WorldWideScience

Sample records for mining fuzzy association

  1. Using fuzzy association rule mining in cancer classification

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

    2011-01-01

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

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

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

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

    Kaya, Mehmet; Alhajj, Reda

    2005-04-01

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

  4. Sanitizing sensitive association rules using fuzzy correlation scheme

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

    2013-01-01

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

  5. Application of fuzzy mathematics in assessment of mine design bidding

    Zhu Sen

    1988-12-01

    Assessment of mine design bidding is mainly to evaluate the quality of a mine design. The paper established a 3-stage model to assess quality of mine design using fuzzy criterion. A concept of assessment figures was proposed in the analysis of the results. Finally, a mine design was assessed. 2 refs., 2 figs., 1 tab.

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

    Soumadip Ghosh

    2014-11-01

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

  7. Fuzzy associative memories for instrument fault detection

    Heger, A.S.

    1996-01-01

    A fuzzy logic instrument fault detection scheme is developed for systems having two or three redundant sensors. In the fuzzy logic approach the deviation between each signal pairing is computed and classified into three fuzzy sets. A rule base is created allowing the human perception of the situation to be represented mathematically. Fuzzy associative memories are then applied. Finally, a defuzzification scheme is used to find the centroid location, and hence the signal status. Real-time analyses are carried out to evaluate the instantaneous signal status as well as the long-term results for the sensor set. Instantaneous signal validation results are used to compute a best estimate for the measured state variable. The long-term sensor validation method uses a frequency fuzzy variable to determine the signal condition over a specific period. To corroborate the methodology synthetic data representing various anomalies are analyzed with both the fuzzy logic technique and the parity space approach. (Author)

  8. Applying Fuzzy Data Mining to Telecom Churn Management

    Liao, Kuo-Hsiung; Chueh, Hao-En

    Customers tend to change telecommunications service providers in pursuit of more favorable telecommunication rates. Therefore, how to avoid customer churn is an extremely critical topic for the intensely competitive telecommunications industry. To assist telecommunications service providers in effectively reducing the rate of customer churn, this study used fuzzy data mining to determine effective marketing strategies by analyzing the responses of customers to various marketing activities. These techniques can help telecommunications service providers determine the most appropriate marketing opportunities and methods for different customer groups, to reduce effectively the rate of customer turnover.

  9. Fuzzy Comprehensive Evaluation of Ecological Risk Based on Cloud Model: Taking Chengchao Iron Mine as Example

    Ruan, Jinghua; Chen, Yong; Xiao, Xiao; Yong, Gan; Huang, Ranran; Miao, Zuohua

    2018-01-01

    Aimed at the fuzziness and randomness during the evaluation process, this paper constructed a fuzzy comprehensive evaluation method based on cloud model. The evaluation index system was established based on the inherent risk, present level and control situation, which had been proved to be able to convey the main contradictions of ecological risk in mine on the macro level, and be advantageous for comparison among mines. The comment sets and membership functions improved by cloud model could reflect the uniformity of ambiguity and randomness effectively. In addition, the concept of fuzzy entropy was introduced to further characterize the fuzziness of assessments results and the complexities of ecological problems in target mine. A practical example in Chengchao Iron Mine evidenced that, the assessments results can reflect actual situations appropriately and provide a new theoretic guidance for comprehensive ecological risk evaluation of underground iron mine.

  10. Fuzzy linear model for production optimization of mining systems with multiple entities

    Vujic, Slobodan; Benovic, Tomo; Miljanovic, Igor; Hudej, Marjan; Milutinovic, Aleksandar; Pavlovic, Petar

    2011-12-01

    Planning and production optimization within multiple mines or several work sites (entities) mining systems by using fuzzy linear programming (LP) was studied. LP is the most commonly used operations research methods in mining engineering. After the introductory review of properties and limitations of applying LP, short reviews of the general settings of deterministic and fuzzy LP models are presented. With the purpose of comparative analysis, the application of both LP models is presented using the example of the Bauxite Basin Niksic with five mines. After the assessment, LP is an efficient mathematical modeling tool in production planning and solving many other single-criteria optimization problems of mining engineering. After the comparison of advantages and deficiencies of both deterministic and fuzzy LP models, the conclusion presents benefits of the fuzzy LP model but is also stating that seeking the optimal plan of production means to accomplish the overall analysis that will encompass the LP model approaches.

  11. Integration of fuzzy reasoning approach (FRA and fuzzy analytic hierarchy process (FAHP for risk assessment in mining industry

    Shikha Verma

    2014-10-01

    Full Text Available Purpose: Mining industry has always been known for its unsafe working environment. This industry is one of the most hazard prone industries. To maintain safety in workplace timely assessment of risk associated with different operations performed to extract ore from the ore body has become necessity. To serve the said purpose, present work demonstrates a robust hybrid risk assessment approach for mining industry.Design/Methodology: Accident data from 1995 to 2012 is reviewed to identify hazards contributed to negative outcomes. The FRA approach is implemented to evaluate the risk levels associated with identified hazard factors. Thereafter AHP pairwise comparison matrix is developed to obtain priority weights for the hazard factors. Final priority of hazards based on severity of level of risk associated with them is obtained considering the outcome of FRA approach in terms of risk score for the hazards, combined with the priority weights obtained from AHP technique.Findings: Defuzzified FAHP weight of hazard factors, this weight gives priority sequence of hazards to be considered for development of plan of mitigation.Originality/Value: Risk assessment is a requirement of the Occupational Health and Safety Act 2000 (Section 7& 8. The data required to assess the risk is uncertain, and in such case fuzzy approach is well suited to process the data and get the crisp output. The output of fuzzy approach is made robust with its integration to AHP. In this way FAHP can be used as robust technique for risk assessment in this industry and this technique develops an efficient safety management system for the achievement of goal to develop the workplace with zero accident, which many other countries have already achieved.

  12. Fuzzy Modeled K-Cluster Quality Mining of Hidden Knowledge for Decision Support

    S. Parkash  Kumar; K. S. Ramaswami

    2011-01-01

    Problem statement: The work presented Fuzzy Modeled K-means Cluster Quality Mining of hidden knowledge for Decision Support. Based on the number of clusters, number of objects in each cluster and its cohesiveness, precision and recall values, the cluster quality metrics is measured. The fuzzy k-means is adapted approach by using heuristic method which iterates the cluster to form an efficient valid cluster. With the obtained data clusters, quality assessment is made by predictive mining using...

  13. Human health and safety risks management in underground coal mines using fuzzy TOPSIS

    Mahdevari, Satar, E-mail: satar.mahdevari@aut.ac.ir [Department of Mining and Metallurgical Engineering, Amirkabir University of Technology, Tehran (Iran, Islamic Republic of); Shahriar, Kourosh [Department of Mining and Metallurgical Engineering, Amirkabir University of Technology, Tehran (Iran, Islamic Republic of); Esfahanipour, Akbar [Industrial Engineering Department, Amirkabir University of Technology, Tehran (Iran, Islamic Republic of)

    2014-08-01

    The scrutiny of health and safety of personnel working in underground coal mines is heightened because of fatalities and disasters that occur every year worldwide. A methodology based on fuzzy TOPSIS was proposed to assess the risks associated with human health in order to manage control measures and support decision-making, which could provide the right balance between different concerns, such as safety and costs. For this purpose, information collected from three hazardous coal mines namely Hashouni, Hojedk and Babnizu located at the Kerman coal deposit, Iran, were used to manage the risks affecting the health and safety of their miners. Altogether 86 hazards were identified and classified under eight categories: geomechanical, geochemical, electrical, mechanical, chemical, environmental, personal, and social, cultural and managerial risks. Overcoming the uncertainty of qualitative data, the ranking process is accomplished by fuzzy TOPSIS. After running the model, twelve groups with different risks were obtained. Located in the first group, the most important risks with the highest negative effects are: materials falling, catastrophic failure, instability of coalface and immediate roof, firedamp explosion, gas emission, misfire, stopping of ventilation system, wagon separation at inclines, asphyxiation, inadequate training and poor site management system. According to the results, the proposed methodology can be a reliable technique for management of the minatory hazards and coping with uncertainties affecting the health and safety of miners when performance ratings are imprecise. The proposed model can be primarily designed to identify potential hazards and help in taking appropriate measures to minimize or remove the risks before accidents can occur. - Highlights: • Risks associated with health and safety of coal miners were investigated. • A reliable methodology based on Fuzzy TOPSIS was developed to manage the risks. • Three underground mines in Kerman

  14. Human health and safety risks management in underground coal mines using fuzzy TOPSIS

    Mahdevari, Satar; Shahriar, Kourosh; Esfahanipour, Akbar

    2014-01-01

    The scrutiny of health and safety of personnel working in underground coal mines is heightened because of fatalities and disasters that occur every year worldwide. A methodology based on fuzzy TOPSIS was proposed to assess the risks associated with human health in order to manage control measures and support decision-making, which could provide the right balance between different concerns, such as safety and costs. For this purpose, information collected from three hazardous coal mines namely Hashouni, Hojedk and Babnizu located at the Kerman coal deposit, Iran, were used to manage the risks affecting the health and safety of their miners. Altogether 86 hazards were identified and classified under eight categories: geomechanical, geochemical, electrical, mechanical, chemical, environmental, personal, and social, cultural and managerial risks. Overcoming the uncertainty of qualitative data, the ranking process is accomplished by fuzzy TOPSIS. After running the model, twelve groups with different risks were obtained. Located in the first group, the most important risks with the highest negative effects are: materials falling, catastrophic failure, instability of coalface and immediate roof, firedamp explosion, gas emission, misfire, stopping of ventilation system, wagon separation at inclines, asphyxiation, inadequate training and poor site management system. According to the results, the proposed methodology can be a reliable technique for management of the minatory hazards and coping with uncertainties affecting the health and safety of miners when performance ratings are imprecise. The proposed model can be primarily designed to identify potential hazards and help in taking appropriate measures to minimize or remove the risks before accidents can occur. - Highlights: • Risks associated with health and safety of coal miners were investigated. • A reliable methodology based on Fuzzy TOPSIS was developed to manage the risks. • Three underground mines in Kerman

  15. Research on forecast technology of mine gas emission based on fuzzy data mining (FDM)

    Xu Chang-kai; Wang Yao-cai; Wang Jun-wei [CUMT, Xuzhou (China). School of Information and Electrical Engineering

    2004-07-01

    The safe production of coalmine can be further improved by forecasting the quantity of gas emission based on the real-time data and historical data which the gas monitoring system has saved. By making use of the advantages of data warehouse and data mining technology for processing large quantity of redundancy data, the method and its application of forecasting mine gas emission quantity based on FDM were studied. The constructing fuzzy resembling relation and clustering analysis were proposed, which the potential relationship inside the gas emission data may be found. The mode finds model and forecast model were presented, and the detailed approach to realize this forecast was also proposed, which have been applied to forecast the gas emission quantity efficiently.

  16. Hybrid Type II fuzzy system & data mining approach for surface finish

    Tzu-Liang (Bill Tseng

    2015-07-01

    Full Text Available In this study, a new methodology in predicting a system output has been investigated by applying a data mining technique and a hybrid type II fuzzy system in CNC turning operations. The purpose was to generate a supplemental control function under the dynamic machining environment, where unforeseeable changes may occur frequently. Two different types of membership functions were developed for the fuzzy logic systems and also by combining the two types, a hybrid system was generated. Genetic algorithm was used for fuzzy adaptation in the control system. Fuzzy rules are automatically modified in the process of genetic algorithm training. The computational results showed that the hybrid system with a genetic adaptation generated a far better accuracy. The hybrid fuzzy system with genetic algorithm training demonstrated more effective prediction capability and a strong potential for the implementation into existing control functions.

  17. Fuzzy-logic assessment of failure hazard in pipelines due to mining activity

    A. A. Malinowska

    2015-11-01

    Full Text Available The present research is aimed at a critical analysis of a method presently used for evaluating failure hazard in linear objects in mining areas. A fuzzy model of failure hazard of a linear object was created on the basis of the experience gathered so far. The rules of Mamdani fuzzy model have been used in the analyses. Finally the scaled model was integrated with a Geographic Information System (GIS, which was used to evaluate failure hazard in a water pipeline in a mining area.

  18. Fuzzy Clustering: An Approachfor Mining Usage Profilesfrom Web

    Ms.Archana N. Boob; Prof. D. M. Dakhane

    2012-01-01

    Web usage mining is an application of data mining technology to mining the data of the web server log file. It can discover the browsing patterns of user and some kind of correlations between the web pages. Web usage mining provides the support for the web site design, providing personalization server and other business making decision, etc. Web mining applies the data mining, the artificial intelligence and the chart technology and so on to the web data and traces users' visiting characteris...

  19. A Fuzzy-Logic Generalization of a Data Mining Approach

    Holeňa, Martin

    2001-01-01

    Roč. 11, č. 6 (2001), s. 595-610 ISSN 1210-0552. [SOFSEM 2001 Workshop on Soft Computing. Piešťany, 29.11.2001-30.11.2001] R&D Projects: GA AV ČR IAA1030004 Institutional research plan: AV0Z1030915 Keywords : data analysis * vague hypotheses * vague significante level * fuzzy prediacate calculus * basic fuzzy logic * generalized quantifiers * method GUHA Subject RIV: BA - General Mathematics

  20. Multitask TSK fuzzy system modeling by mining intertask common hidden structure.

    Jiang, Yizhang; Chung, Fu-Lai; Ishibuchi, Hisao; Deng, Zhaohong; Wang, Shitong

    2015-03-01

    The classical fuzzy system modeling methods implicitly assume data generated from a single task, which is essentially not in accordance with many practical scenarios where data can be acquired from the perspective of multiple tasks. Although one can build an individual fuzzy system model for each task, the result indeed tells us that the individual modeling approach will get poor generalization ability due to ignoring the intertask hidden correlation. In order to circumvent this shortcoming, we consider a general framework for preserving the independent information among different tasks and mining hidden correlation information among all tasks in multitask fuzzy modeling. In this framework, a low-dimensional subspace (structure) is assumed to be shared among all tasks and hence be the hidden correlation information among all tasks. Under this framework, a multitask Takagi-Sugeno-Kang (TSK) fuzzy system model called MTCS-TSK-FS (TSK-FS for multiple tasks with common hidden structure), based on the classical L2-norm TSK fuzzy system, is proposed in this paper. The proposed model can not only take advantage of independent sample information from the original space for each task, but also effectively use the intertask common hidden structure among multiple tasks to enhance the generalization performance of the built fuzzy systems. Experiments on synthetic and real-world datasets demonstrate the applicability and distinctive performance of the proposed multitask fuzzy system model in multitask regression learning scenarios.

  1. Fuzzy C-Means Clustering Model Data Mining For Recognizing Stock Data Sampling Pattern

    Sylvia Jane Annatje Sumarauw

    2007-06-01

    Full Text Available Abstract Capital market has been beneficial to companies and investor. For investors, the capital market provides two economical advantages, namely deviden and capital gain, and a non-economical one that is a voting .} hare in Shareholders General Meeting. But, it can also penalize the share owners. In order to prevent them from the risk, the investors should predict the prospect of their companies. As a consequence of having an abstract commodity, the share quality will be determined by the validity of their company profile information. Any information of stock value fluctuation from Jakarta Stock Exchange can be a useful consideration and a good measurement for data analysis. In the context of preventing the shareholders from the risk, this research focuses on stock data sample category or stock data sample pattern by using Fuzzy c-Me, MS Clustering Model which providing any useful information jar the investors. lite research analyses stock data such as Individual Index, Volume and Amount on Property and Real Estate Emitter Group at Jakarta Stock Exchange from January 1 till December 31 of 204. 'he mining process follows Cross Industry Standard Process model for Data Mining (CRISP,. DM in the form of circle with these steps: Business Understanding, Data Understanding, Data Preparation, Modelling, Evaluation and Deployment. At this modelling process, the Fuzzy c-Means Clustering Model will be applied. Data Mining Fuzzy c-Means Clustering Model can analyze stock data in a big database with many complex variables especially for finding the data sample pattern, and then building Fuzzy Inference System for stimulating inputs to be outputs that based on Fuzzy Logic by recognising the pattern. Keywords: Data Mining, AUz..:y c-Means Clustering Model, Pattern Recognition

  2. Study on Fuzzy Comprehensive Evaluation Model for the Safety of Mine Belt Conveyor

    Gong Xiaoyan

    2017-01-01

    Full Text Available To improve the situation of the frequent failures of mine belt conveyor during operation, a model was used to evaluate the safety of mine belt conveyor. Based on the foundation of collecting and analyzing a large quantity of fault information of belt conveyor in the nationwide coal mine, the fault tree model of belt conveyor has been built, then the safety evaluation index system was established by analyzing and removing some secondary indicators. Furthermore, the weighted value of safety evaluation indexs was determined by analytic hierarchy process(AHP, and the single factor fuzzy evaluation matrix was constructed by experts grading method. Additionally, the model was applied in evaluating the security of belt conveyor in Nanliang coal mine. The results shows the security level is recognized to the “general”, which means that this model can be adopted widely in evaluating the safety of mine belt conveyor.

  3. Data mining in forecasting PVT correlations of crude oil systems based on Type1 fuzzy logic inference systems

    El-Sebakhy, Emad A.

    2009-09-01

    Pressure-volume-temperature properties are very important in the reservoir engineering computations. There are many empirical approaches for predicting various PVT properties based on empirical correlations and statistical regression models. Last decade, researchers utilized neural networks to develop more accurate PVT correlations. These achievements of neural networks open the door to data mining techniques to play a major role in oil and gas industry. Unfortunately, the developed neural networks correlations are often limited, and global correlations are usually less accurate compared to local correlations. Recently, adaptive neuro-fuzzy inference systems have been proposed as a new intelligence framework for both prediction and classification based on fuzzy clustering optimization criterion and ranking. This paper proposes neuro-fuzzy inference systems for estimating PVT properties of crude oil systems. This new framework is an efficient hybrid intelligence machine learning scheme for modeling the kind of uncertainty associated with vagueness and imprecision. We briefly describe the learning steps and the use of the Takagi Sugeno and Kang model and Gustafson-Kessel clustering algorithm with K-detected clusters from the given database. It has featured in a wide range of medical, power control system, and business journals, often with promising results. A comparative study will be carried out to compare their performance of this new framework with the most popular modeling techniques, such as neural networks, nonlinear regression, and the empirical correlations algorithms. The results show that the performance of neuro-fuzzy systems is accurate, reliable, and outperform most of the existing forecasting techniques. Future work can be achieved by using neuro-fuzzy systems for clustering the 3D seismic data, identification of lithofacies types, and other reservoir characterization.

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

    Mitra, Soumyaroop; Lam, Sarah S.

    2012-02-01

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

  5. Improved estimation of electricity demand function by integration of fuzzy system and data mining approach

    Azadeh, A.; Saberi, M.; Ghaderi, S.F.; Gitiforouz, A.; Ebrahimipour, V.

    2008-01-01

    This study presents an integrated fuzzy system, data mining and time series framework to estimate and predict electricity demand for seasonal and monthly changes in electricity consumption especially in developing countries such as China and Iran with non-stationary data. Furthermore, it is difficult to model uncertain behavior of energy consumption with only conventional fuzzy system or time series and the integrated algorithm could be an ideal substitute for such cases. To construct fuzzy systems, a rule base is needed. Because a rule base is not available, for the case of demand function, look up table which is one of the extracting rule methods is used to extract the rule base. This system is defined as FLT. Also, decision tree method which is a data mining approach is similarly utilized to extract the rule base. This system is defined as FDM. Preferred time series model is selected from linear (ARMA) and nonlinear model. For this, after selecting preferred ARMA model, McLeod-Li test is applied to determine nonlinearity condition. When, nonlinearity condition is satisfied, preferred nonlinear model is selected and compare with preferred ARMA model and finally one of this is selected as time series model. At last, ANOVA is used for selecting preferred model from fuzzy models and time series model. Also, the impact of data preprocessing and postprocessing on the fuzzy system performance is considered by the algorithm. In addition, another unique feature of the proposed algorithm is utilization of autocorrelation function (ACF) to define input variables, whereas conventional methods which use trial and error method. Monthly electricity consumption of Iran from 1995 to 2005 is considered as the case of this study. The MAPE estimation of genetic algorithm (GA), artificial neural network (ANN) versus the proposed algorithm shows the appropriateness of the proposed algorithm

  6. Evaluation of the nutritional effects of fasting on cardiovascular diseases, using fuzzy data mining

    Mostafa Abbasi Joshaghan

    2014-02-01

    Full Text Available Background: Advances in information technology and data collection methods have enabled high-speed collection and storage of huge amounts of data. Data mining can be used to derive laws from large data volumes and their characteristics. Similarly, fuzzy logic by facilitating the understanding of events is considered a suitable complement to scientific data mining. Materials and Methods: The present study used clustering to identify the independent characteristics of data. Related fuzzy sets, linguistic variables, and data classifications were defined, and the index was introduced based on the characteristics extracted from useful results. By considering the disease risk factors, the results were analyzed. Results: Two factors contributing to the health improvement or deterioration were defined: ‘age’ and ‘the appropriateness or inappropriateness between insulin level and blood sugar’. In addition, according to the results, fasting had a positive effect on fatty substances of the blood (cholesterol and triglycerides. Conclusion: The results can help us determine whether or not an individual with a cardiovascular disease should fast in the month of Ramadan. However, due to variations in some features such as blood pressure throughout the day, there are uncertainties in some input data; therefore, the results could be far from reality. If it is possible to generate fuzzy data, then we can obtain more accurate results.

  7. A Collaborative Educational Association Rule Mining Tool

    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…

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

    Mirjana Maksimović

    2014-09-01

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

  9. Evaluation of Underground Zinc Mine Investment Based on Fuzzy-Interval Grey System Theory and Geometric Brownian Motion

    Zoran Gligoric

    2014-01-01

    Full Text Available Underground mine projects are often associated with diverse sources of uncertainties. Having the ability to plan for these uncertainties plays a key role in the process of project evaluation and is increasingly recognized as critical to mining project success. To make the best decision, based on the information available, it is necessary to develop an adequate model incorporating the uncertainty of the input parameters. The model is developed on the basis of full discounted cash flow analysis of an underground zinc mine project. The relationships between input variables and economic outcomes are complex and often nonlinear. Fuzzy-interval grey system theory is used to forecast zinc metal prices while geometric Brownian motion is used to forecast operating costs over the time frame of the project. To quantify the uncertainty in the parameters within a project, such as capital investment, ore grade, mill recovery, metal content of concentrate, and discount rate, we have applied the concept of interval numbers. The final decision related to project acceptance is based on the net present value of the cash flows generated by the simulation over the time project horizon.

  10. Relational Demonic Fuzzy Refinement

    Fairouz Tchier

    2014-01-01

    Full Text Available We use relational algebra to define a refinement fuzzy order called demonic fuzzy refinement and also the associated fuzzy operators which are fuzzy demonic join (⊔fuz, fuzzy demonic meet (⊓fuz, and fuzzy demonic composition (□fuz. Our definitions and properties are illustrated by some examples using mathematica software (fuzzy logic.

  11. Human action quality evaluation based on fuzzy logic with application in underground coal mining.

    Ionica, Andreea; Leba, Monica

    2015-01-01

    The work system is defined by its components, their roles and the relationships between them. Any work system gravitates around the human resource and the interdependencies between human factor and the other components of it. Researches in this field agreed that the human factor and its actions are difficult to quantify and predict. The objective of this paper is to apply a method of human actions evaluation in order to estimate possible risks and prevent possible system faults, both at human factor level and at equipment level. In order to point out the importance of the human factor influence on all the elements of the working systems we propose a fuzzy logic based methodology for quality evaluation of human actions. This methodology has a multidisciplinary character, as it gathers ideas and methods from: quality management, ergonomics, work safety and artificial intelligence. The results presented refer to a work system with a high degree of specificity, namely, underground coal mining and are valuable for human resources risk evaluation pattern. The fuzzy logic evaluation of the human actions leads to early detection of possible dangerous evolutions of the work system and alarm the persons in charge.

  12. Regional Management of an Aquifer for Mining Under Fuzzy Environmental Objectives

    BogáRdi, IstváN.; BáRdossy, AndráS.; Duckstein, Lucien

    1983-12-01

    A methodology is developed for the dynamic multiobjective management of a multipurpose regional aquifer. In a case study of bauxite mining in Western Hungary, ore deposits are often under the piezometric level of a karstic aquifer, while this same aquifer also provides recharge flows for thermal springs. N + 1 objectives are to be minimized, the first one being total discounted cost of control by dewatering or grouting; the other N objectives consist of the flow of thermal springs at N control points. However, there is no agreement among experts as to a set of numerical values that would constitute a "sound environment"; for this reason a fuzzy set analysis is used, and the N environmental objectives are combined into a single fuzzy membership function. The constraints include ore availability, various capacities, and the state transition function that describes the behavior of both piezometric head and underground flow. The model is linearized and solved as a biobjective dynamic program by using multiobjective compromise programming. A numerical example with N = 2 appears to lead to realistic control policies. Extension of the model to the nonlinear case is discussed.

  13. Mine-associated wetlands as avian habitat

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

    1998-01-01

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

  14. Expert evaluation of innovation projects of mining enterprises on the basis of methods of system analysis and fuzzy logics

    Pimonov Alexander

    2017-01-01

    Full Text Available This paper presents the multipurpose approach to evaluation of research and innovation projects based on the method of analysis of hierarchies and fuzzy logics for the mining industry. The approach, implemented as part of a decision support system, can reduce the degree of subjectivity during examinations by taking into account both quantitative and qualitative characteristics of the compared innovative alternatives; it does not depend on specific conditions of examination and allows engagement of experts of various fields of knowledge. The system includes the mechanism of coordination of several experts’ views. Using of fuzzy logics allows evaluating the qualitative characteristics of innovations in the form of formalized logical conclusions.

  15. THE DEVELOPMENT OF A NOVEL MODEL FOR MINING METHOD SELECTION IN A FUZZY ENVIRONMENT; CASE STUDY: TAZAREH COAL MINE, SEMNAN PROVINCE, IRAN

    Fatemeh Asadi Ooriad

    2018-01-01

    Full Text Available Mining method selection (MMS for mineral resources is one of the most significant steps in mining production management. Due to high costs involved and environmental problems, it is usually not possible to change the coal mining method after planning and starting the operation. In most cases, MMS can be considered as an irreversible process. Selecting a method for mining mainly depends on geological, geometrical properties of the resource, environmental impacts of exploration, impacts of hazardous activities and land use management. This paper seeks to develop a novel model for mining method selection in order to achieve a stable production rate and to reduce environmental problems. This novel model is illustrated by implementing for Tazareh coal mine. Given the disadvantages of the previous models for selecting coal mining method, the purpose of this research is modifying the previous models and offering a comprehensive model. In this respect, TOPSIS method is used as a powerful multi attribute decision-making procedure in Fuzzy environment. After implementation of the presented model in Tazareh coal mine, long wall mining method has been selected as the most appropriate mining method.

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

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

    2018-06-01

    In China, floods are considered as the most frequent natural disaster responsible for severe economic losses and serious damages recorded in agriculture and urban infrastructure. Based on the international experience prevention of flood events may not be completely possible, however identifying susceptible and vulnerable areas through prediction models is considered as a more visible task with flood susceptibility mapping being an essential tool for flood mitigation strategies and disaster preparedness. In this context, the present study proposes a novel approach to construct a flood susceptibility map in the Poyang County, JiangXi Province, China by implementing fuzzy weight of evidence (fuzzy-WofE) and data mining methods. The novelty of the presented approach is the usage of fuzzy-WofE that had a twofold purpose. Firstly, to create an initial flood susceptibility map in order to identify non-flood areas and secondly to weight the importance of flood related variables which influence flooding. Logistic Regression (LR), Random Forest (RF) and Support Vector Machines (SVM) were implemented considering eleven flood related variables, namely: lithology, soil cover, elevation, slope angle, aspect, topographic wetness index, stream power index, sediment transport index, plan curvature, profile curvature and distance from river network. The efficiency of this new approach was evaluated using area under curve (AUC) which measured the prediction and success rates. According to the outcomes of the performed analysis, the fuzzy WofE-SVM model was the model with the highest predictive performance (AUC value, 0.9865) which also appeared to be statistical significant different from the other predictive models, fuzzy WofE-RF (AUC value, 0.9756) and fuzzy WofE-LR (AUC value, 0.9652). The proposed methodology and the produced flood susceptibility map could assist researchers and local governments in flood mitigation strategies. Copyright © 2017 Elsevier B.V. All rights reserved.

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

    Qin Ding; William Perrizo

    2007-01-01

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

  18. Hospitalization patterns associated with Appalachian coal mining.

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

    2007-12-01

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

  19. Hazards associated with stage one-mining

    Anon.

    1975-01-01

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

  20. Relational Demonic Fuzzy Refinement

    Tchier, Fairouz

    2014-01-01

    We use relational algebra to define a refinement fuzzy order called demonic fuzzy refinement and also the associated fuzzy operators which are fuzzy demonic join $({\\bigsqcup }_{\\mathrm{\\text{f}}\\mathrm{\\text{u}}\\mathrm{\\text{z}}})$ , fuzzy demonic meet $({\\sqcap }_{\\mathrm{\\text{f}}\\mathrm{\\text{u}}\\mathrm{\\text{z}}})$ , and fuzzy demonic composition $({\\square }_{\\mathrm{\\text{f}}\\mathrm{\\text{u}}\\mathrm{\\text{z}}})$ . Our definitions and properties are illustrated by some examples using ma...

  1. Mining Hesitation Information by Vague Association Rules

    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.

  2. A Study on the Rare Factors Exploration of Learning Effectiveness by Using Fuzzy Data Mining

    Chen, Chen-Tung; Chang, Kai-Yi

    2017-01-01

    The phenomenon of low fertility has been negatively impacted on the social structure of the educational environment in Taiwan. To increase the learning effectiveness of students became the most important issue for the Universities in Taiwan. Due to the subjective judgment of evaluators and the attributes of influenced factors are always fuzzy, it…

  3. Quantum algorithm for association rules mining

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

    2016-10-01

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

  4. Mining rare associations between biological ontologies.

    Benites, Fernando; Simon, Svenja; Sapozhnikova, Elena

    2014-01-01

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

  5. Mining rare associations between biological ontologies.

    Fernando Benites

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

  6. Fuzzy, crisp, and human logic in e-commerce marketing data mining

    Hearn, Kelda L.; Zhang, Yanqing

    2001-03-01

    In today's business world there is an abundance of available data and a great need to make good use of it. Many businesses would benefit from examining customer habits and trends and making marketing and product decisions based on that analysis. However, the process of manually examining data and making sound decisions based on that data is time consuming and often impractical. Intelligent systems that can make judgments similar to human judgments are sorely needed. Thus, systems based on fuzzy logic present themselves as an option to be seriously considered. The work described in this paper attempts to make an initial comparison between fuzzy logic and more traditional hard or crisp logic to see which would make a better substitute for human intervention. In this particular case study, customers are classified into categories that indicate how desirable the customer would be as a prospect for marketing. This classification is based on a small set of customer data. The results from these investigations make it clear that fuzzy logic is more able to think for itself and make decisions that more closely match human decision and is therefore significantly closer to human logic than crisp logic.

