• 인간식물환경학회지
• /
• 제24권5호
• /
• pp.451-460
• /
• 2021

Background and objective: The prolonged COVID-19 pandemic has had significant impacts on mental health, which has emerged as a major public health issue around the world. This study aimed to analyze trends and network structure of 'grow-your-own (GYO)' through Instagram, one of the most influential social media platforms, to encourage and sustain home gardening activities for promotion of emotional support and physical health. Methods: A total of 6,388 posts including keyword hashtags '#gyo' and '#growyourown' on Instagram from June 13, 2020 to April 13, 2021 were collected. Word embedding was performed using Word2Vec library, and 7 clusters were identified with K-means clustering: GYO, garden and gardening, allotment, kitchen garden, sustainability, urban gardening, etc. Moreover, we conducted social network analysis to determine the centrality of related words and visualized the results using Gephi 0.9.2. Results: The analysis showed that various combinations of words, such as #growourrownfood, #growourrownveggies, and #growwhatyoueat revealed preference and interest of users in GYO, and appeared to encourage their activities on Instagram. In particular, #gardeningtips, #greenfingers, #goodlife, #gardeninglife, #gardensofinstagram were found to express positive emotions and pride as a gardener by sharing their daily gardening lives. Users were participating in urban gardening through #allotment, #raisedbeds, #kitchengarden and we could identify trends toward self-sufficiency and sustainable living. Conclusion: Based on these findings, it is expected that the trend data of GYO, which is a form of urban gardening, can be used as the basic data to establish urban gardening plans considering each characteristic, such as the emotions and identity of participants as well as their dispositions.

• 한국수자원학회:학술대회논문집
• /
• 한국수자원학회 2023년도 학술발표회
• /
• pp.104-104
• /
• 2023

최근 2017년 청주, 천안의 홍수, 2020년 용담댐 상류와 대청댐 상류의 홍수, 2022년 청주의 도시침수를 비롯한 서울 도심의 침수피해와 같은 홍수 발생은 지역의 국민들에게 막대한 재산상의 피해를 입히고 있다. 국가적 차원에서 치수의 목적을 달성하고 경제적으로 적절한 규모의 수리구조물을 설계하기 위해 하천의 주요지점에 대한 신뢰성 있는 설계홍수량의 제시는 반드시 필요한 현실에 직면해 있다. 특히 해당 지점의 수리시설물은 점빈도분석에 의한 설계홍수량을 적용하나, 관측자료가 없는 미계측 지점에 위치한 수리시설물은 지역빈도분석에 의한 설계홍수량을 산정하여 적용해야 한다. 이에 본 연구에서는 금강 유역을 대상으로 점빈도분석과 지역빈도분석에 의한 설계홍수량 결과를 비교·분석하고자 한다. 지역빈도분석을 위한 수위관측소의 선정은 금강유역 80개 수위관측소 중 장기간 연최대홍수량 자료가 있고 유량자료의 연결성 및 신뢰성이 확보된 46개수위관측소를 대상으로 하였다. 46개 수위관측소의 연최대홍수량 계열을 대상으로 동질성, 독립성 및 이상치 검정을 수행하였으며, 세 가지 검정 모두 적절한 수위 관측소 지점은 36개 지점으로 분석되었다. 36개 수위관측소의 기본통계치(평균, 표준편차, 분산, 왜곡도 및 첨예도)를 산정한 후 3변수 Gamma 분포 계열인 GEV, GLO, GPA의 확률 분포를 적용하였다. 확률 분포별 매개변수는 전산화를 통해 L-모멘트의 차수를 0~4까지 변화시켜 LH-모멘트법에 적용하였다. LH-모멘트법에 의해 산정된 확률 분포들의 매개변수를 적용하여 적합도 검정을 수행하였다. 지역빈도분석을 위해 36개 수위관측소를 K-Means clustering 방법을 통해 4개 지역으로 구분하였다. 이를 통해LH-모멘트의 적정차수와 확률 분포에 따른 점빈도분석(지점 대상)과 지역빈도분석(지역 대상) 결과인 설계홍수량을 산정하였으며, 점빈도분석과 지역빈도분석에 의해 산정된 설계홍수량간의 분석결과를 제시하였다. 본 연구를 통해 수리구조물 설계 시 안정적인 조건 제시 및 관리체계 구축에 기여하고 방재대책 수립 시 경제·사회적 요소를 반영한 합리적 방안을 제시하고자 한다.

