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Significant correlation pattern Mining in Smart Homes

ACM TRANSACTIONS ON INTELLIGENT SYSTEMS AND TECHNOLOGY 2015年第3期6卷 35-35页

作者： Chen, Yi-Cheng Peng, Wen-Chih Huang, Jiun-Long Lee, Wang-Chien Tamkang Univ Dept Comp Sci & Informat Engn New Taipei City Taiwan Natl Chiao Tung Univ Dept Comp Sci Hsinchu City Taiwan Penn State Univ Dept Comp Sci & Engn University Pk PA 16802 USA

Owing to the great advent of sensor technology, the usage data of appliances in a house can be logged and collected easily today. However, it is a challenge for the residents to visualize how these appliances are used. Thus, mining algorithms are much needed to discover appliance usage patterns. Most previous studies on usage pattern discovery are mainly focused on analyzing the patterns of single appliance rather than mining the usage correlation among appliances. In this article, a novel algorithm, namely correlation pattern Miner (CoPMiner), is developed to capture the usage patterns and correlations among appliances probabilistically. CoPMiner also employs four pruning techniques and a statistical model to reduce the search space and filter out insignificant patterns, respectively. Furthermore, the proposed algorithm is applied on a real-world dataset to show the practicability of correlation pattern mining.

关键词： Algorithms Theory Measurement correlation pattern smart home sequential pattern time interval-based data usage representation

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Mining Association and correlation patterns Simultaneously in Database

Mining Association and Correlation Patterns Simultaneously i...

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WASE International Conference on Information Engineering (ICIE 2009)

作者： Zhang, Jianlin Zou, Wensheng Nanchang Univ Sch Software Nanchang 330047 Peoples R China Nanchang Univ Inst Comp Technol Engn Nanchang 330029 Peoples R China

ISBN: (纸本)9780769536798

Data mining aims to discover useful patterns (rules) in large datusets. In order to enhance the interestingness of the patterns produced, we propose an algorithm to mine both association and correlation patterns among items. In the mining process the all-confidence and correlation-confidence measures are adopted simultaneously. The effectiveness of the proposed approach is demonstrated with the experiment results on some real data sets.

关键词： association rule correlation pattern database correlation-confidence data mining

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Finding multiple global linear correlations in sparse and noisy data sets

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KNOWLEDGE-BASED SYSTEMS 2013年第Nov.期53卷 40-50页

作者： Zhu, Shunzhi Tang, Liang Li, Tao Xiamen Univ Technol Sch Comp Sci & Technol Xiamen 361024 Peoples R China Florida Int Univ Sch Comp Sci Miami FL 33199 USA

Finding linear correlations is an important research problem with numerous real-world applications. In real-world data sets, linear correlation may not exist in the entire data set. Some linear correlations are only visible in certain data subsets. On one hand, a lot of local correlation clustering algorithms assume that the data points of a linear correlation are locally dense. These methods may miss some global correlations when data points are sparsely distributed. On the other hand, existing global correlation clustering methods may fail when the data set contains a large amount of non-correlated points or the actual correlations are coarse. This paper proposes a simple and fast algorithm DCSearch for finding multiple global linear correlations in a data set. This algorithm is able to find the coarse and global linear correlation in noisy and sparse data sets. By using the classical divide and conquer strategy, it first divides the data set into subsets to reduce the search space, and then recursively searches and prunes the candidate correlations from the subsets. Empirical studies show that DCSearch can efficiently reduce the number of candidate correlations during each iteration. Experimental results on both synthetic and real data sets demonstrate that DCSearch is effective and efficient in finding global linear correlations in sparse and noisy data sets. (C) 2013 Elsevier B.V. All rights reserved.

关键词： correlation pattern Subspace clustering Global linear correlation Divide and conquer strategy DCSearch

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Initial ensemble generation and validation for ocean data assimilation using HYCOM in the Pacific

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OCEAN DYNAMICS 2008年第2期58卷 81-99页

作者： Wan, Liying Zhu, Jiang Bertino, Laurent Wang, Hui Chinese Acad Sci Inst Atmospher Phys Beijing Peoples R China Chinese Acad Sci Grad Univ Beijing Peoples R China State Ocean Adm Natl Marine Environm Forecasting Ctr Beijing Peoples R China Nansen Environm & Remote Sensing Ctr Mohn Sverdrup Ctr Bergen Norway Chinese Meteorol Adm Chinese Acad Meteorol Sci Beijing Peoples R China

