• Animal Bioscience
• /
• 제37권8호
• /
• pp.1333-1344
• /
• 2024

Objective: Litter size and piglet loss at birth significantly impact piglet production and are closely associated with sow parity. Understanding how these traits vary across different parities is crucial for effective herd management. This study investigates the patterns of the number of born alive piglets (NBA), number of piglet losses (NPL), and the proportion of piglet losses (PPL) at birth in Landrace sows under tropical conditions. Additionally, it aims to identify the most suitable model for describing these patterns. Methods: A dataset comprising 2,322 consecutive reproductive records from 258 Landrace sows, spanning parities from 1 to 9, was analyzed. Modeling approaches including 2nd and 3rd degree polynomial models, the Wood gamma function, and a longitudinal model were applied at the individual level to predict NBA, NPL, and PPL. The choice of the best-fitting model was determined based on the lowest mean and standard deviation of the difference between predicted and actual values, Akaike information criterion (AIC), and Bayesian information criterion (BIC). Results: Sow parity significantly influenced NBA, NPL, and PPL (p<0.0001). NBA increased until the 4th parity and then declined. In contrast, NPL and PPL decreased until the 2nd parity and then steadily increased until the 8th parity. The 2nd and 3rd degree polynomials, and longitudinal models showed no significant differences in predicting NBA, NPL, and PPL (p>0.05). The 3rd degree polynomial model had the lowest prediction standard deviation and yielded the smallest AIC and BIC. Conclusion: The 3rd degree polynomial model offers the most suitable description of NBA, NPL, and PPL patterns. It holds promise for applications in genetic evaluations to enhance litter size and reduce piglet loss at birth in sows. These findings highlight the importance of accounting for sow parity effects in swine breeding programs, particularly in tropical conditions, to optimize piglet production and sow performance.

• 한국지구과학회지
• /
• 제45권1호
• /
• pp.37-47
• /
• 2024

In the summer of 2018, the Korea-Japan (KJ) region experienced an extremely severe and prolonged heatwave. This study examines the GloSea6 model's prediction performance for the 2018 KJ heatwave event and investigates how its prediction skill is related to large-scale circulation patterns identified by the k-means clustering method. Cluster 1 pattern is characterized by a KJ high-pressure anomaly, Cluster 2 pattern is distinguished by an Eastern European high-pressure anomaly, and Cluster 3 pattern is associated with a Pacific-Japan pattern-like anomaly. By analyzing the spatial correlation coefficients between these three identified circulation patterns and GloSea6 predictions, we assessed the contribution of each circulation pattern to the heatwave lifecycle. Our results show that the Eastern European high-pressure pattern, in particular, plays a significant role in predicting the evolution of the development and peak phases of the 2018 KJ heatwave approximately two weeks in advance. Furthermore, this study suggests that an accurate representation of large-scale atmospheric circulations in upstream regions is a key factor in seasonal forecast models for improving the predictability of extreme weather events, such as the 2018 KJ heatwave.

• 지능정보연구
• /
• 제29권2호
• /
• pp.285-301
• /
• 2023

비대면 교육의 중요성 및 필요에 따른 수요가 증가함에 따라 국내외 온라인 교육 오픈 플랫폼이 활성화되고 있다. 본 플랫폼은 대학 등 교육 전문기관과 달리 학습자의 자율성이 높은 특징을 가지며 이에 따라 개인화된 학습 도구를 지원하기 위한 학습 행동 데이터의 분석 연구가 중요시 되고 있다. 실제적인 학습 행동을 이해하고 패턴을 도출하기 위하여 프로세스 마이닝이 다수 활용되었지만 온라인 교육 플랫폼과 같이 자기 관리형(Self-regulated) 환경에서의 학습 로그를 기반한 사례는 부족하다. 또한, 대부분 프로세스 모델 도출 등의 모델 관점에서의 접근이며 분석 결과의 실제적인 적용을 위한 개별 패턴 및 인스턴스 관점에서의 방법 제시는 미흡하다. 본 연구에서는 온라인 교육 오픈 플랫폼 내 학습 패턴을 파악하기 위하여 프로세스 마이닝을 활용한 분석 방법을 제시한다. 학습 패턴을 다각도로 분석하기 위하여 모델, 패턴, 인스턴스 관점에서의 분석 방법을 제시하며, 프로세스 모델 발견, 적합도 검사, 군집화 기법, 예측 알고리즘 등 다양한 기법을 활용한다. 본 방법은 국내 오픈 교육 플랫폼 내 기계학습 관련 강좌의 학습 로그를 추출하여 분석하였다. 분석 결과 온라인 강의의 특성에 맞게 비구조화된 프로세스 모델을 도출할 수 있었으며 구체적으로 한 개의 표준 학습 패턴과 세 개의 이상 학습 패턴으로 세분화할 수 있었다. 또한, 인스턴스별 패턴 분류 예측 모델을 도출한 결과 전체 흐름 중 초기 30%의 흐름을 바탕으로 예측하였을 때 0.86의 분류 정확도를 보였다. 본 연구는 프로세스 마이닝을 활용하여 학습자의 패턴을 체계적으로 분석한다는 점에서 기여점을 가진다.

• 대한기계학회:학술대회논문집
• /
• 대한기계학회 2001년도 춘계학술대회논문집C
• /
• pp.299-304
• /
• 2001

An approach is developed for parametric investigation of the influence of the surface roughness on thermohydrodynamic analysis with film conditions which systemically occur in journal bearings. A parametric investigation is performed for predicting the bearing behaviors such as pressure and temperature distributions in lubricating films between the stationary and moving surfaces determined by absorbed layers and interfaces on the statistical method for rough surface with Gaussian distribution. The layers expressing the effects of surface roughness are expressed as functions of the standard deviations (${\sigma}$) of each surface and surface orientation (j) to explain the flow patterns between both rough surfaces. The coupled effect of surface roughness and shear zone dependency on hydrodynamic pressure and temperature has been found by solving the present model in non-contact mode and contact mode, respectively.

