This study was undertaken to find out national level changes in area, production and yield of two major staple crops wheat and potato in Bangladesh. The time series of secondary data was collected from yearbook of agricultural statistics under Bangladesh Bureau of Statistics (BBS) and used for the statistical analysis during the thirty-year period of 1989/90-2018/19. Moreover, selected data were divided into two groups and regarded as segment (1989/90-2003/04, 2005/06-2018/19) to examine the significant level in each crop. The results of different statistical techniques showed that wheat cultivated area and production were satisfactory level but yield was not too much standard in context of country demand. In the case of potato, yield as well as cultivated area and production were crossed the significant level and fulfilled the demand of population. In recent few years, the ratio of potato production rapidly increased, compared with the cultivation area. Based on segment (period) analysis, at the first half wheat production was always below, compared with the area but second half nine years saw slightly improved. On the other hand, in both segment potato growth rate in area, production and yield were increased throughout the study period. The highest instability was also shown in area, production and yield of potato during whole as well as segmented period. There was always a positive relationship between country’s demand and supply. Both wheat and potato are considered as staple crops and based on the productive capability over cultivated area, potato showed the higher productivity for the country of Bangladesh. In consequences, potato consuming demand also rapidly increased all over the country, compared with past respectively.

The present study aims to investigate the impact of tourism growth on human development in Indian economy. For this purpose, the study uses annual data from 1980 to 2018 and utilizes two proxies for tourism growth – tourism receipt and tourist arrivals – and uses human development index calculated by UNDP. The study uses control variables such as government expenditure and trade openness. The study employs auto regressive distributed lag (ARDL) approach to investigate the cointegrating relationship among the variables in the model. Further, the study also explores the causal nexus between tourism sector and human development by using the Toda-Yamamoto Granger non-causality test. The result of ARDL bounds test reveals the existence of cointegrating relationship between human development indicators, government expenditure, trade openness, and tourism sector growth. The cointegating coefficient confirms a positive and significant relationship between tourism sector growth and human development in India. The causality result suggests that economic growth and tourism have a positive impact while trade openness has a negative impact on human development in India. The major findings of this study suggest that tourism plays an important role in the socio-economic development of Indian economy in recent years and the country must develop this sector to achieve sustainable development.

Extreme low temperature has various effects on society. It has negative impacts on health, industry, agriculture, and transportation during winter season. Therefore, extreme low temperature is recognized as main factor that causing traffic accidents. This study analyzed the relationship between low temperature and traffic accidents from 2012 to 2018. This study also compared the differences in vulnerability to low temperature between urban and rural areas. Generalized Additive Model (GAM) and Poisson regression model are used to estimate the thresholds and the level of traffic accidents. The results show that the thresholds tend to be decreased gradually, but the level of traffic accidents are more likely to increase in both urban and rural areas Comparatively, rural areas are more vulnerable to traffic accident caused by drop in temperature than urban areas.

This research paper examines the causal relationship between India’s economic growth and sectoral contribution to Gross Domestic Product (GDP) and vice versa, in the short-run and long-run, over a 10 years time period. Johansen’s method of cointegration is used to study the cointegration between the sectoral contributions to Indian GDP vis-à-vis India’s economic growth. Further, the route of interconnection between economic growth and sectoral contribution is tested by using Vector Auto Regression (VAR) model. Special attention was given for investigating impulse responses of economic growth depending on the innovations in sectoral contribution using time-series data from 1960 to 2015. This paper highlighted a dynamic co-relationship among industrial sector contribution and agricultural sector contribution and economic development. In the long run, one percent change in industrial sector contribution causes an increase of 3.42 percent in the economic growth and an increase of 1.12 percent in the primary sector contribution, while in the short run industrial and service sector contributions showed significant impact on economic development and agriculture sector. The changing composition of sector contribution is going to be an important activity for the policymakers to monitor and control where the technology and integration of sectors play a significant role in economic development.

