• Journal of Digital Convergence
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• v.15 no.12
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• pp.477-487
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• 2017

This study is for empirical analyzing the ethical contents in using social media, such as what kind of ethical responsibility do the teenage users have, how do they recognize the ethical concept in producing or sharing the information and how these ethical factors affect their behavior of social media uses. After survey with the structured questionnaire, statistical analyses with available 227 cases are processed. As a result, there are 4 ethical factors in using social media which as included 'privacy', 'copyright', 'fullness', 'accuracy', 'truth-telling', 'fairness', 'relief of harmful effect', 'credibility', 'objectivity', 'impartiality', included 'moderation', 'respect', 'autonomy', 'control', 'care of mischief', included 'interactivity', 'multiplicity', 'anonymity', 'divergence', 'social community', included 'transparency', 'openness'. All these ethical factors are positive correlated to the level of social media users' opinion expression, opinion support, information leading, information searching. Especially, is the most effective factor to social media users' behavior.

• Journal of Korean Society of Transportation
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• v.21 no.4
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• pp.47-56
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• 2003

There are no specific criteria deciding what type of crosswalk installs although 4 typed crosswalks at signalized intersections classify according to number of stop line, spacing from the border of intersections and existence of traffic islands or not. Accidents involving pedestrians at signalized intersections are classified by type of crosswalks by traffic volume, pedestrian volume at crosswalk, intersection geometry and phase in view of pedestrians' safety at 50 intersections in Gwangju. The Multiple regression models are applied to express the pedestrian accident rate. In addition, process deciding what type of crosswalk installs which includes accident rate involved pedestrian is changed into number of accident is represented to reduce number of accidents. This paper presents what type of crosswalk installs in order to reduce pedestrian involved accidents at new or existing crosswalk.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.4
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• pp.21-35
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• 2023

Expectations surrounding generative AI technology and its profound ramifications are sweeping across various industrial domains. Given the anticipated pivotal role of the startup ecosystem in the utilization and advancement of generative AI technology, it is imperative to cultivate a deeper comprehension of the present state and distinctive attributes characterizing venture capital (VC) investments within this domain. The current investigation delves into South Korea's landscape of VC investment deals and prognosticates the projected VC investments by juxtaposing these against the United States, the frontrunner in the generative AI industry and its associated ecosystem. For analytical purposes, a compilation of 286 investment deals originating from 117 U.S. generative AI startups spanning the period from 2008 to 2023, as well as 144 investment deals from 42 South Korean generative AI startups covering the years 2011 to 2023, was amassed to construct new datasets. The outcomes of this endeavor reveal an upward trajectory in the count of VC investment deals within both the U.S. and South Korea during recent years. Predominantly, these deals have been concentrated within the early-stage investment realm. Noteworthy disparities between the two nations have also come to light. Specifically, in the U.S., in contrast to South Korea, the quantum of recent VC deals has escalated, marking an augmentation ranging from 285% to 488% in the corresponding developmental stage. While the interval between disparate investment stages demonstrated a slight elongation in South Korea relative to the U.S., this discrepancy did not achieve statistical significance. Furthermore, the proportion of VC investments channeled into generative AI enterprises, relative to the aggregate number of deals, exhibited a higher quotient in South Korea compared to the U.S. Upon a comprehensive sectoral breakdown of generative AI, it was discerned that within the U.S., 59.2% of total deals were concentrated in the text and model sectors, whereas in South Korea, 61.9% of deals centered around the video, image, and chat sectors. Through forecasting, the anticipated VC investments in South Korea from 2023 to 2029 were derived via four distinct models, culminating in an estimated average requirement of 3.4 trillion Korean won (ranging from at least 2.408 trillion won to a maximum of 5.919 trillion won). This research bears pragmatic significance as it methodically dissects VC investments within the generative AI domain across both the U.S. and South Korea, culminating in the presentation of an estimated VC investment projection for the latter. Furthermore, its academic significance lies in laying the groundwork for prospective scholarly inquiries by dissecting the current landscape of generative AI VC investments, a sphere that has hitherto remained void of rigorous academic investigation supported by empirical data. Additionally, the study introduces two innovative methodologies for the prediction of VC investment sums. Upon broader integration, application, and refinement of these methodologies within diverse academic explorations, they stand poised to enhance the prognosticative capacity pertaining to VC investment costs.

