• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.9
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• pp.265-273
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• 2018

In this paper, we propose an acoustic event detection method in tunnels using non-negative tensor factorization (NTF) and hidden Markov model (HMM) applied to multi-channel audio signals. Incidents in tunnel are inherent to the system and occur unavoidably with known probability. Incidents can easily happen minor accidents and extend right through to major disaster. Most incident detection systems deploy visual incident detection (VID) systems that often cause false alarms due to various constraints such as night obstacles and a limit of viewing angle. To this end, the proposed method first tries to separate and detect every acoustic event, which is assumed to be an in-tunnel incident, from noisy acoustic signals by using an NTF technique. Then, maximum likelihood estimation using Gaussian mixture model (GMM)-HMMs is carried out to verify whether or not each detected event is an actual incident. Performance evaluation shows that the proposed method operates in real time and achieves high detection accuracy under simulated tunnel conditions.

• Journal of the Korean Institute of Gas
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• v.27 no.2
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• pp.7-15
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• 2023

The electric submersible pump (ESP) has been operating in production wells around the world because of its high applicability and operational efficiency among artificial lift techniques. When operating an ESP in a reservoir, variables such as temperature, pressure, gas/oil ratio, and flow rate are factors that affect ESP performance. In particular, free gas in the production fluid is a major factor that reduces the life and operational efficiency of ESP. This study presents the flow loop system which can implement the performance and damage tests of ESP considering field operating conditions to quantitatively analyze the variables that affect ESP performance. The developed apparatus in an integrated system that can diagnose the failure and causes of ESP, and detect leak of tubing by linking ESP and tubing as one system. In this study, the flow conditions for stable operation of ESP were identified through single phase and two phase flow experiments related to evaluation for the performance of ESP. The results provide the basic data to develop the failure prediction and diagnosis program of ESP, and are expected to be used for real-time monitoring for optimal operating conditions and failure diagnosis for ESP operation.

• Journal of the Korean Society of Food Culture
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• v.23 no.1
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• pp.130-137
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• 2008

If we may practice the nutrition education planned on the basis which carefully grasped the inappropriate behavioral determinants of middle-school students, it might be an effective method achieving the change in perception and behavior improving the distorted perception about the ideal body shape, so we are to suggest the 8 week program of body shape perception improvement for successful nutrition education as follows. The body shape perception improvement program is a step-by-step group consulting program. At the introduction stage, we let them understand the meaning of true beauty and body change of teenage period and forming of sexual identity. At the stage of perception conversion, we let them have the opportunity to observe the status of body perception of the teenager and self-observation. At the stage of correction, we let them criticize the distorted body image in the society with mass media at the same time with the self-reflection. At the stage of maintenance and evaluation, we suggested the behavior guidance while preparing it. Setting this as the basis, we applied the contents such as the evaluations through cultural sharing events making somethings while directly participating. As the target groups to practice education were middle school students, we considered the learning level and behavioral features of the middle school students, and composed the programs including the methods such as role play, watching real things, media production, discussions and experiences. If the program of body shape perception improvement developed at this study could be utilized at the field of schools, the teenagers can change their ways of thought naturally avoiding the view about unified appearance rightly perceiving negative self-image that the teenagers can have and if the group consulting can be practiced regularly at each school, many students may experience the change in perception, so it might solicit the improvement of health of the families and local societies as well as that of the individual student.

