• Korean Journal of Cognitive Science
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• v.15 no.2
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• pp.1-15
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• 2004

The structure of sensibility from motion was developed for the purpose of understanding relationship between sensibilities and physical factors to apply it to dynamic visual display. Seventy adjectives were collected by assessing adequacy to express sensibilities from motion and reporting sensibilities recalled from dynamic displays with achromatic color. Various motion displays with a moving single dot were rated according to the degree of sensibility corresponding to each adjective, on the basis of the Semantic Differential (SD) method. The results of assessment were analyzed by means of the factor analysis to reduce 70 words into 19 fundamental sensibilities from motion. The Multidimensional Scaling (MDS) technique constructed the sensibility space in motion, in which 19 sensibilities were scattered with two dimensions, active-passive and bright-dark Motion types systemically varied in kinematic factors were placed on the two-dimensional space of motion sensibility, in order to analyze important variables affecting sensibility from motion. Patterns of placement indicate that speed and both of cycle and amplitude in trajectories tend to partially determine sensibility. Although color and motion affected sensibility according to the in dimensions, it seemed that combination of motion and color made each have dominant effect individually in a certain sensibility dimension, motion to active-passive and color to bright-dark.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2003.04a
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• pp.239-246
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• 2003

BPR(Business Process Re-engineering)은 업무 프로세스를 혁신적으로 재설계 함으로써 급속한 외부환경과 내부환경의 변화에 능동적으로 대처하고자 하는 기업의 경영혁신 기법, 조직 재설계의 수단으로 도입되었다. 해마다 시행되고 있는 정보화평가위원회의 국가 정보화 사업에 대한 평가는 정보화 사업의 성과관리에 있어 BPR에 따른 조직과 제도개선 성과를 포함하여 제도혁신에 대한 인센티브 제공 둥 조직과 제도혁신 강화의 필요성이 강하게 주장되는 등 BPR은 공공부문으로 점차 확대 될 추세이다. 본 연구는 조직적 문제의 해결을 통하여 지방자치단체 GIS의 효율성을 제고 하고자 하는 목적으로 출발하였다. 따라서 BPR의 이론적 고찰을 통하여 지자체 GIS BPR의 개념을 정의하고, 지방자치단체의 GIS 시스템 도입 이후의 업무 프로세스의 변화, 업무 변화의 양상, 잠재적 업무 효과를 BPR의 기법을 통해 보여줌으로써 조직 재설계의 수단으로 GIS BPR의 가능성을 모색하였다. 이는 GIS 발달 단계에 따른 효과 창출의 패러다임을 고려한 지방자치단체 GIS 업무의 변화를 수용하는 능동적이고 융통성 있는 조직 모형을 찾는 것이라 할 수 있다. 따라서 단위조직, 진화조직, 전체조직의 GIS 발달 단계에 따른 지방자치단체 GIS 조직 모형을 규정하였다. 본 연구를 통한 시사점은 지방자치단체 GIS 조직이 현재의 단위조직 수준에서 진화조직의 단계를 걸쳐 전체조직으로 향하는 가능성을 제시했다는 점이다. 이는 지방자치단체가 각각의 단계에서 GIS의 도입 효과를 창출하기 위하여 충실히 수행해 할 것이 무엇인지를 BPR을 통해 조직적 차원에서, 그리고 조직이 다루는 업무영역의 차원에서 접근했다는 점에서 그 의의가 있다. 본 연구의 결과를 통해 지방자치단체 GIS 기본계획에 있어 조직 측면의 장기적 비전의 제시가 가능하며 이를 통해 보다 성숙된 GIS 사업의 추진과 효율적인 시스템의 운영이 가능할 것이다.. 이상의 결과를 종합해볼 때, ${\beta}$-glucan은 고용량일 때 직접적으로 또는 $IFN-{\gamma}$ 존재시에는 저용량에서도 복강 큰 포식세로를 활성화시킬 뿐 아니라, 탐식효율도 높임으로써 면역기능을 증진 시키는 것으로 나타났고, 그 효과는 crude ${\beta}$-glucan의 추출조건에 따라 달라지는 것을 알 수 있었다.eveloped. Design concepts and control methods of a new crane will be introduced in this paper.and momentum balance was applied to the fluid field of bundle. while the movement of′ individual material was taken into account. The constitutive model relating the surface force and the deformation of bundle was introduced by considering a representative prodedure that stands for the bundle movement. Then a fundamental equations system could be simplified considering a steady state of the process. On the basis of the simplified model, the simulation was performed and the results could be confirmed by the experiments under various conditions.뢰, 결속 등 다차원의 개념에 대한 심도 깊은 연구와 최근 제기되고 있는 이론의 확대도 필요하다. 마지막으로 신뢰와 결속에 영향을 미치는 요소간의 개념적 분류, 차이의 검증, 영향력 등

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.46 no.11
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• pp.1-11
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• 2009

A content based pub/sub (Publish/subscribe) services at the peer-to-peer network has the requirements about how to distribute contents information of subscriber and to delivery the events efficiently. For satisfying the requirements, a DHT(Distributed Hash Table) based pub/sub overlay networking and tree type topology based network construction using filter technique have been proposed. The DHT based technique is suitable for topic based pub/sub service but it's not good contents based service that has the variable requirements. And also filter based tree topology networking is not efficient at the environment where the user requirements are distributed. In this paper we propose the R-Tree algorithm based pub/sub overlay network construction method. The proposed scheme provides cost effective event delivery method by mapping user requirement to multi-dimension and hierarchical grouping of the requirements. It is verified by simulation at the variable environment of user requirements and events.

