• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.185-202
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• 2012

.Since the value of information has been realized in the information society, the usage and collection of information has become important. A facial expression that contains thousands of information as an artistic painting can be described in thousands of words. Followed by the idea, there has recently been a number of attempts to provide customers and companies with an intelligent service, which enables the perception of human emotions through one's facial expressions. For example, MIT Media Lab, the leading organization in this research area, has developed the human emotion prediction model, and has applied their studies to the commercial business. In the academic area, a number of the conventional methods such as Multiple Regression Analysis (MRA) or Artificial Neural Networks (ANN) have been applied to predict human emotion in prior studies. However, MRA is generally criticized because of its low prediction accuracy. This is inevitable since MRA can only explain the linear relationship between the dependent variables and the independent variable. To mitigate the limitations of MRA, some studies like Jung and Kim (2012) have used ANN as the alternative, and they reported that ANN generated more accurate prediction than the statistical methods like MRA. However, it has also been criticized due to over fitting and the difficulty of the network design (e.g. setting the number of the layers and the number of the nodes in the hidden layers). Under this background, we propose a novel model using Support Vector Regression (SVR) in order to increase the prediction accuracy. SVR is an extensive version of Support Vector Machine (SVM) designated to solve the regression problems. The model produced by SVR only depends on a subset of the training data, because the cost function for building the model ignores any training data that is close (within a threshold ${\varepsilon}$) to the model prediction. Using SVR, we tried to build a model that can measure the level of arousal and valence from the facial features. To validate the usefulness of the proposed model, we collected the data of facial reactions when providing appropriate visual stimulating contents, and extracted the features from the data. Next, the steps of the preprocessing were taken to choose statistically significant variables. In total, 297 cases were used for the experiment. As the comparative models, we also applied MRA and ANN to the same data set. For SVR, we adopted '${\varepsilon}$-insensitive loss function', and 'grid search' technique to find the optimal values of the parameters like C, d, ${\sigma}^2$, and ${\varepsilon}$. In the case of ANN, we adopted a standard three-layer backpropagation network, which has a single hidden layer. The learning rate and momentum rate of ANN were set to 10%, and we used sigmoid function as the transfer function of hidden and output nodes. We performed the experiments repeatedly by varying the number of nodes in the hidden layer to n/2, n, 3n/2, and 2n, where n is the number of the input variables. The stopping condition for ANN was set to 50,000 learning events. And, we used MAE (Mean Absolute Error) as the measure for performance comparison. From the experiment, we found that SVR achieved the highest prediction accuracy for the hold-out data set compared to MRA and ANN. Regardless of the target variables (the level of arousal, or the level of positive / negative valence), SVR showed the best performance for the hold-out data set. ANN also outperformed MRA, however, it showed the considerably lower prediction accuracy than SVR for both target variables. The findings of our research are expected to be useful to the researchers or practitioners who are willing to build the models for recognizing human emotions.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.75-100
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• 2018

