• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.11a
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• pp.36-37
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• 2022

선박의 안천한 항해를 돕기 위하여 해상에 항로표지를 설치하여 운영하고 있다. 해상 ICT(Information and Communications Technology)의 발달로 AtoN AIS(Automatic Identification System) 및 CDMA(Code Division Multiple Access), LTE(Long Term Evolution) 등 다중통신망을 이용하여 항로표지의 상태를 감시하고 제어가 가능해짐에 따라 해양수산부에서는 항로표지 관리운영시스템을 운영하고 있다. e-Navigation 및 자율운항선박 분야 등에 항로표지 스마트화를 위해 정확한 항로표지 정보가 요구된다. 본 논문에서는 정확한 항로표지 정보 제공을 위해 관리운영시스템 표준소프트웨어 문제점을 분석하고 개선방안에 대해서 소개한다.

• Structural Engineering and Mechanics
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• v.53 no.3
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• pp.481-495
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• 2015

Many hydropower stations in southwest China are located in regions of brittle rock mass with high geo-stresses. Under these conditions deep fractured zones often occur in the sidewalls of the underground caverns of a power station. The theory and methods of fracture and damage mechanics are therefore adopted to study the phenomena. First a flexibility matrix is developed to describe initial geometric imperfections of a jointed rock mass. This model takes into account the area and orientation of the fractured surfaces of multiple joint sets, as well as spacing and density of joints. Using the assumption of the equivalent strain principle, a damage constitutive model is established based on the brittle fracture criterion. In addition the theory of fracture mechanics is applied to analyze the occurrence of secondary cracks during a cavern excavation. The failure criterion, for rock bridge coalescence and the damage evolution equation, has been derived and a new sub-program integrated into the FLAC-3D software. The model has then been applied to the stability analysis of an underground cavern group of a hydropower station in Sichuan province, China. The results of this method are compared with those obtained by using a conventional elasto-plastic model and splitting depth calculated by the splitting failure criterion proposed in a previous study. The results are also compared with the depth of the relaxation and fracture zone in the surrounding rock measured by field monitoring. The distribution of the splitting zone obtained both by the proposed model and by the field monitoring measurements are consistent to the validity of the theory developed herein.

• The Bulletin of The Korean Astronomical Society
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• v.39 no.2
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• pp.95-95
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• 2014

The mass measurement of neutron stars or black holes is of fundamental importance in our understanding of the evolution of massive stars and core-collapse supernova explosions as well as some exotic physics of the extreme conditions. Despite the importance, however, it's very difficult to measure mass of these objects directly. One way to do this, if they are in binary systems, to measure their binary motions (i.e., Doppler shifts) which can give us direct information on their mass. Recently many new highly-obscured massive X-ray binaries have been discovered by new hard X-ray satellites such as INTEGRAL and NuSTAR. The new highly-obscured massive X-ray binaries are faint in the optical, but bright in the infrared with many emission lines. Based on the near-infrared spectroscopy, one can first understand the nature of stellar companions to the compact objects, determining its spectral types and luminosity classes as well as mass losses and conditions of (potential) circumstellar material. Next, spectroscopic monitoring of these objects can be used to estimate the mass of compact objects via measuring the Doppler shifts of the lines. For the former, broad-band spectroscopy is essential; for the latter, high-resolution spectroscopy is critical. Therefore, IGRINS appears to be an ideal instrument to study them. An IGRINS survey of these new highly-obscured massive X-ray binaries can give us a rare opportunity to carry out population analyses for understanding the evolution of massive binary systems and formation of compact objects and their mass ranges. In this talk, we will present a sample near-infrared high resolution spectra of HMXB, IGR J19140+0951 and discuss about its spectral feature. These spectra are obtained on 13th July, 2014 from IGRINS commissioning run at McDonald 2.7m telescope. And at final, we will introduce the upgrade plan of IGRINS Operation Software (IGOS), to gather the input from IGRINS observer.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.3
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• pp.206-215
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• 2005

