From 2020, Korean Animal and Plant Quarantine Agency has reset the withdrawal time (WT) for veterinary drugs typically used in livestock in preparation for the introduction of positive list system (PLS) program in 2024. This study was conducted to reset the MRL for amprolium (APL) in broiler chickens as a part of PLS program introduction. Forty-eight healthy Ross broiler chickens were orally administered with APL at the concentration of 60 mg/L (APL-1, n=24) for 14 days and 240 mg/L (APL-2, n=24) for 7 days through drinking water, respectively. After the drug treatment, tissue samples were collected from six broiler chickens at 0, 1, 3 and 5 days, respectively. Residual APL concentrations in poultry tissues were determined using LC-MS/MS. Correlation coefficient (0.99 >), the limits quantification (LOQ, 0.3~5.0 μg/kg), recoveries (81.5~112.4%), and coefficient of variations (<15.5%) were satisfied the validation criteria of Korean Ministry of Food and Drug Safety. In APL-1, APL in all tissues except for kidney was detected less than LOQ at 3 days after drug treatment. In APL-2, APL in liver and kidney was detected more than LOQ at 5 days after treatment. According to the European Medicines Agency’s guideline on determination of withdrawal periods, withdrawal periods of APL-1 and APL-2 in poultry tissues were established to 3 and 2 days, respectively. In conclusion, the developed analytical method is sensitive and reliable for detecting APL in poultry tissues. The estimated WT of APL in poultry tissues is longer than the current WT recommendation of 2 days for APL in broiler chickens.

In this study, we analyze a finite-buffer M/G/1 queueing model with randomized pushout space priority and nonpreemptive time priority. Space and time priority queueing models have been extensively studied to analyze the performance of communication systems serving different types of traffic simultaneously: one type is sensitive to packet delay, and the other is sensitive to packet loss. However, these models have limitations. Some models assume that packet transmission times follow exponential distributions, which is not always realistic. Other models use general distributions for packet transmission times, but their space priority rules are too rigid, making it difficult to fine-tune service performance for different types of traffic. Our proposed model addresses these limitations and is more suitable for analyzing communication systems that handle different types of traffic with general packet length distributions. For the proposed queueing model, we first derive the distribution of the number of packets in the system when the transmission of each packet is completed, and we then obtain packet loss probabilities and the expected number of packets for each type of traffic. We also present a numerical example to explore the effect of a system parameter, the pushout probability, on system performance for different packet transmission time distributions.

The cutting process, which is a key processing technology in various industrial fields is achieving continuous growth, and the demand for high-quality cutting surfaces is continuously demanded. Plasma cutting continues to be studied for its excellent workability and productivity, but problems with cutting surface quality such as dross formation occur, so research to secure excellent cutting surface quality through appropriate control of process variables is essential. In this study, we propose a method for predicting surface roughness using real-time current and cutting speed data obtained while performing plasma cutting on A106 B steel pipe. Surface roughness was predicted based on the RBF algorithm applicable to prediction and control models. It was shown that the surface roughness of the plasma cutting surface can be predicted with the arc current waveform and process speed data. This study can be used as a basic study to control the surface roughness of the cut surface in real time.

The entire industry is increasing the use of big data analysis using artificial intelligence technology due to the Fourth Industrial Revolution. The value of big data is increasing, and the same is true of the production technology. However, small and medium -sized manufacturers with small size are difficult to use for work due to lack of data management ability, and it is difficult to enter smart factories. Therefore, to help small and medium -sized manufacturing companies use big data, we will predict the gross production time through machine learning. In previous studies, machine learning was conducted as a time and quantity factor for production, and the excellence of the ExtraTree Algorithm was confirmed by predicting gross product time. In this study, the worker's proficiency factors were added to the time and quantity factors necessary for production, and the prediction rate of LightGBM Algorithm knowing was the highest. The results of the study will help to enhance the company's competitiveness and enhance the competitiveness of the company by identifying the possibility of data utilization of the MES system and supporting systematic production schedule management.

원전 구조물의 실시간 모니터링 기술이 요구되고 있지만, 현재 운영 중인 지진 감시계통으로는 동특성 추출 등 시스템 식별이 제한 된다. 전역적인 거동 데이터 및 동특성 추출을 위해서는 다수의 센서를 최적 배치하여야 한다. 최적 센서배치 연구는 많이 진행되어 왔 지만 주로 토목, 기계 구조물이 대상이었으며 원전 구조물 대상으로 수행된 연구는 없었다. 원전 구조물은 미미한 신호대잡음비에도 강건한 신호를 획득하여야 하며, 모드 기여도가 저차 모드에 집중되어 있어 모드별 잡음 영향을 고려해야 하는 등 구조물 특성을 고려 해야 한다. 이에 본 연구에서는 잡음에 대한 강건도와 모드별 영향을 평가할 수 있는 최적 센서배치 방법론을 제시하였다. 활용한 지표 로서 auto MAC(Modal Assurance Criterion), cross MAC, 노드별 모드형상 분포를 분석하였으며, 잡음에 대한 강건도 평가의 적합성을 수치해석으로 검증하였다.