• The Journal of the Korea Contents Association
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• v.15 no.8
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• pp.53-68
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• 2015

This study analyzed online word-of-mouth information using content analysis to help practical categorization of two-sided eWOM. A total of 402 online consumer reviews on search goods and experience goods were collected. Descriptive characteristics(information direction, length of review line) and content structural characteristics(product benefit types, information presentation methods) were used as analysis criteria. The study results are as follows. First, the types of two-sided e-WOM direction were made of positive/negative, negative/positive, positive/negative/ positive, and negative/positive/negative. Second, the length of two-sided eWOM was longer than the length of one-sided eWOM and blended type accounted for the highest proportion both one-sided and two-sided eWOM at the aspect of product benefit. Third, holistic presentation method was overwhelmingly high in one-sided eWOM, whereas blended and analytic presentation methods were somewhat high in two-sided eWOM. Fourth, holistic presentation method was high in search goods, whereas blended and analytic presentation methods were high in experience goods. Based on these results, implications for two-sided e-WOM study and further research issues were discussed.

• Journal of Korean Society of Forest Science
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• v.107 no.2
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• pp.184-192
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• 2018

In this study was implemented to develop tree stem weight prediction equation of Larix kaempferi in central region by selecting a standard site, taking into account of diameter and position of the local trees. Fifty five sample trees were selected in total. By utilizing actual data of the sample trees, 11 models were compared and analyzed in order to estimate four different kinds of weights which include fresh weight, ovendry outside bark weight, ovendry inside bark weight and merchantable weight. As to estimate its weight, the study has classified its model according to three parameters: DBH, DBH and height, and volume. The optimal model was chosen by comparing the performance of model using the fit index and standard error of estimate and residual distribution. As a result, the formula utilizing DBH (Variable 1) is $W=a+bD+cD^2$ (3) and its fit index was 90~92%. The formula for DBH and height (Variable 2) is $W=aD^bH^C$ (8) and its fit index was 97~98%. In summation, Variable 2 model showed higher fitness than Variable 1 model. Moreover, fit index of formula for total volume and merchantable volume (W=aV) showed high rate of 98~99%, as well as resulting 7.7-17.5 with SEE and 8.0-10.0 with CV(%) which lead to predominately high fitness in conclusion. This study is expected to provide information on weights for single trees and furthermore, to be used as a basic study for weight of stand unit and biomass estimation equations.

• Proceedings of the Korea Water Resources Association Conference
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• 2007.05a
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• pp.97-105
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• 2007

