Earticle

This study explored the correlation between anti-Mullerian hormone (AMH) levels and reproductive efficiency in native Korean cattle (Hanwoo) as potential oocyte donors in ovum pick-up (OPU) programs. In an effort to enhance the efficiency of oocyte collection, this research explored the correlation between AMH levels and various factors, including the quantity of follicles, retrieved oocytes, and the proportion of transferable embryos. A total of 42 Hanwoo cows were included in this study with AMH levels ranging from 276.5 to 2,212.5 pg/mL. These cows were categorized into three groups based on AMH concentration: high (H), medium (M), and low (L), along with the control group. To monitor the quantity of antral follicles in each group during OPU, Ultrasound scanner was used, and the retrieved oocytes were duly recorded. The implantable embryos produced from the retrieved oocytes were quantified. The results show a significant positive correlation between AMH levels and the numbers of antral follicles (R2 = 0.5785, p < 0.0001), retrieved oocytes (R2 = 0.6857, p < 0.0001) and transferable embryos (R2 = 0.4049, p < 0.0001), indicating that higher AMH levels correspond to increased numbers of antral follicles and retrieved oocytes. However, the correlation between AMH levels and the proportion of transferable embryos was not statistically significant (R2 = 0.1476, p = 0.5225). In conclusion, AMH levels were significantly correlated with the number of antral follicles and retrieved oocytes, demonstrating their potential as indicators for selecting oocyte donors for Hanwoo cattle. Although the relationship with the proportion of transferable embryos was not statistically significant, this study offers valuable insights for the improvement of the efficiency of oocyte donation plans in Hanwoo cattle by considering the AMH levels.

Device-to-device (D2D) or Sidelink aided communication is regarded as one of the most promising technologies to improve the spectral efficiency of the 5G and beyond communication system. However, two main challenges exist: 1) the selection of the optimal number of devices for improving the spectral efficiency, and 2) improving the physical layer security of such a communication system. The optimal device improves the secrecy capacity, and the selection of optimal devices enhances the physical layer security. Therefore, in this paper, we propose a double threshold-based optimal device selection (ODS) scheme for a cooperative wireless network with amplify and forward (AF) protocol in the presence and absence of an eavesdropper to enhance the physical layer security for the D2D network. The proposed scheme is analyzed with different distance cases, device scenarios, and modulation schemes. The bit error rate (BER) performance analysis concludes that a performance gain of more than 4 dB is achieved at the BER of 0.004 for the proposed double threshold-based ODS scheme compared to the existing ODS scheme at a high signal to noise ratio (SNR). Furthermore, the proposed scheme enhances the physical layer security.

Feature subset selection is as a pre-processing step in learning algorithms. In this paper, we propose an efficient algorithm, ModifiedFAST, for feature subset selection. This algorithm is suitable for text datasets, and uses the concept of information gain to remove irrelevant and redundant features. A new optimal value of the threshold for symmetric uncertainty, used to identify relevant features, is found. The thresholds used by previous feature selection algorithms such as FAST, Relief, and CFS were not optimal. It has been proven that the threshold value greatly affects the percentage of selected features and the classification accuracy. A new performance unified metric that combines accuracy and the number of features selected has been proposed and applied in the proposed algorithm. It was experimentally shown that the percentage of selected features obtained by the proposed algorithm was lower than that obtained using existing algorithms in most of the datasets. The effectiveness of our algorithm on the optimal threshold was statistically validated with other algorithms.

본 연구에서는 산불무인감시카메라의 최적 위치 선정을 위한 방법을 제시하기 위하여 경상북도 김천시 를 대상으로 연구를 수행하였다. 산불무인감시카메라는 조망형 카메라를 기준으로 가시권 분석을 수행 하여 비가시 산림의 산불탐지영역 확장을 위한 추가 산불무인감시카메라의 위치를 제시하였다. 위치 선정에 고려된 인자는 읍·면·동 단위의 행정구역별 산림과 가시영역 및 탐지 비율을 고려하였고 1:5,000 수치지형도를 이용하여 넓은 시야가 확보되는 위치를 고려하였다. 산불무인감시카메라 대수의 증가에 따라 가시영역은 증가하지만 중복되는 가시영역도 함께 높아지기 때문에 효율적으로 설치할 필요가 있다. 또한 산불무인감시카메라의 운영을 위한 안정적인 전원공급, 산림 내외의 주요 보호 시설물, 산불 위험도가 높은 지역 등을 함께 고려할 필요가 있다.

