• Journal of the Korean Society for information Management
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• v.20 no.1
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• pp.301-320
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• 2003

The rapidly increasing use of the Internet and advancement of the communication network, the explosive growth of digital contents from personal home pages to professional information service the emerging file exchange service and the development of hacking techniques . these are some of the trends contributing to the spread of illegal reproduction and distribution of digital contents, thus threatening the exclusive copyrights of the creative works that should be legally protected Accordingly, there is urgent need for a digital copyright management system designed to provide centralized management while playing the role of bridge between the copyright owners and users for smooth trading of the rights to digital contents, reliable billing, security measures, and monitoring of illegal use. Therefore, in this study, I examined the requirements of laws and systems for the introduction of the centralized management system to support smooth distribution of digital contents, and also researched on the current status of domestic and international centralized management system for copyrights. Furthermore, 1 tried to provide basic materials for the standardization of digital contents copyright management information through the examination of the essential elements of the centralized digital contents management such as the system for unique identification the standardization for data elements, and the digital rights management (DHM) .

• Journal of Internet Computing and Services
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• v.18 no.2
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• pp.1-11
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• 2017

There are two kinds of wireless network access to a certain place by using smart devices - 1) open (anonymous) - access and 2) user-authorized access. The open-access is a non-authorization connection method which does not need to require Smart device's user authorized information. It means open-access use only user's SSID (Service Set Identifier) information to access the wireless AP devices following public wireless network standard. This access mechanism is not suitable to use all of public wireless networks because users have to get all wireless network information around them. As a result, huge data for smart devices should be one of the most critical overload problems for them. Secondly, the user-authorized access method uses wireless network information (SSID and password) chosen by the users. So, the users have to remember and use the network access information data manually whenever accessing the network. Like open-access, this access method also has the operational and inconvenient problem for the users - manually inputting access information whenever connecting to the network. To overcome this problem in both schemes, we propose two improved wireless network access methods: 1) the implementation of automatic AP connection mechanism using user-authorization and iBeacon messages, and 2) SSID registration form for public wireless networks.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.10A
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• pp.796-806
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• 2009

This paper presents the method of emergency warning system operation based on T-DMB and the design of T-DMB AEAS receiver model. The proposed receiver model compares the geographical location of emergency with the location of DMB transmitting station from T-DMB broadcasting signal and classifies the receiver location into alert region, neighboring region and non-alert region and transmits the emergency alert message according to each region. The geographical location of emergency can be obtained from FIG 5/2 EWS data field for AEAS message and the location of DMB transmitting station can be estimated from either the latitude and the longitude in main identifier and sub identifier in FIG 0/22 data filed for TII(Transmitter Identification Information) or TII distribution database. In our experiment, we implemented the proposed receiver model with display section, storage section, DMB module for receiving broadcasting signal and control section and performed test emergency alert broadcasting using T-DMB signal generator.

• Proceedings of the Korea Contents Association Conference
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• 2008.05a
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• pp.591-594
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• 2008

Currently RFID code systems are classified into ISO, EPC, uCode, KKR code, Mobile RFID code, and etc. According to RFID code systems, RFID system is changed. For various RFID code systems, it's difficult to make it to the network and permanence of RFID business. And the existing system isn't add new RFID code systems to RFID system, and change it efficiently. This paper is proposed to a system of Multi RFID code Identification Translation using Ontology. This system is able to identify code data from RFID reader using ontology build into the identifier info and translation info of RFID code systems, and translate to URN data. Therefore in case of extending and changing RFID code systems, we can add and change the identifier info and translation info of RFID code systems in ontology.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.4
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• pp.127-136
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• 2022

As technological development continues, platforms with more diverse structures are emerging. Existing research predicts that a new structure based on technology and innovation will affect the two-sided market. This study evaluated the decentralized identifier (DID) platform, a new platform based on blockchain technology, of the importance of this platform from the perspective of the two-sided market. Using the Analytic Network Process, IT, platform, and blockchain experts conducted a dual comparison survey. Data with a consistency ratio value of 0.1 or less were selected and analyzed for 12 data. The research results showed the importance of service quality, policy support, openness, and uncertainty. This study is expected to be used to support the development of strategic decision-making for blockchain and DID platform-based business companies.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.1D
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• pp.157-167
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• 2006