  7. Association and Sequence Mining in Web Usage

    Claudia Elena DINUCA

    2011-06-01

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

  8. A BCM theory of meta-plasticity for online self-reorganizing fuzzy-associative learning.

    Tan, Javan; Quek, Chai

    2010-06-01

    Self-organizing neurofuzzy approaches have matured in their online learning of fuzzy-associative structures under time-invariant conditions. To maximize their operative value for online reasoning, these self-sustaining mechanisms must also be able to reorganize fuzzy-associative knowledge in real-time dynamic environments. Hence, it is critical to recognize that they would require self-reorganizational skills to rebuild fluid associative structures when their existing organizations fail to respond well to changing circumstances. In this light, while Hebbian theory (Hebb, 1949) is the basic computational framework for associative learning, it is less attractive for time-variant online learning because it suffers from stability limitations that impedes unlearning. Instead, this paper adopts the Bienenstock-Cooper-Munro (BCM) theory of neurological learning via meta-plasticity principles (Bienenstock et al., 1982) that provides for both online associative and dissociative learning. For almost three decades, BCM theory has been shown to effectively brace physiological evidence of synaptic potentiation (association) and depression (dissociation) into a sound mathematical framework for computational learning. This paper proposes an interpretation of the BCM theory of meta-plasticity for an online self-reorganizing fuzzy-associative learning system to realize online-reasoning capabilities. Experimental findings are twofold: 1) the analysis using S&P-500 stock index illustrated that the self-reorganizing approach could follow the trajectory shifts in the time-variant S&P-500 index for about 60 years, and 2) the benchmark profiles showed that the fuzzy-associative approach yielded comparable results with other fuzzy-precision models with similar online objectives.

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

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

    2010-01-01

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

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

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

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

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

    Miller, C.G.

    1997-01-01

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

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

    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.

  13. Using Fuzzy SOM Strategy for Satellite Image Retrieval and Information Mining

    Yo-Ping Huang

    2008-02-01

    Full Text Available This paper proposes an efficient satellite image retrieval and knowledge discovery model. The strategy comprises two major parts. First, a computational algorithm is used for off-line satellite image feature extraction, image data representation and image retrieval. Low level features are automatically extracted from the segmented regions of satellite images. A self-organization feature map is used to construct a two-layer satellite image concept hierarchy. The events are stored in one layer and the corresponding feature vectors are categorized in the other layer. Second, a user friendly interface is provided that retrieves images of interest and mines useful information based on the events in the concept hierarchy. The proposed system is evaluated with prominent features such as typhoons or high-pressure masses.

  14. FUZZY RINGS AND ITS PROPERTIES

    Karyati Karyati

    2017-01-01

      One of algebraic structure that involves a binary operation is a group that is defined  an un empty set (classical with an associative binary operation, it has identity elements and each element has an inverse. In the structure of the group known as the term subgroup, normal subgroup, subgroup and factor group homomorphism and its properties. Classical algebraic structure is developed to algebraic structure fuzzy by the researchers as an example semi group fuzzy and fuzzy group after fuzzy sets is introduced by L. A. Zadeh at 1965. It is inspired of writing about semi group fuzzy and group of fuzzy, a research on the algebraic structure of the ring is held with reviewing ring fuzzy, ideal ring fuzzy, homomorphism ring fuzzy and quotient ring fuzzy with its properties. The results of this study are obtained fuzzy properties of the ring, ring ideal properties fuzzy, properties of fuzzy ring homomorphism and properties of fuzzy quotient ring by utilizing a subset of a subset level  and strong level  as well as image and pre-image homomorphism fuzzy ring.   Keywords: fuzzy ring, subset level, homomorphism fuzzy ring, fuzzy quotient ring

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

    Yu, Pulan

    2012-01-01

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

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

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

    1995-01-01

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

  17. Identification of artificial groundwater recharging zone using a GIS-based fuzzy logic approach: a case study in a coal mine area of the Damodar Valley, India

    Tiwari, Ashwani Kumar; Lavy, Muriel; Amanzio, Gianpiero; De Maio, Marina; Singh, Prasoon Kumar; Mahato, Mukesh Kumar

    2017-12-01

    The West Bokaro coalfield is a richest coal-mining belt in the Damodar Valley, India. The extensive mining of the area has resulted in disruption of the groundwater availability in terms of both quantity and quality. This has led to a drinking water crisis, especially during the pre-monsoon period in the West Bokaro coalfield area. The characterization of the hydrogeological system and the artificial recharging of the aquifers might help to better manage the problem of the groundwater-level depletion. For this purpose, seven important hydrogeological factors (water depth, slope, drainage, soil, infiltration, lithology, and landuse) have been considered to define the most suitable locations for artificial groundwater recharging in the mining area. Different thematic maps were prepared from existing maps and data sets, remote-sensing images, and field investigations for identification of the most suitable locations for artificial recharge. Thematic layers for these parameters were prepared, classified, weighted, and integrated into a geographic information system (GIS) environment by means of fuzzy logic. The results of the study indicate that about 29 and 31% of the area are very suitable and suitable for recharging purposes in the West Bokaro coalfield. However, the rest of the area is moderate to unsuitable for recharging due to the ongoing mining and related activities in the study area. The groundwater recharging map of the study area was validated with measured electrical conductivity (EC) values in the groundwater, and it indicated that validation can be accepted for the identification of groundwater recharging sites. These findings are providing useful information for the proper planning and sustainable management of the groundwater resources in the study area.

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

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

    2016-05-01

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

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

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

    2010-01-01

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

  20. Software tool for data mining and its applications

    Yang, Jie; Ye, Chenzhou; Chen, Nianyi

    2002-03-01

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

  1. A Fuzzy Query Mechanism for Human Resource Websites

    Lai, Lien-Fu; Wu, Chao-Chin; Huang, Liang-Tsung; Kuo, Jung-Chih

    Users' preferences often contain imprecision and uncertainty that are difficult for traditional human resource websites to deal with. In this paper, we apply the fuzzy logic theory to develop a fuzzy query mechanism for human resource websites. First, a storing mechanism is proposed to store fuzzy data into conventional database management systems without modifying DBMS models. Second, a fuzzy query language is proposed for users to make fuzzy queries on fuzzy databases. User's fuzzy requirement can be expressed by a fuzzy query which consists of a set of fuzzy conditions. Third, each fuzzy condition associates with a fuzzy importance to differentiate between fuzzy conditions according to their degrees of importance. Fourth, the fuzzy weighted average is utilized to aggregate all fuzzy conditions based on their degrees of importance and degrees of matching. Through the mutual compensation of all fuzzy conditions, the ordering of query results can be obtained according to user's preference.

  2. Robust state estimation for uncertain fuzzy bidirectional associative memory networks with time-varying delays

    Vadivel, P.; Sakthivel, R.; Mathiyalagan, K.; Arunkumar, A.

    2013-09-01

    This paper addresses the issue of robust state estimation for a class of fuzzy bidirectional associative memory (BAM) neural networks with time-varying delays and parameter uncertainties. By constructing the Lyapunov-Krasovskii functional, which contains the triple-integral term and using the free-weighting matrix technique, a set of sufficient conditions are derived in terms of linear matrix inequalities (LMIs) to estimate the neuron states through available output measurements such that the dynamics of the estimation error system is robustly asymptotically stable. In particular, we consider a generalized activation function in which the traditional assumptions on the boundedness, monotony and differentiability of the activation functions are removed. More precisely, the design of the state estimator for such BAM neural networks can be obtained by solving some LMIs, which are dependent on the size of the time derivative of the time-varying delays. Finally, a numerical example with simulation result is given to illustrate the obtained theoretical results.

  3. Robust state estimation for uncertain fuzzy bidirectional associative memory networks with time-varying delays

    Vadivel, P; Sakthivel, R; Mathiyalagan, K; Arunkumar, A

    2013-01-01

    This paper addresses the issue of robust state estimation for a class of fuzzy bidirectional associative memory (BAM) neural networks with time-varying delays and parameter uncertainties. By constructing the Lyapunov–Krasovskii functional, which contains the triple-integral term and using the free-weighting matrix technique, a set of sufficient conditions are derived in terms of linear matrix inequalities (LMIs) to estimate the neuron states through available output measurements such that the dynamics of the estimation error system is robustly asymptotically stable. In particular, we consider a generalized activation function in which the traditional assumptions on the boundedness, monotony and differentiability of the activation functions are removed. More precisely, the design of the state estimator for such BAM neural networks can be obtained by solving some LMIs, which are dependent on the size of the time derivative of the time-varying delays. Finally, a numerical example with simulation result is given to illustrate the obtained theoretical results. (paper)

  4. PREVENTION OF ZERO DAY VULNERABILITY IN NETWORK USING ENSEMBLE FUZZY ASSOCIATION AND CUTTLE FISH

    M Masthan

    2017-06-01

    Full Text Available The data communication between different parts of the universe is managed by the computer networks and the Enterprise Information System (EIS which rely on them. The privacy and security are the most important factor to be maintained in any network systems. This paper deals about the detection of intrusion attack in the eclipse database using Ensemble fuzzy association (EFA and Cuttle Fish Algorithm (CFA. The proposed methodology creates a rule-based ensemble model for network diversity metric modeling for the efficient detection of zeroday attacks and to reduce the time consumption. The simulation result shows that the EFA and CFA having efficient detection rates as compared to the existing systems.

  5. Natural radioactivity associated with bituminous coal mining in Nigeria

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

    2003-01-01

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

  6. Equipment Selection by using Fuzzy TOPSIS Method

    Yavuz, Mahmut

    2016-10-01

    In this study, Fuzzy TOPSIS method was performed for the selection of open pit truck and the optimal solution of the problem was investigated. Data from Turkish Coal Enterprises was used in the application of the method. This paper explains the Fuzzy TOPSIS approaches with group decision-making application in an open pit coal mine in Turkey. An algorithm of the multi-person multi-criteria decision making with fuzzy set approach was applied an equipment selection problem. It was found that Fuzzy TOPSIS with a group decision making is a method that may help decision-makers in solving different decision-making problems in mining.

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

    Hossein Ghayoumi Zadeh

    2012-10-01

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

  8. Mining

    Khairullah Khan

    2014-09-01

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

  9. Clinical signs of pneumonia in children: association with and prediction of diagnosis by fuzzy sets theory

    Pereira J.C.R.

    2004-01-01

    Full Text Available The present study compares the performance of stochastic and fuzzy models for the analysis of the relationship between clinical signs and diagnosis. Data obtained for 153 children concerning diagnosis (pneumonia, other non-pneumonia diseases, absence of disease and seven clinical signs were divided into two samples, one for analysis and other for validation. The former was used to derive relations by multi-discriminant analysis (MDA and by fuzzy max-min compositions (fuzzy, and the latter was used to assess the predictions drawn from each type of relation. MDA and fuzzy were closely similar in terms of prediction, with correct allocation of 75.7 to 78.3% of patients in the validation sample, and displaying only a single instance of disagreement: a patient with low level of toxemia was mistaken as not diseased by MDA and correctly taken as somehow ill by fuzzy. Concerning relations, each method provided different information, each revealing different aspects of the relations between clinical signs and diagnoses. Both methods agreed on pointing X-ray, dyspnea, and auscultation as better related with pneumonia, but only fuzzy was able to detect relations of heart rate, body temperature, toxemia and respiratory rate with pneumonia. Moreover, only fuzzy was able to detect a relationship between heart rate and absence of disease, which allowed the detection of six malnourished children whose diagnoses as healthy are, indeed, disputable. The conclusion is that even though fuzzy sets theory might not improve prediction, it certainly does enhance clinical knowledge since it detects relationships not visible to stochastic models.

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

    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.

  11. The foundations of fuzzy control

    Lewis, Harold W

    1997-01-01

    Harold Lewis applied a cross-disciplinary approach in his highly accessible discussion of fuzzy control concepts. With the aid of fifty-seven illustrations, he thoroughly presents a unique mathematical formalism to explain the workings of the fuzzy inference engine and a novel test plant used in the research. Additionally, the text posits a new viewpoint on why fuzzy control is more popular in some countries than in others. A direct and original view of Japanese thinking on fuzzy control methods, based on the author's personal knowledge of - and association with - Japanese fuzzy research, is also included.

  12. Information mining in remote sensing imagery

    Li, Jiang

    The volume of remotely sensed imagery continues to grow at an enormous rate due to the advances in sensor technology, and our capability for collecting and storing images has greatly outpaced our ability to analyze and retrieve information from the images. This motivates us to develop image information mining techniques, which is very much an interdisciplinary endeavor drawing upon expertise in image processing, databases, information retrieval, machine learning, and software design. This dissertation proposes and implements an extensive remote sensing image information mining (ReSIM) system prototype for mining useful information implicitly stored in remote sensing imagery. The system consists of three modules: image processing subsystem, database subsystem, and visualization and graphical user interface (GUI) subsystem. Land cover and land use (LCLU) information corresponding to spectral characteristics is identified by supervised classification based on support vector machines (SVM) with automatic model selection, while textural features that characterize spatial information are extracted using Gabor wavelet coefficients. Within LCLU categories, textural features are clustered using an optimized k-means clustering approach to acquire search efficient space. The clusters are stored in an object-oriented database (OODB) with associated images indexed in an image database (IDB). A k-nearest neighbor search is performed using a query-by-example (QBE) approach. Furthermore, an automatic parametric contour tracing algorithm and an O(n) time piecewise linear polygonal approximation (PLPA) algorithm are developed for shape information mining of interesting objects within the image. A fuzzy object-oriented database based on the fuzzy object-oriented data (FOOD) model is developed to handle the fuzziness and uncertainty. Three specific applications are presented: integrated land cover and texture pattern mining, shape information mining for change detection of lakes, and

  13. Fuzzy logic

    Smets, P

    1995-01-01

    We start by describing the nature of imperfect data, and giving an overview of the various models that have been proposed. Fuzzy sets theory is shown to be an extension of classical set theory, and as such has a proeminent role or modelling imperfect data. The mathematic of fuzzy sets theory is detailled, in particular the role of the triangular norms. The use of fuzzy sets theory in fuzzy logic and possibility theory,the nature of the generalized modus ponens and of the implication operator for approximate reasoning are analysed. The use of fuzzy logic is detailled for application oriented towards process control and database problems.

  14. Fuzzy Languages

    Rahonis, George

    The theory of fuzzy recognizable languages over bounded distributive lattices is presented as a paradigm of recognizable formal power series. Due to the idempotency properties of bounded distributive lattices, the equality of fuzzy recognizable languages is decidable, the determinization of multi-valued automata is effective, and a pumping lemma exists. Fuzzy recognizable languages over finite and infinite words are expressively equivalent to sentences of the multi-valued monadic second-order logic. Fuzzy recognizability over bounded ℓ-monoids and residuated lattices is briefly reported. The chapter concludes with two applications of fuzzy recognizable languages to real world problems in medicine.

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

    Wood, R.M.

    1994-01-01

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

  16. Fuzzy comprehensive evaluation method of F statistics weighting in ...

    In order to rapidly identify the source of water inrush in coal mine, and provide the theoretical basis for mine water damage prevention and control, fuzzy comprehensive evaluation model was established. The F statistics of water samples was normalized as the weight of fuzzy comprehensive evaluation for determining the ...

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

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

    2015-04-01

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

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

    Yusoff Ismail

    1994-01-01

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

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

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

    1984-07-01

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

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

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

    2018-04-01

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

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

    Haswell, Melissa R; Bethmont, Anna

    2016-01-01

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

  2. On Algebraic Study of Type-2 Fuzzy Finite State Automata

    Anupam K. Singh

    2017-08-01

    Full Text Available Theories of fuzzy sets and type-2 fuzzy sets are powerful mathematical tools for modeling various types of uncertainty. In this paper we introduce the concept of type-2 fuzzy finite state automata and discuss the algebraic study of type-2 fuzzy finite state automata, i.e., to introduce the concept of homomorphisms between two type-2 fuzzy finite state automata, to associate a type-2 fuzzy transformation semigroup with a type-2 fuzzy finite state automata. Finally, we discuss several product of type-2 fuzzy finite state automata and shown that these product is a categorical product.

  3. Fuzzy-predictive direct power control implementation of a grid connected photovoltaic system, associated with an active power filter

    Ouchen, Sabir; Betka, Achour; Abdeddaim, Sabrina; Menadi, Abdelkrim

    2016-01-01

    Highlights: • An implementation on dSPACE 1104 of a double stage grid connected photovoltaic system, associated with an active power filter. • A fuzzy logic controller for maximum power point tracking of photovoltaic generator using a boost converter. • Predictive direct power control almost eliminates the effect of harmonics under a unite power factor. • The robustness of control strategies was examined in different irradiance level conditions. - Abstract: The present paper proposes a real time implementation of an optimal operation of a double stage grid connected photovoltaic system, associated with a shunt active power filter. On the photovoltaic side, a fuzzy logic based maximum power point taking control is proposed to track permanently the optimum point through an adequate tuning of a boost converter regardless the solar irradiance variations; whereas, on the grid side, a model predictive direct power control is applied, to ensure both supplying a part of the load demand with the extracted photovoltaic power, and a compensation of undesirable harmonic contents of the grid current, under a unity power factor operation. The implementation of the control strategies is conducted on a small scale photovoltaic system, controlled via a dSPACE 1104 single card. The obtained experimental results show on one hand, that the proposed Fuzzy logic based maximum power taking point technique provides fast and high performances under different irradiance levels while compared with a sliding mode control, and ensures 1.57% more in efficiency. On the other hand, the predictive power control ensures a flexible settlement of active power amounts exchanges with the grid, under a unity power functioning. Furthermore, the grid current presents a sinusoidal shape with a tolerable total harmonic distortion coefficient 4.71%.

  4. Combinational Reasoning of Quantitative Fuzzy Topological Relations for Simple Fuzzy Regions

    Liu, Bo; Li, Dajun; Xia, Yuanping; Ruan, Jian; Xu, Lili; Wu, Huanyi

    2015-01-01

    In recent years, formalization and reasoning of topological relations have become a hot topic as a means to generate knowledge about the relations between spatial objects at the conceptual and geometrical levels. These mechanisms have been widely used in spatial data query, spatial data mining, evaluation of equivalence and similarity in a spatial scene, as well as for consistency assessment of the topological relations of multi-resolution spatial databases. The concept of computational fuzzy topological space is applied to simple fuzzy regions to efficiently and more accurately solve fuzzy topological relations. Thus, extending the existing research and improving upon the previous work, this paper presents a new method to describe fuzzy topological relations between simple spatial regions in Geographic Information Sciences (GIS) and Artificial Intelligence (AI). Firstly, we propose a new definition for simple fuzzy line segments and simple fuzzy regions based on the computational fuzzy topology. And then, based on the new definitions, we also propose a new combinational reasoning method to compute the topological relations between simple fuzzy regions, moreover, this study has discovered that there are (1) 23 different topological relations between a simple crisp region and a simple fuzzy region; (2) 152 different topological relations between two simple fuzzy regions. In the end, we have discussed some examples to demonstrate the validity of the new method, through comparisons with existing fuzzy models, we showed that the proposed method can compute more than the existing models, as it is more expressive than the existing fuzzy models. PMID:25775452

  5. Associating Human-Centered Concepts with Social Networks Using Fuzzy Sets

    Yager, Ronald R.

    The rapidly growing global interconnectivity, brought about to a large extent by the Internet, has dramatically increased the importance and diversity of social networks. Modern social networks cut across a spectrum from benign recreational focused websites such as Facebook to occupationally oriented websites such as LinkedIn to criminally focused groups such as drug cartels to devastation and terror focused groups such as Al-Qaeda. Many organizations are interested in analyzing and extracting information related to these social networks. Among these are governmental police and security agencies as well marketing and sales organizations. To aid these organizations there is a need for technologies to model social networks and intelligently extract information from these models. While established technologies exist for the modeling of relational networks [1-7] few technologies exist to extract information from these, compatible with human perception and understanding. Data bases is an example of a technology in which we have tools for representing our information as well as tools for querying and extracting the information contained. Our goal is in some sense analogous. We want to use the relational network model to represent information, in this case about relationships and interconnections, and then be able to query the social network using intelligent human-centered concepts. To extend our capabilities to interact with social relational networks we need to associate with these network human concepts and ideas. Since human beings predominantly use linguistic terms in which to reason and understand we need to build bridges between human conceptualization and the formal mathematical representation of the social network. Consider for example a concept such as "leader". An analyst may be able to express, in linguistic terms, using a network relevant vocabulary, properties of a leader. Our task is to translate this linguistic description into a mathematical formalism

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

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

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

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

    Amoudru, C.

    1980-01-01

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

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

    Hu, S.J.

    1979-04-01

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

  9. On the Fuzzy Convergence

    Abdul Hameed Q. A. Al-Tai

    2011-01-01

    Full Text Available The aim of this paper is to introduce and study the fuzzy neighborhood, the limit fuzzy number, the convergent fuzzy sequence, the bounded fuzzy sequence, and the Cauchy fuzzy sequence on the base which is adopted by Abdul Hameed (every real number r is replaced by a fuzzy number r¯ (either triangular fuzzy number or singleton fuzzy set (fuzzy point. And then, we will consider that some results respect effect of the upper sequence on the convergent fuzzy sequence, the bounded fuzzy sequence, and the Cauchy fuzzy sequence.

  10. Fuzzy Commitment

    Juels, Ari

    The purpose of this chapter is to introduce fuzzy commitment, one of the earliest and simplest constructions geared toward cryptography over noisy data. The chapter also explores applications of fuzzy commitment to two problems in data security: (1) secure management of biometrics, with a focus on iriscodes, and (2) use of knowledge-based authentication (i.e., personal questions) for password recovery.

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

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

    2015-01-01

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

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

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

    2011-01-01

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

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

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

    2009-12-01

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

  14. Wetland and waterbody restoration and creation associated with mining

    Brooks, R.P.

    1990-01-01

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

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

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

    2015-01-01

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

  16. IDENTIFYING ROOF FALL PREDICTORS USING FUZZY CLASSIFICATION

    Bertoncini, C. A.; Hinders, M. K.

    2010-01-01

    Microseismic monitoring involves placing geophones on the rock surfaces of a mine to record seismic activity. Classification of microseismic mine data can be used to predict seismic events in a mine to mitigate mining hazards, such as roof falls, where properly bolting and bracing the roof is often an insufficient method of preventing weak roofs from destabilizing. In this study, six months of recorded acoustic waveforms from microseismic monitoring in a Pennsylvania limestone mine were analyzed using classification techniques to predict roof falls. Fuzzy classification using features selected for computational ease was applied on the mine data. Both large roof fall events could be predicted using a Roof Fall Index (RFI) metric calculated from the results of the fuzzy classification. RFI was successfully used to resolve the two significant roof fall events and predicted both events by at least 15 hours before visual signs of the roof falls were evident.

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

    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.

  18. A study on generalized hesitant intuitionistic Fuzzy soft sets

    Nazra, A.; Syafruddin; Wicaksono, G. C.; Syafwan, M.

    2018-03-01

    By combining the concept of hesitant intuitionistic fuzzy sets, fuzzy soft sets and fuzzy sets, we extend hesitant intuitionistic fuzzy soft sets to a generalized hesitant intuitionistic fuzzy soft sets. Some operations on generalized hesitant intuitionistic fuzzy soft sets, such as union, complement, operations “AND” and “OR”, and intersection are defined. From such operations the authors obtain related properties such as commutative, associative and De Morgan's laws. The authors also get an algebraic structure of the collection of all generalized hesitant intuitionistic fuzzy soft sets over a set.

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

    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.

  20. Lithium-ion battery state of function estimation based on fuzzy logic algorithm with associated variables

    Gan, L.; Yang, F.; Shi, Y. F.; He, H. L.

    2017-11-01

    Many occasions related to batteries demand to know how much continuous and instantaneous power can batteries provide such as the rapidly developing electric vehicles. As the large-scale applications of lithium-ion batteries, lithium-ion batteries are used to be our research object. Many experiments are designed to get the lithium-ion battery parameters to ensure the relevance and reliability of the estimation. To evaluate the continuous and instantaneous load capability of a battery called state-of-function (SOF), this paper proposes a fuzzy logic algorithm based on battery state-of-charge(SOC), state-of-health(SOH) and C-rate parameters. Simulation and experimental results indicate that the proposed approach is suitable for battery SOF estimation.

  1. Fuzzy promises

    Anker, Thomas Boysen; Kappel, Klemens; Eadie, Douglas

    2012-01-01

    as narrative material to communicate self-identity. Finally, (c) we propose that brands deliver fuzzy experiential promises through effectively motivating consumers to adopt and play a social role implicitly suggested and facilitated by the brand. A promise is an inherently ethical concept and the article...... concludes with an in-depth discussion of fuzzy brand promises as two-way ethical commitments that put requirements on both brands and consumers....

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

    Hymers, L.; Heenan, S.

    2009-05-01

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

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

    Yang, Jianji; Logan, Judith

    2006-01-01

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

  4. Social big data mining

    Ishikawa, Hiroshi

    2015-01-01

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

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

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

    2015-11-01

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

  6. Fuzzy GML Modeling Based on Vague Soft Sets

    Bo Wei

    2017-01-01

    Full Text Available The Open Geospatial Consortium (OGC Geography Markup Language (GML explicitly represents geographical spatial knowledge in text mode. All kinds of fuzzy problems will inevitably be encountered in spatial knowledge expression. Especially for those expressions in text mode, this fuzziness will be broader. Describing and representing fuzziness in GML seems necessary. Three kinds of fuzziness in GML can be found: element fuzziness, chain fuzziness, and attribute fuzziness. Both element fuzziness and chain fuzziness belong to the reflection of the fuzziness between GML elements and, then, the representation of chain fuzziness can be replaced by the representation of element fuzziness in GML. On the basis of vague soft set theory, two kinds of modeling, vague soft set GML Document Type Definition (DTD modeling and vague soft set GML schema modeling, are proposed for fuzzy modeling in GML DTD and GML schema, respectively. Five elements or pairs, associated with vague soft sets, are introduced. Then, the DTDs and the schemas of the five elements are correspondingly designed and presented according to their different chains and different fuzzy data types. While the introduction of the five elements or pairs is the basis of vague soft set GML modeling, the corresponding DTD and schema modifications are key for implementation of modeling. The establishment of vague soft set GML enables GML to represent fuzziness and solves the problem of lack of fuzzy information expression in GML.

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

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

    2014-01-01

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

  8. Mine Water Treatment in Hongai Coal Mines

    Dang Phuong Thao; Dang Vu Chi

    2018-01-01

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

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

    Mallik, Saurav; Mukhopadhyay, Anirban; Maulik, Ujjwal

    2015-01-01

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

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

    Feng Guangwen; Jia Xiahui

    2012-01-01

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

  11. Classification of EEG Signals by Radial Neuro-Fuzzy Systems

    Coufal, David

    2006-01-01

    Roč. 5, č. 2 (2006), s. 415-423 ISSN 1109-2777 R&D Projects: GA MŠk ME 701 Institutional research plan: CEZ:AV0Z10300504 Keywords : neuro-fuzzy systems * radial fuzzy systems * data mining * hybrid systems Subject RIV: BA - General Mathematics

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

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

    2004-01-01

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

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

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

    2014-01-01

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

  14. Fuzzy Clustering

    Berks, G.; Keyserlingk, Diedrich Graf von; Jantzen, Jan

    2000-01-01

    A symptom is a condition indicating the presence of a disease, especially, when regarded as an aid in diagnosis.Symptoms are the smallest units indicating the existence of a disease. A syndrome on the other hand is an aggregate, set or cluster of concurrent symptoms which together indicate...... and clustering are the basic concerns in medicine. Classification depends on definitions of the classes and their required degree of participant of the elements in the cases' symptoms. In medicine imprecise conditions are the rule and therefore fuzzy methods are much more suitable than crisp ones. Fuzzy c......-mean clustering is an easy and well improved tool, which has been applied in many medical fields. We used c-mean fuzzy clustering after feature extraction from an aphasia database. Factor analysis was applied on a correlation matrix of 26 symptoms of language disorders and led to five factors. The factors...

  15. Kajian Data Mining Customer Relationship Management pada Lembaga Keuangan Mikro

    Tikaridha Hardiani

    2016-01-01

    Full Text Available Companies are required to be ready to face the competition will be intense with other companies, including micro-finance institutions. Faced more intense competition, has led to many businesses in microfinance institutions find profitable strategy to distinguish from the others. Strategy that can be applied is implementing Customer Relationship Management (CRM and data mining. Data mining can be used to microfinance institutions that have a large enough data. Determine the potential customers with customer segmentation can help the decision-making marketing strategy that will be implemented . This paper discusses several data mining techniques that can be used for customer segmentation. Proposed method of data mining technique is fuzzy clustering with fuzzy C-Means algorithm and fuzzy RFM. Keywords : Customer relationship management; Data mining; Fuzzy clustering; Micro-finance institutions; Fuzzy C-Means; Fuzzy RFM

  16. Diamond Fuzzy Number

    T. Pathinathan

    2015-01-01

    Full Text Available In this paper we define diamond fuzzy number with the help of triangular fuzzy number. We include basic arithmetic operations like addition, subtraction of diamond fuzzy numbers with examples. We define diamond fuzzy matrix with some matrix properties. We have defined Nested diamond fuzzy number and Linked diamond fuzzy number. We have further classified Right Linked Diamond Fuzzy number and Left Linked Diamond Fuzzy number. Finally we have verified the arithmetic operations for the above mentioned types of Diamond Fuzzy Numbers.

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

    Lemly, A Dennis

    2007-02-01

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

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

    Ngole-Jeme, Veronica Mpode; Fantke, Peter

    2017-01-01

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

  19. A genetic fuzzy system for unstable angina risk assessment.

    Dong, Wei; Huang, Zhengxing; Ji, Lei; Duan, Huilong

    2014-02-18

    Unstable Angina (UA) is widely accepted as a critical phase of coronary heart disease with patients exhibiting widely varying risks. Early risk assessment of UA is at the center of the management program, which allows physicians to categorize patients according to the clinical characteristics and stratification of risk and different prognosis. Although many prognostic models have been widely used for UA risk assessment in clinical practice, a number of studies have highlighted possible shortcomings. One serious drawback is that existing models lack the ability to deal with the intrinsic uncertainty about the variables utilized. In order to help physicians refine knowledge for the stratification of UA risk with respect to vagueness in information, this paper develops an intelligent system combining genetic algorithm and fuzzy association rule mining. In detail, it models the input information's vagueness through fuzzy sets, and then applies a genetic fuzzy system on the acquired fuzzy sets to extract the fuzzy rule set for the problem of UA risk assessment. The proposed system is evaluated using a real data-set collected from the cardiology department of a Chinese hospital, which consists of 54 patient cases. 9 numerical patient features and 17 categorical patient features that appear in the data-set are selected in the experiments. The proposed system made the same decisions as the physician in 46 (out of a total of 54) tested cases (85.2%). By comparing the results that are obtained through the proposed system with those resulting from the physician's decision, it has been found that the developed model is highly reflective of reality. The proposed system could be used for educational purposes, and with further improvements, could assist and guide young physicians in their daily work.

