• Title/Summary/Keyword: 과학 문제해결 모형

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Performance Evaluation of a Fat-tree Network with Output-Buffered $a{\times}b$ Switches (출력 버퍼형 $a{\times}b$스위치로 구성된 Fat-tree 망의 성능 분석)

  • 신태지;양명국
    • Journal of KIISE:Information Networking
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    • v.30 no.4
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    • pp.520-534
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    • 2003
  • In this paper, a performance evaluation model of the Fat-tree Network with the multiple-buffered crossbar switches is proposed and examined. Buffered switch technique is well known to solve the data collision problem of the switch network. The proposed evaluation model is developed by investigating the transfer patterns of data packets in a switch with output-buffers. Two important parameters of the network performance, throughput and delay, are then evaluated. The proposed model takes simple and primitive switch networks, i.e., no flow control and drop packet, to demonstrate analysis procedures clearly. It, however, can not only be applied to any other complicate modern switch networks that have intelligent flow control but also estimate the performance of any size networks with multiple-buffered switches. To validate the proposed analysis model, the simulation is carried out on the various sizes of Fat-tree networks that uses the multiple buffered crossbar switches. Less than 2% differences between analysis and simulation results are observed.

Development of a Model of Brain-based Evolutionary Scientific Teaching for Learning (뇌기반 진화적 과학 교수학습 모형의 개발)

  • Lim, Chae-Seong
    • Journal of The Korean Association For Science Education
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    • v.29 no.8
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    • pp.990-1010
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    • 2009
  • To derive brain-based evolutionary educational principles, this study examined the studies on the structural and functional characteristics of human brain, the biological evolution occurring between- and within-organism, and the evolutionary attributes embedded in science itself and individual scientist's scientific activities. On the basis of the core characteristics of human brain and the framework of universal Darwinism or universal selectionism consisted of generation-test-retention (g-t-r) processes, a Model of Brain-based Evolutionary Scientific Teaching for Learning (BEST-L) was developed. The model consists of three components, three steps, and assessment part. The three components are the affective (A), behavioral (B), and cognitive (C) components. Each component consists of three steps of Diversifying $\rightarrow$ Emulating (Executing, Estimating, Evaluating) $\rightarrow$ Furthering (ABC-DEF). The model is 'brain-based' in the aspect of consecutive incorporation of the affective component which is based on limbic system of human brain associated with emotions, the behavioral component which is associated with the occipital lobes performing visual processing, temporal lobes performing functions of language generation and understanding, and parietal lobes, which receive and process sensory information and execute motor activities of the body, and the cognitive component which is based on the prefrontal lobes involved in thinking, planning, judging, and problem solving. On the other hand, the model is 'evolutionary' in the aspect of proceeding according to the processes of the diversifying step to generate variants in each component, the emulating step to test and select useful or valuable things among the variants, and the furthering step to extend or apply the selected things. For three components of ABC, to reflect the importance of emotional factors as a starting point in scientific activity as well as the dominant role of limbic system relative to cortex of brain, the model emphasizes the DARWIN (Driving Affective Realm for Whole Intellectual Network) approach.

Interrelationship Between Regional Population Migration, Crop Area, and Foreign Workers (지역 간 인구이동, 경지면적, 외국인 근로자의 관계 분석)

  • Seojin Cho;Heeyeun Yoon
    • Journal of the Korean Regional Science Association
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    • v.40 no.2
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    • pp.21-38
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    • 2024
  • Understanding the interrelationship between regional population dynamics and cultivated land is crucial for promoting regional economic vitality and enhancing food security. While prior research often addressed population migration and changes in crop area separately, this study employs a Panel Vector Auto Regression Model to examine the dynamic interaction between regional population shifts, changes in crop area, and the influx of foreign workers in agriculture. The results reveal a reciprocal relationship between population influx and crop area, indicating a negative impact on each other. Moreover, the analysis demonstrates that an expansion in crop area, particularly in field cultivation, significantly correlates with an increase in foreign workers. These findings underscore the mutual influence of labor shortages and diminished land availability in agriculture, with the influx of foreign workers potentially offering a positive impact on addressing structural challenges in rural areas.

