• Journal of Food Hygiene and Safety
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• v.39 no.5
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• pp.404-411
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• 2024

Paralytic Shellfish Poisoning (PSP) occurs when humans consume shellfish contaminated with saxitoxin (STX) and its derivatives. It causes symptoms ranging from numbness and nausea to severe muscle paralysis and respiratory failure. Toxic equivalency factors (TEFs) are used to standardize the toxic effects of various PSP toxins for risk assessment. Traditional detection methods, such as mouse bioassays, have been used to set the TEFs, but ethical concerns over in vivo studies have shifted the focus toward analytical methods, such as high-performance liquid chromatography. However, in vivo data are essential for establishing TEFs, particularly for emerging marine biotoxins. This study employed a three-level response surface pathway (RSP) design, which reduced the number of animals used to evaluate the median lethal dose (LD₅₀) of STX and its derivatives. The LD₅₀ and TEF values for STX dihydrochloride, neosaxitoxin, decarbamoylsaxitoxin, gonyautoxins 1 & 4 (GTX1&4), GTX2&3, and dcGTX2&3 were 451.3 (1.00), 306.5 (1.47), 860.9 (0.52), 644.5 (0.70), 915.3 (0.49), and 2409.3 (0.19) ㎍/kg, respectively. These TEFs closely aligned with the WHO recommendations and prior oral LD₅₀ values, with Pearson correlation coefficients of 0.969 and 0.994, respectively. This study highlights the need for accurate TEF assignments for PSP toxins and new marine biotoxins, demonstrating that the three-level RSP design balances ethical concerns and provides reliable toxicity data.

• The Journal of the Convergence on Culture Technology
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• v.10 no.6
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• pp.855-861
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• 2024

The power industry is undergoing a rapid transformation with the adoption of smart grid standards, advanced communication infrastructure, and new technologies for distributed power. MVDC (Medium Voltage Direct Current) technology plays a vital role in promoting efficient energy transmission and reducing greenhouse gas emissions, necessitating a structured architecture for stable management. This paper implements services defined in IEC 61850 and IEC 62541, defining a Virtual Manufacturing Device (VMD) to objectify the DTS (Digital Twin System). The VMD abstracts essential functions for control and monitoring, which are realized in DTS to enhance capabilities. The objectified DTS data facilitates server-client data exchange. Additionally, the proposed DTS-MS communication protocol defines transmitted data in JSON for remote access, providing node functionality for MVDC testing environments. The paper analyzes reference models for Digital Twin, proposes an Ethernet-based DTS architecture using international standards, and verifies the real-time performance improvements of the proposed system through mathematical simulations.

• The Journal of the Convergence on Culture Technology
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• v.10 no.6
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• pp.759-764
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• 2024

An agricultural drones are the increasing demand for the use of multicopters in spraying operations, there is a growing emphasis on high operational efficiency, convenience, and applicability. In agricultural spraying tasks, efforts to address the issue of spraying drift have led to experimental validation of various nozzle designs aimed at reducing drift through comparative analysis with prior research. This study aims to experimentally validate the characteristics of drift associated with different nozzles and predict application performance by evaluating the target areas post-spraying. The results showed that the DG nozzle achieved a relatively higher coverage rate. As flight speed increased, coverage rate decreased relatively. This was due to reduced downward wind resulting from changes in the aircraft's tilt and increased rotor thrust, which enhanced drift and reduced the number of droplets reaching the target area. This was because higher flight altitude resulted in a wider effective spraying distance, which reduced the droplet deposition per unit area. Similarly, as flight altitude increased, the coverage rate also decreased relatively. This decrease in coverage was due to the wider effective spraying distance at higher altitudes, resulting in reduced droplet deposition per unit area. These findings allow for the derivation of optimal spraying conditions(flight altitude and speed) and aim to minimize drift in pest control operations, thereby applying these optimal conditions to improve the spraying process.

