With a grant from the Italian Ministry of the Environment, the National Institute of Health (Istituto Superiore di Sanita) promoted and coordinated some activities aimed at determining the extent and the intensity of ...With a grant from the Italian Ministry of the Environment, the National Institute of Health (Istituto Superiore di Sanita) promoted and coordinated some activities aimed at determining the extent and the intensity of contamination of waters used for human consumption by some chemical agents, and describing causes and modalities of contamination and human health implications. The chemical agents examined were herbicides, nitrates, trihalomethanes, asbestos, manganese and fluoride. In this paper a first nationwide picture of these problems is reported.展开更多
Real world study (RWS) has become a hotspot for clinical research. Data quality plays a vital role in research achievement and other clinical research fields. In this paper, the common quality problems in the RWS of...Real world study (RWS) has become a hotspot for clinical research. Data quality plays a vital role in research achievement and other clinical research fields. In this paper, the common quality problems in the RWS of traditional Chinese medicine are discussed, and a countermeasure is proposed.展开更多
There is growing interest in power quality issues due to wider developments in power delivery engineering.In order to maintain good power quality,it is necessary to detect and monitor power quality problems.The power ...There is growing interest in power quality issues due to wider developments in power delivery engineering.In order to maintain good power quality,it is necessary to detect and monitor power quality problems.The power quality monitoring requires storing large amount of data for analysis.This rapid increase in the size of databases has demanded new technique such as data mining to assist in the analysis and understanding of the data.This paper presents the classification of power quality problems such as voltage sag,swell,interruption and unbalance using data mining algorithms:J48,Random Tree and Random Forest decision trees.These algorithms are implemented on two sets of voltage data using WEKA software.The numeric attributes in first data set include 3-phase RMS voltages at the point of common coupling.In second data set,three more numeric attributes such as minimum,maximum and average voltages,are added along with 3-phase RMS voltages.The performance of the algorithms is evaluated in both the cases to determine the best classification algorithm,and the effect of addition of the three attributes in the second case is studied,which depicts the advantages in terms of classification accuracy and training time of the decision trees.展开更多
Health condition monitoring of induction motors is important because of their vital role and wide us in a variety of industries.A stator inter-turn fault(SITF)is considered to be the most common electrical failure acc...Health condition monitoring of induction motors is important because of their vital role and wide us in a variety of industries.A stator inter-turn fault(SITF)is considered to be the most common electrical failure according to statisti-cal studies.In this paper,an algorithm for the detection of an SITF is presented.It is based on one of the blind source separation techniques called principal component analysis(PCA).The proposed algorithm uses PCA to discriminate between the faulty components of motor current signatures and motor voltage signatures from other components.The standard deviation of one of the decomposed vectors is used as a statistical SITF criterion.The proposed criterion is robust to non-fault conditions including voltage quality problems and large mechanical load changes as well as harmonic contaminants in the voltage supply.In addition,with a straightforward and low computational burden in the fault detection process,the proposed method is computationally efficient.To evaluate the performance of the proposed method,large numbers of practical and simulation scenarios are considered,and the results confrm the good performance,high degree of accuracy,and good convergence speed of the proposed method.展开更多
文摘With a grant from the Italian Ministry of the Environment, the National Institute of Health (Istituto Superiore di Sanita) promoted and coordinated some activities aimed at determining the extent and the intensity of contamination of waters used for human consumption by some chemical agents, and describing causes and modalities of contamination and human health implications. The chemical agents examined were herbicides, nitrates, trihalomethanes, asbestos, manganese and fluoride. In this paper a first nationwide picture of these problems is reported.
文摘Real world study (RWS) has become a hotspot for clinical research. Data quality plays a vital role in research achievement and other clinical research fields. In this paper, the common quality problems in the RWS of traditional Chinese medicine are discussed, and a countermeasure is proposed.
文摘There is growing interest in power quality issues due to wider developments in power delivery engineering.In order to maintain good power quality,it is necessary to detect and monitor power quality problems.The power quality monitoring requires storing large amount of data for analysis.This rapid increase in the size of databases has demanded new technique such as data mining to assist in the analysis and understanding of the data.This paper presents the classification of power quality problems such as voltage sag,swell,interruption and unbalance using data mining algorithms:J48,Random Tree and Random Forest decision trees.These algorithms are implemented on two sets of voltage data using WEKA software.The numeric attributes in first data set include 3-phase RMS voltages at the point of common coupling.In second data set,three more numeric attributes such as minimum,maximum and average voltages,are added along with 3-phase RMS voltages.The performance of the algorithms is evaluated in both the cases to determine the best classification algorithm,and the effect of addition of the three attributes in the second case is studied,which depicts the advantages in terms of classification accuracy and training time of the decision trees.
文摘Health condition monitoring of induction motors is important because of their vital role and wide us in a variety of industries.A stator inter-turn fault(SITF)is considered to be the most common electrical failure according to statisti-cal studies.In this paper,an algorithm for the detection of an SITF is presented.It is based on one of the blind source separation techniques called principal component analysis(PCA).The proposed algorithm uses PCA to discriminate between the faulty components of motor current signatures and motor voltage signatures from other components.The standard deviation of one of the decomposed vectors is used as a statistical SITF criterion.The proposed criterion is robust to non-fault conditions including voltage quality problems and large mechanical load changes as well as harmonic contaminants in the voltage supply.In addition,with a straightforward and low computational burden in the fault detection process,the proposed method is computationally efficient.To evaluate the performance of the proposed method,large numbers of practical and simulation scenarios are considered,and the results confrm the good performance,high degree of accuracy,and good convergence speed of the proposed method.