• Journal of Climate Change Research
• /
• v.9 no.4
• /
• pp.461-470
• /
• 2018

The frequency of extreme weather events was analyzed using meteorological data (air temperature, precipitation, and duration of sunshine) collected from 61 stations over a 36-year span (1981-2016). The 10-day meteorological data were used as a basic unit for this analysis. On average, the frequency of occurrence of abnormal weather was 9.88 per year and has increased significantly during this 36-year period. According to the type of abnormal weather, the frequencies of occurrence of abnormally high air temperature and short duration of sunshine have increased by 0.50 and 0.41 per 10 years, respectively; however, that for abnormally low air temperature has decreased by 0.31 per 10 years and the trend was statistically significant. The highest frequency of abnormal weather appeared in 2007, with a frequency of 14.31. Abnormal weather was the most frequent at Yeongdeok station with an average frequency of 11.78 per year over this 36-year span.

• Journal of Distribution Science
• /
• v.16 no.10
• /
• pp.55-64
• /
• 2018

Purpose - The most important goal of corporate management is the maximization of firm value in the market. Executives of companies are making effort to increase corporate value and initiate various management strategies, which is to develop the products or service with value. Through these efforts, consumer satisfaction grows and loyalty increases, which leads to the positive change of customer satisfaction index. The purpose of this research is to find out the abnormal return after the KCSI(Korean Customer Satisfaction Index) is announced. Research design, data, and methodology - This research data is collected from 11 years' stock price in KOSPI market and KCSI. The authors analyze the abnormal return triggered by the announcement of KCSI through the event study. Results - First, newly enlisted companies in the KCSI show statistically significant short-term abnormal rate of return. Second, the value of the customer satisfaction index is not the level of customer satisfaction but the direction of the change in the CSI. Conclusion - Customer satisfaction has the important intangible asset in the marketing area. However, firms' investment for CS is not an easy decision, because of the difficulty to measure the effect on corporate market value. This research investigates the change of the market value after the announcement of KCSI. Based on the results, firms have to keep trying to increase KCSI relative to the previous year. And the small company has to struggle for being newly listed in the KCSI.

• Journal of the Korean Geotechnical Society
• /
• v.26 no.10
• /
• pp.69-79
• /
• 2010

To detect abnormal events in slopes, Principal Component Analysis (PCA) is applied to the slope that was collapsed during monitoring. Principal component analysis is a kind of statical methods and is called non-parametric modeling. In this analysis, principal component score indicates an abnormal behavior of slope. In an abnormal event, principal component score is relatively higher or lower compared to a normal situation so that there is a big score change in the case of abnormal. The results confirm that the abnormal events and collapses of slope were detected by using principal component analysis. It could be possible to predict quantitatively the slope behavior and abnormal events using principal component analysis.

• Journal of Environmental Science International
• /
• v.21 no.10
• /
• pp.1287-1295
• /
• 2012

Abnormal change in Gyeongpo beach shoreline in June of 2012 was illustrated using DGPS (Differential Global Positioning System, resolution < 0.6m) observation and drift experiment. Abrupt change in the shoreline was occurred in the latter part of June, 2012, this change was compared with that in June from 2009 to 2011. In the northern part of the beach, sand accumulated and it made beach extension and movement of the shoreline towards sea compared with that in June from 2009 to 2011. While on the other, in the southern part, the beach was eroded and it formed a steep slope around the southernmost of the beach. The shoreline in the southern part of the beach was shifted more towards land than that in the past. Change in the position of shoreline was higher in the northernmost and southernmost of the beach compared with those in the other parts. Drift in the southern part of the beach moved faster along the beach than that in the northern part of it.

• Journal of Integrative Natural Science
• /
• v.17 no.1
• /
• pp.1-12
• /
• 2024

Many abnormal climate events are occurring around the world. The cause of abnormal climate is related to temperature. Factors that affect temperature include excessive emissions of carbon and greenhouse gases from a global perspective, and air circulation from a local perspective. Due to the air circulation, many abnormal climate phenomena such as abnormally high temperature and abnormally low temperature are occurring in certain areas, which can cause very serious human damage. Therefore, the problem of abnormal temperature should not be approached only as a case of climate change, but should be studied as a new category of climate crisis. In this study, we proposed a model for the classification of abnormal temperature using random forests based on various meteorological data such as longitudinal observations, yellow dust, ultraviolet radiation from 2018 to 2022 for each region in Korea. Here, the meteorological data had an imbalance problem, so the imbalance problem was solved by oversampling. As a result, we found that the variables affecting abnormal temperature are different in different regions. In particular, the central and southern regions are influenced by high pressure (Mainland China, Siberian high pressure, and North Pacific high pressure) due to their regional characteristics, so pressure-related variables had a significant impact on the classification of abnormal temperature. This suggests that a regional approach can be taken to predict abnormal temperatures from the surrounding meteorological environment. In addition, in the event of an abnormal temperature, it seems that it is possible to take preventive measures in advance according to regional characteristics.

