• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2143-2145
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• 2003

In the linear system identification using the discrete time constant coefficients, there is a subspace method based on 4SID recently much suggested instead of the parametric method like as the maximum likelihood method. The subspace method is not related with the impulse response and difference equation in its input-output equation, but with the system matrix of the direct state space model from the input-output data. The subspace method is a very useful tool to adopt in the multivariable system identification, but it has a shortage unable to adopt in the closed-loop system identification. In this paper, we are suggested the methods to get rid of the shortage of the subspace method in the closed-loop system identification. The subspace method is used in the estimate of the output prediction values from the estimating of the state space vector. And we have compared the results with the outputs of the recursive least square method in the numerical simulation.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.6
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• pp.2473-2481
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• 2013

The two characteristics of two-lane-and-two-way traffic flow are platoon and overtaking triggered by low-speed vehicle. It is crucial to develop a robust model which simultaneously generates the behaviors of platoon by low-speed vehicle and overtaking using opposite lane. Hence, a microscopic two-lane and two-way vehicle model was introduced (B. Yoon, 2011), which is based on CA (Cellular Automata) which is one of discrete time-space models, in Korea. While the model very reasonably explains the behaviour of overtaking low-speed vehicle in stable traffic flow below critical density, it has shortcomings to the overtaking process in unstable traffic flow above the critical density. Therefore, the objective of this study is to develope a vehicle model to more realistically explain overtaking process in unstable traffic flow state based on the model developed in the previous study. The experimental results revealed that the car-following model robustly generates the various macroscopic relationships of traffic flow generating stop-and-go traffic flow and the overtaking model reasonably explains the behaviors of overtaking under the conditions of both opposite traffic flow and stochastic parameter to consider overtaking in unstable traffic flow state. The vehicle model presented in this study can be expected to be utilized for the analysis of two-lane-and-two-way traffic flows more realistically than before.

• Journal of the Korea Society of Computer and Information
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• v.1 no.1
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• pp.147-158
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• 1996

This paper proposed a concurrency control structure based on specialized data flow graphs that was analysed a run-time concurrency control activity to be integrated with the task scheduler Data were viewed as flowing on the arcs from one node to another in a stream of discrete to tokens. The network that Is based upon the Entity-Relationship model, can be viewed a fixed problems used query tokens as a data flow graph. The performance was measured used in the various expriments compared the overall performance of the different concurrency control methods, DBFG (DataBase Flow graphs) scheduling had the knowledge to obtain better performance than 2PL in a distributed environment.

• Korean Journal of Construction Engineering and Management
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• v.16 no.5
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• pp.114-122
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• 2015

Real estate development requires significant amount of capital investment. The project duration has been increased according to its enlarged size. For this reason, cost overrun and time delay are important risk factors that should be managed properly. As a method to hedge the risk, varoius real option methods have been presented. However, conventional project value assesment methods such as NPV(Net Present Value) have weakness to support decision making by reflecting dynamic situations in terms of variation of cost and time. Furthermore, the decision making process is serious of actions rather than discrete event. The purpose of this paper is to present a multiple real option valuation method to overcome the deterministic aspect of real option presented in previous research and practice. The method is developed as following: firstly, to select the model that can be applied in the real estate development project through a survey from previous literature on real options analysis; secondly, to apply data from office development case in order to verify the model by applying conventional real option and multiple real option valuation. According to analysis result, multiple real option provides enhanced values comparing to NPV and single real option.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.9 no.1
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• pp.54-62
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• 1995

This paper is a study on a speed control of an induction motor used the MRA-DSM(Mode1 Reference Adaptive-Discrete Sliding Mode) controller. In this paper, when controls motor speed, DSM algorithm is proposed for having Robustness against disturbance and parameter variation. and it is also proposed MRA-DSM including the additional load model reference algorithm, which can be compensated the discontinuous control imputs at sliding mode and followed the model Preference independent of parameter variation of control subjects. The control system is composed of the parallel processing control system using the microprocessor for maximizing the performance of control systems and the real time processing. Also it simplifies the hardware composed of controlling the system by software and improves the reliability of the system. And while MRA-DSM control, faster response characteristics of 27.2 % is obtained than DSM control.

• Journal of the Semiconductor & Display Technology
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• v.22 no.1
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• pp.11-17
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• 2023

This paper proposes a lightweight deep learning network for detecting an image splicing forgery. The research on image forgery detection using CNN, a deep learning network, and research on detecting and localizing forgery in pixel units are in progress. Among them, CAT-Net, which learns the discrete cosine transform coefficients of images together with images, was released in 2022. The DCT coefficients presented by CAT-Net are combined with the JPEG artifact learning module and the backbone model as pre-learning, and the weights are fixed. The dataset used for pre-training is not included in the public dataset, and the backbone model has a relatively large number of network parameters, which causes overfitting in a small dataset, hindering generalization performance. In this paper, this learning module is designed to learn the characterization depending on the DCT domain in real-time during network training without pre-training. The DCT RRU-Net proposed in this paper is a network that combines RRU-Net which detects forgery by learning only images and JPEG artifact learning module. It is confirmed that the network parameters are less than those of CAT-Net, the detection performance of forgery is better than that of RRU-Net, and the generalization performance for various datasets improves through the network architecture and training method of DCT RRU-Net.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2008.03a
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• pp.330-339
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• 2008

