• Title/Summary/Keyword: 패턴 적용

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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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The Study to Suggest a Methods to Evaluate Heating and Cooling Energy Performance based on Daily Life (실생활기반 냉난방에너지 성능평가 방법 제안 연구)

  • Jeon, Gangmin;Lee, Heangwoo;Kim, Yongseong
    • Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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    • v.5 no.3
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    • pp.291-299
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    • 2015
  • With recent surge of attention to heating and air conditioning energy consumption, the need for evaluating performance of heating and air conditioning energy is also on the rise. This research aims to propose daily-life based evaluation method as an alternative to existing one, as well as to apply the method in real life to prove its validity. The results are as following. 1) I studied temperatures preferred by persons indoors and appropriate level of temperature, and the results show that properties of such persons such as age is directly linked with pleasantness of the room, but the issue lies with the fact that such properties are not considered in existing performance evaluation of heating and air conditioning. 2) Daily life based evaluation proposed herein reflects such properties of persons indoors. It controls heating / air conditioning devices installed in the test bed with the same size as a real life room to get quantitative and visual performances in our daily life as well as simple temperature information. 3) To verify validity of daily life based evaluation, I conducted different evaluation sessions with and without a blind and also based on ages of persons indoors. Results based on properties of persons showed difference of 77.6%, leading to effective analysis of energy consumption pattern by heating / air conditioning devices. This research takes significance in that it comes with a new performance evaluation method based on real life, and I gather that further studies are required to develop more multilateral performance evaluation in order to verify and improve technology for reduction of energy consumption.

A Ukulele Playing Intervention for Improving the Hand Function of Patients With Central Nervous System Damage: A TIMP Case Study (중추신경계 손상 성인 대상 손 기능 향상을 위한 우쿨렐레 활용 치료적 악기연주(TIMP) 사례)

  • Joo, Ye-Eun;Park, Jin-Kyoung
    • Journal of Music and Human Behavior
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    • v.19 no.2
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    • pp.81-103
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    • 2022
  • The effects of therapeutic instrumental music performance (TIMP) using a ukulele were examined in adults with central nervous system damage and impaired hand functions. The participants were three adults with neurological damage who participated in 30-min sessions twice a week over 6 weeks. Changes in hand function was measured by the Box and Block Test (BBT), the 9-Hole Peg Test (9-HPT), and the Jebsen-Taylor Hand Function Test (JTHFT). Following the intervention, all three participants showed increases in the BBT and 9-HPT scores, indicating positive changes in fine motor coordination and dexterity. In terms of the JTHFT, all three participants showed increases in the "writing" and "card flipping" subtask scores, indicating that the intervention was effective in improving more coordinated finger movements. All participants reported the satisfaction with the intervention. They also pointed out that they were motivated to play the ukulele and that following the intervention used their affected hand more frequently in daily activities. These findings suggest that TIMP with a ukulele for patients with central nervous system damage can have positive effects on their functional hand movements and motivate these patients to practice their rehabilitation exercises.

Water temperature prediction of Daecheong Reservoir by a process-guided deep learning model (역학적 모델과 딥러닝 모델을 융합한 대청호 수온 예측)

