산지재해는 1차적으로 산지사면에서 산사태가 발생되어 2차적으로 계류를 따라 토석류로 이동 및 확산되면서 산지 하부지역의 시설지와 주거지에 피해를 발생시킨다. 따라서 본 연구는 전라북도 지역의 토석류 발생지 79개소를 조사 대상으로 현장조사를 통한 발생 길이에 영향을 미치는 인자를 구명하고, 수량화이론(I)을 이용하여 발생 길이에 대한 각 인자의 기여도 분석을 통해 예방적인 측면에서 전라북도 지역 내 토석류 발생 위험지역에 대한 예측기준을 작성하였다. 토석류의 발생 길이에 영향을 미치는 인자는 모암(화성암), 횡단사면(복합사면), 입목 흉고직경(6cm 이하), 표고(501m 이상), 발생위치(산록) 등이었다. 각 인자의 범위를 추정한 결과, 모암(0.5633)이 가장 높게 나타나 전라북도 지역의 토석류 발생 위험도에 큰 영향을 미치는 것으로 추정되었으며, 다음으로는 횡단사면(0.4565), 사면위치(0.3568), 흉고직경(0.3274), 표고(0.3052)순으로 나타났다. 전라북도 지역 산지에서 토석류 발생 위험도 판정식을 기준으로 5개 인자의 카테고리별 점수를 계산한 추정치 범위는 0점에서 2.0092점 사이에 분포하였다. 중앙값인 1.0046점을 기준으로 토석류 위험도 예측을 위한 등급을 분류한 결과 Ⅰ등급은 1.5070 이상, Ⅱ등급 1.0047 ∼ 1.5069, Ⅲ등급 0.5023 ∼ 1.0046, IV등급 0.5022 이하로 나타났고, Ⅰ등급과 Ⅱ등급에서 토석류 발생비율이 76%로서 비교적 높은 적중률을 보였다. 따라서 본 판정표는 전라북도의 산지에서 지역의 위험 비탈면에 있어서 토석류 발생 위험도 판정에 유용하게 활용할 수 있을 것으로 판단된다.

PURPOSES : In this study, the wetting band depths of road slopes estimated using numerical analyses and one-dimensional empirical equations were evaluated. METHODS : The one-dimensional empirical equations used in this study to estimate the wetting band depth were the Pradel and Raad equation, based on modifying the Green and Ampt equation, Lumb's equation, and Sun equation. The numerical analysis of a finite load slope model was carried out using the Seep/w program (2D). In particular, the effect of the initial suction, which indicated the effect of the antecedent rainfall based on the soil–water characteristic curve, was examined as one condition. The results of the wetting band depths obtained using the empirical equations were evaluated and compared with those of the numerical analysis. RESULTS : The wetting band depths obtained using one-dimensional empirical equations were greater than those from the analytical results. In the case of empirical equations, the estimated results obtained for the wetting band depth might be misleading because it has the limitation of being expressed using a one-dimensional equation with an error, owing to several assumptions for the water infiltration phenomenon. It was also found that the accuracy of the wetting band depth was closely related to the results of the soil–water characteristic curve. CONCLUSIONS : Because the wetting band depths obtained using the empirical equation may lead to overestimation, the slope stability could be evaluated as low; however, there was an advantage in terms of inducing conservative design of the road slope. In addition, it was confirmed that the estimated value of the wetting band depth obtained using the Pradel and Raad equation varied with the suction and volumetric function ratios, and further attention should be paid to these two variables.

The fourth industrial revolution encourages manufacturing industry to pursue a new paradigm shift to meet customers' diverse demands by managing the production process efficiently. However, it is not easy to manage efficiently a variety of tasks of all the processes including materials management, production management, process control, sales management, and inventory management. Especially, to set up an efficient production schedule and maintain appropriate inventory is crucial for tailored response to customers' needs. This paper deals with the optimized inventory policy in a steel company that produces granule products under supply contracts of three targeted on-time delivery rates. For efficient inventory management, products are classified into three groups A, B and C, and three differentiated production cycles and safety factors are assumed for the targeted on-time delivery rates of the groups. To derive the optimized inventory policy, we experimented eight cases of combined safety stock and data analysis methods in terms of key performance metrics such as mean inventory level and sold-out rate. Through simulation experiments based on real data we find that the proposed optimized inventory policy reduces inventory level by about 9%, and increases surplus production capacity rate, which is usually used for the production of products in Group C, from 43.4% to 46.3%, compared with the existing inventory policy.

Interest rate spreads indicate the conditions of the economy and serve as an indicator of the recession. The purpose of this study is to predict Korea's interest rate spreads using US data with long-term continuity. To this end, 27 US economic data were used, and the entire data was reduced to 5 dimensions through principal component analysis to build a dataset necessary for prediction. In the prediction model of this study, three RNN models (BasicRNN, LSTM, and GRU) predict the US interest rate spread and use the predicted results in the SVR ensemble model to predict the Korean interest rate spread. The SVR ensemble model predicted Korea's interest rate spread as RMSE 0.0658, which showed more accurate predictive power than the general ensemble model predicted as RMSE 0.0905, and showed excellent performance in terms of tendency to respond to fluctuations. In addition, improved prediction performance was confirmed through period division according to policy changes. This study presented a new way to predict interest rates and yielded better results. We predict that if you use refined data that represents the global economic situation through follow-up studies, you will be able to show higher interest rate predictions and predict economic conditions in Korea as well as other countries.

As the damage caused by earthquakes gradually increases, seismic retrofitting for existing public facilities has been implemented in Korea. Several types of structural analysis methods can be used to evaluate the seismic performance of structures. Among them, for nonlinear dynamic analysis, the hysteresis model must be carefully applied because it can significantly affect the behavior. In order to find a hysteresis model that predicts rational behavior, this study compared the experimental results and analysis results of the existing non-seismic reinforced concrete frames. For energy dissipation, the results were close to the experimental values in the order of Pivot, Concrete, Degrading, and Takeda models. The Concrete model underestimated the energy dissipation due to excessive pinching. In contrast, the other ones except the Pivot model showed the opposite results with relatively little pinching. In the load-displacement curves, the experimental and analysis results tended to be more similar when the column axial force was applied to columns.