Unsteady Reacting Real-Fluid Flows Project

    Data.gov (United States)

    National Aeronautics and Space Administration — A design and analysis computational tool is proposed for simulating unsteady reacting flows in combustor devices used in reusable launch vehicles. Key aspects...

  16. Polypharmacy in older adults: Association Rule and Frequent-Set Analysis to evaluate concomitant medication use.

    Science.gov (United States)

    Held, Fabian; Le Couteur, David G; Blyth, Fiona M; Hirani, Vasant; Naganathan, Vasi; Waite, Louise M; Seibel, Markus J; Handelsman, David J; Cumming, Robert G; Allore, Heather G; Gnjidic, Danijela

    2017-02-01

    The aim of this study was to apply Association Rule and Frequent-Set analysis, and novel means of data visualisation to ascertain patterns of medication use and medication combinations contributing to medication group clusters according to geriatric syndrome status in older adults. Participants were community-dwelling men (aged ≥70 years, n=1686), Sydney, Australia. Medication exposure was categorised at medication class level and data were analysed according to geriatric syndrome status (presence of at least one syndrome including frailty, falls, cognitive impairment and urinary incontinence). Association Rule and Frequent-Set analysis were performed to identify "interesting" patterns of medication combinations that occur together. This analysis involves advanced computer algorithms that investigated all possible combinations of medications in the dataset in order to identify those which are observed more or much less frequently than expected. Frequent-Set Analysis demonstrated one unexpected medication combination, antiulcer and antidiabetic medications (3.5% of participants) in the overall population (n=1687). Frequency of medication combinations was similar in participants with (n=666) and without (n=1020) geriatric syndromes. Among participants with geriatric syndromes, the most frequent combinations included antigout with lipid-lowering agents (5.7%) followed by angiotensin II and diuretics combination (22%). This novel methodology can be used to detect common medication combinations overall by data visualisation, and against specific adverse drug reactions such as geriatric syndromes. This methodology may be a valuable pharmacovigilance approach to monitor large databases for the safety of medications.

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

    Science.gov (United States)

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

    2011-09-21

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

  18. A Chaotic Home Environment Accounts for the Association between Respect for Rules Disposition and Reading Comprehension: A Twin Study.

    Science.gov (United States)

    Taylor, Jeanette; Hart, Sara A

    2014-10-01

    This study examined the association between socioemotional dispositions from the developmental propensity model and reading comprehension and whether those associations could be accounted for by level of chaos in the home. Data from 342 monozygotic and 333 same-sex dizygotic twin pairs age 7-13 years were used. A parent rated the twins on sympathy, respect for rules, negative emotionality, and daring and level of chaos in the twins' home. Reading comprehension was measured using a state-wide school assessment. Only respect for rules significantly and uniquely predicted reading comprehension. Biometric models indicated that respect for rules was positively associated with reading comprehension via the shared environment and home chaos accounted for a significant amount of that shared environmental variance even after controlling for family income. Children with higher respect for rules have better reading comprehension scores in school and this relationship owes partly to the level of chaos in the family home.

  19. The speed of learning instructed stimulus-response association rules in human: experimental data and model.

    Science.gov (United States)

    Bugmann, Guido; Goslin, Jeremy; Duchamp-Viret, Patricia

    2013-11-01

    Humans can learn associations between visual stimuli and motor responses from just a single instruction. This is known to be a fast process, but how fast is it? To answer this question, we asked participants to learn a briefly presented (200ms) stimulus-response rule, which they then had to rapidly apply after a variable delay of between 50 and 1300ms. Participants showed a longer response time with increased variability for short delays. The error rate was low and did not vary with the delay, showing that participants were able to encode the rule correctly in less than 250ms. This time is close to the fastest synaptic learning speed deemed possible by diffusive influx of AMPA receptors. Learning continued at a slower pace in the delay period and was fully completed in average 900ms after rule presentation onset, when response latencies dropped to levels consistent with basic reaction times. A neural model was proposed that explains the reduction of response times and of their variability with the delay by (i) a random synaptic learning process that generates weights of average values increasing with the learning time, followed by (ii) random crossing of the firing threshold by a leaky integrate-and-fire neuron model, and (iii) assuming that the behavioural response is initiated when all neurons in a pool of m neurons have fired their first spike after input onset. Values of m=2 or 3 were consistent with the experimental data. The proposed model is the simplest solution consistent with neurophysiological knowledge. Additional experiments are suggested to test the hypothesis underlying the model and also to explore forgetting effects for which there were indications for the longer delay conditions. This article is part of a Special Issue entitled Neural Coding 2012.

  20. DMET-Miner: Efficient discovery of association rules from pharmacogenomic data.

    Science.gov (United States)

    Agapito, Giuseppe; Guzzi, Pietro H; Cannataro, Mario

    2015-08-01

    Microarray platforms enable the investigation of allelic variants that may be correlated to phenotypes. Among those, the Affymetrix DMET (Drug Metabolism Enzymes and Transporters) platform enables the simultaneous investigation of all the genes that are related to drug absorption, distribution, metabolism and excretion (ADME). Although recent studies demonstrated the effectiveness of the use of DMET data for studying drug response or toxicity in clinical studies, there is a lack of tools for the automatic analysis of DMET data. In a previous work we developed DMET-Analyzer, a methodology and a supporting platform able to automatize the statistical study of allelic variants, that has been validated in several clinical studies. Although DMET-Analyzer is able to correlate a single variant for each probe (related to a portion of a gene) through the use of the Fisher test, it is unable to discover multiple associations among allelic variants, due to its underlying statistic analysis strategy that focuses on a single variant for each time. To overcome those limitations, here we propose a new analysis methodology for DMET data based on Association Rules mining, and an efficient implementation of this methodology, named DMET-Miner. DMET-Miner extends the DMET-Analyzer tool with data mining capabilities and correlates the presence of a set of allelic variants with the conditions of patient's samples by exploiting association rules. To face the high number of frequent itemsets generated when considering large clinical studies based on DMET data, DMET-Miner uses an efficient data structure and implements an optimized search strategy that reduces the search space and the execution time. Preliminary experiments on synthetic DMET datasets, show how DMET-Miner outperforms off-the-shelf data mining suites such as the FP-Growth algorithms available in Weka and RapidMiner. To demonstrate the biological relevance of the extracted association rules and the effectiveness of the

  1. Adaptive Interval Configuration to Enhance Dynamic Approach for Mining Association Rules

    Institute of Scientific and Technical Information of China (English)

    1999-01-01

    Most proposed algorithms for mining association rules follow the conventional le vel-wise approach. The dynamic candidate generation idea introduced in the dyna mic itemset counting (DIC) a lgorithm broke away from the level-wise limitation which could find the large i t emsets using fewer passes over the database than level-wise algorithms. However , the dynamic approach is very sensitive to the data distribution of the database and it requires a proper interval size. In this paper an optimization technique named adaptive interval configuration (AIC) has been developed to enhance the d y namic approach. The AIC optimization has the following two functions. The first is that a homogeneous distribution of large itemsets over intervals can be achie ved so that less unnecessary candidates could be generated and less database sca nning passes are guaranteed. The second is that the near optimal interval size c ould be determined adaptively to produce the best response time. We also develop ed a candidate pruning technique named virtual partition pruning to reduce the s ize-2 candidate set and incorporated it into the AIC optimization. Based on the optimization technique, we proposed the efficient AIC algorithm for mining asso c iation rules. The algorithms of AIC, DIC and the classic Apriori were implemente d on a Sun Ultra Enterprise 4000 for performance comparison. The results show th at the AIC performed much better than both DIC and Apriori, and showed a strong robustness.

  2. [Exploration on eighteen incompatible medicaments of chest pain prescriptions based on association rules mining].

    Science.gov (United States)

    Zhang, Yuhua; Hua, Haoming; Fan, Xinsheng; Wang, Chongjun; Duan, Jinao

    2011-12-01

    To investigate the laws of eighteen incompatible medicaments of the chest pain prescriptions based on association rules mining. The database of chest pain prescription was established and then the chest pain prescriptions composed of eighteen incompatible medicaments were screened. The dynasty, couplet medicines, the property and flavor of drugs and preparation form were analyzed with the frequent item sets and corresponding analysis methods. Eight hundred and fifty chest pain prescriptions were collected, and 88 of them contained eighteen incompatible medicaments, taking 10.3% of all; the applications of ancient and modern chest pain prescriptions containing eighteen incompatible medicaments are significant difference (P dynasty and tang dynasty, are more often used than the modern formulas. The most common anti-drugs is on the Fuzi-Pinellia, Chuanwu-Pinellia; the property and flavor of drugs is bitter cold most closely; the decoction of the formulas is mostly used. Eighteen incompatible medicaments account for about ten percent of the chest pain prescription, not an uncommon side. There are certain rules for application of anti-drug compatibility to treat chest pain.

  3. Influence analysis of flow rule in mine fire during injecting inert gases

    Institute of Scientific and Technical Information of China (English)

    NIU Hui-yong; WANG Hai-qiao

    2011-01-01

    According to the action law of gas flow during injecting inert gases as the research main line,and hydromechanics and thermodynamics theories,the characteristic of gas delamination that was caused by injecting inert gases to closed fire zone was analyzed.The criterion was brought forward,which could scale disappearing probability of turbulent state.Formation mechanism of gas layer in turbulent state was discussed primarily.Simultaneously,the condition was pointed out,which could make the gas in turbulent state by injecting different gases.The mathematical model about dynamic changes of oxygen and methane concentration in the process of injecting gases was erected.The mixture mechanism about injecting different flow inert gases and flammable gas layer in closed fire zone was revealed.

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

    Directory of Open Access Journals (Sweden)

    So Hyun Park

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

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

    CERN Document Server

    Martin, A; Venkatesan, Dr V Prasanna

    2011-01-01

    Today in every organization financial analysis provides the basis for understanding and evaluating the results of business operations and delivering how well a business is doing. This means that the organizations can control the operational activities primarily related to corporate finance. One way that doing this is by analysis of bankruptcy prediction. This paper develops an ontological model from financial information of an organization by analyzing the Semantics of the financial statement of a business. One of the best bankruptcy prediction models is Altman Z-score model. Altman Z-score method uses financial rations to predict bankruptcy. From the financial ontological model the relation between financial data is discovered by using data mining algorithm. By combining financial domain ontological model with association rule mining algorithm and Zscore model a new business intelligence model is developed to predict the bankruptcy.

  6. Customer Requirements Mapping Method Based on Association Rule Mining for Mass Customization

    Institute of Scientific and Technical Information of China (English)

    XIA Shi-sheng; WANG Li-ya

    2008-01-01

    Customer requirements analysis is the key step for product variety design of mass customiza-tion(MC). Quality function deployment (QFD) is a widely used management technique for understanding thevoice of the customer (VOC), however, QFD depends heavily on human subject judgment during extractingcustomer requirements and determination of the importance weights of customer requirements. QFD pro-cess and related problems are so complicated that it is not easily used. In this paper, based on a generaldata structure of product family, generic bill of material (CBOM), association rules analysis was introducedto construct the classification mechanism between customer requirements and product architecture. The newmethod can map customer requirements to the items of product family architecture respectively, accomplishthe mapping process from customer domain to physical domain directly, and decrease mutual process betweencustomer and designer, improve the product design quality, and thus furthest satisfy customer needs. Finally,an example of customer requirements mapping of the elevator cabin was used to illustrate the proposed method.

  7. WEB-BASED DATA MINING TOOLS : PERFORMING FEEDBACK ANALYSIS AND ASSOCIATION RULE MINING

    Directory of Open Access Journals (Sweden)

    Pratiyush Guleria

    2015-11-01

    Full Text Available This paper aims to explain the web-enabled tools for educational data mining. The proposed web-based tool developed using Asp.Net framework and php can be helpful for universities or institutions providing the students with elective courses as well improving academic activities based on feedback collected from students. In Asp.Net tool, association rule mining using Apriori algorithm is used whereas in php based Feedback Analytical Tool, feedback related to faculty and institutional infrastructure is collected from students and based on that Feedback it shows performance of faculty and institution. Using that data, it helps management to improve in-house training skills and gains knowledge about educational trends which is to be followed by faculty to improve the effectiveness of the course and teaching skills.

  8. Text Classification using Association Rule with a Hybrid Concept of Naive Bayes Classifier and Genetic Algorithm

    CERN Document Server

    Kamruzzaman, S M; Hasan, Ahmed Ryadh

    2010-01-01

    Text classification is the automated assignment of natural language texts to predefined categories based on their content. Text classification is the primary requirement of text retrieval systems, which retrieve texts in response to a user query, and text understanding systems, which transform text in some way such as producing summaries, answering questions or extracting data. Now a day the demand of text classification is increasing tremendously. Keeping this demand into consideration, new and updated techniques are being developed for the purpose of automated text classification. This paper presents a new algorithm for text classification. Instead of using words, word relation i.e. association rules is used to derive feature set from pre-classified text documents. The concept of Naive Bayes Classifier is then used on derived features and finally a concept of Genetic Algorithm has been added for final classification. A system based on the proposed algorithm has been implemented and tested. The experimental ...

  9. An Overview of Secure Mining of Association Rules in Horizontally Distributed Databases

    Directory of Open Access Journals (Sweden)

    Sonal Patil

    2015-10-01

    Full Text Available In this paper, propose a protocol for secure mining of association rules in horizontally distributed databases. Now a day the current leading protocol is Kantarcioglu and Clifton. This protocol is based on the Fast Distributed Mining (FDM algorithm which is an unsecured distributed version of the Apriori algorithm. The main ingredients in this protocol are two novel secure multi-party algorithms 1. That computes the union of private subsets that each of the interacting players hold, and 2. Tests the inclusion of an element held by one player in a subset held by another. In this protocol offers enhanced privacy with respect to the other one. Differences in this protocol, it is simpler and is significantly more efficient in terms of communication rounds, communication cost and computational cost [1].

  10. Cerebral Arteriovenous Malformation Flow Is Associated With Venous Intimal Hyperplasia.

    Science.gov (United States)

    Shakur, Sophia F; Hussein, Ahmed E; Amin-Hanjani, Sepideh; Valyi-Nagy, Tibor; Charbel, Fady T; Alaraj, Ali

    2017-04-01

    The pathogenesis of venous intimal hyperplasia and venous outflow stenosis associated with cerebral arteriovenous malformation (AVM) draining veins is poorly understood. We sought to determine the relationship between maximum vein wall thickness and AVM flow. Patients who underwent AVM surgical resection and had flow measured before treatment using quantitative magnetic resonance angiography were retrospectively reviewed. Specimens were mounted on slides and stained with elastin special stain. Perinidal veins were identified, and maximum wall thickness was measured from digitized images. Relationship between maximum vein wall thickness and AVM flow was assessed. Twenty-eight patients were included. Spearman correlation revealed a statistically significant relationship between maximum vein wall thickness and total AVM flow (ρ=+0.51; P=0.006), AVM flow per draining vein (ρ=+0.41; P=0.03), and mean intranidal vessel diameter (ρ=+0.39; P=0.04). Maximum vein wall thickness increases with higher total AVM flow and AVM flow per draining vein. This finding implicates chronically high AVM inflow in venous intimal hyperplasia. © 2017 American Heart Association, Inc.

  11. Knowledge discovery and sequence-based prediction of pandemic influenza using an integrated classification and association rule mining (CBA) algorithm.

    Science.gov (United States)

    Kargarfard, Fatemeh; Sami, Ashkan; Ebrahimie, Esmaeil

    2015-10-01

    Pandemic influenza is a major concern worldwide. Availability of advanced technologies and the nucleotide sequences of a large number of pandemic and non-pandemic influenza viruses in 2009 provide a great opportunity to investigate the underlying rules of pandemic induction through data mining tools. Here, for the first time, an integrated classification and association rule mining algorithm (CBA) was used to discover the rules underpinning alteration of non-pandemic sequences to pandemic ones. We hypothesized that the extracted rules can lead to the development of an efficient expert system for prediction of influenza pandemics. To this end, we used a large dataset containing 5373 HA (hemagglutinin) segments of the 2009 H1N1 pandemic and non-pandemic influenza sequences. The analysis was carried out for both nucleotide and protein sequences. We found a number of new rules which potentially present the undiscovered antigenic sites at influenza structure. At the nucleotide level, alteration of thymine (T) at position 260 was the key discriminating feature in distinguishing non-pandemic from pandemic sequences. At the protein level, rules including I233K, M334L were the differentiating features. CBA efficiently classifies pandemic and non-pandemic sequences with high accuracy at both the nucleotide and protein level. Finding hotspots in influenza sequences is a significant finding as they represent the regions with low antibody reactivity. We argue that the virus breaks host immunity response by mutation at these spots. Based on the discovered rules, we developed the software, "Prediction of Pandemic Influenza" for discrimination of pandemic from non-pandemic sequences. This study opens a new vista in discovery of association rules between mutation points during evolution of pandemic influenza.

  12. Kinetic Monte Carlo simulations of one-dimensional and two-dimensional traffic flows: Comparison of two look-ahead rules

    Science.gov (United States)

    Sun, Yi; Timofeyev, Ilya

    2014-05-01

    We employ an efficient list-based kinetic Monte Carlo (KMC) method to study traffic flow models on one-dimensional (1D) and two-dimensional (2D) lattices based on the exclusion principle and Arrhenius microscopic dynamics. This model implements stochastic rules for cars' movements based on the configuration of the traffic ahead of each car. In particular, we compare two different look-ahead rules: one is based on the distance from the car under consideration to the car in front of it, and the other one is based on the density of cars ahead. The 1D numerical results of these two rules suggest different coarse-grained macroscopic limits in the form of integro-differential Burgers equations. The 2D results of both rules exhibit a sharp phase transition from freely flowing to fully jammed, as a function of the initial density of cars. However, the look-ahead rule based on the density of the traffic produces more realistic results. The KMC simulations reported in this paper are compared with those from other well-known traffic flow models and the corresponding empirical results from real traffic.

  13. Effect of overpasses in the Biham-Middleton-Levine traffic flow model with random and parallel update rule

    Science.gov (United States)

    Ding, Zhong-Jun; Jiang, Rui; Gao, Zi-You; Wang, Bing-Hong; Long, Jiancheng

    2013-08-01

    The effect of overpasses in the Biham-Middleton-Levine traffic flow model with random and parallel update rules has been studied. An overpass is a site that can be occupied simultaneously by an eastbound car and a northbound one. Under periodic boundary conditions, both self-organized and random patterns are observed in the free-flowing phase of the parallel update model, while only the random pattern is observed in the random update model. We have developed mean-field analysis for the moving phase of the random update model, which agrees with the simulation results well. An intermediate phase is observed in which some cars could pass through the jamming cluster due to the existence of free paths in the random update model. Two intermediate states are observed in the parallel update model, which have been ignored in previous studies. The intermediate phases in which the jamming skeleton is only oriented along the diagonal line in both models have been analyzed, with the analyses agreeing well with the simulation results. With the increase of overpass ratio, the jamming phase and the intermediate phases disappear in succession for both models. Under open boundary conditions, the system exhibits only two phases when the ratio of overpasses is below a threshold in the random update model. When the ratio of the overpass is close to 1, three phases could be observed, similar to the totally asymmetric simple exclusion process model. The dependence of the average velocity, the density, and the flow rate on the injection probability in the moving phase has also been obtained through mean-field analysis. The results of the parallel model under open boundary conditions are similar to that of the random update model.

  14. Rules for confidence intervals of permeability coefficients for water flow in over-broken rock mass

    Institute of Scientific and Technical Information of China (English)

    Liu Weiqun; Fei Xiaodong; Fang Jingnian

    2012-01-01

    Based on the steady-state seepage method,we used the Mechanical Testing and Simulation 815.02 System and a self-designed seepage instrument for over-broken stone to measure seepage properties of water flows in three types of crushed rock samples.Three methods of confidence interval in describing permeability coefficients are presented:the secure interval,the calculated interval and the systemic interval.The lower bound of the secure interval can be applied to water-inrush and the upper bound can solve the problem of connectivity.For the calculated interval,as the axial pressure increases,the length of confidence interval is shortened and the upper and lower bounds are reduced.For the systemic interval,the length of its confidence interval,as well as the upper and lower bounds,clearly vary under low axial pressure but are fairly similar under high axial pressure.These three methods provide useful information and references for analyzing the permeability coefficient of over-broken rock.

  15. 75 FR 1426 - National Futures Association; Notice of Filing and Immediate Effectiveness of Proposed Rule...

    Science.gov (United States)

    2010-01-11

    ... advertising of security futures products. The NFA believes the proposed rule change accomplishes this by... From the Federal Register Online via the Government Publishing Office SECURITIES AND EXCHANGE... Section 19b(7) of the Securities Exchange Act of 1934 (``Act''),\\1\\ and Rule 19b-7 under the...

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

    Directory of Open Access Journals (Sweden)

    Frances Meeten

    2016-11-01

    Full Text Available Excessive and uncontrollable worry is a defining feature of Generalized Anxiety Disorder. An important endeavor in the treatment of pathological worry is to understand why some people are unable to stop worrying once they have started. Worry perseveration is associated with a tendency to deploy goal-directed worry rules (known as ‘as many as can’ worry rules; AMA. These require attention to the goal of the worry task and continuation of worry until the aims of the ‘worry bout’ are achieved. This study examined the association between the tendency to use AMA worry rules and neural and autonomic responses to a perseverative cognition induction. To differentiate processes underlying AMA worry rule use from trait worry, we also examined the relationship between scores on the Penn State Worry Questionnaire and neural and autonomic responses following the same induction. We used resting-state functional magnetic resonance brain imaging while measuring emotional bodily arousal from heart rate variability (where decreased HRV indicates stress-related parasympathetic withdrawal in 19 patients with GAD and 21 control participants. Seed-based analyses were conducted to quantify brain changes in functional connectivity with the amygdala. The tendency to adopt an AMA worry rule was associated with validated measures of worry, anxiety, depression, and rumination. AMA worry rule endorsement predicted a stronger decrease in HRV and was positively associated with increased connectivity between right amygdala and locus coeruleus, a brainstem noradrenergic projection nucleus. Higher AMA scores were also associated with increased connectivity between amygdala and rostral superior frontal gyrus. Higher PSWQ scores amplified decreases in functional connectivity between right amygdala and subcallosal cortex, bilateral inferior frontal gyrus, middle frontal gyrus, and areas of parietal cortex. Our results identify neural mechanisms underlying the deployment of

  17. 结合SOM的关联规则挖掘研究%Research on association rule based on SOM

    Institute of Scientific and Technical Information of China (English)

    景波; 刘莹; 陈耿

    2014-01-01

    为了实现在海量数据中的审计线索的快速发现,通过数据挖掘FMA算法对被审数据和审计专家经验库进行关联规则快速提取;再利用自组织神经网络改良CLARANS算法对审计专家经验库抽取的规则划分出相似规则群;然后通过对被审单位关联规则集合和专家经验的相似规则群进行相对强弱、趋近率和价值率的比较,最终得到审计线索集合。%In order to achieve the audit trail of the massive data quickly found through data mining FMA algorithms to quickly extract trial data and audit expertise library association rules;re-use of self-organizing neural network improved CLARANS algorithm to extract audit expertise library divide a similar rule base rules;then by trial set of association rules and expert experience similar rules group relative strength, the approach value and the different rate of comparing the resulting set of audit trail.

  18. PMCR-Miner: parallel maximal confident association rules miner algorithm for microarray data set.

    Science.gov (United States)

    Zakaria, Wael; Kotb, Yasser; Ghaleb, Fayed F M

    2015-01-01

    The MCR-Miner algorithm is aimed to mine all maximal high confident association rules form the microarray up/down-expressed genes data set. This paper introduces two new algorithms: IMCR-Miner and PMCR-Miner. The IMCR-Miner algorithm is an extension of the MCR-Miner algorithm with some improvements. These improvements implement a novel way to store the samples of each gene into a list of unsigned integers in order to benefit using the bitwise operations. In addition, the IMCR-Miner algorithm overcomes the drawbacks faced by the MCR-Miner algorithm by setting some restrictions to ignore repeated comparisons. The PMCR-Miner algorithm is a parallel version of the new proposed IMCR-Miner algorithm. The PMCR-Miner algorithm is based on shared-memory systems and task parallelism, where no time is needed in the process of sharing and combining data between processors. The experimental results on real microarray data sets show that the PMCR-Miner algorithm is more efficient and scalable than the counterparts.

  19. Associated rules between microstructure characterization parameters and contact characteristic parameters of two cylinders

    Institute of Scientific and Technical Information of China (English)

    周炜; 唐进元; 何艳飞; 廖东日

    2015-01-01

    The contact strength calculation of two curved rough surfaces is a forefront issue of Hertz contact theory and method. Associated rules between rough surface characterization parameters(correlation length, and root mean square deviation) and contact characteristic parameters(contact area, maximum contact pressure, contact number, and contact width) of two rough cylinders are mainly studied. The contact model of rough cylinders is deduced based on GW model. As there is no analytical solution for the pressure distribution equation, an approximate iterative solution method for the pressure distribution is adopted. Furthermore, the quantitative relationships among the correlation length, the root mean square deviation, the asperity radius of curvature and the asperity density are also obtained based on a numerical simulation method. The maximum contact pressure and the contact number decrease with the increase of correlation length, while the contact width and the contact area are on the contrary. The contact width increases with the increase of root mean square deviation while the maximum contact pressure, the contact area and the contact number decrease.

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

    Directory of Open Access Journals (Sweden)

    Nidhi Kushwaha

    2014-11-01

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

  1. An improved predictive association rule based classifier using gain ratio and T-test for health care data diagnosis

    Indian Academy of Sciences (India)

    M Nandhini; S N Sivanandam

    2015-09-01

    Health care data diagnosis is a significant task that needs to be executed precisely, which requires much experience and domain-knowledge. Traditional symptoms-based disease diagnosis may perhaps lead to false presumptions. In recent times, Associative Classification (AC), the combination of association rule mining and classification has received attention in health care applications which desires maximum accuracy. Though several AC techniques exist, they lack in generating quality rules for building efficient associative classifier. This paper aims to enhance the accuracy of the existing CPAR (Classification based on Predictive Association Rule) algorithm by generating quality rules using Gain Ratio. Mostly, health care applications deal with high dimensional datasets. Existence of high dimensions causes unfair estimates in disease diagnosis. Dimensionality reduction is commonly applied as a preprocessing step before classification task to improve classifier accuracy. It eliminates redundant and insignificant dimensions by keeping good ones without information loss. In this work, dimensionality reductions by T-test and reduct sets (or simply reducts) are performed as preprocessing step before CPAR and CPAR using Gain Ratio (CPAR-GR) algorithms. An investigation was also performed to determine the impact of T-test and reducts on CPAR and CPAR-GR. This paper synthesizes the existing work carried out in AC, and also discusses the factors that influence the performance of CPAR and CPAR-GR. Experiments were conducted using six health care datasets from UCI machine learning repository. Based on the experiments, CPAR-GR with T-test yields better classification accuracy than CPAR.

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

    Science.gov (United States)

    Cyr, André; Boukadoum, Mounir

    2013-03-01

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

  3. Data-flow Analysis of Programs with Associative Arrays

    Directory of Open Access Journals (Sweden)

    David Hauzar

    2014-05-01

    Full Text Available Dynamic programming languages, such as PHP, JavaScript, and Python, provide built-in data structures including associative arrays and objects with similar semantics—object properties can be created at run-time and accessed via arbitrary expressions. While a high level of security and safety of applications written in these languages can be of a particular importance (consider a web application storing sensitive data and providing its functionality worldwide, dynamic data structures pose significant challenges for data-flow analysis making traditional static verification methods both unsound and imprecise. In this paper, we propose a sound and precise approach for value and points-to analysis of programs with associative arrays-like data structures, upon which data-flow analyses can be built. We implemented our approach in a web-application domain—in an analyzer of PHP code.

  4. Detachment and flow cytometric quantification of seagrass-associated bacteria.

    Science.gov (United States)

    Trevathan-Tackett, Stacey; Macreadie, Peter; Ralph, Peter; Seymour, Justin

    2014-07-01

    A new protocol was developed to detach bacteria from seagrass tissue and subsequently enumerate cells using flow cytometry (FCM). A method involving addition of the surfactant Tween 80 and vortexing resulted in maximum detachment efficiency of seagrass attached bacteria, providing a robust protocol for precisely enumerating seagrass-associated bacteria with FCM. Using this approach we detected cell concentrations between 2.0×10(5) and 8.0×10(6)cells mg(-1) DW tissue.

  5. Rules for Scoring Respiratory Events in Sleep: Update of the 2007 AASM Manual for the Scoring of Sleep and Associated Events

    Science.gov (United States)

    Berry, Richard B.; Budhiraja, Rohit; Gottlieb, Daniel J.; Gozal, David; Iber, Conrad; Kapur, Vishesh K.; Marcus, Carole L.; Mehra, Reena; Parthasarathy, Sairam; Quan, Stuart F.; Redline, Susan; Strohl, Kingman P.; Ward, Sally L. Davidson; Tangredi, Michelle M.

    2012-01-01

    The American Academy of Sleep Medicine (AASM) Sleep Apnea Definitions Task Force reviewed the current rules for scoring respiratory events in the 2007 AASM Manual for the Scoring and Sleep and Associated Events to determine if revision was indicated. The goals of the task force were (1) to clarify and simplify the current scoring rules, (2) to review evidence for new monitoring technologies relevant to the scoring rules, and (3) to strive for greater concordance between adult and pediatric rules. The task force reviewed the evidence cited by the AASM systematic review of the reliability and validity of scoring respiratory events published in 2007 and relevant studies that have appeared in the literature since that publication. Given the limitations of the published evidence, a consensus process was used to formulate the majority of the task force recommendations concerning revisions. The task force made recommendations concerning recommended and alternative sensors for the detection of apnea and hypopnea to be used during diagnostic and positive airway pressure (PAP) titration polysomnography. An alternative sensor is used if the recommended sensor fails or the signal is inaccurate. The PAP device flow signal is the recommended sensor for the detection of apnea, hypopnea, and respiratory effort related arousals (RERAs) during PAP titration studies. Appropriate filter settings for recording (display) of the nasal pressure signal to facilitate visualization of inspiratory flattening are also specified. The respiratory inductance plethysmography (RIP) signals to be used as alternative sensors for apnea and hypopnea detection are specified. The task force reached consensus on use of the same sensors for adult and pediatric patients except for the following: (1) the end-tidal PCO2 signal can be used as an alternative sensor for apnea detection in children only, and (2) polyvinylidene fluoride (PVDF) belts can be used to monitor respiratory effort (thoracoabdominal belts

  6. Multi-objective Numeric Association Rules Mining via Ant Colony Optimization for Continuous Domains without Specifying Minimum Support and Minimum Confidence

    Directory of Open Access Journals (Sweden)

    Parisa Moslehi

    2011-09-01

    Full Text Available Currently, all search algorithms which use discretization of numeric attributes for numeric association rule mining, work in the way that the original distribution of the numeric attributes will be lost. This issue leads to loss of information, so that the association rules which are generated through this process are not precise and accurate. Based on this fact, algorithms which can natively handle numeric attributes would be interesting. Since association rule mining can be considered as a multi-objective problem, rather than a single objective one, a new multi-objective algorithm for numeric association rule mining is presented in this paper, using Ant Colony Optimization for Continuous domains (ACOR. This algorithm mines numeric association rules without any need to specify minimum support and minimum confidence, in one step. In order to do this we modified ACOR for generating rules. The results show that we have more precise and accurate rules after applying this algorithm and the number of rules is more than the ones resulted from previous works.

  7. [A method to enhance user experience of EMR based on mining association rules of incremental updating data].

    Science.gov (United States)

    Zhou, Bao-zhuo; Li, Chuan-fu; Dai, Liang-liang; Feng, Huan-qing

    2009-03-01

    The user experience (EX) of current Electronic Medical Record systems (EMR) is needed to improve. This paper proposed a new method to enhance EX of EMR. Firstly, system template and text characterization are used to make the EMR data structured. Then, the structured date are mined based on mining the association rules of incremental updating data to find the association of the elements of template of EMR and the values of elements. Finally, with the help of mined results, the users of EMR are able to input data effectively and quickly.

  8. Plasma Flows Associated with Two Kink-Unstable Flux Ropes

    Science.gov (United States)

    DeHaas, Timothy; Gekelman, W.; Van Compernolle, B.

    2013-07-01

    Magnetic flux ropes are self-organized, magnetized plasma structures embedded in an ambient medium. Their structure consists of helical field lines which vary in pitch due to the electric current flowing along a background magnetic field.1 Multiple braided flux ropes have been observed in the solar corona, and their unraveling is theorized to be the signature of magnetic reconnection.2 Two flux ropes (L=10 m, A=7 cm2, J=10 amp/cm2) were created in the Large Plasma Device (LAPD) at UCLA (Bo=330 G, no = 1012 cm-3, Te=4eV, Ar). The flux ropes are highly kink unstable, which cause the ropes to twist and oscillate at frequencies associated with shear Alfven waves. Through the use of a six-faced Mach probe, volumetric data was taken to determine the three-dimensional plasma flow. Volumetric b-field information was also obtained through use of a three-axis magnetic probe. The data collected from these probes is laden with Lorentzian pulses, a characteristic of deterministic chaos.3 The flux ropes are shown to twist, interact, then merge; while the plasma flows are shown to spiral around the two flux ropes in a singular O-point. A quasi-separatrix layer (QSL) forms as the flux ropes collide and the magnetic field lines reconnect. The relationship between flow and reconnection sites is explored. 1Gekelman, W. et al. ApJ 753, 131 2Cirtain, J.W. et al. Nature 493, 501-503 (2013) 3Maggs, J.E. et al. Phys. Rev. Lett. 107, 185003 (2011)

  9. Targeting Association Rule Mining Without Support Constraint%无支持度约束的靶向式关联规则挖掘

    Institute of Scientific and Technical Information of China (English)

    李凯里; 王立宏

    2012-01-01

    Some concepts such as all attribute itemset, absolute association rule, key antecedent of association rule are proposed to solve information annihilating problem caused by the combination explosive of itemset in associated rules mining without support. This paper proves an important theory, the association rule with the antecedent of key antecedent's super set must be absolute association rule, and it is upward closure. Based on this principle, a targeting association rule mining algorithm is designed to eliminate redundancy association rule significantly. Through an instance, the feasibility and effectiveness of the algorithm are verified.%为解决不考虑支持度时关联规则挖掘中数据项集组合爆炸引起的信息湮灭问题,给出全属性项目集、完全关联规则、关联规则的关键前提等概念.证明以关键前提的超集作为前提的关联规则也一定是完全关联规则,即向上闭合特性.根据该原理设计一个能够消除大量冗余关联规则的靶向式关联规则挖掘算法.通过挖掘实例验证了该算法的可行性和有效性.

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

    Science.gov (United States)

    Tian, Yangge; Bian, Fuling

    2007-06-01

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

  11. In Vivo Flow Cytometry of Circulating Tumor-Associated Exosomes

    Directory of Open Access Journals (Sweden)

    Jacqueline Nolan

    2016-01-01

    Full Text Available Circulating tumor cells (CTCs demonstrated the potential as prognostic markers of metastatic development. However, the incurable metastasis can already be developed at the time of initial diagnosis with the existing CTC assays. Alternatively, tumor-associated particles (CTPs including exosomes can be a more valuable prognostic marker because they can be released from the primary tumor long before CTCs and in larger amount. However, little progress has been made in high sensitivity detection of CTPs, especially in vivo. We show here that in vivo integrated photoacoustic (PA and fluorescence flow cytometry (PAFFC platform can provide the detection of melanoma and breast-cancer-associated single CTPs with endogenously expressed melanin and genetically engineered proteins or exogenous dyes as PA and fluorescent contrast agents. The two-beam, time-of-light PAFFC can measure the sizes of CTCs and CTPs and identify bulk and rolling CTCs and CTC clusters, with no influence on blood flow instability. This technique revealed a higher concentration of CTPs than CTCs at an early cancer stage. Because a single tumor cell can release many CTPs and in vivo PAFFC can examine the whole blood volume, PAFFC diagnostic platform has the potential to dramatically improve (up to 105-fold the sensitivity of cancer diagnosis.

  12. Association between restless leg syndrom and slow coronary flow.

    Science.gov (United States)

    Erden, İsmail; Çakcak Erden, Emine; Durmuş, Hacer; Tıbıllı, Hakan; Tabakçı, Mustafa; Kalkan, Mehmet Emin; Türker, Yasin; Akçakoyun, Mustafa

    2014-11-01

    Restless legs syndrome (RLS) is a common sleep disorder in which patients feel unpleasent leg sensations and urge to move the legs during rest, especially at night, and symptoms are improved by leg movement. Prior studies analyzing the associations between cardiovascular disease and restless legs syndrome has shown controversial results. The goal of the study was to estimate the relationship between restless legs syndrome and slow coronary flow (SCF). The present study was cross-sectional and observational and consists of 176 individuals who underwent coronary angiography and had angiographically normal coronary arteries of varying coronary flow rates. The study included 86 patients with isolated SCF and 90 control participants with normal coronary flow (NCF). RLS was assessed the day after the coronry flow was evaluated, using a self-administered questionnaire based on the International Restless Legs Study Group criteria. The following question was asked: "Do you have unpleasant leg sensations (like crawling, paraesthesia, or pain) combined with motor restlessness and an urge to move?" The possible responses were as follows: no, less than once/month, 2-4 times/month, 5-14 times/month, and 15 or more times per month. Those who answered that they had these feelings were asked the following two more questions: 1) "Do these symptoms occur only at rest and does moving improve them?" and 2) "Are these symptoms worsen in the evening/at night compared with the morning?" RLS is considered to be probable if the participant has answered "yes" for all three of the above questions, and has a frequency of ≥5 times/month. Student's t-test, Mann-Whitney U test, multiple logistic regression analysis were used for statistical analysis. The prevalence of restless legs syndrome was 48 (27%) and increased significantly with age. Patients with SCF have more likely had RLS than the control group (p<0.001). The age-adjusted prevalence odds of SCF were 3.11 times higher (95% CI: 1

  13. 基于领域知识的冗余关联规则消除算法%Elimination algorithm of redundant rules in association rules mining based on domain knowledge

    Institute of Scientific and Technical Information of China (English)

    张晶; 张斌; 胡学钢

    2011-01-01

    Many association rule mining algorithms have been developed to extract interesting patterns from large databases. However, a large amount of knowledge explicitly represented in domain knowledge(DK) has not been used to reduce the number of association rules. A significant number of well known dependences are unnecessarily extracted by association rule mining algorithrns, which results in the generation of hundreds or thousands of non-interesting association rules. This paper presents a DKARM algorithm, which takes both database and relative DK into account, to eliminate all associations explicitly represented in DK. Experiments on the proposed algorithm show the significant reduction of the number of rules and the elimination of non-interesting rules.%关联规则挖掘算法用于从大型数据库中提取感兴趣的规则,然而,在领域知识中已经能清晰表示的知识并没有被充分考虑,关联规则挖掘算法提取的规则中包含了大量已知的关联性,从而产生了很多冗余规则.文章提出一种算法DKARM,同时考虑了数据本身以及相关的领域知识,以消除在领域知识中清晰表示的已知关联性.实验表明,该算法合理消除了冗余规则,有效降低了规则数目.

  14. Processing of audiovisual associations in the human brain: dependency on expectations and rule complexity

    Directory of Open Access Journals (Sweden)

    Riikka eLindström

    2012-05-01

    Full Text Available In order to respond to environmental changes appropriately, the human brain must not only be able to detect environmental changes but also to form expectations of forthcoming events. The events in the external environment often have a number of multisensory features such as pitch and form. For integrated percepts of objects and events, crossmodal processing and crossmodally induced expectations of forthcoming events are needed. The aim of the present study was to determine whether the expectations created by visual stimuli can modulate the deviance detection in the auditory modality, as reflected by auditory event-related potentials (ERPs. Additionally, it was studied whether the complexity of the rules linking auditory and visual stimuli together affects this process. The N2 deflection of the ERP was observed in response to violations in the subjects' expectation of a forthcoming tone. Both temporal aspects and cognitive demands during the audiovisual deviance detection task modulated the brain processes involved.

