• Title/Summary/Keyword: 자기조직화 방법

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Investigation on Characteristics of Summertime Extreme Temperature Events Occurred in South Korea Using Self-Organizing Map (자기조직화지도(Self-Organizing Map)를 이용한 최근 우리나라 여름철 극한온도 특성 분류)

  • Lim, Won-Il;Seo, Kyong-Hwan
    • Atmosphere
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    • v.28 no.3
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    • pp.305-315
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    • 2018
  • This study investigates the characteristic spatial patterns and dynamic processes associated with the summertime extreme temperature events in South Korea during the last 20 years (1995~2014) using Self-Organizing Map (SOM). The classified SOM patterns commonly have high temperature and anticyclonic circulation anomalies over South Korea. The two major teleconnection patterns are identified: one is from the subtropical western North Pacific (WNP) affecting to the north and the other is from the North Atlantic (NA) affecting downstream region. The meridional teleconnection pattern is related to the forcing of positive sea surface temperature (SST) anomaly over the WNP. The northward propagating Rossby wave generates the East Asia-Pacific (EAP) pattern to form an anticyclonic circulation anomaly over South Korea. On the other hand, NA SST anomalies generate an eastward Rossby wave train across the Eurasian continent, leading to the development of an anticyclonic circulation anomaly over South Korea. The EAP pattern occurs more frequently in July and August, whereas the midlatitude teleconnection pattern associated with NA SST anomalies develops more frequently in early summer (June).

Research On Technical Writing Educational Methods Based On Complex Learning Systems (학습복잡계 기반의 공학적 글쓰기 교수 방법 연구)

  • Kim, Hae-Kyung;Kim, Cha-Jong
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.14 no.7
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    • pp.1521-1528
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    • 2010
  • This paper examines technical writing and teaching methods based on the perspectives of the complex learning system theory. So, the paper first discusses the constituent elements and characteristics of the complex learning system theory and continues to examine the potential of applying the complex learning system theory to new teaching methods. As a result, not only did the research expand the approach methods of providing technical writing education but also confirmed the potential of actual implementation. Such results will provide a leeway to start applying new teaching methods for technical writing education. Furthermore, the paper proposes more detailed case studies related to this topic as well as development of this research to produce textbooks and other higher level researches.

Unsupervised Texture Image Segmentation with Textural Orientation Feature (텍스쳐 방향특징에 의한 비교사 텍스쳐 영상 분할)

  • 이우범;김욱현
    • Proceedings of the Korea Institute of Convergence Signal Processing
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    • 2000.08a
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    • pp.325-328
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    • 2000
  • 텍스쳐 분석은 장면 분할, 물체 인식, 모양과 깊이 인식 등의 많은 영상 처리 분야에서 중요한 기술 중의 하나이다. 그러나 실영상에 포함된 다양한 텍스쳐 성분에 대해서 보편적으로 적용 가능한 효율적인 방법들에 대한 연구는 미흡한 실정이다. 본 논문에서는 텍스쳐 인식을 위해서 비교사 학습 방법에 기반 한 효율적인 텍스쳐 분석 기법을 제안한다. 제안된 방법은 텍스쳐 영상이 지닌 방향특징 정보로서 각(angle)과 강도(power)를 추출하여 자기 조직화 신경회로망에 의해서 블록기반으로 군집화(clustering)된다. 비교사적 군집 결과는 통합(merging)과 불림(dilation) 과정을 통해서 영상에 내재된 텍스쳐 성분의 분할을 수행한다. 제안된 시스템의 성능 평가를 위해서는 다양한 형태의 다중 텍스쳐 영상을 생성하여 적용한 후 그 유효성을 보인다.

