• Journal of Korean Society of Forest Science
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• v.80 no.3
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• pp.303-310
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• 1991

Seasonal patterns of decomposition and nutrient release from the needle litter were examined using litter-bags in coastal Pinus thunbergii forests in nothern Kyushu, Japan. Dry matter losses from decomposing needle litter were smillar in all standsover a experimental period. Mass loss in dry weight is lost rapidly during the first year, and thereafter the rate of loss slows. Litter lost approximately 40% of initial mass in 1 yr. The predicted decay constant, k values ranged from 0.5 to 0.6 Decomposition half-times($t_{0.50}$) ranged from 1.1 to 1.4 year. In the decomposing needle litter, the concentrations of N and P generally increased with time while the concentration of K decreased. A decrease in absolute amount was noted for K during decomposition while in an increase was found for N. The order of mobility of elements was K>P>N. Mineralization phase of N had not appeared during the experiment.

• Journal of environmental and Sanitary engineering
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• v.13 no.3
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• pp.79-84
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• 1998

The study result on the domestic waste occurrence and admistration condition of Iksan City as follows ; 1. The year of 1995 has observed a radically decreasing ratio of per capita waste generation compared to the previous year by 26.2%, owing to the publication of the new amendment of volume based charge as well as to the rural population included through the merger of Iksan City and Iksan Country ; the daily quantity of domestic waste for Iksan residents in 1997 was calculated to be $0.66kg/capita{\cdot}day$. 2. Waste generation in nonresidential areas were $8.04kg/capita{\cdot}day$ in average ; the quantity per capita in market places was observed to generate the largest, $36.76kg/capita{\cdot}day$, while that of services was the smallest $0.25kg/capita{\cdot}day$. 3. The average generation per capita of household waste was $0.23kg/capita{\cdot}day$ in the area which has no volume based charge system. This area showed no difference from those of other areas ; the apparent density of the waste recorded the lowest $0.llkg/{\ell}$ for District Offices, while the highest among the classified fields was $0.40kg/{\ell}$ of the Fire Station. 4. Iksan City showed great contribution by decreasing the absolute quantity of waste for landfill by waste classfication, according to the days of the week and reutilizing recyclable waste since August, 1997. 5. Location of a landfill site for disposal of nonrecyclable waste will cause a serious problem to the community and it will be highly recommendable to have governmental support and professtional consultation as well as open discussions, such as hearings, for the settlement of the problem.

• Journal of the Korean Wood Science and Technology
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• v.35 no.6
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• pp.57-64
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• 2007

Tree-ring dating can be used to date scientifically prehistoric timbers, historical buildings or woodcrafts. It gives a calendar year to each tree ring and produces the felling dates of logs or wood panels. In this study, we applied tree-ring dating to two medicine cabinets, known to be made in Kyônggi Province. Two cabinets were dated A.D. 1884 and 1874 to the last rings, respectively. Even with closed ages, two cabinets show different styles and structures. Tree-ring patterns indicated that the origins of woods for both cabinets would be near Sorak mountains and Kangneung area in Kangwon province.

• Atmosphere
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• v.28 no.3
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• pp.291-303
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• 2018

In this study, a new consensus technique for predicting tropical cyclone (TC) intensity in the western North Pacific was developed. The most important feature of the present consensus model is to select and combine the guidance numerical models with the best performance in the previous years based on various evaluation criteria and averaging methods. Specifically, the performance of the guidance models was evaluated using both the mean absolute error and the correlation coefficient for each forecast lead time, and the number of the numerical models used for the consensus model was not fixed. In averaging multiple models, both simple and weighted methods are used. These approaches are important because that the performance of the available guidance models differs according to forecast lead time and is changing every year. In particular, this study develops both a multi-consensus model (M-CON), which constructs the best consensus models with the lowest error for each forecast lead time, and a single best consensus model (S-CON) having the lowest 72-hour cumulative mean error, through on training process. The evaluation results of the selected consensus models for the training and forecast periods reveal that the M-CON and S-CON outperform the individual best-performance guidance models. In particular, the M-CON showed the best overall performance, having advantages in the early stages of prediction. This study finally suggests that forecaster needs to use the latest evaluation results of the guidance models every year rather than rely on the well-known accuracy of models for a long time to reduce prediction error.