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

    Science.gov (United States)

    Cottrell, Randall R; Cooper, Hanna

    2009-07-01

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

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

    Directory of Open Access Journals (Sweden)

    Piontkivska Helen

    2009-07-01

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

  17. A Set Operation Based Algorithm for Association Rules Mining%基于集合运算的关联规则采掘算法

    Institute of Scientific and Technical Information of China (English)

    铁治欣; 陈奇; 俞瑞钊

    2001-01-01

    Mining association rules are an important data mining problem. In this paper ,an association rules mining algorithm,ARDBSO,which is based on set operation,is given. It can find all large itemsets in the database while only scan the database once. So,the time for I/O is reduced enormously and the efficiency of ARDBSO is improved. The experiments show that the efficiency of ARDBSO is 80~ 150times of Apriori's.

  18. Analysis of Medical Domain Using CMARM: Confabulation Mapreduce Association Rule Mining Algorithm for Frequent and Rare Itemsets

    Directory of Open Access Journals (Sweden)

    Dr. Jyoti Gautam

    2015-11-01

    Full Text Available In Human Life span, disease is a major cause of illness and death in the modern society. There are various factors that are responsible for diseases like work environment, living and working conditions, agriculture and food production, housing, unemployment, individual life style etc. The early diagnosis of any disease that frequently and rarely occurs with the growing age can be helpful in curing the disease completely or to some extent. The long-term prognosis of patient records might be useful to find out the causes that are responsible for particular diseases. Therefore, human being can take early preventive measures to minimize the risk of diseases that may supervene with the growing age and hence increase the life expectancy chances. In this paper, a new CMARM: Confabulation-MapReduce based association rule mining algorithm is proposed for the analysis of medical data repository for both rare and frequent itemsets using an iterative MapReduce based framework inspired by cogency. Cogency is the probability of the assumed facts being true if the conclusion is true, means it is based on pairwise item conditional probability, so the proposed algorithm mine association rules by only one pass through the file. The proposed algorithm is also valuable for dealing with infrequent items due to its cogency inspired approach.

  19. Action Rules Mining

    CERN Document Server

    Dardzinska, Agnieszka

    2013-01-01

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

  20. A Novel Association Rule Mining with IEC Ratio Based Dissolved Gas Analysis for Fault Diagnosis of Power Transformers

    Directory of Open Access Journals (Sweden)

    Ms. Kanika Shrivastava

    2012-06-01

    Full Text Available Dissolved gas Analysis (DGA is the most importantcomponent of finding fault in large oil filledtransformers. Early detection of incipient faults intransformers reduces costly unplanned outages. Themost sensitive and reliable technique for evaluatingthe core of transformer is dissolved gas analysis. Inthis paper we evaluate different transformercondition on different cases. This paper usesdissolved gas analysis to study the history ofdifferent transformers in service, from whichdissolved combustible gases (DCG in oil are usedas a diagnostic tool for evaluating the condition ofthe transformer. Oil quality and dissolved gassestests are comparatively used for this purpose. In thispaper we present a novel approach which is basedon association rule mining and IEC ratio method.By using data mining concept we can categorizefaults based on single and multiple associations andalso map the percentage of fault. This is an efficientapproach for fault diagnosis of power transformerswhere we can find the fault in all obviousconditions. We use java for programming andcomparative study.

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

    KAUST Repository

    Boudellioua, Imane

    2016-07-08

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

  2. Algorithm for Generating Non-Redundant Association Rules%一种无冗余的关联规则发现算法

    Institute of Scientific and Technical Information of China (English)

    高峰; 谢剑英

    2001-01-01

    关联规则是数据挖掘的重要研究内容之一,而传统算法生成的关联规则之间存在着大量的冗余规则.本文提出了一种通用的由最大频繁项目集生成无冗余关联规则的GNRR算法,利用规则之间的冗余关系,按一定顺序挖掘不同的规则,消除了规则之间的冗余性,使发现的规则数目呈指数倍减少.%The discovery of association rules is an important research topic in data mining, but the traditional association rules discovery algorithm produces too many redundant rules. This paper presented a general algorithm for mining non-redundant rules from the largest frequent itemsets using the redundant relationship of rules. The algorithm eliminates the redundancy between the rules and reduces the number of rules exponentially.

  3. Comprehensive screening for reg1α gene rules out association with tropical calcific pancreatitis

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    AIM: To investigate the allelic and haplotypic association of regla gene with tropical calcific pancreatitis (TCP). Since TCP is known to have a variable genetic basis, we investigated the interaction between mutations in the susceptibility genes, SPINK1 and CTSB with reg1α polymorphisms.METHODS: we analyzed the polymorphisms in the regla gene by sequencing the gene including its promoter region in 195 TCP patients and 150 ethnically matched controls, compared their allele and haplotype frequencies, and their association with the pathogenesis and pancreaticolithiasis in TCP and fibro-calculous pancreatic diabetes.RESULTS: We found 8 reported and 2 novel polymo-rphisms including an insertion-deletion polymorphism in the promoter region of reg1α. None of the 5' UTR variants altered any known transcription factor binding sites, neither did any show a statistically significant association with TCP. No association with any reg1α variants was observed on dichotomization of patients based on their N34S SPINK1 or L26V CTSB status.CONCLUSION: Polymorphisms in reg1α gene, including the regulatory variants singly or in combination with the known mutations in SPINK1 and/or CTSB genes, are not associated with tropical calcific pancreatitis.

  4. Rules of chemokine receptor association with T cell polarization in vivo

    OpenAIRE

    2001-01-01

    Current concepts of chemokine receptor (CKR) association with Th1 and Th2 cell polarization and effector function have largely ignored the diverse nature of effector and memory T cells in vivo. Here, we systematically investigated the association of 11 CKRs, singly or in combination, with CD4 T cell polarization. We show that Th1, Th2, Th0, and nonpolarized T cells in blood and tissue can express any of the CKRs studied but that each CKR defines a characteristic pool of polarized and nonpolar...

  5. 交通流数据清洗规则研究%Research on Traffic Flow Data Cleaning Rules

    Institute of Scientific and Technical Information of China (English)

    王晓原; 张敬磊; 吴芳

    2011-01-01

    交通检测器获得的数据存在无效、冗余、错误、时间点漂移及丢失等质量问题.为此,在分析影响数据质量问题原因的基础上,给出交通流数据清洗的概念,研究“脏数据”的清洗规则与清洗步骤,并对环形线圈检测器检测到的数据进行验证.结果表明,该清洗规则对错误、丢失、冗余等“脏数据”的识别率均在90%以上.%Aiming at that many quality problems are existed inevitably in detected data, including inefficacy, redundancy, error, missing, time dot excursion etc, the definition of data cleaning is proposed on the basis of sufficient study and analysis for the influence reasons of data quality, the cleaning rules and cleaning steps of "dirty data" are studied at the same time. And the proposed cleaning rules are calibrated with the detected data of loop vehicle detector. Results show that the recognition rates of "dirty data" is up to 90%.

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

    Science.gov (United States)

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

    2014-06-01

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

  7. DETERMINING THE CORE PART OF SOFTWARE DEVELOPMENT CURRICULUM APPLYING ASSOCIATION RULE MINING ON SOFTWARE JOB ADS IN TURKEY

    Directory of Open Access Journals (Sweden)

    Ilkay Yelmen

    2016-01-01

    Full Text Available The software technology is advancing rapidly over the years. In order to adapt to this advancement, the employees on software development should renew themselves consistently. During this rapid change, it is vital to train the proper software developer with respect to the criteria desired by the industry. Therefore, the curriculum of the programs related to software development at the universities should be revised according to software industry requirements. In this study, the core part of Software Development Curriculum is determined by applying association rule mining on Software Job ads in Turkey. The courses in the core part are chosen with respect to IEEE/ACM computer science curriculum. As a future study, it is also important to gather the academic personnel and the software company professionals to determine the compulsory and elective courses so that newly graduated software dev

  8. Discovery of Web Topic-Specific Association Rules%Web主题关联知识自学习算法

    Institute of Scientific and Technical Information of China (English)

    杨沛; 郑启伦; 彭宏

    2003-01-01

    There are hidden and rich information for data mining in the topology of topic-specific websites. A new topic-specific association rules mining algorithm is proposed to further the research on this area. The key idea is to analyze the frequent hyperlinked relati ons between pages of different topics. In the topic-specific area, if pages of onetopic are frequently hyperlinked by pages of another topic, we consider the two topics are relevant. Also, if pages oftwo different topics are frequently hyperlinked together by pages of the other topic, we consider the two topics are relevant.The initial experiments show that this algorithm performs quite well while guiding the topic-specific crawling agent and it can be applied to the further discovery and mining on the topic-specific website.

  9. A Priority Rule-Based Heuristic for Resource Investment Project Scheduling Problem with Discounted Cash Flows and Tardiness Penalties

    Directory of Open Access Journals (Sweden)

    Amir Abbas Najafi

    2009-01-01

    Full Text Available Resource investment problem with discounted cash flows (RIPDCFs is a class of project scheduling problem. In RIPDCF, the availability levels of the resources are considered decision variables, and the goal is to find a schedule such that the net present value of the project cash flows optimizes. In this paper, we consider a new RIPDCF in which tardiness of project is permitted with defined penalty. We mathematically formulated the problem and developed a heuristic method to solve it. The results of the performance analysis of the proposed method show an effective solution approach to the problem.

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

    Directory of Open Access Journals (Sweden)

    Chao Wang

    Full Text Available BACKGROUND: 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. METHODOLOGY/PRINCIPAL FINDINGS: 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. CONCLUSIONS/SIGNIFICANCE: 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.

  11. 2D design rule and layout analysis using novel large-area first-principles-based simulation flow incorporating lithographic and stress effects

    Science.gov (United States)

    Prins, Steven L.; Blatchford, James; Olubuyide, Oluwamuyiwa; Riley, Deborah; Chang, Simon; Hong, Qi-Zhong; Kim, T. S.; Borges, Ricardo; Lin, Li

    2009-03-01

    As design rules and corresponding logic standard cell layouts continue to shrink node-on-node in accordance with Moore's law, complex 2D interactions, both intra-cell and between cells, become much more prominent. For example, in lithography, lack of scaling of λ/NA implies aggressive use of resolution enhancement techniques to meet logic scaling requirements-resulting in adverse effects such as 'forbidden pitches'-and also implies an increasing range of optical influence relative to cell size. These adverse effects are therefore expected to extend well beyond the cell boundary, leading to lithographic marginalities that occur only when a given cell is placed "in context" with other neighboring cells in a variable design environment [1]. This context dependence is greatly exacerbated by increased use of strain engineering techniques such as SiGe and dual-stress liners (DSL) to enhance transistor performance, both of which also have interaction lengths on the order of microns. The use of these techniques also breaks the formerly straightforward connection between lithographic 'shapes' and end-of-line electrical performance, thus making the formulation of design rules that are robust to process variations and complex 2D interactions more difficult. To address these issues, we have developed a first-principles-based simulation flow to study contextdependent electrical effects in layout, arising not only from lithography, but also from stress and interconnect parasitic effects. This flow is novel in that it can be applied to relatively large layout clips- required for context-dependent analysis-without relying on semi-empirical or 'black-box' models for the fundamental electrical effects. The first-principles-based approach is ideal for understanding contextdependent effects early in the design phase, so that they can be mitigated through restrictive design rules. The lithographic simulations have been discussed elsewhere [1] and will not be presented in detail. The

  12. Rules of chemokine receptor association with T cell polarization in vivo

    Science.gov (United States)

    Kim, Chang H.; Rott, Lusijah; Kunkel, Eric J.; Genovese, Mark C.; Andrew, David P.; Wu, Lijun; Butcher, Eugene C.

    2001-01-01

    Current concepts of chemokine receptor (CKR) association with Th1 and Th2 cell polarization and effector function have largely ignored the diverse nature of effector and memory T cells in vivo. Here, we systematically investigated the association of 11 CKRs, singly or in combination, with CD4 T cell polarization. We show that Th1, Th2, Th0, and nonpolarized T cells in blood and tissue can express any of the CKRs studied but that each CKR defines a characteristic pool of polarized and nonpolarized CD4 T cells. Certain combinations of CKRs define populations that are markedly enriched in major subsets of Th1 versus Th2 cells. For example, although Th0, Th1, and Th2 cells are each found among blood CD4 T cells coordinately expressing CXCR3 and CCR4, Th1 but not Th2 cells can be CXCR3+CCR4–, and Th2 but only rare Th1 cells are CCR4+CXCR3–. Contrary to recent reports, although CCR7– cells contain a higher frequency of polarized CD4 T cells, most Th1 and Th2 effector cells are CCR7+ and thus may be capable of lymphoid organ homing. Interestingly, Th1-associated CKRs show little or no preference for Th1 cells except when they are coexpressed with CXCR3. We conclude that the combinatorial expression of CKRs, which allow tissue- and subset-dependent targeting of effector cells during chemotactic navigation, defines physiologically significant subsets of polarized and nonpolarized T cells. PMID:11696578

  13. New Procedure to Derive the Performance Indices Associated with Reservoir Operation Rule

    Institute of Scientific and Technical Information of China (English)

    WANG Jin-wen; ZHANG Yong-chuan; ZHANG You-quan

    2002-01-01

    Stochastic dynamic programming (SDP) is extensively used in the optimization for long-term reservoir operations. Generally, both of the steady state optimal policy and its associated performance indices (PIs) for multipurpose reservoir are of prime importance. To derive the PIs there are two typical ways: simulation and probability formula. Among the disadvantages, one is that these approaches require the pre-specified operation policy. IHuminated by the convergence of objective function in SDP, a new approach, which has the advantage that its use can be concomitant with the solving of SDP, is proposed to determine the desired PIs. In the case study, its efficiency is also practically tested.

  14. Order batching in warehouses by minimizing total tardiness: a hybrid approach of weighted association rule mining and genetic algorithms.

    Science.gov (United States)

    Azadnia, Amir Hossein; Taheri, Shahrooz; Ghadimi, Pezhman; Saman, Muhamad Zameri Mat; Wong, Kuan Yew

    2013-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Amir Hossein Azadnia

    2013-01-01

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

  16. Unsteady flow phenomena associated with leading-edge vortices

    Science.gov (United States)

    Breitsamter, C.

    2008-01-01

    This paper presents selected results from extensive experimental investigations on turbulent flow fields and unsteady surface pressures caused by leading-edge vortices, in particular, for vortex breakdown flow. Such turbulent flows may cause severe dynamic aeroelastic problems like wing and/or fin buffeting on fighter-type aircraft. The wind tunnel models used include a generic delta wing as well as a detailed aircraft configuration of canard-delta wing type. The turbulent flow structures are analyzed by root-mean-square and spectral distributions of velocity and pressure fluctuations. Downstream of bursting local maxima of velocity fluctuations occur in a limited radial range around the vortex center. The corresponding spectra exhibit significant peaks indicating that turbulent kinetic energy is channeled into a narrow band. These quasi-periodic velocity oscillations arise from a helical mode instability of the breakdown flow. Due to vortex bursting there is a characteristic increase in surface pressure fluctuations with increasing angle of attack, especially when the burst location moves closer to the apex. The pressure fluctuations also show dominant frequencies corresponding to those of the velocity fluctuations. Using the measured flow field data, scaling parameters are derived for design purposes. It is shown that a frequency parameter based on the local semi-span and the sinus of angle of attack can be used to estimate the frequencies of dynamic loads evoked by vortex bursting.

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

    Directory of Open Access Journals (Sweden)

    Ravikumar KE

    2012-10-01

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

  18. 基于多维关联规则的本体规则扩展方法%Methods for the Extension Rules of Ontology Based on Multidimensional Association Rules

    Institute of Scientific and Technical Information of China (English)

    董俊; 王锁萍; 熊范纶; 张友华

    2009-01-01

    Currently, the extension and enrichment for ontology have some limitations. Therefore, an approach is presented to extend ontology rules with multi-dimensional association rule technology. The conception ontology is enriched and extended by ontology rules extraction, consistency treatment under guidance of the ontology, rules mapping establishment, and the re-identification and update for conception ontology. The experimental results of tea diseases and pests predicting ontology show that the proposed approach can be easily implemented and has good feasibility and validity.%目前扩充和丰富本体存在很大的局限性.对此,文中提出采用多维关联规则技术扩展本体规则方法.通过对本体规则提取,在本体指导下的一致性处理,规则映射的建立,以及对概念本体的重新识别和更新等技术和方法充实和扩展概念本体.茶病虫害预测本体的实验结果表明该方法易于实现且具有较高的可行性和有效性.

  19. Mining Association Rules in Big Data for E-healthcare Information System

    Directory of Open Access Journals (Sweden)

    N. Rajkumar

    2014-08-01

    Full Text Available Big data related to large volume, multiple ways of growing data sets and autonomous sources. Now the big data is quickly enlarged in many advanced domains, because of rapid growth in networking and data collection. The study is defining the E-Healthcare Information System, which needs to make logical and structural method of approaching the knowledge. And also effectually preparing and controlling the data generated during the diagnosis activities of medical application through sharing information among E-Healthcare Information System devices. The main objective is, A E-Healthcare Information System which is extensive, integrated knowledge system designed to control all the views of a hospital operation, such as medical data’s, administrative, financial, legal information’s and the corresponding service processing. At last the analysis of result will be generated using Association Mining Techniques which processed from big data of hospital information datasets. Finally mining techniques result could be evaluated in terms of accuracy, precision, recall and positive rate.

  20. ASEAN Single Market: Revisiting Rules and Strategies on the Enforcement of Free Flow of Goods in ASEAN

    Directory of Open Access Journals (Sweden)

    Riyad Febrian Anwar

    2015-08-01

    Full Text Available Whether we are ready or not, people in Indonesia and the rest of Southeastern Asia will soon welcome the ASEAN Economic Communities (AEC by the end 2015. Therefore, there are needs to evaluate the progress in ASEAN rules and strategies thus far. By employing normative study, this paper finds and further recommends the following: Firstly, ASEAN almost reached its peak points in eliminating the tariff barriers, yet to come are the elimination on ‘sensitive’ and ‘highly sensitive list’ tariffs on imported agriculture commodities; Secondly, Non-Tariff Barriers (NTB remain to be one of the major problems in intra-ASEAN trades; Thirdly, Member States reluctances to invoke the ASEAN dispute settlement mechanism for their trading disputes may potentially hinder the effectiveness of AEC in the future; and Finally, the protection of intellectual property remains low in the region as the ASEAN Intellectual Property Rights (IPR Action plan 2011-2015 is still deemed ineffective to reforms the IP regulations within Member States.

  1. Mining Algorithm of Normalized Weighted Association Rules in Database%数据库中标准加权关联规则挖掘算法

    Institute of Scientific and Technical Information of China (English)

    杜鹢; 藏海霞

    2001-01-01

    在原有的关联规则挖掘算法的研究中,认为所有的属性的重要程度相同,提出标准加权关联规则的挖掘算法,能够解决因属性重要程度不一样带来的问题。%Previous algorithms on mining association rules maintain that theimportance of each item in database is equal. This paper presents a method of mining weighted association rules in database, which can solve the problems caused by the unequal importance of the items.

  2. Identifying users of traditional and Internet-based resources for meal ideas: An association rule learning approach.

    Science.gov (United States)

    Doub, Allison E; Small, Meg L; Levin, Aron; LeVangie, Kristie; Brick, Timothy R

    2016-08-01

    Increasing home cooking while decreasing the consumption of food prepared away from home is a commonly recommended weight management strategy, however research on where individuals obtain ideas about meals to cook at home is limited. This study examined the characteristics of individuals who reported using traditional and Internet-based resources for meal ideas. 583 participants who were ≥50% responsible for household meal planning were recruited to approximate the 2014 United States Census distribution on sex, age, race/ethnicity, and household income. Participants reported demographic characteristics, home cooking frequency, and their use of 4 traditional resources for meal ideas (e.g., cookbooks), and 7 Internet-based resources for meal ideas (e.g., Pinterest) in an online survey. Independent samples t-tests compared home cooking frequency by resource use. Association rule learning identified those demographic characteristics that were significantly associated with resource use. Family and friends (71%), food community websites (45%), and cookbooks (41%) were the most common resources reported. Cookbook users reported preparing more meals at home per week (M = 9.65, SD = 5.28) compared to non-cookbook users (M = 8.11, SD = 4.93; t = -3.55, p Resource use was generally higher among parents and varied systematically with demographic characteristics. Findings suggest that home cooking interventions may benefit by modifying resources used by their target population.

  3. A Novel Association Rule Mining with IEC Ratio Based Dissolved Gas Analysis for Fault Diagnosis of Power Transformers

    Directory of Open Access Journals (Sweden)

    Kanika Shrivastava

    2012-06-01

    Full Text Available Dissolved gas Analysis (DGA is the most important component of finding fault in large oil filled transformers. Early detection of incipient faults in transformers reduces costly unplanned outages. The most sensitive and reliable technique for evaluating the core of transformer is dissolved gas analysis. In this paper we evaluate different transformer condition on different cases. This paper uses dissolved gas analysis to study the history of different transformers in service, from which dissolved combustible gases (DCG in oil are used as a diagnostic tool for evaluating the condition of the transformer. Oil quality and dissolved gasses tests are comparatively used for this purpose. In this paper we present a novel approach which is based on association rule mining and IEC ratio method. By using data mining concept we can categorize faults based on single and multiple associations and also map the percentage of fault. This is an efficient approach for fault diagnosis of power transformers where we can find the fault in all obvious conditions. We use java for programming and comparative study.

  4. HST observations rule out the association between Cir X-1 and SNR G321.9-0.3

    CERN Document Server

    Mignani, R P; Caraveo, P A; Mirabel, I F

    2002-01-01

    Cir X-1 is one of the most intriguing galactic X-ray sources. It is a ~16.6 days variable X/radio source, a type-I X-ray burster and a QPO emitter. In spite of an uncertain optical counterpart classification, all these properties identify the source as an LMXB. The morphology of the surrounding radio nebula has suggested an association with the nearby (~25 arcmin) SNR G321.9-0.3, implying that Cir X-1 is a runaway binary originated from the supernova explosion 10^5 years ago. To investigate this hypothesis, we carried out a proper motion measurement of the Cir X-1 m ~19 optical counterpart using a set of HST/WFC and WFPC2 observations taken ~8.6 years apart. We obtained a 3 sigma upper limit of ~5 mas/yr on the source proper motion. Since the runaway hypothesis would have implied a proper motion due North ranging between 15 and 75 mas/yr, depending on the actual age of the SNR, our result definitively rules out the association between Cir X-1 and SNR G321.9-0.3.

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

    Science.gov (United States)

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

    2016-04-27

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

  6. Stimulated bioluminescence by fluid shear stress associated with pipe flow

    Energy Technology Data Exchange (ETDEWEB)

    Cao Jing; Wang Jiangan; Wu Ronghua, E-mail: caojing981@126.com [Col. of Electronic Eng., Naval University of Engineering, Wuhan 430033 (China)

    2011-01-01

    Dinoflagellate can be stimulated bioluminescence by hydrodynamic agitation. Two typical dinoflagellate (Lingulodinium polyedrum and Pyrocystis noctiluca) was choosed to research stimulated bioluminescence. The bioluminescence intensity and shear stress intensity were measured using fully developed pipe flow. There is shear stress threshold to agitate organism bioluminescence. From these experiment, the response thresholds of the stimulated bioluminscence always occurred in laminar flows at a shear stress level of 0.6-3 dyn/cm{sup 2}. At the same time, the spectral characteristc of dinoflagellate was recorded, the wavelength of them is about 470nm, and the full width at half maximum is approximate 30nm.

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

    Science.gov (United States)

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

    2011-05-25

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

  8. A curve shortening flow rule for closed embedded plane curves with a prescribed rate of change in enclosed area.

    Science.gov (United States)

    Dallaston, Michael C; McCue, Scott W

    2016-01-01

    Motivated by a problem from fluid mechanics, we consider a generalization of the standard curve shortening flow problem for a closed embedded plane curve such that the area enclosed by the curve is forced to decrease at a prescribed rate. Using formal asymptotic and numerical techniques, we derive possible extinction shapes as the curve contracts to a point, dependent on the rate of decreasing area; we find there is a wider class of extinction shapes than for standard curve shortening, for which initially simple closed curves are always asymptotically circular. We also provide numerical evidence that self-intersection is possible for non-convex initial conditions, distinguishing between pinch-off and coalescence of the curve interior.

  9. Method of data tendency measure mining in dynamic association rules%动态关联规则的趋势度挖掘方法

    Institute of Scientific and Technical Information of China (English)

    张忠林; 曾庆飞; 许凡

    2012-01-01

    针对规则随着时间变化的特点,在分析原有定义和对支持度向量(SV)和置信度向量分类的基础上,提出了动态关联规则趋势度的挖掘方法.首先,利用趋势度阈值消除无价值的规则,减小候选项集;其次,产生动态关联规则的趋势度元规则,找出具有价值的规则,提高挖掘质量;最后,通过对具有增减和周期趋势的事物数据库分析,证明了所提方法的有效性.%Based on the original definition and classification of Support Vector (SV) and confidence vector, this paper put forward a method of data tendency measure mining in dynamic association rules, according to the characteristic of rules with time changing. First, taking advantage of tendency measure threshold to eliminate useless rules, the item sets candidates can be reduced. Second, producing the dynamic association rule, this method found out valuable rules and improved the mining quality. Finally, by analyzing a transaction database that is characterized by the tendency of changes and cycles, the analytical results verify the validity of the proposed method.

  10. Optimization of Association Rule Apriori Algorithm%关联规则挖掘算法的优化

    Institute of Scientific and Technical Information of China (English)

    张青

    2015-01-01

    Apriori算法是关联规则挖掘的经典算法,该算法在处理规模巨大的候选项目集时存在耗时长和效率低的问题,提出了采用分割法对数据进行分片的优化算法。实验证明该算法不仅能减少数据挖掘对系统资源的占用,而且解决了数据库中数据分割下局部频繁项目序列集产生和全局频繁项目序列集的转换问题。%The Apriori algorithm is a classical methodology used for data mining association rules ,but this algorithm is rather time-consuming and low-efficient in dealing with massive sets of candidate items. This thesis has put forth an optimal algorithm of data segmentation based on data division,and the experiments prove that this new algorithm not only works well to make a significiant reduction in the amount of systemic resources engaged in data mining,but also provides a fine solution to the formation and conversion of series of item sets occuring frequently in the process of data-segmentation and data-division in databases.

  11. [Apply association rules to analysis adverse drug reactions of shuxuening injection based on spontaneous reporting system data].

    Science.gov (United States)

    Yang, Wei; Xie, Yan-Ming; Xiang, Yong-Yang

    2014-09-01

    This research based on the analysis of spontaneous reporting system (SRS) data which the 9 601 case reports of Shuxuening injection adverse drug reactions (ADR) in national adverse drug reaction monitoring center during 2005-2012. Apply to the association rules to analysis of the relationship between Shuxuening injection's ADR and the characteristics of ADR reports were. We found that ADR commonly combination were "nausea + breath + chills + vomiting", "nausea + chills + vomiting + palpitations", and their confidence level were 100%. The ADR and the case reports information commonly combination were "itching, and glucose and sodium chloride Injection, and generally ADR report, and normal dosage", "palpitation, and glucose and sodium chloride injection, and normal dosage, and new report", "chills, and generally ADR report, and normal dosage, and 0.9% sodium chloride injection", and their confidence level were 100% too. The results showed that patients using Shuxuening injection occurred most of ADRs were systemic damage, skin and its accessories damage, digestive system damage, etc. And most of cases were generally and new reports, and patients with normal dosage. The ADR's occurred had little related with solvent. It is showed that the Shuxuening injection occurred of ADR mainly related to drug composition. So Shuxuening injection used in clinical need to closely observation, and focus on the ADR reaction, and to do a good job of drug risk management.

  12. Association Rule Mining Based on the Interestingness About Vocational College Courses%基于兴趣度的高职课程关联规则挖掘

    Institute of Scientific and Technical Information of China (English)

    董辉

    2012-01-01

    研究关联规则数据挖掘,讨论兴趣度的概念,设计基于此概念的算法.以高职成绩数据库为处理对象,分析课程间的关联规则,并以兴趣度为约束条件,剔除具有欺骗性的无效关联,挖掘一些合理可靠的课程间有趣的关联规则,从而为高职课程设置和教学大纲的修订提供参考,同时也验证了算法的有效性.%This paper studies the association rules data mining, the concept of interestingness and algorithm design based on the concept. Taking vocational college's achievement database for processing object,this paper analyzes the association rules of courses; and with interestingness as constraint conditions, decep- tive invalid association rules are eliminated, and some reliable interesting association rules of courses are discovered. This paper provides reference for vocational college curriculum design and syllabus revision, and it also verifies the validity of the algorithm.

  13. Lithofacies classification and development rule of gravity flows deposits%重力流沉积岩相划分及其发育规律

    Institute of Scientific and Technical Information of China (English)

    张雷; 李振海; 张学娟; 刘敏; 申家年

    2015-01-01

    在Tailling等分类的基础上建立基于沉积过程中的流变学特征和沉积物支撑机制的滑塌流-浊流-碎屑流三分(滑塌岩相、碎屑流岩相和浊积岩相)14个序列的重力流岩相划分体系;结合鄂尔多斯盆地合水地区长7段大量的岩心资料,并借助于测井曲线和录井数据,对合水地区长7段重力流沉积的岩相及岩相组合进行识别。结果表明:合水地区主要发育5类重力流沉积岩相组合类型,即低密度浊流组合、高密度浊流组合、黏滞性碎屑流组合、弱黏滞性碎屑流组合以及滑塌岩组合;对比合水地区重力流沉积空间发现,滑塌岩相发育范围相对局限,主要发育于三角洲前缘失稳区,碎屑流沉积主要发育于斜坡带-坡折带处,浊流沉积的分布范围最广;“浅水凸形”坡折带位于三角洲前缘或三角洲平原附近,是重力流重要的触发区,主要控制正常牵引流三角洲前缘中松散的水下分流河道砂体沉积;“深水凹形”坡折带位于前三角洲深水区,是深水重力流砂体主要的卸载沉积区。%Building upon prior investigations of Talling and others, a three-fold classification of gravity flow lithofacies was es-tablished based primarily on fluid rheological characteristics and sediment-support mechanisms of depositional processes. The new classification mainly contains slumps lithofacies, debris flow lithofacies and turbidite lithofacies, corresponding to the de-posits of slump, debris flow and turbidity current respectively, and can be further subdivided into 14 lithofacies. Using the a-bundant core data and logging data, lithofacies and lithofacies associations of gravity flows deposits were identified in Chang 7 Member of Heshui region, Ordos Basin. The results show that there are five types of lithofacies associations developed in Hes-hui region, including the low density turbidite association, the high density turbidite

  14. Perceived rules and accessibility: measurement and mediating role in the association between parental education and vegetable and soft drink intake

    National Research Council Canada - National Science Library

    Gebremariam, Mekdes K; Lien, Nanna; Torheim, Liv Elin; Andersen, Lene F; Melbye, Elisabeth L; Glavin, Kari; Hausken, Solveig E S; Sleddens, Ester F C; Bjelland, Mona

    .... The aims of this study were (a) to assess the psychometric properties of new scales assessing the perceived rules and accessibility related to the consumption of vegetables and soft drinks and (b...

  15. Energy/material flows associated with cyclic petrochemicals

    Energy Technology Data Exchange (ETDEWEB)

    1979-10-01

    A detailed product flow analysis, starting with the refinery reformate stream, was prepared to identify the major products of interest. The selection of the products and their derivatives for detailed analysis was based on 1978 consumption data which is reported. The products selected for detailed analysis were: Benzene (from Toluene), Polystyrene, Polyester fibers, Cyclohexane, Nylon 6,6, Nylon 6, ABS + SAN, Phenolic resins, Urethane foams, Unsaturated polyesters and SBR. Data on the selling price of these products and the companies which market these products are tabulated. The production routes were analyzed to determine the key manufacturing processes available. A detailed analysis of the important steps in the production of these materials is presented. For each step in the manaufacturing process a process description, a block flow diagram, the energy consumption, and the feedstock conversions are provided. If more than one process was available and was determined to be commercially important, this route was also presented in detail. If the alternate process was not as significant, then this process was noted and briefly described.

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

    Science.gov (United States)

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

    2013-10-01

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

  17. 一种基于后项不定长关联规则的Web个性化推荐方法%A Web Personalized Recommendation Method Based on Uncertain Consequent Association Rules

    Institute of Scientific and Technical Information of China (English)

    丁增喜; 王菊英; 王大玲; 鲍玉斌; 于戈

    2003-01-01

    Web usage mining plays an important part in supporting personalized recommendation on Web and association rule uncovers the interesting relations among items hidden in data. The paper gives an idea of association rule merging-deleting based on the analysis of association rule characteristics and implements it in the rule preparation before the Web personalized recommendation. Furthermore, based on the comparisons in precision, coverage and F1 of recommendation system and the rule numbers used in three kinds of association rules, a Web personalized recommendation method based on uncertain consequent is put forward. After integrative analysis of several recommendation methods, the method given in the paper can be thought as a good selection. At last several pageweighted techniques are introduced in the paper.

  18. 关联规则快速挖掘在CRM中的应用%Fast Association Rule Mining in CRM

    Institute of Scientific and Technical Information of China (English)

    王扶东; 李洁; 薛劲松; 朱云龙

    2004-01-01

    交叉销售分析是CRM中的主要分析内容之一.提出了一种前件固定、后件受约束的关联规则快速挖掘算法,该算法的挖掘结果可以帮助企业利用销售情况好的产品促进其他产品的销售;同时提出了一种后件固定、前件受约束的关联规则快速挖掘算法,该算法的挖掘结果可以有效地帮助企业利用交叉销售方法为新产品开拓市场.仿真结果表明,这两种算法能够帮助企业快速准确地得到所需的信息.%The analysis of cross-selling is one of the important parts in analytical CRM. We present a constraint-based association rules mining algorithm AApriori with the specified antecedent and the constrained consequent. The outcome of this algorithm can help enterprises use selling products to popularize products that are unpopular. At the same time, an algorithm CApriori that the consequent is specified and the antecedent is constraind is presented.It can effectively support enterprises to exploit the market of new products. The evaluation demonstrated that the algorithm AApriori and CApriori could quickly get exact information that the enterprise wants.

  19. Photospheric Magnetic Flux Transport - Supergranules Rule

    Science.gov (United States)

    Hathaway, David H.; Rightmire-Upton, Lisa

    2012-01-01

    Observations of the transport of magnetic flux in the Sun's photosphere show that active region magnetic flux is carried far from its origin by a combination of flows. These flows have previously been identified and modeled as separate axisymmetric processes: differential rotation, meridional flow, and supergranule diffusion. Experiments with a surface convective flow model reveal that the true nature of this transport is advection by the non-axisymmetric cellular flows themselves - supergranules. Magnetic elements are transported to the boundaries of the cells and then follow the evolving boundaries. The convective flows in supergranules have peak velocities near 500 m/s. These flows completely overpower the superimposed 20 m/s meridional flow and 100 m/s differential rotation. The magnetic elements remain pinned at the supergranule boundaries. Experiments with and without the superimposed axisymmetric photospheric flows show that the axisymmetric transport of magnetic flux is controlled by the advection of the cellular pattern by underlying flows representative of deeper layers. The magnetic elements follow the differential rotation and meridional flow associated with the convection cells themselves -- supergranules rule!

  20. An application of improved association rules of an association graph in a recommendation system%基于关联图的改进关联规则在推荐系统中的应用

    Institute of Scientific and Technical Information of China (English)

    王林林; 石冰; 胡元; 邢海华

    2011-01-01

    提出了推荐模型中的关联规则挖掘方法的改进,给出了自定义的页面权值的定义,并改进了基于关联图的关联规则挖掘算法,将页面权值应用于关联规则的挖掘中。此算法是利用Web日志中经过预处理后得到的数据进行规则挖掘,将处理后的数据应用正态分布函数来得到页面权值。用页面权值重新计算支持度,最后将得到的支持度应用于改进的规则挖掘算法中,形成一种基于权值的关联图的关联规则算法。%This paper presents an improved association rule mining algorithm for the recommended system, and our definition for the page weights. We improve the association graph based association rules mining algorithm, and apply the page weights to the mining of association rules. This algorithm employs the data acquired after pretreatment to web log to mine the association rules. Page weights are obtained through the processing of such data with a normal distribution function. The algorithm then uses the page weights to recalculate the page support, which is applied to the improved rule mining algorithm. We can therefore acquire page weights based association rule algorithm of an association graph.

  1. Altered Regional Cerebral Blood Flow in Chronic Whiplash Associated Disorder

    NARCIS (Netherlands)

    Vállez García, David; Otte, A.; Willemsen, A. T. M.; Dierckx, R. A. J. O.; Doorduin, J.; Hostege, G.

    2015-01-01

    Aim: Whiplash trauma in one of the most frequent consequencesof motor vehicle accidents. While initial symptoms resolve withina few weeks in many cases, some patients develop persistentsymptoms that include pain, headache, visual, and/or psychologicaldisturbances, termed as Whiplash-associated

  2. Altered Regional Cerebral Blood Flow in Chronic Whiplash Associated Disorders

    NARCIS (Netherlands)

    Vállez García, David; Doorduin, Janine; Willemsen, Antoon T.M.; Dierckx, Rudi A.j.o.; Otte, Andreas

    2016-01-01

    There is increasing evidence of central hyperexcitability in chronic whiplash-associated disorders (cWAD). However, little is known about how an apparently simple cervical spine injury can induce changes in cerebral processes. The present study was designed (1) to validate previous results showing a

  3. Evaluation of the SediMax automated microscopy sediment analyzer and the Sysmex UF-1000i flow cytometer as screening tools to rule out negative urinary tract infections.

    Science.gov (United States)

    Íñigo, Melania; Coello, Andreu; Fernández-Rivas, Gema; Carrasco, María; Marcó, Clara; Fernández, Anabel; Casamajor, Teresa; Ausina, Vicente

    2016-05-01

    Urinary tract infections (UTI) are highly prevalent in nosocomial and community settings, and their diagnosis is costly and time-consuming. Screening methods represent an important advance towards the final UTI diagnosis, diminishing inappropriate treatment or clinical complications. Automated analyzers have been developed and commercialized to screen and rule out negative urine samples. The aim of this study was to evaluate two of these automated analyzers (SediMax, an automatic sediment analyzer and UF-1000i a flow cytometer) to predict negative urine cultures. A total of 1934 urine samples were analyzed. A very strong correlation for white blood cells (WBC) (rs: 0.928) and a strong correlation for bacteria (BAC) (rs: 0.693) were obtained. We also calculated optimal cut-off points for both autoanalyzers: 18 WBC/μL and 97 BAC/μL for SediMax (sensitivity=96.25%, specificity=63.04%, negative predictive value=97.97%), and 40 WBC/μL and 460 BAC/μL for UF-1000i (sensitivity=98.13%, specificity=79.16%, negative predictive value=99.18%). The use of SediMax and UF-1000i resulted in a 46.33% and 57.19% reduction of all samples cultured, respectively. In conclusion, both analyzers are good UTI screening tools in our setting.

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

    Science.gov (United States)

    Dold, Bernhard

    2006-02-01

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

  5. A Helioseismic Survey of Near-surface Flows Around Active Regions and their Association with Flares

    CERN Document Server

    Braun, D C

    2016-01-01

    We use helioseismic holography to study the association of shallow flows with solar flare activity in about 250 large sunspot groups observed between 2010 and 2014 with the Helioseismic and Magnetic Imager on the Solar Dynamics Observatory. Four basic flow parameters: horizontal speed, horizontal component of divergence, vertical component of vorticity, and a vertical kinetic helicity proxy, are mapped for each active region during its passage across the solar disk. Flow indices are derived representing the mean and standard deviation of these parameters over magnetic masks and compared with contemporary measures of flare X-ray flux. A correlation exists for several of the flow indices, especially those based on the speed and the standard deviation of all flow parameters. However, their correlation with X-ray flux is similar to that observed with the mean unsigned magnetic flux density over the same masks. The temporal variation of the flow indices are studied, and a superposed epoch analysis with respect to ...