The purpose of this study was to develop a period analysis algorithm for detecting new variable stars in the time-series data observed by charge coupled device (CCD). We used the data from a variable star monitoring program of the CBNUO. The R filter data of some magnetic cataclysmic variables observed for more than 20 days were chosen to achieve good statistical results. World Coordinate System (WCS) Tools was used to correct the rotation of the observed images and assign the same IDs to the stars included in the analyzed areas. The developed algorithm was applied to the data of DO Dra, TT Ari, RXSJ1803, and MU Cam. In these fields, we found 13 variable stars, five of which were new variable stars not previously reported. Our period analysis algorithm were tested in the case of observation data mixed with various fields of view because the observations were carried with 2K CCD as well as 4K CCD at the CBNUO. Our results show that variable stars can be detected using our algorithm even with observational data for which the field of view has changed. Our algorithm is useful to detect new variable stars and analyze them based on existing time-series data. The developed algorithm can play an important role as a recycling technique for used data

As part of the Four Major Rivers Restoration Project, multifunctional weirs have been constructed in the rivers and operated for river-level management. As the weirs play a role in draining water from tributaries, the aim of this study was to determine the influence of the weirs on the water level of the Nam River, which is one of the Nakdong River’s tributaries. Self-organizing maps (SOMs) and a locally weighted scatterplot smoothing (LOWESS) technique were applied to analyze the patterns and trends of water level and quality of the Nakdong River, considering the operation of the Changnyeong-Haman weir, which is located where the Nam River flows into the Nakdong River. The software program HEC-RAS was used to find the boundary points where the water is well drained. Per the study results at the monitoring points ranging between the junction of the two rivers and 17.5 km upstream toward the Nam River, the multifunctional weir influenced the water level at the Geoyrong and Daesan observation stations on the Nam River and the water quality based on automatic monitoring at the Chilseo station on the Nakdong River was affected strongly by the Nakdong River and partly by the Nam River.

At riverbank filtration sites, groundwater levels of alluvial aquifers near rivers are sensitive to variation in river discharge and pumping quantities. In this study, the groundwater level fluctuation, pumping quantity, and streamflow rate at the site of a riverbank filtration plant, which produces drinking water, in the lower Nakdong River basin, South Korea were interrelated. The relationship between drawdown ratio and river discharge was very strong with a correlation coefficient of 0.96, showing a greater drawdown ratio in the wet season than in the dry season. Autocorrelation and cross-correlation were carried out to characterize groundwater level fluctuation. Autoregressive model analysis of groundwater water level fluctuation led to efficient estimation and prediction of pumping for riverbank filtration in relation to river discharge rates, using simple inputs of river discharge and pumping data, without the need for numerical models that require data regarding several aquifer properties and hydrologic parameters.

지속가능한 빗물정원 설계를 위해서는 내부 구성요소 (식물, 토양, 여재층 등)의 최적화된 상호작용에 의하여 나타나는데 특히 국내 기후 환경에서는 함수량의 변동이 심하며 적용 가능한 식물의 종이 선정이 중요하다. 지속적 빗물정원으로서의 효율은 빗물의 유입패턴에 따른 적용가능한 식물과 여재의 종류에 의해 결정되고, 식생의 생장 차이에 따른 식재공간 유지 정도에 의해 지속성이 좌우된다. 본 연구는 근부 생장이 활발한 습생식물의 정원용 소재로서의 평가를 위해 식물별 침입수준(invasion level)을 분석하여 최적의 식재조합을 설계하는데 기 초자료로 활용하고자 한다. 대상식물은 속새 외 19종의 습생식물을 관상기준에 따라 직립형, 분지형, 포복형으로 나누고 5월부터 10월까 지 월 2회 각 식물의 피복율을 측정하였다. 20종 중 단위공간 피복율이 100%를 넘어 침입성이 높은 수준의 식물은 부처꽃, 박하, 아스타, 낙지다리, 갯까치수영, 삿갓사초, 고랭이로 나타났고 식재 초기부터 급속한 성장을 보인 식물은 갯까치수영, 박하, 낙지다리, 삿갓사초, 부 처꽃 순으로 식재설계시 고려해야할 수종으로 나타났다.

