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Unsupervised outlier detection in multidimensional data
Published 2022“…<p>Detection and removal of outliers in a dataset is a fundamental preprocessing task without which the analysis of the data can be misleading. …”
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Development of an Optimization Algorithm for Internet Data Traffic
Published 2020“…The algorithm monitors data repetitions in IP datagram and prepares a compression code in response of this repetition. …”
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UAV-Aided Projection-Based Compressive Data Gathering in Wireless Sensor Networks
Published 2018“…Devices in such scenarios are normally extremely energy-constrained and often exist in large numbers and can be located in hard-to-reach areas; the fact that necessitates the design and implementation of effective energy-aware data collection mechanisms. To this end, we propose the utilization of Unmanned Aerial Vehicles (UAVs) to collect data in dense wireless sensor networks (WSNs) using projection-based Compressive Data Gathering (CDG) as a novel solution methodology. …”
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Energy-aware adaptive compression for mobile devices. (c2009)
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Use of Data Mining Techniques to Detect Fraud in Procurement Sector
Published 2022“…The method used in this research is a classification of models and algorithms used in data mining. All techniques also will be studied; they include clustering, tracking patterns, classifications and outlier detection. …”
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A Fuzzy Low-Dimensional Intersection Graph Representation Approach for Graph Compression and Anonymization
Published 2021“…The objective is to answer adjacency queries as accurately as possible and to achieve an effective compression. We examine several heuristic algorithms in an attempt to achieve these two main objectives and conduct a thorough experimental analysis providing evidence of the effectiveness of our graph mapping approach. …”
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Novel Peak Detection Algorithms for Pileup Minimization in Gamma Ray Spectroscopy
Published 2006“…Gamma pulses from a 3" Na(TI) scintillation detector were captured as single and double pulses for the purpose of testing the peak detection algorithms. The pulse classification technique was tested successfully on a TMS320C6000 high performance floating-point processor yielding a reduction of the execution time to 2 msec…”
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An image processing and genetic algorithm-based approach for the detection of melanoma in patients
Published 2018“…The second phase classifies lesions using a Genetic Algorithm. Our technique shows a significant improvement over other well-known algorithms and proves to be more stable on both training and testing data.…”
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Application of Machine Learning Algorithms to Enhance Money Laundering and Financial Crime Detection
Published 2011“…In order to analyze the performance of machine learning algorithms, data was provided by a bank to be used for educational purposes and shall remain undisclosed. …”
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Using machine learning algorithm for detection of cyber-attacks in cyber physical systems
Published 2022“…In addition, the framework outperforms conventional detection algorithms in words of detection rate, the rate of the false positive, and calculation time, respectively.…”
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Interval-Valued SVM Based ABO for Fault Detection and Diagnosis of Wind Energy Conversion Systems
Published 2022“…The proposed improved ABO method consists in reducing the number of samples in the training data set using the Euclidean distance and extracting the most significant features from the reduced data using ABO algorithm. …”
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Application of updated joint detection algorithm for the analysis of drilling parameters of roof bolters in multiple joints conditions
Published 2017“…This paper reviews testing procedures, data analysis, updated algorithms used for joint detection, and discusses the latest round of testing in samples with simulated joints at various angles along the borehole.…”
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Genetic-Algorithm-Based Neural Network for Fault Detection and Diagnosis: Application to Grid-Connected Photovoltaic Systems
Published 2022“…The classification performance is determined via different metrics for various GA-based ANN classifiers using data extracted from the healthy and faulty data of the GCPV system. …”
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Detecting latent classes in tourism data through response-based unit segmentation (REBUS) in Pls-Sem
Published 2016“…This research note describes Response-Based Unit Segmentation (REBUS), a “latent class detection” technique used in partial least squares–structural equation modeling (PLS-SEM) to examine data heterogeneity. …”
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