  • Kim, Sung Jin;Park, Hyungseok;Lee, Gun Ho;Chung, Se Woong
    • Proceedings of the Korea Water Resources Association Conference
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    • 2021.06a
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    • pp.88-88
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    • 2021
  • 최근 수자원과 수질관리 분야에 자료기반 머신러닝 모델과 딥러닝 모델의 활용이 급증하고 있다. 그러나 딥러닝 모델은 Blackbox 모델의 특성상 고전적인 질량, 운동량, 에너지 보존법칙을 고려하지 않고, 데이터에 내재된 패턴과 관계를 해석하기 때문에 물리적 법칙을 만족하지 않는 예측결과를 가져올 수 있다. 또한, 딥러닝 모델의 예측 성능은 학습데이터의 양과 변수 선정에 크게 영향을 받는 모델이기 때문에 양질의 데이터가 제공되지 않으면 모델의 bias와 variation이 클 수 있으며 정확도 높은 예측이 어렵다. 최근 이러한 자료기반 모델링 방법의 단점을 보완하기 위해 프로세스 기반 수치모델과 딥러닝 모델을 결합하여 두 모델링 방법의 장점을 활용하는 연구가 활발히 진행되고 있다(Read et al., 2019). Process-Guided Deep Learning (PGDL) 방법은 물리적 법칙을 반영하여 딥러닝 모델을 훈련시킴으로써 순수한 딥러닝 모델의 물리적 법칙 결여성 문제를 해결할 수 있는 대안으로 활용되고 있다. PGDL 모델은 딥러닝 모델에 물리적인 법칙을 해석할 수 있는 추가변수를 도입하며, 딥러닝 모델의 매개변수 최적화 과정에서 Cost 함수에 물리적 법칙을 위반하는 경우 Penalty를 추가하는 알고리즘을 도입하여 물리적 보존법칙을 만족하도록 모델을 훈련시킨다. 본 연구의 목적은 대청호의 수심별 수온을 예측하기 위해 역학적 모델과 딥러닝 모델을 융합한 PGDL 모델을 개발하고 적용성을 평가하는데 있다. 역학적 모델은 2차원 횡방향 평균 수리·수질 모델인 CE-QUAL-W2을 사용하였으며, 대청호를 대상으로 2017년부터 2018년까지 총 2년간 수온과 에너지 수지를 모의하였다. 기상(기온, 이슬점온도, 풍향, 풍속, 운량), 수문(저수위, 유입·유출 유량), 수온자료를 수집하여 CE-QUAL-W2 모델을 구축하고 보정하였으며, 모델은 저수위 변화, 수온의 수심별 시계열 변동 특성을 적절하게 재현하였다. 또한, 동일기간 대청호 수심별 수온 예측을 위한 순환 신경망 모델인 LSTM(Long Short-Term Memory)을 개발하였으며, 종속변수는 수온계 체인을 통해 수집한 수심별 고빈도 수온 자료를 사용하고 독립 변수는 기온, 풍속, 상대습도, 강수량, 단파복사에너지, 장파복사에너지를 사용하였다. LSTM 모델의 매개변수 최적화는 지도학습을 통해 예측값과 실측값의 RMSE가 최소화 되로록 훈련하였다. PGDL 모델은 동일 기간 LSTM 모델과 동일 입력 자료를 사용하여 구축하였으며, 역학적 모델에서 얻은 에너지 수지를 만족하지 않는 경우 Cost Function에 Penalty를 추가하여 물리적 보존법칙을 만족하도록 훈련하고 수심별 수온 예측결과를 비교·분석하였다.

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A Study on the Classification of Road Type by Mixture Model (혼합모형을 이용한 도로유형분류에 관한 연구)

  • Lim, Sung Han;Heo, Tae Young;Kim, Hyun Suk
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.28 no.6D
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    • pp.759-766
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    • 2008
  • Road classification system is the first step for determining the road function and design standards. Currently, roads are classified by various indices such as road location and function. In this study, we classify road using various traffic indices as well as to identify traffic characteristics for each type of road. To accomplish the objectives, mixture model was applied for classifying road and analyzing traffic characteristics using traffic data that observed at permanent traffic count stations. A total of 8 variables were applied: annual average daily traffic(AADT), $K_{30}$ coefficient, heavy vehicle proportion, day volume proportion, peak hour volume proportion, sunday coefficient, vacation coefficient, and coefficient of variation(COV). A total of 350 permanent traffic count points were categorized into three groups : Group I (Urban road), Group II (Rural road), and Group III (Recreational road). AADT were 30,000 for urban, 16,000 for rural, and 5,000 for recreational road. Group III was typical recreational road showing higher average daily traffic volume during Sunday and vacational periods. Group I showed AM peak and PM peak, while group II and group III did not show AM peak and PM peak.

On the Change of Extreme Weather Event using Extreme Indices (극한지수를 이용한 극한 기상사상의 변화 분석)

  • Kim, Bo Kyung;Kim, Byung Sik;Kim, Hung Soo
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.28 no.1B
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    • pp.41-53
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    • 2008
  • Unprecedented weather phenomena are occurring because of climate change: extreme heavy rains, heat waves, and severe rain storms after the rainy season. Recently, the frequency of these abnormal phenomena has increased. However, regular pattern or cycles cannot be found. Analysis of annual data or annual average data, which has been established a research method of climate change, should be applied to find frequency and tendencies of extreme climate events. In this paper, extreme indicators of precipitation and temperature marked by objectivity and consistency were established to analyze data collected by 66 observatories throughout Korea operated by the Meteorological Administration. To assess the statistical significance of the data, linear regression and Kendall-Tau method were applied for statistical diagnosis. The indicators were analyzed to find tendencies. The analysis revealed that an increase of precipitation along with a decrease of the number of rainy days. A seasonal trend was also found: precipitation rate and the heavy rainfall threshold increased to a greater extent in the summer(June-August) than in the winter (September-November). In the meanwhile, a tendency of temperature increase was more prominent in the winter (December-February) than in the summer (June-August). In general, this phenomenon was more widespread in inland areas than in coastal areas. Furthermore, the number of winter frost days diminished throughout Korea. As was mentioned in the literature, the progression of climate change has influenced the increase of temperature in the winter.

