Search Results - (( pattern detection method algorithm ) OR ( variable integration based algorithm ))

Artificial immune system based on real valued negative selection algorithms for anomaly detection by Khairi, Rihab Salah

“…With respect to all the algorithms, V-Detector proved to be superior and surpassed all other algorithms based on performance and execution time.…”
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A simple model-free butterfly shape-based detection (BSD) method integrated with deep learning CNN for valve stiction detection and quantification by Kamaruddin, B., Zabiri, H., Mohd Amiruddin, A.A.A., Teh, W.K., Ramasamy, M., Jeremiah, S.S.

“…In this paper, a â��butterflyâ�� shape derived from the manipulation of the standard PV and OP data, which is more robust towards different loop dynamics, is developed for stiction detection. This simple model-free butterfly shape-based detection (BSD) method uses Stenman's one parameter stiction model, which results in a distinctive â��butterflyâ�� pattern in the presence of stiction. …”
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Landslide susceptibility mapping using decision-tree based chi-squared automatic interaction detection (CHAID) and logistic regression (LR) integration by Althuwaynee, Omar F., Pradhan, Biswajeet, Ahmad, Noordin

“…This article uses methodology based on chi-squared automatic interaction detection (CHAID), as a multivariate method that has an automatic classification capacity to analyse large numbers of landslide conditioning factors. …”
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Liver segmentation on CT images using random walkers and fuzzy c-means for treatment planning and monitoring of tumors in liver cancer patients by Moghbel, Mehrdad

“…The proposed segmentation is evaluated on real-world clinical data using publicly accessible benchmark clinical liver datasets containing one of the highest numbers of tumors and pathological livers utilized for liver tumor and vasculature segmentation. The proposed method is based on a hybrid method integrating random walkers algorithm with integrated priors and particle swarm optimized spatial fuzzy c-means (FCM) algorithm with level set method and AdaBoost classifier. …”
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An integrated anomaly intrusion detection scheme using statistical, hybridized classifiers and signature approach by Mohamed Yassin, Warusia

“…Detection methods based on statistical and data mining techniques are widely deployed as anomaly-based detection system (ADS). …”
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Abnormal Pattern Detection In Ppg Signals Using Time Series Analysis by Siti Nur Hidayah, Mazelan

“…This project’s objectives are to implement rule-based algorithm method for abnormal pattern detection in PPG signals, and to investigate the accuracy and performance of rule-based algorithm in detecting the abnormal pattern. …”
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Fraud detection in telecommunication using pattern recognition method / Mohd Izhan Mohd Yusoff by Mohd Yusoff, Mohd Izhan

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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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Moiré Method Based Tilt Sensing System For Landslides Monitoring Using Raspberry PI by Toh, Han Yaung

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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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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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Classification and detection of intelligent house resident activities using multiagent by ,, Mohd. Marufuzzaman, M. B. I., Raez, M. A. M., Ali, Rahman, Labonnah F.

“…The intelligent home research requires understanding of the human behavior and recognizing patterns of activities of daily living (ADL).However instead of understand the psychosomatic nature of human early projects in this area simply employed intelligence to the household appliance.This paper proposed an algorithm for detecting ADL.The proposed method is based on two opposite state entity extraction.The method reflects on the common data flow of smart home event sequence.The developed algorithm clusters the smart home events by isolating opposite status of home appliance. …”
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Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak by Dak, Ahmad Yusri

“…The first stage is to apply reverse engineering method to obtain the specific patterns of individual jammers. …”
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Pattern Recognition Approach Of Stress Wave Propagation In Carbon Steel Tubes For Defect Detection by Abd Halim, Zakiah, Jamaludin, Nordin, Junaidi, Syarif, Syed Yusainee, Syed Yahya

“…The pattern recognition results showed that the AR algorithm is more effective in defect identification. …”
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Automated Face Detection Using Skin Color Segmentation and Viola-Jones Algorithm by Ahmad Fakhri, Ab. Nasir, Ahmad Shahrizan, Abdul Ghani, Muhammad Aizzat, Zakaria, Anwar, P. P. Abdul Majeed, Ahmad Najmuddin, Ibrahim

“…Viola-Jones algorithm can be categorized as one of an established and effective method (feature-based approach) for detecting face. …”
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Swarm negative selection algorithm for electroencephalogram signals classification by Sahel Ba-Karait, Nasser Omer, Shamsuddin, Siti Mariyam, Sudirman, Rubita

“…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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Cabbage disease detection system using k-NN algorithm by Mohamad Ainuddin Sahimat

“…Then, the segmented cabbage sample will use the GLCM method for feature extraction. It is a method of extracting second-order statistical texture features to detect diseases more efficiently. …”
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Process fault detection and diagnosis using Boolean representation on fatty acid fractionation column by Othman, M. R., Ali, Mohamad Wijayanuddin, Kamsah, Mohd. Zaki

“…Through the proposed algorithm, various faults could be simulated and detected using the system. …”
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A Novel Algorithm for Breast Lesion Detection Using Textons and Local Configuration Pattern Features With Ultrasound Imagery by Acharya, U. Rajendra, Meiburger, Kristen M., Wei Koh, Joel En, Ciaccio, Edward J., Arunkumar, N., See, Mee Hoong, Mohd Taib, Nur Aishah, Vijayananthan, Anushya, Rahmat, Kartini, Fadzli, Farhana, Leong, Sook Sam, Westerhout, Caroline Judy, Chantre-Astaiza, Angela, Ramirez-Gonzalez, Gustavo

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Pattern Recognition for Human Diseases Classification in Spectral Analysis by Nur Hasshima Hasbi, Abdullah Bade, Fuei, Pien Chee, Muhammad Izzuddin Rumaling

“…Typically, pattern recognition consists of two components: exploratory data analysis and classification method. …”
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