• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.28 no.7A
• /
• pp.451-466
• /
• 2003

Untethered nodes in mobile ad-hoc networks strongly depend on the efficient use of their batteries. In this paper, we propose a new metric, the drain rate, to forecast the lifetime of nodes according to current traffic conditions. This metric is combined with the value of the remaining battery capacity to determine which nodes can be part of an active route. We describe new route selection mechanisms for MANET routing protocols, which we call the Minimum Drain Rate (MDR) and the Conditional Minimum Drain Rate (CMDR). MDR extends nodal battery life and the duration of paths, while CMDR also minimizes the total transmission power consumed per packet. Using the ns-2 simulator and the dynamic source routing (DSR) protocol, we compare MDR and CMDR against prior proposals for power-aware routing and show that using the drain rate for power-aware route selection offers superior performance results.

• Proceedings of the Korean System Dynamics Society
• /
• 2006.04a
• /
• pp.19-40
• /
• 2006

A system dynamics model is developed to investigate the applicability of the agent based modeling concept in the system dynamics model. The assumed problem is to forecast the size and structure of the organization with the developing market environment. The agent based modeling concept is applied to the organization part, and the other parts of the model such as market, facilities, etc. are developed with the traditional system dynamics technique. The simulation results show the agent based modeling part can be combined with the traditional system dynamics modeling with more precisions. However, the complexity increases and the simulation times are longer than those of the traditional method.

• Journal of applied mathematics & informatics
• /
• v.12 no.1_2
• /
• pp.233-241
• /
• 2003

The rolling schedule procedure has been an important part of the Enterprise Resource Planning (ERP) systems. The performance of production planning in an ERP system depends on the selection of the three parameters in rolling schedule procedure: frozen interval, replanning interval, and planning horizon (forecast window). This research investigated, in a theoretical approach, the combined impact of selections of those three parameters. The proven mathematical theorems provided guidance to re-duction of instability (nervousness) and to seek the optimal balance between stability and responsiveness of ERP systems. Further the theorems are extended to incorporate the cost structure.

• Journal of the Korean Society of Clothing and Textiles
• /
• v.30 no.1 s.149
• /
• pp.167-175
• /
• 2006

The purpose of this study is to clarify the expansion of functions of clothes by analyzing the characteristics of transformation, and to forecast future trends in fashion through systematization of the aforementioned analyses. Analysis of 20th century Modernism and Post-Modernism in a sociocultural sense confirms that transformation in clothes was formed by environmental, functional, deconstructive, and expressive factors. In this sense, the formative factors mentioned above conceptually include nomadic characteristics, usefulness, irregularity, and expressiveness. The nomadic characteristics found in clothes transformation signify the change of clothes into environmental nomadic everyday implements, used as tools for the body. Usefulness of clothes means that it is worn for variability, multipurpose multi-functionality, and combined multiple use. Irregularity means the clothes can change indefinitely, according to random manipulation on the wearer's part. Last of all, expressiveness conveys the designer's internal sensitivity and imagination onto an external object through the induction of various expressive factors.

• Korean System Dynamics Review
• /
• v.7 no.1
• /
• pp.27-49
• /
• 2006

A system dynamics model is developed to investigate the applicability of the agent based modeling concept in the system dynamics model. The assumed problem is to forecast the size and structure of the organization with the developing market environment. The agent based modeling concept is applied to the organization part, and the other parts of the model such as market, facilities, etc. are developed with the traditional system dynamics technique. The simulation results show the agent based modeling part can be combined with the traditional system dynamics modeling with more precisions. However, the complexity increases and the simulation times are longer than those of the traditional method.

• The Bulletin of The Korean Astronomical Society
• /
• v.44 no.2
• /
• pp.35.3-35.3
• /
• 2019

The new era of multi-messenger astronomy (MMA) has arrived in 2017 with the detection of the binary neutron star merger in both gravitational wave (GW) and electromagnetic radiation (EM). Now, the new run of GW detectors are providing numerous GW events and the number GW events are expected to increase dramatically in future as the GW sensitivities improve. When the GW studies are combined with EM counterpart observations, a great synergy is expected in many areas of study such as the physical process following the compact object merger, the environment of such events (and galaxy evolution), and cosmology, Therefore, it has now become crucial to identify and characterize these GW events in optical/IR EM. In the past, we have been performing optical/NIR observation of GW events using a worldwide network of more than 10 telescopes, and are getting more actively involved in MMA of GW sources. In this talk, we will present our network of telescopes, the EM follow-up observation results of GW events including GW170817 and the O3 events in 2019, and the current issues in MMA. We will also give the future prospects of MMA, showing the forecast for the GW events and the outlook of EM MMA observations.

