• Journal of Korea Entertainment Industry Association
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• v.15 no.3
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• pp.243-250
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• 2021

The purpose of this study is to discuss the implicit meaning of advertising content with highly persuasive language formats from a communication perspective and its interpretation process in relation to communication education, while simultaneously developing interpretative codes for media literacy education in modern society. For a successful discussion, I assumed the narrative content of advertising content that implements a special purpose as a general conversational act, and raised the issue anew that regularity exists for implicit semantic expressions. It also said that in order for media literacy education in the present society to proceed correctly, linguistic interpretations of implicit meaning cannot be guided as a principle of communication in prior research. As a solution, we confirm that socio-cultural sharing knowledge and recognition are essential interpretation codes. For further discussion, the analysis of advertising media languages with special purposes in terms of language usage was conducted to verify the process of interpreting the implicit meaning shown in them. After analyzing the implicit advertising language that I arbitrarily typified, I found that the linguistic meaning implicit with the intention of persuading the speaker can be provided mostly as media literacy education as a framework for analysis by various information and cognitive effects. In other words, acceptors should not perform only literal interpretations in the process of interpreting the implicit meaning inherent in the media language. If guided by including native language materials and background knowledge, socio-cultural customs, and general common knowledge, efficient media literacy education can be expected.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.2
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• pp.267-277
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• 2017

One of fundamental problems in developing robust distributed services is how to achieve distributed consensus agreeing some data values that should be shared among participants in a distributed service. As one of algorithms for distributed consensus, Raft is known as a simple and understandable algorithm by decomposing the distributed consensus problem into three subproblems(leader election, log replication and safety). But, the algorithm dose not mention any types of dynamic configuration of participant peers such as adding new peers to a consensus group or deleting peers from the group. In this paper, we present a new consensus algorithm named Raft-D, which supports the dynamic configuration of participant peers by extending the Raft algorithm. For this, Raft-D manages the additional information maintained by participant nodes, and provides a technique to check the connection status of the nodes belonging to the consensus group. Based on the technique, Raft-D defines conditions and states to deal with adding new peers to the consensus group or deleting peers from the group. Based on those conditions and states, Raft-D performs the dynamic configuration process for a consensus group through the log update mechanism of the Raft algorithm.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.284-301
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• 2023

The changes in rice climatic yield potential (CYP) across the Korean Peninsula are evaluated based on the new climate change scenario produced by the National Institute of Agricultural Sciences with 18 ensemble members at 1 km resolution under a Shared Socioeconomic Pathway (SSP) and Representative Concentration Pathways (RCP) emission scenarios. To overcome the data availability, we utilize solar radiation f or CYP instead of sunshine duration which is relatively uncommon in the climate prediction f ield. The result show that maximum CYP(CYPmax) decreased, and the optimal heading date is progressively delayed under warmer temperature conditions compared to the current climate. This trend is particularly pronounced in the SSP5-85 scenario, indicating faster warming, except for the northeastern mountainous regions of North Korea. This shows the benef its of lower emission scenarios and pursuing more efforts to limit greenhouse gas emissions. On the other hand, the CYPmax shows a wide range of feasible futures, which shows inherent uncertainties in f uture climate projections and the risks when analyzing a single model or a small number of model results, highlighting the importance of the ensemble approach. The f indings of this study on changes in rice productivity and uncertainties in temperature and solar radiation during the 21st century, based on climate change scenarios, hold value as f undamental information for climate change adaptation efforts.

