• Journal of Korea Society of Digital Industry and Information Management
• /
• v.6 no.2
• /
• pp.209-224
• /
• 2010

This study is focus on consumer innovativeness. The purpose of this study is to explore variable that affect users' perceived value of mobile advertising and actual response intension to analyze relationship among variables. We built research new model based on the Technology Acceptance Model(TAM) and the Ducoffe's model(1996). The result of this study can be summarized as below. First, consumer innovativeness had a positive effect on convenience, the entertaining element and informativeness. Second, credibility and convenience had a positive effect on mobile advertising value. Third, Mobile advertising value had a positive effect on actual response intention to mobile advertising. As shown in the result of this study, the relation between perceived value of mobile advertising and actual response intention, depending on innovativeness in accordance with mobile advertising characters elements.

• Proceedings of the Korea Society for Simulation Conference
• /
• 1998.10a
• /
• pp.65-65
• /
• 1998

Manufacturing systems like a motor production process are analyzed using simulations than numerical analyses and/or heuristic methods due to their stochastic properties. The SME(small and medium enterprise) producing automotive motors that develop CIM systems to improve production performance is focused as an application site. We analyze and understand the system exactly using layout based simulation, and then we will suggest the initial feashible production-plan dependent on the layout to overcome weak-points of the current system(i.e., high WIPs, bottle-neck processes, due-date delays and etc.). And, solutions are suggested to increase performances of SMEs producing automotive motors in this paper. The simulation model built in this study is moedlled and analyzed with fully object-oriented methodology using SiMPLE++TM according to properties of production processes of the automotive motor. And, we will introduce ways to verify the model with developed templates for reusability when new needs will be occurred such as designing a new ship, extension or rearrangement of the system, change of production-plans, receiving urgent orders, and so on.

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.16 no.9 s.114
• /
• pp.949-957
• /
• 2006

In this Paper, reduction of noise and vibration in ship cabins by using floating floor is studied. Two theoretical models are presented and predicted insertion losses of floating floor are compared to experimental results, where measurements have been done in mock-up built for simulating typical ship cabin structures. In ships, mineral wool is usually used as the impact absorbing materials. The first model (M-S-Plate Model) is that upper plate and mineral wool are assumed as a one-dimensional mass-spring system, which is in turn attached to the simply supported elastic floor. The second model (Wave-Plate Model) is that mineral wool is assumed as an elastic medium for wave propagation. The comparisons show that M-S-Plate model is in good agreement with experimental results when density of mineral wool is 140K, and fiber direction is horizontal. For higher density and vertical fiber direction, Wave-Plate model shows good agreements with measurements. It is found that including the elastic behavior of the floor is essential in improving accuracy of the prediction for low frequency ranges below $100{sim}200Hz$.

• Journal of Information Technology Applications and Management
• /
• v.26 no.2
• /
• pp.111-123
• /
• 2019

In this paper, software activity, software activity instance, and the quality of the activity instance are defined as the 'activity which is performed on the software product by a person or a group of persons,' the 'distinctive and individual performance of software activity,' and the 'performer's evaluation on how good or bad his/her own activity instance is,' respectively. The representative values of the instance quality population associated with a product and its sub-population are defined as the (software) activity quality and activity quality characteristic of the product, respectively. The activity quality model in this paper classifies activity quality characteristics according to the classification hierarchy of software activity by the goal. In the model, a quality characteristic can have two types of sub-characteristics : Special sub-characteristic and component sub-characteristic, where the former is its super-characteristic too simultaneously and the latter is not its super-characteristic but a part of its super-characteristic. The activity quality model is parsimonious, coherent, and easy to understand and use. The activity quality model can serve as a corner stone on which a software quality body of knowledge, which constituted with a set of models parsimonious, coherent, and easy to understand and use and the theories explaining the cause-and-relationships among the models, can be built. The body of knowledge can be called the (grand) activity-centric quality model of software.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.38 no.1
• /
• pp.139-152
• /
• 2013

The purpose of this study is to claim the validity of tuning the architecture of neural network models for multi-class classification. A neural network model for multi-class classification is basically constructed by building a series of neural network models for binary classification. Building a neural network model, we are required to set the values of parameters such as number of hidden nodes and weight decay parameter in advance, which draws special attention as the performance of the model can be quite different by the values of the parameters. For better performance of the model, it is absolutely necessary to have a prior process of tuning the parameters every time the neural network model is built. Nonetheless, previous studies have not mentioned the necessity of the tuning process or proved its validity. In this study, we claim that we should tune the parameters every time we build the neural network model for multi-class classification. Through empirical analysis using wine data, we show that the performance of the model with the tuned parameters is superior to those of untuned models.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2011.04a
• /
• pp.443-444
• /
• 2011