• Smart Media Journal
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• v.10 no.1
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• pp.16-24
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• 2021

The exiting word embedding methodology such as word2vec represents words, which only occur in the raw training corpus, as a fixed-length vector into a continuous vector space, so when mapping the words incorporated in the raw training corpus into a fixed-length vector in morphologically rich language, out-of-vocabulary (OOV) problem often happens. Even for sentence embedding, when representing the meaning of a sentence as a fixed-length vector by synthesizing word vectors constituting a sentence, OOV words make it challenging to meaningfully represent a sentence into a fixed-length vector. In particular, since the agglutinative language, the Korean has a morphological characteristic to integrate lexical morpheme and grammatical morpheme, handling OOV words is an important factor in improving performance. In this paper, we propose parallel Tri-LSTM sentence embedding that is robust to the OOV problem by extending utilizing the morphological information of words into sentence-level. As a result of the sentiment analysis task with corpus in Korean, we empirically found that the character unit is better than the morpheme unit as an embedding unit for Korean sentence embedding. We achieved 86.17% accuracy on the sentiment analysis task with the parallel bidirectional Tri-LSTM sentence encoder.

• Journal of Service Research and Studies
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• v.12 no.3
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• pp.1-25
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• 2022

This study was conducted for technology development and industrial and enterprise system design for the sustainable life of mankind. Human society is facing a crisis. As the power of mankind has increased due to the development of nuclear weapons and information and communication technologies, the risk of human society has greatly increased. The value of growth and freedom is increasing due to capitalism and democratic systems, so technological innovation is accelerating, and industries and companies are growing significantly. New technologies and industries can greatly develop human society and put it at risk. This study was conducted with the aim of redesigning technology, industry, and enterprise systems so that humans who live on Earth can be more sustainable for a longer time. It presented a practical alternative for a long-term sustainable human society. It suggested alternatives for what philosophy and methodology should be developed for the whole of humanity and in each individual national society, for developing technologies, fostering industries, and operating corporate systems. First of all, the problems of the technology development system, industrial system, and enterprise system of human society were analyzed. The characteristics and problems were analyzed in terms of sustainability of human society. The necessary and sufficient conditions for an alternative system to solve the raised problems were derived. A system that satisfies these conditions was designed and presented. The alternative system was named as a servicism system as a system based on the service philosophy. The structure, operation model, and implementation plan of the new technology industry enterprise system were presented. In the future, follow-up studies are needed to be concreted at the level of individual countries and human society as a whole.

• The Korean Journal of Applied Statistics
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• v.37 no.1
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• pp.1-12
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• 2024

In many real-world data, multiple response variables are often dependent on the same set of explanatory variables. In particular, if several response variables are correlated with each other, simultaneous estimation considering the correlation between response variables might be more effective way than individual analysis by each response variable. In this multivariate regression analysis, least distance estimator (LDE) can estimate the regression coefficients simultaneously to minimize the distance between each training data and the estimates in a multidimensional Euclidean space. It provides a robustness for the outliers as well. In this paper, we examine the least distance estimation method in multivariate linear regression analysis, and furthermore, we present the penalized least distance estimator (PLDE) for efficient variable selection. The LDE technique applied with the adaptive group LASSO penalty term (AGLDE) is proposed in this study which can reflect the correlation between response variables in the model and can efficiently select variables according to the importance of explanatory variables. The validity of the proposed method was confirmed through simulations and real data analysis.

• The KIPS Transactions:PartA
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• v.11A no.4
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• pp.243-250
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• 2004

Monitoring is used to see if a real-time system provides a service on time. Generally, monitoring for real-time focuses on investigating the current status of a real-time system. To support a stable performance of a real-time system, it should have not only a function to see the current status of real-time process but also a function to predict executions of real-time processes, however. The legacy prediction model has some limitation to apply it to a real-time monitoring. First, it performs a static prediction after a real-time process finished. Second, it needs a statistical pre-analysis before a prediction. Third, transition probability and data about clustering is not based on the current data. We propose the execution prediction model based on learning algorithm to solve these problems and apply it to real-time monitoring. This model gets rid of unnecessary pre-processing and supports a precise prediction based on current data. In addition, this supports multi-level prediction by a trend analysis of past execution data. Most of all, We designed the model to support dynamic prediction which is performed within a real-time process' execution. The results from some experiments show that the judgment accuracy is greater than 80% if the size of a training set is set to over 10, and, in the case of the multi-level prediction, that the prediction difference of the multi-level prediction is minimized if the number of execution is bigger than the size of a training set. The execution prediction model proposed in this model has some limitation that the model used the most simplest learning algorithm and that it didn't consider the multi-regional space model managing CPU, memory and I/O data. The execution prediction model based on a learning algorithm proposed in this paper is used in some areas related to real-time monitoring and control.