During the first and second NGIS projects by the Korean government, The first one (1995~2000) was limited on constructing geographic information and the second (2001~2005) was focused on circulation and practical use of geoinformation from the result of the first project. In the latter half of 2nd NGIS project, However, the geographic information from the NGIS projects have not been renewed even though there were significant geographical changes. The accurate renewal of geoinformation is a matter of great importance to the next generation industry (e.g. LBS, Ubiquitous, Telematics). In this respect, it is time to update the geographic information in the latter half of the second NGIS project. Therefore, It is not only important to build an accurate geoinformation but also rapid and correct renewal of the geoinformation. NGII (National Geographic Information Institute) has been studying for improvement of digital map that was constructed by the result of the 1st NGIS project. Through the construction of clean digital map, NGII constructed Framework Data to three kinds of formats (NGI, NDA, NRL). Framework Data was contained to other database, and provided the reference system of location or contents for combining geoinformation. Framework Data is consist of Data Set, Data Model and UFID (Unique Feature Identifier). It will be achieved as national infrastructure data. This paper attempts to explore a method of the update to practical framework data with realtime geoinformation on feature's creation, modification and destruction managed by 'Feature management agency' using UFID's process. Furthermore, it suggests a method which can provide important data in order to plan the Framework update with the land change ratio.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.7
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• pp.11-22
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• 1992

In this paper, a new indexing technique is proposed for efficient evaluation of nested queries on aggregation hierarchy in object-oriented data model. As an index data structure, an extended $B^{+}$ tree is introduced in which instance identifier to be searched and path information used for update of index record are stored in leaf node and subleaf node, respectively. the retrieval and update algorithm on the introduced index data structure is provided. Comparisons under a variety of conditions are given with current indexing techniques, showing improved performance in cost, i.e., the total number of pages accessed for retrieval and update.

• Journal of IKEEE
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• v.22 no.4
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• pp.1140-1146
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• 2018

Recently, a methodology for analyzing complex bio-signals using a deep learning model has emerged among studies that recognize human emotions. At this time, the accuracy of emotion classification may be changed depending on the evaluation method and reliability depending on the kind of data to be learned. In the case of biological signals, the reliability of data is determined according to the noise ratio, so that the noise detection method is as important as that. Also, according to the methodology for defining emotions, appropriate emotional evaluation methods will be needed. In this paper, we propose a wavelet -based noise threshold setting algorithm for verifying the reliability of data for multimodal bio-signal data labeled Valence and Arousal and a method for improving the emotion recognition rate by weighting the evaluation data. After extracting the wavelet component of the signal using the wavelet transform, the distortion and kurtosis of the component are obtained, the noise is detected at the threshold calculated by the hampel identifier, and the training data is selected considering the noise ratio of the original signal. In addition, weighting is applied to the overall evaluation of the emotion recognition rate using the euclidean distance from the median value of the Valence-Arousal plane when classifying emotional data. To verify the proposed algorithm, we use ASCERTAIN data set to observe the degree of emotion recognition rate improvement.

• Journal of the Korea Society of Computer and Information
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• v.23 no.11
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• pp.17-24
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• 2018

Today, we are living in the era of data and information. With the advent of Internet of Things (IoT), the popularity of social networking sites, and the development of mobile devices, a large amount of data is being produced in diverse areas. The collection of such data generated in various area is called big data. As the importance of big data grows, there has been a growing need to share big data containing information regarding an individual entity. As big data contains sensitive information about individuals, directly releasing it for public use may violate existing privacy requirements. Thus, privacy-preserving data publishing (PPDP) has been actively studied to share big data containing personal information for public use, while preserving the privacy of the individual. K-anonymity, which is the most popular method in the area of PPDP, transforms each record in a table such that at least k records have the same values for the given quasi-identifier attributes, and thus each record is indistinguishable from other records in the same class. As the size of big data continuously getting larger, there is a growing demand for the method which can efficiently anonymize vast amount of dta. Thus, in this paper, we develop an efficient k-anonymity method by using Spark distributed framework. Experimental results show that, through the developed method, significant gains in processing time can be achieved.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.6
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• pp.441-446
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• 2000

This paper presents an approach for the prediction of optimal heating load using a diagonal recurrent neural networks(DRNN) and data base system of outdoor temperature. In the DRNN, a dynamic backpropagation(DBP) with delta-bar-delta teaming method is used to train an optimal heating load identifier. And the data base system is utilized for outdoor temperature prediction. Compared to other kinds of methods, the proposed method gives better prediction performance of heating load. Also a hardware for the controller is developed using a microprocessor. The experimental results show that prediction enhancement for heating load can be achieved with the proposed method regardless of the its inherent nonlinearity and large time constant.