• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.87-89
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• 2022

Recently, as more consumers spend more time at home due to COVID-19, the time spent on digital consumption such as SNS and OTT, which can be easily used non-face-to-face, naturally increased. Since 2019, when COVID-19 occurred, digital consumption has doubled from 44% to 82%, and it is important to quickly and accurately grasp and apply trends by analyzing consumers' emotions due to the rapidly changing digital characteristics. However, there are limitations in actually implementing services using emotional analysis in small systems rather than large-scale systems, and there are not many cases where they are actually serviced. However, if even a small system can easily analyze consumer trends, it will help the rapidly changing modern society. In this paper, we propose a lightweight trend analysis system that builds a learning network through Transfer Learning (Fine Tuning) of the BERT Model and interlocks Crawler for real-time data collection.

• Journal of the Institute of Convergence Signal Processing
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• v.24 no.1
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• pp.51-56
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• 2023

This study investigates the effect of sEMG sampling frequency on CNN learning performance at Korean finger number recognition application. Since the bigger sampling frequency of sEMG signals generates bigger size of input data and takes longer CNN's learning time. It makes making real-time system implementation more difficult and more costly. Thus, there might be appropriate sampling frequency when collecting sEMG signals. To this end, this work choose five different sampling frequencies which are 1,024Hz, 512Hz, 256Hz, 128Hz and 64Hz and investigates CNN learning performance with sEMG data taken at each sampling frequency. The comparative study shows that all CNN recognized Korean finger number one to five at the accuracy of 100% and CNN with sEMG signals collected at 256Hz sampling frequency takes the shortest learning time to reach the epoch at which korean finger number gestures are recognized at the accuracy of 100%.

• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.151-171
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• 2015

This study examined the concepts of the Internet of Things(IoT), the major issue and IoT trend in the domestic and international market. also reviewed the advent of IoT era which caused a 'Paradigm Shift'. This study proposed a solution for the appropriate corresponding strategy in terms of Enterprise. Global competition began in the IoT market. So, Businesses to be competitive and responsive, the government's efforts, as well as the efforts of companies themselves is needed. In particular, in order to cope with the dynamic environment appropriately, faster and more efficient strategy is required. In other words, proposed a management strategy that can respond the IoT competitive era on tipping point through the vision of paradigm shift. We forecasted and proposed the emergence of paradigm shift through a comparative analysis of past management paradigm and IoT management paradigm as follow; I) Knowledge & learning oriented management, II) Technology & innovation oriented management, III) Demand driven management, IV) Global collaboration management. The Knowledge & learning oriented management paradigm is expected to be a new management paradigm due to the development of IT technology development and information processing technology. In addition to the rapid development such as IT infrastructure and processing of data, storage, knowledge sharing and learning has become more important. Currently Hardware-oriented management paradigm will be changed to the software-oriented paradigm. In particular, the software and platform market is a key component of the IoT ecosystem, has been estimated to be led by Technology & innovation oriented management. In 2011, Gartner announced the concept of "Demand-Driven Value Networks(DDVN)", DDVN emphasizes value of the whole of the network. Therefore, Demand driven management paradigm is creating demand for advanced process, not the process corresponding to the demand simply. Global collaboration management paradigm create the value creation through the fusion between technology, between countries, between industries. In particular, cooperation between enterprises that has financial resources and brand power and venture companies with creative ideas and technical will generate positive synergies. Through this, The large enterprises and small companies that can be win-win environment would be built. Cope with the a paradigm shift and to establish a management strategy of Enterprise process, this study utilized the 'RTE cyclone model' which proposed by Gartner. RTE concept consists of three stages, Lead, Operate, Manage. The Lead stage is utilizing capital to strengthen the business competitiveness. This stages has the goal of linking to external stimuli strategy development, also Execute the business strategy of the company for capital and investment activities and environmental changes. Manege stage is to respond appropriately to threats and internalize the goals of the enterprise. Operate stage proceeds to action for increasing the efficiency of the services across the enterprise, also achieve the integration and simplification of the process, with real-time data capture. RTE(Real Time Enterprise) concept has the value for practical use with the management strategy. Appropriately applied in this study, we propose a 'IoT-RTE Cyclone model' which emphasizes the agility of the enterprise. In addition, based on the real-time monitoring, analysis, act through IT and IoT technology. 'IoT-RTE Cyclone model' that could integrate the business processes of the enterprise each sector and support the overall service. therefore the model be used as an effective response strategy for Enterprise. In particular, IoT-RTE Cyclone Model is to respond to external events, waste elements are removed according to the process is repeated. Therefore, it is possible to model the operation of the process more efficient and agile. This IoT-RTE Cyclone Model can be used as an effective response strategy of the enterprise in terms of IoT era of rapidly changing because it supports the overall service of the enterprise. When this model leverages a collaborative system among enterprises it expects breakthrough cost savings through competitiveness, global lead time, minimizing duplication.