The port throughput situation has changed since the 2008 financial crisis in the US. Therefore, we studied the situation, accurately estimating port traffic of Korean port after the 2008 financial crisis. We ensured the proper port facilities in response to changes in port traffic. In the results of regression analysis, Korean GDP and the real effective exchange rate of Korean Won were found to increase the container throughput in Korean and Busan port, as well as trade volume with China. Also, the real effective exchange rate of Korean Won was found to increase the port transshipment cargo volume. Based on the ARIMA models, we forecasted port throughput and port transshipment cargo volume for the next six years (72 months), from 2015 to 2020. As a result, port throughput of Korean and Busan ports was forecasted by increasing annual the average from about 3.5% to 3.9%, and transshipment cargo volume was forecasted by increasing the annual average about 4.5%.

There is a need to analyze unconfined groundwater behavior since the demand of groundwater use has been increasing. While unconfined groundwater temperature is tend to be affected by air temperature, it is hard to find an empirical study in South Korea. In this research, we try to determine the relationship between daily average air temperature and daily average groundwater temperature by time-sequential analysis of groundwater monitoring wells in Galshin basin in Yesan-Gun, Chungcheongnam-Do. In addition, models to estimate groundwater temperature from air temperature were developed. In this research 101-day moving average method with measured air temperature is used to estimate groundwater temperature. To verify the developed model, estimated values of average groundwater temperature with 101 moving average are compared to the measured data from September 10 2007 to September 9 2008. And, Nash-Stucliff Efficiency and Coefficient of Determination were 0.970 and 0.976, therefore it was concluded that the model allowing groundwater temperature estimation from air temperature is with reasonable applicability.

수문 시계열의 분석은 수문자료를 활용한 수자원의 효율적인 운영 및 관리에 필수적인 부분이며, 특히 장기적인 수문량 예측에 널리 활용되고 있다. 이러한 수문 시계열 분석은 전통적으로 하나의 자료계열을 하나의 요인으로 파악하여 자료를 분석하고 예측해왔지만 시계열 자료가 여러 가지 요인으로 혼합되 어 하나의 자료계열로 나타내질 수 있다는 가정 하에 각 요인들을 분해하여 분석하는 방법도 널리 연구되고 있다. 본 연구에서는 경험적 모드분해법을 이용하여 주어진 수문 시계열을 다중 성분으로 분해하고 분해된 각 요소를 시계열 모형으로 재구축한 후, 구축된 요소별 시계열 모형으로부터 예측된 값을 합하여 시계열을 예측하는 방법을 이용하였으며 이를 국내 댐 유입량에 적용한 후 그 결과를 나타내었다. 기존 시계열 모형과 경험적 모드분해법을 이용한 방법의 정확도를 비교한 결과, 기존의 시계열 모형을 이용하여 자료를 예측한 결과보다 경험적 모드분해법을 적용하여 자료를 분해한 후 시계열 자료를 예측한 결과가 주어진 시계열 자료를 더 잘 나타내는 것을 알 수 있었다.

In this study, among the reliability assessment method for measured data of dam instrumentation, time series analysis and behavior analysis were introduced and the reliability assessment cases for seepag weir, pore-pressure meter, concrete stress meter and joint meter were presented.

