• Journal of Hospice and Palliative Care
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• v.16 no.2
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• pp.74-79
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• 2013

The purpose of this paper is to suggest a direction for future studies based on the analysis of the articles published in the Korean Journal of Hospice and Palliative Care from 1998 to 2012. A total of 240 articles (51 reviews, 189 original) were examined in three five-year groups. Categories of analysis include authors' background (profession, region) and general characteristics and qualitative aspects of the original paper (participants, topic, study design, data analysis, ethical consideration, multidisciplinary approach, research funds and sample size estimation). While the journal publishes more of articles than before, it is mainly due to the increase in the number of review articles, not original articles. As for study topics, healthcare industry and physical symptoms were most frequently studied. The disparity in authors' regional background is fading, and more articles are published by nurses than before. Moreover, more studies are funded while fewer papers tend to adopt a multidisciplinary approach or focus on care givers. Also, in terms of a study design, the number of experimental and methodological studies has slightly increased. In the qualitative aspect, studies considered ethical issues and collected participation consent, and fewer studies reported an estimated sample size. In data analysis, post-adjustment comparison decreased, and new analytical methods are increasingly used. Our results indicate the need to conduct research with more extensive scientific data in various fields of hospice and palliative care.

• Imaging Science in Dentistry
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• v.54 no.2
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• pp.129-137
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• 2024

Purpose: Patients with head and neck cancer (HNC) who undergo dental procedures during radiotherapy (RT) face an increased risk of developing osteoradionecrosis (ORN). Accordingly, new tools must be developed to extract critical information regarding the dose delivered to the teeth and mandible. This article proposes a novel approach for visualizing 3-dimensional planned dose distributions on panoramic reconstruction computed tomography (pCT) images. Materials and Methods: Four patients with HNC who underwent volumetric modulated arc therapy were included. One patient experienced ORN and required the extraction of teeth after RT. In the study approach, the dental arch curve (DAC) was defined using an open-source platform. Subsequently, pCT images and dose distributions were generated based on the new coordinate system. All teeth and mandibles were delineated on both the original CT and pCT images. To evaluate the consistency of dose metrics, the Mann-Whitney U test and Student t-test were employed. Results: A total of 61 teeth and 4 mandibles were evaluated. The correlation coefficient between the 2 methods was 0.999, and no statistically significant difference was observed (P>0.05). This method facilitated a straightforward and intuitive understanding of the delivered dose. In 1 patient, ORN corresponded to the region of the root and the gum receiving a high dosage (approximately 70 Gy). Conclusion: The proposed method particularly benefits dentists involved in the management of patients with HNC. It enables the visualization of a 3-dimensional dose distribution in the teeth and mandible on pCT, enhancing the understanding of the dose delivered during RT.

• Journal of the Korean Vacuum Society
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• v.20 no.6
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• pp.461-467
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• 2011

The valence band maximum and the conduction band miminum of GaAs, GaSb, InAs, and InSb (constituent binaries of the quaternaty alloy $Ga_xIn_{1-x}Sb_yAs_{1-y}$) are calculated by using TB analytical approach method. The band alignment types of their heterojunctions are determined directly from their relative position of band edges (VBM and CBM). For example, the GaAs/InAs, GaAs/InSb, and GaSb/InSb are in a type-I, the GaAs/GaSb in a type-II, and the GaSb/InAs and InSb/InAs in a type-III, respectively. The composition dependent VBM and CBM for the $Ga_xIn_{1-x}Sb_yAs_{1-y}$ alloy are obtained by using the univeral tight binding method. For the alloyed heterojunctions, the band alignments can be controlled by changing the composition which induce a band type transition. For the alloy $Ga_xIn_{1-x}Sb_yAs_{1-y}$ lattice mathced to GaSb, the type-II band alignment in the region of $x{\leq}0.15$ is changed to the type-III in the region of $x{\geq}0.81$. On the other hand, the alloy $Ga_xIn_{1-x}Sb_yAs_{1-y}$ lattice mathced to InAs has the type-II band alignment in the region of $x{\leq}0.15$ and the type-III band alignment in the region of $x{\geq}0.81$, respectively.

