• Journal of Navigation and Port Research
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• v.45 no.3
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• pp.87-94
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• 2021

The IMO has adopted emission standards that strictly restrict the use of bunker C oil for vessels. Accordingly, research and bunkering pilot projects for LNG fueled ships are being actively carried out, which is expected to substantially reduce environmental pollution. In this study, we have adopted the turret moored Floating LNG Bunkering Terminal (FLBT) designed to receive the LNG from LNGCs and to transfer LNG to LNG bunkering shuttles in ship to ship moored condition. Numerical simulations have been performed with a 1-year return period of wind, wave, and current. Damping values of numerical model were adjusted from the results of model tests to obtain accurate simulation results. The results confirm safe berthing operation during the 1-year return period of environmental condition. Safety depends on the direction of environment, with increasingly stable operation facilitated by the application of heading-control function of FLBT to avoid beam-sea conditions.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.1
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• pp.93-98
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• 2021

Due to the development of deep learning and AI, the scale of the model has grown, and it has been integrated into other fields to blend into our lives. However, in environments with limited resources such as embedded devices, it is exist difficult to apply the model and problems such as power shortages. To solve this, lightweight methods such as clouding or offloading technologies, reducing the number of parameters in the model, or optimising calculations are proposed. In this paper, quantization of learned models is applied to ONNX models used in various framework interchange formats, neural network structure and inference performance are compared with existing models, and various module methods for quantization are analyzed. Experiments show that the size of weight parameter is compressed and the inference time is more optimized than before compared to the original model.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.5
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• pp.17-22
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• 2022

In this paper, we design a lightweight embedded device that can support intelligent edge computing, and show that the device quickly detects an object in an image input from a camera device in real time. The proposed system can be applied to environments without pre-installed infrastructure, such as an intelligent video control system for industrial sites or military areas, or video security systems mounted on autonomous vehicles such as drones. The On-Device AI(Artificial intelligence) technology is increasingly required for the widespread application of intelligent vision recognition systems. Computing offloading from an image data acquisition device to a nearby edge device enables fast service with less network and system resources than AI services performed in the cloud. In addition, it is expected to be safely applied to various industries as it can reduce the attack surface vulnerable to various hacking attacks and minimize the disclosure of sensitive data.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.5
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• pp.786-792
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• 2022

In the cloud computing environment, there has been a lot of research into the Fog/Edge Computing (FEC) paradigm for securing user proximity of application services and computation offloading to alleviate service delay difficulties. The method of predicting dynamic location change patterns of edge devices (moving objects) requesting application services is critical in this FEC environment for efficient computing resource distribution and deployment. This paper proposes an optimal moving pattern extraction algorithm in which variable weights (distance, time, congestion) are applied to selected paths in addition to a support factor threshold for frequency patterns (moving objects) of edge devices. The proposed algorithm is compared to the OPE_freq [8] algorithm, which just applies frequency, as well as the A^* and Dijkstra algorithms, and it can be shown that the execution time and number of nodes accessed are reduced, and a more accurate path is extracted through experiments.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.4
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• pp.77-82
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• 2024

Recent advancements in artificial intelligence (AI) technology have led to an increase in the implementation of AI applications in mobile environments. However, due to the limited resources in mobile devices compared to desktops and servers, there is growing interest in research aimed at efficiently executing AI workloads on mobile platforms. While most studies focus on offloading to edge or cloud solutions to mitigate computing resource constraints, research on the characteristics of file I/O related to storage access in mobile settings remains underexplored. This paper analyzes file I/O traces generated during the execution of deep learning applications in mobile environments and investigates how they differ from traditional mobile workloads. We anticipate that the findings of this study will be utilized to design future smartphone system software more efficiently, considering the file access characteristics of deep learning.

• Journal of the Korean Society of Marine Environment & Safety
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• v.22 no.1
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• pp.129-137
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• 2016

In the present study we verified performance of feed-forward control algorithm using short term prediction of ship motion information by taking advantage of developed numerical simulation model of FPSO motion. Up until now, various studies have been conducted about thrust control and allocation for dynamic positioning systems maintaining positions of ships or marine structures in diverse sea environmental conditions. In the existing studies, however, the dynamic positioning systems consist of only feedback control gains using a motion of vessel derived from environmental loads such as current, wind and wave. This study addresses dynamic positioning systems which have feedforward control gain derived from forecasted value of a motion of vessel occurred by current, wind and wave force. In this study, the future motion of vessel is forecasted via Brown's Exponential Smoothing after calculating the vessel motion via a selected mathematical model, and the control force for maintaining the position and heading angle of a vessel is decided by the feedback controller and the feedforward controller using PID theory and forecasted vessel motion respectively. For the allocation of thrusts, the Lagrange Multiplier Method is exploited. By constructing a simulation code for a dynamic positioning system of FPSO, the performance of feedforward control system which has feedback controller and feedforward controller was assessed. According to the result of this study, in case of using feedforward control system, it shows smaller maximum thrust power than using conventional feedback control system.