  6. Computation of rotordynamic coefficients associated with leakage steam flow through labyrinth seal

    Energy Technology Data Exchange (ETDEWEB)

    Wang, W.Z.; Liu, Y.Z.; Chen, H.P. [Shanghai Jiaotong University, Thermal Fluid Flow and Turbomachinery Lab., School of Mechanical Engineering, Shanghai (China); Jiang, P.N. [Shanghai Turbine Company, Department of R and D, Shanghai (China)

    2007-08-15

    A mathematical model of calculating rotordynamic coefficients associated with leakage steam flow through labyrinth seals was presented. Particular attention was given to incorporating thermal properties of the steam fluid into prediction of leakage flow and subsequent derivation of rotordynamic coefficients, which quantitatively characterize influence of aerodynamic forcing of the leakage steam flow on the rotordynamics. By using perturbation analysis, we determined periodic and analytic solutions of the continuity and circumferential momentum equations for the time-dependent flow induced by non-axisymmetric rotation of the rotor encompassed by a labyrinth seal. Pressure distributions along labyrinth seal cavities and rotordynamic coefficients were compared at the same condition for air and steam flows. Influence of steam flow through the labyrinth seal cavities on rotordynamic coefficients was analyzed in terms of inlet pressure, inlet swirl velocity and rotor speed. (orig.)

  7. Research on the Spatial Distribution and Flow Rules of Chinese Inbound Business Tourist Flows%中国入境商务旅游流空间分布特征及流动规律研究

    Institute of Scientific and Technical Information of China (English)

    唐澜; 吴晋峰; 王金莹; 杨新菊

    2012-01-01

    通过构建中国入境商务旅游流网络,运用社会网络分析法定量分析中国入境商务旅游流的空间分布特征及流动规律。研究表明:①中国入境商务旅游流地理分布不均衡,在空间上形成"四点"(广州、北京、上海、香港)、"两面"(长江三角洲、珠江三角洲)的地理分布格局。②广州是入境商务旅游流最重要的集散中心,入境商务旅游流主要在北京、上海、广州、香港之间转移流动。③中国入境商务旅游流网络中节点由四个层次城市组成,分别是一级核心城市(广州、北京、上海、香港);二级核心城市(苏州、桂林、杭州);三级核心城市(义乌、西安、黄山、深圳、无锡、厦门、澳门)及边缘城市(网络中其他节点城市)。%Through building the inbound business tourist flow network of China,this research analyzed the geographical distribution and flowing rules of inbound business tourist flows in China with the methodologies derived from the social network analysis.The study results are:1.The geographical distribution of the inbound business tourist flows on China is unbalanced and the concentrating distribution destinaiton cities and regions are: Guangzhou,Beijing,Shanghai,Hongkong,the Yangtze River Delta and Pearl River Delta.2.Guangzhou is the centre of the inbound business tourist network in China and is the most important gathering and distributing centre of inbound business tourist flows.3.The nodes in the inbound business tourist flow network can be classified into four levels: the first level including Guangzhou,Beijing,Shanghai,Hongkong,which are the first-order core cities in the inbound business tourist flow network,the second level including Suzhou,Guilin,Hangzhou,which are the secondary core cities in the inbound business tourist flow network,the third level including Yiwu,Xi’an,Huangshan,Shenzhen,Macao,Wuxi,Xiamen,which are the third core cities in the

  8. Analysis on Composition Rules of Chinese Patent Drugs with Tonifying Spleen Based on Association Rules and Clustering Algorithm%基于关联规则与熵聚类的健脾类中成药组方规律研究

    Institute of Scientific and Technical Information of China (English)

    金燕萍; 吴嘉瑞; 张冰; 杨冰; 周唯; 张晓朦

    2015-01-01

    目的:探讨常用健脾类中成药组方规律。方法:收录《新编国家中成药》中的健脾类中成药处方,采用关联规则Apriori 算法和复杂系统熵聚类等方法,确定处方中药物的使用频次及药物之间的关联规则等。结果:高频次药物包括茯苓、白术、甘草、党参、陈皮等;高频次药物组合包括“白术、茯苓”“甘草、茯苓”“甘草、白术”等;置信度较高的关联规则包括“陈皮->白扁豆”“陈皮->半夏”等。结论:处方用药中除常见的健脾类中药外,尚包括具有健脾作用的部分理气药、消食药及其他类药物。%Objective:To investigate composition rules of Chinese patent drugs with tonifying spleen.Methods:The prescriptions of Chinese patent drugs with tonifying spleen in “The New National Medicine”were collected to build a database.The methods of association rules with apriori algorithm and complex system entropy cluster were used to achieve the frequency of medicines and as-sociation rules between drugs.Results:The data-mining results indicated that in the prescriptions of Chinese patent drugs with ton-ifying spleen,the most frequency used drugs were Poria Cocos Wolff,Rhizoma Atractylodis Macrocephalae,Radix Glycyrrhizae, Radix Codonopsitis,Pericarpium Citri Reticulatae.The most common drug combinations were”Rhizoma Atractylodis Macrocepha-lae,Poria Cocos Wolff”,”Radix Glycyrrhizae,Poria Cocos Wolff”,”Radix Glycyrrhizae,Rhizoma Atractylodis Macrocephalae”. The drugs with a high degree confidence coefficient of association rules include “Pericarpium Citri Reticulatae->Semen Dolicho-ris”,“Pericarpium Citri Reticulatae->Pinellia ternata”.Conclusion:There are not only the common drugs tonifying spleen,but also drugs regulating the flow of vital energy,removing obstruction toit,and helping digest.

  9. RESEARCH ON ALL NEGATIVE ASSOCIATION RULES MINING IN A DATABASE%数据库中全部负关联规则挖掘研究

    Institute of Scientific and Technical Information of China (English)

    李红; 宗瑜; 解浚源

    2011-01-01

    数据库中关联规则信息是知识的表述形式之一,负关联规则挖掘是数据库关联信息挖掘的重要研究内容,具有广泛的应用范围.现有的挖掘方法不能获取数据库中全部的负关联规则,考虑从数据库中提取全部的负关联规则,通过(1)扫描数据库建立数据库频繁模式树DFP-tree( Database Frequent Pattern tree);(2)在精简DFP-tree的基础上获取全部极小非频繁项集ASI;(3)对ASI中极大频繁项集的向上闭包,得到全部非频繁项集;(4)在此基础上采用相关度作为规则兴趣度量之一提取负关联规则.理论和实验表明算法的正确性和效率.%In a database, associated rule information is one of the representation formats for knowledge. Negative association rule mining is so important to study in database association information mining that it bears wide application value. Existing mining approaches can not obtain all negative rules from a database. The paper considers to extract all negative association rules from a database through: (1) scanning the database to build a database frequent pattern tree called DFP-tree; (2) acquiring based on pruning the DFP-tree all small infrequent itemsets; (3) acquiring via upward closure packets of large frequent itemsets in ASI all infrequent itemsets; (4) based on the previous 3 steps adopting correlation metric as one of rule interest measurements to extract negative association rules. Theories and experiments validate the correctness and efficiency of the presented algorithm.

  10. Cubic Plus Association Equation of State for Flow Assurance Projects

    DEFF Research Database (Denmark)

    dos Santos, Leticia Cotia; Abunahman, Samir Silva; Tavares, Frederico Wanderley

    2015-01-01

    Thermodynamic hydrate inhibitors such as methanol, ethanol, (mono) ethylene glycol (MEG), and triethylene glycol (TEG) are widely used in the oil and gas industry. On modeling these compounds, we show here how the CPA equation of state was implemented in an in-house process simulator as an in......-built model: To validate the implementation, we show calulations for binary systems containing hydrate inhibitors and water or hydrocarbons using the Cubic Plus Association (CPA) and Soave-Redlich-Kwong (SRK) equation of states, also comparing against experimental data. For streams containing natural gas...

  11. Objective Evaluation Method of Association Rule Interestingness%基于客观兴趣度的关联规则评价方法①

    Institute of Scientific and Technical Information of China (English)

    亓文娟; 晏杰

    2013-01-01

    目前衡量和生成关联规则的主要准则是考虑支持度和置信度阈值,而在实际应用中仅按此准则来挖掘是不够的,这主要是因为关联规则的评价标准不合理产生的。针对关联规则评价指标进行了深入的研究,分析了“支持度-置信度”架构的局限性,提出了基于相关性的兴趣度的评价指标PS公式,根据其数学特性指出了它的优点与不足,为关联规则评价体系的改进奠定了理论基础。%Current main guidelines is to measure and generate Association rules take into account support and confidence threshold, and only in the practical application of this guideline to mining is insufficient, this is mainly because the associated rule evaluation criterion is not reasonable. This article for the associated rule evaluation conducted an in-depth study, analyzed the "support-confidence" schema limitations, presenting an interest based on correlation degree of evaluation indicators PS formula, based on its mathematical properties that has its advantages and disadvantages, laid the theoretical foundation for improvement of evaluation system of Mining Association rules.

  12. 基于关联规则的Web挖掘技术研究%Research on Web Mining Based on Association Rules

    Institute of Scientific and Technical Information of China (English)

    夏惠芬; 董卫民

    2011-01-01

    Association rules is an important area of Web mining. In order to dig out the hidden correlation among the data, the concept of association rules was introduced into the Web mining, and the user's access was expressed in the form of association rules. With the idea of Aporiori algorithm, the new Aporiori algorithm role and pattern appropriate for Web mining are presented. The results were verified in some simple webs, and a good result was obtained.%关联规则是Web挖掘中一个重要的研究领域.为了挖掘出隐藏在数据间的相互关系,将关联规则的概念引入到Web挖掘系统中,把用户的访问路径以关联规则的形式表现出来.基于Apriori算法的思想,给出了适合Web挖掘用户访问的新Apriori算法规则及其模式,最后将结果在一些较简单的网页上进行了验证,取得了较好的应用效果.

  13. 基于MDPI的多维关联规则算法的研究%The Research for Multidimensional Association Rules Algorithm Based on MDPI

    Institute of Scientific and Technical Information of China (English)

    彭硕; 吴昊

    2011-01-01

    Multidimensional data mining association rules is an important research direction. In this paper, we propose an efficient algorithm for mining multidimensial association rules,which combine data cube technique with FP-Growth efficiently by constructing a MDPI-tree,the algorithm can explores both inter-dimension and hybrid-dimension association rules. Lastly this algorithm is applied to cross-selling model of mobile communication, and we can verificate the practicality and effectiveness of the algorithm by experiment.%多维关联规则是数据挖掘中的一个重要研究方向,由此提出了一种高效的多维关联规则挖掘算法,该方法通过引入MDPI-tree(多维谓词索引树)结构,有效地将数据立方体技术和频繁项集挖掘算法FP-Growth结合起来,能用于挖掘维间和混合维关联规则.最后将此算法应用于移动通信交叉销售模型,通过实验验证算法的有效性和实用性.

  14. Behavior of boundary string field theory associated with integrable massless flow.

    Science.gov (United States)

    Fujii, A; Itoyama, H

    2001-06-04

    We put forward an idea that the boundary entropy associated with integrable massless flow of thermodynamic Bethe ansatz (TBA) is identified with tachyon action of boundary string field theory. We show that the temperature parametrizing a massless flow in the TBA formalism can be identified with tachyon energy for the classical action at least near the ultraviolet fixed point, i.e., the open string vacuum.

  15. Association of cognitive judgment and shyness with frequency and quality of flow experience

    Directory of Open Access Journals (Sweden)

    Hirao K

    2012-11-01

    Full Text Available Kazuki Hirao, Ryuji Kobayashi, Kenji YabuwakiDepartment of Occupational Therapy, School of Health Science and Social Welfare, Kibi International University, Takahashi City, Okayama, JapanObjective: To determine the association of cognitive judgment and shyness with frequency and quality of flow experience.Design and methods: This was a cross-sectional survey of the relationship between psychological tendency and frequency and quality of flow experience in 68 college students, undertaken in Hiroshima, Japan. The predictors were Shyness Scale scores, measure of ambiguity tolerance scores, and Life Orientation Test scores, and the outcome was the frequency and quality of flow experience.Results: The results of the binary logistic regression analysis indicated that only the measure of ambiguity tolerance (P = 0.02, odds ratio = 1.06, and 95% confidence interval = 1.01–1.11 was a predictor of the quality of flow experience, and only the Shyness Scale (P = 0.007, odds ratio = 0.95, and 95% confidence interval = 0.91–0.98 was a predictor of the frequency of flow experience.Conclusion: The findings suggest that ambiguity tolerance and shyness are associated with the frequency and quality of the flow experience.Keywords: Flow experience, positive psychology, shyness, ambiguity tolerance, life orientation

  16. 基于关联规则的地铁施工事故分析%Subway Construction Accident Analysis Based on Multidimensional Association Rules

    Institute of Scientific and Technical Information of China (English)

    陈伟珂; 李金玲; 聂凌毅

    2011-01-01

    With the rapid development of Metro construction, the subway construction accidents frequently happen. For the characteristics of the increasingly complex relationship between subway constructions accidents data, this paper puts forward a method of the multi-dimensional association rule's specifically applying in subway construction accidents data. With this "multi-dimensional association rule" tool, the potential relations of subway construction accident are to be found out, showing specifically how to find out this procedure of strong association rules between "person-instrument-environment-management " and the types of accidents. The strong association rule of construction collapse accidents can be figured out through searching the combination of frequent factors that probably lead to subway construction accidents. Furthermore,on the basis of the evaluation of strong association rules,the potential laws for subway construction accidents will be found. And these laws are used as the basis of managers making accident-prevention security measures in reality.%针对地铁施工事故数据间关系日益复杂的特点,提出了多维关联规则在地铁施工事故数据的具体应用方法.利用关联规则工具挖掘出施工事故潜在的关系,具体展示了“人-机-环境-管理”和事故发生类型之间如何挖掘强关联规则的过程.通过找出可能导致地铁施工事故发生的频繁因素的组合,来发现施工坍塌事故发生的强关联规则.在评价强关联规则的基础上,找到适合地铁施工事故发生的潜在规律,并将这些规律作为现实中管理者做出预防安全事故发生措施的依据.

  17. A Method of Association Rules Data Mining Based on Star Schema%一种星型模式下的关联规则挖掘方法

    Institute of Scientific and Technical Information of China (English)

    李艳; 白玉峰

    2011-01-01

    目前的数据挖掘基本上都是基于普通数据集的挖掘,针对星型模式结构的数据挖掘的研究工作较少,为此定义星型模式挖掘结构,并在此基础上构建一种关联规则挖掘算法,该算法先扫描事实表,产生最大频繁项集和关联规则,进而以此为基础,提出一种基于连接条件和关联规则局部有效性的理论,并在此基础上建立一种快速扫描维表属性的方法,一次产生维表隐藏的关联规则,这个扫描是基于局部的,不是基于全局的,同时可根据需要,对于不明确的关联规则,通过构建扩展的维表,进行隐知识的挖掘.算法挖掘速度快,若合理地构建扩展维表,能够发现扩展的隐藏信息.%Current data mining is based on the mining of general data set basically. The research to data mining of the star schema structure is less. So the star schema mining structure is defined, and based on which an mining algorithm with association rules is constructed. The algorithm first scans the fact table, and produces maximal frequency item sets and association rules, with which as the basis, the theory based on the local efficiency principle of linking conditions and association rules is put forward, and the method scans the dimension table attributes quickly. It produces the association rules one-off. The scan is based on the part, not global. At the same time the undefined association rules are dealt with by mining the implicit knowledge through constructing extended dimension table. The mining speed of the algorithm is faster. Through building expanded dimension table reasonably, the extended hidden information can be found in this way.

  18. Generalized Deterministic Traffic Rules

    CERN Document Server

    Fuks, H; Fuks, Henryk; Boccara, Nino

    1997-01-01

    We study a family of deterministic models for highway traffic flow which generalize cellular automaton rule 184. This family is parametrized by the speed limit $m$ and another parameter $k$ that represents a ``degree of aggressiveness'' in driving, strictly related to the distance between two consecutive cars. We compare two driving strategies with identical maximum throughput: ``conservative'' driving with high speed limit and ``aggressive'' driving with low speed limit. Those two strategies are evaluated in terms of accident probability. We also discuss fundamental diagrams of generalized traffic rules and examine limitations of maximum achievable throughput. Possible modifications of the model are considered.

  19. Hybrid modeling of convective laminar flow in a permeable tube associated with the cross-flow process

    Science.gov (United States)

    Venezuela, A. L.; Pérez-Guerrero, J. S.; Fontes, S. R.

    2009-03-01

    The confined flows in tubes with permeable surfaces are associated to tangential filtration processes (microfiltration or ultrafiltration). The complexity of the phenomena do not allow for the development of exact analytical solutions, however, approximate solutions are of great interest for the calculation of the transmembrane outflow and estimate of the concentration polarization phenomenon. In the present work, the generalized integral transform technique (GITT) was employed in solving the laminar and permanent flow in permeable tubes of Newtonian and incompressible fluid. The mathematical formulation employed the parabolic differential equation of chemical species conservation (convective-diffusive equation). The velocity profiles for the entrance region flow, which are found in the connective terms of the equation, were assessed by solutions obtained from literature. The velocity at the permeable wall was considered uniform, with the concentration at the tube wall regarded as variable with an axial position. A computational methodology using global error control was applied to determine the concentration in the wall and concentration boundary layer thickness. The results obtained for the local transmembrane flux and the concentration boundary layer thickness were compared against others in literature.

  20. Prospective association of fetal liver blood flow at 30 weeks gestation with newborn adiposity.

    Science.gov (United States)

    Ikenoue, Satoru; Waffarn, Feizal; Ohashi, Masanao; Sumiyoshi, Kaeko; Ikenoue, Chigusa; Buss, Claudia; Gillen, Daniel L; Simhan, Hyagriv N; Entringer, Sonja; Wadhwa, Pathik D

    2017-08-01

    The production of variation in adipose tissue accretion represents a key fetal adaptation to energy substrate availability during gestation. Because umbilical venous blood transports nutrient substrate from the maternal to the fetal compartment and because the fetal liver is the primary organ in which nutrient interconversion occurs, it has been proposed that variations in the relative distribution of umbilical venous blood flow shunting either through ductus venosus or perfusing the fetal liver represents a mechanism underlying this adaptation. The objective of the present study was to determine whether fetal liver blood flow assessed before the period of maximal fetal fat deposition (ie, the third trimester of gestation) is prospectively associated with newborn adiposity. A prospective study was conducted in a cohort of 62 uncomplicated singleton pregnancies. Fetal ultrasonography was performed at 30 weeks gestation for conventional fetal biometry and characterization of fetal liver blood flow (quantified by subtracting ductus venosus flow from umbilical vein flow). Newborn body fat percentage was quantified by dual energy X-ray absorptiometry imaging at 25.8 ± 3.3 (mean ± standard error of the mean) postnatal days. Multiple regression analysis was used to determine the proportion of variation in newborn body fat percentage explained by fetal liver blood flow. Potential confounding factors included maternal age, parity, prepregnancy body mass index, gestational weight gain, gestational age at birth, infant sex, postnatal age at dual energy X-ray absorptiometry scan, and mode of infant feeding. Newborn body fat percentage was 13.5% ± 2.4% (mean ± standard error of the mean). Fetal liver blood flow at 30 weeks gestation was significantly and positively associated with newborn total fat mass (r=0.397; Pliver blood flow explained 13.5% of the variance in newborn fat mass. The magnitude of this association was pronounced particularly in nonoverweight

  1. Rules for scoring respiratory events in sleep: update of the 2007 AASM Manual for the Scoring of Sleep and Associated Events. Deliberations of the Sleep Apnea Definitions Task Force of the American Academy of Sleep Medicine.

    Science.gov (United States)

    Berry, Richard B; Budhiraja, Rohit; Gottlieb, Daniel J; Gozal, David; Iber, Conrad; Kapur, Vishesh K; Marcus, Carole L; Mehra, Reena; Parthasarathy, Sairam; Quan, Stuart F; Redline, Susan; Strohl, Kingman P; Davidson Ward, Sally L; Tangredi, Michelle M

    2012-10-15

    The American Academy of Sleep Medicine (AASM) Sleep Apnea Definitions Task Force reviewed the current rules for scoring respiratory events in the 2007 AASM Manual for the Scoring and Sleep and Associated Events to determine if revision was indicated. The goals of the task force were (1) to clarify and simplify the current scoring rules, (2) to review evidence for new monitoring technologies relevant to the scoring rules, and (3) to strive for greater concordance between adult and pediatric rules. The task force reviewed the evidence cited by the AASM systematic review of the reliability and validity of scoring respiratory events published in 2007 and relevant studies that have appeared in the literature since that publication. Given the limitations of the published evidence, a consensus process was used to formulate the majority of the task force recommendations concerning revisions.The task force made recommendations concerning recommended and alternative sensors for the detection of apnea and hypopnea to be used during diagnostic and positive airway pressure (PAP) titration polysomnography. An alternative sensor is used if the recommended sensor fails or the signal is inaccurate. The PAP device flow signal is the recommended sensor for the detection of apnea, hypopnea, and respiratory effort related arousals (RERAs) during PAP titration studies. Appropriate filter settings for recording (display) of the nasal pressure signal to facilitate visualization of inspiratory flattening are also specified. The respiratory inductance plethysmography (RIP) signals to be used as alternative sensors for apnea and hypopnea detection are specified. The task force reached consensus on use of the same sensors for adult and pediatric patients except for the following: (1) the end-tidal PCO(2) signal can be used as an alternative sensor for apnea detection in children only, and (2) polyvinylidene fluoride (PVDF) belts can be used to monitor respiratory effort (thoracoabdominal

  2. Flows Associated to Cameron-martin Type Vector Fields on Path Spaces Over a Riemannian Manifold

    Institute of Scientific and Technical Information of China (English)

    Jing-xiao ZHANG

    2013-01-01

    The flow on the Wiener space associated to a tangent process constructed by Cipriano and Cruzeiro,as well as by Gong and Zhang does not allow to recover Driver's Cameron-Martin theorem on Riemannian path space.The purpose of this work is to refine the method of the modified Picard iteration used in the previous work by Gong and Zhang and to try to recapture and extend the result of Driver.In this paper,we establish the existence and uniqueness of a flow associated to a Cameron-Martin type vector held on the path space over a Riemannian manifold.

  3. 基于关联规则与熵聚类的安神类中成药组方规律研究%Analysis on Composition Rules of TCM Tranquilizer Based on Association Rules and Clustering Algorithm

    Institute of Scientific and Technical Information of China (English)

    吴嘉瑞; 金燕萍; 张晓朦; 张冰; 盛晓光

    2015-01-01

    Objective:To explore composition rules of TCM tranquilizer prescriptions.Methods:The tranquilizer prescriptions in“The New National Medicine”were collected to build a database based on traditional Chinese medicine inheritance assist system. The methods of association rules with apriori algorithm and complex system entropy cluster were used to achieve the frequency of medicines and association rules between drugs.Results:The data-mining results indicated that in the tranquilizer prescriptions,the highest frequently used drugs were Poria Cocos Wolff,Radix Glycyrrhizae,Angelica sinensis,Radix Ophiopogonis,Cinnabaris. The most frequent drug combinations were “Angelica sinensis,Poria Cocos Wolff”,“Poria Cocos Wolff,Parched Semen Ziziphi Spinosae”,“Radix Glycyrrhizae,Poria Cocos Wolff”.The drugs with a high degree confidence coefficient of association rules in-cluded “Calculus Bovis,Cinnabaris”,“Semen Ziziphi Spinosae,Poria Cocos Wolff”.The new prescriptions contained Poria Co-cos Wolff,Parched Semen Ziziphi Spinosae,Radix Rehmanniae Preparata,Fructus Schisandrae Chinensis,Radix Salviae Miltior-rhizae,Radix Ophiopogonis,and Radix Rehmanniae Exsiccata.Conclusion:Chinese medicine drugs in tranquilizer prescriptions usually have the effects of nourishing the blood,calming mind,benefiting the qi,replenishing the yin and quieting the spirit.%目的:分析常用安神类中成药的处方用药规律。方法:收集《新编国家中成药》中的安神类药品处方,基于中医传承辅助系统建立处方数据库,采用关联规则apriori算法、复杂系统熵聚类等方法开展研究,确定处方中各种药物的使用频次及药物之间的关联规则等。结果:高频次药物包括茯苓、甘草、当归、麦冬、朱砂等;高频次药物组合包括“当归、茯苓”“茯苓、炒酸枣仁”“甘草、茯苓”等;置信度较高的关联规则包括“牛黄、朱砂”“酸枣仁、茯苓”等,新处

  4. Effect of pulsatile and continuous flow on yes-associated protein.

    Science.gov (United States)

    Chitragari, Gautham; Shalaby, Sherif Y; Sumpio, Brandon J; Sumpio, Bauer E

    2014-09-01

    Yes-associated protein (YAP) is a mechanosignaling protein that relays mechanical information to the nucleus by changing its level of phosphorylation. We hypothesize that different flow patterns show differential effect on phosphorylated YAP (pYAP) (S127) and total YAP and could be responsible for flow dependent localization of atherosclerosis. Confluent human umbilical vein endothelial cells (HUVECs) seeded on fibronectin-coated glass slides were exposed to continuous forward flow (CFF) and pulsatile forward flow (PFF) using a parallel plate flow chamber system for 30 minutes. Cell lysates were prepared and immunoblotted to detect the levels of phosphorylated YAP and total YAP. HUVECs exposed to both PFF and CFF showed a mild decrease in the levels of both pYAP (S127) and total YAP. While the levels of pYAP (S127) decreased to 87.85 and 85.21% of static control with PFF and CFF, respectively, the levels of total YAP significantly decreased to 91.31 and 92.27% of static control. No significant difference was seen between CFF and PFF on their effect on pYAP (S127), but both conditions resulted in a significant decrease in total YAP at 30 minutes. The results of this experiment show that the possible effect of different types of flow on YAP is not induced before 30 minutes. Experiments exposing endothelial cells to various types of flow for longer duration of time could help to elucidate the role of YAP in the pathogenesis of atherosclerosis.

  5. Aerobic fitness is associated with greater hippocampal cerebral blood flow in children

    Directory of Open Access Journals (Sweden)

    Laura Chaddock-Heyman

    2016-08-01

    Full Text Available The present study is the first to investigate whether cerebral blood flow in the hippocampus relates to aerobic fitness in children. In particular, we used arterial spin labeling (ASL perfusion MRI to provide a quantitative measure of blood flow in the hippocampus in 73 7- to 9-year-old preadolescent children. Indeed, aerobic fitness was found to relate to greater perfusion in the hippocampus, independent of age, sex, and hippocampal volume. Such results suggest improved microcirculation and cerebral vasculature in preadolescent children with higher levels of aerobic fitness. Further, aerobic fitness may influence how the brain regulates its metabolic demands via blood flow in a region of the brain important for learning and memory. To add specificity to the relationship of fitness to the hippocampus, we demonstrate no significant association between aerobic fitness and cerebral blood flow in the brainstem. Our results reinforce the importance of aerobic fitness during a critical period of child development.

  6. Research on risk web information mining technology based on improved association rules%基于改进关联规则的危险Web信息挖掘技术研究

    Institute of Scientific and Technical Information of China (English)

    黄宏本

    2016-01-01

    The security of cyber information space is threatened by the hazard information that caused by different protocols and network channels in Web network,and the cyber space is purified to ensure the network security by mining the hazard Web information accurately. The algorithm of the fuzzy association rules are used in the traditional method to excavate and classified the dangerous Web information. The fuzzy clustering is easy to be disturbed in the influence background and has low efficiency, so it is hard to establish effective association rules. Because of this,the risk Web information mining technology based on the im⁃proved association rules is proposed. Before establishing the association rules,Takens theorem is introduced to reconstruct the phase space of the hazard Web information data to establish the channel model for the hazard information mining in Web net⁃work and make classification design for the multisource progress of the risk Web information flow. An adaptive IIR cascade filtering algorithm is designed to filter the data influence,improve the progress of the association rules,and realize the accurate mining of the risk Web information. The simulation results for the performance verification show that this algorithm has advantages of good filtering interference performance and high accuracy.%在Web网络中承载着不同的协议和网络信道,由此产生危险信息,给网络信息空间带来安全威胁,通过对危险Web信息的准确挖掘,可净化网络空间,确保网络安全。传统方法采用模糊关联规则算法进行危险Web信息分类挖掘,在干扰背景下,模糊聚类过容易受到干扰,导致很难建立有效的关联规则,挖掘效率较低。提出一种基于改进关联规则的危险Web信息挖掘技术。在建立关联规则前,引入Takens 定理进行危险Web信息数据的相空间重构,构建Web网络的危险信息挖掘的信道模型,并对危险Web信息的信息流多

  7. Plasminogen associates with phosphatidylserine-exposing platelets and contributes to thrombus lysis under flow.

    Science.gov (United States)

    Whyte, Claire S; Swieringa, Frauke; Mastenbroek, Tom G; Lionikiene, Ausra S; Lancé, Marcus D; van der Meijden, Paola E J; Heemskerk, Johan W M; Mutch, Nicola J

    2015-04-16

    The interaction of plasminogen with platelets and their localization during thrombus formation and fibrinolysis under flow are not defined. Using a novel model of whole blood thrombi, formed under flow, we examine dose-dependent fibrinolysis using fluorescence microscopy. Fibrinolysis was dependent upon flow and the balance between fibrin formation and plasminogen activation, with tissue plasminogen activator-mediated lysis being more efficient than urokinase plasminogen activator-mediated lysis. Fluorescently labeled plasminogen radiates from platelet aggregates at the base of thrombi, primarily in association with fibrin. Hirudin attenuates, but does not abolish plasminogen binding, denoting the importance of fibrin. Flow cytometry revealed that stimulation of platelets with thrombin/convulxin significantly increased the plasminogen signal associated with phosphatidylserine (PS)-exposing platelets. Binding was attenuated by tirofiban and Gly-Pro-Arg-Pro amide, confirming a role for fibrin in amplifying plasminogen binding to PS-exposing platelets. Confocal microscopy revealed direct binding of plasminogen and fibrinogen to different platelet subpopulations. Binding of plasminogen and fibrinogen co-localized with PAC-1 in the center of spread platelets. In contrast, PS-exposing platelets were PAC-1 negative, and bound plasminogen and fibrinogen in a protruding "cap." These data show that different subpopulations of platelets harbor plasminogen by diverse mechanisms and provide an essential scaffold for the accumulation of fibrinolytic proteins that mediate fibrinolysis under flow.

  8. Explicit isospectral flows associated to the AKNS operator on the unit interval. II

    Science.gov (United States)

    Amour, Laurent

    2012-10-01

    Explicit flows associated to any tangent vector fields on any isospectral manifold for the AKNS operator acting in L2 × L2 on the unit interval are written down. The manifolds are of infinite dimension (and infinite codimension). The flows are called isospectral and also are Hamiltonian flows. It is proven that they may be explicitly expressed in terms of regularized determinants of infinite matrix-valued functions with entries depending only on the spectral data at the starting point of the flow. The tangent vector fields are decomposed as ∑ξkTk where ξ ∈ ℓ2 and the Tk ∈ L2 × L2 form a particular basis of the tangent vector spaces of the infinite dimensional manifold. The paper here is a continuation of Amour ["Explicit isospectral flows for the AKNS operator on the unit interval," Inverse Probl. 25, 095008 (2009)], 10.1088/0266-5611/25/9/095008 where, except for a finite number, all the components of the sequence ξ are zero in order to obtain an explicit expression for the isospectral flows. The regularized determinants induce counter-terms allowing for the consideration of finite quantities when the sequences ξ run all over ℓ2.

  9. Data Mining of Front Pages of Medical Records Based on Association Rules%基于关联规则的病案首页数据挖掘

    Institute of Scientific and Technical Information of China (English)

    杜军; 郭慧敏; 杜静静; 李宁; 黄路非; 杨建南

    2016-01-01

    Objectives To find the association rules of each index of discharged patients’information in the use of Apriori algorithm, provide a theoretical basis for hospital management and decision making. Methods Apriori correlation analysis was conducted on discharged patients in 2015 with the application of R software, to explore gender department and hospital, medical treatment, hospital departments, hospitalization days and total expenses, medical treatment, hospital departments and association rules whether the operation, and analyzed its causes. Results After the field analysis on the front pages of medical records of 49737 cases of patients discharged in 2015, we found the rules below:the discharged number in respiratory ward, digestion ward, general surgery ward, male were more than female patients, and the confidence of the strong association rules were 0.621, 0.531,0.518;in neurology ward and ophthalmology ward, female were more than male in discharged patients, and the confidence of the strong association rules were 0.565, 0.561;health care hospital hospitalization expenses was closely related with the duration of hospitalization, and the confidence of the strong association rules were 0.731、0.649、0.745、0.545;whether to adopt surgical treatment and there was a close relationship between departments, and the confidence of the strong association rules were 0.951、0.748、0.985、0.974、0.735. Conclusions The potential association rules of association rules could explore different indicators, and provide the basis for hospital management and policy decision.%目的:利用Apriori算法找到出院患者信息各个指标中的关联规则,为医院管理和决策提供理论依据。方法利用R软件中的arules包对2015年某院出院患者做Apriori关联分析,探索出院科室与性别,费别、出院科室、住院天数与总费用,费别、出院科室与是否手术的关联规则,并分析其原因。结果对2015

  10. Mean arterial pressure change associated with cerebral blood flow in healthy older adults.

    Science.gov (United States)

    Deverdun, Jeremy; Akbaraly, Tasnime N; Charroud, Celine; Abdennour, Meriem; Brickman, Adam M; Chemouny, Stephane; Steffener, Jason; Portet, Florence; Bonafe, Alain; Stern, Yaakov; Ritchie, Karen; Molino, François; Le Bars, Emmanuelle; Menjot de Champfleur, Nicolas

    2016-10-01

    We investigate over a 12-year period the association between regional cerebral blood flow (CBF) and cardiovascular risk factors in a prospective cohort of healthy older adults (81.96 ± 3.82 year-old) from the Cognitive REServe and Clinical ENDOphenotype (CRESCENDO) study. Cardiovascular risk factors were measured over 12 years, and gray matter CBF was measured at the end of the study from high-resolution magnetic resonance imaging using arterial spin labeling. The association between cardiovascular risk factors, their long-term change, and CBF was assessed using multivariate linear regression models. Women were observed to have higher CBF than men (p < 0.05). Increased mean arterial pressure (MAP) over the 12-year period was correlated with a low cerebral blood flow (p < 0.05, R(2) = 0.21), whereas no association was detected between CBF and MAP at the time of imaging. High levels of glycemia tended to be associated with low cerebral blood flow values (p < 0.05). Age, alcohol consumption, smoking status, body mass index, history of cardiovascular disease, and hypertension were not associated with CBF. Our main result suggests that change in MAP is the most significant predictor of future CBF in older adults.

  11. Improved association rules and its application in Computer Forensics%关联规则改进及其在计算机取证中的应用

    Institute of Scientific and Technical Information of China (English)

    刘锋; 詹焰霞; 陈玉萍

    2012-01-01

    随着科学技术的发展,计算机早已走进千家万户,由此带来的计算机犯罪等一系列问题也越发引起社会的关注,而计算机取证是遏制这种行为的一个强有力的工具。本文将计算机取证技术与数据挖掘中的关联规则挖掘结合起来,首先介绍了数据挖掘和关联规则的相关概念,提出了关联规则挖掘中最典型的Apriori算法,并总结了其不足之处,然后针对不足提出了基于排序的apriori改进算法,提高了算法的效率,并将之运用到计算机取证中,通过具体实例验证了其可行性。%With the development of science and technology, computer has already gone into thousands of households, which brings a series of problems such as computer crime which is also increasingly attracted the attention of the society, and computer forensics is a powerful tool to curb the behavior. In this paper, the technology of computer forensics and association rules mining are combined, first introduced the data mining, association rule and the related concept, and then proposed the typical Apriori algorithm of associa- tion rules mining, and summarizes its deficiency, then put forward the improved Apriori algorithm based on sort, improves the effi- ciency of algorithm, and apply it to computer forensics, through specific example test and verify its feasibility.

  12. On the Mining Algorithm Based on BDIF Association Rule%基于BDIF的关联规则挖掘算法研究

    Institute of Scientific and Technical Information of China (English)

    郭昌建

    2015-01-01

    This article describes research on association rule mining and classification methods of association rules, analyzes and evaluates the classic Apriori algorithm, which gives rise to an efficient frequent BDIF (Based Transactional Databases Including Frequent Item Set) algorithm. It thereby reduces scanning data block and improves algorithm efficiency by dividing data block and quickly searching for frequent item set.%阐述了关联规则挖掘的研究情况,关联规则的分类方法等,对经典Apriori算法进行了分析和评价,在此基础上提出了一种高效产生频繁集的BDIF(Based Transactional Databases Including Frequent ItemSet)算法;它通过划分数据块,快速的搜寻频繁项目集,从而减少对数据块的扫描次数,提高了算法的效率。并用BorlandC++Builder6.0开发环境来调试、验证该算法。

  13. Price Adjustment by Mining Negative Association Rules%基于负关联规则挖掘的价格调整

    Institute of Scientific and Technical Information of China (English)

    黄发良; 郑小建; 张师超

    2006-01-01

    定制优良的产品价格是激烈竞争的市场中一个关键,基于负关联规则挖掘的技术提出一种新的定价方法,它可通过人力参与和完全自动两种方式进行,该方法具有易操作与易扩展的优点.实验表明该方法是有效的.%Well-determining product price has been a crucial problem in marketing competition. A novel pricing method based on negative association rules identified from past data is proposed, which is easily-manipulated and well-extended for end users. In our approach, an optimal price can be generated with two alternative strategies: human-assisted pricing strategy and automatic pricing strategy. In addition, an efficient algorithm for generating short negative association rules is devised. The results show that the approach is promising and efficient.

  14. Book Lending Data Mining Based on Association Rules%基于关联规则的图书借阅数据挖掘

    Institute of Scientific and Technical Information of China (English)

    吴玉春; 龙小建

    2016-01-01

    Based on the university libraries’ actual business needs, this article uses association rules to analyze book lending data of students in university libraries. First the article puts forward library history lending data pretreatment, including data cleaning, data integration, data transformation and transactional database construction. Then we apply MFP-Miner algorithm to the transaction database mining, aiming to excavate the association rules of lending books, providing scientific data support for lending books and books services, so as to enhance the university libraries’ service quality.%文章根据高校图书馆的实际业务需要,运用关联规则对高校图书馆学生的借阅数据进行了挖掘分析。首先将图书馆历史借阅数据进行预处理,预处理包括对数据进行清理、集成、转换以及建立事务数据库;然后利用关联规则挖掘算法(MFP-Miner算法)对事务数据库进行挖掘处理,挖掘出图书借阅的关联规则,为图书借阅、图书推荐等服务提供科学的数据支持,从而提升图书馆服务质量。

  15. NARG Algorithm of Extracting Non-redundant Association Rule in Concept Lattice%概念格上无冗余关联规则的提取算法NARG

    Institute of Scientific and Technical Information of China (English)

    苗茹; 沈夏炯; 胡小华

    2009-01-01

    Association roles are the very valuable kind of law in data mining. A large number of rules arc usually generated from database using ordinary mining algorithms. Especially when the minimal support and minimal confidence are reduced, the number of association rules rise rapidly. The key of eliminating redundant association rules is to reduce rules without losing data information. This paper presents a new algorithm called NARG to extract non-redundant association rules based on concept lattice and properties of redundant association rules. This algorithm can gain the minimal non-redundant set of association rules while effectively improve efficiency of extracting rules without losing any information of data.%在数据挖掘中,关联规则是很有价值的一类规律.普通的挖掘算法会产生大量的规则,尤其是当最小支持度和最小可信度减少时,关联规则的数目急剧上升.如何对规则进行约减而又不丢失数据信息是消除冗余关联规则的关键.根据概念格的理论和冗余关联规则的性质,提出在概念格上提取无冗余关联规则的NARG算法.该算法可以得到最小的无冗余的关联规则集,而且不丢失任何信息,可有效提高关联规则生成的效率.

