This study developed and tested a pilot-scale biowindow for simultaneous removal of odor and methane from landfills. The test was conducted in a sanitary landfill site during the summer season (July and August). The average temperature inside the biowindow was 5°C higher than the average air temperature, rising to 37–48oC when the outdoor temperature was very hot. The complex odor removal rate (based on the dilution-to-threshold value) in the biowindow during the summer was 91.3- 98.8% (with an average of 96.2±4.2%). The average concentration of hydrogen sulfide was 3,024.9±805.8 ppb, and its concentration was found to be the highest among 22 odorous compounds. The removal efficiencies of hydrogen sulfide and methyl mercaptan were 89.1% and 83.2%, respectively. The removal of dimethyl sulfide was 17.7%, and no ammonia removal was observed. Additionally, the removal efficiencies of toluene and xylene were 85.2% and 72.5%, respectively. Although the initial methane removal was low (24.9%), the methane removal performance improved to 53.7–75.6% after the 11th day of operation. These results demonstrate that the odor and methane removal performance of the pilot-scale biowindow was relatively stable even when the internal temperature of the biowindow rose above 40oC in the summer. Since the main microorganisms responsible for decomposing odor and methane are replaced by thermotolerant or thermophilic microorganisms, and high community diversity is maintained, odor and methane in the biowindow could be stably removed even under high-temperature conditions.

The objective of this study is to identify the priority of elements for effective implementation of MES in small and medium-sized manufacturing enterprises trying to develop into smart factories. For this purpose, the Delphi method and the Analytic Hierarchy Process(AHP) mothod are applied. As a result of the study, the cooperation of the members in the supply chain is the most important factor for small and medium-sized enterprises in order to survive in the global competitive environment. Therefore, the enterprises need to make various efforts to create synergies through the technical strength of suppliers and the cooperation in the process of introducing and operating MES.

PURPOSES : This study analyzes the accident damage scale of hazardous material transportation vehicles not monitored in real time by the Hazardous Material Transportation Safety (HMTS) management center. METHODS : To simulate hazardous-material transportation vehicle accidents, a preliminary analysis of transportation vehicle registration status was conducted. Simulation analyses were conducted for hazardous substance and flammable gas transportation vehicles with a high proportion of small- and medium-sized vehicles. To perform a spill accident damage-scale simulation of hazardous-substance transportation vehicles, the fluid analysis software ANSYS Fluent was used. Additionally, to analyze explosion accidents in combustible gas transportation vehicles, the risk assessment software Phast and Aloha were utilized. RESULT : Simulation analysis of hazardous material transportation vehicles revealed varying damage scales based on vehicle capacity. Simulation analysis of spillage accidents showed that the first arrival time at the side gutter was similar for various vehicle capacities. However, the results of the cumulative pollution analysis based on vehicle capacity exhibited some differences. In addition, the simulation analysis of the explosion overpressure and radiant heat intensity of the combustible gas transportation vehicle showed that the difference in the danger radius owing to the difference in vehicle capacity was insignificant. CONCLUSIONS : The simulation analysis of hazardous-material transportation vehicles indicated that accidents involving small- and medium-sized transportation vehicles could result in substantial damage to humans and ecosystems. For safety management of these small and medium-sized hazardous material transportation vehicles, it is expected that damage can be minimized with the help of rapid accident response through real-time vehicle control operated by the existing HMTS management center.

This study introduces and experimentally validates a novel approach that combines Instruction fine-tuning and Low-Rank Adaptation (LoRA) fine-tuning to optimize the performance of Large Language Models (LLMs). These models have become revolutionary tools in natural language processing, showing remarkable performance across diverse application areas. However, optimizing their performance for specific domains necessitates fine-tuning of the base models (FMs), which is often limited by challenges such as data complexity and resource costs. The proposed approach aims to overcome these limitations by enhancing the performance of LLMs, particularly in the analysis precision and efficiency of national Research and Development (R&D) data. The study provides theoretical foundations and technical implementations of Instruction fine-tuning and LoRA fine-tuning. Through rigorous experimental validation, it is demonstrated that the proposed method significantly improves the precision and efficiency of data analysis, outperforming traditional fine-tuning methods. This enhancement is not only beneficial for national R&D data but also suggests potential applicability in various other data-centric domains, such as medical data analysis, financial forecasting, and educational assessments. The findings highlight the method's broad utility and significant contribution to advancing data analysis techniques in specialized knowledge domains, offering new possibilities for leveraging LLMs in complex and resource- intensive tasks. This research underscores the transformative potential of combining Instruction fine-tuning with LoRA fine-tuning to achieve superior performance in diverse applications, paving the way for more efficient and effective utilization of LLMs in both academic and industrial settings.

