• Title/Summary/Keyword: Technology network analysis

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Analysis and Implementation of Distance Video Lecturing System (초고속통신망환경에서의 원격화상강의시스템 구현 및 분석)

  • 안종민;장종욱
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2002.05a
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    • pp.90-95
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    • 2002
  • This thesis is aiming at analysis and implementing Distance Video Lecturing System to guarantee the high quality in service through using less Network resource. Most of the usual Distance Video Lecturing System has been designed not in the system of Multiuser Conference but Point-to-Point. But from now on Distance Video Lecturing System is to be demanded on not only the expansion to Multiuser Distance Video Lecturing System, but high quality in service for users. To solve these problems, the Multicast Transmission Technology as the dimension of Network as well as highly efficient, advanced Compression Technology should be applied to Video Conference System in company with the expansion of Network bandwidth. The system suggested in this thesis is to help to offer an application service as Distance Video Lecturing System that will make popular on the basis of the character that the next generation Internet will be high speed Network.

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Concurrent Engineering Based Collaborative Design Under Network Environment

  • Jiang Gongliang;Huang Hong-Zhong;Fan Xianfeng;Miao Qiang;Ling Dan
    • Journal of Mechanical Science and Technology
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    • v.20 no.10
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    • pp.1534-1540
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    • 2006
  • Concurrent Engineering (CE) is a popular method employed in product development. It treats the whole product design process by the consideration of product quality, cost, rate of progress, and demands of customers. The development of computer and network technologies provides a strong support to the realization of CE in practice. Aiming at the characteristics of CE and network collaborative design, this paper built network collaborative design system frame. Through the analysis of the network collaborative design modes based on CE, this paper provided a novel network collaborative design integration model. This model can integrate the product design information, design process, and knowledge. Intelligent collaboration was considered in the proposed model. The study showed that the proposed model considered main factors such as information, knowledge, and design process in collaborative design. It has potential application in CE fields.

Analysis of Experience Knowledge of Shooting Simulation for Training Using the Text Mining and Network Analysis (Text Mining과 네트워크 분석을 활용한 교육훈련용 모의사격 시뮬레이션 경험지식 분석)

  • Kim, Sungkyu;Son, Changho;Kim, Jongman;Chung, Sehkyu;Park, Jaehyun;Jeon, Jeonghwan
    • Journal of the Korea Institute of Military Science and Technology
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    • v.20 no.5
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    • pp.700-707
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    • 2017
  • Recently, the military need more various education and training because of the increasing necessity of various operation. But the education and training of the military has the various difficulties such as the limitations of time, space and finance etc. In order to overcome the difficulties, the military use Defense Modeling and Simulation(DM&S). Although the participants in training has the empirical knowledge from education and training based on the simulation, the empirical knowledge is not shared because of particular characteristics of military such as security and the change of official. This situation obstructs the improving effectiveness of education and training. The purpose of this research is the systematizing and analysing the empirical knowledge using text mining and network analysis to assist the sharing of empirical knowledge. For analysing texts or documents as the empirical knowledge, we select the text mining and network analysis. We expect our research will improve the effectiveness of education and training based on simulation of DM&S.

Dynamic Analysis of Automotive Firm's Convergence Patents using Social Network Analysis (소셜네트워크분석을 이용한 자동차 기업 융합특허의 동태적 변화 분석)

  • Park, Eunyoung;Koh, Myounju;Cho, Keuntae
    • Journal of Technology Innovation
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    • v.26 no.3
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    • pp.1-36
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    • 2018
  • In the era of the 4th Industrial Revolution, it is important for companies to understand the changing environment by converging various technologies and to respond to the changing business environment. In this study, we conducted a social network analysis on 10 firms in the automotive industry, which have recently been accelerating their competition for technology development, by extracting convergence patents co-classified in two or more of the US registered patents in the last 6 years. As a result, it has been confirmed that the number of technology related to the convergence of the automotive field is greatly increasing, and the convergence between the technologies is becoming stronger. In addition, Volkswagen, Ford and Hyundai showed significant changes in technology convergence. They were analyzed as having a change in strategy in eco-friendly automotive technologies. This study suggests various ways for companies to utilize the results of network analysis more meaningfully.

Vehicle Detection in Aerial Images Based on Hyper Feature Map in Deep Convolutional Network

  • Shen, Jiaquan;Liu, Ningzhong;Sun, Han;Tao, Xiaoli;Li, Qiangyi
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.4
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    • pp.1989-2011
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    • 2019
  • Vehicle detection based on aerial images is an interesting and challenging research topic. Most of the traditional vehicle detection methods are based on the sliding window search algorithm, but these methods are not sufficient for the extraction of object features, and accompanied with heavy computational costs. Recent studies have shown that convolutional neural network algorithm has made a significant progress in computer vision, especially Faster R-CNN. However, this algorithm mainly detects objects in natural scenes, it is not suitable for detecting small object in aerial view. In this paper, an accurate and effective vehicle detection algorithm based on Faster R-CNN is proposed. Our method fuse a hyperactive feature map network with Eltwise model and Concat model, which is more conducive to the extraction of small object features. Moreover, setting suitable anchor boxes based on the size of the object is used in our model, which also effectively improves the performance of the detection. We evaluate the detection performance of our method on the Munich dataset and our collected dataset, with improvements in accuracy and effectivity compared with other methods. Our model achieves 82.2% in recall rate and 90.2% accuracy rate on Munich dataset, which has increased by 2.5 and 1.3 percentage points respectively over the state-of-the-art methods.