Mobile devices have become an important channel for news content usage in our daily life. However, online news content readers' resistance to online news monetization is more serious than other digital content businesses, such as webtoons, music sources, videos, and games. Since major portal sites distribute online news content free of charge to increase their traffics, customers have been accustomed to free news content; hence this makes online news providers more difficult to switch their policies on business models (i.e., monetization policy). As a result, most online news providers are highly dependent on the advertising business model, which can lead to increasing number of false, exaggerated, or sensational advertisements inside the news website to maximize their advertising revenue. To reduce this advertising dependencies, many online news providers had attempted to switch their 'free' readers to 'paid' users, but most of them failed. However, recently, some online news media have been successfully applying the Pay-What-You-Want (PWYW) payment model, which allows readers to voluntarily pay fees for their favorite news content. These successful cases shed some lights to the managers of online news content provider regarding that the PWYW model can serve as an alternative business model. In this study, therefore, we collected 379 online news articles from Ohmynews.com that has been successfully employing the PWYW model, and analyzed the comparative importance of systematic attributes of online news content on readers' voluntary payment. More specifically, we derived the six systematic attributes (i.e., Type of Article Title, Image Stimulation, Article Readability, Article Type, Dominant Emotion, and Article-Image Similarity) and three or four levels within each attribute based on previous studies. Then, we conducted content analysis to measure five attributes except Article Readability attribute, measured by Flesch readability score. Before conducting main content analysis, the face reliabilities of chosen attributes were measured by three doctoral level researchers with 37 sample articles, and inter-coder reliabilities of the three coders were verified. Then, the main content analysis was conducted for two months from March 2017 with 379 online news articles. All 379 articles were reviewed by the same three coders, and 65 articles that showed inconsistency among coders were excluded before employing conjoint analysis. Finally, we examined the comparative importance of those six systematic attributes (Study 1), and levels within each of the six attributes (Study 2) through conjoint analysis with 314 online news articles. From the results of conjoint analysis, we found that Article Readability, Article-Image Similarity, and Type of Article Title are the most significant factors affecting online news readers' voluntary payment. First, it can be interpreted that if the level of readability of an online news article is in line with the readers' level of readership, the readers will voluntarily pay more. Second, the similarity between the content of the article and the image within it enables the readers to increase the information acceptance and to transmit the message of the article more effectively. Third, readers expect that the article title would reveal the content of the article, and the expectation influences the understanding and satisfaction of the article. Therefore, it is necessary to write an article with an appropriate readability level, and use images and title well matched with the content to make readers voluntarily pay more. We also examined the comparative importance of levels within each attribute in more details. Based on findings of two studies, two major and nine minor propositions are suggested for future empirical research. This study has academic implications in that it is one of the first studies applying both content analysis and conjoint analysis together to examine readers' voluntary payment behavior, rather than their intention to pay. In addition, online news content creators, providers, and managers could find some practical insights from this research in terms of how they should produce news content to make readers voluntarily pay more for their online news content.

• The Journal of Korean Society for Radiation Therapy
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• v.32
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• pp.93-109
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• 2020

Purpose: The radiochromic film (Gafchromic EBT3, Ashland Advanced Materials, USA) and 3-dimensional analysis system dosimetry checkTM (DC, MathResolutions, USA) were evaluated for patient-specific quality assurance (QA) of helical tomotherapy. Materials and Methods: Depending on the tumors' positions, three types of targets, which are the abdominal tumor (130.6㎤), retroperitoneal tumor (849.0㎤), and the whole abdominal metastasis tumor (3131.0㎤) applied to the humanoid phantom (Anderson Rando Phantom, USA). We established a total of 12 comparative treatment plans by the four geometric conditions of the beam irradiation, which are the different field widths (FW) of 2.5-cm, 5.0-cm, and pitches of 0.287, 0.43. Ionization measurements (1D) with EBT3 by inserting the cheese phantom (2D) were compared to DC measurements of the 3D dose reconstruction on CT images from beam fluence log information. For the clinical feasibility evaluation of the DC, dose reconstruction has been performed using the same cheese phantom with the EBT3 method. Recalculated dose distributions revealed the dose error information during the actual irradiation on the same CT images quantitatively compared to the treatment plan. The Thread effect, which might appear in the Helical Tomotherapy, was analyzed by ripple amplitude (%). We also performed gamma index analysis (DD: 3mm/ DTA: 3%, pass threshold limit: 95%) for pattern check of the dose distribution. Results: Ripple amplitude measurement resulted in the highest average of 23.1% in the peritoneum tumor. In the radiochromic film analysis, the absolute dose was on average 0.9±0.4%, and gamma index analysis was on average 96.4±2.2% (Passing rate: >95%), which could be limited to the large target sizes such as the whole abdominal metastasis tumor. In the DC analysis with the humanoid phantom for FW of 5.0-cm, the three regions' average was 91.8±6.4% in the 2D and 3D plan. The three planes (axial, coronal, and sagittal) and dose profile could be analyzed with the entire peritoneum tumor and the whole abdominal metastasis target, with planned dose distributions. The dose errors based on the dose-volume histogram in the DC evaluations increased depending on FW and pitch. Conclusion: The DC method could implement a dose error analysis on the 3D patient image data by the measured beam fluence log information only without any dosimetry tools for patient-specific quality assurance. Also, there may be no limit to apply for the tumor location and size; therefore, the DC could be useful in patient-specific QAl during the treatment of Helical Tomotherapy of large and irregular tumors.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.1
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• pp.115-127
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• 2018

