• Industrial Engineering and Management Systems
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• v.3 no.1
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• pp.38-51
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• 2004

Over the years, most or many companies have focused their attention to the effectiveness and efficiency of their business units. As a new way of doing business, these companies have begun to realize the strategic importance of planning, controlling, and designing their own supply chain system. This paper analyzes the coordination issues in supply chains that consist of one manufacturer and multiple retailers operating under uncertain end customer demand and delivery lead-time. We use the Genetic Algorithm (GA) to determine the appropriate ordering and inventory level at which the manufacturer and multiple retailers can maximize the profit of the chain. This is performed under three controlling policies: the traditionally centralized controlling policy under the manufacturer's perspective, the entire chain’s perspective, and lastly the coordinating controlling policy with an incentive scheme. The outcome from the study reveals that the coordinating controlling policy with an incentive scheme can outperform the traditional centralized controlling policies by creating a win-win situation in which all members of the chain benefit from higher profit, thus resulting in more willingness from all members to join the chain.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.3
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• pp.327-336
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• 2004

In distributed autonomous mobile robot system, each robot (predator or prey) must behave by itself according to its states and environments, and if necessary, must cooperate with other robots in order to carry out a given task. Therefore it is essential that each robot have both learning and evolution ability to adapt to dynamic environment. This paper proposes a pursuing system utilizing the artificial life concept where virtual robots emulate social behaviors of animals and insects and realize their group behaviors. Each robot contains sensors to perceive other robots in several directions and decides its behavior based on the information obtained by the sensors. In this paper, a neural network is used for behavior decision controller. The input of the neural network is decided by the existence of other robots and the distance to the other robots. The output determines the directions in which the robot moves. The connection weight values of this neural network are encoded as genes, and the fitness individuals are determined using a genetic algorithm. Here, the fitness values imply how much group behaviors fit adequately to the goal and can express group behaviors. The validity of the system is verified through simulation. Besides, in this paper, we could have observed the robots' emergent behaviors during simulation.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.645-650
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• 2003

Legged robots can avoid an obstacle by crawling-over or striding, according to the obstacle’s nature and the current state of the robot. Thus, it can be observed that the mobility efficiency to reach a destination is improved by such action. Moreover, if robots have many legs like 4-legged or 6-legged types, then the robot movement range is affected by the order of swing leg. In this paper, the avoidance action of a quadruped robot is generated by a neural network (NN) whose inputs are information on the position of the destination, the obstacle configuration and the robot's self-state. To realize a free gait in static walking, the order of swing leg is determined using an another NN whose inputs are the amount of movements and the robot’s self-state. The design parameter of the latter NN is adjusted by using genetic algorithm (GA).

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.8
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• pp.3841-3861
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• 2017

Virtualized small cell network is a promising architecture which can realize efficient utilization of the network resource. However, conventional full duplex self-backhauls lead to residual self-interference, which limits the network performance. To handle this issue, this paper proposes a virtual resource allocation, in which the residual self-interference is fully exploited by employing a physical-layer network coding (PNC) aided self-backhaul scheme. We formulate the features of PNC as time slot and information rate constraints, and based on that, the virtual resource allocation is formulated as a mixed combinatorial optimization problem. To solve the problem efficiently, it is decomposed into two sub problems, and a two-phase iteration algorithm is developed accordingly. In the algorithm, the first sub problem is approximated and transferred into a convex problem by utilizing the upper bound of the PNC rate constraint. On the basis of that, the convexity of the second sub problem is also proved. Simulation results show the advantages of the proposed scheme over conventional solution in both the profits of self-backhauls and utility of the network resource.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.8C
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• pp.729-740
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• 2002

This paper studies the issues arising in the virtual topology reconfiguration phase of Multi-wavelength Routed Optical Networks. This reconfiguration process means to change the virtual topology in response to the changing traffic patterns in the higher layer. We formulate the optimal reconfiguration policy as a multi-stage decision-making problem to maximize the expected reward and cost function over an infinite horizon. Then we propose a new heuristic algorithm based on node-exchange to reconfigure the virtual topology to meet the traffic requirement. To counter the continual approximation problem brought by heuristic approach, we take the traffic prediction into consideration. We further propose a new heuristic reconfiguration algorithm called Prediction based Multi-stage Reconfiguration approach to realize the optimal reconfiguration policy based on predicted traffic. Simulation results show that our reconfiguration policy significantly outperforms the conventional one, while the required physical resources are limited.