수문학적 토양유형은 복잡하게 세분되어 있는 토양의 종류를 수문학적인 목적에 따라 단순화하기 위해 만든 것으로 미농무성 토양보전국에서 고안한 개념이다. 우리나라 토양을 이 방법으로 구분하고자 하는 몇번의 시도가 있으며 그 중 대표적인 것이 정 등(1995)이 분류한 수문학적 토양군이다. 이는 토양의 침투 투수특성에 대한 실측자료가 부족한 우리나라의 실정을 감안하여 토성속(textural family), 배수등급(drainage class), 불투수층(impermeable layer), 투수성(permeability)의 네가지 토양특성을 분류특성으로 하여 각각에 1-4점 범위로 점수를 매긴 후 합산한 점수를 기준으로 수문학적 토양유형을 분류하는 것이다. 최근에는 토양의 한계침투속도에 따라 수문학적 토양유형을 분류하고자 하는 시도가 있으며 본 논문에서는 새로운 방법으로 분류할 때 기존의 방법과 어떠한 차이가 있는지 비교하고자 하였다. 정 등(1995)의 분류방법은 개념상 몇가지 문제점을 안고 있다. 먼저 토양의 수리특성은 같은 토성속이라 하여도 토양생성 과정과 토지이용 방법에 따라 그 차이가 매우 큼에도 불구하고 이에 대해 고려하지 못하였으며 다음으로 지표유거가 많아 배수가 양호한 토양의 강우 유출을 과소평가한다. 또한 얕은 토심에 존재하는 불투수층이 존재하는 경우 토양의 수리특성에 관계없이 적은 양의 강우에도 유출이 발생하므로 별도의 제한인자로 간주하여야 한다. 토양의 한계 침투속도를 이용한 분류방법은 이러한 문제점을 상당 부분 개선할 수 있다. 토양의 한계침투속도를 산정하기 위해 현장에서 지표 한계침투속도와 투수속도를 측정하였으며 이 자료를 확장하여 해석하기 위해 입자특성을 이용한 Pedo Transfer Function을 개발하였다. 토심 50 cm 포화시 토양 투수성을 한계 침투속도로 가정하였으며 50 cm 이내에 암반층과 지하수위가 존재할 경우 투수성에 관계없이 D유형으로 분류하였다. 새로운 방법으로 분류한 결과 기존의 분류와 몇가지 차이점이 발견되었다. 가장 큰 차이는 대부분의 논토양이 느린 한계침투속도의 영향으로 D유형에 속한 것이다. 산림토양과 밭토양은 기존 방법과 마찬가지로 A, B유형이 많았으며 암반층을 고려하기 전에는 기존 분류에 비해 강우 유출 가능성이 적은 쪽으로 평가되었다. 그러나 암반층이 존재하는 토양을 고려한 결과 A 또는 B 유형에 속하던 상당수의 산림토양이 새로운 분류에서 D유형으로 분류되었다. 지표 유거가 많아 배수등급이 매우양호로 분류되던 토양은 정 등(1995)의 분류와 비교하여 대부분 강우 유출 가능성이 큰 쪽으로 조정되었다. 새로운 수문학적 토양유형을 이용할 경우 낮은 토심에서 암반층이 발견되는 산림토양이 분포한 유역이나 산림, 밭 등에 식질 토양이 많이 분포하는 유역에서는 기존의 방법을 이용하는 것보다 강우 유출량이 높게 평가될 것으로 판단된다. 앞으로 강우 유출량 실측자료와의 비교를 통해 지속적인 보정을 하여야 할 것이며 특히 불투수층의 존재시 일괄적으로 D유형으로 분류된 토양의 경우 깊이에 따라 C 또는 D 유형으로 세분하여 조정할 필요가 있다.

• Journal of Korean Physical Therapy Science
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• v.27 no.2
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• pp.25-35
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• 2020

Background: There are many situations where walking in an actual community needs to change direction along with walking on a straight path, and this situation needs to be reflected in assessing walking ability of the community. Therefore, in this study, we tried to determine whether the assessments can distinguish the level of walking in the community. Design: Retrospective cohort study. Methods: Fifty-two survivors with chronic stroke have participated in the study. According to the evaluation result of 10mWT, the subjects of 0.8m/s and above were classified as the group who could walk in the community (n=22), and the subjects of 0.4m/s~0.8m/s were classified into the group who could not walk in the community (n=30). Modified Rivermead Mobility Index, Postural Assessment Scale for Stroke, Fugl-Meyer Assessment, Berg Balance Scale, 10-meter Walk Test (10mWT) were used to evaluate the motor skills. Furthermore, Activities-specific Balance Confidence Scale was used to evaluate psychological factors, and Timed Up & Go Test (TUG), Figure-of-Eight Walk Test (F8WT), Four Square Step Test (FSST), Step Test (ST) were applied to evaluate dynamic balance and mobility. Results: As a result for distinguishing walking levels in the community, TUG was 14.25 seconds, F8WT was 13.34 seconds, FST was 19.43 seconds, and ST of affected side and non-affected side were 6.5 points and 7.5 points, respectively. TUG (AUC=0.923), F8WT (AUC=0.905), and FST (AUC=0.941) were highly accurate, but the ST of affected side and non-affected side (AUC=0.806, 0.705) showed the accuracy of the median degree, respectively. Conclusion: To distinguish walking levels in the community of survivors with chronic stroke, TUG and FSST have been found to be the best assessment tool, and in particular, FSST could be very valuable in clinical use as the most important assessment tool to distinguish walking levels in the community.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.14 no.3
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• pp.297-305
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• 2016

