• Journal of Internet Computing and Services
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• v.22 no.2
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• pp.59-68
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• 2021

As artificial intelligence(AI) technologies, which have made rapid growth recently, began to be applied to the marine environment such as ships, there have been active researches on the application of CNN-based models specialized for digital videos. In E-Navigation service, which is combined with various technologies to detect floating objects of clash risk to reduce human errors and prevent fires inside ships, real-time processing is of huge importance. More functions added, however, mean a need for high-performance processes, which raises prices and poses a cost burden on shipowners. This study thus set out to propose a method capable of processing information at a high rate while maintaining the accuracy by applying Quantization techniques of a deep learning model. First, videos were pre-processed fit for the detection of floating matters in the sea to ensure the efficient transmission of video data to the deep learning entry. Secondly, the quantization technique, one of lightweight techniques for a deep learning model, was applied to reduce the usage rate of memory and increase the processing speed. Finally, the proposed deep learning model to which video pre-processing and quantization were applied was applied to various embedded boards to measure its accuracy and processing speed and test its performance. The proposed method was able to reduce the usage of memory capacity four times and improve the processing speed about four to five times while maintaining the old accuracy of recognition.

• Journal of Neurogastroenterology and Motility
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• v.24 no.4
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• pp.656-668
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• 2018

Background/Aims MicroRNAs (miRNAs) were reported to be responsible for intestinal permeability in diarrhea-predominant irritable bowel syndrome (IBS-D) rats in our previous study. However, whether and how miRNAs regulate visceral hypersensitivity in IBS-D remains largely unknown. Methods We established the IBS-D rat model and evaluated it using the nociceptive visceral hypersensitivity test, myeloperoxidase activity assay, restraint stress-induced defecation, and electromyographic (EMG) activity. The distal colon was subjected to miRNA microarray analysis followed by isolation and culture of colonic epithelial cells (CECs). Bioinformatic analysis and further experiments, including dual luciferase assays, quantitative real-time polymerase chain reaction, western blot, and enzyme-linked immunosorbent assay, were used to detect the expression of miRNAs and how it regulates visceral hypersensitivity in IBS-D rats. Results The IBS-D rat model was successfully established. A total of 24 miRNAs were differentially expressed in the distal colon of IBS-D rats; 9 were upregulated and 15 were downregulated. Among them, the most significant upregulation was miR-200a, accompanied by downregulation of cannabinoid receptor 1 (CNR1) and serotonin transporter (SERT). MiR-200a mimic markedly inhibited the expression of CNR1/SERT. Bioinformatic analysis and luciferase assay confirmed that CNR1/SERT are direct targets of miR-200a. Rescue experiments that overexpressed CNR1/SERT significantly abolished the inhibitory effect of miR-200a on the IBS-D rats CECs. Conclusions This study suggests that miR-200a could induce visceral hyperalgesia by targeting the downregulation of CNR1 and SERT, aggravating or leading to the development and progression of IBS-D. MiR-200a may be a regulator of visceral hypersensitivity, which provides potential targets for the treatment of IBS-D.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.6
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• pp.457-467
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• 2018

Currently, the regulation and rules for public surveying and the UCPs (Unified Control Points) adapts those of the triangulated traverse surveying. In addition, such regulations do not take account of the unique characteristics of GNSS (Global Navigation Satellite System) surveying, thus there are difficulties in field work and data processing afterwards. A detailed procesure of GNSS processing has not yet been described either, and the verification of accuracy does not follow the generic standards. In order to propose an appropriate procedure for field surveys, we processed a short session (30 minutes) based on the scenarios similar to actual situations. The reference network in Seoul was used to process the same data span for 3 days. The temporal variation during the day was evaluated as well. We analyzed the accuracy of the estimated coordinates depending on the parameterization of tropospheric delay, which was compared with the 24-hr static processing results. Estimating the tropospheric delay is advantageous for the accuracy and stability of the coordinates, resulting in about 5 mm and 10 mm of RMSE (Root Mean Squared Error) for horizontal and vertical components, respectively. Based on the test results, we propose a procedure to estimate the daily solution and then combine them to estimate the final solution by applying the minimum constraints (no-net-translation condition). It is necessary to develop a web-based processing system using a high-end softwares. Additionally, it is also required to standardize the ID of the public control points and the UCPs for the automatic GNSS processing.

• Journal of IKEEE
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• v.23 no.2
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• pp.743-746
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• 2019

In this paper we proposed a new ocean radiation automatic monitoring system. The proposed system has the following characteristics: First, using NaI + PVT mixed detectors, the response speed is fast and precision analysis is possible. Second, the application of temperature compensation algorithm to scintillator-type sensors does not require additional cooling devices and enables stable operation in the changing ocean environment. Third, since cooling system is not needed, electricity consumption is low, and electricity can be supplied reliably by utilizing solar energy, which can be installed at the observation deck of ocean environment. Fourth, using GPS and wireless communications, accurate location information and real-time data transmission function for measurement areas enables immediate warning response in the event of nuclear accidents such as those involving neighboring countries. The results tested by the authorized testing agency to assess the performance of the proposed system were measured in the range of $5{\mu}Sv/h$ to 15mSv/h, which is the highest level in the world, and the accuracy was determined to be ${\pm}8.1%$, making normal operation below the international standard ${\pm}15%$. The internal environmental grade (waterproof) was achieved, and the rate of variation was measured within 5% at operating temperature of $-20^{\circ}C$ to $50^{\circ}C$ and stability was verified. Since the measured value change rate was measured within 10% after the vibration test, it was confirmed that there will be no change in the measured value due to vibration in the ocean environment caused by waves.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.3
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• pp.146-154
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• 2019