  16. Optimal experience and optimal identity: A multinational study of the associations between flow and social identity

    Directory of Open Access Journals (Sweden)

    Yanhui eMao

    2016-02-01

    Full Text Available Eudaimonistic identity theory posits a link between activity and identity, where a self-defining activity promotes the strength of a person’s identity. An activity engaged in with high enjoyment, full involvement, and high concentration can facilitate the subjective experience of flow. In the present paper, we hypothesised in accordance with the theory of psychological selection that beyond the promotion of individual development and complexity at the personal level, the relationship between flow and identity at the social level is also positive through participation in self-defining activities. Three different samples (i.e., American, Chinese, and Spanish filled in measures for flow and social identity, with reference to four previously self-reported activities, characterized by four different combinations of skills (low versus high and challenges (low versus high. Findings indicated that flow was positively associated with social identity across each of the above samples, regardless of participants’ gender and age. The results have implications for increasing social identity via participation in self-defining group activities that could facilitate flow.

  17. Optimal Experience and Optimal Identity: A Multinational Study of the Associations Between Flow and Social Identity.

    Science.gov (United States)

    Mao, Yanhui; Roberts, Scott; Pagliaro, Stefano; Csikszentmihalyi, Mihaly; Bonaiuto, Marino

    2016-01-01

    Eudaimonistic identity theory posits a link between activity and identity, where a self-defining activity promotes the strength of a person's identity. An activity engaged in with high enjoyment, full involvement, and high concentration can facilitate the subjective experience of flow. In the present paper, we hypothesized in accordance with the theory of psychological selection that beyond the promotion of individual development and complexity at the personal level, the relationship between flow and identity at the social level is also positive through participation in self-defining activities. Three different samples (i.e., American, Chinese, and Spanish) filled in measures for flow and social identity, with reference to four previously self-reported activities, characterized by four different combinations of skills (low vs. high) and challenges (low vs. high). Findings indicated that flow was positively associated with social identity across each of the above samples, regardless of participants' gender and age. The results have implications for increasing social identity via participation in self-defining group activities that could facilitate flow.

  18. Collaboration rules.

    Science.gov (United States)

    Evans, Philip; Wolf, Bob

    2005-01-01

    Corporate leaders seeking to boost growth, learning, and innovation may find the answer in a surprising place: the Linux open-source software community. Linux is developed by an essentially volunteer, self-organizing community of thousands of programmers. Most leaders would sell their grandmothers for workforces that collaborate as efficiently, frictionlessly, and creatively as the self-styled Linux hackers. But Linux is software, and software is hardly a model for mainstream business. The authors have, nonetheless, found surprising parallels between the anarchistic, caffeinated, hirsute world of Linux hackers and the disciplined, tea-sipping, clean-cut world of Toyota engineering. Specifically, Toyota and Linux operate by rules that blend the self-organizing advantages of markets with the low transaction costs of hierarchies. In place of markets' cash and contracts and hierarchies' authority are rules about how individuals and groups work together (with rigorous discipline); how they communicate (widely and with granularity); and how leaders guide them toward a common goal (through example). Those rules, augmented by simple communication technologies and a lack of legal barriers to sharing information, create rich common knowledge, the ability to organize teams modularly, extraordinary motivation, and high levels of trust, which radically lowers transaction costs. Low transaction costs, in turn, make it profitable for organizations to perform more and smaller transactions--and so increase the pace and flexibility typical of high-performance organizations. Once the system achieves critical mass, it feeds on itself. The larger the system, the more broadly shared the knowledge, language, and work style. The greater individuals' reputational capital, the louder the applause and the stronger the motivation. The success of Linux is evidence of the power of that virtuous circle. Toyota's success is evidence that it is also powerful in conventional companies.

  19. Control of unsteady separated flow associated with the dynamic stall of airfoils

    Science.gov (United States)

    Wilder, M. C.

    1995-01-01

    An effort to understand and control the unsteady separated flow associated with the dynamic stall of airfoils was funded for three years through the NASA cooperative agreement program. As part of this effort a substantial data base was compiled detailing the effects various parameters have on the development of the dynamic stall flow field. Parameters studied include Mach number, pitch rate, and pitch history, as well as Reynolds number (through two different model chord lengths) and the condition of the boundary layer at the leading edge of the airfoil (through application of surface roughness). It was found for free stream Mach numbers as low as 0.4 that a region of supersonic flow forms on the leading edge of the suction surface of the airfoil at moderate angles of attack. The shocks which form in this supersonic region induce boundary-layer separation and advance the dynamic stall process. Under such conditions a supercritical airfoil profile is called for to produce a flow field having a weaker leading-edge pressure gradient and no leading-edge shocks. An airfoil having an adaptive-geometry, or dynamically deformable leading edge (DDLE), is under development as a unique active flow-control device. The DDLE, formed of carbon-fiber composite and fiberglass, can be flexed between a NACA 0012 profile and a supercritical profile in a controllable fashion while the airfoil is executing an angle-of-attack pitch-up maneuver. The dynamic stall data were recorded using point diffraction interferometry (PDI), a noninvasive measurement technique. A new high-speed cinematography system was developed for recording interferometric images. The system is capable of phase-locking with the pitching airfoil motion for real-time documentation of the development of the dynamic stall flow field. Computer-aided image analysis algorithms were developed for fast and accurate reduction of the images, improving interpretation of the results.

  20. Culturing pancreatic islets in microfluidic flow enhances morphology of the associated endothelial cells.

    Directory of Open Access Journals (Sweden)

    Krishana S Sankar

    Full Text Available Pancreatic islets are heavily vascularized in vivo with each insulin secreting beta-cell associated with at least one endothelial cell (EC. This structure is maintained immediately post-isolation; however, in culture the ECs slowly deteriorate, losing density and branched morphology. We postulate that this deterioration occurs in the absence of blood flow due to limited diffusion of media inside the tissue. To improve exchange of media inside the tissue, we created a microfluidic device to culture islets in a range of flow-rates. Culturing the islets from C57BL6 mice in this device with media flowing between 1 and 7 ml/24 hr resulted in twice the EC-density and -connected length compared to classically cultured islets. Media containing fluorescent dextran reached the center of islets in the device in a flow-rate-dependant manner consistent with improved penetration. We also observed deterioration of EC morphology using serum free media that was rescued by addition of bovine serum albumin, a known anti-apoptotic signal with limited diffusion in tissue. We further examined the effect of flow on beta-cells showing dampened glucose-stimulated Ca(2+-response from cells at the periphery of the islet where fluid shear-stress is greatest. However, we observed normal two-photon NAD(PH response and insulin secretion from the remainder of the islet. These data reveal the deterioration of islet EC-morphology is in part due to restricted diffusion of serum albumin within the tissue. These data further reveal microfluidic devices as unique platforms to optimize islet culture by introducing intercellular flow to overcome the restricted diffusion of media components.

  1. Rule, Britannia

    DEFF Research Database (Denmark)

    Christensen, Jørgen Riber

    2011-01-01

    Thomas Arne’s The Masque of Alfred (1740) with a libretto by James Thomson and David Mallet was written and performed in the historical context of George II’s reign where a kind of constitutional monarchy based on the Bill of Rights from 1689 was granting civil rights to the early bourgeoisie...... of the Proms, and this article considers it as a global real-time media event. “Rule, Britannia!” is placed in the contexts of political history, cultural history and experience economy....

  2. Elevational speciation in action? Restricted gene flow associated with adaptive divergence across an altitudinal gradient

    Science.gov (United States)

    Funk, W. C.; Murphy, M.A.; Hoke, K. L.; Muths, Erin L.; Amburgey, Staci M.; Lemmon, Emily M.; Lemmon, A. R.

    2016-01-01

    Evolutionary theory predicts that divergent selection pressures across elevational gradients could cause adaptive divergence and reproductive isolation in the process of ecological speciation. Although there is substantial evidence for adaptive divergence across elevation, there is less evidence that this restricts gene flow. Previous work in the boreal chorus frog (Pseudacris maculata) has demonstrated adaptive divergence in morphological, life history and physiological traits across an elevational gradient from approximately 1500–3000 m in the Colorado Front Range, USA. We tested whether this adaptive divergence is associated with restricted gene flow across elevation – as would be expected if incipient speciation were occurring – and, if so, whether behavioural isolation contributes to reproductive isolation. Our analysis of 12 microsatellite loci in 797 frogs from 53 populations revealed restricted gene flow across elevation, even after controlling for geographic distance and topography. Calls also varied significantly across elevation in dominant frequency, pulse number and pulse duration, which was partly, but not entirely, due to variation in body size and temperature across elevation. However, call variation did not result in strong behavioural isolation: in phonotaxis experiments, low-elevation females tended to prefer an average low-elevation call over a high-elevation call, and vice versa for high-elevation females, but this trend was not statistically significant. In summary, our results show that adaptive divergence across elevation restricts gene flow in P. maculata, but the mechanisms for this potential incipient speciation remain open.

  3. Application of scaling-rule theory in crustal rock fracture to studying characteristics of seismological precursors associated with M=6.1 Shandan-Minle earthquake

    Institute of Scientific and Technical Information of China (English)

    RONG Dai-lu; LI Ya-rong; HAN Xiao-ming

    2006-01-01

    In the paper, we introduce Allegre's scaling-rule theory of rock fracture and the probability to develop a method for predicting earthquake occurrence time on its basis. As an example, we study the characteristics of seismological precursors (seismic spatial correlation length and coda Qc) associated with the earthquake (M=6.1) occurred in Shandan-Minle, Gansu Province. The results show an increasing trend of seismic spatial correlation length and coda Qc before the earthquake. And a power exponent relation is used to fit the increasing variation form of these two parameters. The study has provided a basis for creating a method and finding indexes to predict the earthquake occurrence time by using the monitored seismic spatial correlation length and coda Qc.

  4. Nonzero Solubility Rule

    Institute of Scientific and Technical Information of China (English)

    尉志武; 周蕊; 刘芸

    2002-01-01

    A solubility-related rule, nonzero solubility rule, is introduced in this paper. It is complementary to the existing rules such as the "like dissolves like" rule and can be understood on the basis of classical chemical thermodynamics.

  5. 基于Apriori算法的购物篮关联规则分析%Apriori Algorithm Based on Association Rules Analysis of the Shopping Basket

    Institute of Scientific and Technical Information of China (English)

    赵祖应; 丁勇; 邓平

    2012-01-01

    Data mining is the new discipline evolved due to the need of information retrieval from immense amount of data in databases.It relates to subjects in statistics,machine learning,database technique,pattern recognition,artificial intelligence,etc.The competition in IT jobs market is enormous,and data mining-the core technique in data processingis gaining more and more attention.Association rules are commonly used to figure out what relations exist between different data sets in transactional databases and to find out further the customers′purchasing behavior pattern,for example,the influence on customers′buying other products after having bought some kind of products.These rules can be applied in supermarkets to product shelf design,goods deposit and classification of customers according to customers′purchasing pattern.Through discovering of the association rules the development and trend of the underlying objects can be better realized and mastered.In marketing and business investment data mining plays an important role.%数据挖掘是适应信息社会从海量的数据库中提取信息的需要而产生的新学科。它是统计学、机器学习、数据库、模式识别、人工智能等学科的交叉。IT就业市场竞争已经相当激烈,而数据处理的核心技术——数据挖掘更是得到了前所未有的重视。关联规则一般用以发现交易数据库中不同商品(项)之间的联系,用这些规则找出顾客的购买行为模式,比如购买了某一种商品对购买其他商品的影响,这种规则可以应用于超市商品货架设计、货物摆放以及根据购买模式对用户进行分类等。通过发现这个关联的规则,可以更好地了解和掌握事物的发展、动向等。在市场营销、企业投资中具有重要的作用。

  6. 关联规则评分预测的协同过滤推荐算法%Collaborative Filtering Recommendation Algorithm Based on Association Rule Score Prediction

    Institute of Scientific and Technical Information of China (English)

    王竹婷

    2016-01-01

    协同过滤算法是目前应用于电子商务个性化推荐系统中的一种最成功的推荐算法。为缓解因数据稀疏性问题导致的算法推荐质量下降,将关联规则分析引入协同过滤算法中,预测部分未评分项目的评分值,再运用传统的基于用户的协同过滤算法实施推荐。实验结果表明:与传统的协同过滤算法相比,采用关联规则预测评分可以一定程度提高算法推荐质量。%Collaborative filtering algorithm is one of the most successful recommendation algorithms ap-plied to the personalized recommendation system of E-commerce.In order to alleviate the problem of the algorithm recommendation quality decline that caused by the data sparse,the association rule anal-ysis is introduced into the collaborative filtering algorithm,which predicts the item ratings of the non rating items,and then uses the traditional user_based collaborative filtering algorithm to implement the recommendation.The experimental results show that compared with the traditional collaborative filte-ring algorithm,the algorithm uses association rules to predict the item ratings can improve the recom-mended quality.

  7. Debris Flow Vulnerability Assessment in Urban Area Associated with Landslide Hazard Map : Application to Busan, Korea

    Science.gov (United States)

    Okjeong, Lee; Yoonkyung, Park; Mookwang, Sung; Sangdan, Kim

    2016-04-01

    In this presentation, an urban debris flow disaster vulnerability assessment methodology is suggested with major focus on urban social and economic aspect. The proposed methodology is developed based on the landslide hazard maps that Korean Forest Service has utilized to identify landslide source areas. Frist, debris flows are propagated to urban areas from such source areas by Flow-R model, and then urban vulnerability is evaluated by two categories; physical and socio-economic aspect. The physical vulnerability is associated to buildings that can be broken down by a landslide event directly. This study considers two popular building structure types, reinforced concrete frame and non-reinforced concretes frame, to evaluate the physically-based vulnerability. The socio-economic vulnerability is measured as a function of the resistant levels of the exposed people, the intensity and magnitude of indirect or intangible losses, and preparedness level of the local government. An indicator-based model is established to evaluate the life and indirect loss under urban debris flow disasters as well as the resilience ability against disasters. To illuminate the validity of the suggested methodology, physical and socio-economic vulnerability levels are investigated for Daejeon, Korea using the proposed approach. The results reveal that the higher population density areas under a weaker fiscal condition that are located at the downstream of mountainous areas are more vulnerable than the areas in opposite conditions. Key words: Debris flow disasters, Physical vulnerability, Socio-economic Vulnerability, Urban Acknowledgement This research was supported by a grant(13SCIPS04) from Smart Civil Infrastructure Research Program funded by Ministry of Land, Infrastructure and Transport(MOLIT) of Korea government and Korea Agency for Infrastructure Technology Advancement(KAIA).

  8. Pacific Basin tsunami hazards associated with mass flows in the Aleutian arc of Alaska

    Science.gov (United States)

    Waythomas, Christopher F.; Watts, Philip; Shi, Fengyan; Kirby, James T.

    2009-01-01

    that range from 40 to 80 km, maximum thicknesses of 400–800 m, and maximum widths of 10–40 km. We also evaluate tsunami generation by volcanic debris avalanches associated with flank collapse, at four locations (Makushin, Cleveland, Seguam and Yunaska SW volcanoes), which represent large to moderate sized events in this region. We calculate tsunami sources using the numerical model TOPICS and simulate wave propagation across the Pacific using a spherical Boussinesq model, which is a modified version of the public domain code FUNWAVE. Our numerical simulations indicate that geologically plausible mass flows originating in the North Pacific near the Aleutian Islands can indeed generate large local tsunamis as well as large transoceanic tsunamis. These waves may be several meters in elevation at distal locations, such as Japan, Hawaii, and along the North and South American coastlines where they would constitute significant hazards.

  9. Hepatic encephalopathy is associated with decreased cerebral oxygen metabolism and blood flow, not increased ammonia uptake

    DEFF Research Database (Denmark)

    Dam, Gitte; Keiding, Susanne; Munk, Ole L

    2013-01-01

    Studies have shown decreased cerebral oxygen metabolism (CMRO(2)) and blood flow (CBF) in patients with cirrhosis with hepatic encephalopathy (HE). It remains unclear, however, whether these disturbances are associated with HE or with cirrhosis itself and how they may relate to arterial blood...... ammonia concentration and cerebral metabolic rate of blood ammonia (CMRA). We addressed these questions in a paired study design by investigating patients with cirrhosis during and after recovery from an acute episode of HE type C. CMRO(2), CBF, and CMRA were measured by dynamic positron emission...

  10. UPIOM: a new tool of MFA and its application to the flow of iron and steel associated with car production.

    Science.gov (United States)

    Nakamura, Shinichiro; Kondo, Yasushi; Matsubae, Kazuyo; Nakajima, Kenichi; Nagasaka, Tetsuya

    2011-02-01

    Identification of the flow of materials and substances associated with a product system provides useful information for Life Cycle Analysis (LCA), and contributes to extending the scope of complementarity between LCA and Materials Flow Analysis/Substances Flow Analysis (MFA/SFA), the two major tools of industrial ecology. This paper proposes a new methodology based on input-output analysis for identifying the physical input-output flow of individual materials that is associated with the production of a unit of given product, the unit physical input-output by materials (UPIOM). While the Sankey diagram has been a standard tool for the visualization of MFA/SFA, with an increase in the complexity of the flows under consideration, which will be the case when economy-wide intersectoral flows of materials are involved, the Sankey diagram may become too complex for effective visualization. An alternative way to visually represent material flows is proposed which makes use of triangulation of the flow matrix based on degrees of fabrication. The proposed methodology is applied to the flow of pig iron and iron and steel scrap that are associated with the production of a passenger car in Japan. Its usefulness to identify a specific MFA pattern from the original IO table is demonstrated.

  11. Perspectives on Knowledge Discovery Algorithms Recently Introduced in Chemoinformatics: Rough Set Theory, Association Rule Mining, Emerging Patterns, and Formal Concept Analysis.

    Science.gov (United States)

    Gardiner, Eleanor J; Gillet, Valerie J

    2015-09-28

    Knowledge Discovery in Databases (KDD) refers to the use of methodologies from machine learning, pattern recognition, statistics, and other fields to extract knowledge from large collections of data, where the knowledge is not explicitly available as part of the database structure. In this paper, we describe four modern data mining techniques, Rough Set Theory (RST), Association Rule Mining (ARM), Emerging Pattern Mining (EP), and Formal Concept Analysis (FCA), and we have attempted to give an exhaustive list of their chemoinformatics applications. One of the main strengths of these methods is their descriptive ability. When used to derive rules, for example, in structure-activity relationships, the rules have clear physical meaning. This review has shown that there are close relationships between the methods. Often apparent differences lie in the way in which the problem under investigation has been formulated which can lead to the natural adoption of one or other method. For example, the idea of a structural alert, as a structure which is present in toxic and absent in nontoxic compounds, leads to the natural formulation of an Emerging Pattern search. Despite the similarities between the methods, each has its strengths. RST is useful for dealing with uncertain and noisy data. Its main chemoinformatics applications so far have been in feature extraction and feature reduction, the latter often as input to another data mining method, such as an Support Vector Machine (SVM). ARM has mostly been used for frequent subgraph mining. EP and FCA have both been used to mine both structural and nonstructural patterns for classification of both active and inactive molecules. Since their introduction in the 1980s and 1990s, RST, ARM, EP, and FCA have found wide-ranging applications, with many thousands of citations in Web of Science, but their adoption by the chemoinformatics community has been relatively slow. Advances, both in computer power and in algorithm development

  12. Association of Indicators of Dehydration and Haemoconcentration with the Coronary Slow Flow Phenomenon

    Directory of Open Access Journals (Sweden)

    Suzan Hatipoğlu

    2010-08-01

    Full Text Available Objectives: The coronary slow flow phenomenon (CSFP, characterized by decreased distal progression of dye to coronary arteries, is a distinct angiographic phenomenon and little is known about its pathophysiology. Although several hypotheses have been suggested, the underlying mechanism of CSFP has not been well established yet.The aim of this study was to determine the roles of indicators of dehydration and haemoconcentration in CSFP which have blood flow abnormality effects. Methods: The study consisted of 33 patients with CSFP (group 1, and 31 normal subjects as control group (group 2 detected by coronary angiography. CSFP was diagnosed by the TIMI frame count method. Serum electrolytes, osmolarity and haematological parameters were measured. Results: Compared with control subjects, patient with CSFP had increased levels of calculated osmolarity, tonicity, sodium, glucose and blood urea nitrogen (BUN. Significant differences were also observed in the haematocrit, haemoglobin concentration, and calculated osmolarity but not in total cholesterol and albumin. Conclusions: The results of the present study indicate that the markers of haemoconcentration and dehydration are significantly associated with CSFP. The markers may be important in the coronary blood flow anomaly.

  13. Channel and tube flow features associated with the Twin Craters Lava Flow, Zuni-Bandera Volcanic Field, NM: Insights into similar features on Mars

    Science.gov (United States)

    Samuels, R.; deWet, A.; Bleacher, J. E.; von Meerscheidt, H. C.; Hamilton, C.; Garry, W. B.

    2013-12-01

    The Zuni-Bandera Volcanic Field lies near the center of the Jemez lineament that extends from central Arizona to northeastern New Mexico. The Jemez lineament is a result of rifting in the Earth's crust and is associated with volcanic activity that spans the last 16 Ma. The youngest volcanic activity associated with the lineament includes basaltic lava that was erupted 3 ka ago to form the McCartys Flow. The Twin Craters flow is moderately older (18.0 ka), but it also well-preserved and provides an ideal location to investigate volcanic processes and landforms. In this study, we combined detailed field observations and mapping with remote sensing to better understand variations in morphology along the transport system of the flow . The Twin Craters flow is characterized as an aā and tube-fed pāhoehoe flow with braided or branching tubes and channels; and associated aā and pāhoehoe break-outs. It is possible that the variations in morphology along the same transport structure might be related to pre-flow slope, which might have also been variable along flow. Shatter ring features are thought to be related to changes in eruption rate, and therefore, local flux through the system. However, over-pressurization of the tube might also be related to changes in local discharge rate associated with the ponding and release of lava within the transport system that may be due to interactions between the lava and obstacles along the flow's path (see Mallonee et al., this meeting). Many of these features are similar to features present in the Tharsis Montes region of Mars and particularly on the southern apron of Ascraeus Mons. The detailed description of the morphology of the Twin Craters Lava Flow and the understanding of the emplacement mechanisms will be crucial in identifying the processes that formed the Ascraeus flows and channels. This will aid in determining if the lava surface textures are directly related to eruption conditions or if they have been significantly

  14. Transcranial magnetic stimulation-induced global propagation of transient phase resetting associated with directional information flow

    Directory of Open Access Journals (Sweden)

    Masahiro eKawasaki

    2014-03-01

    Full Text Available Electroencephalogram (EEG phase synchronization analyses can reveal large-scale communication between distant brain areas. However, it is not possible to identify the directional information flow between distant areas using conventional phase synchronization analyses. In the present study, we applied transcranial magnetic stimulation (TMS to the occipital area in subjects who were resting with their eyes closed, and analyzed the spatial propagation of transient TMS-induced phase resetting by using the transfer entropy (TE, to quantify the causal and directional flow of information. The time-frequency EEG analysis indicated that the theta (5 Hz phase locking factor (PLF reached its highest value at the distant area (the motor area in this study, with a time lag that followed the peak of the transient PLF enhancements of the TMS-targeted area at the TMS onset. PPI (phase-preservation index analyses demonstrated significant phase resetting at the TMS-targeted area and distant area. Moreover, the TE from the TMS-targeted area to the distant area increased clearly during the delay that followed TMS onset. Interestingly, the time lags were almost coincident between the PLF and TE results (152 vs. 165 ms, which provides strong evidence that the emergence of the delayed PLF reflects the causal information flow. Such tendencies were observed only in the higher-intensity TMS condition, and not in the lower-intensity or sham TMS conditions. Thus, TMS may manipulate large-scale causal relationships between brain areas in an intensity-dependent manner. We demonstrated that single-pulse TMS modulated global phase dynamics and directional information flow among synchronized brain networks. Therefore, our results suggest that single-pulse TMS can manipulate both incoming and outgoing information in the TMS-targeted area associated with functional changes.

  15. NCAA Rule 48: Origins and Reactions.

    Science.gov (United States)

    Wieder, Alan

    1986-01-01

    National Collegiate Athletic Association Rule 48 sets academic standards for high school which incoming freshmen must have met in order to receive a grant-in-aid and play intercollegiate athletics. The author discusses why tougher standards are needed, how Rule 48 operates, what problems are, and why there is opposition to the rule. (MT)

  16. Statistical inference of static analysis rules

    Science.gov (United States)

    Engler, Dawson Richards (Inventor)

    2009-01-01

    Various apparatus and methods are disclosed for identifying errors in program code. Respective numbers of observances of at least one correctness rule by different code instances that relate to the at least one correctness rule are counted in the program code. Each code instance has an associated counted number of observances of the correctness rule by the code instance. Also counted are respective numbers of violations of the correctness rule by different code instances that relate to the correctness rule. Each code instance has an associated counted number of violations of the correctness rule by the code instance. A respective likelihood of the validity is determined for each code instance as a function of the counted number of observances and counted number of violations. The likelihood of validity indicates a relative likelihood that a related code instance is required to observe the correctness rule. The violations may be output in order of the likelihood of validity of a violated correctness rule.

  17. Number-conserving cellular automaton rules

    CERN Document Server

    Boccara, N; Boccara, Nino; Fuks, Henryk

    1999-01-01

    A necessary and sufficient condition for a one-dimensional q-state n-input cellular automaton rule to be number-conserving is established. Two different forms of simpler and more visual representations of these rules are given, and their flow diagrams are determined. Various examples are presented and applications to car traffic are indicated. Two nontrivial three-state three-input self-conjugate rules have been found. They can be used to model the dynamics of random walkers.

  18. Spatio-Temporal Rule Mining

    DEFF Research Database (Denmark)

    Gidofalvi, Gyozo; Pedersen, Torben Bach

    2005-01-01

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

  19. Pengembangan Sistem Rekomendasi Penelusuran Buku dengan Penggalian Association Rule Menggunakan Algoritma Apriori (Studi Kasus Badan Perpustakaan dan Kearsipan Provinsi Jawa Timur

    Directory of Open Access Journals (Sweden)

    Nugroho Wandi

    2012-09-01

    Full Text Available Bapersip Provinsi Jawa Timur merupakan Badan Pemerintahan yang bertugas untuk melaksanakan penyusunan dan pelaksanaan kebijakan Daerah yang bersifat spesifik yaitu dibidang perpustakaan dan kearsipan. Berdasarkan data yang didapatkan dari tahun 2010 hingga 2012 (hingga bulan Maret, perbandingan masyarakat Surabaya dengan buku yang dipinjam hanya 1:76, yang artinya kesadaran masyarakat untuk membaca sangat minim.Untuk meningkatkan minat baca masyarakat Surabaya, penulis melakukan analisa terhadap histori dari transaksi peminjaman buku yang ada. Pemilihan data histori sebagai bahan analisa dikarenakan dari data ini bisa digali pola-pola asosiasi antar buku yang dipinjam pada transaksi-transaksi yang ada. Metode yang digunakan dalam identifikasi pola yang dimaksud adalah association rule dengan algoritma apriori. Metode dan algoritma ini menghasilkan transaksi-transaksi peminjaman buku dengan strong association (keterkaitan yang kuat antar buku dalam transaksi yang digunakan sebagai rekomendasi peminjaman buku yang membantu pengguna mendapatkan rekomendasi buku lain ketika pengguna melihat rincian dari buku yang dipilih atau hendak dipinjam. Dari hasil uji coba pada penelitian ini, ditemukan bahwa semakin besar minimum support (minsup dan minimum confidence (minconf, semakin sedikit waktu yang dibutuhkan untuk menghasilkan rekomendasi serta semakin sedikit rekomendasi yang diberikan, namun rekomendasi yang diberikan berasal dari transaksi yang sering muncul

  20. Associations between air pollution and peak expiratory flow among patients with persistent asthma.

    Science.gov (United States)

    Qian, Zhengmin; Lin, Hung-Mo; Chinchilli, Vernon M; Lehman, Erik B; Stewart, Walter F; Shah, Nirav; Duan, Yinkang; Craig, Timothy J; Wilson, William E; Liao, Duanping; Lazarus, Stephen C; Bascom, Rebecca

    2009-01-01

    Responses of patients with persistent asthma to ambient air pollution may be different from those of general populations. For example, asthma medications may modify the effects of ambient air pollutants on peak expiratory flow (PEF). Few studies examined the association between air pollution and PEF in patients with persistent asthma on well-defined medication regimens using asthma clinical trial data. Airway obstruction effects of ambient air pollutants, using 14,919 person-days of daily self-measured peak expiratory flow (PEF), were assessed from 154 patients with persistent asthma during the 16 wk of active treatment in the Salmeterol Off Corticosteroids Study trial. The three therapies were an inhaled corticosteroid, an inhaled long-acting beta-agonist, and placebo. The participants were nonsmokers aged 12 through 63 yr, recruited from 6 university-based ambulatory care centers from February 1997 to January 1999. Air pollution data were derived from the U.S. Environmental Protection Agency Aerometric Information Retrieval System. An increase of 10 ppb of ambient daily mean concentrations of NO2 was associated with a decrease in PEF of 1.53 L/min (95% confidence interval [CI] -2.93 to -0.14) in models adjusted for age, gender, race/ethnicity, asthma clinical center, season, week, daily average temperature, and daily average relative humidity. The strongest association between NO2 and PEF was observed among the patients treated with salmeterol. Negative associations were also found between PEF and SO2 and between PEF and PM(10), respectively. The results show that the two medication regimens protected against the effects of PM(10). However, salmeterol increased the sensitivity to NO2 and triamcinalone enhanced the sensitivity to SO2.

  1. Comparing Simple Flood Reservoir Operation Rules

    Directory of Open Access Journals (Sweden)

    James Connaughton

    2014-09-01

    Full Text Available The effectiveness of three simple flood operating rules in reducing the peak flow is compared for four simplified hydrograph shapes. The Minimize Flood Peak rule uses available flood storage capacity to store peak flows from an accurate hydrograph forecast. The less demanding Minimize Flooding Frequency operating rule releases water at or below channel capacity until the flood storage pool is filled and outflows are forced to exceed the channel capacity. The Short Forecast Peak Minimization rule minimizes flood peak over a short foreseeable future with existing flood storage capacity. Four simplified hydrograph shapes (triangular, abrupt wave, flood pulse and broad peak were used. The Minimize Flood Peak rule reduces peak flows better than alternatives, but is often impractical. The Short Forecast Peak Minimization rule reduces peak flows for a wide range of conditions. The Minimize Flood Frequency rule may be more relevant where damages occur abruptly, as in many leveed systems. All rules reduce peak outflow more efficiently for more steeply rising hydrographs. The approach suggests some general insights for flood operations of reservoirs.

  2. 一种面向时空数据的关联规则更新算法%An Updating Algorithm for Spatial and Temporal Data Association Rule

    Institute of Scientific and Technical Information of China (English)

    刘伯红; 王娟娟

    2015-01-01

    Most of the present updating association rule algorithms have drawbacks that produce a large number of can‐didate sets ,multiple scans of the database ,and have a little research on the spatial and temporal data .To solve this problem , an updating association rule algorithm based on sliding window is proposed in this paper which encodes access data in memory and then only mines the encoding data in memory directly ,without repeatedly reading the database information .Meanwhile , the algorithm adds a space constraints to filter irrelevant space data when generating candidate sets by frequent itemsets to improve the execution speed and processing performance .Experiment results show that the algorithm has higher mining effi‐ciency and has important application value for intelligent transportation ,command and control ,etc .%现有的关联规则更新算法大多具有产生大量候选项集和多次扫描数据库的弊端,而且对时空数据的研究少之又少。针对此问题,论文提出一种基于滑动窗口的关联规则更新算法,此算法将访问数据进行行程长度编码并存储于存储器中,然后只需对存储器中的编码数据进行挖掘,不需反复读取数据库信息。同时该算法在由频繁项集产生候选项集时添加了空间约束条件,过滤了空间不相关数据,提高了算法的执行速度和处理效能。通过实验论证,此算法具有更高的挖掘效率,对智能交通、指挥控制等领域有着重要的应用价值。

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

    NARCIS (Netherlands)

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

    2016-01-01

    Background: Unhealthy eating habits in adolescence lead to a wide variety of health problems and disorders. The aim of this study was to assess the prevalence of absence of parental rules on eating and unhealthy eating behaviour and to explore the relationships between parental rules on eating and a

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

    NARCIS (Netherlands)

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

    2016-01-01

    Background: Unhealthy eating habits in adolescence lead to a wide variety of health problems and disorders. The aim of this study was to assess the prevalence of absence of parental rules on eating and unhealthy eating behaviour and to explore the relationships between parental rules on eating and a

  5. Numerical Simulations of Texture Development and Associated Rheological Anisotropy in Regions of Complex Mantle Flow

    Science.gov (United States)

    Blackman, D. K.; Castelnau, O.; Becker, T. W.

    2008-12-01

    The aim of this study is to compare the predictions of different micromechanical approaches that have been employed recently to study mineral alignment during flow in the upper mantle. Computational capabilities are reaching a point where the potential rheological effects of such lattice-preferred orientation (LPO) can be considered as an integral part of determining the flow pattern and evolution. But, in order to have confidence in taking this next step, the detailed behavior of the different micromechanical models needs to be understood. An important consequence of LPO development is the subsequent anisotropy of the mechanical properties. Curiously, most published geophysical studies only address the elastic anisotropy, probably because of its link with the observed seismic anisotropy. The viscoplastic (or rheological) anisotropy has received much less attention, although it may have a notable influence on regional and global convective flow pattern, which in turn controls the LPO development. Micromechanical approaches aim at linking the rheological behaviour at the grain scale, associated with the activate deformation mechanisms (dislocation glide and climb, diffusion creep, "), with the overall rheology at the sample scale, including also other mechanisms such as recrystallization. This is achieved by an evaluation of the internal stress generated by the (strong) mechanical interaction between neighbour grains. All models proposed in the literature (kinematic model, finite strain model, tangent self-consistent model, lower bound model, ") make simplifying assumptions, since the mechanical problem is very complicated. One can distinguish between rather simple models that allow some freedom in deformation of individual grains, and more advanced techniques (and generally more accurate) that require a minimum number (=4) of independent slip systems (or directional deformation mechanisms) for the plastic strain to occur. In respect to this, unlike all other models

  6. Mindset Changes Lead to Drastic Impairments in Rule Finding

    Science.gov (United States)

    ErEl, Hadas; Meiran, Nachshon

    2011-01-01

    Rule finding is an important aspect of human reasoning and flexibility. Previous studies associated rule finding "failure" with past experience with the test stimuli and stable personality traits. We additionally show that rule finding performance is severely impaired by a mindset associated with applying an instructed rule. The mindset was…

  7. Transient flows of the solar wind associated with small-scale solar activity in solar minimum

    Science.gov (United States)

    Slemzin, Vladimir; Veselovsky, Igor; Kuzin, Sergey; Gburek, Szymon; Ulyanov, Artyom; Kirichenko, Alexey; Shugay, Yulia; Goryaev, Farid

    The data obtained by the modern high sensitive EUV-XUV telescopes and photometers such as CORONAS-Photon/TESIS and SPHINX, STEREO/EUVI, PROBA2/SWAP, SDO/AIA provide good possibilities for studying small-scale solar activity (SSA), which is supposed to play an important role in heating of the corona and producing transient flows of the solar wind. During the recent unusually weak solar minimum, a large number of SSA events, such as week solar flares, small CMEs and CME-like flows were observed and recorded in the databases of flares (STEREO, SWAP, SPHINX) and CMEs (LASCO, CACTUS). On the other hand, the solar wind data obtained in this period by ACE, Wind, STEREO contain signatures of transient ICME-like structures which have shorter duration (<10h), weaker magnetic field strength (<10 nT) and lower proton temperature than usual ICMEs. To verify the assumption that ICME-like transients may be associated with the SSA events we investigated the number of weak flares of C-class and lower detected by SPHINX in 2009 and STEREO/EUVI in 2010. The flares were classified on temperature and emission measure using the diagnostic means of SPHINX and Hinode/EIS and were confronted with the parameters of the solar wind (velocity, density, ion composition and temperature, magnetic field, pitch angle distribution of the suprathermal electrons). The outflows of plasma associated with the flares were identified by their coronal signatures - CMEs (only in few cases) and dimmings. It was found that the mean parameters of the solar wind projected to the source surface for the times of the studied flares were typical for the ICME-like transients. The results support the suggestion that weak flares can be indicators of sources of transient plasma flows contributing to the slow solar wind at solar minimum, although these flows may be too weak to be considered as separate CMEs and ICMEs. The research leading to these results has received funding from the European Union’s Seventh Programme

  8. EISCAT observations of unusual flows in the morning sector associated with weak substorm activity

    Directory of Open Access Journals (Sweden)

    N. J. Fox

    Full Text Available A discussion is given of plasma flows in the dawn and nightside high-latitude ionospheric regions during substorms occurring on a contracted auroral oval, as observed using the EISCAT CP-4-A experiment. Supporting data from the PACE radar, Greenland magnetometer chain, SAMNET magnetometers and geostationary satellites are compared to the EISCAT observations. On 4 October 1989 a weak substorm with initial expansion phase onset signatures at 0030 UT, resulted in the convection reversal boundary observed by EISCAT (at ~0415 MLT contracting rapidly poleward, causing a band of elevated ionospheric ion temperatures and a localised plasma density depletion. This polar cap contraction event is shown to be associated with various substorm signatures; Pi2 pulsations at mid-latitudes, magnetic bays in the midnight sector and particle injections at geosynchronous orbit. A similar event was observed on the following day around 0230 UT (~0515 MLT with the unusual and significant difference that two convection reversals were observed, both contracting poleward. We show that this feature is not an ionospheric signature of two active reconnection neutral lines as predicted by the near-Earth neutral model before the plasmoid is "pinched off", and present two alternative explanations in terms of (1 viscous and lobe circulation cells and (2 polar cap contraction during northward IMF. The voltage associated with the anti-sunward flow between the reversals reaches a maximum of 13 kV during the substorm expansion phase. This suggests it to be associated with the polar cap contraction and caused by the reconnection of open flux in the geomagnetic tail which has mimicked "viscous-like" momentum transfer across the magnetopause.

  9. Rule Changes Passed at the NCAA Convention.

    Science.gov (United States)

    Chronicle of Higher Education, 1987

    1987-01-01

    Recent changes in National Collegiate Athletic Association rules concerning academics, recruiting, amateurism, membership and classification, championships, playing and practice seasons, general policies, and eligibility are summarized. (MSE)

  10. Multivariate analyses with end-member mixing to characterize groundwater flow: Wind Cave and associated aquifers

    Science.gov (United States)

    Long, Andrew J.; Valder, Joshua F.

    2011-10-01

    SummaryPrincipal component analysis (PCA) applied to hydrochemical data has been used with end-member mixing to characterize groundwater flow to a limited extent, but aspects of this approach are unresolved. Previous similar approaches typically have assumed that the extreme-value samples identified by PCA represent end members. The method presented herein is different from previous work in that (1) end members were not assumed to have been sampled but rather were estimated and constrained by prior knowledge; (2) end-member mixing was quantified in relation to hydrogeologic domains, which focuses model results on major hydrologic processes; (3) a method to select an appropriate number of end members using a series of cluster analyses is presented; and (4) conservative tracers were weighted preferentially in model calibration, which distributed model errors of optimized values, or residuals, more appropriately than would otherwise be the case. The latter item also provides an estimate of the relative influence of geochemical evolution along flow paths in comparison to mixing. This method was applied to groundwater in Wind Cave and the associated karst aquifer in the Black Hills of South Dakota, USA. The end-member mixing model was used to test a hypothesis that five different end-member waters are mixed in the groundwater system comprising five hydrogeologic domains. The model estimated that Wind Cave received most of its groundwater inflow from local surface recharge with an additional 33% from an upgradient aquifer. Artesian springs in the vicinity of Wind Cave primarily received water from regional groundwater flow.

  11. Terahertz time-domain spectroscopy combined with fuzzy rule-building expert system and fuzzy optimal associative memory applied to diagnosis of cervical carcinoma.

