• Magazine of the Korean Society of Agricultural Engineers
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• v.45 no.1
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• pp.102-114
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• 2003

The objectives of the paper are to evaluate cell based pollutant loadings for different storm events, to monitor the hydrology and water quality of the Baran HP#6 watershed, and to validate AGNPS with the field data. Simplification was made to AGNPS in estimating storm erosivity factors from a triangular rainfall distribution. GIS-AGNPS interface model consists of three subsystems; the input data processor based on a geographic information system. the models. and the post processor Land use patten at the tested watershed was classified from the Landsat TM data using the artificial neural network model that adopts an error back propagation algorithm. AGNPS model parameters were obtained from the GIS databases, and additional parameters calibrated with field data. It was then tested with ungauged conditions. The simulated runoff was reasonably in good agreement as compared with the observed data. And simulated water quality parameters appear to be reasonably comparable to the field data.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.6 no.2
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• pp.78-92
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• 1994

Thermal performance of pipe network of continuous heating system controlled by thermostat and flow control valve was simulated in consideration of radiation heat transfer and solved by linear analysis method. Thermal performance of real apartment building with radiant floor heating system was simulated by equivalence heat resistance-capacity method. This method enables to simulate the unsteady variation of temperature or each element of building. Heat transfer characteristics of each element were also investigated.

• Journal of the Semiconductor & Display Technology
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• v.16 no.3
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• pp.127-130
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• 2017

In this research, we present a path planning method for an autonomous flight of unmanned aerial vehicles (UAVs) through reinforcement learning under simulated environment. We design the simulator for reinforcement learning of uav. Also we implement interface for compatibility of Deep Q-Network(DQN) and simulator. In this paper, we perform reinforcement learning through the simulator and DQN, and use Q-learning algorithm, which is a kind of reinforcement learning algorithms. Through experimentation, we verify performance of DQN-simulator. Finally, we evaluated the learning results and suggest path planning strategy using reinforcement learning.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.7
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• pp.2191-2208
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• 2022

Motion blur in PET (Positron emission tomography) images induced by respiratory motion will reduce the quality of imaging. Although exiting methods have positive performance for respiratory motion correction in medical practice, there are still many aspects that can be improved. In this paper, an improved 3D unsupervised framework, Res-Voxel based on U-Net network was proposed for the motion correction. The Res-Voxel with multiple residual structure may improve the ability of predicting deformation field, and use a smaller convolution kernel to reduce the parameters of the model and decrease the amount of computation required. The proposed is tested on the simulated PET imaging data and the clinical data. Experimental results demonstrate that the proposed achieved Dice indices 93.81%, 81.75% and 75.10% on the simulated geometric phantom data, voxel phantom data and the clinical data respectively. It is demonstrated that the proposed method can improve the registration and correction performance of PET image.

• Journal of National Security and Military Science
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• s.1
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• pp.345-360
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• 2003

To build an information oriented armed forces, the Korean military telecommunication networks adopt TCP/IP standard communication infrastructures based on ATM packet switched networks. Utilizing this network infrastructure, the Korean armed forces also applies to the areas of battleship management for efficient operation command controls and resource management for efficient resource allocations. In this military communication networks, it is essential to determine the least cost network topology under equal performance and reliability constraints. Basically, this type of communication network design problem is known in the literature as an NP Hard problem. As the number of network node increases, it is very hard to obtain an optimal solution in polynomial time. Therefore, it is reasonable to use a heuristic algorithm which provides a good solution with minimal computational efforts. In this study, we developed a simulated annealing based heuristic algorithm which can be utilized for the design of military communication networks. The developed algorithm provides a good packet switched network topology which satisfies a given set of performance and reliability constraints with reasonable computation times.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.82-85
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• 2004

This paper proposes the development of delay compensator to minimize performance degradation caused by time delays in network-based real-time control systems. The delay compensator uses the time-stamp method as a direct delay measuring method to measure time delays generated between network nodes. The delay compensator predicts the network time delays of next period in the views point of time delays and minimizes performance degradation from network through considering predicted time delays. Control output considering network time delays is generated by the defuzzification of probable time delays of next period. The time delays considered in the delay compensator are modeled by using a timed Petri net model. The proposed delay prediction mechanism for the delay compensator is evaluated through some simulation tests by measuring deviation of the predicted delays from simulated delays.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.5
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• pp.205-212
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• 2019

Scene graph is a kind of knowledge graph that represents both objects and their relationships found in a image. This paper proposes a 3D scene graph generation model for three-dimensional indoor environments. An 3D scene graph includes not only object types, their positions and attributes, but also three-dimensional spatial relationships between them, An 3D scene graph can be viewed as a prior knowledge base describing the given environment within that the agent will be deployed later. Therefore, 3D scene graphs can be used in many useful applications, such as visual question answering (VQA) and service robots. This proposed 3D scene graph generation model consists of four sub-networks: object detection network (ObjNet), attribute prediction network (AttNet), transfer network (TransNet), relationship prediction network (RelNet). Conducting several experiments with 3D simulated indoor environments provided by AI2-THOR, we confirmed that the proposed model shows high performance.

• Journal of the Korea Society of Computer and Information
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• v.9 no.1
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• pp.87-93
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• 2004

In the design of mobile wireless communication network, BSC(Base Station Location), BSC(Base Station Controller) and MSC(Mobile Switching Center) are the most important parameters. Designing base station location, the cost must be minimized by combining various, complex parameters. We can solve this Problem by combining optimization algorithm, such as Simulated Annealing, Tabu Search, Genetic Algorithm, Random Walk Algorithm that have been used extensively for global optimization. This paper shows the 4 kinds of algorithm to be applied to the optimization of base station location for communication system and then compares, analyzes the results and shows optimization process of algorithm.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.5 no.1
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• pp.33-44
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• 2012

A class of recurrent neural networks is proposed and proven to be capable of identifying any discrete-time dynamical system. The applications of the proposed network are addressed in the encoding, identification, and extraction of finite state automata. Simulation results show that the identification of finite state automata using the proposed network, trained by the hybrid greedy simulated annealing with a modified error function in the learning stage, exhibits generally better performance than other conventional identification schemes.

• Journal of Communications and Networks
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• v.3 no.4
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• pp.365-373
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• 2001

We propose a new channel reservation protocol which can reduce message delay by using a counter for detection of d source conflict in a WDM single-hop network with non-equivalent propagation delay. A source convict occurs when a source node has the right to transmit more than or equal to two messages simultaneously, which are transmitted using different wavelengths. In such a case, the source node has to newly obtain the right to transmit the message. In the proposed protocol, by using a source conflict counter a source node can detect a source conflict before a wave-length assignment is performed. Therefore, the source node can start a procedure to newly obtain the right to transmit the message which cannot be transmitted due to a source conflict. We analyse the throughput performance by taking the effect of a source conflict into account, and show that the approximate analysis and the computer simulated results are close. Also, from computer simulated results, we show that our proposed protocol can reduce mean message delay dramatically without degrading throughput performance as the offered load becomes large.