Industry Activation Scheme through mVoIP Technology Trends and Market Analysis

  • Park, Se-Hwan;Park, Jong-Kyu;Kim, Cheong-Ghil
    • International journal of advanced smart convergence
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    • v.1 no.2
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    • pp.59-63
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    • 2012
  • The mVoIP service is the technology which focuses on the wireless data service as the IP network having the transmission rate of 100 Mbps classes on the high-speed middle of movement through the WiFi, WiBro and 3G mobile radio communication network, and etc. and is developed. Since 2010, the mVoIP (mobile VoIP) service shows the rapid growth due to 4G-LTE service seriously disclosed from July with the Smart phone and 2,011 it begins to be rapidly popularized. In this research, additionally the mVoIP service industry activation plan is presented with the trends of technology development including the chip-set/module/terminal, etc. based upon local and foreign market trend searchlight through the market demand analysis. The mVoIP service downloads App to the mobile apparatus and or can provide the service as the software through the WiFi network. Therefore, the change which is large in the products development aspect is to be have no. Expected to is being provided as the added service in the case of 4G-LTE as a matter of course, the service deployment where it is based on the market principle and demand needs is needed.

A Bayesian network based framework to evaluate reliability in wind turbines

  • Ashrafi, Maryam;Davoudpour, Hamid;Khodakarami, Vahid
    • Wind and Structures
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    • v.22 no.5
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    • pp.543-553
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    • 2016
  • The growing complexity of modern technological systems requires more flexible and powerful reliability analysis tools. Existing tools encounter a number of limitations including lack of modeling power to address components interactions for complex systems and lack of flexibility in handling component failure distribution. We propose a reliability modeling framework based on the Bayesian network (BN). It can combine historical data with expert judgment to treat data scarcity. The proposed methodology is applied to wind turbines reliability analysis. The observed result shows that a BN based reliability modeling is a powerful potential solution to modeling and analyzing various kinds of system components behaviors and interactions. Moreover, BN provides performing several inference approaches such as smoothing, filtering, what-if analysis, and sensitivity analysis for considering system.

Research Trend Analysis for Smart Grid using Social Network Analysis (사회연결망분석을 활용한 스마트그리드 연구동향 분석)

  • Na, Sang-Tae;Ahn, Joo-Eon;Jung, Min-Ho;Kim, Ja-Hee
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.66 no.12
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    • pp.1697-1704
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    • 2017
  • As the power grid has been changed to a smart grid, existing power technologies are evolving into convergence technology through interdisciplinary research. According to the government policy to increase the proportion of renewable energy to 20% by 2030, the speed seems to be accelerating. This study analyzes the relationship between research technologies in order to grasp research trends of smart grid technology. To this end, we analyze the relationship between keywords extracted from topic modeling using social network analysis methodology. This is because, in the field where interdisciplinary research such as smart grid is active, each research topic is not independent, but research technologies emerging in one topic coexist in different topics, and linkage between research technologies can be important information. Therefore, this study can contribute to the analysis of research trend as it can be used as a package tool together with a topic modeling methodology.

Analysis of Trends for Weapon System Accidents Using Social Network Analysis (사회 연결망 분석을 활용한 무기체계 안전사고 동향 분석)

  • Kang, Eonbi;Park, Sanghyun;Kwon, Kiseok;Jeon, Jeonghwan
    • Journal of the Korea Institute of Military Science and Technology
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    • v.25 no.1
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    • pp.82-95
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    • 2022
  • Since military weapon accidents or breakdowns are directly linked to enormous damage, it is important to analyze the causes of weapons system accidents. Recently, in the defense sector, there have been cases in which budget has been saved through analysis of the causes of frequent breakdowns and improvement activities that have occurred in the process of operating weapon systems since 2015. But due to the nature of the defense sector, it is not easy to collect data and studies on weapons system accidents have been insufficient so far. Therefore, this study aims to investigate the causes and types of military weapon accidents by collecting military weapon accident data for military weapon systems and analyzing trends by weapon system classification through the analysis process. It analyzes statistically and visually through social network analysis, NodeXL. It is expected that this study will help improve the stability of the weapon system by reducing the number of military weapon accidents and failures.

A Study on Market Convergence Dynamics Based on Startup Data: Focusing on Korea (스타트업 데이터 기반의 시장융합 다이내믹스 분석: 한국을 중심으로)

  • Song, Chie Hoon
    • Journal of the Korean Society of Industry Convergence
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    • v.25 no.4_2
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    • pp.627-636
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    • 2022
  • Market convergence plays an increasingly important role in sustaining competitiveness and providing impetus for the new product development. However, existing research focused mostly on the analysis of convergence at technology level. This study examines the phenomenon of market convergence based on the start-up data. Similar to the analysis of technology convergence, this study adopts the concept of co-classification analysis for constructing the co-occurrence matrix and the corresponding network. In this context, network centrality measures were calculated to assess the influence of individual market segments. Based on three metrics "growth", "persistence" and "novelty", the market convergence dynamics were explored and promising interactions between two distinct market segments were highlighted. The findings suggest that both segments "AI" and "blockchain" are acting as a driver that fosters market convergence in the startup landscape. The analysis results can provide valuable information for the R&D managers and policy makers in the design of targeted policies and programs, which can promote market convergence and interdisciplinary knowledge transfer.