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Robot Knowledge Framework of a Mobile Robot for Object Recognition and Navigation (이동 로봇의 물체 인식과 주행을 위한 로봇 지식 체계)

  • Lim, Gi-Hyun;Suh, Il-Hong
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.44 no.6
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    • pp.19-29
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    • 2007
  • This paper introduces a robot knowledge framework which is represented with multiple classes, levels and layers to implement robot intelligence at real environment for mobile robot. Our root knowledge framework consists of four classes of knowledge (KClass), axioms, rules, a hierarchy of three knowledge levels (KLevel) and three ontology layers (OLayer). Four KClasses including perception, model, activity and context class. One type of rules are used in a way of unidirectional reasoning. And, the other types of rules are used in a way of bi-directional reasoning. The robot knowledge framework enable a robot to integrate robot knowledge from levels of its own sensor data and primitive behaviors to levels of symbolic data and contextual information regardless of class of knowledge. With the integrated knowledge, a robot can have any queries not only through unidirectional reasoning between two adjacent layers but also through bidirectional reasoning among several layers even with uncertain and partial information. To verify our robot knowledge framework, several experiments are successfully performed for object recognition and navigation.

A Detection Model using Labeling based on Inference and Unsupervised Learning Method (추론 및 비교사학습 기법 기반 레이블링을 적용한 탐지 모델)

  • Hong, Sung-Sam;Kim, Dong-Wook;Kim, Byungik;Han, Myung-Mook
    • Journal of Internet Computing and Services
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    • v.18 no.1
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    • pp.65-75
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    • 2017
  • The Detection Model is the model to find the result of a certain purpose using artificial intelligent, data mining, intelligent algorithms In Cyber Security, it usually uses to detect intrusion, malwares, cyber incident, and attacks etc. There are an amount of unlabeled data that are collected in a real environment such as security data. Since the most of data are not defined the class labels, it is difficult to know type of data. Therefore, the label determination process is required to detect and analysis with accuracy. In this paper, we proposed a KDFL(K-means and D-S Fusion based Labeling) method using D-S inference and k-means(unsupervised) algorithms to decide label of data records by fusion, and a detection model architecture using a proposed labeling method. A proposed method has shown better performance on detection rate, accuracy, F1-measure index than other methods. In addition, since it has shown the improved results in error rate, we have verified good performance of our proposed method.

Processing of the Syntactic Ambiguity Resolution in English as a Foreign Language (외국어로서의 영어 구문 중의성 해결 과정)

