• Journal of the Korea institute for structural maintenance and inspection
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• v.19 no.3
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• pp.73-82
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• 2015

In evaluating lateral behavior on the seismic and wind load, the purpose of sensitivity analysis is to find critical variables and to identify characteristic response with variability of variables. The sensitivity analysis is very important in structural diagnosis, repair and reinforcement field. This study investigates the sensitivity by linear static analysis applying the TDA method in changing angles of diagrid braces on the same height structures. In case of mid rise model, under the seismic load, the brace member is determined as a major variable at $58^{\circ}$ but a high rise model, under the wind load, has the brace member as a major variable at $67.4^{\circ}$. In addition, location of critical sensitivity on the mid rise model is distributed over middle section, while it is distributed lower section on the high rise model.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.12
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• pp.5309-5314
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• 2016

Background: Breast cancer is the most common type of cancer amongst women throughout the world. Currently, there are various follow-up strategies implemented in Iran, which are usually dependent on clinic policies and agreement among the resident oncologists. Purpose: A cost-effectiveness analysis was performed to assess the cost-effectiveness of intensive follow-up versus standard models for early breast cancer patients in Iran. Materials and methods: This cross sectional study was performed with 382 patients each in the intensive and standard groups. Costs were identified and measured from a payer perspective, including direct medical outlay. To assess the effectiveness of the two follow-up models we used a decision tree along with indicators of detection of recurrence and metastasis, calculating expected costs and effectiveness for both cases; in addition, incremental cost-effectiveness ratios were determined. Results: The results of decision tree showed expected case detection rates of 0.137 and 0.018 and expected costs of US$24,494.62 and US$6,859.27, respectively, for the intensive and standard follow-up models. Tornado diagrams revealed the highest sensitivity to cost increases using the intensive follow-up model with an ICER=US$148,196.2. Conclusion: Overall, the results showed that the intensive follow-up method is not cost-effective when compared to the standard model.

• Journal of The Geomorphological Association of Korea
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• v.19 no.4
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• pp.73-81
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• 2012

This study analyzed and examined the entries of natural disasters recorded in Samguk-sagi in relation to the natural thoughts. In the ancient Korean view of nature thought the Unified Shilla dynasty surveyed their view on nature in terms of terrestrial upheavals. In the first place, I came to know that the important natural disasters such as droughts, floods, hails, locusts, earthquakes, thunderstroke, storms uprooting trees, tornado etc. recorded in Samguk-sagi have something in common with the entries of natural disasters in the ancient Chinese histories. Accordingly, they interpreted natural disasters in terms of good omens and heavenly punishments. The king refrained from luxurious food and drink, released prisoners or reduced their sentence as a sign of his benevolence. They thought that natural disasters were caused by the heavenly instruction due to lack of virtue on the part of the king. I think that these were acts of ritual on the part of the king as a ruler to fulfill his responsibility for a benevolent administration.

• International Journal of Computer Science & Network Security
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• v.23 no.9
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• pp.1-7
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• 2023

Demand prediction is an essential component of any business or supply chain. Large retailers need to keep track of tens of millions of items flows each day to ensure smooth operations and strong margins. The demand prediction is in the epicenter of this planning tornado. For business processes in retail companies that deal with a variety of products with short shelf life and foodstuffs, forecast accuracy is of the utmost importance due to the shifting demand pattern, which is impacted by an environment of dynamic and fast response. All sectors strive to produce the ideal quantity of goods at the ideal time, but for retailers, this issue is especially crucial as they also need to effectively manage perishable inventories. In light of this, this research aims to show how Machine Learning approaches can help with demand forecasting in retail and future sales predictions. This will be done in two steps. One by using historic data and another by using open data of weather conditions, fuel, Consumer Price Index (CPI), holidays, any specific events in that area etc. Several machine learning algorithms were applied and compared using the r-squared and mean absolute percentage error (MAPE) assessment metrics. The suggested method improves the effectiveness and quality of feature selection while using a small number of well-chosen features to increase demand prediction accuracy. The model is tested with a one-year weekly dataset after being trained with a two-year weekly dataset. The results show that the suggested expanded feature selection approach provides a very good MAPE range, a very respectable and encouraging value for anticipating retail demand in retail systems.

• International Journal of Computer Science & Network Security
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• v.23 no.8
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• pp.210-216
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• 2023

Demand prediction is an essential component of any business or supply chain. Large retailers need to keep track of tens of millions of items flows each day to ensure smooth operations and strong margins. The demand prediction is in the epicenter of this planning tornado. For business processes in retail companies that deal with a variety of products with short shelf life and foodstuffs, forecast accuracy is of the utmost importance due to the shifting demand pattern, which is impacted by an environment of dynamic and fast response. All sectors strive to produce the ideal quantity of goods at the ideal time, but for retailers, this issue is especially crucial as they also need to effectively manage perishable inventories. In light of this, this research aims to show how Machine Learning approaches can help with demand forecasting in retail and future sales predictions. This will be done in two steps. One by using historic data and another by using open data of weather conditions, fuel, Consumer Price Index (CPI), holidays, any specific events in that area etc. Several machine learning algorithms were applied and compared using the r-squared and mean absolute percentage error (MAPE) assessment metrics. The suggested method improves the effectiveness and quality of feature selection while using a small number of well-chosen features to increase demand prediction accuracy. The model is tested with a one-year weekly dataset after being trained with a two-year weekly dataset. The results show that the suggested expanded feature selection approach provides a very good MAPE range, a very respectable and encouraging value for anticipating retail demand in retail systems.