Exploring Pre-Service Earth Science Teachers' Understandings of Computational Thinking (지구과학 예비교사들의 컴퓨팅 사고에 대한 인식 탐색)

  • Young Shin Park;Ki Rak Park
    • Journal of the Korean earth science society
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    • v.45 no.3
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    • pp.260-276
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    • 2024
  • The purpose of this study is to explore whether pre-service teachers majoring in earth science improve their perception of computational thinking through STEAM classes focused on engineering-based wave power plants. The STEAM class involved designing the most efficient wave power plant model. The survey on computational thinking practices, developed from previous research, was administered to 15 Earth science pre-service teachers to gauge their understanding of computational thinking. Each group developed an efficient wave power plant model based on the scientific principal of turbine operation using waves. The activities included problem recognition (problem solving), coding (coding and programming), creating a wave power plant model using a 3D printer (design and create model), and evaluating the output to correct errors (debugging). The pre-service teachers showed a high level of recognition of computational thinking practices, particularly in "logical thinking," with the top five practices out of 14 averaging five points each. However, participants lacked a clear understanding of certain computational thinking practices such as abstraction, problem decomposition, and using bid data, with their comprehension of these decreasing after the STEAM lesson. Although there was a significant reduction in the misconception that computational thinking is "playing online games" (from 4.06 to 0.86), some participants still equated it with "thinking like a computer" and "using a computer to do calculations". The study found slight improvements in "problem solving" (3.73 to 4.33), "pattern recognition" (3.53 to 3.66), and "best tool selection" (4.26 to 4.66). To enhance computational thinking skills, a practice-oriented curriculum should be offered. Additional STEAM classes on diverse topics could lead to a significant improvement in computational thinking practices. Therefore, establishing an educational curriculum for multisituational learning is essential.

Three Teaching-Learning Plans for Integrated Science Teaching of 'Energy' Applying Knowledge-, Social Problem-, and Individual Interest-Centered Approaches (지식내용, 사회문제, 개인흥미 중심의 통합과학교육 접근법을 적용한 '에너지' 주제의 교수.학습 방안 개발(II))

  • Lee, Mi-Hye;Son, Yeon-A;Young, Donald B.;Choi, Don-Hyung
    • Journal of The Korean Association For Science Education
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    • v.21 no.2
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    • pp.357-384
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    • 2001
  • In this paper, we described practical teaching-learning plans based on three different theoretical approaches to Integrated Science Education (ISE): a knowledge centered ISE, a social problem centered ISE, and an individual interest centered ISE. We believe that science teachers can understand integrated science education through this paper and they are able to apply simultaneously our integrated science teaching materials to their real instruction in classroom. For this we developed integrated science teaching-learning plans for the topic of energy which has a integrated feature strongly among integrated science subject contents. These modules were based upon the teaching strategies of 'Energy' following each integrated directions organized in the previous paper (Three Strategies for Integrated Science Teaching of "Energy" Applying Knowledge, Social Problem, and Individual Interest Centered Approaches) and we applied instruction models fitting each features of integrated directions to the teaching strategies of 'Energy'. There is a concrete describing on the above three integrated science teaching-learning plans as follows. 1. For the knowledge centered integration, we selected the topic, 'Journey of Energy' and we tried to integrate the knowledge of physics, chemistry, biology, and earth science applying the instruction model of 'Free Discovery Learning' which is emphasized on concepts and inquiry. 2. For the social problem centered integration, we selected the topic, 'Future of Energy' to resolve the science-related social problems and we applied the instruction model of 'Project Learning' which is emphasized on learner's cognitive process to the topic. 3. For the individual interest centered integration, we selected the topic, 'Transformation of Energy' for the integration of science and individual interest and we applied the instruction model of 'Project Learning' centering learner's interest and concern. Based upon the above direction, we developed the integrated science teaching-learning plans as following steps. First, we organized 'Integrated Teaching-Learning Contents' according to the topics. Second, based upon the above organization, we designed 'Instructional procedures' to integrate within the topics. Third, in accordance with the above 'Instructional Procedures', we created 'Instructional Coaching Plan' that can be applied in the practical world of real classrooms. These plans can be used as models for the further development of integrated science instruction for teacher preparation, textbook development, and classroom learning.

