• International conference on construction engineering and project management
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• 2007.03a
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• pp.279-288
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• 2007

Attempts to achieve a higher productivity have led studies to focus on process improvement. Information has been found as an essential element for process improvement. This research has introduced and focused on two types of information, namely: related jobsite information along the process and feedback information. Related jobsite information along the process which needs to be processed and delivered in a timely manner, accurate, and real time is required to streamline the decision making process. Whereas feedback information about process' current practices which have to be captured and stored is a useful for continuous improvement in identifying the problem origin and determining corrective action. In the current practices, although these two types of information are essential for process improvement, construction process has faced barriers in obtaining that information. Therefore, this research will propose a new information system to overcome the aforementioned barriers. The new information system consists of RFID as an automatic identification and data collection device integrated with database to support construction processes. The new system attempts to provide related jobsite information along the process and feedback information to support decision making process and continuous process improvement respectively. A case study of prefabrication installation process in housing projects has been selected to be implemented in conceptual model of RFID application in construction industry. Conceptual model will be presented in this paper as an initial stage of this ongoing research. Expected outcomes of the new system and future works will be discussed briefly.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.458-459
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• 2021

Recently, researches using deep learning technology based on Wi-Fi fingerprints have been conducted for accurate services in indoor location-based services. Among the deep learning models, an RNN model that can store information from the past can store continuous movements in indoor positioning, thereby reducing positioning errors. At this time, continuous sequential data is required as training data. However, since Wi-Fi fingerprint data is generally managed only with signals for a specific location, it is inappropriate to use it as training data for an RNN model. This paper proposes a path generation method through prediction of a moving path based on Wi-Fi fingerprint data extended to region data through clustering to generate sequential input data of the RNN model.

• Journal of Mechanical Science and Technology
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• v.14 no.8
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• pp.807-815
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• 2000

In this paper, modified discrete time preview control algorithms for active and semi-active suspension systems are derived based on a simple mathematical 4 DOF half-car model. The discrete time preview control laws for ride comfort are employed in the simulation. The algorithms for MIMO system contain control strategies reacting against body forces that occur at cornering, accelerating, braking, or under payload, in addition to road disturbances. Matlab simulation results for the discrete time case are compared with those for the continuous time case and the appropriateness of the discrete time algorithms are verified by the of simulation results. Passive, active, and semi-active system responses to a sinusoidal input and an asphalt road input are analysed and evaluated. The simulation results show the extent of performance degradation due to numerical errors related to the length of the sampling time and time delay.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.267-269
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• 2005

This paper describes a consideration on the sampling in linearly time-varying (LTV) systems in view of the convenience in digital signal processing. The relation between a continuous-time and a discrete-time system models is investigated for a simple linear time-invariant system. Based on the results of the investigation, we first consider discrete-time models for LTV systems, Then the simplicity of the models in terms of microprocessor-based digital signal processing is compared.

• Transactions of the Korean Society of Automotive Engineers
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• v.10 no.5
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• pp.29-34
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• 2002

This study presents the process of the continuous-time system identification for unknown nonlinear systems. The Radial Basis Function(RBF) error filtering identification model is introduced at first. This identification scheme includes RBF network to approximate unknown function of nonlinear system which is structured by affine form. The neural network is trained by the adaptive law based on Lyapunov synthesis method. The identification scheme is applied to engine and the performance of RBF error filtering Identification model is verified by the simulation with a three-state engine model. The simulation results have revealed that the values of the estimated function show favorable agreement with the real values of the engine model. The introduced identification scheme can be effectively applied to model-based nonlinear control.

• The Transactions of the Korean Institute of Power Electronics
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• v.10 no.4
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• pp.347-355
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• 2005

In this paper, a new continuous~time small signal model of an average current mode control is proposed. Sampling effect Is considered to obtain the proposed small signal model. By the proposed model, the high frequency response characteristics of current loop gain might be predicted accurately compared to previous models. And this leads the prediction of inductor current response of the proposed model to be accurate compared to others. In order to show the usefulness of the proposed model, prediction results of the proposed model are compared to those of the circuit level simulator, PSIM and experiment.