• 한국프랜차이즈경영연구
• /
• 제7권1호
• /
• pp.21-29
• /
• 2016

Purpose - The primary purpose of this study is to employ effective marketing methods using market segmentation of coffee shops by determining how motivations to visit coffee shops have different impacts on demographic profile of visitors and characteristics of coffee shop visits, so as to draw out a better understanding of customers of coffee market. Research design, data, and methodology - Data were collected using surveys of self-administered questionnaires toward coffee shop users in Daejeon, Korea. A number of samples used in data analysis were 253 excluding unusable responses. The data were analyzed through frequency, reliability, and factor analysis using SPSS 20.0. Factor analysis was conducted through the principal component analysis and varimax rotation method to derive factors of one or more eigen values. In addition, the cluster analysis, multivariate ANOVA, and cross-tab analysis were used for the market segmentation based on the types of motivation for coffee shop visits. The process of the cluster analysis is as follows. Four clusters were derived through hierarchical clustering, and k-means cluster analysis was then carried out using mean value of the four clusters as the initial seed value. Result - The factor analysis delineated four dimensions of motivation to visit coffee shops: ostentation motivation, hedonic motivation, esthetic motivation, utility motivation. The cluster analysis yielded four clusters: utility and esthetic seekers, hedonic seekers, utility seekers, ostentation seekers. In order to further specify the profile of four clusters, each cluster was cross tabulated with socio-demographics and characteristics of coffee shop visits. Four clusters are significantly different from each other by four types of motivations for coffee shop visits. Conclusions - This study has empirically examined the difference in demographic profile of visitors and characteristics of coffee shop visits by motivation to visit coffee shops. There are significant differences according to age, education background, marital status, occupation and monthly income. In addition, coffee shops use pattern characterization in frequency of visits to coffee shops, relationships with companion, purpose of visit, information sources, brand type, average expense per visit, important elements of selection attribute were significantly different depending on motivations for coffee shop visits.

• International Journal of Computer Science & Network Security
• /
• 제24권6호
• /
• pp.8-16
• /
• 2024

Communication with the deaf has always been crucial. Deaf and hard-of-hearing persons can now express their thoughts and opinions to teachers through sign language, which has become a universal language and a very effective tool. This helps to improve their education. This facilitates and simplifies the referral procedure between them and the teachers. There are various bodily movements used in sign language, including those of arms, legs, and face. Pure expressiveness, proximity, and shared interests are examples of nonverbal physical communication that is distinct from gestures that convey a particular message. The meanings of gestures vary depending on your social or cultural background and are quite unique. Sign language prediction recognition is a highly popular and Research is ongoing in this area, and the SVM has shown value. Research in a number of fields where SVMs struggle has encouraged the development of numerous applications, such as SVM for enormous data sets, SVM for multi-classification, and SVM for unbalanced data sets.Without a precise diagnosis of the signs, right control measures cannot be applied when they are needed. One of the methods that is frequently utilized for the identification and categorization of sign languages is image processing. African Buffalo Optimization using Support Vector Machine (ABO+SVM) classification technology is used in this work to help identify and categorize peoples' sign languages. Segmentation by K-means clustering is used to first identify the sign region, after which color and texture features are extracted. The accuracy, sensitivity, Precision, specificity, and F1-score of the proposed system African Buffalo Optimization using Support Vector Machine (ABOSVM) are validated against the existing classifiers SVM, CNN, and PSO+ANN.

• 한국간호교육학회지
• /
• 제30권2호
• /
• pp.182-191
• /
• 2024

Purpose: The purpose of this study was to explore the characteristics of social networks among registered nurses in acute nursing care units. Methods: This study used a survey design. Four nursing units from two acute hospitals were selected using a convenience method, and 83 nurses from those nursing units participated in the study in July 2022. The positive influences among nurses included friendship, collaboration, advice, and referent networks, and the negative influences included avoidance and bullying networks. Using the NetMiner program, the k-means clustering technique was applied to create groups of nodes with similar characteristics. The general characteristics of the participants were analyzed by mean, standard deviation, frequency, and ANOVA or chi-squared test. Results: As a result of dividing the 83 nurse participants into four clusters, positive influencers, silent peers, unwelcome peers, and active bullies were identified. Positive influence group nurses were frequently mentioned in the friendship, collaboration, advice, and referent networks. On the other hand, nurses in the unwelcome group and the active bullying group were frequently mentioned in the avoidance and bullying networks. Conclusion: Social networks that have a positive or negative impact on nursing performance are created through different relationships between nurses. Nurse managers can use the findings to create a more supportive and collaborative environment. Further research is needed to develop intervention programs to improve interactions and relationships between fellow nurses.

