Search Results - (( framework implementation case algorithm ) OR ( java data detection algorithm ))
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Using GA and KMP algorithm to implement an approach to learning through intelligent framework documentation
Published 2023“…The main objective of this paper is to propose and implement an intelligent framework documentation approach that integrates case-based learning (CBL) with genetic algorithm (GA) and Knuth-Morris-Pratt (KMP) pattern matching algorithm with the intention of making learning a framework more effective. …”
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Implementing case-based reasoning approach to framework documentation
Published 2023“…This paper discusses and implements the case-based reasoning (CBR) approach to documenting a framework. …”
Conference paper -
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Low-level hybridization scripting language with dynamic parameterization in PSO-GA / Suraya Masrom
Published 2015“…However, in many cases, implementing the suitable hybrid algorithms for a given optimization problem is a considerably difficult, which in most cases, is time consuming. …”
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Quantum Processing Framework And Hybrid Algorithms For Routing Problems
Published 2010“…The framework is used to increase the implementation performance of quantum algorithms. …”
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Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…The simulation will be carried on WEKA tool, which allows us to call some data mining methods under JAVA environment. The proposed model will be tested and evaluated on both NSL-KDD and KDD-CUP 99 using several performance metrics.…”
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A test case generation framework based on UML statechart diagram
Published 2018“…The results of the experts’ review show that the framework is practical, easy to implement due to it is suitability to generate the test cases. …”
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Prevention And Detection Mechanism For Security In Passive Rfid System
Published 2013“…A GUI is created in a form of JAVA application to display data detected from tag. …”
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An improved diabetes risk prediction framework : An Indonesian case study
Published 2018“…However,there is the issue of noisy dataset detected as incomplete data and the outlier class problem that affects sampling bias.Existing frameworks were deemed difficult in identifying the critical risk factors of diabetes;some of which were considerably inaccurate and consume substantial computation time.The purpose of this study is to develop a suitable framework for predicting diabetes risks.From a complete blood test,the framework can predict and classify the output of either having diabetes risk or no diabetes risk.A Diabetes Risk Prediction Framework (DRPF) was developed from the literature review and case studies were afterwards conducted in three private hospitals in Semarang.Analyses were conducted to find a suitable component of the framework—due to lack of comparison and analysis on the combination of feature selection and classification algorithm.DRPF comprises four main sections: pre-processing,outlier detection,risk weighting,and learning. …”
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An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…In the second phase, a classifier ensemble learning model is proposed consisting of separate outputs: (i) To select a relevant subset of original features based on Binary Quantum Gravitational Search Algorithm (QBGSA), (ii) To mine data streams using various data chunks and overcome a failure of single classifiers based on SVM, MLP and K-NN algorithms. …”
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Image clustering comparison of two color segmentation techniques
Published 2010“…The clustering research is regarding the area of data mining and implementation of the clustering algorithms. …”
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Low-level hybridization scripting language with dynamic parameterization in PSO-GA / Suraya Masrom
Published 2015“…However, in many cases, implementing the suitable hybrid algorithms for a given optimization problem is a considerably difficult, which in most cases, is time consuming. …”
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Book Section -
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Manufacturing process planning optimisation in reconfigurable multiple parts flow lines
Published 2008“…Design/methodology/approach: The genetic algorithm methodology implements a genetic algorithm that is augmented by application specific heuristics in order to guide the search for an optimal solution. …”
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A malware analysis and detection system for mobile devices / Ali Feizollah
Published 2017“…We then used feature selection algorithms and deep learning algorithms to build a detection model. …”
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Error concealment technique using wavelet neural network for wireless transmitted digital images
Published 2012“…In the case, where the missing regions of pixels are containing textures, edges, and other image features that are not easily handled by concealment algorithms. …”
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Flexible window-based scheduling with critical worst case latency evaluations for real time traffic in time sensitive networks
Published 2022“…The first part introduces a flexible window-overlapping scheduling (FWOS) algorithm that allows the TT windows to overlap in GCL implementations. …”
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Runtime pluggable CPU scheduler for linux operating system
Published 2010“…The total memory was utilized by the framework was almost negligible at 396 KB. RPSP achieves the process communication in all the cases with 3.5% better than the vanilla kernel. …”
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A computational framework for predicting software quality-in-use from software reviews
Published 2015“…As for future research, it is recommended to extend QinUF to support additional QinU characteristics, enhance sentiment orientation, specialize the framework to a certain software domain, and implement the framework in a large-scale system.…”
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The implications for ahybrid detection technique against malicious sqlattacks on web applications
Published 2025“…The methodology is based on JavaScript and PHP languages for developing a new technique called DetectCombined capable of filtering queries using parameterized queries to protect against SQL injection which is a safe method. …”
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