• Environmental Engineering Research
• /
• v.16 no.3
• /
• pp.175-183
• /
• 2011

The climate of the $21^{st}$ century is likely to be significantly different from that of the 20th century because of human-induced climate change. An extreme weather event is defined as a climate phenomenon that has not been observed for the past 30 years and that may have occurred by climate change and climate variability. The abnormal climate change can induce natural disasters such as floods, droughts, typhoons, heavy snow, etc. How will the frequency and intensity of extreme weather events be affected by the global warming change in the $21^{st}$ century? This could be a quite interesting matter of concern to the hydrologists who will forecast the extreme weather events for preventing future natural disasters. In this study, we establish the extreme indices and analyze the trend of extreme weather events using extreme indices estimated from the observed data of 66 stations controlled by the Korea Meteorological Administration (KMA) in Korea. These analyses showed that spatially coherent and statistically significant changes in the extreme events of temperature and rainfall have occurred. Under the global climate change, Korea, unlike in the past, is now being affected by extreme weather events such as heavy rain and abnormal temperatures in addition to changes in climate phenomena.

• International conference on construction engineering and project management
• /
• 2015.10a
• /
• pp.51-53
• /
• 2015

As abnormal climate phenomena occur more frequently due to climate change, damage which results from meteorological disaster increases accordingly and its scale and variety are becoming wider. This paper draws out planning and design elements and application techniques to build cities more adaptive to climate change from urban development cases in US and Europe. An urban model is suggested, that enables built environment to be more resilient to risks caused by climate change is applicable to urban development projects in practice.

• Korean Journal of Remote Sensing
• /
• v.36 no.5_1
• /
• pp.667-677
• /
• 2020

Crop water stress can be detected based on soil moisture content, crop physiological characteristics and remote-sensing technology. The detection of crop water stress is an important issue for the accurate assessment of yield decline. The crop water stress index (CWSI) has been introduced based on the difference between leaf and air temperature. In this paper, drone-based thermal infrared image was used to map of crop water stress in water control plot (WCP) and water deficit plot (WDP) over spring chinese cabbage fields. The spatial distribution map of CWSI was in strong agreement with the abnormal growth response factors (plant height, plant diameter, and measured value by chlorophyll meter). From these results, CWSI can be used as a good method for evaluation of crop abnormal growth monitoring.

• The Journal of Asian Finance, Economics and Business
• /
• v.8 no.5
• /
• pp.523-531
• /
• 2021

Vietnam's Oil and gas industry make a significant contribution to the Gross Domestic Product of Vietnam. The ongoing COVID-19 pandemic has hit every industry hard, but perhaps the one industry which has taken the biggest hit is the global oil and gas industry. The purpose of this article is to examine how the COVID-19 pandemic affects the share price of the Vietnam Oil and Gas industry. The event study method applied to Oil and Gas industry index data around three event days includes: (i) The date Vietnam recognized the first patient to be COVID-19 positive was January 23, 2020; (ii) The second outbreak of COVID-19 infection in the community began on March 6, 2020; (iii) The date (30/3/2020) when Vietnam announced the COVID-19 epidemic in the whole territory. This study found that the share price of the Vietnam Oil and Gas industry responded positively after the event (iii) which is manifested by the cumulative abnormal return of CAR (0; 3] = 3.8% and statistically significant at 5 %. In the study, event (ii) has the most negative and strong impact on Oil and Gas stock prices. Events (i) favor negative effects, events (iii) favor positive effects, but abnormal return change sign quickly from positive to negative after the event date and statistically significant shows the change on investors' psychology.

• Journal of Sensor Science and Technology
• /
• v.29 no.4
• /
• pp.249-254
• /
• 2020

It is difficult to control children who exhibit negative behavior in dental clinics. Various methods are used for preventing pediatric dental patients from being afraid and for eliminating the factors that cause psychological anxiety. However, when it is difficult to apply this routine behavioral control technique, sedation therapy is used to provide quality treatment. When the sleep anesthesia treatment is performed at the dentist's clinic, it is challenging to identify emergencies using the current breath detection method. When a dentist treats a patient that is under the influence of an anesthetic, the patient is unconscious and cannot immediately respond, even if the airway is blocked, which can cause unstable breathing or even death in severe cases. During emergencies, respiratory instability is not easily detected with first aid using conventional methods owing to time lag or noise from medical devices. Therefore, abnormal breathing needs to be evaluated in real-time using an intuitive method. In this paper, we propose a method for identifying abnormal breathing in real-time using an intuitive method. Respiration signals were measured using a 3M Littman electronic stethoscope when the patient's posture was supine. The characteristics of the signals were analyzed by applying the signal processing theory to distinguish abnormal breathing from normal breathing. By applying a short-time Fourier transform to the respiratory signals, the frequency range for each patient was found to be different, and the frequency of abnormal breathing was distributed across a broader range than that of normal breathing. From the wavelet transform, time-frequency information could be identified simultaneously, and the change in the amplitude with the time could also be determined. When the difference between the amplitude of normal breathing and abnormal breathing in the time domain was very large, abnormal breathing could be identified.