• Journal of Broadcast Engineering
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• v.6 no.3
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• pp.246-259
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• 2001

Due to recent rapid deployment of Internet streaming service and digital broadcasting service, the issue of how to efficiently support streaming workload in so called "Internet Home Appliance" receives prime interests from industry as well as academia. The underlying dilemma is that it may not be feasible to put cutting edge CPU, boards, disks and other peripherals into that type of device. The primary reason is its cost. Usually, Internet Home Appliances has its dedicated usage, e.g. Internet Radio, and thus it does not require high-end CPU nor high-end Va subsystem. The same reasoning applies to I/O subsystem. In Internet Home Appliances dedicated to handle compressed moving picture, it is not equipped with high end SCSI disk with fast rotational speed. Thus, it is mandatory to devise elaborate software algorithm to exploit the available hardware resources and maximize the efficiency of the system. This paper presents our experiences in the design and implementation of a new multimedia file system which can efficiently deliver the required disk bandwidth for a periodic I/O workload. We have implemented the file system on the Linux operating system, and examined itsperformance under streaming I/O workload. The results of the study show that the proposed file system exhibits superior performance than the Linux Ext2 file system under streaming I/O workload. The result of this work not only contribute to advance the state f art file system technology for multimedia streaming but also put forth the software which is readily available and can be deployed. deployed.

• Journal of KIISE:Information Networking
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• v.33 no.6
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• pp.407-419
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• 2006

As substituting IPv6 network for all IPv4 network in a short time seems unattainable due to high cost and technical limitation, IPv4 and IPv6 are expected to coexist for a certain period of time. Under the co]existing environment of IPv4 and IPv6, interworking brings a number of extra security considerations even if it may have no security problem for each protocol respectively. Thus, the analysis and solutions for those various attacks toward IPv4/IPv6 interworking-related security are inevitably required for the sake of effective transition and settlement to IPv6. In this paper we carried out a proper rule of packet filtering for IPv6-in-IPv4 tunneling interworking environment to protect the IPv4/IPv6 interworking-related security attacks. Design and implementation of the packet filtering system suitable for IPv4/IPv6 tunneling environment in the form of Linux netfilter and ip6tables are also shown. Thru this study, the packet filtering system was found operating correctly ill the tunneling mechanism.

• Journal of KIISE:Software and Applications
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• v.29 no.7
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• pp.436-449
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• 2002

This paper describes on our experience of developing the Database Connector as an interconnection method between multimedia database, and the streaming framework. It is possible to support diverse and mature multimedia database services such as retrieval and join operation during the streaming if an interconnection method is provided in between streaming system and multimedia databases. The currently available interconnection schemes, however have mainly used the file systems or the relational databases that are Implemented with separated form of meta data, which deafs with information of multimedia contents, and streaming data which deals with multimedia data itself. Consequently, existing interconnection mechanisms could not come up with many virtues of multimedia database services during the streaming operation. In order to resolve these drawbacks, we propose a novel scheme for an interconnection between streaming framework and multimedia database, called the Inter-Process Communication (IPC) based Database connector, under the assumption that two systems are located in a same host. We define four transaction primitives; Read, Write, Find, Play, as well as define the interface for transactions that are implemented based on the plug-in, which in consequence can extend to other multimedia databases that will come for some later years. Our simulation study show that performance of the proposed IPC based interconnection scheme is not much far behind compared with that of file systems.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.6
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• pp.722-728
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• 2012