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

    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.

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

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

    2015-03-01

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

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

    Huang, Zhong

    2014-01-01

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

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

    Qiuhong Sun

    2014-04-01

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

  4. "Fuzzy stuff"

    Christensen, Line Hjorth

    "Fuzzy stuff". Exploring the displacement of the design sketch. What kind of knowledge can historical sketches reveal when they have outplayed their primary instrumental function in the design process and are moved into a museum collection? What are the rational benefits of ‘archival displacement...

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

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

    2017-08-16

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

  6. Uncertainty modeling for data mining a label semantics approach

    Qin, Zengchang

    2014-01-01

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

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

    Jensen, Kasper; Panagiotou, Gianni; Kouskoumvekaki, Irene

    2014-01-01

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

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

    Amoundru, C.

    1980-10-01

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

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

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

    2014-11-01

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

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

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

    1979-07-01

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

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

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

    1979-07-01

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

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

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

    2001-01-01

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

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

    Kaufmann, R.F.

    1981-01-01

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

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

    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.

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

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

    2016-06-06

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

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

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

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

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

    2005-01-01

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

  18. 5th International Conference on Fuzzy and Neuro Computing

    Panigrahi, Bijaya; Das, Swagatam; Suganthan, Ponnuthurai

    2015-01-01

    This proceedings bring together contributions from researchers from academia and industry to report the latest cutting edge research made in the areas of Fuzzy Computing, Neuro Computing and hybrid Neuro-Fuzzy Computing in the paradigm of Soft Computing. The FANCCO 2015 conference explored new application areas, design novel hybrid algorithms for solving different real world application problems. After a rigorous review of the 68 submissions from all over the world, the referees panel selected 27 papers to be presented at the Conference. The accepted papers have a good, balanced mix of theory and applications. The techniques ranged from fuzzy neural networks, decision trees, spiking neural networks, self organizing feature map, support vector regression, adaptive neuro fuzzy inference system, extreme learning machine, fuzzy multi criteria decision making, machine learning, web usage mining, Takagi-Sugeno Inference system, extended Kalman filter, Goedel type logic, fuzzy formal concept analysis, biclustering e...

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

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

    2011-01-01

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

  20. Mine Water Treatment in Hongai Coal Mines

    Dang, Phuong Thao; Dang, Vu Chi

    2018-03-01

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

  1. Mine Water Treatment in Hongai Coal Mines

    Dang Phuong Thao

    2018-01-01

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

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

    Jie Zhang

    2013-01-01

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

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

    Zhang, Jie; Wang, Yuping; Feng, Junhong

    2013-01-01

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

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

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

    2014-01-01

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

  5. On Bipolar Valued Fuzzy k-Ideals in Hermirings

    Mahmood, T.; Ejaz, A.

    2015-01-01

    In this paper we discuss some results associated with bipolar valued fuzzy k -ideals of hermirings. We also define bipolar valued fuzzy k-intrinsic product and characterize k-hemiregular hermirings by using their bipolar valued fuzzy k -ideals. (author)

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

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

    2011-07-01

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

  7. Introduction to type-2 fuzzy logic control theory and applications

    Mendel, Jerry M; Tan, Woei-Wan; Melek, William W; Ying, Hao

    2014-01-01

    Written by world-class leaders in type-2 fuzzy logic control, this book offers a self-contained reference for both researchers and students. The coverage provides both background and an extensive literature survey on fuzzy logic and related type-2 fuzzy control. It also includes research questions, experiment and simulation results, and downloadable computer programs on an associated website. This key resource will prove useful to students and engineers wanting to learn type-2 fuzzy control theory and its applications.

  8. Comprehensive evaluation on rationality of ventilation system in uranium underground mine

    Zhou Qinglin

    1991-01-01

    A new method is presented for evaluating rationality of uranium mine ventilation system using fuzzy mathematics. The mathematical models for fuzzy comprehensive evaluation are introduced. Based on practice of uranium mine ventilation, the evaluation factors and the evaluation procedure are given. Using the presented method, a comprehensive evaluation was carried out for ventilation systems before and after regulation in Fuzhou Uranium Mine

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

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

    1991-01-01

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

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

    Nkosi, Vusumuzi; Wichmann, Janine; Voyi, Kuku

    2015-04-03

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

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

    Daher Jean Raymond

    2016-01-01

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

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

    Garcia Fernandez, G.; Romero Diaz, A.

    2009-01-01

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

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

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

    2017-07-01

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

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

    Garcia Fernandez, G.; Romero Diaz, A.

    2009-07-01

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

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

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

    2015-06-06

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

  16. Introduction to fuzzy systems

    Chen, Guanrong

    2005-01-01

    Introduction to Fuzzy Systems provides students with a self-contained introduction that requires no preliminary knowledge of fuzzy mathematics and fuzzy control systems theory. Simplified and readily accessible, it encourages both classroom and self-directed learners to build a solid foundation in fuzzy systems. After introducing the subject, the authors move directly into presenting real-world applications of fuzzy logic, revealing its practical flavor. This practicality is then followed by basic fuzzy systems theory. The book also offers a tutorial on fuzzy control theory, based mainly on th

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

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

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

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

    Street, Tamara D.; Thomas, Drew L.

    2016-01-01

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

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

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

    2016-01-01

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

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

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

    2013-01-01

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

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

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

    2009-09-01

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

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

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

    2014-03-01

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

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

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

    2002-01-01

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

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

    Chunhua Ju

    2015-01-01

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

  5. Intuitionistic supra fuzzy topological spaces

    Abbas, S.E.

    2004-01-01

    In this paper, We introduce an intuitionistic supra fuzzy closure space and investigate the relationship between intuitionistic supra fuzzy topological spaces and intuitionistic supra fuzzy closure spaces. Moreover, we can obtain intuitionistic supra fuzzy topological space induced by an intuitionistic fuzzy bitopological space. We study the relationship between intuitionistic supra fuzzy closure space and the intuitionistic supra fuzzy topological space induced by an intuitionistic fuzzy bitopological space

  6. Hesitant fuzzy sets theory

    Xu, Zeshui

    2014-01-01

    This book provides the readers with a thorough and systematic introduction to hesitant fuzzy theory. It presents the most recent research results and advanced methods in the field. These includes: hesitant fuzzy aggregation techniques, hesitant fuzzy preference relations, hesitant fuzzy measures, hesitant fuzzy clustering algorithms and hesitant fuzzy multi-attribute decision making methods. Since its introduction by Torra and Narukawa in 2009, hesitant fuzzy sets have become more and more popular and have been used for a wide range of applications, from decision-making problems to cluster analysis, from medical diagnosis to personnel appraisal and information retrieval. This book offers a comprehensive report on the state-of-the-art in hesitant fuzzy sets theory and applications, aiming at becoming a reference guide for both researchers and practitioners in the area of fuzzy mathematics and other applied research fields (e.g. operations research, information science, management science and engineering) chara...

  7. Fuzzy logic in management

    Carlsson, Christer; Fullér, Robert

    2004-01-01

    Fuzzy Logic in Management demonstrates that difficult problems and changes in the management environment can be more easily handled by bringing fuzzy logic into the practice of management. This explicit theme is developed through the book as follows: Chapter 1, "Management and Intelligent Support Technologies", is a short survey of management leadership and what can be gained from support technologies. Chapter 2, "Fuzzy Sets and Fuzzy Logic", provides a short introduction to fuzzy sets, fuzzy relations, the extension principle, fuzzy implications and linguistic variables. Chapter 3, "Group Decision Support Systems", deals with group decision making, and discusses methods for supporting the consensus reaching processes. Chapter 4, "Fuzzy Real Options for Strategic Planning", summarizes research where the fuzzy real options theory was implemented as a series of models. These models were thoroughly tested on a number of real life investments, and validated in 2001. Chapter 5, "Soft Computing Methods for Reducing...

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

    Raies, A. B.

    2014-11-14

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

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

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

    2015-01-01

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

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

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

    2011-06-01

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

  11. Probabilistic Quadratic Programming Problems with Some Fuzzy Parameters

    S. K. Barik

    2012-01-01

    making problem by using some specified random variables and fuzzy numbers. In the present paper, randomness is characterized by Weibull random variables and fuzziness is characterized by triangular and trapezoidal fuzzy number. A defuzzification method has been introduced for finding the crisp values of the fuzzy numbers using the proportional probability density function associated with the membership functions of these fuzzy numbers. An equivalent deterministic crisp model has been established in order to solve the proposed model. Finally, a numerical example is presented to illustrate the solution procedure.

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

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

    2017-09-25

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

  13. Fuzzy modeling and control theory and applications

    Matía, Fernando; Jiménez, Emilio

    2014-01-01

    Much work on fuzzy control, covering research, development and applications, has been developed in Europe since the 90's. Nevertheless, the existing books in the field are compilations of articles without interconnection or logical structure or they express the personal point of view of the author. This book compiles the developments of researchers with demonstrated experience in the field of fuzzy control following a logic structure and a unified the style. The first chapters of the book are dedicated to the introduction of the main fuzzy logic techniques, where the following chapters focus on concrete applications. This book is supported by the EUSFLAT and CEA-IFAC societies, which include a large number of researchers in the field of fuzzy logic and control. The central topic of the book, Fuzzy Control, is one of the main research and development lines covered by these associations.

  14. Why fuzzy controllers should be fuzzy

    Nowe, A.

    1996-01-01

    Fuzzy controllers are usually looked at as crisp valued mappings especially when artificial intelligence learning techniques are used to build up the controller. By doing so the semantics of a fuzzy conclusion being a fuzzy restriction on the viable control actions is non-existing. In this paper the authors criticise from an approximation point of view using a fuzzy controller to express a crisp mapping does not seem the right way to go. Secondly it is illustrated that interesting information is contained in a fuzzy conclusion when indeed this conclusion is considered as a fuzzy restriction. This information turns out to be very valuable when viability problems are concerned, i.e. problems where the objective is to keep a system within predefined boundaries

  15. Fuzzy Neuroidal Nets and Recurrent Fuzzy Computations

    Wiedermann, Jiří

    2001-01-01

    Roč. 11, č. 6 (2001), s. 675-686 ISSN 1210-0552. [SOFSEM 2001 Workshop on Soft Computing. Piešťany, 29.11.2001-30.11.2001] R&D Projects: GA ČR GA201/00/1489; GA AV ČR KSK1019101 Institutional research plan: AV0Z1030915 Keywords : fuzzy computing * fuzzy neural nets * fuzzy Turing machines * non-uniform computational complexity Subject RIV: BA - General Mathematics

  16. Fifty years of fuzzy logic and its applications

    Rishe, Naphtali; Kandel, Abraham

    2015-01-01

    This book presents a comprehensive report on the evolution of Fuzzy Logic since its formulation in Lotfi Zadeh’s seminal paper on “fuzzy sets,” published in 1965. In addition, it features a stimulating sampling from the broad field of research and development inspired by Zadeh’s paper. The chapters, written by pioneers and prominent scholars in the field, show how fuzzy sets have been successfully applied to artificial intelligence, control theory, inference, and reasoning. The book also reports on theoretical issues; features recent applications of Fuzzy Logic in the fields of neural networks, clustering, data mining, and software testing; and highlights an important paradigm shift caused by Fuzzy Logic in the area of uncertainty management. Conceived by the editors as an academic celebration of the fifty years’ anniversary of the 1965 paper, this work is a must-have for students and researchers willing to get an inspiring picture of the potentialities, limitations, achievements and accomplishments...

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

    Milev, A

    2013-10-01

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

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

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

    2015-07-10

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

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

    Hauben, Manfred

    2004-09-01

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

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

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

    2018-07-01

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

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

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

    1999-01-01

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

  2. Fuzzy Itand#244; Integral Driven by a Fuzzy Brownian Motion

    Didier Kumwimba Seya

    2015-11-01

    Full Text Available In this paper we take into account the fuzzy stochastic integral driven by fuzzy Brownian motion. To define the metric between two fuzzy numbers and to take into account the limit of a sequence of fuzzy numbers, we invoke the Hausdorff metric. First this fuzzy stochastic integral is constructed for fuzzy simple stochastic functions, then the construction is done for fuzzy stochastic integrable functions.

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

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

    2016-01-01

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

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

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

    2012-01-01

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

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

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

    2016-01-01

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

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

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

    2013-01-01

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

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

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

    2013-07-01

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

  8. Multivariate spatial condition mapping using subtractive fuzzy cluster means.

    Sabit, Hakilo; Al-Anbuky, Adnan

    2014-10-13

    Wireless sensor networks are usually deployed for monitoring given physical phenomena taking place in a specific space and over a specific duration of time. The spatio-temporal distribution of these phenomena often correlates to certain physical events. To appropriately characterise these events-phenomena relationships over a given space for a given time frame, we require continuous monitoring of the conditions. WSNs are perfectly suited for these tasks, due to their inherent robustness. This paper presents a subtractive fuzzy cluster means algorithm and its application in data stream mining for wireless sensor systems over a cloud-computing-like architecture, which we call sensor cloud data stream mining. Benchmarking on standard mining algorithms, the k-means and the FCM algorithms, we have demonstrated that the subtractive fuzzy cluster means model can perform high quality distributed data stream mining tasks comparable to centralised data stream mining.

  9. Paired fuzzy sets

    Rodríguez, J. Tinguaro; Franco de los Ríos, Camilo; Gómez, Daniel

    2015-01-01

    In this paper we want to stress the relevance of paired fuzzy sets, as already proposed in previous works of the authors, as a family of fuzzy sets that offers a unifying view for different models based upon the opposition of two fuzzy sets, simply allowing the existence of different types...

  10. Fuzzy measures and integrals

    Mesiar, Radko

    2005-01-01

    Roč. 28, č. 156 (2005), s. 365-370 ISSN 0165-0114 R&D Projects: GA ČR(CZ) GA402/04/1026 Institutional research plan: CEZ:AV0Z10750506 Keywords : fuzzy measures * fuzzy integral * regular fuzzy integral Subject RIV: BA - General Mathematics Impact factor: 1.039, year: 2005

  11. Fuzzy Graph Language Recognizability

    Kalampakas , Antonios; Spartalis , Stefanos; Iliadis , Lazaros

    2012-01-01

    Part 5: Fuzzy Logic; International audience; Fuzzy graph language recognizability is introduced along the lines of the established theory of syntactic graph language recognizability by virtue of the algebraic structure of magmoids. The main closure properties of the corresponding class are investigated and several interesting examples of fuzzy graph languages are examined.

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

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

    2012-01-01

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

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

    Veronica Mpode Ngole-Jeme

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

  14. Intuitionistic Fuzzy Subbialgebras and Duality

    Wenjuan Chen

    2014-01-01

    Full Text Available We investigate connections between bialgebras and Atanassov’s intuitionistic fuzzy sets. Firstly we define an intuitionistic fuzzy subbialgebra of a bialgebra with an intuitionistic fuzzy subalgebra structure and also with an intuitionistic fuzzy subcoalgebra structure. Secondly we investigate the related properties of intuitionistic fuzzy subbialgebras. Finally we prove that the dual of an intuitionistic fuzzy strong subbialgebra is an intuitionistic fuzzy strong subbialgebra.

  15. Risk Assessment in Underground Coalmines Using Fuzzy Logic in the Presence of Uncertainty

    Tripathy, Debi Prasad; Ala, Charan Kumar

    2018-04-01

    Fatal accidents are occurring every year as regular events in Indian coal mining industry. To increase the safety conditions, it has become a prerequisite to performing a risk assessment of various operations in mines. However, due to uncertain accident data, it is hard to conduct a risk assessment in mines. The object of this study is to present a method to assess safety risks in underground coalmines. The assessment of safety risks is based on the fuzzy reasoning approach. Mamdani fuzzy logic model is developed in the fuzzy logic toolbox of MATLAB. A case study is used to demonstrate the applicability of the developed model. The summary of risk evaluation in case study mine indicated that mine fire has the highest risk level among all the hazard factors. This study could help the mine management to prepare safety measures based on the risk rankings obtained.

  16. A comparative study of fuzzy target selection methods in direct marketing

    Costa Sousa, da J.M.; Kaymak, U.; Madeira, S.

    2002-01-01

    Target selection in direct marketing is an important data mining problem for which fuzzy modeling can be used. The paper compares several fuzzy modeling techniques applied to target selection based on recency, frequency and monetary value measures. The comparison uses cross validation applied to

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

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

    2015-06-01

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

  18. Probabilistic fuzzy systems as additive fuzzy systems

    Almeida, R.J.; Verbeek, N.; Kaymak, U.; Costa Sousa, da J.M.; Laurent, A.; Strauss, O.; Bouchon-Meunier, B.; Yager, R.

    2014-01-01

    Probabilistic fuzzy systems combine a linguistic description of the system behaviour with statistical properties of data. It was originally derived based on Zadeh’s concept of probability of a fuzzy event. Two possible and equivalent additive reasoning schemes were proposed, that lead to the

  19. Optimality Conditions for Fuzzy Number Quadratic Programming with Fuzzy Coefficients

    Xue-Gang Zhou

    2014-01-01

    Full Text Available The purpose of the present paper is to investigate optimality conditions and duality theory in fuzzy number quadratic programming (FNQP in which the objective function is fuzzy quadratic function with fuzzy number coefficients and the constraint set is fuzzy linear functions with fuzzy number coefficients. Firstly, the equivalent quadratic programming of FNQP is presented by utilizing a linear ranking function and the dual of fuzzy number quadratic programming primal problems is introduced. Secondly, we present optimality conditions for fuzzy number quadratic programming. We then prove several duality results for fuzzy number quadratic programming problems with fuzzy coefficients.

  20. Countable Fuzzy Topological Space and Countable Fuzzy Topological Vector Space

    Apu Kumar Saha

    2015-06-01

    Full Text Available This paper deals with countable fuzzy topological spaces, a generalization of the notion of fuzzy topological spaces. A collection of fuzzy sets F on a universe X forms a countable fuzzy topology if in the definition of a fuzzy topology, the condition of arbitrary supremum is relaxed to countable supremum. In this generalized fuzzy structure, the continuity of fuzzy functions and some other related properties are studied. Also the class of countable fuzzy topological vector spaces as a generalization of the class of fuzzy topological vector spaces has been introduced and investigated.

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

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

    2014-09-26

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

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

    Hamamura, Natsuko; Fukushima, Koh; Itai, Takaaki

    2013-01-01

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

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

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

    2014-07-01

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

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

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

    2011-01-01

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

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

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

    2011-09-01

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

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

    Hur, Junguk; Özgür, Arzucan; He, Yongqun

    2017-03-14

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

  7. Recurrent fuzzy ranking methods

    Hajjari, Tayebeh

    2012-11-01

    With the increasing development of fuzzy set theory in various scientific fields and the need to compare fuzzy numbers in different areas. Therefore, Ranking of fuzzy numbers plays a very important role in linguistic decision-making, engineering, business and some other fuzzy application systems. Several strategies have been proposed for ranking of fuzzy numbers. Each of these techniques has been shown to produce non-intuitive results in certain case. In this paper, we reviewed some recent ranking methods, which will be useful for the researchers who are interested in this area.

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

    Michael E. Munson

    2014-01-01

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

  9. Fuzzy social choice theory

    B Gibilisco, Michael; E Albert, Karen; N Mordeson, John; J Wierman, Mark; D Clark, Terry

    2014-01-01

    This book offers a comprehensive analysis of the social choice literature and shows, by applying fuzzy sets, how the use of fuzzy preferences, rather than that of strict ones, may affect the social choice theorems. To do this, the book explores the presupposition of rationality within the fuzzy framework and shows that the two conditions for rationality, completeness and transitivity, do exist with fuzzy preferences. Specifically, this book examines: the conditions under which a maximal set exists; the Arrow’s theorem;  the Gibbard-Satterthwaite theorem; and the median voter theorem.  After showing that a non-empty maximal set does exists for fuzzy preference relations, this book goes on to demonstrating the existence of a fuzzy aggregation rule satisfying all five Arrowian conditions, including non-dictatorship. While the Gibbard-Satterthwaite theorem only considers individual fuzzy preferences, this work shows that both individuals and groups can choose alternatives to various degrees, resulting in a so...

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

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

    2003-07-01

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

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

    Joanna F Dipnall

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

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

    Sasao, Eiji

    2012-07-01

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

  13. Quick fuzzy backpropagation algorithm.

    Nikov, A; Stoeva, S

    2001-03-01

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

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

    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.

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

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

    2011-05-01

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

  16. Solving fully fuzzy transportation problem using pentagonal fuzzy numbers

    Maheswari, P. Uma; Ganesan, K.

    2018-04-01

    In this paper, we propose a simple approach for the solution of fuzzy transportation problem under fuzzy environment in which the transportation costs, supplies at sources and demands at destinations are represented by pentagonal fuzzy numbers. The fuzzy transportation problem is solved without converting to its equivalent crisp form using a robust ranking technique and a new fuzzy arithmetic on pentagonal fuzzy numbers. To illustrate the proposed approach a numerical example is provided.

  17. effect of varying controller parameters on the performance of a fuzzy

    Dr Obe

    is given the primary attention. The adjustments ... hope that this discovery will make it easier to .... deciding what the output fuzzy set should be ... Such a matrix is called a fuzzy associative memory (F ..... and approximate reasoning," Proc. IEEE ...

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

    Binoy B. Nair

    2015-04-01

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

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

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

    1989-01-20

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

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

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

    1982-01-01

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

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

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

    2013-04-15

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

  2. On defining and computing fuzzy kernels on L-valued simple graphs

    Bisdorff, R.; Roubens, M.

    1996-01-01

    In this paper we introduce the concept of fuzzy kernels defined on valued-finite simple graphs in a sense close to fuzzy preference modelling. First we recall the classic concept of kernel associated with a crisp binary relation defined on a finite set. In a second part, we introduce fuzzy binary relations. In a third part, we generalize the crisp kernel concept to such fuzzy binary relations and in a last part, we present an application to fuzzy choice functions on fuzzy outranking relations

  3. Introduction to Fuzzy Set Theory

    Kosko, Bart

    1990-01-01

    An introduction to fuzzy set theory is described. Topics covered include: neural networks and fuzzy systems; the dynamical systems approach to machine intelligence; intelligent behavior as adaptive model-free estimation; fuzziness versus probability; fuzzy sets; the entropy-subsethood theorem; adaptive fuzzy systems for backing up a truck-and-trailer; product-space clustering with differential competitive learning; and adaptive fuzzy system for target tracking.

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

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

    2010-09-01

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

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

    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.

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

    Bhasuran, Balu; Subramanian, Devika; Natarajan, Jeyakumar

    2018-05-02

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

  7. Decomposition of fuzzy continuity and fuzzy ideal continuity via fuzzy idealization

    Zahran, A.M.; Abbas, S.E.; Abd El-baki, S.A.; Saber, Y.M.

    2009-01-01

    Recently, El-Naschie has shown that the notion of fuzzy topology may be relevant to quantum paretical physics in connection with string theory and E-infinity space time theory. In this paper, we study the concepts of r-fuzzy semi-I-open, r-fuzzy pre-I-open, r-fuzzy α-I-open and r-fuzzy β-I-open sets, which is properly placed between r-fuzzy openness and r-fuzzy α-I-openness (r-fuzzy pre-I-openness) sets regardless the fuzzy ideal topological space in Sostak sense. Moreover, we give a decomposition of fuzzy continuity, fuzzy ideal continuity and fuzzy ideal α-continuity, and obtain several characterization and some properties of these functions. Also, we investigate their relationship with other types of function.

  8. Fuzzy risk matrix

    Markowski, Adam S.; Mannan, M. Sam

    2008-01-01

    A risk matrix is a mechanism to characterize and rank process risks that are typically identified through one or more multifunctional reviews (e.g., process hazard analysis, audits, or incident investigation). This paper describes a procedure for developing a fuzzy risk matrix that may be used for emerging fuzzy logic applications in different safety analyses (e.g., LOPA). The fuzzification of frequency and severity of the consequences of the incident scenario are described which are basic inputs for fuzzy risk matrix. Subsequently using different design of risk matrix, fuzzy rules are established enabling the development of fuzzy risk matrices. Three types of fuzzy risk matrix have been developed (low-cost, standard, and high-cost), and using a distillation column case study, the effect of the design on final defuzzified risk index is demonstrated

  9. Foundations Of Fuzzy Control

    Jantzen, Jan

    The objective of this textbook is to acquire an understanding of the behaviour of fuzzy logic controllers. Under certain conditions a fuzzy controller is equivalent to a proportional-integral-derivative (PID) controller. Using that equivalence as a link, the book applies analysis methods from...... linear and nonlinear control theory. In the linear domain, PID tuning methods and stability analyses are transferred to linear fuzzy controllers. The Nyquist plot shows the robustness of different settings of the fuzzy gain parameters. As a result, a fuzzy controller is guaranteed to perform as well...... as any PID controller. In the nonlinear domain, the stability of four standard control surfaces is analysed by means of describing functions and Nyquist plots. The self-organizing controller (SOC) is shown to be a model reference adaptive controller. There is a possibility that a nonlinear fuzzy PID...

  10. Intuitionistic fuzzy calculus

    Lei, Qian

    2017-01-01

    This book offers a comprehensive and systematic review of the latest research findings in the area of intuitionistic fuzzy calculus. After introducing the intuitionistic fuzzy numbers’ operational laws and their geometrical and algebraic properties, the book defines the concept of intuitionistic fuzzy functions and presents the research on the derivative, differential, indefinite integral and definite integral of intuitionistic fuzzy functions. It also discusses some of the methods that have been successfully used to deal with continuous intuitionistic fuzzy information or data, which are different from the previous aggregation operators focusing on discrete information or data. Mainly intended for engineers and researchers in the fields of fuzzy mathematics, operations research, information science and management science, this book is also a valuable textbook for postgraduate and advanced undergraduate students alike.

  11. Uranium mining

    2008-01-01

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

  12. Metamathematics of fuzzy logic

    Hájek, Petr

    1998-01-01

    This book presents a systematic treatment of deductive aspects and structures of fuzzy logic understood as many valued logic sui generis. Some important systems of real-valued propositional and predicate calculus are defined and investigated. The aim is to show that fuzzy logic as a logic of imprecise (vague) propositions does have well-developed formal foundations and that most things usually named `fuzzy inference' can be naturally understood as logical deduction.

  13. Fuzzy Control Tutorial

    Dotoli, M.; Jantzen, Jan

    1999-01-01

    The tutorial concerns automatic control of an inverted pendulum, especially rule based control by means of fuzzy logic. A ball balancer, implemented in a software simulator in Matlab, is used as a practical case study. The objectives of the tutorial are to teach the basics of fuzzy control......, and to show how to apply fuzzy logic in automatic control. The tutorial is distance learning, where students interact one-to-one with the teacher using e-mail....

  14. Intuitionistic fuzzy logics

    T Atanassov, Krassimir

    2017-01-01

    The book offers a comprehensive survey of intuitionistic fuzzy logics. By reporting on both the author’s research and others’ findings, it provides readers with a complete overview of the field and highlights key issues and open problems, thus suggesting new research directions. Starting with an introduction to the basic elements of intuitionistic fuzzy propositional calculus, it then provides a guide to the use of intuitionistic fuzzy operators and quantifiers, and lastly presents state-of-the-art applications of intuitionistic fuzzy sets. The book is a valuable reference resource for graduate students and researchers alike.

  15. Fuzzy control and identification

    Lilly, John H

    2010-01-01

    This book gives an introduction to basic fuzzy logic and Mamdani and Takagi-Sugeno fuzzy systems. The text shows how these can be used to control complex nonlinear engineering systems, while also also suggesting several approaches to modeling of complex engineering systems with unknown models. Finally, fuzzy modeling and control methods are combined in the book, to create adaptive fuzzy controllers, ending with an example of an obstacle-avoidance controller for an autonomous vehicle using modus ponendo tollens logic.

  16. Fuzzy Modelling for Human Dynamics Based on Online Social Networks.

    Cuenca-Jara, Jesus; Terroso-Saenz, Fernando; Valdes-Vela, Mercedes; Skarmeta, Antonio F

    2017-08-24

    Human mobility mining has attracted a lot of attention in the research community due to its multiple implications in the provisioning of innovative services for large metropolises. In this scope, Online Social Networks (OSN) have arisen as a promising source of location data to come up with new mobility models. However, the human nature of this data makes it rather noisy and inaccurate. In order to deal with such limitations, the present work introduces a framework for human mobility mining based on fuzzy logic. Firstly, a fuzzy clustering algorithm extracts the most active OSN areas at different time periods. Next, such clusters are the building blocks to compose mobility patterns. Furthermore, a location prediction service based on a fuzzy rule classifier has been developed on top of the framework. Finally, both the framework and the predictor has been tested with a Twitter and Flickr dataset in two large cities.

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

    Street, Tamara D; Thomas, Drew L

    2017-03-01

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

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

    Ismail, Walaa N; Hassan, Mohammad Mehedi

    2017-04-26

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

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

    Walaa N. Ismail

    2017-04-01

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

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

    Dipnall, Joanna F.

    2016-01-01

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

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

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

    2008-12-01

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

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

    Yu-Ling Shih

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

  3. Relations Among Some Fuzzy Entropy Formulae

    卿铭

    2004-01-01

    Fuzzy entropy has been widely used to analyze and design fuzzy systems, and many fuzzy entropy formulae have been proposed. For further in-deepth analysis of fuzzy entropy, the axioms and some important formulae of fuzzy entropy are introduced. Some equivalence results among these fuzzy entropy formulae are proved, and it is shown that fuzzy entropy is a special distance measurement.

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

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

    2014-01-01

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

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

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

    2016-04-01

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

  6. Automated Detection of Cancer Associated Genes Using a Combined Fuzzy-Rough-Set-Based F-Information and Water Swirl Algorithm of Human Gene Expression Data.

