• 영어영문학
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• 제64권3호
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• pp.453-468
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• 2018

Nat Turner's rebellion in 1831 was considered pre Civil War South's most dreadful nightmare due to the merciless murder of white slave owner victims. The motive of vengeance has been emphasized as that of Turner's notorious black preacher religious fanaticism. However, the recent film, The Birth of a Nation (2016) directed by Nate Parker, utilized the identical title of a film (1915) directed by D. W. Griffith. Providing limited evidence, information about the rebellion in Thomas Gray's pamphlet The Confessions of Nat Turner (1831), was the only accessible historical source for the factual event of the slaves' rebellion. In addition, William Styron's The Confessions of Turner (1967), a fictionalized biography, also examined Turner's life in the harshness of slavery. Although these two texts deal with the personal level of Nat Turner's rage and religious enthusiasm, both provide only fractured parts of the motive of vengeance. Strikingly, Parker's film interrogates the ideology of "victims," as well as the hierarchical term of "confessions," with their different positions between whites and blacks. More specifically, Parker's film offers discursive fields of proslavery arguments regarding biblical interpretations in addition to external visualization of slaves' inner emotional lives. The film demonstrates how the institution of slavery allowed slaves to be exploited, beaten, raped, through interrogating the problematic image of the "contested hero" Nat Turner. In contrast to the traditional image of blacks' bloody rebellion, the film underlines the absurdity of certain Biblical misinterpretations. It furthermore implies how the 1915 film manipulated proslavery propaganda in America.

• 한국콘텐츠학회논문지
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• 제22권3호
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• pp.62-70
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• 2022

이 연구는 통신사 유동인구 데이터를 활용하여 코로나 기간 전후 대구의 대학가 유동인구 변화를 집중적으로 분석하였다. 이 과정에서 서울 대학가와 비교하면서, 대구에서 나타난 현상의 특징을 파악하였다. 연구 대상은 비슷한 재학생 수를 지닌 경북대와 고려대로 선정하였다. 통신사 데이터를 제공하는 공공 웹사이트에서 각 대학 소재지 인근의 유동인구를 수집하였다. 데이터를 시각화하여 두 도시 간 유동인구에서 나타난 차이를 분석하였다. 통계적 검정을 위해 T-검정을 실시하였다. 마지막으로 시간에 따른 변화를 확인하기 위해 기간을 나누어 선형회귀 분석을 실시하였다. 그 결과, 2020년 상반기에서는 두 도시의 패턴이 유사하였지만, 하반기 코로나의 확산세가 안정된 대구는 유동인구가 2019년 대비 오히려 증가하였고 서울은 감소한 형태를 나타냈으며, 단기적인 선형성 또한 관찰할 수 있었다. 연구를 통해서 도시의 특성과 코로나의 확산 정도 등에 따라 유동인구가 변화하는 패턴을 확인하였다.

• 인간식물환경학회지
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• 제24권2호
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• pp.229-244
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• 2021

Background and objective: The purpose of this study was to comprehensively analyze the user behavior in order to cope appropriately with the increasing demand for mountain usage of those in their 20s and 30s and to allocate resources efficiently. Methods: To analyze the behavior of mountain hiking users, an exploratory data analysis (EDA) was conducted on the data which had been collected in the app Tranggle. The main target are users in their 20s and 30s who visited the mountains in the metropolitan area in 2019-2020. Among them, we have selected data on the top 13 mountains based on the frequency of visits. After data pre-processing, mountain usage patterns were analyzed through statistical analysis and visualization. Results: Compared to 2019, the number of users in 2020 increased 1.36 times. The utilization rate of the well-established hiking trails has also increased. The usage of mountain on weekends (Saturday > Sunday) was still the highest, and the difference in the usage between the days of the week decreased. Outside of work hours, early morning usage has increased and night-time usage has decreased. There was no significant change in usages depending on activity type, level (experience point) and exercise properties. Conclusion: Since the COVID-19 outbreak, the usage of mountains has been changing towards low user density and short-distance trip. in the post-COVID-19 era, the function and role of forests in daily life are expected to increase. To cope with this, further research needs to be carried out with consideration of the wider demographic and social characteristics.

