• Journal of the Korea Institute of Military Science and Technology
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• v.14 no.3
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• pp.501-508
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• 2011

In this paper, we propose a channel allocation algorithm of MSAP(Mobile Subscriber Access Point) and data delivery scheme exploiting the symbol level network coding. The network is comprised of TS(Tactical Switch) as a backbone node, MSAPs, and TMFTs(Tactical Multi-Function Terminal). The TS performs the channel allocation considering the communication range overlapping between the neighboring MSAPs and applies the symbol level network coding, if necessary, depending on the position of the TMFTs. Assuming the number of available antennas of TMFT and MSAP will be extended to two from one, we propose two schemes: single mode and dual mode. Through the simulation, we show that the proposed delivery scheme provides higher delivery ratio and lower delivery delay compared with the legacy store-and-forward scheme.

• Proceedings of the SAREK Conference
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• 2008.11a
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• pp.351-356
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• 2008

When various kinds of outputs are produced from a single energy system, the methodology which allocates the common cost to each output cost is very important because it is directly related with the profit and loss of producers and purchasers. In the cost allocation methodology of the heat and the electricity on a cogeneration, there are energy method, work method, proportional method, benefit distribution method, various exergetic methods, and so on. On the other hand, we have proposed a worth evaluation method which can be applied to any system. The definition of this methodology is that the unit cost of a product is proportion to the worth. Where, worth is a certain evaluating basis that can equalize the worth of products. In this study, we applied this methodology to a gas-turbine cogeneration which produces 119.2 GJ/h of electricity and 134.7 GJ/h of heat, and then we allocated 3,150 $/h of fuel cost to electricity cost and heat cost. Also, we compared with various cost allocation methods. As the result, we conclude that exergy of various kinds of worth basis evaluates the worth of heat and electricity most reasonably on this system.

• Journal of Communications and Networks
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• v.15 no.1
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• pp.102-110
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• 2013

This paper considers a cooperative orthogonal frequency division multiple access (OFDMA)-based cognitive radio network where the primary system leases some of its subchannels to the secondary system for a fraction of time in exchange for the secondary users (SUs) assisting the transmission of primary users (PUs) as relays. Our aim is to determine the cooperation strategies among the primary and secondary systems so as to maximize the sum-rate of SUs while maintaining quality-of-service (QoS) requirements of PUs. We formulate a joint optimization problem of PU transmission mode selection, SU (or relay) selection, subcarrier assignment, power control, and time allocation. By applying dual method, this mixed integer programming problem is decomposed into parallel per-subcarrier subproblems, with each determining the cooperation strategy between one PU and one SU. We show that, on each leased subcarrier, the optimal strategy is to let a SU exclusively act as a relay or transmit for itself. This result is fundamentally different from the conventional spectrum leasing in single-channel systems where a SU must transmit a fraction of time for itself if it helps the PU's transmission. We then propose a subgradient-based algorithm to find the asymptotically optimal solution to the primal problem in polynomial time. Simulation results demonstrate that the proposed algorithm can significantly enhance the network performance.

• Journal of Power Electronics
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• v.10 no.4
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• pp.419-427
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• 2010

A parallel control strategy in capacity proportion frequency allocation mode for shunt active power filters (APFs) is proposed to overcome some of the difficulties in high power applications. To improve the compensation accuracy and overall system stability, an improved selective harmonic current control based on multiple synchronous rotating reference coordinates is presented in a single APF unit, which approximately implements zero steady-state error compensation. The combined decoupling strategy is proposed and theoretically analyzed to simplify selective harmonic current control. Improved selective harmonic current control forms the basis for multi-APF parallel operation. Therefore, a parallel control strategy is proposed to realize a proper optimization so that the APFs with a larger capacity compensate more harmonic current and the ones with a smaller capacity compensate less harmonic current, which is very practical for accurate harmonic current compensation and stable grid operation in high power applications. This is verified by experimental results. The total harmonic distortion (THD) is reduced from 29% to 2.7% for a typical uncontrolled rectifier load with a resistor and an inductor in a laboratory platform.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.21 no.4
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• pp.252-259
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• 2009

