Search Results - (( data selection sensor algorithm ) OR ( data detection method algorithm ))
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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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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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Data redundancy reduction scheme for data aggregation in wireless sensor network
Published 2020“…This research proposes Data Redundancy Reduction Scheme (DRRS) which includes three algorithms namely, Metadata Classification (MC), Selection Active Nodes (SAN) and Anomaly Detection (AD) algorithms that works before data aggregation, when multiple composite events simultaneously occur in the different locations within the cluster. …”
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Survey on Clustered Routing Protocols Adaptivity for Fire Incidents: Architecture Challenges, Data Losing, and Recommended Solutions
Published 2025“…Clustering in WSNs is a reliable method of effectively transferring data within the network through routing. …”
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Vibration-based structural damage detection and system identification using wavelet multiresolution analysis / Seyed Alireza Ravanfar
Published 2017“…However, most of existing damage detection methods requires reference data which are not always available. …”
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Void avoidance opportunistic routing density rank based for underwater sensor networks
Published 2021“…Finally, the algorithm Void Avoidance Opportunistic Routing Density Rank Based (ORDRB) was developed to deal with the communication void by introducing a simple method to detect a void node and avoid it during the forwarding process. …”
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Totally opportunistic routing algorithm for underwater wireless sensor network
Published 2019“…Whereas in NA-TORA, Expected Transmission Count (ETX) and residual energy of a node are considered for data transmission to ensure packet delivery. The suggested data forwarding algorithms are designed to abstain horizontal transmission, to lower end to end delay and improve throughput and energy efficiency. …”
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Spectral discrimination and index development of roofing materials and conditions using field spectroscopy and worldview-3 satellite image
Published 2016“…Three feature selection algorithms of Genetic Algorithm (GA), Support Vector Machine (SVM) and Random Forest (RF) were used to select the most significant wavelengths since the algorithms works well with large size of data and widely applied for feature selection of hyperspectral remote sensing data. …”
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Fault detection and diagnosis using correlation coefficients
Published 2005“…Faults considered in the research are sensor faults, valve faults and controller faults generated in the fault data (OC). …”
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An acquisition and a modulated recognition system for driver profiling in Malaysia / Ward Ahmed Alaulddin Al-Hussein
Published 2022“…Previous studies in Malaysia relied on simulators, questionnaires, and surveys to collect driving data. Such methods were criticized for being biased and untrustworthy. …”
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Configuration and analysis of piezoelectric-based in socket sensory system for transfemoral prosthetic Gait detection / Farahiyah Jasni
Published 2018“…The methodology comprised of selecting: (a) the best piezoelectric sensor to be used in terms of the material, size and shape, (b) the method of mounting the sensors onto the socket, and (c) the placement of the sensors. …”
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Forensic language of property theft genre based on mathematical formulae and machine learning algorithms / Hana' Abd Razak
Published 2020“…Four traits was discovered namely spine, pelvis, knee and ankle. Next, data collection of normal and anomalous behaviour is collected using Kinect sensor. …”
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Pipe Leak Diagnostic Using High Frequency Piezoelectric Pressure Sensor And Automatic Selection Of Intrinsic Mode Function
Published 2017“…However, the advantage of HHT is its difficulty in selecting the suitable IMF for the next data postprocessing method which is Hilbert Transform (HT). …”
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Imaging of solid flow in a gravity flow rig using infra-red tomography
Published 2005“…The software development involves data acquisition system, sensor modeling, image algorithms, and programming for a tomographic display to provide solids flow information in pipeline such as concentration and velocity profiles. …”
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A performance comparison study of pattern recognition systems for volatile organic compounds detection / Emilia Noorsal, Muhammad Khusairi Osman and Norfadzilah Mokhtar
Published 2007“…It is well known that the use of a gas sensor array and pattern recognition system offers an effective technique for the identification of volatile organic molecules because of the poor selectivity of a lot of other gas sensors. …”
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Research Reports -
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Wavelet based fault tolerant control of induction motor / Khalaf Salloum Gaeid
Published 2012“…The fault detection algorithm identifies the time and location of each fault. …”
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Effect of LiDAR mounting parameters and speed on HDL graph SLAM-Based 3D mapping for autonomous vehicles
Published 2025“…HDL Graph SLAM was selected as the offline post-processing method due to its self-correcting functions for estimating and auto-correcting positional errors from LiDAR data. …”
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Whale optimization algorithm based on tent chaotic map for feature selection in soft sensors
Published 2025“…The soft sensor was designed using several stages, including data collection, preprocessing, clustering, feature selection, and classification. …”
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Oil palm female inflorescences anthesis stages identification using selected emissivities through thermal imaging and Machine Learning
Published 2022“…This research studies different Machine Learning (ML) classification and ensemble techniques for the assessment of the four pollination stages consist of pre-anthesis I, pre-anthesis II, pre-anthesis III, and anthesis using thermal imaging. Different ML algorithms such as Random Forest (RF), k Nearest Neighbor (kNN), Support Vector Machine (SVM), Artificial Neural Network (ANN) as well as an ensemble method are used on data extracted from thermal images collected during infield oil palms pollination stages monitoring. …”
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