    Science.gov (United States)

    Qi, Na; Zhang, Zhuoyong; Xiang, Yuhong; Yang, Yuping; Harrington, Peter de B

    2015-01-01

    Combined with terahertz time-domain spectroscopy, the feasibility of fast and reliable diagnosis of cervical carcinoma by a fuzzy rule-building expert system (FuRES) and a fuzzy optimal associative memory (FOAM) had been studied. The terahertz spectra of 52 specimens of cervix were collected in the work. The original data of samples were preprocessed by Savitzky-Golay first derivative (χderivative), principal component orthogonal signal correction (PC-OSC) and emphatic orthogonal signal correction to improve the performance of FuRES and FOAM models. The effect of the different pretreating methods to improve prediction accuracy was evaluated. The FuRES and FOAM models were validated using bootstrapped Latin-partition method. The obtained results showed that the FuRES and FOAM model optimized with the combination S-G first derivative and PC-OSC method had the better predictive ability with classification rates of 92.9 ± 0.4 and 92.5 ± 0.4 %, respectively. The proposed procedure proved that terahertz spectroscopy combined with fuzzy classifiers could supply a technology which has potential for diagnosis of cancerous tissue.

  12. FP-tree association rules algorithm in recommendation system%基于FP-tree算法的推荐系统设计与实现

    Institute of Scientific and Technical Information of China (English)

    刘华; 张亚昕

    2015-01-01

    当前是信息爆炸的时代,推荐系统已成为解决当前网络信息超载的有效工具。文章针对网上书店的电子商务网站的销售特点,详细地设计了推荐系统,并利用挖掘技术中的FP-tree关联规则算法实现数据挖掘运算,很好的实现了在线推荐的系统功能。%This is the era of information explosion, recommendation system has become an effective tool for solving the current network information overload. Aiming at the characteristics of online bookstores sell e-commerce site, a detailed design of the recommendation system, and using mining techniques in FP-tree data mining association rules algorithm computation, to achieve a good online recommendation system functions.

  13. Tree-Based Methods for Discovery of Association between Flow Cytometry Data and Clinical Endpoints.

    Science.gov (United States)

    Eliot, M; Azzoni, L; Firnhaber, C; Stevens, W; Glencross, D K; Sanne, I; Montaner, L J; Foulkes, A S

    2009-01-01

    We demonstrate the application and comparative interpretations of three tree-based algorithms for the analysis of data arising from flow cytometry: classification and regression trees (CARTs), random forests (RFs), and logic regression (LR). Specifically, we consider the question of what best predicts CD4 T-cell recovery in HIV-1 infected persons starting antiretroviral therapy with CD4 count between 200 and 350 cell/muL. A comparison to a more standard contingency table analysis is provided. While contingency table analysis and RFs provide information on the importance of each potential predictor variable, CART and LR offer additional insight into the combinations of variables that together are predictive of the outcome. In all cases considered, baseline CD3-DR-CD56+CD16+ emerges as an important predictor variable, while the tree-based approaches identify additional variables as potentially informative. Application of tree-based methods to our data suggests that a combination of baseline immune activation states, with emphasis on CD8 T-cell activation, may be a better predictor than any single T-cell/innate cell subset analyzed. Taken together, we show that tree-based methods can be successfully applied to flow cytometry data to better inform and discover associations that may not emerge in the context of a univariate analysis.

  14. Tree-Based Methods for Discovery of Association between Flow Cytometry Data and Clinical Endpoints

    Directory of Open Access Journals (Sweden)

    M. Eliot

    2009-01-01

    Full Text Available We demonstrate the application and comparative interpretations of three tree-based algorithms for the analysis of data arising from flow cytometry: classification and regression trees (CARTs, random forests (RFs, and logic regression (LR. Specifically, we consider the question of what best predicts CD4 T-cell recovery in HIV-1 infected persons starting antiretroviral therapy with CD4 count between 200 and 350 cell/μL. A comparison to a more standard contingency table analysis is provided. While contingency table analysis and RFs provide information on the importance of each potential predictor variable, CART and LR offer additional insight into the combinations of variables that together are predictive of the outcome. In all cases considered, baseline CD3-DR-CD56+CD16+ emerges as an important predictor variable, while the tree-based approaches identify additional variables as potentially informative. Application of tree-based methods to our data suggests that a combination of baseline immune activation states, with emphasis on CD8 T-cell activation, may be a better predictor than any single T-cell/innate cell subset analyzed. Taken together, we show that tree-based methods can be successfully applied to flow cytometry data to better inform and discover associations that may not emerge in the context of a univariate analysis.

  15. Association of arterial stiffness with coronary flow reserve in revascularized coronary artery disease patients

    Institute of Scientific and Technical Information of China (English)

    Vlassis Tritakis; Stavros Tzortzis; Ignatios Ikonomidis; Kleanthi Dima; Georgios Pavlidis; Paraskevi Trivilou; Ioannis Paraskevaidis; Giorgos Katsimaglis; John Parissis; John Lekakis

    2016-01-01

    AIM: To investigate the association of arterial wave reflection with coronary flow reserve(CFR) in coronary artery disease(CAD) patients after successful revascularization.METHODS: We assessed 70 patients with angiographically documented CAD who had undergone recent successful revascularization. We measured(1) reactive hyperemia index(RHI) using fingertip peripheral arterial tonometry(RH-PAT Endo-PAT);(2) carotid to femoral pulse wave velocity(PWVc-Complior);(3) augmentation index(AIx), the diastolic area(DAI%) and diastolic reflection area(DRA) of the central aortic pulse wave(Arteriograph);(4) CFR using Doppler echocardiography; and(5) blood levels of lipoprotein-phospholipase A2(LpPLA2).RESULTS: After adjustment for age, sex, blood pressure parameter, lipidemic, diabetic and smoking status, we found that coronary flow reserve was independently related to AIx(b =-0.38, r = 0.009), DAI(b = 0.36, P = 0.014), DRA(b = 0.39, P = 0.005) and RT(b =-0.29,P = 0.026). Additionally, patients with CFR < 2.5 had higher PWVc(11.6 ± 2.3 vs 10.2 ± 1.4 m/s, P = 0.019), SBPc(139.1 ± 17.8 vs 125.2 ± 19.1 mm Hg, P = 0.026), AIx(38.2% ± 14.8% vs 29.4% ± 15.1%, P = 0.011) and lower RHI(1.26 ± 0.28 vs 1.50 ± 0.46, P = 0.012), DAI(44.3% ± 7.9% vs 53.9% ± 6.7%, P = 0.008), DRA(42.2 ± 9.6 vs 51.6 ± 11.4, P = 0.012) and Lp PLA2(268.1 ± 91.9 vs 199.5 ± 78.4 ng/m L, P = 0.002) compared with those with CFR ≥ 2.5. Elevated Lp PLA2 was related with reduced CFR(r =-0.33, P = 0.001), RHI(r =-0.37, P < 0.001) and DRA(r =-0.35, P = 0.001) as well as increased PWVc(r = 0.34, P = 0.012) and AIx(r = 0.34, P = 0.001). CONCLUSION: Abnormal arterial wave reflections are related with impaired coronary flow reserve despite successful revascularization in CAD patients. There is a common inflammatory link between impaired aortic wall properties, endothelial dysfunction and coronary flow impairment in CAD.

  16. 大数据环境下相容数据集的关联规则数据挖掘%Data Mining Algorithm of Association Rules Among Compatible Datasets in Big Data Environment

    Institute of Scientific and Technical Information of China (English)

    张春生

    2016-01-01

    在对不可连接数据集充分分析的基础上,给出基于不可连接数据集的相容数据集和不相容数据集2个定义,给出相容数据集的一些基本理论,在这些理论基础上给出一个基于相容数据集的关联规则挖掘方案,实现每个相容数据集挖掘的关联规则直接合并,生成整个相容数据集的关联规则,实现普通数据挖掘算法无法实现的关联规则挖掘。方案扩展了关联规则算法的应用领域,提高了数据挖掘效率,在一定程度上也实现了隐私保护。%On the basis of the data set which can not be connecteel ,the definitions of the compatible data set and incompatible data set 2 based on the data sets not to be connected are given ,some basic theories about compatible data set are presented ,an association rule mining programme based on compatible data set is proposed .It is realized that association rules of compatible data set mining merge directly ,so that association rules of the whole compatible data set are generated and the algorithm can realize an association rule mining which cannot be realized by the common data mining .The algorithm expands the application field of association rule algorithm and improves the efficiency of data mining ,meanwhile ,it realized the privacy protection in a certain extent .

  17. Association of Life Activities With Cerebral Blood Flow in Alzheimer Disease

    Science.gov (United States)

    Scarmeas, Nikolaos; Zarahn, Eric; Anderson, Karen E.; Habeck, Christian G.; Hilton, John; Flynn, Joseph; Marder, Karen S.; Bell, Karen L.; Sackeim, Harold A.; Van Heertum, Ronald L.; Moeller, James R.; Stern, Yaakov

    2011-01-01

    Background Regional cerebral blood flow (CBF), a good indirect index of cerebral pathologic changes in Alzheimer disease (AD), is more severely reduced in patients with higher educational attainment and IQ when controlling for clinical severity. This has been interpreted as suggesting that cognitive reserve allows these patients to cope better with the pathologic changes in AD. Objective To evaluate whether premorbid engagement in various activities may also provide cognitive reserve. Design We evaluated intellectual, social, and physical activities in 9 patients with early AD and 16 healthy elderly controls who underwent brain H215O positron emission tomography. In voxelwise multiple regression analyses that controlled for age and clinical severity, we investigated the association between education, estimated premorbid IQ, and activities, and CBF. Results In accordance with previous findings, we replicated an inverse association between education and CBF and IQ and CBF in patients with AD. In addition, there was a negative correlation between previous reported activity score and CBF in patients with AD. When both education and IQ were added as covariates in the same model, a higher activity score was still associated with more prominent CBF deficits. No significant associations were detected in the controls. Conclusions At any given level of clinical disease severity, there is a greater degree of brain pathologic involvement in patients with AD who have more engagement in activities, even when education and IQ are taken into account. This may suggest that interindividual differences in lifestyle may affect cognitive reserve by partially mediating the relationship between brain damage and the clinical manifestation of AD. PMID:12633147

  18. Service dogs. Final rule.

    Science.gov (United States)

    2012-09-05

    The Department of Veterans Affairs (VA) amends its regulations concerning veterans in need of service dogs. Under this final rule, VA will provide to veterans with visual, hearing, or mobility impairments benefits to support the use of a service dog as part of the management of such impairments. The benefits include assistance with veterinary care, travel benefits associated with obtaining and training a dog, and the provision, maintenance, and replacement of hardware required for the dog to perform the tasks necessary to assist such veterans.

  19. Choosing goals, not rules: deciding among rule-based action plans.

    Science.gov (United States)

    Klaes, Christian; Westendorff, Stephanie; Chakrabarti, Shubhodeep; Gail, Alexander

    2011-05-12

    In natural situations, movements are often directed toward locations different from that of the evoking sensory stimulus. Movement goals must then be inferred from the sensory cue based on rules. When there is uncertainty about the rule that applies for a given cue, planning a movement involves both choosing the relevant rule and computing the movement goal based on that rule. Under these conditions, it is not clear whether primates compute multiple movement goals based on all possible rules before choosing an action, or whether they first choose a rule and then only represent the movement goal associated with that rule. Supporting the former hypothesis, we show that neurons in the frontoparietal reach areas of monkeys simultaneously represent two different rule-based movement goals, which are biased by the monkeys' choice preferences. Apparently, primates choose between multiple behavioral options by weighing against each other the movement goals associated with each option.

  20. Evaluation of bias associated with capture maps derived from nonlinear groundwater flow models

    Science.gov (United States)

    Nadler, Cara; Allander, Kip K.; Pohll, Greg; Morway, Eric; Naranjo, Ramon C.; Huntington, Justin

    2017-01-01

    The impact of groundwater withdrawal on surface water is a concern of water users and water managers, particularly in the arid western United States. Capture maps are useful tools to spatially assess the impact of groundwater pumping on water sources (e.g., streamflow depletion) and are being used more frequently for conjunctive management of surface water and groundwater. Capture maps have been derived using linear groundwater flow models and rely on the principle of superposition to demonstrate the effects of pumping in various locations on resources of interest. However, nonlinear models are often necessary to simulate head-dependent boundary conditions and unconfined aquifers. Capture maps developed using nonlinear models with the principle of superposition may over- or underestimate capture magnitude and spatial extent. This paper presents new methods for generating capture difference maps, which assess spatial effects of model nonlinearity on capture fraction sensitivity to pumping rate, and for calculating the bias associated with capture maps. The sensitivity of capture map bias to selected parameters related to model design and conceptualization for the arid western United States is explored. This study finds that the simulation of stream continuity, pumping rates, stream incision, well proximity to capture sources, aquifer hydraulic conductivity, and groundwater evapotranspiration extinction depth substantially affect capture map bias. Capture difference maps demonstrate that regions with large capture fraction differences are indicative of greater potential capture map bias. Understanding both spatial and temporal bias in capture maps derived from nonlinear groundwater flow models improves their utility and defensibility as conjunctive-use management tools.

  1. Mantle flow and dynamic topography associated with slab window opening: Insights from laboratory models

    Science.gov (United States)

    Guillaume, Benjamin; Moroni, Monica; Funiciello, Francesca; Martinod, Joseph; Faccenna, Claudio

    2010-12-01

    We present dynamically self-consistent mantle-scale laboratory models that have been conducted to improve our understanding of the influence of slab window opening on subduction dynamics, mantle flow and associated dynamic topography over geological time scales. The adopted setup consists of a two-layer linearly viscous system simulating the subduction of a fixed plate of silicone (lithosphere) under negative buoyancy in a viscous layer of glucose syrup (mantle). Our experimental setting is also characterized by a constant-width rectangular window located at the center of a laterally confined slab, modeling the case of the interaction of a trench-parallel spreading ridge with a wide subduction zone. We found that the opening of a slab window does not produce consistent changes of the geometry and the kinematics of the slab. On the contrary, slab-induced mantle circulation, quantified both in the vertical and horizontal sections using the Feature Tracking image analysis technique, is strongly modified. In particular, rollback subduction and the opening of the slab window generate a complex mantle circulation pattern characterized by the presence of poloidal and toroidal components, with the importance of each evolving according to kinematic stages. Mantle coming from the oceanic domain floods through the slab window, indenting the supra-slab mantle zone and producing its deformation without any mixing between mantle portions. The opening of the slab window and the upwelling of sub-slab mantle produce a regional-scale non-isostatic topographic uplift of the overriding plate that would correspond to values ranging between ca. 1 and 5 km in nature. Assuming that our modeling results can be representative of the natural behavior of subduction zones, we compared them to the tectonics and volcanism of the Patagonian subduction zone. We found that the anomalous backarc volcanism that has been developing since the middle Miocene could result from the lateral flow of sub

  2. Nutrient flows and related impacts between a Mediterranean river and the associated coastal area

    Science.gov (United States)

    Markogianni, Vassiliki; Varkitzi, Ioanna; Pagou, Kalliopi; Dimitriou, Elias

    2017-02-01

    Taking into consideration the Water Framework Directive's requirements, water samples were collected monthly and/or bimonthly between 2014 and 2015 from Spercheios River, its estuary and the adjacent Maliakos Gulf in order to assess the quality of these water bodies. A study on dissolved nitrate, nitrite, ammonium, phosphate and chlorophyll-a concentrations was carried out, to investigate the impact between the river and the associated coastal area and assess the nutrient loads based on water flows from Spercheios River into the marine system.Furthermore a seasonal distribution of nutrient concentrations have been studied, dividing the sampling period into dry and wet season according to the river's discharges. Correlation analysis and hierarchical cluster analysis among the available chemical data were conducted in order to enhance the detection of the two systems' interaction. Nutrients' concentrations increased from upstream to downstream sampling stations, particularly in areas where human-induced activities are detected. Marine samples were characterized by lower nutrient concentrations than the river ones, and the ecological quality of Maliakos Gulf, based on chlorophyll-a values, is characterized as moderate, except for the stations close to the river, which constantly presented poor quality. Chemical analyses and statistical analysis indicated high nutrient flows and a strong impact between the freshwater and marine systems, accompanied by the profound effect of the adjacent aquafarming areas and the wastewater treatment plant of Lamia city. The highest nutrients' and chlorophyll-a values of the coastal stations were detected close to the river mouth and they were decreasing towards the outer Maliakos Gulf.

  3. Novel Power Flow Problem Solutions Method’s Based on Genetic Algorithm Optimization for Banks Capacitor Compensation Using an Fuzzy Logic Rule Bases for Critical Nodal Detections

    Directory of Open Access Journals (Sweden)

    Nasri Abdelfatah

    2011-01-01

    Full Text Available The Reactive power flow’s is one of the most electrical distribution systems problem wich have great of interset of the electrical network researchers, it’s  cause’s active power transmission reduction, power losses decreasing, and  the drop voltage’s increase. In this research we described the efficiency of the FLC-GAO approach to solve the optimal power flow (OPF combinatorial problem. The proposed approach employ tow algorithms, Fuzzy logic controller (FLC algorithm for critical nodal detection and gentic algorithm  optimization (GAO algorithm for optimal seizing capacitor.GAO method is more efficient in combinatory problem solutions. The proposed approach has been examined and tested on the standard IEEE 57-bus the resulats show the power loss minimization denhancement, voltage profile, and stability improvement. The proposed approach results have been compared to those that reported in the literature recently. The results are promising and show the effectiveness and robustness of the proposed approach.

  4. Cerebral Blood Flow during Rest Associates with General Intelligence and Creativity

    Science.gov (United States)

    Takeuchi, Hikaru; Taki, Yasuyuki; Hashizume, Hiroshi; Sassa, Yuko; Nagase, Tomomi; Nouchi, Rui; Kawashima, Ryuta

    2011-01-01

    Recently, much scientific attention has been focused on resting brain activity and its investigation through such methods as the analysis of functional connectivity during rest (the temporal correlation of brain activities in different regions). However, investigation of the magnitude of brain activity during rest has focused on the relative decrease of brain activity during a task, rather than on the absolute resting brain activity. It is thus necessary to investigate the association between cognitive factors and measures of absolute resting brain activity, such as cerebral blood flow (CBF), during rest (rest-CBF). In this study, we examined this association using multiple regression analyses. Rest-CBF was the dependent variable and the independent variables included two essential components of cognitive functions, psychometric general intelligence and creativity. CBF was measured using arterial spin labeling and there were three analyses for rest-CBF; namely mean gray matter rest-CBF, mean white matter rest-CBF, and regional rest-CBF. The results showed that mean gray and white matter rest-CBF were significantly and positively correlated with individual psychometric intelligence. Furthermore, mean white matter rest-CBF was significantly and positively correlated with creativity. After correcting the effect of mean gray matter rest-CBF the significant and positive correlation between regional rest-CBF in the perisylvian anatomical cluster that includes the left superior temporal gyrus and insula and individual psychometric intelligence was found. Also, regional rest-CBF in the precuneus was significantly and negatively correlated with individual creativity. Significance of these results of regional rest-CBF did not change when the effect of regional gray matter density was corrected. The findings showed mean and regional rest-CBF in healthy young subjects to be correlated with cognitive functions. The findings also suggest that, even in young cognitively intact

  5. Bed Stability and Debris Flow Erosion: A Dynamic "Shields Criterion" Associated with Bed Structure

    Science.gov (United States)

    Longjas, A.; Hill, K. M.

    2015-12-01

    Debris flows are mass movements that play an important role in transporting sediment from steep uplands to rivers at lower slopes. As the debris flow moves downstream, it entrains materials such as loose boulders, gravel, sand and mud deposited locally by shorter flows such as slides and rockfalls. To capture the conditions under which debris flows entrain bed sediment, some models use something akin to the Shields' criterion and an excess shear stress of the flow. However, these models typically neglect granular-scale effects in the bed which can modify the conditions under which a debris flow is erosional or depositional. For example, it is well known that repeated shearing causes denser packing in loose dry soils, which undoubtedly changes their resistance to shear. Here, we present laboratory flume experiments showing that the conditions for entrainment by debris flows is significantly dependent on the aging of an erodible bed even for narrowly distributed spherical particles. We investigate this quantitatively using particle tracking measurements to quantify instantaneous erosion rates and the evolving bed structure or "fabric". With progressive experiments we find a signature that emerges in the bed fabric that is correlated with an increasing apparent "fragility" of the bed. Specifically, a system that is originally depositional may become erosional after repeated debris flow events, and an erodible bed becomes increasingly erodible with repeated flows. We hypothesize that related effects of bed aging at the field scale may be partly responsible for the increasing destructiveness of secondary flows of landslides and debris flows.

  6. NAGWS Volleyball Rulebook, 1992. Official Rules & Interpretations/Officiating.

    Science.gov (United States)

    American Alliance for Health, Physical Education, Recreation and Dance, Reston, VA. National Association for Girls and Women in Sport.

    The National Association for Girls and Women in Sport (NAGWS) Volleyball Rules, are based on the United States Volleyball Rules, which in turn are adopted from the rules and interpretations of the International Volleyball Federation Rules. Following a foreword by Doris Hardy, NAGWS President, the publication is organized into five sections as…

  7. NAGWS Volleyball Rulebook, 1993. Official Rules & Interpretations/Officiating.

    Science.gov (United States)

    1993

    The National Association for Girls and Women in Sport (NAGWS) Volleyball Rules are based on the United States Volleyball Rules, which in turn are adopted from the rules and interpretations of the International Volleyball Federation Rules. Following a foreword by Robertha Abney, NAGWS President, the publication is organized into six sections as…

  8. Triple-rule-out computed tomography angiography with 256-slice computed tomography scanners: patient-specific assessment of radiation burden and associated cancer risk.

    Science.gov (United States)

    Perisinakis, Kostas; Seimenis, Ioannis; Tzedakis, Antonis; Papadakis, Antonios E; Damilakis, John

    2012-02-01

    Risk-benefit analysis of triple-rule-out 256-slice computed tomography angiography (TRO-CTA) requires data on associated cancer risks, currently not available. The aim of the current study was to provide estimates of patient radiation burden and lifetime attributable risk (LAR) of radiation-induced cancer in patients undergoing typical 256-slice TRO-CTA. Standard step-and-shoot 256-slice TRO-CTA exposures were simulated on 31 male and 31 female individual-specific voxelized phantoms using a Monte Carlo CT dosimetry software. Dose images were generated depicting the dose deposition on the exposed body region of the patient. Organ doses were obtained for all primarily irradiated radiosensitive organs. Organ doses were correlated to patient body size. TRO-CTA effective dose was estimated from (a) organ doses and (b) dose-length product data. Recently published sex-, age-, and organ-specific cancer risk factors were used to estimate the total LAR of radiation-induced cancer. The theoretical risks of radiation-induced cancer to the lung and breast following a 256-slice TRO-CTA were compared with the corresponding nominal risks for each of the studied patients. The highest organ doses were observed for the breast, heart, esophagus, and lung. Mean effective dose estimated using organ dose data was found to be 6.5 ± 1.0 mSv for female and 3.8 ± 0.7 mSv for male individuals subjected to 256-slice TRO-CTA. The associated mean LARs of cancer was found to be 41 per 10 female and 17 per 10 male patients. The total radiation-induced cancer risk was found to markedly decrease with patient age. TRO-CTA exposure was found to increase the intrinsic risks of developing lung or breast cancer during the remaining lifetime by less than 0.5% and 0.1%, respectively. The mean theoretical risk of radiation-induced cancer for a patient cohort subjected to step-and-shoot 256-slice TRO-CTA may be considered to be low compared with the intrinsic risk of developing cancer.

  9. Study on the Flow Rules of Highway Rainwater Runoff Pollutants%高速公路路面雨水径流污染物出流规律研究

    Institute of Scientific and Technical Information of China (English)

    徐明; 李贺; 傅大放

    2012-01-01

    Based on the monitoring data of rainwater runoff at Lukou viaduct of Nanjing airport highway, as well as the research achievements both at home and abroad, the flow rules of highway rainwater runoff pollutants were discussed, the event mean concentration ( EMC) and influential factors of the highway runoff were studied. The results showed that the flow rules of COD and SS were similar, when the precipitation a-mount and intensity were large, the concentrations of COD and SS were high, then gradually decreased and finally became stable, the primary runoff effect was significant; but when the precipitation amount and intensity became small, the concentrations of COD and SS experienced small fluctuations without significant primary effect. The rainwater runoff of road surface was seriously polluted, the EMCs of each pollutants were 238, 196, 3. 86, 11. 93 and 0. 89 mg/L for SS, COD, NH3-N and TP. The pollutants were influenced by the factors in this order; number of previous sunny days > precipitation intensity > rainfall amount and rainfall duration.%基于南京机场高速公路禄口高架桥降雨径流监测资料,结合国内外的研究成果,探讨了高速公路路面降雨径流污染物的出流规律,路面径流事件平均浓度及其影响因素.研究表明,COD与SS的出流规律基本类似,当降雨量和降雨强度较大时初期浓度较高,随后逐渐减小,最终趋于稳定,径流初期效应显著;当降雨量和降雨历时较小时,COD与SS浓度波动较小,初期效应不明显.路面降雨径流污染严重,各污染物EMC平均值分别为:SS 238 mg/L、COD 196 mg/L、NH3-N 3.86 mg/L、TN 11.93 mg/L、TPO.89 mg/L.降雨特性对各污染物影响权重为:前期晴天数>降雨强度>降雨量、降雨历时.

  10. Higher CHADS2 score is associated with impaired coronary flow reserve: A study using phase contrast cine magnetic resonance imaging.

    Science.gov (United States)

    Kirigaya, Hidekuni; Kato, Shingo; Gyotoku, Daiki; Yamada, Nao; Iinuma, Naoki; Kusakawa, Yuka; Iguchi, Kohei; Miki, Yuko; Nakachi, Tatsuya; Fukui, Kazuki; Iwasawa, Tae; Kimura, Kazuo

    2016-10-15

    The presence of coronary microvascular dysfunction (CMD) is an important prognostic marker for coronary artery disease (CAD) patients. The purpose of this study was to investigate whether the CHADS2 score is associated with CMD evaluated by magnetic resonance imaging (MRI). One hundred forty three patients with known or suspected CAD (mean age 70.3±9.5years) were enrolled. All patients did not have any significant coronary stenosis on X-ray coronary angiography (CAG) at the time of MRI acquisition. By using a 1.5T MRI scanner, breath-hold phase contrast cine MRI images of coronary sinus (CS) were obtained to assess the blood flow of CS both at rest and during adenosine triphosphate (ATP) infusion. Coronary flow reserve (CFR) was calculated as CS blood flow during ATP infusion divided by CS blood flow at rest. CMD was defined as CFRcine MRI. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  11. Relating diseases by integrating gene associations and information flow through protein interaction network.

    Science.gov (United States)

    Hamaneh, Mehdi Bagheri; Yu, Yi-Kuo

    2014-01-01

    Identifying similar diseases could potentially provide deeper understanding of their underlying causes, and may even hint at possible treatments. For this purpose, it is necessary to have a similarity measure that reflects the underpinning molecular interactions and biological pathways. We have thus devised a network-based measure that can partially fulfill this goal. Our method assigns weights to all proteins (and consequently their encoding genes) by using information flow from a disease to the protein interaction network and back. Similarity between two diseases is then defined as the cosine of the angle between their corresponding weight vectors. The proposed method also provides a way to suggest disease-pathway associations by using the weights assigned to the genes to perform enrichment analysis for each disease. By calculating pairwise similarities between 2534 diseases, we show that our disease similarity measure is strongly correlated with the probability of finding the diseases in the same disease family and, more importantly, sharing biological pathways. We have also compared our results to those of MimMiner, a text-mining method that assigns pairwise similarity scores to diseases. We find the results of the two methods to be complementary. It is also shown that clustering diseases based on their similarities and performing enrichment analysis for the cluster centers significantly increases the term association rate, suggesting that the cluster centers are better representatives for biological pathways than the diseases themselves. This lends support to the view that our similarity measure is a good indicator of relatedness of biological processes involved in causing the diseases. Although not needed for understanding this paper, the raw results are available for download for further study at ftp://ftp.ncbi.nlm.nih.gov/pub/qmbpmn/DiseaseRelations/.

  12. Simulating Cerebrospinal Fluid Flow and Spinal Cord Movement Associated with Syringomyelia

    OpenAIRE

    Vinje, Vegard

    2016-01-01

    Syringomyelia is a progressive disease where fluid filled cavities develop inside the spinal cord, and is frequently seen together with Chiari Malformation I (CMI). CMI is characterized by downwards displacements of the Cerebellar Tonsils obstructing flow in the Subarachnoid space, (SAS) which causes abnormal Cerebrospinal fluid (CSF) flow. Many theories on the pathogenesis of syringomyelia have been proposed, many related to abnormal CSF flow, but a full explanation has not yet been given. I...

  13. Predicting the delivery of sediment and associated nutrients from post-fire debris flows in small upland catchments

    Science.gov (United States)

    Nyman, Petter; Sheridan, Gary; Smith, Hugh; Lane, Patrick

    2014-05-01

    detailed predictions of sediment entrainment, deposition, the overall source contribution and the associated constituents. Future work will aim to link models of debris flow magnitude with models of initiation and debris flow frequency after fire.

  14. Onset of small intestinal atrophy is associated with reduced intestinal blood flow in TPN-fed neonatal piglets

    DEFF Research Database (Denmark)

    Niinikoski, Harri; Stoll, Barbara; Guan, Xinfu

    2004-01-01

    Our aim was to determine the speed of onset of total parenteral nutrition (TPN)-induced mucosal atrophy, and whether this is associated with changes in intestinal blood flow and tissue metabolism in neonatal piglets. Piglets were implanted with jugular venous and duodenal catheters and either...... 24 h of TPN, and protein mass was lower (P parenteral nutrition induced a rapid (

  15. Associations between labial and whole salivary flow rates, systemic diseases and medications in a sample of older people

    DEFF Research Database (Denmark)

    Smidt, Dorte; Torpet, Lis Andersen; Nauntofte, Birgitte;

    2010-01-01

    Smidt D, Torpet LA, Nauntofte B, Heegaard KM, Pedersen AML. Associations between labial and whole salivary flow rates, systemic diseases and medications in a sample of older people. Community Dent Oral Epidemiol 2010; 38: 422-435. © 2010 John Wiley & Sons A/S Abstract - Objective: To investigate ...

  16. Association Between Parent Television-Viewing Practices and Setting Rules to Limit the Television-Viewing Time of Their 8- to 12-Year-Old Children, Minnesota, 2011–2015

    Science.gov (United States)

    Gurvich, Olga V.; Fulkerson, Jayne A.

    2017-01-01

    Introduction Television (TV) viewing is popular among adults and children, and child TV-viewing time is positively associated with parent TV-viewing time. Efforts to limit the TV-viewing time of children typically target parent rule-setting. However, little is known about the association between parent TV-viewing practices and rule-setting. Methods We used baseline height and weight data and survey data collected from 2011 through 2015 on parents and their 8- to 12-year-old children (N = 212 parent/child dyads) who were participants in 2 community-based obesity prevention intervention trials conducted in metropolitan Minnesota. Multivariable binary logistic regression analysis was used to assess the association between parent TV-viewing time on weekdays or weekend days (dichotomized as ≤2 hrs/d vs ≥2.5 hrs/d) and parent rules limiting child TV-viewing time. Results Child mean age was 10 (standard deviation [SD], 1.4) years, mean body mass index (BMI) percentile was 81 (SD, 16.7), approximately half of the sample were boys, and 42% of the sample was nonwhite. Parent mean age was 41 (SD, 7.5) years, and mean BMI was 29 (SD, 7.5); most of the sample was female, and 36% of the sample was nonwhite. Parents who limited their TV-viewing time on weekend days to 2 hours or fewer per day were almost 3 times more likely to report setting rules limiting child TV-viewing time than were parents who watched 2.5 hours or more per day (P = .01). A similar association was not seen for parent weekday TV-viewing time. Conclusion For most adults and children, a meaningful decrease in sedentariness will require reductions in TV-viewing time. Family-based interventions to reduce TV-viewing time that target the TV-viewing practices of both children and parents are needed. PMID:28103183

  17. 关联规则在阿尔茨海默病中医诊疗中的应用研究%Study on the Application of Association Rules in the TCM Diagnosis and Treatment of Alzheimer Disease

    Institute of Scientific and Technical Information of China (English)

    杨婕

    2013-01-01

    Objectives:find out the relation between Alzheimer disease TCM syndrome and symptom. Methods:mine the data of 109 pieces of clinical cases with Apriori method under association rules, and meanwhile, aimed at the specialty of TCM data, put forward improvements for Apriori method. Results: a series of association rules were mined, which provide important basis for the definite diagnosis of Alzheimer disease. Conclusions:association rules are suitable for interior principles of TCM treatment based on syndrome differentiation in study of Alzheimer disease and provide reliable basis for the definite diagnosis of Alzheimer disease.%  目的:寻找阿尔茨海默病中医证型与中医症状之间的关系。方法:利用关联规则的Apriori算法对109例临床数据进行挖掘,同时针对中医药数据的特殊性,提出关于Apriori算法的改进。结果:挖掘出一系列关联规则,为阿尔茨海默病的确诊提供了重要依据。结论:关联规则适合于研究阿尔茨海默病中医药辨证论治的内部规律,为阿尔茨海默病的确诊提供可靠依据。

  18. Mountain accidents associated with winter northern flows in the Mediterranean Pyrenees

    Directory of Open Access Journals (Sweden)

    R. Pascual

    2010-01-01

    Full Text Available The Mediterranean Pyrenees, at the eastern end of the range, is a very popular area. Its highest peak is at 2900 m a.s.l. and there are numerous peaks above 2000 m, with rounded relief and sparse vegetation on the latter height. One of its significant winter climatic features is the sudden entrance of cold air with violent northern winds, drop in temperatures and very low wind chill values. Such advections are established after the passage of a snowy cold front and, consequently, there is abundant transport of both new and existing snow that reduces horizontal visibility. The post-frontal conditions at high altitudes represent a serious threat to humans. The review done shows that the hikers immersed in an environment of low visibility, strong winds and very low temperatures can quickly become disoriented, suffer frostbite and hypothermia and slip on the ice. The characterization of a series of accidents occurred in this geographical area, identified in the press, shows in this paper that the phenomena associated with northern winter advections is an element of danger to be considered in the evaluation of natural hazards in that area. In addition, the multiple character of many of the events suggests that there is high vulnerability to such dangers. The climatological analysis presented suggests that such weather conditions are not uncommon in the winter, although the most serious accidents have been registered under especially strong and cold flows. The conclusions recommend that the weather conditions described, locally called torb, should be known by the visitors to these mountains in the winter, and its appearance should be announced in weather reports, which in turn must be sufficiently disseminated in the areas of greater abundance of tourists and hikers.

  19. Bonnet Ruled Surfaces

    Institute of Scientific and Technical Information of China (English)

    Filiz KANBAY

    2005-01-01

    We consider the Bonnet ruled surfaces which admit only one non-trivial isometry that preserves the principal curvatures. We determine the Bonnet ruled surfaces whose generators and orthogonal trajectories form a special net called an A-net.

  20. Cosmological diagrammatic rules

    CERN Document Server

    Giddings, Steven B

    2010-01-01

    A simple set of diagrammatic rules is formulated for perturbative evaluation of ``in-in" correlators, as is needed in cosmology and other nonequilibrium problems. These rules are both intuitive, and efficient for calculational purposes.

  1. Cosmological diagrammatic rules

    Energy Technology Data Exchange (ETDEWEB)

    Giddings, Steven B. [Department of Physics, University of California, Santa Barbara, CA 93106 (United States); Sloth, Martin S., E-mail: giddings@physics.ucsb.edu, E-mail: sloth@cern.ch [CERN, Physics Department, Theory Unit, CH-1211 Geneva 23 (Switzerland)

    2010-07-01

    A simple set of diagrammatic rules is formulated for perturbative evaluation of ''in-in'' correlators, as is needed in cosmology and other nonequilibrium problems. These rules are both intuitive, and efficient for calculational purposes.

  2. Phonological reduplication in sign language: rules rule

    Directory of Open Access Journals (Sweden)

    Iris eBerent

    2014-06-01

    Full Text Available Productivity—the hallmark of linguistic competence—is typically attributed to algebraic rules that support broad generalizations. Past research on spoken language has documented such generalizations in both adults and infants. But whether algebraic rules form part of the linguistic competence of signers remains unknown. To address this question, here we gauge the generalization afforded by American Sign Language (ASL. As a case study, we examine reduplication (X→XX—a rule that, inter alia, generates ASL nouns from verbs. If signers encode this rule, then they should freely extend it to novel syllables, including ones with features that are unattested in ASL. And since reduplicated disyllables are preferred in ASL, such rule should favor novel reduplicated signs. Novel reduplicated signs should thus be preferred to nonreduplicative controls (in rating, and consequently, such stimuli should also be harder to classify as nonsigns (in the lexical decision task. The results of four experiments support this prediction. These findings suggest that the phonological knowledge of signers includes powerful algebraic rules. The convergence between these conclusions and previous evidence for phonological rules in spoken language suggests that the architecture of the phonological mind is partly amodal.

  3. Consumption of energy beverage is associated with attenuation of arterial endothelial flow-mediated dilatation.

    Science.gov (United States)

    Higgins, John P; Yang, Benjamin; Herrin, Nikki E; Yarlagadda, Santi; Le, George T; Ortiz, Brandon L; Ali, Asif; Infanger, Stephen C

    2017-02-26

    To investigate whether consumption of an energy drink will acutely impair endothelial function in young healthy adults. Energy drinks are being consumed more and more worldwide, and have been associated with some deaths in adolescents and young adults, especially when consumed while exercising. After fasting and not smoking for at least 8 h prior, eleven medical students (9 males) received an electrocardiogram, blood pressure and pulse check, and underwent baseline testing (BL) of endothelial function using the technique of endothelium-dependent flow mediated dilatation (FMD) with high-resolution ultrasound (according to recommended guidelines of the University of Wisconsin Atherosclerosis Imaging Research Program Core Laboratory). The subjects then drank an energy beverage (EB), a 24-oz can of Monster Energy, and the above was repeated at 90 min after consumption. The relative FMD (%) was calculated as the ratio between the average post-cuff release and the baseline diameter. Each image was checked for quality control, and each artery diameter was measured from the media to media points by two experts, 3 measurements at the QRS complex, repeated on 3 separate beats, and then all were averaged. Subjects characteristics averages (given with standard deviations) include: Age 24.5 ± 1.5 years, sex 9 male and 2 female, weight 71.0 ± 9.1 kg, height 176.4 ± 6.0 cm, BMI 22.8 ± 2.7 kg/m(2). The hemodynamics were as follows, BL vs EB group respectively (mean ± SD): Heart rate 65.2 ± 11.3 vs 68.2 ± 11.8 beats per minute, systolic blood pressure 114.0 ± 10.4 mmHg vs 114.1 ± 10.4 mmHg, diastolic blood pressure 68.8 ± 9.3 mmHg vs 70.6 ± 7.1 mmHg; all were not significantly different. However after drinking the EB, a significantly attenuated peak FMD response was measured (mean ± SD): BL group 5.9% ± 4.6% vs EB group 1.9% ± 2.1%; P = 0.03). Given the increased consumption of energy beverages associated with exercise in young adults, more research is needed. Energy

  4. Velocity bias induced by flow patterns around ADCPs and associated deployment platforms

    Science.gov (United States)

    Mueller, David S.

    2015-01-01

    Velocity measurements near the Acoustic Doppler Current Profiler (ADCP) are important for mapping surface currents, measuring velocity and discharge in shallow streams, and providing accurate estimates of discharge in the top unmeasured portion of the water column. Improvements to ADCP performance permit measurement of velocities much closer (5 cm) to the transducer than has been possible in the past (25 cm). Velocity profiles collected by the U.S. Geological Survey (USGS) with a 1200 kHz Rio Grande Zedhead ADCP in 2002 showed a negative bias in measured velocities near the transducers. On the basis of these results, the USGS initiated a study combining field, laboratory, and numerical modeling data to assess the effect of flow patterns caused by flow around the ADCP and deployment platforms on velocities measured near the transducers. This ongoing study has shown that the negative bias observed in the field is due to the flow pattern around the ADCP. The flow pattern around an ADCP violates the basic assumption of flow homogeneity required for an accurate three-dimensional velocity solution. Results, to date (2014), have indicated velocity biases within the measurable profile, due to flow disturbance, for the TRDI 1200 kHz Rio Grande Zedhead and the SonTek RiverSurveyor M9 ADCPs. The flow speed past the ADCP, the mount and the deployment platform have also been shown to play an important role in the magnitude and extent of the velocity bias.

