• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.22 no.9
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• pp.614-619
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• 2010

Recently, a problem related to the thermal management in portable electronic and telecommunication devices is becoming issued. That is due to the trend of a slimness of the devices, so it is not easy to find the optimal thermal management solution for the devices. From now on, a pressed circular type cooling device has been mainly used, however the cooling device with thin thickness is becoming needed by the inner space constraint of the applications. In the present study, the silicon flat plate type cooling device with the separated vapor and liquid flow path was designed and fabricated. The normal isothermal characteristics created by vapor-liquid phase change was confirmed through the experimental study. The cooling device with 70 mm of total length showed 6.8 W of the heat transfer rate within the range of $4{\sim}5^{\circ}C/W$ of thermal resistance. In the future, it will be possible to develop the commercialized cooling device by revising the fabrication process and enhancing the thermal performance of the silicon and glass cooling device.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.370-374
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• 2005

This study deals with the method of post-processing in the automatic tool path generation for 5-axis NC machining. The 5-axis NC machining cannot only cope with the manufacturing of complicated shapes, but also offers numerous advantages such as reasonable tool employment, great reduction of set-up process and so on. Thus 5-axis NC machining has been used fur aircraft parts, mold and die as well as for complicated shapes such as impeller, propeller and rotor. However, most of the present CAM systems for 5-axis NC machining have limited functions in terms of tool collision, machine limits and post-processing. Especially 5-axis machine configurations are various according to the method which the rotational axes are adapted with the table and spindle. For that reason, in many cases the optimal numerical control (NC) data cannot be obtained or considerable time is consumed. To solve this problem, we applied a general post-processor fur 5-axis NC machining. The validity of this post-processor should be experimentally confirmed by successfully milling to a helix shaped workpiece.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.11a
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• pp.625-632
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• 2004

This study presents the NDE (non-destructive evaluation) technique for detecting the loosened bolts on joint steel structures on the basis of TOF (time of flight) and amplitudes of Lamb waves. Probabilistic neural network (PNN) technique which is an effective tool for pattern classification problem was applied to the damage estimation using PZT induced Lamb waves. Two kinds of damages were introduced by dominant damages (DD) which mean loosened bolts within the Lamb waves beam width and minor damages (MD) which mean loosened bolts out of the Lamb waves beam width. They were investigated for the establishment of the optimal decision boundaries which divide each damage class's region including the intact class. In this study, the applicability of the probabilistic neural networks was identified through the test results for the damage cases within and out of wave beam path. It has been found that the present methods are very efficient and reasonable in predicting the loosened bolts on the joint steel structures probabilistically.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.5
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• pp.1973-1991
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• 2018

Multimedia applications over wireless networks have been evolving to augmented reality or virtual reality services. However, a rich data size compared to conventional multimedia services causes bandwidth bottlenecks over wireless networks, which is one of the main reasons why those applications are not used widely. To overcome this limitation, bandwidth aggregation techniques, which exploit a multi-path transmission, have been considered to maximize link utilization. Currently, most of the conventional researches have been focusing on the user end problems to improve the quality of service (QoS) through optimal load distribution. In this paper, we address the joint pricing and load distribution problem for multi-homing in heterogeneous wireless access networks (ANs), considering the interests of both the users and the service providers. Specifically, we consider profit from resource allocation and cost of power consumption expenditure for operation as an utility of each service provider. Here, users decide how much to request the resource and how to split the resource over heterogeneous wireless ANs to minimize their cost while supporting the required QoS. Then, service providers compete with each other by setting the price to maximize their utilities over user reactions. We study the behaviors of users and service providers by analyzing their hierarchical decision-making process as a multileader-, multifollower Stackelberg game. We show that both the user and service provider strategies are closed form solutions. Finally, we discuss how the proposed scheme is well converged to equilibrium points.

• Journal of information and communication convergence engineering
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• v.20 no.3
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• pp.181-188
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• 2022

An intelligent distributed multi-agent system (IDMS) using reinforcement learning (RL) is a challenging and intricate problem in which single or multiple agent(s) aim to achieve their specific goals (sub-goal and final goal), where they move their states in a complex and cluttered environment. The environment provided by the IDMS provides a cumulative optimal reward for each action based on the policy of the learning process. Most actions involve interacting with a given IDMS environment; therefore, it can provide the following elements: a starting agent state, multiple obstacles, agent goals, and a cluttered index. The reward in the environment is also reflected by RL-based agents, in which agents can move randomly or intelligently to reach their respective goals, to improve the agent learning performance. We extend different cases of intelligent multi-agent systems from our previous works: (a) a proposed environment-clutter-based-index for agent sub-goal selection and analysis of its effect, and (b) a newly proposed RL reward scheme based on the environmental clutter-index to identify and analyze the prerequisites and conditions for improving the overall system.

