• Korean Chemical Engineering Research
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• v.57 no.2
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• pp.274-282
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• 2019

In recent years, big data analysis has been expanded to include automatic control through reinforcement learning as well as prediction through modeling. Research on the utilization of image data is actively carried out in various industrial fields such as chemical, manufacturing, agriculture, and bio-industry. In this paper, we applied NASNet, which is an AutoML reinforced learning algorithm, to DeepU-Net neural network that modified U-Net to improve image semantic segmentation performance. We used BRATS2015 MRI data for performance verification. Simulation results show that DeepU-Net has more performance than the U-Net neural network. In order to improve the image segmentation performance, remove dropouts that are typically applied to neural networks, when the number of kernels and filters obtained through reinforcement learning in DeepU-Net was selected as a hyperparameter of neural network. The results show that the training accuracy is 0.5% and the verification accuracy is 0.3% better than DeepU-Net. The results of this study can be applied to various fields such as MRI brain imaging diagnosis, thermal imaging camera abnormality diagnosis, Nondestructive inspection diagnosis, chemical leakage monitoring, and monitoring forest fire through CCTV.

• Journal of the Korean Geosynthetics Society
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• v.19 no.4
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• pp.41-50
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• 2020

Since cracks in concrete structures expedite corrosion of reinforced concrete over a long period of time, regular on-site inspections are essential to ensure structural usability and prevent degradation. Most of the safety inspections of facilities rely on visual inspection with naked eye, so cost and time consuming are severe, and the reliability of results differs depending on the inspector. In this study, a portable measuring device that can be used for safety diagnosis and maintenance was developed as a device that measures the width and length of concrete cracks through image analysis of cracks photographed with a camera. This device captures the cracks found within a close distance (3 m), and accurately calculates the unit pixel size by laser distance measurement, and automatically calculates the crack length and width with the image processing algorithm developed in this study. In measurement results using the crack image applied to the experiment, the measurement of the length of a 0.3 mm crack within a distance of 3 m was possible with a range of about 10% error. The crack width showed a tendency to be overestimated by detecting surrounding pixels due to vibration and blurring effect during the binarization process, but it could be effectively corrected by applying the crack width reduction function.

• Journal of the Korean Society of Radiology
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• v.16 no.4
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• pp.387-394
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• 2022

120 kVp FBP reconstruction image standard by using raw data after scanning by changing tube voltage among the NECK CT protocols that are broad applied in clinical practice using a human phantom including thyroid gland The usefulness of the DLIR reconstruction technique was investigated. As a result, CTDIvol decreased when the DLIR reconstruction technique was applied, and in particular, the image quality obtained under the same standard scanning conditions at a lower dose for ASIR-V and DLIR reconstruction was reached than when FBP was applied at the same kVp In addition, as a result of SNR and CNR analysis, the DLIR reconstructed image was analyzed with high SNR and CNR values, and SSIM analysis, the SSIM index of the 100 kVp, DLIR reconstructed image was measured to be close to 1, and it was analyzed that the similarity of the reconstructed image to the original image was high (p>0.05). If the results of this study are used to supplement clinical image evaluation and further develop an algorithm applicable to various anatomical structures, it is thought that it will be useful for clinical application as it is possible to maintain the image quality while lowering the examination dose.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.285-301
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• 2023

Due to the increasing demand and importance of non-face-to-face education, open online learning platforms are getting interests both domestically and internationally. These platforms exhibit different characteristics from online courses by universities and other educational institutions. In particular, students engaged in these platforms can receive more learner autonomy, and the development of tools to assist learning is required. From the past, researchers have attempted to utilize process mining to understand realistic study behaviors and derive learning patterns. However, it has a deficiency to employ it to the open online learning platforms. Moreover, existing research has primarily focused on the process model perspective, including process model discovery, but lacks a method for the process pattern and instance perspectives. In this study, we propose a method to identify learning patterns within an open online learning platform using process mining techniques. To achieve this, we suggest three different viewpoints, e.g., model-level, variant-level, and instance-level, to comprehend the learning patterns, and various techniques are employed, such as process discovery, conformance checking, autoencoder-based clustering, and predictive approaches. To validate this method, we collected a learning log of machine learning-related courses on a domestic open education platform. The results unveiled a spaghetti-like process model that can be differentiated into a standard learning pattern and three abnormal patterns. Furthermore, as a result of deriving a pattern classification model, our model achieved a high accuracy of 0.86 when predicting the pattern of instances based on the initial 30% of the entire flow. This study contributes to systematically analyze learners' patterns using process mining.