• Journal of Internet Computing and Services
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• v.24 no.6
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• pp.81-89
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• 2023

In modern society, blind people face difficulties in navigating common environments such as sidewalks, elevators, and crosswalks. Research has been conducted to alleviate these inconveniences for the visually impaired through the use of visual and audio aids. However, such research often encounters limitations when it comes to practical implementation due to the high cost of wearable devices, high-performance CCTV systems, and voice sensors. In this paper, we propose an artificial intelligence fusion algorithm that utilizes low-cost video sensors integrated into smartphones to help blind people safely navigate their surroundings during walking. The proposed algorithm combines motion capture and object detection algorithms to detect moving people and various obstacles encountered during walking. We employed the MediaPipe library for motion capture to model and detect surrounding pedestrians during motion. Additionally, we used object detection algorithms to model and detect various obstacles that can occur during walking on sidewalks. Through experimentation, we validated the performance of the artificial intelligence fusion algorithm, achieving accuracy of 0.92, precision of 0.91, recall of 0.99, and an F1 score of 0.95. This research can assist blind people in navigating through obstacles such as bollards, shared scooters, and vehicles encountered during walking, thereby enhancing their mobility and safety.

• Knowledge Management Research
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• v.24 no.4
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• pp.131-152
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• 2023

One of the key domains within a smart tourism city, smart mobility, encompasses advanced transportation means and services rooted in Information and Communication Technology (ICT). This includes shared bicycles, scooters, car-sharing services, smart transportation infrastructure, and more, aiming to surpass limitations of conventional transport and improve the movement of people and goods. It also serves tourists as an affordable and convenient mode of transport between attractions while also enhancing the overall travel experience. This study has defined 'smart tourism mobility' as a form of mobility grounded in ICT, exhibiting exceptional connectivity, serving public interest, and serving as a mode of transport for both residents and tourists in a smart tourism city. The research aimed to outline the scope of smart tourism mobility-related industries through expert Delphi surveys and estimate their economic effects within a smart tourism city. Specifically, this study updated 2015 input-output table and made 2020 regional input-output table of Seoul adopting RAS method and location quotient method. The results showed that the about 2.8 billion KRW investment of Seoul in smart tourism mobility may create more than 4.1 billion KRW in production inducement effect which is expected to create more than 1.6 billion KRW of income-inducing effect, 3.6 billion KRW of value-added-inducing effect, and 54 employment across all industries in Seoul in 2022.

• Atmosphere
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• v.34 no.2
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• pp.123-138
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• 2024

Using 18 multi-model-based a Shared Socioeconomic Pathway (SSP) and Representative Concentration Pathways (RCP) climate change scenarios, future changes in temperature and warmth index on the Korean Peninsula in the 21st century (2011~2100) were analyzed. In the analysis of the current climate (1981~2010), the ensemble averaged model results were found to reproduce the observed average values and spatial patterns of temperature and warmth index similarly well. In the future climate projections, temperature and warmth index are expected to rise in the 21st century compared to the current climate. They go further into the future and the higher carbon scenario (SSP5-8.5), the larger the increase. In the 21st century, in the low-carbon scenario (SSP1-2.6), temperature and warmth index are expected to rise by about 2.5℃ and 24.6%, respectively, compared to the present, while in the high-carbon scenario, they are expected to rise by about 6.2℃ and 63.9%, respectively. It was analyzed that reducing carbon emissions could contribute to reducing the increase in temperature and warmth index. The increase in the warmth index due to climate change can be positively analyzed to indicate that the effective heat required for plant growth on the Korean Peninsula will be stably secured. However, it is necessary to comprehensively consider negative aspects such as changes in growth conditions during the plant growth period, increase in extreme weather such as abnormally high temperatures, and decrease in plant diversity. This study can be used as basic scientific information for adapting to climate change and preparing response measures.

• Journal of Ecology and Environment
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• v.48 no.1
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• pp.96-109
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• 2024