A method to initialize an ensemble, introduced by Evensen (Physica, D 77:108-129, 1994a;J Geophys Res 99(C5):10143-10162, 1994b;Ocean Dynamics 53:343-367, 2003), was applied to the Ocean General Circulation Model (OGCM) HYbrid Coordinate Ocean Model (HYCOM) for the Pacific Ocean. Taking advantage of the hybrid coordinates, an initial ensemble is created by first perturbing the layer interfaces and then running the model for a spin-up period of 1 month forced by randomly perturbed atmospheric forcing fields. In addition to the perturbations of layer interfaces, we implemented perturbations of the mixed layer temperatures. In this paper, we investigate the quality of the initial ensemble generated by this scheme and the influence of the horizontal decorrelation scale and vertical correlation on the statistics of the resulting ensemble. We performed six ensemble generation experiments with different combinations of horizontal decorrelation scales and with/without perturbations in the mixed layer. The resulting six sets of initial ensembles are then analyzed in terms of sustainability of the ensemble spread and realism of the correlation patterns. The ensemble spreads are validated against the difference between model and observations after 20 years of free run. The correlation patterns of six sets of ensemble are compared to each other. This study shows that the ensemble generation scheme can effectively generate an initial ensemble whose spread is consistent with the observed errors. The correlation pattern of the ensemble also exhibits realistic features. The addition of mixed layer perturbations improves both the spread and correlation. Some limitations of the ensemble generation scheme are also discussed. We found that the vertical shift of isopycnal coordinates provokes unrealistically large deviations in shallow layers near the islands of the West Pacific. A simple correction circumvents the problem.

关键词： ensemble Kalman filter initial ensemble HYCOM model model uncertainty ensemble spread correlation pattern

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VARIATION IN THE SPATIAL-ORGANIZATION OF DAILY RAINFALL DURING THE NORTH QUEENSLAND WET SEASONS, 1979-82

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THEORETICAL AND APPLIED CLIMATOLOGY 1988年第2期39卷 59-72页

作者： SUMNER, G BONELL, M JAMES COOK UNIV N QUEENSLAND TOWNSVILLEQLD 4811AUSTRALIA

Daily rainfall correlation fields are examined for the north Queensland wet season months (November-March) for four consecutive years. Considerable monthly variation in correlation patterns is exhibited which is shown to be closely associated with the nature of the prevailing atmospheric circulation. Daily rainfall patterns are characteristically sporadic during the early part of the wet season (November and December), but later, and during January in particular, rainfall is more widespread and better organised. In February and March the degree of organisation decreases markedly as rainfall activity along the monsoon trough moves progressively northwards. During the period January to March and for days on which the monsoon trough is particularly active, there is a tendency for rainfall to be preferentially organised along marked axes. Axial eccentricity in correlation fields is related to orientation of the monsoon through when it is in the north of the region, and is also influenced by the trend of the east coast and adjacent high ground.

关键词： Atmospheric Circulation Daily Rainfall Rainfall pattern correlation pattern Monthly Variation

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Microevolutionary trends in the dentition of the Red fox (Vulpes vulpes)

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JOURNAL OF ZOOLOGICAL SYSTEMATICS AND EVOLUTIONARY RESEARCH 2003年第1期41卷 47-56页

作者： Szuma, E Polish Acad Sci Mammal Res Inst PL-17230 Bialowieza Poland

Microevolutionary trends in dental traits were studied in a Polish population of the Red fox, Vulpes vulpes (Linnaeus, 1758). Changes in qualitative and quantitative traits over a 70-year interval were analysed in 1453 museum specimens collected between 1927 and 1996. Over that period, there were qualitative trends towards increasing complication of occlusal crown surface in posterior premolars (i.e. P-4, P-3, P-4) and I-3. Other cheek teeth did not undergo directional change. Changes in trait correlations were assessed using samples from the 1960s and 1990s. The correlations between C-1 -C-1 and M-1-M-2 increased, while correlation values in the incisor region (I-1-I-2, I-1-I-1, I-1-I-2, I-3-I-2), carnassial region (P-4-M-1, P-4-M-1 and M-1-M-1) and in P-2-P-1 decreased. These changes may be related to increasing dietary opportunism of the Red fox during the 20th century.

关键词： Vulpes vulpes dentition morphotypes correlation pattern microevolutionary trends chronology

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DEPENDENCE OF THE TDPAC SPECTRA ON THE ORIENTATION OF THE PRINCIPAL AXIS SYSTEM OF THE ELECTRIC-FIELD GRADIENT

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HYPERFINE INTERACTIONS 1979年第5期7卷 323-331页

作者： ROTS, M CLAES, J NAMAVAR, F Instituut voor Kern-en Stralingsfysika Katholieke Universiteit Leuven Leuven Belgium

Analytical expressions are derived, which give the frequency amplitudes of a time differential perturbed angular correlation pattern, as a function of the orientation angles of the principal axis system of the electric field gradient tensor. We show, that allowed β-γ TDPAC experiments are anisotropic only if the main axis of the electric field gradient forms a unique angle with the crystal symmetry axis or if the multiple crystallographically equivalent directions in a cubic crystal are unequally populated.