• Journal of Gastric Cancer
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• v.23 no.1
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• pp.146-158
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• 2023

Endoscopic resection (ER) is widely performed for early gastric cancer (EGC) with a negligible risk of lymph node metastasis (LNM) in Eastern Asian countries. In particular, endoscopic submucosal dissection (ESD) leads to a high en bloc resection rate, enabling accurate pathological evaluation. As undifferentiated EGC (UD-EGC) is known to result in a higher incidence of LNM and infiltrative growth than differentiated EGC (D-EGC), the indications for ER are limited compared with those for D-EGC. Previously, clinical staging as intramucosal UD-EGC ≤2 cm, without ulceration, was presented as 'weakly recommended' or 'expanded indications' for ER in the guidelines of the United States, Europe, Korea, and Japan. Based on promising long-term outcomes from a prospective multicenter study by the Japan Clinical Oncology Group (JCOG) 1009/1010, the status of this indication has expanded and is now considered 'absolute indications' in the latest Japanese guidelines published in 2021. In this study, which comprised 275 patients with UD-EGC (cT1a, ≤2 cm, without ulceration) treated with ESD, the 5-year overall survival (OS) was 99.3% (95% confidence interval, 97.1%-99.8%), which was higher than the threshold 5-year OS (89.9%). Currently, the levels of evidence grades and recommendations for ER of UD-EGC differ among Japan, Korea, and Western countries. Therefore, a further discussion is warranted to generalize the indications for ER of UD-EGC in countries besides Japan.

• 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 Preventive Medicine and Public Health
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• v.57 no.2
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• pp.120-127
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• 2024

Objectives: The coronavirus disease 2019 (COVID-19) pandemic led to increased mortality rates. To assess this impact, this ecological study aimed to estimate the excess death counts in southern Iran. Methods: The study obtained weekly death counts by linking the National Death Registry and Medical Care Monitoring Center repositories. The P-score was initially estimated using a simple method that involved calculating the difference between the observed and expected death counts. The interrupted time series analysis was then used to calculate the mean relative risk (RR) of death during the first year of the pandemic. Results: Our study found that there were 5571 excess deaths from all causes (P-score=33.29%) during the first year of the COVID-19 pandemic, with 48.03% of these deaths directly related to COVID-19. The pandemic was found to increase the risk of death from all causes (RR, 1.26; 95% confidence interval [CI], 1.19 to 1.33), as well as in specific age groups such as those aged 35-49 (RR, 1.21; 95% CI, 1.12 to 1.32), 50-64 (RR, 1.38; 95% CI, 1.28 to 1.49), and ≥65 (RR, 1.29; 95% CI, 1.12 to 1.32) years old. Furthermore, there was an increased risk of death from cardiovascular diseases (RR, 1.17; 95% CI, 1.11 to 1.22). Conclusions: There was a 26% increase in the death count in southern Iran during the COVID-19 pandemic. More than half of these excess deaths were not directly related to COVID-19, but rather other causes, with cardiovascular diseases being a major contributor.

• Korean Journal of Agricultural Science
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• v.50 no.3
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• pp.373-389
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• 2023

The downstream submergence damages caused during the flood season in 2020, around the Yongdam-dam and five other sites, were analyzed using related dam management data. Hourly- and daily-data were collected from public national websites and to conduct various analyses, such as autocorrelation, partial-correlation, stationary test, trend test, Granger causality, Rescaled analysis, and principal statistical analysis, to find the cause of the catastrophic damages in 2020. The damage surrounding the Yongdam-dam in 2020 was confirmed to be caused by mis-management of the flood season water level. A similar pattern was found downstream of the Namgang- and Hapcheon-dams, however the damage caused via discharges from these dams in same year is uncertain. Conversely, a different pattern from that of the Yongdam-dam was seen in the areas downstream of Sumjingang- and Daecheongdams, in which the management of the flood season water level appeared appropriate and hence, the damages is assumed to have occurred via the increase in the absolute discharge amount from the dams and flood control capacity leakage of the downstream river. Because of the non-stationarity of the management data, we adapted the wavelet transform analysis to observe the behaviors of the dam management data in detail. Based on the results, an increasing trend in the discharge amount was observed from the dams after the year 2000, which may serve as a warning about similar trends in the future. Therefore, additional and continuous research on downstream safety against dam discharges is necessary.

• Korean Journal of Soil Science and Fertilizer
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• v.45 no.6
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• pp.897-899
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• 2012

In this study, spatial analyses of chemical properties were studied to find inter-relation among these properties from 5 year old general paddy field after arable land rearrangement and remodeled paddy field near 4 river project. In addition, comparison of spatial variations between two paddy fields was performed to characterize paddy fields by different formation and provide interpretation of these variations and parameters (Semivariogram and Kriging) from spatial analyses. Total of 400 ($20{\times}20$) soil samples were taken at 5 m interval from 1 ha of 5 year old general paddy field and analyzed. Total number of 54 ($6{\times}9$) soil samples were taken from remodeled paddy fields at 10m interval for the analyses. The results of pH, available Phosphate and organic matter among the analyzed results were used for interpretation. The pH values were relatively high from Gumi region. The values of available Phosphate and organic matter showed greater variant coefficients and this represented that there were greater heterogeneity in available phosphate and organic matter distributions across one paddy field. The values of skewness and kurtosis as absolute values, showed almost normal distributions. The paddy field in Ansung had available Phosphate (72.8) ${\fallingdotseq}$ pH (73.8) and greater values of organic matter (159.3), while upland in Gumi had the range value of organic (6.5) < available Phosphate (33.5) < pH (46.6). Based on these results, younger soils (0 year old) require more sampling to characterize the whole field than 5 year old soils.