Urban sewer systems has a limitation of capacity of rainwater storage and problem of occurrence of untreated sewage, so adopting a storage facility for sewer flooding prevention and urban non-point pollution reduction has a big attention. The Korea Ministry of Environment has recently introduced a new concept of "multi-functional storage facility", which is crucial not only in preventive stormwater management but also in dealing with combined sewer overflow and sanitary sewer discharge, and also has been promoting its adoption. However, reserving a space for a single large-scale storage facility might be difficult especially in urban areas. Thus, decentralized construction of small- and midium-sized storage facilities and its operation have been introduced as an alternative way. In this paper, we propose a model predictive control scheme for an optimized operation of distributed storage facilities and sewer networks. To this aim, we first describe the mathematical model of each component of networks system which enables us to analyze its detailed dynamic behavior. Second, overflow locations and volumes will be predicted based on the developed network model with data on the external inflow occurred at specific locations of the network. MPC scheme based on the introduced particle swarm optimization technique then produces the optimized the gate setting for sewer network flow control, which minimizes sewer flooding and maximizes the potential storage capacity. Finally, the operational efficacy of the proposed control scheme is demonstrated by simulation study with virtual rainstorm event.

• The Journal of the Korea Contents Association
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• v.19 no.5
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• pp.553-561
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• 2019

In this study, the method of quality measurement for the statistical usefulness of de-identified data was examined in terms of prediction accuracy by statistical modeling. In the era of the 4th industrial revolution, effective use of big data is essential to innovation through information and communication technology, but personal information issues are constrained to actively utilize big data. In order to solve this problem, de-identification guidelines have been established and the possibility of actual re-identification of personal information has become very low due to the utilization of various de-identification methods. On the other hand, strong de-identification can have side effects that degrade the usefulness of the data. We have studied the quality of statistical usefulness of the de-identified data by KLT model which is a representative de-identification method, A case study was conducted to see how statistical accuracy of prediction is degraded by de-identification. We also proposed a new measure of data usefulness of the de-identified data by quantifying how much data is added to the de-identified data to restore the accuracy of the predictive model.

• Geophysics and Geophysical Exploration
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• v.26 no.3
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• pp.114-125
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• 2023

The physics-informed neural network (PINN) has been proposed to overcome the limitations of various numerical methods used to solve partial differential equations (PDEs) and the drawbacks of purely data-driven machine learning. The PINN directly applies PDEs to the construction of the loss function, introducing physical constraints to machine learning training. This technique can also be applied to wave equation modeling. However, to solve the wave equation using the PINN, second-order differentiations with respect to input data must be performed during neural network training, and the resulting wavefields contain complex dynamical phenomena, requiring careful strategies. This tutorial elucidates the fundamental concepts of the PINN and discusses considerations for wave equation modeling using the PINN approach. These considerations include spatial coordinate normalization, the selection of activation functions, and strategies for incorporating physics loss. Our experimental results demonstrated that normalizing the spatial coordinates of the training data leads to a more accurate reflection of initial conditions in neural network training for wave equation modeling. Furthermore, the characteristics of various functions were compared to select an appropriate activation function for wavefield prediction using neural networks. These comparisons focused on their differentiation with respect to input data and their convergence properties. Finally, the results of two scenarios for incorporating physics loss into the loss function during neural network training were compared. Through numerical experiments, a curriculum-based learning strategy, applying physics loss after the initial training steps, was more effective than utilizing physics loss from the early training steps. In addition, the effectiveness of the PINN technique was confirmed by comparing these results with those of training without any use of physics loss.

• Journal of the Korean Geotechnical Society
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• v.24 no.10
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• pp.83-91
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• 2008

Previous settlement prediction methods based on settlement monitoring were developed under instantaneous loading condition and have restriction to be applied to soft ground under ramp loading condition. In this study, settlement prediction method under ramp loading was developed. New settlement prediction method under ramp loading considered influence factors of consolidation settlement such as thickness of clayed layer, quantity of surcharge load and preconsolidation pressure, etc. Geometrical correction method based on hyperbolic method (1991) and correction method based on probability theory were applied to increase accuracy of settlement prediction using field monitoring data after ramp loading. Large consolidation tests for ideally controlled one dimensional consolidation under ramp loading condition were performed and the settlement behavior was predicted based on the monitoring data. New prediction method yielded good result of entire settlement behavior by using data during an early stage of ramp load. Additionally, new prediction method offered better settlement prediction which had final settlement prediction in close proximity and low RMSE(Root Mean Square Error) than previous method such as hyperbolic method did.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.6
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• pp.785-791
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• 2023

