Chronic kidney disease (CKD) is a condition distinguished by structural and functional changes to... more Chronic kidney disease (CKD) is a condition distinguished by structural and functional changes to the kidney over time. Studies show that 10% of adults worldwide are affected by some kind of CKD, resulting in 1.2 million deaths. Recently, CKD has emerged as a leading cause of mortality worldwide, making it necessary to develop a Computer-Aided Diagnostic (CAD) system to diagnose CKD automatically. Machine Learning (ML) based CAD system can be used by a clinician to automatically diagnoses mass people. Since ML models are considered a black box, it is also necessary to expose influential causes behind a model's prediction of a particular output. So that, a doctor can make a more rational decision based on the model's output and analysis of the features influence on the model. In this paper, we have used the XGBoost as the ML classifier to predict whether a patient has CKD or not. Using the XGBoost classifier, we have obtained an accuracy, precision, recall, and F1 score of $$...
Today, the world is experiencing a tremendous catastrophic disaster that can lead to potential en... more Today, the world is experiencing a tremendous catastrophic disaster that can lead to potential environmental damage. However, awareness of how to deal with this catastrophic situation still remains very low. One of the most critical issues in disaster response is assigning disaster victims to the best emergency shelter location. This article reviews various existing studies to develop a new approach to determining emergency shelter locations. There are four evaluation criteria that are reviewed: optimization objective, decision variable, methodology, and victim identification. From the investigation, there are two major evaluations that can be further developed. In terms of decision variables, most of the previous research applies direct distance (Euclidean Distance) in the analysis process. However, the application of travel distance can represent a real evacuation process. Another interesting point is the victim identification process. Recent research applies grid-based partitioni...
Cracks in concrete surfaces are one of the most prominent causes of the degradation of concrete s... more Cracks in concrete surfaces are one of the most prominent causes of the degradation of concrete structures such as bridges, roads, buildings, etc. Hence, it is very crucial to detect cracks at an early stage to inspect the structural health of the concrete structure. To solve the drawbacks of manual inspection, Image Processing Techniques (IPTs), especially those based on Deep Learning (DL) methods, have been investigated for the past few years. Due to the groundbreaking development of this field, researchers have devoted their endeavors to detecting cracks using DL-based IPTs and as a result, the techniques have given answers to many challenging problems. However, to the best of our knowledge, a state-of-the-art systematic review paper is lacking in this field that would present a scientometric analysis as well as a critical survey of the existing works to document the research trends and summarize the prominent IPTs for detecting cracks in concrete structures. Therefore, this arti...
The objective of this study is to explore the feasibility of using ultrasonic pulse wave measurem... more The objective of this study is to explore the feasibility of using ultrasonic pulse wave measurements as an early detection method for corrosion-induced concrete damages. A series of experiments are conducted using concrete cube specimens, at a size of 200 mm, with a reinforcing steel bar (rebar) embedded in the center. The main variables include the water-to-cement ratio of the concrete (0.4, 0.5, and 0.6), the diameter of the rebar (10 mm, 13 mm, 19 mm, and 22 mm), and the corrosion level (ranging from 0% to 20% depending on rebar diameter). The impressed current technique is used to accelerate corrosion of rebars in concrete immersed in a 3% NaCl solution. Ultrasonic pulse waves are collected from the concrete specimens using a pair of 50 kHz P-wave transducers in the through-transmission configuration before and after the accelerated corrosion test. Deep learning techniques, specifically three recurrent neural network (RNN) models (long short-term memory, gated recurrent unit, a...
In recent years, the omnipresence of cardiac problems has been recognized as an epidemic. With th... more In recent years, the omnipresence of cardiac problems has been recognized as an epidemic. With the correct and quick diagnosis, both mortality and morbidity from cardiac disorders can be dramatically reduced. However, frequent medical check-ups are pricey and out of reach for a large number of people, particularly those living in low-income areas. In this paper, certain time-honored statistical techniques are used to determine the factors that lead to heart disease. Also, the findings were validated using various promising machine learning tools. Feature importance approach was employed to rank the clinical parameters of the patients based on the correlation of heart disease. In the case of statistical investigations, nonparametric tests such as the Mann Whitney U test and the Chi square test, as well as correlation analysis with Pearson correlation and Spearman Correlation were used. For additional validation, seven of the potential feature important based ML algorithms were applie...