Ground-based interceptors(GBI) comprise a major element of the strategic defense against hostile targets like Intercontinental Ballistic Missiles(ICBM) and reentry vehicles(RV) dispersed from them. An optimum design of the subsystems is required to increase the performance and reliability of these GBI. Propulsion subsystem design and optimization is the motivation for this effort. This paper describes an effort in which an entire GBI missile system, including a multi-stage solid rocket booster, is considered simultaneously in a Genetic Algorithm(GA) performance optimization process. Single goal, constrained optimization is performed. For specified payload and miss distance, time of flight, the most important component in the optimization process is the booster, for its takeoff weight, time of flight, or a combination of the two. The GBI is assumed to be a multistage missile that uses target location data provided by two ground based RF radar sensors and two low earth orbit(LEO) IR sensors. 3Dimensional model is developed for a multistage target with a boost phase acceleration profile that depends on total mass, propellant mass and the specific impulse in the gravity field. The monostatic radar cross section (RCS) data of a three stage ICBM is used. For preliminary design, GBI is assumed to have a fixed initial position from the target launch point and zero launch delay. GBI carries the Kill Vehicle(KV) to an optimal position in space to allow it to complete the intercept. The objective is to design and optimize the propulsion system for the GBI that will fulfill mission requirements and objectives. The KV weight and volume requirements are specified in the problem definition before the optimization is computed. We have considered only continuous design variables, while considering discrete variables as input. Though the number of stages should also be one of the design variables, however, in this paper it is fixed as three. The elite solution from GA is passed on to(Sequential Quadratic Programming) SQP as near optimal guess. The SQP then performs local convergence to identify the minimum mass of the GBI. The performance of the three staged GBI is validated using a ballistic missile intercept scenario modeled in Matlab/SIMULINK.

• International conference on construction engineering and project management
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• 2011.02a
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• pp.187-194
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• 2011

Optimizing truck dispatching-intervals is imperative in ready mixed concrete (RMC) delivery process. Intervals shorter than optimal may induce queuing of idle trucks at a construction site, resulting in a long delivery cycle time. On the other hand, intervals longer than optimal can trigger work discontinuity due to a lack of available trucks where required. Therefore, the RMC delivery process should be systematically scheduled in order to minimize the occurrence of waiting trucks as well as guarantee work continuity. However, it is challenging to find optimal intervals, particularly in urban areas, due to variations in both traffic conditions and concrete placement rates at the site. Truck dispatching intervals are usually determined based on the concrete plant managers' intuitive judgments, without sufficient and reliable information regarding traffic and site conditions. Accordingly, the RMC delivery process often experiences inefficiency and/or work discontinuity. Automatic data collection (ADC) techniques (e.g., RFID or GPS) can be effective tools to assist plant managers in finding optimal dispatching intervals, thereby enhancing delivery performance. However, quantitative evidence of the extent of performance improvement has rarely been reported to data, and this is a central reason for a general reluctance within the industry to embrace these techniques, despite their potential benefits. To address this issue, this research reports on the development of a discrete event simulation model and its application to a large-scale building project in Abu Dhabi. The simulation results indicate that ADC techniques can reduce the truck idle time at site by 57% and also enhance the pouring continuity in the RMC delivery process.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.5
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• pp.67-75
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• 2023

This paper deals with the operation of air taxis, which is one of the latest innovative technologies aimed at solving the issue of traffic congestion in cities. A key challenge for the successful introduction of the technology and efficient operation is a vertiport location problem. This paper employs a discrete choice model to calculate choice probabilities of transportation modes for each route, taking into account factors such as cost and travel time associated with different modes. Based on this probability, a mathematical formulation to maximize the utilization rate for air taxi is proposed. However, the proposed model is NP-hard, effective and efficient solution methodology is required. Compared to previous studies that simply proposed the optimization models, this study presents a solution methodology using the cross-entropy algorithm and confirms the effectiveness and efficiency of the algorith through numerical experiments. In addition to the academic excellence of the algorithm, it suggests that decision-making that considers actual data and air taxi utilization plans can increase the practial usability.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.4
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• pp.159-167
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• 2015

We consider a wafer lot transfer/release planning problem from semiconductor wafer fabrication facilities to probing facilities with the objective of minimizing the deviation of workload and total tardiness of customers' orders. Due to the complexity of the considered problem, we propose a two-level hierarchical production planning method for the lot transfer problem between two parallel facilities to obtain an executable production plan and schedule. In the higher level, the solution for the reduced mathematical model with Lagrangian relaxation method can be regarded as a coarse good lot transfer/release plan with daily time bucket, and discrete-event simulation is performed to obtain detailed lot processing schedules at the machines with a priority-rule-based scheduling method and the lot transfer/release plan is evaluated in the lower level. To evaluate the performance of the suggested planning method, we provide computational tests on the problems obtained from a set of real data and additional test scenarios in which the several levels of variations are added in the customers' demands. Results of computational tests showed that the proposed lot transfer/planning architecture generates executable plans within acceptable computational time in the real factories and the total tardiness of orders can be reduced more effectively by using more sophisticated lot transfer methods, such as considering the due date and ready times of lots associated the same order with the mathematical formulation. The proposed method may be implemented for the problem of job assignment in back-end process such as the assignment of chips to be tested from assembly facilities to final test facilities. Also, the proposed method can be improved by considering the sequence dependent setup in the probing facilities.