Search Results - (( data replication server algorithm ) OR ( data normalization based algorithm ))
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Managing Heterogeneous Database Replication Using Persistence Layer Synchronous Replication (PLSR)
Published 2013“…Proper mechanism is significantly required in order to manage the complex heterogeneous data replication. This paper presents a new algorithm namely the Persistence Layer Synchronous Replication (PLSR) in order to manage the agent handling the replication. …”
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Adaptive persistence layer for synchronous replication (PLSR) in heterogeneous system
Published 2011“…All the replication servers established its connection through interfaces. …”
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Improving response time, availability and reliability through asynchronous replication technique in cluster architecture of web server cluster
Published 2010“…This paper proposes an algorithm of data replication scheme based on asynchronous replication in order to improve web server cluster system reliability. …”
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A technique of dispatching algorithms for web-server cluster
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Fault Tolerence on Binary Vote Assignment Cloud Quorum (BVACQ) Replication Technique
Published 2013“…It also increases the degrees of data availability. This is because the missing data from during the server failure has been reconciled and replicated after that server recovered.…”
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Fault Tolerance On Binary Vote Assignment Cloud Quorum (BVACQ) Replication Technique
Published 2013“…It also increases the degrees of data availability. This is be cause the missing data from during the server failure has been reconciled and replicated after that server recovered.…”
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Binary Vote Assignment on Cloud Quorum Algorithm for Fragmented MyGRANTS Database Replication
Published 2015“…Data replication is one of the mechanisms to manage data since it improves data accessibility and reliability. …”
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Binary vote assignment on grid quorum replication technique with association rule
Published 2018“…However, these techniques have its weaknesses in terms of communication costs that is the total replication servers needed to replicate the data. Furthermore, these techniques also do not consider the correlation between data during the fragmentation process. …”
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Algorithm enhancement for host-based intrusion detection system using discriminant analysis
Published 2004“…Anomaly detection algorithms model normal behavior. Anomaly detection models compare sensor data to normal patterns learned from the training data by using statistical method and try to detect activity that deviates from normal activity. …”
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Classification of Cardiac Disorders Based on Electrocardiogram Data with Fuzzy Cognitive Map (FCM) Algorithm Approach
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The effect of dose calculation algorithms on the normal tissue complication probability values of thoracic cancer
Published 2015“…Purpose: To identify the effect of dose calculation algorithms on the Normal Tissue Complication Probability values of thoracic cancer. …”
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A study on advanced statistical analysis for network anomaly detection
Published 2005“…Anomaly detection algorithms model normal behavior. Anomaly detection models compare sensor data to normal patterns learned from the training data by using statistical method and try to detect activity that deviates from normal activity. …”
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Data normalization techniques in swarm-based forecasting models for energy commodity spot price
Published 2014“…Data mining is a fundamental technique in identifying patterns from large data sets.The extracted facts and patterns contribute in various domains such as marketing, forecasting, and medical.Prior to that, data are consolidated so that the resulting mining process may be more efficient.This study investigates the effect of different data normalization techniques.which are Min-max, Z-score and decimal scaling, on Swarm-based forecasting models.Recent swarm intelligence algorithms employed includes the Grey Wolf Optimizer (GWO) and Artificial Bee Colony (ABC).Forecasting models are later developed to predict the daily spot price of crude oil and gasoline.Results showed that GWO works better with Z-score normalization technique while ABC produces better accuracy with the Min-Max.Nevertheless, the GWO is more superior than ABC as its model generates the highest accuracy for both crude oil and gasoline price.Such a result indicates that GWO is a promising competitor in the family of swarm intelligence algorithms.…”
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An alternative approach to normal parameter reduction algorithms for decision making using a soft set theory / Sani Danjuma
Published 2017“…In addition, the algorithm was relatively easy to understand compare to the state of the art of normal parameter reduction algorithm. …”
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Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly
Published 2019“…Even a normal people using clustering to grouping their data. …”
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An improved recommender system based on normalization of matrix factorization and collaborative filtering algorithms
Published 2015“…The hypothesis is that the tendency of normalization technique to simplify the data combined with the accuracy of the neighborhood models can improve the accuracy of the RS. …”
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Adaptive grid-meshed-buffer clustering algorithm for outlier detection in evolving data stream
Published 2023“…Existing clustering algorithms for outlier detection encounter significant challenges due to insufficient data pre-processing methods and the absence of a suitable data summarization framework for effective data stream clustering. …”
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Pengkelasan Sel Kanser Pangkal Rahim Kepada Sel Normal Dan Tidak Normal Menggunakan Analisis Pembezalayan Dan Rangkaian Neural
Published 2006“…The system is built to classify some certain data into two classes, which are normal or abnormal cells. …”
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