• 대한인간공학회지
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• 제33권3호
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• pp.215-227
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• 2014

Objective: The purpose of this study was to evaluate Korea's Honam express train's first- and second-class seat discomfort by using pressure measurement, subjective discomfort rating, and physical compatibility. Background: Over the years, the demand for an express train service is continually increasing. A comfortable ride is important to achieving passenger satisfaction. A train seat plays a significant role in fulfilling passenger seating comfort. With this in view, a field survey and pressure measurements were performed on the selected train seat. Method: The pressure ratio at the body-seat interface (thigh and buttock regions) was measured by the pressure mat system. The interface pressure ratio was calculated and compared. The subjective discomfort rating scale was used to evaluate the subjects' overall feeling. The dimensions of train seats were analysed according to the anthropometric and demographic characteristics of the population data from Size Korea. Results: The results highlighted that the interface pressure ratio was greater while participants sat on the second-class seat than the first-class seat in the left- and right-side thigh regions. Also the pressure ratio was greater for the participants in the 1st~25th percentile height groups (149.8~160.8cm). The subjects rated higher discomfort for the second-class seat than the first-class seat. The physical compatibility results showed that the second-class seat's breadth was inadequate for the 95th and 99th percentile male. Conclusion: Overall, interface pressure measurement, subjective discomfort score and physical compatibility results showed that the second-class seat was more uncomfortable for the passengers than the first-class seat. Application: The adopted methodologies could be used to measure the seating comfort of the train seats.

• Journal of the Korean Data and Information Science Society
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• 제23권6호
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• pp.1137-1144
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• 2012

요즘 대부분의 대학들이 국제화를 목표로 재학생들의 어학능력 및 국제적 경쟁력 강화와 함께 영어강의의 중요성이 증대되고 있다. 본 연구에서는 강의평가점수를 이용해서 과목특성 변수들과 개인특성 변수들 별로 영어강의와 한국어강의의 효과성을 비교하였다. 또한 로지스틱회귀분석과 의사결정나무분석을 이용하여 어떤 요인들이 영어강의가 한국어강의에 비해서 효과적인지를 주효과와 상호작용효과 측면에서 분석하였다. 분석결과에 따르면 영어강의의 효과성에 영향을 미치는 변수로는 학년, 계열, 강좌규모, 평균평점, 계열, 전형방법 등으로 나타났다. 또한 영어강의 효과성이 특히 높은 그룹은 1학년이면서 인문계열인 경우, 그리고 1학년이면서 자연 및 예체능계열이고 평균평점이 높은 그룹이 높게 나타났다. 그리고 영어강의의 효과성 비율이 특히 낮은 그룹은 2-3학년 학생이면서 강좌규모가 크고 인문계열인 경우로 나타났다.

• 대한소아치과학회지
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• 제44권3호
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• pp.263-271
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• 2017

본 연구는 Molar-incisor hypomineralization(MIH)에 이환된 제1대구치를 그 결손의 크기 별로 분류를 시행하고, 수복치료 후 수복재료에 따른 예후 평가를 목적으로 수행되었다. MIH에 이환되어 맹출 후 치관 붕괴가 관찰된 제1대구치를 Class I에서 III까지 세 단계로 분류하고, 수복치료 이후 수행된 재치료 빈도를 Class와 수복재료별로 나누어 살펴보았다. MIH Class I 결손에서는 실런트, Class II 결손에서는 복합레진이 가장 높은 유지율을 보였다. Class III 결손에서는 기성금속관의 유지율이 가장 높게 나타났다.

• 한국학교수학회논문집
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• 제2권1호
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• pp.67-77
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• 1999

The purpose of this study was to design models of CAI programs for the graphing of quadratic functions. In order to achieve this aim, I researched the relationship between mathematics educations computer programing, and theoretical approaches of CAI. The CAI program, which was developed based on my research was then positively applied to the mathematics education class in a middle school. First of all, I selected two classes -An experimental class and a comparative class. The experimental class was taught using the CAI program and the comparative class was taught by conventional methods of instruction. The results of this study are as follows: 1. The class taught by using the CAI program scored higher academic achievement than the class taught by conventional methods of instruction. 2. The analysis of the two classes' academic scores shows that the instruction using CAI program is more effective than that by conventional methods in improving students' academic achievement. The followings are suggestion for developing CAI programs and students' understanding through this study. 1. Non computer specialists will require a few months to develope an effect CAI program. Thus, development of easier, more clearly defined and flexible models must be constructed. 2. Teachers should be eager to use pre-existing models to motivate their students irregardless of their own development of programs. 3. School should provide computer rooms with a perfect net work in proportion to class size. 4. CAI programs can make students understand faster and more directly than blackboard examples. However, inconsideration of mathematical characteristics, arithmetic by hand is more effective for the students' memory retention. Computers is an effective tool of instruction. But it is most effective when used in conjunction with other methods that complement its use.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권9호
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• pp.3102-3119
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• 2021