This paper presents a novel approach for typhoon track prediction that potentially impacts a regi... more This paper presents a novel approach for typhoon track prediction that potentially impacts a region using ensemble k-Nearest Neighbor (k-NN) in a GIS environment. In this work, the past typhoon tracks are zonally split into left and right classes by the current typhoon track and then grouped as an ensemble member containing three (left-center-right) typhoons. The proximity of the current typhoon to the left and/or right class is determined by using a supervised classification k-NN algorithm. The track dataset created from the current and similar class typhoons is trained by using the supervised regression k-NN to predict current typhoon tracks. The ensemble averaging is performed for all typhoon track groups to obtain the final track prediction. It is found that the number of ensemble members does not necessarily affect the accuracy; the determination of similarity at the beginning, however, plays an important key role. A series of tests yields that the present method is able to pro...
The Internet of Things (IoT) is essential in innovative applications such as smart cities, smart ... more The Internet of Things (IoT) is essential in innovative applications such as smart cities, smart homes, education, healthcare, transportation, and defense operations. IoT applications are particularly beneficial for providing healthcare because they enable secure and real-time remote patient monitoring to improve the quality of people’s lives. This review paper explores the latest trends in healthcare-monitoring systems by implementing the role of the IoT. The work discusses the benefits of IoT-based healthcare systems with regard to their significance, and the benefits of IoT healthcare. We provide a systematic review on recent studies of IoT-based healthcare-monitoring systems through literature review. The literature review compares various systems’ effectiveness, efficiency, data protection, privacy, security, and monitoring. The paper also explores wireless- and wearable-sensor-based IoT monitoring systems and provides a classification of healthcare-monitoring sensors. We also ...
The purpose of this study is to develop an advanced signal interpretation algorithm for an automa... more The purpose of this study is to develop an advanced signal interpretation algorithm for an automated impact-echo (IE) testing system. It will be a part of a multi-purpose air-coupled ultrasonic testing system for assessment of concrete bridge decks. An intelligent signal processing algorithm is an essential part of the automated IE testing system. As such it will provide reliable and consistent results by eliminating human errors, and significantly save time for post-processing (i.e., signal processing, data interpretation, and decision). For this purpose, a numerical model, finite element analysis (FEM) is developed to simulate transient behavior of stress waves in air-concrete domain. Using this model, a series of numerical simulations is conducted to investigate the effects of source locations over delamination defects at various depths (60 and 160 mm) and widths (300, 450, and 600 mm). Frequency responses from numerical IE tests are presented as 2-D spectral B-scan images. From ...
Chronic kidney disease (CKD) is a condition distinguished by structural and functional changes to... more Chronic kidney disease (CKD) is a condition distinguished by structural and functional changes to the kidney over time. Studies show that 10% of adults worldwide are affected by some kind of CKD, resulting in 1.2 million deaths. Recently, CKD has emerged as a leading cause of mortality worldwide, making it necessary to develop a Computer-Aided Diagnostic (CAD) system to diagnose CKD automatically. Machine Learning (ML) based CAD system can be used by a clinician to automatically diagnoses mass people. Since ML models are considered a black box, it is also necessary to expose influential causes behind a model's prediction of a particular output. So that, a doctor can make a more rational decision based on the model's output and analysis of the features influence on the model. In this paper, we have used the XGBoost as the ML classifier to predict whether a patient has CKD or not. Using the XGBoost classifier, we have obtained an accuracy, precision, recall, and F1 score of $$...
Today, the world is experiencing a tremendous catastrophic disaster that can lead to potential en... more Today, the world is experiencing a tremendous catastrophic disaster that can lead to potential environmental damage. However, awareness of how to deal with this catastrophic situation still remains very low. One of the most critical issues in disaster response is assigning disaster victims to the best emergency shelter location. This article reviews various existing studies to develop a new approach to determining emergency shelter locations. There are four evaluation criteria that are reviewed: optimization objective, decision variable, methodology, and victim identification. From the investigation, there are two major evaluations that can be further developed. In terms of decision variables, most of the previous research applies direct distance (Euclidean Distance) in the analysis process. However, the application of travel distance can represent a real evacuation process. Another interesting point is the victim identification process. Recent research applies grid-based partitioni...
Cracks in concrete surfaces are one of the most prominent causes of the degradation of concrete s... more Cracks in concrete surfaces are one of the most prominent causes of the degradation of concrete structures such as bridges, roads, buildings, etc. Hence, it is very crucial to detect cracks at an early stage to inspect the structural health of the concrete structure. To solve the drawbacks of manual inspection, Image Processing Techniques (IPTs), especially those based on Deep Learning (DL) methods, have been investigated for the past few years. Due to the groundbreaking development of this field, researchers have devoted their endeavors to detecting cracks using DL-based IPTs and as a result, the techniques have given answers to many challenging problems. However, to the best of our knowledge, a state-of-the-art systematic review paper is lacking in this field that would present a scientometric analysis as well as a critical survey of the existing works to document the research trends and summarize the prominent IPTs for detecting cracks in concrete structures. Therefore, this arti...
