• Korean journal of communication and information
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• v.66
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• pp.110-132
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• 2014

This study attempts to redefine the concept of 'fairness' of Korean public broadcasting and tries to build a new model for evaluating the fairness of Korean public broadcasting. The author insists that the fairness in public broadcasting consists of binary components of the public and rightful reporting, and views that the public reporting represents of neutralness, balance and impartiality while the rightful reporting represents of factuality, multiplicity and the protection of social minorities. The author suggests that two criteria of the public and rightful reporting results in four models of 'shepherd', 'acrobat', 'tribune', and 'trumpeter' in accord with its focus on the public and the rightful reporting. Survey toward the professionals in public broadcasting in academia was conducted and addressed the fact that Korean public broadcasting is close to the trumpeter model with some feature of acrobat.

• The Journal of the Korea Contents Association
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• v.20 no.1
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• pp.617-629
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• 2020

In the historical and cultural blocks with the most concentrated urban cultural heritage, the development of both side streets is impacted by the development of the main street, which shows a gradual decline. The loss of placeness on both side streets has resulted in more empty houses. Therefore, it is urgent to pay attention and take countermeasures to the empty houses in historical and cultural blocks. In this study, the vacant houses on Zhongshan Road in Hangzhou, China were taken as the object of study to understand the location theory and the six dimensions of Matthew Carmona's urban design. Meanwhile, it further analyzed the evaluative features of the placeness of the vacant houses in the historical and cultural street, to provide direction and basis for the flexible using of other empty houses in Zhongshan Road. Then by applying the Analytic Hierarchy Process (AHP), it obtained the importance scale of each evaluative feature and compared the evaluation results of experts with the analysis results of cases, getting the results as follows: In the flexible application of vacant houses in historical and cultural street, the evaluation result of placeness indicates that this kind of usage should be in order of societal level, perceptional level, functional level, morphological level, visual hierarchy and temporal level; among the evaluative features, security, identity, usability, individuality, aesthetics, connection, diversity, openness, continuity, accessibility, order and history should be considered in turn.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.7
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• pp.157-168
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• 2014

We propose an novel artificial visual attention model that is capable of automatic detection and segmentation of saliency region on natural images in this paper. The proposed model is based on human visual perceptions in biological vision and contains there are main contributions. Firstly, we propose a novel framework of artificial visual attention model based on the opponent process theory using intensity and color features, and an entropy filter is designed to perceive salient regions considering the amount of information from intensity and color feature channels. The entropy filter is able to detect and segment salient regions in high segmentation accuracy and precision. Lastly, we also propose an adaptive combination method to generate a final saliency map. This method estimates scores about intensity and color conspicuous maps from each perception model and combines the conspicuous maps with weight derived from scores. In evaluation of saliency map by ROC analysis, the AUC of proposed model as 0.9256 approximately improved 15% whereas the AUC of previous state-of-the-art models as 0.7824. And in evaluation of salient region segmentation, the F-beta of proposed model as 0.7325 approximately improved 22% whereas the F-beta of previous state-of-the-art models.

• Journal of agriculture & life science
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• v.43 no.1
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• pp.61-71
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• 2009

The objectives of this study were to confirm the necessity of classifying rural areas into several zone, which is being required to carry out vanous regional development projects in rural areas sponsored by govermnent effectively, make the standard for the classification. To summarize the results obtained from this study are as follows Based on the evaluation on the resource amount, the region of eup and myeon in the five gun were classified into five type(A, B, C, D, E). From the classification result, 6 eup and myeon were classified into A type, 13 eup and myeon into B type, 14 eup and myeon into C type, 18 eup and myeon into D type, 11 eup and myeon into E type. This showed that the five belts were distributed evenly in the five gun. The regions of eup and key myeon in each gun were classified into A type(Urbanization). The evaluation on the resource amount of the region that held beautiful view of nature and great tourist attractions was high although the region was close to E type (Mountains) in geographical feature. The regional characteristics of each eup or myeon are different although eup and myeon that were located in the same gun or adjacent each other. Therefore, it is thought that when the project for development of rural areas is planned, the regional characteristic of each eup and myeon should be considered to utilize the potential of each region fully. In summary, it is believed that to get productive results from the development Project in rural areas, strategics should be different based on the regional characteristic of each zone.

• Ecology and Resilient Infrastructure
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• v.8 no.4
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• pp.253-265
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• 2021

In this study, crop cultivation filed was extracted by using Unmanned Aerial Vehicle (UAV) imagery and deep learning models to overcome the limitations of satellite imagery and to contribute to the technological development of understanding the status of crop cultivation field. The study area was set around Chungbuk Goesan-gun Gammul-myeon Yidam-li and orthogonal images of the area were acquired by using UAV images. In addition, study data for deep learning models was collected by using Farm Map that modified by fieldwork. The Attention U-Net was used as a deep learning model to extract feature of UAV in this study. After the model learning process, the performance evaluation of the model for corn cultivation extraction was performed using non-learning data. We present the model's performance using precision, recall, and F1-score; the metrics show 0.94, 0.96, and 0.92, respectively. This study proved that the method is an effective methodology of extracting corn cultivation field, also presented the potential applicability for other crops.

