전 세계적으로 급격하게 성장하는 스마트농업의 중요 요소 중 하나인 자동 관개시스템은 토양수분 센서에서 계측한 데이터를 기반으로 관개시점과 관개량을 판단하기 때문에 토양수분 센서의 설치가 필수적이다. 하지만 국내의 경우 토양을 고려하지 않고 단순히 포장의 가운데에 센서를 설치하는 등 토양수분 센서의 설치 위치에 대한 기준이 마련되어 있지 않아 토양수분 계측 위치에 관한 기준 검토가 필요하다. 본 연구에서 통계학적 방법을 이용하여 토양수분의 대표 계측지점을 선정 연구를 수행하였다. 토양은 수직적 또는 수평적으로 불균일성을 갖기에 구명이 쉽지 않다. 따라서 포장 전체에 걸쳐 지속해서 편향이 발생하지만 특정 위치에서의 평균 토양수분이 시간에 따라 유지한다는 시간 안정성 개념을 기반으로, 평균 토양수분을 나타내는 대표지점 선정 연구를 수행하였다. 토양수분을 측정하기 위한 시스템을 제작하였고, TDR (Time Domain Reflectometry) 센서를 이용하여 총 30개 지점을 측정하였다. 2023년 5월부터 8월까지 측정한 날짜·지점별 데이터를 이용하여, 지점의 편향을 정량화하여 식별할 수 있는 MRD (Mean Relative Difference, 평균상대차이)와 측정의 정밀도를 나타내는 RD (Relative Difference, 상대차이)의 SDRD (Standard Deviation of Relative Difference, 표준편차)를 산출하고, MRD와 SDRD를 통합한 지표로써 RMSE (Root Mean Square Error, 평균제곱근오차) 를 구하여, 시간 안정성이 가장 높은 지점인 RMSE의 수치가 최소인 지점을 대표지점으로 선정하였다. 토양수분 센서로 측정한 데이터를 사용하여 지점별 RMSE를 산출하고 비교하여, 평균적인 토양수분을 나타내는 대표지점을 선정할 수 있음을 확인하였다.

국내 중·저준위 방사성폐기물은 영구적 격리를 위해 처분장에 매립하고 있으며 그 위치는 경주에 있다. 이러한 방 사성폐기물의 영구적인 격리를 위한 처분시설은 공학적 방벽과 자연 방벽으로 구성되어 있으며 자연 방벽을 특성을 파악 하기 위하여 한국원자력환경공단에서는 2006년부터 부지특성조사를 수행하였고, 이후 부지감시 및 조사계획에 따른 감시 를 수행하여 부지특성의 변화를 지속적으로 확인하고 있다. 중저준위 방폐장의 수리지화학적 환경은 자연 방벽의 평가를 위해 중요한 요소로 손꼽히고 있으나 동해와 가까운 경주의 지역적 특성상 해수의 영향을 반드시 고려해야 한다. 따라서 본 연구에서는 처분 부지의 지하수 관정 7개 및 관정의 심도별 수질 자료를 취합해 지하수 자료 총 30개를 해수 2개소와 비교 분석하여 수리지화학적 환경을 해석하였다. 분석 자료는 수질 10개 항목(온도, EC, HCO3, Na, K, Ca, Mg, Cl, SO4, SiO2)을 2017년 3분기부터 2022년 3분기까지 총 5년간 20회의 자료를 활용하였다. 특히, EC, HCO3, Na, Cl의 농도 변화 를 통해 연구 지역의 배경 농도 및 관정의 구간별 해수의 영향을 파악하였으며, 시계열 군집 분석을 통해 담수, 기수, 해 수의 분류를 시도하였다. 그 결과, 기존의 모니터링 방법으로는 확인하지 못한 부지내 수리지화학적 변화를 제시하였다.

