• Title/Summary/Keyword: 전략패턴

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The effect of urban conditions, external influences, and O&M efficiency on urban water system from the perspective of water-energy nexus (도시 여건, 외부 영향 및 운영관리 효율이 넥서스 관점에서 도시 물순환 시스템에 미치는 영향)

  • Choi, Seo Hyung;Shin, Bongwoo;Shin, Eunher
    • Proceedings of the Korea Water Resources Association Conference
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    • 2022.05a
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    • pp.31-31
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    • 2022
  • 기후변화, 물 부족, 인구 증가와 도시화로 인한 물 수요 증가, 수질 악화, 노후화된 인프라와 같은 세계적인 물문제의 증가로 인해, 도시 물순환 시스템 관리는 더 큰 어려움을 겪고 있다. 취수, 도·송수, 정수처리, 배·급수, 용수 사용, 하수 집수, 하수 처리, 재이용 및 배출 과정을 포함하는 도시 물순환 시스템의 과정은 매우 에너지 집약적인 활동이며, 이와 같은 에너지 소비는 탄소 배출과 양의 직접적인 상관관계가 있다. 따라서 자원 관리 및 데이터 관리를 최적화하기 위해 넥서스 관점의 접근법이 도시 물순환 시스템에 점차적으로 도입되고 있는 추세이다. 도시 물순환 시스템 넥서스에서는 일반적으로 에너지 인텐시티로 표현되는 물을 위한 에너지를 이해하는 것이 중요하다. 에너지 인텐시티의 차이는 기후(연평균 강수량, 단기 기후 변동성, 기후패턴 등), 지리적 특징(표고차, 평지비, 위치 등), 시스템 특성(총급수량, 인구, 인구밀도, 관로 연장 등) 및 운영관리 효율(수압, 누수율, 에너지 효율 등)과 밀접한 관계가 있다. 그리고 도시 물순환 시스템에서 에너지 관리를 증진시킨 방안은 유지관리 효율 개선(물·에너지 관리전략, 물손실 관리, 수요 관리 및 수요 대응 등), 신기술 도입, 그리고 에너지 회수로 나누어진다. 본 연구에서는 기존 문헌의 자료를 분석하여 도시 물순환 시스템의 각 공정별 에너지 인텐시티를 분석하였으며, 시스템 다이나믹스를 적용하여 다양한 도시 여건(인구, lpcd, 누수율, 취수원, 에너지 인텐시티)에서 외부영향(기후변화, 도시화)과 운영효율 변동(운영효율 향상, 신시술 도입)에 따른 도시 물순환 시스템 내 자원 사용 및 이동을 분석하였다. 에너지 인텐시티는 전체 도시 물순환 시스템, 상수 시스템, 하수시스템에서 각각 2.334 kWh/m3, 1.029 kWh/m3, 1.024 kWh/m3를 나타내었으며, 용수사용, 담수화, 재이용 과정에서는 매우 높은 값이 나타났다. 에너지 인틴시티의 값은 외부 영향에 크게 좌우되는 것으로 분석되었으며, 운영효율의 변동에 따라서 물 및 에너지 사용량은 변화하였지만 에너지 인텐시티의 변동은 크지 않았다. 이에 따라 도시 물순환 시스템을 넥서스 관점에서 관리하기 위해서는 에너지 인텐시티 이외에 물 및 에너지 사용량, 유수수량 관점 에너지 인텐시티, 사용수량 관점 에너지 인텐시티를 종합적으로 고려하는 것이 필요하다.

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Biomechanical Analysis of Elderly Fall Related Risk Factors using Downhill Walking on Treadmill (트레드밀 내리막 보행을 이용한 노인 낙상관련 위험요인의 운동역학적 분석)