  • 정유진;이윤형;황유미;남기춘
    • Proceedings of the Korean Society for Cognitive Science Conference
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    • 2000.05a
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    • pp.261-266
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    • 2000
  • 글을 이해하기 위해서는 어휘와 어휘간의 연결 및 전체 구조를 아는 것이 필요하다. 이는 비단 한국어뿐만 아니라 영어나 기타 다른 외국어에서도 마찬가지일 것이다. 본고는 두 가지를 고찰하기 위해 진행되었는데 우선 외국어로서 영어를 처리하는데 발생하는 구문적 중의성을 해결하는데 Garden Path Sentence(GPS), Late Closure(LC), PP의 세 문형에 따라 어떻게 해결하는지 알아보기 위한 것이다. 그리고 각 문형의 중의적 어절에서의 반응과 애매성 해소 어절에서의 반응에 따라 sysntactic module이 작용하는 것인지 알아보고자 한다. 예를 들어 "The boat floated down the streams sank"란 Garden Path 문장이 제시된 경우에 독자는 "sank"란 어휘가 제시되기 전까지 "floated"를 동사로 생각하게 되나 다음에 본동사인 "sank"가 제시될 경우 문장의 해석에 혼란을 갖게 될 것이다. 예문에서 "floated"가 문장에서 어떤 역할을 하는지 결정하는 것은 "sank"를 보고서야 가능하다. 이런 구문적 중의성을 해결하는 방식을 알아보기 위해 어절 단위로 제시된 자극을 읽는 자기 조절 읽기 과제(self-paced reading task)를 사용하였다. 각 어절을 읽는데 걸리는 시간을 측정한 실험 결과 GPS, PP, LC 모두 중의성을 지닌 영역이 중의성을 해소한 후와 각각 유형적으로 큰 차이가 없는 것으로 나타났다. 다만 GPS, CGPS, PP와 CPP는 어절 후반으로 갈수록 반응시간이 짧아졌다. 이는 우리나라 사람의 경우 외국어인 영어의 구문 중의성 해소는 구문 분석 단원(syntactic module)에 의한 자동적 처리라기보다 의미를 고려해 가면서 문법지식을 이용해 추론을 통한 구문 분석이라 할 수 있다.에 의한 자동적 처리라기보다 의미를 고려해 가면서 문법지식을 이용해 추론을 통한 구문 분석이라 할 수 있다.많았다(P<0.05).조군인 Group 1에서보다 높은 수준으로 발현되었다. 하지만 $12.5{\;}\mu\textrm{g}/ml$의 T. denticola sonicated 추출물로 전처리한 Group 3에서는 IL-2와 IL-4의 수준이 유의성있게 억제되어 발현되었다 (p < 0.05). 이러한 결과를 통하여 T. denticola에서 추출된 면역억제 단백질이 Th1과 Th2의 cytokine 분비 기능을 억제하는 것으로 확인 되었으며 이 기전이 감염 근관에서 발견되는 T. denticola의 치수 및 치근단 질환에 대한 병인기전과 관련이 있는 것으로 사료된다.을 보였다. 본 실험 결과, $Depulpin^{\circledR}은{\;}Tempcanal^{\circledR}와{\;}Vitapex^{\circledR}$에 비해 높은 세포 독성을 보여주공 있으나, 좀 더 많은 임상적 검증이 필요할 것으로 사료된다.중요한 역할을 하는 것으로 추론할 수 있다.근관벽을 처리하는 것이 필요하다고 사료된다.크기에 의존하며, 또한 이러한 영향은 $(Ti_{1-x}AI_{x})N$ 피막에 존재하는 AI의 함량이 높고, 초기에 증착된 막의 업자 크기가 작을 수록 클 것으로 여겨진다. 그리고 환경의 의미의 차이에 따라 경관의 미학적 평가가 달라진 것으로 나타났다.corner$적 의도에 의한 경관구성의 일면을 확인할수 있지만 엄밀히 생각하여 보면 이러한 예의 경우도 최락의 총체적인 외형은 마찬가지로 $\ulcorner$순응$\lrcorner$의 범위를 벗어나지 않는다. 그렇기 때문에도 $\ulcorner$순응$\lrcorner$$\ulcorner$표현$\lrcorner$의 성격과 형태를 외형상으로 더욱이 공간상에서는 뚜렷하게 경계

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A New Memory-based Learning using Dynamic Partition Averaging (동적 분할 평균을 이용한 새로운 메모리 기반 학습기법)

  • Yih, Hyeong-Il
    • Journal of the Korean Institute of Intelligent Systems
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    • v.18 no.4
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    • pp.456-462
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    • 2008
  • The classification is that a new data is classified into one of given classes and is one of the most generally used data mining techniques. Memory-Based Reasoning (MBR) is a reasoning method for classification problem. MBR simply keeps many patterns which are represented by original vector form of features in memory without rules for reasoning, and uses a distance function to classify a test pattern. If training patterns grows in MBR, as well as size of memory great the calculation amount for reasoning much have. NGE, FPA, and RPA methods are well-known MBR algorithms, which are proven to show satisfactory performance, but those have serious problems for memory usage and lengthy computation. In this paper, we propose DPA (Dynamic Partition Averaging) algorithm. it chooses partition points by calculating GINI-Index in the entire pattern space, and partitions the entire pattern space dynamically. If classes that are included to a partition are unique, it generates a representative pattern from partition, unless partitions relevant partitions repeatedly by same method. The proposed method has been successfully shown to exhibit comparable performance to k-NN with a lot less number of patterns and better result than EACH system which implements the NGE theory and FPA, and RPA.