Background: Khyber Pakhtunkhwa government initiated the Billion Tree Tsunami Afforestation Project including regeneration and afforestation approaches. An effort was made to assess the distribution characteristics of afforested species under present and future climatic scenarios using ecological niche modelling. For sustainable forest management, landscape ecology can play a significant role. A significant change in the potential distribution of tree species is expected globally with changing climate. Ecological niche modeling provides the valuable information about the current and future distribution of species that can play crucial role in deciding the potential sites for afforestation which can be used by government institutes for afforestation programs. In this context, the potential distribution of 8 tree species, Cedrus deodara, Dalbergia sissoo, Juglans regia, Pinus wallichiana, Eucalyptus camaldulensis, Senegalia modesta, Populus ciliata, and Vachellia nilotica was modeled. Results: Maxent species distribution model was used to predict current and future distribution of tree species using bioclimatic variables along with soil type and elevation. Future climate scenarios, shared socio-economic pathways (SSP)2-4.5 and SSP5-8.5 were considered for the years 2041-2060 and 2081-2100. The model predicted high risk of decreasing potential distribution under SSP2-4.5 and SSP5-8.5 climate change scenarios for years 2041-2060 and 2081-2100, respectively. Recent afforestation conservation sites of these 8 tree species do not fall within their predicted potential habitat for SSP2-4.5 and SSP5-8.5 climate scenarios. Conclusions: Each tree species responded independently in terms of its potential habitat to future climatic conditions. Cedrus deodara and P. ciliata are predicted to migrate to higher altitude towards north in present and future climate scenarios. Habitat of D. sissoo, P. wallichiana, J. regia, and V. nilotica is practiced to be declined in future climate scenarios. Eucalyptus camaldulensis is expected to be expanded its suitability area in future with eastward shift. Senegalia modesta habitat increased in the middle of the century but decreased afterwards in later half of the century. The changing and shifting forests create challenges for sustainable landscapes. Therefore, the study is an attempt to provide management tools for monitoring the climate change-driven shifting of forest landscapes.

• Journal of the Korea Computer Graphics Society
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• v.30 no.3
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• pp.81-86
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• 2024

The Image Signal Processor (ISP) converts RAW images captured by the camera sensor into user-preferred sRGB images. While RAW images contain more meaningful information for image processing than sRGB images, RAW images are rarely shared due to their large sizes. Moreover, the actual ISP process of a camera is not disclosed, making it difficult to model the inverse process. Consequently, research on learning the conversion between sRGB and RAW has been conducted. Recently, the ParamISP[1] model, which directly incorporates camera parameters (exposure time, sensitivity, aperture size, and focal length) to mimic the operations of a real camera ISP, has been proposed by advancing the simple network structures. However, existing studies, including ParamISP[1], have limitations in modeling the camera ISP as they do not consider the degradation caused by lens shading, optical aberration, and lens distortion, which limits the restoration performance. This study introduces Positional Encoding to enable the camera ISP neural network to better handle degradations caused by lens. The proposed positional encoding method is suitable for camera ISP neural networks that learn by dividing the image into patches. By reflecting the spatial context of the image, it allows for more precise image restoration compared to existing models.

• Asia pacific journal of information systems
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• v.18 no.3
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• pp.21-43
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• 2008

