A failure risk assessment method for lithium-ion batteries based on big data of after-sales vehicles

C Liu, K Zhang, Z Deng, X Zhao, X Zhang… - Engineering Failure …, 2024 - Elsevier
Accurate prediction of battery failure has always been a challenge in the field of electric
vehicles. In existing prediction methods, battery current, voltage and temperature of a single …

Machine Learning and Electrocardiography Signal‐Based Minimum Calculation Time Detection for Blood Pressure Detection

M Nour, D Kandaz, MK Ucar, K Polat… - … Methods in Medicine, 2022 - Wiley Online Library
Objective. Measurement and monitoring of blood pressure are of great importance for
preventing diseases such as cardiovascular and stroke caused by hypertension. Therefore …

Machine Learning–Based Framework for Prediction of Retroreflectivity Degradation of Pavement Markings across the US

II Idris, M Mousa, MM Hassan - Journal of Transportation …, 2024 - ascelibrary.org
Pavement markings are essential traffic control devices that enhance safety for motorists
during nighttime. Numerous statistical learning models have been developed in prior studies …

Modeling retroreflectivity degradation of pavement markings across the US with advanced machine learning algorithms

II Idris, M Mousa, M Hassan - Journal of Infrastructure Preservation and …, 2024 - Springer
Retroreflectivity is the primary metric that controls the visibility of pavement markings during
nighttime and in adverse weather conditions. Maintaining the minimum level of …

Potential Health Risks of Chloroacetanilide Herbicides: An In Silico Analysis

AA Berber, ŞN Demir, NA Kenanoğlu - Sakarya University Journal of …, 2023 - dergipark.org.tr
The extensive use of herbicidal products in agriculture and forestry has raised concerns over
potential adverse effects on human health and the environment. Chloroacetanilide …

[PDF][PDF] Determining effective features to use the EOG sign as a source sign

I Zengin, MR Bozkurt, MK Ucar… - … University Journal of …, 2019 - dergipark.org.tr
In this study, the processing of the Electrooculogram (EOG) signal for human machine
interface (IMA) was performed to facilitate the lives of paralyzed patients. Eye movements …

EOG İşaretini Kaynak İşaret Olarak Kullanmak Üzere Etkin Özelliklerin Belirlenmesi

İ Zengin, MR Bozkurt, MK Uçar - Sakarya University Journal of …, 2019 - saucis.sakarya.edu.tr
Bu çalışmada, özellikle felçli hastaların yaşamlarını kolaylaştırmak için Elektrookülogram
(EOG) işaretinin insan makine arabirimi (İMA) için işlenmesi gerçekleştirilmiştir. Göz …

Tarımda Kaliteli Tohum Üretimi için Kuru Fasulye Türlerinin Yapay Zekâ Tabanlı Sınıflandırılması

U Kadıoğlu, MK Uçar, S Yıldırım - El-Cezeri, 2022 - dergipark.org.tr
2020 yılında Dünya genelinde 27, 5 milyon ton, Türkiye de 279, 5 bin ton kuru fasulye
üretilmiştir. Kuru fasulye geniş bir çeşitliliğe sahiptir. Bir çeşidi soğuk iklim koşullarında …

Diagnosis of Lung Cancer with Hybrid Artificial Intelligence Method

GM Kalkan, B Dönmez, YC Tok, S Gürel… - 2022 Medical …, 2022 - ieeexplore.ieee.org
Lung cancer is a deadly disease that is difficult to diagnose and incurable. It is caused by the
uncontrolled growth of cancerous cells in the lungs. Early diagnosis is vital for such an …

A Novel Machine Learning-based Diagnostic Algorithm for Detection of Onychomycosis through Nail Appearance

S Düzayak, MK Uçar - Sakarya University Journal of Science - dergipark.org.tr
Onychomycosis is the most common nail fungus disease in clinical practice worldwide,
caused by the localization of various fungal agents, including dermatophytes, on the nail …