• The KIPS Transactions:PartD
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• v.14D no.3 s.113
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• pp.273-284
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• 2007

RFID middleware systems collect and filter the RFID streaming data gathered continuously by numerous readers in order to process requests from applications. These requests are called continuous queries because they are kept on executing during certain periods. To enhance the performance of the middleware, it is required to build an index to process the continuous queries efficiently. Several approaches of building an index on not data records but queries, called Query Index, are proposed and widely used for evaluating continuous queries over streaming data. The EPCglobal proposed an Event Cycle Specification (ECSpec) model, which is a standard query interface for RFID applications. Continuous queries based on ECSpec consist of a large number of segments for representing the query conditions. The problem with using any of the existing query indexes on these continuous queries is that it takes a long time to build the index because it is necessary to insert a large number of segments into the index. To solve this problem, we propose an Aggregate Transformation that converts a group of segments into a compressed data which is representative of the segments. We compare the performance of a transformed index with the existing query indexes.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.36 no.1
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• pp.105-114
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• 2016

With approximately 20 million transportation card data entries of the metropolitan districts being generated per day, application of the data to management and policy interventions is becoming an issue of interest. The research herein attempts a model of the possibility of dynamic demand change predictions and its purpose is thereby to construct a Dynamic Passengers Trip Assignment Model. The model and algorithm created are targeted at city rail lines operated by seven different transport facilities with the exclusion of travel by bus, as passenger movements by this mode can be minutely disaggregated through card tagging. The model created has been constructed in continuous time as is fitting to the big data characteristic of transport card data, while passenger path choice behavior is effectively represented using a perception parameter as a function of increasing number of transfers. Running the model on 800 pairs of metropolitan city rail data has proven its capability in determining dynamic demand at any moment in time, in line with the typical advantages expected of a continuous time-based model. Comparison against data measured by the eye of existing rail operating facilities to assess changes in congestion intensity shows that the model closely approximates the values and trends of the existing data with high levels of confidence. Future research efforts should be directed toward continued examination into construction of an integrated bus-city rail system model.

• Journal of the Korean Regional Science Association
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• v.13 no.2
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• pp.93-118
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• 1997

Main findings of this study are as follows. Time-space model of Korea for urban growth model is established. The variables of space model resulted in job and education, which both are significant at 0.01 level and positive. The effect of job and education on the urban growth are 0.76 and 0.29 respectively in average. the determinants for deciding the influences for job variable are income variable and price-level variable. Income variable contributes 68.66% and the direction is negative while contribution of price-level variable is 29.90% and the direction is positive. The determinants for education variable are income, unemployment and wage difference between university graduates and high school graduates. The contribution and the high school graduates. The contribution and the direction of each variable for education variable are 63.6% and positive for the unemployment variable, 15.99% and negative for the income variable and 13.75% and positive for the wage difference variable. This study in different from previous works in three ways. The first is to establish the time-space model which could consider the time and space factor simultaneously. The second is to build data bases which contain the data of almost every city and every year in Korea during the objective period, which make the analysis continuous. The third is that the general analytic framework for the study is macrosocial one rather than a behavioral one, which means the unit of analysis is the metropolitan community and each city occupies population actively through it's potential power such as jobs, education and so on rather than a city population is the passive result of migration.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.13 no.4
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• pp.461-473
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• 2000

This paper deals with a numerical model for the time-dependent analysis of steel and concrete composite beams with partial shear connection. A linear partial interaction theory is adopted in formulation of structural slip behavior, and the effect of concrete creep and shrinkage are considered. The proposed model is effective in simulating the slip behavior, combined with concrete creep and shrinkage, of multi-span continuous composite beams. Finally, correlation studies and several parameter studies are conducted with the objective to establish the validity of the proposed model.