In the modern rapid growing web era, the scope of web publication is about accessing the web resources. Due to the increased size of web, the search engines face many challenges, in indexing the web pages as well as producing result to the user query. Methodologies discussed in literatures towards clustering web documents suffer in producing higher clustering accuracy. Problem is mitigated using, the proposed scheme, Semantic Conceptual Relational Similarity (SCRS) based clustering algorithm which, considers the relationship of any document in two ways, to measure the similarity. One is with the number of semantic relations of any document class covered by the input document and the second is the number of conceptual relation the input document covers towards any document class. With a given data set Ds, the method estimates the SCRS measure for each document Di towards available class of documents. As a result, a class with maximum SCRS is identified and the document is indexed on the selected class. The SCRS measure is measured according to the semantic relevancy of input document towards each document of any class. Similarly, the input query has been measured for Query Relational Semantic Score (QRSS) towards each class of documents. Based on the value of QRSS measure, the document class is identified, retrieved and ranked based on the QRSS measure to produce final population. In both the way, the semantic measures are estimated based on the concepts available in semantic ontology. The proposed method had risen efficient result in indexing as well as search efficiency also has been improved.

• 한국지구과학회지
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• 제41권1호
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• pp.1-18
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• 2020

본 논문은 기상 모델의 미세구름물리 모수화 과정 내의 눈송이의 질량-크기 관계가 지표 강수 모의에 미치는 영향에 대해 연구에 관한 것이다. WDM6와 WSM6 미세구름물리 모수화 방안이 연구를 위해 사용되었다. 실제 관측된 자료를 바탕으로 산출된 Thompson의 눈송이의 질량-크기 관계를 도입하여 WDM6와 WSM6 내의 눈송이의 질량-크기 관계식을 대체하였다. 이상적인 스콜선과 한반도 겨울철 강수 사례에 대해 수정된 WDM6와 WSM6를 사용하여 민감도 실험을 실시하였다. 결과적으로, 대기 하층에서는 싸락눈과 빗방울의 혼합비가 증가하였고 눈송이의 혼합비는 감소하였다. 이러한 혼합비와 지표 강수의 변화는 빗방울과 눈송이의 충돌 및 병합 과정과 싸락눈의 융해 과정에 기인한 것으로 분석되었다.

• 한국소성가공학회:학술대회논문집
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• 한국소성가공학회 2009년도 추계학술대회 논문집
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• pp.89-92
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• 2009

As a class of materials, Ni-base superalloys are among the most difficult metal alloys to forge together with refractory metals and cobalt-base superalloys. The mechanical properties of Ni-base superalloys depend very much on grain size and the strengthening phases, $\gamma$' ($Ni_3$(Al,Ti)-type) and $\gamma$".($Ni_3$Nb-type). Especially, the control of grain size remains as a sole means for the control of mechanical properties. The grain size and distribution changes of the wrought superalloys during hot working and heat treatment are mainly controlled by the recrystallization and grain growth behaviors. In this presentation, prediction technology of grain size through the computer-aided process design, and numerical modeling for predicting the microstructure evolution of Ni-base superalloy during hot working were introduced. Also, some case studies were dealt with actual forming processes of Ni-base superalloys.

• 한국주거학회:학술대회논문집
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• 한국주거학회 2003년도 정기총회 및 추계학술대회
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• pp.289-294
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• 2003

Purpose of this study is to supply data that need in qualitative improvement and plan for middle class through a post occupancy evaluation by the tenants in the rental apartment of national housing size. The results of this study are as follows; 1) Characteristic of household differ as the size tenants live in at present. But, usually characteristic of household was family life cycle was from child-rearing time to secondary education time, a family's number was 3${\sim}$4 person, and income per month was 1${\sim}$3 million won. 2) The satisfaction of whole and physical environment were satisfied more than average 3 points. However, the satisfaction of economic performance and administration environment were dissatisfied by average 3 points low. 3) Factors that affect in housing satisfaction were administration environment, the housing size, a family's number.

• Journal of Microbiology
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• 제34권4호
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• pp.300-304
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• 1996

To define the effects of zooplankton and phytoplankton to bacteria, bacterial numbers, frequency of dividing cells (FDC) and size distribution were performed with image analysis in the surface layer of Lake Soyang. In August 1992, when Anabaena was blooming, the bacterial number increased at daytime. Bacterial numbers and FDC value had a negative correlation (r = 0.83, P < 0.01). Bacterial size spectrums were dynamically changed during the day and night, especially the small bacteria less than $0.5\;{\mu}m^3$. Meanwhile, in October, after the bloom, the bacterial number was only one third of that in August, even though the FDC was higher than that in August. The bacterial numbers of small size class dropped at 13:00. But the size spectrums were relatively constant during the night time. These results suggest that the bacterial growth was tightly coupled with phytoplankton during Anabaena bloom. And after the bloom, the bacterial number was controlled grazing activity of zooplankton at daytime.

• 산업기술연구
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• 제28권A호
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• pp.185-189
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• 2008

Practical pattern recognition systems should overcome very large class problem. Sometimes it is almost impossible to build every model for every class due to memory and time constraints. For this case, grouping similar models will be helpful. In this paper, we propose GMC(Group Model Clustering) to build a large class Chinese character recognition system. We built hidden Markov models for 10% of total classes, then classify the rest of classes into already trained group classes. Finally group models are trained using group model clustered data. Recognition is performed using only group models, in order to achieve reduced model size and improved recognition speed.