This study aims to propose management strategies of ventilation paths for improving urban thermal environments. For this purpose, Gimhae-si in Gyeongsangnamdo was selected as a study area. We analyzed hot spots and cool spots in Gimhae by using Landsat 8 satellite image data and spatial statistical analysis, and finally derived the vulnerable areas to thermal environment. In addition, the characteristics of ventilation paths including wind direction and wind speed were analyzed by using data of the wind resource map provided by Korea Meteorological Administration. As a result, it was found that a lot of hot spots were similar to those with weak wind such as Jinyoung-eup, Jillye-myeon, Juchon-myeon and the downtown area. Based on the analysis, management strategies of ventilation paths in Gimhye were presented as follows. Jinyoung-eup and Jillye-myeon with hot spot areas and week wind areas have a strong possibility that hot spot areas will be extended and strengthened, because industrial areas are being built. Hence, climate-friendly urban and architectural plans considering ventilation paths is required in these areas. In Juchon-myeon, where industrial complexes and agricultural complexes are located, climate-friendly plans are also required because high-rise apartment complexes and an urban development zone are planned, which may induce worse thermal environment in the future. It is expected that a planning of securing and enlarging ventilation paths will be established for climate-friendly urban management. and further the results will be utilized in urban renewal and environmental planning as well as urban basic plans. In addition, we expect that the results can be applied as basic data for climate change adaptation plan and the evaluation system for climate-friendly urban development of Gimhye.

• Geophysics and Geophysical Exploration
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• v.21 no.3
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• pp.171-182
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• 2018

We performed the seismic field data processing using an open-source software (Madagascar) to verify if it is applicable to processing of field data, which has low signal-to-noise ratio and high uncertainties in velocities. The Madagascar, based on Python, is usually supposed to be better in the development of processing technologies due to its capabilities of multidimensional data analysis and reproducibility. However, this open-source software has not been widely used so far for field data processing because of complicated interfaces and data structure system. To verify the effectiveness of the Madagascar software on field data, we applied it to a typical seismic data processing flow including data loading, geometry build-up, F-K filter, predictive deconvolution, velocity analysis, normal moveout correction, stack, and migration. The field data for the test were acquired in Gunsan Basin, Yellow Sea using a streamer consisting of 480 channels and 4 arrays of air-guns. The results at all processing step are compared with those processed with Landmark's ProMAX (SeisSpace R5000) which is a commercial processing software. Madagascar shows relatively high efficiencies in data IO and management as well as reproducibility. Additionally, it shows quick and exact calculations in some automated procedures such as stacking velocity analysis. There were no remarkable differences in the results after applying the signal enhancement flows of both software. For the deeper part of the substructure image, however, the commercial software shows better results than the open-source software. This is simply because the commercial software has various flows for de-multiple and provides interactive processing environments for delicate processing works compared to Madagascar. Considering that many researchers around the world are developing various data processing algorithms for Madagascar, we can expect that the open-source software such as Madagascar can be widely used for commercial-level processing with the strength of expandability, cost effectiveness and reproducibility.

• The Korean Journal of Archival Studies
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• no.19
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• pp.3-55
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• 2009

Records of architectural cultural properties, in case of accidents, show who are to blame, present what evidences are to establish the cause, and also are used for checking if there were any problem in policies and regulations in preserving and caring architectural cultural properties. These records are of great importance in their roles and are of essential use regardless of time and space. Considering its significance, In that architectural cultural properties requires setting clear goals and directions and as well, criteria, for management, we need methods of systematical control and consideration for its characteristics. This research started with the sense of purpose that managing architectural cultural properties are in need of systematic and concrete control, based on the perception that they need protecting and transmitting. The goal of this thesis is to work on the current archiving status of architectural cultural properties by monitoring patterns and processes in archival administration, to diagnose problems by looking into the records creation and management, and to present the improvement plan which would lead to the architectural cultural properties' more efficient management and better use in the future. The management of architectural cultural properties begins with registering and assigning. Cultural Heritage Administration is in charge of control, supervision, and budget and local governments deal with direct management. Accordingly, records are by the hands of each local governmental body. Currently, each cultural property has its management depending on every different working environment in each governmental body. Architectural cultural properties needs managing in one body through the synthetic and unified, concrete and systematic manual and guide for management. Archiving architectural cultural properties have need of unitive management through a professional system, considering the physical characteristics and history of archiving. Unified management system will enhance efficiency and actual use of architectural cultural property records if one governmental body undertakes uniting records through standardization and professional supervision, and data-based unified search engine would enhance efficiency and actual use. Therefore, I suggest that Archives for Architectural Cultural Properties should be established as a professional Archives and wholly responsible body for the purpose of systematically and unifiedly managing architectural cultural property records with professional personnel and facility and transmitting their historical, cultural, and academic value. In Korea, studies up to the present have mainly focused on managing architectural records and records of drawing while few efforts were made to directly deal with managing architectural cultural properties themselves. The focus of this thesis is to study the current status and establish problems of the management of architectural cultural properties in administrative process, and as a result, to propose to establish Archives for Architectural Cultural Properties as a professional archives.