PURPOSES : The purpose of this study is to statistically analyze the meteorological factors that contribute to the formation of road surface icing based on actual cases of icing accidents and provide directions for improving icing evaluation criteria. METHODS : In this study, we collected cases of domestic road icing accidents by searching news articles with the keyword ‘icing collision accidents’. Subsequently, we determined the latitude, longitude, and altitude of accident locations using satellite map service. We applied the Inverse Distance Weighting (IDW) method and temperature lapse rate to estimate meteorological data at each location. Finally, statistical analysis was conducted for temperature, humidity, and precipitation occurrence using probability density functions. RESULTS : As a result, road icing accident data points with identifiable location coordinates were collected. Among these, temperature, humidity, and precipitation occurrence from Automated Weather Stations (AWS) data were selected for analysis. During the process of correcting meteorological factors using the Inverse Distance Weighting (IDW) method, the optimal Weighting Exponent (p) that minimizes the error was determined and applied. The results showed that accidents occurring in the morning indicated the highest accident occurrence rate. The average temperature at the time of the accidents was -1.4°C, with a humidity level of 85.1%. Precipitation was observed at the time of the accident in 19 cases. CONCLUSIONS : Icing on pavement can occur not only under extreme weather conditions but also under typical meteorological conditions. Typically, icing can occur when the relative humidity is above 70%. Accordingly, for future improvements in the evaluation criteria for icing-prone areas by the Ministry of Land, Infrastructure and Transport, it is possible to incorporate the temperature and humidity ranges that generally lead to icing, taking into account climate characteristics.

프로바이오틱스 제품에 대한 수요가 지속적으로 증가하 고 있으며, Lactobacillus 균주가 가장 대중적인 프로바이 오틱스로 널리 사용되고 있다. 프로바이오틱스는 기준에 적합한 균수의 확보가 중요하며 제조원가나 시간 등을 낮 추기 위해 배양법의 개발이 필요하므로 Lactobacillus 생 산을 위한 배양 조건이 최적화되었다. 반응표면방법론에 의한 통계적 최적화에서 반응 변수에 영향을 미치는 독립 변수의 최적 조건은 Lactobacillus acidophilus의 경우 22.55 시간(배양시간), 25oC(배양온도), 3.41%(프리바이오틱스 농 도); Lactiplantibacillus plantarum의 경우 24시간, 30.86oC, 2.00%; Lacticaseibacillus rhamnosus의 경우 66.67시간, 35oC, 3.41%이었다. Lactobacillus의 최적 배양조건은 예측 한 결과와 실제 결과가 밀접하게 일치하는 것을 확인하였 다. 이러한 데이터는 수율 높은 Lactobacillus를 생산하는 데 중요한 포인트를 제공할 것이다.

In light of recent social concerns related to issues such as water supply pipe deterioration leading to problems like leaks and degraded water quality, the significance of maintenance efforts to enhance water source quality and ensure a stable water supply has grown substantially. In this study, scan statistic was applied to analyze water quality complaints and water leakage accidents from 2015 to 2021 to present a reasonable method to identify areas requiring improvement in water management. SaTScan, a spatio-temporal statistical analysis program, and ArcGIS were used for spatial information analysis, and clusters with high relative risk (RR) were determined using the maximum log-likelihood ratio, relative risk, and Monte Carlo hypothesis test for I city, the target area. Specifically, in the case of water quality complaints, the analysis results were compared by distinguishing cases occurring before and after the onset of "red water." The period between 2015 and 2019 revealed that preceding the occurrence of red water, the leak cluster at location L2 posed a significantly higher risk (RR: 2.45) than other regions. As for water quality complaints, cluster C2 exhibited a notably elevated RR (RR: 2.21) and appeared concentrated in areas D and S, respectively. On the other hand, post-red water incidents of water quality complaints were predominantly concentrated in area S. The analysis found that the locations of complaint clusters were similar to those of red water incidents. Of these, cluster C7 exhibited a substantial RR of 4.58, signifying more than a twofold increase compared to pre-incident levels. A kernel density map analysis was performed using GIS to identify priority areas for waterworks management based on the central location of clusters and complaint cluster RR data.