Risk management is essential for preventing accidents arising from uncertainties in TBM tunnel projects, especially concerning managing the risk of TBM tunnel collapse, which can cause extensive damage from the tunnel face to the ground surface. In addition, prioritizing risks is necessary to allocate resources efficiently within time and cost constraints. Therefore, this study aimed to establish a TBM risk database through case studies of TBM accidents and determine a risk priority for TBM tunnel collapse using the Bayes theorem. The database consisted of 87 cases, dealing with three accidents and five geological sources. Applying the Bayes theorem to the database, it was found that fault zones and weak ground significantly increased the probability of tunnel collapse, while the other sources showed low correlations with collapse. Therefore, the risk priority for TBM tunnel collapse, considering geological sources, is as follows: 1) Fault zone, 2) Weak ground, 3) Mixed ground, 4) High in-situ stress, and 5) Expansive ground. In practice, the derived risk priority can serve as a valuable reference for risk management, enhancing the safety and efficiency of TBM construction. It provides guidance for developing appropriate countermeasure plans and allocating resources effectively to mitigate the risk of TBM tunnel collapse.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.6
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• pp.536-542
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• 2023

Satellites represent cutting-edge technology, of ering significant advantages in spatial and temporal observations. National agencies worldwide harness satellite data to respond to marine accidents and analyze ocean fluctuations effectively. However, challenges arise with high-resolution satellite-based sea surface temperature data (Operational Sea Surface Temperature and Sea Ice Analysis, OSTIA), where gaps or empty areas may occur due to satellite instrumentation, geographical errors, and cloud cover. These issues can take several hours to rectify. This study addressed the issue of missing OSTIA data by employing LaMa, the latest deep learning-based algorithm. We evaluated its performance by comparing it to three existing image processing techniques. The results of this evaluation, using the coefficient of determination (R²) and mean absolute error (MAE) values, demonstrated the superior performance of the LaMa algorithm. It consistently achieved R² values of 0.9 or higher and kept MAE values under 0.5 ℃ or less. This outperformed the traditional methods, including bilinear interpolation, bicubic interpolation, and DeepFill v1 techniques. We plan to evaluate the feasibility of integrating the LaMa technique into an operational satellite data provision system.

• Journal of Wetlands Research
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• v.26 no.1
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• pp.41-50
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• 2024

Plant Microbial Fuel Cells (P-MFCs) are biomass-based energy technologies that generate electricity from plant and root microbial communities and are suitable for natural fundamental solutions considering sustainable environments. In order to develop P-MFC technology suitable for domestic waterfront space, it is necessary to analyze international research trends first. Therefore, in this study, 700 P-MFC-related research papers were investigated in Web of Science, and the core keywords were derived using VOSviewer, a word analysis program, and the research trends were analyzed. First, P-MFC-related research has been on the rise since 1998, especially since the mid to late 2010s. The number of papers submitted by each country was "China," "U.S." and "India." Since the 2010s, interest in P-MFCs has increased, and the number of publications in the Philippines, Ukraine, and Mexico, which have abundant waterfront space and wetland environments, is increasing. Secondly, from the perspective of research trends in different periods, 1998-2015 mainly carried out microbial fuel cell performance verification research in different environments. The 2016-2020 period focuses on the specific conditions of microbial fuel cell use, the structure of P-MFC and how it develops. From 2021 to 2023, specific research on constraints and efficiency improvement in the development of P-MFC was carried out. The P-MFC-related international research trends identified through this study can be used as useful data for developing technologies suitable for domestic waterfront space in the future. In addition to this study, further research is needed on research trends and levels in subsectors, and in order to develop and revitalize P-MFC technologies in Korea, research on field applicability should be expanded and policies and systems improved.