  • Woo, Jeong-Hyun;Park, Sang-Kyoon
    • 한국체육학회지인문사회과학편
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    • v.55 no.2
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    • pp.643-655
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    • 2016
  • The purpose of this study was to investigate biomechanical differences between young and old adults during downhill walking on a treadmill in order to understand the mechanisms of elderly falls. Eighteen healthy young females(YG: yrs: 21.17±1.5) and eighteen healthy old females(OG: yrs: 66.67±1.33) participated in this study. They were asked to walk at their preferred speed on a treadmill at level, 7.5° and 15° decline. OG walked more wobbly in the medial and lateral directions than YG(p<.05). As slope got steeper, OG had smaller ROM(range of motion) of ankle and knee joints compared with YG. However, there was no difference in ROM of the hip between OG and YG, but maximum extension angle of OG was smaller compared with YG(p<.05). Smaller extensor moment was generated on OG during downhill walking(p<.05). It was hypothesized that more risk factors would be found on older people compared to young people during downhill. However, older people actually walks with a safer strategy compared to young people during downhill. Finally, current findings about biomechanical characteristics of elderly walking would provide useful fundamental information for a follow-up study regarding the prevention of elderly fall during their daily life.

Evaluation of Habitat Suitability of Major Honey Trees in the Mt. Gariwang and Mt. Yumeong through Machine Learning Approach (머신러닝기법을 활용한 가리왕산과 유명산 지역 주요 밀원수의 서식지 적합성 평가)

  • Yong-Ju Lee;Min-Ki Lee;Hae-In Lee;Chang-Bae Lee;Hyeong-Seok Sim
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.25 no.4
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    • pp.311-325
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    • 2023
  • This study was conducted to analyze the habitat suitability of the major honey trees including Kalopanax septemlobus Koidz., Prunus spp., Tilia spp., and Styrax obassia Siebold & Zucc. indigenous to mountain Gariwang and Yumeong using the machine learning approach (i.e., MaxEnt model). The AUC values of the model predictions were mostly above 0.7, and the results of the response curves showed that the environmental drivers that had effects on the habitat suitability of the major honey trees were elevation, mean annual precipitation, and mean annual temperature. These results indicate that climatic drivers along the elevation gradient are the main environmental drivers in explaining the distribution patterns of the major honey trees. In addition, the results of the response curves of Prunus spp. and Styrax obassia Siebold & Zucc. differed slightly in terms of slope and mean annual solar radiation as the main environmental drivers. The results of this study will be valuable for the establishment of honey tree forests and management plans for the natural and artificial forests in South Korea, as well as for the mapping the distribution of honey trees. Further studies at different regional levels, reflecting biotic drivers, will be needed to expand the production of honey and pollen at different strata and to produce honey annually.

Determining Food Nutrition Information Preference Through Big Data Log Analysis (빅데이터 로그분석을 통한 식품영양정보 선호도 분석)

  • Hana Song;Hae-Jeung, Lee;Hunjoo Lee
    • Journal of Food Hygiene and Safety
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    • v.38 no.5
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    • pp.402-408
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    • 2023
  • Consumer interest in food nutrition continues to grow; however, research on consumer preferences related to nutrition remains limited. In this study, big data analysis was conducted using keyword logs collected from the national information service, the Korean Food Composition Database (K-FCDB), to determine consumer preferences for foods of nutritional interest. The data collection period was set from January 2020 to December 2022, covering a total of 2,243,168 food name keywords searched by K-FCDB users. Food names were processed by merging them into representative food names. The search frequency of food names was analyzed for the entire period and by season using R. In the frequency analysis for the entire period, steamed rice, chicken, and egg were found to be the most frequently consumed foods by Koreans. Seasonal preference analysis revealed that in the spring and summer, foods without broth and cold dishes were consumed frequently, whereas in fall and winter, foods with broth and warm dishes were more popular. Additionally, foods sold by restaurants as seasonal items, such as Naengmyeon and Kongguksu, also exhibited seasonal variations in frequency. These results provide insights into consumer interest patterns in the nutritional information of commonly consumed foods and are expected to serve as fundamental data for formulating seasonal marketing strategies in the restaurant industry, given their indirect relevance to consumer trends.

