
Chao-Tung YangTunghai University · Department of Computer Science
Chao-Tung Yang
Doctor of Philosophy
About
483
Publications
72,485
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4,775
Citations
Introduction
Dr. Chao-Tung Yang is a Distinguished Professor of Computer Science at Tunghai University in Taichung, Taiwan. He received a B.Sc. degree in Computer Science from Tunghai University, Taichung, Taiwan, in 1990, and the M.Sc. degree in Computer Science from National Chiao Tung University, Hsinchu, Taiwan, in 1992. He received the Ph.D. degree in Computer Science from National Chiao Tung University in July 1996. Dr. Yang has published more than 280 papers in journals, book chapters and conference proceedings. His present research interests are in Cloud computing and Big data, Parallel and multicore computing, and Web-based applications. He is both a member of the IEEE Computer Society and ACM. He is also a member of IICM and TACC in Taiwan.
Additional affiliations
August 2001 - July 2007
October 1996 - July 2001
January 1995 - July 1996
Taipei Rapid Transit Corporation (TRTC)
Position
- Assistant Engineer
Education
August 1992 - July 1996
August 1990 - July 1992
August 1986 - July 1990
Publications
Publications (483)
This paper addresses the increasing demand for efficient and scalable streaming service applications within the context of edge computing, utilizing NVIDIA Jetson Xavier NX hardware and Docker. The study evaluates the performance of DeepStream and Simple Realtime Server, demonstrating that containerized applications can achieve performance levels c...
Identifying pavement damage is a crucial component in road maintenance and infrastructure management. Prompt detection and corrective action of pavement defects can prevent severe deterioration, maintain safety, and prolong the useful life of road infrastructure. Computer vision is widely applied to vehicle applications, such as driver assistance a...
Background: The prevalence of diabetes is increasing worldwide, particularly in the Pacific Ocean island nations. Although machine learning (ML) models and data mining approaches have been applied to diabetes research, there was no study utilizing ML models to predict diabetes incidence in Taiwan. We aimed to predict the onset of diabetes in order...
Background and objective:
Cardiovascular disease (CVD), one of the chronic non-communicable diseases (NCDs), is defined as a cardiac and vascular disorder that includes coronary heart disease, heart failure, peripheral arterial disease, cerebrovascular disease (stroke), congenital heart disease, rheumatic heart disease, and elevated blood pressure...
This study leverages IoT technology to develop a real-time monitoring system for large motorcycles. We collaborated with professional mechanics to define the required data types and system architecture, ensuring practicality and efficiency. The system integrates the NB-IoT for efficient remote data transmission and uses MQTT for optimized messaging...
This research investigates the revolutionary influence of Software Defined Networks (SDNs) on traditional network architectures, focusing particularly on their role in mitigating Denial of Service (DoS) attacks. Conventional network setups involve intermediary devices managing both control and data planes, directing network packets. SDNs, however,...
This paper focuses on the use of smart manufacturing in lathe-cutting tool machines, which can experience thermal deformation during long-term processing, leading to displacement errors in the cutting head and damage to the final product. This study uses time-series thermal compensation to develop a predictive system for thermal displacement in mac...
In a traditional computer network, each device has its configuration. The Software Defined Network (SDN) architecture ensures that every device in the network will become a dummy device, which must connect to a controller before action can be taken on every packet that the device receives. Each device does not require manual configuration with the...
In order to achieve the Sustainable Development Goals (SDG), it is imperative to ensure the safety of drinking water. The characteristics of each drinkable water, encompassing taste, aroma, and appearance, are unique. Inadequate water infrastructure and treatment can affect these features and may also threaten public health. This study utilizes the...
This research aims to develop an AI-based Ergonomics risk hazard posture recognition system to help reduce the risk of injury to workers and improve work safety in factories and warehouses. The background shows that ergonomic risk hazards are one of the most important risk factors in the workplace, among which the risk of posture hazards is higher...
