• Journal of the Korea Society of Computer and Information
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• v.15 no.1
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• pp.149-157
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• 2010

As the use of the Internet has recently increased, the demand for opinion information posted on the Internet has grown. However, such resources only exist on the website. People who want to search for information on the Internet find it inconvenient to visit each website. This paper focuses on the opinion information extraction and analysis system through Web mining that is based on statistics collected from Web contents. That is, users' opinion information which is scattered across several websites can be automatically analyzed and extracted. The system provides the opinion information search service that enables users to search for real-time positive and negative opinions and check their statistics. Also, users can do real-time search and monitoring about other opinion information by putting keywords in the system. Proposed technologies proved to have outstanding capabilities in comparison to existing ones through tests. The capabilities to extract positive and negative opinion information were assessed. Specifically, test movie review sentence testing data was tested and its results were analyzed.

• The Journal of Korean Academy of Prosthodontics
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• v.59 no.3
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• pp.299-304
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• 2021

Purpose. The purpose of the present study was to investigate the effects of image matching experience of operators on the accuracy and working time of image registration between radiographic and optical scan images. Materials and methods. Computed tomography and optical scan of a dentate dental arch were obtained. Image matching between the computed tomography and the optical scan (IDC S1, Amann Girrbach, Koblah, Austria) was performed using the point-based automatic registration method in planning software programs (Implant Studio, 3Shape, Copenhagen, Denmark) using two different experience conditions on image registration: experienced group and inexperienced group (n = 15 per group, N = 30). The accuracy of image registration in each group was evaluated by measuring linear discrepancies between matched images, and working time was recorded. Independent t test was used to statistically analyze the result data (α = .05). Results. In the linear deviation, no statistically significant difference was found between the experienced and inexperienced groups. Meanwhile, the working time for image registration was significantly shorter in the experienced group than in the inexperienced group (P = .007). Conclusion. Difference in the image matching experience may not influence the accuracy of image registration of optical scan to computed tomography when the point-based automatic registration was used, but affect the working time for the image registration.

• The Journal of the Korea Contents Association
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• v.21 no.1
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• pp.552-560
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• 2021

Currently, the domestic aquaculture industry is pursuing smartization, but it is still proceeding with human subjective judgment in many processes in the aquaculture stage. The prerequisite for the smart aquaculture industry is to effectively grasp the condition of fish in the farm. If real-time monitoring is possible by identifying the number of fish populations, size, pathways, and speed of movement, various forms of automation such as automatic feed supply and disease determination can be carried out. In this study, we proposed an algorithm to identify the state of fish in real time using underwater video data. The fish detection performance was compared and evaluated by applying the latest deep learning-based object detection models, and an algorithm was proposed to measure fish object identification, path tracking, and moving speed in continuous image frames in the video using the fish detection results. The proposed algorithm showed 92% object detection performance (based on F1-score), and it was confirmed that it effectively tracks a large number of fish objects in real time on the actual test video. It is expected that the algorithm proposed in this paper can be effectively used in various smart farming technologies such as automatic feed feeding and fish disease prediction in the future.

• Journal of Apiculture
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• v.34 no.1
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• pp.47-55
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• 2019

Honey bees are a vital part of the food chain as the most important pollinators for a broad palette of crops and wild plants. The climate change and colony collapse disorder (CCD) phenomenon make it challenging to develop ICT solutions to predict changes in beehive and alert about potential threats. In this paper, we report the test results of the bee-counting system which stands out against the previous analogues due to its comprehensive components including an improved dual infrared sensor to detect honey bees entering and leaving the hive, environmental sensors that measure ambient and interior, a wireless network with the bluetooth low energy (BLE) to transmit the sensing data in real time to the gateway, and a cloud which accumulate and analyze data. To assess the system accuracy, 3 persons manually counted the outgoing and incoming honey bees using the video record of 360-minute length. The difference between automatic and manual measurements for outgoing and incoming scores were 3.98% and 4.43% respectively. These differences are relatively lower than previous analogues, which inspires a vision that the tested system is a good candidate to use in precise apicultural industry, scientific research and education.

