Search Results - (( variable activation detection algorithm ) OR ( java application tree 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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Study and Implementation of Data Mining in Urban Gardening
Published 2019“…Using the J48 tree algorithm implemented through WEKA API on a Java Servlet, data provided is processed to derive a health index of the plant, with the possible outcomes set to “Good,” “Okay”, or “Bad”. …”
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Mining Sequential Patterns using I-PrefixSpan
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Citation Index Journal -
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Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde
Published 2022“…This thesis is based on the application of sentiment classification algorithm to tweet data with the goal of classifying messages based on the polarity of sentiment towards a particular topic (or subject matter). …”
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Automated QT interval measurement using modified Pan-Tompkins algorithm with independent isoelectric line approach
Published 2020“…The performance of the algorithm achieved a sensitivity of 100% for QRS onset detection and 100% for T offset detection. …”
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MotionSure: a cloud-based algorithm for detection of injected object in data in motion
Published 2017“…Mostly, the Man In The Middle (MITM) attack happens in this stage by hijacking active session variables, manipulating files and objects. …”
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Proceeding Paper -
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SIMULATION AND ANALYSIS OF HARMONIC DETECTION AND MITIGATION SYSTEM USING ACTIVE FILTER
Published 2019“…The main objective for this study is to analyse the harmonics components in AC power system using Fast Fourier Transforms (FFT) algorithm. Other than that, the objective is also to design and develop the harmonic detection system for power quality of AC power system. …”
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Final Year Project Report / IMRAD -
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Mining Sequential Patterns Using I-PrefixSpan
Published 2007“…In this paper, we propose an improvement of pattern growth-based PrefixSpan algorithm, called I-PrefixSpan. The general idea of I-PrefixSpan is to use the efficient data structure for general tree-like framework and separator database to reduce the execution time and memory usage. …”
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Conference or Workshop Item -
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Multi-sensor fusion and deep learning framework for automatic human activity detection and health monitoring using motion sensor data / Henry Friday Nweke
Published 2019“…Human activity detection through fusion of multimodal sensors are vital steps to achieve automatic and comprehensive monitoring of human behaviours, build smart home systems and detect sports activities. …”
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AI powered asthma prediction towards treatment formulation: an android app approach
Published 2022“…We utilized eight robust machine learning algorithms to analyze this dataset. We found that the Decision tree classifier had the best performance, out of the eight algorithms, with an accuracy of 87%. …”
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DESIGN AND IMPLEMENTATION OF INTELLIGENT MONITORING SYSTEMS FOR THERMAL POWER PLANT BOILER TRIPS
Published 2011“…The first intelligent monitoring system represents the use of the pure artificial neural network system for boiler trip detection. The final architecture for this system has been explored after investigation of various main neural network topology combinations which include one and two hidden layers, one to ten neurons for each hidden layer, three types of activation function, and four types of multidimensional minimization training algorithms. …”
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Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad
Published 2018“…This improved algorithm, known as the edge-template Contour Delineation (etCD), is based on the fusion of edge detection with corner-template detection and dynamic thresholding to produce enhanced edge map. …”
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AI powered asthma prediction towards treatment formulation : An android app approach
Published 2022“…We utilized eight robust machine learning algorithms to analyze this dataset. We found that the Decision tree classifier had the best performance, out of the eight algorithms, with an accuracy of 87%. …”
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A peer-to-peer blockchain based interconnected power system
Published 2021“…It describes the simulation analysis and reduction of harmonics detection in a peer-to-peer interconnected 3-phase power system with the help of an FFT algorithm. …”
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Analyzing land surface temperature in response to massive urbanization by using single window algorithm in Penang Island / Ainna Naeemah Zainal Abidin
Published 2019“…Large scales of human activities are continuously increasing the area which can be term as urban. …”
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An integrated anomaly intrusion detection scheme using statistical, hybridized classifiers and signature approach
Published 2015“…Intrusion detection systems (IDSs) effectively balance additional security in a computer system by identifying intrusive activities on a computer system, and their enhancements are developing at a surprising rate. …”
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Rough Neural Networks Architecture For Improving Generalization In Pattern Recognition
Published 2004“…The RSNN provides a novel methodology for designing nonlinear filters without prior knowledge of the problem domain. The RNN was used to detect patterns present in satellite image. A novel feature extraction algorithm was developed to extract the feature vectors. …”
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Thesis -
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New synchronization protocol for distributed system with TCP extension
Published 2013“…In the worst condition, it optimized 3.99% higher than the most fault-tolerant previous works. The resulting algorithm does not involve variability in the hardware type nor is it based on specific distributed application software or databases. …”
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