열적외선 위성영상은 저비용으로 안전하게 지표온도를 추정할 수 있으며, 따라서 열적외선 위성영상을 활용하는 것으로 화산활동의 전조현상 모니터링이 가능하다. 그러나, 지표온도를 추정하기 위해 필요한 요소인 지표의 복사율 결정과 대기효과 보정은 쉽지 않기 때문에, 높은 정밀도를 기대하기 어렵다는 단점이 존재해왔다. 이에 본 연구에서는 최근 개발된 LSTD(Land Surface Temperature Difference)기법을 활용하여, 높은 정밀도의 지표온도 추정방법을 제안하고자 한다. 이 방법은 임의의 기준점으로부터 상대적인 지표온도의 차이를 구하는 것으로 대기효과를 보정하며, 복사율이 잘 알려진 식생지역에 한정적으로 적용함으로써 0.5K 이하의 높은 정밀도의 지표온도 추정이 가능한 것으로 알려져있다. 이 방법은 1) 대기효과 보정, 2) 식생지역의 추출, 3) 기준점의 지표온도로부터 상대적인 지표온도차 계산 및 4) 온도감률로부터 지형효과 보정의 단계로 이루어진다. 제안된 방법의 실험을 위하여, 화산활동이 활발한 아프리카의 Nyiragongo화산과 최근 전조현상이 발생하고 있는 백두산을 연구지역으로 선정하였으며, 열적외선 밴드를 탑재한 Landsat TM/ETM+ 영상을 수집하였다. 제안된 방법은 식생지역에만 적용되는 것으로서 공간적인 한계가 있으나, 높은 정밀도로 지표온도의 추정이 가능하기 때문에 화산활동의 전조현상을 관측할 수 있을 것으로 기대된다.

Lime-bordeaux mixture has been used to prevent diseases in the field of ginseng. The purpose of this study is to investigate the efficacy of lime-bordeaux depending on the concentration and treatment time on major diseases of ginseng such as Alternaria blight and anthracnose, and to evaluate the root growth of ginseng. Lime-bordeaux caused damage on leaf when it was sprayed on ginseng between April and early May. No difference was found in root growth by spraying lime-bordeaux mixture between ratio 4-4 and 8-8 ratio in concentration. Plot of 6-6 raito and 8-8 ratio appeared to be similar efficacy compared to that of practical chemical control. However, the plot of 4-4 ratio showed lower than that of chemical control.

We present the Hilbert-Huang transform (HHT) analysis on the quasi-periodic modulation of SMC X-1. SMC X-1, consistingof a neutron star and a massive companion, exhibits superorbital modulation with a period varying between ~40 d and ~65 d.We applied the HHT on the light curve observed by the All-Sky Monitor onboard Rossi X-ray Timing Explorer (RXTE) to obtainthe instantaneous frequency of the superorbital modulation of SMC X-1. The resultant Hilbert spectrum is consistent with thedynamic power spectrum while it shows more detailed information in both the time and frequency domains. According to theinstantaneous frequency, we found a correlation between the superorbital period and the modulation amplitude. Combiningthe spectral observation made by the Proportional Counter Array onboard RXTE and the superorbital phase derived in theHHT, we performed a superorbital phase-resolved spectral analysis of SMC X-1. An analysis of the spectral parameters versusthe orbital phase for different superorbital states revealed that the diversity of nH has an orbital dependence. Furthermore,we obtained the variation in the eclipse profiles by folding the All Sky Monitor light curve with orbital period for differentsuperorbital states. A dip feature, similar to the pre-eclipse dip of Her X-1, can be observed only in the superorbital ascendingand descending states, while the width is anti-correlated with the X-ray flux.

Fluctuation patterns of groundwater level as a factor that reflects the characteristics of groundwater system can be categorized as the various types of aquifer with the time-series data. Time-series data on groundwater level obtained from 115 monitoring wells in Jeju Island were classified according to variation types, which were largely affected by rainfall(Dr), rainfall and pumping(Drp), and unknown cause(De). Analysis results indicate that 106 wells belong to Dr and Drp and the ratio of the wells with the wide range of fluctuation in the western and northern regions was higher than that in the eastern and southern regions. From the results that Drp is relatively higher than Dr in the western region which has the largest agricultural areas, groundwater level fluctuations may be affected significantly due to the intensive agricultural use. Non-parametric trend analysis results for 115 monitoring wells show that the increasing and decreasing trends as the ratio of groundwater levels were 14.8% and 22.6%, respectively, and groundwater levels revealed to be increased in the western, southern and northern regions excluding eastern region. Results of correlation analysis that cross-correlation coefficients and the time lags in the eastern and western regions are relatively high and short, respectively, indicate that the rainfall recharge effect in these regions is relatively larger due to the gentle slope of topography compared to that in the southern and northern regions.