A Study of the Beauty Commerce Customer Segment Classification and Application based on Machine Learning: Focusing on Untact Service (머신러닝 기반의 뷰티 커머스 고객 세그먼트 분류 및 활용 방안: 언택트 서비스 중심으로)

  • Sang-Hyeak Yoon;Yoon-Jin Choi;So-Hyun Lee;Hee-Woong Kim
    • Information Systems Review
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    • v.22 no.4
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    • pp.75-92
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    • 2020
  • As population and generation structures change, more and more customers tend to avoid facing relation due to the development of information technology and spread of smart phones. This phenomenon consists with efficiency and immediacy, which are the consumption patterns of modern customers who are used to information technology, so offline network-oriented distribution companies actively try to switch their sales and services to untact patterns. Recently, untact services are boosted in various fields, but beauty products are not easy to be recommended through untact services due to many options depending on skin types and conditions. There have been many studies on recommendations and development of recommendation systems in the online beauty field, but most of them are the ones that develop recommendation algorithm using survey or social data. In other words, there were not enough studies that classify segments based on user information such as skin types and product preference. Therefore, this study classifies customer segments using machine learning technique K-prototypesalgorithm based on customer information and search log data of mobile application, which is one of untact services in the beauty field, based on which, untact marketing strategy is suggested. This study expands the scope of the previous literature by classifying customer segments using the machine learning technique. This study is practically meaningful in that it classifies customer segments by reflecting new consumption trend of untact service, and based on this, it suggests a specific plan that can be used in untact services of the beauty field.

A Case Study on the Smart Tourism City Using Big Data: Focusing on Tourists Visiting Jeju Province (빅 데이터를 활용한 스마트 관광 도시 사례 분석 연구: 제주특별자치도 관광객 데이터를 중심으로)

  • Junhwan Moon;Sunghyun Kim;Hesub Rho;Chulmo Koo
    • Information Systems Review
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    • v.21 no.2
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    • pp.1-27
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    • 2019
  • It is possible to provide Smart Tourism Service through the development of information technology. It is necessary for the tourism industry to understand and utilize Big Data that has tourists' consumption patterns and service usage patterns in order to continuously create a new business model by converging with other industries. This study suggests to activate Jeju Smart Tourism by analyzing Big Data based on credit card usage records and location of tourists in Jeju. The results of the study show that First, the percentage of Chinese tourists visiting Jeju has decreased because of the effect of THAAD. Second, Consumption pattern of Chinese tourists is mostly occurring in the northern areas where airports and duty-free shops are located, while one in other regions is very low. The regional economy of Jeju City and Seogwipo City shows a overall stagnation, without changes in policy, existing consumption trends and growth rates will continue in line with regional characteristics. Third, we need a policy that young people flow into by building Jeju Multi-complex Mall where they can eat, drink, and go shopping at once because the number of young tourists and the price they spend are increasing. Furthermore, it is necessary to provide services for life-support related to weather, shopping, traffic, and facilities etc. through analyzing Wi-Fi usage location. Based on the results, we suggests the marketing strategies and public policies for understanding Jeju tourists' patterns and stimulating Jeju tourism industry.

Exploring Collaborative Learning Dynamics in Science Classes Using Google Docs: An Epistemic Network Analysis of Student Discourse (공유 문서를 활용한 과학 수업에서 나타난 학생 담화의 특징 -인식 네트워크 분석(ENA)의 활용-)

  • Eunhye Shin
    • Journal of The Korean Association For Science Education
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    • v.44 no.1
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    • pp.77-86
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    • 2024
  • This study analyzed students' discourse and learning to investigate the impact of using Google Docs in science classes. The researcher, who is also a science teacher, conducted classes for 49 second-year middle school students. The classes included one using Google Docs and another using traditional paper worksheets covering identical content. Students' discourse collected from each class was compared and analyzed using Epistemic Network Analysis (ENA). The findings indicated that in the class using Google Docs, the proportion of discourse related to task was higher compared to the traditional class. More specifically, discourse regarding taking and uploading photos was prominent. However, such discourse did not lead to peer learning as intended by the teacher. An analysis based on achievement levels revealed that the class utilizing Google Docs had a relatively higher proportion of discourse from lower-achieving students. Additionally, differences were observed in the types of utterances and connection structures between the higher and lower-achieving students. The higher-achieving students took a leading role in providing suggestions and explanations, while the lower-achieving students played a role in transcribing them, with this tendency being more pronounced in the class using Google Docs. Lastly, students' changes in perception regarding the cause of static electricity were visualized using ENA. Based on the research findings, this study proposes strategies to enhance collaborative learning using Google Docs, including the use of open-ended problems to allow diverse opinions and outputs, and exploring the potential use of ENA to assess the learning effects of conceptual learning.

