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1
A Model for Evaluation of Cryptography Algorithm on UUM Portal
Published 2004“…The purpose of this project are to construct and provide guidelines to develop a simulation model to evaluate cryptography algorithm in terms of encryption speed and descryption speed on UUM portal. …”
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Thesis -
2
A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment
Published 2013“…This thesis describes original research in the field of software quality model by presenting a Feature Ranking Algorithm (FRA) for Pragmatic Quality Factor (PQF) model. …”
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Thesis -
3
Just Queuing: Policy-Based Scheduling Mechanism for Packet Switching Networks
Published 2011“…In terms of the complexity property, genetic algorithm has an advantage in holding the fitness score of the queue in separate storage space which potentially minimises the complexity of the algorithm. …”
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Thesis -
4
Factor Strategy Model: Proofs of Prototype Concept for Software Quality Evaluation
Published 2010“…The objective of this study is to provide software developers some measures to evaluate software quality of a Java program. Studies on software quality requirements, software quality models (as a quantifying measurement technique) and various good design rules are required for. …”
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5
Fuzzy modeling using Bat Algorithm optimization for classification
Published 2018“…A Sazonov Engine which is a fuzzy java engine is use to apply Bat Algorithm in the experiment. …”
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Undergraduates Project Papers -
6
Fault detection of aircraft engine components using fuzzy unordered rule induction algorithm
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Proceeding Paper -
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Automated feature selection using boruta algorithm to detect mobile malware
Published 2020“…The malware has potential to compromise and steal the private data, classified data, instant messages, private business contacts, and confidential schedule. …”
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Software metrics selection model for predicting maintainability of object-oriented software using genetic algorithms
Published 2016“…The latest effort to solve this selection problem is the development of the metrics selection model that uses genetic algorithm (GA). However, the process failed to state clearly the encoding strategy in its initial stage. …”
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9
AI chatbot system for educational institutions
Published 2023“…This project presents the design and development of an advanced chatbot system powered by deep learning algorithms for intent classification. The chatbot's primary goal is to facilitate effective communication and support for users, particularly students inquiring about admission processes. …”
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Final Year Project / Dissertation / Thesis -
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Wearable based-sensor fall detection system using machine learning algorithm
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Proceeding Paper -
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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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Thesis -
12
Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing
Published 2011“…A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against existing grid resource management algorithms such as Antz algorithm, Particle Swarm Optimization algorithm, Space Shared algorithm and Time Shared algorithm, in terms of processing time and resource utilization. …”
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13
A comprehensive review of optimization techniques in industrial applications: Trends, classifications, and future directions
Published 2025“…The research contribution of this review is to provide a structured classification of optimization methods—namely exact algorithms, heuristics, metaheuristics, and AI-integrated hybrid models—and to critically evaluate their practical applications, limitations, and emerging trends across industries. …”
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Article -
14
Landslide Susceptibility Mapping with Stacking Ensemble Machine Learning
Published 2024“…One of the prominent methods to improve machine learning accuracy is by using ensemble method which basically employs multiple base models. In this paper, the stacking ensemble method is used to increase the accuracy of the machine learning model for LSM where the base (first-level) learners use five ML algorithms namely decision tree (DT), k-nearest neighbor (KNN), AdaBoost, extreme gradient boosting (XGB) and random forest (RF). …”
Conference Paper -
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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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16
Talkout : Protecting mental health application with a lightweight message encryption
Published 2022“…The investigation of lightweight message encryption algorithms is conducted with systematic quantitative literature and experiment implementation in Java and Android running environment. …”
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Academic Exercise -
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An enhancement of multi-factor weighted approach technique in prioritizing test cases by comparing similarity distance
Published 2025“…Software testing is one of the most critical phases in the software development life cycle model (SDLC), where the quality of a software product is evaluated. …”
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Article -
18
A multi-filter feature selection in detecting distributed denial-of-service attack
Published 2019“…Subsequently, an experimental evaluation of the proposed Multi-Filter Feature Selection (M2FS) method is performed by using the benchmark dataset, NSL-KDD and employed the J48 classification algorithm. …”
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Conference or Workshop Item -
19
Logistics center location-inventory-routing problem optimization: a systematic review using PRISMA method
Published 2022“…A total of 112 LIRP-related studies published between 2010 and 2021 are reviewed and classified based on 10 abstract and citation databases. The classification includes four aspects: problem characteristics, demand data types, model-based solutions, and application fields. …”
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