• 복식문화연구
• /
• 제32권2호
• /
• pp.199-214
• /
• 2024

Until now, research on consumers' purchasing behavior has primarily focused on psychological aspects or depended on consumer surveys. However, there may be a gap between consumers' self-reported perceptions and their observable actions. In response, this study aimed to investigate consumer purchasing behavior utilizing a big data approach. To this end, this study investigated the purchasing patterns of fashion items, both online and in retail stores, from a data-driven perspective. We also investigated whether individual consumers switched between online websites and retail establishments for making purchases. Data on 516,474 purchases were obtained from fashion companies. We used association rule analysis and K-means clustering to identify purchase patterns that were influenced by customer loyalty. Furthermore, sequential pattern analysis was applied to investigate the usage patterns of online and offline channels by consumers. The results showed that high-loyalty consumers mainly purchased infrequently bought items in the brand line, as well as high-priced items, and that these purchase patterns were similar both online and in stores. In contrast, the low-loyalty group showed different purchasing behaviors for online versus in-store purchases. In physical environments, the low-loyalty consumers tended to purchase less popular or more expensive items from the brand line, whereas in online environments, their purchases centered around items with relatively high sales volumes. Finally, we found that both high and low loyalty groups exclusively used a single preferred channel, either online or in-store. The findings help companies better understand consumer purchase patterns and build future marketing strategies around items with high brand centrality.

• 지능정보연구
• /
• 제21권3호
• /
• pp.19-36
• /
• 2015

대표적 소셜미디어인 유튜브는 기존 폐쇄형 콘텐츠 서비스와는 다르게 개방형 콘텐츠 서비스로 이용자들의 참여와 공유를 통하여 많은 인기를 유지하고 있다. 콘텐츠 산업에서 중요한 위치를 차지하고 있는 유투브 상의 콘텐츠 확산 요인에 관한 기존의 연구들은 댓글 수 등과 같은 일반적 정보 특성 요인과 조회 수 간에 상관관계 등을 분석하는 것이 대부분이었다. 최근 네트워크 구조를 기반으로 한 연구들도 진행되었으나 대부분 콘텐츠를 이용하는 대상인 구독자나 지인 등을 중심으로 한 인적 관계 네트워크 구조 연구가 대부분이었다. 이에 본 연구에서는 실질적인 콘텐츠를 중심으로 한 네트워크 구조와 일반요인을 통합한 모델을 제시하고 확산요인을 분석하고자 한다. 이를 위해 통합 모델 인과관계 분석과 함께 21,307개의 유튜브 콘텐츠를 콘텐츠 기반 네트워크 구조로 분석하였다. 본 연구를 통해 기존에 알려진 일반적 요인과 네트워크 요인들이 모두 조회수에 영향을 주는 인과관계를 통계적으로 재검증하였으며 통합적으로는 등록자의 구독자 수, 경과시간, 매개 중심성, 댓글 수, 근접 중심성, 클러스터링 계수, 평균 평점 순으로 조회 수에 긍정적인 영향을 미치는 것으로 분석되었다. 하지만 네트워크 요인중 연결정도 중심성과 고유벡터 중심성은 부정적 영향을 주는 것으로 분석되었다. 본 연구를 통하여 유튜브 콘텐츠 확산에 대한 일반영향요인과 구조적인 현상을 함께 규명하였다. 본 연구는 기업들이 유튜브와 같은 콘텐츠 서비스를 통한 온라인 마케팅 활동 시 콘텐츠들의 구조적인 면을 고려할 수 있는 근거를 제공하였으며 음반산업의 수요예측이나 콘텐츠 제작 업체들의 원활한 서비스 제공을 위한 설명력있는 영향요인 및 모델이 될 수 있을 것이다.

• 지능정보연구
• /
• 제18권3호
• /
• pp.53-77
• /
• 2012

본 연구는 경향신문, 한겨레, 동아일보 세 개의 신문기사가 가지고 있는 내용 및 논조에 어떠한 차이가 있는지를 객관적인 데이터를 통해 제시하고자 시행되었다. 본 연구는 텍스트 마이닝 기법을 활용하여 신문기사의 키워드 단순빈도 분석과 Clustering, Classification 결과를 분석하여 제시하였으며, 경제, 문화 국제, 사회, 정치 및 사설 분야에서의 신문사 간 차이점을 분석하고자 하였다. 신문기사의 문단을 분석단위로 하여 각 신문사의 특성을 파악하였고, 키워드 네트워크로 키워드들 간의 관계를 시각화하여 신문사별 특성을 객관적으로 볼 수 있도록 제시하였다. 신문기사의 수집은 신문기사 데이터베이스 시스템인 KINDS에서 2008년부터 2012년까지 해당 주제로 주제어 검색을 하여 총 3,026개의 수집을 하였다. 수집된 신문기사들은 불용어 제거와 형태소 분석을 위해 Java로 구현된 Lucene Korean 모듈을 이용하여 자연어 처리를 하였다. 신문기사의 내용 및 논조를 파악하기 위해 경향신문, 한겨레, 동아일보가 정해진 기간 내에 일어난 특정 사건에 대해 언급하는 단어의 빈도 상위 10위를 제시하여 분석하였고, 키워드들 간 코사인 유사도를 분석하여 네트워크 지도를 만들었으며 단어들의 네트워크를 통해 Clustering 결과를 분석하였다. 신문사들마다의 논조를 확인하기 위해 Supervised Learning 기법을 활용하여 각각의 논조에 대해 분류하였으며, 마지막으로는 분류 성능 평가를 위해 정확률과 재현률, F-value를 측정하여 제시하였다. 본 연구를 통해 문화 전반, 경제 전반, 정치분야의 통합진보당 이슈에 대한 신문기사들에 전반적인 내용과 논조에 차이를 보이고 있음을 알 수 있었고, 사회분야의 4대강 사업에 대한 긍정-부정 논조에 차이가 있음을 발견할 수 있었다. 본 연구는 지금까지 연구되어왔던 한글 신문기사의 코딩 및 담화분석 방법에서 벗어나, 텍스트 마이닝 기법을 활용하여 다량의 데이터를 분석하였음에 의미가 있다. 향후 지속적인 연구를 통해 분류 성능을 보다 높인다면, 사람들이 뉴스를 접할 때 그 뉴스의 특정 논조 성향에 대해 우선적으로 파악하여 객관성을 유지한 채 정보에 접근할 수 있도록 도와주는 신뢰성 있는 툴을 만들 수 있을 것이라 기대한다.

