• Electronics and Telecommunications Trends
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• v.16 no.4 s.70
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• pp.87-95
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• 2001

IP 기술은 개방성과 유연성, 규모성 등에서 많은 장점을 가지나 비 연결성의 최선형 서비스로 차후 활성화 될 실시간 멀티미디어 서비스를 수용하기에는 아직도 많은 문제점이 있다. 그 대표적인 예가, QoS와 이동성 제공 및 무선구간에서의 오버헤드 문제 등이다. 본 고에서는 기존의 Mobile IP 방법과는 다른 새로운 마이크로 이동성 기술을 다루기 위하여 최근 신설된 IETF의 SeaMoby WG의 표준화 동향에 대하여 최근까지 작성된 문서를 중심으로 살펴본다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.44 no.3
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• pp.407-416
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• 2024

Over the past 20 years, there has been a rapid increase in the number and size of subway stations and underground structures worldwide, and the importance of safety for subway users has also continuously grown. Subway stations, due to their structural characteristics, have limited visibility and escape routes in disaster situations, posing a high risk of human casualties and economic losses. Therefore, an analysis of disaster vulnerabilities is essential not only for existing subway systems but also for deep underground facilities like GTX. This paper presents a case study applying a betweenness centrality-based disaster vulnerability analysis framework to the case of Gwanggyo Central Station. The analysis of Gwanggyo Central Station's base model and various disaster scenarios revealed that the betweenness centrality distribution is symmetrical, following the symmetrical spatial structure of the station, with high centrality concentrated in the central areas of basement levels one and two. These areas exhibited values more than 220% above the average, indicating a high likelihood of bottleneck phenomena during evacuation in disaster situations. To mitigate this vulnerability, scenarios were proposed to distribute evacuation flows concentrated in the central areas, enhancing the usability of peripheral areas as evacuation routes by connecting staircases continuously. This modification, when considered, showed a decrease in centrality concentration, confirming that the proposed addition of evacuation paths could effectively contribute to dispersing the flow of evacuation in Gwanggyo Central Station. This case study demonstrates the effectiveness of the proposed framework for assessing evacuation vulnerability in enhancing subway station user safety and can be effectively applied in disaster response and management plans for major underground facilities.

• The Journal of the Korea Contents Association
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• v.20 no.1
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• pp.448-459
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• 2020

Recently, the necessities of gathering, producing, and sharing criminal information are critically important as intelligence functions of police agencies to improving public safety and national security. However, the inadequacies and barriers within which police agencies have in regard to intelligence functions impede criminal information gathering, intelligence producing within their agency, and intelligence sharing with other agencies. In this study, we analyzed informal networks constructed from a survey dataset of information and intelligence sharing among officers in police agencies. The results revealed the different structural properties of intelligence networks between police agencies. We did find that officers with high indegree and outdegree in a network played critical role on the dynamics and degree of intelligence gathering and assessment responsibilities. Finally, we could find evidence that the potential role of intermediary triggered relational dynamics for developing and sharing critical information among all police agencies.

• Journal of the Korean Society for information Management
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• v.26 no.3
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• pp.295-316
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• 2009

This research applied the concepts of IT architecture and IT governance for managing with an integrated computing environment and organized structure, which base a digital library's management and operation. It also aims to analyze the structural system between information technology of human resources and strategy alignment elements of business, which both constitute the core content. Social network analysis software was used to investigate the complicated relationship between IT and business-related strategy alignment elements. The following is the results of carrying out this research on the social network structure and features of strategy alignment elements for a digital library. First, analysis indexes for strategy alignment elements and social network of a digital library were developed. Second, an analysis model was designed based on the analysis index for social network as to strategy alignment elements. Analysis model was appraised by collecting social network datasets for such strategy alignment elements as Communications, Competency and Value, Governance, Partnership, Scope and Architecture, and Skills against the Business strategy, Information strategy, Business and Technology of a digital library. As for the content of analysis, social network structure and specific features were analyzed in relation to a digital library's (1) General social network, (2) Structure of strategy alignment elements, (3) Strategy fit and Functional integration.

