Search Results - (( sequence extraction method algorithm ) OR ( pattern detection method algorithm ))
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Classification and detection of intelligent house resident activities using multiagent
Published 2013“…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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Conference or Workshop Item -
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A study on component-based technology for development of complex bioinformatics software
Published 2004“…Based on the protein sequence datasets obtained from PISCES database, they found iii that the R-HCSVM performs outstanding result in predicting protein local structure from a given protein subsequence compared to other methods. …”
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Monograph -
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Whole-exome sequencing and bioinformatic analyses revealed differences in gene mutation profiles in papillary thyroid cancer patients with and without benign thyroid goitre backgro...
Published 2023“…Whole-exome sequencing (WES) was performed on genomic DNA extracted from thyroid tissue specimens. …”
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Article -
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Abnormal Pattern Detection In Ppg Signals Using Time Series Analysis
Published 2022“…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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Undergraduates Project Papers -
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Algorithm enhancement for host-based intrusion detection system using discriminant analysis
Published 2004“…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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Thesis -
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A study on advanced statistical analysis for network anomaly detection
Published 2005“…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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Monograph -
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Autonomous anomaly detection using density-based features in streaming data / Muhammmad Yunus Iqbal Basheer
Published 2023“…Hence, it is critical for an anomaly detection algorithm to detect data anomalies patterns. …”
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Thesis -
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Computational Technique for an Efficient Classification of Protein Sequences With Distance-Based Sequence Encoding Algorithm
Published 2017“…The major problems in classifying protein sequences into existing families/superfamilies are the following: the selection of a suitable sequence encoding method, the extraction of an optimized subset of features that possesses significant discriminatory information, and the adaptation of an appropriate learning algorithm that classifies protein sequences with higher classification accuracy. …”
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SOMEA: self-organizing map based extraction algorithm for DNA motif identification with heterogeneous model
Published 2011“…This assumption has some limitations because both sequence signals have distinct properties. Results: This paper aims to develop a Self-Organizing Map (SOM) based clustering algorithm for extracting binding sites in DNA sequences. …”
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Malignant transformation of benign thyroid nodule is caused by prolonged H2O2 insult that interfered with the STAT3 pathway?
Published 2016“…Whole-exome capture sequencing of extracted DNA from the PTC tissue revealed mutations of 1799 T>A (p.V600E) and c.353 G>A (p.R118Q) in the V-Raf Murine Sarcoma Viral Oncogene Homolog B (BRAF) and the Thyrotropin-Releasing Hormone (TRH) genes, respectively. …”
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Improving performance of automated coronary arterial tree center-line extraction, stent localization and tracking
Published 2012“…This problem is addressed by proposing an accurate and robust centerline extraction method. Starting at each detected seed point, the centerline extraction method utilizes eigenvalues and eigenvectors of Hessian matrix for the pixels located on a semi-circular scanning profile for robust estimation of the next centerline point. …”
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Thesis -
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Natural gas liquid (NGL) distillation process using driving force and thermal pinch analysis methods: Energy and economic assessment / Munawar Zaman Shahruddin ... [et al.]
Published 2020“…Then, the extracted data from the simulation will be used for thermal pinch analysis via problem table algorithm (PTA). …”
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Spectral texture segmentation of Magnetic Resonance Imaging (MRI) brain images for glioma brain tumour detection / Rosniza Roslan
Published 2013“…A new double thresholding algorithm and a fully automated multiple seed points selection algorithm that works on all three MRI image sequences are also proposed. …”
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Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak
Published 2019“…The first stage is to apply reverse engineering method to obtain the specific patterns of individual jammers. …”
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Thesis -
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Pattern Recognition Approach Of Stress Wave Propagation In Carbon Steel Tubes For Defect Detection
Published 2015“…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
Published 2019“…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
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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Cabbage disease detection system using k-NN algorithm
Published 2022“…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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