• 로봇학회논문지
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• 제3권3호
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• pp.255-261
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• 2008

This paper describes a network framework that support network based humanoid. The framework utilizes middleware such as CORBA (ACE/TAO) that provides PnP capability for network based humanoid. The network framework transfers data gathered from a network based humanoid to a processing group that is distributed on a network. The data types are video stream, audio stream and control data. Also, the network framework transfers service data produced by the processing group to the network based humanoid. By using this network framework, the network based humanoid can provide high quality of intelligent services to user.

• 디지털산업정보학회논문지
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• 제11권4호
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• pp.33-45
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• 2015

Currently, Internet is used an essential tool in the business area. Despite this importance, there is a risk of network attacks attempting collection of fraudulence, private information, and cyber terrorism. Firewalls and IDS(Intrusion Detection System) are tools against those attacks. IDS is used to determine whether a network data is a network attack. IDS analyzes the network data using various techniques including expert system, data mining, and state transition analysis. This paper tries to compare the performance of two data mining models in detecting network attacks. They are decision tree (C4.5), and neural network (FANN model). I trained and tested these models with data and measured the effectiveness in terms of detection accuracy, detection rate, and false alarm rate. This paper tries to find out which model is effective in intrusion detection. In the analysis, I used KDD Cup 99 data which is a benchmark data in intrusion detection research. I used an open source Weka software for C4.5 model, and C++ code available for FANN model.

• 한국컴퓨터정보학회지
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• 제1권2호
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• pp.73-94
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• 1995

본 논문은 유통정보 네트워크 활성화 방안에 대하여 효율적인 NDB(Network Data Base)을 설계하였다. NDB(Network Data Base)의 구조는 논리 구조, 격납 구조, 물리 구조로 형성되어 데이터는 하나의 레코드로서 표현되고 데이터들 간의 관계는 링크로서 표현되었다. 또한 데이터베이스의 논리적 구조를 표현한 자료 구조도(Data Structure Diagram:DSD)가 계층 모델로 나타내었다. 각 노드는 레코드 타입을 나타내었고, 타입들을 연결하는 방향을 지닌 링크, 논리적인 격납 형태로 구성되어 데이터베이스를 설계하는데 물리 매체상 서로 연관성 있게 설계되어 자료의 검색과 억세스 효율에 큰 영향을 미쳤다. 또한 설계된 시스템에 네트워크를 형성하고, 네트워크 표준화를 위해 OSI 환경하에서 POS(Point Of Sale)시스템을 이용하여 효율적인 유통 정보 네트워크를 활성화시켰다.

• 대한임베디드공학회논문지
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• 제11권1호
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• pp.9-14
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• 2016

Since Devices such labtop, tablet, smartphone have been developed, a lots of huge data that can be classified as content is flooded in the network. According to changing Internet usage, Content-Centric Network(CCN) what is new concept of Internet Architecture is appeared. Initially, CCN is studied on wired network. but recently, CCN is also studied on wireless network. Since a characteristic of wireless environment is different from a characteristic of wired environment, There are issues in wireless CCN. In this paper, we discuss improvement method of Data spread issue on wireless CCN. The proposed scheme of this paper use MAC Address of nodes when Interest and Data Packet are forwarded. As using the proposed scheme, we reduce the spread of Data and offer priority of forwarding to nodes of shortest path, reduce delay by modifying retransmission waiting time.

• International Journal of Contents
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• 제13권1호
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• pp.31-37
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• 2017

Using the network analysis method, this study investigates the communication structure of Open Data on the Twitter sphere. It addresses the communication path by mapping influential activities and comparing the contents of tweets about Open Data. In the years 2015 and 2016, the NodeXL software was applied to collect tweets from the Twitter network, containing the term "opendata". The structural patterns of social media communication were analyzed through several network characteristics. The results indicate that the most common activities on the Twitter network are related to the subjects such as new applications and new technologies in Open Data. The study is the first to focus on the structural and informational pattern of Open Data based on social network analysis and content analysis. It will help researchers, activists, and policy-makers to come up with a major realization of the pattern of Open Data through Twitter.

