A failure risk assessment method for lithium-ion batteries based on big data of after-sales vehicles
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 …
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
Objective. Measurement and monitoring of blood pressure are of great importance for
preventing diseases such as cardiovascular and stroke caused by hypertension. Therefore …
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
Pavement markings are essential traffic control devices that enhance safety for motorists
during nighttime. Numerous statistical learning models have been developed in prior studies …
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
Retroreflectivity is the primary metric that controls the visibility of pavement markings during
nighttime and in adverse weather conditions. Maintaining the minimum level of …
nighttime and in adverse weather conditions. Maintaining the minimum level of …
Potential Health Risks of Chloroacetanilide Herbicides: An In Silico Analysis
The extensive use of herbicidal products in agriculture and forestry has raised concerns over
potential adverse effects on human health and the environment. Chloroacetanilide …
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 …
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 …
(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 …
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 …
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
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 …
caused by the localization of various fungal agents, including dermatophytes, on the nail …