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method algorithm » mould algorithm (Expand Search)
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method algorithm » mould algorithm (Expand Search)
using algorithm » cosine algorithm (Expand Search)
data detection » data injection (Expand Search)
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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. …”
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Unsupervised outlier detection in multidimensional data
Published 2022“…Furthermore, two proposed techniques presented in this paper use transformation of data to a unidimensional distance space to detect the outliers, so irrespective of the data’s high dimensions, the techniques remain computationally inexpensive and feasible. …”
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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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Improved Transportation Model with Internet of Things Using Artificial Intelligence Algorithm
Published 2023“…Furthermore, a route management technique is combined with Artificial Intelligence (AI) algorithm to transmit the data to appropriate central servers. …”
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Detecting sleep outside the clinic using wearable heart rate devices
Published 2022“…Personalized yet device-agnostic algorithms can sidestep laborious human annotations and objectify cross-cohort comparisons. …”
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An Effective Hash Based Assessment and Recovery Algorithm for Healthcare Systems
Published 2019“…Also, it is possible that the attack is not directly detected. Hence, this highlights the need for an algorithm that is capable of assessing the widespread damage scale before starting the repair of the inconsistent medical database. …”
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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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Novel Peak Detection Algorithms for Pileup Minimization in Gamma Ray Spectroscopy
Published 2006“…This study uses the above facility in developing algorithms for digitally determining the basic pulse parameters and tackling the problem of pulse pile-up in Gamma-ray spectroscopy. …”
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Meta-Heuristic Algorithm-Tuned Neural Network for Breast Cancer Diagnosis Using Ultrasound Images
Published 2022“…The main novelty of this work is the computer-aided diagnosis scheme for detecting abnormalities in breast ultrasound images by integrating a wavelet neural network (WNN) and the grey wolf optimization (GWO) algorithm. …”
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A Hybrid Intrusion Detection Model Using EGA-PSO and Improved Random Forest Method
Published 2022“…Machine learning (ML) methods are widely used in IDS. Due to a limited training dataset, an ML-based IDS generates a higher false detection ratio and encounters data imbalance issues. …”
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Ensemble-Based Spam Detection in Smart Home IoT Devices Time Series Data Using Machine Learning Techniques
Published 2020“…The obtained results illustrate the efficacy of the proposed algorithm to analyze the time series data from the IoT devices for spam detection.…”
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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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Capturing outline of fonts using genetic algorithm and splines
Published 2001“…We present a method to convert the original problem into a discrete combinatorial optimization problem and solve it by a genetic algorithm. We also incorporate a corner detection algorithm to detect significant points which are necessary to capture a pleasant looking spline fitting for shapes such as fonts. …”
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Android Malware Detection Using Machine Learning
Published 2024“…Detecting and preventing malware is crucial for several reasons, including the security of personal information, data loss and tampering, system disruptions, financial losses, and reputation damage. …”
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Online Recruitment Fraud (ORF) Detection Using Deep Learning Approaches
Published 2024“…In recent studies, traditional machine learning and deep learning algorithms have been implemented to detect fake job postings; this research aims to use two transformer-based deep learning models, i.e., Bidirectional Encoder Representations from Transformers (BERT) and Robustly Optimized BERT-Pretraining Approach (RoBERTa) to detect fake job postings precisely. …”
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The effects of data balancing approaches: A case study
Published 2023“…In this article, we present a case study approach for investigating the effects of data balancing approaches. The case study concerns the discrimination between growth hormone treated and non-treated animals using Liquid Chromatography-High Resolution Mass Spectrometry (LC-HRMS) data. …”
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