• 제목/요약/키워드: Image Signature

검색결과 143건 처리시간 0.018초

향토음식 특화 거리의 관광상품화와 활성화 방안 연구 - 담양 죽순 푸드빌리지를 중심으로 - (A Study on the Damyang Area Restaurants in Bamboo food village)

  • 김수인;박연진;김소영;장혜진
    • 한국식생활문화학회지
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    • 제28권4호
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    • pp.348-355
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    • 2013
  • This study intends to provide preliminary data for improving dining experience in the restaurants of Bamboo food village and help draw up guidelines for the improvement of these dining venues by surveying customer perception and satisfaction in 15-restaurants of the food village. The restaurants were surveyed mainly for satisfaction of the menu, especially, on the signature dishes of Damyang, "ddeokgalbi" (grilled short rib balls) and "daetongbab"-the grilled short rib balls and bamboo rice. The two dishes were more liked by people in the the 20- to 29-year age group with a score of 3.92 and 4.11, respectively. Although the 30-49 age group showed the highest satisfaction score on the fixed price menu, there was no statistically significant difference. The age group of 20-29 also showed the highest satisfaction on plating and table setting with a score of 4.09 and 4.04, respectively, and there was significant difference among age groups in this regard (p<0.05). All the age groups surveyed answered "time-honored taste" should be captured when working on menus, which suggests it should be the first choice for the restaurants in the food village when they develop their menus. When it comes to the restaurant environment, satisfaction on sanitary conditions was significantly different among the groups with a score of 4.21 given by 30-49 age group and 3.88 by the 50 and over group (p<0.05). In the category of service satisfaction, the two aforementioned age groups again showed significant difference in catering to customer needs with a score of 3.99 and 3.63, respectively (p<0.05), whereas welcoming customers and serving food was scored without statistical difference by age. Being asked what needs to be done to strengthen competitive advantage of the restaurants, all the age groups answered "taste" would matter the most while the 20 to 29 and 30 to 49 age groups picked "hygiene" and the 50 and over selected "table setting and ambience" next, which was statistically different with a p value of <0.05. Regarding the competitive advantage of the Korean restaurants in Damyang Bamboo food village, the first two younger groups (20 to 29 and 30 to 49) chose "table setting and ambience" and the eldest (50 and over) age group answered "location wise advantage," indicating significant difference by age. More than 80 percent of the people surveyed were willing to revisit the venues, which suggests improving restaurant environment in Bamboo food village and offering customers a better experience are very likely to build a image of culinary tourism for Damyang.

AIRSAR 다중편파 자료를 이용한 굴 양식장 산란현상 연구 (Study of Scattering Mechanism in Oyster Farm by using AIRSAR Polarimetric Data)

  • 이승국;홍상훈;원중선
    • 대한원격탐사학회지
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    • 제21권4호
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    • pp.303-316
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    • 2005
  • 연안의 굴 양식장은 레이더 영상에서 강한 산란체로 나타나며, 긴밀도 높은 레이더 간섭쌍을 제공한다. 굴 양식장에서 일어나는 강한 신호의 간섭위상과 반사강도를 이용하여 조위를 관측하는 방법이 개발된 바 있다. 레이더를 이용한 조위 측정방법은 이중 반사가 일어나는 굴 양식장에서 적용되어야 한다. 이 논문에서는 굴 양식장 구조물에서 일어나는 산란의 특징을 분석한다. 실내실험은 다중편파 Ku-밴드를 이용하여 전파암실에서 축소된 산란체를 제작하여 수행하였다. 산란체의 수직막대로부터 돌아오는 신호는 수평 막대로부터 돌아오는 신호보다 10.5 dB정도 강하게 나타났다. 단일 반사 성분은 이중 반사 성분과 유사한 정도로 큰 값을 나타냈으나 안테나의 관측방향에 매우 민감하였다. 또한 수직막대의 높이가 증가함에 따라 이중 반사 성분이 비례하여 증가하였고, 이중 반사 성분이 조위관측에 더 유용하게 이용될 수 있음을 확인하였다. L-밴드 AIRSAR 영상을 단일 반사와 이중 반사, 체적산란으로 분류하였다. 그 결과 굴 양식장에서는 항상 이중 반사만이 일어나고 있는 것은 아닌 것으로 나타났다. 해수면 위로 노출된 굴 양식장에서는 이중 반사가 우세하게 일어나지만, 조위가 낮아 바닥의 조간대 면이 공기 중에 노출되면 단일 반사 성분이 주요 산란 특징으로 나타났다. 전자의 경우 단일 반사와 이중 반사의 비율은 0.46인 반면, 바닥면이 노출된 경우에는 이 비율이 5.62로 급격히 증가하는 것을 알 수 있다. DInSAR 기술을 이용한 조위 관측을 위해서는 이중 반사가 우세하게 일어나는 지역을 선정하여야한다.

Automatic Detection of Type II Solar Radio Burst by Using 1-D Convolution Neutral Network

  • Kyung-Suk Cho;Junyoung Kim;Rok-Soon Kim;Eunsu Park;Yuki Kubo;Kazumasa Iwai
    • 천문학회지
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    • 제56권2호
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    • pp.213-224
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    • 2023
  • Type II solar radio bursts show frequency drifts from high to low over time. They have been known as a signature of coronal shock associated with Coronal Mass Ejections (CMEs) and/or flares, which cause an abrupt change in the space environment near the Earth (space weather). Therefore, early detection of type II bursts is important for forecasting of space weather. In this study, we develop a deep-learning (DL) model for the automatic detection of type II bursts. For this purpose, we adopted a 1-D Convolution Neutral Network (CNN) as it is well-suited for processing spatiotemporal information within the applied data set. We utilized a total of 286 radio burst spectrum images obtained by Hiraiso Radio Spectrograph (HiRAS) from 1991 and 2012, along with 231 spectrum images without the bursts from 2009 to 2015, to recognizes type II bursts. The burst types were labeled manually according to their spectra features in an answer table. Subsequently, we applied the 1-D CNN technique to the spectrum images using two filter windows with different size along time axis. To develop the DL model, we randomly selected 412 spectrum images (80%) for training and validation. The train history shows that both train and validation losses drop rapidly, while train and validation accuracies increased within approximately 100 epoches. For evaluation of the model's performance, we used 105 test images (20%) and employed a contingence table. It is found that false alarm ratio (FAR) and critical success index (CSI) were 0.14 and 0.83, respectively. Furthermore, we confirmed above result by adopting five-fold cross-validation method, in which we re-sampled five groups randomly. The estimated mean FAR and CSI of the five groups were 0.05 and 0.87, respectively. For experimental purposes, we applied our proposed model to 85 HiRAS type II radio bursts listed in the NGDC catalogue from 2009 to 2016 and 184 quiet (no bursts) spectrum images before and after the type II bursts. As a result, our model successfully detected 79 events (93%) of type II events. This results demonstrates, for the first time, that the 1-D CNN algorithm is useful for detecting type II bursts.