• Proceedings of the Korean Society of Computer Information Conference
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• 2016.07a
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• pp.245-246
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• 2016

본 연구는 구리시를 중심으로 도시행정에 있어서 인문정책의 필요성을 주창한 인문도시의 가능성을 탐구한 것이다. 구리시는 인문도시발전모형에 적합한 인문강좌와 인문체험 그리고 인문축제를 진행할 수 있는 요건을 갖춘 도시이다. 이러한 인문도시사업이 시민들에게 공유되고 소통되기 위해서는 스마트폰 앱 안에 인문도시지도만들기가 필요하다. 각각의 인문도시들이 앱을 통해 연결되고 무료로 이용된다면 시민에 찾아가는 도시행정이 될 것이고 시민은 행복할 것이다.

• Annual Conference on Human and Language Technology
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• 1995.10a
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• pp.310-318
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• 1995

본 논문에서는 한국어의 대표적 일치 현상으로 일컬어지는 존대법을 살펴보고, 영어의 일치 현상과 한국어 존대법 '일치' 현상을 동일한 차원에서 다루는데 대한 문제점을 지적한다. 적어도 최근 생성문법에서 영어나 인구어를 중심으로 도입, 활용되는 Agr과 한국어 존대법은 간과 할 수 없는 중요한 차이점이 있음을 밝힌다. 또한 존대법과 공손법 사이의 연관성을 바탕으로 하여 그 둘을 연결하는 공통의 존대요소를 설정하여 일치현상으로 설명하려 할 경우 모순이 생겨난다는 점과, 이러한 문제는 존대법 자체에도 마찬가지로 적용된다는 점을 지적한다.

• The Magazine of the IEIE
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• v.33 no.3 s.262
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• pp.41-48
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• 2006

정보 네트워크는 데이터 뿐 아니라 사물들의 연결성을 부추기고 있으며, 이에 따라 소프트웨어의 현실에 대한 영향력은 더욱 커지고 있다. 한편 로봇의 몸체(하드웨어)와 두뇌(소프트웨어)를 분리하고 네트워크를 통해 연결하는 연구개발시도가 늘어나고 있으며 이는 저가형의 경제성 있는 로봇을 개발하는 원동력이 되고 있기도 하다. 따라서 소프트웨어를 중심으로 한 로봇의 필요성, 역할 비중, 가능성은 그 어느 때 보다 크다. 이 글에서는 소프트웨어 로봇의 기능을 자동으로 확장할 수 있는 체계 구축의 가능성을 따져보고 이를 가능하게 하는 기반 기술로서 웹서비스와 시맨틱웹 기술 동향을 소개한다. 이들은 열린 웹 공간에서 서비스와 지식을 공유할 수 있는 표준 프로토콜과 지식 표현 체계를 제공한다. 이들 기술과 열린 네트워크 환경을 기반으로 스스로 지식과 서비스 수단을 습득하여 능력을 확장할 수 있는 소프트웨어 로봇을 구현할 수 있으리라 기대한다.

• Journal of the Korean Data and Information Science Society
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• v.26 no.2
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• pp.335-346
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• 2015

The purpose of this study is to compare not only network influence of individual coauthor but also the types and properties of two coauthor networks of Communications for Statistical Applications and Methods and the Korean Journal of Applied Statistics which are published by the Korean Statistical Society using social network analysis.As the result of two network structure comparison, density, inclusiveness, reciprocity and clustering coefficient which represent the type of coauthor networks show almost similar values and the Korean Journal of Applied Statistics has bigger values in average degree, average distance and diameter because it has more nodes than Communications for Statistical Applications and Methods. Finally two journals have very similar type of coauthor network. In the comparison of network centrality of two coauthor networks, closeness centrality and betweenness centrality of the Korean Journal of Applied Statistics are bigger than those of Communications for Statistical Applications and Methods at the statistical significance level 0.05. The coauthor network of the Korean Journal of Applied Statistics has faster information delivery and stronger betweenness than that of Communications for Statistical Applications.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.23-46
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• 2021

