• Journal of Intelligence and Information Systems
• /
• v.27 no.1
• /
• pp.47-64
• /
• 2021

The global spread of COVID-19 around the world has not only affected many parts of our daily life but also has a huge impact on many areas, including the economy and society. As the number of confirmed cases and deaths increases, medical staff and the public are said to be experiencing psychological problems such as anxiety, depression, and stress. The collective tragedy that accompanies the epidemic raises fear and anxiety, which is known to cause enormous disruptions to the behavior and psychological well-being of many. Long-term negative emotions can reduce people's immunity and destroy their physical balance, so it is essential to understand the psychological state of COVID-19. This study suggests a method of monitoring medial news reflecting current days which requires striving not only for physical but also for psychological quarantine in the prolonged COVID-19 situation. Moreover, it is presented how an easier method of analyzing social media networks applies to those cases. The aim of this study is to assist health policymakers in fast and complex decision-making processes. News plays a major role in setting the policy agenda. Among various major media, news headlines are considered important in the field of communication science as a summary of the core content that the media wants to convey to the audiences who read it. News data used in this study was easily collected using "Bigkinds" that is created by integrating big data technology. With the collected news data, keywords were classified through text mining, and the relationship between words was visualized through semantic network analysis between keywords. Using the KrKwic program, a Korean semantic network analysis tool, text mining was performed and the frequency of words was calculated to easily identify keywords. The frequency of words appearing in keywords of articles related to COVID-19 emotions was checked and visualized in word cloud 'China', 'anxiety', 'situation', 'mind', 'social', and 'health' appeared high in relation to the emotions of COVID-19. In addition, UCINET, a specialized social network analysis program, was used to analyze connection centrality and cluster analysis, and a method of visualizing a graph using Net Draw was performed. As a result of analyzing the connection centrality between each data, it was found that the most central keywords in the keyword-centric network were 'psychology', 'COVID-19', 'blue', and 'anxiety'. The network of frequency of co-occurrence among the keywords appearing in the headlines of the news was visualized as a graph. The thickness of the line on the graph is proportional to the frequency of co-occurrence, and if the frequency of two words appearing at the same time is high, it is indicated by a thick line. It can be seen that the 'COVID-blue' pair is displayed in the boldest, and the 'COVID-emotion' and 'COVID-anxiety' pairs are displayed with a relatively thick line. 'Blue' related to COVID-19 is a word that means depression, and it was confirmed that COVID-19 and depression are keywords that should be of interest now. The research methodology used in this study has the convenience of being able to quickly measure social phenomena and changes while reducing costs. In this study, by analyzing news headlines, we were able to identify people's feelings and perceptions on issues related to COVID-19 depression, and identify the main agendas to be analyzed by deriving important keywords. By presenting and visualizing the subject and important keywords related to the COVID-19 emotion at a time, medical policy managers will be able to be provided a variety of perspectives when identifying and researching the regarding phenomenon. It is expected that it can help to use it as basic data for support, treatment and service development for psychological quarantine issues related to COVID-19.

• Journal of Food Hygiene and Safety
• /
• v.36 no.6
• /
• pp.493-503
• /
• 2021

The study was designed to analyze raw and auxiliary materials of Korean traditional cookies such as Yugwa and Gangjeong, equipment and tools, personal hygiene of workers and microbial contamination of materials by each manufacturing process. In addition, it looked at washing method for reducing microorganisms at the site and reduction effect of microorganisms by frequency in the manufacturing processes of Yugwa. In the process of producing Korean traditional cookies, the level of total aerobic bacteria (TAB) in popped rice was 1.2 Log CFU/g and the level of TAB in finished products increased to 3.7 Log CFU/g. In the process of producing Yugwa, the level of TAB increased to a maximum of 6.5 Log CFU/g in the soaking process but decreased to 1.3 Log CFU/g in the frying process. However, the level of TAB increased again to 1.3 Log CFU/g in finished products that proves its recontamination. It is estimated that he manufacturing process causes cross-contamination that comes from the work tools, equipment or workers. In particular, the spatula, one of the work tools, was found to have 4.4 Log CFU/g of aerobic bacteria and 4.2 Log CFU/g of colon bacillus that show they are highly contaminated. In the soaking process of Yugwa that lasts seven days, the level of TAB was a maximum of 10 Log CFU/g and the level of total colon bacillus was 6.8 Log CFU/g. When compared with washing methods, using hands and tools or running water, it is confirmed that the level of both TAB and total colon bacillus decreased to 5.0 Log CFU/g and 2.8 Log CFU/g respectively when hands were washed with running water 10 times. The above result shows that it's required for workers to wash their hands as well as wash and disinfect work tools and equipment in the process of producing Korean traditional cookies at small-scale companies. In addition, to reduce the level of microbial contamination in finished products, workers are required to apply their reduction method at the site.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.24 no.4
• /
• pp.41-54
• /
• 2021