This paper discusses a model order reduction for large order rotor dynamics systems results from the finite element discretization. Typical rotor systems consist of a rotor, built-on parts, and a support system, and require prudent consideration in their dynamic analysis models because they include unsymmetric stiffness, localized nonproportional damping and frequency dependent gyroscopic effects. When the finite element model has a very large number of degrees of freedom because of complex geometry, repeated dynamic analyses to investigate the critical speeds, stability, and unbalanced response are computationally very expensive to finish within a practical design cycle. In this paper, the Krylov-based model order reduction via moment matching significantly speeds up the dynamic analyses necessary to check eigenvalues and critical speeds of a Nelson-Vaugh rotor system. With this approach the dynamic simulation is efficiently repeated via a reduced system by changing a running rotational speed because it can be preserved as a parameter in the process of model reduction. The Campbell diagram by the reduced system shows very good agreement with that of the original system. A 3-D finite element model of the Nelson-Vaugh rotor system is taken as a numerical example to demonstrate the advantages of this model reduction for rotor dynamic simulation.

• Korean Journal of Construction Engineering and Management
• /
• v.6 no.3 s.25
• /
• pp.100-110
• /
• 2005

As construction projects are getting more complex and larger in size, the amount of information is increased exponentially, which requires information management systems to accumulate as-built information throughout the project life-cycle. Particularly, a daily report system is very important, since it helps them keep track of various as-built information at the most detailed level. However, there have been many problems with daily reporting since its process is time-consuming and contains a lot of redundancies and ambiguities. Therefore, the objective of this research is to improve a process of collecting as-built information and managing daily report. To do so, this research developed a to-be process model and a daily report system. The daily report system developed in this research consists of interactive task generator and daily report management modules. The system has been successfully implemented in a real world construction project. The system development processes including process analysis, information models and system features are described along with discussions on the results and improvements.

• Asian Journal of Atmospheric Environment
• /
• v.2 no.1
• /
• pp.60-67
• /
• 2008

The spatial limitations of urban environments in general lead to invention and design of a wide range of underground transportation systems such as subways, underground roads and paths, etc. Among them, the application of subway systems in metropolitan cities is most commonly observed to ease those confronted difficulties on this purpose. It in turn leaves passengers and workers to be exposed to indoor air potentially polluted by various sources existing in this underground environment. Specifically when considering the IAQ in a subway station, there exist many IAQ-related parameters to be counted either as individual or as integrated exposures. In this study, a model system has been developed to manage the general IAQ in a subway station. Field survey and $CO_2$ measurements were initially conducted to analyze and understand the relationship between the indoor and outdoor air quality while considering the internal pollution sources such as passengers, subway trains, etc. The measurement data were then employed for the model development with other static information. For the model development, the algorithm of simple continuity was built and applied to model the subway IAQ concerned. In this paper, the recent updated draft version of model developed will be reported and demonstrated.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2019.05a
• /
• pp.156-156
• /
• 2019

In this study, a gated recurrent unit (GRU) network is constructed based on a deep neural network (DNN) with the aim of restoring the missing daily flow data in river basins. Lai Chau hydrological station is located upstream of the Da river basin (Vietnam) is selected as the target station for this study. Input data of the model are data on observed daily flow for 24 years from 1961 to 1984 (before Hoa Binh dam was built) at 5 hydrological stations, in which 4 gauge stations in the basin downstream and restoring - target station (Lai Chau). The total available data is divided into sections for different purposes. The data set of 23 years (1961-1983) was employed for training and validation purposes, with corresponding rates of 80% for training and 20% for validation respectively. Another data set of one year (1984) was used for the testing purpose to objectively verify the performance and accuracy of the model. Though only a modest amount of input data is required and furthermore the Lai Chau hydrological station is located upstream of the Da River, the calculated results based on the suggested model are in satisfactory agreement with observed data, the Nash - Sutcliffe efficiency (NSE) is higher than 95%. The finding of this study illustrated the outstanding performance of the GRU network model in recovering the missing flow data at Lai Chau station. As a result, DNN models, as well as GRU network models, have great potential for application within the field of hydrology and hydraulics.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.49 no.12
• /
• pp.226-233
• /
• 2012

In this paper, we propose a 'linear approximation method' which is an accelerated BER (Bit Error Rate) test method for high speed interfaces, based on an analytical BER model. Both the conventional 'Q-factor estimation method' and 'linear approximation method' can predict a timing margin for $10^{-13}$ BER with an error of about 0.03UI. This linear approximation method is implemented on a hardware as an accelerated Built-In Self Test (BIST) with an internal BERT (BET Tester). While a direct measurement of a timing margin in a 3Gbps interface takes about 5.6 hours with $10^{-13}$ BER requirement and 95% confidence level, the accelerated BIST estimates a timing margin within 0.6 second without a considerable loss of accuracy. The test results show that the error between the estimated timing margin and the timing margin from an actual measurement using the internal BERT is less than 0.045UI.