• 대한한의학회지
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• 제43권1호
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• pp.73-86
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• 2022

Objectives: In the health care industry, the influence of online reviews is growing. As medical services are provided mainly by providers, those services have been managed by hospitals and clinics. However, direct promotions of medical services by providers are legally forbidden. Due to this reason, consumers, like patients and clients, search a lot of reviews on the Internet to get any information about hospitals, treatments, prices, etc. It can be determined that online reviews indicate the quality of hospitals, and that analysis should be done for sustainable hospital marketing. Method: Using a Python-based crawler, we collected reviews, written by real patients, who had experienced Korean medicine, about more than 14,000 reviews. To extract the most representative words, reviews were divided by positive and negative; after that reviews were pre-processed to get only nouns and adjectives to get TF(Term Frequency), DF(Document Frequency), and TF-IDF(Term Frequency - Inverse Document Frequency). Finally, to get some topics about reviews, aggregations of extracted words were analyzed by using LDA(Latent Dirichlet Allocation) methods. To avoid overlap, the number of topics is set by Davis visualization. Results and Conclusions: 6 and 3 topics extracted in each positive/negative review, analyzed by LDA Topic Model. The main factors, consisting of topics were 1) Response to patients and customers. 2) Customized treatment (consultation) and management. 3) Hospital/Clinic's environments.

• 예술인문사회 융합 멀티미디어 논문지
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• 제7권6호
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• pp.777-784
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• 2017

사용자의 행위는 건축물의 질을 규정하는 가중 중요한 기준중의 하나다. 일반적으로 건축공간에서의 사용자 행위에 대한 평가는 건물이 완성된 이후에 이루어 졌으며 최근 전산기술을 통한 사전 시뮬레이션에 대한 관심과 노력이 계속되고 있는 실정이다. 그러나 현존하는 사용자 시뮬레이션은 주로 대규모 공간의 단순한 탈출 등에 관한 것이 주를 이루고 있어 건축 공간상에서 벌어지는 다양한 사용자의 행태에 대한 시뮬레이션은 불가능한 상태이다. 본 연구는 보다 고도화된 사용자 시뮬레이션을 위한 사람형상의 지능형 에이전트의 개발은 위한 연구로서 온톨로지를 이용한 NPC의 지능화에 관한 연구이다. 연구의 주안점은 온톨로지를 통하여 구현된 공간정보와 사용자 정보를 추론하여 NPC(Non-player Character)가 가상공간 상에서 보다 지능적으로 자율주행 및 행동하게 하는 것이다. 본 연구에서는 온톨로지 추론을 기술을 가상공간에 접목시키는 방법에 대하여 주로 논의하고자 한다. 또한 이를 공간정보 상에서 온톨로지를 기반으로 기술된 정보와 이의 변화를 가시적으로 확인할 수 있는 온톨로지 가시화 기술을 제시한다.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2021년도 춘계학술대회
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• pp.151-154
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• 2021

빅데이터 분석은 데이터 저장소에 저장된 대용량 데이터 속에서 의미 있는 새로운 상관관계, 패턴, 추세를 발견하여 새로운 가치를 창출하는 과정이다. 또한 대부분의 빅데이터 분석 기술 방법들은 기존 통계학과 전산학에서 사용되던 데이터 마이닝, 기계 학습, 자연 언어 처리, 패턴 인식 등이 이에 해당된다. 그리고 빅데이터 분석 도구인 R언어를 이용하여 전-처리된 텍스트 데이터를 이용하여 다양한 시각화 함수를 통해 분석결과를 표현할 수 있다. 본 연구에서 사용된 데이터는 한국정보통신학회 학회지 논문 중에서 2021년 3월호 논문 21편을 대상으로 분석을 하였다. 최종 분석결과는 가장 많이 언급된 키워드는 "데이터"가 305회로 1위를 차지하였다. 따라서 이러한 분석결과를 바탕으로 연구의 한계와 이론적 실무적 시사점을 제시하고자 한다.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2021년도 춘계학술대회
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• pp.326-327
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• 2021

최근 빅데이터 활용은 매우 다양한 산업 분야에서 광범위하게 관심을 가지고 있다. 빅데이터 분석은 데이터 저장소에 저장된 대용량 데이터 속에서 의미 있는 새로운 상관관계, 패턴, 추세를 발견하여 새로운 가치를 창출하는 과정이다. 또한 대부분의 빅데이터 분석 기술 방법들은 기존 통계학과 전산학에서 사용되던 데이터 마이닝, 기계 학습, 자연 언어 처리, 패턴 인식 등이 이에 해당된다. 그리고 빅데이터 분석 도구인 R언어를 이용하여 전-처리된 텍스트 데이터를 이용하여 다양한 시각화 함수를 통해 분석결과를 표현할 수 있다. 본 연구에서 사용된 데이터는 특정 학회지 논문 중에서 29편을 대상으로 분석을 하였다. 최종 분석결과는 가장 많이 언급된 키워드는 "연구"가 743회로 1위를 차지하였다. 따라서 이러한 분석결과를 바탕으로 연구의 한계와 이론적 실무적 시사점을 제시하고자 한다.