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Segmentation of Color Image using the Deterministic Annealing EM Algorithm (결정적 어닐링 EM 알고리즘을 이요한 칼라 영상의 분할)

  • Cho, Wan-Hyun;Park, Jong-Hyun;Park, Soon-Young
    • Journal of KIISE:Databases
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    • v.28 no.3
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    • pp.324-333
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    • 2001
  • In this paper we present a novel color image segmentation algorithm based on a Gaussian Mixture Model(GMM). It is introduced a Deterministic Annealing Expectation Maximization(DAEM) algorithm which is developed using the principle of maximum entropy to overcome the local maxima problem associated with the standard EM algorithm. In our approach, the GMM is used to represent the multi-colored objects statistically and its parameters are estimated by DAEM algorithm. We also develop the automatic determination method of the number of components in Gaussian mixtures models. The segmentation of image is based on the maximum posterior probability distribution which is calculated by using the GMM. The experimental results show that the proposed DAEM can estimate the parameters more accurately than the standard EM and the determination method of the number of mixture models is very efficient. When tested on two natural images, the proposed algorithm performs much better than the traditional algorithm in segmenting the image fields.

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A Study on the Timing of Convertible Bonds Using the Machine Learning Model (기계학습 모형을 이용한 전환사채 행사 시점에 관한 연구)

  • Ryu, Jae Pil
    • Journal of the Korea Convergence Society
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    • v.12 no.10
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    • pp.81-88
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    • 2021
  • Convertible bonds are financial products that contain the nature of both bonds and shares, which are generally issued by companies with lower credit ratings to increase liquidity. Conversion bonds rely on qualitative judgment in the past, although decision-making on whether and when to exercise the right to convert is the most important issue. Therefore, this paper proposes to apply artificial neural network techniques to scientifically determine the exercise of conversion rights. We distinguish between a total of 1,800 learning data published in the past and 200 predictive experimental data and build an artificial neural network learning model. As a result, the parity performance in most groups was excellent, achieving an average excess of about 10% or more. In particular, groups 3-6 recorded an average excess of about 20% and group 6 recorded an average excess of about 37%. This paper is meaningful in that it focused on solving decision problems by converging and applying machine learning techniques, a representative technology of the fourth industry, to the financial sector.

Evaluation of Streamflow using measured Slope and Slope length at Doam Dam Watershed (실측 경사도 및 경사장을 고려한 도암호 유역의 유출량 평가)

  • Park, Geonwoo;Lee, Seoro;Lee, Gwanjae;Choi, Yujin;Lim, Kyoung Jae
    • Proceedings of the Korea Water Resources Association Conference
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    • 2019.05a
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    • pp.114-114
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    • 2019
  • 최근 들어 집중호우 및 토지이용 변화로 인한 고탁수 문제가 빈번히 발생하고 있다. 이러한 탁수 및 수질오염 문제를 해결하기 위해 환경부는 비점오염원 관리지역을 선정하였으며, Best Management Pratices(BMPs), Low Impact Development(LID) 등 다양한 저감 대책을 시행하고 있다. 비점오염원의 발생원인과 발생위치를 정확하게 증명할 수 없으므로 유역 내 수문 및 수질을 모의할 수 있는 Soil and Water Assessment Tool(SWAT) 모델이 다양한 비점오염원 연구에 널리 활용되고 있다. 그러나 SWAT 모델은 Hydrologic Response Unit(HRU)의 경사도와 경사장을 산정할 때 소유역 내 평균 경사도를 이용하여 토양유실량 및 유출특성을 모의에 필요한 매개변수들을 산정한다는 한계점이 있다. 본 연구에서는 이러한 SWAT 모형의 단점을 보완하기 위하여 실제 경작지를 기준으로 HRU를 생성하고, 실측 경사도와 경사장을 적용하기 위한 기술을 개발하였다. 본 연구에서 개발한 기술을 고탁수로 인해 비점오염원 관리지역으로 지정된 도암호 유역에 적용하여 실측 경사도와 경사장을 적용하여 모의한 유출량과 기존의 SWAT 모델을 통해 모의한 유출량을 비교 분석하였다. 기존 모델의 결과와 본 연구에서 개발한 기술을 적용하여 모의한 결과를 비교하였을 때 수문 컴포넌트 중 중간유출과 기저유출에 있어서 차이가 발생한 것을 알 수 있었다. 또한 본 연구에서 개발된 기술을 적용함으로써 도암호 유역에서 비교적 정확한 토양유실과 Suspended Solids(SS) 모의 결과를 나타냈다. 하지만 본 연구는 도암호 유역만을 대상으로 수행되었기 때문에 다른 비점오염 관리지역에 확대 적용하여 본 연구의 결과를 재검토할 필요가 있다.