  5. Evolution of Photospheric Flow and Magnetic Fields Associated with the 2015 June 22 M6.5 Flare

    Science.gov (United States)

    Wang, Jiasheng; Liu, Chang; Deng, Na; Wang, Haimin

    2017-08-01

    The evolution of photospheric flow and magnetic fields before and after flares can provide important information regarding the flare triggering and back reaction processes. However, such studies on the flow field are rare due to the paucity of high-resolution observations covering the entire flaring period. Here we study the structural evolution of penumbra and shear flows associated with the 2015 June 22 M6.5 flare in NOAA AR 12371, using high-resolution imaging observation in the TiO band taken by the 1.6 m New Solar Telescope at Big Bear Solar Observatory, with the aid of the differential affine velocity estimator(DAVE) method for flow tracking. The accompanied photospheric vector magnetic field changes are also analyzed using data from the Helioseismic and Magnetic Imager. As a result, we found, for a penumbral segment in the negative field adjacent to the magnetic polarity inversion line (PIL), an enhancement of penumbral flows (up to ~2 km s-1) and extension of penumbral fibrils after the first peak of the flare hard X-ray (HXR) emission. We also found a shear flow region at the PIL, which is co-spatial with a precursor brightening kernel and exhibits a gradual increase of shear flow velocity (up to ~0.9 km s-1) after the flare. The enhancing penumbral and shear flow regions are also accompanied by an increase of horizontal field and decrease of magnetic inclination angle. These results are discussed in the context of the theory of back reaction of coronal restructuring on the photosphere as a result of flare energy release.

  6. Flow cytometric detection of neutrophil-associated immunoglobulin in patients with or without neutropenia and establishment of the reference interval.

    Science.gov (United States)

    Hwang, Keumrock; Park, Chan-Jeoung; Huh, Hee Jin; Han, Sang Hee; Jang, Seongsoo; Chi, Hyun-Sook

    2011-01-01

    We measured neutrophil-associated immunoglobulin (NAIg) levels using flow cytometry to establish the reference interval for NAIg and to estimate NAIg in patients with or without neutropenia. Peripheral blood from 152 individuals was analyzed for NAIg detection by flow cytometry. Using fluorescescent-conjugated anti-CD10 monoclonal antibody and anti-human immunoglobulins, proportions of NAIgG, NAIgA, and NAIgM bound to neutrophils were measured. Reference intervals for NAIg were set as NAIgG reference intervals defined herein, patients with neutropenia or adverse transfusion reactions may be evaluated in a clinically relevant manner.

  7. Triggering conditions and mobility of debris flows associated to complex earthflows

    Science.gov (United States)

    Malet, J.-P.; Laigle, D.; Remaître, A.; Maquaire, O.

    2005-03-01

    Landslides on black marl slopes of the French Alps are, in most cases, complex catastrophic failures in which the initial structural slides transform into slow-moving earthflows. Under specific hydrological conditions, these earthflows can transform into debris flows. Due to their sediment volume and their high mobility, debris flow induced by landslides are far much dangerous than these resulting from continuous erosive processes. A fundamental point to correctly delineate the area exposed to debris flows on the alluvial fans is therefore to understand why and how some earthflows transform into debris flow while most of them stabilize. In this paper, a case of transformation from earthflow to debris flow is presented and analysed. An approach combining geomorphology, hydrology, geotechnics and rheology is adopted to model the debris flow initiation (failure stage) and its runout (postfailure stage). Using the Super-Sauze earthflow (Alpes-de-Haute-Provence, France) as a case study, the objective is to characterize the hydrological and mechanical conditions leading to debris flow initiation in such cohesive material. Results show a very good agreement between the observed runout distances and these calculated using the debris flow modeling code Cemagref 1-D. The deposit thickness in the depositional area and the velocities of the debris flows are also well reproduced. Furthermore, a dynamic slope stability analysis shows that conditions in the debris source area under average pore water pressures and moisture contents are close to failure. A small excess of water can therefore initiate failure. Seepage analysis is used to estimate the volume of debris that can be released for several hydroclimatic conditions. The failed volumes are then introduced in the Cemagref 1-D runout code to propose debris flow hazard scenarios. Results show that clayey earthflow can transform under 5-year return period rainfall conditions into 1-km runout debris flow of volumes ranging

  8. Parton model sum rules

    CERN Document Server

    Hinchliffe, Ian; Hinchliffe, Ian; Kwiatkowski, Axel

    1996-01-01

    This review article discusses the experimental and theoretical status of various Parton Model sum rules. The basis of the sum rules in perturbative QCD is discussed. Their use in extracting the value of the strong coupling constant is evaluated and the failure of the naive version of some of these rules is assessed.

  9. Modifying Intramural Rules.

    Science.gov (United States)

    Rokosz, Francis M.

    1981-01-01

    Standard sports rules can be altered to improve the game for intramural participants. These changes may improve players' attitudes, simplify rules for officials, and add safety features to a game. Specific rule modifications are given for volleyball, football, softball, floor hockey, basketball, and soccer. (JN)

  10. Association Relationship between Functions and Flavors of TCM Based on Classification Association Rules%基于分类关联规则的中药功效与药味关联关系研究

    Institute of Scientific and Technical Information of China (English)

    杨雪梅; 赖新梅; 陈梅妹; 林端宜

    2013-01-01

    目的 为中药药性五味理论的全面总结奠定大样本数据挖掘的基础,并为中药新资源的开发及临床用药提供五味药性判定的理论线索.方法 选择《中华本草》所载8980味中药的五味数据及关联的药物功效索引数据作为数据集,采用IBM SPSS Clementine 14.1数据挖掘平台,选择Apriori模型挖掘分类关联规则,设置规则前件最小支持度阈值为0.5%,最小置信度阈值为80%.结果 共挖掘出涉及甘、辛、苦3种药味的分类关联规则21条.具有生津止渴、补气、补阴、润肺、补肺、生津止渴&清热、润肺止咳、补气&补血、润燥、除烦、补脾益气功能的中药其药味多为“甘”;具有发散风寒、解表、温中、散寒止痛功能的中药其药味多为“辛”;具有消肿止痛&清热解毒、清热泻火、清热燥湿、化瘀止血&清热解毒、杀虫&清热解毒、止痛&清热解毒功能的中药其药味多为“苦”.结论 本研究挖掘出的功效与甘、辛、苦三味之间的关联规律完全基于大量中药数据,后续还需通过各种试验多方验证以构建完整的中药药性理论体系.%Objective To lay the foundation of the large sample data mining for a comprehensive summary concerning five flavors theory of TCM, and provide theory clues on determination of five flavors for the new resource development of TCM and clinical use of Chinese medicine. Methods Five flavors data of 8 980 Chinese medicines from Chinese Herbal Medicine (CHM) and associated function index data were chose as data sets. IBM SPSS Clementine 14.1 data mining platform and Apriori model were adopted to mining classification-association rules, setting the minimum support threshold of rule antecedent and the minimum confidence threshold as 0.5% and 80%. Results Twenty-one classification-association rules involved in sweet, pungent and bitter flavors were found. It was discovered that the TCM with functions of "producing

  11. Association of Coronary Stenosis and Plaque Morphology With Fractional Flow Reserve and Outcomes

    DEFF Research Database (Denmark)

    Ahmadi, Amir; Stone, Gregg W; Leipsic, Jonathon

    2016-01-01

    IMPORTANCE: Obstructive coronary lesions with reduced luminal dimensions may result in abnormal regional myocardial blood flow as assessed by stress-induced myocardial perfusion imaging or a significant fall in distal perfusion pressure with hyperemia-induced vasodilatation (fractional flow reserve......: Having a normal FFR requires unimpaired vasoregulatory ability and significant luminal stenosis. Therefore, FFR should identify lesions that are unlikely to possess large necrotic core, rendering them safe for treatment with medical therapy alone. Further studies are warranted to determine whether...

  12. Satellite-based measurements of surface deformation reveal fluid flow associated with the geological storage of carbon dioxide

    Energy Technology Data Exchange (ETDEWEB)

    Vasco, D.W.; Rucci, A.; Ferretti, A.; Novali, F.; Bissell, R.; Ringrose, P.; Mathieson, A.; Wright, I.

    2009-10-15

    Interferometric Synthetic Aperture Radar (InSAR), gathered over the In Salah CO{sub 2} storage project in Algeria, provides an early indication that satellite-based geodetic methods can be effective in monitoring the geological storage of carbon dioxide. An injected volume of 3 million tons of carbon dioxide, from one of the first large-scale carbon sequestration efforts, produces a measurable surface displacement of approximately 5 mm/year. Using geophysical inverse techniques we are able to infer flow within the reservoir layer and within a seismically detected fracture/ fault zone intersecting the reservoir. We find that, if we use the best available elastic Earth model, the fluid flow need only occur in the vicinity of the reservoir layer. However, flow associated with the injection of the carbon dioxide does appear to extend several kilometers laterally within the reservoir, following the fracture/fault zone.

  13. Fusion rules of equivariantizations of fusion categories

    OpenAIRE

    2012-01-01

    We determine the fusion rules of the equivariantization of a fusion category $\\mathcal{C}$ under the action of a finite group $G$ in terms of the fusion rules of $\\mathcal{C}$ and group-theoretical data associated to the group action. As an application we obtain a formula for the fusion rules in an equivariantization of a pointed fusion category in terms of group-theoretical data. This entails a description of the fusion rules in any braided group-theoretical fusion category.

  14. Fusion rules of equivariantizations of fusion categories

    OpenAIRE

    Burciu, Sebastian; Natale, Sonia

    2012-01-01

    We determine the fusion rules of the equivariantization of a fusion category $\\mathcal{C}$ under the action of a finite group $G$ in terms of the fusion rules of $\\mathcal{C}$ and group-theoretical data associated to the group action. As an application we obtain a formula for the fusion rules in an equivariantization of a pointed fusion category in terms of group-theoretical data. This entails a description of the fusion rules in any braided group-theoretical fusion category.

  15. Binary effectivity rules

    DEFF Research Database (Denmark)

    Keiding, Hans; Peleg, Bezalel

    2006-01-01

    is binary if it is rationalized by an acyclic binary relation. The foregoing result motivates our definition of a binary effectivity rule as the effectivity rule of some binary SCR. A binary SCR is regular if it satisfies unanimity, monotonicity, and independence of infeasible alternatives. A binary...... effectivity rule is regular if it is the effectivity rule of some regular binary SCR. We characterize completely the family of regular binary effectivity rules. Quite surprisingly, intrinsically defined von Neumann-Morgenstern solutions play an important role in this characterization...

  16. New Safety rules

    CERN Multimedia

    Safety Commission

    2008-01-01

    The revision of CERN Safety rules is in progress and the following new Safety rules have been issued on 15-04-2008: Safety Procedure SP-R1 Establishing, Updating and Publishing CERN Safety rules: http://cern.ch/safety-rules/SP-R1.htm; Safety Regulation SR-S Smoking at CERN: http://cern.ch/safety-rules/SR-S.htm; Safety Regulation SR-M Mechanical Equipment: http://cern.ch/safety-rules/SR-M.htm; General Safety Instruction GSI-M1 Standard Lifting Equipment: http://cern.ch/safety-rules/GSI-M1.htm; General Safety Instruction GSI-M2 Standard Pressure Equipment: http://cern.ch/safety-rules/GSI-M2.htm; General Safety Instruction GSI-M3 Special Mechanical Equipment: http://cern.ch/safety-rules/GSI-M3.htm. These documents apply to all persons under the Director General’s authority. All Safety rules are available at the web page: http://www.cern.ch/safety-rules The Safety Commission

  17. Flow-associated dilatory capacity of the brachial artery is intact in early autosomal dominant polycystic kidney disease

    DEFF Research Database (Denmark)

    Clausen, Peter; Feldt-Rasmussen, Bo; Iversen, Jens;

    2006-01-01

    females and 18 males, age 36 +/- 10 years) with polycystic kidney disease and normal renal function were compared to 27 healthy controls. The dilatory responses of the brachial artery to postischemic increased blood flow [endothelium-dependent flow-associated dilatation (FAD)] and to nitroglycerin......-selectin and von Willebrand factor antigen were also measured. RESULTS: No differences in FAD or NID were found between patients and controls (104.6 +/- 4.2 vs. 105.3 +/- 3.9%, mean +/- SD, p = 0.55, and 117.0 +/- 8.4 vs. 117.5 +/- 7.6%, p = 0.75). However, the plasma concentration of VCAM-1 was elevated...... and the plasma concentration of NOx was reduced in patients with polycystic kidney disease. CONCLUSION: Biochemical markers confirm an association between polycystic kidney disease and endothelial dysfunction. However, a normal FAD of the brachial artery suggests that the endothelial dysfunction does not involve...

  18. Hybrid Flow Shop Scheduling by Using Ant Colony System Combined with Dispatching Rules%蚁群系统结合指派规则求解HFS调度问题

    Institute of Scientific and Technical Information of China (English)

    屈国强; 李俊芳; 侯东亮

    2012-01-01

    以NP-难的最小化时间表长为目标的混合流水车间调度问题为研究对象.把工件在第1阶段开始加工的排序问题转化为旅行商问题,采用蚁群系统求得初始排序;在第1阶段后各阶段采用工件先到先服务规则选择工件、最先空闲机器优先规则选择机器以构建初始工件的机器指派与排序;充分利用已知的机器布局和工件加工时间特点,确定工件加工瓶颈阶段,并以此为基础对工件的机器指派与排序进行改进.用Carlier和Neron设计的Benchmark算例仿真后与著名的NEH算法比较,表明这种算法是有效的.%The scheduling problem of hybrid flow shop with makespan as objective is discussed. In a hybrid flow shop, there are multiple machines at each stage and its scheduling problem is known to be NP-hard. A new method is proposed in this paper. By the proposed method, for the first stage, the job sequencing is formulated as a traveling salesman problem and the ant colony method is used to solve it. For the following stages, dispatching rules, such as first come first served and first available machine first, are used to obtain an initial solution. Then, the initial solution is improved by identifying the bottleneck stage in taking the advantage of knowledge about job processing times and machine configurations. To evaluate the performance of the proposed algorithm, it is tested by using the Carlier and Neron's benchmark problems. It is shown that proposed method is effective and outperforms the well-known Nawaz-Enscore-Ham (NEH) heuristic.

  19. A new formulation to compute self-potential signals associated with ground water flow

    Directory of Open Access Journals (Sweden)

    A. Bolève

    2007-06-01

    Full Text Available The classical formulation of the coupled hydroelectrical flow in porous media is based on a linear formulation of two coupled constitutive equations for the electrical current density and the seepage velocity of the water phase and obeying Onsager's reciprocity. This formulation shows that the streaming current density is controlled by the gradient of the fluid pressure of the water phase and a streaming current coupling coefficient that depends on the so-called zeta potential. Recently a new formulation has been introduced in which the streaming current density is directly connected to the seepage velocity of the water phase and to the excess of electrical charge per unit pore volume in the porous material. The advantages of this formulation are numerous. First this new formulation is more intuitive not only in terms of constitutive equation for the generalized Ohm's law but also in specifying boundary conditions for the influence of the flow field upon the streaming potential. With the new formulation, the streaming potential coupling coefficient shows a decrease of its magnitude with permeability in agreement with published results. The new formulation is also easily extendable to non-viscous laminar flow problems (high Reynolds number ground water flow in cracks for example and to unsaturated conditions with applications to the vadose zone. We demonstrate here that this formulation is suitable to model self-potential signals in the field. We investigate infiltration of water from an agricultural ditch, vertical infiltration of water into a sinkhole, and preferential horizontal flow of ground water in a paleochannel. For the three cases reported in the present study, a good match is obtained between the finite element simulations performed with the finite element code Comsol Multiphysics 3.3 and field observations. Finally, this formulation seems also very promising for the inversion of the geometry of ground water flow from the

  20. 多时间序列关联规则分析的论坛舆情趋势预测%Forum Sentiment Trend Prediction Based on Multi Time Series Association Rule Analysis

    Institute of Scientific and Technical Information of China (English)

    钱爱玲; 瞿彬彬; 卢炎生; 陈攀攀; 陈国栋

    2012-01-01

    为了预测论坛舆情及其动态演变趋势,基于多时间序列的关联分析,集中分析了论坛中3个量的时间序列之间的关联规则:活跃者之间的关系强度的时间序列、坚定支持者人数的时间序列以及坚定支持者成员的变化频度的时间序列.然后给出了一种新的基于多时间序列关联分析的论坛舆情预测算法(Forum sentiment trend prediction based on multi time series association rule analysis,TPMTSA),并在真实数据集和拟合数据集上进行了大量的实验.结果表明:TPMTSA算法具有有效性和较高的运行效率.研究结果可用于论坛舆情预警监控.%In order to predict the evolving trend of forum sentiment, based on the association analysis of multi time series, the association rules of three-quantity time series over forum sentiment are anlyzed, namely, the strength of relationship between actors, the number of pillars, and the changing frequency of pillars. Then a novel prediction algorithm, forum sentiment trend prediction based on multi time series association rule analysis (TPMTSA), is proposed. Extensive experiments over real and synthetic datasets are conducted. Results show the effectiveness and the efficiency of TPMTSA. The research results can be used to monitor the forum opinion.

  1. Regional cerebral blood flow changes associated with clitorally induced orgasm in healthy women

    NARCIS (Netherlands)

    Georgiadis, Janniko R.; Kortekaas, Rudie; Kuipers, Rutger; Nieuwenburg, Arie; Pruim, Jan; Reinders, A. A. T. Simone; Holstege, Gert

    2006-01-01

    There is a severe lack of knowledge regarding the brain regions involved in human sexual performance in general, and female orgasm in particular. We used [(15)O]-H(2)O positron emission tomography to measure regional cerebral blood flow (rCBF) in 12 healthy women during a nonsexual resting state, cl

  2. Regional cerebral blood flow changes associated with clitorally induced orgasm in healthy women

    NARCIS (Netherlands)

    Georgiadis, Janniko R.; Kortekaas, Rudie; Kuipers, Rutger; Nieuwenburg, Arie; Pruim, Jan; Reinders, A. A. T. Simone; Holstege, Gert

    2006-01-01

    There is a severe lack of knowledge regarding the brain regions involved in human sexual performance in general, and female orgasm in particular. We used [(15)O]-H(2)O positron emission tomography to measure regional cerebral blood flow (rCBF) in 12 healthy women during a nonsexual resting state,

  3. Conformance Testing: Measurement Decision Rules

    Science.gov (United States)

    Mimbs, Scott M.

    2010-01-01

    The goal of a Quality Management System (QMS) as specified in ISO 9001 and AS9100 is to provide assurance to the customer that end products meet specifications. Measuring devices, often called measuring and test equipment (MTE), are used to provide the evidence of product conformity to specified requirements. Unfortunately, processes that employ MTE can become a weak link to the overall QMS if proper attention is not given to the measurement process design, capability, and implementation. Documented "decision rules" establish the requirements to ensure measurement processes provide the measurement data that supports the needs of the QMS. Measurement data are used to make the decisions that impact all areas of technology. Whether measurements support research, design, production, or maintenance, ensuring the data supports the decision is crucial. Measurement data quality can be critical to the resulting consequences of measurement-based decisions. Historically, most industries required simplistic, one-size-fits-all decision rules for measurements. One-size-fits-all rules in some cases are not rigorous enough to provide adequate measurement results, while in other cases are overly conservative and too costly to implement. Ideally, decision rules should be rigorous enough to match the criticality of the parameter being measured, while being flexible enough to be cost effective. The goal of a decision rule is to ensure that measurement processes provide data with a sufficient level of quality to support the decisions being made - no more, no less. This paper discusses the basic concepts of providing measurement-based evidence that end products meet specifications. Although relevant to all measurement-based conformance tests, the target audience is the MTE end-user, which is anyone using MTE other than calibration service providers. Topics include measurement fundamentals, the associated decision risks, verifying conformance to specifications, and basic measurement

  4. Measuring interesting rules in Characteristic rule

    CERN Document Server

    Warnars, Spits

    2010-01-01

    Finding interesting rule in the sixth strategy step about threshold control on generalized relations in attribute oriented induction, there is possibility to select candidate attribute for further generalization and merging of identical tuples until the number of tuples is no greater than the threshold value, as implemented in basic attribute oriented induction algorithm. At this strategy step there is possibility the number of tuples in final generalization result still greater than threshold value. In order to get the final generalization result which only small number of tuples and can be easy to transfer into simple logical formula, the seventh strategy step about rule transformation is evolved where there will be simplification by unioning or grouping the identical attribute. Our approach to measure interesting rule is opposite with heuristic measurement approach by Fudger and Hamilton where the more complex concept hierarchies, more interesting results are likely to be found, but our approach the simple...

  5. Symmetrization Selection Rules, 2

    CERN Document Server

    Page, P R

    1996-01-01

    We introduce strong interaction selection rules for the two-body decay and production of hybrid and conventional mesons coupling to two S-wave hybrid or conventional mesons. The rules arise from symmetrization in states in the limit of non-relativistically moving quarks. The conditions under which hybrid coupling to S-wave states is suppressed are determined by the rules, and the nature of their breaking is indicated.

  6. Association rules of data mining in library service application research%关联规则数据挖掘在图书馆个性化服务中的应用研究

    Institute of Scientific and Technical Information of China (English)

    刘志勇; 王阿利; 魏迎; 郭轶

    2012-01-01

    随着计算机技术、网络技术以及现代通信技术的蓬勃发展,数据挖掘作为信息技术飞速发展的衍生物,为数字知识资源的有效管理提供了技术保障。文章通过对关联规则数据挖掘技术以及图书馆个性化服务相关内容的介绍,探讨了关联规则数据挖掘在数字化图书馆中的应用,说明关联规则挖掘技术在数字图书馆应用的必要性,以及在提升图书馆服务质量和服务水平方面的发挥的重要作用。%Along with the computer technology,network technology and modern communication technology rapid development,the data mining as the rapid development of information technology the derivatives,for digital intellectual resources effective management to provide technical support.Based on the association rules in data mining technology and library personalized service related content introduction,discusses the association rules in data mining in digital library application,illustrate the association rules mining technology in the digital library the application necessity,as well as in the promotion of library service quality and service level of the play important role.

  7. Sum rules in the oscillator radiation processes

    Energy Technology Data Exchange (ETDEWEB)

    Casana, R. [Instituto de Fisica Teorica-IFT/UNESP, Rua Pamplona 145, 01405-900 Sao Paulo, SP (Brazil)]. E-mail: casana@ift.unesp.br; Flores-Hidalgo, G. [Instituto de Fisica Teorica-IFT/UNESP, Rua Pamplona 145, 01405-900 Sao Paulo, SP (Brazil)]. E-mail: gflores@ift.unesp.br; Pimentel, B.M. [Instituto de Fisica Teorica-IFT/UNESP, Rua Pamplona 145, 01405-900 Sao Paulo, SP (Brazil)]. E-mail: pimentel@ift.unesp.br

    2005-03-28

    We consider the problem of a harmonic oscillator coupled to a scalar field in the framework of recently introduced dressed coordinates. We compute all the probabilities associated with the decay process of an excited level of the oscillator. Instead of doing direct quantum mechanical calculations we establish some sum rules from which we infer the probabilities associated to the different decay processes of the oscillator. Thus, the sum rules allows to show that the transition probabilities between excited levels follow a binomial distribution.

  8. Sum rules in the oscillator radiation processes

    Science.gov (United States)

    Casana, R.; Flores-Hidalgo, G.; Pimentel, B. M.

    2005-03-01

    We consider the problem of a harmonic oscillator coupled to a scalar field in the framework of recently introduced dressed coordinates. We compute all the probabilities associated with the decay process of an excited level of the oscillator. Instead of doing direct quantum mechanical calculations we establish some sum rules from which we infer the probabilities associated to the different decay processes of the oscillator. Thus, the sum rules allows to show that the transition probabilities between excited levels follow a binomial distribution.

  9. Medical images data mining using classification algorithm based on association rule%基于关联分类算法的医学图像数据挖掘

    Institute of Scientific and Technical Information of China (English)

    邓薇薇; 卢延鑫

    2012-01-01

    Objective In order to assist clinicians in diagnosis and treatment of brain disease,a classifier for medical images which contains tumora inside,based on association rule data mining techniques was constructed.Methtoods After a pre-processing phase of the medical images,the related features from those images were extracted and discretized as the input of association rule,then the medical images classifier was constructed by improved Apriori algorithm.Results The medical images classifier was constructed.The known type of medical images was utilized to train the classifier so as to mine the association rules that satisfy the constraint conditions.Then the brain tumor in an unknown type of medical image was classified by the classifier constructed.Conclusion Classification algorithm based on association rule can be effectively used in mining image features,and constructing an image classifier to identify benign or malignant tumors.%目的 利用关联分类算法,构造医学图像分类器,对未知类型的脑肿瘤图像进行自动判别和分类,以帮助临床医生进行脑疾病的诊断和治疗.方法 对医学图像经过预处理后进行特征提取,再将提取的特征离散化后放到事务数据库中作为关联分类规则的输入,然后利用改进的Apriori算法构造医学图像分类器.结果 构造了医学图像分类器,用已知类型的图像训练分类器挖掘满足约束条件的关联规则,然后利用发现的关联规则对未知类型的医学图像进行分类以判断脑肿瘤的良恶性.结论 利用关联分类算法可以有效地挖掘医学图像特征,进而构造图像分类器,实现脑肿瘤良恶性的自动判别.

  10. Research and Realization of Mining Association Rules in Book Circulation Based on Visual FoxPro%基于Visual FoxPro编程的图书流通关联规则挖掘研究与实现

    Institute of Scientific and Technical Information of China (English)

    卢红杰

    2012-01-01

    对关联规则挖掘的经典Apriori算法进行了深入细致研究.在Visual FoxPro环境下,通过编程实现了经典的Apriori算法,完成了对辽宁石油化工大学近十年来图书借阅数据的关联规则挖掘.得出了专业图书间的借阅关联关系.为预测读者的借阅倾向、辅助采购决策、主动推送相关信息等服务提供了较为翔实的数据支持.%The classic Apriori algorithm for raining association rules is deeply studied. According to Visual FoxPro software, the classic Apriori algorithm is programmed through the computer, achieved mining association rules of borrowing books data of Liaoning Shihua University over the past decade. The association relationship of borrowing professional books is obtained. It not only provides more details about borrowing books data, but also forecasts the readers borrowing tendencies, assists to purchase the strategies of books, and actively provides some related information.

  11. Material and Energy Flows Associated with Select Metals in GREET 2. Molybdenum, Platinum, Zinc, Nickel, Silicon

    Energy Technology Data Exchange (ETDEWEB)

    Benavides, Pahola T. [Argonne National Lab. (ANL), Argonne, IL (United States); Dai, Qiang [Argonne National Lab. (ANL), Argonne, IL (United States); Sullivan, John L. [Argonne National Lab. (ANL), Argonne, IL (United States); Kelly, Jarod C. [Argonne National Lab. (ANL), Argonne, IL (United States); Dunn, Jennifer B. [Argonne National Lab. (ANL), Argonne, IL (United States)

    2015-09-01

    In this work, we analyzed the material and energy consumption from mining to production of molybdenum, platinum, zinc, and nickel. We also analyzed the production of solar- and semiconductor-grade silicon. We described new additions to and expansions of the data in GREET 2. In some cases, we used operating permits and sustainability reports to estimate the material and energy flows for molybdenum, platinum, and nickel, while for zinc and silicon we relied on information provided in the literature.

  12. Associations of stream health to altered flow and water temperature in the Sierra Nevada, California

    Science.gov (United States)

    Carlisle, Daren M.; S. Mark Nelson,; May, Jason

    2016-01-01

    Alteration of streamflow and thermal conditions may adversely affect lotic invertebrate communities, but few studies have assessed these phenomena using indicators that control for the potentially confounding influence of natural variability. We designed a study to assess how flow and thermal alteration influence stream health – as indicated by the condition of invertebrate communities. We studied thirty streams in the Sierra Nevada, California, that span a wide range of hydrologic modification due to storage reservoirs and hydroelectric diversions. Daily water temperature and streamflows were monitored, and basic chemistry and habitat conditions were characterized when invertebrate communities were sampled. Streamflow alteration, thermal alteration, and invertebrate condition were quantified by predicting site-specific natural expectations using statistical models developed using data from regional reference sites. Monthly flows were typically depleted (relative to natural expectations) during fall, winter, and spring. Most hydrologically altered sites experienced cooled thermal conditions in summer, with mean daily temperatures as much 12 °C below natural expectations. The most influential predictor of invertebrate community condition was the degree of alteration of March flows, which suggests that there are key interactions between hydrological and biological processes during this month in Sierra Nevada streams. Thermal alteration was also an important predictor – particularly at sites with the most severe hydrological alteration.

  13. Research on e-commerce commodity recommendation system based on mining algorithm of weighted association rules%基于加权关联规则挖掘算法的电子商务商品推荐系统研究

    Institute of Scientific and Technical Information of China (English)

    郝海涛; 马元元

    2016-01-01

    To solve the direct commodity rapid and accurate matching problem between electronic shoppers and merchants, the e⁃commerce commodity recommendation system based on mining algorithm of weighted association rules is researched. Ai⁃ming at the insufficiency of the classic Apriori algorithm,a new weighted fuzzy association rules mining algorithm is put forward to ensure the downward closure of frequent item sets. The work flow of the recommendation system was tested through the struc⁃tural design of e⁃commerce recommendation system,data preprocessing module design and recommendation module design. The hit rate is selected as the evaluation standard of different recommendation models. The contrastive analysis for the practical col⁃lected data was conducted with the half⁃off cross test method. The experimental results show that the hit rate of Top⁃N products in association rule set is significantly higher than that of the interest recommendation method and best selling recommendation method.%为了解决电子购物者和商家直接的商品快速、准确匹配问题,进行基于加权关联规则挖掘算法的电子商务商品推荐系统研究。首先指出了经典Apriori算法的缺点和不足,并提出一种新的加权模糊关联挖掘模型算法,以保证频繁项集的向下封闭性;通过对电子商务推荐系统的结构化设计、数据预处理模块设计、推荐模块设计,完成了推荐系统的工作流程测试;最后选取命中率作为不同推荐模型的评价标准,通过五折交叉试验法对实际采集数据进行了对比分析,试验结果表明关联规则集的Top⁃N产品命中率要明显高于兴趣推荐和畅销推荐法。

  14. Association Rules Mining Based on SVM and Its Application in Simulated Moving Bed PX Adsorption Process%基于支持向量基的关联规则挖掘及其在模拟移动床PX吸附分离过程中的应用

    Institute of Scientific and Technical Information of China (English)

    张英; 苏宏业; 褚健

    2005-01-01

    In this paper, a novel data mining method is introduced to solve the multi-objective optimization problems of process industry. A hyperrectangle association rule mining (HARM) algorithm based on support vector machines (SVMs) is proposed. Hyperrectangles rules are constructed on the base of prototypes and support vectors (SVs) under some heuristic limitations. The proposed algorithm is applied to a simulated moving bed (SMB) paraxylene (PX) adsorption process. The relationships between the key process variables and some objective variables such as purity, recovery rate of PX are obtained. Using existing domain knowledge about PX adsorption process, most of the obtained association rules can be explained.

  15. A rare association of cerebral dural arteriovenous fistula with venous aneurysm and contralateral flow-related middle cerebral artery aneurysm.

    Science.gov (United States)

    Onu, David O; Hunn, Andrew W; Harle, Robin A

    2013-09-19

    The association of cerebral dural arteriovenous fistula (DAVF) and ipsilateral flow related aneurysm has infrequently been reported. We describe a male patient who presented with an acute haemorrhagic stroke and was found to have a large right fronto-parietal intra-parenchymal haemorrhage from the ruptured Borden type II DAVF in addition to a large venous aneurysm and a flow related intraosseous aneurysm of the contralateral middle meningeal artery (MMA) all clearly delineated by CT and DSA. He underwent emergency stereotactic evacuation of the intraparenchymal haemorrhage and successful surgical treatment of all the vascular lesions at the same time with residual neurological deficit. To our knowledge, this is the first such reported case. We discuss the challenging surgical treatment, emphasising the role of CT/DSA in management, and provide a literature review.

  16. Implementation of an Associative Flow Rule Including Hydrostatic Stress Effects Into the High Strain Rate Deformation Analysis of Polymer Matrix Composites

    Science.gov (United States)

    Goldberg, Robert K.; Roberts, Gary D.; Gilat, Amos

    2003-01-01

    A previously developed analytical formulation has been modified in order to more accurately account for the effects of hydrostatic stresses on the nonlinear, strain rate dependent deformation of polymer matrix composites. State variable constitutive equations originally developed for metals have been modified in order to model the nonlinear, strain rate dependent deformation of polymeric materials. To account for the effects of hydrostatic stresses, which are significant in polymers, the classical J2 plasticity theory definitions of effective stress and effective inelastic strain, along with the equations used to compute the components of the inelastic strain rate tensor, are appropriately modified. To verify the revised formulation, the shear and tensile deformation of two representative polymers are computed across a wide range of strain rates. Results computed using the developed constitutive equations correlate well with experimental data. The polymer constitutive equations are implemented within a strength of materials based micromechanics method to predict the nonlinear, strain rate dependent deformation of polymer matrix composites. The composite mechanics are verified by analyzing the deformation of a representative polymer matrix composite for several fiber orientation angles across a variety of strain rates. The computed values compare well to experimentally obtained results.

  17. Seafloor geomorphology and glacimarine sedimentation associated with fast-flowing ice sheet outlet glaciers in Disko Bay, West Greenland

    Science.gov (United States)

    Streuff, Katharina; Ó Cofaigh, Colm; Hogan, Kelly; Jennings, Anne; Lloyd, Jeremy M.; Noormets, Riko; Nielsen, Tove; Kuijpers, Antoon; Dowdeswell, Julian A.; Weinrebe, Wilhelm

    2017-08-01

    Fast-flowing outlet glaciers currently drain the Greenland Ice Sheet (GIS), delivering ice, meltwater and debris to the fjords around Greenland. Although such glaciers strongly affect the ice sheet's mass balance, their glacimarine processes and associated products are still poorly understood. This study provides a detailed analysis of lithological and geophysical data from Disko Bay and the Vaigat Strait in central West Greenland. Disko Bay is strongly influenced by Jakobshavn Isbræ, Greenland's fastest-flowing glacier, which currently drains ∼7% of the ice sheet. Streamlined glacial landforms record the former flow of an expanded Jakobshavn Isbræ and adjacent GIS outlets through Disko Bay and the Vaigat Strait towards the continental shelf. Thirteen vibrocores contain a complex set of lithofacies including diamict, stratified mud, interbedded mud and sand, and bioturbated mud deposited by (1) suspension settling from meltwater plumes and the water column, (2) sediment gravity flows, and (3) iceberg rafting and ploughing. The importance of meltwater-related processes to glacimarine sedimentation in West Greenland fjords and bays is emphasised by the abundance of mud preserved in the cores. Radiocarbon dates constrain the position of the ice margin during deglaciation, and suggest that Jakobshavn Isbræ had retreated into central Disko Bay before 10.6 cal ka BP and to beyond Isfjeldsbanken by 7.6-7.1 cal ka BP. Sediment accumulation rates were up to 1.7 cm a-1 for ice-proximal glacimarine mud, and ∼0.007-0.05 cm a-1 for overlying distal sediments. In addition to elucidating the deglacial retreat history of Jakobshavn Isbræ, our findings show that the glacimarine sedimentary processes in West Greenland are similar to those in East Greenland, and that variability in such processes is more a function of time and glacier proximity than of geographic location and associated climatic regime.

  18. Object-oriented High Resolution Image Classification based on Association-rule%基于关联规则的面向对象高分辨率影像分类

    Institute of Scientific and Technical Information of China (English)

    张扬; 周子勇

    2012-01-01

    以北京市昌平区Geoeye-1高分辨率遥感影像为试验数据,研究了关联规则挖掘和面向对象相结合的地物分类方法。首先探讨了关联分类法的原理,再通过图像分割、特征提取、关联规则挖掘、分类器构建一系列过程实现了基于关联规则的面向对象高分辨率影像分类,最终评估分类精度并与K—近邻法进行了对比。结果表明,该方法具有较好精度,能够在一定程度上摆脱地物分类对于专家知识的依赖。%This paper has explored the method of high resolution image classification by combining association rule mining and object-oriented method.Firstly,according to the theory of Classification Based on Association(CBA),and a modified classifier builder was discussed.Secondly,the object-oriented high resolution image classification was achieved by image segmentation,feature extraction,association-rule extracted and classifier building.After that,Class Association Rules(CARs) was mined by the process of CBA-RG.It was proved that these rules correspond with the features of the ground object.According to the order of "confidence → spectrum complexity → support → generation sequence",a modified classifier was built based on these rules.Finally,we evaluated the precision of the classification result and compared it with the result of K-Nearest Neighbors.The experiment shows that the precision is relatively high and can move away from the dependence on the expert knowledge in a certain degree.

  19. Selecting the Model of Teaching Methods Based on The Application Type of Tax Mining Association Rules%基于关联规则挖掘的应用型税法教学方法选择模型

    Institute of Scientific and Technical Information of China (English)

    刘纯林; 孙睿潇

    2016-01-01

    针对目前税法教学方法无法达到实践应用技术型人才的培养目标,并且独立院校对应用型税法教学方法的选择上也无法满足应用技术型人才培养的需求,本文提出了一种基于模糊集优化关联规则挖掘的应用型税法教学方法选择模型,它是建立在关联规则挖掘算法的原则之上,运用模糊集提升了它准确性,再将专题法、案例法、讲授法、归纳比较法、“讲、读、练”法分别对五个不同的班级进行应用型税法教学,最后采用基于模糊集优化关联规则挖掘的应用型税法教学方法选择模型对其进行分析,并将得到的关联规则的强弱替代教学方法的优劣性。算法仿真结果证明了本文提出的优化模型比原算法更加准确。%Based on the fact that current teaching methods of revenue can not achieve the training objectives of cultivating practical and technical personnel, and independent institutions to choose the tax applied on teaching methods can not meet the needs of training practical and technical personnel, this paper presents a new teaching method applied tax rules mining selection model based on a fuzzy set optimization association. It is built on association rule mining algorithm, and its accuracy is improved based on fuzzy sets. What is more, teaching law, special law, case law, comparative law induction,"speaking, reading practicing"law have been conducted on tax applied teaching in five different classes. Finally, choose the model to analyze them using teaching methods of applied tax based on related optimization rule mining of fuzzy sets, and replace pros and cons of teaching method with resulting substitute teaching association rules. Algorithm simulation results show that the improved model have more accuracy compared to the original one.

  20. NAGWS Volleyball Guide 1990: Official Rules & Interpretations/Officiating.

    Science.gov (United States)

    American Alliance for Health, Physical Education, Recreation and Dance, Reston, VA. National Association for Girls and Women in Sport.

    This guide presents the 1990 update of the National Association for Girls & Women in Sport (NAGWS) interscholastic and collegiate volleyball rules. It includes the official U.S. volleyball rules and a summary of rule changes, definitions of skills and fouls, and a summary of penalties. Officiating techniques and mechanics are covered with a…

  1. Stable canonical rules

    NARCIS (Netherlands)

    Iemhoff, R.; Bezhanishvili, N.; Bezhanishvili, Guram

    2016-01-01

    We introduce stable canonical rules and prove that each normal modal multi-conclusion consequence relation is axiomatizable by stable canonical rules. We apply these results to construct finite refutation patterns for modal formulas, and prove that each normal modal logic is axiomatizable by stable

  2. Branes and wrapping rules

    CERN Document Server

    Bergshoeff, Eric A

    2011-01-01

    We show that the branes of ten-dimensional IIA/IIB string theory must satisfy, upon toroidal compactification, specific wrapping rules in order to reproduce the number of supersymmetric branes that follows from a supergravity analysis. The realization of these wrapping rules suggests that IIA/IIB string theory contains a whole class of generalized Kaluza-Klein monopoles.

  3. Branes and Wrapping Rules

    NARCIS (Netherlands)

    Bergshoeff, E.; Riccioni, F.

