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Robust remote heart rate estimation from multiple asynchronous noisy channels using autoregressive model with Kalman filter by Nooralishahi, Parham, Loo, Chu Kiong, Shiung, Liew Wei

“…The results of three experiments demonstrate that our algorithm substantially outperforms all previous methods. …”
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An integrated anomaly intrusion detection scheme using statistical, hybridized classifiers and signature approach by Mohamed Yassin, Warusia

“…Thus, IADS is a better solution for anomaly detection methods in detecting untrustworthy behaviour and to define attack and normal behaviours more accurately.…”
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Fault detection and diagnosis using rule-based support system on fatty acid fractionation column by Yann, H. H., Ali, Mohamad Wijayanuddin, Kamsah, Mohd Zaki

“…Process history based methods (rule-based feature extraction) is used to implement the FDD rule-based support system. …”
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Automated detection and evaluation of ischemic stroke on ct brain imaging using machine learning techniques by Sharuddin, Nur Amirah Atikah

“…This study investigates the application of machine learning algorithms for the detection of ischemic stroke using CT brain images. …”
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Computer-aided diagnosis of diabetic subjects by heart rate variability signals using discrete wavelet transform method by Acharya, U.R., Sudarshan, V.K., Ghista, D.N., Lim, W.J.E., Molinari, F., Sankaranarayanan, M.

“…These features are ranked by using various ranking methods, namely, Bhattacharyya space algorithm, t-test, Wilcoxon test, Receiver Operating Curve (ROC) and entropy. …”
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Ultrasound-based tissue characterization and classification of fatty liver disease: A screening and diagnostic paradigm by Acharya, U.R., Faust, O., Molinari, F., Sree, S.V., Junnarkar, S.P., Sudarshan, V.

“…In this paper, we first review the advantages and limitations of different diagnostic methods which are currently available to detect FLD. …”
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Algorithm enhancement for host-based intrusion detection system using discriminant analysis by Dahlan, Dahliyusmanto

“…Anomaly detection algorithms model normal behavior. Anomaly detection models compare sensor data to normal patterns learned from the training data by using statistical method and try to detect activity that deviates from normal activity. …”
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A study on advanced statistical analysis for network anomaly detection by Ngadi, Md. Asri, Idris, Mohd. Yazid, Abdullah, Abd. Hanan

“…Anomaly detection algorithms model normal behavior. Anomaly detection models compare sensor data to normal patterns learned from the training data by using statistical method and try to detect activity that deviates from normal activity. …”
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Adaptive grid-meshed-buffer clustering algorithm for outlier detection in evolving data stream by Abdulateef, Alaa Fareed

“…This research introduces Adaptive Grid-Meshed-Buffer Stream Clustering Algorithm (AGMB), that addresses these weaknesses and improves outlier detection. …”
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Integrating genetic algorithms and fuzzy c-means for anomaly detection by Chimphlee, Witcha, Abdullah, Abdul Hanan, Sap, Noor Md., Chimphlee, Siriporn, Srinoy, Surat

“…In this paper we propose an intrusion detection method that combines Fuzzy Clustering and Genetic Algorithms. …”
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Weighting method for modal parameter based damage detection algorithms by Fayyadh, M.M., Abdul Razak, H.

“…This study proposes weighting method for damage detection algorithms based on the bending mode shapes for beam structures. …”
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Autonomous anomaly detection using density-based features in streaming data / Muhammmad Yunus Iqbal Basheer by Iqbal Basheer, Muhammmad Yunus

“…Hence, it is critical for an anomaly detection algorithm to detect data anomalies patterns. …”
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Anomaly behavior detection using flexible packet filtering and support vector machine algorithms by Abdul Wahid, Mohammed N.

“…The User Profile Filter (UPF) was proposed to aid the SVM algorithm to classify the captured traffics into normal and abnormal behavior. …”
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A clustering-based method for outlier detection under concept drift by Tahir, Mahjabeen, Abdullah, Azizol, Udzir, Nur Izura, Kasmiran, Khairul Azhar

“…Anomaly-based strategies, diverging from traditional signature-based methods, gain popularity for their effectiveness in detecting new attacks. …”
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A traffic signature-based algorithm for detecting scanning internet worms by M. Rasheed, Mohammad, Ghazali, Osman, Md Norwawi, Norita, M. Kadhum, Mohammed

“…The proposed method has two algorithms. The first part is an Intelligent Failure Connection Algorithm (IFCA) using Artificial Immune System; IFCA is concerned with detecting the internet worm and stealthy worm. …”
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Early detection and mitigation of DDoS attacks in software defined networks by Al-Saadi, Mustafa Yahya Zakariya

“…To find the proper detection threshold a series of tests on different scenarios of normal and attack traffic were conducted. …”
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An efficient attack detection for Intrusion Detection System (IDS) in internet of medical things smart environment with deep learning algorithm by Abdulkareem, Fatimah Saleem, Mohd Sani, Nor Fazlida

“…To achieve this, we measured the performance of three deep learning algorithms for normal and abnormal detection of IDS, and a comparison was made to select the best performance of the deep learning algorithm for detection in IDS, such as RNN, DBN and CNN. …”
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Glove defect detection using image processing / Farid Zuhri Kamal by Kamal, Farid Zuhri

“…Glove defect detection using image processing is a convenient method to identify failure in glove production industry. …”
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An efficient intrusion detection model based on hybridization of artificial bee colony and dragonfly algorithms for training multilayer perceptrons by Ghanem, Waheed Ali H. M., Aman, Jantan, Ahmed Ghaleb, Sanaa Abduljabbar, Naseer, Abdullah B.

“…The results of our experiments have demonstrated a significant improvement in inefficient network intrusion detection over other classification methods.…”
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Integrated face detection approach for far image application by Salka, Tanko Daniel

“…The noise reduction method in the proposed algorithm consists of a combination of a morphological filter and a rejection method. …”
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