Changes in Floating Population Distribution in Jeju Island Tourist Destinations Before and After COVID-19 Using Spatial Big Data Analysis (공간 빅데이터 분석을 활용한 COVID-19 전후 제주도 관광지의 유동인구 분포 변화)

  • Heonkyu Jeong;Yong-Bok Choi
    • Journal of the Korean Association of Geographic Information Studies
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    • v.27 no.1
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    • pp.12-28
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    • 2024
  • This study aims to identify the trend of changes in tourist floating population before and after COVID-19 in major tourist destinations in Jeju Island through spatial analysis. Seongsan-eup and Andeok-myeon in Jeju Island were selected as the research area, and the research period was set at 1 year before and 2 years after the COVID-19 outbreak. For the analysis, mobile floating population data was refined and processed to calculate floating population distribution and floating population increase/decrease data. This was converted into spatial data and an overlay analysis was performed with location data of major tourist attractions. As a result of the analysis, it was confirmed that the floating population of indoor tourist attractions and small facilities decreased immediately after COVID-19, and that in open coastal areas or large facilities, the floating population decreased less or actually increased. In conclusion, in tourism development, it is necessary to identify changes in floating population according to the characteristics of tourist facilities, and it is necessary to develop tourism facilities and strategies that can respond to risk situations such as pandemics when developing tourist destinations.

Analysis of Ecological Connectivity of Forest Habitats Using Spatial Morphological Characteristics and Roadkill Data (공간형태학적 특성 및 로드킬 자료를 활용한 산림서식지의 생태적 연결성 분석)

  • Hyunjin Seo;Chulhyun Choi;Seungwon Lee;Jinhyo Kim
    • Korean Journal of Ecology and Environment
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    • v.57 no.2
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    • pp.75-82
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    • 2024
  • This study examined the spatial morphological patterns of forest habitats and the characteristics of roadkill occurrences in the forests of Mungyeong, Yecheon, Yeongju, Andong, and Bonghwa in Gyeongsangbukdo. It involved building a resistance map between habitats and analyzing connectivity based on the least-cost distance. The analysis of the distance between the forest habitat Cores derived from MSPA and roadkill points showed that roadkill occurrences were concentrated approximately 74.11 m away from the Cores, with most roadkills happening within 360m from the habitats. The connectivity analysis between core habitats larger than 1 km2 revealed 141 core habitats and 242 least-cost paths between them. The corridor distance value was found to be highest in Mungyeong city, indicating an urgent need for strategies to enhance habitat connectivity there. This research is expected to serve as foundational data for developing strategies to enhance ecosystem connectivity and restore habitats, by analyzing ecosystem connectivity and roadkill issues due to habitat fragmentation.

A Study of Service Innovation in the Airport Industry using AHP (계층화 분석법을 활용한 공항 산업 서비스 혁신 연구)

  • Hong hwan Ahn;Han Sol Lim;Seung Kyun Ra;Bong Gyou Lee
    • Journal of Internet Computing and Services
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    • v.25 no.3
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    • pp.71-81
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    • 2024
  • In response to the COVID-19 pandemic, the global airport industry is actively introducing 4th Industrial Revolution technology-based systems for quarantine and passenger safety, and test bed construction and prior verification using airport infrastructure and resources are actively being conducted. Analysis of recent cases shows that despite the changing travel patterns of airport users and the diversification of airport service demands, most testbeds construction studies are still focused on suppliers, and task prioritization is also determined by decision makers. There is a tendency to rely on subjective judgment. In order to find practical ways to become a first mover that leads innovation in the aviation industry, this study selected tasks and derived priorities to build testbeds from a service perspective that reflects various customer service needs and changes. Research results using the AHP analysis method resulted in priorities in the order of access transportation and parking services (29.2%), security screening services (23.4%), and departure services (21.8%), and these analysis results were tested in the airport industry. It shows that innovation in testbeds construction is an important factor. In particular, the establishment of smart parking and UAM transportation testbeds not only helps strengthen airports as centers of technological innovation, but also promotes cooperation with companies, research institutes, and governments, and provides an environment for testing and developing new technologies and services. It can be a foundation for what can be done. The results and implications produced through this study can serve as useful guidelines for domestic and foreign airport practitioners to build testbeds and establish strategies.