It is very essential to estimate the water body area using remote exploration for water resource management, analysis and prediction of water disaster damage. Hydrophysical detection using satellites has been mainly performed on large satellites equipped with optical and SAR sensors. However, due to the long repeat cycle, there is a limitation that timely utilization is impossible in the event of a disaster/disaster. With the recent active development of Micro satellites, it has served as an opportunity to overcome the limitations of time resolution centered on existing large satellites. The Micro satellites currently in active operation are ICEYE in Finland and Capella satellites in the United States, and are operated in the form of clusters for earth observation purposes. Due to clustering operation, it has a short revisit cycle and high resolution and has the advantage of being able to observe regardless of weather or day and night with the SAR sensor mounted. In this study, the operation status and characteristics of micro satellites were described, and the water area estimation technology optimized for micro SAR satellite images was applied to the Daecheong Dam basin on the Korean Peninsula. In addition, accuracy verification was performed based on the reference value of the water generated from the optical satellite Sentinel-2 satellite as a reference. In the case of the Capella satellite, the smallest difference in area was shown, and it was confirmed that all three images showed high correlation. Through the results of this study, it was confirmed that despite the low NESZ of Micro satellites, it is possible to estimate the water area, and it is believed that the limitations of water resource/water disaster monitoring using existing large SAR satellites can be overcome.

• Analytical Science and Technology
• /
• v.35 no.3
• /
• pp.136-142
• /
• 2022

According to media reports, the carcasses of euthanized abandoned dogs were processed at high temperature and pressure to make powder, and then used as feed materials (meat and bone meal), raising the possibility of residuals in the feed of the anesthetic ketamine and dexmedetomidine used for euthanasia. Therefore, a simultaneous analysis method using QuEChERS combined with high-performance liquid chromatography coupled with electrospray ionization tandem mass spectrometry was developed for rapid residue analysis. The method developed in this study exhibited linearity of 0.999 and higher. Selectivity was evaluated by analyzing blank and spiked samples at the limit of quantification. The MRM chromatograms of blank samples were compared with those of spiked samples with the analyte, and there were no interferences at the respective retention times of ketamine and dexmedetomidine. The detection and quantitation limits of the instrument were 0.6 ㎍/L and 2 ㎍/L, respectively. The limit of quantitation for the method was 10 ㎍/kg. The results of the recovery test on meat and bone meal, meat meal, and pet food showed ketamine in the range of 80.48-98.63 % with less than 5.00 % RSD, and dexmedetomidine in the range of 72.75-93.00 % with less than 4.83 % RSD. As a result of collecting and analyzing six feeds, such as meat and bone meal, prepared at the time the raw material was distributed, 10.8 ㎍/kg of ketamine was detected in one sample of meat and bone meal, while dexmedetomidine was found to have a concentration below the limit of quantitation. It was confirmed that the detected sample was distributed before the safety issue was known, and thereafter, all the meat and bone meal made with the carcasses of euthanized abandoned dogs was recalled and completely discarded. To ensure the safety of the meat and bone meal, 32 samples of the meat and bone meal as well as compound feed were collected, and additional residue investigations were conducted for ketamine and dexmedetomidine. As a result of the analysis, no component was detected. However, through this investigation, it was confirmed that some animal drugs, such as anesthetics, can remain without decomposition even at high temperature and pressure; therefore, there is a need for further investigation of other potentially hazardous substances not controlled in the feed.

