• The Journal of the Korea Contents Association
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• v.13 no.12
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• pp.38-47
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• 2013

An image coding based on MRC model, a kind of multi-layer image model, first segments a screen image into foreground, mask, and background layers, and then compresses each layer using a codec that is suitable to the layer. The mask layer defines the position of foreground regions such as textual and graphical contents. The colour signal of the foreground (background) region is saved in the foreground (background) layer. The mask layer which contains the segmentation result of foreground and background regions is of importance since its accuracy directly affects the overall coding performance of the codec. This paper proposes a new layer segmentation algorithm for the MRC based image coding. The proposed method extracts text pixels from the background using morphological top hat filtering. The application of white or black top hat transformation to local blocks is controlled by the information of relative brightness of text compared to the background. In the proposed method, the boundary information of text that is extracted from the edge map of the block is used for the robust decision on the relative brightness of text. Simulation results show that the proposed method is superior to the conventional methods.

• Journal of Broadcast Engineering
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• v.26 no.4
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• pp.429-440
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• 2021

With the recent development of deep convolutional neural network learning, deep learning techniques applied to single image super-resolution are showing good results. One of the existing deep learning-based super-resolution techniques is RDN(Residual Dense Network), in which the initial feature information is transmitted to the last layer using residual dense blocks, and subsequent layers are restored using input information of previous layers. However, if all hierarchical features are connected and learned and a large number of residual dense blocks are stacked, despite good performance, a large number of parameters and huge computational load are needed, so it takes a lot of time to learn a network and a slow processing speed, and it is not applicable to a mobile system. In this paper, we use the residual dense structure, which is a continuous memory structure that reuses previous information, and the residual dense channel attention block using the channel attention method that determines the importance according to the feature map of the image. We propose a method that can increase the depth to obtain a large receptive field and maintain a concise model at the same time. As a result of the experiment, the proposed network obtained PSNR as low as 0.205dB on average at 4× magnification compared to RDN, but about 1.8 times faster processing speed, about 10 times less number of parameters and about 1.74 times less computation.

• Journal of Korea Port Economic Association
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• v.38 no.4
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• pp.45-64
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• 2022

Due to the recent and rapid globalization, logistics outsourcing has expanded globally and is seen as a means of creating a robust logistics system. However, many businesses continue to have difficulties with their logistics outsourcing contracts, which compels them to reinstate the logistics function for internal management. This study aims to investigate how organizational capabilities of logistics service providers (LSPs), notably flexibility, integration, innovation, and technological capabilities, impact on the logistics outsourcing success in Ugandan food processing firms. Using a structured questionnaire survey, cross-sectional data collected from 211 food processing firms in Kampala - Uganda were analyzed by partial least squares-structural equation modeling (PLS-SEM) using SmartPLS 3.3.7 software to examine the theorized relationships. The study findings revealed that whereas the technological and innovation capabilities positively and significantly influence logistics outsourcing success, the effects of flexibility and integration capabilities were insignificant. Additionally, the importance-performance map analysis (IPMA) reveals that the technological capability is a priority capability, followed by the innovation capability if logistics outsourcing success is to be achieved. Conversely, flexibility and integration capabilities are of low priority.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.26 no.6
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• pp.67-84
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• 2023

In some areas of the Republic of Korea, the designation and management of conservation areas do not adequately reflect regional characteristics and often impose behavioral regulations without considering the local context. One prominent example is the Busan EDC area. As a result, conflicts may arise, including large-scale civil complaints, regarding the conservation and utilization of these areas. Therefore, for the efficient designation and management of protected areas, it is necessary to consider various ecosystem factors, changes in land use, and regional characteristics. In this study, we specifically focused on the Busan EDC area and applied machine learning techniques to analyze the habitat of regional species. Additionally, we employed Explainable Artificial Intelligence techniques to interpret the results of our analysis. To analyze the regional characteristics of the waterfront area in the Busan EDC district and the habitat of migratory birds, we used bird observations as dependent variables, distinguishing between presence and absence. The independent variables were constructed using land cover, elevation, slope, bridges, and river depth data. We utilized the XGBoost (eXtreme Gradient Boosting) model, known for its excellent performance in various fields, to predict the habitat probabilities of 11 bird species. Furthermore, we employed the SHapley Additive exPlanations technique, one of the representative methodologies of XAI, to analyze the relative importance and impact of the variables used in the model. The analysis results showed that in the EDC business district, as one moves closer to the river from the waterfront, the likelihood of bird habitat increases based on the overlapping habitat probabilities of the analyzed bird species. By synthesizing the major variables influencing the habitat of each species, key variables such as rivers, rice fields, fields, pastures, inland wetlands, tidal flats, orchards, cultivated lands, cliffs & rocks, elevation, lakes, and deciduous forests were identified as areas that can serve as habitats, shelters, resting places, and feeding grounds for birds. On the other hand, artificial structures such as bridges, railways, and other public facilities were found to have a negative impact on bird habitat. The development of a management plan for conservation areas based on the objective analysis presented in this study is expected to be extensively utilized in the future. It will provide diverse evidential materials for establishing effective conservation area management strategies.