In this paper, we propose a new design method of Genetic Algorithm Processor(GAP) and Evolvable Hardware(EHW). All sorts of creature evolve its structure or shape in order to adapt itself to environments. Evolutionary Computation based on the process of natural selection not only searches the quasi-optimal solution through the evolution process, but also changes the structure to get best results. On the other hand, Genetic Algorithm(GA) is good fur finding solutions of complex optimization problems. However, it has a major drawback, which is its slow execution speed when is implemented in software of a conventional computer. Parallel processing has been one approach to overcome the speed problem of GA. In a point of view of GA, long bit string length caused the system of GA to spend much time that clear up the problem. Evolvable Hardware refers to the automation of electronic circuit design through artificial evolution, and is currently increased with the interested topic in a research domain and an engineering methodology. The studies of EHW generally use the XC6200 of Xilinx. The structure of XC6200 can configure with gate unit. Each unit has connected up, down, right and left cell. But the products can't use because had sterilized. So this paper uses Vertex-E (XCV2000E). The cell of FPGA is made up of Configuration Logic Block (CLB) and can't reconfigure with gate unit. This paper uses Vertex-E is composed of the component as cell of XC6200 cell in VertexE

• Journal of Information Processing Systems
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• v.14 no.3
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• pp.569-589
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• 2018

Cloud computing, also known as "country as you go", is used to turn any computer into a dematerialized architecture in which users can access different services. In addition to the daily evolution of stakeholders' number and beneficiaries, the imbalance between the virtual machines of data centers in a cloud environment impacts the performance as it decreases the hardware resources and the software's profitability. Our axis of research is the load balancing between a data center's virtual machines. It is used for reducing the degree of load imbalance between those machines in order to solve the problems caused by this technological evolution and ensure a greater quality of service. Our article focuses on two main phases: the pre-classification of tasks, according to the requested resources; and the classification of tasks into levels ('odd levels' or 'even levels') in ascending order based on the meta-heuristic "Bat-algorithm". The task allocation is based on levels provided by the bat-algorithm and through our mathematical functions, and we will divide our system into a number of virtual machines with nearly equal performance. Otherwise, we suggest different classes of virtual machines, but the condition is that each class should contain machines with similar characteristics compared to the existing binary search scheme.

• Journal of KIISE:Software and Applications
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• v.28 no.9
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• pp.669-680
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• 2001

Genetic Algorithms are optimization algorithm that mimics biological evolution to solve optimization problems. Genetic algorithms provide an alternative to traditional optimization techniques by using directed random searches to locate optimal solutions in complex fitness landscapes. Hybrid genetic algorithm that is combined with local search called learning can sustain the balance between exploration and exploitation. The genetic traits that each individual in the population learns through evolution are transferred back to the next generation, and when this learning is combined with genetic algorithm we can expect the improvement of the search speed. This paper proposes a genetic algorithm based Cellular Learning with accelerated learning capability for function optimization. Proposed Cellular Learning strategy is based on periodic and convergent behaviors in cellular automata, and on the theory of transmitting to offspring the knowledge and experience that organisms acquire in their lifetime. We compared the search efficiency of Cellular Learning strategy with those of Lamarckian and Baldwin Effect in hybrid genetic algorithm. We showed that the local improvement by cellular learning could enhance the global performance higher by evaluating their performance through the experiment of various test bed functions and also showed that proposed learning strategy could find out the better global optima than conventional method.