• Atmosphere
• /
• v.25 no.4
• /
• pp.577-589
• /
• 2015

An unusual long-period and heavy snowfall occurred in the Yeongdong region from 6 to 14 February 2014. This event produced snowfall total of 194.8 cm and the recordbreaking 9-day snowfall duration in the 103-year local record at Gangneung. In this study, satellite-derived cloud-top brightness temperatures from the infrared channel in the atmospheric window ($10{\mu}m{\sim}11{\mu}m$) are examined to find out the characteristics of clouds related with this heavy snowfall event. The analysis results reveal that a majority of precipitation is related with the low-level stratiform clouds whose cloud-top brightness temperatures are distributed from -15 to $-20^{\circ}C$ and their standard deviations over the analysis domain (${\sim}1,000km^2$, 37 satellite pixels) are less than $2^{\circ}C$. It is also found that in the above temperature range precipitation intensity tends to increase with colder temperature. When the temperatures are warmer than $-15^{\circ}C$, there is no precipitation or light precipitation. Furthermore this relation is confirmed from the examination of some other heavy snowfall events and light precipitation events which are related with the low-level stratiform clouds. This precipitation-brightness temperature relation may be explained by the combined effect of ice crystal growth processes: the maximum in dendritic ice-crystal growth occurs at about $-15^{\circ}C$ and the activation of ice nuclei begins below temperatures from approximately -7 to $-16^{\circ}C$, depending on the composition of the ice nuclei.

• Asian Journal of Innovation and Policy
• /
• v.9 no.2
• /
• pp.187-206
• /
• 2020

Under the on-going evolution of the COVID-19 pandemic, estimating the economic impact of the pandemic is highly uncertain and challenging. This situation makes it difficult for policymakers, governors, and economic entities to formulate appropriate responses and decision makings. To provide useful information about the effect of the COVID-19 pandemic on the Korean economy, this study examined macroeconomic impact analysis stemming from the pandemic shocks with different scenarios for the Korean economy. Based on three scenarios using the growth rate of 2020 GDP and consumer expenditure patterns, the 2021 GDP by industry sector was forecast with two new approaches. First, the recovering process of the Korean economy from the shock was analyzed by applying a Flex-IO method. Second, a new forecasting approach combined with an IO coefficient matrix was applied to forecast the future GDP changes. The findings of this study are summarized as follows: First, the total GDP growth rate under the Pessimistic Scenario demonstrates less rebound from the shock than that of the Base Scenario. Second, agriculture, culture, and tourism-related sectors that are suffering from the severe losses of COVID-19 showed lower resilience than other different industries. Third, information and communications technology (ICT) industry maintains a stable growth trend and is expected to take the leading role for the Korean economy in the post-COVID-19 and the Industry 4.0 eras. The findings deliver that it needs to analyze how government expenditure responding the shock into the forecasting model, which can be more useful and reliable to simulate the resilience from the pandemic.

• Structural Engineering and Mechanics
• /
• v.29 no.2
• /
• pp.135-154
• /
• 2008

The moving vehicle loads on a bridge deck is one of the most important live loads of bridges. They should be understood, monitored and controlled before the bridge design as well as when the bridge is open for traffic. A MOM-based algorithm (MOMA) is proposed for identifying the timevarying moving vehicle loads from the responses of bridge deck in this paper. It aims at an acceptable solution to the ill-conditioning problem that often exists in the inverse problem of moving force identification. The moving vehicle loads are described as a combination of whole basis functions, such as orthogonal Legendre polynomials or Fourier series, and further estimated by solving the new system equations developed with the basis functions. A number of responses have been combined, some numerical simulations on single axle, two axle and multiple-axle loads, being either constant or timevarying, have been carried out and compared with the existing time domain method (TDM) in this paper. The illustrated results show that the MOMA has higher identification accuracy and robust noise immunity as well as producing an acceptable solution to ill-conditioning cases to some extent when it is used to identify the moving force from bridge responses.

• The Korean Journal of Applied Statistics
• /
• v.36 no.1
• /
• pp.49-62
• /
• 2023

Solar energy, which is rapidly increasing in proportion, is being continuously developed and invested. As the installation of new and renewable energy policy green new deal and home solar panels increases, the supply of solar energy in Korea is gradually expanding, and research on accurate demand prediction of power generation is actively underway. In addition, the importance of solar radiation prediction was identified in that solar radiation prediction is acting as a factor that most influences power generation demand prediction. In addition, this study can confirm the biggest difference in that it attempted to predict solar radiation using medium-term forecast weather data not used in previous studies. In this paper, we combined the multi-linear regression model, KNN, random fores, and SVR model and the clustering technique, K-means, to predict solar radiation by hour, by calculating the probability density function for each cluster. Before using medium-term forecast data, mean absolute error (MAE) and root mean squared error (RMSE) were used as indicators to compare model prediction results. The data were converted into daily data according to the medium-term forecast data format from March 1, 2017 to February 28, 2022. As a result of comparing the predictive performance of the model, the method showed the best performance by predicting daily solar radiation with random forest, classifying dates with similar climate factors, and calculating the probability density function of solar radiation by cluster. In addition, when the prediction results were checked after fitting the model to the medium-term forecast data using this methodology, it was confirmed that the prediction error increased by date. This seems to be due to a prediction error in the mid-term forecast weather data. In future studies, among the weather factors that can be used in the mid-term forecast data, studies that add exogenous variables such as precipitation or apply time series clustering techniques should be conducted.