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Online Human Tracking Based on Convolutional Neural Network and Self Organizing Map for Occupancy Sensors (점유 센서를 위한 합성곱 신경망과 자기 조직화 지도를 활용한 온라인 사람 추적)

  • Gil, Jong In;Kim, Manbae
    • Journal of Broadcast Engineering
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    • v.23 no.5
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    • pp.642-655
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    • 2018
  • Occupancy sensors installed in buildings and households turn off the light if the space is vacant. Currently PIR(pyroelectric infra-red) motion sensors have been utilized. Recently, the researches using camera sensors have been carried out in order to overcome the demerit of PIR that cannot detect stationary people. The detection of moving and stationary people is a main functionality of the occupancy sensors. In this paper, we propose an on-line human occupancy tracking method using convolutional neural network (CNN) and self-organizing map. It is well known that a large number of training samples are needed to train the model offline. To solve this problem, we use an untrained model and update the model by collecting training samples online directly from the test sequences. Using videos capurted from an overhead camera, experiments have validated that the proposed method effectively tracks human.

Assessing applicability of self-organizing map for regional rainfall frequency analysis in South Korea (Self-organizing map을 이용한 강우 지역빈도해석의 지역구분 및 적용성 검토)

  • Ahn, Hyunjun;Shin, Ju-Young;Jeong, Changsam;Heo, Jun-Haeng
    • Journal of Korea Water Resources Association
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    • v.51 no.5
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    • pp.383-393
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    • 2018
  • The regional frequency analysis is the method which uses not only sample of target station but also sample of neighborhood stations in which are classified as hydrological homogeneous regions. Consequently, identification of homogeneous regions is a very important process in regional frequency analysis. In this study, homogeneous regions for regional frequency analysis of precipitation were identified by the self-organizing map (SOM) which is one of the artificial neural network. Geographical information and hourly rainfall data set were used in order to perform the SOM. Quantization error and topographic error were computed for identifying the optimal SOM map. As a result, the SOM model organized by $7{\times}6$ array with 42 nodes was selected and the selected stations were classified into 6 clusters for rainfall regional frequency analysis. According to results of the heterogeneity measure, all 6 clusters were identified as homogeneous regions and showed more homogeneous regions compared with the result of previous study.

Big Data Analysis of Financial Product Transaction Trends Using Associated Analysis (연관분석을 이용한 금융 상품 거래 동향의 빅데이터 분석)

  • Ryu, Jae Pil;Shin, Hyun-Joon
    • Journal of the Korea Convergence Society
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    • v.12 no.12
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    • pp.49-57
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    • 2021
  • With the advent of the era of the fourth industry, more and more scientific techniques are being used to solve decision-making problems. In particular, big data analysis technology is developing as it becomes easier to collect numerical data. Therefore, in this study, in order to overcome the limitations of qualitatively analyzing investment trends, the association of various products was analyzed using associated analysis techniques. For the experiment, two experimental periods were divided based on the COVID-19 economic crisis, and sales information from individuals, institutions, and foreign investors was collected, and related analysis algorithms were implemented through r software. As a result of the experiment, institutions and foreigners recently invested in the KOSPI and KOSDAQ markets and bought futures and products such as ETF. Individuals purchased ETN and ETF products together, which is presumed to be the result of the recent great interest in sector investment. In addition, after COVID-19, all investors tended to be passive in investing in high-risk products of futures and options. This paper is thought to be a useful reference for product sales and product design in the financial field.

A Study on Clustering Representative Color of Natural Environment of Korean Peninsula for Optimal Camouflage Pattern Design (최적 위장무늬 디자인을 위한 한반도 자연환경 대표 색상 군집화 연구)