• 복식문화연구
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• 제31권1호
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• pp.53-69
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• 2023

This study aims to analyze research trends regarding outdoor wear. For this purpose, the data-collection period was limited to January 2002-October 2022, and the collection consisted of titles of papers, academic names, abstracts, and publication years from the Research Information Sharing Service (RISS). Frequency analysis was conducted on 227 papers in total to check academic journals and annual trends, and LDA topic-modeling analysis was conducted using 20,964 tokens. Data pre-processing was performed prior to topic-modeling analysis; after that, topic-modeling analysis, core topic derivation, and visualization were performed using a Python algorithm. A total of eight topics were obtained from the comprehensive analysis: experiential marketing and lifestyle, property and evaluation of outdoor wear, design and patterns of outdoor wear, outdoor-wear purchase behavior, color, designs and materials of outdoor wear, promotional strategies for outdoor wear, purchase intention and satisfaction depending on the brand image of outdoor wear, differences in outdoor wear preferences by consumer group. The results of topic-modeling analysis revealed that the topic, which includes a study on the design and material of outdoor wear and the pattern of jackets related to the overall shape, was the highest at 30.9% of the total topics. The next highest topic was also the design and color of outdoor wear, indicating that design-related research was the main research topic in outdoor wear research. It is hoped that analyzing outdoor wear research will help comprehend the research conducted thus far and reveal future directions.

• 대한한의학방제학회지
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• 제31권2호
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• pp.81-98
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• 2023

Objectives : This study aimed to analyze the trends in research and development projects related to herbal medicine and natural products in the field of traditional Korean medicine (TKM) over the past 20 years. Methods : Research projects were identified using "Korean medicine" as the subject heading in the National Science and Technology Information Service. The included projects investigated Korean medicine, natural products, or were related to the TKM industry. Data pre-processing and network analysis were performed using Python and Networkx package, and the network was visualized using the ForceAtlas2 visualization algorithm. Results : 1. Over the study period, 4,020 projects were conducted with a research budget of KRW 835.2 billion. Seven institutions performed over 100 projects each, accounting for 2.4% of all participating institutions, and the top 10 institutions accounted for 58.9% of total projects. 2. Obesity was the most frequently mentioned disease-related keyword. Chronic or age-related diseases such as diabetes, osteoporosis, dementia, parkinson's disease, cancer, inflammation, and asthma were also frequent research topics. Clinical research, safety, and standardization were also frequently mentioned. 3. Centrality analysis found that obesity was the only disease-related keyword identified, alongside TKM-related keywords. Standardization, safety, and clinical trials were identified as central keywords. Conclusions : The study found that research projects in TKM have focused on standardizing and ensuring the safety of herbal medicine, as well as on chronic and age-related diseases. Clinical studies aimed at verifying the effectiveness of herbal medicine were also frequent. These findings can guide future research and development in herbal medicine.

• 대한임베디드공학회논문지
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• 제18권6호
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• pp.267-275
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• 2023

This paper presents the development of specialized software for annotating volume-of-interest on ¹⁸F-FDG PET/CT images with the goal of facilitating the studies and diagnosis of head and neck cancer (HNC). To achieve an efficient annotation process, we employed the SE-Norm-Residual Layer-based U-Net model. This model exhibited outstanding proficiency to segment cancerous regions within ¹⁸F-FDG PET/CT scans of HNC cases. Manual annotation function was also integrated, allowing researchers and clinicians to validate and refine annotations based on dataset characteristics. Workspace has a display with fusion of both PET and CT images, providing enhance user convenience through simultaneous visualization. The performance of deeplearning model was validated using a Hecktor 2021 dataset, and subsequently developed semi-automatic annotation functionalities. We began by performing image preprocessing including resampling, normalization, and co-registration, followed by an evaluation of the deep learning model performance. This model was integrated into the software, serving as an initial automatic segmentation step. Users can manually refine pre-segmented regions to correct false positives and false negatives. Annotation images are subsequently saved along with their corresponding ¹⁸F-FDG PET/CT fusion images, enabling their application across various domains. In this study, we developed a semi-automatic annotation software designed for efficiently generating annotated lesion images, with applications in HNC research and diagnosis. The findings indicated that this software surpasses conventional tools, particularly in the context of HNC-specific annotation with ¹⁸F-FDG PET/CT data. Consequently, developed software offers a robust solution for producing annotated datasets, driving advances in the studies and diagnosis of HNC.