This study explores the application of artificial intelligence in lathe cutting machine tools in smart manufacturing. Long-term processing will cause thermal deformation of the lathe cutting tool machine, which will cause displacement errors of the cutting head and damage to the final product. Using time-series thermal compensation, the research de...
In this study, transfer learning techniques will be used for model training, using edge computing [1] and deep learning object detection technology, combined with image road pothole detection applications, and deploying devices and tools that accelerate neural network operations, including DeepStream [2] and Intel NCS2. The performance and accuracy...
This study is based on deep learning techniques, which compare various detection algorithms and implement the suitable one for firework detection. The considered factors include streaming, speed, accuracy, and portability. Through a detection algorithm, it can simultaneously identify the positions of smoke and fire, providing subsequent control of...
Edge computing is a new paradigm for processing data at the edge of networks. There are a variety of edge computing scenarios, depending on the situation. In this paper, we investigate an architecture with heterogenous devices for intelligence aquaculture. The system will collect water sensor data and run real-time video-based fish detection with a...
Air quality is a pressing global concern, resulting in millions of premature deaths annually. Accurate monitoring is vital to assess pollutant levels against established standards. Real-time systems are crucial in addressing air pollution challenges. This study aims to create a cost-effective, energy-efficient real-time air quality monitoring syste...
Background
This study examined the long-term risks of heart failure (HF) and coronary heart disease (CHD) following traumatic brain injury (TBI), focusing on gender differences.
Methods
Data from Taiwan’s National Health Insurance Research Database included 29,570 TBI patients and 118,280 matched controls based on propensity scores.
Results
The T...
Objectives
This study mainly uses machine learning (ML) to make predictions by inputting features during training and inference. The method of feature selection is an important factor affecting the accuracy of ML models, and the process includes data extraction, which is the collection of all data required for ML. It also needs to import the concep...
Varicocele is a major cause of male infertility. However, few studies have discussed the potential associations between the pain caused by varicocele and preoperative and intraoperative factors. The aim of this study was to evaluate factors potentially associated with changes in pain score after microsurgical varicocelectomy. This retrospective stu...
Background
Predicting physical function upon discharge among hospitalized older adults is important. This study has aimed to develop a prediction model of physical function upon discharge through use of a machine learning algorithm using electronic health records (EHRs) and comprehensive geriatrics assessments (CGAs) among hospitalized older adults...
Wireless network stability is critical for organizations. Most companies rely on a solid internet connection for at least part of their day-to-day activities. It is essential to show the fast and high capacity of Wi-Fi. Wireless network management also significantly supplies the user with quality service and helps the system administrator manage an...
Background
Indoor CO 2 concentration is an important metric of indoor air quality (IAQ). The dynamic temporal pattern of CO 2 levels in intensive care units (ICUs), where healthcare providers experience high cognitive load and occupant numbers are frequently changing, has not been comprehensively characterized.
Objective
We attempted to describe t...
Background
Air pollution is a key public health factor with the capacity to induce diseases. The risk of ischemia heart disease (IHD) in those suffering from systemic lupus erythematosus (SLE) from air pollution exposure is ambiguous. This study aimed to: (1) determine the hazard ratio (HR) of IHD after the first-diagnosed SLE and (2) examine the e...
Quantum computing is currently being researched in many countries, and if implemented in the near future, it may pose a threat to existing encryption standards. In the quantum computer environment, asymmetric encryption can be solved by Shor’s Algorithm in polynomial time, and the difficulty of breaking symmetric encryption using brute force is red...
This paper implemented image classification for smoke and flame detection. CNN model was trained in three topologies of InceptionV3, MobileNet, and VGG16. These three models were then tested on Raspberry Pi 4 with Intel Neural Compute Stick 2 (NCS 2). The experimental results demonstrated that MobileNetV2 is a superior model to the other two models...
Many sectors have experienced the impact of the COVID-19 outbreak, without exception education. The method of process learning transformed from face-to-face meeting learning became online learning. Learners tried to adapt to this unexpected circumstance. In the online learning approach, the instructors only assumed the degree of learners’ understan...