• Journal of Digital Convergence
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• v.10 no.10
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• pp.523-528
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• 2012

The recent appearance and evolution of cloud service including IaaS(Infrastructure as a Service), PaaS(Platform as a Service) and SaaS(Software as a Service) is potentially one of the major advances in information and communication technology. While a lot of studies are currently taking place in the technology itself, there is an equally urgent need for understanding and researching the business-related issues surrounding cloud service. As more and more individuals and companies use the cloud service, their concerns are beginning to grow about just how safe and reliable an environment it is. This paper focus on SaaS as an one of the important cloud service. For successful implementation of SaaS service, it is necessary to establish the certification systems to ensure safety and reliability of SaaS. This paper provides the safe and reliable framework for systematic SaaS certification systems. In order to develop it, the critical issues related to service quality and certification of SaaS service are identified and the systematic framework for certification systems of SaaS service and service provider domains are developed. An evaluation methodology for the developed certification systems is also proposed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.8
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• pp.3474-3497
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• 2016

Network Function Virtualization (NFV) and Software Defined Networking (SDN) are recently considered as very promising drivers of the evolution of existing middlebox services, which play intrinsic and fundamental roles in today's networks. To address the virtual service deployment issues that caused by introducing NFV or SDN to networks, this paper proposes an optimal solution by combining quantum genetic algorithm with cooperative game theory. Specifically, we first state the concrete content of the service deployment problem and describe the system framework based on the architecture of SDN. Second, for the service location placement sub-problem, an integer linear programming model is built, which aims at minimizing the network transport delay by selecting suitable service locations, and then a heuristic solution is designed based on the improved quantum genetic algorithm. Third, for the service amount placement sub-problem, we apply the rigorous cooperative game-theoretic approach to build the mathematical model, and implement a distributed algorithm corresponding to Nash bargaining solution. Finally, experimental results show that our proposed method can calculate automatically the optimized placement locations, which reduces 30% of the average traffic delay compared to that of the random placement scheme. Meanwhile, the service amount placement approach can achieve the performance that the average metric values of satisfaction degree and fairness index reach above 90%. And evaluation results demonstrate that our proposed mechanism has a comprehensive advantage for network application.

• Journal of Korea Multimedia Society
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• v.21 no.2
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• pp.188-198
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• 2018

With recent development of high-speed wide-area wireless networks and wide spread of highperformance wireless devices, the demand on seamless video streaming services in Long Term Evolution (LTE) network environments is ever increasing. To meet the demand and provide enhanced Quality of Experience (QoE) with mobile users, the Dynamic Adaptive Streaming over HTTP (DASH) has been actively studied to achieve QoE enhanced video streaming service in dynamic network environments. However, the existing DASH algorithm to select the quality of requesting video segments is based on a procedural algorithm so that it reveals a limitation to adapt its performance to dynamic network situations. To overcome this limitation this paper proposes a novel quality selection mechanism based on a Deep Q-Network (DQN) model, the DQN-based DASH ABR($DQN_{ABR}$) mechanism. The $DQN_{ABR}$ mechanism replaces the existing DASH ABR algorithm with an intelligent deep learning model which optimizes service quality to mobile users through reinforcement learning. Compared to the existing approaches, the experimental analysis shows that the proposed solution outperforms in terms of adapting to dynamic wireless network situations and improving QoE experience of end users.

• Nuclear Engineering and Technology
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• v.53 no.5
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• pp.1540-1555
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• 2021

The plate-type fuel assembly adopted in nuclear research reactor suffers from complicated effect induced by non-uniform irradiation, which might affect its stress conditions, mechanical behavior and thermal-hydraulic performance. A reliable numerical method is of great importance to reveal the complex evolution of mechanical deformation, flow redistribution and temperature field for the plate-type fuel assembly under non-uniform irradiation. This paper is the first part of a two-part study developing the numerical methodology for the thermal-fluid-structure coupling behaviors of plate-type fuel assembly under irradiation. In this paper, the thermal-fluid-structure coupling methodology has been developed for plate-type fuel assembly under non-uniform irradiation condition by exchanging thermal-hydraulic and mechanical deformation parameters between Finite Element Model (FEM) software and Computational Fluid Dynamic (CFD) software with Mesh-based parallel Code Coupling Interface (MpCCI), which has been validated with experimental results. Based on the established methodology, the effects of non-uniform irradiation and fluid were discussed, which demonstrated that the maximum mechanical deformation with irradiation was dozens of times larger than that without irradiation and the hydraulic load on fuel plates due to differential pressure played a dominant role in the mechanical deformation.