Recently, a system has been developed and applied to establish and utilize HD maps through R&D. The biggest problem, however, is the lack of a proper HD map update system, which requires the development and adoption of such a system as soon as possible. In addition, in the case of updating HD maps for automated driving, integrity and accuracy of maps are required for safe driving, so an test of these technologies and data quality is required. In April 2018, the Ministry of Land, Infrastructure and Transport implemented a project to 'Develop Technology to Demonstrate and Share the Instant Road Change Detection and Update Technology for automated driving. This paper analyzed the technology for updating map based on the investigation and analysis of relevant technology trends for the development of integrated demonstration and sharing technology of road change rapid detection and updating map technology, and put forward the criteria for road change rapid detection, integrated quality verification of update technology. It is expected that the results of this study will contribute to quality assurance of HD maps that support safety driving for automated vehicles.

• Journal of Korean Society of Forest Science
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• v.100 no.1
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• pp.14-24
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• 2011

Anticancer activity of Acer mono aqueous extracts was enhanced by nano-encapsulation process of gelatin. The cytotoxicity on human normal lung cell (HEL299) of the extracts from WE (water extract at 100) showed 23.51%, lower than that from NE (nano-encapsulatioin of water extract of Acer mono) in adding the maximum concentration of 1.0 mg/mL. NE showed more potent scavenging effect as 73.15% than the WE. On SOD-like test, the NE showed highest activity as 32.33% at 1.0 mg/mL concentration. Human stomach adenocarcinoma, liver adenocarcinoma, breast adenocarcinoma and lung adenocarcinoma cell growth were inhibited up to about 59-73%, in adding 1.0 mg/mL of NE. NE was 15% higher than conventional water extraction. Among several cancer cell lines (stomach adenocarcinoma, liver adenocarcinoma), the growth of digestive related cancer cells were most effectively inhibited as about 71-73%. The size of nano particles was in the ranges of 100-200 nm, which can effectively the penetrate into the cells, it was observed by real time confocal microscope. It tells that the aqueous extracts of Acer mono bark could be definitely enhanced by nano-encapsulation process.

• 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.

• Korean Journal of Remote Sensing
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• v.36 no.6_1
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• pp.1323-1337
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• 2020

GEO-KOMPSAT-2A AMI (Advanced Meteorological Imager) radiometric calibration evaluation is an essential element not only for functional and performance verification of the payload but for the quality of the sensor data. AMI instrument consists of six reflective channels and ten thermal infrared ones. One of the key parameters representing radiometric properties of the sensor is a SNR (Signal-to-Noise Ratio) for the reflective channels and a NEdT (Noise Equivalent delta Temperature) for the IR ones respectively. Other important radiometric calibration parameters are a dynamic range and a gain value related with the responsivity of detectors. To verify major radiometric calibration performance of AMI, an offline radiometric evaluation tool was developed separately with a real-time AMI data processing system. Using the evaluation tool, validation activities were carried out during the GEO-KOMPSAT-2A In-Orbit Test period. The results from the evaluation tool were cross checked with those of the HARRIS, which is the AMI payload vendor. AMI radiometric evaluation activities were conducted through three phases for both sides (Side 1 and Side 2) of AMI payload. Results showed that performances of the key radiometric properties were outstanding with respect to the radiometric requirements of the payload. The effectiveness of the evaluation tool was verified as well.

• Smart Media Journal
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• v.10 no.1
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• pp.9-15
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• 2021

The eye tracking system designed in this paper is an eye-based computer input device designed to give an easy access for those who are uncomfortable with Lou Gehrig's or various muscle-related diseases. It is an eye-based-computer-using device for users whose potential demand alone amounts to 30,000. Combining the number of Lou Gehrig's patients in Korea estimated at around 1,700, and those who are unable to move their bodies due to various accidents or diseases. Because these eye input devices are intended for a small group of users, many types of commercial devices are available on the market. It is making them more expensive and difficult to use for these potential users, less accessible. For this reason, each individual's economic situation and individual experience with smart devices are slightly different. Therefore, making it difficult to access them in terms of cost or usability to use a commercial eye tracking system. Accordingly, attempts to improve accessibility to IT devices through low-cost but easy-to-use technologies are essential. Thus, this paper proposes a complementary superior performance eye tracking system that can be conveniently used by far more people and patients by improving the deficiencies of the existing system. Through voluntary VoCs(Voice of Customers) of users who have used different kinds of eye tracking systems that satisfies it through various usability tests, and we propose a reduced system that the amount of calculation to 1/15th, and eye-gaze tracking error rate to 0.5~1 degree under.

• Smart Media Journal
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• v.11 no.4
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• pp.46-55
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• 2022

It is very important to first detect and remove defective fruits with scratches or bruised areas in the automatic fruit quality screening system. This paper proposes a method of detecting defective areas in fruits using the latest artificial intelligence technology, the Yolo V4 deep learning model in order to overcome the limitations of the method of detecting fruit's defective areas using the existing image processing techniques. In this study, a total of 2,400 defective fruits, including 1,000 defective apples and 1,400 defective fruits with scratch or decayed areas, were learned using the Yolo V4 deep learning model and experiments were conducted to detect defective areas. As a result of the performance test, the precision of apples is 0.80, recall is 0.76, IoU is 69.92% and mAP is 65.27%. The precision of pears is 0.86, recall is 0.81, IoU is 70.54% and mAP is 68.75%. The method proposed in this study can dramatically improve the performance of the existing automatic fruit quality screening system by accurately selecting fruits with defective areas in real time rather than using the existing image processing techniques.