We used the measurement data derived from a proton transfer reaction time-offlight mass spectrometry (PTR-ToF-MS) to ascertain the source profile of volatile organic compounds (VOCs) from 4 major industrial classifications which showed the highest emissions from a total of 26 industrial classifications of A industrial complex. Methanol (MOH) was indicated as the highest VOC in the industrial classification of fabricated metal manufacture, and it was followed by dichloromethane (DM), ethanol (EN) and acetaldehyde (AAE). In the industrial classification of printing and recording media, the emission of ethylacetate (EA) and toluene (TOL) were the highest, and were followed by acetone (ACT), ethanol (EN) and acetic acid (AA). TOL, MOH, 2-butanol (MEK) and AAE were measured at high concentrations in the classification of rubber and plastic manufacture. In the classification of sewage, wastewater and manure treatment, TOL was the highest, and it was followed by MOH, H2S, and ethylbenzene (EBZ). In future studies, the source profiles for various industrial classifications which can provide scientific evidence must be completed, and then specified mitigation plans of VOCs for each industrial classification should be established.

This paper is proposing a novel machine scheduling model for the unrelated parallel machine scheduling problem without setup times to minimize the total completion time, also known as “makespan”. This problem is a NP-complete problem, and to date, most approaches for real-life situations are based on the operator’s experience or simple heuristics. The new model based on the Memetic Algorithm, which was proposed by P. Moscato in 1989, is a hybrid algorithm that includes genetic algorithm and local search optimization. The new model is tested on randomly generated datasets, and is compared to optimal solution, and four scheduling models; three rule-based heuristic algorithms, and a genetic algorithm based scheduling model from literature; the test results show that the new model performed better than scheduling models from literature.

생산적인 인문학기반 융합연구를 위해서는 방법론에 관한 고찰이 필요하다. 본고의 목적은 현상학과 인지 과학의 융합연구라는 맥락 안에서 이러한 방법론의 사례를 소개하고 평가하는 것이다. 본고는 에드문트 후설의 시간의식 현상학을 신경과학 연구에 선행적재하는 프란시스코 바렐라의 신경현상학 연구를 소개 하고, 이러한 방법론의 의의와 한계, 그리고 인문학기반 융합연구에 대한 시사점을 평가한다. 바렐라의 연구는 현상학의 현재장 분석, 즉 파지-근원인상-예지 구조를 동역학 이론을 매개로 뇌 활동이라는 생물 학적 기반과 연결한다. 이에 따르면 뇌 활동은 기초 규모, 통합 규모, 서사 규모라는 시간성의 세 규모에서 일어나는데, 특히 통합 규모가 현재장에 상응한다. 이러한 연구의 의의는 시간의식을 설명하는 매개를 제공한다는 점, 그리고 의식의 ‘어려운 문제’와 관련하여 ‘설명 간극’에 다리를 놓는다는 점이다. 그러나 이 연구의 한계는 ‘의식의 시간’을 가지고 ‘시간의 의식’을 설명하는 오류를 범한다는 점, 그리고 체험과 신경과정 사이의 동형성 이상을 제공하기 어렵다는 점이다. 나아가 이 연구가 인문학기반 융합연구에 대해 시사하는 점은 인문학이 자신의 고유한 이념과 방법론을 유지해야 한다는 점, 그리고 인문학이 과학 의 이론적 토대로서 기여할 수 있다는 점이다.

It is essential to determine a proper earthquake time history as a seismic load in a seismic design for a critical structure. In the code, a seismic load should satisfy a design response spectrum and include the characteristic of a target fault. The characteristic of a fault can be represented by a definition of a type of possible earthquake time history shape that occurred in a target fault. In this paper, the pseudo-basis function is proposed to be used to construct a specific type of earthquake, including the characteristic of a target fault. The pseudo-basis function is derived from analyzing the earthquake time history of specific fault harmonic wavelet transform. To show the feasibility of this method, the proposed method was applied to the faults causing the Gyeong-Ju ML5.8 and Pohang ML5.3 earthquakes.

