• Journal of the Korean Society of Radiology
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• v.12 no.7
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• pp.895-908
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• 2018

As modern science is developed and advanced, examination and number of times using radiation are increasing daily. General diagnostic X-ray generator is installed on stationary form, But X-ray generator was developed because patient who is in the intensive care unit, operation room, emergency room can not move to general x-ray room. What we examine patient by x-ray generator is certainly necessary, So patient exposure is inevitable. but reducing radiation exposure is highly important matter about radiation technology, guardian, patient in the same hospital room, nurse etc. For this reason, rule regarding safety control of diagnostic x-ray generator revised for radiation worker, patient and protector proclaim that mobile diagnostic x-ray shield must placed in case of examine different location excluding operation room, emergency room, intensive care unit. But, radiogical technologist is having a lot of difficulties to examine with mobile x-ray generator, diagnostic x-ray shield partition, image plate and lead apron. So, when we use x-ray generator, we manufacture shield tools can be attached to the mobile x-ray generator On behalf of x-ray shield partition and conduct analysis and in comparison to part of body and distribution of dose rate and find way to reduce radiation exposure through distribution of dose rate of patient within the radiogical technologist, medical team. Mobile x-ray generator aimed at SHIMADZU inc. R-20, We manufactured equipment for shielding x-ray scattered x-ray by installing shielding wall from side to side based on support beam on the mobile x-ray generator. Shielding wall when moving can be folded and designed to expand when examine. Experiment measured five times in each by an angle for dose rate of eyes, thyroid, breast, abdomen and gonad on exposure condition of upper and lower extremity, chest, abdomen which is examined many times by mobile x-ray generator. We used dosimeter RSM-100 made by IJRAD and measured a horizontal dose rate by body part. The result of an experiment, shielding decreasing rate of the front and the rear showed 77 ~ 98.7%. Therefore using self-production shielding wall reduce scattered x-ray occurrence rate and confirm can decrease exposure dose consequently. Therefore, through this study, reduction result which is used shielding wall of self-production will be a role of shielding optimization and it could be answer about reduction of medical exposure recommended by ICRP 103.

• Journal of fish pathology
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• v.35 no.1
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• pp.1-25
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• 2022

The aquaculture industry has developed rapidly over the last three decades and is an important industry that supplies over 15% of humans' animal protein intake; therefore, there is a need to increase production to meet the continuous demand. The fish cage farms on the southern coast (Kyengsangnam-do and Jeollanam-do) of Korea are critical resources in aquaculture because they account for approximately 90% of the national total fish cage farms by water area ratio. However, the current aquaculture environment is being gradually affected by climate change, which is a global issue, and its effects are expected to intensify in the future. Therefore, it is urgently imperative to accurately evaluate the effects of climate change on South Korean aquaculture industries and to develop social and national strategies to minimize damage to the fishing industry. The damage to fish farmed in cage farms on the southern coast is increasing annually and the leading causes are high and low water temperature and red tides, which are directly or indirectly related to climate change. At present, global warming can provide opportunities for aquaculture industrialization of fish or other novel species, with economic implications. However, despite such opportunities, the influx of new species can also cause problems such as ecological disturbances, increase in the reproduction frequency of microalgae such as red tide, increase in disease incidence, and occurrence and periods of high water temperatures in summer. The scale of farmed fish mortality is increasing due to the complex effects of these factors. Increased damages due to fish mortality not only have severe economic impacts on the aquaculture industry, but the social costs of responding to the damage and follow-up measures also increase. various active responses can reduce the mortality damage in fish farms such as improving the management skills in aquaculture, improved species breeding, efficient food management, disease prevention, proactive responses, and system-wide improvements. This review article analyzes the large-scale mortality cases occurring in fish cage farms on the southern coast of Korea and proposes measures to mitigate mortality and enhance responses to such scenarios.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.11
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• pp.471-480
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• 2023