• Journal of Broadcast Engineering
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• v.17 no.2
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• pp.305-315
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• 2012

Color correction between two or multiple images is very crucial for the development of subsequent algorithms and stereoscopic 3D camera system. Even though various color correction methods are proposed recently, there are few methods for measuring the performance of these methods. In addition, when two images have view variation by camera positions, previous methods for the performance measurement may not be appropriate. In this paper, we propose a method of measuring color difference between corresponding images for color correction. This method finds matching points that have the same colors between two scenes to consider the view variation by correspondence searches. Then, we calculate statistics from neighbor regions of these matching points to measure color difference. From this approach, we can consider misalignment of corresponding points contrary to conventional geometric transformation by a single homography. To handle the case that matching points cannot cover the whole regions, we calculate statistics of color difference from the whole image regions. Finally, the color difference is computed by the weighted summation between correspondence based and the whole region based approaches. This weight is determined by calculating the ratio of occupying regions by correspondence based color comparison.

• Journal of The Korean Society of Agricultural Engineers
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• v.62 no.2
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• pp.97-109
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• 2020

Drought is one of the most influential disasters in sustainable agriculture and food security of nations. In order to preemptively respond to agricultural droughts, vulnerability assessments were conducted to predict the possibility of drought in the region, the degree of direct or indirect damage, and the ability to cope with the damage. Information on agricultural drought vulnerability status of different regions is extremely useful for implementation of long term drought management measures. The purpose of this study is to develop and implement a quantitative approach for measuring agricultural drought vulnerability at sub-district level based on agricultural water and reservoirs. To assess the vulnerability in a quantitative manner and also to deal with different physical and socioeconomic data on the occurrence of agricultural drought, we selected the appropriate factors for the assessment of agricultural drought vulnerability through preceding studies, and analyzed the meteorological and agricultural reservoir data from 2015 to 2018. Each item was weighted using AHP (Analytic Hierarchy Process) analysis and evaluated through the agricultural drought vulnerability estimation. The entire national vulnerability assessments showed that Ganghwa, Naju, and Damyang were the most vulnerable to agricultural droughts. As a result of analyzing spatial expression, Gyeongsang-do is relatively more vulnerable to drought than Gangwon-do and Gyeonggi-do. The results revealed that the methodology and evaluation items achieved good performance in drought response. In addition, vulnerability assessments based on agricultural reservoir are expected to contribute supporting effective drought decisions in the field of agricultural water management.

• Korean Chemical Engineering Research
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• v.55 no.3
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• pp.332-340
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• 2017

This study aims to propose a new optimization-based approach for design and analysis of the stand-alone hybrid energy supply system using renewable energy sources (RES). In the energy supply system, we include multiple energy production technologies such as Photovoltaics (PV), Wind turbine, and fossil-fuel-based AC generator along with different types of energy storage and conversion technologies such as battery and inverter. We then select six different regions of Korea to represent various characteristics of different RES potentials and demand profiles. We finally designed and analyzed the optimal RES stand-alone energy supply system in the selected regions using multiobjective optimization (MOOP) technique, which includes two objective functions: the minimum cost and the minimum $CO_2$ emission. In addition, we discussed the feasibility and expecting benefits of the systems by comparing to conventional systems of Korea. As a result, the region of the highest RES potential showed the possibility to remarkably reduce $CO_2$ emissions compared to the conventional system. Besides, the levelized cost of electricity (LCOE) of the RES-based energy system is identified to be slightly higher than conventional energy system: 0.35 and 0.46 $/kWh, respectively. However, the total life-cycle emission of $CO_2$ ($LCE_{CO2}$) can be reduced up to 470 g$CO_2$/kWh from 490 g$CO_2$/kWh of the conventional systems.

• The Journal of Information Systems
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• v.26 no.3
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• pp.171-185
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• 2017