This study was conducted to propose a method for selecting the optimal locations for unmanned forest fire monitoring cameras, focusing on Gimcheon, Gyeongsangbuk-do. A visibility analysis was performed based on panoramic cameras, and additional locations for unmanned forest fire monitoring cameras were suggested to expand fire detecton coverage in non-visible forest areas. Factors considered for site selection included forest areas, visibility coverage, and detection rates by administrative districts. Additionally, locations with wide visibility were identified using a 1:5000 digital topographic map. While increasing the number of cameras expands the visibility area, it also leads to greater overlap, necessitating efficient placement. Furthermore, stable power supply, key protective facilities within and outside the forest, and high-risk forest fire areas must be considered.

수질 예측은 수질 환경 관리에서 가장 중요한 요소로, 최근 다양한 기계 학습 및 딥러닝 기법을 활용한 연구가 활발히 이루어지고 있다. 환경부에서 유기물질 측정 지표를 CODmn에서 TOC로 전환하는 등 TOC에 대한 중요성이 증대됨에 따라 본 연구는 인천광역시 연수구 승기천을 대상으로 TOC 농도 예측 모델 생성을 위한 최적 입력 변수 및 예측 모델을 제안하는 것을 목표로 한다. 최적 입력 변수 선정은 Pearson 상관도 분석과 Exhaustive Search를 통해 도출하였으며, 최적 예측 모델은 회귀분석, 다층 퍼셉트 론(MLP) 인공신경망, 랜덤포레스트 모델의 정확도를 비교하였다. 모델 성능 비교 결과 T-N, DTN, NH3-N, BOD, NO3-N을 입력 변수로 사용하는 MLP 모델이 가장 우수한 성능을 보였으며, R² 값 0.6280과 RMSE 0.8656의 결과를 기록하였다. 본 연구는 승기천의 TOC 농도 예측을 위한 최적의 입력 변수를 제안함과 동시에, 앞서 언급한 다섯 가지 주요 수질 인자를 활용한 MLP 모델이 유사한 특성을 가진 다른 하천에서 도 TOC 예측에 높은 신뢰도를 제공할 수 있다는 가능성을 제시한다.

Water quality prediction is a key factor in water environment management, with growing interest in utilizing machine learning and deep learning techniques. As the Ministry of Environment transitions the organic matter measurement indicator from CODmn to TOC, the importance of TOC has significantly increased. This study aims to propose optimal input variables and a prediction model for TOC concentration in Seunggi- Stream, Yeonsu-gu, Incheon. Input variables were derived using Pearson correlation analysis and Exhaustive Search. The prediction models tested include Regression Analysis, Multi-Layer Perceptron (MLP) Neural Networks, and Random Forest. Among them, the MLP model using T-N, DTN, NH3-N, BOD, and NO3-N as input variables showed the best performance, achieving an R² of 0.6280 and an RMSE of 0.8656. This study identifies optimal input variables for TOC prediction and suggests that the MLP model can provide reliable TOC predictions for streams with similar characteristics.

The performance of a deep learning model significantly improves on challenging datasets when using transfer learning. However, the pre-trained networks have certain constraints in terms of their architecture. For example, the available pre-trained models are trained for a specific input size. Therefore, require resizing the input images of different sizes. When training a model from scratch, higher resolution image offers better performance. However, our study has shown that this is not true when using pre-trained models. We have compared the pre-trained MobileNetV2 performance on CIFAR10 and CIFAR100 datasets. The pre-trained weights of MobileNetV2 are available for image resolutions of 92x92, 128x128, 160x160, 192x192 and 224x224. The performance of the model is evaluated in terms of classification accuracy. Our analysis have shown that for image resolution of 160x160, the pre-trained model has achieved better classification accuracy.

In this paper, we consider the portfolio choice problem for Gul(1991)'s disappointment averse investors in continuous time economy. Assuming a complete market and general ge- ometric Brownian motions for asset prices, we provide the analytic method to derive the formulas for the optimal wealth and portfolio weight. In order to explore some important implications, we use the disappointment aversion preferences of Gul(1991) associated with the constant relative risk aversion utility and compare it to the standard CRRA utility. We show that the portfolio weight under the disappointment aversion model is less than under the standard CRRA model. This result partially explains the portfolio puzzle of Mankiw and Zeldes(1991). Also, we ¯nd that the portfolio weight under the disappointment aversion model is changed among the time horizon.