The Korean construction order volume in South Korea grew significantly from 91.3 trillion won in public orders in 2013 to a total of 212 trillion won in 2021, particularly in the private sector. As the size of the domestic and overseas markets grew, the scale and complexity of EPC (Engineering, Procurement, Construction) projects increased, and risk management of project management and ITB (Invitation to Bid) documents became a critical issue. The time granted to actual construction companies in the bidding process following the EPC project award is not only limited, but also extremely challenging to review all the risk terms in the ITB document due to manpower and cost issues. Previous research attempted to categorize the risk terms in EPC contract documents and detect them based on AI, but there were limitations to practical use due to problems related to data, such as the limit of labeled data utilization and class imbalance. Therefore, this study aims to develop an AI model that can categorize the contract terms based on the FIDIC Yellow 2017(Federation Internationale Des Ingenieurs-Conseils Contract terms) standard in detail, rather than defining and classifying risk terms like previous research. A multi-text classification function is necessary because the contract terms that need to be reviewed in detail may vary depending on the scale and type of the project. To enhance the performance of the multi-text classification model, we developed the ELECTRA PLM (Pre-trained Language Model) capable of efficiently learning the context of text data from the pre-training stage, and conducted a four-step experiment to validate the performance of the model. As a result, the ensemble version of the self-developed ITB-ELECTRA model and Legal-BERT achieved the best performance with a weighted average F1-Score of 76% in the classification of 57 contract terms.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.29 no.1
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• pp.56-76
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• 2024

We for the first time made a successful longest continuous sectional observation in the East Sea by an underwater glider during 95 days from September 18 to December 21 2020 in the Korea along the 106 Line (129.1 °E ~ 131.5 °E at 37.9 °N) of the regular shipboard measurements by the National Institute of Fishery Science (NIFS) and obtained twelve hydrographic sections with high spatiotemporal resolution. The glider was deployed at 129.1 °E in September 18 and conducted 88-days flight from September 19 to December 15 2020, yielding twelve hydrographic sections, and then recovered at 129.2 °E in December 21 after the last 6 days virtual mooring operation. During the total traveled distance of 2550 km, the estimated deviation from the predetermined zonal path had an average RMS distance of 262 m. Based on these high-resolution long-term glider measurements, we conducted a comparative study with the bi-monthly NIFS measurements in terms of spatial and temporal resolutions, and found distinguished features. One is that spatial features of sub-mesoscale such as sub-mesoscale frontal structure and intensified thermocline were detected only in the glider measurements, mainly due to glider's high spatial resolution. The other is the detection of intramonthly variations from the weekly time series of temperature and salinity, which were extracted from glider's continuous sections. Lastly, there were deviations and bias in measurements from both platforms. We argued these deviations in terms of the time scale of variation, the spatial scale of fixed-point observation, and the calibration status of CTD devices of both platforms.

• Research in Plant Disease
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• v.30 no.1
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• pp.66-77
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• 2024

Black wood ear mushroom (Auricularia auricula-judae) is one of the most economically important mushrooms in China, Japan, and Korea. The cultivation of wood ear mushrooms on artificial substrates is more efficient in terms of time and cost compared with their natural growth on trees. However, if the substrate cultivation is infected by fast-growing fungi, the relatively slow-growing ear mushroom will be outcompeted, leading to economic losses. In this study, we investigated the competitive fungal isolates from substrates infected with fast-growing fungi for the cultivation of ear mushrooms in Jangheung and Sunchon, Korea. We collected 54 isolates and identified them by sequencing their internal transcribed spacer region with morphological identification. Among the isolates, the dominant isolates were Trichoderma spp. (92.6%), Penicillium spp. (5.6%), and Talaromyces sp. (1.8%). To find an appropriate eco-friendly biocontrol agent, we used five Streptomyces spp. and Benomyl, as controls against Trichoderma spp. and Penicillium spp. Among the six Streptomyces spp., Streptomyces sp. JC203-3 effectively controlled the fungi Trichoderma spp. and Penicillium spp., which pose a significant problem for the substrates of black wood ear mushrooms. This result indicated that this Streptomyces sp. JC203-3 can be used as biocontrol agents to protect against Trichoderma and Penicillium spp.