    Pugalendhi Ganesh Kumar

    Full Text Available This study describes a novel approach to reducing the challenges of highly nonlinear multiclass gene expression values for cancer diagnosis. To build a fruitful system for cancer diagnosis, in this study, we introduced two levels of gene selection such as filtering and embedding for selection of potential genes and the most relevant genes associated with cancer, respectively. The filter procedure was implemented by developing a fuzzy rough set (FR-based method for redefining the criterion function of f-information (FI to identify the potential genes without discretizing the continuous gene expression values. The embedded procedure is implemented by means of a water swirl algorithm (WSA, which attempts to optimize the rule set and membership function required to classify samples using a fuzzy-rule-based multiclassification system (FRBMS. Two novel update equations are proposed in WSA, which have better exploration and exploitation abilities while designing a self-learning FRBMS. The efficiency of our new approach was evaluated on 13 multicategory and 9 binary datasets of cancer gene expression. Additionally, the performance of the proposed FRFI-WSA method in designing an FRBMS was compared with existing methods for gene selection and optimization such as genetic algorithm (GA, particle swarm optimization (PSO, and artificial bee colony algorithm (ABC on all the datasets. In the global cancer map with repeated measurements (GCM_RM dataset, the FRFI-WSA showed the smallest number of 16 most relevant genes associated with cancer using a minimal number of 26 compact rules with the highest classification accuracy (96.45%. In addition, the statistical validation used in this study revealed that the biological relevance of the most relevant genes associated with cancer and their linguistics detected by the proposed FRFI-WSA approach are better than those in the other methods. The simple interpretable rules with most relevant genes and effectively

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

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

    2012-06-15

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

  8. On Intuitionistic Fuzzy Filters of Intuitionistic Fuzzy Coframes

    Rajesh K. Thumbakara

    2013-01-01

    Full Text Available Frame theory is the study of topology based on its open set lattice, and it was studied extensively by various authors. In this paper, we study quotients of intuitionistic fuzzy filters of an intuitionistic fuzzy coframe. The quotients of intuitionistic fuzzy filters are shown to be filters of the given intuitionistic fuzzy coframe. It is shown that the collection of all intuitionistic fuzzy filters of a coframe and the collection of all intutionistic fuzzy quotient filters of an intuitionistic fuzzy filter are coframes.

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

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

    2015-01-01

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

  10. Generalized coherent state approach to star products and applications to the fuzzy sphere

    Alexanian, G.; Pinzul, A.; Stern, A.

    2001-01-01

    We construct a star product associated with an arbitrary two-dimensional Poisson structure using generalized coherent states on the complex plane. From our approach one easily recovers the star product for the fuzzy torus, and also one for the fuzzy sphere. For the latter we need to define the 'fuzzy' stereographic projection to the plane and the fuzzy sphere integration measure, which in the commutative limit reduce to the usual formulae for the sphere

  11. Possibility Fuzzy Soft Set

    Shawkat Alkhazaleh

    2011-01-01

    Full Text Available We introduce the concept of possibility fuzzy soft set and its operation and study some of its properties. We give applications of this theory in solving a decision-making problem. We also introduce a similarity measure of two possibility fuzzy soft sets and discuss their application in a medical diagnosis problem.

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

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

    2016-01-01

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

  13. Properties of Bipolar Fuzzy Hypergraphs

    Akram, M.; Dudek, W. A.; Sarwar, S.

    2013-01-01

    In this article, we apply the concept of bipolar fuzzy sets to hypergraphs and investigate some properties of bipolar fuzzy hypergraphs. We introduce the notion of $A-$ tempered bipolar fuzzy hypergraphs and present some of their properties. We also present application examples of bipolar fuzzy hypergraphs.

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

    Dinesh J. Prajapati

    2017-06-01

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

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

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

    2017-01-01

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

  16. Dynamic cluster generation for a fuzzy classifier with ellipsoidal regions.

    Abe, S

    1998-01-01

    In this paper, we discuss a fuzzy classifier with ellipsoidal regions that dynamically generates clusters. First, for the data belonging to a class we define a fuzzy rule with an ellipsoidal region. Namely, using the training data for each class, we calculate the center and the covariance matrix of the ellipsoidal region for the class. Then we tune the fuzzy rules, i.e., the slopes of the membership functions, successively until there is no improvement in the recognition rate of the training data. Then if the number of the data belonging to a class that are misclassified into another class exceeds a prescribed number, we define a new cluster to which those data belong and the associated fuzzy rule. Then we tune the newly defined fuzzy rules in the similar way as stated above, fixing the already obtained fuzzy rules. We iterate generation of clusters and tuning of the newly generated fuzzy rules until the number of the data belonging to a class that are misclassified into another class does not exceed the prescribed number. We evaluate our method using thyroid data, Japanese Hiragana data of vehicle license plates, and blood cell data. By dynamic cluster generation, the generalization ability of the classifier is improved and the recognition rate of the fuzzy classifier for the test data is the best among the neural network classifiers and other fuzzy classifiers if there are no discrete input variables.

  17. Statistical Methods for Fuzzy Data

    Viertl, Reinhard

    2011-01-01

    Statistical data are not always precise numbers, or vectors, or categories. Real data are frequently what is called fuzzy. Examples where this fuzziness is obvious are quality of life data, environmental, biological, medical, sociological and economics data. Also the results of measurements can be best described by using fuzzy numbers and fuzzy vectors respectively. Statistical analysis methods have to be adapted for the analysis of fuzzy data. In this book, the foundations of the description of fuzzy data are explained, including methods on how to obtain the characterizing function of fuzzy m

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

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

    2016-11-01

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

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

    Ö. Aydan

    2015-11-01

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

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

    Kao Hung-An

    2017-01-01

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

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

    Mohd Khairudin, Nazli; Mustapha, Aida

    2014-01-01

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

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

    Isphording, W.C.

    1992-01-01

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

  3. Construction of fuzzy automata by fuzzy experiments

    Mironov, A.

    1994-01-01

    The solving the problem of canonical realization of partial reaction morphisms (PRM) for automata in toposes and fuzzy automata is addressed. This problem extends the optimal construction problem for finite deterministic automata by experiments. In the present paper the conception of canonical realization of PRM for automata in toposes is introduced and the sufficient conditions for the existence of canonical realizations for PRM in toposes are presented. As a consequence of this result the existence of canonical realizations for PRM in the category of fuzzy sets over arbitrary complete chain is proven

  4. Construction of fuzzy automata by fuzzy experiments

    Mironov, A [Moscow Univ. (Russian Federation). Dept. of Mathematics and Computer Science

    1994-12-31

    The solving the problem of canonical realization of partial reaction morphisms (PRM) for automata in toposes and fuzzy automata is addressed. This problem extends the optimal construction problem for finite deterministic automata by experiments. In the present paper the conception of canonical realization of PRM for automata in toposes is introduced and the sufficient conditions for the existence of canonical realizations for PRM in toposes are presented. As a consequence of this result the existence of canonical realizations for PRM in the category of fuzzy sets over arbitrary complete chain is proven.

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

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

    2010-01-01

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

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

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

    2013-12-01

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

  7. Creating Clinical Fuzzy Automata with Fuzzy Arden Syntax.

    de Bruin, Jeroen S; Steltzer, Heinz; Rappelsberger, Andrea; Adlassnig, Klaus-Peter

    2017-01-01

    Formal constructs for fuzzy sets and fuzzy logic are incorporated into Arden Syntax version 2.9 (Fuzzy Arden Syntax). With fuzzy sets, the relationships between measured or observed data and linguistic terms are expressed as degrees of compatibility that model the unsharpness of the boundaries of linguistic terms. Propositional uncertainty due to incomplete knowledge of relationships between clinical linguistic concepts is modeled with fuzzy logic. Fuzzy Arden Syntax also supports the construction of fuzzy state monitors. The latter are defined as monitors that employ fuzzy automata to observe gradual transitions between different stages of disease. As a use case, we re-implemented FuzzyARDS, a previously published clinical monitoring system for patients suffering from acute respiratory distress syndrome (ARDS). Using the re-implementation as an example, we show how key concepts of fuzzy automata, i.e., fuzzy states and parallel fuzzy state transitions, can be implemented in Fuzzy Arden Syntax. The results showed that fuzzy state monitors can be implemented in a straightforward manner.

  8. Model predictive control using fuzzy decision functions

    Kaymak, U.; Costa Sousa, da J.M.

    2001-01-01

    Fuzzy predictive control integrates conventional model predictive control with techniques from fuzzy multicriteria decision making, translating the goals and the constraints to predictive control in a transparent way. The information regarding the (fuzzy) goals and the (fuzzy) constraints of the

  9. Identification of different geologic units using fuzzy constrained resistivity tomography

    Singh, Anand; Sharma, S. P.

    2018-01-01

    Different geophysical inversion strategies are utilized as a component of an interpretation process that tries to separate geologic units based on the resistivity distribution. In the present study, we present the results of separating different geologic units using fuzzy constrained resistivity tomography. This was accomplished using fuzzy c means, a clustering procedure to improve the 2D resistivity image and geologic separation within the iterative minimization through inversion. First, we developed a Matlab-based inversion technique to obtain a reliable resistivity image using different geophysical data sets (electrical resistivity and electromagnetic data). Following this, the recovered resistivity model was converted into a fuzzy constrained resistivity model by assigning the highest probability value of each model cell to the cluster utilizing fuzzy c means clustering procedure during the iterative process. The efficacy of the algorithm is demonstrated using three synthetic plane wave electromagnetic data sets and one electrical resistivity field dataset. The presented approach shows improvement on the conventional inversion approach to differentiate between different geologic units if the correct number of geologic units will be identified. Further, fuzzy constrained resistivity tomography was performed to examine the augmentation of uranium mineralization in the Beldih open cast mine as a case study. We also compared geologic units identified by fuzzy constrained resistivity tomography with geologic units interpreted from the borehole information.

  10. Uncertain rule-based fuzzy systems introduction and new directions

    Mendel, Jerry M

    2017-01-01

    The second edition of this textbook provides a fully updated approach to fuzzy sets and systems that can model uncertainty — i.e., “type-2” fuzzy sets and systems. The author demonstrates how to overcome the limitations of classical fuzzy sets and systems, enabling a wide range of applications from time-series forecasting to knowledge mining to control. In this new edition, a bottom-up approach is presented that begins by introducing classical (type-1) fuzzy sets and systems, and then explains how they can be modified to handle uncertainty. The author covers fuzzy rule-based systems – from type-1 to interval type-2 to general type-2 – in one volume. For hands-on experience, the book provides information on accessing MatLab and Java software to complement the content. The book features a full suite of classroom material. Presents fully updated material on new breakthroughs in human-inspired rule-based techniques for handling real-world uncertainties; Allows those already familiar with type-1 fuzzy se...

  11. Approximations of Fuzzy Systems

    Vinai K. Singh

    2013-03-01

    Full Text Available A fuzzy system can uniformly approximate any real continuous function on a compact domain to any degree of accuracy. Such results can be viewed as an existence of optimal fuzzy systems. Li-Xin Wang discussed a similar problem using Gaussian membership function and Stone-Weierstrass Theorem. He established that fuzzy systems, with product inference, centroid defuzzification and Gaussian functions are capable of approximating any real continuous function on a compact set to arbitrary accuracy. In this paper we study a similar approximation problem by using exponential membership functions

  12. Beyond fuzzy spheres

    Govindarajan, T R; Padmanabhan, Pramod; Shreecharan, T

    2010-01-01

    We study polynomial deformations of the fuzzy sphere, specifically given by the cubic or the Higgs algebra. We derive the Higgs algebra by quantizing the Poisson structure on a surface in R 3 . We find that several surfaces, differing by constants, are described by the Higgs algebra at the fuzzy level. Some of these surfaces have a singularity and we overcome this by quantizing this manifold using coherent states for this nonlinear algebra. This is seen in the measure constructed from these coherent states. We also find the star product for this non-commutative algebra as a first step in constructing field theories on such fuzzy spaces.

  13. Risk Mapping of Cutaneous Leishmaniasis via a Fuzzy C Means-based Neuro-Fuzzy Inference System

    P. Akhavan

    2014-10-01

    Full Text Available Finding pathogenic factors and how they are spread in the environment has become a global demand, recently. Cutaneous Leishmaniasis (CL created by Leishmania is a special parasitic disease which can be passed on to human through phlebotomus of vector-born. Studies show that economic situation, cultural issues, as well as environmental and ecological conditions can affect the prevalence of this disease. In this study, Data Mining is utilized in order to predict CL prevalence rate and obtain a risk map. This case is based on effective environmental parameters on CL and a Neuro-Fuzzy system was also used. Learning capacity of Neuro-Fuzzy systems in neural network on one hand and reasoning power of fuzzy systems on the other, make it very efficient to use. In this research, in order to predict CL prevalence rate, an adaptive Neuro-fuzzy inference system with fuzzy inference structure of fuzzy C Means clustering was applied to determine the initial membership functions. Regarding to high incidence of CL in Ilam province, counties of Ilam, Mehran, and Dehloran have been examined and evaluated. The CL prevalence rate was predicted in 2012 by providing effective environmental map and topography properties including temperature, moisture, annual, rainfall, vegetation and elevation. Results indicate that the model precision with fuzzy C Means clustering structure rises acceptable RMSE values of both training and checking data and support our analyses. Using the proposed data mining technology, the pattern of disease spatial distribution and vulnerable areas become identifiable and the map can be used by experts and decision makers of public health as a useful tool in management and optimal decision-making.

  14. Risk Mapping of Cutaneous Leishmaniasis via a Fuzzy C Means-based Neuro-Fuzzy Inference System

    Akhavan, P.; Karimi, M.; Pahlavani, P.

    2014-10-01

    Finding pathogenic factors and how they are spread in the environment has become a global demand, recently. Cutaneous Leishmaniasis (CL) created by Leishmania is a special parasitic disease which can be passed on to human through phlebotomus of vector-born. Studies show that economic situation, cultural issues, as well as environmental and ecological conditions can affect the prevalence of this disease. In this study, Data Mining is utilized in order to predict CL prevalence rate and obtain a risk map. This case is based on effective environmental parameters on CL and a Neuro-Fuzzy system was also used. Learning capacity of Neuro-Fuzzy systems in neural network on one hand and reasoning power of fuzzy systems on the other, make it very efficient to use. In this research, in order to predict CL prevalence rate, an adaptive Neuro-fuzzy inference system with fuzzy inference structure of fuzzy C Means clustering was applied to determine the initial membership functions. Regarding to high incidence of CL in Ilam province, counties of Ilam, Mehran, and Dehloran have been examined and evaluated. The CL prevalence rate was predicted in 2012 by providing effective environmental map and topography properties including temperature, moisture, annual, rainfall, vegetation and elevation. Results indicate that the model precision with fuzzy C Means clustering structure rises acceptable RMSE values of both training and checking data and support our analyses. Using the proposed data mining technology, the pattern of disease spatial distribution and vulnerable areas become identifiable and the map can be used by experts and decision makers of public health as a useful tool in management and optimal decision-making.

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

    Harris, F.

    2014-01-01

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

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

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

    2015-11-01

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

  17. On Some Nonclassical Algebraic Properties of Interval-Valued Fuzzy Soft Sets

    Xiaoyan Liu

    2014-01-01

    Full Text Available Interval-valued fuzzy soft sets realize a hybrid soft computing model in a general framework. Both Molodtsov’s soft sets and interval-valued fuzzy sets can be seen as special cases of interval-valued fuzzy soft sets. In this study, we first compare four different types of interval-valued fuzzy soft subsets and reveal the relations among them. Then we concentrate on investigating some nonclassical algebraic properties of interval-valued fuzzy soft sets under the soft product operations. We show that some fundamental algebraic properties including the commutative and associative laws do not hold in the conventional sense, but hold in weaker forms characterized in terms of the relation =L. We obtain a number of algebraic inequalities of interval-valued fuzzy soft sets characterized by interval-valued fuzzy soft inclusions. We also establish the weak idempotent law and the weak absorptive law of interval-valued fuzzy soft sets using interval-valued fuzzy soft J-equal relations. It is revealed that the soft product operations ∧ and ∨ of interval-valued fuzzy soft sets do not always have similar algebraic properties. Moreover, we find that only distributive inequalities described by the interval-valued fuzzy soft L-inclusions hold for interval-valued fuzzy soft sets.

  18. On some nonclassical algebraic properties of interval-valued fuzzy soft sets.

    Liu, Xiaoyan; Feng, Feng; Zhang, Hui

    2014-01-01

    Interval-valued fuzzy soft sets realize a hybrid soft computing model in a general framework. Both Molodtsov's soft sets and interval-valued fuzzy sets can be seen as special cases of interval-valued fuzzy soft sets. In this study, we first compare four different types of interval-valued fuzzy soft subsets and reveal the relations among them. Then we concentrate on investigating some nonclassical algebraic properties of interval-valued fuzzy soft sets under the soft product operations. We show that some fundamental algebraic properties including the commutative and associative laws do not hold in the conventional sense, but hold in weaker forms characterized in terms of the relation = L . We obtain a number of algebraic inequalities of interval-valued fuzzy soft sets characterized by interval-valued fuzzy soft inclusions. We also establish the weak idempotent law and the weak absorptive law of interval-valued fuzzy soft sets using interval-valued fuzzy soft J-equal relations. It is revealed that the soft product operations ∧ and ∨ of interval-valued fuzzy soft sets do not always have similar algebraic properties. Moreover, we find that only distributive inequalities described by the interval-valued fuzzy soft L-inclusions hold for interval-valued fuzzy soft sets.

  19. On Some Nonclassical Algebraic Properties of Interval-Valued Fuzzy Soft Sets

    2014-01-01

    Interval-valued fuzzy soft sets realize a hybrid soft computing model in a general framework. Both Molodtsov's soft sets and interval-valued fuzzy sets can be seen as special cases of interval-valued fuzzy soft sets. In this study, we first compare four different types of interval-valued fuzzy soft subsets and reveal the relations among them. Then we concentrate on investigating some nonclassical algebraic properties of interval-valued fuzzy soft sets under the soft product operations. We show that some fundamental algebraic properties including the commutative and associative laws do not hold in the conventional sense, but hold in weaker forms characterized in terms of the relation =L. We obtain a number of algebraic inequalities of interval-valued fuzzy soft sets characterized by interval-valued fuzzy soft inclusions. We also establish the weak idempotent law and the weak absorptive law of interval-valued fuzzy soft sets using interval-valued fuzzy soft J-equal relations. It is revealed that the soft product operations ∧ and ∨ of interval-valued fuzzy soft sets do not always have similar algebraic properties. Moreover, we find that only distributive inequalities described by the interval-valued fuzzy soft L-inclusions hold for interval-valued fuzzy soft sets. PMID:25143964

  20. Fuzzy Rough Ring and Its Prop erties

    REN Bi-jun; FU Yan-ling

    2013-01-01

    This paper is devoted to the theories of fuzzy rough ring and its properties. The fuzzy approximation space generated by fuzzy ideals and the fuzzy rough approximation operators were proposed in the frame of fuzzy rough set model. The basic properties of fuzzy rough approximation operators were analyzed and the consistency between approximation operators and the binary operation of ring was discussed.

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

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

    1988-01-01

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

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

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

    2013-01-01

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

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

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

    2015-12-01

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

  4. Fuzzy data analysis

    Bandemer, Hans

    1992-01-01

    Fuzzy data such as marks, scores, verbal evaluations, imprecise observations, experts' opinions and grey tone pictures, are quite common. In Fuzzy Data Analysis the authors collect their recent results providing the reader with ideas, approaches and methods for processing such data when looking for sub-structures in knowledge bases for an evaluation of functional relationship, e.g. in order to specify diagnostic or control systems. The modelling presented uses ideas from fuzzy set theory and the suggested methods solve problems usually tackled by data analysis if the data are real numbers. Fuzzy Data Analysis is self-contained and is addressed to mathematicians oriented towards applications and to practitioners in any field of application who have some background in mathematics and statistics.

  5. Fuzzy stochastic multiobjective programming

    Sakawa, Masatoshi; Katagiri, Hideki

    2011-01-01

    With a stress on interactive decision-making, this work breaks new ground by covering both the random nature of events related to environments, and the fuzziness of human judgements. The text runs from mathematical preliminaries to future research directions.

  6. A Principal Component Analysis/Fuzzy Comprehensive Evaluation for Rockburst Potential in Kimberlite

    Pu, Yuanyuan; Apel, Derek; Xu, Huawei

    2018-02-01

    Kimberlite is an igneous rock which sometimes bears diamonds. Most of the diamonds mined in the world today are found in kimberlite ores. Burst potential in kimberlite has not been investigated, because kimberlite is mostly mined using open-pit mining, which poses very little threat of rock bursting. However, as the mining depth keeps increasing, the mines convert to underground mining methods, which can pose a threat of rock bursting in kimberlite. This paper focuses on the burst potential of kimberlite at a diamond mine in northern Canada. A combined model with the methods of principal component analysis (PCA) and fuzzy comprehensive evaluation (FCE) is developed to process data from 12 different locations in kimberlite pipes. Based on calculated 12 fuzzy evaluation vectors, 8 locations show a moderate burst potential, 2 locations show no burst potential, and 2 locations show strong and violent burst potential, respectively. Using statistical principles, a Mahalanobis distance is adopted to build a comprehensive fuzzy evaluation vector for the whole mine and the final evaluation for burst potential is moderate, which is verified by a practical rockbursting situation at mine site.

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

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

    1997-01-01

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

  8. Fuzzy expert systems models for operations research and management science

    Turksen, I. B.

    1993-12-01

    Fuzzy expert systems can be developed for the effective use of management within the domains of concern associated with Operations Research and Management Science. These models are designed with: (1) expressive powers of representation embedded in linguistic variables and their linguistic values in natural language expressions, and (2) improved methods of interference based on fuzzy logic which is a generalization of multi-valued logic with fuzzy quantifiers. The results of these fuzzy expert system models are either (1) approximately good in comparison with their classical counterparts, or (2) much better than their counterparts. Moreover, for fuzzy expert systems models, it is only necessary to obtain ordinal scale data. Whereas for their classical counterparts, it is generally required that data be at least on ratio and absolute scale in order to guarantee the additivity and multiplicativity assumptions.

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

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

    2014-10-01

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

  10. Fuzzy Control Teaching Models

    Klaus-Dietrich Kramer

    2016-05-01

    Full Text Available Many degree courses at technical universities include the subject of control systems engineering. As an addition to conventional approaches Fuzzy Control can be used to easily find control solutions for systems, even if they include nonlinearities. To support further educational training, models which represent a technical system to be controlled are required. These models have to represent the system in a transparent and easy cognizable manner. Furthermore, a programming tool is required that supports an easy Fuzzy Control development process, including the option to verify the results and tune the system behavior. In order to support the development process a graphical user interface is needed to display the fuzzy terms under real time conditions, especially with a debug system and trace functionality. The experiences with such a programming tool, the Fuzzy Control Design Tool (FHFCE Tool, and four fuzzy teaching models will be presented in this paper. The methodical and didactical objective in the utilization of these teaching models is to develop solution strategies using Computational Intelligence (CI applications for Fuzzy Controllers in order to analyze different algorithms of inference or defuzzyfication and to verify and tune those systems efficiently.

  11. Fuzzy forecasting based on fuzzy-trend logical relationship groups.

    Chen, Shyi-Ming; Wang, Nai-Yi

    2010-10-01

    In this paper, we present a new method to predict the Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX) based on fuzzy-trend logical relationship groups (FTLRGs). The proposed method divides fuzzy logical relationships into FTLRGs based on the trend of adjacent fuzzy sets appearing in the antecedents of fuzzy logical relationships. First, we apply an automatic clustering algorithm to cluster the historical data into intervals of different lengths. Then, we define fuzzy sets based on these intervals of different lengths. Then, the historical data are fuzzified into fuzzy sets to derive fuzzy logical relationships. Then, we divide the fuzzy logical relationships into FTLRGs for forecasting the TAIEX. Moreover, we also apply the proposed method to forecast the enrollments and the inventory demand, respectively. The experimental results show that the proposed method gets higher average forecasting accuracy rates than the existing methods.

  12. Analisis Perbandingan Algoritma Fuzzy C-Means dan K-Means

    Yohannes, Yohannes

    2016-01-01

    Klasterisasi merupakan teknik pengelompokkan data berdasarkan kemiripan data. Teknik klasterisasi ini banyak digunakan pada bidang ilmu komputer khususnya pengolahan citra, pengenalan pola, dan data mining. Banyak sekali algoritma yang digunakan untuk klasterisasi data. Algoritma yang sering digunakan untuk klasterisasi data pada umumnya adalah Fuzzy C-Means dan K-Means. Algoritma Fuzzy C-Means merupakan algoritma klasterisasi dimana data dikelompokkan ke dalam suatu pusat cluster data denga...

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

    Tamara D. Street

    2017-03-01

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

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

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

    2009-01-01

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

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

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

    1997-01-01

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

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

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

    2018-01-01

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

  17. Introduction to n-adaptive fuzzy models to analyze public opinion on AIDS

    Kandasamy, D W B V; Kandasamy, Dr.W.B.Vasantha; Smarandache, Dr.Florentin

    2006-01-01

    There are many fuzzy models like Fuzzy matrices, Fuzzy Cognitive Maps, Fuzzy relational Maps, Fuzzy Associative Memories, Bidirectional Associative memories and so on. But almost all these models can give only one sided solution like hidden pattern or a resultant output vector dependent on the input vector depending in the problem at hand. So for the first time we have defined a n-adaptive fuzzy model which can view or analyze the problem in n ways (n >=2) Though we have defined these n- adaptive fuzzy models theorectically we are not in a position to get a n-adaptive fuzzy model for n > 2 for practical real world problems. The highlight of this model is its capacity to analyze the same problem in different ways thereby arriving at various solutions that mirror multiple perspectives. We have used the 2-adaptive fuzzy model having the two fuzzy models, fuzzy matrices model and BAMs viz. model to analyze the views of public about HIV/ AIDS disease, patient and the awareness program. This book has five chapters ...

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

    Restu Juniah

    2017-12-01

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

  19. Rough-fuzzy pattern recognition applications in bioinformatics and medical imaging

    Maji, Pradipta

    2012-01-01

    Learn how to apply rough-fuzzy computing techniques to solve problems in bioinformatics and medical image processing Emphasizing applications in bioinformatics and medical image processing, this text offers a clear framework that enables readers to take advantage of the latest rough-fuzzy computing techniques to build working pattern recognition models. The authors explain step by step how to integrate rough sets with fuzzy sets in order to best manage the uncertainties in mining large data sets. Chapters are logically organized according to the major phases of pattern recognition systems dev

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

    Steffi Kopprasch

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

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

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

    2002-01-01

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

  2. Shapley's value for fuzzy games

    Raúl Alvarado Sibaja

    2009-02-01

    Full Text Available This is the continuation of a previous article titled "Fuzzy Games", where I defined a new type of games based on the Multilinear extensions f, of characteristic functions and most of standard theorems for cooperative games also hold for this new type of games: The fuzzy games. Now we give some other properties and the extension of the definition of Shapley¨s Value for Fuzzy Games Keywords: game theory, fuzzy sets, multiattribute decisions.

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

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

    2012-04-01

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

  4. CHARACTERIZATIONS OF FUZZY SOFT PRE SEPARATION AXIOMS

    El-Latif, Alaa Mohamed Abd

    2015-01-01

    − The notions of fuzzy pre open soft sets and fuzzy pre closed soft sets were introducedby Abd El-latif et al. [2]. In this paper, we continue the study on fuzzy soft topological spaces andinvestigate the properties of fuzzy pre open soft sets, fuzzy pre closed soft sets and study variousproperties and notions related to these structures. In particular, we study the relationship betweenfuzzy pre soft interior fuzzy pre soft closure. Moreover, we study the properties of fuzzy soft pre regulars...

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

    Schutte, PC

    2012-03-01

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

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

    Dawd, Jemal Edris

    2016-07-01

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

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

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

    2006-01-01

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

  8. A neural fuzzy controller learning by fuzzy error propagation

    Nauck, Detlef; Kruse, Rudolf

    1992-01-01

    In this paper, we describe a procedure to integrate techniques for the adaptation of membership functions in a linguistic variable based fuzzy control environment by using neural network learning principles. This is an extension to our work. We solve this problem by defining a fuzzy error that is propagated back through the architecture of our fuzzy controller. According to this fuzzy error and the strength of its antecedent each fuzzy rule determines its amount of error. Depending on the current state of the controlled system and the control action derived from the conclusion, each rule tunes the membership functions of its antecedent and its conclusion. By this we get an unsupervised learning technique that enables a fuzzy controller to adapt to a control task by knowing just about the global state and the fuzzy error.

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

    Yang, Chencheng; Tang, Gang; Hu, Xiong

    2017-07-01

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

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

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

    2015-01-01

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

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

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

    2001-12-01

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

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

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

    2016-01-01

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

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

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

    2014-10-01

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

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

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

    2016-01-01

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

  15. Mining Views : database views for data mining

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

    2008-01-01

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

  16. Mining Views : database views for data mining

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

    2007-01-01

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

  17. WHY FUZZY QUALITY?

    Abbas Parchami

    2016-09-01

    Full Text Available Such as other statistical problems, we may confront with uncertain and fuzzy concepts in quality control. One particular case in process capability analysis is a situation in which specification limits are two fuzzy sets. In such a uncertain and vague environment, the produced product is not qualified with a two-valued Boolean view, but to some degree depending on the decision-maker strictness and the quality level of the produced product. This matter can be cause to a rational decision-making on the quality of the production line. First, a comprehensive approach is presented in this paper for modeling the fuzzy quality concept. Then, motivations and advantages of applying this flexible approach instead of using classical quality are mentioned.

  18. Fuzzy compromise: An effective way to solve hierarchical design problems

    Allen, J. K.; Krishnamachari, R. S.; Masetta, J.; Pearce, D.; Rigby, D.; Mistree, F.

    1990-01-01

    In this paper, we present a method for modeling design problems using a compromise decision support problem (DSP) incorporating the principles embodied in fuzzy set theory. Specifically, the fuzzy compromise decision support problem is used to study hierarchical design problems. This approach has the advantage that although the system modeled has an element of uncertainty associated with it, the solution obtained is crisp and precise. The efficacy of incorporating fuzzy sets into the solution process is discussed in the context of results obtained for a portal frame.

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

    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.

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

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

    2011-01-01

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

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

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

    2011-01-01

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

  2. (L,M-Fuzzy σ-Algebras

    Fu-Gui Shi

    2010-01-01

    Full Text Available The notion of (L,M-fuzzy σ-algebras is introduced in the lattice value fuzzy set theory. It is a generalization of Klement's fuzzy σ-algebras. In our definition of (L,M-fuzzy σ-algebras, each L-fuzzy subset can be regarded as an L-measurable set to some degree.

  3. The first order fuzzy predicate logic (I)

    Sheng, Y.M.

    1986-01-01

    Some analysis tools of fuzzy measures, Sugeno's integrals, etc. are introduced into the semantic of the first order predicate logic to explain the concept of fuzzy quantifiers. The truth value of a fuzzy quantification proposition is represented by Sugeno's integral. With this framework, several important notions of formation rules, fuzzy valutions and fuzzy validity are discussed

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

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

    2013-04-01

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

  5. Data mining in radiology

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

    2014-01-01

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

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

    Williams, G.A.

    1990-01-01

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

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

    Byeongjoon Noh

    2017-11-01

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

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

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

    1976-01-01

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

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

    Chen Hsin-Hsi

    2008-10-01

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

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

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

    2016-08-01

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

  11. Fuzzy efficiency without convexity

    Hougaard, Jens Leth; Balezentis, Tomas

    2014-01-01

    approach builds directly upon the definition of Farrell's indexes of technical efficiency used in crisp FDH. Therefore we do not require the use of fuzzy programming techniques but only utilize ranking probabilities of intervals as well as a related definition of dominance between pairs of intervals. We...