본 연구는 기후변화에 따른 연안 재해 위험에 대응하고자 고해상도 항공사진과 AHP(계층화 분석법) 기법을 활용하여 객관적인 해안방재림 조성 입지 지표를 개발하였다. 분석 결과, ‘안전성 및 시공성’(0.442)이 가장 중요한 대항목으로 도출되었으며, 주요 시설과의 거리(0.404)와 만조 해안선 거리(0.399)가 핵심 지표로 확인되었다. 최근 10년간 조성된 사업지(110개소)의 입지 적합성 지수(SSI) 평균값인 0.414를 신규 조성을 위한 임계치로 설정하고 이를 전국 신규 조성대상지(1,327.2ha)에 적용한 결과, 우선 조성이 필요한 55.4ha(4.2%)의 핵심 대상지를 식별하였다. 이에, 해당 지역을 거점으로 잔여 대상지에 대한 단계적 확충 로드맵을 수립한다면 보다 실효성 있는 방재 안전망 구축이 가능할 것으로 기대된다. 본 연구는 정성적 판단에서 벗어난 과학적 입지 선정 체계를 마련하였다는데 의의가 있으며, 향후 체계적인 해안방재림 조성 계획 수립에 기여할 것으로 사료된다.

This study developed objective site selection criteria for coastal disaster prevention forests using high-resolution aerial photographs and the Analytic Hierarchy Process (AHP) to address increasing coastal disaster risks. AHP analysis revealed that ‘Safety & Constructability’ (0.442) was the most critical criterion, with ‘Distance to Facilities’ (0.404) and ‘Distance from High Tide Line’ (0.399) identified as key sub-criteria. By applying these to 110 established sites, a Site Suitability Index (SSI) average of 0.414 was set as the quantitative threshold for new plantations. Applying this threshold to 1,327.2 ha of potential sites identified 55.4 ha of core target areas (4.2%), which should be prioritized for immediate establishment to serve as hubs for a phased expansion roadmap. This study provides a scientific framework moving beyond qualitative judgment, contributing to the systematic and effective planning of future coastal disaster prevention efforts.

Municipal solid waste (MSW) management is possible to be identified as one of the mostly cited fields in the optimization applications. This is because optimization of solid waste management is most general in contemporary research applications as the issue is being becoming more complex and impasse with rapidly increasing of urban population particularly in the developing world. Optimal site selection is to be identified as one of the famous facility location problems in the discipline of location science. With a range of growing impediments, such as scarcity of suitable lands for dumping, increasing of transportation and labour costs, diversifying of environmental pollutions etc, the application of optimization approaches on municipal solid waste management has been very famous among scholars and policy planners. The city of Colombo is a famous rapidly growing and propelling city in the South Asia. This is because many forms of internal migration flows can be seen into the city of Colombo. On this background, daily tonnage of solid waste accumulation has been augmented exponentially. At present, the issue has been become one of the burning dilemmas in the city. In this context, the purpose of this paper is to identify the potential, optimal and safe sites for SMW management in the city of Colombo by using GIS and Analytic Hierarchy Process (AHP). The study used mainly five criteria (Inhabited and build-up areas, Slopes, Elevation, Water bodies, and Road categories) and different constraints for each of them in terms of the optimal and safe site selection mechanism. The AHP approach is applied in order to obtain acute factor scoring and weighting scheme. Finally, the study used Weighted Overlay method in ArcGIS 10.2 environment for the optimal and safe site selection. The analyses of the results are revealed that six vacant sites are available and they are potentials to be used as optimal and safe sites for the MSW management practices. The study suggests that the preliminary sites investigations are needed to be done in order to clarify the ownerships and land valuation in advance.

This study was carried out to obtain basic data on physiological characteristics for an artificial cultivation of Grifola frondosa. Ten strains of G. frondosa were collected from Korea, China and Japan and those were isolated and tested. PDA medium was selected for the favorable culture medium. The optimal conditions for the mycelial growth of G. frondosa were 25℃ and pH 4∼5 respectively. The carbon and nitrogen sources for the optimum mycelial growth were fructose and peptone, respectively. Highest mycelial growth was observed when the C/N ratio was 10∼20. Significant differences among lines were found for production yield and crop cycle time. KME44009 had a short spawn run time, high yield, good color and quality compare with other strains. To find out the suitable medium composition of G. frondosa, physicochemical conditions were investigated. The T2 formulation (55:25:8:12 mixing ratio of oak sawdust, oak chip, wheat bran and soybean cake) showed the shortest time to complete the crop cycle and the highest yields(weight of fresh mushrooms harvested at maturity). Among the physicochemical factors, pH, crude oil and total nitrogen may affect mushroom yield. Therefore, development of suitable medium would benefit from increased production efficiency of G. frondosa mushrooms and be commercial potential.