• Journal of the Korean Society of Radiology
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• v.16 no.7
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• pp.871-877
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• 2022

This study was conducted to improve the problems of exposure dose and image reading applied to patients due to the incorrect use of AEC during chest radiography. Images were acquired by dividing the case where AEC was used as the test condition and the case where AEC was not used. As a result of the study, the dose was reduced by 1.17% in 110 kVp without AEC than with AEC, 17.2% decrease at 100 kVp, 30.19% decrease at 90 kVp, and 46.45% decrease at 80 kVp. There was a significant difference in the statistical values according to the tube voltage change in the lung, trachea, and heart SNR average values with AEC and without AEC 110 kVp, but the difference in image quality was insignificant in actual images. When AEC was not applied at the same tube voltage, the dose could be reduced by 17.2% while maintaining the image quality similar to that of with AEC at 100 kVp without AEC. Therefore, rather than relying on AE conditions during chest radiographic examination, it is considered that the conditions should be considered for the examination while lowering the dose by selecting an appropriate tube voltage.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.7
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• pp.1038-1043
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• 2021

Guaranteed seafarer wage payment is essential to ensure a stable supply of seafarers. However, disputes over non-payment of wages to seafarers often occur. In this study, an automatic wage payment system was designed using a blockchain-based smart contract to resolve the problem of seafarers' wage arrears. The designed system consists of an information register, a matching processing unit, a review rating management unit, and wage remittance before deploying smart contracts. The matching process was designed to send an automatic notification to seafarers and shipowners if the sum of the weight of the four variables, namely wages, ship type/fishery, position, and license, exceeded a pre-defined threshold. In addition, a review rating management system, based on a combination of mean and median, was presented to serve as a medium to mutually fulfill the normal working conditions. The smart contract automatically fulfills the labor contract between the parties without an intermediary. This system will naturally resolve problems such as fraudulent advance payment to seafarers, embezzlement by unregistered employment agencies, overdue wages, and forgery of seafarers' books. If this system design is commercialized and institutionally activated, it is expected that stable wages will be guaranteed to seafarers, and in turn, the difficulties in human resources supply will be solved. We plan to test it in a local environment for further developing this system.

• Journal of Korea Society of Industrial Information Systems
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• v.14 no.1
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• pp.1-8
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• 2009

The objective of this study is to design a system that automatically monitors the state of interior spaces like offices where lots of people are coming and going through image data and environment data, which includes temperature, humidity, and other conditions, and implement and test related application programs. In practice, there are lots of image data automatically obtained by unmanned equipments, such as certain types of CCTVs, for monitoring situation in usual interior spaces. This image data can be used as a more effective manner by establishing a system that recognizes situation in specific interior spaces based on the relationship between image and environment data. For instance, it is possible to perform unmanned on/off controls for various electronic equipments, such as air conditioners, lights, and other devices, through analyzing the data acquisited from environment sensors (temperature, humidity, and illumination) as dynamic states are not maintained for a specified period of time. For implementing these controls, this study analyzes environment data acquisited from temperature and humidity sensors and image data input from wireless cameras to recognize situation and that can be used to automatically control environment variables configured by users. Experiments were applied in a laboratory where unmanned controls were effectively performed as automatic on/off controls for the air conditioner and lights installed in the laboratory as certain motions were detected or undetected for a specified period of time.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.2D
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• pp.245-253
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• 2009

Road facility is the most fundamental infrastructure for traffic and various information for smooth traffic is included in road surfaces. Various information included in road surfaces should be often removed and reinstalled by partial damage and aging. In addition, the existing road surface information should be removed in order to mark new information as traffic information changes. The existing road surface removal method suing grinders and torches had problems such as dangerous working equipment and workers' direct exposure to cars. In addition, although water-jet system using super high-pressure water was used to remove road surface in order of improvement of traditional method, there are another problems such as limitations according to water-tanks and water frost on the road surfaces after work. Therefore, this study analyzes and suggests systems to develop prototype after analyzing dry ice blaster in order to improve the current road surface removal methods. In addition, the study analyzes the possibility of introduction of dry ice blaster through a test for proposing an automatized equipment for new road surface mark removal considering environment and work efficiency, and compare traditional method with introduced dry ice blaster for operating cost.