    2012-01-01

    We show that the branes of ten-dimensional IA/IIB string theory must satisfy, upon toroidal compactification, specific wrapping rules in order to reproduce the number of supersymmetric branes that follows from a supergravity analysis. The realization of these wrapping rules suggests that IA/IIB stri

  4. Scoped Dynamic Rewrite Rules

    NARCIS (Netherlands)

    Visser, Eelco

    2002-01-01

    The applicability of term rewriting to program transformation is limited by the lack of control over rule application and by the context-free nature of rewrite rules. The first problem is addressed by languages supporting user-definable rewriting strategies. This paper addresses the second problem b

  5. When do ruling elites support productive sectors?

    DEFF Research Database (Denmark)

    Kjær, Anne Mette

    that the ruling elite initially supported the fishing industry because of industry pressure. They have failed to enforce fisheries management because there are big political costs associated with such enforcement. The dairy sector in the southwestern milk region was initially supported because the ruling elite......This paper explains the differences in ruling elite support for the fisheries and dairy sectors in Uganda. Although production in Uganda has not generally been promoted in any sustained way, ruling elites have to varying degrees supported the dairy and fisheries sectors. The paper shows...... production is possible if there is strong industry pressure and when the initiatives to promote the sector are also seen to help build or maintain the ruling coalition....

  6. Analysis of the dynamic energy flow associated with phagocytosis of bacteria

    Directory of Open Access Journals (Sweden)

    Paul Okpala

    2015-09-01

    Full Text Available This paper treats the phenomenon of phagocytosis from the flow of energy point of view. Considerable efforts have been made towards elucidating the subject of phagocytosis in other fields of learning, but little has been said about the mechanical work that is done during phagocytosis. Phagocytosis without doubt is an interaction that involves the flow of energy. Energy equation model of phagocytosis is then presented in this paper to analyze the mechanical energy that is involved in the build-up of the engulfment of bacteria by the phagocytes. Data of the E Coli bacteria from published work was then applied to the solution of the energy equation. A borderline contact angle ϑ of 77.356° between the phagocyte and the bacteria at χ=0 was deduced in this work. It was shown that when ϑ77.356°, χ>0, engulfment is not favoured for E-coli. This condition is conceptually in line with ΔFNET approach reported in the literature. Data of four different bacterial species were also used to plot the graphs of the engulfment parameter χ against contact angle ϑ which revealed that the more hydrophobic bacteria are easily phagocytized than the more hydrophilic ones.

  7. 改进的关联规则在文献个性化检索中的应用研究%Application Research on Improved Association Rules in Literature Personalized Searching

    Institute of Scientific and Technical Information of China (English)

    郑羽洁; 章杰鑫

    2011-01-01

    In accordance with the shortcomings of library literature searching system which can not provide personalized searching service for different readers, this paper researches how to carry out personalized searching, brings up an idea of applying association rules in the original searching result personalized sorting by readers level, through data of a certain university library, describes the process of sorting for the mining result, to test and verify the feasibility of application association rules in literature personalized searching.%针对当前高校图书馆文献检索系统不能面向不同读者提供个性化检索服务的弱点,进行文献个性化检索的研究,提出将关联规则运用于对原始检索结果集按照读者层次进行个性化排序的设想,并以某高校图书馆的数据为例,详细描述利用改进的关联规则算法挖掘历史借阅数据,然后利用挖掘结果进行排序的过程,理论和实验验证将关联规则应用在文献个性化检索中的可行性.

  8. Application Research in Medicine Based on Texture Features Association Rules Mining%基于纹理特征的关联规则挖掘方法的医学应用

    Institute of Scientific and Technical Information of China (English)

    于超; 王璐; 吴琼; 裴志松

    2012-01-01

    In order to meet the requirement of medical image auxiliary diagnosis, we present a feature fusion algorithm based on Apriori algorithm: texture features and patient natural features in HIS ( Hospital Information System). Accordingly, the combination of pruning methods associated rule base, prototype system for a CT (Computer Tomography) image is divided into normal and abnormal categories. Experiments were evaluated in accordance with the system, showing that association rules established by the algorithm library, in the auxiliary doctor diagnosed, with good results.%为满足借助医学图像辅助诊断的要求,提出了一种基于Apriori算法的特征融合算法:融合图像的纹理特征和医院信息系统( HIS:Hospital Information System)中病患自然特征.结合剪枝方法建立关联规则库,实现了一个可以自动将CT( Computer Tomography)图像分为正常与异常两类的原型系统.依据该系统进行了评价实验.实验表明,通过该算法建立的关联规则库,对辅助医生诊断具有较好的效果.

  9. System and Empirical Study on Adverse Drug Reaction Warning Based on Association Rule%基于关联规则的ADR预警系统及实证研究

    Institute of Scientific and Technical Information of China (English)

    冯秀珍; 贺小红; 冯变玲

    2012-01-01

    针对目前我国药品不良反应(ADR)预警的不足,基于数据立方的多维关联规则挖掘方法引入药品不良反应预警领域,提出基于关联规则的ADR预警系统框架,并结合药品不良反应自发呈报系统(SRSs)实际数据进行实证分析.根据支持度和置信度,从药品和用药患者两个维度实现预警,为ADR预测预警问题提供一种新方法,为医生用药提供决策支持.%To deal with the current insufficiency on adverse drug reaction (ADR) warning in our country, the paper firstly introduced the multidimensional association rule mining methods based on data cube into the field of warning of ADR, then proposed the warning system framework of ADR based on association rule, and finally carried on an empirical analysis combining the data from ADR spontaneous reporting systems. Based on the support and confidence, the paper re-alized the warning function from two dimensions of patients and drugs, which provided a new method for the problem of ADR warning. This was significantly meaningful to provide supports for prescription on the illnesses treatments.

  10. CONGESTIVE HEART FAILURE IN DOGS IS ASSOCIATED WITH INCREASED PLATELET LEUKOCYTE AGGREGATION MEASURED BY FLOW CYTOMETRY

    DEFF Research Database (Denmark)

    Tarnow, Inge; Andreasen, Susanne SH; Olsen, Lisbeth Høier

    2010-01-01

    CONGESTIVE HEART FAILURE IN DOGS IS ASSOCIATED WITH ENHANCED PLATELET-LEUKOCYTE AGGREGATES - A MARKER FOR PLATELET ACTIVATION. I Tarnow1, LH Olsen2, SHS Andreasen2, SG Moesgaard2, CE Rasmussen2, AT Kristensen1, T Falk2. 1Departments of Small Animal Clinical Sciences and 2Animal and Veterinary Basic...... Sciences, Faculty of Life Science, University of Copenhagen, Denmark. Chronic congestive heart failure (CHF) in humans is associated with abnormal hemostasis, and changes in hemostatic biomarkers carry a poor prognosis. CHF in dogs has been associated with plasma markers of hypercoagulability, however...

  11. Analysis of virtual water flows associated with the trade of maize in the SADC region: importance of scale

    CSIR Research Space (South Africa)

    Dabrowski, James M

    2009-10-01

    Full Text Available stream_source_info Dabrowski_2009.pdf.txt stream_content_type text/plain stream_size 52531 Content-Encoding UTF-8 stream_name Dabrowski_2009.pdf.txt Content-Type text/plain; charset=UTF-8 Hydrol. Earth Syst. Sci., 13..., 1967–1977, 2009 www.hydrol-earth-syst-sci.net/13/1967/2009/ © Author(s) 2009. This work is distributed under the Creative Commons Attribution 3.0 License. Hydrology and Earth System Sciences Analysis of virtual water flows associated...

  12. 基于磁盘表存储FP-TREE的关联规则挖掘算法%Mining Algorithm of Association Rules Based on Disk Table Resident FP-TREE

    Institute of Scientific and Technical Information of China (English)

    申彦; 宋顺林; 朱玉全

    2012-01-01

    随着现实待挖掘数据库规模不断增长,系统可使用的内存成为用FP-GROWTH算法进行关联规则挖掘的瓶颈.为了摆脱内存的束缚,对大规模数据库中的数据进行关联规则挖掘,基于磁盘的关联规则挖掘成为重要的研究方向.对此,改进原始的FP-TREE数据结构,提出了一种新颖的基于磁盘表的DTRFP-GROWTH (disk table resident FP-TREE growth)算法.该算法利用磁盘表存储FPTREE,降低内存使用,在传统FP-GROWTH算法占用过多内存、挖掘工作无法进行时,以独特的磁盘表存储FP-TREE技术,减少内存使用,能够继续完成挖掘工作,适合空间性能优先的场合.不仅如此,该算法还将关联规则挖掘和关系型数据库整合,克服了基于文件系统相关算法效率较低、开发难度较大等问题.在真实数据集上进行了验证实验以及性能分析.实验结果表明,在内存空间有限的情况下,DTRFP-GROWTH算法是一种有效的基于磁盘的关联规则挖掘算法.%As the size of the database to be mined is increasing constantly, the size of physical memory available has become a bottleneck when using FP-GROWTH algorithm for association rules mining. So. it is necessary to tackle space scalability by some new algorithms in order to mine association rules in huge database. Nowadays, disk-resident algorithm has become the main target. Therefore, the original data structure of FP-TREE is improved and a novel algorithm called DTRFP-GROWTH (disk table resident FP-TREE growth) is presented. This algorithm uses disk table for storing FP-TREE to decrease memory usage. When the mining works failed for FP-GROWTH using too much memory, DTRFP GROWTH can continue to mine association rules from huge database by its special skill called disk table resident FP-TREE, which is suitable to occasions of space performance priority. In addition, this algorithm also integrates association rules mining with RDBMS system. It overcomes the problems of

  13. A novel method for analyzing seismic energy loss associated with wave-induced fluid flow

    Science.gov (United States)

    Solazzi, Santiago G.; Germán Rubino, J.; Müller, Tobias M.; Milani, Marco; Guarracino, Luis; Holliger, Klaus

    2014-05-01

    Whenever a seismic wave propagates through a fluid saturated porous rock that contains heterogeneities in the mesoscopic scale, that is, heterogeneities larger than the typical pore size but smaller than the predominant wavelengths, local gradients in the pore-fluid pressure arise. These pressure gradients, which are due to the uneven response of the heterogeneities to the stress applied by the passing seismic wavefield, induce viscous fluid flow and energy dissipation. Consequently, seismic waves tend to be strongly attenuated and dispersed in this kind of media. This attenuation mechanism scales with the compressibility contrast between heterogeneities and the background. Correspondingly, environments characterized by patchy saturation as well as fractured media represent two prominent scenarios where seismic attenuation due to wave-induced fluid flow is expected to be the predominant energy dissipation mechanism. Numerical oscillatory compressibility and shear tests based on the quasistatic poroelasticity equations provide an effective means to compute equivalent viscoelastic moduli for representative rock samples of the heterogeneous media under study. Approaches of this type rely on the existence of a dynamic-equivalent medium, that is, the heterogeneous porous rock is represented by an equivalent homogeneous viscoelastic solid that exhibits an overall response similar to that of the original heterogeneous porous sample. This methodology allows for extracting the equivalent seismic attenuation and phase velocity of the sample, but fails to provide any information with regard to the underlying physical processes. In this work, we present a novel approach based on the quantification of the energy loss taking place in the interior of the considered heterogeneous rock sample. To this end, we first determine the spatial distribution of the energy dissipation in response to the applied oscillatory stresses. Next, we quantify the total dissipated energy as well as

  14. Effect of mild cognitive impairment and APOE genotype on resting cerebral blood flow and its association with cognition.

    Science.gov (United States)

    Wierenga, Christina E; Dev, Sheena I; Shin, David D; Clark, Lindsay R; Bangen, Katherine J; Jak, Amy J; Rissman, Robert A; Liu, Thomas T; Salmon, David P; Bondi, Mark W

    2012-08-01

    Using whole-brain pulsed arterial spin labeling magnetic resonance imaging, resting cerebral blood flow (CBF) was measured in 20 mild cognitive impairment (MCI; 11 ɛ3 and 9 ɛ4) and 40 demographically matched cognitively normal (CN; 27 ɛ3 and 13 ɛ4) participants. An interaction of apolipoprotein (APOE) genotype (ɛ3 and ɛ4) and cognitive status (CN and MCI) on quantified gray-matter CBF corrected for partial volume effects was found in the left parahippocampal and fusiform gyri (PHG/FG), right middle frontal gyrus, and left medial frontal gyrus. In the PHG/FG, CBF was elevated for CN ɛ4 carriers but decreased for MCI ɛ4 carriers. The opposite pattern was seen in frontal regions: CBF was decreased for CN ɛ4 carriers but increased for MCI ɛ4 carriers. Cerebral blood flow in the PHG/FG was positively correlated with verbal memory for CN ɛ4 adults (r=0.67, P=0.01). Cerebral blood flow in the left medial frontal gyrus was positively correlated with verbal memory for MCI ɛ4 adults (r=0.70, P=0.05). Findings support dynamic pathophysiologic processes in the brain associated with Alzheimer's disease risk and indicate that cognitive status and APOE genotype have interactive effects on CBF. Correlations between CBF and verbal memory suggest a differential neurovascular compensatory response in posterior and anterior cortices with cognitive decline in ɛ4 adults.

  15. Research of the methods of association rules in image database%图像数据库关联规则的挖掘方法研究

    Institute of Scientific and Technical Information of China (English)

    王远敏

    2012-01-01

      In multimedia applications,the use of the image database is increasingly widespread. In order to use image database more effectively,many data mining techniques is used in image database.This paper uses FP_tree techniques in data mining to mine the rule in image database and constructs an new image database system.%  在多媒体应用中,图像数据库的使用日趋广泛,为了更有效地使用图像数据库,许多数据挖掘技术被用于图像数据库中。本文使用数据挖掘中的关联规则方法来进一步提高图像数据库的性能,基于此构建了一个图像数据库系统,在这个系统中使用了FP增长算法挖掘图像数据的关联规则。

  16. Efficient ecologic and economic operational rules for dammed systems by means of nondominated sorting genetic algorithm II

    Science.gov (United States)

    Niayifar, A.; Perona, P.

    2015-12-01

    River impoundment by dams is known to strongly affect the natural flow regime and in turn the river attributes and the related ecosystem biodiversity. Making hydropower sustainable implies to seek for innovative operational policies able to generate dynamic environmental flows while maintaining economic efficiency. For dammed systems, we build the ecological and economical efficiency plot for non-proportional flow redistribution operational rules compared to minimal flow operational. As for the case of small hydropower plants (e.g., see the companion paper by Gorla et al., this session), we use a four parameters Fermi-Dirac statistical distribution to mathematically formulate non-proportional redistribution rules. These rules allocate a fraction of water to the riverine environment depending on current reservoir inflows and storage. Riverine ecological benefits associated to dynamic environmental flows are computed by integrating the Weighted Usable Area (WUA) for fishes with Richter's hydrological indicators. Then, we apply nondominated sorting genetic algorithm II (NSGA-II) to an ensemble of non-proportional and minimal flow redistribution rules in order to generate the Pareto frontier showing the system performances in the ecologic and economic space. This fast and elitist multiobjective optimization method is eventually applied to a case study. It is found that non-proportional dynamic flow releases ensure maximal power production on the one hand, while conciliating ecological sustainability on the other hand. Much of the improvement in the environmental indicator is seen to arise from a better use of the reservoir storage dynamics, which allows to capture, and laminate flood events while recovering part of them for energy production. In conclusion, adopting such new operational policies would unravel a spectrum of globally-efficient performances of the dammed system when compared with those resulting from policies based on constant minimum flow releases.

  17. Rules on Paper, Rules in Practice

    OpenAIRE

    Al-Dahdah, Edouard; Corduneanu-Huci, Cristina; Raballand, Gael; Sergenti, Ernest; Ababsa, Myriam

    2016-01-01

    The primary focus of this book is on a specific outcome of the rule of law: the practical enforcement of laws and policies, and the determinants of this enforcement, or lack thereof. Are there significant and persistent differences in implementation across countries? Why are some laws and policies more systematically enforced than others? Are “good” laws likely to be enacted, and if not, what stands in the way? We answer these questions using a theoretical framework and detailed empirical...

  18. An improvement of tree-Rule firewall for a large network: supporting large rule size and low delay

    NARCIS (Netherlands)

    Chomsiri, Thawatchai; He, Xiangjian; Nanda, Priyadarsi; Tan, Zhiyuan

    2016-01-01

    Firewalls are important network devices which provide first hand defense against network threat. This level of defense is depended on firewall rules. Traditional firewalls, i.e., Cisco ACL, IPTABLES, Check Point and Juniper NetScreen firewall use listed rule to regulate packet flows. However, the li

  19. The effect of corrosion inhibitors on microbial communities associated with corrosion in a model flow cell system.

    Science.gov (United States)

    Duncan, Kathleen E; Perez-Ibarra, Beatriz Monica; Jenneman, Gary; Harris, Jennifer Busch; Webb, Robert; Sublette, Kerry

    2014-01-01

    A model flow cell system was designed to investigate pitting corrosion in pipelines associated with microbial communities. A microbial inoculum producing copious amounts of H₂S was enriched from an oil pipeline biofilm sample. Reservoirs containing a nutrient solution and the microbial inoculum were pumped continuously through six flow cells containing mild steel corrosion coupons. Two cells received corrosion inhibitor "A", two received corrosion inhibitor "B", and two ("untreated") received no additional chemicals. Coupons were removed after 1 month and analyzed for corrosion profiles and biofilm microbial communities. Coupons from replicate cells showed a high degree of similarity in pitting parameters and in microbial community profiles, as determined by 16S rRNA gene sequence libraries but differed with treatment regimen, suggesting that the corrosion inhibitors differentially affected microbial species. Viable microbial biomass values were more than 10-fold higher for coupons from flow cells treated with corrosion inhibitors than for coupons from untreated flow cells. The total number of pits >10 mils diameter and maximum pitting rate were significantly correlated with each other and the total number of pits with the estimated abundance of sequences classified as Desulfomicrobium. The maximum pitting rate was significantly correlated with the sum of the estimated abundance of Desulfomicrobium plus Clostridiales, and with the sum of the estimated abundance of Desulfomicrobium plus Betaproteobacteria. The lack of significant correlation with the estimated abundance of Deltaproteobacteria suggests not all Deltaproteobacteria species contribute equally to microbiologically influenced corrosion (MIC) and that it is not sufficient to target one bacterial group when monitoring for MIC.

  20. Do Fiscal Rules Matter?

    DEFF Research Database (Denmark)

    Grembi, Veronica; Nannicini, Tommaso; Troiano, Ugo

    2016-01-01

    Fiscal rules are laws aimed at reducing the incentive to accumulate debt, and many countries adopt them to discipline local governments. Yet, their effectiveness is disputed because of commitment and enforcement problems. We study their impact applying a quasi-experimental design in Italy. In 1999......, the central government imposed fiscal rules on municipal governments, and in 2001 relaxed them below 5,000 inhabitants. We exploit the before/after and discontinuous policy variation, and show that relaxing fiscal rules increases deficits and lowers taxes. The effect is larger if the mayor can be reelected...

  1. Climate-friendly Default Rules

    DEFF Research Database (Denmark)

    Sunstein, Cass R.; Reisch, Lucia A.

    . The underlying reasons include the power of suggestion; inertia and procrastination; and loss aversion. If well-chosen, climate-friendly defaults are likely to have large effects in reducing the economic and environmental harms associated with various products and activities. In deciding whether to establish...... between climate-friendly products or services and alternatives that are potentially damaging to the climate but less expensive? The answer may well depend on the default rule. Indeed, climate-friendly default rules may well be a more effective tool for altering outcomes than large economic incentives...... climate-friendly defaults, choice architects (subject to legal constraints) should consider both consumer welfare and a wide range of other costs and benefits. Sometimes that assessment will argue strongly in favor of climate-friendly defaults, particularly when both economic and environmental...

  2. Cold molecular gas in the Perseus cluster core - Association with X-ray cavity, Halpha filaments and cooling flow -

    CERN Document Server

    Salomé, P; Crawford, C; Edge, A C; Erlund, M; Fabian, A C; Hatch, N A; Johnstone, R M; Sanders, J S; Wilman, R J

    2006-01-01

    Cold molecular gas has been recently detected in several cooling flow clusters of galaxies where huge optical nebulosities often stand. These optical filaments are tightly linked to the cooling flow and to the related phenomena, like the rising bubbles of relativistic plasma, fed by the radio jets. We present here a map in the CO(2-1) rotational line of the cold molecular gas associated with some Halpha filaments surrounding the central galaxy of the Perseus cluster: NGC 1275. The map, extending to about 50 kpc (135 arcsec) from the center of the galaxy, has been made with the 18-receiver array HERA, at the focus of the IRAM 30m telescope. Although most of the cold gas is concentrated to the center of the galaxy, the CO emission is also clearly associated to the extended filaments conspicuous in ionised gas and could trace a possible reservoir fueling the star formation there. Some of the CO emission is also found where the X-ray gas could cool down more efficiently: at the rims of the central X-ray cavity (w...

  3. Pressure enhancement associated with meridional flow in high-speed solar wind: possible evidence for an interplanetary magnetic flux rope

    Directory of Open Access Journals (Sweden)

    C.-Y. Tu

    Full Text Available A sizable total-pressure (magnetic pressure plus kinetic pressure enhancement was found within the high-speed wind stream observed by Helios 2 in 1976 near 0.3 AU. The proton density and temperature and the magnetic magnitude simultaneously increased for about 6 h. This pressure rise was associated with a comparatively large southward flow velocity component (with Vz ≈ –100 km · s–1 and magnetic-field rotation. The pressure enhancement was associated with unusual features in the electron distribution function. It shows a wide angular distribution of electron counting rates in the low-energy (57.8 eV channel, while previous to the enhancement it exhibits a wide angular distribution of electron count rate in the high-energy (112, 221 and 309 eV channels, perhaps indicating the mirroring of electrons in the converging field lines of the background magnetic field. These fluid and kinetic phenomena may be explained as resulting from an interplanetary magnetic flux rope which is not fully convected by the flow but moves against the background wind towards the Sun.

  4. Free Association in Sex Education: Understanding Sexuality as the Flow of Thought in Conversation and Curriculum

    Science.gov (United States)

    Casemore, Brian

    2010-01-01

    This paper draws on the theory and method of free association in psychoanalysis to frame an investigation of the content, structure, and function of the thinking expressed in conversations about sexuality and sexual health. The investigation emerges from an ongoing three-year study of the way adolescents, teachers, and peer sex educators negotiate…

  5. Free Association in Sex Education: Understanding Sexuality as the Flow of Thought in Conversation and Curriculum

    Science.gov (United States)

    Casemore, Brian

    2010-01-01

    This paper draws on the theory and method of free association in psychoanalysis to frame an investigation of the content, structure, and function of the thinking expressed in conversations about sexuality and sexual health. The investigation emerges from an ongoing three-year study of the way adolescents, teachers, and peer sex educators negotiate…

  6. Dodgson's Rule Approximations and Absurdity

    CERN Document Server

    McCabe-Dansted, John C

    2010-01-01

    With the Dodgson rule, cloning the electorate can change the winner, which Young (1977) considers an "absurdity". Removing this absurdity results in a new rule (Fishburn, 1977) for which we can compute the winner in polynomial time (Rothe et al., 2003), unlike the traditional Dodgson rule. We call this rule DC and introduce two new related rules (DR and D&). Dodgson did not explicitly propose the "Dodgson rule" (Tideman, 1987); we argue that DC and DR are better realizations of the principle behind the Dodgson rule than the traditional Dodgson rule. These rules, especially D&, are also effective approximations to the traditional Dodgson's rule. We show that, unlike the rules we have considered previously, the DC, DR and D& scores differ from the Dodgson score by no more than a fixed amount given a fixed number of alternatives, and thus these new rules converge to Dodgson under any reasonable assumption on voter behaviour, including the Impartial Anonymous Culture assumption.

  7. General Quantization Rule

    CERN Document Server

    Maiz, F

    2012-01-01

    A general quantization rule for bound states of the Schrodinger equation is presented. Like fundamental theory of integral, our idea is mainly based on dividing the potential into many pieces, solving the Schr\\"odinger equation, and deriving the general quantization rule. For both exactly and non-exactly solvable systems, the energy levels of all the bound states can be easily calculated from the general quantization rule. Using this new general quantization rule, we re-calculate the energy levels for the one-dimensional system, with an infinite square well, with the harmonic oscillator potential, with the Morse Potential, with the symmetric and asymmetric Rosen-Morse potentials, with the first P\\"oschl-Teller potential, with the Coulomb Potential, with the V-shape Potential, and the ax^4 potential, and for the three dimensions systems, with the harmonic oscillator potential, with the ordinary Coulomb potential, and for the hydrogen atom.

  8. Drug Plan Coverage Rules

    Science.gov (United States)

    ... get about Medicare Lost/incorrect Medicare card Report fraud & abuse File a complaint Identity theft: protect yourself ... drug plan How Part D works with other insurance Find health & drug plans Drug plan coverage rules ...

  9. Staff rules and regulations

    CERN Multimedia

    HR Department

    2007-01-01

    The 11th edition of the Staff Rules and Regulations, dated 1 January 2007, adopted by the Council and the Finance Committee in December 2006, is currently being distributed to departmental secretariats. The Staff Rules and Regulations, together with a summary of the main modifications made, will be available, as from next week, on the Human Resources Department's intranet site: http://cern.ch/hr-web/internal/admin_services/rules/default.asp The main changes made to the Staff Rules and Regulations stem from the five-yearly review of employment conditions of members of the personnel. The changes notably relate to: the categories of members of the personnel (e.g. removal of the local staff category); the careers structure and the merit recognition system; the non-residence, installation and re-installation allowances; the definition of family, family allowances and family-related leave; recognition of partnerships; education fees. The administrative circulars, some of which are being revised following the ...

  10. TANF Rules Data Base

    Data.gov (United States)

    U.S. Department of Health & Human Services — Single source providing information on Temporary Assistance for Needy Families (TANF) program rules among States and across years (currently 1996-2010), including...

  11. Revised Total Coliform Rule

    Science.gov (United States)

    The Revised Total Coliform Rule (RTCR) aims to increase public health protection through the reduction of potential pathways for fecal contamination in the distribution system of a public water system (PWS).

  12. Rules Governing Female Professionals——Symposium sponsored by the Working Committee of Professional Women, under the China Personnel Research Association

    Institute of Scientific and Technical Information of China (English)

    1996-01-01

    THE number of nongovernmental women’s organizations in China has increased dramatically in recent years. The long list includes friendship organizations of women in the same trade and a number of academic research associations. The Working Committee on Female Professionals, under China Personnel Research Association represents on the major national academic women’s societies. The association’s goal is to study problems confronting female professional women, establishing for

  13. The flame anchoring mechanism and associated flow structure in bluff-body stabilized lean premixed flames

    Science.gov (United States)

    Michaels, Dan; Shanbhogue, Santosh; Ghoniem, Ahmed

    2015-11-01

    We present numerical analysis of a lean premixed flame anchoring on a heat conducting bluff-body. Different mixtures of CH4/H2/air are analyzed in order to systematically vary the burning velocity, adiabatic flame temperature and extinction strain rate. The study was motivated by our experimental measurements in a step combustor which showed that both the recirculation zone length and stability map under acoustically coupled conditions for different fuels and thermodynamic conditions collapse using the extinction strain rate. The model fully resolves unsteady two-dimensional flow with detailed chemistry and species transport, and without artificial flame anchoring boundary conditions. The model includes a low Mach number operator-split projection algorithm, coupled with a block-structured adaptive mesh refinement and an immersed boundary method for the solid body. Calculations reveal that the recirculation zone length correlates with the flame extinction strain rate, consistent with the experimental evidence. It is found that in the vicinity of the bluff body the flame is highly stretched and its leading edge location is controlled by the reactants combustion characteristics under high strain. Moreover, the flame surface location relative to the shear layer influences the vorticity thus impacting the velocity field and the recirculation zone. The study sheds light on the experimentally observed collapse of the combustor dynamics using the reactants extinction strain rate.

  14. (FIELD) SYMMETRIZATION SELECTION RULES

    Energy Technology Data Exchange (ETDEWEB)

    P. PAGE

    2000-08-01

    QCD and QED exhibit an infinite set of three-point Green's functions that contain only OZI rule violating contributions, and (for QCD) are subleading in the large N{sub c} expansion. We prove that the QCD amplitude for a neutral hybrid {l_brace}1,3,5. . .{r_brace}{+-} exotic current to create {eta}{pi}{sup 0} only comes from OZI rule violating contributions under certain conditions, and is subleading in N{sub c}.

  15. Symmetrization Selection Rules, 1

    CERN Document Server

    Page, P R

    1996-01-01

    We introduce a category of strong and electromagnetic interaction selection rules for the two-body connected decay and production of exotic J^{PC} = 0^{+-}, 1^{-+}, 2^{+-}, 3^{-+}, ... hybrid and four-quark mesons. The rules arise from symmetrization in states in addition to Bose symmetry and CP invariance. Examples include various decays to \\eta'\\eta, \\eta\\pi, \\eta'\\pi and four-quark interpretations of a 1^{-+} signal.

  16. News and Trading Rules

    Science.gov (United States)

    2003-01-01

    indexes or small groups of forex series. Although I use a shorter time period – five years for the work on technical analysis and machine learning, only...I start with practitioner-developed technical analysis constructs, sys- tematically examining their ability to generate trading rules profitable on...a large universe of stocks. Then, I use these technical analysis constructs as the underlying representation for a simple trading rule leaner, with

  17. Data breaches. Final rule.

    Science.gov (United States)

    2008-04-11

    This document adopts, without change, the interim final rule that was published in the Federal Register on June 22, 2007, addressing data breaches of sensitive personal information that is processed or maintained by the Department of Veterans Affairs (VA). This final rule implements certain provisions of the Veterans Benefits, Health Care, and Information Technology Act of 2006. The regulations prescribe the mechanisms for taking action in response to a data breach of sensitive personal information.

  18. 聚类与关联规则在信息舞弊识别中的应用%The Application of Clustering and Associate Rule Mining to Fraud Information Identification

    Institute of Scientific and Technical Information of China (English)

    幸莉仙; 黄慧连

    2012-01-01

    针对现代电子数据迅速膨胀,传统的审计方式已经无法应对海量的业务数据,试图将数据挖掘中的聚类和关联规则算法引入审计领域.在研究聚类与关联规则算法的含义及相关算法—K-Means和Apriori算法的基础上,提出了一种基于聚类与关联规则的审计模型,并以某市城镇医疗保险的审计为例,首先利用聚类分析进行数据筛选,然后利用关联规则挖掘海量数据之间潜在的关系,为审计提供线索.文章通过案例分析为数据挖掘在信息舞弊识别领域的应用提供参考.%Considering that with the rapid expansion of electronic data, the traditional audit approachs can not cope with vast business data, this paper intend to introduce the Clustering and Association Rule Mining in the audit fields. Based on the study of the meaning of Clustering and Association Rule Mining and their Algorithm—K-Means and Apriori, this article proposed an audit model which is based on the Clustering and Association Rule Mining, at the same time, taking the audit of medical insurance of some a city as an example, it detailed first how to use the Clustering to filter data, then how to mining the potential relationships in vast data so as to determine the audit priorities and audit clues.Through the case, the article is committed to provide a reference for the application of data mining in the fraud information identification.

  19. Biological mechanisms associated with triazophos (TAP) removal by horizontal subsurface flow constructed wetlands (HSFCW).

    Science.gov (United States)

    Wu, Juan; Feng, Yuqin; Dai, Yanran; Cui, Naxin; Anderson, Bruce; Cheng, Shuiping

    2016-05-15

    Triazophos (TAP) is a widely used pesticide that is easily accumulated in the environment due to its relatively high stability: this accumulation from agricultural runoff results in potential hazards to aquatic ecosystems. Constructed wetlands are generally considered to be an effective technology for treating TAP polluted surface water. However, knowledge about the biological mechanisms of TAP removal is still lacking. This study investigates the responses of a wetland plant (Canna indica), substrate enzymes and microbial communities in bench-scale horizontal subsurface-flow constructed wetlands (HSCWs) loaded with different TAP concentrations (0, 0.1, 0.5 and 5 mg · L(-1)). The results indicate that TAP stimulated the activities of superoxide dismutase (SOD) and peroxidase (POD) in the roots of C. indica. The highest TAP concentrations significantly inhibited photosynthetic activities, as shown by a reduced effective quantum yield of PS II (ΦPS II) and lower electron transport rates (ETR). However, interestingly, the lower TAP loadings exhibited some favorable effects on these two variables, suggesting that C. indica is a suitable species for use in wetlands designed for treatment of low TAP concentrations. Urease and alkaline phosphatase (ALP) in the wetland substrate were activated by TAP. Two-way ANOVA demonstrated that urease activity was influenced by both the TAP concentrations and season, while acidphosphatase (ACP) only responded to seasonal variations. Analysis of high throughput sequencing of 16S rRNA revealed seasonal variations in the microbial community structure of the wetland substrate at the phylum and family levels. In addition, urease activity had a greater correlation with the relative abundance of some functional microbial groups, such as the Bacillaceae family, and the ALP and ACP may be influenced by the plant more than substrate microbial communities. Copyright © 2016 Elsevier B.V. All rights reserved.

  20. Regional cerebral blood flow changes associated with transcranial magnetic stimulation in refractory depressed patients

    Energy Technology Data Exchange (ETDEWEB)

    Kim, C. H.; Chung, Y. A.; Chae, J. H.; Oh, J. H.; Kim, S. H.; Sohn, H. S.; Chung, S. K. [The Catholic University of Korea, Seoul (Korea, Republic of)

    2005-07-01

    Imaging studies by repetitive transcranial magnetic stimulation (rTMS) demonstrates biological activities of the brain. The aim of this study was to investigate the patterns of regional cerebral blood flow (rCBF) after a series of therapeutic rTMS sessions. Nine patients with refractory depression who had not been responsive to appropriate pharmacotherapy over 1 year were randomly assigned to daily 1 Hz right-sided rTMS or 20 Hz left-sided rTMS sessions for over 3 weeks. Baseline and 3-week post-rTMS treatment SPECT images were obtained 40 minutes after intravenous injection of approximately 740925 MBq of Tc-99m ECD using a multi-detector scanner (ECAM plus; Siemens, Erlangen, Germany) equipped with a low-energy, fan-beam collimator. All patients showed a good clinical outcome. Statistically significant common increase in rCBF patterns was found in the fusiform gyrus of left temporal lobe, left hippocampus, left superior parietal lobule, superior frontal gyrus of right frontal lobe, right lateral globus pallidus and cingulated gyrus of both limbic lobes. And in the fusiform gyrus of left occipital lobe and middle frontal gyrus of right frontal lobe decreased uptake was seen compared to controls. Low-frequency rTMS on the right prefrontal cortex and high-frequency rTMS on the left prefrontal cortex for 3 weeks as an add-on regimen have increased activity in specific brain regions in patients with treatment refractory depression. Therapeutic TMS seems to influence distinct cortical regions, as well as different pathways, affecting rCBF in a homogeneous manner that is probably region dependent and illness related.

  1. Impaired Flow-mediated Dilation Is Associated with Low Pulmonary Function and Emphysema in Ex-smokers

    Science.gov (United States)

    Barr, R. Graham; Mesia-Vela, Sonia; Austin, John H. M.; Basner, Robert C.; Keller, Brad M.; Reeves, Anthony P.; Shimbo, Daichi; Stevenson, Lori

    2007-01-01

    Rationale: Basic science research suggests a causal role for endothelial dysfunction in chronic obstructive pulmonary disease (COPD). Clinical studies examining endothelial function are lacking, particularly early in the disease. Flow-mediated dilation (FMD) is a physiologic measure of endothelial reactivity to endogenous nitric oxide. Objectives: We hypothesized that lower FMD among former smokers would be associated with lower post-bronchodilator FEV1, higher percentage of emphysema using computed tomography (CT) and lower diffusing capacity. Methods: We measured FMD, pulmonary function, and CT percentage of emphysema in a random sample of 107 cotinine-confirmed former smokers in the ongoing EMCAP study. FMD was defined as percentage change in the brachial artery diameter with reactive hyperemia. Generalized additive models were used to adjust for potential confounders and assess linearity. Measurements and Main Results: Mean age of participants was 71 ± 5 years, 46% were female, and pack-years averaged 48 ± 26. Mean FMD was 3.8 ± 3.1%; mean post-bronchodilator FEV1, 2.3 ± 0.8 L; and mean CT percentage of emphysema, 26 ± 10%. A 1 SD decrease in FMD was associated with a 132-ml (95% confidence interval, 16–248 ml; P = 0.03) decrement in post-bronchodilator FEV1 and a 2.6% (95% confidence interval, 0.5–4.7%; P = 0.02) increase in CT percentage of emphysema in fully adjusted models. These associations were linear across the spectrum from normality to disease, independent of smoking history, and also significant among participants without COPD. Associations with diffusing capacity were consistent but nonsignificant (P = 0.09). The FMD–FEV1 association was entirely attributable to percentage of emphysema. Conclusions: Impaired endothelial function, as measured by FMD, was associated with lower FEV1 and higher CT percentage of emphysema in former smokers early in COPD. PMID:17761614

  2. RG Flows and Bifurcations

    CERN Document Server

    Gukov, Sergei

    2016-01-01

    Interpreting RG flows as dynamical systems in the space of couplings we produce a variety of constraints, global (topological) as well as local. These constraints, in turn, rule out some of the proposed RG flows and also predict new phases and fixed points, surprisingly, even in familiar theories such as O(N) model, QED-3, or QCD-4.

  3. Association between uterine artery Doppler blood flow changes and arterial wall elasticity in pregnant women.

    Science.gov (United States)

    von Wowern, Emma; Andersson, Jakob; Skarping, Ida Dalene; Howie, Maria Teresa; Olofsson, Per

    2017-10-01

    Uterine artery (UtA) Doppler velocimetry changes and increased arterial stiffness are associated with preeclampsia. We aimed to investigate the relation between UtA velocimetry changes and arterial stiffness in pregnant women. Doppler velocimetry and photoplethysmographic digital pulse wave analysis (DPA) were performed in 173 pregnant women in the second or the third trimester, where UtA Doppler pulsatility index (PI), diastolic notching, and UtA score (UAS) combining notching and high PI were calculated. DPA stiffness parameters representing large arteries were ejection elasticity index (EEI) and b/a, small arteries dicrotic index (DI) and d/a, and global stiffness the aging index (AI). One hundred and thirty women had normal Doppler and 43 had diastolic notching, of whom nine had high PI. DI indicated increased stiffness in small arteries when notching was present (p = 0.044) and showed a significant but weak correlation to UAS (p = 0.025, tau 0.12). EEI and b/a indicated increased large artery stiffness (p ≤0.014), d/a small artery stiffness (p = 0.023), and AI a systemic stiffness (p = 0.040) when high PI. High UtA PI was associated with increased systemic arterial stiffness, whereas notching was related to increased stiffness in small arteries only. This indicates pathophysiological differences between the two Doppler parameters.