기후변화 영향으로 이상고수온, 태풍, 홍수, 가뭄 등 재난 및 안전 관리기술은 지속적으로 고도화를 요구받고 있으며, 특히 해 수면 온도는 한반도 주변에서 발생되는 여름철 적조 발생과 동해안 냉수대 출현, 소멸 등에 영향을 신속하게 분석할 수 있는 중요한 인자 이다. 따라서, 본 연구에서는 해수면 온도 자료를 해양 이상현상 및 연구에 적극 활용되기 위해 통계적 방법과 딥러닝 알고리즘을 적용하 여 예측성능을 평가하였다. 예측에 사용된 해수면 수온자료는 흑산도 조위관측소의 2018년부터 2022년까지 자료이며, 기존 통계적 ARIMA 방법과 Long Short-Term Memory(LSTM), Gated Recurrent Unit(GRU)을 사용하였고, LSTM의 성능을 더욱 향상할 수 있는 Sequence-to-Sequence(s2s) 구조에 Attention 기법을 추가한 Attention Long Short-Term Memory (LSTM)기법을 사용하여 예측 성능 평가를 진행하 였다. 평가 결과 Attention LSTM 모델이 타 모델과 비교하여 더 좋은 성능을 보였으며, Hyper parameter 튜닝을 통해 해수면 수온 성능을 개 선할 수 있었다.

In recent years, an array of studies has focused on ‘translationese’ (i.e., unique features that manifest in translated texts, causing second language (L2) writings to be similar to translated texts but different from native language (L1) writings). This intriguing linguistic pattern has motivated scholars to investigate potential markers for predicting the divergence of L1 and L2 texts. This study builds on this work, evaluating the feature importance ranking of specific translationese markers, including standardized type-token ratio (STTR), mean sentence length, bottom-frequency words, connectives, and n-grams. A random forest model was used to compare these markers in L1 and L2 academic journal article abstracts, providing a robust quantitative analysis. We further examined the consistency of these markers across different academic disciplines. Our results indicate that bottom-frequency words are the most reliable markers across disciplines, whereas connectives show the least consistency. Interestingly, we identified three-word lexical bundles as discipline-specific markers. These findings present several implications and open new avenues for future research into translationese in L2 writing.

새만금호는 우리나라 최대의 인공호수로 호수의 수질은 갈수록 악화되어 가고 있어 호수의 특성에 맞는 새로운 수질관리 대 책이 필요하다. 이에 새만금호의 국가수질측정망 자료를 이용하여 통계분석 기법에 의한 새만금호의 시공간적 수질특성을 분석하였다. 수질항목간의 상관성에서 수온과 TP는 상관성이 있고, 염분과 TN, 그리고 pH와 COD가 상관성이 높았다. 그 외 항목들 간에는 낮은 상관 성을 나타내어 관련성이 낮았다. 주성분 분석을 이용한 새만금호의 공간적 수질특성을 보면, 크게 4개의 그룹으로 구분되었는데, 담수 영 향구역과 해수 영향구역, 해수와 담수가 혼합되는 중간 수역이 2개 그룹으로 구분되어 각각 다른 수질특성을 나타내었다. 주성분분석을 이용한 시간적 수질특성은 계절적으로 4가지 그룹으로 구분되었다. 그룹Ⅰ은 늦봄과 초여름에 해당되는 5, 6월이고, 그룹 Ⅱ는 계절적으 로 초봄(3, 4월)과 늦가을(11, 12월)에 해당되는 시기로 나타났으며, 그룹 Ⅲ은 낮은 수온에 의한 용존산소의 증가가 나타나는 계절인 겨울 철(1, 2월)의 수질 특성을 보였고, 그룹 Ⅳ는 하계(7, 8, 9, 10월) 성층의 발달로 저층 퇴적물의 높은 인농도와 하계 고수온의 상관성을 가지 는 그룹으로 구분되었다. 이는 새만금호가 인위적으로 조성된 호수로써 상류 만경강과 동진강의 유입 영향을 받는 것과 동시에 새만금 방조제에 설치된 가력과 신시갑문을 통한 외해수 유입의 영향을 받음으로써 수질의 변동요소가 달라진 것으로 평가된다. 새만금호의 목 표수질을 달성하기 위해서는 상류 유역의 오염원 관리 대책과 함께 새만금호의 수질관리 대책을 수립할 필요가 있다.