• 한국측량학회지
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• 제37권2호
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• pp.91-97
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• 2019

In automatic map generalization, the formalization of cartographic principles is important. This study proposes and evaluates the selection method for road network generalization that analyzes existing maps using reverse engineering and formalizes the selection rules for the road network. Existing maps with a 1:5,000 scale and a 1:25,000 scale are compared, and the criteria for selection of the road network data and the relative importance of each network object are determined and analyzed using $T{\ddot{o}}pfer^{\prime}s$ Radical Law as well as the logistic regression model. The selection model derived from the analysis result is applied to the test data, and road network data for the 1:25,000 scale map are generated from the digital topographic map on a 1:5,000 scale. The selected road network is compared with the existing road network data on the 1:25,000 scale for a qualitative and quantitative evaluation. The result indicates that more than 80% of road objects are matched to existing data.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2017년도 추계학술대회
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• pp.531-532
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• 2017

oneM2M의 domain은 Device, Network, Application domain으로 구분되며, 다양한 device에서 생성되는 데이터를 IoT/M2M gateway를 통해 취합, Core/Access Network를 거쳐 적합한 IoT/M2M Infrastructure에 전달한다. 그러나 device가 동일한 지역 내에 위치하는 Infrastructure에 데이터를 전달 할 경우에도 Core/Access Network에 접근이 필요하다. 본 논문에서는 oneM2M domain에 지역 network domain의 개념을 추가하여 데이터의 지역정보를 판단 후 전송, 불필요한 Core/Access Network의 접근을 방지하는 지역 gateway 기반 데이터 전송방법을 제안한다.

• 한국IT서비스학회지
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• 제16권3호
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• pp.167-183
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• 2017

The rapid growth of information technology and mobile service platforms, i.e., internet, google, and facebook, etc. has led the abundance of data. Due to this environment, the world is now facing a revolution in the process that data is searched, collected, stored, and shared. Abundance of data gives us several opportunities to knowledge discovery and data mining techniques. In recent years, data mining methods as a solution to discovery and extraction of available knowledge in database has been more popular in e-commerce service fields such as, in particular, movie recommendation. However, most of the classification approaches for predicting the movie popularity have used only several types of information of the movie such as actor, director, rating score, language and countries etc. In this study, we propose a classification-based support vector machine (SVM) model for predicting the movie popularity based on movie's genre data and social network data. Social network analysis (SNA) is used for improving the classification accuracy. This study builds the movies' network (one mode network) based on initial data which is a two mode network as user-to-movie network. For the proposed method we computed degree centrality, betweenness centrality, closeness centrality, and eigenvector centrality as centrality measures in movie's network. Those four centrality values and movies' genre data were used to classify the movie popularity in this study. The logistic regression, neural network, $na{\ddot{i}}ve$ Bayes classifier, and decision tree as benchmarking models for movie popularity classification were also used for comparison with the performance of our proposed model. To assess the classifier's performance accuracy this study used MovieLens data as an open database. Our empirical results indicate that our proposed model with movie's genre and centrality data has by approximately 0% higher accuracy than other classification models with only movie's genre data. The implications of our results show that our proposed model can be used for improving movie popularity classification accuracy.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 1996년도 Proceedings International Workshop on New Video Media Technology
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• pp.1-6
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• 1996

To promote academic researches on earth environment utilizing satellite data, research infrastructure such as satellite data reception processing, distribution and archival systems should be fully provided. The means to enhance the infrastructure were discussed by a working group and“Satellite Data Center via Network”has been proposed. This concept has three principles; (1) To realize necessary functions by organizing experts distributed all over Japan and connecting them by network, (2) To realize“Satellite Data Center via Network”for GMS and NOAA Satellites, which are widely used for research, and (3) Satellite data set oriented to specific research area should be generated by researchers having definite research purposes of sensor algorithms and hugh volume data processing. Utilization of the Science Information Network (SINET) has been discussed to realize this concept, and to accelerate this project an experiment“Network Utilization for Wide Area Use of Satellite Image Data”under“Cooperative Experiment on Multimedia Communication”has been introduced. And the roles of the Institute of Industrial Science, University of Tokyo to contribute this project has been described.

• 디지털산업정보학회논문지
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• 제10권1호
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• pp.39-45
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• 2014

This paper proposes an architecture of a sensor network for gathering data under a powerful beam cluster tree architecture. This architecture is used when there is a need to gather data from sensor node where there is no sink node connected to an existing network, or it is required to get a series of data specific to an event or time. The transmit distance of the beam signal is longer than that of the usual sensor node. The nodes of the network make a tree network when receiving a beam message transmitting from the powerful root node. All sensor nodes in a sink tree network synchronize to the superframe and know exactly the sequence value of the current superframe. When there is data to send to the sink node, the sensor node sends data at the corresponding allocated channel. Data sending schemes under the guaranteed time slot are tested and the delay and jitter performance is explained.