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Detecting Remote-To-Local (R2L) attack using Decision Tree algorithm / Ahmad Nasreen Aqmal Mohd Nordin by Mohd Nordin, Ahmad Nasreen Aqmal

“…The project successfully achieves its predetermined objectives, culminating in the development of an effective Remote to Local (R2L) Intrusion Detection System utilizing the Decision Tree algorithm. …”
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E2IDS: an enhanced intelligent intrusion detection system based on decision tree algorithm by Bouke, Mohamed Aly, Abdullah, Azizol, ALshatebi, Sameer Hamoud, Abdullah, Mohd Taufik

“…Fortunately, Artificial Intelligence (AI) has recently attracted a lot of attention, and it is now a principal component of these systems. This work presents an enhanced intelligent intrusion detection model (E2IDS) to detect state of the art known cyberattacks. …”
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The effect of different distance measures in detecting outliers using clustering-based algorithm for circular regression model by Nur Faraidah, Muhammad Di, Siti Zanariah, Satari

“…Outlier detection in linear data sets has been done vigorously but only a small amount of work has been done for outlier detection in circular data. …”
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Machine Learning Algorithm for Malware Detection: Taxonomy, Current Challenges, and Future Directions by Gorment N.Z., Selamat A., Cheng L.K., Krejcar O.

A Recent Research on Malware Detection Using Machine Learning Algorithm: Current Challenges and Future Works by Gorment N.Z., Selamat A., Krejcar O.

Assesment of robust tree detection technique for inter row trees tracking UAV based on simultaneous localization method / Norashikin M. Thamrin and Nor Hashim Mohd. Arshad by M. Thamrin, Norashikin, Mohd. Arshad, Nor Hashim

“…UAV has not been specifically designed to function on row tracking but has been used as platform for tree detection from aerial platform view, however such technique, inherit problems in identifying individual trees from different row with narrow inter-row spaces or recognizing row that is completely covered by multi-layered tree crowns.…”
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Intrusion Detection Systems, Issues, Challenges, and Needs by Aljanabi, Mohammad, Mohd Arfian, Ismail, Ali, Ahmed Hussein

“…However, these algorithms suffer from many lacks especially when apply to detect new type of attacks, and need for new algorithms such as JAYA algorithm, teaching learning-based optimization algorithm (TLBO) algorithm is arise. …”
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Application Of Multi-Layer Perceptron Technique To Detect And Locate The Base Of A Young Corn Plant by Morshidi, Malik Arman

“…Another structure of MLP trained using backpropagation algorithm is used to detect and locate the base of the young corn tree using the skeleton of the segmented image. …”
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Image Based Oil Palm Tree Crowns Detection by Muhammad Afif Zakwan, Zaili

“…Image Based Oil Palm Tree Crowns Detection system is a basic system that enables the detection of oil palm tree crowns from red, green and blue (RGB) aerial images. …”
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Cloud Worm Detection and Response Technique By Integrating The Enhanced Genetic Algorithm An Threat Level by Hasan Mahmoud Sha'ban Kanaker

Improving performance of automated coronary arterial tree center-line extraction, stent localization and tracking by Boroujeni, Farsad Zamani

“…The first contribution is automatic detection of seed points which serve as a prerequisite step for centerline extraction algorithm. …”
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Polymorphic malware detection based on dynamic analysis and supervised machine learning / Nur Syuhada Selamat by Selamat, Nur Syuhada

“…The benefit of this work indicated that the implementation of a feature selection technique plays an important role in machine learning algorithms to increase the performance of detection.…”
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An intelligent DDoS attack detection tree-based model using Gini index feature selection method by Bouke, Mohamed Aly, Abdullah, Azizol, ALshatebi, Sameer Hamoud, Abdullah, Mohd Taufik, Atigh, Hayate El

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Correlation analysis and predictive performance based on KNN and decision tree with augmented reality for nuclear primary cooling process / Ahmad Azhari Mohamad Nor by Mohamad Nor, Ahmad Azhari

“…Subsequently, predictive models employing k-nearest neighbour and decision tree algorithms are constructed and evaluated based on accuracy, precision, and recall metrics. …”
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Translating conventional wisdom on chicken comb color into automated monitoring of disease-infected chicken using chromaticity-based machine learning models by Bakar M.A.A.A., Ker P.J., Tang S.G.H., Baharuddin M.Z., Lee H.J., Omar A.R.

“…Logistic Regression, Support Vector Machines (SVMs), K-Nearest Neighbors (KNN), and Decision Trees have been developed to detect infected chickens using the chromaticity data. …”

Evaluating the performance of machine learning techniques in the classification of Wisconsin Breast Cancer by Obaid, Omar Ibrahim, Mohammed, Mazin Abed, Abd Ghani, Mohd Khanapi, A. Mostafa, Salama, AL-Dhief, Fahad Taha

“…In this paper, three machine-learning algorithms (Support Vector Machine, K-nearest neighbors, and Decision tree) have been used and the performance of these classifiers has been compared in order to detect which classifier works better in the classification of breast cancer. …”
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Cancer Prediction Based On Data Mining Using Decision Tree Algorithm by Loh, Kin Ming

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Early detection of basal stem rot disease (Ganoderma) in oil palms based on hyperspectral reflectance data using pattern recognition algorithms by Liaghat, Shohreh, Ehsani, Reza, Mansor, Shattri, Mohd Shafri, Helmi Zulhaidi, Meon, Sariah, Sankaran, Sindhuja, Azam, Siti H. M. N.

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Data Classification and Its Application in Credit Card Approval by Thai , VinhTuan

“…This project is involved with identification of the available algorithms used in data classification and the implementation of C4.5 decision tree induction algorithm in solving the data classifying task. …”
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Drowsiness Detection Using Ocular Indices from EEG Signal by Tarafder, S., Badruddin, N., Yahya, N., Nasution, A.H.

“…Recently, there has been considerable interest in utilizing features extracted from electroen-cephalography (EEG) signals to detect driver drowsiness. However, in most of the work performed in this area, the eyeblink or ocular artifacts present in EEG signals are considered noise and are removed during the preprocessing stage. …”
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