Mass production of high-quality carbon nanotubes (CNTs) remains a challenge, requiring the development of new wetimpregnated catalyst suitable for the catalytic chemical vapor deposition (CCVD) of CNTs in a fluidized bed reactor. For the successful development of a new catalyst, a highly robust system to synthesize CNTs must be established. Here, we systematically investigated the robustness of CNT synthesis by CCVD using a wet-impregnated catalyst. We statistically tested four factors that could potentially affect the robustness of CNT synthesis system, focusing on carbon yield and IG/ID. First, we tested the effect of vacuum baking before CNT growth. F test and CV equality test concluded that vacuum baking recipe did not significantly reduce the variability of the CNT synthesis. Second, we tested the batch-to-batch variation of catalysts. The results of t test and one-way analysis of variance indicate that there is significant difference in carbon yield and IG/ID among catalysts from different batches. Third, we confirmed that there is spatial non-uniformity of wet-impregnated catalysts within a batch when they are produced in large scale. Finally, we developed a multi-step heating recipe to mitigate the temperature overshooting during the CNT synthesis. The multi-step recipe increased the mean of carbon yield, but did not influence the variability of CNT synthesis. We believe that our research can contribute to the establishment of a robust CNT synthesis system and development of new wet-impregnated catalysts.

The homogeneity of radioactive spent ion exchange resins (IERs) distribution inside waste form is one of the important characteristics for acceptance of waste forms in long-term storage because heterogenous immobilization can lead to the poor structural stability of waste form. In this study, the homogeneity of metakaolin-based geopolymer waste form containing simulant IERs was evaluated using a laser-induced breakdown spectroscopy (LIBS) and statistical approach. The cation-anion mixed IERs (IRN150) were used to prepare the simulant spent IERs contaminated by non-radioactive Cs, Fe, Cr, Mn, Ni, Co, and Sr (0.44, 8.03, 6.22, 4.21, 4.66, 0.48, and 0.90 mg/g-dried IER, respectively). The K2SiO3 solution to metakaolin ratio was kept constant at 1.2 and spent IERs loading was 5wt%. For the synthesis of homogeneous geopolymer waste form, spent IERs were mixed with K2SiO3 solution and metakaolin first, and then the fresh mixture slurry was poured into plastic molds (diameter: 2.9 cm and height: 6.0 cm). The heterogeneous geopolymer waste form was also fabricated by stacking two kinds of mixtures (8wt% IERs loading in bottom and 2wt% in top) in one mold. Geopolymers were cured for 7d (1d at room temperature and 6d at 60°C). The hardened geopolymers were cut into top, middle, and bottom parts. The LIBS spectra and intensities for Cs were obtained from the top and bottom of each part. Cs was selected for target nuclide because of its good sensitivity for measurement. Shapiro-Wilk test was performed to determine the normality of LIBS data, and it revealed that data from the homogeneous sample is normal distribution (p-value = 0.9246, if p-value is higher than 0.05, it is considered as normal distribution). However, data from the heterogeneous sample showed abnormal distribution (p-value = 7.765×10-8). The coefficient of variation (CoV) was also calculated to examine the dispersion of data. It was 31.3% and 51.8% from homogeneous and heterogeneous samples, respectively. These results suggest that LIBS analysis and statistical approaches can be used to evaluate the homogeneity of waste forms for the acceptance criterion in repositories.