• 한국경영과학회:학술대회논문집
• /
• 한국경영과학회 1997년도 추계학술대회발표논문집; 홍익대학교, 서울; 1 Nov. 1997
• /
• pp.207-210
• /
• 1997

The drastic structural changes in telecommunications industry are imposing new strains on operators, regulators and customers. Many researchers have offered diverse frameworks for the changes from the perspectives of sociology, technology, and/or economics. However, there have been few attempts to document the competitive phenomena from management perspectives because of the technological complexities and dynamism in the fundamental transition of competition. In this study, we examine competitive environment in telecommunications industry, and identified five structural elements; telecom operator, competitors, regulation, suppliers, and customer demand. The suggested framework is used to provide a basis for explaining the changes in the characteristics of individual elements and the interactions among them. The dynamic industry-specific changes will be explained through an evolutionary model. We specify the characteristics of progressive stages and the determinants of the evolution. Changes are reviewed in terms of five criteria; regulations and competitions, value chain, technology, customers demand, and internal operations. The result of this study will be useful in analyzing and predicting industry structure and major participants' strategic behaviors and decision patterns. This study can alse be extended to other industries facing dynamic structural changes.

• 유체기계공업학회:학술대회논문집
• /
• 유체기계공업학회 2000년도 유체기계 연구개발 발표회 논문집
• /
• pp.91-98
• /
• 2000

Developed is a computer program for the prediction of the aero-acoustic performance characteristics such as discharge pressure, efficiency, power and noise level in the basic design step of axial flow fan. The flow field and the aerodynamic performance of fan are analyzed by using the streamline curvature computing scheme with total pressure loss and flow deviation models. Fan noise is assumed to be generated due to the pressure fluctuations induced by wake vortices of fan blades and to radiate via dipole distribution. The vortex-induced fluctuating pressure on blade surface is calculated by combining thin airfoil theory and the predicted flow field data. The predicted aerodynamic performances, sound pressure level and noise directivity patterns of fan by the present computer program are favorably compared with the test data of actual fan. Furthermore, the present computer program is shown to be very useful in optimizing design variables of fan with high efficiency and low noise level and in analyzing their design sensitivities.

• 한국소음진동공학회:학술대회논문집
• /
• 한국소음진동공학회 2000년도 춘계학술대회논문집
• /
• pp.371-379
• /
• 2000

A noise prediction method of axial flow fan is developed by incorporating through-flow method and vortex shedding noise model. Fan noise is assumed to be generated due to the pressure fluctuation induced by wake vortices of fan blades and radiate as diploe distribution. The wake vortices are analyzed by combining Karman vortex street model and through-flow analysis results, and the vortex-induced fluctuating pressure on blade surface is calculated by thin airfoil theory. The predicted sound pressure levels and directivity patterns of fan noise by the present method are favorably compared with fan noise test data. Furthermore, the present method is shown to be very useful for predicting the aero-acoustic performance map of the fan operated at off-design point.

• International Journal of Advanced Culture Technology
• /
• 제5권3호
• /
• pp.40-45
• /
• 2017

This data mining technique was used to extract useful information from percutaneous coronary intervention data obtained from the US public data homepage. The experiment was performed by extracting data on the area, frequency of operation, and the number of deaths. It led us to finding of meaningful correlations, patterns, and trends using various algorithms, pattern techniques, and statistical techniques. In this paper, information is obtained through efficient decision tree and cluster analysis in predicting the incidence of percutaneous coronary intervention and mortality. In the cluster analysis, EM algorithm was used to evaluate the suitability of the algorithm for each situation based on performance tests and verification of results. In the cluster analysis, the experimental data were classified using the EM algorithm, and we evaluated which models are more effective in comparing functions. Using data mining technique, it was identified which areas had effective treatment techniques and which areas were vulnerable, and we can predict the frequency and mortality of percutaneous coronary intervention for heart disease.

• BMB Reports
• /
• 제46권2호
• /
• pp.97-102
• /
• 2013

The use of various cancer cell lines can recapitulate known tumor-associated mutations and genetically define cancer subsets. This approach also enables comparative surveys of associations between cancer mutations and drug responses. Here, we analyzed the effects of ~40,000 compounds on cancer cell lines that showed diverse mutation-dependent sensitivity profiles. Over 1,000 compounds exhibited unique sensitivity on cell lines with specific mutational genotypes, and these compounds were clustered into six different classes of mutation-oriented sensitivity. The present analysis provides new insights into the relationship between somatic mutations and selectivity response of chemicals, and these results should have applications related to predicting and optimizing thera-peutic windows for anti-cancer agents.

• 대한치과교정학회지
• /
• 제45권2호
• /
• pp.66-73
• /
• 2015

Objective: To compare condylar position and morphology among different vertical skeletal patterns. Methods: Diagnostic cone-beam computed tomography images of 60 adult patients (120 temporomandibular joints) who visited the orthodontic clinic of Hallym University Sacred Heart Hospital were reviewed. The subjects were divided into three equal groups according to the mandibular plane angle: hypodivergent, normodivergent, and hyperdivergent groups. Morphology of the condyle and mandibular fossa and condylar position were compared among the groups. Results: The hypodivergent and hyperdivergent groups showed significant differences in superior joint spaces, antero-posterior condyle width, medio-lateral condyle width, condyle head angle, and condylar shapes. Conclusions: Condylar position and morphology vary according to vertical facial morphology. This relationship should be considered for predicting and establishing a proper treatment plan for temporomandibular diseases during orthodontic treatment.