The Impact of Technology Innovation Capacity and Social Capital on Non-Financial Performance - For small and medium-sized businesses in the metropolitan area - (기술혁신역량과 사회적 자본이 비재무성과에 미치는 영향 - 수도권 중소기업을 대상으로 -)

  • Ryu, Gil-Ho;Yi, Seon-Gyu
    • Journal of Convergence for Information Technology
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    • v.9 no.11
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    • pp.92-102
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    • 2019
  • This study analyzed the effect of technology innovation capacity and social capital on the non-financial performance of SMEs in the metropolitan area. Technology innovation capacity is defined as R & D capacity and technology accumulation capacity, and social capital is defined as interaction, goal sharing, and member trust. The samples were collected through a survey conducted in-person and through telephone calls, e-mail, and fax. The sample data used for analysis was 223 copies. Analysis results showed that R & D capacity and technology accumulation capacity (for technology innovation capacity) and interaction and member trust (for social capital) were variables that significantly affect non-financial performance, but not goal sharing. The findings of this study were as follows. First, despite lacking sufficient technology or capital, SMEs are constantly engaging in innovation to survive in the competitive market environment. Second, the members of SMEs make considerable efforts to achieve performance based on interaction and member trust, however, they hold a negative perception toward sharing the goals pursued by their company.

A Study on Performance Improvement of Recurrent Neural Networks Algorithm using Word Group Expansion Technique (단어그룹 확장 기법을 활용한 순환신경망 알고리즘 성능개선 연구)

  • Park, Dae Seung;Sung, Yeol Woo;Kim, Cheong Ghil
    • Journal of Industrial Convergence
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    • v.20 no.4
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    • pp.23-30
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    • 2022
  • Recently, with the development of artificial intelligence (AI) and deep learning, the importance of conversational artificial intelligence chatbots is being highlighted. In addition, chatbot research is being conducted in various fields. To build a chatbot, it is developed using an open source platform or a commercial platform for ease of development. These chatbot platforms mainly use RNN and application algorithms. The RNN algorithm has the advantages of fast learning speed, ease of monitoring and verification, and good inference performance. In this paper, a method for improving the inference performance of RNNs and applied algorithms was studied. The proposed method used the word group expansion learning technique of key words for each sentence when RNN and applied algorithm were applied. As a result of this study, the RNN, GRU, and LSTM three algorithms with a cyclic structure achieved a minimum of 0.37% and a maximum of 1.25% inference performance improvement. The research results obtained through this study can accelerate the adoption of artificial intelligence chatbots in related industries. In addition, it can contribute to utilizing various RNN application algorithms. In future research, it will be necessary to study the effect of various activation functions on the performance improvement of artificial neural network algorithms.

Quantitative assessment of spalling depth and width using statistical inference theory in underground openings (통계추론을 이용한 지하암반공동에서의 스폴링 깊이와 폭에 대한 정량적 평가)

  • Bang, Joon-Ho;Lee, In-Mo
    • Journal of Korean Tunnelling and Underground Space Association
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    • v.12 no.1
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    • pp.1-14
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    • 2010
  • Until now, the evaluation method of spalling depth using Martin et al. (1999)'s linear regression relations has long been known applicable. However, it is not likely that the proposed equation is applicable to the openings other than circular type and mostly overpredict the spalling depth in comparison with actual spalling cases. Moreover, the evaluation method to estimate the spalling width has not been presented yet; it is essential to evaluate the spalling width in addition to the spalling depth, because the shape of the spalled region influences the choice of suitable rock reinforcement. In this study, linear regression equations, in which normalized spalling depth ($d_f/W_D$) and normalized spalling width ($w_f/W_D$) are functions of three spalling evaluation indices, ${\sigma}_1/{\sigma}_c,\;D_{is}(={\sigma}_{max}/{\sigma}_c)$ and ${\sigma}_{dev}/{\sigma}_{cm}$, are established based on in-situ spalling observations and CWFS simulation results. Confidence intervals of 95% using the statistical inference theory are used in verifying the reliability of linear regression equations. Spalling depth ($d_f$) and spalling width ($w_f$) predicted from the proposed linear regression relations, which take three spalling evaluation indices into account, showed reasonable match with in-situ observations by adopting weighting factors considering the degree of variance of linear regression relations.

