• Proceedings of the Korean Institute of Surface Engineering Conference
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• 1998.05a
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• pp.160-161
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• 1998

• Bulletin of the Korean Mathematical Society
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• v.59 no.5
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• pp.1105-1117
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• 2022

In this paper, we obtain a second main theorem for holomorphic curves and moving hyperplanes of Pⁿ(C) where the counting functions are truncated multiplicity and have different weights. As its application, we prove a uniqueness theorem for holomorphic curves of finite growth index sharing moving hyperplanes with different multiple values.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.11
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• pp.4347-4366
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• 2015

Distinguished with traditional strategies which offload an application's computation to a single server, parallel computation offloading can promote the performance by simultaneously delivering the computation to multiple computing resources around the mobile terminal. However, due to the variability of communication and computation environments, static application component multi-partitioning algorithms are difficult to maintain the optimality of their solutions in time-varying scenarios, whereas, over-frequent algorithm executions triggered by changes of environments may bring excessive algorithm costs. To this end, an adaptive application component mapping algorithm for parallel computation offloading in variable environments is proposed in this paper, which aims at minimizing computation costs and inter-resource communication costs. It can provide the terminal a suitable solution for the current environment with a low incremental algorithm cost. We represent the application component multi-partitioning problem as a graph mapping model, then convert it into a pathfinding problem. A genetic algorithm enhanced by an elite-based immigrants mechanism is designed to obtain the solution adaptively, which can dynamically adjust the precision of the solution and boost the searching speed as transmission and processing speeds change. Simulation results demonstrate that our algorithm can promote the performance efficiently, and it is superior to the traditional approaches under variable environments to a large extent.

• Proceedings of the KIPE Conference
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• 2018.07a
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• pp.522-524
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• 2018

A New Direct AC LED Driver has been proposed for wide output power range and precise constant current regulation using an advanced auto commutation topology. The conventional shunt regulation method provides a stepped input current shape by fixed regulation references in the linear regulator of the each channel, which results in poor current regulation and high THD. The conventional method needs to assign a linear regulator in each LED channel so that the number of linear regulator increases when extending the number of channels especially at high power application. The proposed regulation method can drive multiple switches to regulate each LED channel current by a single amplifier with sinusoidal reference so that large number of LED channel can be simply extended with less BOM cost and low THD is obtained with the accurate current regulation thanks to the sinusoidal input current control in the closed loop control. To confirm the validity of the proposed circuit, theoretical analysis and experimental results from a 20-W LED driver prototype are presented.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.14 no.4
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• pp.257-264
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• 2002

This paper is concerned with the analysis of wave reflection and transmission from multiple floating breakwaters. Linear potential theory was used for modeling wave field, and the behaviors of the floating breakwaters was represented as linearized equation of motions. The boundary value problem for the wave field was discretized by Galerkin technique. The radiation condition at infinity was modeled as infinite elements developed by Park et al.(1991). The validation of the developed model was given through the comparison with hydraulic experimental data conducted by Park et al.(2000). The possibility for the application of multiple floating breakwaters was also discussed based on the numerical experiments.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.3 no.2 s.5
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• pp.9-17
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• 2004

In this paper, we examine the MIMO(Multiple Input Multiple Output) system in the point of mobile communication that is used for railway environment. First, under the radio environment, wireless channel characteristics are analyzed between moving train and base station, both assuming track side base stations and non-track side base stations. Next, the paper introduces the MIMO system which can be used to solve the problem of performance degradation in railway environment, and analyzes its performance in terms of channel capacity and diversity. We especially compares open-loop scheme with closed loop scheme at the diversity and analyses their performance according to antenna correlation. Finally, the we presents experimental result from the ESCORT project that was studied in railway environment with the MIMO system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.2
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• pp.702-723
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• 2020

The application of machine learning (ML) in intrusion detection has attracted much attention with the rapid growth of information security threat. As an efficient multi-label classifier, kernel extreme learning machine (KELM) has been gradually used in intrusion detection system. However, the performance of KELM heavily relies on the kernel selection. In this paper, a novel multiple kernel extreme learning machine (MKELM) model combining the ReliefF with nature-inspired methods is proposed for intrusion detection. The MKELM is designed to estimate whether the attack is carried out and the ReliefF is used as a preprocessor of MKELM to select appropriate features. In addition, the nature-inspired methods whose fitness functions are defined based on the kernel alignment are employed to build the optimal composite kernel in the MKELM. The KDD99, NSL and Kyoto datasets are used to evaluate the performance of the model. The experimental results indicate that the optimal composite kernel function can be determined by using any heuristic optimization method, including PSO, GA, GWO, BA and DE. Since the filter-based feature selection method is combined with the multiple kernel learning approach independent of the classifier, the proposed model can have a good performance while saving a lot of training time.

• Current Industrial and Technological Trends in Aerospace
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• v.7 no.1
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• pp.141-152
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• 2009

The simultaneous operation of multiple UAV's makes it possible for us to raise the mission accomplishment and cost efficiency. For this we need an easily scalable control algorithm, and swarm intelligence having the characteristics such as flexibility, robustness, decentralized control and self-organization comes into the spotlight as a practical substitute. In this paper the features of swarm intelligence are described, and various research results are introduced which show that the application of swarm intelligence to the control of multiple UAV's enables the missions of surveillance, path planning, target tracking and attack to be accomplished efficiently by simulations and tests.

• Journal of Korean Institute of Industrial Engineers
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• v.32 no.3
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• pp.226-235
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• 2006

Telematics is expected to be one of the fastest growing businesses in information technology area. It may create a new emerging market in industry related to automotive, telecommunications, and information services. Especially vehicle navigation service is considered as a killer application among telematics service applications. The current vehicle navigation service typically recommends a single path that is based on the traveling time or distance from the origin to the destination. The system provides two options for users to choose either via highway or via any road. Since the traffics and road conditions of big cities are very complicated and dynamic, the demand of multi-path guidance system is increasing in telematics market. The multi-path guidance system should allow drivers to choose a path based on their individual preferences such as traveling time, distance, or route familiarity. Using the Lawler's algorithm, it is possible to find multiple paths; however, due to the lengthy computational time, it is not suitable for the real-time services. This study suggests a computationally feasible and efficient heuristic multiple paths finding algorithm that is reliable for the real-time vehicle navigation services.

• Journal of the Korean Operations Research and Management Science Society
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• v.39 no.4
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• pp.51-69
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• 2014

Times to multiple events (TMEs) are a major data type in large-scale business and medical data. Despite its importance, the analysis of TME data has not been well studied because of the analysis difficulty from censoring of observation. To address this difficulty, we have developed a Bayesian-based multivariate survival analysis method, which can successfully estimate the joint probability density of survival times. In this work, we extended this method for the analysis of precedence, dependency and causality among multiple events. We applied this method to the electronic health records of 2,111 patients in a children's hospital in the US and the proposed analysis successfully shows the relation between times to two types of hospital visits for different medical issues. The overall result implies the usefulness of the multivariate survival analysis method in large-scale big data in a variety of areas including marketing, human resources, and e-commerce. Lastly, we suggest our future research directions based multivariate survival analysis method.