Purpose Recently, there has been an increase in attempts to analyze social phenomena, consumption trends, and consumption behavior through a vast amount of customer data such as web search traffic information and social buzz information in various fields such as flu prediction and real estate price prediction. Internet portal service providers such as google and naver are disclosing web search traffic information of online users as services such as google trends and naver trends. Academic and industry are paying attention to research on information search behavior and utilization of online users based on the web search traffic information. Although there are many studies predicting social phenomena, consumption trends, political polls, etc. based on web search traffic information, it is hard to find the research to explain and predict tourism demand and establish tourism policy using it. In this study, we try to use web search traffic information to explain the tourism demand for major cities in Gangwon-do, the representative tourist area in Korea, and to develop a nowcasting model for the demand. Design/methodology/approach In the first step, the literature review on travel demand and web search traffic was conducted in parallel in two directions. In the second stage, we conducted a qualitative research to confirm the information retrieval behavior of the traveler. In the next step, we extracted the representative tourist cities of Gangwon-do and confirmed which keywords were used for the search. In the fourth step, we collected tourist demand data to be used as a dependent variable and collected web search traffic information of each keyword to be used as an independent variable. In the fifth step, we set up a time series benchmark model, and added the web search traffic information to this model to confirm whether the prediction model improved. In the last stage, we analyze the prediction models that are finally selected as optimal and confirm whether the influence of the keywords on the prediction of travel demand. Findings This study has developed a tourism demand forecasting model of Gangwon-do, a representative tourist destination in Korea, by expanding and applying web search traffic information to tourism demand forecasting. We compared the existing time series model with the benchmarking model and confirmed the superiority of the proposed model. In addition, this study also confirms that web search traffic information has a positive correlation with travel demand and precedes it by one or two months, thereby asserting its suitability as a prediction model. Furthermore, by deriving search keywords that have a significant effect on tourism demand forecast for each city, representative characteristics of each region can be selected.

• Journal of Broadcast Engineering
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• v.13 no.4
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• pp.544-553
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• 2008

With the development of video editing technology, there are growing uses of overlay text inserted into video contents to provide viewers with better visual understanding. Since the content of the scene or the editor's intention can be well represented by using inserted text, it is useful for video information retrieval and indexing. Most of the previous approaches are based on low-level features, such as edge, color, and texture information. However, existing methods experience difficulties in handling texts with various contrasts or inserted in a complex background. In this paper, we propose a novel framework to localize the overlay text in a video scene. Based on our observation that there exist transient colors between inserted text and its adjacent background a transition map is generated. Then candidate regions are extracted by using the transition map and overlay text is finally determined based on the density of state in each candidate. The proposed method is robust to color, size, position, style, and contrast of overlay text. It is also language free. Text region update between frames is also exploited to reduce the processing time. Experiments are performed on diverse videos to confirm the efficiency of the proposed method.

• KSBB Journal
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• v.21 no.2
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• pp.144-150
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• 2006

The exploitation of metagenome, the access to the natural extant of enormous potential resources, is the way for elucidating the functions of organism in environmental communities, for genomic analyses of uncultured microorganism, and also for the recovery of entirely novel natural products from microbial communities. The major breakthrough in metagenomics is opened by the construction of libraries with total DNAs directly isolated from environmental samples and screening of these libraries by activity and sequence-based approaches. Screening with activity-based approach is presumed as a plausible route for finding new catabolic genes under designed conditions without any prior sequence information. The main limitation of these approaches, however, is the very low positive hits in a single round of screening because transcription, translation and appropriate folding are not always possible in E. coli, a typical surrogate host. Thus, to obtain information about these obstacles, we studied the genetic organization of individual URF's(unidentified open reading frame from metagenome sequenced and deposited in GenBank), especially on the expression factors such as codon usage, promoter region and ribosome binding site(rbs), based on DNA sequence analyses using bioinformatics tools. And then we also investigated the above-mentioned properties for 4100 ORFs(Open Reading Frames) of E. coli K-12 generally used as a host cell for the screening of noble genes from metagenome. Finally, we analyzed the differences between the properties of URFs of metagenome and ORFs of E. coli. Information derived from these comparative metagenomic analyses can provide some specific features or environmental blueprint available to screen a novel biocatalyst efficiently.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.2
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• pp.165-172
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• 2010

In clinical data minig, choosing the optimal subset of features is such important, not only to reduce the computational complexity but also to improve the usefulness of the model constructed from the given data. Moreover the threshold values (i.e., cut-off points) of selected features are used in a clinical decision criteria of experts for differential diagnosis of diseases. In this paper, we propose a fuzzy discretization approach, which is evaluated by measuring the degree of separation of redundant attribute values in overlapping region, based on spatial distribution of data with continuous attributes. The weighted average of the redundant attribute values is then used to determine the threshold value for each feature and rough set theory is utilized to select a subset of relevant features from the overall features. To verify the validity of the proposed method, we compared experimental results, which applied to classification problem using 668 patients with a chief complaint of dyspnea, based on three discretization methods (i.e., equal-width, equal-frequency, and entropy-based) and proposed discretization method. From the experimental results, we confirm that the discretization methods with fuzzy partition give better results in two evaluation measures, average classification accuracy and G-mean, than those with hard partition.