• Journal of the Korean Society for information Management
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• v.38 no.3
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• pp.23-39
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• 2021

This study aims to explore research trends in Blockchain studies in South Korea using dynamic topic modeling and network analysis. To achieve this goal, we conducted the university & institute collaboration network analysis, the keyword co-occurrence network analysis, and times series topic analysis using dynamic topic modeling. Through the university & institute collaboration network analysis, we found major universities such as Soongsil University, Soonchunhyang University, Korea University, Korea Advanced Institute of Science and Technology (KAIST) and major institutes such as Ministry of National Defense, Korea Railroad Research Institute, Samil PricewaterhouseCoopers, Electronics and Telecommunications Research Institute that led collaborative research. Next, through the analysis of the keyword co-occurrence network, we found major research keywords including virtual assets (Cryptocurrency, Bitcoin, Ethereum, Virtual currency), blockchain technology (Distributed ledger, Distributed ledger technology), finance (Smart contract), and information security (Security, privacy, Personal information). Smart contracts showed the highest scores in all network centrality measures showing its importance in the field. Finally, through the time series topic analysis, we identified five major topics including blockchain technology, blockchain ecosystem, blockchain application 1 (trade, online voting, real estate), blockchain application 2 (food, tourism, distribution, media), and blockchain application 3 (economy, finance). Changes of topics were also investigated by exploring proportions of representative keywords for each topic. The study is the first of its kind to attempt to conduct university & institute collaboration networks analysis and dynamic topic modeling-based times series topic analysis for exploring research trends in Blockchain studies in South Korea. Our results can be used by government agencies, universities, and research institutes to develop effective strategies of promoting university & institutes collaboration and interdisciplinary research in the field.

• Journal of Korean Society of Transportation
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• v.26 no.3
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• pp.223-232
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• 2008

It can be expected, recently, that the traffic congestion grows worse because the 48% of passenger cars are concentrated in the metropolitan area. However, there is an enforcement regulation that must limit onsite parking lot establishment in some downtown, so it is forecasted that parking lot supply is insufficient. Therefore, this study concentrate upon the subject that solves the problem which drivers are difficult to find parking lots because of increasing demand for parking. This study includes the concept about walking distance because the choice of parking lots is happened within walking distance. The algorithm of this study applies to toy-network, and then this study analyze the result of toy-network. It is proper to consider user's preference because the patterns of choice are different. Moreover, this study suggests the vision that will can offer drivers more correct information by real time information sharing in course of ubiquitous age.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.249-252
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• 2008

A wearable ubiquitous health care monitoring system using integrated ECG and accelerometersensors based on WSN is designed and developed. Wireless sensor network technology is applied for non intrusive healthcare in some wide area coverage with small battery support for RF transmission. We developed wearable devices which are wearable USN node, sensor board and base-station. Low power operating ECG and accelerometer sensor board was integrated to wearable USN node for user's health monitoring. The wearable ubiquitous healthcare monitoring system allows physiological data to be transmitted in wireless sensor network from on body wearable sensor devices to a base-station connected to server PC using IEEE 802.15.4. Physiological data displays and stores on server PC continuously.