• Korean Journal of Construction Engineering and Management
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• v.24 no.1
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• pp.40-50
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• 2023

Quality control (QC) is an essential work for the successful construction project execution. Recently, robust application of ICT to the QC tasks leads to utilizing innovative technologies and equipment. However, overall planing of QC works needs to take place before applying new technologies to each and individual QC task. The objectives of this research involve developing a database and an algorithm that identifies QC tasks and related information upfront. In addition, the researchers developed a methodology to generate inspection tasks in conjunction with construction work tasks. The Korean Ministry of Land and Transportation provides standard supervision checklists. They were classified based on criteria of inspection items, methods, period and the scope. Reinforced concrete work was selected as a case study for validation of the method. This framework can function when planing construction tasks with any type of planning tools and innovative technologies. The researchers expect this framework may contribute to various construction projects when developing QC plans and tasks with applicable technologies.

• Journal of Internet Computing and Services
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• v.25 no.1
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• pp.99-107
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• 2024

Along with economic growth and industrial development, there is an increasing demand for various electronic components and device production of semiconductor, SMT component, and electrical battery products. However, these products may contain foreign substances coming from manufacturing process such as iron, aluminum, plastic and so on, which could lead to serious problems or malfunctioning of the product, and fire on the electric vehicle. To solve these problems, it is necessary to determine whether there are foreign materials inside the product, and may tests have been done by means of non-destructive testing methodology such as ultrasound ot X-ray. Nevertheless, there are technical challenges and limitation in acquiring X-ray images and determining the presence of foreign materials. In particular Small-sized or low-density foreign materials may not be visible even when X-ray equipment is used, and noise can also make it difficult to detect foreign objects. Moreover, in order to meet the manufacturing speed requirement, the x-ray acquisition time should be reduced, which can result in the very low signal- to-noise ratio(SNR) lowering the foreign material detection accuracy. Therefore, in this paper, we propose a five-step approach to overcome the limitations of low resolution, which make it challenging to detect foreign substances. Firstly, global contrast of X-ray images are increased through histogram stretching methodology. Second, to strengthen the high frequency signal and local contrast, we applied local contrast enhancement technique. Third, to improve the edge clearness, Unsharp masking is applied to enhance edges, making objects more visible. Forth, the super-resolution method of the Residual Dense Block (RDB) is used for noise reduction and image enhancement. Last, the Yolov5 algorithm is employed to train and detect foreign objects after learning. Using the proposed method in this study, experimental results show an improvement of more than 10% in performance metrics such as precision compared to low-density images.

• Korean Journal of Agricultural and Forest Meteorology
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• v.19 no.3
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• pp.153-163
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• 2017

The objective of this study is to enhance the model's speed of estimating weather variables (e.g., minimum/maximum temperature, sunshine hour, PRISM (Parameter-elevation Regression on Independent Slopes Model) based precipitation), which are applied to the Agrometeorological Early Warning System (http://www.agmet.kr). The current process of weather estimation is operated on high-performance multi-core CPUs that have 8 physical cores and 16 logical threads. Nonetheless, the server is not even dedicated to the handling of a single county, indicating that very high overhead is involved in calculating the 10 counties of the Seomjin River Basin. In order to reduce such overhead, several cache and parallelization techniques were used to measure the performance and to check the applicability. Results are as follows: (1) for simple calculations such as Growing Degree Days accumulation, the time required for Input and Output (I/O) is significantly greater than that for calculation, suggesting the need of a technique which reduces disk I/O bottlenecks; (2) when there are many I/O, it is advantageous to distribute them on several servers. However, each server must have a cache for input data so that it does not compete for the same resource; and (3) GPU-based parallel processing method is most suitable for models such as PRISM with large computation loads.