An approach to assess inadvertent human intrusion into radwaste repository was proposed with the assumption that the intrusion occurs after a loss of knowledge of the hazardous nature of the disposal facility. The essential boundary conditions were derived on the basis of international recommendations, followed by an overall approach to deal with inadvertent human intrusion. The interrelation between societal factors, human intrusion scenarios, and protective measures is described to provide a concrete explanation of the approach, including the detailed procedures to set up the human intrusion scenario. The procedure for deriving protective measures is also explained with four steps, including how to derive a safety framework, general measures, potential measures, and eventual protective measures on the basis of stylized scenarios. It is expected that the approach proposed in this study will be used effectively to reduce the potential for and/or the consequences of human intrusion during the entire process of realizing a disposal facility.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.3
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• pp.133-140
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• 2022

We investigate the performance of deep learning-based Korean language models on a task of predicting the score range of Korean essays written by foreign students. We construct a data set containing a total of 304 essays, which include essays discussing the criteria for choosing a job ('job'), conditions of a happy life ('happ'), relationship between money and happiness ('econ'), and definition of success ('succ'). These essays were labeled according to four letter grades (A, B, C, and D), and a total of eleven essay score range prediction experiments were conducted (i.e., five for predicting the score range of 'job' essays, five for predicting the score range of 'happiness' essays, and one for predicting the score range of mixed topic essays). Three deep learning-based Korean language models, KoBERT, KcBERT, and KR-BERT, were fine-tuned using various training data. Moreover, two traditional probabilistic machine learning classifiers, naive Bayes and logistic regression, were also evaluated. Experiment results show that deep learning-based Korean language models performed better than the two traditional classifiers, with KR-BERT performing the best with 55.83% overall average prediction accuracy. A close second was KcBERT (55.77%) followed by KoBERT (54.91%). The performances of naive Bayes and logistic regression classifiers were 52.52% and 50.28% respectively. Due to the scarcity of training data and the imbalance in class distribution, the overall prediction performance was not high for all classifiers. Moreover, the classifiers' vocabulary did not explicitly capture the error features that were helpful in correctly grading the Korean essay. By overcoming these two limitations, we expect the score range prediction performance to improve.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.1
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• pp.1-12
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• 2023

The ongoing Yongsan Park development project began in 1988 with the development of a utilization plan for the US Army base in Yongsan after the Army relocation. This study aimed to draw implications for the Yongsan Park project by focusing on Yongsan Family Park. Among the public records of Yongsan Park and Yongsan Family Park transferred to the Seoul Metropolitan Archives, 53 major records were analyzed. The results are as follows. First, Yongsan Family Park, built on the site of the US Army golf course in 1992, was considered a part of the Yongsan Park plan and holds status as the first phase of the Yongsan Park project. Second, despite its status, Yongsan Family Park opened as a temporary park occupied by urban facilities. A design and detailed roadmap of the development process is necessary to make Yongsan Park more resilient. Third, organizing and systematizing public records is necessary because lessons learned through past park development processes can be applied to the current project. This study is meaningful since it uncovered important issues of urban planning discussed in the process of Yongsan Family Park development through a complete analysis of public records, examined the linkage between Yongsan Family Park, which was not known until now, and the ongoing Yongsan Park project, and reaffirmed the importance of park archiving for long-term development projects.