• Proceedings of the Korean Society of Crop Science Conference
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• 2023.04a
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• pp.7-7
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• 2023

Currently, the main technologies of various fourth industries are big data, the Internet of Things, artificial intelligence, blockchain, mixed reality (MR), and drones. In particular, "digital twin," which has recently become a global technological trend, is a concept of a virtual model that is expressed equally in physical objects and computers. By creating and simulating a Digital twin of software-virtualized assets instead of real physical assets, accurate information about the characteristics of real farming (current state, agricultural productivity, agricultural work scenarios, etc.) can be obtained. This study aims to streamline agricultural work through automatic water management, remote growth forecasting, drone control, and pest forecasting through the operation of an integrated control system by constructing digital twin data on the main production area of the nojinot industry and designing and building a smart farm complex. In addition, it aims to distribute digital environmental control agriculture in Korea that can reduce labor and improve crop productivity by minimizing environmental load through the use of appropriate amounts of fertilizers and pesticides through big data analysis. These open-field agricultural technologies can reduce labor through digital farming and cultivation management, optimize water use and prevent soil pollution in preparation for climate change, and quantitative growth management of open-field crops by securing digital data for the national cultivation environment. It is also a way to directly implement carbon-neutral RED++ activities by improving agricultural productivity. The analysis and prediction of growth status through the acquisition of the acquired high-precision and high-definition image-based crop growth data are very effective in digital farming work management. The Southern Crop Department of the National Institute of Food Science conducted research and development on various types of open-field agricultural smart farms such as underground point and underground drainage. In particular, from this year, commercialization is underway in earnest through the establishment of smart farm facilities and technology distribution for agricultural technology complexes across the country. In this study, we would like to describe the case of establishing the agricultural field that combines digital twin technology and open-field agricultural smart farm technology and future utilization plans.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.1-19
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• 2018

Large amount of data is now available for research and business sectors to extract knowledge from it. This data can be in the form of unstructured data such as audio, text, and image data and can be analyzed by deep learning methodology. Deep learning is now widely used for various estimation, classification, and prediction problems. Especially, fashion business adopts deep learning techniques for apparel recognition, apparel search and retrieval engine, and automatic product recommendation. The core model of these applications is the image classification using Convolutional Neural Networks (CNN). CNN is made up of neurons which learn parameters such as weights while inputs come through and reach outputs. CNN has layer structure which is best suited for image classification as it is comprised of convolutional layer for generating feature maps, pooling layer for reducing the dimensionality of feature maps, and fully-connected layer for classifying the extracted features. However, most of the classification models have been trained using online product image, which is taken under controlled situation such as apparel image itself or professional model wearing apparel. This image may not be an effective way to train the classification model considering the situation when one might want to classify street fashion image or walking image, which is taken in uncontrolled situation and involves people's movement and unexpected pose. Therefore, we propose to train the model with runway apparel image dataset which captures mobility. This will allow the classification model to be trained with far more variable data and enhance the adaptation with diverse query image. To achieve both convergence and generalization of the model, we apply Transfer Learning on our training network. As Transfer Learning in CNN is composed of pre-training and fine-tuning stages, we divide the training step into two. First, we pre-train our architecture with large-scale dataset, ImageNet dataset, which consists of 1.2 million images with 1000 categories including animals, plants, activities, materials, instrumentations, scenes, and foods. We use GoogLeNet for our main architecture as it has achieved great accuracy with efficiency in ImageNet Large Scale Visual Recognition Challenge (ILSVRC). Second, we fine-tune the network with our own runway image dataset. For the runway image dataset, we could not find any previously and publicly made dataset, so we collect the dataset from Google Image Search attaining 2426 images of 32 major fashion brands including Anna Molinari, Balenciaga, Balmain, Brioni, Burberry, Celine, Chanel, Chloe, Christian Dior, Cividini, Dolce and Gabbana, Emilio Pucci, Ermenegildo, Fendi, Giuliana Teso, Gucci, Issey Miyake, Kenzo, Leonard, Louis Vuitton, Marc Jacobs, Marni, Max Mara, Missoni, Moschino, Ralph Lauren, Roberto Cavalli, Sonia Rykiel, Stella McCartney, Valentino, Versace, and Yve Saint Laurent. We perform 10-folded experiments to consider the random generation of training data, and our proposed model has achieved accuracy of 67.2% on final test. Our research suggests several advantages over previous related studies as to our best knowledge, there haven't been any previous studies which trained the network for apparel image classification based on runway image dataset. We suggest the idea of training model with image capturing all the possible postures, which is denoted as mobility, by using our own runway apparel image dataset. Moreover, by applying Transfer Learning and using checkpoint and parameters provided by Tensorflow Slim, we could save time spent on training the classification model as taking 6 minutes per experiment to train the classifier. This model can be used in many business applications where the query image can be runway image, product image, or street fashion image. To be specific, runway query image can be used for mobile application service during fashion week to facilitate brand search, street style query image can be classified during fashion editorial task to classify and label the brand or style, and website query image can be processed by e-commerce multi-complex service providing item information or recommending similar item.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.1
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• pp.51-60
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• 2014