본 논문은 1998년부터 2011년까지 강릉 지역의 지방 방사능 측정소에서 측정된 공간 감마선량률의 통계 적인 성질을 조사하였다. Autocorrelation Function Analysis(ACF), Rescaled Range Analysis(R/S Analysis), DetrendedFluctuation Analysis(DFA)의 방법들이 사용되었으며, 이 중 DFA는 non-stationary한 시계열의 장거리 상관성을 보여주는 좋은 방법으로 알려져 있다. 우리는 이 연구를 통해 다음의 사실을 알았다. 첫 번째, 공간 감마선량률은 두 가지다른 경향을 갖는 크로스 오버가 나타난다. 이것은 연중 공간 감마선량률은 강한 장기 기억 특성이 나타나는데 비해연간으로 넘어가면 상관성이 사라지는 것을 의미한다. 두 번째, 각 분석 방법들의 지수들이 있는데 이 지수들 사이의관계식이 맞음을 확인 하였다.

Time-series change in Gyeongpo beach shoreline was illustrated using DGPS(Differential Global Positioning System, resolution < 0.6m) observation from April, 2009 to April, 2010. The shoreline was subdivided into 12 areas, and westward and eastward movement of shoreline position at each area was calculated. In general, the shoreline moved toward sea during summer, and it moved toward land during winter. The southern and northern part of the shoreline had different pattern in time-series. The shoreline in the southern part moved toward sea during summer and moved toward land during winter, but time-series pattern of the shoreline in the northern part was more complicated than that in the southern part. Pattern of time-series change in the northern part was made up of three different types; the first is that the shoreline moves continuously toward land, and the second thing is that the shoreline's movement is the opposite to the southern part, and the third thing is that the shoreline maintains a state of equilibrium without any great fluctuation. The total length of the shoreline was the largest during winter and the smallest during summer. In general, time-series change in the shoreline had positive(+) relationship with sea surface pressure and wind speed.

예측의 정확성은 비용의 감소나 고객서비스의 제고를 위해 필수적으로 선행되어야 하기에 현재까지도 많은 연구자들에 의해 연구되고 있는 분야이다. 본 연구에서는 국내 항만의 컨테이너 물동량 예측에 있어 대표적인 비선형예측모형인 인공신경망모형과 ARIMA모형에 대한 비교연구를 수행하는데 목적을 두었고, 컨테이너 물동량 예측력 제고를 위해 ARIMA모형과 인공신경망(ANN)모형을 결합한 하이브리드모형을 사용해 다른 모형들과 예측성과를 비교하고자 한다. 특히 인공신경망모형의 네트워크 구조 설계에 부분에 있어 방대하며 복잡한 탐색공간에서도 전역해 찾기에 효과적인 기법으로 알려져 있는 유전알고리즘을 사용함과 동시에 인공신경망의 대표적인 모형으로 알려진 다층 퍼셉트론(MLP)뿐만 아니라 시간지연네트워크(TDNN)를 사용해 예측성과를 비교하였다. 그 결과 ANN모형과 하이브리드모형이 ARIMA모형보다 더 뛰어난 예측성과를 보이는 것으로 나왔다.

한정된 기간의 짧은 유출량 기록을 갖는 댐 유역에서의 수자원 시스템 거동예측은 수문학적 지속성여부에 대한 판단이 선행 되어야 하며 가용한 시계열자료에 대한 추계학적 분석을 통하여 실시하여야 한다. 본 연구에서는 계절형 ARIMA모형을 통하여 안동댐 유역의 강우량, 증발량 및 유출량 시계열자료로 월별 수문시스템 거동을 예측하였으며, 예측된 결과를 토대로 TANK모형과 ARIMA+TANK결합모형에 의한 장기유출모의를 실시하였다. 분석결과 관측자료의 특성을