Search Results - (( java implementation modified algorithm ) OR ( using fiber learning algorithm ))
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Direct approach for mining association rules from structured XML data
Published 2012“…The thesis also provides a two different implementation of the modified FLEX algorithm using a java based parsers and XQuery implementation. …”
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OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT
Published 2023“…To achieve this, we propose a new noble mechanism called Optimized Min-Min (OMin-Min) algorithm, inspired by the Min-Min algorithm. The objectives of this work are: i) to provide a comprehensive review of the cloud and scheduling process; ii) to classify the scheduling strategies and scientific workflows; iii) to implement our proposed algorithm with various scheduling algorithms (i.e., Min-Min, Round-Robin, Max-Min, and Modified Max-Min) for performance comparison, within different cloudlet sizes (i.e., small, medium, large, and heavy) in three scientific workflows (i.e., Montage, Epigenomics, and SIPHT); and iv) to investigate the performance of the implemented algorithms by using CloudSim. …”
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Prevention And Detection Mechanism For Security In Passive Rfid System
Published 2013“…The proposed protocol is designed with lightweight cryptographic algorithm, including XOR, Hamming distance, rotation and a modified linear congruential generator (MLCG). …”
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Automatic generation of content security policy to mitigate cross site scripting
Published 2016“…It can be extended to support generating CSP for contents that are modified by JavaScript after loading. Current approach inspects the static contents of URLs.…”
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Conference or Workshop Item -
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Using Machine Learning Algorithms to Estimate the Compressive Property of High Strength Fiber Reinforced Concrete
Published 2022“…Using machine learning (ML) techniques, concrete properties prediction is an effective solution to conserve construction time and cost. …”
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State-of-the-art ensemble learning and unsupervised learning in fatigue crack recognition of glass fiber reinforced polyester composite (GFRP) using acoustic emission
Published 2023“…This study evaluates the damage progression on glass fiber reinforced polyester composite specimens using different approaches of machine learning. …”
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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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Investigation of machine learning models in predicting compressive strength for ultra-high-performance geopolymer concrete: A comparative study
Published 2025“…Overall, the dataset of 128 CS results was used to develop the machine learning (ML) models. …”
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Predicting the rutting parameters of nanosilica/waste denim fiber composite asphalt binders using the response surface methodology and machine learning methods
Published 2023“…The study conducts an extensive investigation using ML algorithms to accurately predict the multiple stress creep recovery (MSCR) rutting parameters for the base and modified asphalt binders. …”
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Challenges of hidden data in the unused area two within executable files
Published 2009“…Results: The programs were coded in Java computer language and implemented on Pentium PC. …”
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Mitigation of Mach Zehnder modulator nonlinearity in millimeter wave radio over fiber system using digital predistortion
Published 2017“…The coefficient computation is performed using recursive prediction error method (RPEM) algorithm which shows a dominant spectral regrowth reduction and in-band distortion reduction with reduced complexity compared to the commonly used slow converging, least mean square algorithm. …”
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Parametric analysis of critical buckling in composite laminate structures under mechanical and thermal loads: a finite element and machine learning approach
Published 2024“…Subsequently, simulation data from numerous cases are utilized to identify the best parameter combination using machine learning algorithms. Various ML techniques such as linear regression, lasso regression, decision tree, random forest, and gradient boosting are employed to assess their accuracy in comparison with finite element results. …”
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Adaptive Mechanism for GA-NN to Enhance Prediction Model
Published 2015“…Data included in the model is MDF properties and its fiber characteristics. The focus of this study is the Multilayer Perceptron NN model, which is reliable to learn from seven inputs fed to the network to produce prediction of three targets. …”
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EstiCal: food calorie image recognition mobile application by using feature descriptor technique / Muhammad Asyraf Suhaimi
Published 2018“…The future work of the project can be done with additional features such as using a hybrid algorithm which is combining algorithms to improvise the feature descriptor or applying a machine learning technique to increase the efficiency of food recognition.…”
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Student Project -
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Fuzzy-based multi-agent approach for reliability assessment and improvement of power system protection
Published 2015“…Meanwhile, the second MAS model has been designed using two agents as follows: the first agent is a fault current agent that is to determine the fault current at all points before and after grounding; the second agent is the time operating of the agent which is used to determine the relay operating time before and after modifying fault current. The simulation results for the first and second models are done using the data obtained from Malaysia distribution network (DISCO-Net) and 69 bus test system that were implemented using Java Agent Development Framework package software. …”
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Evolutionary cost-cognizant regression test case prioritization for object-oriented programs
Published 2019“…There is also a need to consider implementing this strategy for dynamic object-oriented languages such as Python, Lisp, and Smalltalk.…”
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