• Journal of the Korean Society for Railway
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• v.17 no.4
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• pp.307-312
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• 2014

This study suggested the ARIMA model taking into consideration the seasonal characteristic factor as a method for efficiently forecasting passenger transport demand of the Joongang Line. The forecasting model was built including the demand for the central inland region tourist train (O-train, V-train), which was opened to traffic in April-, 2013 and run in order to reflect the recent demand for the tourism industry. By using the monthly time series data (103) from January-, 2005 to July-, 2013, the optimum model was selected. The forecasting results of passenger transport demand of the Joongang Line showed continuous increase. The developed model forecasts the short-term demand of the Joongang Line.

• International Journal of Computer Science & Network Security
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• v.21 no.12
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• pp.9-20
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• 2021

Abstraction applied in computer networking hides network details behind a well-defined representation by building a model that captures an essential aspect of the network system. Two current methods of representation are available, one based on graph theory, where a network node is reduced to a point in a graph, and the other the use of non-methodological iconic depictions such as human heads, walls, towers or computer racks. In this paper, we adopt an abstract representation methodology, the thinging machine (TM), proposed in software engineering to model computer networks. TM defines a single coherent network architecture and topology that is constituted from only five generic actions with two types of arrows. Without loss of generality, this paper applies TM to model the area of network monitoring in packet-mode transmission. Complex network documents are difficult to maintain and are not guaranteed to mirror actual situations. Network monitoring is constant monitoring for and alerting of malfunctions, failures, stoppages or suspicious activities in a network system. Current monitoring systems are built on ad hoc descriptions that lack systemization. The TM model of monitoring presents a theoretical foundation integrated with events and behavior descriptions. To investigate TM modeling's feasibility, we apply it to an existing computer network in a Kuwaiti enterprise to create an integrated network system that includes hardware, software and communication facilities. The final specifications point to TM modeling's viability in the computer networking field.

• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.1
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• pp.119-127
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• 2023

Recently, deep learning has been used in the development of various institutional devices and services to help the visually impaired people in their daily lives. This is because not only are there few products and facility guides written in braille, but less than 10% of the visually impaired can use braille. In this paper, we propose a system that recognizes beverage cans in real time and outputs the beverage can name with sound for the convenience of the visually impaired. Five commercially available beverage cans were selected, and a CNN model and a YOLO model were designed to recognize the beverage cans. After augmenting the image data, model training was performed. The accuracy of the proposed CNN model and YOLO model is 91.2% and 90.8%, respectively. For practical verification, a system was built by attaching a camera and speaker to a Raspberry Pi. In the system, the YOLO model was applied. It was confirmed that beverage cans were recognized and output as sound in real time in various environments.

• Nuclear Engineering and Technology
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• v.54 no.11
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• pp.4181-4194
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• 2022

Main steam safety valves are commonly used in nuclear power plants to provide final protections from overpressure events. Blowdown and dynamic stability are two critical characteristics of safety valves. However, due to the parameter sensitivity and multi-parameter features of safety valves, using traditional method to design and/or optimize them is generally difficult and/or inefficient. To overcome these problems, a surrogate model-based valve design optimization is carried out in this study, of particular interest are methods of valve surrogate modeling, valve parameters global sensitivity analysis and valve performance optimization. To construct the surrogate model, Design of Experiments (DoE) and Computational Fluid Dynamics (CFD) simulations of the safety valve were performed successively, thereby an ensemble surrogate model (E-AHF) was built for valve blowdown and stability predictions. With the developed E-AHF model, global sensitivity analysis (GSA) on the valve parameters was performed, thereby five primary parameters that affect valve performance were identified. Finally, the k-sigma method is used to conduct the robust optimization on the valve. After optimization, the valve remains stable, the minimum blowdown of the safety valve is reduced greatly from 13.30% to 2.70%, and the corresponding variance is reduced from 1.04 to 0.65 as well, confirming the feasibility and effectiveness of the optimization method proposed in this paper.

• Journal of the Korean Solar Energy Society
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• v.30 no.3
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• pp.10-15
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• 2010

The aim of this study was to analysis the Heating/cooling performance of Solar Window System built in apartments. The solar window is the idea to integrate daylight as a third form of solar energy into a PV/Solar Collector system and allows more control due to the possibility to close the reflectors. However, there can be a conflict between the desire for on one hand daylight and view and on the other hand optimal energy conversion for the PV/Solar Collector system. The process of this study is as follows: 1) The Solar Window system is designed through the investigation of previous paper and work. 2)The simulation program(ESP-r, Therm5.0, Window6.0) was used in energy performance analysis. The reference model of simulation was made up to analysis energy performance on Solar Window system. 3)Selected reference model(Floors:15, Area of Unit:$148.5m^2$) for heating/cooling energy analysis, Energy performance simulation with various variants, such as U-value of Solar Window system according to its position and angle. Consequently, When Solar Window system is equipped with balcony window of Apartment, Annual heating and cooling energy of reference model was cut down about 5%~11%.