• Journal of The Geomorphological Association of Korea
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• v.18 no.4
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• pp.153-162
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• 2011

This study analyzed and examined the entries of natural disasters recorded in Samguk-sagi in relation to the mythological thoughts. In the ancient Korean view of nature thought the Three Kingdoms surveyed their view on nature in terms of natural calamities and terrestrial upheavals. In the first place, I came to know that the important natural disasters such as droughts, floods, hails, locusts, earthquakes, landslides, storms uprooting trees, tornado recorded in Samguk-sagi have something in common with the entries of natural disasters in the ancient Chinese histories. Accordingly, they interpreted natural disasters in terms of good omens and heavenly punishments. The king refrained from luxurious food and drink, released prisoners or reduced their sentence as a sign of his benevolence. they thought that natural disasters were caused by the heavenly instruction due to lack of virtue on the part of the king. I think that these were acts of ritual on the part of the king as a ruler to fulfill his responsibility for a benevolent administration.

• Land and Housing Review
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• v.15 no.1
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• pp.135-146
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• 2024

This study predicts the means sharing ratio of the urban air transportation (UAM) when the VertiHub of the UAM in the southern western part is built at Songjeong Station in Gwanju. Based on Monte Carlo simulation of the utility function and means selection logit model for each means of transportation, our findings indicate an average mode share of 0.95%, with a variability range from 0.07% to 4.7%. Moreover, 95% of the simulation outcomes fall below a 2.02% mode share. Sensitivity analysis, conducted via Tornado Plot, highlights that the mode share is principally influenced by factors such as the unit fare, cost parameter, basic fare, and the time required for takeoff and landing. Notably, a negative correlation exists for unit fare, basic fare, and takeoff and landing time, suggesting the necessity of setting an appropriate level of fair to enhance UAM utilization.

• Journal of the Korean Geographical Society
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• v.47 no.1
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• pp.60-78
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• 2012

The main objective of this study is to conduct subnational population projections of Korea based on a Myriad Things" (萬物門), which is part of Seongho's representative work entitled $Miscellaneous$ $Explanations$ $of$ $Seongho$ (星湖僿說), has been in this paper in order to understand Seongho's "thinking on geography". To do so, contents related to geography were selected and these were discussed and interpreted in terms of the classification system of today's geographical knowledge. Following is the result of this research. First, information on astronomical geography and natural geography such as uplift, tornado, structure of soil, and the $yut$ board as well as humangeographical topics such as wild $ginseng$, cigarettes, hot pepper, traditional fruits and nuts (chestnuts, jujubes, and persimmons), Goryeo paper (Korean paper), mulberry trees, cotton plants, natural dye, policy about horses, magnetic compass needles, and farming implements for rice transplantation are mentioned in "Myriad Things" in relation to geography. Second, the depth of information described varies from topic to topic, but the topics on tornado and magnetic compass needles, horses, wild ginseng, traditional fruits and nuts, and $yut$ board are described in depth and in detail. Third, authenticity of the contents on these topics are "true" insofar as bibliographical information and citations are provided for support. Fourth, these topics reflect the interests and circumstances that are related to the "economic improvement of common people's livelihood" in those days, such as agriculture, crops, and transportation of goods. Fifth, the bibliography and citations explaining all instances reveal that China (Qing) is a great civilization of the advanced world and that the scholarship of Joseon relied on and accepted it. Sixth, except for horse raising and management, farming implements for rice transplantation, sericulture, and natural dying of cloth, most of the topics are useful even today. In short, theres is a profound aspect to the content that makes it possible to estimate the "geographical thinking". In general, the focus of the content of this book directly linked to the practical agricultural economy of the common people.

• Journal of the Korean earth science society
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• v.37 no.4
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• pp.187-199
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• 2016

The purpose of this study is to investigate the formation mechanism of landspout by using the Cloud Resolving Storm Simulator (CReSS). The landspout occurred over Ilsan, Goyang City, the Republic of Korea on June 10, 2014 with the damage of a private property. In synoptic environment, a cold dry air on the upper layers of the atmosphere, and there was an advection with warm and humid air in the lower atmosphere. Temperature differences between upper and lower layers resulted in thermal instability. The storm began to arise at 1920 KST and reached the mature stage in ten minutes. The cloud top height was estimated at 9 km and the hook echo was appeared at the rear of a storm in simulation result. Model results showed that the downburst was generated in the developed storm over the Ilsan area. This downburst caused the horizontal flow when it diverged near the surface. The horizontal flow was switched to updraft at the rear of storm, and the rear-flank downdrafts (RFDs) current occurred from simulation result. The RFDs took down the vertical flow to the surface. After then, the vertical vorticity could be generated on the surface in simulation result. Subsequently, the vertical vorticity was stretched to form a landspout. The cyclonic vorticity of echo hook from simulation was greater than $3{\times}10^{-2}s^{-1}$(height of 360 m) and landspout diameter was estimated at 1 km.

• Journal of Korea Multimedia Society
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• v.16 no.11
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• pp.1239-1249
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• 2013

According to development of weather radar, researches about observation, analysis or forecast of weather phenomena such as tornado, flash-flood etc. were encouraged by reducing frequency interferences, transmission noises, attenuations of radar signal. In contrast, there is a growing interest in the visualization and expression methods for weather radar data but weather radar manufacturers or the organs of government for weather are just busy interpreting expressed weather images projected on GIS. We propose an effective high definition weather radar information visualization method able to apply various GIS platforms to observe and take actions against rapid local weather changes effectively. In this paper, first we change information acquired from weather radar to raster or vector type high definition data structures using specific algorithms. And then, we quadrate our processed raster/vector type weather data with various GIS platforms accurately to make observers can recognize and check weather situations over exact geographical positions and elevations intuitively. Experimental results verify that our method make observers can recognize and analyze weather changes, tornados, local downpours or flash floods accurately by analyzing high definition weather radar data combined with GIS platform including detailed target locations and elevations.