This study was carried out to obtain basic data on physiological characteristics for an artificial cultivation of Grifola frondosa. Ten strains of G. frondosa were collected from Korea, China and Japan and those were isolated and tested. PDA medium was selected for the favorable culture medium. The optimal conditions for the mycelial growth of G. frondosa were 25℃ and pH 4～5 respectively. The carbon and nitrogen sources for the optimum mycelial growth were fructose and peptone, respectively. Highest mycelial growth was observed when the C/N ratio was 10～20. Significant differences among lines were found for production yield and crop cycle time. KME44009 had a short spawn run time, high yield, good color and quality compare with other strains. To find out the suitable medium composition of G. frondosa, physicochemical conditions were investigated. The T2 formulation(55:25:8:12 mixing ratio of oak sawdust, oak chip, wheat bran and soybean cake) showed the shortest time to complete the crop cycle and the highest yields(weight of fresh mushrooms harvested at maturity). Among the physicochemical factors, pH, crude oil and total nitrogen may affect mushroom yield. Therefore, development of suitable medium would benefit from increased production efficiency of G. frondosa mushrooms and be commercial potential.

최근 디지털 데이터 양의 기하급수적 증가는 데이터 처리 시스템의 중요성을 부각시켰다. 이 연구는 클라우드 컴퓨팅 (CC; cloud computing), 엣지 컴퓨팅 (EC; edge computing), 그리고 UAV (unmanned aerial vehicle) 기반 지능형 에지 컴퓨팅 (UEC; unmanned aerial vehicle-based intelligent edge computing) 간의 성능을 비교하였으며, 특히 회랑감시와 같은 실시간 대용량 데이터 처리 상황에 초점을 맞추었습니다. UAV 기반 지능형 에지 컴퓨팅은 이동성과 특수 환경에서의 대규모 데이터 처리 및 분석에 높은 효과성을 보인다. 이러한 연구 결과를 바탕으로 각 상황에 맞게 최적화된 시스템 선택 방법론을 제안한다.

Recently, as the amount of digital data increases exponentially, the importance of data processing systems is being emphasized. In this situation, the selection and construction of data processing systems are becoming more important. In this study, the performance of cloud computing (CC), edge computing (EC), and UAV-based intelligent edge computing (UEC) was compared as a way to solve this problem. The characteristics, strengths, and weaknesses of each method were analyzed. In particular, this study focused on real-time large-capacity data processing situations such as corridor monitoring. When conducting the experiment, a specific scenario was assumed and a penalty was given to the infrastructure. In this way, it was possible to evaluate performance in real situations more accurately. In addition, the effectiveness and limitations of each computing method were more clearly understood, and through this, the help was provided to enable more effective system selection.

The purpose of this study was that the optimal hydrolysis conditions of endo- and exo-type enzymes were selected to utilize organic cheese byproducts. Optimal substrate concentration and optimum enzyme ratio were measured by using 4 kinds of endo-type enzymes (alcalase, neutrase, protamex, and foodpro alkaline protease) and two exo-type enzymes (flavourzyme and prozyme 2000P) for whey protein hydrolysis were analyzed using liquid chromatography. As a result, the optimal endo-type enzyme through the first enzyme reaction was selected as alcalse, and as a result of the secondary enzyme reaction, flavourzme was selected as the Exo type enzyme. The concentration of whey protein substrate for optimal primary and secondary enzyme reactions was 10%. In addition, the optimum ratio of enzyme was 0.5% of alcalase and 0.2% of flavourzyme, which showed low molecular weight chromatography pattern compared to 2% of alcalase and 1% of flavourzyme hydrolyzate. Therefore, hydrolyzing the endo-type enzyme alcalase at a concentration of 0.5% for 10 hours and then hydrolyzing the exo-type enzyme flavouryme at a concentration of 0.2% for 4 hours was considered to be the optimum condition.

The object of the thermal error compensation system in machine tools is improving the accuracy of a machine tool through real time error compensation. The accuracy of the machine tool totally depends on the accuracy of thermal error model. A thermal error model can be obtained by appropriate combination of temperature variables. The proposed method for optimal variable selection in the thermal error model is based on correlation grouping and successive regression analysis. Collinearity matter is improved with the correlation grouping and the judgment function which minimizes residual mean square is used. The linear model is more robust against measurement noises than an engineering judgement model that includes the higher order terms of variables. The proposed method is more effective for the applications in real time error compensation because of the reduction in computational time, sufficient model accuracy, and the robustness.

