• 한국지역사회생활과학회지
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• 제19권4호
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• pp.697-706
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• 2008

Generally, tourism environments are classified as macro or micro environments. Hotel revenues are influenced directly and indirectly by macro and micro environments. This study aims to examine the determinants of the change in macro-environments on hotel revenue. The explanatory variables in this research were wage, exchange rates (ER), consumer price index (CPI) and seasonality. The results of this study were as follows; The CPI and ER significantly affected the hotel food and beverage sales. The seasonality (summer and autumn) and wage significantly affected the hotel room sales. Wage and seasonality (summer and autumn) also significantly affected the total sale on the hotels.

• 생물정신의학
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• 제17권3호
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• pp.153-160
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• 2010

Objectives : Recurrence of mood episodes associated with a specific season has been described in various mood disorders. Seasonal change in mood and behavior as a lifetime trait is also observed in healthy individuals. This study aimed at comparing the lifetime trait of seasonal variations of mood and behavior between bipolar disorder patients and controls as well as investigating associated factors of seasonality. Methods : Subjects were ninety-four clinically stable patients with bipolar disorder and 188 age- and sex-matched healthy controls. Seasonality of mood and behavior was assessed retrospectively on lifetime basis using Seasonal Pattern Assessment Questionnaire(SPAQ). Results : The patient group showed a higher median global seasonality score(GSS) of SPAQ and a higher rate of seasonal affective disorder(SAD) compared to the control group(p < 0.0001). For subjects showing prominent seasonality, the seasonal symptom profile and seasonal pattern was similar in both patient and control groups. In addition to the diagnosis, female gender was shown to be a predictor of seasonality in the multiple linear regression analysis(p = 0.045). Conclusion : This study suggests that lifetime trait of seasonality may be related to the susceptibility of bipolar disorder.

• Ocean and Polar Research
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• 제23권4호
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• pp.433-440
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• 2001

Marine organisms in Antarctica live in an environment which exhibits variability in physical processes over a wide range of temporal scales, from seconds to millennia. This time scale tends to be correlated with the spatial scale over which a given process operates, though this relationship is influenced by biology. The way organisms respond to variability in the physical environment depends on the time-scale of that variability in relation to life-span. Short-term variations are perceived largely as noise and probably have little direct impact on ecology. Of much greater importance to organisms in Antarctica are seasonal and decadal variations. Although seasonality has long been recognised as a key feature of polar environments, the realization that decadal scale variability is important is relatively recent. Long-term change has always been a feature of polar environments and may be a key factor in the evolution of the communities we see today.

• 환경생물
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• 제37권3호
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• pp.317-334
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• 2019

The present study was conducted to investigate the differences in managed farming practices, including low-intensive farming, duck farming, and golden apple snail farming, in a rice ecosystem by comparing terrestrial arthropod communities. A total of 75 species from 70 genera belonging to 43 families in 11 orders were identified from 9,622 collected arthropods. Araneae, Hemiptera, and Coleoptera were the richest taxa. Collembola was the most abundant, followed by Diptera, Hemiptera, and Araneae. Bray-Curtis similarity among the farming practices was very high (76.7%). The biodiversity of each farming practice showed a similar seasonality pattern. The richest species group was the predators, followed by the herbivores. The species richness and diversity of ecologically functional groups among the farming practices were not statistically significant, except for the abundance of predators in golden apple snail farming. The biodiversity seasonality of ecological functional groups in each farming practice showed similar patterns. The biomass of Araneae, Hemiptera, Coleoptera, and Diptera was greater than the other taxa, in general. The biomass of each ecological functional group showed little difference and the biomass fluctuation patterns in each farming practice were almost the same. Collectively, the community structures and biodiversity of terrestrial arthropods among the farming practices in the present study were not different. The present study may contribute to sustain rich biodiversity in irrigated rice fields and to advanced studies of food webs or energy flow structures in rice fields for ecological and sustainable agriculture.

• 대한교통학회지
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• 제29권5호
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• pp.139-155
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• 2011

본 연구에서는 계절성(seasonality)을 감안한 적분된 자기회귀 이동평균 모형(ARIMA model)을 이용하여 우리나라 지역 간 철도의 동태적 변화과정을 추정하고 장래 통행수요를 예측하고자 하였다. 기존 국내연구에서 고려하지 않은 계절성 요인을 감안한 ARIMA 모형(Seasonal ARIMA model)과 월별 지역 간 철도 통행실적자료를 이용하여 교통수요 동태적 변화모형을 구축하였다. 구체적으로 2000년 1월부터 2008년 12월까지의 월별 수송인원 및 수송인-km 기준 지역 간 통행실적 자료를 이용하여 Box et al. (1994)에서 제시한 Seasonal ARIMA 모형을 적용하였으며 이에 따라 장래 지역 간 철도 통행수요를 예측하였다. 장래 통행수요 예측 결과에 따르면 수송인원 기준으로 2015년 및 2020년에는 2008년의 각각 약 1.36배와 1.71배 수준으로 산정되었다. 또한 수송인-km 기준으로 2015년과 2020년에는 2008년의 각각 약 1.25배와 1.78배 정도로 예측되었다.

• 융합경영연구
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• 제9권2호
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• pp.1-10
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• 2021

Purpose: In this work, we examine several time series models to predict internet and mobile transaction amount in South Korea, whereas Jeong (2020) has obtained the optimal forecasts for online shopping transaction amount by using time series models. Additionally, optimal forecasts based on the model considered can be calculated and applied to the Corona 19 situation. Research design, data, and methodology: The data are extracted from the online shopping trend survey of the National Statistical Office, and homogeneous and comparable in size based on 46 realizations sampled from January 2007 to October 2020. To achieve the goal of this work, both multiplicative ARIMA model and Holt-Winters Multiplicative seasonality method are taken into account. In addition, goodness-of-fit measures are used as crucial tools of the appropriate construction of forecasting model. Results: All of the optimal forecasts for the next 12 months for two online shopping transactions maintain a pattern in which the slope increases linearly and steadily with a fixed seasonal change that has been subjected to seasonal fluctuations. Conclusions: It can be confirmed that the mobile shopping transactions is much larger than the internet shopping transactions for the increase in trend and seasonality in the future.

