Open Access. Powered by Scholars. Published by Universities.®
- Publication
- Publication Type
Articles 1 - 11 of 11
Full-Text Articles in Computer Engineering
Machine Learning Approaches In Comparative Studies For Alzheimer’S Diagnosis Using 2d Mri Slices, Zhen Zhao, Joon Huang Chuah, Chee-Onn Chow, Kaijian Xia, Yee Kai Tee, Yan Chai Hum, Khin Wee Lai
Machine Learning Approaches In Comparative Studies For Alzheimer’S Diagnosis Using 2d Mri Slices, Zhen Zhao, Joon Huang Chuah, Chee-Onn Chow, Kaijian Xia, Yee Kai Tee, Yan Chai Hum, Khin Wee Lai
Turkish Journal of Electrical Engineering and Computer Sciences
Alzheimer’s disease (AD) is an illness that involves a gradual and irreversible degeneration of the brain. It is crucial to establish a precise diagnosis of AD early on in order to enable prompt therapies and prevent further deterioration. Researchers are currently focusing increasing attention on investigating the potential of machine learning techniques to simplify the automated diagnosis of AD using neuroimaging. The present study involved a comparison of models for the detection of AD through the utilization of 2D image slices obtained from magnetic resonance imaging brain scans. Five models, namely ResNet, ConvNeXt, CaiT, Swin Transformer, and CVT, were implemented …
Focal Modulation Network For Lung Segmentation In Chest X-Ray Images, Şaban Öztürk, Tolga Çukur
Focal Modulation Network For Lung Segmentation In Chest X-Ray Images, Şaban Öztürk, Tolga Çukur
Turkish Journal of Electrical Engineering and Computer Sciences
Segmentation of lung regions is of key importance for the automatic analysis of Chest X-Ray (CXR) images, which have a vital role in the detection of various pulmonary diseases. Precise identification of lung regions is the basic prerequisite for disease diagnosis and treatment planning. However, achieving precise lung segmentation poses significant challenges due to factors such as variations in anatomical shape and size, the presence of strong edges at the rib cage and clavicle, and overlapping anatomical structures resulting from diverse diseases. Although commonly considered as the de-facto standard in medical image segmentation, the convolutional UNet architecture and its variants …
Automated Question Generation And Question Answering From Turkish Texts, Fati̇h Çağatay Akyön, Ali̇ Devri̇m Eki̇n Çavuşoğlu, Cemi̇l Cengi̇z, Si̇nan Onur Altinuç, Alpteki̇n Temi̇zel
Automated Question Generation And Question Answering From Turkish Texts, Fati̇h Çağatay Akyön, Ali̇ Devri̇m Eki̇n Çavuşoğlu, Cemi̇l Cengi̇z, Si̇nan Onur Altinuç, Alpteki̇n Temi̇zel
Turkish Journal of Electrical Engineering and Computer Sciences
While exam-style questions are a fundamental educational tool serving a variety of purposes, manual construction of questions is a complex process that requires training, experience and resources. Automatic question generation (QG) techniques can be utilized to satisfy the need for a continuous supply of new questions by streamlining their generation. However, compared to automatic question answering (QA), QG is a more challenging task. In this work, we fine-tune a multilingual T5 (mT5) transformer in a multitask setting for QA, QG and answer extraction tasks using Turkish QA datasets. To the best of our knowledge, this is the first academic work …
Exploiting Bert And Roberta To Improve Performance For Aspect Based Sentiment Analysis, Gagan Reddy Narayanaswamy
Exploiting Bert And Roberta To Improve Performance For Aspect Based Sentiment Analysis, Gagan Reddy Narayanaswamy
Dissertations
Sentiment Analysis also known as opinion mining is a type of text research that analyses people’s opinions expressed in written language. Sentiment analysis brings together various research areas such as Natural Language Processing (NLP), Data Mining, and Text Mining, and is fast becoming of major importance to companies and organizations as it is started to incorporate online commerce data for analysis. Often the data on which sentiment analysis is performed will be reviews. The data can range from reviews of a small product to a big multinational corporation. The goal of performing sentiment analysis is to extract information from those …
Finetuning Bert And Xlnet For Sentiment Analysis Of Stock Market Tweets Using Mixout And Dropout Regularization, Shubham Jangir
Finetuning Bert And Xlnet For Sentiment Analysis Of Stock Market Tweets Using Mixout And Dropout Regularization, Shubham Jangir
Dissertations
Sentiment analysis is also known as Opinion mining or emotional mining which aims to identify the way in which sentiments are expressed in text and written data. Sentiment analysis combines different study areas such as Natural Language Processing (NLP), Data Mining, and Text Mining, and is quickly becoming a key concern for businesses and organizations, especially as online commerce data is being used for analysis. Twitter is also becoming a popular microblogging and social networking platform today for information among people as they contribute their opinions, thoughts, and attitudes on social media platforms over the years. Because of the large …
Transformer Fault Diagnosis Based On Feature Extraction Of Relative Transformation Principal Component Analysis, Yongbo Tang, Yinguo Xiong
