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  1. 1
    Epileptic Seizure Detection Using Singular Values And Classical Features Of EEG Signals

    Epileptic Seizure Detection Using Singular Values And Classical Features Of EEG Signals by Ahmed, Ahmed Elsayed Elmahdy

    Published 2014
    “…This project aims at developing an automated epileptic seizure event detection algorithm. The proposed algorithm depends on using five features which are singular values, total power, delta band power, variance and mean. …”
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  2. 2
    Focal and non-focal epilepsy localization: a review

    Focal and non-focal epilepsy localization: a review by Hussein, Ahmed Faeq, N., Arunkumar, Gomes, Gorakanage Arosha Chandima, Alzubaidi, Abbas K., Habash, Qais Ahmed, Granados, Luz Santamaria, Moreno, Juan Francisco Mendoza, Gonzalez, Gustavo Ramirez

    Published 2018
    “…This study reviews many recently-proposed algorithms for detecting the focal epileptic seizures. …”
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  3. 3
    Detection of partial seizure: An application of fuzzy rule system for wearable ambulatory systems

    Detection of partial seizure: An application of fuzzy rule system for wearable ambulatory systems by Shakir, Mohamed, Malik, Aamir Saeed, Kamel , Nidal, Qidwai, Uvais

    Published 2014
    “…This can be observed and the algorithm with the detection structure can produce cautioning signals for epileptic seizure.…”
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  4. 4
    Detection of partial seizure: An application of fuzzy rule system for wearable ambulatory systems

    Detection of partial seizure: An application of fuzzy rule system for wearable ambulatory systems by Shakir, M., Malik, A.S., Kamel, N., Qidwai, U.

    Published 2014
    “…This can be observed and the algorithm with the detection structure can produce cautioning signals for epileptic seizure. …”
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  5. 5
    Embedded fuzzy classifier for detection and classification of preseizure state using real EEG data

    Embedded fuzzy classifier for detection and classification of preseizure state using real EEG data by Qidwai, U., Malik, A.S., Shakir, M.

    Published 2014
    “…However, the common clinical methods are insufficient when it comes to design an automated module to detect and predict partial seizure for epileptic patients. …”
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  6. 6
    Fuzzy Platform for Embedded Wearable EEG Seizure Detection in Ambulatory State

    Fuzzy Platform for Embedded Wearable EEG Seizure Detection in Ambulatory State by Shakir, Mohamed, Malik, Aamir Saeed, Kamel , Nidal, Qidwai, Uvais

    Published 2014
    “…This paper describes a classification method is presented using an Fuzzy System to detect the occurrences of Partial Seizures from Epilepsy data, which can be implemented in any embedded system as a wearable detection system. …”
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  7. 7
    Rule-base wearable embedded platform for seizure detection from real EEG data in ambulatory state

    Rule-base wearable embedded platform for seizure detection from real EEG data in ambulatory state by Shakir, M., Malik, A.S., Kamel, N., Qidwai, U.

    Published 2014
    “…This paper describes a classification method is presented using an empirical Rule-base System to detect the occurrences of Partial Seizures from Epilepsy data, which can be implemented in any embedded system as a wearable detection system. …”
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  8. 8
    Embedded wearable EEG seizure detection in ambulatory state

    Embedded wearable EEG seizure detection in ambulatory state by Shakir, M., Malik, A.S., Kamel, N., Qidwai, U.

    Published 2014
    “…This paper describes a classification method is presented using a Fuzzy System to detect the occurrences of Partial Seizures from Epilepsy data, which can be implemented in any embedded system as a wearable detection system. …”
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  9. 9
    Detection of Epileptic EEG Signal Using Wavelet Transform and Adaptive Neuro-Fuzzy Inference System

    Detection of Epileptic EEG Signal Using Wavelet Transform and Adaptive Neuro-Fuzzy Inference System by Khosropanah, Pegah

    Published 2011
    “…Such algorithms use brain electrical activity signals called electro encephalography (EEG) and have 2 methods of detection: visual (by specialist inspection) and automatic (by using signal processing knowledge). …”
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  10. 10
    Embedded Fuzzy Classifier for Detection and Classification of Preseizure State Using Real EEG Data

    Embedded Fuzzy Classifier for Detection and Classification of Preseizure State Using Real EEG Data by Qidwai, Uvais, Malik, Aamir Saeed, Shakir, Mohamed