  12. Trust Mines

    The United States and the Navajo Nation entered into settlement agreements that provide funds to conduct investigations and any needed cleanup at 16 of the 46 priority mines, including six mines in the Northern Abandoned Uranium Mine Region.

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

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

    2011-01-01

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

  14. Fuzzy modelling of Atlantic salmon physical habitat

    St-Hilaire, André; Mocq, Julien; Cunjak, Richard

    2015-04-01

    Fish habitat models typically attempt to quantify the amount of available river habitat for a given fish species for various flow and hydraulic conditions. To achieve this, information on the preferred range of values of key physical habitat variables (e.g. water level, velocity, substrate diameter) for the targeted fishs pecies need to be modelled. In this context, we developed several habitat suitability indices sets for three Atlantic salmon life stages (young-of-the-year (YOY), parr, spawning adults) with the help of fuzzy logic modeling. Using the knowledge of twenty-seven experts, from both sides of the Atlantic Ocean, we defined fuzzy sets of four variables (depth, substrate size, velocity and Habitat Suitability Index, or HSI) and associated fuzzy rules. When applied to the Romaine River (Canada), median curves of standardized Weighted Usable Area (WUA) were calculated and a confidence interval was obtained by bootstrap resampling. Despite the large range of WUA covered by the expert WUA curves, confidence intervals were relatively narrow: an average width of 0.095 (on a scale of 0 to 1) for spawning habitat, 0.155 for parr rearing habitat and 0.160 for YOY rearing habitat. When considering an environmental flow value corresponding to 90% of the maximum reached by WUA curve, results seem acceptable for the Romaine River. Generally, this proposed fuzzy logic method seems suitable to model habitat availability for the three life stages, while also providing an estimate of uncertainty in salmon preferences.

  15. Neuro-fuzzy system modeling based on automatic fuzzy clustering

    Yuangang TANG; Fuchun SUN; Zengqi SUN

    2005-01-01

    A neuro-fuzzy system model based on automatic fuzzy clustering is proposed.A hybrid model identification algorithm is also developed to decide the model structure and model parameters.The algorithm mainly includes three parts:1) Automatic fuzzy C-means (AFCM),which is applied to generate fuzzy rules automatically,and then fix on the size of the neuro-fuzzy network,by which the complexity of system design is reducesd greatly at the price of the fitting capability;2) Recursive least square estimation (RLSE).It is used to update the parameters of Takagi-Sugeno model,which is employed to describe the behavior of the system;3) Gradient descent algorithm is also proposed for the fuzzy values according to the back propagation algorithm of neural network.Finally,modeling the dynamical equation of the two-link manipulator with the proposed approach is illustrated to validate the feasibility of the method.

  16. Hierarchical type-2 fuzzy aggregation of fuzzy controllers

    Cervantes, Leticia

    2016-01-01

    This book focuses on the fields of fuzzy logic, granular computing and also considering the control area. These areas can work together to solve various control problems, the idea is that this combination of areas would enable even more complex problem solving and better results. In this book we test the proposed method using two benchmark problems: the total flight control and the problem of water level control for a 3 tank system. When fuzzy logic is used it make it easy to performed the simulations, these fuzzy systems help to model the behavior of a real systems, using the fuzzy systems fuzzy rules are generated and with this can generate the behavior of any variable depending on the inputs and linguistic value. For this reason this work considers the proposed architecture using fuzzy systems and with this improve the behavior of the complex control problems.

  17. Word Similarity from Dictionaries: Inferring Fuzzy Measures from Fuzzy Graphs

    Vicenc Torra

    2008-01-01

    Full Text Available WORD SIMILARITY FROM DICTIONARIES: INFERRING FUZZY MEASURES FROM FUZZY GRAPHS The computation of similarities between words is a basic element of information retrieval systems, when retrieval is not solely based on word matching. In this work we consider a measure between words based on dictionaries. This is achieved assuming that a dictionary is formalized as a fuzzy graph. We show that the approach permits to compute measures not only for pairs of words but for sets of them.

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

    Jun Li

    2010-02-01

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

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

    Jun Li

    2009-12-01

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

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

    2002-01-01

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

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

    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.

  2. Characterizations of intuitionistic fuzzy ideals and filters based on lattice operations

    Soheyb Milles

    2017-11-01

    Full Text Available In a recent paper, Thomas and Nair have introduced the notions of intuitionistic fuzzy ideal and intuitionistic fuzzy filter on a lattice and some basic properties were proved. In this paper, we characterize these notions in terms of the lattice operations and in terms of their associated crisp sets. We introduce the notions of prime intuitionistic fuzzy ideal and filter as interesting kinds, and then we investigate their various characterizations and different properties.

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

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

    1995-01-01

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

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

    Arranz-Gonzalez, J. C.

    2011-07-01

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

  5. Fuzzy control. Fundamentals, stability and design of fuzzy controllers

    Michels, K. [Fichtner GmbH und Co. KG, Stuttgart (Germany); Klawonn, F. [Fachhochschule Braunschweig/Wolfenbuettel (Germany). Fachbereich Informatik; Kruse, R. [Magdeburg Univ. (Germany). Fakultaet Informatik, Abt. Wiss.- und Sprachverarbeitung; Nuernberger, A. (eds.) [California Univ., Berkeley, CA (United States). Computer Science Division

    2006-07-01

    The book provides a critical discussion of fuzzy controllers from the perspective of classical control theory. Special emphases are placed on topics that are of importance for industrial applications, like (self-) tuning of fuzzy controllers, optimisation and stability analysis. The book is written as a textbook for graduate students as well as a comprehensive reference book about fuzzy control for researchers and application engineers. Starting with a detailed introduction to fuzzy systems and control theory the reader is guided to up-to-date research results. (orig.)

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

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

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

  7. Fuzzy pharmacology: theory and applications.

    Sproule, Beth A; Naranjo, Claudio A; Türksen, I Burhan

    2002-09-01

    Fuzzy pharmacology is a term coined to represent the application of fuzzy logic and fuzzy set theory to pharmacological problems. Fuzzy logic is the science of reasoning, thinking and inference that recognizes and uses the real world phenomenon that everything is a matter of degree. It is an extension of binary logic that is able to deal with complex systems because it does not require crisp definitions and distinctions for the system components. In pharmacology, fuzzy modeling has been used for the mechanical control of drug delivery in surgical settings, and work has begun evaluating its use in other pharmacokinetic and pharmacodynamic applications. Fuzzy pharmacology is an emerging field that, based on these initial explorations, warrants further investigation.

  8. Evaluating supplier quality performance using fuzzy analytical hierarchy process

    Ahmad, Nazihah; Kasim, Maznah Mat; Rajoo, Shanmugam Sundram Kalimuthu

    2014-12-01

    Evaluating supplier quality performance is vital in ensuring continuous supply chain improvement, reducing the operational costs and risks towards meeting customer's expectation. This paper aims to illustrate an application of Fuzzy Analytical Hierarchy Process to prioritize the evaluation criteria in a context of automotive manufacturing in Malaysia. Five main criteria were identified which were quality, cost, delivery, customer serviceand technology support. These criteria had been arranged into hierarchical structure and evaluated by an expert. The relative importance of each criteria was determined by using linguistic variables which were represented as triangular fuzzy numbers. The Center of Gravity defuzzification method was used to convert the fuzzy evaluations into their corresponding crisps values. Such fuzzy evaluation can be used as a systematic tool to overcome the uncertainty evaluation of suppliers' performance which usually associated with human being subjective judgments.

  9. Stochastic Optimal Estimation with Fuzzy Random Variables and Fuzzy Kalman Filtering

    FENG Yu-hu

    2005-01-01

    By constructing a mean-square performance index in the case of fuzzy random variable, the optimal estimation theorem for unknown fuzzy state using the fuzzy observation data are given. The state and output of linear discrete-time dynamic fuzzy system with Gaussian noise are Gaussian fuzzy random variable sequences. An approach to fuzzy Kalman filtering is discussed. Fuzzy Kalman filtering contains two parts: a real-valued non-random recurrence equation and the standard Kalman filtering.

  10. Intuitionistic fuzzy aggregation and clustering

    Xu, Zeshui

    2012-01-01

    This book offers a systematic introduction to the clustering algorithms for intuitionistic fuzzy values, the latest research results in intuitionistic fuzzy aggregation techniques, the extended results in interval-valued intuitionistic fuzzy environments, and their applications in multi-attribute decision making, such as supply chain management, military system performance evaluation, project management, venture capital, information system selection, building materials classification, and operational plan assessment, etc.

  11. On the mathematics of fuzziness

    Chulichkov, A.I.; Chulichkova, N.M.; Pyt`ev, Y. P.; Smolnik, L.

    1994-12-31

    The problem of the minimax linear interpretation of stochastic measurements with fuzzy conditions on values of the object`s parameters is considered. The result of a measurement interpretation is the fuzzy element (u, h, alpha, mu(.,.,.)), where u is the object`s parameter estimation, h is the estimation accuracy and alpha is the reliability of interpretation, mu is the characteristic function of a fuzzy element. Reliability is the characteristic of the agreement between fuzzy a priori information and measuring data. The information on the values of the parameters of an object under investigation is interactively submitted to the computer.

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

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

    2016-01-01

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

  13. Fuzzy logic and image processing techniques for the interpretation of seismic data

    Orozco-del-Castillo, M G; Ortiz-Alemán, C; Rodríguez-Castellanos, A; Urrutia-Fucugauchi, J

    2011-01-01

    Since interpretation of seismic data is usually a tedious and repetitive task, the ability to do so automatically or semi-automatically has become an important objective of recent research. We believe that the vagueness and uncertainty in the interpretation process makes fuzzy logic an appropriate tool to deal with seismic data. In this work we developed a semi-automated fuzzy inference system to detect the internal architecture of a mass transport complex (MTC) in seismic images. We propose that the observed characteristics of a MTC can be expressed as fuzzy if-then rules consisting of linguistic values associated with fuzzy membership functions. The constructions of the fuzzy inference system and various image processing techniques are presented. We conclude that this is a well-suited problem for fuzzy logic since the application of the proposed methodology yields a semi-automatically interpreted MTC which closely resembles the MTC from expert manual interpretation

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

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

    2016-04-29

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

  15. A fuzzy method for improving the functionality of search engines based on user's web interactions

    Farzaneh Kabirbeyk

    2015-04-01

    Full Text Available Web mining has been widely used to discover knowledge from various sources in the web. One of the important tools in web mining is mining of web user’s behavior that is considered as a way to discover the potential knowledge of web user’s interaction. Nowadays, Website personalization is regarded as a popular phenomenon among web users and it plays an important role in facilitating user access and provides information of users’ requirements based on their own interests. Extracting important features about web user behavior plays a significant role in web usage mining. Such features are page visit frequency in each session, visit duration, and dates of visiting a certain pages. This paper presents a method to predict user’s interest and to propose a list of pages based on their interests by identifying user’s behavior based on fuzzy techniques called fuzzy clustering method. Due to the user’s different interests and use of one or more interest at a time, user’s interest may belong to several clusters and fuzzy clustering provide a possible overlap. Using the resulted cluster helps extract fuzzy rules. This helps detecting user’s movement pattern and using neural network a list of suggested pages to the users is provided.

  16. Fuzzy vulnerability matrix

    Baron, Jorge H.; Rivera, S.S.

    2000-01-01

    The so-called vulnerability matrix is used in the evaluation part of the probabilistic safety assessment for a nuclear power plant, during the containment event trees calculations. This matrix is established from what is knows as Numerical Categories for Engineering Judgement. This matrix is usually established with numerical values obtained with traditional arithmetic using the set theory. The representation of this matrix with fuzzy numbers is much more adequate, due to the fact that the Numerical Categories for Engineering Judgement are better represented with linguistic variables, such as 'highly probable', 'probable', 'impossible', etc. In the present paper a methodology to obtain a Fuzzy Vulnerability Matrix is presented, starting from the recommendations on the Numerical Categories for Engineering Judgement. (author)

  17. Spinning the fuzzy sphere

    Berenstein, David; Dzienkowski, Eric; Lashof-Regas, Robin

    2015-01-01

    We construct various exact analytical solutions of the SO(3) BMN matrix model that correspond to rotating fuzzy spheres and rotating fuzzy tori. These are also solutions of Yang Mills theory compactified on a sphere times time and they are also translationally invariant solutions of the N=1"∗ field theory with a non-trivial charge density. The solutions we construct have a ℤ_N symmetry, where N is the rank of the matrices. After an appropriate ansatz, we reduce the problem to solving a set of polynomial equations in 2N real variables. These equations have a discrete set of solutions for each value of the angular momentum. We study the phase structure of the solutions for various values of N. Also the continuum limit where N→∞, where the problem reduces to finding periodic solutions of a set of coupled differential equations. We also study the topology change transition from the sphere to the torus.

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

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

    2016-01-01

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

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

    Boudellioua, Imene

    2016-07-08

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

  20. Radial Fuzzy Systems

    Coufal, David

    2017-01-01

    Roč. 319, 15 July (2017), s. 1-27 ISSN 0165-0114 R&D Projects: GA MŠk(CZ) LD13002 Institutional support: RVO:67985807 Keywords : fuzzy systems * radial functions * coherence Subject RIV: BA - General Mathematics OBOR OECD: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8) Impact factor: 2.718, year: 2016

  1. Prediksi Kelulusan Mata Kuliah Menggunakan Hybrid Fuzzy Inference System

    Abidatul Izzah

    2016-07-01

    Full Text Available AbstrakPerguruan Tinggi merupakan salah satu institusi yang menyimpan data yang sangat informatif jika diolah secara baik. Prediksi kelulusan mahasiswa merupakan kasus di Perguruan Tinggi yang cukup banyak diteliti. Dengan mengetahui prediksi status kelulusan mahasiswa di tengah semester, dosen dapat mengantisipasi atau memberi perhatian khusus pada siswa yang diprediksi tidak lulus. Metode yang digunakan sangat bervariatif termasuk metode Fuzzy Inference System (FIS. Namun dalam implementasinya, proses pembangkitan rule fuzzy sering dilakukan secara random atau berdasarkan pemahaman pakar sehingga tidak merepresentasikan sebaran data. Oleh karena itu, dalam penelitian ini digunakan teknik Decision Tree (DT untuk membangkitkan rule. Dari uraian tersebut, penelitian bertujuan untuk memprediksi kelulusan mata kuliah menggunakan hybrid FIS dan DT. Data yang digunakan dalam penelitian ini adalah data nilai Posttest, Tugas, Kuis, dan UTS dari 106 mahasiswa Politeknik Kediri pengikut mata kuliah Algoritma dan Struktur Data. Penelitian ini diawali dari membangkitkan 5 rule yang selanjutnya digunakan dalam inferensi. Tahap selanjutnya adalah implementasi FIS dengan tahapan fuzzifikasi, inferensi, dan defuzzifikasi. Hasil yang diperoleh adalah akurasi, sensitivitas, dan spesifisitas  masing-masing adalah 94.33%, 96.55%, dan 84.21%.Kata kunci: Decision Tree, Educational Data Mining, Fuzzy Inference System, Prediksi. AbstractCollege is an institution that holds very informative data if it mined properly. Prediction about student’s graduation is a common case that many discussed. Having the predictions of student’s graduation in the middle semester, lecturer will anticipate or give some special attention to students who would be not passed. The method used to prediction is very varied including Fuzzy Inference System (FIS. However, fuzzy rule process is often generated randomly or based on knowledge experts that not represent the data distribution

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

    Isinkaye, O. [Ekiti State University (Nigeria)

    2014-07-01

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

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

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

    2001-07-01

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

  4. Fuzzy Clustering Methods and their Application to Fuzzy Modeling

    Kroszynski, Uri; Zhou, Jianjun

    1999-01-01

    Fuzzy modeling techniques based upon the analysis of measured input/output data sets result in a set of rules that allow to predict system outputs from given inputs. Fuzzy clustering methods for system modeling and identification result in relatively small rule-bases, allowing fast, yet accurate....... An illustrative synthetic example is analyzed, and prediction accuracy measures are compared between the different variants...

  5. Process mining : overview and opportunities

    Aalst, van der W.M.P.

    2012-01-01

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

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

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

    2015-12-01

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

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

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

    2013-01-01

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

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

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

    2015-01-01

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

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

    Микола Тихонович Фісун

    2015-06-01

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

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

    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.

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

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

    2013-01-01

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

  12. Fuzzy linguistic model for interpolation

    Abbasbandy, S.; Adabitabar Firozja, M.

    2007-01-01

    In this paper, a fuzzy method for interpolating of smooth curves was represented. We present a novel approach to interpolate real data by applying the universal approximation method. In proposed method, fuzzy linguistic model (FLM) applied as universal approximation for any nonlinear continuous function. Finally, we give some numerical examples and compare the proposed method with spline method

  13. Fuzzy Logic in Medicine and Bioinformatics

    Angela Torres

    2006-01-01

    Full Text Available The purpose of this paper is to present a general view of the current applications of fuzzy logic in medicine and bioinformatics. We particularly review the medical literature using fuzzy logic. We then recall the geometrical interpretation of fuzzy sets as points in a fuzzy hypercube and present two concrete illustrations in medicine (drug addictions and in bioinformatics (comparison of genomes.

  14. Algebraic Aspects of Families of Fuzzy Languages

    Asveld, P.R.J.; Heylen, Dirk K.J.; Nijholt, Antinus; Scollo, Giuseppe

    2000-01-01

    We study operations on fuzzy languages such as union, concatenation,Kleene $\\star$, intersection with regular fuzzy languages, and several kinds of (iterated) fuzzy substitution. Then we consider families of fuzzy languages, closed under a fixed collection of these operations, which results in the

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

    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

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

    Lee, Hyeonjeong; Shin, Miyoung

    2017-01-01

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

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

    McAdoo, Mitchell A.; Kozar, Mark D.

    2017-11-14

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

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

    NONE

    1998-12-31

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

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

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

    2005-01-01

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

  20. Fuzzy control in environmental engineering

    Chmielowski, Wojciech Z

    2016-01-01

    This book is intended for engineers, technicians and people who plan to use fuzzy control in more or less developed and advanced control systems for manufacturing processes, or directly for executive equipment. Assuming that the reader possesses elementary knowledge regarding fuzzy sets and fuzzy control, by way of a reminder, the first parts of the book contain a reminder of the theoretical foundations as well as a description of the tools to be found in the Matlab/Simulink environment in the form of a toolbox. The major part of the book presents applications for fuzzy controllers in control systems for various manufacturing and engineering processes. It presents seven processes and problems which have been programmed using fuzzy controllers. The issues discussed concern the field of Environmental Engineering. Examples are the control of a flood wave passing through a hypothetical, and then the real Dobczyce reservoir in the Raba River, which is located in the upper Vistula River basin in Southern Poland, th...

  1. Design of interpretable fuzzy systems

    Cpałka, Krzysztof

    2017-01-01

    This book shows that the term “interpretability” goes far beyond the concept of readability of a fuzzy set and fuzzy rules. It focuses on novel and precise operators of aggregation, inference, and defuzzification leading to flexible Mamdani-type and logical-type systems that can achieve the required accuracy using a less complex rule base. The individual chapters describe various aspects of interpretability, including appropriate selection of the structure of a fuzzy system, focusing on improving the interpretability of fuzzy systems designed using both gradient-learning and evolutionary algorithms. It also demonstrates how to eliminate various system components, such as inputs, rules and fuzzy sets, whose reduction does not adversely affect system accuracy. It illustrates the performance of the developed algorithms and methods with commonly used benchmarks. The book provides valuable tools for possible applications in many fields including expert systems, automatic control and robotics.

  2. On Intuitionistic Fuzzy Sets Theory

    Atanassov, Krassimir T

    2012-01-01

    This book aims to be a  comprehensive and accurate survey of state-of-art research on intuitionistic fuzzy sets theory and could be considered a continuation and extension of the author´s previous book on Intuitionistic Fuzzy Sets, published by Springer in 1999 (Atanassov, Krassimir T., Intuitionistic Fuzzy Sets, Studies in Fuzziness and soft computing, ISBN 978-3-7908-1228-2, 1999). Since the aforementioned  book has appeared, the research activity of the author within the area of intuitionistic fuzzy sets has been expanding into many directions. The results of the author´s most recent work covering the past 12 years as well as the newest general ideas and open problems in this field have been therefore collected in this new book.

  3. Safety critical application of fuzzy control

    Schildt, G.H.

    1995-01-01

    After an introduction into safety terms a short description of fuzzy logic will be given. Especially, for safety critical applications of fuzzy controllers a possible controller structure will be described. The following items will be discussed: Configuration of fuzzy controllers, design aspects like fuzzfiication, inference strategies, defuzzification and types of membership functions. As an example a typical fuzzy rule set will be presented. Especially, real-time behaviour a fuzzy controllers is mentioned. An example of fuzzy controlling for temperature control purpose within a nuclear reactor together with membership functions and inference strategy of such a fuzzy controller will be presented. (author). 4 refs, 17 figs

  4. Image matching navigation based on fuzzy information

    田玉龙; 吴伟仁; 田金文; 柳健

    2003-01-01

    In conventional image matching methods, the image matching process is mostly based on image statistic information. One aspect neglected by all these methods is that there is much fuzzy information contained in these images. A new fuzzy matching algorithm based on fuzzy similarity for navigation is presented in this paper. Because the fuzzy theory is of the ability of making good description of the fuzzy information contained in images, the image matching method based on fuzzy similarity would look forward to producing good performance results. Experimental results using matching algorithm based on fuzzy information also demonstrate its reliability and practicability.

  5. Radiation protection and fuzzy set theory

    Nishiwaki, Y.

    1993-01-01

    In radiation protection we encounter a variety of sources of uncertainties which are due to fuzziness in our cognition or perception of objects. For systematic treatment of this type of uncertainty, the concepts of fuzzy sets or fuzzy measures could be applied to construct system models, which may take into consideration both subjective or intrinsic fuzziness and objective or extrinsic fuzziness. The theory of fuzzy sets and fuzzy measures is still in a developing stage, but its concept may be applied to various problems of subjective perception of risk, nuclear safety, radiation protection and also to the problems of man-machine interface and human factor engineering or ergonomic

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

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

    2015-07-01

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

  7. Detecting a Weak Association by Testing its Multiple Perturbations: a Data Mining Approach

    Lo, Min-Tzu; Lee, Wen-Chung

    2014-05-01

    Many risk factors/interventions in epidemiologic/biomedical studies are of minuscule effects. To detect such weak associations, one needs a study with a very large sample size (the number of subjects, n). The n of a study can be increased but unfortunately only to an extent. Here, we propose a novel method which hinges on increasing sample size in a different direction-the total number of variables (p). We construct a p-based `multiple perturbation test', and conduct power calculations and computer simulations to show that it can achieve a very high power to detect weak associations when p can be made very large. As a demonstration, we apply the method to analyze a genome-wide association study on age-related macular degeneration and identify two novel genetic variants that are significantly associated with the disease. The p-based method may set a stage for a new paradigm of statistical tests.

  8. High resolution microgravity investigations for the detection and characterisation of subsidence associated with abandoned, coal, chalk and salt mines

    Styles, P.; Toon, S.; Branston, M.; England, R. [Keele Univ., Applied And Environmental Geophysics Group, School of Physical and Geographical Sciences (United Kingdom); Thomas, E.; Mcgrath, R. [Geotechnology, Neath (United Kingdom)

    2005-07-01

    The closure and decay of industrial activity involving mining has scarred the landscape of urban areas and geo-hazards posed by subsurface cavities are ubiquitous throughout Europe. Features of concern consist of natural solution cavities (e.g. swallow holes and sinkholes in limestone gypsum and chalk) and man-made cavities (mine workings, shafts) in a great variety of post mining environments, including coal, salt, gypsum, anhydrite, tin and chalk. These problems restrict land utilisation, hinder regeneration, pose a threat to life, seriously damage property and services and blight property values. This paper outlines the application of microgravity techniques to characterise abandoned mining hazard in case studies from Coal, Chalk and Salt Mining environments in the UK. (authors)

  9. High resolution microgravity investigations for the detection and characterisation of subsidence associated with abandoned, coal, chalk and salt mines

    Styles, P.; Toon, S.; Branston, M.; England, R.; Thomas, E.; Mcgrath, R.

    2005-01-01

    The closure and decay of industrial activity involving mining has scarred the landscape of urban areas and geo-hazards posed by subsurface cavities are ubiquitous throughout Europe. Features of concern consist of natural solution cavities (e.g. swallow holes and sinkholes in limestone gypsum and chalk) and man-made cavities (mine workings, shafts) in a great variety of post mining environments, including coal, salt, gypsum, anhydrite, tin and chalk. These problems restrict land utilisation, hinder regeneration, pose a threat to life, seriously damage property and services and blight property values. This paper outlines the application of microgravity techniques to characterise abandoned mining hazard in case studies from Coal, Chalk and Salt Mining environments in the UK. (authors)

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

    Gabriele Prati

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

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

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

    Gene Wiki Plus (GeneWiki+) and the Online Mendelian Inheritance in Man (OMIM) are publicly available resources for sharing information about disease-gene and gene-SNP associations in humans. While immensely useful to the scientific community, both resources are manually curated, thereby making the data entry and publication process time-consuming, and to some degree, error-prone. To this end, this study investigates Semantic Web technologies to validate existing and potentially discover new genotype-phenotype associations in GWP and OMIM. In particular, we demonstrate the applicability of SPARQL queries for identifying associations not explicitly stated for commonly occurring chronic diseases in GWP and OMIM, and report our preliminary findings for coverage, completeness, and validity of the associations. Our results highlight the benefits of Semantic Web querying technology to validate existing disease-gene associations as well as identify novel associations although further evaluation and analysis is required before such information can be applied and used effectively. PMID:24303249

  12. Hierarchical Fuzzy Feature Similarity Combination for Presentation Slide Retrieval

    A. Kushki

    2009-02-01

    Full Text Available This paper proposes a novel XML-based system for retrieval of presentation slides to address the growing data mining needs in presentation archives for educational and scholarly settings. In particular, contextual information, such as structural and formatting features, is extracted from the open format XML representation of presentation slides. In response to a textual user query, each extracted feature is used to compute a fuzzy relevance score for each slide in the database. The fuzzy scores from the various features are then combined through a hierarchical scheme to generate a single relevance score per slide. Various fusion operators and their properties are examined with respect to their effect on retrieval performance. Experimental results indicate a significant increase in retrieval performance measured in terms of precision-recall. The improvements are attributed to both the incorporation of the contextual features and the hierarchical feature combination scheme.

  13. Mining potential biomarkers associated with space flight in Caenorhabditis elegans experienced Shenzhou-8 mission with multiple feature selection techniques

    Zhao, Lei; Gao, Ying; Mi, Dong; Sun, Yeqing

    2016-01-01

    Highlights: • A combined algorithm is proposed to mine biomarkers of spaceflight in C. elegans. • This algorithm makes the feature selection more reliable and robust. • Apply this algorithm to predict 17 positive biomarkers to space environment stress. • The strategy can be used as a general method to select important features. - Abstract: To identify the potential biomarkers associated with space flight, a combined algorithm, which integrates the feature selection techniques, was used to deal with the microarray datasets of Caenorhabditis elegans obtained in the Shenzhou-8 mission. Compared with the ground control treatment, a total of 86 differentially expressed (DE) genes in responses to space synthetic environment or space radiation environment were identified by two filter methods. And then the top 30 ranking genes were selected by the random forest algorithm. Gene Ontology annotation and functional enrichment analyses showed that these genes were mainly associated with metabolism process. Furthermore, clustering analysis showed that 17 genes among these are positive, including 9 for space synthetic environment and 8 for space radiation environment only. These genes could be used as the biomarkers to reflect the space environment stresses. In addition, we also found that microgravity is the main stress factor to change the expression patterns of biomarkers for the short-duration spaceflight.

  14. Mining potential biomarkers associated with space flight in Caenorhabditis elegans experienced Shenzhou-8 mission with multiple feature selection techniques

    Zhao, Lei [Institute of Environmental Systems Biology, College of Environmental Science and Engineering, Dalian Maritime University, Dalian 116026 (China); Gao, Ying [Center of Medical Physics and Technology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Shushanhu Road 350, Hefei 230031 (China); Mi, Dong, E-mail: mid@dlmu.edu.cn [Department of Physics, Dalian Maritime University, Dalian 116026 (China); Sun, Yeqing, E-mail: yqsun@dlmu.edu.cn [Institute of Environmental Systems Biology, College of Environmental Science and Engineering, Dalian Maritime University, Dalian 116026 (China)

    2016-09-15

    Highlights: • A combined algorithm is proposed to mine biomarkers of spaceflight in C. elegans. • This algorithm makes the feature selection more reliable and robust. • Apply this algorithm to predict 17 positive biomarkers to space environment stress. • The strategy can be used as a general method to select important features. - Abstract: To identify the potential biomarkers associated with space flight, a combined algorithm, which integrates the feature selection techniques, was used to deal with the microarray datasets of Caenorhabditis elegans obtained in the Shenzhou-8 mission. Compared with the ground control treatment, a total of 86 differentially expressed (DE) genes in responses to space synthetic environment or space radiation environment were identified by two filter methods. And then the top 30 ranking genes were selected by the random forest algorithm. Gene Ontology annotation and functional enrichment analyses showed that these genes were mainly associated with metabolism process. Furthermore, clustering analysis showed that 17 genes among these are positive, including 9 for space synthetic environment and 8 for space radiation environment only. These genes could be used as the biomarkers to reflect the space environment stresses. In addition, we also found that microgravity is the main stress factor to change the expression patterns of biomarkers for the short-duration spaceflight.

  15. Human exposure and risk assessment associated with mercury contamination in artisanal gold mining areas in the Brazilian Amazon.