• 한국신재생에너지학회:학술대회논문집
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• 2010.11a
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• pp.65.2-65.2
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• 2010

The aim of this study was to analysis the Heating/cooling performance of Solar Window built in apartments. The solar window is the idea to integrate daylight as a third form of solar energy into a PV/Solar Collector system and allows more control due to the possibility to close the reflectors. However, there can be a conflict between the desire for on one hand daylight and view and on the other hand optimal energy conversion for the PV/Solar Collector system. The process of this study is as follows: 1) The Solar Window system is designed through the investigation of previous paper and work. 2)The simulation program(ESP-r, Therm5.0, Window6.0) was used in Heating/cooling performance analysis. The reference model of simulation was made up to analysis Heating/cooling performance on Solar Window. 3)Selected reference model(Floors:15, Area of Unit:$148.5m^2$) for heating energy analysis, Energy performance simulation with various variants, such as U-value of Solar Window system according to its position and angle. Consequently, When Solar Window system is equipped with balcony window of Apartment, Annual heating and cooling energy of reference model was cut down about 5%~11%.

• Journal of Environmental Impact Assessment
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• v.21 no.3
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• pp.409-415
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• 2012

Post-kyoto regime has been discussing with the GHG reduction commitment. GHG energy target management system also has been applied for the domestic measures in the country. Universities are major emission sources for GHG. It is very important for campus to built the GHG inventory system and estimate the potential GHG emission reduction. In general, GHG inventory on the campus was taken by the IPCC guidance with the classification of scope 1, 2, and 3. Electricity was the highest portion of GHG emission on the campus as 5,053.90 $tonsCO_2eq/yr$ in 2009. Manufacturing sector was the second high emission and meant GHG in laboratory. Potential GHG reduction was planned by several assumptions such as installation of occupancy sensor, exchanging LED lamp and photovoltaic power generation. These reduction scenarios was simulated by LEAP model. In 2020, outlook of GHG emission was estimated by 17,435.98 tons of $CO_2$ without any plans of reduction. If the reduction scenarios was applied in 2020, GHG emission would be 16,507.60 tons of $CO_2$ as 5.3% potential reduction.

• Journal of Korean Society of Transportation
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• v.20 no.5
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• pp.145-152
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• 2002

Real-time queueing information and/or predictive queue built-up information can be a good criterion in selecting travel options, such as routes, both for users, and for operators in operating transportation system. Provided properly, it will be a key information for reducing traffic congestion. Also, it helps drivers be able to select optimal roues and operators be able to manage the system effectively as a whole. To produce the predictive queue information, this paper proposes a predictive model for estimating and predicting queue lengths, mainly based on Kalman Filter. It has a structure of having state space model for predicting queue length which is set as observational variable. It has been applied for the Namsan first tunnel and the application results indicate that the model is quite reasonable in its efficacy and can be applicable for various ATIS system architecture. Some limitations and future research agenda have also been discussed.

• KCID journal
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• v.17 no.2
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• pp.71-81
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• 2010

Stream Pilot Project, which began in May 2003 and finished in December 2003, was selected to develop effective methods applicable to nature-like streams. Stream restoration projects aim to maintain or increase ecosystem goods and services while protecting downstream and coastal ecosystems. Fields environmental monitoring such as flow discharge and precipitation were conducted along the Idong stream for amount of channel zone change in 2007. This study selected three monitoring positions to measure the water level and discharge of flowing water. A stage-discharge relation is obtained from direct discharge measurements for three stations by fitting an empirical relationship to the data set. Since discharge measures are made only for low flow conditions, a curve of discharge against stage can then be built by fitting these data with a power curve. And this study used data obtained from floodmark checkup as well as HEC-RAS model to analyze the hydrodynamic characteristics of monitoring sites. Reach-averaged hydraulic parameters for the supply reach were calculated from the small area's HEC-RAS model for Idong stream, and a HEC-RAS model used to analyze hydraulics for a period in 2007, after the stream was considered bank stabilization.

• Journal of the Korean Society for information Management
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• v.18 no.2
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• pp.203-230
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• 2001

The purpose of this study is to develop a document clustering model for automatic classification of knowledge. Two test collections of newspaper article texts and journal article abstracts are built for the clustering experiment. Various feature reduction criteria as well as term weighting methods are applied to the term sets of the test collections, and cosine and Jaccard coefficients are used as similarity measures. The performances of complete linkage and K-means clustering algorithms are compared using different feature selection methods and various term weights. It was found that complete linkage clustering outperforms K-means algorithm and feature reduction up to almost 10% of the total feature sets does not lower the performance of document clustering to any significant extent.