• Journal of Digital Convergence
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• v.12 no.9
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• pp.193-199
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• 2014

In the application development process is an important task to improve the quality of the data is the principal means for achieving the functional requirements of the wireless sensor network applications because it is the data obtained in the real world. It should be possible to meet the requirements for the quality improvement to those detailed for improving the quality in a short period of time for developing a prototype of an application and low cost. However, development of the existing methods can not be satisfied simultaneously in order to use a consistent abstraction because antinomical relation between ability of description and ease of description. In this paper, we propose a meta-data designed to support the improvement of data quality through abstract modeling language is also used in combination to a multiple of the other.

• Journal of KIISE:Software and Applications
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• v.36 no.8
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• pp.633-641
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• 2009

In this paper, we proposed a new pattern classifier which can be incrementally learned, be added new class in learning time, and handle with analog data. Proposed pattern classifier has hierarchical structure and the classification rate is improved by using different metric for each levels. Proposed model is based on the Gaussian ARTMAP which is an artificial neural network model for the pattern classification. We hierarchically constructed the Gaussian ARTMAP and proposed the Principal Component Emphasis(P.C.E) method to be learned different features in each levels. And we defined new metric based on the P.C.E. P.C.E is a method that discards dimensions whose variation are small, that represents common attributes in the class. And remains dimensions whose variation are large. In the learning process, if input pattern is misclassified, P.C.E are performed and the modified pattern is learned in sub network. Experimental results indicate that Hierarchical Gaussian ARTMAP yield better classification result than the other pattern recognition algorithms on variable data set including real applicable problem.

• Proceedings of the KSR Conference
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• 2011.10a
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• pp.181-187
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• 2011

Since 2003, state transportation study core technology development is being promoted as part of the bimodal trams operating in accordance with the development of refractive vehicle as research infrastructure for building high-tech road transport system has been the research and development. Bimodal trams of refraction as the vehicle for him to introduce domestic first ever operation management system also developed in Korea according to case-based technology system, but most of the country, and, in this study, mainly those based on technology integration building management system and the bimodal trams of refraction of a vehicle operated was to highlight the features and benefits. Bimodal tram station itself is the way the exclusive properties and to operate the route with large transport capacity has the characteristics of the railway, but the only routes such as railroad lines is not of closed roads under certain circumstances, the flexibility to use has to be integrated operations management system of bimodal trams characteristics of the railroads and public transportation by combining the characteristics of a flexible, convenient and secure services to users with the aim of providing research and will denote the system developed. In this study, bimodal integration system required for the operation of the tram station around the wired and wireless network management center, applying the organic integration into one system so that you have to be centrally managed. In addition, the existing traffic management system operates as a unidirectional rather than monitoring all system-wide management via the interactive network through real-time requests and responses were configured to allow management and control. These findings of the existing traffic operation management system that you can jump step can be based on future unmanned vehicles and related systems through control of the operation management system will be offered as a basis.

• Journal of Digital Contents Society
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• v.15 no.2
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• pp.271-281
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• 2014

This study aimed to investigate the types that readers enjoying cartoons appreciated cartoons under the premise that cartoons enjoyed over the internet would expand their sensitivity through media such as monitors and mice. The sensitivity of readers enjoying digital cartoons can be stimulated through communication with carton writers or other readers as the interaction of the real-time response to the network. The choice and control are possible with a vertical scroll bar. Accordingly, readers can be absorbed in a work and focus on its story much more. As a result of extracting emotional stimulation factors to verify these assumptions, factors were able to classify the sensitivity that readers enjoying cartoons obtained from digital cartoons into two types, communication and story-focus type, based on the phases that emotional stimuli were strengthened. This study will be significant as a study to identify the relationship between media-technological factors and readers enjoying cartoons in relation to digital cartoons.