    Castilhos, Zuleica; Rodrigues-Filho, Saulo; Cesar, Ricardo; Rodrigues, Ana Paula; Villas-Bôas, Roberto; de Jesus, Iracina; Lima, Marcelo; Faial, Kleber; Miranda, Antônio; Brabo, Edilson; Beinhoff, Christian; Santos, Elisabeth

    2015-08-01

    Mercury (Hg) contamination is an issue of concern in the Amazon region due to potential health effects associated with Hg exposure in artisanal gold mining areas. The study presents a human health risk assessment associated with Hg vapor inhalation and MeHg-contaminated fish ingestion, as well as Hg determination in urine, blood, and hair, of human populations (about 325 miners and 321 non-miners) from two gold mining areas in the Brazilian Amazon (São Chico and Creporizinho, Pará State). In São Chico and Creporizinho, 73 fish specimens of 13 freshwater species, and 161 specimens of 11 species, were collected for total Hg determination, respectively. The hazard quotient (HQ) is a risk indicator which defines the ratio of the exposure level and the toxicological reference dose and was applied to determine the threat of MeHg exposure. The mean Hg concentrations in fish from São Chico and Creporizinho were 0.83 ± 0.43 and 0.36 ± 0.33 μg/g, respectively. More than 60 and 22 % of fish collected in São Chico and Creporizinho, respectively, were above the Hg limit (0.5 μg/g) recommended by WHO for human consumption. For all sampling sites, HQ resulted from 1.5 to 28.5, except for the reference area. In Creporizinho, the values of HQ are close to 2 for most sites, whereas in São Chico, there is a hot spot of MeHg contamination in fish (A2-São Chico Reservoir) with the highest risk level (HQ = 28) associated with its human consumption. Mean Hg concentrations in urine, blood, and hair samples indicated that the miners group (in São Chico: urine = 17.37 μg/L; blood = 27.74 μg/L; hair = 4.50 μg/g and in Creporizinho: urine = 13.75 μg/L; blood = 25.23 μg/L; hair: 4.58 μg/g) was more exposed to mercury compared to non-miners (in São Chico: urine = 5.73 μg/L; blood = 16.50 μg/L; hair = 3.16 μg/g and in Creporizinho: urine = 3.91 μg/L; blood = 21.04 μg/L, hair = 1.88 μg/g). These high Hg levels (found

  16. Modeling and mining term association for improving biomedical information retrieval performance.

    Hu, Qinmin; Huang, Jimmy Xiangji; Hu, Xiaohua

    2012-06-11

    The growth of the biomedical information requires most information retrieval systems to provide short and specific answers in response to complex user queries. Semantic information in the form of free text that is structured in a way makes it straightforward for humans to read but more difficult for computers to interpret automatically and search efficiently. One of the reasons is that most traditional information retrieval models assume terms are conditionally independent given a document/passage. Therefore, we are motivated to consider term associations within different contexts to help the models understand semantic information and use it for improving biomedical information retrieval performance. We propose a term association approach to discover term associations among the keywords from a query. The experiments are conducted on the TREC 2004-2007 Genomics data sets and the TREC 2004 HARD data set. The proposed approach is promising and achieves superiority over the baselines and the GSP results. The parameter settings and different indices are investigated that the sentence-based index produces the best results in terms of the document-level, the word-based index for the best results in terms of the passage-level and the paragraph-based index for the best results in terms of the passage2-level. Furthermore, the best term association results always come from the best baseline. The tuning number k in the proposed recursive re-ranking algorithm is discussed and locally optimized to be 10. First, modelling term association for improving biomedical information retrieval using factor analysis, is one of the major contributions in our work. Second, the experiments confirm that term association considering co-occurrence and dependency among the keywords can produce better results than the baselines treating the keywords independently. Third, the baselines are re-ranked according to the importance and reliance of latent factors behind term associations. These latent

  17. Mine drivage in hydraulic mines

    Ehkber, B Ya

    1983-09-01

    From 20 to 25% of labor cost in hydraulic coal mines falls on mine drivage. Range of mine drivage is high due to the large number of shortwalls mined by hydraulic monitors. Reducing mining cost in hydraulic mines depends on lowering drivage cost by use of new drivage systems or by increasing efficiency of drivage systems used at present. The following drivage methods used in hydraulic mines are compared: heading machines with hydraulic haulage of cut rocks and coal, hydraulic monitors with hydraulic haulage, drilling and blasting with hydraulic haulage of blasted rocks. Mining and geologic conditions which influence selection of the optimum mine drivage system are analyzed. Standardized cross sections of mine roadways driven by the 3 methods are shown in schemes. Support systems used in mine roadways are compared: timber supports, roof bolts, roof bolts with steel elements, and roadways driven in rocks without a support system. Heading machines (K-56MG, GPKG, 4PU, PK-3M) and hydraulic monitors (GMDTs-3M, 12GD-2) used for mine drivage are described. Data on mine drivage in hydraulic coal mines in the Kuzbass are discussed. From 40 to 46% of roadways are driven by heading machines with hydraulic haulage and from 12 to 15% by hydraulic monitors with hydraulic haulage.

  18. Fuzzy portfolio model with fuzzy-input return rates and fuzzy-output proportions

    Tsaur, Ruey-Chyn

    2015-02-01

    In the finance market, a short-term investment strategy is usually applied in portfolio selection in order to reduce investment risk; however, the economy is uncertain and the investment period is short. Further, an investor has incomplete information for selecting a portfolio with crisp proportions for each chosen security. In this paper we present a new method of constructing fuzzy portfolio model for the parameters of fuzzy-input return rates and fuzzy-output proportions, based on possibilistic mean-standard deviation models. Furthermore, we consider both excess or shortage of investment in different economic periods by using fuzzy constraint for the sum of the fuzzy proportions, and we also refer to risks of securities investment and vagueness of incomplete information during the period of depression economics for the portfolio selection. Finally, we present a numerical example of a portfolio selection problem to illustrate the proposed model and a sensitivity analysis is realised based on the results.

  19. Improvement of Fuzzy Image Contrast Enhancement Using Simulated Ergodic Fuzzy Markov Chains

    Behrouz Fathi-Vajargah

    2014-01-01

    Full Text Available This paper presents a novel fuzzy enhancement technique using simulated ergodic fuzzy Markov chains for low contrast brain magnetic resonance imaging (MRI. The fuzzy image contrast enhancement is proposed by weighted fuzzy expected value. The membership values are then modified to enhance the image using ergodic fuzzy Markov chains. The qualitative performance of the proposed method is compared to another method in which ergodic fuzzy Markov chains are not considered. The proposed method produces better quality image.

  20. The World of Combinatorial Fuzzy Problems and the Efficiency of Fuzzy Approximation Algorithms

    Yamakami, Tomoyuki

    2015-01-01

    We re-examine a practical aspect of combinatorial fuzzy problems of various types, including search, counting, optimization, and decision problems. We are focused only on those fuzzy problems that take series of fuzzy input objects and produce fuzzy values. To solve such problems efficiently, we design fast fuzzy algorithms, which are modeled by polynomial-time deterministic fuzzy Turing machines equipped with read-only auxiliary tapes and write-only output tapes and also modeled by polynomia...

  1. Data mining theories, algorithms, and examples

    Ye, Nong

    2013-01-01

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

  2. AprioriGWAS, a new pattern mining strategy for detecting genetic variants associated with disease through interaction effects.

    Zhang, Qingrun; Long, Quan; Ott, Jurg

    2014-06-01

    Identifying gene-gene interaction is a hot topic in genome wide association studies. Two fundamental challenges are: (1) how to smartly identify combinations of variants that may be associated with the trait from astronomical number of all possible combinations; and (2) how to test epistatic interaction when all potential combinations are available. We developed AprioriGWAS, which brings two innovations. (1) Based on Apriori, a successful method in field of Frequent Itemset Mining (FIM) in which a pattern growth strategy is leveraged to effectively and accurately reduce search space, AprioriGWAS can efficiently identify genetically associated genotype patterns. (2) To test the hypotheses of epistasis, we adopt a new conditional permutation procedure to obtain reliable statistical inference of Pearson's chi-square test for the [Formula: see text] contingency table generated by associated variants. By applying AprioriGWAS to age-related macular degeneration (AMD) data, we found that: (1) angiopoietin 1 (ANGPT1) and four retinal genes interact with Complement Factor H (CFH). (2) GO term "glycosaminoglycan biosynthetic process" was enriched in AMD interacting genes. The epistatic interactions newly found by AprioriGWAS on AMD data are likely true interactions, since genes interacting with CFH are retinal genes, and GO term enrichment also verified that interaction between glycosaminoglycans (GAGs) and CFH plays an important role in disease pathology of AMD. By applying AprioriGWAS on Bipolar disorder in WTCCC data, we found variants without marginal effect show significant interactions. For example, multiple-SNP genotype patterns inside gene GABRB2 and GRIA1 (AMPA subunit 1 receptor gene). AMPARs are found in many parts of the brain and are the most commonly found receptor in the nervous system. The GABRB2 mediates the fastest inhibitory synaptic transmission in the central nervous system. GRIA1 and GABRB2 are relevant to mental disorders supported by multiple

  3. The South African mining industry

    Langton, G.

    1982-01-01

    This paper covers six of the many mining and associated developments in South Africa. These are: (1) Deep level gold mining at Western Deep Levels Limited - (2) Palabora Mining Company Limited - SA's unique copper mine - (3) Production of steel and vanadium-rich slag at Highveld Steel and Vanadium Corporation - (4) Coal mining at Kriel and Kleinkopje Collieries - (5) A mass mining system for use below the Gabbro Sill at Premier Diamond Mine - (6) Uranium production - joint metallurgical scheme- Orange Free State Gold Mines. - For publication in this journal the original paper has been summarised. Should any reader wish to have the full text in English he should write to the author at the address below. (orig.) [de

  4. Two non-synonymous markers in PTPN21, identified by genome-wide association study data-mining and replication, are associated with schizophrenia.

    Chen, Jingchun

    2011-09-01

    We conducted data-mining analyses of genome wide association (GWA) studies of the CATIE and MGS-GAIN datasets, and found 13 markers in the two physically linked genes, PTPN21 and EML5, showing nominally significant association with schizophrenia. Linkage disequilibrium (LD) analysis indicated that all 7 markers from PTPN21 shared high LD (r(2)>0.8), including rs2274736 and rs2401751, the two non-synonymous markers with the most significant association signals (rs2401751, P=1.10 × 10(-3) and rs2274736, P=1.21 × 10(-3)). In a meta-analysis of all 13 replication datasets with a total of 13,940 subjects, we found that the two non-synonymous markers are significantly associated with schizophrenia (rs2274736, OR=0.92, 95% CI: 0.86-0.97, P=5.45 × 10(-3) and rs2401751, OR=0.92, 95% CI: 0.86-0.97, P=5.29 × 10(-3)). One SNP (rs7147796) in EML5 is also significantly associated with the disease (OR=1.08, 95% CI: 1.02-1.14, P=6.43 × 10(-3)). These 3 markers remain significant after Bonferroni correction. Furthermore, haplotype conditioned analyses indicated that the association signals observed between rs2274736\\/rs2401751 and rs7147796 are statistically independent. Given the results that 2 non-synonymous markers in PTPN21 are associated with schizophrenia, further investigation of this locus is warranted.

  5. Towards a database for genotype-phenotype association research: mining data from encyclopaedia

    Pajić, V.S.; Pavlović-Lažetić, G.M.; Beljanski, M.V.; Brandt, B.W.; Pajić, M.B.

    2013-01-01

    To associate phenotypic characteristics of an organism to molecules encoded by its genome, there is a need for well-structured genotype and phenotype data. We use a novel method for extracting data on phenotype and genotype characteristics of microorganisms from text. As a resource, we use an

  6. Canadian Nuclear Association brief to the standing committee on Energy, Mines and Resources

    NONE

    1991-10-01

    The Canadian Nuclear Association outlines points on electricity demand, environmental impact of electricity production, Canada`s nuclear technology and uranium deposits. Several recommendations are discussed that promote the Canadian nuclear industry and outline issues related to greenhouse gas emmisions, nuclear waste containment, funding of R and D and outlines the need for improving the environmental assessment approval processes.

  7. Canadian Nuclear Association brief to the standing committee on Energy, Mines and Resources

    1991-10-01

    The Canadian Nuclear Association outlines points on electricity demand, environmental impact of electricity production, Canada's nuclear technology and uranium deposits. Several recommendations are discussed that promote the Canadian nuclear industry and outline issues related to greenhouse gas emmisions, nuclear waste containment, funding of R and D and outlines the need for improving the environmental assessment approval processes

  8. Web Mining

    Fürnkranz, Johannes

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

  9. Assessment of radioactivity associated with a low ore grade open cast mine at Banduhurang, Jharkhand, India and estimation of occupational exposure to the miners

    Rana, B.K.; Shukla, A.K.; Topno, R.; Tripathi, R.M.; Puranik, V.D.

    2010-01-01

    The study summarizes radiological characteristics of Banduhurang open cast mine which includes qualitative and quantitative behavior of 222 Rn concentration, external gamma radiation level over the mine pit as well as in its adjoining environment, long-lived alpha (LLα) activity concentration associated with the respirable size of ore dust and assessment of dose to the mine workers in 2006-2008. The investigations reveal that geometric means (χg) of measured radon concentration were 36.39, 38.69, 26.64 and 24 Bq m -3 with respective geometric standard deviations (σg) were 1.52, 1.55, 1.36 and 1.68 Bq m -3 and χg of gamma absorbed dose rates were 0.54, 0.64, 0. 45 and 0.15 μGy h -1 with respective σg were 1.63, 1.53, 1.52 and 1.72 μGy h -1 over the mine pit, ore yard, waste yard and in the surrounding environment within a 10 km radius to the mine, respectively. The χg of LLα activity was observed to be 16 mBq m-3 with σg of 1.9 mBq m -3 . The annual mean effective dose equivalent received by the member radiation workers of Banduhurang mine was estimated to 1.41 mSv y -1 , which is about 7% of the prescribed dose limits of 20 mSv y -1 . (author)

  10. Collaborative Data Mining Tool for Education

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

    2009-01-01

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

  11. Text Mining.

    Trybula, Walter J.

    1999-01-01

    Reviews the state of research in text mining, focusing on newer developments. The intent is to describe the disparate investigations currently included under the term text mining and provide a cohesive structure for these efforts. A summary of research identifies key organizations responsible for pushing the development of text mining. A section…

  12. Surface mining

    Robert Leopold; Bruce Rowland; Reed Stalder

    1979-01-01

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

  13. Uranium mining

    Lange, G.

    1975-01-01

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

  14. Detection of antipersonnel (AP) mines using mechatronics approach

    Shahri, Ali M.; Naghdy, Fazel

    1998-09-01

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

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

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

    2018-04-01

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

  16. DESTAF: A database of text-mined associations for reproductive toxins potentially affecting human fertility

    Dawe, Adam Sean; Radovanovic, Aleksandar; Kaur, Mandeep; Sagar, Sunil; Seshadri, Sundararajan Vijayaraghava; Schaefer, Ulf; Kamau, Allan; Christoffels, Alan G.; Bajic, Vladimir B.

    2012-01-01

    The Dragon Exploration System for Toxicants and Fertility (DESTAF) is a publicly available resource which enables researchers to efficiently explore both known and potentially novel information and associations in the field of reproductive toxicology. To create DESTAF we used data from the literature (including over 10. 500 PubMed abstracts), several publicly available biomedical repositories, and specialized, curated dictionaries. DESTAF has an interface designed to facilitate rapid assessment of the key associations between relevant concepts, allowing for a more in-depth exploration of information based on different gene/protein-, enzyme/metabolite-, toxin/chemical-, disease- or anatomically centric perspectives. As a special feature, DESTAF allows for the creation and initial testing of potentially new association hypotheses that suggest links between biological entities identified through the database.DESTAF, along with a PDF manual, can be found at http://cbrc.kaust.edu.sa/destaf. It is free to academic and non-commercial users and will be updated quarterly. © 2011 Elsevier Inc.

  17. Type-2 fuzzy granular models

    Sanchez, Mauricio A; Castro, Juan R

    2017-01-01

    In this book, a series of granular algorithms are proposed. A nature inspired granular algorithm based on Newtonian gravitational forces is proposed. A series of methods for the formation of higher-type information granules represented by Interval Type-2 Fuzzy Sets are also shown, via multiple approaches, such as Coefficient of Variation, principle of justifiable granularity, uncertainty-based information concept, and numerical evidence based. And a fuzzy granular application comparison is given as to demonstrate the differences in how uncertainty affects the performance of fuzzy information granules.

  18. Fuzzy resource optimization for safeguards

    Zardecki, A.; Markin, J.T.

    1991-01-01

    Authorization, enforcement, and verification -- three key functions of safeguards systems -- form the basis of a hierarchical description of the system risk. When formulated in terms of linguistic rather than numeric attributes, the risk can be computed through an algorithm based on the notion of fuzzy sets. Similarly, this formulation allows one to analyze the optimal resource allocation by maximizing the overall detection probability, regarded as a linguistic variable. After summarizing the necessary elements of the fuzzy sets theory, we outline the basic algorithm. This is followed by a sample computation of the fuzzy optimization. 10 refs., 1 tab

  19. Fuzzy improvement of the SQL

    Hudec Miroslav

    2011-01-01

    Full Text Available Structured Query Language (SQL is used to obtain data from relational databases. Fuzzy improvement of SQL queries has advantages in cases when the user cannot unambiguously define selection criteria or when the user wants to examine data that almost meet the given criteria. In this paper we examine a realization of the fuzzy querying concept. For this purposes the fuzzy generalized logical condition for the WHERE part of the SQL is created. It allows users to create queries by linguistic terms. The proposed model is an extension of the SQL so that no modification inside databases has to be undertaken.

  20. Fuzzy expert systems using CLIPS

    Le, Thach C.

    1994-01-01

    This paper describes a CLIPS-based fuzzy expert system development environment called FCLIPS and illustrates its application to the simulated cart-pole balancing problem. FCLIPS is a straightforward extension of CLIPS without any alteration to the CLIPS internal structures. It makes use of the object-oriented and module features in CLIPS version 6.0 for the implementation of fuzzy logic concepts. Systems of varying degrees of mixed Boolean and fuzzy rules can be implemented in CLIPS. Design and implementation issues of FCLIPS will also be discussed.

  1. Evaluating the role of vegetation on the transport of contaminants associated with a mine tailing using the Phyto-DSS

    Cano-Resendiz, Omar; Rosa, Guadalupe de la; Cruz-Jimenez, Gustavo; Gardea-Torresdey, Jorge L.; Robinson, Brett H.

    2011-01-01

    We identified contaminants associated with the Cata mine tailing depot located in the outskirts of the city of Guanajuato, Mexico. We also investigated strategies for their phytomanagement. Silver and antimony were present at 39 and 31 mg kg -1 , respectively, some twofold higher than the Dutch Intervention Values. Total and extractable boron (B) occurred at concentrations of 301 and 6.3 mg L -1 , respectively. Concentrations of B in soil solution above 1.9 mg L -1 have been shown to be toxic to plants. Plant growth may also be inhibited by the low concentrations of extractable plant nutrients. Analysis of the aerial portions of Aloe vera (L. Burm.f.) revealed that this plant accumulates negligible concentrations of the identified contaminants. Calculations using a whole system model (Phyto-DSS) showed that establishing a crop of A. vera would have little effect on the drainage or leaching from the site. However, this plant would reduce wind and water erosion and potentially produce valuable cosmetic products. In contrast, crops of poplar, a species that is tolerant to high soil B concentrations, would mitigate leaching from this site. Alternate rows of trees could be periodically harvested and be used for timber or bioenergy.

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

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

    2017-04-01

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

  3. Evaluating the role of vegetation on the transport of contaminants associated with a mine tailing using the Phyto-DSS

    Cano-Resendiz, Omar [Departamento de Ingenieria Quimica, Universidad de Guanajuato, Noria Alta s/n, CP 36050 Guanajuato (Mexico); Rosa, Guadalupe de la, E-mail: delarosa@quijote.ugto.mx [Departamento de Ingenieria Quimica, Universidad de Guanajuato, Noria Alta s/n, CP 36050 Guanajuato (Mexico); Cruz-Jimenez, Gustavo [Departamento de Farmacia, Universidad de Guanajuato, Noria Alta s/n, CP 36050 Guanajuato (Mexico); Gardea-Torresdey, Jorge L. [Chemistry Department and Environmental Science and Engineering, Ph.D. Program, The University of Texas at El Paso, 500 W. University Ave., 79968 El Paso, TX (United States); Robinson, Brett H. [Agriculture and Life Sciences, Lincoln University, P.O. Box 84 Lincoln, Canterbury 7646 (New Zealand)

    2011-05-15

    We identified contaminants associated with the Cata mine tailing depot located in the outskirts of the city of Guanajuato, Mexico. We also investigated strategies for their phytomanagement. Silver and antimony were present at 39 and 31 mg kg{sup -1}, respectively, some twofold higher than the Dutch Intervention Values. Total and extractable boron (B) occurred at concentrations of 301 and 6.3 mg L{sup -1}, respectively. Concentrations of B in soil solution above 1.9 mg L{sup -1} have been shown to be toxic to plants. Plant growth may also be inhibited by the low concentrations of extractable plant nutrients. Analysis of the aerial portions of Aloe vera (L. Burm.f.) revealed that this plant accumulates negligible concentrations of the identified contaminants. Calculations using a whole system model (Phyto-DSS) showed that establishing a crop of A. vera would have little effect on the drainage or leaching from the site. However, this plant would reduce wind and water erosion and potentially produce valuable cosmetic products. In contrast, crops of poplar, a species that is tolerant to high soil B concentrations, would mitigate leaching from this site. Alternate rows of trees could be periodically harvested and be used for timber or bioenergy.

  4. Integrating Fuzzy AHP and Fuzzy ARAS for evaluating financial performance

    Abdolhamid Safaei Ghadikolaei

    2014-09-01

    Full Text Available Multi Criteria Decision Making (MCDM is an advanced field of Operation Research; recently MCDM methods are efficient and common tools for performance evaluation in many areas such as finance and economy. The aim of this study is to show one of applications of mathematics in real word. This study with considering value based measures and accounting based measures simultaneously, provided a hybrid approach of MCDM methods in fuzzy environment for financial performance evaluation of automotive and parts manufacturing industry of Tehran stock exchange (TSE.for this purpose Fuzzy analytic hierarchy process (FAHP is applied to determine the relative important of each criterion, then The companies are ranked according their financial performance by using fuzzy additive ratio assessment (Fuzzy ARAS method. The finding of this study showed effective of this approach in evaluating financial performance.

  5. Submission to Energy and Mines Ministers Conference by the Canadian Energy Pipeline Association

    2002-01-01

    Almost all of the oil and natural gas in Canada is transported from supply basins to customers across the country through the critical network operated by the members of the Canadian Energy Pipeline Association (CEPA). More than 50 per cent of the liquid hydrocarbons transported last year were exported to the United States. The issues discussed in this paper are pipeline safety and integrity, landowner relations, climate change, Aboriginal consultation, and economic regulation and taxation. Each of these topics is discussed in detail. CEPA members are working closely with industry partners and their associations in both the United States and Canada, especially so since the events of September 11, as well as with federal and provincial governments in the field of critical infrastructure protection. Landowners agree to the tune of 87 per cent with the statement to the effect that Canadians can trust pipelines to safely transport oil and natural gas products across the country. CEPA members continue to strive to meet the communication and information needs of stakeholders. Climate change poses significant challenges to the industry, which is committed to doing its part to reduce the emissions of greenhouse gases. Consultation with Aboriginals is taking place in the eight provinces and two territories where CEPA members operate. The issues discussed are environmental protection, preservation of cultural and heritage resources, education and training, employment, contracting, and business opportunities. A vital component of the Canadian economy, the pipeline industry improves the quality of life for all Canadians, but the regulators are awarding low rates of return, creating a disadvantage for Canadians in the marketplace. Adjustments in this field are required, in the opinion of CEPA members. The current Capital Cost Allowance (CCA) rate for pipeline compressor assets is an issue that is being defended by CEPA members along with the Canadian Gas Association and

  6. Deep mining heterogeneous networks of biomedical linked data to predict novel drug-target associations.

    Zong, Nansu; Kim, Hyeoneui; Ngo, Victoria; Harismendy, Olivier

    2017-08-01

    A heterogeneous network topology possessing abundant interactions between biomedical entities has yet to be utilized in similarity-based methods for predicting drug-target associations based on the array of varying features of drugs and their targets. Deep learning reveals features of vertices of a large network that can be adapted in accommodating the similarity-based solutions to provide a flexible method of drug-target prediction. We propose a similarity-based drug-target prediction method that enhances existing association discovery methods by using a topology-based similarity measure. DeepWalk, a deep learning method, is adopted in this study to calculate the similarities within Linked Tripartite Network (LTN), a heterogeneous network generated from biomedical linked datasets. This proposed method shows promising results for drug-target association prediction: 98.96% AUC ROC score with a 10-fold cross-validation and 99.25% AUC ROC score with a Monte Carlo cross-validation with LTN. By utilizing DeepWalk, we demonstrate that: (i) this method outperforms other existing topology-based similarity computation methods, (ii) the performance is better for tripartite than with bipartite networks and (iii) the measure of similarity using network topology outperforms the ones derived from chemical structure (drugs) or genomic sequence (targets). Our proposed methodology proves to be capable of providing a promising solution for drug-target prediction based on topological similarity with a heterogeneous network, and may be readily re-purposed and adapted in the existing of similarity-based methodologies. The proposed method has been developed in JAVA and it is available, along with the data at the following URL: https://github.com/zongnansu1982/drug-target-prediction . nazong@ucsd.edu. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

  7. The Association between Noise, Cortisol and Heart Rate in a Small-Scale Gold Mining Community—A Pilot Study

    Allyson Green

    2015-08-01

    Full Text Available We performed a cross-sectional pilot study on salivary cortisol, heart rate, and personal noise exposures in a small-scale gold mining village in northeastern Ghana in 2013. Cortisol level changes between morning and evening among participants showed a relatively low decline in cortisol through the day (−1.44 ± 4.27 nmol/L, n = 18, a pattern consistent with chronic stress. A multiple linear regression, adjusting for age, sex, smoking status, and time between samples indicated a significant increase of 0.25 nmol/L cortisol from afternoon to evening per 1 dBA increase in equivalent continuous noise exposure (Leq over that period (95% CI: 0.08–0.42, Adj R2 = 0.502, n = 17. A mixed effect linear regression model adjusting for age and sex indicated a significant increase of 0.29 heart beats per minute (BPM for every 1 dB increase in Leq. Using standard deviations (SDs as measures of variation, and adjusting for age and sex over the sampling period, we found that a 1 dBA increase in noise variation over time (Leq SD was associated with a 0.5 BPM increase in heart rate SD (95% CI: 0.04–−0.9, Adj. R2 = 0.229, n = 16. Noise levels were consistently high, with 24-hour average Leq exposures ranging from 56.9 to 92.0 dBA, with a mean daily Leq of 82.2 ± 7.3 dBA (mean monitoring duration 22.1 ± 1.9 hours, n = 22. Ninety-five percent of participants had 24-hour average Leq noise levels over the 70 dBA World health Organization (WHO guideline level for prevention of hearing loss. These findings suggest that small-scale mining communities may face multiple, potentially additive health risks that are not yet well documented, including hearing loss and cardiovascular effects of stress and noise.

  8. Optimization of cultural conditions for growth associated chromate reduction by Arthrobacter sp. SUK 1201 isolated from chromite mine overburden

    Dey, Satarupa, E-mail: dey1919@gmail.com [Microbiology Laboratory, Department of Botany, University of Calcutta, Kolkata 700019 (India); Paul, A.K., E-mail: amalk_paul@yahoo.co.in [Microbiology Laboratory, Department of Botany, University of Calcutta, Kolkata 700019 (India)

    2012-04-30

    Highlights: Black-Right-Pointing-Pointer Isolation of a potent Cr(VI) resistant and reducing Arthrobacter SUK 1201 from chromite mine overburdens of Orissa, India. Black-Right-Pointing-Pointer Phylogenetically (16S rDNA analysis), Arthrobacter SUK 1201 showed 99% nucleotide base pair similarity with Arthrobacter GZK-1. Black-Right-Pointing-Pointer Production of insoluble chromium precipitates during chromate reduction under batch culture by the isolate SUK 1201. Black-Right-Pointing-Pointer Confirmation of formation of insoluble chromium precipitate during reduction studies by EDX analysis. Black-Right-Pointing-Pointer Optimization of cultural conditions for Cr(VI) reduction under batch culture leading to complete reduction of 2 mM of Cr(VI). - Abstract: Arthrobacter sp. SUK 1201, a chromium resistant and reducing bacterium having 99% sequence homology of 16S rDNA with Arthrobacter sp. GZK-1 was isolated from chromite mine overburden dumps of Orissa, India. The objective of the present study was to optimize the cultural conditions for chromate reduction by Arthrobacter sp. SUK 1201. The strain showed 67% reduction of 2 mM chromate in 7 days and was associated with the formation of green insoluble precipitate, which showed characteristic peak of chromium in to energy dispersive X-ray analysis. However, Fourier transform infrared spectra have failed to detect any complexation of end products of Cr(VI) reduction with the cell mass. Reduction of chromate increased with increased cell density and was maximum at 10{sup 10} cells/ml, but the reduction potential decreased with increase in Cr(VI) concentration. Chromate reducing efficiency was promoted when glycerol and glucose was used as electron donors. Optimum pH and temperature of Cr(VI) reduction was 7.0 and 35 Degree-Sign C respectively. The reduction process was inhibited by several metal ions and metabolic inhibitors but not by Cu(II) and DNP. These findings suggest that Arthrobacter sp. SUK 1201 has great promise

  9. The Association between Noise, Cortisol and Heart Rate in a Small-Scale Gold Mining Community-A Pilot Study.

    Green, Allyson; Jones, Andrew D; Sun, Kan; Neitzel, Richard L

    2015-08-21

    We performed a cross-sectional pilot study on salivary cortisol, heart rate, and personal noise exposures in a small-scale gold mining village in northeastern Ghana in 2013. Cortisol level changes between morning and evening among participants showed a relatively low decline in cortisol through the day (-1.44 ± 4.27 nmol/L, n = 18), a pattern consistent with chronic stress. A multiple linear regression, adjusting for age, sex, smoking status, and time between samples indicated a significant increase of 0.25 nmol/L cortisol from afternoon to evening per 1 dBA increase in equivalent continuous noise exposure (Leq) over that period (95% CI: 0.08-0.42, Adj R(2) = 0.502, n = 17). A mixed effect linear regression model adjusting for age and sex indicated a significant increase of 0.29 heart beats per minute (BPM) for every 1 dB increase in Leq. Using standard deviations (SDs) as measures of variation, and adjusting for age and sex over the sampling period, we found that a 1 dBA increase in noise variation over time (Leq SD) was associated with a 0.5 BPM increase in heart rate SD (95% CI: 0.04--0.9, Adj. R(2) = 0.229, n = 16). Noise levels were consistently high, with 24-hour average Leq exposures ranging from 56.9 to 92.0 dBA, with a mean daily Leq of 82.2 ± 7.3 dBA (mean monitoring duration 22.1 ± 1.9 hours, n = 22). Ninety-five percent of participants had 24-hour average Leq noise levels over the 70 dBA World health Organization (WHO) guideline level for prevention of hearing loss. These findings suggest that small-scale mining communities may face multiple, potentially additive health risks that are not yet well documented, including hearing loss and cardiovascular effects of stress and noise.

  10. Pemodelan Sistem Fuzzy Dengan Menggunakan Matlab

    Afan Galih Salman

    2010-12-01

    Full Text Available Fuzzy logic is a method in soft computing category, a method that could process uncertain, inaccurate, and less cost implemented data. Some methods in soft computing category besides fuzzy logic are artificial network nerve, probabilistic reasoning, and evolutionary computing. Fuzzy logic has the ability to develop fuzzy system that is intelligent system in uncertain environment. Some stages in fuzzy system formation process is input and output analysis, determining input and output variable, defining each fuzzy set member function, determining rules based on experience or knowledge of an expert in his field, and implementing fuzzy system. Overall, fuzzy logic uses simple mathematical concept, understandable, detectable uncertain and accurate data. Fuzzy system could create and apply expert experiences directly without exercise process and effort to decode the knowledge into a computer until becoming a modeling system that could be relied on decision making.