A Development of Optimum Operation Models for Express-Rail Systems (급행열차 도입을 통한 최적운행방안 수립에 관한 연구 - 수도권 광역 도시철도를 중심으로 -)

  • Park, Jeong-Soo;Lee, Hoon-Hee;Won, Jai-Mu
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.26 no.4D
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    • pp.679-686
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    • 2006
  • Recently, the city railway in the Seoul Metropolitan Area (SMA) has offered a low quality of service as a passage time, because it was operated slowly. So, the people who live in modern society are not satisfied about passage time, therefore, this study tried to make that the subway in the SMA becomes a more functional and effective wide-area-transportation-network through an express train introduction's method which examined cases from abroad and current system. and then presented how express train could be applied to current system. In a case study, We used the An-San Line and Su-In Line as a examples and developed a schedule which can minimize the delaying time of subway by using Branch & Bound Algorithm. The train operational plan was loaded to consider a railroad siding, Obtained site, and the dispatch interval(three to ten minutes) for the express and local lines and finally, We presented an alternative operational plan which made by those factors.

Influence of Socially-Prescribed Perfectionism on Social anxiety and Depression in Academic High School Students: Mediation Effects of Self-focused Attention and Self-Criticism (인문계 고등학생의 사회부과 완벽주의가 우울과 사회불안에 미치는 영향: 자기초점적 주의와 자기비난의 매개효과)

  • Kim, Seul-Ki;Lee, Dong-gwi
    • Korean Journal of School Psychology
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    • v.15 no.2
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    • pp.243-264
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    • 2018
  • The study examined the influence of socially-prescribed perfectionism (SPP) on depression and social anxiety, and further investigated the mediating effects of self-focused attention and self-criticism. The questionnaires designed to measure multidimensional perfectionism, social anxiety, depression, self-focused attention, self-criticism scale for adolescents were administered twice at an interval of three weeks to 273 students (83 men, 190 women) enrolled at high schools in Gyeonggi-do Province. The findings for the present study were as follows. First, SPP, depression, social anxiety, self-focused attention, and self-criticism showed all positive correlations. Second, the mediation effect from the SPP to depression via self-focused attention was statistically significant, whereas the indirect effect from the SPP to depression via self-criticism was not. Third, the pattern in depression was the same in social anxiety. The results provide indirect support for the social anxiety cognitive model (Clark & Wells) with regards to social anxiety particularly in Korean high school students. Finally, the implications and limitations of this study and suggestions for future research were discussed.

Design and fAbrication of Triple Band WLAN Antenna Applicable to Wi-Fi 6E Band with DGS (DGS를 갖는 Wi-Fi 6E 대역을 위한 삼중대역 WLAN 안테나 설계 및 제작)

  • Sang-Wook Park;Gi-Young Byun;Joong-Han Yoon
    • The Journal of the Korea institute of electronic communication sciences
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    • v.19 no.2
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    • pp.345-354
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    • 2024
  • In this paper, we propose a triple band WLAN antenna for Wi-Fi 6E band with DGS. The proposed antenna has the characteristics required frequency band and bandwidth by considering the interconnection of two strip lines and three areas on the ground place. The total substrate size is 31 mm (W) × 50 mm (L), thickness (h) 1.6 mm, and the dielectric constant is 4.4, which is made of 22 mm (W6 + W4 + W5) × 43mm (L1 + L2 + L3 + L5) antenna size on the FR-4 substrate. From the fabrication and measurement results, bandwidths of 340 MHz (1.465 to 1.805 GHz) for 900 MHz band, 480 MHz (2.155 to 2.635 GHz) for 2.4 GHz band and 1950 MHz (4.975 to 6.925 GHz) for 5.0/6.0 GHz band were obtained on the basis of -10 dB. Also, gain and radiation pattern characteristics are measured and shown in the frequency triple band as required.

How to Identify Customer Needs Based on Big Data and Netnography Analysis (빅데이터와 네트노그라피 분석을 통합한 온라인 커뮤니티 고객 욕구 도출 방안: 천기저귀 온라인 커뮤니티 사례를 중심으로)

  • Soonhwa Park;Sanghyeok Park;Seunghee Oh
    • Information Systems Review
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    • v.21 no.4
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    • pp.175-195
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    • 2019
  • This study conducted both big data and netnography analysis to analyze consumer needs and behaviors of online consumer community. Big data analysis is easy to identify correlations, but causality is difficult to identify. To overcome this limitation, we used netnography analysis together. The netnography methodology is excellent for context grasping. However, there is a limit in that it is time and costly to analyze a large amount of data accumulated for a long time. Therefore, in this study, we searched for patterns of overall data through big data analysis and discovered outliers that require netnography analysis, and then performed netnography analysis only before and after outliers. As a result of analysis, the cause of the phenomenon shown through big data analysis could be explained through netnography analysis. In addition, it was able to identify the internal structural changes of the community, which are not easily revealed by big data analysis. Therefore, this study was able to effectively explain much of online consumer behavior that was difficult to understand as well as contextual semantics from the unstructured data missed by big data. The big data-netnography integrated model proposed in this study can be used as a good tool to discover new consumer needs in the online environment.