• Journal of the Korean Society of Food Science and Nutrition
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• v.36 no.9
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• pp.1172-1181
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• 2007

This research involved 226 Jeonbuk Province school dietitians as subjects to investigate intake and perceptions of the healthy functional foods. Sixty nine percent of the school dietitians didn't even know about the law enforcement concerning the health functional foods. Although 68.1% of the respondents said that they slightly knew about health functional foods, only 25% knew exactly what it was. As shown in the survey, most didn't have the cognitive understanding did not understand which should be obtained by education. Sixty two percent of the answerers said they had experience of taking health various functional food products of various kinds such as supplements (57.9%), red ginseng products (52.9%), and chlorella products (30.0%). The motive of intake was in the order of fatigue restoration (25.7%), sickness prevention (22.9%), and nutrient replenishment (22.9%). A fascinating fact from this study was that the reason for healthy functional product intake was different between groups that was primarily interested in the products and those that was not. For those who had interest, the reason for intake was for sickness prevention. On the other hand, for those who didn't have any interest, the reasons was primarily for fatigue restoration and they were mostly persuaded by close friends and relatives. Main concerns were in the order of side effects (4.72), efficacy after intake (4.59), cleanliness (4.51), reliability of the company (4.29), and price (4.23). In view of the study, it is clear that a lot of people are showing interest in healthy functional food products. However, dietitians who are experts in food and nutrition lacked knowledge and information on healthy functional food.

• FLOWER RESEARCH JOURNAL
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• v.18 no.3
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• pp.186-192
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• 2010

An infrared heating system, installed in a small venlo-type glasshouse ($280m^2$) in Gyeongsang National University, Jinju, Korea, was used to investigate its heating effect with potted Phalaenopsis, Schefflera arboricola 'Hongkong', Ficus elastica 'Variegata', and Rosa hybrida 'Yellow King' as the test plants. Temperature changes in test plants with the system turned 'On' and 'Off' were measured by using an infrared camera and the consumption of electricity by this infrared heating system was measured and analyzed. In potted Phalaenopsis, when the set air temperature of the greenhouse was $18^{\circ}C$, temperature of leaves and the growing medium were $22.8{\sim}27^{\circ}C$ and $21.3{\sim}24.3^{\circ}C$, respectively. In such tall plants as Schefflera arboricola 'Hongkong' and Ficus elastica 'Variegata', the upper part showed the highest temperature of 24.0 and $26.9^{\circ}C$, respectively. From the results of temperature change measurements, the plant temperatures were near or above the set point temperatures with some fluctuations depending on the position or distance from the infrared heating system. When air temperature between night and dawn dropped sharply, plant temperatures were maintained close to the set temperature ($18^{\circ}C$). There was a significant difference between 'On' and 'Off' states of the infrared heating system in average temperatures of root zone and leaf: 21.8 and $17.8^{\circ}C$ with the system 'On' and 20.4 and $15.5^{\circ}C$ with the system 'Off', respectively, in a cut rose Rosa hybrida 'Yellow King'. The heating load was about $24,850{\sim}35,830kcal{\cdot}h^{-1}$, which comes to about 27,000~40,000 won in Korean currency when calculated in terms of the cost of heating by a hot water heating system heated by petroleum. The cost for heating by the infrared heating system was about 35% of that of a hot water heating system. With the infrared heating system, the air temperature during the night was maintained slightly lower than the set point air temperature, probably due to the lack of air tightness of the glasshouse. Therefore, glasshouses with an infrared heating system requires further investigation including the installation space of the heat-emitting units, temperature sensor positions, and convection.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.87-109
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• 2020