Image recognition has been widely used in many places in our life. For license plate recognition, it can replace the manual inspection and registration of vehicles in the parking lot to complete automation, and it can also facilitate the management of the place to track the entry and exit of vehicles. In this implementation, we use OpenALPR and Tes...
The internet has reached a mature stage of development, and Online Social Media (OSM) platforms such as Twitter and Facebook have become vital channels for public communication and discussion on matters of public interest. However, these platforms are often plagued by improper statements or content, propagated by anonymous users and trolls, which n...
Background:
Insulin resistance (IR) is associated with diabetes mellitus, cardiovascular disease (CV), and mortality. Few studies have used machine learning to predict IR in the non-diabetic population.
Methods:
In this prospective cohort study, we trained a predictive model for IR in the non-diabetic populations using the US National Health and...
An important consideration in medical plastic surgery is the evaluation of the patient’s facial symmetry. However, because facial attractiveness is a slightly individualized cognitive experience, it is difficult to determine face attractiveness manually. This study aimed to train a model for assessing facial attractiveness using transfer learning w...
As plants and animals grow, there are many factors that influence the changes that will affect how plants grow and how botanical experts distinguish them. The use of the Internet of Things (IoT) for data collection is an important part of smart agriculture. Many related studies have shown that remote data management and cloud computing make it poss...
This research combines the application of artificial intelligence in the production equipment fault monitoring of aerospace components. It detects three-phase current abnormalities in large hot-pressing furnaces through smart meters and provides early preventive maintenance. Different anomalies are classified, and a suitable monitoring process algo...
In human communication, the resource of primary information can be read from a human’s face. Health problems occur in line with age, and one way to detect health issues is through changes in facial skin. People typically pay less attention to initial facial skin changes, even though the changes might be linked to a particular disease, such as Lupus...
Smart manufacturing has become a big trend of a new industrial revolution in the manufacturing industry. The advancement of the Internet of Things has made production more efficient and effective through the automated collecting data system and Big Data technology. Dealing with a large amount of real-time production data will be a significant issue...
Given the potential of machine learning algorithms in revolutionizing the bioengineering field, this paper examined and summarized the literature related to artificial intelligence (AI) in the bioprocessing field. Natural language processing (NLP) was employed to explore the direction of the research domain. All the papers from 2013 to 2022 with sp...
The coronavirus disease (COVID-19) outbreak has turned the world upside down bringing about a massive impact on society due to enforced measures such as the curtailment of personal travel and limitations on economic activities. The global pandemic resulted in numerous people spending their time at home, working, and learning from home hence exposin...
With the ubiquity of high-speed networks and cloud technologies, hyper-convergence (HC) has become commonplace and satisfies flex allocation requirements. This study compared the VMware virtual storage area network (vSAN), which has the largest market share, with Cisco HyperFlex, released by Cisco for high-level network applications, to assess the...
The sequential organ failure assessment (SOFA) and quick sequential organ failure assessment (qSOFA) scores are new tools which are used to assess sepsis based on the Third International Consensus Definitions for Sepsis and Septic Shock Task Force. This study aimed to evaluate the feasibility of using the SOFA and qSOFA to predict post-ureteroscopi...
Edge Computing is the new paradigm to process data at the edge of the network. The scenario of edge computing varies, depending on the case and problem. In this paper, we investigate an architecture that is suitable for Intelligence Aquaculture. This system will handle tasks such as collecting the water sensor data and running an Artificial Intelli...
Society nowadays is provided with a maturely developed internet, and On-line Social Media (OSM) such as Twitter and Facebook are one of the vital communication channels for information exchange and public affairs discussion. Unfortunately , due to anonymity and trolls, improper statement or content are corroding these OSM platforms and their users....
This study develops real-time flame and smoke recognition on an intelligent edge using transfer learning and deep learning. In this case, the inference application was deployed on edge devices. There are devices and tools to accelerate the operation of neural networks, including Intel Neural Compute Stick v.2 (NCS2) on Raspberry Pi4 and DeepStream...