• Journal of the Korean Society of Marine Environment & Safety
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• v.22 no.7
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• pp.900-905
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• 2016

The field of power system harmonics has been receiving a great deal of attention recently. This is primarily due to the fact that non-linear (or harmonic-producing) loads comprise an ever-increasing portion of what is handled at a typical industrial plant. The incidence rate of harmonic-related problems is low, but awareness of harmonic issues can still help increase offshore power plant system reliability. On the rare occasion that harmonics become a problem, this is either due to the magnitude of harmonics produced or power system resonance. This harmonic study used an electrical configuration for the offloading scenario of a Floating LNG (FLNG) unit, considering power load. This electrical network configuration is visible in the electrical network load flow study part of the project. This study has been carried out to evaluate the performance of an electric power system, focusing on the harmonic efficiency of an electrically driven motor system to ensure offshore plant safety. In addition, the design part of this study analyzed the electric power system of an FLNG unit to improve the safety of operation and maintenance.

• Journal of Navigation and Port Research
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• v.42 no.1
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• pp.9-16
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• 2018

The development of limited petroleum resources for use with mankind inevitably explores and seeks to develop oil fields in the deep sea area, under the rise of the oil prices market situation. The use of Oceanic Thermal Energy Conversion (OTEC) technology, which operates the power generation facility using the temperature differences between the deep water and the surface water, is progressing actively as a trend to follow. In this study, the application of the Discharged Thermal Energy Conversion (DTEC) was designed and analyzed under the condition that the supply condition of seawater used in the FPSO installed in the deep sea area is changed up to 400m depth. In this case, it was confirmed that the design of the system that can generate more electric power according to the depth of water is confirmed, by thus applying the DTEC system by taking the cooling water at a deeper water depth than the existing design water depth. The FPSO considers the similarity of the OTEC power generation facilities, and will apply the DTEC system to FPSO in the deep sea area to accumulate technology and the conversion to further utilize the OTEC power generation facilities after the end of life cycle of oil production, which could be a solution to two important issues, namely, resource development and sustainable development.

• Journal of KIISE:Computer Systems and Theory
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• v.31 no.11
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• pp.626-634
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• 2004

In a client-server model, network server systems suffer from both heavy communication and computational loads. While communication channels become increasingly speedy, the existing protocol stack architectures still include mainly three performance bottlenecks of protocol stack processing, system call, and network interrupt overheads. To address these obstacles, in this paper we present a host-independent network system where a network interface card (NIC) is utilized in an efficient manner. First, by offloading network-related portion to the NIC, the host can fully utilize its processing power for other useful purposes. Second, it eliminates the system call overhead, such as context-switching and memory copy operations, since the host communicates with the NIC through its user-level libraries. Third, it a] so reduces the network interrupt operation count as the host handles the interrupt in a segment instead of a packet. The experimental results show that the proposed network system reduces the host CPU overhead for communication system by 68-71%. It also shows that the proposed system improves the communication speed by 11-83% under heavy computational and communication load conditions.

• Journal of the Korean Institute of Gas
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• v.19 no.2
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• pp.74-82
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• 2015

Carbon dioxide was designated as one of greenhouse gases that cause global warming. Among various ways to solve the $CO_2$ emission issue, the 3rd-generation biomass (algae) production is considered as a viable method to reduce $CO_2$ in the atmosphere. In this research, we propose a design of an innovative sustainable production system by utilizing the 3rd generation biomass in the environment of floating production storage and offloading (FPSO). Existing biomass production systems depend on the solar energy and they cannot continue producing biomass at night. Electricity produced from offshore wind farms also need an efficient way to store the energy through energy storage system (ESS) or deliver it real-time through power grid, both requiring heavy investment of capital. Thus, we design an offshore grid structure harnessing LED lights to supply the necessary light energy, by using the electricity produced from the wind farm, resulting in the maximized production of biomass and efficient use of wind farm energy. The final design integrates the biomass production system enhanced by LED lights with a wind power generation. The suggested NLP model for the optimal design, implemented in GAMS, would be useful for designing improved offshore biomass production systems combined with the wind farm.