Konu "Machine learning" için Fakülteler listeleme
Toplam kayıt 21, listelenen: 1-20
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Artificial Intelligence Based Intrusion Detection System for IEC 61850 Sampled Values Under Symmetric and Asymmetric Faults
(IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC445 HOES LANE, PISCATAWAY, NJ 08855-4141, 2021)Modern power systems require increased connectivity to implement novel coordination and control schemes. Wide-spread use of information technology in smartgrid domain is an outcome of this need. IEC 61850-based communication ... -
Automated quantification of immunomagnetic beads and leukemia cells from optical microscope images
(ELSEVIER SCI LTD, THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND, 2019)Quantification of tumor cells is crucial for early detection and monitoring the progress of cancer. Several methods have been developed for detecting tumor cells. However, automated quantification of cells in the presence ... -
Comparative analysis of machine learning approaches for predicting respiratory virus infection and symptom severity
(PEERJ INC, 2023)Respiratory diseases are among the major health problems causing a burden on hospitals. Diagnosis of infection and rapid prediction of severity without time-consuming clinical tests could be beneficial in preventing the ... -
A comprehensive experimental and modeling study of the strain rate- and temperature-dependent deformation behavior of bio-degradable Mg-CeO2 nanocomposites
(ELSEVIER, 2024)A comprehensive study was undertaken on the temperature-dependent and strain rate-sensitive deformation behavior of near-dense low-volume fraction magnesium-cerium dioxide (Mg-CeO2 ) nanocomposites synthesized by powder ... -
CoviDetector: A transfer learning-based semi supervised approach to detect Covid-19 using CXR images
(ELSEVIER, 2023)COVID-19 was one of the deadliest and most infectious illnesses of this century. Research has been done to decrease pandemic deaths and slow down its spread. COVID-19 detection investigations have utilised Chest X-ray ... -
EdgeAISim: A toolkit for simulation and modelling of AI models in edge computing environments
(ELSEVIER, 2024)To meet next-generation Internet of Things (IoT) application demands, edge computing moves processing power and storage closer to the network edge to minimize latency and bandwidth utilization. Edge computing is becoming ... -
An efficient network intrusion detection approach based on logistic regression model and parallel artificial bee colony algorithm
(ELSEVIER, 2024)In recent years, the widespread use of the Internet has created many issues, especially in the area of cybersecurity. It is critical to detect intrusions in network traffic, and researchers have developed network intrusion ... -
An empirical study of sentiment analysis utilizing machine learning and deep learning algorithms
(SPRINGER, 2023)Among text-mining studies, one of the most studied topics is the text classifcation task applied in various domains, including medicine, social media, and academia. As a sub-problem in text classifcation, sentiment ... -
Ensemble feature selection and classification methods for machine learning-based coronary artery disease diagnosis
(ELSEVIER, 2023)Coronary artery disease (CAD) is a condition in which the heart is not fed sufficiently as a result of the accumulation of fatty matter. As reported by the World Health Organization, around 32% of the total deaths in the ... -
Lung cancer subtype differentiation from positron emission tomography images
(TUBITAK SCIENTIFIC & TECHNICAL RESEARCH COUNCIL TURKEY, ATATURK BULVARI NO 221, KAVAKLIDERE, ANKARA, 00000, TURKEY, 2020)Lung cancer is one of the deadly cancer types, and almost 85% of lung cancers are nonsmall cell lung cancer (NSCLC). In the present study we investigated classification and feature selection methods for the differentiation ... -
Machine learning approaches for underwater sensor network parameter prediction
(ELSEVIER, 2023)Underwater Acoustic Sensor Networks (UASNs) have recently attracted scientists due to its wide range of real -world applications. However, there are design challenges in UASNs, such as limited network lifetime and low ... -
Microstructural, mechanical, tribological, and corrosion behavior of ultrafine bio-degradable Mg/CeO2 nanocomposites: Machine learning-based modeling and experiment
(ELSEVIER SCI LTD, 2023)The present study investigated the microstructural, mechanical, tribological, and corrosion behavior of near-dense and low-volume fraction magnesium-cerium dioxide (Mg/CeO2 ) (x = 0.5, 1, and 1.5 vol.%) nanocomposites ... -
miRcorrNet: machine learning-based integration of miRNA and mRNA expression profiles, combined with feature grouping and ranking
(PEERJ INC341-345 OLD ST, THIRD FLR, LONDON EC1V 9LL, ENGLAND, 2021)A better understanding of disease development and progression mechanisms at the molecular level is critical both for the diagnosis of a disease and for the development of therapeutic approaches. The advancements in high ... -
Multi fragment melting analysis system (MFMAS) for one-step identification of lactobacilli
(ELSEVIER, RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS, 2020)The accurate identification of lactobacilli is essential for the effective management of industrial practices associated with lactobacilli strains, such as the production of fermented foods or probiotic supplements. For ... -
NeRNA: A negative data generation framework for machine learning applications of noncoding RNAs
(PERGAMON-ELSEVIER SCIENCE, 2023)Many supervised machine learning based noncoding RNA (ncRNA) analysis methods have been developed to classify and identify novel sequences. During such analysis, the positive learning datasets usually consist of known ... -
Performance Analysis of Machine Learning and Bioinformatics Applications on High Performance Computing Systems
(Akademik Perspektif Derneği, 2020)Nowadays, it is becoming increasingly important to use the most efficient and most suitable computational resources for algorithmic tools that extract meaningful information from big data and make smart decisions. In this ... -
PriPath: identifying dysregulated pathways from differential gene expression via grouping, scoring, and modeling with an embedded feature selection approach
(BMC, 2023)BackgroundCell homeostasis relies on the concerted actions of genes, and dysregulated genes can lead to diseases. In living organisms, genes or their products do not act alone but within networks. Subsets of these networks ... -
ROSE: A Novel Approach for Protein Secondary Structure Prediction
(Springer Science and Business Media Deutschland GmbH, 2021)Three-dimensional structure of protein gives important information about protein’s function. Since it is time-consuming and costly to find the structure of protein by experimental methods, estimation of three-dimensional ... -
Stacking Ensemble Learning-Based Wireless Sensor Network Deployment Parameter Estimation
(Institute for Ionics, 2023)In wireless sensor network projects, it is generally desired to cover the area to be monitored at a given cost and to achieve the maximum useful network lifetime. In the deployment of the wireless sensors, it is necessary ... -
SVM-RCE-R-OPT: Optimization of Scoring Function for SVM-RCE-R
(SPRINGER INTERNATIONAL PUBLISHING AGGEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND, 2021)Gene expression data classification provides a challenge in classification due to it having high dimensionality and a relatively small sample size. Different feature selection approaches have been used to overcome this ...