• Journal of the Korea Society of Computer and Information
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• v.28 no.10
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• pp.27-35
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• 2023

In this paper, we propose a process of increasing productivity by applying a deep learning-based defect detection and classification system to the prepreg fiber manufacturing process, which is in high demand in the field of producing composite materials. In order to apply it to toe prepreg manufacturing equipment that requires a solution due to the occurrence of a large amount of defects in various conditions, the optimal environment was first established by selecting cameras and lights necessary for defect detection and classification model production. In addition, data necessary for the production of multiple classification models were collected and labeled according to normal and defective conditions. The multi-classification model is made based on CNN and applies pre-learning models such as VGGNet, MobileNet, ResNet, etc. to compare performance and identify improvement directions with accuracy and loss graphs. Data augmentation and dropout techniques were applied to identify and improve overfitting problems as major problems. In order to evaluate the performance of the model, a performance evaluation was conducted using the confusion matrix as a performance indicator, and the performance of more than 99% was confirmed. In addition, it checks the classification results for images acquired in real time by applying them to the actual process to check whether the discrimination values are accurately derived.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.5
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• pp.127-136
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• 2023

Gyeonggi Province has established a bus information system to provide real-time bus arrival information, aiming to make bus usage convenient for its residents. While the Gyeonggi bus information system is becoming more advanced through the application of IT technology, there are still information-vulnerable groups finding it difficult to use. In particular, the elderly have a low level of digital information literacy and habe difficulty using it. In this regard, this study aims to address the information usage disparity among the elderly in public transportation by utilizing expert in-depth survey methodology known as the Delphi technique. The study classified the policy initiatives that Gyeonggi Province should undertake into three categories: user education and expanded promotion, technological development and dissemination, and providing convenient usage environment. Through two rounds of surveys, the study assessed the priority of ten specific sub-tasks within these categories. Additionally, it gathered opinions on the effectiveness and feasibility of each item. The results yielded prioritization and evaluation of effectiveness and feasibility for nine sub-tasks. Based on these outcomes, the study proposed future projects that Gyeonggi Province should implement to address the information disparity among the elderly, offering a comprehensive approach to bridge the gap.

• Journal of the Korean Society of Radiology
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• v.17 no.6
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• pp.911-917
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• 2023

The method of observing nodular changes on the liver surface using clinical ultrasonography is useful for diagnosing cirrhosis. However, the speckle noise that inevitably occurs in ultrasound images makes it difficult to identify changes in the liver surface and echo patterns, which has a negative impact on the diagnosis of cirrhosis. The purpose of this study is to model the median modified Wiener filter (MMWF), which can efficiently reduce noise in cirrhotic ultrasound images, and confirm its applicability. Ultrasound images were acquired using an ACR phantom and an actual cirrhotic patient, and the proposed MMWF algorithm and conventional noise reduction algorithm were applied to each image. Coefficient of variation (COV) and edge rise distance (ERD) were used as quantitative image quality evaluation factors for the acquired ultrasound images. We confirmed that the MMWF algorithm improved both COV and ERD values compared to the conventional noise reduction algorithm in both ACR phantom and real ultrasound images of cirrhotic patients. In conclusion, the proposed MMWF algorithm is expected to contribute to improving the diagnosis rate of cirrhosis patients by reducing the noise level and improving spatial resolution at the same time.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1195-1210
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• 2023

Coastal debris has emerged as a salient issue due to its adverse effects on coastal aesthetics, ecological systems, and human health. In pursuit of effective countermeasures, the present study delineated the construction of a specialized image dataset for coastal debris detection and embarked on a comparative analysis between two paramount real-time object detection algorithms, YOLOv8 and RT-DETR. Rigorous assessments of robustness under multifarious conditions were instituted, subjecting the models to assorted distortion paradigms. YOLOv8 manifested a detection accuracy with a mean Average Precision (mAP) value ranging from 0.927 to 0.945 and an operational speed between 65 and 135 Frames Per Second (FPS). Conversely, RT-DETR yielded an mAP value bracket of 0.917 to 0.918 with a detection velocity spanning 40 to 53 FPS. While RT-DETR exhibited enhanced robustness against color distortions, YOLOv8 surpassed resilience under other evaluative criteria. The implications derived from this investigation are poised to furnish pivotal directives for algorithmic selection in the practical deployment of marine debris monitoring systems.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.44 no.1
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• pp.85-93
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• 2024

