• Atmosphere
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• v.26 no.4
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• pp.565-576
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• 2016

The yellow dust events in Korea are often associated with extratropical cyclones (ETCs) that travel across the source regions of yellow dusts. Although such synoptic patterns are well documented, climatic features of ETCs themselves during the yellow dust events are not well understood. The present study reports climatic features of spring-time ETCs, which accompany the yellow dust events in Korea, by tracking individual ETCs with an automated tracking algorithm. By analyzing Lagrangian tracks of ETCs from 1979 to 2014, it is found that, during yellow dust events, ETCs are located around Vladivostok, Russia. They are typically originated from the leeside of Altai-Sayan mountains about three days before the onset of the yellow dust events, and travel either eastward or southeastward in time. While their tracks are not unusual, they grow faster over the source regions of the yellow dusts, possibly lifting desert dusts above the planetary boundary layer, and further develop slowly as they travel eastward.

• Current Research on Agriculture and Life Sciences
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• v.17
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• pp.31-38
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• 1999

Trend of some hydrologic features such as precipitation, runoff and reservoir storage rates in the five great river systems of Han, Nakdong, Keum, Yeongsan and Seomjin river watershed areas were surveyed and analysed. The sample period of Sept. 1994 to Aug. 1998 (four years) was chracterized by unusual climatic features such as El Nino, La Nina and areal terrible storms. And also average values of rainfall and runoff of the priod of 1961 to 1990 (30 years) were surveyed and analysed compared with the sample preiod events for the same river systems. In case of the monthly mean rainfall of the sample period (Sept. 1994 to Aug. 1998 : 48 months) in the five great river systems, 20 months, 19 months, 20 months, 21 months and 18 months in the Han, Nakdong, Keum, Yeongsan and Seomjin river system respectively were higher than monthly average rainfall records of the 30 year records. For the monthly runoff in the same river systems, 7 months, 9 months, 7 months, 11 months and 11 month in the Han, Nakdong, Keum, Yeongsan and Seomjin river systems respectively were higher than the monthly average runoff of the period of 30 years. For the storage rates, most of the dams in the Han river systems were highly stored through the year continuously and Paldang dam was specially higher than the other dams in the same river system. And most of the dams in the other river systems were stored irregularly but getting much better than early time during the 48 months. And special climatic features were not found during the sample period of 48 months, Sept. 1994 to Aug. 1998.

• Journal of The Korean Astronomical Society
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• v.29 no.spc1
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• pp.411-412
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• 1996

We present the update information on the International Radio Astronomy Observatory Suffa project and describe the original design of new 70-m radiotelescope RT-70 for millimeter astronomy as well. Some oreographic, seeing and climatic features of Suffa are also given.

• International Journal of Aeronautical and Space Sciences
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• v.10 no.1
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• pp.91-97
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• 2009

It is undertaken systematization of results of satellite and ground observation parameters characterizing a current condition and climatic variability of two selected geographical areas. One of them covers territory of Azerbaijan and another covers a wide area of Caspian See region. Average values and mean square deviations of following values are investigated: outgoing long wave radiation during a day and night (in nebulosity and cloudless). absorbed within a day of the stream of a sunlight of the system in "a terrestrial surface-atmosphere". degree of a covering by clouds of the selected areas during a day and at night, ground temperature values of air. pressure and speed of a wind. Monthly average values of corresponding parameters create a basis of suggested investigations. It has been presented features of a time course of investigated parameters for each month and year in the whole due to the continuously observations since 1982-2000. The scientific problem consists that there are no existed models which authentically would be cover the main aspects of a realities specified changes: they are identified by economic activities. growth of the population and other features of development of a human society or internal fluctuations of biogeophysical/climatic system. Possibilities of predictability of biosphere and climate changes depend on available timely supervision. adequacy of construction of appropriate models. understanding of mechanisms of direct and feedback influences in such complicated systems.

• International Journal of Industrial Entomology and Biomaterials
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• v.29 no.1
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• pp.93-119
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• 2014

Tropical tasar silkworm, Antheraea mylitta (Lepidoptera: Saturniidae) is a polyphagous silk producing forest silkworm of commercial importance in India. Forest dependent people rear its larvae on different forestry host plants twice or thrice in a year for small household income. Larvae of A. mylitta feeds on many forest tree species, but always show a great degree of selectivity as a function of its behavioural responses to physical structure and chemical features of the host plants. Cocoon crop of A. mylitta is influenced by heterogeneity of tasar food plants and climatic conditions of the habitat. The role of host plants, temperature, humidity, rainfall, photoperiod and climatic variables on the growth and development of insects have clearly been demonstrated. This article entails an in-depth analysis on ecological and nutritional aspects of A. mylitta, which may provide selective information to researcher and forest managers, who are particularly associated with livelihood improvement of the poor people in forested area through location specific forest insect industry.

• Journal of the Korea Society of Computer and Information
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• v.28 no.7
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• pp.57-65
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• 2023

Various studies to enhance the accuracy of rice production forecasting are focused on improving the accuracy of the models. In contrast, there is a relative lack of research regarding the data itself, which the prediction models are applied to. When applying the same dependent variable and prediction model to two different sets of rice production data composed of distinct features, discrepancies in results can occur. It is challenging to determine which dataset yields superior results under such circumstances. To address this issue, by identifying potential influential features within the data before applying the prediction model and centering the modeling around these, it is possible to achieve stable prediction results regardless of the composition of the data. In this study, we propose a method to adjust the composition of the data's features in order to select optimal base variables, aiding in achieving stable and consistent predictions for rice production. This method makes use of the Korea Meteorological Administration's ASOS data. The findings of this study are expected to make a substantial contribution towards enhancing the utility of performance evaluations in future research endeavors.