• Atmosphere
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• v.34 no.4
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• pp.463-480
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• 2024

This study aims to assess the performance of climate prediction systems around the world, and understand objective seasonal prediction skill of KMA's GloSea6. Using the 2023 hindcast verification values provided by the WMO Lead Centre for Long-Range Forecast (LC-LRF), we analyzed the skill in the global, East Asia, and European regions. The differences in prediction skill and RMSE between GPC (Global Producing Centers) were very small in this challenging area. Overall, GloSea6 showed the best ACC across variables and periods. Operating this outstanding climate prediction system not only ensures the provision of the best forecasting services but also offers excellent research and development tools. This result also suggests that seasonal forecasting requires different strategies against short- to medium-range forecast to account for climate prediction sources and reduce uncertainties. The skill differences between GloSea6-Seoul and GloSea6-Exeter, especially in high latitude, could be due to differences in snow and soil temperature initialization. Understanding these differences is important for future prediction system development. GPCs that use atmospheric only models instead of coupled, showed the limitations for seasonal predictions. Systems developed a relatively long time ago tended to perform low, suggesting that continuous improvements and upgrades are important. Among variables, SST showed the best prediction skill with the lowest RMSE. Temperature and pressure variables showed practical skill levels, around 0.5. We aimed to quantitatively assess the skills of climate prediction systems, and this assessment can guide the improvement and development of future systems and serve as a reference.

• Annual Conference of KIPS
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• 2007.05a
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• pp.540-543
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• 2007

최근의 그리드 컴퓨팅 시스템 환경은 단일 환경에서 작게는 2~4CPU, 많게는 수백 CPU 이상의 시스템으로 구축되고 있고, 더욱이 지역적으로도 멀리 떨어져 있다. 따라서 이를 운용하는 기업에서는 시스템의 사용 현황을 신속하게 분석할 필요가 있다. 그러나 이렇게 혼재된 이 기종 및 컴퓨팅 환경하에서의 각 지역별 시스템 사용현황을 효과적으로 분석 한다는 것은 매우 어려운 일이다. 기존에 사용되어 온 그리드 컴퓨팅 시스템 환경에서의 사용율 관리 방법들은 Queueing 시스템이 가지고 있는 Accounting 분석 명령어로 text 형태의 Accounting raw data 의 결과를 추출하여 가공 처리하므로 데이터 증가 시 반응 속도가 현격하게 느려지는 상황이 발생한다. 또한 원격지 그리드 컴퓨팅 시스템 군의 사용율 분석은 데이터 분석 시 매번 원격지접근 절차를 사용하여 그리드 컴퓨팅 시스템 군에 접근한 후 해당 로컬 시스템 분석을 해야 하고 각 원격지시스템군별로 추출 된 데이터를 통합 관리해야 하는 문제점을 가지고 있다. 따라서 이러한 문제점을 해결하고자 하는 것이 본 논문에서 제안하는 3-tier 구조의 GSA(Grid System Account)이다. 제안한 GSA 는 각 원격지 별 데이터를 객체화하여 Database 에 저장 함으로써 데이터 분석 시 효과적으로 처리할 수 있으며, 다수의 원격지 그리드 컴퓨팅 시스템 군에 대한 복합적인 분석이 필요할 때 효율적으로 대처할 수 있다. 본 논문에서는 GSA 의 설계방법을 제안하고 구현하여 실 성능을 시험함으로써 보다 효율적인 그리드 컴퓨팅 시스템의 사용율 분석 관리가 가능함을 보였다.포는 감수성을 보이지 않았다. 따라서 위의 결과로부터 SLT-I에 감수성을 보이지 않은 Raw264.7세포를 대상으로 Gb3 발현 정도와 SLT-I의 세포독성의 관계를 규명하고자 Gb3의 발현을 증가시킨 후 SLT-I의 세포독성을 재차 평가하였다. 이 결과 $TNF-{\alpha}$의 처리에 의하여 6 hrs에 Gb3의 발현이 정점(43.5%)에 이르렀으며 36 hrs에 정상 수준(25.0%)으로 환원되었다. 그러나, Gb3의 발현이 증가함에도 불구하고 SLT-I의 세포독성에는 변화가 관찰되지 않았다. 따라서, SLT-I에 의한 세포독성은 세포의 종류에 따라서 다르며 또한, Gb3의 발현정도에만 의존적이지는 않을 것으로 생각된다. 이와 같은 결과는 E. coli 0157의 감염증 병인 연구에 있어 SLT-I과 Gb3의 발현의 상관관계에 대한 보다 심도 있는 연구가 필요함을 시사한다.만 분할률, 배반포 형성률 및 배반포의 세포수를 증가시키는 것으로 사료된다.수의 유출입 지점에 온도센서를 부착하여 냉각수의 온도를 측정하고 냉각수의 공급량과 대기의 온도 등을 측정하여 대사열의 발생을 추정할 수 있었다. 동시에 이를 이용하여 유가배양시 기질을 공급하는 공정변수로 사용하였다 [8]. 생물학적인 폐수처리장치인 활성 슬러지법에서 미생물의 활성을 측정하는 방법은 아직 그다지 개발되어있지 않다. 본 연구에서는 슬러지의 주 구성원이 미생물인 점에 착안하여 침전시 슬러지층과 상등액의 온도차를 측정하여 대사열량의 발생량을 측정하고 슬러지의 활성을 측정할 수 있는 방법을 개발하였다.enin과 Rhaponticin의 작용(作用)에 의(依)한 것이며, 이