  11. Implementation of Steiner point of fuzzy set.

    Liang, Jiuzhen; Wang, Dejiang

    2014-01-01

    This paper deals with the implementation of Steiner point of fuzzy set. Some definitions and properties of Steiner point are investigated and extended to fuzzy set. This paper focuses on establishing efficient methods to compute Steiner point of fuzzy set. Two strategies of computing Steiner point of fuzzy set are proposed. One is called linear combination of Steiner points computed by a series of crisp α-cut sets of the fuzzy set. The other is an approximate method, which is trying to find the optimal α-cut set approaching the fuzzy set. Stability analysis of Steiner point of fuzzy set is also studied. Some experiments on image processing are given, in which the two methods are applied for implementing Steiner point of fuzzy image, and both strategies show their own advantages in computing Steiner point of fuzzy set.

  12. Dissolved metals and associated constituents in abandoned coal-mine discharges, Pennsylvania, USA. Part 1: Constituent quantities and correlations

    Cravotta, Charles A.

    2008-01-01

    Complete hydrochemical data are rarely reported for coal-mine discharges (CMD). This report summarizes major and trace-element concentrations and loadings for CMD at 140 abandoned mines in the Anthracite and Bituminous Coalfields of Pennsylvania. Clean-sampling and low-level analytical methods were used in 1999 to collect data that could be useful to determine potential environmental effects, remediation strategies, and quantities of valuable constituents. A subset of 10 sites was resampled in 2003 to analyze both the CMD and associated ochreous precipitates; the hydrochemical data were similar in 2003 and 1999. In 1999, the flow at the 140 CMD sites ranged from 0.028 to 2210 L s -1 , with a median of 18.4 L s -1 . The pH ranged from 2.7 to 7.3; concentrations (range in mg/L) of dissolved (0.45-μm pore-size filter) SO 4 (34-2000), Fe (0.046-512), Mn (0.019-74), and Al (0.007-108) varied widely. Predominant metalloid elements were Si (2.7-31.3 mg L -1 ), B ( -1 ), Ge ( -1 ), and As ( -1 ). The most abundant trace metals, in order of median concentrations (range in μg/L), were Zn (0.6-10,000), Ni (2.6-3200), Co (0.27-3100), Ti (0.65-28), Cu (0.4-190), Cr ( -1 in 97% of the samples, with a maximum of 0.0175 μg L -1 . No samples had detectable concentrations of Hg, Os or Pt, and less than half of the samples had detectable Pd, Ag, Ru, Ta, Nb, Re or Sn. Predominant rare-earth elements, in order of median concentrations (range in μg/L), were Y (0.11-530), Ce (0.01-370), Sc (1.0-36), Nd (0.006-260), La (0.005-140), Gd (0.005-110), Dy (0.002-99) and Sm ( C > P = N = Se) were not elevated in the CMD samples compared to average river water or seawater. Compared to seawater, the CMD samples also were poor in halogens (Cl > Br > I > F), alkalies (Na > K > Li > Rb > Cs), most alkaline earths (Ca > Mg > Sr), and most metalloids but were enriched by two to four orders of magnitude with Fe, Al, Mn, Co, Be, Sc, Y and the lanthanide rare-earth elements, and one order of

  13. Priority pollutants and associated constituents in untreated and treated discharges from coal mining or processing facilities in Pennsylvania, USA

    Cravotta, III, Charles A.; Brady, Keith B.C.

    2015-01-01

    Clean sampling and analysis procedures were used to quantify more than 70 inorganic constituents, including 35 potentially toxic or hazardous constituents, organic carbon, and other characteristics of untreated (influent) and treated (effluent) coal-mine discharges (CMD) at 38 permitted coal-mining or coal-processing facilities in the bituminous coalfield and 4 facilities in the anthracite coalfield of Pennsylvania. Of the 42 facilities sampled during 2011, 26 were surface mines, 11 were underground mines, and 5 were coal refuse disposal operations. Treatment of CMD with caustic soda (NaOH), lime (CaO or Ca(OH)2), flocculent, or limestone was ongoing at 21%, 40%, 6%, and 4% of the facilities, respectively; no chemicals were added at the remaining facilities. All facilities with CMD treatment incorporated structures for active or passive aeration and settling of metal-rich precipitate.

  14. Fuzzy histogram for internal and external fuzzy directional relations

    Salamat , Nadeem; Zahzah , El-Hadi

    2009-01-01

    5 Pages; Spatial relations have key point importance in image analysis and computer vision. Numerous technics have been developed to study these relations especially directional relations. Modern digital computers give rise to quantitative methods and among them fuzzy methods have core importance due to handling imprecise knowledge information and vagueness. In most fuzzy methods external directional relations are considered which are useful for small scale space image analysis but in large s...

  15. Solution of Fuzzy Differential Equations Using Fuzzy Sumudu Transforms

    Raheleh Jafari

    2018-01-01

    Full Text Available The uncertain nonlinear systems can be modeled with fuzzy differential equations (FDEs and the solutions of these equations are applied to analyze many engineering problems. However, it is very difficult to obtain solutions of FDEs. In this paper, the solutions of FDEs are approximated by utilizing the fuzzy Sumudu transform (FST method. Significant theorems are suggested in order to explain the properties of FST. The proposed method is validated with three real examples.

  16. Contract Mining versus Owner Mining

    Owner

    mining companies can concentrate on their core businesses while using specialists for ... 2 Definition of Contract and Owner. Mining ... equipment maintenance, scheduling and budgeting ..... No. Region. Amount Spent on. Contract Mining. ($ billion). Percent of. Total. 1 ... cost and productivity data based on a large range.

  17. Theta-Generalized closed sets in fuzzy topological spaces

    El-Shafei, M.E.; Zakari, A.

    2006-01-01

    In this paper we introduce the concepts of theta-generalized closed fuzzy sets and generalized fuzzy sets in topological spaces. Furthermore, generalized fuzzy sets are extended to theta-generalized fuzzy sets. Also, we introduce the concepts of fuzzy theta-generalized continuous and fuzzy theta-generalized irresolute mappings. (author)

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

    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.

  19. Granitoid-associated gold mineralization in Egypt: a case study from the Atalla mine

    Zoheir, Basem; Deshesh, Fatma; Broman, Curt; Pitcairn, Iain; El-Metwally, Ahmed; Mashaal, Shabaan

    2018-06-01

    Gold-bearing sulfide-quartz veins cutting mainly through the Atalla monzogranite intrusion in the Eastern Desert of Egypt are controlled by subparallel NE-trending brittle shear zones. These veins are associated with pervasive sericite-altered, silicified, and ferruginated rocks. The hosting shear zones are presumed as high-order structures of the Najd-style faults in the Central Eastern Desert ( 615-585 Ma). Ore minerals include an early pyrite-arsenopyrite (±pyrrhotite) mineralization, partly replaced by a late pyrite-galena-sphalerite-chalcopyrite (±gold/electrum ± tetrahedrite ± hessite) assemblage. Gold occurs as small inclusions in pyrite and arsenopyrite, or more commonly as intergrowths with galena and sphalerite/tetrahedrite in microfractures. Arsenopyrite geothermometry suggests formation of the early Fe-As-sulfide mineralization at 380-340 °C, while conditions of deposition of the late base metal-gold assemblage are assumed to be below 300 °C. Rare hessite, electrum, and Bi-galena are associated with sphalerite and gold in the late assemblage. The early and late sulfide minerals show consistently a narrow range of δ34S ‰ (3.4-6.5) that overlaps with sulfur isotopic values in ophiolitic rocks. The Au-quartz veins are characterized by abundant CO2 and H2O ± CO2 ± NaCl inclusions, where three-dimensional clusters of inclusions show variable aqueous/carbonic proportions and broad range of total (bimodal) homogenization temperatures. Heterogeneous entrapment of immiscible fluids is interpreted to be caused by unmixing of an originally homogenous, low salinity ( 2 eq. mass % NaCl) aqueous-carbonic fluid, during transition from lithostatic to hydrostatic conditions. Gold deposition occurred generally under mesothermal conditions, i.e., 1.3 kbar and 280 °C, and continued during system cooling to chemistry of the ore fluids.

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

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

    2012-10-05

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

  1. A review of mortality associated with elongate mineral particle (EMP) exposure in occupational epidemiology studies of gold, talc, and taconite mining.

    Mandel, Jeffrey H; Alexander, Bruce H; Ramachandran, Gurumurthy

    2016-12-01

    Mining of gold, taconite, and talc may involve exposure to elongate mineral particles (EMP). The involved EMPs are typically non-asbestiform, include dimensions that regulatory definitions exclude, and have been less studied. A review of the literature was undertaken for this exposure and occupational epidemiological studies that occur in gold, talc, and taconite mining. Quantitative EMP exposure information in these industries is incomplete. However, there are consistent findings of pneumoconiosis in each of these types of mining. A recent case-control study suggests a possible association between this exposure and mesothelioma. Lung cancer is inconsistently reported in these industries and is an unlikely outcome of non-asbestiform EMP exposure. There is evidence of cardiovascular mortality excess across all of these types of mining. Non-malignant respiratory disease and cardiovascular mortality have been consistently increased in these industries. Further investigation, including additional insights for the role of non-asbestiform EMP, is warranted. Am. J. Ind. Med. 59:1047-1060, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

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

    Chen, X

    2011-11-01

    We conducted data-mining analyses using the Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) and molecular genetics of schizophrenia genome-wide association study supported by the genetic association information network (MGS-GAIN) schizophrenia data sets and performed bioinformatic prioritization for all the markers with P-values ≤0.05 in both data sets. In this process, we found that in the CMYA5 gene, there were two non-synonymous markers, rs3828611 and rs10043986, showing nominal significance in both the CATIE and MGS-GAIN samples. In a combined analysis of both the CATIE and MGS-GAIN samples, rs4704591 was identified as the most significant marker in the gene. Linkage disequilibrium analyses indicated that these markers were in low LD (3 828 611-rs10043986, r(2)=0.008; rs10043986-rs4704591, r(2)=0.204). In addition, CMYA5 was reported to be physically interacting with the DTNBP1 gene, a promising candidate for schizophrenia, suggesting that CMYA5 may be involved in the same biological pathway and process. On the basis of this information, we performed replication studies for these three single-nucleotide polymorphisms. The rs3828611 was found to have conflicting results in our Irish samples and was dropped out without further investigation. The other two markers were verified in 23 other independent data sets. In a meta-analysis of all 23 replication samples (family samples, 912 families with 4160 subjects; case-control samples, 11 380 cases and 15 021 controls), we found that both markers are significantly associated with schizophrenia (rs10043986, odds ratio (OR)=1.11, 95% confidence interval (CI)=1.04-1.18, P=8.2 × 10(-4) and rs4704591, OR=1.07, 95% CI=1.03-1.11, P=3.0 × 10(-4)). The results were also significant for the 22 Caucasian replication samples (rs10043986, OR=1.11, 95% CI=1.03-1.17, P=0.0026 and rs4704591, OR=1.07, 95% CI=1.02-1.11, P=0.0015). Furthermore, haplotype conditioned analyses indicated that the association

  3. An extension of fuzzy decisi

    Basem Mohamed Elomda

    2013-07-01

    Full Text Available This paper presents a new extension to Fuzzy Decision Maps (FDMs by allowing use of fuzzy linguistic values to represent relative importance among criteria in the preference matrix as well as representing relative influence among criteria for computing the steady-state matrix in the stage of Fuzzy Cognitive Map (FCM. The proposed model is called the Linguistic Fuzzy Decision Networks (LFDNs. The proposed LFDN provides considerable flexibility to decision makers when solving real world Multi-Criteria Decision-Making (MCDM problems. The performance of the proposed LFDN model is compared with the original FDM using a previously published case study. The result of comparison ensures the ability to draw the same decisions with a more realistic decision environment.

  4. Mining, Validation, and Clinical Significance of Colorectal Cancer (CRC)-Associated lncRNAs.

    Sun, Xiangwei; Hu, Yingying; Zhang, Liang; Hu, Changyuan; Guo, Gangqiang; Mao, Chenchen; Xu, Jianfeng; Ye, Sisi; Huang, Guanli; Xue, Xiangyang; Guo, Aizhen; Shen, Xian

    2016-01-01

    Colorectal cancer (CRC) is one of the deadliest tumours, but its pathogenesis remains unclear. The involvement of differentially expressed long non-coding RNAs (lncRNAs) in CRC tumorigenesis makes them suitable tumour biomarkers. Here, we screened 150 cases of CRC and 85 cases of paracancerous tissues in the GEO database for differentially expressed lncRNAs. The levels of lncRNA candidates in 84 CRC and paracancerous tissue samples were validated by qRT-PCR and their clinical significance was analyzed. We identified 15 lncRNAs with differential expression in CRC tumours; among them, AK098081 was significantly up-regulated, whereas AK025209, BC040303, BC037331, AK026659, and CR749831 were down-regulated in CRC. In a receiver operating characteristic curve analysis, the area under the curve for the six lncRNAs was 0.914. High expression of AK098081 and low expression of BC040303, CR749831, and BC037331 indicated poor CRC differentiation. CRC patients with lymph node metastasis had lower expression of BC037331. In addition, the group with high AK098081 expression presented significantly lower overall survival and disease-free survival rates than the low-expression group, confirming AK098081 as an independent risk factor for CRC patients. In conclusion, we have identified multiple CRC-associated lncRNAs from microarray expression profiles that can serve as novel biomarkers for the diagnosis and prognosis of CRC.

  5. Fish gill responses to pollutants from oil sands mining-associated waters

    Lee, L.E.J.; Willfang, S.; Lamb, M.P.; Nero, V.; Farwell, A.J.; Dixon, D.G.

    2002-01-01

    The processing of Athabasca Deposit oil sands results in large amounts of liquid wastes associated with oil sand tailings. In addition to containing polycyclic aromatic hydrocarbons (PAHs), these waste waters are high in salinity and naphthenic acids which may be toxic to aquatic biota and their effects must be clarified. This study presents a suite of tests for in-depth and quick analysis of tailings water toxicity and contributes to the assessment of environmental risk. Yellow perch, fathead minnows, and rainbow trout were exposed to reclamation ponds where both in vivo and in vitro evaluation of crude and individual naphthenic acids and salts were conducted to examine their effect on fish gills which are very susceptible to contaminants. The fish exposed to the reclamation ponds showed higher incidence of gill pathological changes than control fish in Mildred Lake, a reservoir lake whose waters are diverted for use in oil sands extraction. Notable gill histopathological changes were observed when fish were exposed in vivo to sulfate/chloride salts and to abietic acid. Changes in membrane integrity, lysosomal activity and general morphology were observed when fished were exposed in vitro to salts, commercial napthenic acids or crude naphthenic extracts from the reclamation ponds

  6. QTL detection and elite alleles mining for stigma traits in Oryza sativa by association mapping

    Xiaojing Dang

    2016-08-01

    Full Text Available Stigma traits are very important for hybrid seed production in Oryza sativa, which is a self-pollinated crop; however, the genetic mechanism controlling the traits is poorly understood. In this study, we investigated the phenotypic data of 227 accessions across two years and assessed their genotypic variation with 249 simple sequence repeat (SSR markers. By combining phenotypic and genotypic data, a genome-wide association (GWA map was generated. Large phenotypic variations in stigma length (STL, stigma brush-shaped part length (SBPL and stigma non-brush-shaped part length (SNBPL were found. Significant positive correlations were identified among stigma traits. In total, 2,072 alleles were detected among 227 accessions, with an average of 8.3 alleles per SSR locus. GWA mapping detected 6 quantitative trait loci (QTLs for the STL, 2 QTLs for the SBPL and 7 QTLs for the SNBPL. Eleven, 5, and 12 elite alleles were found for the STL, SBPL and SNBPL, respectively. Optimal cross designs were predicted for improving the target traits. The detected genetic variation in stigma traits and QTLs provides helpful information for cloning candidate STL genes and breeding rice cultivars with longer STLs in the future.

  7. FUZZY LOGIC IN LEGAL EDUCATION

    Z. Gonul BALKIR

    2011-04-01

    Full Text Available The necessity of examination of every case within its peculiar conditions in social sciences requires different approaches complying with the spirit and nature of social sciences. Multiple realities require different and various perceptual interpretations. In modern world and social sciences, interpretation of perception of valued and multi-valued have been started to be understood by the principles of fuzziness and fuzzy logic. Having the verbally expressible degrees of truthness such as true, very true, rather true, etc. fuzzy logic provides the opportunity for the interpretation of especially complex and rather vague set of information by flexibility or equivalence of the variables’ of fuzzy limitations. The methods and principles of fuzzy logic can be benefited in examination of the methodological problems of law, especially in the applications of filling the legal loopholes arising from the ambiguities and interpretation problems in order to understand the legal rules in a more comprehensible and applicable way and the efficiency of legal implications. On the other hand, fuzzy logic can be used as a technical legal method in legal education and especially in legal case studies and legal practice applications in order to provide the perception of law as a value and the more comprehensive and more quality perception and interpretation of value of justice, which is the core value of law. In the perception of what happened as it has happened in legal relationships and formations, the understanding of social reality and sociological legal rules with multi valued sense perspective and the their applications in accordance with the fuzzy logic’s methods could create more equivalent and just results. It can be useful for the young lawyers and law students as a facilitating legal method especially in the materialization of the perception and interpretation of multi valued and variables. Using methods and principles of fuzzy logic in legal

  8. On the mathematics of fuzziness

    Kerre, E. [Ghent Univ. (Belgium)

    1994-12-31

    During the past twenty-five years, the scientific community has been working very extensively on the development of reliable models for the representation and manipulation of impreciseness and uncertainty that pervade the real world. Fuzzy set theory is one of the most popular theories able to treat incomplete information. In this paper, the basic mathematical principles underlying fuzzy set theory are outlined. Special attention is paid to the way that set theory has influenced the development of mathematics in a positive way.

  9. On the mathematics of fuzziness

    Kerre, E.

    1994-01-01

    During the past twenty-five years, the scientific community has been working very extensively on the development of reliable models for the representation and manipulation of impreciseness and uncertainty that pervade the real world. Fuzzy set theory is one of the most popular theories able to treat incomplete information. In this paper, the basic mathematical principles underlying fuzzy set theory are outlined. Special attention is paid to the way that set theory has influenced the development of mathematics in a positive way

  10. Fuzzy reasoning on Horn Set

    Liu, X.; Fang, K.

    1986-01-01

    A theoretical study in fuzzy reasoning on Horn Set is presented in this paper. The authors first introduce the concepts of λ-Horn Set of clauses and λ-Input Half Lock deduction. They then use the λ-resolution method to discuss fuzzy reasoning on λ-Horn set of clauses. It is proved that the proposed λ-Input Half Lock resolution method is complete with the rules in certain format

  11. Supervisory System and Multivariable Control Applying Weighted Fuzzy-PID Logic in an Alcoholic Fermentation Process

    Márcio Mendonça

    2015-10-01

    Full Text Available In this work, it is analyzed a multivariate system control of an alcoholic fermentation process with no minimum phase. The control is made with PID classic controllers associated with a supervisory system based on Fuzzy Systems. The Fuzzy system, a priori, send set-points to PID controllers, but also adds protection functions, such as if the biomass valued is at zero or very close. The Fuzzy controller changes the campaign to prevent or mitigate the paralyzation of the process. Three control architectures based on Fuzzy Control Systems are presented and compared in performance with classic control in different campaigns. The third architecture, in particular, adds an adaptive function. A brief summary of Fuzzy theory and correlated works will be presented. And, finally simulations results, conclusions and future works end the article.

  12. Structuring osteosarcoma knowledge: an osteosarcoma-gene association database based on literature mining and manual annotation.

    Poos, Kathrin; Smida, Jan; Nathrath, Michaela; Maugg, Doris; Baumhoer, Daniel; Neumann, Anna; Korsching, Eberhard

    2014-01-01

    Osteosarcoma (OS) is the most common primary bone cancer exhibiting high genomic instability. This genomic instability affects multiple genes and microRNAs to a varying extent depending on patient and tumor subtype. Massive research is ongoing to identify genes including their gene products and microRNAs that correlate with disease progression and might be used as biomarkers for OS. However, the genomic complexity hampers the identification of reliable biomarkers. Up to now, clinico-pathological factors are the key determinants to guide prognosis and therapeutic treatments. Each day, new studies about OS are published and complicate the acquisition of information to support biomarker discovery and therapeutic improvements. Thus, it is necessary to provide a structured and annotated view on the current OS knowledge that is quick and easily accessible to researchers of the field. Therefore, we developed a publicly available database and Web interface that serves as resource for OS-associated genes and microRNAs. Genes and microRNAs were collected using an automated dictionary-based gene recognition procedure followed by manual review and annotation by experts of the field. In total, 911 genes and 81 microRNAs related to 1331 PubMed abstracts were collected (last update: 29 October 2013). Users can evaluate genes and microRNAs according to their potential prognostic and therapeutic impact, the experimental procedures, the sample types, the biological contexts and microRNA target gene interactions. Additionally, a pathway enrichment analysis of the collected genes highlights different aspects of OS progression. OS requires pathways commonly deregulated in cancer but also features OS-specific alterations like deregulated osteoclast differentiation. To our knowledge, this is the first effort of an OS database containing manual reviewed and annotated up-to-date OS knowledge. It might be a useful resource especially for the bone tumor research community, as specific

  13. Fuzzy logic and neural networks in artificial intelligence and pattern recognition

    Sanchez, Elie

    1991-10-01

    With the use of fuzzy logic techniques, neural computing can be integrated in symbolic reasoning to solve complex real world problems. In fact, artificial neural networks, expert systems, and fuzzy logic systems, in the context of approximate reasoning, share common features and techniques. A model of Fuzzy Connectionist Expert System is introduced, in which an artificial neural network is designed to construct the knowledge base of an expert system from, training examples (this model can also be used for specifications of rules in fuzzy logic control). Two types of weights are associated with the synaptic connections in an AND-OR structure: primary linguistic weights, interpreted as labels of fuzzy sets, and secondary numerical weights. Cell activation is computed through min-max fuzzy equations of the weights. Learning consists in finding the (numerical) weights and the network topology. This feedforward network is described and first illustrated in a biomedical application (medical diagnosis assistance from inflammatory-syndromes/proteins profiles). Then, it is shown how this methodology can be utilized for handwritten pattern recognition (characters play the role of diagnoses): in a fuzzy neuron describing a number for example, the linguistic weights represent fuzzy sets on cross-detecting lines and the numerical weights reflect the importance (or weakness) of connections between cross-detecting lines and characters.

  14. Fuzzy multiobjective models for optimal operation of a hydropower system

    Teegavarapu, Ramesh S. V.; Ferreira, André R.; Simonovic, Slobodan P.

    2013-06-01

    Optimal operation models for a hydropower system using new fuzzy multiobjective mathematical programming models are developed and evaluated in this study. The models use (i) mixed integer nonlinear programming (MINLP) with binary variables and (ii) integrate a new turbine unit commitment formulation along with water quality constraints used for evaluation of reservoir downstream impairment. Reardon method used in solution of genetic algorithm optimization problems forms the basis for development of a new fuzzy multiobjective hydropower system optimization model with creation of Reardon type fuzzy membership functions. The models are applied to a real-life hydropower reservoir system in Brazil. Genetic Algorithms (GAs) are used to (i) solve the optimization formulations to avoid computational intractability and combinatorial problems associated with binary variables in unit commitment, (ii) efficiently address Reardon method formulations, and (iii) deal with local optimal solutions obtained from the use of traditional gradient-based solvers. Decision maker's preferences are incorporated within fuzzy mathematical programming formulations to obtain compromise operating rules for a multiobjective reservoir operation problem dominated by conflicting goals of energy production, water quality and conservation releases. Results provide insight into compromise operation rules obtained using the new Reardon fuzzy multiobjective optimization framework and confirm its applicability to a variety of multiobjective water resources problems.

  15. Applying fuzzy analytic network process in quality function deployment model

    Mohammad Ali Afsharkazemi

    2012-08-01

    Full Text Available In this paper, we propose an empirical study of QFD implementation when fuzzy numbers are used to handle the uncertainty associated with different components of the proposed model. We implement fuzzy analytical network to find the relative importance of various criteria and using fuzzy numbers we calculate the relative importance of these factors. The proposed model of this paper uses fuzzy matrix and house of quality to study the products development in QFD and also the second phase i.e. part deployment. In most researches, the primary objective is only on CRs to implement the quality function deployment and some other criteria such as production costs, manufacturing costs etc were disregarded. The results of using fuzzy analysis network process based on the QFD model in Daroupat packaging company to develop PVDC show that the most important indexes are being waterproof, resistant pill packages, and production cost. In addition, the PVDC coating is the most important index in terms of company experts’ point of view.

  16. Fuzzy barrier distributions

    Piasecki, E.

    2009-01-01

    Heavy-ion collisions often produce a fusion barrier distribution with structures displaying a fingerprint of couplings to highly collective excitations [1]. Basically the same distribution can be obtained from large-angle quasi-elastic scattering, though here the role of the many weak direct-reaction channels is unclear. For 2 0N e + 9 0Z r we have observed the barrier structures expected for the highly deformed neon projectile, but for 2 0N e + 9 2Z r we find completely smooth distribution (see Fig.1). We find that transfer channels in these systems are of similar strength but single particle excitations are significantly stronger in the latter case. They apparently reduce the 'resolving power' of the quasi-elastic channel, what leads to smeared out, or 'fuzzy' barrier distribution. This is the first case when such a phenomenon has been observed.(author)

  17. A cross-sectional survey on knowledge and perceptions of health risks associated with arsenic and mercury contamination from artisanal gold mining in Tanzania

    Charles Elias

    2013-01-01

    Full Text Available Abstract Background An estimated 0.5 to 1.5 million informal miners, of whom 30-50% are women, rely on artisanal mining for their livelihood in Tanzania. Mercury, used in the processing gold ore, and arsenic, which is a constituent of some ores, are common occupational exposures that frequently result in widespread environmental contamination. Frequently, the mining activities are conducted haphazardly without regard for environmental, occupational, or community exposure. The primary objective of this study was to assess community risk knowledge and perception of potential mercury and arsenic toxicity and/or exposure from artisanal gold mining in Rwamagasa in northwestern Tanzania. Methods A cross-sectional survey of respondents in five sub-villages in the Rwamagasa Village located in Geita District in northwestern Tanzania near Lake Victoria was conducted. This area has a history of artisanal gold mining and many of the population continue to work as miners. Using a clustered random selection approach for recruitment, a total of 160 individuals over 18 years of age completed a structured interview. Results The interviews revealed wide variations in knowledge and risk perceptions concerning mercury and arsenic exposure, with 40.6% (n=65 and 89.4% (n=143 not aware of the health effects of mercury and arsenic exposure respectively. Males were significantly more knowledgeable (n=59, 36.9% than females (n=36, 22.5% with regard to mercury (x2=3.99, px2=22.82, p= Conclusions The knowledge of individuals living in Rwamagasa, Tanzania, an area with a history of artisanal gold mining, varied widely with regard to the health hazards of mercury and arsenic. In these communities there was limited awareness of the threats to health associated with exposure to mercury and arsenic. This lack of knowledge, combined with minimal environmental monitoring and controlled waste management practices, highlights the need for health education, surveillance, and policy

  18. On Fuzzy β-I-open sets and Fuzzy β-I-continuous functions

    Keskin, Aynur

    2009-01-01

    In this paper, first of all we obtain some properties and characterizations of fuzzy β-I-open sets. After that, we also define the notion of β-I-closed sets and obtain some properties. Lastly, we introduce the notions of fuzzy β-I-continuity with the help of fuzzy β-I-open sets to obtain decomposition of fuzzy continuity.

  19. On Fuzzy {beta}-I-open sets and Fuzzy {beta}-I-continuous functions

    Keskin, Aynur [Department of Mathematics, Faculty of Science and Arts, Selcuk University, Campus, 42075 Konya (Turkey)], E-mail: akeskin@selcuk.edu.tr

    2009-11-15

    In this paper, first of all we obtain some properties and characterizations of fuzzy {beta}-I-open sets. After that, we also define the notion of {beta}-I-closed sets and obtain some properties. Lastly, we introduce the notions of fuzzy {beta}-I-continuity with the help of fuzzy {beta}-I-open sets to obtain decomposition of fuzzy continuity.

  20. Evaluation of environment benefits based on new-type mining of coal resources

    Xu, Futong; Ren, Zaixiang

    2017-08-01

    According to the energy structure characteristics in China, this paper analyzed the current situation of liquefaction and gasification exploitation of coal as an emerging mining method. Simultaneously, setting the UCG (UCG) as an example, this paper analyzed the factors impacting the new-type mining method of coal resources and the mining damages, obtaining that the main damages of UCG include surface subsidence, groundwater pollution and other pollution. This paper, which proposed to evaluate the environmental benefits of the new-type mining method, established a evaluation system of environmental benefits of UCG and adopted fuzzy comprehensive evaluation, obtaining four-class comprehensive evaluation indexes of the new-type mining method.

  1. Comparative Performance Of Using PCA With K-Means And Fuzzy C Means Clustering For Customer Segmentation

    Fahmida Afrin

    2015-08-01

    Full Text Available Abstract Data mining is the process of analyzing data and discovering useful information. Sometimes it is called knowledge Discovery. Clustering refers to groups whereas data are grouped in such a way that the data in one cluster are similar data in different clusters are dissimilar. Many data mining technologies are developed for customer segmentation. PCA is working as a preprocessor of Fuzzy C means and K- means for reducing the high dimensional and noisy data. There are many clustering method apply on customer segmentation. In this paper the performance of Fuzzy C means and K-means after implementing Principal Component Analysis is analyzed. We analyze the performance on a standard dataset for these algorithms. The results indicate that PCA based fuzzy clustering produces better results than PCA based K-means and is a more stable method for customer segmentation.

  2. Mining with Rare Cases

    Weiss, Gary M.

    Rare cases are often the most interesting cases. For example, in medical diagnosis one is typically interested in identifying relatively rare diseases, such as cancer, rather than more frequently occurring ones, such as the common cold. In this chapter we discuss the role of rare cases in Data Mining. Specific problems associated with mining rare cases are discussed, followed by a description of methods for addressing these problems.

  3. Exploring the challenges associated with the greening of supply chains in the South African manganese and phosphate mining industry

    R.I. David Pooe

    2014-11-01

    Full Text Available As with most mining activities, the mining of manganese and phosphate has serious consequences for the environment. Despite a largely adequate and progressive framework for environmental governance developed since 1994, few mines have integrated systems into their supply chain processes to minimise environmental risks and ensure the achievement of acceptable standards. Indeed, few mines have been able to implement green supply chain management (GrSCM. The purpose of this article was to explore challenges related to the implementation of GrSCM and to provide insight into how GrSCM can be implemented in the South African manganese and phosphate industry. This article reported findings of a qualitative study involving interviews with 12 participants from the manganese and phosphate industry in South Africa. Purposive sampling techniques were used. Emerging from the study were six themes, all of which were identified as key challenges in the implementation of GrSCM in the manganese and phosphate mining industry. From the findings, these challenges include the operationalisation of environmental issues, lack of collaboration and knowledge sharing, proper application of monitoring and control systems,lack of clear policy and legislative direction, the cost of implementing GrSCM practices, and the need for strong leadership and management of change. On the basis of the literature reviewed and empirical findings, conclusions were drawn and policy and management recommendations were accordingly made.