Conceptual Cost Estimating System Development for Public Apartment Projects (공공아파트 프로젝트 기획단계 공사비 산정시스템 개발)

  • Lee, Hyun-Soo;Lee, Heung-Keun;Park, Moon-Seo;Kim, Soo-Young;Ahn, Jo-Seph
    • Korean Journal of Construction Engineering and Management
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    • v.13 no.4
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    • pp.152-163
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    • 2012
  • At the conceptual phase of a construction project, estimated construction cost is very important as it significantly influences the owner's decision-making. Accurate cost estimating, in the early stage of a public construction project, serves as a critical factor because initial decision-making effects the final cost of a construction project. However in the cases of Korean public apartment projects, excluding a few of the public owners, there is a problem in properly estimating construction cost due to the lack of construction cost estimating system. Thus, this research developed a public apartment cost estimating system using case-based reasoning that was suggested by a previous research with 66 cases of Korean public apartment projects. Based on the system experiments involving 19 public officers and 10 cases of Korean public apartment projects, the effectiveness of the system in terms of estimation accuracy and user-friendly was confirmed. As a result, the developed system has an error range of 1.47% to 13.74% and mean of 6.15%. In addition, the system was evaluated that it could greatly improve the current estimation task of public officers. Consequently, the results of this research can be used as a foundation for a technological advance in estimating construction cost and improving the accuracy and consistency of construction cost estimation.

Stream Discharge Estimation by Runoff Component Analysis on the Control Point (유출성분 분석에 의한 제어지점의 유출량 산정)

  • Lee, Sang-Jin;Hwang, Man-Ha;Lee, Bae-Sung;Park, Joo-Seong
    • Proceedings of the Korea Water Resources Association Conference
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    • 2006.05a
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    • pp.785-789
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    • 2006
  • 유역 수자원의 효율적인 관리 및 배분을 위해서는 세밀한 강우-유출관계의 규명이 무엇보다 중요하다. 이를 위해서는 먼저 하천 유출지점의 정확한 유량정보가 획득되어야 하며, 장기간에 걸쳐 신뢰성 있는 유량자료의 확보는 더욱 중요한 사항이다. 본 연구에서는 하천에서 관측된 유량자료를 장기간(1983년${\sim}$2004년)에 걸친 유출성분으로 분리하는 기법을 활용하여 제어지점의 유출량을 검증하였다. 유량자료를 출구지점의 관측유량$(Q_{ob})$을 회귀수$({\alpha}Q_e)$, 상류유입량$(Q_{up})$ 및 관측강우-유출량$({\beta}Q_{Rain})$의 성분으로 구분하여 산정하는 방식으로 유출량을 추정하였다. 여기서, 회귀수$({\alpha}Q_e)$란 유역 및 하도내 용수이용량의 회귀수, 상류유입량$(Q_{up})$은 상류 유출 제어지점의 관측유량으로 대청댐 방류량, 관측강우-유출량$({\beta}Q_{Rain})$은 유역내 강우에 의한 자연유출량이다. 여기서 사용된 수문기초자료는 대청댐 방류량, 대전 및 청주권 취수량, 강우에 의한 자연유출량, 공주관측유량 등으로 각 성분별로 생성된 일자료를 이용하여 공주지점의 월별, 분기별, 년도별 유출량을 산정하였다. 이 결과는 금강유역에 이미 구축되어있는 SSARR모형을 기반으로 한 RRFS(Rainfall Runoff Forecasting System, 유출예측 시스템)의 결과 및 관측치와 비교되었다. 계산결과 RRFS에 의한 유출량과 대청-공주구간의 유출성분분리에 의한 유출량은 관측값과 전반적으로 근사함을 확인하였으며, 검증지점의 정확한 유출율을 산정할 수 있다면, 관측자료의 연속성 및 신뢰도를 파악하는 척도를 제공할 수 있을 것으로 판단된다.측결과 있는 대상유역에 대한 적용이 요구된다.-Moment 방법에 의해 추정된 매개변수를 사용한 Power 분포를 적용하였으며 이들 분포의 적합도를 PPCC Test를 사용하여 평가해봄으로써 낙동강 유역에서의 저수시의 유출량 추정에 대한 Power 분포의 적용성을 판단해 보았다. 뿐만 아니라 이와 관련된 수문요소기술을 확보할 수 있을 것이다.역의 물순환 과정을 보다 명확히 규명하고자 노력하였다.으로 추정되었다.면으로의 월류량을 산정하고 유입된 지표유량에 대해서 배수시스템에서의 흐름해석을 수행하였다. 그리고, 침수해석을 위해서는 2차원 침수해석을 위한 DEM기반 침수해석모형을 개발하였고, 건물의 영향을 고려할 수 있도록 구성하였다. 본 연구결과 지표류 유출 해석의 물리적 특성을 잘 반영하며, 도시지역의 복잡한 배수시스템 해석모형과 지표범람 모형을 통합한 모형 개발로 인해 더욱 정교한 도시지역에서의 홍수 범람 해석을 실시할 수 있을 것으로 판단된다. 본 모형의 개발로 침수상황의 시간별 진행과정을 분석함으로써 도시홍수에 대한 침수위험 지점 파악 및 주민대피지도 구축 등에 활용될 수 있을 것으로 판단된다. 있을 것으로 판단되었다.4일간의 기상변화가 자발성 기흉 발생에 영향을 미친다고 추론할 수 있었다. 향후 본 연구에서 추론된 기상변화와 기흉 발생과의 인과관계를 확인하고 좀 더 구체화하기 위한 연구가 필요할 것이다.게 이루어질 수 있을 것으로 기대된다.는 초과수익률이 상승하지만, 이후로는 감소하므로, 반전거래전략을 활용하는 경우 주식투자기간은 24개월이하의 중단기가 적합함을 발견하였다. 이상의 행태적 측면과 투자성과측면의 실증결과를 통하여 한국주식시장에 있어서 시장수익률을 평균적으로 초과할 수 있는 거래전략은 존재하므로 이러한 전략을 개발 및 활용할 수 있으며, 특히, 한국주식시장에 적합한 거래전략은 반전거래전략이고, 이 전략의 유용성은 투자자가 설정한 투자기간보다 더욱 긴