When various kinds of outputs are produced from a single energy system, the methodology which allocates the common cost to each output cost is very important because it is directly related with the profit and loss of producers and purchasers. In the cost allocation methodology of the heat and the electricity on a cogeneration, there are energy method, work method, proportional method, benefit distribution method, various exergetic methods, and so on. On the other hand, we have proposed a worth evaluation method which can be applied to any system. The definition of this methodology is that the unit cost of a product is proportion to the worth. Where, worth is a certain evaluating basis that can equalize the worth of products. In this study, we applied this methodology to a gas-turbine cogeneration which produces 119.2 GJ/h of electricity and 134.7 GJ/h of steam, and then we allocated 3,150 $/h of fuel cost to electricity cost and steam cost. Also, we compared with various cost allocation methods. As the result, we conclude that reversible work of various kinds of worth basis evaluates the worth of heat and electricity most reasonably.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.9
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• pp.2764-2781
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• 2024

Federated learning (FL) has been proposed as an emerging distributed machine learning framework, which lowers the risk of privacy leakage by training models without uploading original data. Therefore, it has been widely utilized in the Industrial Internet of Things (IIoT). Despite this, FL still faces challenges including the non-independent identically distributed (Non-IID) data and heterogeneity of devices, which may cause difficulties in model convergence. To address these issues, a local surrogate function is initially constructed for each device to ensure a smooth decline in global loss. Subsequently, aiming to minimize the system energy consumption, an FL approach for joint CPU frequency control and bandwidth allocation, called FCBAFL is proposed. Specifically, the maximum delay of a single round is first treated as a uniform delay constraint, and a limited-memory Broyden-Fletcher-Goldfarb-Shanno bounded (L-BFGS-B) algorithm is employed to find the optimal bandwidth allocation with a fixed CPU frequency. Following that, the result is utilized to derive the optimal CPU frequency. Numerical simulation results show that the proposed FCBAFL algorithm exhibits more excellent convergence compared with baseline algorithm, and outperforms other schemes in declining the energy consumption.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.36 no.4
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• pp.130-137
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• 2013

In this paper, we consider a two-agent scheduling with sequence-dependent exponential learning effects consideration, where two agents A and B have to share a single machine for processing their jobs. The objective function for agent A is to minimize the total completion time of jobs for agent A subject to a given upper bound on the objective function of agent B, representing the makespan of jobs for agent B. By assuming that the learning ratios for all jobs are the same, we suggest an enumeration-based backward allocation scheduling for finding an optimal solution and exemplify it by using a small numerical example. This problem has various applications in production systems as well as in operations management.

• Journal of Korea Society of Digital Industry and Information Management
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• v.16 no.2
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• pp.11-25
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• 2020

This study proposes a method to manipulate fragmentation of disks by arbitrarily allocating and releasing the status of a disk cluster in the NTFS file system. This method allows experiments to be performed in several studies related to fragmentation problems on disk cluster. Typical applicable research examples include testing the performance of disk defragmentation tools according to the state of fragmentation, establishing an experimental environment for fragmented file carving methods for digital forensics, setting up cluster fragmentation for testing the robustness of data hiding methods within directory indexes, and testing the file system's disk allocation methods according to the various version of Windows. This method suggests how a single file occupies a cluster and presents an algorithm with a flowchart. It raises three tricky problems to solve the method, and we propose solutions to the problems. Experiments for allocating the disk cluster to be fragmented to the maximum extent possible, it then performs a disk defragmentation experiment to prove the proposed method is effective.

• Journal of the Korean Statistical Society
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• v.35 no.2
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• pp.157-166
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• 2006

This research proposes an efficient Monte Carlo algorithm for computing error probability in high performance digital communication st stems. It characterizes special features of the problem and suggests an importance sampling algorithm specially designed to handle the problem. It uses a shifted exponential density as the importance sampling density, and shows an adaptive way of choosing the rate and the origin of the shifted exponential density. Instead of equal allocation, an intelligent allocation of the samples is proposed so that more samples are allocated to more important part of the error probability. The algorithm uses the nested feature of the error space and avoids redundancy in estimating the probability. The algorithm is applied to an example data set and shows a great improvement in accuracy of the error probability estimation.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2008.10a
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• pp.65-75
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• 2008

Over the last three decades, there are many researches focusing on the practice and theory of RM in airlines. Most of them have dealt with a seat assignment problem for maximizing the total revenue. In this study, we focus on a seat assignment problem in airlines. The seat assignment problem can be modeled as a stochastic programming model which is difficulty to solve optimally. However, with some assumptions on the demand distribution functions and a linear approximation technique, we can transform the complex stochastic programming model to a Linear Programming model. Some computational experiments are performed to evaluate out model with randomly generated data. They show that our model has a good performance comparing to existing models, and can be considered as a basis for further studies on improving existing seat assignment models.