• Korea Information Processing Society Review
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• v.11 no.6
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• pp.56-75
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• 2004

In this article we address some system characteristics and challenging issues in developing Context-aware Middleware for Ubiquitous Computing. The functionalities of a Context-aware Middleware includes gathering context data from hardware/software sensors, reasoning and inferring high-level context data, and disseminating/delivering appropriate context data to interested applications/services. The Middleware should facilitate the query, aggregation, and discovery for the contexts, as well as facilities to specify their privacy policy. Following a formal context model using ontology would enable syntactic and semantic interoperability, and knowledge sharing between different domains. Moddleware should also provide different kinds of context classification mechanical as pluggable modules, including rules written in different types of logic (first order logic, description logic, temporal/spatial logic, fuzzy logic, etc.) as well as machine-learning mechanical (supervised and unsupervised classifiers). Different mechanisms have different power, expressiveness and decidability properties, and system developers can choose the appropriate mechanism that best meets the reasoning requirements of each context. And finally, to promote the context-trigger actions in application level, it is important to provide a uniform and platform-independent interface for applications to express their need for different context data without knowing how that data is acquired. The action could involve adapting to the new environment, notifying the user, communicating with another device to exchange information, or performing any other task.

• Journal of Korean Society of Transportation
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• v.33 no.1
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• pp.14-28
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• 2015

Numerous research has been conducted using internet search data since the mid-2000s. For example, Google Inc. developed a service predicting influenza patterns using the internet search data. The main objective of this study is to prove the hypothesis that highway traffic indices are similar to the internet search patterns. In order to achieve this objective, a model to predict the number of vehicles entering the expressway and space-mean speed was developed and the goodness-of-fit of the model was assessed. The results revealed several findings. First, it was shown that the Google search traffic was a good predictor for the TCS entering traffic volume model at sites with frequent commute trips, and it had a negative correlation with the TCS entering traffic volume. Second, the Naver search traffic was utilized for the TCS entering traffic volume model at sites with numerous recreational trips, and it was positively correlated with the TCS entering traffic volume. Third, it was uncovered that the VDS speed had a negative relationship with the search traffic on the time series diagram. Lastly, it was concluded that the transfer function noise time series model showed the better goodness-of-fit compared to the other time series model. It is expected that "Big Data" from the internet search data can be extensively applied in the transportation field if the sources of search traffic, time difference and aggregation units are explored in the follow-up studies.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.1
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• pp.198-204
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• 2012

Generally, the clustering of sensor nodes in WSN is a useful mechanism that helps to cope with scalability problem and, if combined with network data aggregation, may increase the energy efficiency of the network. The Hierarchical clustering routing algorithm is a typical algorithm for enhancing overall energy efficiency of network, which selects cluster-head in order to send the aggregated data arriving from the node in cluster to a base station. In this paper, we propose the improved-LEACH that uses comparably simple and light-weighted policy to select cluster-head nodes, which results in reduction of the clustering overhead and overall power consumption of network. By using fine-grained power model, the simulation results show that i-LEACH can reduce clustering overhead compared with the well-known previous works such as LEACH. As result, i-LEACH algorithm and LEACH algorithm was compared, network power-consumption of i-LEACH algorithm was improved than LEACH algorithm with 25%, and network-traffic was improved 16%.

• Journal of Digital Convergence
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• v.10 no.6
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• pp.189-196
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• 2012

In this paper, we propose a Scorm-based Sequencing & Navigation Model for Collaborative Learning. It is an e-Learning process control model that is used to efficiently and graphically defining Scorm's content aggregation model and its sequencing prerequistites through a formal approach. To define a process based model uses the expanded ICN(Information Control Net) model. which is called SCOSNCN(SCO Sequencing & Navigation Control Net). We strongly believe that the process-driven model delivers a way of much more convenient content aggregating work and system, in terms of not only defining the intended sequence and ordering of learning activities, but also building the runtime environment for sequencing and navigation of learning activities and experiences.

• Informatization Policy
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• v.19 no.3
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• pp.19-35
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• 2012

As Internet users increasingly consume news through the Internet, Internet portals face criticism that they are quickening the softening of public news and molding public opinions. Some portals have started to provide newscast services that directly connect the press, not grouping news sources on their own standards. This study aims to clarify how news grouping models and newscast models are different in terms of news softening and agenda setting. Specifically, authors conduct a content analysis on time-specific news content provided by top three portals-Naver, Daum, and Nate. By doing so, this study examines characteristics of news service models of Internet portals and their social and political implications. According to our study, the softening and tabloidization of portal news had not been improved even after adopting the newscast model. Therefore, portal journalism should be reorganized as a way to circulate healthy and qualified news content.