• Journal of The Korean Astronomical Society
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• v.56 no.2
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• pp.213-224
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• 2023

Type II solar radio bursts show frequency drifts from high to low over time. They have been known as a signature of coronal shock associated with Coronal Mass Ejections (CMEs) and/or flares, which cause an abrupt change in the space environment near the Earth (space weather). Therefore, early detection of type II bursts is important for forecasting of space weather. In this study, we develop a deep-learning (DL) model for the automatic detection of type II bursts. For this purpose, we adopted a 1-D Convolution Neutral Network (CNN) as it is well-suited for processing spatiotemporal information within the applied data set. We utilized a total of 286 radio burst spectrum images obtained by Hiraiso Radio Spectrograph (HiRAS) from 1991 and 2012, along with 231 spectrum images without the bursts from 2009 to 2015, to recognizes type II bursts. The burst types were labeled manually according to their spectra features in an answer table. Subsequently, we applied the 1-D CNN technique to the spectrum images using two filter windows with different size along time axis. To develop the DL model, we randomly selected 412 spectrum images (80%) for training and validation. The train history shows that both train and validation losses drop rapidly, while train and validation accuracies increased within approximately 100 epoches. For evaluation of the model's performance, we used 105 test images (20%) and employed a contingence table. It is found that false alarm ratio (FAR) and critical success index (CSI) were 0.14 and 0.83, respectively. Furthermore, we confirmed above result by adopting five-fold cross-validation method, in which we re-sampled five groups randomly. The estimated mean FAR and CSI of the five groups were 0.05 and 0.87, respectively. For experimental purposes, we applied our proposed model to 85 HiRAS type II radio bursts listed in the NGDC catalogue from 2009 to 2016 and 184 quiet (no bursts) spectrum images before and after the type II bursts. As a result, our model successfully detected 79 events (93%) of type II events. This results demonstrates, for the first time, that the 1-D CNN algorithm is useful for detecting type II bursts.

• The Korean Society of Law and Medicine
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• v.24 no.3
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• pp.125-153
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• 2023

The Supreme Court's en banc decision on December 12, 2022 (docket number 2016Do21314) presented a new standard for determining whether the use of diagnostic medical devices by Korean medical doctors constitutes oriental medical doctors constitutes unlicensed medical practice. Based on this standard, it was determined that the use of ultrasound by Korean medical doctors was not an unlicensed medical practice. Supreme Court's Decision 2016Du51405 on August 18, 2023, is the first case in which a new standard was applied to determine that an Korean medical doctor's use of electroencephalography to diagnose Parkinson's disease and dementia was not an unlicensed medical practice. The Supreme Court abolished the previous standard that Western medical knowledge and technology should not be required for Korean medical doctors to use medical devices. However, it was unclear whether Western medical diagnosis of Korean medical doctors using diagnostic medical devices would be viewed as an an auxiliary method of diagnosis. Parkinson's disease and dementia are Western medical diagnoses. The Supreme Court judged that the Western medical diagnosis of Korean medical doctors was not an unlicensed medical practice. This clearly explains what an auxiliary method of diagnosis means. In addition, the Supreme Court excluded the principles of development and production of electroencephalography from its judgment criteria. Automatic extraction and automatic reading of test results were also excluded. The criminal court's view that the meaning of oriental medical practice should be clearly and strictly interpreted from the perspective of an oriental doctor, and it was clarified that diagnostic medical devices were excluded from criminal punishment unless it was clear that they were not related to the principle of oriental medical practice. As a result, the Supreme Court made it clear that the use of diagnostic medical devices is excluded from criminal punishment unless it is clear that they are not related to the principles of Korean medicine.