• Journal of agricultural medicine and community health
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• v.26 no.1
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• pp.19-35
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• 2001

This study was conducted to investigate the internal changes and the countermeasure for performance improvement by Separation of Prescribing and Dispensing Practice (SPDP) in Health Center. Data were collected from two sources: Performance report before and after SPDP of 25 Health Centers in Kyongsangbuk-do and 6 Health Centers in Daegu-City and self-administerd questionnaire survey of 221 officials at health center. The results of this study were summarized as follows: Twenty-four health centers(77.4%) of 31 health centers took convenience measures for medical treatment of citizens and convenience measures were getting map of pharmacy, improvement of health center interior, introduction of order communication system in order. After the SPDP in health centers, 19.4% of health centers increased doctors and 25.8% decreased pharmacists. 58.1% of health centers showed that number of medical treatments were decreased. 96.4%, 80.6% 80.6% 96.7% of health centers showed that number of prescriptions, total medical treatment expenses, amounts paid by the insureds and the expenses to purchase drugs, respectively, were decreased. More than fifty percent(54.2%) of health centers responded that the relative importance of health works increased compared to medical treatments after the SPDP, and number of patients decreased compared to those in before the SPDP. And there was a drastic reduction in number of prescriptions, total medical treatment expenses, amounts paid by insureds, the expenses to purchase drugs after the SPDP. Above fifty percent(57.6%) of officers at health center responded that the function of medical treatment should be reduced after the SPDP. Fields requested improvement in health centers were 'development of heath works contents'(62.4%), 'rearrangement of health center personnel'(51.6%), 'priority setting for health works'(48.4%), 'restructuring the organization'(36.2%), 'quality impro­vement for medical services'(32.1%), 'replaning the budgets'(23.1%) in order. And to better the image of health centers, health center officers replied that 'health information management'(60.7%), 'public relations for health center'(15.8%), 'kindness of health center officers'(15.3%) were necessary in order. Health center officers suggested that 'vaccination program', 'health promotion', 'maternal and children health', 'communicable disease management', 'community health planning' were relatively important works, in order, performed by health center after SPDP. In the future, medical services in health centers should be cut down with a momentum of the SPDP so that health centers might reestablish their functions and roles as public health organizations, but quality of medical services must be improved. Also health centers should pay attention to residents for improving health through 'vaccination program', 'health promotion', 'mother-children health', 'acute and chronic communicable disease management', 'community health planning', 'oral health', 'chronic degenerative disease management', etc. And there should be a differentiation of relative importance between health promotion services and medical treatment services by character of areas(metropolitan, city, county).

• Journal of Intelligence and Information Systems
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• v.19 no.4
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• pp.81-96
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• 2013

Video information retrieval has become a very important issue because of the explosive increase in video data from Web content development. Meanwhile, content-based video analysis using visual features has been the main source for video information retrieval and browsing. Content in video can be represented with content-based analysis techniques, which can extract various features from audio-visual data such as frames, shots, colors, texture, or shape. Moreover, similarity between videos can be measured through content-based analysis. However, a movie that is one of typical types of video data is organized by story as well as audio-visual data. This causes a semantic gap between significant information recognized by people and information resulting from content-based analysis, when content-based video analysis using only audio-visual data of low level is applied to information retrieval of movie. The reason for this semantic gap is that the story line for a movie is high level information, with relationships in the content that changes as the movie progresses. Information retrieval related to the story line of a movie cannot be executed by only content-based analysis techniques. A formal model is needed, which can determine relationships among movie contents, or track meaning changes, in order to accurately retrieve the story information. Recently, story-based video analysis techniques have emerged using a social network concept for story information retrieval. These approaches represent a story by using the relationships between characters in a movie, but these approaches have problems. First, they do not express dynamic changes in relationships between characters according to story development. Second, they miss profound information, such as emotions indicating the identities and psychological states of the characters. Emotion is essential to understanding a character's motivation, conflict, and resolution. Third, they do not take account of events and background that contribute to the story. As a result, this paper reviews the importance and weaknesses of previous video analysis methods ranging from content-based approaches to story analysis based on social network. Also, we suggest necessary elements, such as character, background, and events, based on narrative structures introduced in the literature. We extract characters' emotional words from the script of the movie Pretty Woman by using the hierarchical attribute of WordNet, which is an extensive English thesaurus. WordNet offers relationships between words (e.g., synonyms, hypernyms, hyponyms, antonyms). We present a method to visualize the emotional pattern of a character over time. Second, a character's inner nature must be predetermined in order to model a character arc that can depict the character's growth and development. To this end, we analyze the amount of the character's dialogue in the script and track the character's inner nature using social network concepts, such as in-degree (incoming links) and out-degree (outgoing links). Additionally, we propose a method that can track a character's inner nature by tracing indices such as degree, in-degree, and out-degree of the character network in a movie through its progression. Finally, the spatial background where characters meet and where events take place is an important element in the story. We take advantage of the movie script to extracting significant spatial background and suggest a scene map describing spatial arrangements and distances in the movie. Important places where main characters first meet or where they stay during long periods of time can be extracted through this scene map. In view of the aforementioned three elements (character, event, background), we extract a variety of information related to the story and evaluate the performance of the proposed method. We can track story information extracted over time and detect a change in the character's emotion or inner nature, spatial movement, and conflicts and resolutions in the story.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.1009-1029
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• 2023