There are growing concerns that the recently implemented Earthquake Early Warning service is overestimating the rapidly provided earthquake magnitudes (M). As a result, the predicted damages unnecessarily activate earthquake protection systems for critical facilities and lifeline infrastructures that are far away. This study is conducted to improve the estimation accuracy of M by incorporating the observed S-wave seismograms in the near source region after removing the site effects of the seismograms in real time by filtering in the time domain. The ensemble of horizontal S-wave spectra from at least five seismograms without site effects is calculated and normalized to a hypocentric target distance (21.54 km) by using the distance attenuation model of Q(f)=348f0.52 and a cross-over distance of 50 km. The natural logarithmic mean of the S-wave ensemble spectra is then fitted to Brune’s source spectrum to obtain the best estimates for M and stress drop (SD) with the fitting weight of 1/standard deviation. The proposed methodology was tested on the 18 recent inland earthquakes in South Korea, and the condition of at least five records for the near-source region is sufficiently fulfilled at an epicentral distance of 30 km. The natural logarithmic standard deviation of the observed S-wave spectra of the ensemble was calculated to be 0.53 using records near the source for 1~10 Hz, compared to 0.42 using whole records. The result shows that the root-mean-square error of M and ln(SD) is approximately 0.17 and 0.6, respectively. This accuracy can provide a confidence interval of 0.4~2.3 of Peak Ground Acceleration values in the distant range.

The purpose of this study intends to development of a lap scale 1-ton standard combustion chamber. The manufactured standard combustion chamber analyzes pilot combustion tests and emission standard data of MGO fuel oil. The actual capacity of the standard combustion chamber is about 900L, total weight of 265kg. As a result of the pilot combustion test, the O2 was about 8.01% and the CO2 was about 9.34%. In the case of NOx, it was about 33.50 ppm, and SOx (SO2) was about 0.76ppm. The combustion efficiency was about 72.41%, the exhaust gas temperature was 366.7℃, and the combustion chamber internal temperature was about 448.0℃.

본 연구는 2020년 10월 중 충청남도내 단체 급식소에서 발생한 대규모 집단 식중독 원인에 대하여 분석하였다. 전 체 급식원 135명 중 21명(15.6%)에서 음식을 섭취한 후 1 시간 이내에 주로 매스꺼움과 구토 증상을 보였다. 유증 상자 21명 중 11명과, 조리종사자 1명, 조리기구 2건과 보 존식 8건에서 B. cereus가 검출됨에 따라 B. cereus에 의 한 집단 식중독으로 판단하였다. 분리된 21개의 균주를 PFGE 분석한 결과, 19개의 균주가 동일한 것으로 판단되 었고, 이들 균주가 가지고 있는 독소 유전자는 CER, nheA, entFM이었다. 실험결과, CER을 포함하고, 증상 발현 시간 이 1시간 이내로 매우 짧아 B. cereus의 구토형 식중독으 로 판단하였다. 집단식중독 원인으로 안전하지 않은 급식 환경과 제대로 관리되지 않은 음식에 의한 것이라 조사되 었다. 이러한 결과는 단체급식에서의 급식환경과 제공되 는 음식이 철저하게 관리되어야 한다는 것을 보여준다. 이 와 더불어 보존식에서 원인 병원체를 찾아내는 것은 식중 독의 원인을 추정하는데 매우 중요하므로, 집단급식소에 서 규정에 맞는 보존식 용기를 이용하여 이를 적정온도에 잘 보관해야한다. 또한 정밀한 식중독 역학조사를 기반으 로 사례를 분석하고 결과를 전파함으로써 유사한 식중독 이 재발하지 않도록 해야 한다.

Recently, ESG management has become a global trend, receiving increasing attention from stakeholders such as consumers, investors, and governments, as regulations related to ESG disclosure and supply chain due diligence have been strengthened since the United Nations Principles of Responsible Investment (UN PRI) was announced in 2006. ESG is an acronym for the environment (E), social (S), and governance (G) and is accepted as a key factor for the continuous survival and growth of a company. As a result, there are over 600 ESG management evaluation indicators operated domestically and internationally, and numerous global initiatives have emerged. Korea’s Ministry of Trade, Industry and Energy also announced “K-ESG Guidelines (December 2011)” and “K-ESG Guidelines for Supply Chain Response (December 22)” to help SMEs introduce ESG management and respond to supply chain due diligence. However, small-scale manufacturing companies with poor financial, human resources, and technological capabilities face significant challenges in introducing ESG management. Accordingly, this study aims to examine the current status of ESG management adoption in small-scale manufacturing companies with less than 150 people in Korea and propose activation plan ESG management based on the diagnostic requirements of the “Supply Chain Response K-ESG Guidelines.”