최근 기후변화로 가뭄, 홍수 등 재해의 빈도와 강도가 높아지고 있다. 이러한 재해의 피해를 줄이기 위해서는 시공간적 현황 파악을 통한 대비가 필요하다. 본 연구에서는 가뭄의 피해를 최소화하고자 지역별 밭작물의 필요수량과 공급량을 고려하여 밭가뭄 지역 등급화 실시하였고, 월별 비교를 통해 가뭄 취약 시기를 파악하였다. 전국 148개 지역 중 안전지역(Ⅰ), 안전지역(Ⅱ), 우려지역, 상습지역으로 구분한 25개 지역을 선정하였으며, 이 지역의 월별 필요수량 대비 공급량 분석을 하였다. 필요수량 산정의 재배작물은 콩으로 선정하였으며, 공급량은 공공관정, 민간관정, 상수도 자료를 분석하였다. 필요수량 대비 공급량이 봄철은 안전지역(Ⅰ), 안전지역(Ⅱ), 우려지역, 상습지역에서 각 1,281.5%, 667.6%, 729.5%, 316.3%, 가을철에는 각 436.0%, 212.8%, 213.9%, 105.3%로 공급이 충분할 것으로 분석되었으나 여름철에는 각 82.4%, 40.6%, 42.6%, 20.0%로 용수공급 이 부족한 것으로 분석되었다. 콩의 재배 기간인 5~9월에 관정(공공+민간)으로의 공급량은 대부분 지역에서 부족한 것으로 분석되었다. 이러한 분석을 통해 용수 부족이 발생하는 재배기간 동안 용수확보 방안이 필요하다.

영남 평야지에서는 추석전 햅쌀 출하를 목적으로 조기재배나 극조기재배가 증가하고 있는 추세이다. 그러나 극조기 벼 수확 이후에 후작물로 적합한 작목이 없어서 휴경을 하는 농가가 많아 적합한 작부체계 개발을 위한 재배법 개발이 필요한 실정이다. 따라서 본 시험은 극조기 벼 수확 후 이모작 작부체계에 적합한 벼 품종 및 재배시기 설정을 위해 수행하였다. 조생종 14개 품종을 4월 7일, 4월 14일, 4월 21일, 4월 28일에 각각 이앙하였을 때, 극조기 벼 이모작을 위한 기준 출수기인 7월 10일 이전에 출수가능한 품종은 백일미, 주남조생, 중모1032, 진옥이었다. 이 품종들의 적산온도로 추정한 적정 이앙시기는 4월 10일에서 4월 20일 사이로, 이 시기에 이앙할 경우 8월 20일 이내에 수확이 가능하여 8월 하순 후작물과의 작기연결성에 유리한 적합 품종으로 판단된다.

PURPOSES : The purposes of this study are to identify appropriate numbers of drivers for different time periods by analyzing the service times of the Special Transportation System and to shorten the waiting time to within 15 minutes. METHODS : In this study, the service time is divided into the call connection time (At), dispatch time after reception (Bt), vehicle arrival time after dispatch (Ct), and vehicle boarding time (Dt), and the annual average value for each time zone is calculated by analyzing the dispatch system database. Furthermore, the number of drivers working in each time period is extracted and the appropriate number of drivers for ensuring the dispatch waiting time remains within 15 minutes is determined. RESULTS : It is more accurate to interpret the decrease in dispatches during lunchtime as a decrease in the number of operational vehicles owing to the drivers' lunchtimes rather than a decrease in demand. During lunchtime (as in previous studies) the number of operations decreases, but the average dispatch time (Bt) greatly increases to 22:42; thus, it cannot be seen as a decrease in dispatch demand. The number of operations during lunchtime is proportional to the number of drivers on duty. The number of drivers on duty is inversely proportional to the average dispatch time. If the number of drivers is increased by 11.6%, the average waiting time can be reduced to within 15 minutes. CONCLUSIONS : To resolve delayed call connection issues, we will introduce an artificial intelligence (AI) call center. During the hours of 7 PM to 6 AM, calls will mainly be handled by AI and the counseling personnel will switch to daytime work. We will also increase the number of drivers by 11.6% to ensure that the dispatch time does not exceed an average of 15 minutes after receiving a call. In particular, we will generate the work schedule such that more than 131 drivers work in the 12:00 to 13:00 hours during lunch time to improve the situation where users have to wait for a long time. To do this, we will overlap the work hours for 2 hours in Jeonju and 1 hour in other cities and counties. We have to increase the number of night shift workers from seven to 15 so that all cities and counties can operate vehicles 24 hours a day, 365 days a year.