Transformer Fault Diagnosis Based On Feature Extraction Of Relative Transformation Principal Component Analysis, Yongbo Tang, Yinguo Xiong
Journal of System Simulation
Abstract: In order to handle the problem that the feature extraction of dissolved gas analysis (DGA) data by principal component analysis (PCA) is not distinct, a new transformer fault diagnosis method based on relative transformation (RT) PCA is proposed. The original data space is converted to the relative data space by relative transformation which makes the transformed data more distinguishable. PCA is employed to reduce the dimension of relative space to make the features more representative in the relative space. Diagnosis model based on least squares support vector machine (LSSVM) is set up according to the fault characteristic of transformer. …
The Process Of Creeping Discharge-Caused Damage On Oil/Pressboard Insulation, Ruijin Liao, Ende Hu, Lijun Yang, Lian Duan
The Process Of Creeping Discharge-Caused Damage On Oil/Pressboard Insulation, Ruijin Liao, Ende Hu, Lijun Yang, Lian Duan
Turkish Journal of Electrical Engineering and Computer Sciences
This paper presents experimental research on creeping discharge by using cylinder-plate electrode configurations under AC voltages. The process of creeping discharge-caused damage on the oil/pressboard insulation was studied. First, the electric field distribution was achieved by Multiphysics software simulation. Afterwards, the phenomena that occurred in the entire damage process, such as ``white smoke'', ``white mark'', and ``black mark'', were recorded and analyzed. Furthermore, the micromorphology of the oil-impregnated pressboard was observed via scanning electron microscope (SEM). Finally, the inner mechanism of the damage to the oil/pressboard insulation was explored according to the phenomena and the SEM morphologies. Results showed that …
Winding Temperature Prediction In Split-Winding Traction Transformer, Davood Azizian
Winding Temperature Prediction In Split-Winding Traction Transformer, Davood Azizian
Turkish Journal of Electrical Engineering and Computer Sciences
No abstract provided.
A Robust Algorithm Based On A Failure-Sensitive Matrix For Fault Diagnosis Of Power Systems: An Application On Power Transformers, Yunus Bi̇çen, Faruk Aras
A Robust Algorithm Based On A Failure-Sensitive Matrix For Fault Diagnosis Of Power Systems: An Application On Power Transformers, Yunus Bi̇çen, Faruk Aras
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, a robust algorithm for fault diagnosis of power system equipment based on a failure-sensitive matrix (FSM) is presented. The FSM is a dynamic matrix structure updated by multiple measurements (online) and test results (offline) on the systems. The algorithm uses many different artificial intelligence and expert system methods for adaptively detecting the location of faults, emerging failures, and causes of failures. In this algorithm, all data obtained from the power transformer, which have various nonlinear input and output parameters, are processed using the parallel matrix structure of the FSM to reach a global solution quickly. The parameters …
Characterization Of Internal Disturbances And External Faults In Transformers Using An S-Transform--Based Algorithm, Abdolaziz Ashrafian, Mehrdad Rostami, Gevorg .B Gharehpetian
Characterization Of Internal Disturbances And External Faults In Transformers Using An S-Transform--Based Algorithm, Abdolaziz Ashrafian, Mehrdad Rostami, Gevorg .B Gharehpetian
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, the S-transform is used to discriminate between the internal disturbances and external faults of transformers. The proposed algorithm consists of 2 stages. The internal disturbances and the external faults are distinguished in the first stage. Next, the S-transform is applied to differential currents of faulty phases and the absolute deviation of the S-matrix is calculated. The relay scheme issues a trip signal in the case of an internal fault, according to the absolute deviation of the S-matrix. The scheme is implemented in a MATLAB environment and the inputs are differential currents, derived from EMTP software. In order …
Insulation Condition Assessment Of Power Transformers Using Accelerated Ageing Tests, Mohammad Mirzaie, Ahmad Gholami, Hamid Reza Tayebi
Insulation Condition Assessment Of Power Transformers Using Accelerated Ageing Tests, Mohammad Mirzaie, Ahmad Gholami, Hamid Reza Tayebi
Turkish Journal of Electrical Engineering and Computer Sciences
Thermal stress due to losses and environment temperature causes degradation to paper/oil insulation systems in transformers, even at operating temperature. Experience indicates that thermal ageing of oil and paper in power transformers leads to the change of some insulation characteristics. In this paper, insulating papers immersed in oil have been acceleratory aged at 140, 150, and 160 °C under laboratory conditions. Some of the oil properties, such as water content, breakdown voltage, acidity, together with the aged insulating paper properties such as electric strength, dielectric dissipation factor and tensile strength were measured and analyzed. Also, insulation system conditions under thermal …