• The Journal of Engineering Geology
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• v.28 no.4
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• pp.687-699
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• 2018

Understanding rain infiltration into the ground is an important feature of landslide risk evaluation. In this study, a landslide risk index for the study area is suggested, wherein the result of the landslide risk evaluation, based on the factor of safety (FS), is used. The landslide risk index is a landslide risk prediction index that utilizes the saturated depth ratio of the ground. Based on the landslide risk result for the study area, it was found that the FS was first to decrease. However, it gradually became convergent over the 50-year rainfall intensity study period, a result that is similar to the relationship between the saturated depth ratio and soil thickness. Moreover, saturated depth was also found to be deeper on gentle slopes than steep slopes. As such, the landslide risk index, based on the Inhu-ri study result, is thus suggested. Additionally, the suggested landslide risk index was compared and analyzed against the rainfall intensity of previous landslide experience. Results thus revealed that almost all landslides that occurred were over 0.7, which is the second grade, based on the landslide risk index.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1015-1023
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• 2022

The Entry-Descent-Landing process of a lander involves many environmental and technical challenges. To solve these problems, recently, terrestrial relative navigation (TRN) technology has been essential for landers. TRN is a technology for estimating the position and attitude of a lander by comparing Inertial Measurement Unit (IMU) data and image data collected from a descending lander with pre-built reference data. In this paper, we present a method for generating descent dataset and extracting landmarks, which are key elements for developing TRN technologies to be used on Mars. The proposed method generates IMU data of a descending lander using a simulated Mars landing trajectory and generates descent images from high-resolution ortho-map and digital elevation map through a ray tracing technique. Landmark extraction is performed by an area-based extraction method due to the low-textured surfaces on Mars. In addition, search area reduction is carried out to improve matching accuracy and speed. The performance evaluation result for the descent dataset generation method showed that the proposed method can generate images that satisfy the imaging geometry. The performance evaluation result for the landmark extraction method showed that the proposed method ensures several meters of positioning accuracy while ensuring processing speed as fast as the feature-based methods.

• Journal of Biomedical Engineering Research
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• v.43 no.1
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• pp.52-60
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• 2022

Purpose: For now, cognitive load is assessed based on survey-based methods, which can be difficult to track the amount of cognitive load in real-time. In this study, we investigated the difference in electrophysiological activation due to different levels of cognitive load not only at sensor-level but also at source-level using electroencephalogram that might be potentially used for quantitative cognitive load evaluation. Materials and Methods: In this study, ten healthy subjects (mean age 24.3 ± 2.1, three female) participated the experiment. All participants performed 4 sessions of n-back task in different difficulties: 0-, 1-, 2-, and 3-back during electroencephalogram recording. For sensor-level analysis, we calculated the event-related potential and event-related spectral perturbation while low resolution brain electromagnetic tomography (LORETA) to estimate the source activation. Each result was compared between different workload conditions using statistical analysis. Results: Statistical results revealed that the accuracy of the task performance was significantly different between different cognitive loads (p = 0.018). The post-hoc analysis confirmed that the accuracy of the 3-back task was significantly decreased compared to 1-back condition (p = 0.018), but not with 2-back condition (p = 0.180). ERP results showed that P300 target amplitude between 1-back and 3-back had a marginal difference in Cz (p = 0.059) and Pz(p = 0.093). A significant inhibition in Cz high-beta activation (p = 0.017) and decrease in source activation of right parahippocampal gyrus was found in 3-back condition compared to 1-back condition (p < 0.05). Conclusion: In this study, we compared the sensor- and source-level differences in electroencephalogram between different levels of cognitive load, that were found to be in line with the previous reports related to cognitive load evaluation. We expect that the outcome of the current study can be used as a feature to establish a quantitative cognitive load assessment system.

• Journal of the Institute of Convergence Signal Processing
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• v.24 no.3
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• pp.134-139
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• 2023

Rehabilitators perform outpatient treatment and daily rehabilitation exercises to recover physical function with the aim of quickly returning to society after surgical treatment. Unlike performing exercises in a hospital with the help of a professional therapist, there are many difficulties in performing rehabilitation exercises by the patient on a daily basis. In this paper, we propose a CNN-LSTM-based upper limb rehabilitation real-time monitoring system so that patients can perform rehabilitation efficiently and with correct posture on a daily basis. The proposed system measures biological signals through shoulder-mounted hardware equipped with EMG and IMU, performs preprocessing and normalization for learning, and uses them as a learning dataset. The implemented model consists of three polling layers of three synthetic stacks for feature detection and two LSTM layers for classification, and we were able to confirm a learning result of 97.44% on the validation data. After that, we conducted a comparative evaluation with the Teachable machine, and as a result of the comparative evaluation, we confirmed that the model was implemented at 93.6% and the Teachable machine at 94.4%, and both models showed similar classification performance.

• Phonetics and Speech Sciences
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• v.15 no.4
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• pp.61-69
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• 2023

Sulcus vocalis is characterized by incomplete closure of the vocal folds, with a high mean airflow rate (MFR) as a distinctive feature. The MFR is measured using two aerodynamic analysis methods [the maximum sustained phonation protocol (MXPH) and voicing efficiency protocol (VOEF)] of the phonatory aerodynamic system (PAS), and the results may vary depending on the method. This study compared the differences in MFR before and after treatment (microsurgery and voice therapy) according to the MXPH and VOEF of the PAS in 30 patients with sulcus vocalis. Additionally, we examined whether there were differences in the subjective voice evaluation (voice handicap index, VHI), perceptual voice evaluation (GRBS), and fundamental frequency (F0) before and after treatment. The results showed significant differences between the two methods, both before and after treatment, in patients with sulcus vocalis. However, there were no significant differences by methods in the changes before and after treatment. The VHI and GRBS scores significantly decreased after treatment; however, F0 showed no significant differences before and after treatment. This study indicates that when evaluating MFR changes in patients with sulcus vocalis, it is acceptable to use either aerodynamic analysis (MXPH or VOEF).