Search Results - (( associative classification modelling algorithm ) OR ( java application server algorithm ))
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Network game (Literati) / Chung Mei Kuen
Published 2003“…Java applet is a well-known and widely used example of mobile code (a variation on the traditional client-server model). …”
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Selection and optimization of peak features for event-related eeg signals classification / Asrul bin Adam
Published 2017“…Four different existing peak models with the associated features and full features set model are considered as inputs to the classifier. …”
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Adaptive persistence layer for synchronous replication (PLSR) in heterogeneous system
Published 2011“…The PLSR architecture model, workflow and algorithms are described. The PLSR has been developed using Java Programming language. …”
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Computer remote monitoring via mobile phones using socket programming / Samih Omer Fadlelmola Elkhider
Published 2011“…The studies show beyond technical algorithms, physical aspects plays a big rule in client server model. …”
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Classification of Diabetes Mellitus (DM) using Machine Learning Algorithms
Published 2021“…Whereas for the German Frankfurt dataset, best DM classification model was found using Random Forest algorithm with an accuracy of 98.77%.…”
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Final Year Project -
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Classification of Diabetes Mellitus using Ensemble Algorithms
Published 2021“…Proposed DM classification model is chosen based on an optimized model reflected by their accuracy and performance of the model. …”
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Conference or Workshop Item -
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Audio Streaming System Using Real-Time Transport Protocol Based on Java Media Framework
Published 2004“…A design proposal was outlined to provide an adaptive client/server approach to stream audio contents using Real-Time Transport Protocol (RTP) involving architecture based on the Java Media Framework (JMF) Application Programmable Interfaces (API).RTP protocol is the Internet-standard protocol for the transport of real-time data, including audio and video and can be implemented by using Java Media Framework (JMF). …”
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Using fuzzy association rule mining in cancer classification
Published 2011“…A new algorithm has been developed to identify the fuzzy rules and significant genes based on fuzzy association rule mining. …”
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Implementation of (AES) Advanced Encryption Standard algorithm in communication application
Published 2014“…On the basis of the results of this research, it can be concluded that the developed prototype had high accuracy and security when transferring the file between the sender and receiver that was implemented in client-server application. This research hopes to give a clear idea to the readers about ABS algorithm. …”
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Undergraduates Project Papers -
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Integrated framework with association analysis for gene selection in microarray data classification
Published 2011“…The experimental results showed that the recommended GO based models, KEGG based models, and GO-KEGG based models outperformed the expression-only models by attaining better classification accuracies with less number of genes. …”
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Classification System for Heart Disease Using Bayesian Classifier
Published 2007“…This system was mainly developing using java programming. Apache Tom cat was used as a server in order to run the application smoothly. …”
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Irrelevant feature and rule removal for structural associative classification
Published 2015“…In the classification task, the presence of irrelevant features can significantly degrade the performance of classification algorithms,in terms of additional processing time, more complex models and the likelihood that the models have poor generalization power due to the over fitting problem.Practical applications of association rule mining often suffer from overwhelming number of rules that are generated, many of which are not interesting or not useful for the application in question.Removing rules comprised of irrelevant features can significantly improve the overall performance.In this paper, we explore and compare the use of a feature selection measure to filter out unnecessary and irrelevant features/attributes prior to association rules generation.The experiments are performed using a number of real-world datasets that represent diverse characteristics of data items.Empirical results confirm that by utilizing feature subset selection prior to association rule generation, a large number of rules with irrelevant features can be eliminated.More importantly, the results reveal that removing rules that hold irrelevant features improve the accuracy rate and capability to retain the rule coverage rate of structural associative association.…”
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Crytojacking Classification based on Machine Learning Algorithm
Published 2024journal::journal article -
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Study and Implementation of Data Mining in Urban Gardening
Published 2019“…Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. These data are processed and stored in appropriate formats in a MySQL server database. …”
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An extended oversampling method for imbalanced Quranic text classification based on a genetic algorithm
Published 2023“…Overall, this paper highlights the importance of Quranic text classification and the challenges associated with it. …”
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Detection of corneal arcus using rubber sheet and machine learning methods
Published 2019“…The benchmark of the classification algorithm for CA is needed to analyze the optimal output of the algorithm. …”
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Neural network diagnostic system for dengue patients risk classification
Published 2012“…Secondly, Multilayer perceptron neural network models trained via Levenberg-Marquardt and Scaled Conjugate Gradient algorithms was employed for constructing the diagnostic system. …”
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