Collaborative filtering, which is often used in personalization recommendations, is recognized as a very useful technique to find similar customers and recommend products to them based on their purchase history. However, the traditional collaborative filtering technique has raised the question of having difficulty calculating the similarity for new customers or products due to the method of calculating similaritiesbased on direct connections and common features among customers. For this reason, a hybrid technique was designed to use content-based filtering techniques together. On the one hand, efforts have been made to solve these problems by applying the structural characteristics of social networks. This applies a method of indirectly calculating similarities through their similar customers placed between them. This means creating a customer's network based on purchasing data and calculating the similarity between the two based on the features of the network that indirectly connects the two customers within this network. Such similarity can be used as a measure to predict whether the target customer accepts recommendations. The centrality metrics of networks can be utilized for the calculation of these similarities. Different centrality metrics have important implications in that they may have different effects on recommended performance. In this study, furthermore, the effect of these centrality metrics on the performance of recommendation may vary depending on recommender algorithms. In addition, recommendation techniques using network analysis can be expected to contribute to increasing recommendation performance even if they apply not only to new customers or products but also to entire customers or products. By considering a customer's purchase of an item as a link generated between the customer and the item on the network, the prediction of user acceptance of recommendation is solved as a prediction of whether a new link will be created between them. As the classification models fit the purpose of solving the binary problem of whether the link is engaged or not, decision tree, k-nearest neighbors (KNN), logistic regression, artificial neural network, and support vector machine (SVM) are selected in the research. The data for performance evaluation used order data collected from an online shopping mall over four years and two months. Among them, the previous three years and eight months constitute social networks composed of and the experiment was conducted by organizing the data collected into the social network. The next four months' records were used to train and evaluate recommender models. Experiments with the centrality metrics applied to each model show that the recommendation acceptance rates of the centrality metrics are different for each algorithm at a meaningful level. In this work, we analyzed only four commonly used centrality metrics: degree centrality, betweenness centrality, closeness centrality, and eigenvector centrality. Eigenvector centrality records the lowest performance in all models except support vector machines. Closeness centrality and betweenness centrality show similar performance across all models. Degree centrality ranking moderate across overall models while betweenness centrality always ranking higher than degree centrality. Finally, closeness centrality is characterized by distinct differences in performance according to the model. It ranks first in logistic regression, artificial neural network, and decision tree withnumerically high performance. However, it only records very low rankings in support vector machine and K-neighborhood with low-performance levels. As the experiment results reveal, in a classification model, network centrality metrics over a subnetwork that connects the two nodes can effectively predict the connectivity between two nodes in a social network. Furthermore, each metric has a different performance depending on the classification model type. This result implies that choosing appropriate metrics for each algorithm can lead to achieving higher recommendation performance. In general, betweenness centrality can guarantee a high level of performance in any model. It would be possible to consider the introduction of proximity centrality to obtain higher performance for certain models.

• Korean Journal of Culture and Social Issue
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• v.27 no.2
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• pp.191-216
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• 2021

How an individual construes one's future influences everyday decisions. For example, savings and impulsive purchasing, which is highly familiar with our life, are related to future time perception. Drawing on the idea of future self-continuity, the perceived connectedness between the current and future self, this study demonstrated whether media images with various age ranges influence a sense of connectedness with one's future self as well as impatience. Furthermore, the study measured whether these relationships were moderated by the positivity of older adults and an individual's dispositional optimism in general. Results showed that watching various images of people with a wide range of age (from the 20s to 90s) in social media increased young adults' (the 20s) self-continuity and decreased their intention of impatient consumption. This effect was also moderated by the degree to which the participants perceive aging positively.