Big data and artificial intelligence (AI) technology are complicated systems that will continue developing in recent years. This paper implemented a data lake architecture to handle massive data and perform data analysis in a real-time system. Using a data lake and AI model, a NetFlow storage monitoring system was deployed to perform a platform tha...
Big Data and Cloud Computing are two major information technologies for processing data to translate data to knowledge [...]
Diabetic foot ulcers (DFUs) are considered the most challenging forms of chronic ulcerations to handle their multifactorial nature. It is necessary to establish a comprehensive treatment plan, accurate, and systematic evaluation of a patient with a DFU. This paper proposed an image recognition of diabetic foot wounds to support the effective execut...
Backgrounds
Falls are currently one of the important safety issues of elderly inpatients. Falls can lead to their injury, reduced mobility and comorbidity. In hospitals, it may cause medical disputes and staff guilty feelings and anxiety. We aimed to predict fall risks among hospitalized elderly patients using an approach of artificial intelligence...
The usage of artificial intelligence and machine learning methods on cyberattacks increasing significantly recently. For the defense method of cyberattacks, it is possible to detect and identify the attack event by observing the log data and analyzing whether it has abnormal behavior or not. This paper implemented the ELK Stack network log system (...
The COVID-19 pandemic raises awareness of how the fatal spreading of infectious disease impacts economic, political, and cultural sectors, which causes social implications. Across the world, strategies aimed at quickly recognizing risk factors have also helped shape public health guidelines and direct resources; however, they are challenging to ana...
This paper proposed implementing a water and air monitoring system using sensor development and a LoRa Network. To transmit data, a self-made PCB board integrates the terminal sensors with Renesas RX64M MCU and LoRa. There are 16 monitoring point stations for the media experiment. The sensors were used to measure the water and air parameters such a...
Physicians spend much time observing the facial symmetry of patients and collecting various data to arrive at an accurate clinical judgment. This study presents a transfer learning method for evaluating the degree of facial symmetry. The contour map of a face is used as training data, and the training module then classifies and scores the degree of...
This paper implements deep learning methods of recurrent neural networks and short-term memory models. Two kinds of time-series data were used: air pollutant factors, such as O3, SO2, and CO2 from 2017 to 2019, and meteorological factors such as temperature, humidity, wind direction, and wind speed. A trained model was used to predict air pollution...
This paper proposed the forecasting model of Influenza-like Illness (ILI) and respiratory disease. The dataset was extracted from the Taiwan Environmental Protection Administration (EPA) for air pollutants data and the Centers for Disease Control (CDC) for disease cases from 2009 to 2018. First, this paper applied the ARIMA method, which trained ba...
Due to the openness and easy accessibility of online social media (OSM), anyone can easily contribute a simple paragraph of text to express their opinion on an article that they have seen. Without access control mechanisms, it has been reported that there are many suspicious messages and accounts spreading across multiple platforms. Accordingly, id...
Machine health monitoring systems are vital components of modern manufacturing industries. As advanced sensors collecting machine health-related data become commonplace, such systems have started adopting data-driven approaches to harness the collected data. However, dealing with noisy data and gleaning the spatial and temporal correlation within t...
In the past decade, Internet of Things (IoT) technology has been widely used in various applications in daily life. Currently, IoT applications primarily depend on powerful cloud data centers as computing and storage centers. However, with such cloud-centric frameworks, numerous data are transferred between end devices and remote cloud data centers...
In recent years, virtualization is one of the key technologies of next-generation data centers. However, the problem of virtualization technology is that each instance needs to run a client operating system and a lot of applications. Therefore, it might generate a heavy load and affect the system efficiency and performance. In this work, the perfor...
Network log data is significant for network administrators, since it contains information on every event that occurs in a network, including system errors, alerts, and packets sending statuses. Effectively analyzing large volumes of diverse log data brings opportunities to identify issues before they become problems and to prevent future cyberattac...