The objective of this study is to explore the feasibility of using ultrasonic pulse wave measurem... more The objective of this study is to explore the feasibility of using ultrasonic pulse wave measurements as an early detection method for corrosion-induced concrete damages. A series of experiments are conducted using concrete cube specimens, at a size of 200 mm, with a reinforcing steel bar (rebar) embedded in the center. The main variables include the water-to-cement ratio of the concrete (0.4, 0.5, and 0.6), the diameter of the rebar (10 mm, 13 mm, 19 mm, and 22 mm), and the corrosion level (ranging from 0% to 20% depending on rebar diameter). The impressed current technique is used to accelerate corrosion of rebars in concrete immersed in a 3% NaCl solution. Ultrasonic pulse waves are collected from the concrete specimens using a pair of 50 kHz P-wave transducers in the through-transmission configuration before and after the accelerated corrosion test. Deep learning techniques, specifically three recurrent neural network (RNN) models (long short-term memory, gated recurrent unit, a...
In recent years, the omnipresence of cardiac problems has been recognized as an epidemic. With th... more In recent years, the omnipresence of cardiac problems has been recognized as an epidemic. With the correct and quick diagnosis, both mortality and morbidity from cardiac disorders can be dramatically reduced. However, frequent medical check-ups are pricey and out of reach for a large number of people, particularly those living in low-income areas. In this paper, certain time-honored statistical techniques are used to determine the factors that lead to heart disease. Also, the findings were validated using various promising machine learning tools. Feature importance approach was employed to rank the clinical parameters of the patients based on the correlation of heart disease. In the case of statistical investigations, nonparametric tests such as the Mann Whitney U test and the Chi square test, as well as correlation analysis with Pearson correlation and Spearman Correlation were used. For additional validation, seven of the potential feature important based ML algorithms were applie...
This paper presents a novel approach for typhoon track prediction that potentially impacts a regi... more This paper presents a novel approach for typhoon track prediction that potentially impacts a region using ensemble k-Nearest Neighbor (k-NN) in a GIS environment. In this work, the past typhoon tracks are zonally split into left and right classes by the current typhoon track and then grouped as an ensemble member containing three (left-center-right) typhoons. The proximity of the current typhoon to the left and/or right class is determined by using a supervised classification k-NN algorithm. The track dataset created from the current and similar class typhoons is trained by using the supervised regression k-NN to predict current typhoon tracks. The ensemble averaging is performed for all typhoon track groups to obtain the final track prediction. It is found that the number of ensemble members does not necessarily affect the accuracy; the determination of similarity at the beginning, however, plays an important key role. A series of tests yields that the present method is able to pro...
The Internet of Things (IoT) is essential in innovative applications such as smart cities, smart ... more The Internet of Things (IoT) is essential in innovative applications such as smart cities, smart homes, education, healthcare, transportation, and defense operations. IoT applications are particularly beneficial for providing healthcare because they enable secure and real-time remote patient monitoring to improve the quality of people’s lives. This review paper explores the latest trends in healthcare-monitoring systems by implementing the role of the IoT. The work discusses the benefits of IoT-based healthcare systems with regard to their significance, and the benefits of IoT healthcare. We provide a systematic review on recent studies of IoT-based healthcare-monitoring systems through literature review. The literature review compares various systems’ effectiveness, efficiency, data protection, privacy, security, and monitoring. The paper also explores wireless- and wearable-sensor-based IoT monitoring systems and provides a classification of healthcare-monitoring sensors. We also ...
The purpose of this study is to develop an advanced signal interpretation algorithm for an automa... more The purpose of this study is to develop an advanced signal interpretation algorithm for an automated impact-echo (IE) testing system. It will be a part of a multi-purpose air-coupled ultrasonic testing system for assessment of concrete bridge decks. An intelligent signal processing algorithm is an essential part of the automated IE testing system. As such it will provide reliable and consistent results by eliminating human errors, and significantly save time for post-processing (i.e., signal processing, data interpretation, and decision). For this purpose, a numerical model, finite element analysis (FEM) is developed to simulate transient behavior of stress waves in air-concrete domain. Using this model, a series of numerical simulations is conducted to investigate the effects of source locations over delamination defects at various depths (60 and 160 mm) and widths (300, 450, and 600 mm). Frequency responses from numerical IE tests are presented as 2-D spectral B-scan images. From ...
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Papers by SEONG-HOON KEE