  4. An association between dietary habits and traffic accidents in patients with chronic liver disease: A data-mining analysis.

    Kawaguchi, Takumi; Suetsugu, Takuro; Ogata, Shyou; Imanaga, Minami; Ishii, Kumiko; Esaki, Nao; Sugimoto, Masako; Otsuyama, Jyuri; Nagamatsu, Ayu; Taniguchi, Eitaro; Itou, Minoru; Oriishi, Tetsuharu; Iwasaki, Shoko; Miura, Hiroko; Torimura, Takuji

    2016-05-01

    The incidence of traffic accidents in patients with chronic liver disease (CLD) is high in the USA. However, the characteristics of patients, including dietary habits, differ between Japan and the USA. The present study investigated the incidence of traffic accidents in CLD patients and the clinical profiles associated with traffic accidents in Japan using a data-mining analysis. A cross-sectional study was performed and 256 subjects [148 CLD patients (CLD group) and 106 patients with other digestive diseases (disease control group)] were enrolled; 2 patients were excluded. The incidence of traffic accidents was compared between the two groups. Independent factors for traffic accidents were analyzed using logistic regression and decision-tree analyses. The incidence of traffic accidents did not differ between the CLD and disease control groups (8.8 vs. 11.3%). The results of the logistic regression analysis showed that yoghurt consumption was the only independent risk factor for traffic accidents (odds ratio, 0.37; 95% confidence interval, 0.16-0.85; P=0.0197). Similarly, the results of the decision-tree analysis showed that yoghurt consumption was the initial divergence variable. In patients who consumed yoghurt habitually, the incidence of traffic accidents was 6.6%, while that in patients who did not consume yoghurt was 16.0%. CLD was not identified as an independent factor in the logistic regression and decision-tree analyses. In conclusion, the difference in the incidence of traffic accidents in Japan between the CLD and disease control groups was insignificant. Furthermore, yoghurt consumption was an independent negative risk factor for traffic accidents in patients with digestive diseases, including CLD.

  5. An association between dietary habits and traffic accidents in patients with chronic liver disease: A data-mining analysis

    KAWAGUCHI, TAKUMI; SUETSUGU, TAKURO; OGATA, SHYOU; IMANAGA, MINAMI; ISHII, KUMIKO; ESAKI, NAO; SUGIMOTO, MASAKO; OTSUYAMA, JYURI; NAGAMATSU, AYU; TANIGUCHI, EITARO; ITOU, MINORU; ORIISHI, TETSUHARU; IWASAKI, SHOKO; MIURA, HIROKO; TORIMURA, TAKUJI

    2016-01-01

    The incidence of traffic accidents in patients with chronic liver disease (CLD) is high in the USA. However, the characteristics of patients, including dietary habits, differ between Japan and the USA. The present study investigated the incidence of traffic accidents in CLD patients and the clinical profiles associated with traffic accidents in Japan using a data-mining analysis. A cross-sectional study was performed and 256 subjects [148 CLD patients (CLD group) and 106 patients with other digestive diseases (disease control group)] were enrolled; 2 patients were excluded. The incidence of traffic accidents was compared between the two groups. Independent factors for traffic accidents were analyzed using logistic regression and decision-tree analyses. The incidence of traffic accidents did not differ between the CLD and disease control groups (8.8 vs. 11.3%). The results of the logistic regression analysis showed that yoghurt consumption was the only independent risk factor for traffic accidents (odds ratio, 0.37; 95% confidence interval, 0.16–0.85; P=0.0197). Similarly, the results of the decision-tree analysis showed that yoghurt consumption was the initial divergence variable. In patients who consumed yoghurt habitually, the incidence of traffic accidents was 6.6%, while that in patients who did not consume yoghurt was 16.0%. CLD was not identified as an independent factor in the logistic regression and decision-tree analyses. In conclusion, the difference in the incidence of traffic accidents in Japan between the CLD and disease control groups was insignificant. Furthermore, yoghurt consumption was an independent negative risk factor for traffic accidents in patients with digestive diseases, including CLD. PMID:27123257

  6. Where do we stand with fuzzy project scheduling?

    Bonnal, Pierre; Lacoste, Germain

    2004-01-01

    Fuzzy project scheduling has interested several researchers in the past two decades; about 20 articles have been written on this issue. Contrary to stochastic project-scheduling approaches that are used by many project schedulers, and even if the axiomatic associated to the theory of probabilities is not always compatible with decision-making situations, fuzzy project-scheduling approaches that are most suited to these situations have been kept in the academic sphere. This paper starts by recalling the differences one can observe between uncertainty and imprecision. Then most of the published research works that have been done in this field are summarized. Finally, a framework for addressing the resource-constrained fuzzy project- scheduling problem is proposed. This framework uses temporal linguistic descriptors, which might become very interesting features to the project-scheduling practitioners.

  7. Risk evaluation in Columbian electricity market using fuzzy logic

    Medina, S.; Moreno, J.

    2007-01-01

    This article proposes a model based on Fuzzy Logic to evaluate the market risk that a trading agent faces in the electric power negotiation in Colombia, as part of a general model of negotiation. The proposed model considers single external factors as regulatory changes, social and political issues, and the condition of the national transmission net. Variables of the market associated to these risk factors were selected and some graphic and statistical analyses were made in order to check their relationship with the electricity prices and to determine why the experts consider these factors in their analyses. According to the obtained results a Mamdani Fuzzy Inference System which contains the expert knowledge was developed and it is presented in a fuzzy cognitive map. (author)

  8. Supply chain management under fuzziness recent developments and techniques

    Öztayşi, Başar

    2014-01-01

    Supply Chain Management Under Fuzziness presents recently developed fuzzy models and techniques for supply chain management. These include: fuzzy PROMETHEE, fuzzy AHP, fuzzy ANP, fuzzy VIKOR, fuzzy DEMATEL, fuzzy clustering, fuzzy linear programming, and fuzzy inference systems. The book covers both practical applications and new developments concerning these methods. This book offers an excellent resource for researchers and practitioners in supply chain management and logistics, and will provide them with new suggestions and directions for future research. Moreover, it will support graduate students in their university courses, such as specialized courses on supply chains and logistics, as well as related courses in the fields of industrial engineering, engineering management and business administration.

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

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

    2018-01-01

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

  10. Stability Analysis of Interconnected Fuzzy Systems Using the Fuzzy Lyapunov Method

    Ken Yeh

    2010-01-01

    Full Text Available The fuzzy Lyapunov method is investigated for use with a class of interconnected fuzzy systems. The interconnected fuzzy systems consist of J interconnected fuzzy subsystems, and the stability analysis is based on Lyapunov functions. Based on traditional Lyapunov stability theory, we further propose a fuzzy Lyapunov method for the stability analysis of interconnected fuzzy systems. The fuzzy Lyapunov function is defined in fuzzy blending quadratic Lyapunov functions. Some stability conditions are derived through the use of fuzzy Lyapunov functions to ensure that the interconnected fuzzy systems are asymptotically stable. Common solutions can be obtained by solving a set of linear matrix inequalities (LMIs that are numerically feasible. Finally, simulations are performed in order to verify the effectiveness of the proposed stability conditions in this paper.

  11. Fuzzy relational calculus theory, applications and software

    Peeva, Ketty

    2004-01-01

    This book examines fuzzy relational calculus theory with applications in various engineering subjects. The scope of the text covers unified and exact methods with algorithms for direct and inverse problem resolution in fuzzy relational calculus. Extensive engineering applications of fuzzy relation compositions and fuzzy linear systems (linear, relational and intuitionistic) are discussed. Some examples of such applications include solutions of equivalence, reduction and minimization problems in fuzzy machines, pattern recognition in fuzzy languages, optimization and inference engines in textile and chemical engineering, etc. A comprehensive overview of the authors' original work in fuzzy relational calculus is also provided in each chapter. The attached CD-Rom contains a toolbox with many functions for fuzzy calculations, together with an original algorithm for inverse problem resolution in MATLAB. This book is also suitable for use as a textbook in related courses at advanced undergraduate and graduate level...

  12. Compound Option Pricing under Fuzzy Environment

    Xiandong Wang

    2014-01-01

    Full Text Available Considering the uncertainty of a financial market includes two aspects: risk and vagueness; in this paper, fuzzy sets theory is applied to model the imprecise input parameters (interest rate and volatility. We present the fuzzy price of compound option by fuzzing the interest and volatility in Geske’s compound option pricing formula. For each α, the α-level set of fuzzy prices is obtained according to the fuzzy arithmetics and the definition of fuzzy-valued function. We apply a defuzzification method based on crisp possibilistic mean values of the fuzzy interest rate and fuzzy volatility to obtain the crisp possibilistic mean value of compound option price. Finally, we present a numerical analysis to illustrate the compound option pricing under fuzzy environment.

  13. Fuzzy Nonnative Phonolexical Representations Lead to Fuzzy Form-to-Meaning Mappings

    Svetlana V Cook

    2016-09-01

    Full Text Available The present paper explores nonnative (L2 phonological encoding of lexical entries and dissociates the difficulties associated with L2 phonological and phonolexical encoding by focusing on similarly sounding L2 words that are not differentiated by difficult phonological contrasts. We test two main claims of the fuzzy lexicon hypothesis: (1 L2 fuzzy phonolexical representations are not fully specified and lack details at both phonological and phonolexical levels of representation (Experiment 1; and (2 fuzzy phonolexical representations can lead to establishing incorrect form-to-meaning mappings (Experiment 2.The Russian-English Translation Priming task (Experiment 1, TJT explores how the degree of phonolexical similarity between a word and its lexical competitor affects lexical access of Russian words. Words with smaller phonolexical distance (e.g., parent - parrot show longer reaction times and lower accuracy compared to words with a larger phonolexical distance (e.g., parent – parchment in lower-proficiency nonnative speakers, and, to a lesser degree, higher-proficiency speakers. This points to a lack of detail in nonnative phonolexical representations necessary for efficient lexical access. The Russian Pseudo-Semantic Priming task (Experiment 2, PSP addresses the vulnerability of form-to-meaning mappings as a consequence of fuzzy phonolexical representations in L2. We primed the target with a word semantically related to its phonological competitor, or a potentially confusable word. The findings of Experiment 2 extend the results of Experiment 1 that, unlike native speakers, nonnative speakers do not properly encode phonolexical information. As a result, they are prone to access an incorrect lexical representation of a competitor word, as indicated by a slowdown in the judgments to confusable words.The study provides evidence that fuzzy phonolexical representations result in unfaithful form-to-meaning mappings, which lead to retrieval of

  14. Heavy metal pollution in soil associated with a large-scale cyanidation gold mining region in southeast of Jilin, China.

    Chen, Mo; Lu, Wenxi; Hou, Zeyu; Zhang, Yu; Jiang, Xue; Wu, Jichun

    2017-01-01

    Different gold mining and smelting processes can lead to distinctive heavy metal contamination patterns and results. This work examined heavy metal pollution from a large-scale cyanidation gold mining operation, which is distinguished from artisanal and small-scale amalgamation gold mining, in Jilin Province, China. A total of 20 samples including one background sample were collected from the surface of the mining area and the tailings pond in June 2013. These samples were analyzed for heavy metal concentrations and degree of pollution as well as sources of Cr, Cu, Zn, Pb, Ni, Cd, As, and Hg. The mean concentrations of Pb, Hg, and Cu (819.67, 0.12, and 46.92 mg kg -1 , respectively) in soil samples from the gold mine area exceeded local background values. The mean Hg content was less than the first-class standard of the Environmental Quality for Soils, which suggested that the cyanidation method is helpful for reducing Hg pollution. The geochemical accumulation index and enrichment factor results indicated clear signs that enrichment was present for Pb, Cu, and Hg, with the presence of serious Pb pollution and moderate presence to none of Hg and Cu pollution. Multivariate statistical analysis showed that there were three metal sources: (1) Pb, Cd, Cu, and As came from anthropogenic sources; (2) Cr and Zn were naturally occurring; whereas (3) Hg and Ni had a mix of anthropogenic and natural sources. Moreover, the tailings dam plays an important role in intercepting the tailings. Furthermore, the potential ecological risk assessment results showed that the study area poses a potentially strong risk to the ecological health. Furthermore, Pb and Hg (due to high concentration and high toxicity, respectively) are major pollutants on the risk index, and both Pb and Hg pollution should be of great concern at the Haigou gold mines in Jilin, China.

  15. Fuzzy Arden Syntax: A fuzzy programming language for medicine.

    Vetterlein, Thomas; Mandl, Harald; Adlassnig, Klaus-Peter

    2010-05-01

    The programming language Arden Syntax has been optimised for use in clinical decision support systems. We describe an extension of this language named Fuzzy Arden Syntax, whose original version was introduced in S. Tiffe's dissertation on "Fuzzy Arden Syntax: Representation and Interpretation of Vague Medical Knowledge by Fuzzified Arden Syntax" (Vienna University of Technology, 2003). The primary aim is to provide an easy means of processing vague or uncertain data, which frequently appears in medicine. For both propositional and number data types, fuzzy equivalents have been added to Arden Syntax. The Boolean data type was generalised to represent any truth degree between the two extremes 0 (falsity) and 1 (truth); fuzzy data types were introduced to represent fuzzy sets. The operations on truth values and real numbers were generalised accordingly. As the conditions to decide whether a certain programme unit is executed or not may be indeterminate, a Fuzzy Arden Syntax programme may split. The data in the different branches may be optionally aggregated subsequently. Fuzzy Arden Syntax offers the possibility to formulate conveniently Medical Logic Modules (MLMs) based on the principle of a continuously graded applicability of statements. Furthermore, ad hoc decisions about sharp value boundaries can be avoided. As an illustrative example shows, an MLM making use of the features of Fuzzy Arden Syntax is not significantly more complex than its Arden Syntax equivalent; in the ideal case, a programme handling crisp data remains practically unchanged when compared to its fuzzified version. In the latter case, the output data, which can be a set of weighted alternatives, typically depends continuously from the input data. In typical applications an Arden Syntax MLM can produce a different output after only slight changes of the input; discontinuities are in fact unavoidable when the input varies continuously but the output is taken from a discrete set of possibilities

  16. Economic impact of world mining

    Walser, G.

    2002-01-01

    Mining plays a vital role in the economic development of many countries. The emerging economies are now major players in the production and availability of key commodities such as copper (70%), bauxite (40%), iron ore and precious metals. Mining also has a positive impact on the economy of many countries. Another impact of mining can be measured in terms of employment opportunities and income generation. Commercial scale mining provides employment and skills transfer to more than 2 million workers. The multiplier effect increases this benefit by a factor of between 2 and 5. The World Bank Mining Department has carried out an in-depth study on economic and social impact of mining at the community level in Chile, Peru, Bolivia, Papua New Guinea and Mali. This study demonstrates that there are substantial social and economic benefits to the community. The most positive cases are related to the growth of local small- and micro-enterprise activities. However, mining remains controversial, as true sustainable development is not only a matter of financial flows. Mining has also been associated with a number of economic and social problems. As a result there are questions about the sustainability of the economic outcome of mining. The contribution of mining to sustainable development needs to be considered in terms of economic and technical viability, ecological sustainability and social equity. To achieve this, governments, mining companies and local communities must work together to address these issues. (author)

  17. Fuzzy Neuron: Method and Hardware Realization

    Krasowski, Michael J.; Prokop, Norman F.

    2014-01-01

    This innovation represents a method by which single-to-multi-input, single-to-many-output system transfer functions can be estimated from input/output data sets. This innovation can be run in the background while a system is operating under other means (e.g., through human operator effort), or may be utilized offline using data sets created from observations of the estimated system. It utilizes a set of fuzzy membership functions spanning the input space for each input variable. Linear combiners associated with combinations of input membership functions are used to create the output(s) of the estimator. Coefficients are adjusted online through the use of learning algorithms.

  18. ANALYSIS OF FUZZY QUEUES: PARAMETRIC PROGRAMMING APPROACH BASED ON RANDOMNESS - FUZZINESS CONSISTENCY PRINCIPLE

    Dhruba Das; Hemanta K. Baruah

    2015-01-01

    In this article, based on Zadeh’s extension principle we have apply the parametric programming approach to construct the membership functions of the performance measures when the interarrival time and the service time are fuzzy numbers based on the Baruah’s Randomness- Fuzziness Consistency Principle. The Randomness-Fuzziness Consistency Principle leads to defining a normal law of fuzziness using two different laws of randomness. In this article, two fuzzy queues FM...

  19. Fuzzy upper bounds and their applications

    Soleimani-damaneh, M. [Department of Mathematics, Faculty of Mathematical Science and Computer Engineering, Teacher Training University, 599 Taleghani Avenue, Tehran 15618 (Iran, Islamic Republic of)], E-mail: soleimani_d@yahoo.com

    2008-04-15

    This paper considers the concept of fuzzy upper bounds and provides some relevant applications. Considering a fuzzy DEA model, the existence of a fuzzy upper bound for the objective function of the model is shown and an effective approach to solve that model is introduced. Some dual interpretations are provided, which are useful for practical purposes. Applications of the concept of fuzzy upper bounds in two physical problems are pointed out.

  20. Neuro-fuzzy Control of Integrating Processes

    Anna Vasičkaninová

    2011-11-01

    Full Text Available Fuzzy technology is adaptive and easily applicable in different areas.Fuzzy logic provides powerful tools to capture the perceptionof natural phenomena. The paper deals with tuning of neuro-fuzzy controllers for integrating plant and for integrating plantswith time delay. The designed approach is verified on three examples by simulations and compared plants with classical PID control.Designed fuzzy controllers lead to better closed-loop control responses then classical PID controllers.

  1. FFLP problem with symmetric trapezoidal fuzzy numbers

    Reza Daneshrad

    2015-04-01

    Full Text Available The most popular approach for solving fully fuzzy linear programming (FFLP problems is to convert them into the corresponding deterministic linear programs. Khan et al. (2013 [Khan, I. U., Ahmad, T., & Maan, N. (2013. A simplified novel technique for solving fully fuzzy linear programming problems. Journal of Optimization Theory and Applications, 159(2, 536-546.] claimed that there had been no method in the literature to find the fuzzy optimal solution of a FFLP problem without converting it into crisp linear programming problem, and proposed a technique for the same. Others showed that the fuzzy arithmetic operation used by Khan et al. (2013 had some problems in subtraction and division operations, which could lead to misleading results. Recently, Ezzati et al. (2014 [Ezzati, R., Khorram, E., & Enayati, R. (2014. A particular simplex algorithm to solve fuzzy lexicographic multi-objective linear programming problems and their sensitivity analysis on the priority of the fuzzy objective functions. Journal of Intelligent and Fuzzy Systems, 26(5, 2333-2358.] defined a new operation on symmetric trapezoidal fuzzy numbers and proposed a new algorithm to find directly a lexicographic/preemptive fuzzy optimal solution of a fuzzy lexicographic multi-objective linear programming problem by using new fuzzy arithmetic operations, but their model was not fully fuzzy optimization. In this paper, a new method, by using Ezzati et al. (2014’s fuzzy arithmetic operation and a fuzzy version of simplex algorithm, is proposed for solving FFLP problem whose parameters are represented by symmetric trapezoidal fuzzy number without converting the given problem into crisp equivalent problem. By using the proposed method, the fuzzy optimal solution of FFLP problem can be easily obtained. A numerical example is provided to illustrate the proposed method.

  2. Neutralization and attenuation of metal species in acid mine drainage and mine leachates using magnesite: a batch experimental approach

    Masindi, Vhahangwele

    2014-08-01

    Full Text Available International Mine Water Association Conference – An Interdisciplinary Response to Mine Water Challenges, China University of Mining and Technogy, China, China, 18-22 August 2014 Neutralization and Attenuation of Metal Species in Acid Mine Drainage and Mine...

  3. Higher spin gauge theory on fuzzy \\boldsymbol {S^4_N}

    Sperling, Marcus; Steinacker, Harold C.

    2018-02-01

    We examine in detail the higher spin fields which arise on the basic fuzzy sphere S^4N in the semi-classical limit. The space of functions can be identified with functions on classical S 4 taking values in a higher spin algebra associated to \

  4. A SELF-ORGANISING FUZZY LOGIC CONTROLLER

    ES Obe

    One major drawback of fuzzy logic controllers is the difficulty encountered in the construction of a rule- base ... The greatest limitation of fuzzy logic control is the lack ..... c(kT)= e(kT)-e((k-1)T). (16) .... with the aid of fuzzy models”, It in Industrial.

  5. Forecasting Enrollments with Fuzzy Time Series.

    Song, Qiang; Chissom, Brad S.

    The concept of fuzzy time series is introduced and used to forecast the enrollment of a university. Fuzzy time series, an aspect of fuzzy set theory, forecasts enrollment using a first-order time-invariant model. To evaluate the model, the conventional linear regression technique is applied and the predicted values obtained are compared to the…

  6. On the intuitionistic fuzzy inner product spaces

    Goudarzi, M.; Vaezpour, S.M.; Saadati, R.

    2009-01-01

    In this paper, the definition of intuitionistic fuzzy inner product is given. By virtue of this definition, some convergence theorems, Schwarts inequality and the orthogonal concept for intuitionistic fuzzy inner product spaces are established and introduced. Moreover the relationship between this kind of spaces and intuitionistic fuzzy normed spaces is considered.

  7. Fuzzy control of pressurizer dynamic process

    Ming Zhedong; Zhao Fuyu

    2006-01-01

    Considering the characteristics of pressurizer dynamic process, the fuzzy control system that takes the advantages of both fuzzy controller and PID controller is designed for the dynamic process in pressurizer. The simulation results illustrate this type of composite control system is with better qualities than those of single fuzzy controller and single PID controller. (authors)

  8. Possible use of fuzzy logic in database

    Vaclav Bezdek

    2011-04-01

    Full Text Available The article deals with fuzzy logic and its possible use in database systems. At first fuzzy thinking style is shown on a simple example. Next the advantages of the fuzzy approach to database searching are considered on the database of used cars in the Czech Republic.

  9. Effectiveness of Securities with Fuzzy Probabilistic Return

    Krzysztof Piasecki

    2011-01-01

    Full Text Available The generalized fuzzy present value of a security is defined here as fuzzy valued utility of cash flow. The generalized fuzzy present value cannot depend on the value of future cash flow. There exists such a generalized fuzzy present value which is not a fuzzy present value in the sense given by some authors. If the present value is a fuzzy number and the future value is a random one, then the return rate is given as a probabilistic fuzzy subset on a real line. This kind of return rate is called a fuzzy probabilistic return. The main goal of this paper is to derive the family of effective securities with fuzzy probabilistic return. Achieving this goal requires the study of the basic parameters characterizing fuzzy probabilistic return. Therefore, fuzzy expected value and variance are determined for this case of return. These results are a starting point for constructing a three-dimensional image. The set of effective securities is introduced as the Pareto optimal set determined by the maximization of the expected return rate and minimization of the variance. Finally, the set of effective securities is distinguished as a fuzzy set. These results are obtained without the assumption that the distribution of future values is Gaussian. (original abstract

  10. The majority rule in a fuzzy environment.

    Montero, Javier

    1986-01-01

    In this paper, an axiomatic approach to rational decision making in a fuzzy environment is studied. In particular, the majority rule is proposed as a rational way for aggregating fuzzy opinions in a group, when such agroup is defined as a fuzzy set.

  11. The fuzzy approach to statistical analysis

    Coppi, Renato; Gil, Maria A.; Kiers, Henk A. L.

    2006-01-01

    For the last decades, research studies have been developed in which a coalition of Fuzzy Sets Theory and Statistics has been established with different purposes. These namely are: (i) to introduce new data analysis problems in which the objective involves either fuzzy relationships or fuzzy terms;

  12. Classification Identification of Acoustic Emission Signals from Underground Metal Mine Rock by ICIMF Classifier

    Hongyan Zuo

    2014-01-01

    Full Text Available To overcome the drawback that fuzzy classifier was sensitive to noises and outliers, Mamdani fuzzy classifier based on improved chaos immune algorithm was developed, in which bilateral Gaussian membership function parameters were set as constraint conditions and the indexes of fuzzy classification effectiveness and number of correct samples of fuzzy classification as the subgoal of fitness function. Moreover, Iris database was used for simulation experiment, classification, and recognition of acoustic emission signals and interference signals from stope wall rock of underground metal mines. The results showed that Mamdani fuzzy classifier based on improved chaos immune algorithm could effectively improve the prediction accuracy of classification of data sets with noises and outliers and the classification accuracy of acoustic emission signal and interference signal from stope wall rock of underground metal mines was 90.00%. It was obvious that the improved chaos immune Mamdani fuzzy (ICIMF classifier was useful for accurate diagnosis of acoustic emission signal and interference signal from stope wall rock of underground metal mines.

  13. Fuzzy commutative algebra and its application in mechanical engineering

    Han, J.; Song, H.

    1996-01-01

    Based on literature data, this paper discusses the whole mathematical structure about point-fuzzy number set F(R). By introducing some new operations about addition, subtraction, multiplication, division and scalar multiplication, we prove that F(R) can form fuzzy linear space, fuzzy commutative ring, fuzzy commutative algebra in order. Furthermore, we get that A is fuzzy commutative algebra for any fuzzy subset. At last, we give an application of point-fuzzy number to mechanical engineering

  14. Radiation in mines

    Rose, H.J.M.

    1982-01-01

    Radiation in mines is primarily associated with, but not restricted to, the exploitation of uranium bearing orebodies. The intent of this chapter is to convey some aspects of radiation control in the mining industry, the behaviour of the parent radon and its daughter products. An attempt was made to demonstrate that anything less than complete diligence by the ventilation personnel could result in rapid deterioration of the mine environment, and consequently high exposure rates. When the maximum annual exposure limit is 4,0 WLM (Working level month exposure) the ventilation official is not allowed the privilege of making an error. Ventilation planning in uranium mines is of prime importance and is very much a group involvement

  15. Mercury and trace element contents of Donbas coals and associated mine water in the vicinity of Donetsk, Ukraine

    Kolker, A.; Panov, B.S.; Panov, Y.B.; Landa, E.R.; Conko, K.M.; Korchemagin, V.A.; Shendrik, T.; McCord, J.D.

    2009-01-01

    Mercury-rich coals in the Donets Basin (Donbas region) of Ukraine were sampled in active underground mines to assess the levels of potentially harmful elements and the potential for dispersion of metals through use of this coal. For 29 samples representing c11 to m3 Carboniferous coals, mercury contents range from 0.02 to 3.5 ppm (whole-coal dry basis). Mercury is well correlated with pyritic sulfur (0.01 to 3.2 wt.%), with an r2 of 0.614 (one outlier excluded). Sulfides in these samples show enrichment of minor constituents in late-stage pyrite formed as a result of interaction of coal with hydrothermal fluids. Mine water sampled at depth and at surface collection points does not show enrichment of trace metals at harmful levels, indicating pyrite stability at subsurface conditions. Four samples of coal exposed in the defunct open-cast Nikitovka mercury mines in Gorlovka have extreme mercury contents of 12.8 to 25.5 ppm. This coal was formerly produced as a byproduct of extracting sandstone-hosted cinnabar ore. Access to these workings is unrestricted and small amounts of extreme mercury-rich coal are collected for domestic use, posing a limited human health hazard. More widespread hazards are posed by the abandoned Nikitovka mercury processing plant, the extensive mercury mine tailings, and mercury enrichment of soils extending into residential areas of Gorlovka.

  16. Reduction of the safety and health risk associated with the generation of dust on strip coal mine haul roads.

    Thompson, RJ

    2000-01-01

    Full Text Available mine haul roads. This would be used to identify suitable spray-on or mix-in surface treatments to reduce the generation of dust, within the constraints of cost effectiveness and maintainability, through consideration of wearing course material type...

  17. Fuzzy logic of Aristotelian forms

    Perlovsky, L.I. [Nichols Research Corp., Lexington, MA (United States)

    1996-12-31

    Model-based approaches to pattern recognition and machine vision have been proposed to overcome the exorbitant training requirements of earlier computational paradigms. However, uncertainties in data were found to lead to a combinatorial explosion of the computational complexity. This issue is related here to the roles of a priori knowledge vs. adaptive learning. What is the a-priori knowledge representation that supports learning? I introduce Modeling Field Theory (MFT), a model-based neural network whose adaptive learning is based on a priori models. These models combine deterministic, fuzzy, and statistical aspects to account for a priori knowledge, its fuzzy nature, and data uncertainties. In the process of learning, a priori fuzzy concepts converge to crisp or probabilistic concepts. The MFT is a convergent dynamical system of only linear computational complexity. Fuzzy logic turns out to be essential for reducing the combinatorial complexity to linear one. I will discuss the relationship of the new computational paradigm to two theories due to Aristotle: theory of Forms and logic. While theory of Forms argued that the mind cannot be based on ready-made a priori concepts, Aristotelian logic operated with just such concepts. I discuss an interpretation of MFT suggesting that its fuzzy logic, combining a-priority and adaptivity, implements Aristotelian theory of Forms (theory of mind). Thus, 2300 years after Aristotle, a logic is developed suitable for his theory of mind.

  18. Environmental effects of uranium exploration and mining

    Tibbs, N.H.; Rath, D.L.; Donovan, T.K.

    1977-01-01

    Uranium exploration and mining is increasing as the Nation's demand for energy grows. The environmental impacts associated with this exploration and mining are not severe and compare favorably with impacts from the production of other energy resources

  19. Ensemble of ground subsidence hazard maps using fuzzy logic

    Park, Inhye; Lee, Jiyeong; Saro, Lee

    2014-06-01

    Hazard maps of ground subsidence around abandoned underground coal mines (AUCMs) in Samcheok, Korea, were constructed using fuzzy ensemble techniques and a geographical information system (GIS). To evaluate the factors related to ground subsidence, a spatial database was constructed from topographic, geologic, mine tunnel, land use, groundwater, and ground subsidence maps. Spatial data, topography, geology, and various ground-engineering data for the subsidence area were collected and compiled in a database for mapping ground-subsidence hazard (GSH). The subsidence area was randomly split 70/30 for training and validation of the models. The relationships between the detected ground-subsidence area and the factors were identified and quantified by frequency ratio (FR), logistic regression (LR) and artificial neural network (ANN) models. The relationships were used as factor ratings in the overlay analysis to create ground-subsidence hazard indexes and maps. The three GSH maps were then used as new input factors and integrated using fuzzy-ensemble methods to make better hazard maps. All of the hazard maps were validated by comparison with known subsidence areas that were not used directly in the analysis. As the result, the ensemble model was found to be more effective in terms of prediction accuracy than the individual model.

  20. Extending mine life

    Anon.

    1984-01-01

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