• 대한미생물학회지
• /
• 제35권1호
• /
• pp.31-40
• /
• 2000

Bacillus anthracis, the etiological agent of anthrax has been classified into the Bacillus subgroup I with B. cereus, B. mycoides and B. thuringiensis based on morphological and DNA similarity. DNA studies have further indicated that these species have very AT-rich genomes and high homology, indeed it has been proposed that these four sub-species be recognized as members of the one species. Several methods have been developed to obtain good differentiation between these species. However, none of these methods provides the means for an absolutely correct differntiation. The analysis of fatty acid methyl esters (FAMEs) was employed as a quick, simple and reliable method for the identification of 21 B. anthracis strains and closley related strains. The most significant differences were found between B. anthracis and B. anthracis closely related strains in FAMEs profiles. All tested strains of B. anthracis had a branched fatty acid C17:1 Anteiso A, whereas the fraction of unsaturated fatty acid Iso C17:1 w10c was found in B. anthracis closely related strains. By UPGMA clustering analysis of FAMEs profiles, all of the tested strains were classified into two clusters defined at Euclidian distance value of 24.5. The tested strains of B. anthracis were clustered together including Bacillus sp. Kyungjoo 3. However, the isolates of B. anthracis closely related spp. Rho, S10A, 11R1, CAU9910, CAU9911, CAU9912 and CAU9913 were clustered with the other group. On the basis of these results, isolates of B. anthracis Bongchon, Kyungjoo 1, 2 and Bacillus sp. Kyungjoo 3 were reclassified as a B. anthracis. It is concluded that FAMEs analysis provides a sensitive and reliable method for the identification of B. anthracis from closely related taxa.

• Journal of Nutrition and Health
• /
• 제40권3호
• /
• pp.259-269
• /
• 2007

Recently, dietary pattern analysis was emerged as an approach to examine the relationships between diet and risk of chronic diseases. This study was to identify groups with population who report similar dietary pattern in Korean genome epidemiology study (KoGES) and association with several chronic diseases. The cohort participants living in Ansung and Ansan (Gyeonggi province) were totally 10,038. Among those, 6,873 subjects with no missing values in food frequency questionnaire were included in this analysis. After combining 103 food items into 17 food groups, 4 dietary factors were obtained by factor analysis based on their weights. Factor 1 showed high factor loadings in vegetables, mushrooms, meats, fish, beverages, and oriental-cereals. Factor 2 had high factor loadings in vegetables, fruits, fish, and factor 3 had high factor loadings in cereal-oriental, cerial-western and snacks. Factor 4 showed positive high factor loadings in rice and Kimchi and negative factor loadings in mushrooms and milk and dairy products. Using factor scores of four factors, subjects were classified into 3 clusters by K-means clustering. We named those 'Rice and Kimchi eating' group, 'Contented eating' group, and 'Healthy and light eating' group depending on their eating characteristics. 'Rice and Kimchi eating' group showed high prevalence in men, farmers and 60s. 'Contented eating' group and 'Healthy and light eating' group had high prevalence in women, people living in urban area (Ansan Citizen), with high-school education and above, and a monthly income of one million won and more. 'Contented eating' group appeared lower distribution proportion in the sixties and 'Healthy and light eating' group does higher in the fifties. 'Contented eating' versus 'Rice and Kimchi eating', odds ratio for hypertension, diabetes, metabolic syndrome and obesity significantly decreased after adjusting age and sex (OR=0.64, 0.73, and 0.85 respectively, 95% CI). Although our results were from a cross-sectional study, these imply that the dietary patterns were related to diseases.