• The Transactions of the Korea Information Processing Society
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• v.7 no.2
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• pp.536-541
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• 2000

Turbo code has excellent decoding performance but had limitations for real time communications because of the system complexity and time delay in decoding procedure. To overcome this problem, a new SRI(Semi-Random Interleaver) algorithm which realize the reduction of the interleaver size is proposed for reducing the time delay during the decoding prodedure. SRI compose the interleaver 0.5 size from the input data sequence. In writing the interleaver, data is recorded by row such as block interleaver. But, in reading, data is read by randomly and the text data is located by the just address simultaneously. Therefore, the processing time of with the preexisting method such as block, helical random interleaver.

• Nuclear Engineering and Technology
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• v.55 no.6
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• pp.1966-1973
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• 2023

Virtual reality technology has been widely used in the field of nuclear and radiation safety, dose rate computing in virtual environment is essential for optimizing radiation protection and planning the work in radioactive-controlled area. Because the CPU-based gamma dose rate computing takes up a large amount of time and computing power for voxelization of volumetric radioactive source, it is inefficient and limited in its applied scope. This study is to develop an efficient gamma dose rate computing code and apply into fast virtual simulation. To improve the computing efficiency of the point kernel algorithm in the reference (Li et al., 2020), we design a GPU-based computing framework for taking full advantage of computing power of virtual engine, propose a novel voxelization algorithm of volumetric radioactive source. According to the framework, we develop the GPPK(GPU-based point kernel gamma dose rate computing) code using GPU programming, to realize the fast dose rate computing in virtual world. The test results show that the GPPK code is play and plug for different scenarios of virtual simulation, has a better performance than CPU-based gamma dose rate computing code, especially on the voxelization of three-dimensional (3D) model. The accuracy of dose rates from the proposed method is in the acceptable range.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.5
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• pp.2294-2309
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• 2020

In this article, a new Aloha-based tag identification protocol is presented to improve the reading efficiency of the EPC C1 Gen2-based UHF RFID system. Collision detection (CD) plays a vital role in tag identification process which determines the efficiency of anti-collision protocols since most Aloha-based protocols optimize the incoming frame length based on the collisions in current frame. Existing CD methods are ineffective in identifying collision, resulting in a degradation of identification performance. Our proposed algorithm adopts an enhanced CD (ECD) scheme based on the EPC C1 Gen2 standard to optimize identification performance. The ECD method can realize timely and effective CD by detecting the pulse width of the randomly sent by tags. According to the ECD, the reader detects the slot distribution and predicts tag cardinality in every collision slot. The tags involved in each collision slot are identified by independently assigned sub-frames. A large number of numerical results show that the proposed solution is superior to other existing anti-collision protocols in various performance evaluation metrics.

• Korean Journal of Computational Design and Engineering
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• v.11 no.4
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• pp.315-325
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• 2006

It is very often necessary to search for similar parts during designing a new product because its parts are often easily designed by modifying existing similar parts. In this way, the design time and cost can be reduced. Thus it would be nice to have an efficient similarity comparison algorithm that can be used anytime in the design process. There have been many approaches to compare shape similarity between two solids. In this paper, two parts represented in B-Rep is compared in two steps: one for overall appearances and the other for detail features. In the first step, geometric information is used in low level of detail for easy and fast pre-classification by the overall appearance. In the second step, feature information is used to compare the detail shape in high level of detail to find more similar design. To realize the idea above, a multi resolution algorithm is proposed so that a given solid is described by an overall appearance in a low resolution and by detail features in high resolution. Using this multi-resolution representation, parts can be compared based on the overall appearance first so that the number of parts to be compared in high resolution is reduced, and then detail features are investigated to retrieve the most similar part. In this way, computational time can be reduced by the fast classification in the first step while reliability can be preserved by detail comparison in the second step.

• Journal of the Korea Society of Computer and Information
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• v.25 no.4
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• pp.105-112
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• 2020

In the fourth industrial revolution represented by hyper-connected and intelligence, cloud computing is drawing attention as a technology to realize big data and artificial intelligence technologies. The proliferation of cloud computing has also increased the number of threats. In this paper, we propose one way to effectively monitor to the resources assigned to clients by the IaaS service provider. The method we propose in this paper is to model the use of resources allocated to cloud systems using ARIMA algorithm, and it identifies abnormal situations through the use and trend analysis. Through experiments, we have verified that the client service provider can effectively monitor using the proposed method within the minimum amount of access to the client systems.