In this study, ICT medical service provider's level of knowledge fire fighting safety and methods on coping with fires in the regions of Gwangju and Jeonam Province of Korea were investigated to determine the elements affecting such levels and provide basic information on the manuals for educating how to cope with the fire fighting safety in medical facilities. The data were analyzed using SPSS Win 14.0. The scores of level of knowledge fire fighting safety of ICT medical service provider's were 7.06(10 point scale), and the scores of level of recognizing how to cope with fire fighting safety were 6.61(11 point scale). level of recognizing how to cope with fire fighting safety were significantly different according to gender(t=4.12, p<.001), age(${\chi}^2$=17.24, p<.001), length of career(${\chi}^2$=22.76, p<.001), experience with fire fighting safety education(t=6.10, p<.001), level of subjective knowledge on fire fighting safety(${\chi}^2$=53.83, p<.001). In order to enhance the level of understanding of fire fighting safety and methods of coping by the ICT medical service providers it is found that: self-directed learning through avoiding the education just conveying knowledge by lecture tailored learning for individuals fire fighting education focused on experiencing actual work by developing various contents emphasizing cooperative learning deploying patients by classification systems using simulations and a study on the implementation of digital anti-fire monitoring system with multipoint communication protocol, a design and development of the smoke detection system using infra-red laser for fire detection in the wide space, video based fire detection algorithm using gaussian mixture mode developing an education manual for coping with fire fighting safety through multi learning approach at the medical facilities are required.

• Cartoon and Animation Studies
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• s.24
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• pp.223-246
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• 2011

Today, cultural content industry could be defined to service business rather than manufacturing business because of its own trait. Also, it has the realistic restriction that it can't hold the dominant position in the market competition when it can't provide consumers satisfaction regardless of its quality or degree of completion. In other word, it can only expect great success when the business plan and the activities get the perfect balance with its best quality and perfect of completion. As the result, it emphasizes the importance of business competition in the global market. In briefly, there is no doubt that the creativeness of content is very important in the cultural content industry but in the future, making system to maintain the distribution process and share the profits fairly will be taken more important role. Especially, animation genre has the feature, which compares to other genres, such as film or TV drama, would be free from cultural barriers, and it is a great advantage. So to speak, animation can get little influence from cultural discount. However, Korean animation can't use the advantage properly for the foreign distribution because of its poor infrastructure and short of professional human resources. For those reasons, it has been needed to set up the realistic and specific action plan to overcome the situation. Therefore, considering those needs and the situations of Korean animation facing, making B2B online marketplace could be a great solution. The online marketplace stands for taking more efficient and broad distribution channel instead of the passive way, which we have now. If we have the B2B online marketplace, we can share all the information about the Korean animation with the potential customers whom live outside of Korea at real time. It also could be use to the windows of multiple distribution, which can make additional profits and activate the optional markets for the Korean animation. Through the method, Korean animation would be expected to get the higher international competitiveness, and it would be developed in quality and quantity of the business. Finally, it would be a great chance to Korean animation, which can get the unique brand power by improving the backward distribution circumstances.