Search Results - (( java location based algorithm ) OR ( learning classification protocol algorithm ))

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  1. 1

    A protocol for developing a classification system of mosquitoes using transfer learning by Pradeep Isawasan, Zetty Ilham Abdullah, Ong, Song Quan, Khairulliza Ahmad Salleh

    Published 2022
    “…This protocol aims to develop step-by-step procedure in developing a classification system with transfer learning algorithm for mosquito, we demonstrate the protocol to classify two species of Aedes mosquito - Aedes aegypti L. and Aedes albopitus L, but user can adopt the protocol for higher number of species classification. …”
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    Article
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    A Machine Learning Classification Approach To Detect Tls-Based Malware Using Entropy-Based Flow Set Features by Keshkeh, Kinan

    Published 2022
    “…This study also investigates TLSMalDetect detection performance using seven ML classification algorithms and identifies the one with the highest accuracy.…”
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    Machine learning-based enhanced deep packet inspection for IP packet priority classification with differentiated services code point for advance network management by Khan, Fazeel Ahmed, Abubakar, Adamu

    Published 2024
    “…This study presents an approach to enhance intelligent packet forwarding priority classification on Differentiated Services Code Point (DSCP), leveraging classifiers from machine learning algorithms for Deep Packet Inspection (DPI). …”
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    Mitigating Slow Hypertext Transfer Protocol Distributed Denial of Service Attacks in Software Defined Networks by Akanji, Oluwatobi Shadrach, Abisoye, Opeyemi Aderiike, Iliyasu, Mohammed Awwal

    Published 2021
    “…This study contributes to the ongoing research in detecting and mitigating slow HTTP DDoS attacks with emphasis on the use of machine learning classification and meta-heuristic algorithms.…”
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    Group formation using genetic algorithm by Che Ani, Zhamri, Husin, Mohd Zabidin, Yasin, Azman

    Published 2009
    “…However, due to lack of programming skills especially in Java programming language and the inability to have meetings frequently among the group members,most of the students’ software project cannot be delivered successfully.To solve this problem, systematic group formation is one of the initial factors that should be considered to ensure that every group consists of quality individuals who are good in Java programming and also to ensure that every group member in a group are staying closer to each other.In this research, we propose a method for group formation using Genetic Algorithms, where the members for each group will be generated based on the students’ programming skill and location of residential colleges.…”
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    Prediction of sleep pattern for university students using machine learning by Widya, Muhammad Faishal Atha, Utoro, Rio Korio, Roedavan, Rickman, Soegiarto, Duddy, Moorthy, Kohbalan, Pratondo, Agus

    Published 2026
    “…Data was collected through an online survey of 286 respondents, covering features related to demographics, daily habits, and personal perceptions. The Random Forest algorithm was employed for classification, evaluated using a 5-Fold Cross-Validation protocol, and achieved an average accuracy of 81.46%. …”
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    Multi-floor indoor location estimation system based on wireless local area network by Chua, Tien Han

    Published 2007
    “…The most probable match is selected and returned as estimated location based on Bayesian filtering algorithm. Estimated location is reported as physical location and symbolic location. …”
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    A Machine Learning Classification Approach to Detect TLS-based Malware using Entropy-based Flow Set Features by Keshkeh, Kinan, Jantan, Aman, Alieyan, Kamal

    Published 2022
    “…Due to the complexity of TLS traffic decryption, several anomaly-based detection studies have been conducted to detect TLS-based malware using different features and machine learning (ML) algorithms. However, most of these studies utilized flow features with no feature transformation or relied on inefficient flow feature transformations like frequency-based periodicity analysis and outliers percentage. …”
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    Internet of Things (IoT) based activity recognition strategies in smart homes: a review by Babangida, Lawal, Perumal, Thinagaran, Mustapha, Norwati, Yaakob, Razali

    Published 2022
    “…The obtained data can be subjected to extensive preprocessing and feature extraction tasks before being learned using appropriate machine learning or deep learning algorithms to generate a model capable of managing human activities more effectively. …”
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    Cyber attacks analysis and mitigation with machine learning techniques in ICS SCADA systems by Mubarak, Sinil, Habaebi, Mohamed Hadi, Abdul Rahman, Farah Diyana, Khan, Sheroz, Islam, Md Rafiqul

    Published 2019
    “…Mitigation techniques such as honeypot simulation which helps in vulnerability assessment, along with machine learning algorithms, suitable for intrusion detection and prevention of cyber-attacks in SCADA systems has been detailed.…”
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    Classification of acute leukemia using image processing and machine learning techniques / Hayan Tareq Abdul Wahhab by Wahhab, Hayan Tareq Abdul

    Published 2015
    “…This combination resulted in a new algorithm we named CBCSA. Based on the Relative Ultimate Measurement Accuracy for Area, the proposed algorithm was able to achieve an accuracy of 96% and 94% in the extraction of the blast cell region and the nuclear region, respectively. …”
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    Intrusion Detection in Mobile Ad Hoc Networks Using Transductive Machine Learning Techniques by Farhan, Farhan Abdel-Fattah Ahmad

    Published 2011
    “…Moreover, the algorithm can provide a graded confidence that indicates the reliability of the classification. …”
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    Automated feature extraction on brain MRI images for predicting multiple sclerosis patient disability by M. Muslim, Ali

    Published 2022
    “…This was based on machine learning and regression algorithms at the first phase. …”
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    Mathematical simulation for 3-dimensional temperature visualization on open source-based grid computing platform by Alias, Norma, Satam, Noriza, Abd. Ghaffar, Zarith Safiza, Darwis, Roziha, Hamzah, Norhafiza, Islam, Md. Rajibul

    Published 2009
    “…The development of this architecture is based on several programming language as it involves algorithm implementation on C, parallelization using Parallel Virtual Machine (PVM) and Java for web services development. …”
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