Scoplanmine and hyoscyamine which belong to tropane alkaloids are the pharmaceutically valuable anticholinergic drugs. In order to increase the productivities, the effects of elicitation were investigated during hairy root cultures of Scopolia parviflora. Biltic elicitors originated from 3 fungi and 1 yeast were prepared as homogenate and supernatant and added to 30week0old cultures. Both of homogenate and supernatant of Candida albicans elicitors increased the scopolamine production. The production of hyoscyamine was enhanced by homogenate of Fusarium solani and supernatant of C. albicans. Most of the other fungal elicitors were also improved on the tropane alkaloid production compared to non-treatment. Among the elicitors tested, C. albicans was proved the optimal biotic elicitor on tropane alkaloids production. These results will be served mass production of tropane alkaloids by large-scale production.

In process planning for pocket machining, the selection of tool size, tool path, overlap distance, and the calculation of machining time are very important factors to obtain the optimal process planning result. Among those factors, the tool size is the most important one because the others depend on tool size. And also, it is not easy to determine the optimal tool size even though the shape of pocket is simple. Therefore, the optimal selection of tool size is the most essential task in process planning for machining a pocket. This paper presents a method for selecting optimal toos in pocket machining. The branch and bound method is applied to select the optimal tools which minimize the machining time by using the range of feasible tools and the breadth-first search.

이상기후와 댐 시설의 노후화로 인해 댐에 대한 위험관리 요구가 증대되고 있다. 하지만 저수지·댐 등의 붕괴에 따른 비상대처계획에서는 단일호우사상에 의해 댐 붕괴가 발생한 경우만을 다루고 있다. 이에 본 연구에서는 연속호우사상으로 인한 댐 하류부의 피해 발생 상황을 모의하고, 각각의 상황에 대한 최적 대피소를 선정하여 저수지·댐 등의 붕괴에 따른 비상대처계획 수립 방안을 제시하였다. 충주댐 유역을 대상으로 500년 빈도의 확률강우량이 연속적으로 발생하는 거대강우 시나리오를 정의하고, 이로 인해서 발생하는 거대홍수량을 산정하였다. 거대강우 시나리오가 충주댐에 발생하였을 때 무피해방류량 이상의 방류로 인해서 하류부에 침수피해가 발생하는 경우 (시나리오 A)와 댐 붕괴가 발생하는 경우 (시나리오 B)로 나누어 하류부에 발생하는 피해를 분석하였다. 2개의 시나리오에 따른 침수피해를 분석한 결과, 시나리오 A에서의 침수면적은 50.06 km²이며, 시나리오 B에서의 침수면적은 약 6.1배 큰 307.45 km²로 나타났다. 침수피해가 발생한 하류부 지역 중 시가화 지역의 비율이 높은 충주시를 대상으로 행정구역별 최적 대피소를 선정하였다. 국내·외 대피소 선정기준들을 이용하여 7가지 대피소 평가지표들을 설정하였으며, 계층화(Analytic Hierarchy Process, AHP) 기법을 활용하여 대피소 대안들을 평가하였다. 각 시나리오별로 최적 대피소를 선정한 결과, 선정된 6개의 최적 대피소 중에서 5곳이 학교로 선정되었다. 본 연구에서는 기존의 비상대처계획에서 고려되지 않았던 연속호우 사상에 의한 상황을 추가적으로 고려하였으며, 본 연구의 결과는 추후 비상대처계획 수립 시 참고 자료로 활용될 수 있을 것이라고 판단된다.

There is a growing demand for the stability of existing dams due to abnormal climate and the aging of dams. Emergency Action Plans (EAPs) for reservoir or dam failure only consider a single rainfall event. Therefore, this study simulates dam failure caused by continuous rainfall events, and proposes the establishment of EAP by selecting the optimal shelters. We define a mega rainfall event scenario caused by continuous rainfall events with 500-year frequency in the Chungju Dam watershed and estimate the mega flood. The mega flood event scenario is divided into two cases: scenario A represents the flooding case caused by discharge release from a dam, while scenario B is the case of a dam break. As a result of flood inundation analysis, the flooded damage area by the scenario A is 50.06 km² and the area by the scenario B is 6.1 times of scenario A (307.45 km²). We select optimal shelters for each administrative region in the city of Chungju, which has the highest inundation rate in the urban area. Seven shelter evaluation indicators from domestic and foreign shelter selection criteria are chosen, and Analytical Hierarchy Process (AHP) method is used to evaluate the alternatives. As a result of the optimal shelter selection, the six shelters are selected and five are schools. This study considers continuous rainfall events for inundation analysis and selection of optimal shelters. Also, the results of this study could be used as a reference for establishment of the EAP.