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57 articles for “Anomalies”
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Research ArticleOpen accessIn the abstractA Comparative Study of Resampling, Cost-Sensitive, and Ensemble Techniques for Handling Class Imbalance in Indonesian Financial DataGunawan Kurnia, Ditdit Nugeraha UtamaHandling class imbalance is a critical challenge in machine learning applications, particularly in financial domains where minority instances often represent significant anomalies such as fraud or audit risks. Various oversampling and undersampling methods were tested, alongside cost-sensitive adjustments and ensemble models including Random Forest, AdaBoost, Gradient Boosting, and XGBoost. The evaluation, based on 10-fold stratified cross-validation and performance metrics such … …Journal of Computer Science, Vol. 22, Issue 2 · 27 Feb 2026 · 1,874 accessesView PDFCite
Research ArticleOpen accessIn the abstractOptimized XGBoost for Ethereum Fraud Detection: A Cost-Sensitive ApproachSupriya P., Rubah Sheriff, Shreya Padaki et al.In today’s technologically advancing world, many fields from finance to healthcare and education are shifting toward a digital and decentralized format. A significant transformation is underway with the currency of the masses. Blockchain-based cryptocurrencies like Bitcoin and Ethereum allow users to generate fungible tokens anonymously through smart contracts. However, these features also facilitate illicit transactions and cybercrimes like fraud, phishing, … …Journal of Computer Science, Vol. 21, Issue 12 · 10 Jan 2026 · 2,770 accessesView PDFCite
Research ArticleOpen accessIn the abstractAutoregressive Integrate Mean Average as Approaches for Modeling Energy Production in the Electricity Network by Seasons of the Electric Energy Company in Lomé, TogoApaloo Bara Komla Kpomonè et al.The work accumulated in this article presents the results of modeling the tduction of electrical energy for the CEET network in Lomé, Togo, taking into account the seasons of the area. The objective is to evaluate the forecasts over the periods in relation to the seasons of the year. Four seasons are detected, namely: Long dry season, long rainy season, … …American Journal of Engineering and Applied Sciences, Vol. 17, Issue 4 · 20 Dec 2024 · 3,922 accessesView PDFCite
Research ArticleOpen accessIn the abstractLung Cancer Detection Using Regularized Extreme Learning Machine and PCA FeaturesK. Kavitha, Dr. V. Saravana Kumar, V. Bhoopathy et al.When finding abnormalities in target images is time-sensitive, as it is with many cancer tumors, image processing techniques have recently found widespread use across various medical industries to improve images for early detection and treatment stages. In the setting of cancer, where time is of the essence in detecting anomalies within medical imaging, our research takes on further urgency. In … …Journal of Computer Science, Vol. 20, Issue 10 · 5 Aug 2024 · 5,302 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Novel Anomaly Detection Approach for Nifty Stocks using Machine Learning for Construction of Efficient Portfolio to Reduce Losses and Protect GainsVirrat Devaser, Priyanka ChawlaMachine Learning is the most essential and widely utilized methodological approach these days for performing, organizing, and analyzing data using a variety of approaches to produce correct and efficient results. Machine learning methodologies are also applicable to stock markets, which have grown multi-fold in recent years, and with the amount of money involved, the possibility of manipulation is always present … …Journal of Computer Science, Vol. 18, Issue 5 · 6 Jun 2022 · 6,443 accessesView PDFCite
Research ArticleOpen accessIn the abstractAnalysis of Photosynthetic Pigment Content and Leaf Structure of Pteroceltis Tatarinowii Mutant with Yellow LeafYongchang Yu, Chen Lv, Min Liu, Tiantian ChenThe relationship betweenleaf variation characteristics and leaf structure characteristics of Pteroceltistatarinowii with yellow leaf was explored to provide a theoretical basisfor the breeding of other ornamental plants. In this study, the differences inpigment content, leaf structure, and chloroplast ultrastructure in leaves of Pteroceltistatarinowii mutant with yellow leaf 'Huiguang' and its original species'Lingyansi No. 1’ were studied. The results showed that … …American Journal of Biochemistry and Biotechnology, Vol. 18, Issue 3 · 20 Sep 2022 · 5,598 accessesView PDFCite
Research ArticleOpen accessIn the abstractAnomaly Detection Algorithms for Streaming Data: Performance ComparisonZirije HasaniToday’s most of the data are streaming time-series data, where is very important anomaly detection over this data because gives significant information of possible critical situations. Detecting anomalies in big streaming data is yet difficult task because we have to process them in real time, even before they are stored and instantly alarm on potential threats. For real time streaming … …Journal of Computer Science, Vol. 16, Issue 7 · 18 Jul 2020 · 7,288 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Clustering based Approach for Contextual Anomaly Detection in Internet of ThingsDina ElMenshawy, Waleed Helmy, Neamat El-TaziInternet of Things (IoT) is a network which connects different communication devices with the internet to attain quick, robust and real-time information transfer and communication, achieving intelligent management. IoT is still in its infancy so it faces numerous challenges varying from data management to security concerns. Sensors generate enormous quantities of data that need to be handled efficiently to have … …Journal of Computer Science, Vol. 15, Issue 8 · 24 Aug 2019 · 7,582 accessesView PDFCite
Research ArticleOpen accessIn the abstractReal Time Anomaly Detection in Massive Data Streams with ELK StackJakup Fondaj, Zirije HasaniReal time anomaly detection is very popular topic nowadays this because the number of data generated every day is larger and larger. Facing with the phenomena of Big Data is not an easy task. The main aim of this research is to fine appropriate architecture for real-time big data analytic and its main task is to detect anomalies in this … …Journal of Computer Science, Vol. 15, Issue 6 · 17 Jun 2019 · 7,794 accessesView PDFCite
Research ArticleOpen accessIn the abstractGeochemical and Petrology Properties of Zafarghand Index and Kahang Deposit of Porphyry Copper-MolybdenumMohsen Dehghanipoodeh, Hooshang Asadi Haroni, Mahin Mansouri Esfahani et al.The probability of the occurrence of porphyry copper ore associated with subduction zone of the Neo-Tethys ocean and volcanic arc of Iran (Urumieh-Dokhtar) justifies the necessity of exploration and prospection of this type of ore in Iran. Zafarghand index and Kahang deposit of porphyry copper-molybdenum located in Isfahan province, center of Iran using Satellite data interpretations were discovered in the … …American Journal of Engineering and Applied Sciences, Vol. 13, Issue 4 · 19 Nov 2020 · 6,796 accessesView PDFCite