  • Chun, Sungkuk;Kim, Hoemin;Yoon, Seon Kyu;Yun, Jeongrok;Kim, Un Yong
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2019.07a
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    • pp.315-316
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    • 2019
  • 전투복, 군용 천막 등에 사용되는 위장무늬는 군 작전 수행 시 주변 환경의 색상, 패턴을 모사하여 개인병사 및 무기체계의 위장 기능을 극대화하고, 이를 통해 아군의 생명과 시설피해를 최소화하기 위한 목적으로 사용된다. 특히 최근 들어 군의 작전환경과 임무가 복잡하고 다양해짐에 따라, 작전환경에 대한 데이터의 취득 및 정량적 분석을 통해 전장 환경에 최적화된 위장무늬 패턴 및 색상 추출에 대한 연구의 필요성이 증대되고 있다. 본 논문에서는 한반도 자연환경 영상에 대한 자기 조직화 지도(SOM, Self-organizing Map) 기반의 한반도 자연환경 대표 색상 군집화 연구 방법에 대해 서술한다. 이를 위해 한반도 내 위도를 고려한 장소에서 시간별, 계절별 자연환경 영상 수집을 진행하며, 수집된 영상 내 다수의 화소의 군집화를 위해 2차원 SOM을 활용한다. 영상 내 각 화소의 색상 값에 대한 SOM의 학습 시, RGB공간상의 색차/색상 인지 왜곡을 피하기 위하여 CIEDE2000 색차 식을 통해 군집화를 진행한다. 실험결과에서는 온라인상으로 수집한 여름 및 가을철 대표 색상 군집화 결과와, 현재까지 수집된 계절별 자연환경 사진 내 6억 7648개 화소에 대한 대표 색상 군집화 결과를 보여준다.

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Parallel Implementations of the Self-Organizing Network for Normal Mixtures (병렬처리를 통한 정규혼합분포의 추정)

  • Lee, Chul-Hee;Ahn, Sung-Mahn
    • Communications for Statistical Applications and Methods
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    • v.19 no.3
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    • pp.459-469
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    • 2012
  • This article proposes a couple of parallel implementations of the self-organizing network for normal mixtures. In principle, self-organizing networks should be able to be implemented in a parallel computing environment without issue. However, the network for normal mixtures has inherent problem in being operated parallel in pure sense due to estimating conditional expectations of the mixing proportion in each iteration. This article shows the result of the parallel implementations of the network using Java. According to the results, both of the implementations achieved a faster execution without any performance degradation.

A Study on the Level of Self-regulated Learning Ability for Engineering College Students (공과대학 학생들의 자기조절 학습능력 수준에 관한 연구)

  • Shin, Min-Hee
    • Journal of Engineering Education Research
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    • v.12 no.4
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    • pp.84-92
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    • 2009
  • The purpose of this study was to investigate the level of self-regulated learning ability for engineering students. Self-regulated learning theory has been studied as the theoretical background and assessment framework explaining life-long ability. A survey was conducted to engineering students from an engineering-centered university, located in Seoul. The research findings were as follows. First, each mean of cognitive regulation, motivation regulation, and behavior regulation was 3.041, 3.051, and 2.996 respectively, indicating that the scores were not high. Second, there was no significant difference in the mean score of self-regulated learning ability between female and male students. Third, students in ABEEK accredited program scored meaningfully higher than students in non-accredited program on only 3 sub-components of organization strategy, metacognition, and task value. Fourth, senior students scored meaningfully higher than 1st year students on only 3 sub-components of metacognition, intrinsic motivation, learning environment management. The results revealed that instructional interventions should be provided for engineering students to develop self-regulated learning ability.

Certificate Issuing using Proxy Signature and Threshold Signature in Self-initialized Ad Hoc Network (자기 초기화하는 Ad Hoc 네트워크에서의 대리 서명과 임계 서명 기법을 이용한 인증서 발급 기법)

  • Kang, Jeon-Il;Choi, Young-Geun;Kim, Koon-Soon;Nyang, Dae-Hun
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.17 no.3
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    • pp.55-67
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    • 2007
  • In ad hoc network, especially in the environment which the system authority only exists at the beginning of the network, it is very important problem how to issue the certificates in self-initialized public key scheme that a node generates its certificate with public and private key pair and is signed that by the system authority. In order to solve this problem, early works present some suggestions; remove the system authority itself and use certificate chain, or make nodes as system authorities for other nodes' certificates. In this paper, we suggest another solution, which can solve many problem still in those suggestions, using proxy signature and threshold signature, and prove its performance using simulation and analyse its security strength in many aspects.