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Exploring Teachers' Responsive Teaching Practice in Argumentation-Based Science Classroom: Focus on Structural and Dialogical Aspects of Argument (논변 활동 중심 과학 수업에서 교사의 반응적 교수 실행 탐색 -논변의 구조적·대화적 측면을 중심으로-)

  • Park, Jiyoung;Kim, Heui-Baik
    • Journal of The Korean Association For Science Education
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    • v.38 no.1
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    • pp.69-85
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    • 2018
  • The purpose of this study is to explore teachers' responsive moves that affect students' argumentation practices, and to propose responsive teaching strategies in argumentation-based science classroom. Two teachers, who have not implemented argumentation in their classes, and 57 students, participated in this study. We recorded and transcribed their classes and interviews for the analysis. According to grounded theory approach, we categorized the teachers' responsive moves as focused on either structural or dialogical aspects of argumentation, and qualitatively analyzed their responsive teaching practices in classes. We discovered that the teachers mostly responded to structural rather than dialogical aspects of argumentation, particularly during the students' small-group discussions. This was mainly due to their instructional goals, which focused on the structural aspect of argumentation, and the limited time available for supporting small-groups. Regarding the structural aspects, those responsive moves that explored the students' thinking or facilitated their reasoning helped them to share their thinking and justify their arguments further with recognition of learning goals in the argumentation activities. Regarding the dialogical aspects, which were seen mostly in whole-class discussions, the moves that underlined similarities and differences between arguments, facilitated the sharing of a small-group's arguments with the entire class, or asked a specific student to evaluate the arguments were notable. These moves supported clarification of various small-groups' arguments, which led to reconstruction of coherent argument through evaluation and rebuttal of these arguments, consequentially facilitating dialogical interactions. Based on these results, we proposed responsive teaching strategies in an argumentation-based science classroom.