• Journal of Korea Water Resources Association
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• v.57 no.10
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• pp.769-783
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• 2024

This study conducted a comparative analysis by simultaneously applying the widely used SWAT (Soil and Water Assessment Tool) and HSPF (Hydrological Simulation Program-Fortran) models to estimate the inflow of discharge, total phosphorus (TP), total nitrogen (TN), and total suspended solids (TSS) into Okjeong Lake, located in the upper reaches of the Seomjin River. Data provided by the Ministry of Environment from 2012 to 2021 were used as input and calibration data for both models, and performance evaluation metrics such as the coefficient of determination (R²), Nash-Sutcliffe Efficiency (NSE), and Percent Bias (PBIAS) were utilized to assess model accuracy. For flow calibration, the SWAT model showed slightly better performance, with an average R² of 0.82 and NSE of 0.72 across all stations, compared to the HSPF model's R² of 0.76 and NSE of 0.67. However, for water quality calibration, the SWAT model had an average PBIAS of 13.2% for TN, 19.1% for TP, and 31.5% for TSS, while the HSPF model had an average PBIAS of 17.2% for TN, 23.2% for TP, and 25.9% for TSS. These results suggest that both models are limited in their ability to accurately simulate real world water quality. Based on the predicted results of the two models, this study analyzed the causes of the errors and provided useful examples for selecting an appropriate watershed model for water quality management of Okjeong Lake, including non-point source pollution load reduction.

• Journal of the Korean Society of Marine Environment & Safety
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• v.30 no.5
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• pp.415-425
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• 2024

The global maritime industry is developing rapidly owing to the emergence of autonomous ship technology, and interest in utilizing artificial intelligence derived from marine data is increasing. Among the diverse technological developments, ship-route clustering is emerging as an important technology for the commercialization of autonomous ships. Through route clustering, ship-route patterns are extracted from the sea to obtain the fastest and safest route and serve as a basis for the development of a collision-prevention system. High-quality, well-processed data are essential in ensuring the accuracy and efficiency of route-clustering algorithms. In this study, among the various route-clustering methods, we focus on the ship-route-similarity-based clustering method, which can accurately reflect the actual shape and characteristics of a route. To maximize the efficiency of this method, we attempt to formulate an optimal combination of data-preprocessing technologies. Specifically, we combine four methods of measuring similarity between ship routes and three dimensionality-reducing methods. We perform k-means cluster analysis for each combination and then quantitatively evaluate the results using the silhouette index to obtain the best-performing preprocessing combination. This study extends beyond merely identifying the optimal preprocessing technique and emphasizes the importance of extracting meaningful information from a wide range of ocean data. Additionally, this study can be used as a reference for effectively responding to the digital transformation of the maritime and shipping industry in the Fourth Industrial Revolution era.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.5
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• pp.274-292
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• 2024