Currently, thanks to the major stride made in developing wired and wireless communication technology, a variety of IT services are available on land. This trend is leading to an increasing demand for IT services to vessels on the water as well. And it is expected that the request for various IT services such as two-way digital data transmission, Web, APP, etc. is on the rise to the extent that they are available on land. However, while a high-speed information communication network is easily accessible on land because it is based upon a fixed infrastructure like an AP and a base station, it is not the case on the water. As a result, a radio communication network-based voice communication service is usually used at sea. To solve this problem, an additional frequency for digital data exchange was allocated, and a ship ad-hoc network (SANET) was proposed that can be utilized by using this frequency. Instead of satellite communication that costs a lot in installation and usage, SANET was developed to provide various IT services to ships based on IP in the sea. Connectivity between land base stations and ships is important in the SANET. To have this connection, a ship must be a member of the network with its IP address assigned. This paper proposes a SANET-CC protocol that allows ships to be assigned their own IP address. SANET-CC propagates several non-overlapping IP addresses through the entire network from land base stations to ships in the form of the tree. Ships allocate their own IP addresses through the exchange of simple requests and response messages with land base stations or M-ships that can allocate IP addresses. Therefore, SANET-CC can eliminate the IP collision prevention (Duplicate Address Detection) process and the process of network separation or integration caused by the movement of the ship. Various simulations were performed to verify the applicability of this protocol to SANET. The outcome of such simulations shows us the following. First, using SANET-CC, about 91% of the ships in the network were able to receive IP addresses under any circumstances. It is 6% higher than the existing studies. And it suggests that if variables are adjusted to each port's environment, it may show further improved results. Second, this work shows us that it takes all vessels an average of 10 seconds to receive IP addresses regardless of conditions. It represents a 50% decrease in time compared to the average of 20 seconds in the previous study. Also Besides, taking it into account that when existing studies were on 50 to 200 vessels, this study on 100 to 400 vessels, the efficiency can be much higher. Third, existing studies have not been able to derive optimal values according to variables. This is because it does not have a consistent pattern depending on the variable. This means that optimal variables values cannot be set for each port under diverse environments. This paper, however, shows us that the result values from the variables exhibit a consistent pattern. This is significant in that it can be applied to each port by adjusting the variable values. It was also confirmed that regardless of the number of ships, the IP allocation ratio was the most efficient at about 96 percent if the waiting time after the IP request was 75ms, and that the tree structure could maintain a stable network configuration when the number of IPs was over 30000. Fourth, this study can be used to design a network for supporting intelligent maritime control systems and services offshore, instead of satellite communication. And if LTE-M is set up, it is possible to use it for various intelligent services.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.173-198
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• 2020

For a long time, many studies have been conducted on predicting the success of campaigns for customers in academia, and prediction models applying various techniques are still being studied. Recently, as campaign channels have been expanded in various ways due to the rapid revitalization of online, various types of campaigns are being carried out by companies at a level that cannot be compared to the past. However, customers tend to perceive it as spam as the fatigue of campaigns due to duplicate exposure increases. Also, from a corporate standpoint, there is a problem that the effectiveness of the campaign itself is decreasing, such as increasing the cost of investing in the campaign, which leads to the low actual campaign success rate. Accordingly, various studies are ongoing to improve the effectiveness of the campaign in practice. This campaign system has the ultimate purpose to increase the success rate of various campaigns by collecting and analyzing various data related to customers and using them for campaigns. In particular, recent attempts to make various predictions related to the response of campaigns using machine learning have been made. It is very important to select appropriate features due to the various features of campaign data. If all of the input data are used in the process of classifying a large amount of data, it takes a lot of learning time as the classification class expands, so the minimum input data set must be extracted and used from the entire data. In addition, when a trained model is generated by using too many features, prediction accuracy may be degraded due to overfitting or correlation between features. Therefore, in order to improve accuracy, a feature selection technique that removes features close to noise should be applied, and feature selection is a necessary process in order to analyze a high-dimensional data set. Among the greedy algorithms, SFS (Sequential Forward Selection), SBS (Sequential Backward Selection), SFFS (Sequential Floating Forward Selection), etc. are widely used as traditional feature selection techniques. It is also true that if there are many risks and many features, there is a limitation in that the performance for classification prediction is poor and it takes a lot of learning time. Therefore, in this study, we propose an improved feature selection algorithm to enhance the effectiveness of the existing campaign. The purpose of this study is to improve the existing SFFS sequential method in the process of searching for feature subsets that are the basis for improving machine learning model performance using statistical characteristics of the data to be processed in the campaign system. Through this, features that have a lot of influence on performance are first derived, features that have a negative effect are removed, and then the sequential method is applied to increase the efficiency for search performance and to apply an improved algorithm to enable generalized prediction. Through this, it was confirmed that the proposed model showed better search and prediction performance than the traditional greed algorithm. Compared with the original data set, greed algorithm, genetic algorithm (GA), and recursive feature elimination (RFE), the campaign success prediction was higher. In addition, when performing campaign success prediction, the improved feature selection algorithm was found to be helpful in analyzing and interpreting the prediction results by providing the importance of the derived features. This is important features such as age, customer rating, and sales, which were previously known statistically. Unlike the previous campaign planners, features such as the combined product name, average 3-month data consumption rate, and the last 3-month wireless data usage were unexpectedly selected as important features for the campaign response, which they rarely used to select campaign targets. It was confirmed that base attributes can also be very important features depending on the type of campaign. Through this, it is possible to analyze and understand the important characteristics of each campaign type.