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Efficient Rendering Engine of Large Scale Terrain Data for Streaming Services (대용량 위성영상 지형 데이타의 스트리밍 서비스를 위한 효율적인 렌더링 모듈)

  • Park, Tae-Joo;Lee, Sang-Jun
    • Journal of KIISE:Computing Practices and Letters
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    • v.14 no.7
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    • pp.748-752
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    • 2008
  • Various services are developed from advancement of satellite imagery methodologies and internet infrastructure expansions. However, most of these services still rely upon low-resolution satellite images combined with DEM models. In this paper, we have implemented the raw data processing modules and other modules that transfer and render high-spatial resolution satellite images for efficient streaming services in web environments. By utilizing the Bukhan-mountain data as a pilot study, the paper has proposed the efficient approach to solve graphical problems in real time processing the large geographical area.

Current Psychological Studies on Deductive Reasoning (연역추리에 관한 심리학 연구 동향)

  • Do, Kyung Soo
    • Communications of the Korean Institute of Information Scientists and Engineers
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    • v.30 no.12
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    • pp.26-34
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    • 2012
  • 지금까지 간략히 살펴본 것처럼 심리학에서 연역추리를 연구하는 이론과 가정이 변화하고 있는데, 크게 네 가지 흐름으로 요약할 수 있다[2,6,7]. 가장 큰 변화는 연역 추리와 귀납 추리의 구분이 점차로 흐려지고 있다는 것이다. 두 번째 변화는 연역 추리를 이해하는 관점이 달라지고 있다는 점이다. 심리학에서 연역추리를 본격적으로 다루기 시작한 1960년대에는 사람들이 논리적인 사고를 하느냐에 관심이 모아졌다. 그러다 1980년대와 1990년대에는 연역추리를 하는 기제에 관한 심성 논리 이론과 심성 모형 이론 간의 논쟁이 치열하게 전개되면서 내용효과와 같은 실용적 요인들에 대한 연구도 많이 수행되었다. 그리고 1990년대 들어서면서 연역추리를 정보 획득의 관점에서 접근하는 확률적 접근, 연역 추리 과정을 heuristic 처리 단계와 분석적 처리 단계로 나누어 접근하는 이중 과정 이론이 등장하면서 기본적인 이론틀의 변화도 일어나고 있다. 세 번째 변화는 연역 추리를 문제 해결이나 의사결정과 같은 다른 인지 처리와 연결하려는 시도들이 진행되고 있다는 점이다. 마지막으로 심리학의 다른 분야에서와 마찬가지로 연역 추리에 관여하는 뇌 부위를 알아보는 뇌 영상 연구들이 점차 증가하고 있다. 이런 연구들의 결과로 연역 추리 과정에 대한 다차원적인 이해가 증진되고 다른 인지과정과도 연동되는 종합적 이해가 가능해질 것으로 예상한다.