关键词： Thin Film Symmetry Axis Orientation Angle Main Axis correlation pattern

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Analysis of Interaction Structure Among Multiple Functional Process Variables for Process Control in Semiconductor Manufacturing

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IEEE TRANSACTIONS ON SEMICONDUCTOR MANUFACTURING 2010年第2期23卷 263-272页

作者： Zhang, Xi Huang, Qiang Univ S Florida Dept Ind Management & Syst Engn Tampa FL 33620 USA Univ So Calif Daniel J Epstein Dept Ind & Syst Engn Los Angeles CA 90089 USA

Our previous work has shown that complex interaction patterns among functional process variables (FPVs) in semiconductor manufacturing processes can indicate process condition changes. We developed a nonlinear dynamics model to describe interactions among FPVs, which was further used to monitor process condition changes. However, the interaction structure among three or more FPVs has not been thoroughly investigated for the purpose of process control. In this work, we first extend our previously developed nonlinear dynamics model by considering the autocorrelation in each FPV. A generalized least square (GLS) method is applied to estimate the extended model. The interaction structure among FPVs is represented as a complex network in which the directionality and strength of interaction are discovered from the extended nonlinear dynamics model. To validate the proposed method, we first conduct simulation study using van del Pol oscillators. Then two sets of real experimental data from chemical mechanical planarization process are used to investigate the interaction structure change over a polishing cycle. The results show that the extracted patterns of interaction structure among FPVs aid to uncover the polishing mechanisms and provide more insights for condition monitoring and diagnosis.

关键词： correlation pattern interaction multichannel signals network process monitoring

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Statistical and Experimental Analysis of Correlated Time-Varying Process Variables for Conditions Diagnosis in Chemical-Mechanical Planarization

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IEEE TRANSACTIONS ON SEMICONDUCTOR MANUFACTURING 2009年第4期22卷 512-521页

作者： Zhang, Xi Wang, Hui Huang, Qiang Kumar, Ashok Zhai, Jingmei Univ S Florida Dept Ind Management & Syst Engn Tampa FL 33620 USA Univ Michigan Dept Mech Engn Ann Arbor MI 48109 USA Univ So Calif Daniel J Epstein Dept Ind & Syst Engn Los Angeles CA 90089 USA Univ S Florida Dept Mech Engn Tampa FL 33620 USA S China Univ Technol Sch Mech Engn Guangzhou 510641 Peoples R China

During chemical-mechanical planarization (CMP) of semiconductor wafers, chemical and mechanical process variables are strongly correlated and jointly affect polishing performance. The correlation among these process variables could potentially be utilized to characterize process conditions for the purpose of diagnosis. However, process variables measured during CMP, such as the temperature distribution and coefficient of friction between wafer and pad, vary with time and present in a functional form. This significantly increases the complexity of analyzing correlation patterns and relating them with process conditions. The focus of this paper is therefore twofold: 1) experimental investigation of the correlation between sensing process variables and the implication of correlation pattern changes on process conditions and 2) statistical analysis of correlation patterns between process variables in functional form. In the designed CMP experiment, we investigated two failure modes during CMP process: pad failure and slurry failure. Slurry failure was generated by reducing the percentage of oxidizer to investigate its effects on polishing performance and heat generation on the pad. Pad failure was due to variation of diamond abrasive sizes in the conditioner. The post-CMP study of nonuniformity and defects such as scratches on the wafer was conducted to characterize process conditions. The experimental and statistical results support the investigation of correlation among process variables for condition diagnosis.

关键词： correlation pattern interaction multichannel signals process monitoring

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Methods for Abnormal Usage Detection in Developing Intelligent Systems for Smart Homes 7

Methods for Abnormal Usage Detection in Developing Intellige...

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Seventh International Conference on Knowledge and Systems Engineering (KSE)

作者： Tran Nguyen Minh-Thai Nguyen Thai-Nghe Can Tho Univ Can Tho City Vietnam

ISBN: (纸本)9781467380133

Detecting abnormal usages in intelligent systems, especially in smart home systems, is an important task. By exploring log data, useful information and patterns can be discovered which may help users/organizations to better understand the usage of their appliances and to distinguish unnecessary usages as well as abnormal problems which can cause waste, damages, or even fire. This work proposes several methods which can be used to detect the abnormal usages of appliances in smart home system and proposes a parameter tuning strategy to optimize the model's accuracy. The proposed methods are validated by using a real dataset. Experimental results show that these approaches perform nicely and could be applied for practice.

关键词： correlation pattern smart home sequential pattern Extreme Value Theory Intelligent systems

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