    Published 2013
    “…However, the common clinical methods are insufficient when it comes to design an automated module to detect and predict partial seizure for epileptic patients. …”
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  11. 11
    Rule-Base Wearable Embedded Platform for Seizure Detection from Real EEG Data in Ambulatory State

    Rule-Base Wearable Embedded Platform for Seizure Detection from Real EEG Data in Ambulatory State by Mohamed, Shakir, Malik, Aamir Saeed, Kamel , Nidal, Qidwai, Uvais

    Published 2014
    “…This paper describes a classification method is presented using an empirical Rule-base System to detect the occurrences of Partial Seizures from Epilepsy data, which can be implemented in any embedded system as a wearable detection system. …”
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  12. 12
    Intelligent Fuzzy Classifier for Pre-Seizure Detection from Real Epileptic Data

    Intelligent Fuzzy Classifier for Pre-Seizure Detection from Real Epileptic Data by Shakir, Mohamed, Malik, Aamir Saeed, Kamel, Nidal S., Qidwai, Uvais

    Published 2014
    “…In this paper, a classification method is presented using an Fuzzy Inference Engine to detect the incidences of preseizures in real/raw Epilepsy data. …”
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  13. 13
    Intelligent Fuzzy Classifier for pre-seizure detection from real epileptic data

    Intelligent Fuzzy Classifier for pre-seizure detection from real epileptic data by Shakir, M., Malik, A.S., Kamel, N., Qidwai, U.

    Published 2014
    “…In this paper, a classification method is presented using an Fuzzy Inference Engine to detect the incidences of pre-seizures in real/raw Epilepsy data. …”
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  14. 14
    Automatic identification of epileptic seizures from EEG signals using sparse representation-based classification

    Automatic identification of epileptic seizures from EEG signals using sparse representation-based classification by Sobhan Sheykhivand, Tohid Yousefi Rezaii, Zohreh Mousavi, Azra Delpak, Ali Farzamnia

    Published 2020
    “…Compared to state-of-the-art algorithms and other common methods, our method outperformed them in terms of sensitivity, specificity, and accuracy. …”
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  15. 15
    Swarm negative selection algorithm for electroencephalogram signals classification

    Swarm negative selection algorithm for electroencephalogram signals classification by Sahel Ba-Karait, Nasser Omer, Shamsuddin, Siti Mariyam, Sudirman, Rubita

    Published 2009
    “…Such automated systems must rely on robust and effective algorithms for detection and prediction. Approach: The proposed detection system of epileptic seizure in EEG signals is based on Discrete Wavelet Transform (DWT) and Swarm Negative Selection (SNS) algorithm. …”
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  16. 16
    Fuzzification of epileptic data: an application for prediction and identification of partial seizure

    Fuzzification of epileptic data: an application for prediction and identification of partial seizure by Malik, Aamir Saeed, Nasif, Mohammad Shakir, Kamel , Nidal, Qidwai, U.

    Published 2013
    “…However, these approaches fall short when attempting to design an automated system to detect and predict partial seizure for epileptic patients. …”
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  17. 17
    Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm

    Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm by Norulazmi, Kasim

    Published 2008
    “…The prototype system, known as Java Plagiarism Detection System (JPDS) implements the Greedy-String-Tiling algorithm to detect similarities among tokens in a Java source code files. …”
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  18. 18
    A simple predictive method of critical flicker detection for human healthy precaution

    A simple predictive method of critical flicker detection for human healthy precaution by Goh, Zai Peng, Mohd Radzi, Mohd Amran, Hizam, Hashim, Abdul Wahab, Noor Izzri

    Published 2015
    “…In a nutshell, this simple predictive method for critical flicker detection has strong potential to be applied in any human crowded places (such as offices, shopping complexes, and stadiums) for human healthy precaution purpose due to its simplicity.…”
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  19. 19
    An Educational Tool Aimed at Learning Metaheuristics

    An Educational Tool Aimed at Learning Metaheuristics by Kader, Md. Abdul, Jamaluddin, Jamal A., Kamal Z., Zamli

    Published 2020
    “…Implemented with Java, this tool provides a friendly GUI for setting the parameters and display the result from where the learner can see how the selected algorithm converges for a particular problem solution. …”
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  20. 20
    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde

    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde by Ogunfolajin Maruff , Tunde

    Published 2022
    “…The method was implemented using Java and the results of the simulation were evaluated using five standard performance metrics: accuracy, AUC, precision, recall, and f-Measure. …”
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