Background: Korea citation index (KCI) enhances the quality of journals by securing a management system for domestic journals and strengthening the international competitiveness of excellent domestic journals. Errors in studies, papers, and investigations of statistical methods have been reported worldwide in the medical field. However, there is a lack of studies on statistical methods and error investigations in physical therapy journals in Korea. Objectives: To investigated the frequency of statistical methods and research errors in physical therapy journal articles evaluated by KCI. Design: Review. Methods: Ten journals classified as physical therapy journals by December 2021, which are candidate journals or higher, were targeted. The study focused on original articles published from 2017 to 2021 and investigated the frequency of statistical methods used, sample size calculations, result tables, effect sizes, and confidence intervals. Results: Statistical methods used in physical therapy studies in Korean journals mainly employed group comparative analysis. However, in most cases, the basis for sampling, effect size, and confidence interval were not presented, even though most of the results tables were included. Conclusion: This study allowed us to examine the most frequently used statistical methods in Korean physical therapy studies and assess the reporting status of sample size calculations, result tables, effect sizes, and confidence intervals. Efforts are needed to publish high-quality papers to improve the quality of Korean physical therapy journals.

The purpose of this research is to investigate the statistical behavior of fatigue crack propagation(FCP) in magnesium alloy AZ31. FCP tests have been performed on compact specimens of AZ31 at load ratio conditions and maximum fatigue load conditions to obtain statistical data of FCP. It was found that the variability of fatigue crack propagation rate was significantly large at initial stage of FCP and gradually became smaller as the fatigue crack propagated. The finding of the study showed that increasing the load ratio could increase the variability of fatigue crack propagation rate at initial FCP stage. The samller the load ratio, the higher the fatigue crack propagation rate at initial stage. It was also found that the load ratio is a factor affecting the fatigue crack propagation rate in magnesium alloy.

We investigated the records of astronomical phenomena in the Hyeonjong-Donggung-Ilgi written by the educational office for a crown prince, Sigang-won, during the time of a crown prince of the king Hyeonjong (i.e., from 1649 to 1659). Of the total of 3,625 days, 3,044 astronomical accounts were compiled from astronomical records of 2,003 days. We classified these astronomical accounts into 16 items, grouped into five categories, and statistically analyzed each group. In our analysis, the accounts for atmospheric optical phenomena equates to 57.9% of the total, and for celestial phenomena visible during the daytime the percentage is 17.3%. The records related to the approach between two objects such as planets, moon, and stars account for 3.3%, and solar or lunar eclipses take up 0.6%. The ratio of accounts regarding meteor, comet, and fire light (火光) stand at 13.8%, 0.30%, and 6.8%, respectively. Sunny days account for 71.1% of all days per year during this period. We determined that the distribution of the fire light by month is similar to that of the solar halo. We also found that the astronomical records from the Annals of the Joseon Dynasty correspond to only 30% of those of the Hyeonjong-Donggung-Ilgi for the same period. In particular, the phenomena of celestial objects occurring outside the atmosphere are transmitted to the Annals of the Joseon Dynasty in a higher proportion than the phenomena inside the air. It is therefore necessary to use a historical diary like a Donggung-Ilgi to interpret the phenomena in the air such as atmospheric optical events, meteor, and fire light.

As the uncertainty of technology development and market needs increases due to changes in the global business environment, the interest and demand for R&D activities of individual companies are increasing. To respond to these environmental changes, technology commercialization players are paying great attention to enhancing the qualitative competitiveness of R&D. In particular, R&D companies in the marine and fishery sector face many difficulties compared to other industries. For example, the R&D environment is barren, it is challenging to secure R&D human resources, and it is facing a somewhat more difficult environment compared to other sectors, such as the difficulty in maintaining R&D continuity due to the turnover rate of researchers. In this study, based on the empirical data and patent status of private companies closely related to the R&D technology status, big data analysis, and simulation analysis methods were used to identify the relative position of individual companies' R&D capabilities and industrial perspectives. In this study, based on industrial evidence and patent applications closely related to the R&D technology status, the R&D capabilities of individual companies were evaluated using extensive data analysis and simulation analysis methods, and a statistical test was performed to analyze if there were differences in capabilities from an industrial point of view. At this time, the industries to be analyzed were based on all sectors, the maritime industry, the fisheries industry, and the maritime industry integration sector. In conclusion, it was analyzed that there was a certain level of difference in the R&D capabilities of individual companies in each industry sector, Therefore when developing a future R&D capability system, it was confirmed that it was necessary to separate the population for each industry and establish a strategy.