본 연구는 지역 문화예술공연장 규모에 따른 서비스품질과 관람만족의 차이 분 석, 그리고 서비스품질과 관람만족의 관계를 규명하고자 진행되었다. 이를 위해 공연장 서비스품질(유형성, 신뢰성, 응답성, 확신성, 공감성)에 대한 공연장 규모 별 차이, 그리고 관람만족에 영향을 미치는 공연장 서비스품질 요인을 파악하고자 설문조사를 통하여 연구가설을 설정한 후 진행하였다. 연구지역은 광주광역시와 전라남도 소재에 있는 문화예술공연장(소극장, 중극장, 대극장)을 찾아온 관람객 을 대상으로 불성실한 답변을 제외한 총 313부를 유효 표본으로 활용하였다. 분석 결과, 첫째, 공연장 규모에 따른 서비스품질 차이분석 결과 응답성, 확신성, 공감 성에서 소극장이 차이를 보이고 있었다. 둘째, 공연장 규모에 따른 관람만족 차이 분석 결과 소극장에서 관람만족이 가장 높은 것으로 나타났다. 셋째, 공연장 서비 스품질의 공감성, 유형성, 응답성, 확신성은 관람만족에 긍정적 영향을 미치는 것 으로 나타났다. 본 연구 결과는 지역의 문화예술공연장 규모에 따른 서비스품질 중요요인을 추출했다는 점에서 학술적, 현장적 의미가 있다고 할 수 있다.

Wastewater management is increasingly emphasizing economic and environmental sustainability. Traditional methods in sewage treatment plants have significant implications for the environment and the economy due to power and chemical consumption, and sludge generation. To address these challenges, a study was conducted to develop the Intermittent Cycle Extended Aeration System (ICEAS). This approach was implemented as the primary technique in a full-scale wastewater treatment facility, utilizing key operational factors within the standard Sequencing Batch Reactor (SBR) process. The optimal operational approach, identified in this study, was put into practice at the research facility from January 2020 to December 2022. By implementing management strategies within the biological reactor, it was shown that maintaining and reducing chemical quantities, sludge generation, power consumption, and related costs could yield economic benefits. Moreover, adapting operations to influent characteristics and seasonal conditions allowed for efficient blower operation, reducing unnecessary electricity consumption and ensuring proper dissolved oxygen levels. Despite annual increases in influent flow rate and concentration, this study demonstrated the ability to maintain and reduce sludge production, electricity consumption, and chemical usage. Additionally, systematic responses to emergencies and abnormal situations significantly contributed to economic, technical, and environmental benefits.

In this study, the performances of H2S, NH3, and HCl sensors for real-time monitoring in small emission facilities (4, 5 grades in Korea) were evaluated at high concentration conditions of those gases. And the proper approach for the collection of reliable measurement data by sensors was suggested through finding out the effect on sensor performances according to changes in temperature and humidity (relative humidity, RH) settings. In addition, an assessment on sensor data correction considering the effects produced by environmental settings was conducted. The effects were tested in four different conditions of temperature and humidity. The sensor performances (reproducibility, precision, lower detection limit (LDL), and linearity) were good for all three sensors. The intercept (ADC0) values for all three sensors were good for the changes of temperature and humidity conditions. The variation in the slope value of the NH3 sensor showed the highest value, and this was followed by the HCl, H2S sensors. The results of this study can be helpful for data collection by enabling the more reliable and precise measurements of concentrations measured by sensors.

Membrane bioreactor (MBR) provides the benefits on high effluent quality and construction cost without the secondary clarification. Despite of these advantages, fouling, which clogs the pore in membrane modules, affects the membrane life span and effluent quality. Studies on the laboratory scale MBR were focused on the control of particulate fouling, organic fouling and inorganic fouling. However, less studies were focused on the control of biofouling and microbial aspect of membrane. In the full scale operation, most MBR produces high effluent quality to meet the national permit of discharge regulation. In this study, the performance and microbial community analysis were investigated in two MBRs. As the results, the performance of organic removal, nitrogen removal, and phosphorus removal was similar both MBRs. Microbial community analysis, however, showed that Azonexus sp. and Propionivibrio sp. contributed to indirect fouling to cause the chemical cleaning in the DX MBR.

This study attempted to provide implications by analyzing the impact of business Owner’s safety commitment on industrial accidents and examining the mediating role of management supervisors’ safety leadership and worker participation. Analysis was conducted on 2,067 manufacturing sites with 20 to 50 employees in the 10th Occupational Safety and Health Survey data. SPSS waw used to secure the reliability of the measurement variable. Hypothesis vertification was carried out after securing the suitability and validity of the structural model using AMOS. The direct impact of three latent variables on industrial accidents was confirmed: the business owner’s safety commitment, the management supervisor’s safety leadership, and the worker participation. The employer’s safety will and the management supervisor’s safety leadership do not directly affect industial accidents, but it has been verified that worker participation has a diret impact on industrial accident reduction. In addition, it has been confirmed that the safety leadership and worker participation of the management. Supervior have a complete mediating effect on the reduction of industrial accidents by mediating with the safety leadership of the management supervior and the participation of the workers. This study analyzed the impact on industrial accidents by dividing the stakeholders constituting the workplace into three classes: business owners, superviors, and workers, but the results suggest that employers and all workers inside the workplace may be organically linked to achieving the goal of reducing industrial accidents. Therefore, in order to establish an autonomous safety management system for safety and health at workerplaces, efforts are needed to reduce industrial accidents in their respective location by forming an organic community among internal stakeholders.

