WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

Permanent URI for this collectionhttps://hdl.handle.net/11147/7150

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  • Article
    Citation - WoS: 1
    Citation - Scopus: 1
    Electrochemical Sensors for Rapid Cardiovascular Disease Diagnostics
    (Amer Chemical Soc, 2025) Tekin, Hüseyin Cumhur; Tekin, H. Cumhur; 01. Izmir Institute of Technology; 03. Faculty of Engineering; 03.01. Department of Bioengineering
    Cardiovascular diseases (CVDs) remain a leading cause of death, particularly in developing countries, where their incidence continues to rise. Traditional CVD diagnostic methods are often time-consuming and inconvenient, necessitating more efficient alternatives. Rapid and accurate measurement of cardiac biomarkers released into body fluids is critical for early detection, timely intervention, and improved patient outcomes. Electrochemical methods offer a robust solution by enabling rapid, sensitive, selective, and multiplex detection of CVD biomarkers, paving the way for early diagnosis and treatment advancements. This review highlights the performance and potential of electrochemical sensors for detecting specific CVD biomarkers and related organic molecules. It explores electrochemical sensing mechanisms, their evolution, the integration of nanotechnology, and diverse sensing platforms. It also examines emerging technologies such as microfluidic, smartphone-integrated sensors, and microneedle- and tattoo-based sensors. Challenges and opportunities in integrating electrochemical sensors into point-of-care (POC) and wearable devices are discussed. Finally, the review compares commercial CVD sensors with existing methods and outlines future directions to advance the field.
  • Article
    Citation - WoS: 1
    Citation - Scopus: 1
    Reliability Assessment of Structures With Bayesian Model Updating Accelerated Via Polynomial-Chaos Metamodeling
    (Taylor & Francis Ltd, 2025) Hızal, Çağlayan; Aktaş, Engin; Aktas, Engin; 03.03. Department of Civil Engineering; 03. Faculty of Engineering; 01. Izmir Institute of Technology
    Finite element models are often preferred in numerical modeling of structures, but model assumptions lead to inaccuracies and uncertainties. Measuring these is necessary to determine the reliability and accuracy of the numerical model. This has led to the development of FE model update methods that aim to calibrate the numerical model based on data obtained by structural health monitoring (SHM). However, a general framework that provides a realistic life cycle performance assessment of structures by efficiently incorporating monitored data into structural identification has not yet been impeccably presented. Bayesian modeling can characterize uncertain structural parameters as random variables and provide a systematic methodology for integrating a probabilistic SHM framework into model updating. Unfortunately, these lead to complex and time-consuming, causing limitations in their application. Metamodeling techniques which are effective stochastic predictors can be used to decrease the computational burden in the model updating. This study aims at adapting Polynomial-Chaos-Kriging metamodeling technique integrate to Bayesian model updating process to overcome the computational difficulties and reduce different source of uncertainty with using SHM, then, make more accurate reliability assessment. Therefore, an experimental study is used to assess reliability of structure that is exposed to different types of corrosion effects.