• International Journal of Computer Science & Network Security
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• v.22 no.12
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• pp.51-56
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• 2022

In space based constellation network, users are allowed to enter or leave the network arbitrarily. Hence, the number, identities and transmitted data of active users vary with time and have considerable impacts on the receiver's performance. The so-called problem of multiuser detection means identifying the identity of each active user and detecting the data transmitted by each active user. Traditional methods assume that the number of active users is equal to the maximum number of users that the network can hold. The model of traditional methods are simple and the performance are suboptimal. In this paper a Maximum A Posteriori Probability (MAP) based multiuser detection method is proposed. The proposed method models the activity state of users as Markov chain and transforms multiuser detection into searching optimal path in grid map with BCJR algorithm. Simulation results indicate that the proposed method obtains 2.6dB and 1dB E_b/N₀ gains respectively when activity detection error rate and symbol error rate reach 10^-3, comparing with reference methods.

• Journal of Korean Society of Transportation
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• v.22 no.7 s.78
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• pp.107-117
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• 2004

The growing demand for customer-response, made-to-order manufacturing and satisfactory delivery are stimulating the importance of commercial fleet management problem. Moreover, the rapid transformation to the customer-oriented multi-frequency, relatively small fleet, such as home delivery and Perishable goods, requiring prompt delivery and advanced real-time operation of vehicle fleets. In this paper we consider the vehicle routing problem(VRP) to minimize delivery completion time which is equal to the time that last customer wait for the vehicle in fleet operation. The mathematical formulation is different from those for the classical VRP which is minimizing cost/distance/time by running vehicles in manager's point of view. The key aspect of this model is not considering the return time from the last customer to depot in every vehicle path. Thereby, the vehicle dispatcher can afford to dynamically respond to customer demand and vehicle availability. The customer's position concerned with minimizing waiting time that may be applied for the delivery of product required freshness or delivery time. Extensive experiments are carried out to compare the performance of minimizing delivery completion time by using the ILOG Solver which has the advantage of solving quickly an interim solution very near an optimal solution. The experimental results show that the suggested model can easily find near optimal solution in a reasonable computational time under the various combination of customers and vehicles.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.1
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• pp.82-91
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• 2009

Routing (or path selection) is one of the key issues of multi-hop relay networks such as the IEEE 802.16j. Moreover, the allocation of appropriate resource such as bandwidth should not only be made in accordance with the paths selected, but the utilization of radio resource of an entire cell should also be maximized. Due to this interdependency between the problems of resource allocation and routing, it is desired these two problems are addressed simultaneously. In this paper, we propose a joint resource allocation and routing scheme for an OFDMA-based multi-hop cellular system. This scheme uses a polynomial time heuristic algorithm called Multi-Dimensional Multi-choice Knapsack Problem (MMKP) in order to find an approximate solution maximizing the total downlink throughput. In the simulation results, we show that the proposed scheme finds a sub-optimal solution which is superior to a link quality-based routing scheme, but slightly worse than the optimal solution.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.101-114
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• 2023

In the wartime, aircraft carrying out a mission to strike the enemy deep in the depth are exposed to the risk of being shoot down. As a key combat force in mordern warfare, it takes a lot of time, effot and national budget to train military flight personnel who operate high-tech weapon systems. Therefore, this study studied the path problem of predicting the route of emergency escape from enemy territory to the target point to avoid obstacles, and through this, the possibility of safe recovery of emergency escape military flight personnel was increased. based problem, transforming the problem into a TSP, VRP, and Dijkstra algorithm, and approaching it with an optimization technique. However, if this problem is approached in a network problem, it is difficult to reflect the dynamic factors and uncertainties of the battlefield environment that military flight personnel in distress will face. So, MDP suitable for modeling dynamic environments was applied and studied. In addition, GIS was used to obtain topographic information data, and in the process of designing the reward structure of MDP, topographic information was reflected in more detail so that the model could be more realistic than previous studies. In this study, value iteration algorithms and deterministic methods were used to derive a path that allows the military flight personnel in distress to move to the shortest distance while making the most of the topographical advantages. In addition, it was intended to add the reality of the model by adding actual topographic information and obstacles that the military flight personnel in distress can meet in the process of escape and escape. Through this, it was possible to predict through which route the military flight personnel would escape and escape in the actual situation. The model presented in this study can be applied to various operational situations through redesign of the reward structure. In actual situations, decision support based on scientific techniques that reflect various factors in predicting the escape route of the military flight personnel in distress and conducting combat search and rescue operations will be possible.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.3 no.1 s.4
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• pp.31-44
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• 2004

The study of Estimation model for the short-term travel time prediction. There is a different solution which has predicted the link travel time to solve this problem. By using this solution, the link travel time is predicted based on link conditions from time to time. The predicated link travel time is used to search the shortest path. Before providing a dynamic shortest path finding, the prediction model should be verified. To verify the prediction model, three models such as Kalman filtering, Stochastic Process, ARIMA. The ARIMA model should adjust optimal parameters according to the traffic conditions. It requires a frequent adjustment process of finding optimal parameters. As a result of these characteristics, It is difficult to use the ARIMA model as a prediction. Kalman Filtering model has a distinguished prediction capability. It is due to the modification of travel time predictive errors in the gaining matrix. As a result of these characteristics, the Kalman Filtering model is likely to have a non-accumulative errors in prediction. Stochastic Process model uses the historical patterns of travel time conditions on links. It if favorably comparable with the other models in the sense of the recurrent travel time condition prediction. As a result, for the travel time estimation, Kalman filtering model is the better estimation model for the short-term estimation, stochastic process is the better for the long-term estimation.