• Journal of Korea Water Resources Association
• /
• v.56 no.4
• /
• pp.235-243
• /
• 2023

Due to the revision of the River Act and the enactment of the Act on the Investigation, Planning, and Management of Water Resources, a regular bed change survey has become mandatory and a system is being prepared such that local governments can manage water resources in a planned manner. Since the topography of a bed cannot be measured directly, it is indirectly measured via contact-type depth measurements such as level survey or using an echo sounder, which features a low spatial resolution and does not allow continuous surveying owing to constraints in data acquisition. Therefore, a depth measurement method using remote sensing-LiDAR or hyperspectral imaging-has recently been developed, which allows a wider area survey than the contact-type method as it acquires hyperspectral images from a lightweight hyperspectral sensor mounted on a frequently operating drone and by applying the optimal bandwidth ratio search algorithm to estimate the depth. In the existing hyperspectral remote sensing technique, specific physical quantities are analyzed after matching the hyperspectral image acquired by the drone's path to the image of a surface unit. Previous studies focus primarily on the application of this technology to measure the bathymetry of sandy rivers, whereas bed materials are rarely evaluated. In this study, the existing hyperspectral image-based water depth estimation technique is applied to rivers with vegetation, whereas spatio-temporal hyperspectral imaging and cross-sectional hyperspectral imaging are performed for two cases in the same area before and after vegetation is removed. The result shows that the water depth estimation in the absence of vegetation is more accurate, and in the presence of vegetation, the water depth is estimated by recognizing the height of vegetation as the bottom. In addition, highly accurate water depth estimation is achieved not only in conventional cross-sectional hyperspectral imaging, but also in spatio-temporal hyperspectral imaging. As such, the possibility of monitoring bed fluctuations (water depth fluctuation) using spatio-temporal hyperspectral imaging is confirmed.

• Analytical Science and Technology
• /
• v.36 no.3
• /
• pp.135-142
• /
• 2023

The total arsenic and 6 arsenic species were investigated in 56 fish collagen products using ICP-MS (Inductively coupled plasma-mass spectrometer) and HPLC-ICP-MS(High performance liquid chromatography-Inductively coupled plasma-mass spectrometer). The mean concentrations of total arsenic and arsenic species were 40.103±81.133 ㎍/kg (N.D.~586.686) and 30.070±50.378 ㎍/kg (N.D.~313.871), respectively. The mean concentration of inorganic arsenic was 24.610±32.706 ㎍/kg (N.D.~129.331), and the As(V) (Arsenate) was the most dominant. The standards and specifications of arsenic have not been established for fish collagen products. Our study presents that arsenic levels are relatively safe compared with not only previous studies but also domestic and international standards. However, in one sample, the total arsenic concentration was 586.686 ㎍/kg, showing the inorganic was 8.119 ㎍/kg, and the DMA was 305.752 ㎍/kg, which was high than the Canadian standard for organic arsenic. In conclusion, it is necessary to monitor arsenic levels consistently and establish standards and specifications of arsenic in fish collagen products to assure consumer safety.

• Korea Science and Art Forum
• /
• v.23
• /
• pp.111-122
• /
• 2016

The purpose of this multi-disciplinary convergent study is to establish Image Copyright Archive Model for Museums to protect image copyright and vitalize the use of images out of necessity of research and development on copyright services over the life cycle of art contents created by the museums and out of the necessity to vitalize distribution market of image copyright contents in creative industry and to formulate management system of copyright services. This study made various suggestions for enhancement of transparency and efficiency of art contents ecosystem through vitalization of use and recycling of image copyright materials by proposing standard system for calculation, distribution, settlement and monitoring of copyright royalty of 1,000 domestic museums, galleries and exhibit halls. First, this study proposed contents and structure design of image copyright archive model and, by proposing art contents distribution service platform for prototype simulation, execution simulation and model operation simulation, established art contents copyright royalty process model. As billing system and technological development for image contents are still in incipient stage, this study used the existing contents billing framework as basic model for the development of billing technology for distribution of museum collections and artworks and automatic division and calculation engine for copyright royalty. Ultimately, study suggested image copyright archive model which can be used by artists, curators and distributors. In business strategy, study suggested niche market penetration of museum image copyright archive model. In sales expansion strategy, study established a business model in which effective process of image transaction can be conducted in the form of B2B, B2G, B2C and C2B through flexible connection of museum archive system and controllable management of image copyright materials can be possible. This study is expected to minimize disputes between copyright holder of artwork images and their owners and enhance manageability of copyrighted artworks through prevention of such disputes and provision of information on distribution and utilization of art contents (of collections and new creations) owned by the museums. In addition, by providing a guideline for archives of collections of museums and new creations, this study is expected to increase registration of image copyright and to make various convergent businesses possible such as billing, division and settlement of copyright royalty for image copyright distribution service.