Urban trees play a vital role in urban ecosystems,significantly reducing impervious surfaces and impacting carbon cycling within the city. Although previous research has demonstrated the efficacy of employing artificial intelligence in conjunction with airborne light detection and ranging (LiDAR) data to generate urban tree information, the availability and cost constraints associated with LiDAR data pose limitations. Consequently, this study employed freely accessible, high-resolution multispectral satellite imagery (i.e., Sentinel-2 data) to estimate fractional tree canopy cover (FTC) within the urban confines of Suwon, South Korea, employing machine learning techniques. This study leveraged a median composite image derived from a time series of Sentinel-2 images. In order to account for the diverse land cover found in urban areas, the model incorporated three types of input variables: average (mean) and standard deviation (std) values within a 30-meter grid from 10 m resolution of optical indices from Sentinel-2, and fractional coverage for distinct land cover classes within 30 m grids from the existing level 3 land cover map. Four schemes with different combinations of input variables were compared. Notably, when all three factors (i.e., mean, std, and fractional cover) were used to consider the variation of landcover in urban areas(Scheme 4, S4), the machine learning model exhibited improved performance compared to using only the mean of optical indices (Scheme 1). Of the various models proposed, the random forest (RF) model with S4 demonstrated the most remarkable performance, achieving R² of 0.8196, and mean absolute error (MAE) of 0.0749, and a root mean squared error (RMSE) of 0.1022. The std variable exhibited the highest impact on model outputs within the heterogeneous land covers based on the variable importance analysis. This trained RF model with S4 was then applied to the entire Suwon region, consistently delivering robust results with an R² of 0.8702, MAE of 0.0873, and RMSE of 0.1335. The FTC estimation method developed in this study is expected to offer advantages for application in various regions, providing fundamental data for a better understanding of carbon dynamics in urban ecosystems in the future.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.1
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• pp.48-59
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• 2023

Ground-level ozone affects human health and plant growth. Ozone is produced by chemical reactions between oxides of nitrogen (NOx) and volatile organic compounds (VOCs) from anthropogenic and biogenic sources. In this study, two different land cover and emission factor datasets were input to the MEGAN v2.1 emission model to examine how these parameters contribute to the biogenic emissions and ozone production. Four input sensitivity scenarios (A, B, C and D) were generated from land cover and vegetation emission factors combination. The effects of BVOCs emissions by scenario were also investigated. From air quality modeling result using CAMx, maximum 1 hour ozone concentrations were estimated 62 ppb, 60 ppb, 68 ppb, 65 ppb, 55 ppb for scenarios A, B, C, D and E, respectively. For maximum 8 hour ozone concentration, 57 ppb, 56 ppb, 63 ppb, 60 ppb, and 53 ppb were estimated by scenario. The minimum difference by land cover was up to 25 ppb and by emission factor that was up to 35 ppb. From the modeling performance evaluation using ground ozone measurement over the six regions (East Seoul, West Seoul, Incheon, Namyangju, Wonju, and Daegu), the model performed well in terms of the correlation coefficient (0.6 to 0.82). For the 4 urban regions (East Seoul, West Seoul, Incheon, and Namyangju), ozone simulations were not quite sensitive to the change of BVOC emissions. For rural regions (Wonju and Daegu) , however, BVOC emission affected ozone concentration much more than previously mentioned regions, especially in case of scenario C. This implies the importance of biogenic emissions on ozone production over the sub-urban to rural regions.