• Journal of the Korean Institute of Rural Architecture
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• v.2 no.2
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• pp.1-10
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• 2000

The traditional farm houses in Yongdong area of Kangwon province have a different spatial structure from those of the other areas because of the characteristics of the climatic, geographic and sociocultural circumstances between the Taebaek mountains and the East Sea. So the purpose of this study is aimed at grasping how the spatial features of traditional farm houses in Yongdong area have been different in each regional circle. The plans of traditional farm houses of this region which are four types - ㅡ typed house without floor, ㅡ typed house with floor, ㄱ typed house without floor, ㄱ typed house with floor - show very similar but different space arrangements.

• Korean Journal of Construction Engineering and Management
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• v.13 no.3
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• pp.67-77
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• 2012

O Having a highly reliable plan for the process and estimating an accurate construction period during the early stages of a construction project can prevent falsifying the plan and reduce the occurrence of construction delays. Moreover, it allows a succession of swift and accurate decisions to happen. The difficulty in obtaining an accurate estimate of the construction period is especially prominent in high-rise building projects because the works involved are very complicated and costly. As such, it is important that research is done to find out the impacts a reliable plan and good estimate of the construction period can bring with regards to the monthly work efficiency and success of a high-rise building project. However, due to the difference in climatic conditions at high altitude and surface level, the current way of calculating work efficiency in a typical project is inaccurate for a high-rise building project. With that, this paper aims to compute the work efficiency with height, taking into consideration the change in climatic elements at different working heights. A comparison of the results according to the climatic features of each city can also be done in this paper. According to the results calculated in work altitudes, the work efficiency in Busan falls the most. On the other hands, the work efficiency in Seoul falls the least. The reason these results are shown is the influence of wind speed at high altitude. The estimation of work efficiency at high altitude would be used for estimating construction period, feasibility studies, and selecting a city of high-rise building projects.

• Journal of the Korean Geographical Society
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• v.49 no.1
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• pp.1-17
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• 2014

This study estimates geomorphological processes of fluvial terraces by uplifts and bedrock features, by the analyses of topography, distribution, formation age and incision rate of fluvial terraces using Gwang-cheon River in Uljin, Namdae-cheon River in Pyeonghae and Osip-cheon River in Yeongdeok located in the southern Taebaek Mountain Range. The tectonic and climatic terraces I in the upper reaches of Gwang-cheon River with an altitude from riverbed of 9~12m indicate the formation age of MIS 2 with a incision rate of 0.40m/ka. However, the tectonic and climatic terraces I in the upper reaches of Osip-cheon River with an altitude from riverbed of 7~10m show the formation age of MIS 3 with an incision rate of 0.10m/ka. These results suggest that the uplift rate in the Gwang-cheon River basin is likely to be higher than that in the Osip-cheon River basin. Unlike the lower reaches of Osip-cheon River, the thalassostatic terraces are not found in the lower reaches of Gwang-cheon River, because the basin has low maintainable ability of landforms in river valley due to high uplift rate and bedrock properties resistant to weathering and erosion. On the other hand, the lowest tectonic and climatic terraces in the study areas indicate different formative ages and the terraces during the cooling stage in interglacial as well as during interstadial are also found. Therefore, this study suggests that chronological method for fluvial terrace by the previous developmental model of climatic terrace should be reconsidered.

• International Journal of Computer Science & Network Security
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• v.22 no.6
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• pp.131-138
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• 2022

Novel Coronavirus (COVID-19) is viewed as one of the main general wellbeing theaters on the worldwide level all over the planet. Because of the abrupt idea of the flare-up and the irresistible force of the infection, it causes individuals tension, melancholy, and other pressure responses. The avoidance and control of the novel Covid pneumonia have moved into an imperative stage. It is fundamental to early foresee and figure of infection episode during this troublesome opportunity to control of its grimness and mortality. The entire world is investing unimaginable amounts of energy to fight against the spread of this lethal infection. In this paper, we utilized machine learning and deep learning techniques for analyzing what is going on utilizing countries shared information and for detecting the climate factors that effect on spreading Covid-19, such as humidity, sunny hours, temperature and wind speed for understanding its regular dramatic way of behaving alongside the forecast of future reachability of the COVID-2019 around the world. We utilized data collected and produced by Kaggle and the Johns Hopkins Center for Systems Science. The dataset has 25 attributes and 9566 objects. Our Experiment consists of two phases. In phase one, we preprocessed dataset for DL model and features were decreased to four features humidity, sunny hours, temperature and wind speed by utilized the Pearson Correlation Coefficient technique (correlation attributes feature selection). In phase two, we utilized the traditional famous six machine learning techniques for numerical datasets, and Dense Net deep learning model to predict and detect the climatic factor that aide to disease outbreak. We validated the model by using confusion matrix (CM) and measured the performance by four different metrics: accuracy, f-measure, recall, and precision.