• Journal of the Korean Society for Precision Engineering
• /
• v.27 no.3
• /
• pp.118-126
• /
• 2010

The automated mechanical transmission(AMT) is composed of electronic control management(ECM) and automatic shift gear(ASG). The AMT has advantages which are high efficiency of manual transmissions(MT) and offer operation convenience similar to automatic transmissions(AT). However, it has defects that are the torque gap during gear shift transients and shift time is long. To reduce such defects, it is necessary practically to evaluate error and characteristics as developing simulation model before the control algorithm is applied. In this paper, models are composed of vehicle model and AMT shift control model. Particularly AMT shift control model consists of main clutch management model (MCM) and shift control management model(SCM). The developed models were verified by comparing the simulated and experimental results under the same operational conditions. It can also be used to evaluate shift algorithm.

• Journal of Korean Society for Quality Management
• /
• v.35 no.3
• /
• pp.75-87
• /
• 2007

This paper deals with an integration model of three major quality management systems. The well known global standards such as ISO 9001 quality system, Malcolm Baldrige model, and EFQM model are integrated as a prototype quality system. The proposed model is then applied to help a power generation company to select improvement tasks for enhancing quality management. Here, we discuss three quality management systems, an integration process of the three systems, the integrated model, and a real world application case.

• Korean Journal of Construction Engineering and Management
• /
• v.5 no.4 s.20
• /
• pp.79-86
• /
• 2004

One of the most difficult tasks in pavement management information systems is establishing the links between performance measures of a structure and the design and construction inputs. In-situ pavement performance can be considered a response variable to many project input variables, such as design, construction, and traffic loading effects. If we are to fully understand the component of pavement performance and specify the inputs through design and construction specifications to achieve that performance we must develop quantitative relationship between input and response variables through a scientific, fully integrated Pavement Performance Analysis System (PPAS). Hence, the objective of this study is to design a database model required for developing an effective database template that will allow analysis of pavement performance measures based on design and construction information linked by location. In order to select the most appropriate database model, a conceptual database model (Entity Relationship Model) and dimensional model, which is believed to be the most effective modeling technique for data warehouse project, are designed and compared. It is believed that other state highway agencies could adopt the proposed design strategy for implementing a PPAS at the discretion of the state highway agencies.

• The KSFM Journal of Fluid Machinery
• /
• v.2 no.1 s.2
• /
• pp.56-63
• /
• 1999

In this study, the performance prediction programs for centrifugal pumps are developed. To estimate the losses in the centrifugal pump impellers, a two-zone model and TEIS(two elements in series) model are applied to the program. The basic concept of a two zone model considers the primary zone that is an isentropic core flow and the secondary zone that has a non-isentropic region at the impeller exit. The flow goes through two different zones and is mixed out at the impeller exit and the mixing process occurs with an increase in entropy, a decrease in total pressure. The level of the core flow diffusion in an impeller was calculated using TEIS(two elements in series) model. The effects of various parameters which are used in this program on the prediction of head and efficiency are discussed. The correlation curves used to select the effectiveness of the primitive TEIS model were suggested according to the specific speed of the centrifugal pumps.

• Proceedings of the SAREK Conference
• /
• 2008.06a
• /
• pp.231-236
• /
• 2008

The purpose of this study is to develop assessment model for selection of new DSM investment programs. In this research, MAUT method which find assessment value by each attributes related to selecting new DSM investment programs using utility function and integrate with structural frame was used to develop assessment model. In order to validate the usefulness of the model, assessment model was applied for actual candidate group of new DSM investment programs in natural gas domain. By utilize this assessment model to select new DSM investment programs, it is expected to minimize risk of new program launching and to maximize efficiency of DSM investment programs.

• Industrial Engineering and Management Systems
• /
• v.15 no.3
• /
• pp.215-223
• /
• 2016

Design of personnel teams has been studied from diverse perspectives; the most common are the people and systems requirements perspectives. All these point of view are linked, which is the reason why it is necessary to study them simultaneously. Considering this gap, a decision making model is developed based on factors, models, and requirements mentioned in the literature. The model is applied to a real case. The findings indicate that the Personnel Behavior Based Lean model (PBBL) can be converted into a decision making model for the selection of team members. The study is focused not only on the individual candidates' knowledge, skills, and aptitudes, but also on how the model considers the company requirements, conflicts, and the importance of each person to the project.

• Journal of Information Processing Systems
• /
• v.10 no.2
• /
• pp.240-255
• /
• 2014

Cloud computing has increasingly been drawing attention these days. Each big company in IT hurries to get a chunk of meat that promises to be a whopping market in the future. At the same time, information is always associated with security and risk problems. Nowadays, the handling of these risks is no longer just a technology problem, with a good deal of literature focusing on risk or security management and framework in the information system. In this paper, we find the specific business meaning of the BMIS model and try to apply and leverage this model to cloud risk. Through a previous study, we select and determine the causal risk factors in cloud service, which are also known as CSFs (Critical Success Factors) in information management. Subsequently, we distribute all selected CSFs into the BMIS model by mapping with ten principles in cloud risk. Finally, by using the leverage points, we try to leverage the model factors and aim to make a resource-optimized, dynamic, general risk control business model for cloud service providers.

• Communications for Statistical Applications and Methods
• /
• v.29 no.3
• /
• pp.353-371
• /
• 2022

This paper analyzes death counts after World War II of several countries to identify and to compare their stochastic structures. The stochastic structures that this paper entertains are three structural time series models, a local level with a random walk model, a fixed local linear trend model and a local linear trend model. The structural time series models assume that a time series can be formulated directly with the unobserved components such as trend, slope, seasonal, cycle and daily effect. Random effect of each unobserved component is characterized by its own stochastic structure and a distribution of its irregular component. The structural time series models use the Kalman filter to estimate unknown parameters of a stochastic model, to predict future data, and to do filtering data. This paper identifies the best-fitted stochastic model for three types of death counts (Female, Male and Total) of each country. Two diagnostic procedures are used to check the validity of fitted models. Three criteria, AIC, BIC and SSPE are used to select the best-fitted valid stochastic model for each type of death counts of each country.

• Journal of Korea Multimedia Society
• /
• v.23 no.9
• /
• pp.1129-1138
• /
• 2020

The performance of convolutional deep learning networks is generally determined according to parameters of target dataset, structure of network, convolution kernel, activation function, and optimization algorithm. In this paper, a genetic algorithm is used to select the appropriate deep learning model and parameters for Alzheimer's classification and to compare the learning results with preliminary experiment. We compare and analyze the Alzheimer's disease classification performance of VGG-16, GoogLeNet, and ResNet to select an effective network for detecting AD and MCI. The simulation results show that the network structure is ResNet, the activation function is ReLU, the optimization algorithm is Adam, and the convolution kernel has a 3-dilated convolution filter for the accuracy of dementia medical images.

• Spatial Information Research
• /
• v.11 no.3
• /
• pp.241-249
• /
• 2003

The purpose of this paper is to provide the basic data to select the most proper site, which is essential for the economic activation of North Korea by means of the GIS tool. In this purpose, firstly, Nampo area is sampled as model case, classifying the factors into the natural environmental one and socio- cultural one. Secondly, to analyze the land use status and topographic status which is essential for natural environment factor. Besides USLE(Universal Soil Loss Equation), which is one of the disaster effect assessments, is being applied to suggest the selection method for minimizing the environment change by way of assuming the land effluence amount. The started could advance to prove the ideal model in selecting the most suitable site while minimizing the environmental change by means of the composite tool of GIS and USLE.