The monitoring of environmental information (e.g. noise, dust, vibration, temperature, humidity) is crucial to the safe and sustainable operation of a construction site. However, commercial sensors exhibit certain drawbacks when applied on-site. First, the installation cost is prohibitively high. Second, these sensors have been engineered without considering the rugged and harsh conditions of a construction site, resulting in error-prone sensing. Third, construction sites are compelled to allocate additional resources in terms of manpower, expenses, and physical spaces to accommodate individual sensors. This research developed an integrated sensing module to measure the environmental information in construction site. The sensing module slashes the installation cost to 3.3%, is robust enough to harsh and outdoor sites, and consolidates multiple sensors into a single unit. The sensing module also supports GPS, LTE, and real-time sensing. The evaluation showed remarkable results including 97.5% accuracy and 99.9% precision in noise measurement, an 89.7% accuracy in dust measurement, and a 93.5% reliability in data transmission. This research empowers the collection of substantial volumes and high-quality environmental data from construction sites, providing invaluable support to decision-making process. These encompass objective regulatory compliance checking, simulations of environmental data dispersion, and the development of environmental mitigation strategies.

• Journal of the Korea Institute of Building Construction
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• v.24 no.1
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• pp.97-108
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• 2024

This research delves into the escalating concerns of accidents and fatalities in the construction industry over the recent five-year period, focusing on the development of a Safety Perception Model to augment safety measures. Given the rising percentage of elderly workers and the concurrent drop in productivity within the sector, there is a pronounced need for leveraging Fourth Industrial Revolution technologies to bolster safety protocols. The study comprises an in-depth analysis of statistical data regarding construction-related fatalities, aiming to shed light on prevailing safety challenges. Central to this investigation is the formulation of a Safety Perception Model tailored for small-scale construction projects. This model facilitates the quantification of safety risks by evaluating safety grades across construction sites. Utilizing the DWM1000 module, among an array of wireless communication technologies, the model enables the real-time tracking of worker locations and the assessment of safety levels on-site. Furthermore, the deployment of a safety management system allows for the evaluation of risk levels associated with individual workers. Aggregating these data points, the Safety Climate Index(SCLI) is calculated to depict the daily, weekly, and monthly safety climate of the site, thereby offering insights into the effectiveness of implemented safety measures and identifying areas for continuous improvement. This study is anticipated to significantly contribute to the systematic enhancement of safety and the prevention of accidents on construction sites, fostering an environment of improved productivity and strengthened safety culture through the application of the Safety Perception Model.

• Journal of The Korean Association For Science Education
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• v.44 no.1
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• pp.39-55
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• 2024

This study aimed to examine research trends related to Natural Language Processing (NLP) in science education by analyzing 37 domestic and international documents that utilized NLP techniques in the field of science education from 2011 to September 2023. In particular, the study systematically analyzed the content, focusing on the main application areas of NLP techniques in science education, the role of teachers when utilizing NLP techniques, and a comparison of domestic and international perspectives. The analysis results are as follows: Firstly, it was confirmed that NLP techniques are significantly utilized in formative assessment, automatic scoring, literature review and classification, and pattern extraction in science education. Utilizing NLP in formative assessment allows for real-time analysis of students' learning processes and comprehension, reducing the burden on teachers' lessons and providing accurate, effective feedback to students. In automatic scoring, it contributes to the rapid and precise evaluation of students' responses. In literature review and classification using NLP, it helps to effectively analyze the topics and trends of research related to science education and student reports. It also helps to set future research directions. Utilizing NLP techniques in pattern extraction allows for effective analysis of commonalities or patterns in students' thoughts and responses. Secondly, the introduction of NLP techniques in science education has expanded the role of teachers from mere transmitters of knowledge to leaders who support and facilitate students' learning, requiring teachers to continuously develop their expertise. Thirdly, as domestic research on NLP is focused on literature review and classification, it is necessary to create an environment conducive to the easy collection of text data to diversify NLP research in Korea. Based on these analysis results, the study discussed ways to utilize NLP techniques in science education.