Search Results - data processing - method

On-line detection method for outliers of dynamic instability measurement data in geological exploration control process by Liu, Fang, Su, Weixing, Zhao, Jianjun, Liang, Xiaodan

“…Through the experiment and application, it is proven that the anomaly data detection method proposed in this paper is more suitable for the detection data in the process of unstable regulation.…”
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The analytic process of Q methodology / Siti Maftuhah Damio by Damio, Siti Maftuhah

“…The purpose of this article is to describe the analytic process of a method of data collection known as Q Methodology. …”
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Gravity And Magnetic Data Reduction Software (Gramag2dcon) For Sites Characterization by Ismail, Noer El Hidayah

“…By developing new software named GraMag2DCon which include the combination of both gravity and magnetic data processing, data processing for potential field methods will be much easier. …”
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A framework for data-driven fault detection and identification with multiscale kernel fisher discriminant analysis in chemical process systems / Norazwan Md Nor by Norazwan , Md Nor

“…Therefore, data-driven FDI methods, which can make use of process data to capture their trends and dynamics, provide an attractive alternative for the quick development and deployment of FDI solutions. …”
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The necessity of a non-linear & non-stationary data processing in engineering and the new Hilbert Huang Transform (HHT) by Raja, J.E., Loo, C.K., Rao, M.V.C.

“…Hilbert-Huang Transform(HHT) is a new data processing technology developed by NASA Goddard Space Flight Center. …”
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Proposed Data Quality Evaluation Method For A Transportation Agency by Fatimah Mohamad Yunus, Pritheega Magalingam, Nurazean Maarop, Ganthan Narayana Samy, Doris Hooi-Ten Wong, Bharanidharan Shanmugam, Sundresan A/L Perumal

Influence of different pre-processing methods in predicting sugarcane quality from near-infrared (NIR) spectral data by Mat Lazim, Siti Saripa Rabiah, Mat Nawi, Nazmi, Chen, Guangnan, Jensen, Troy, Md Rasli, Ahmad Muslim

“…If no pre-processing method was applied, the coefficient of determination (R2) values for both reflectance and absorbance data were 0.81 and 0.86 respectively. …”
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Web Engineering Methods in Building aWeb-Based School Academic Information System by Helda, Yudiastuti, Irwansyah, .

“…This study focuses on the development of an academic web application aimed at improving the data processing quality in a secondary vocational school where data is currently managed manually using paper and pen.The existing manual method of processing academic data could be more efficient, prone to errors, and susceptible to data loss. …”
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A study on data embedding in Universal Domain / Mustafa S. Abdul Karim by Mustafa S., Abdul Karim

“…This dependency limits the interchangeability among data embedding methods. In other words, the applicability of a conventional data embedding method is restricted to certain types of signal. …”
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Tangible interaction learning model to enhance learning activity processes among children with dyslexia by Jamalai@Jamali, Siti Nurliana

“…A common challenge is the occurrence of missing data during the data input process. Numerous studies have proposed methods to impute missing values for data across multiple fields. …”
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Intelligent imputation method for mix data-type missing values to improve data quality by Alabadla, Mustafa R. A.

“…A common challenge is the occurrence of missing data during the data input process. Numerous studies have proposed methods to impute missing values for data across multiple fields. …”
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Obesity predictive process framework based on dietary patterns from grocery data / Nur’aina Daud by Daud, Nur’aina

“…In bridging the process involving these three domains, the obesity prediction method in this study is proposed in a form of a process framework (G2NOP Framework). …”
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Obesity predictive process framework based on dietary patterns from grocery data / Nur'Aina Daud by Daud, Nur'Aina

“…In bridging the process involving these three domains, the obesity prediction method in this study is proposed in a form of a process framework (G2NOP Framework). …”
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Requirements analysis method for extracting-transformation-loading (ETL) in data warehouse systems by Ta'a, Azman, Abdullah, Mohd Syazwan, Md Norwawi, Norita

“…The data warehouse (DW) system design involves several tasks such as defining the DW schemas and the ETL processes specifications, and these have been extensively studied and practiced for many years.The problems in heterogeneous data integration are still far from being resolved due to the complexity of ETL processes and the fundamental problems of data conflicts in information sharing environments.The understanding of an early phase of DW development is essential in properly tackling the complexity of ETL processes.The method to analyses the DW requirements from the abstract level (e.g. goal, sub-goal, stakeholder, dependency) toward the specification of ETL processes (e.g. extracting, filtering, conversion) are important in order to manage the complexity of the ETL processes design (e.g. semantic heterogeneity problems). …”
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Simulation & data validation of small-scale LNG system by Roslina, Sapuan

“…This method has been chosen because it is difficult to converge the LNG exchanger units without enough or complete process data. …”
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Multivariate Statistical Process Monitoring On Structural Fault by Mohamad Saidi, Afifah

“…Multivariate methods or multivariate statistical process monitoring (MSPM) method take into account the correlation among the process variables and measurements; and it is capable to accurately characterize the behaviour of the processes, subsequently detecting faults, for which univariate method unable to adequately perform. …”
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K Nearest Neighbor Joins And Mapreduce Process Enforcement For The Cluster Of Data Sets In Bigdata by Md Shah, Wahidah, Othman, Mohd Fairuz Iskandar, Hussian Hassan, Ali Abdul, Talib, Mohammed Saad, Mohammed, Ali Abdul Jabbar

“…K Nearest Neighbor Joins (KNN join) are regarded as highly primitive and expensive operations in the data mining.The efficient use of KNN join has proven good results in finding the objects from two data sets prevailed in the huge databases.This has been achieved with the combination of K-Nearest Neighbor query and join operation to find the distinct objects from different data sets.MapReduce is a newly introduced program with the combination of Map Procedure method and Reduce Method widely used in BigData.MapReduce is enriched with parallel distributed algorithm to find the results on a cluster of data sets in BigData.In this paper,the combination of KNN join and MapReduce methods are utilized on the cluster of data sets in BigData for knowledge discovery.Exploring the pinpoint data from huge data sets stored in Big Data demands the distributed large scale data processing.The present research paper is focusing on generic steps for KNN joins exploration operations on MapReduce.The operations of KNN Join are targeted to perform the data partitioning and data pre-processing and necessary calculations.By utilizing the combination of KNN joins with MapReduce methods on BigData data sets will demonstrate a solution for complex computational analysis. …”
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RAMEPs: A requirement analysis method for extracting-transformation-loading (ETL) processes in data warehouse systems by Ta'a, Azman, Abdullah, Mohd Syazwan, Md. Norwawi, Norita

“…This paper proposes the Requirement Analysis Method for ETL processes (RAMEPs) that utilize ontology with the goal-driven approach in analyzing the requirements of ETL processes. …”
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Modelling record times in sport with extreme value methods by Adam, Mohd Bakri, Tawn, Jonathan A.

“…We exploit connections between extreme value theory and record processes to develop inference methods for record processes. …”
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Forecasting Using K-means Clustering and RNN Methods with PCA Feature Selection by Ferna, Marestiani, Sugiyarto, Surono

“…In simple terms, the forecasting flow using the RNN method begins by dividing the test data and training data, the forward calculation process, the backward calculation process, the optimization calculation, and the evaluation calculation of the forecasting model. …”
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