• Journal of Internet Computing and Services
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• v.17 no.1
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• pp.101-107
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• 2016

Due to the recent advancement in digital imaging technology, development of intervention equipment has become generalize. Video arbitration procedure is a process to insert a tiny catheter and a guide wire in the body, so in order to enhance the effectiveness and safety of this treatment, the high-quality of x-ray of image should be used. However, the increasing of radiation has become the problem. Therefore, the studies to improve the performance of x-ray detectors are being actively processed. Moreover, this intervention is based on the reference of the angiographic imaging and 3D medical image processing. In this paper, we propose a guidance system to support this intervention. Through this intervention, it can solve the problem of the existing 2D medical images based vessel that has a formation of cerebrovascular disease, and guide the real-time tracking and optimal route to the target lesion by intervention catheter and guide wire tool. As a result, the system was completely composed for medical image acquisition unit and image processing unit as well as a display device. The experimental environment, guide services which are provided by the proposed system Brain Phantom (complete intracranial model with aneurysms, ref H+N-S-A-010) was taken with x-ray and testing. To generate a reference image based on the Laplacian algorithm for the image processing which derived from the cerebral blood vessel model was applied to DICOM by Volume ray casting technique. $A^*$ algorithm was used to provide the catheter with a guide wire tracking path. Finally, the result does show the location of the catheter and guide wire providing in the proposed system especially, it is expected to provide a useful guide for future intervention service.

• The Korean Journal of Nuclear Medicine Technology
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• v.16 no.1
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• pp.86-90
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• 2012

Purpose: Quantification of myocardial blood flow (MBF) using dynamic PET imaging has the potential to assess coronary artery disease. Rb-82 plays a key role in the clinical assessment of myocardial perfusion using PET. However, MBF could be overestimated due to the underestimation of left ventricular input function in the beginning of the acquisition when the scanner has non-linearity between count rate and activity concentration due to the scanner dead-time. Therefore, in this study, we evaluated the count rate linearity as a function of the activity concentration in PET data acquired in list mode. Materials & methods: A cylindrical phantom (diameter, 12 cm length, 10.5 cm) filled with 296 MBq F-18 solution and 800 mL of water was used to estimate the linearity of the Biograph 40 True Point PET/CT scanner. PET data was acquired with 10 min per frame of 1 bed duration in list mode for different activity concentration levels in 7 half-lives. The images were reconstructed by OSEM and FBP algorithms. Prompt, net true and random counts of PET data according to the activity concentration were measured. Total and background counts were measured by drawing ROI on the phantom images and linearity was measured using background correction. Results: The prompt count rates in list mode were linearly increased proportionally to the activity concentration. At a low activity concentration (<30 kBq/mL), the prompt net true and random count rates were increased with the activity concentration. At a high activity concentration (>30 kBq/mL), the increasing rate of the prompt net true rates was slightly decreased while the increasing rate of random counts was increased. There was no difference in the image intensity linearity between OSEM and FBP algorithms. Conclusion: The Biograph 40 True Point PET/CT scanner showed good linearity of count rate even at a high activity concentration (~370 kBq/mL).The result indicates that the scanner is useful for the quantitative analysis of data in heart dynamic studies using Rb-82, N-13, O-15 and F-18.

• Journal of Sasang Constitutional Medicine
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• v.11 no.1
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• pp.137-157
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• 1999

The purpose of this study is to help classifying Sasang Constitution through correlation with sound characteristic. This study was done it under the suppose that Sasang Constitution has correlation with sound spectrogram. The following result were obtained about correlation between sound spectrogram and Sasang Constitution by comparison and analysis 1. Soeumin answered his voice low tone, smooth and quiet in the survey. Soyangin answered his voice high, clear, fast and speaking random. Taeumin answered his voice low, thick and muddy. 2. Taeyangin was significantly slow compared with the others in the time of reading composition. Taeyangin was significantly slow compared with the others in Formant frequency 1. Taeyangin was significantly discriminated from Soeumin in Formant frequency 5. Taeyangin was significantly low compared with the others in Bandwidth 2. Soeumln was significantly low compared with Taeyangin in Pitch Maximum and Pitch Maximum-Pitch Minimum. Taeyangin was significantly high compared with the others in Energy mean. 3. In list of specification, the discrimination rate was higher than that by lists of 13 in the results of Multi-dimensional 4-class minimum-distance. The discrimination rate of three disposition except Soyangin was higher than that of four disposition in the results of One way ANOVA and Analysis of dis crimination in SPSS/PC+. In CART, the estimate rate of Sasang Constitution discrimination was higher than any other method. It is considered that there is a correlation between sound spectrogram and Sasang constitution according to the results. And method of Sasang constitution classification through sound spectrogram analysis can be one method as assistant for the objectification of Sasang constitution classification.