최근 노인 인구가 증가함에 따라, 이들의 삶의 질에 대한 사회적 관심도가 높아지고 있으며, 노인들의 건강하고 활기찬 노후를 고려하는 활동적 노후 및 고령친화도시의 개념이 주목받고 있다. 이러한 상황에서 많은 지자체는 노인들이 지역 사회에서 여생을 의미 있게 보낼 수 있도록 다양한 노인여가복지 서비스를 제공하기 위해 노력하고 있다. 그러나 실질적인 노인 수요에 부합하는 서비스 공급이 이루어지지 못하고 있으며, 지역별로 노인여가복지 서비스의 공간적 격차가 발생하고 있는 실정이다. 이는 노인여가복지 입지와 관련하여 체계적인 법적 기준이 부재하기 때문이다. 이에 본 연구는 서울시의 노인여가복지 시설에 대한 수요와 공급의 공간적 불일치성을 탐색하고, 공간 효율성과 형평성을 고려한 노인복지센터의 최적 입지 대안을 제시하고 있다. 연구 결과, 여러 입지 시나리오에 따라 서울시 노인복지센터의 공간적 접근성을 향상시킬 수 있는 다양한 최적 입지 대안들을 제시할 수 있었으며, 향후 노인복지 서비스 공급과 관련한 계획 및 정책에 있어 중요한 기초 자료로 활용될 수 있을 것으로 기대된다

The economy of Tanzania relies on agriculture as the main economic activity, because agriculture provides both food and income to the population of the country, especially the rural households. Improvement of market access to crops also increases the productivity. Therefore, in this study, descriptive statistics and statistical analysis of the probit model were used to analyze the factors that determine the market accessibility of small-scale farmers in Chemba, Tanzania. Cross-sectional data collected by the systematic sampling method for 200 corn peasants in Chemba, Tanzania were used. As a result of probit regression analysis, it was found that access to improved seeds and technology had a positive statistically significant effect on the accessibility to the market, while the age of the head of the household, production cost, distance to the market, and household size had a negative statistically significant effect. Therefore, in this study, policy establishment and implementation are recommended. A policy needs to be considered to reduce the transaction costs that eventually allows the farmers to increase the accessibility to markets, enables small-scale farmers to participate in cooperatives, lowers input costs and provides educational programs on quality products to increase their competitiveness in the marketplace.

본 논문에서는 대규모 실시간 매칭의 생존 게임에서 플레이를 위한 유저들의 소셜 관계에 대해 연구한다. 특 히 “사전 팀 구성”을 통한 자의적인 팀 구성이 어떤 방식으로 유저들을 연결하는 지 연구하고자 한다. 다수 의 사람 간 집단 역학에서 나타나는 특성이나 패턴에 대한 조사를 중심으로 하였으며, 개인의 특성은 보조적 인 수단으로만 사용된다. 이번 연구에서는 게임을 플레이하는 유저들의 익명화 된 대규모 데이터를 활용하며 이에 대한 간소화된 집계 방법을 제안한다. 데이터 세트에는 사전 팀 구성에 관한 11,259만 줄의 속성이 포 함되어 있으며, 데이터에서 우리는 250만개의 노드와 1,182만개의 무방향 에지가 있는 협업 네트워크를 구성 하여 대규모 게임 내 협동 네트워크를 만듭니다. 연결 정도, 경로 길이, 클러스터링 및 소속 하위 컴포넌트의 크기 등 네트워크에 관한 수치를 통해 게임내 소셜 활동에 대한 이해를 높이고자 한다. 본 논문에서는 다음 의 두가지 특성을 중심으로 결론을 제시한다. 첫째, 네트워크 내에는 대규모로 연결된 2개(전체의 44% 및 2%)와 나머지의 파편화된 하위 컴포넌트로 구성 되어있다. 이 대규모 컴포넌트 중 작은 쪽은 한국 유저로만 구성되어 있다. 둘째, 컴포넌트 크기 별 평균 연결 거리와 군집화 계수, k-core를 확인함으로써 기타 다른 네 트워크 대비 이웃 간 연결이 강하면서 전체적으로는 비교적 멀리 떨어져 있음을 확인한다.