• ALGAE
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• 제20권4호
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• pp.325-331
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• 2005

Populations of Campylaephora borealis (Nakamura) Seo, Cho et Boo and C. crassa (Okamura) Nakamura show a year-around occurrence of all life-history stages. Such a concurrency of life-history stages produces problems in recognizing species in the field. Here, we invesitgated the morphological variation and life-history stages of both species using a statistical character analysis. Life-history stage was correlated with the seawater temperature in C. borealis, whereas it was dependant on biomass in C. crassa. Thalli had dichotomous branches with adaxial branchlets. The statistics showed that the seasonal change in morphology of C. borealis was significantly different from that of C. crassa in seven qualitative characters and five quantitative characters (p < 0.001), although six quantitative features including tetrasporangial size were similar in both species. The morphological difference between the two species may be due to the annual variation of branchlet number and the variance of branch subangle.

• Journal of Preventive Medicine and Public Health
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• 제43권5호
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• pp.436-444
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• 2010

Objectives: Infectious diseases are known to be affected by climate change. We investigated if the infectious diseases were related to meteorological factors in Korea. Methods: Scrub typhus, hemorrhagic fever with renal syndrome (HFRS), leptospirosis, malaria and Vibrio vulnificus sepsis among the National Notifiable Infectious Diseases were selected as the climate change-related infectious diseases. Temperature, relative humidity and precipitation were used as meteorological factors. The study period was from 2001 through 2008. We examined the seasonality of the diseases and those correlations with meteorological factors. We also analyzed the correlations between the incidences of the diseases during the outbreak periods and monthly meteorological factors in the hyper-endemic regions. Results: All of the investigated diseases showed strong seasonality; malaria and V. vulnificus sepsis were prevalent in summer and scrub typhus, HFRS and leptospirosis were prevalent in the autumn. There were significant correlations between the monthly numbers of cases and all the meteorological factors for malaria and V. vulnificus sepsis, but there were no correlation for the other diseases. However, the incidence of scrub typhus in hyper-endemic region during the outbreak period was positively correlated with temperature and humidity during the summer. The incidences of HFRS and leptospirosis had positive correlations with precipitation in November and temperature and humidity in February, respectively. V. vulnificus sepsis showed positive correlations with precipitation in April/May/July. Conclusions: In Korea, the incidences of the infectious diseases were correlated with meteorological factors, and this implies that the incidences could be influenced by climate change.

• 자원ㆍ환경경제연구
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• 제29권4호
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• pp.419-442
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• 2020

우리나라 도시가스 수요는 난방수요에 기인한 뚜렷한 동고하저의 계절성을 보이며, 기온에 따른 민감도는 시간에 따라 변화하는 것으로 나타났다. 본 연구에서는 시간에 따라 변화하는 계절성을 효과적으로 모형하기 위해서 시간변동 기온반응함수 개념을 도입하여 이를 해당 일의 기온분포로 적분하여 기온에 따른 수요변동을 추정한다. 또한 기상청에서 발표하는 향후 10일의 도시별 기온 예측치를 체계적으로 반영하여 도시가스 수요를 예측하는 방법론을 개발하였다. 평년기온분포를 사용한 것에 비해서 함수적 방법론을 이용하여 기상청의 기온 예측치를 기온분포예측치로 변환하여 예측했을 때 기온분포의 예측 오차율은 2배, 도시가스 수요의 예측 오차는 5배 가까이 감소하는 것을 확인하였다.

• 지적과 국토정보
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• 제47권2호
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• pp.19-37
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• 2017

VIIRS-DNB 데이터는 기존의 DMSP-OLS 데이터에 비해 야간에 발생하는 빛의 밝기를 측정하는데 더 우수한 성능을 보여준다. 하지만 지금까지 우리나라에서 VIIRS-DNB 데이터를 이용해 야간 빛의 분포 변화를 분석한 연구는 상당히 드물다. 이 연구에서는 우리나라의 수도권을 대상으로 2013~2016년간의 야간 빛의 분포 및 변화 패턴을 파악하고, 공간회귀모델을 통해 그 요인을 분석하였다. 이를 위해 두 시점 간의 변화를 살펴봄은 물론 계절간 변화 양상 또한 함께 분석하였다. 주요한 결과는 다음과 같다. 첫째, 2013년과 2016년 두 시점 모두 야간 빛은 서울과, 인천, 그리고 서울과 인접한 경기도의 도시에 집중되어 인구밀도 및 주거지관련요인, 경제토지이용관련요인 등과의 연관성을 나타내었다. 둘째, 2013년과 2016년을 비교해보면 야간 빛의 강도는 특히 서울에서 약화되는 경향을 보이고 있는데, 이는 인구밀도의 변화 및 산업용 건물의 비중과 관련된 것으로 나타났다. 셋째, 서울, 그리고 인천과 경기도의 주변 지역들은 야간 빛의 계절 변동성이 높게 나타났는데, 겨울(12월, 1월, 2월) 및 가을(10월, 11월)에 빛의 강도가 가장 강하게 나타났다. 넷째, 야간 빛의 계절간 변동은 적설면적 변화와 유의미하게 양적 상관관계 나타났고, 알베도의 변화와 유의미하게 음적 상관관계 나타났다.