The purpose of this study is to develop test scenarios utilizing V2X (Vehicle-to-Everything) communication technology for the prevention of pedestrian accidents and to validate these scenarios through simulation. To this end, this researcher used existing traffic accident databases to categorize vehicle-to-pedestrian accident data, and drew key accident patterns through the analysis of accident types and the speeds of pedestrians and vehicles. Based on the analyzed data, scenarios were established where V2X technology can be applied under various conditions of pedestrians and vehicles. These scenarios were specifically classified into conditions where physical avoidance of an accident is impossible and conditions where accident avoidance is possible through V2X technology. In the developed test matrix, simulations were conducted in diverse scenarios to evaluate the performance of the V2X-based accident prevention system. The research results confirmed that the application of V2X technology is effective for preventing pedestrian accidents. It is expected that these scenarios can serve as standardized guidelines for future traffic safety improvements. This study provides useful data for policymakers for traffic safety, vehicle manufacturers, and technology developers, and proposes a new approach to enhance pedestrian safety.

• Journal of Korean Society of Disaster and Security
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• v.17 no.2
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• pp.1-11
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• 2024

Most reservoirs in South Korea are earthen dams, mainly because they are cost-effective and easy to construct. However, earthen dams are highly vulnerable to seepage and overtopping, making them prone to sudden failure during excessive flooding. Such sudden failures can lead to a rapid increase in flood discharge, causing significant damage to downstream rivers and inhabited areas. This study investigates the effect of riprap placement on the slopes of earthen dams in delaying dam failure. Delaying the failure time is crucial as it allows more time for evacuation, significantly reducing potential casualties, which is essential from a disaster response perspective. Hydraulic experiments were conducted in a straight channel, using two different sizes of riprap for protection. Unlike previous studies, these experiments were performed under unsteady flow conditions to reflect the impact of rising water levels inside the dam. The target dam for the study was a cofferdam installed in a diversion tunnel. Experimental results indicated that the presence of riprap protection effectively prevented slope failure under the tested conditions. Without riprap protection, increasing the size of the riprap delayed the failure time. This delay can reduce peak discharge, mitigating damage downstream of the dam. Furthermore, these findings can serve as critical reference material for establishing emergency action plans (EAP) for reservoir failure.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.17 no.4
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• pp.236-244
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• 2024

A representative problem in domestic chestnut industry is the high loss of flesh due to excessive knife peeling in order to increase the peeling rate, resulting in a decrease in production efficiency. In this study, a prediction model for weight loss rate of chestnut by stage of knife peeling process was developed as undergarment study to optimize conditions of the machine. 51 control conditions of the two-stage blade peeler used in the experiment were derived and repeated three times to obtain a total of 153 data. Machine learning(ML) models including artificial neural network (ANN) and random forest (RF) were implemented to predict the weight loss rate by chestnut peel stage (after 1st peeling, 2nd peeling, and after final discharge). The performance of the models were evaluated by calculating the values of coefficient of determination (R), normalized root mean square error (nRMSE), and mean absolute error (MAE). After all peeling stages, RF model have better prediction accuracy with higher R values and low prediction error with lower nRMSE and MAE values, compared to ANN model. The final selected RF prediction model showed excellent performance with insignificant error between the experimental and predicted values. As a result, the proposed model can be useful to set optimum condition of knife peeling for the purpose of minimizing the weight loss of domestic chestnut flesh with maximizing peeling rate.