The task network which is formed of different individuals can be recognized as a social network. Therefore, the way to communicate with people inside or outside the network has considerable influence on their outcome. Moreover, the position on which a member stands in a network shows the different effects of the information systems supporting communication with others. In this paper, it is to be studied how personal CMC (computer-mediated communication) tools affect the mission that those who work for a network perform through diverse task networks. Especially, we focused on synchronicity of CMC. On this score, the perspective of Media Synchronicity Theory was taken that had been suggested by criticizing Media Richness Theory. It is the objective, from this perspective, to find which characteristics of networks make the value of IT supporting synchronicity high. In the research trends of social networks, there have been two traditional perspectives to explain the effect of network: embeddedness and diversity ones. These differ from the aspect which type of social network can provide much more economic benefits. As similar studies have been reported by various researchers, these are also divided into the bonding and bridging views which are based on internal and external tie, respectively, Size, density, and centrality were measured as the characteristics of personal task networks. Size means the level of relationship between members. It is the total number of other colleagues who work with a specific member for a certain project. It means, the larger the size of task network, the more the number of coworkers who interact each other through the job. Density is the ratio of the number of relationships arranged actually to the total number of available ones. In an ego-centered network, it is defined as the ratio of the number of relationship made really to the total number of possible ones between members who are actually involved each other. The higher the level of density, the larger the number of projects on which the members collaborate. Centrality means that his/her position is on the exact center of whole network. There are several methods to measure it. In this research, betweenness centrality was adopted among them. It is measured by the position on which one member stands between others in a network. The determinant to raise its level is the shortest geodesic that represents the shortest distance between members. Centrality also indicates the level of role as a broker among others. To verify the hypotheses, we interviewed and surveyed a group of employees of a nationwide financial organization in which a groupware system is used. They were questioned about two CMC applications: MSN with a higher level of synchronicity and email with a lower one. As a result, the larger the size of his/her own task network, the smaller its density and the higher the level of his/her centrality, the higher the level of the effect using the task network with CMC tools. Above all, this positive effect is verified to be much more produced while using CMC applications with higher-level synchronicity. Among the a variety of situations under which the use of CMC gives more benefits, this research is considered as one of rare cases regarding the characteristics of task network as moderators by focusing ITs for the operation of his/her own task network. It is another contribution of this research to prove empirically that the values of information system depend on the social, or comparative, characteristic of time. Though the same amount of time is shared, the social characteristics of users change its value. In addition, it is significant to examine empirically that the ITs with higher-level synchronicity have the positive effect on productivity. Many businesses are worried about the negative effect of synchronous ITs, for their employees are likely to use them for personal social activities. However. this research can help to dismiss the concern against CMC tools.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.1-18
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• 2016

Owing to the extensive use of Web media and the development of the IT industry, a large amount of data has been generated, shared, and stored. Nowadays, various types of unstructured data such as image, sound, video, and text are distributed through Web media. Therefore, many attempts have been made in recent years to discover new value through an analysis of these unstructured data. Among these types of unstructured data, text is recognized as the most representative method for users to express and share their opinions on the Web. In this sense, demand for obtaining new insights through text analysis is steadily increasing. Accordingly, text mining is increasingly being used for different purposes in various fields. In particular, issue tracking is being widely studied not only in the academic world but also in industries because it can be used to extract various issues from text such as news, (SocialNetworkServices) to analyze the trends of these issues. Conventionally, issue tracking is used to identify major issues sustained over a long period of time through topic modeling and to analyze the detailed distribution of documents involved in each issue. However, because conventional issue tracking assumes that the content composing each issue does not change throughout the entire tracking period, it cannot represent the dynamic mutation process of detailed issues that can be created, merged, divided, and deleted between these periods. Moreover, because only keywords that appear consistently throughout the entire period can be derived as issue keywords, concrete issue keywords such as "nuclear test" and "separated families" may be concealed by more general issue keywords such as "North Korea" in an analysis over a long period of time. This implies that many meaningful but short-lived issues cannot be discovered by conventional issue tracking. Note that detailed keywords are preferable to general keywords because the former can be clues for providing actionable strategies. To overcome these limitations, we performed an independent analysis on the documents of each detailed period. We generated an issue flow diagram based on the similarity of each issue between two consecutive periods. The issue transition pattern among categories was analyzed by using the category information of each document. In this study, we then applied the proposed methodology to a real case of 53,739 news articles. We derived an issue flow diagram from the articles. We then proposed the following useful application scenarios for the issue flow diagram presented in the experiment section. First, we can identify an issue that actively appears during a certain period and promptly disappears in the next period. Second, the preceding and following issues of a particular issue can be easily discovered from the issue flow diagram. This implies that our methodology can be used to discover the association between inter-period issues. Finally, an interesting pattern of one-way and two-way transitions was discovered by analyzing the transition patterns of issues through category analysis. Thus, we discovered that a pair of mutually similar categories induces two-way transitions. In contrast, one-way transitions can be recognized as an indicator that issues in a certain category tend to be influenced by other issues in another category. For practical application of the proposed methodology, high-quality word and stop word dictionaries need to be constructed. In addition, not only the number of documents but also additional meta-information such as the read counts, written time, and comments of documents should be analyzed. A rigorous performance evaluation or validation of the proposed methodology should be performed in future works.