• Journal of the Economic Geographical Society of Korea
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• v.27 no.1
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• pp.38-52
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• 2024

Digital transformation industry contributes to the improvement of productivity in overall industrial production, the smart green industry for carbon neutrality and sustainable growth is growing as a future industry. The purpose of this paper is to explore the status and role of the industry in the future industry innovation ecosystem through the analysis of the growth drivers and location pattern changes of the smart green industry. The industry is on the rise in both metropolitan and non-metropolitan areas, and the growth of the industry can be seen in non-metropolitan and non-urban areas. In particular, due to the smart green industrial complex pilot project, the creation of Gwangju Jeonnam Innovation City, and the promotion of new and renewable energy policies, the emergence of core aggregation areas (HH type) in the coastal areas of Honam and Chungcheongnam-do, and the formation of isolated centers (HL type) in the Gyeongsang region, new and renewable energy production companies are being accumulated in non-metropolitan areas. Therefore, the smart green industry is expected to promote the formation of various specialized spokes in non-urban areas in the future industrial innovation ecosystem that forms a multipolar hub-spoke network structure, where policy factors are the triggers for growth.

• Journal of Korean Society of Forest Science
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• v.95 no.3
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• pp.342-349
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• 2006

The survey guideline of forest products statistics suggests a certain type of standard to aggregate production amount of each item such as dry bracken, raw dates, cracked nuts, It does not, however, give any information about transition ratios, which would apply to convert weights of fresh bracken into dry one, or cracked nuts into the non-cracked. This has been one of the main factors which would make the statistics unreliable. The purpose of this study is to examine the aggregation realities and to put forward some proposals to improve forest products statistics with transition ratios. Targets of this study are 10 forest products that are strongly related to the mentioned problems. With the calculated transition ratios and some assumptions the changing rate of the official statistics of 2004 production amounts ranged from -41% to 474% for the 10 subjects. The suggested figures for transitions are based only on one-year analysis results. Therefore more periods are required to improve the accuracy and the reliability, and this study would be a good starting point.

• Journal of Environmental Policy
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• v.13 no.1
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• pp.69-93
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• 2014

The aim of this research was to develop a climate change vulnerability index at the district level (Si, Gun, Gu) with respect to the health care sector in Korea. The climate change vulnerability index was esimated based on the four major causes of climate-related illnesses : vector, flood, heat waves, and air pollution/allergies. The vulnerability assessment framework consists of six layers, all of which are based on the IPCC vulnerability concepts (exposure, sensitivity, and adaptive capacity) and the pathway of direct and indirect impacts of climate change modulators on health. We collected proxy variables based on the conceptual framework of climate change vulnerability. Data were standardized using the min-max normalization method. We applied the analytic hierarchy process (AHP) weight and aggregated the variables using the non-compensatory multi-criteria approach. To verify the index, sensitivity analysis was conducted by using another aggregation method (geometric transformation method, which was applied to the index of multiple deprivation in the UK) and weight, calculated by the Budget Allocation method. The results showed that it would be possible to identify the vulnerable areas by applying the developed climate change vulnerability assessment index. The climate change vulnerability index could then be used as a valuable tool in setting climate change adaptation policies in the health care sector.

• KDI Journal of Economic Policy
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• v.12 no.4
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• pp.47-69
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• 1990

Using an aggregator model, we look into the possibilities for substitution between Korea's exports, imports, domestic sales and domestic inputs (particularly labor), and substitution between disaggregated export and import components. Our approach heavily draws on an economy-wide GNP function that is similar to Samuelson's, modeling trade functions as derived from an integrated production system. Under the condition of homotheticity and weak separability, the GNP function would facilitate consistent aggregation that retains certain properties of the production structure. It would also be useful for a two-stage optimization process that enables us to obtain not only the net output price elasticities of the first-level aggregator functions, but also those of the second-level individual components of exports and imports. For the implementation of the model, we apply the Symmetric Generalized McFadden (SGM) function developed by Diewert and Wales to both stages of estimation. The first stage of the estimation procedure is to estimate the unit quantity equations of the second-level exports and imports that comprise four components each. The parameter estimates obtained in the first stage are utilized in the derivation of instrumental variables for the aggregate export and import prices being employed in the upper model. In the second stage, the net output supply equations derived from the GNP function are used in the estimation of the price elasticities of the first-level variables: exports, imports, domestic sales and labor. With these estimates in hand, we can come up with various elasticities of both the net output supply functions and the individual components of exports and imports. At the aggregate level (first-level), exports appear to be substitutable with domestic sales, while labor is complementary with imports. An increase in the price of exports would reduce the amount of the domestic sales supply, and a decrease in the wage rate would boost the demand for imports. On the other hand, labor and imports are complementary with exports and domestic sales in the input-output structure. At the disaggregate level (second-level), the price elasticities of the export and import components obtained indicate that both substitution and complement possibilities exist between them. Although these elasticities are interesting in their own right, they would be more usefully applied as inputs to the computational general equilibrium model.