• Korean Journal of Remote Sensing
• /
• v.39 no.2
• /
• pp.193-205
• /
• 2023

A large amount of floating debris from land-based sources during heavy rainfall has negative social, economic, and environmental impacts, but there is a lack of monitoring systems for floating debris accumulation areas and amounts. With the recent development of artificial intelligence technology, there is a need to quickly and efficiently study large areas of water systems using drone imagery and deep learning-based object detection models. In this study, we acquired various images as well as drone images and trained with You Only Look Once (YOLO)v5s and the recently developed YOLO7 and YOLOv8s to compare the performance of each model to propose an efficient detection technique for land-based floating debris. The qualitative performance evaluation of each model showed that all three models are good at detecting floating debris under normal circumstances, but the YOLOv8s model missed or duplicated objects when the image was overexposed or the water surface was highly reflective of sunlight. The quantitative performance evaluation showed that YOLOv7 had the best performance with a mean Average Precision (intersection over union, IoU 0.5) of 0.940, which was better than YOLOv5s (0.922) and YOLOv8s (0.922). As a result of generating distortion in the color and high-frequency components to compare the performance of models according to data quality, the performance degradation of the YOLOv8s model was the most obvious, and the YOLOv7 model showed the lowest performance degradation. This study confirms that the YOLOv7 model is more robust than the YOLOv5s and YOLOv8s models in detecting land-based floating debris. The deep learning-based floating debris detection technique proposed in this study can identify the spatial distribution of floating debris by category, which can contribute to the planning of future cleanup work.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.30 no.3A
• /
• pp.297-307
• /
• 2010

Recently, maintenance engineering and technology for civil and building structures have begun to draw big attention and actually the number of structures that need to be evaluate on structural safety due to deterioration and performance degradation of structures are rapidly increasing. When stiffness is decreased because of deterioration of structures and member cracks, dynamic characteristics of structures would be changed. And it is important that the damaged areas and extent of the damage are correctly evaluated by analyzing dynamic characteristics from the actual behavior of a structure. In general, typical measurement instruments used for structure monitoring are dynamic instruments. Existing dynamic instruments are not easy to obtain reliable data when the cable connecting measurement sensors and device is long, and have uneconomical for 1 to 1 connection process between each sensor and instrument. Therefore, a method without attaching sensors to measure vibration at a long range is required. The representative applicable non-contact methods to measure the vibration of structures are laser doppler effect, a method using GPS, and image processing technique. The method using laser doppler effect shows relatively high accuracy but uneconomical while the method using GPS requires expensive equipment, and has its signal's own error and limited speed of sampling rate. But the method using image signal is simple and economical, and is proper to get vibration of inaccessible structures and dynamic characteristics. Image signals of camera instead of sensors had been recently used by many researchers. But the existing method, which records a point of a target attached on a structure and then measures vibration using image processing technique, could have relatively the limited objects of measurement. Therefore, this study conducted shaking table test and field load test to verify the validity of the method that can measure multi-point displacement responses of structures using image processing technique.

• Korean Journal of Remote Sensing
• /
• v.39 no.6_1
• /
• pp.1321-1330
• /
• 2023

Normalized Difference Vegetation Index (NDVI) is the most widely used remote sensing data in the agricultural field and is currently provided by most optical satellites. In particular, as high-resolution optical satellite images become available, the selection of optimal optical satellite images according to agricultural applications has become a very important issue. In this study, we aim to define the most optimal optical satellite image when monitoring NDVI in rice fields in Korea and derive the resolution-related requirements necessary for this. For this purpose, we compared and analyzed the spatial distribution and time series patterns of the Dangjin rice paddy in Korea from 2019 to 2022 using NDVI images from MOD13, Landsat-8, Sentinel-2A/B, and PlanetScope satellites, which are widely used around the world. Each data is provided with a spatial resolution of 3 m to 250 m and various periods, and the area of the spectral band used to calculate NDVI also has slight differences. As a result of the analysis, Landsat-8 showed the lowest NDVI value and had very low spatial variation. In comparison, the MOD13 NDVI image showed similar spatial distribution and time series patterns as the PlanetScope data but was affected by the area surrounding the rice field due to low spatial resolution. Sentinel-2A/B showed relatively low NDVI values due to the wide near-infrared band area, and this feature was especially noticeable in the early stages of growth. PlanetScope's NDVI provides detailed spatial variation and stable time series patterns, but considering its high purchase price, it is considered to be more useful in small field areas than in spatially uniform rice paddy. Accordingly, for rice field areas, 250 m MOD13 NDVI or 10 m Sentinel-2A/B are considered to be the most efficient, but high-resolution satellite images can be used to estimate detailed physical quantities of individual crops.