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Keyword: OutlierBathtub-Shape Failure Rate Life Time Model in a New Version with the use of Bayesian Prediction Bounds for the Presence of Outliers
The present article explains obtaining of the Bayesian prediction bounds at the maximum and minimum rate taking into account the results of future observation from a new version of a bathtub-shape failure rate distribution of life time type in the presence of outliers. The Type-II censored sample serves as a basis for the intervals of…
Read MorePerformance of Robust Confidence Intervals for Estimating Population Mean Under Both Non-Normality and in Presence of Outliers
We proposed two robust confidence interval estimators, namely, the median interquartile range confidence interval (MDIQR) and the trimean interquartile range confidence interval (TRIQR) for the population mean (µ) as an alternative to the classical confidence interval. The proposed methods are based on the asymptotic normal theorem (ANT) for the sample median (MD) and the sample…
Read MoreReview on Outliers Identification Methods for Univariate Circular Biological Data
Circular data are common in biological studies which are involved angle and direction measurements. An outlier in circular biological data mostly related to the abnormality of the data set. The existence of outliers may affect the final outcome of a data analysis. Thus, an outliers’ identification method is essential in circular biological data to determine…
Read MoreCommunity Detection in Social Network with Outlier Recognition
Exploring communities and outliers in Social Network is based on considering of some nodes have overlapped neighbor node within the same group as well as some nodes have no any link to the other node or have no any overlapped value. The existing approaches are based on the overlapping community detection method were only defined…
Read MorePredictive Analytics in Marketing: Evaluating its Effectiveness in Driving Customer Engagement
Understanding and responding to customer feedback is critical for business success. Customer response data offers valuable insights into preferences, behaviours, and sentiment. By analysing this data, businesses can optimize strategies, enhance customer experiences, and drive growth. Many analysis have been conducted in this field, while the review covers a broad range of AI and ML…
Read MoreEfficiency Comparison in Prediction of Normalization with Data Mining Classification
In research project, efficiency comparison study in prediction of normalization with data mining classification. The purpose of the research was to compare three normalization methods in term of classification accuracy that the normalized data provided: Z-Score, Decimal Scaling and Statistical Column. The six known classifications: K-Nearest Neighbor, Decision Tree, Artificial Neural Network, Support Vector Machine,…
Read MoreKamphaeng Saen Beef Cattle Identification Approach using Muzzle Print Image
Identification of Kamphaeng Saen beef cattle is important of the registration and traceability purposes. For a traditional identification methods, Hot Branding, Freeze Branding, Paint Branding, and RFID Systems can be replaced by genius human. This paper proposed a Kamphaeng Saen beef cattle identification approach using muzzle print images as an Animal Biometric approach. There are…
Read MoreApplication of EARLYBREAK for Line Segment Hausdorff Distance for Face Recognition
The Hausdorff distance (HD) is defined as MAX-MIN distance between two geometric objects for measuring the dissimilarity between two objects. Because MAX-MIN distance is sensitive with the outliers, in face recognition field, average Hausdorff distance is used for measuring the dissimilarity between two sets of features. The computational complexity of HD, and also average HD,…
Read MoreNonlinear \(\ell_{2,p}\)-norm based PCA for Anomaly Network Detection
Intrusion detection systems are well known for their ability to detect internal and external intrusions, it usually recognizes intrusions through learning the normal behaviour of users or the normal traffic of activities in the network. So, if any suspicious activity or behaviour is detected, it informs the users of the network. Nonetheless, intrusion detection system…
Read MoreImproved Nonlinear Fuzzy Robust PCA for Anomaly-based Intrusion Detection
Among the most popular tools in security field is the anomaly based Intrusion Detection System (IDS), it detects intrusions by learning to classify the normal activities of the network. Thus if any abnormal activity or behaviour is recognized it raises an alarm to inform the users of a given network. Nevertheless, IDS is generally susceptible…
Read MoreLow-Dimensional Spaces for Relating Sensor Signals with Internal Data Structure in a Propulsion System
Advances in technology have enabled the installation of an increasing number of sensors in various mechanical systems allowing for more detailed equipment health monitoring capabilities. It is hoped the sensor data will enable development of predictive tools to prevent system failures. This work describes continued analysis of sensor data surrounding a seizure of a turbocharger…
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