  4. Biological mechanisms associated with triazophos (TAP) removal by horizontal subsurface flow constructed wetlands (HSFCW)

    Energy Technology Data Exchange (ETDEWEB)

    Wu, Juan; Feng, Yuqin; Dai, Yanran; Cui, Naxin [State Key Laboratory of Pollution Control and ResourceReuse, College of Environmental Science and Engineering, Tongji University, Shanghai 200092 (China); Anderson, Bruce [Department of Civil Engineering, Queen' s University, Kingston K7L3N6 (Canada); Cheng, Shuiping, E-mail: shpcheng@tongji.edu.cn [State Key Laboratory of Pollution Control and ResourceReuse, College of Environmental Science and Engineering, Tongji University, Shanghai 200092 (China)

    2016-05-15

    Triazophos (TAP) is a widely used pesticide that is easily accumulated in the environment due to its relatively high stability: this accumulation from agricultural runoff results in potential hazards to aquatic ecosystems. Constructed wetlands are generally considered to be an effective technology for treating TAP polluted surface water. However, knowledge about the biological mechanisms of TAP removal is still lacking. This study investigates the responses of a wetland plant (Canna indica), substrate enzymes and microbial communities in bench-scale horizontal subsurface-flow constructed wetlands (HSCWs) loaded with different TAP concentrations (0, 0.1, 0.5 and 5 mg·L{sup −1}). The results indicate that TAP stimulated the activities of superoxide dismutase (SOD) and peroxidase (POD) in the roots of C. indica. The highest TAP concentrations significantly inhibited photosynthetic activities, as shown by a reduced effective quantum yield of PS II (Φ{sub PSII}) and lower electron transport rates (ETR). However, interestingly, the lower TAP loadings exhibited some favorable effects on these two variables, suggesting that C. indica is a suitable species for use in wetlands designed for treatment of low TAP concentrations. Urease and alkaline phosphatase (ALP) in the wetland substrate were activated by TAP. Two-way ANOVA demonstrated that urease activity was influenced by both the TAP concentrations and season, while acidphosphatase (ACP) only responded to seasonal variations. Analysis of high throughput sequencing of 16S rRNA revealed seasonal variations in the microbial community structure of the wetland substrate at the phylum and family levels. In addition, urease activity had a greater correlation with the relative abundance of some functional microbial groups, such as the Bacillaceae family, and the ALP and ACP may be influenced by the plant more than substrate microbial communities. - Highlights: • Physiological responses of the wetland plant to triazophos

  5. 弱关联规则下的联合数据库入侵检测方法研究%Research of Federated Database Intrusion Detection Methods Based on Weak Association Rules

    Institute of Scientific and Technical Information of China (English)

    王世运

    2015-01-01

    Invasion of different joint database intrusion and ordinary, no significant behavioral characteristics of the intrusion data attributes are different, it is difficult to form a unified constraint specification, lead to the traditional intrusion detection methods, due to the intrusion detection by extract intrusion behavior characteristics, unable to effectively and accurately complete federated database intrusion detection, proposes a weak association rules under the joint database intrusion detection method, through the weak correlation patterns in the federated database support and joint database records of the total than the support of weak correlation patterns, frequent weak correlation patterns were obtained, with the improved algorithm of double degree of confidence the confidence level of frequent weak correlation patterns set calculation, get weak association rules, on the basis of weak association rules, using the original database to the classification hyperplane calculated, using the overall classification hyperplane complete joint database, USES the principal components analysis method for joint operations in the database data dimension reduction processing, through different classification method, classified characteristics of joint operation data in the database operation, implement united under weak association rule database intrusion detection effectively. Experiments show that the proposed method has high accuracy and effectiveness.%联合数据库的入侵和普通入侵不同,其无显著的行为特征,入侵数据属性差异较大,很难形成统一的约束规范,导致传统的入侵检测方法,由于通过提取入侵行为特征进行入侵检测,无法有效且准确地完成联合数据库的入侵检测,提出一种弱关联规则下的联合数据库入侵检测方法,通过弱关联模式在联合数据库中支持程度与联合数据库记录总量的比求出弱关联模式的支持度,获取频繁弱关联模

  6. 基于文化免疫克隆算法的关联规则挖掘研究%Mining association rules based on cultured immune clone algorithm

    Institute of Scientific and Technical Information of China (English)

    杨光军

    2013-01-01

      针对关联规则挖掘问题,给出一种基于文化免疫克隆算法的关联规则挖掘方法,该方法将免疫克隆算法嵌入到文化算法的框架中,采用双层进化机制,利用免疫克隆算法的智能搜索能力和文化算法信念空间形成的公共认知信念的引导挖掘规则。该方法重新给出了文化算法中状况知识和历史知识的描述,设计了一种变异算子,能够自适应调节变异尺度,提高免疫克隆算法全局搜索能力。实验表明,该算法的运行速度和所得关联规则的准确率优于免疫克隆算法。%For the association rules mining, a method of mining association rules based on cultured immune clone algorithm is proposed. This method uses two-layer evolutionary mechanism and embeds the immune clone algorithm in the culture algorithm framework. It uses the intelligent searching ability of the immune clone algorithm and the commonly accepted knowledge in the culture algorithm to guide the rules mining. The situational knowledge and history knowledge in the culture algorithm are rede-fined, and a new mutation operator is put forward. This operator has the adaptive adjustment of mutation measure to improve the global search ability of immune clone algorithm. The experiments show that the new algorithm is superior to immune clone algo-rithm in performance speed and the rules’accuracy.

  7. Domain-oriented evaluation method of association rules and its application%面向领域的关联规则评价方法及其应用

    Institute of Scientific and Technical Information of China (English)

    陈鹏; 谭励; 于重重

    2011-01-01

    To deal with the problems of evaluation criteria of support-confidence framework in association rule mining, such as being lack of specific applications analysis and hard to use mining results for decision-making, a method for evaluating domain-oriented association rules is proposed. Taking domain knowledge as a basis, the rules that meet the degrees of technical interest and commercial interest are given out. According to 40 healthy residential survey data in the pilot project of national housing engineer center, some experiments and analysis are carried out. Meanwhile, a data mining system for health living domain is constructed. The system is designed by multi-level software architecture with several modules, including knowledge base management, mining data selection, data preprocessing, domain-driven mining and results evaluation. Consequently, performances of the proposed method are demonstrated by experiments and the application system.%针对关联规则挖掘中,基于支持度-置信度框架的关联规则评价标准存在缺乏具体应用领域的分析,挖掘结果很难用于用户决策等问题,提出一种面向领域关联规则评价方法.该方法以领域知识为基准,发现满足技术兴趣度和商业兴趣度的规则,以国家住宅工程中心40个健康住宅试点项目的实际调查数据为例,进行试验和分析.在此基础上,设计并开发了居住健康领域挖掘系统,该系统采用多层次软件架构,包括知识库管理、挖掘数据选择、数据预处理、领域挖掘和结果评价等功能.实验结果和系统应用结果表明了面向领域关联规则评价方法的有效性.

  8. 基于Apriori关联规则的汽轮机振动监测与故障诊断%Steam Turbine Vibration Based on the Apriori Association Rules Monitoring and Fault Diagnosis

    Institute of Scientific and Technical Information of China (English)

    刘淑艳

    2012-01-01

    In the power plant steam turbine vibration fault depends only on the vibration parameters of fault diagnosis and diagnostic time is long and the diagnosis of the cause and site specific features, is proposed based on the association rules of steam turbine vibration monitoring and fault diagnosis method. Analysis of the steam turbine vibration fault related to vibration parameters and thermal parameters, on the thermodynamic parameters and vibration parameters associated with the fault diagnosis rules, established the running status monitoring and fault diagnosis system design. Through the actual test proved that this method has very strong practical and feasible, for thermal power plant steam turbine vibration fault of equipment research and development and improvement have draw lessons from a meaning.%针对火电厂汽轮机发生振动故障时仅依靠振动参数进行故障诊断而产生诊断时间长与诊断的原因与部位不具体的问题,提出了基于关联规则的汽轮机振动监测与故障诊断方法;分析了汽轮机振动故障产生时涉及到的振动参数与热力参数,研究了将热力参数与振动参数关联结合的故障诊断规则,确立了状态运行监测与故障诊断的系统设计思路;通过实际验证证明这种方法具有很强的实用型与可行性,对火电厂汽轮机振动故障设备的研发与改进有借鉴意义.

  9. 基于公理化模糊集语义图像层次关联规则分类器%Semantic image classifier based on hierarchical association rule with axiomatic fuzzy set

    Institute of Scientific and Technical Information of China (English)

    韦容; 申希兵; 杨毅

    2016-01-01

    In order to improve the performance of semantic image classification, the semantic image classifier based on hierarchical association rule with axiomatic fuzzy set is proposed. Firstly, in order to improve the accuracy of the algorithm, the image data set for feature extraction is constructed based on the axiomatic theory(AFS)to realize AFS image sets fuzzy concept expression, which improves the image set attribute recognition. Secondly, in order to improve the computa-tional efficiency of the algorithm, the hierarchical structure association rules are considered, and it constructs the semantic image classifier, which uses the ontology information to improve the ability of parallel classification. Finally, through the comparison of the algorithm parameters and the horizontal contrast, the results show that the proposed algorithm has high accuracy and computational efficiency.%为提高语义图像分类器性能,提出一种基于公理化模糊集的语义图像层次关联规则分类器。首先,为提高算法精度,在对图像数据集进行特征提取基础上,采用公理化理论(AFS)构建图像集模糊概念的AFS属性表达,提高图像集属性辨识度;其次,为提高算法计算效率,考虑采用层次结构关联规则,构建语义图像分类器,利用概念之间的本体信息,提高并行分类能力;最后,通过对算法参数及横向对比实验,显示所提算法具有较高的计算精度和计算效率。

  10. Quantification of coronary flow reserve in patients with ischaemic and non-ischaemic cardiomyopathy and its association with clinical outcomes

    Science.gov (United States)

    Majmudar, Maulik D.; Murthy, Venkatesh L.; Shah, Ravi V.; Kolli, Swathy; Mousavi, Negareh; Foster, Courtney R.; Hainer, Jon; Blankstein, Ron; Dorbala, Sharmila; Sitek, Arkadiusz; Stevenson, Lynne W.; Mehra, Mandeep R.; Di Carli, Marcelo F.

    2015-01-01

    Aims Patients with left ventricular systolic dysfunction frequently show abnormal coronary vascular function, even in the absence of overt coronary artery disease. Moreover, the severity of vascular dysfunction might be related to the aetiology of cardiomyopathy. We sought to determine the incremental value of assessing coronary vascular dysfunction among patients with ischaemic (ICM) and non-ischaemic (NICM) cardiomyopathy at risk for adverse cardiovascular outcomes. Methods and results Coronary flow reserve (CFR, stress/rest myocardial blood flow) was quantified in 510 consecutive patients with rest left ventricular ejection fraction (LVEF) ≤45% referred for rest/stress myocardial perfusion PET imaging. The primary end point was a composite of major adverse cardiovascular events (MACE) including cardiac death, heart failure hospitalization, late revascularization, and aborted sudden cardiac death. Median follow-up was 8.2 months. Cox proportional hazards model was used to adjust for clinical variables. The annualized MACE rate was 26.3%. Patients in the lowest two tertiles of CFR (CFR ≤ 1.65) experienced higher MACE rates than those in the highest tertile (32.6 vs. 15.5% per year, respectively, P = 0.004), irrespective of aetiology of cardiomyopathy. Conclusion Impaired coronary vascular function, as assessed by reduced CFR by PET imaging, is common in patients with both ischaemic and non-ischaemic cardiomyopathy and is associated with MACE. PMID:25719181

  11. A cohort study of Plasmodium falciparum malaria in pregnancy and associations with uteroplacental blood flow and fetal anthropometrics in Kenya.

    Science.gov (United States)

    McClure, Elizabeth M; Meshnick, Steven R; Lazebnik, Noam; Mungai, Peter; King, Christopher L; Hudgens, Michael; Goldenberg, Robert L; Siega-Riz, Anna-Maria; Dent, Arlene E

    2014-07-01

    To use ultrasound to explore the impact of malaria in pregnancy on fetal growth and newborn outcomes among a cohort of women enrolled in an intermittent presumptive treatment in pregnancy (IPTp) with sulfadoxine/pyrimethamine (SP) program in coastal Kenya. Enrolled women were tested for malaria at first prenatal care visit, and physical and ultrasound examinations were performed. In total, 477 women who had term, live births had malaria tested at delivery and their birth outcomes assessed, and were included in the study. Peripheral malaria was detected via polymerase chain reaction among 10.9% (n=87) at first prenatal care visit and 8.8% (n=36) at delivery. Insecticide-treated bed nets (ITNs) were used by 73.6% (n=583) and were associated with decreased malaria risk. There was a trend for impaired fetal growth and placental blood flow in malaria-infected women in the second trimester, but not later in pregnancy. Among women with low body mass index (BMI), malaria was associated with reduced birth weight (P=0.04); anthropometric measures were similar otherwise. With IPTp-SP and ITNs, malaria in pregnancy was associated with transient differences in utero, and reduced birth weight was restricted to those with low BMI. Copyright © 2014 International Federation of Gynecology and Obstetrics. Published by Elsevier Ireland Ltd. All rights reserved.

  12. Endothelial function and sleep: associations of flow-mediated dilation with perceived sleep quality and rapid eye movement (REM) sleep.

    Science.gov (United States)

    Cooper, Denise C; Ziegler, Michael G; Milic, Milos S; Ancoli-Israel, Sonia; Mills, Paul J; Loredo, José S; Von Känel, Roland; Dimsdale, Joel E

    2014-02-01

    Endothelial function typically precedes clinical manifestations of cardiovascular disease and provides a potential mechanism for the associations observed between cardiovascular disease and sleep quality. This study examined how subjective and objective indicators of sleep quality relate to endothelial function, as measured by brachial artery flow-mediated dilation (FMD). In a clinical research centre, 100 non-shift working adults (mean age: 36 years) completed FMD testing and the Pittsburgh Sleep Quality Index, along with a polysomnography assessment to obtain the following measures: slow wave sleep, percentage rapid eye movement (REM) sleep, REM sleep latency, total arousal index, total sleep time, wake after sleep onset, sleep efficiency and apnea-hypopnea index. Bivariate correlations and follow-up multiple regressions examined how FMD related to subjective (i.e., Pittsburgh Sleep Quality Index scores) and objective (i.e., polysomnography-derived) indicators of sleep quality. After FMD showed bivariate correlations with Pittsburgh Sleep Quality Index scores, percentage REM sleep and REM latency, further examination with separate regression models indicated that these associations remained significant after adjustments for sex, age, race, hypertension, body mass index, apnea-hypopnea index, smoking and income (Ps Quality Index increased (indicating decreased subjective sleep quality) and percentage REM sleep decreased, while REM sleep latency increased (Ps quality and adverse changes in REM sleep were associated with diminished vasodilation, which could link sleep disturbances to cardiovascular disease.

  13. Enhanced long-term organics and nitrogen removal and associated microbial community in intermittently aerated subsurface flow constructed wetlands.

    Science.gov (United States)

    Fan, Jinlin; Zhang, Jian; Guo, Wenshan; Liang, Shuang; Wu, Haiming

    2016-08-01

    The long-term enhanced removal efficiency of organics and nitrogen in subsurface flow constructed wetlands (SSF CWs) with and without intermittent aeration for decentralized domestic wastewater was evaluated, and the function of intermittent aeration on microbial community was also investigated in this study. The high and long-term 95.6% COD, 96.1% NH4(+)-N and 85.8% TN removal efficiencies were achieved in experimental intermittently aerated SSF CW compared with non-aerated SSF CW. Aerated SSF CWs also exhibited the excellent removal performance when comparatively comparing with other strategies and techniques applied in CWs. In addition, fluorescence in situ hybridization (FISH) analysis revealed that associated microbial abundance significantly increased owing to intermittent aeration. These results indicated intermittent aeration CWs might be an effective and sustainable strategy for wastewater treatment in rural areas, but require further full-scale investigation in future.

  14. Macrophyte decomposition in a surface-flow ammonia-dominated constructed wetland: Rates associated with environmental and biotic variables

    Science.gov (United States)

    Thullen, J.S.; Nelson, S.M.; Cade, B.S.; Sartoris, J.J.

    2008-01-01

    Decomposition of senesced culm material of two bulrush species was studied in a surface-flow ammonia-dominated treatment wetland in southern California. Decomposition of the submerged culm material during summer months was relatively rapid (k = 0.037 day-1), but slowed under extended submergence (up to 245 days) and during fall and spring sampling periods (k = 0.009-0.014 day-1). Stepwise regression of seasonal data indicated that final water temperature and abundance of the culm-mining midge, Glyptotendipes, were significantly associated with culm decomposition. Glyptotendipes abundance, in turn, was correlated with water quality parameters such as conductivity and dissolved oxygen and ammonia concentrations. No differences were detected in decomposition rates between the bulrush species, Schoenoplectus californicus and Schoenoplectus acutus.

  15. Human Dignity and the Rule of Law

    Directory of Open Access Journals (Sweden)

    Stephen Riley

    2015-07-01

    Full Text Available The rule of law denotes an expectation of non-arbitrary governance.  It also invokes law’s distinctive characteristics: formality, institutional independence, and authority.  Taken together with a basic conception of the person, the rule of law can be treated as ‘good governance consistent with human rationality or agency’ and is often associated with human dignity.  On the view defended here human dignity in conjunction with the rule of law makes additional, specific, demands on legal systems, namely the reconciliation of the ‘normative holism’ of law (its regulatory reach with permissive, ‘anthropological’, demands.  This line of enquiry provides us with both a distinctive understanding of human dignity and an understanding of law that is normative but still closely related to the formal virtues implied by the rule of law.

  16. Decision Analysis of Dynamic Spectrum Access Rules

    Energy Technology Data Exchange (ETDEWEB)

    Juan D. Deaton; Luiz A. DaSilva; Christian Wernz

    2011-12-01

    A current trend in spectrum regulation is to incorporate spectrum sharing through the design of spectrum access rules that support Dynamic Spectrum Access (DSA). This paper develops a decision-theoretic framework for regulators to assess the impacts of different decision rules on both primary and secondary operators. We analyze access rules based on sensing and exclusion areas, which in practice can be enforced through geolocation databases. Our results show that receiver-only sensing provides insufficient protection for primary and co-existing secondary users and overall low social welfare. On the other hand, using sensing information between the transmitter and receiver of a communication link, provides dramatic increases in system performance. The performance of using these link end points is relatively close to that of using many cooperative sensing nodes associated to the same access point and large link exclusion areas. These results are useful to regulators and network developers in understanding in developing rules for future DSA regulation.

  17. Different Bleeding Patterns with the Use of Levonorgestrel Intrauterine System: Are They Associated with Changes in Uterine Artery Blood Flow?

    Directory of Open Access Journals (Sweden)

    Carlo Bastianelli

    2014-01-01

    Full Text Available Objective. Evaluate if different bleeding patterns associated with the use of the levonorgestrel intrauterine system (LNG-IUS are associated with different uterine and endometrial vascularization patterns, as evidenced by ultrasound power Doppler analysis. Methodology. A longitudinal study, with each subject acting as its own control was conducted between January 2010 and December 2012. Healthy volunteers with a history of heavy but cyclic and regular menstrual cycles were enrolled in the study. Ultrasonographic examination was performed before and after six months of LNG-IUS placement: uterine volume, endometrial thickness, and subendometrial and myometrial Doppler blood flow patterns have been evaluated. Results. A total of 32 women were enrolled out of 186 initially screened. At six months of follow-up, all subjects showed a reduction in menstrual blood loss; for analysis, they were retrospectively divided into 3 groups: normal cycling women (Group I, amenorrheic women (Group II, and women with prolonged bleedings (Group III. Intergroup analysis documented a statistically significant difference in endometrial thickness among the three groups; in addition, mean pulsatility index (PI and resistance index (RI in the spiral arteries were significantly lower in Group I and Group III compared to Group II. This difference persisted also when comparing—within subjects of Group III—mean PI and RI mean values before and after insertion. Conclusions. The LNG-IUS not only altered endometrial thickness, but—in women with prolonged bleedings—also significantly changed uterine artery blood flow. Further studies are needed to confirm these results and enable gynecologists to properly counsel women, improving initial continuation rates.

  18. Blood flow velocity and thickness of the choroid in a patient with chorioretinopathy associated with ocular blunt trauma.

    Science.gov (United States)

    Ishikawa, Yuri; Hashimoto, Yuki; Saito, Wataru; Ando, Ryo; Ishida, Susumu

    2017-06-08

    Choroidal circulation hemodynamics in eyes with ocular blunt trauma has not been quantitatively examined yet. We quantitatively examined changes in choroidal blood flow velocity and thickness at the lesion site using laser speckle flowgraphy (LSFG) and enhanced depth imaging optical coherence tomography (EDI-OCT) in a patient with chorioretinopathy associated with ocular blunt trauma. A 13-year-old boy developed a chorioretinal lesion with pigmentation extending from the optic disc to the superotemporal side in the right eye after ocular blunt trauma. The patient's best-corrected visual acuity (BCVA) was 0.2 in the right eye. Indocyanine green angiography showed hypofluorescence from the initial phase, with a decrease of mean blur rate (MBR) on LSFG color map, which corresponded to the chorioretinal lesion. The BCVA and foveal outer retinal morphologic abnormality spontaneously improved during follow-up. MBR and choroidal thickness increased by 23-31% and 13-17 μm at the lesion site and by 11-22% and 33-42 μm at the fovea, respectively, during the 6-month follow-up period after baseline measurements in the affected eye. In contrast, these parameters showed little or no changes at the normal retinal site in the affected eye and the fovea in the fellow eye. Current data revealed that both blood flow velocity and thickness in the choroid at the lesion site decreased in the acute stage and subsequently increased together with improvements in visual function and outer retinal morphology. These results suggest that LSFG and EDI-OCT may be useful indices that can noninvasively evaluate activity of choroidal involvement in ocular blunt trauma-associated chorioretinopathy.

  19. Associations between flow in paratibial perforating veins and great saphenous vein patterns of reflux

    Directory of Open Access Journals (Sweden)

    Carlos Alberto Engelhorn

    2015-06-01

    Full Text Available Perforating veins contribute to chronic venous valvular insufficiency (CVVI, subset of CVI of lower extremities (LE. We investigated the role of medial, proximal calf paratibial perforating veins (PTPV. Women with PTPV reflux, diameter ≥3 mm, or tortuosity were selected among 2199 LE mappings. Duplex ultrasonography (US was performed standing. Reflux >0.5 s was abnormal. PTPV conditions were related to great saphenous vein (GSV patterns of reflux. US of 442 LE of 379 women were analyzed, all being Clinical-Etiology-Anatomy-Pathophysiology (CEAP classification C1, C2, and/or having intermittent, conditional swelling. Etiology was primary. Pathophysiology was reflux, not thrombosis or obstruction. Most PTPV drained (n=281, 64% of 442 or 13% of 2199, or were source (n=73, 17%/442, 3%/2199 of GSV reflux; 49 (11%/442, 2%/2199 had reflux not associated with GSV; 39 (9%/442, 2%/2199 did not have reflux. PTPV, when significative for CVVI, primarily drained-GSV reflux. PTPV was linked to reflux in 1 of 5 and was a major source of reflux in 1 of 20 legs. Detailed US of PTPV insured over 80% accuracy in CVVI mapping.

  20. Novice Rules for Projectile Motion.

    Science.gov (United States)

    Maloney, David P.

    1988-01-01

    Investigates several aspects of undergraduate students' rules for projectile motion including general patterns; rules for questions about time, distance, solids and liquids; and changes in rules when asked to ignore air resistance. Reports approach differences by sex and high school physics experience, and that novice rules are situation…

  1. The role of traffic rules.

    NARCIS (Netherlands)

    Noordzij, P.C.

    1988-01-01

    Experienced road users seem to have their own set of traffic rules (including rules about when to violate the official rules). The number of violations is enormous, causing great concern for the authorities. The situation could be improved by separating a set of rules with the aim of deterring road

  2. Nature and Function of Rules.

    Science.gov (United States)

    Fields, Barry A.

    1997-01-01

    Surveyed Year 1 and 2 teachers in Australia about their classroom rules. Found that teachers have about six rules for their classes relating to pupil-pupil relations, completing academic tasks, movement around the classroom, property, safety, and other. Most rules concerned pupil-pupil interactions, and all rules can be seen as a way of…

  3. Numerical investigations of the fluid flows at deep oceanic and arctic permafrost-associated gas hydrate deposits

    Science.gov (United States)

    Frederick, Jennifer Mary

    older than the host sediment. Old pore fluid age may reflect complex flow patterns, such a fluid focusing, which can cause significant lateral migration as well as regions where downward flow reverses direction and returns toward the seafloor. Longer pathlines can produce pore fluid ages much older than that expected with a one-dimensional compaction model. For steady-state models with geometry representative of Blake Ridge (USA), a well-studied hydrate province, pore fluid ages beneath regions of topography and within fractured zones can be up to 70 Ma old. Results suggest that the measurements of 129-I/127-I reflect a mixture of new and old pore fluid. However, old pore fluid need not originate at great depths. Methane within pore fluids can travel laterally several kilometers, implying an extensive source region around the deposit. Iodine age measurements support the existence of fluid focusing beneath regions of seafloor topography at Blake Ridge, and suggest that the methane source at Blake Ridge is likely shallow. The response of methane hydrate reservoirs to warming is poorly understood. The great depths may protect deep oceanic hydrates from climate change for the time being because transfer of heat by conduction is slow, but warming will eventually be felt albeit in the far future. On the other hand, unique permafrost-associated methane hydrate deposits exist at shallow depths within the sediments of the circum-Arctic continental shelves. Arctic hydrates are thought to be a relict of cold glacial periods, aggrading when sea levels are much lower and shelf sediments are exposed to freezing air temperatures. During interglacial periods, rising sea levels flood the shelf, bringing dramatic warming to the permafrost- and hydrate-bearing sediments. Permafrost-associated methane hydrate deposits have been responding to warming since the last glacial maximum ~18 kaBP as a consequence of these natural glacial cycles. This `experiment,' set into motion by nature itself

  4. Increasing Lower Extremity Injury Rates Across the 2009-2010 to 2014-2015 Seasons of National Collegiate Athletic Association Football: An Unintended Consequence of the "Targeting" Rule Used to Prevent Concussions?

    Science.gov (United States)

    Westermann, Robert W; Kerr, Zachary Y; Wehr, Peter; Amendola, Annuziato

    2016-12-01

    Sports-related concussions (SRCs) have gained increased societal interest in the past decade. The National Collegiate Athletic Association (NCAA) has implemented legislation and rule changes to decrease the incidence and risk of head injury impacts. The "targeting" rule forbids initiating contact with the crown of a helmet and targeting defenseless players in the head and neck area; however, there are concerns that this rule change has unintentionally led to an increased incidence of lower extremity injuries. The purpose of this study was to evaluate the change in lower extremity injury rates in NCAA football during the 2009-2010 to 2014-2015 seasons. We hypothesized that the lower extremity injury rate has increased across the time period. Descriptive epidemiology study. Sixty-eight NCAA football programs provided 153 team-seasons of data to the NCAA Injury Surveillance Program. Lower extremity injuries (ie, hip/groin, upper leg/thigh, knee, lower leg/Achilles, foot/toes) and SRCs sustained during NCAA football games were examined. We calculated injury rates per 1000 athlete-exposures (AEs) for lower extremity injuries and SRCs. Rate ratios (RRs) compared injury rates between the 2009-2010 to 2011-2012 and 2012-2013 to 2014-2015 seasons. Overall, 2400 lower extremity injuries were reported during the 2009-2010 to 2014-2015 seasons; most were to the knee (33.6%) and ankle (28.5%) and caused by player contact (59.2%). The lower extremity injury rate increased in 2012-2013 to 2014-2015 compared with 2009-2010 to 2011-2012 (23.55 vs 20.45/1000 AEs, respectively; RR, 1.15; 95% CI, 1.06-1.25). This finding was retained when restricted to injuries due to player contact (RR, 1.19; 95% CI, 1.07-1.32) but not for injuries due to noncontact/overuse (RR, 0.96; 95% CI, 0.80-1.14). When examining player contact injury rates by anatomic site, only ankle injuries had an increase (RR, 1.36; 95% CI, 1.13-1.64). The SRC rate also increased in 2012-2013 to 2014-2015 compared with

  5. 关联度最强药物配伍的中医止呕类方数据挖掘%Rule of Remedy for Vomiting in Science of Traditional Chinese Medicine Formu as by Data Mining Based on Both Association and Correlation Rule

    Institute of Scientific and Technical Information of China (English)

    黄颖琦; 贾恒; 何前松; 冯泳

    2012-01-01

    Objective: To look for the rules of compatibility of medicines in historical prescriptions which treat vomiting, mining out new knowledge in science of traditional Chinese medicine ( TCM ) formulas, providing support for making new TCM remedy for vomiting. Method: Created a TCM formulas database to treat vomiting by collecting 985 TCM formulas. A threshold level datamining method which based on both association and correlation rule is used, to mining rule of compatibility of medicines in database of historical prescriptions for vomiting. Result; The most used drug is Zingiber officinale, the using frequency of Z. officinale is 61.23%. The most association and correlation couple of drugs are Poria cocos ( Schw. ) Wolf and Pinellia ternate ( Thunb. ) Breit. the correlation - confidence of this couple is 0. 114 4. The most association and correlation group of drugs are Z. officinale and P. cocos and P. ternate, the correlation-confidence of this group is 0. 295 4, Conclusion; The group of drugs which contain Z. officinale. and P. ternate and P. cocos is most used to treat vomiting. The ternate added in the P. cocos soup, which is ancient famous TCM formulas created by ancient great doctor ZHANG Zhong-jing, is proved that it is the key compatibility of drugs to treat vomiting.%目的:在古今中医文献中寻找止呕方剂配伍规律与用药特点,为中药止呕新药的开发提供理论支持.方法:收录古今止呕类方剂985首建立止呕类方剂数据库,运用相关置信度规则,对中医止呕方剂药物配伍的数据进行挖掘,利用剪枝方法筛选关联度最强的数据.结果:最常用的单味药物为生姜使用频率高达61.23%.关联性最强的核心药对是茯苓配伍姜半夏,其相关置信度为0.1144.关联度最强的药组为生姜、姜半夏、茯苓.结论:生姜、姜半夏、茯苓,其相关置信度为0.2954是中医止呕方剂中最常合用的药物配伍,其3种药物间存在极强的关联性,张仲景创制

  6. Amendments to the Staff Rules and Regulations

    CERN Multimedia

    HR Department

    2006-01-01

    The Staff Rules and Regulations in force since 1 January 1996 are modified as follows as from 1 July 2006: The modifications are listed below: Financial and social conditions for Paid Associates, Fellows and Students (introduction of a new payment scheme for the Paid Scientific Associates Programme - reorganization of the Fellowship Programme - modification of the Student subsistence rates) Protection of members of the personnel against the financial consequences of illness, accident and disability (clarification of the scope of the relevant provisions - new definition of disability and associated benefits - revised role of the Joint Advisory Rehabilitation and Disability Board - bringing together the relevant provisions). Copies of this update (modification# 16) are available in departmental secretariats. In addition, Staff Rules and Regulations are available for consultation on the Web at the following address: http://cern.ch/hr-div/internal/admin_services/rules/default.asp Administrative Circular ...

  7. Amendments to the Staff Rules and Regulations

    CERN Multimedia

    HR Department

    2006-01-01

    The Staff Rules and Regulations in force since 1st January 1996 are modified as follows as of 1st July 2006: Financial and social conditions for Paid Associates, Fellows and Students (introduction of a new payment scheme for the Paid Scientific Associates Programme-reorganisation of the Fellowship Programme-modification of Student subsistence rates) Protection of members of the personnel against the financial consequences of illness, accident and disability (clarification of the scope of the relevant provisions-new definition of disability and associated benefits-revised role of the Joint Advisory Rehabilitation and Disability Board-bringing together of the relevant provisions). Copies of this update (modification No.16) are available from Departmental secretariats. In addition, the Staff Rules and Regulations can be consulted on the Web at the following address: http://cern.ch/hr-div/internal/admin_services/rules/default.asp Administrative Circular No. 14 (Rev. 2)-July 2006 Protection of members o...

  8. The rule of law

    Directory of Open Access Journals (Sweden)

    Besnik Murati

    2015-07-01

    Full Text Available The state as an international entity and its impact on the individual’s right has been and still continues to be a crucial factor in the relationship between private and public persons. States vary in terms of their political system, however, democratic states are based on the separation of powers and human rights within the state. Rule of law is the product of many actors in a state, including laws, individuals, society, political system, separation of powers, human rights, the establishment of civil society, the relationship between law and the individual, as well as, individual-state relations. Purpose and focus of this study is the importance of a functioning state based on law, characteristics of the rule of law, separation of powers and the basic concepts of the rule of law.

  9. Cosmic Sum Rules

    DEFF Research Database (Denmark)

    T. Frandsen, Mads; Masina, Isabella; Sannino, Francesco

    2011-01-01

    We introduce new sum rules allowing to determine universal properties of the unknown component of the cosmic rays and show how it can be used to predict the positron fraction at energies not yet explored by current experiments and to constrain specific models.......We introduce new sum rules allowing to determine universal properties of the unknown component of the cosmic rays and show how it can be used to predict the positron fraction at energies not yet explored by current experiments and to constrain specific models....

  10. Changes in cerebral blood flow and anxiety associated with an 8-week mindfulness programme in women with breast cancer.

    Science.gov (United States)

    Monti, Daniel A; Kash, Kathryn M; Kunkel, Elisabeth J S; Brainard, George; Wintering, Nancy; Moss, Aleezé S; Rao, Hengyi; Zhu, Senhua; Newberg, Andrew B

    2012-12-01

    This study employed functional magnetic resonance imaging to evaluate changes in cerebral blood flow (CBF) associated with the Mindfulness-based Art Therapy (MBAT) programme and correlate such changes to stress and anxiety in women with breast cancer. Eighteen breast cancer patients were randomized to the MBAT or education control group. The patients received the diagnosis of breast cancer between 6 months and 3 years prior to enrollment and were not in active treatment. The age of participants ranged from 52 to 77 years. A voxel-based analysis was performed to assess differences at rest, during meditation and during a stress task. The anxiety sub-scale of the Symptoms Checklist-90-Revised was compared with changes in resting CBF before and after the programmes. Subjects in the MBAT arm demonstrated significant increases in CBF at rest and during meditation in multiple limbic regions, including the left insula, right amygdala, right hippocampus and bilateral caudate. Patients in the MBAT programme also had a significant correlation between increased CBF in the left caudate and decreased anxiety scores. In the MBAT group, responses to a stressful cue resulted in reduced activation of the posterior cingulate. The results demonstrate that the MBAT programme was associated with significant changes in CBF, which correlated with decreased anxiety over an 8-week period.

  11. Association of Monocyte-to-HDL Cholesterol Ratio with Slow Coronary Flow is Linked to Systemic Inflammation.

    Science.gov (United States)

    Canpolat, Ugur; Çetin, Elif Hande; Cetin, Serkan; Aydin, Selahattin; Akboga, Mehmet Kadri; Yayla, Cagri; Turak, Osman; Aras, Dursun; Aydogdu, Sinan

    2016-07-01

    Previous studies proposed that both inflammation, oxidative stress, and impaired endothelial dysfunction have a significant role in occurrence of slow coronary flow (SCF). monocyte-to-high density lipoprotein cholesterol ratio (MHR) is a recently emerged indicator of inflammation and oxidative stress, which have been studied only in patients with chronic kidney disease. We aimed to assess the relationship between MHR and SCF. Patients who had angiographically normal coronary arteries were enrolled in this retrospective study (n = 253 as SCF group and n = 176 as control group). Patients who had corrected thrombolysis in myocardial infarction frame counts (cTFCs) above the normal cutoffs were defined as with SCF. The MHR and high-sensitivity C-reactive protein (hsCRP) were significantly higher in the SCF group. In correlation analysis, MHR has a significantly positive correlation with cTFC and serum hsCRP levels (P MHR was found as independently associated with the presence of SCF (odds ratio: 1.24, P MHR which indicates an enhanced inflammation and oxidative stress was significantly and independently associated with the presence of SCF. Besides, MHR was positively correlated with serum hsCRP level as a conventional marker for systemic inflammation. © The Author(s) 2015.

  12. Association genetics of oleoresin flow in loblolly pine: discovering genes and predicting phenotype for improved resistance to bark beetles and bioenergy potential.

    Science.gov (United States)

    Westbrook, Jared W; Resende, Marcio F R; Munoz, Patricio; Walker, Alejandro R; Wegrzyn, Jill L; Nelson, C Dana; Neale, David B; Kirst, Matias; Huber, Dudley A; Gezan, Salvador A; Peter, Gary F; Davis, John M

    2013-07-01

    Rapidly enhancing oleoresin production in conifer stems through genomic selection and genetic engineering may increase resistance to bark beetles and terpenoid yield for liquid biofuels. We integrated association genetic and genomic prediction analyses of oleoresin flow (g 24 h(-1)) using 4854 single nucleotide polymorphisms (SNPs) in expressed genes within a pedigreed population of loblolly pine (Pinus taeda) that was clonally replicated at three sites in the southeastern United States. Additive genetic variation in oleoresin flow (h(2) ≈ 0.12-0.30) was strongly correlated between years in which precipitation varied (r(a) ≈ 0.95), while the genetic correlation between sites declined from 0.8 to 0.37 with increasing differences in soil and climate among sites. A total of 231 SNPs were significantly associated with oleoresin flow, of which 81% were specific to individual sites. SNPs in sequences similar to ethylene signaling proteins, ABC transporters, and diterpenoid hydroxylases were associated with oleoresin flow across sites. Despite this complex genetic architecture, we developed a genomic prediction model to accelerate breeding for enhanced oleoresin flow that is robust to environmental variation. Results imply that breeding could increase oleoresin flow 1.5- to 2.4-fold in one generation.

  13. The Physical Flow of Materials and the Associated Costs in the Production Process of a Rolling Mill

    Directory of Open Access Journals (Sweden)

    Holisz-Burzyńska, J.

    2007-01-01

    Full Text Available Efficiency of resources use is, in a large extent, determined by the organization of production flow and the way of their control. The optimization of materials flow in the production process requires the identification of physical flows of goods and it cost. In the article the physical flow process of materials stream in the production process in one of Polish rolling mill and also its logistics analysis and cost analysis are presented.

  14. Fluid flow on 3D triangulated fissures: conservative piece-wise constant velocity fields and associated transport processes

    CERN Document Server

    Morales, Fernando A

    2016-01-01

    For a fissured medium with uncertainty in the knowledge of fractures' geometry, a conservative tangential flow field is constructed, which is consistent with the physics of stationary fluid flow in porous media and an interpolated geometry of the cracks. The flow field permits computing preferential fluid flow directions of the medium, rates of mechanical energy dissipations and a stochastic matrix modeling stream lines and fluid mass transportation, for the analysis of solute/contaminant mass advection-diffusion as well as drainage times.

  15. Adler sum rule

    CERN Document Server

    Adler, Stephen L

    2009-01-01

    The Adler sum rule states that the integral over energy of a difference of neutrino-nucleon and antineutrino-nucleon structure functions is a constant, independent of the four-momentum transfer squared. This constancy is a consequence of the local commutation relations of the time components of the hadronic weak current, which follow from the underlying quark structure of the standard model.

  16. TEDXCERN BREAKS THE RULES

    CERN Multimedia

    CERN, Bulletin

    2015-01-01

    On Friday, 9 October, TEDxCERN brought together 14 ‘rule-breakers’ to explore ideas that push beyond the boundaries of academia. They addressed a full house of 600 audience members, as well as thousands watching the event online.

  17. 13 Rules That Expire

    Science.gov (United States)

    Karp, Karen S.; Bush, Sarah B.; Dougherty, Barbara J.

    2014-01-01

    Overgeneralizing commonly accepted strategies, using imprecise vocabulary, and relying on tips and tricks that do not promote conceptual mathematical understanding can lead to misunderstanding later in students' math careers. In this article, the authors present thirteen pervasive mathematics rules that "expire." With the…

  18. Staff rules and regulations

    CERN Document Server

    HR Department

    2007-01-01

    The 11th edition of the Staff Rules and Regulations, dated 1 January 2007, adopted by the Council and the Finance Committee in December 2006, is currently being distributed to departmental secretariats. The Staff Rules and Regulations, together with a summary of the main modifications made, will be available, as from next week, on the Human Resources Department's intranet site: http://cern.ch/hr-web/internal/admin_services/rules/default.asp The main changes made to the Staff Rules and Regulations stem from the five-yearly review of employment conditions of members of the personnel. The changes notably relate to: the categories of members of the personnel (e.g. removal of the local staff category); the careers structure and the merit recognition system; the non-residence, installation and re-installation allowances; the definition of family, family allowances and family-related leave; recognition of partnerships; education fees. The administrative circulars, some of which are being revised following the m...

  19. Post Rule of Law

    DEFF Research Database (Denmark)

    Carlson, Kerstin Bree

    2016-01-01

    addresses the practice of hybridity in ICP, drawing examples from the construction and evolution of hybrid procedure at the International Criminal Tribunal for the Former Yugoslavia (ICTY), to argue that the hybridity practiced by international criminal tribunals renders them ‘post rule of law’ institutions...

  20. Comment concerning Leonardo's rule

    CERN Document Server

    Sotolongo-Costa, O; Oseguera-Manzanilla, T; Díaz-Guerrero, D S

    2016-01-01

    In this comment we propose a novel explanation for the Leonardo's rule concerning the tree branching. According to Leonardo's notebooks he observed that if one observes the branches of a tree, the squared radius of the principal branch is equal to the sum of the squared radius of the branch daughters.