• The Journal of the Korea Contents Association
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• v.21 no.7
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• pp.157-163
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• 2021

A single write operation in a file system can modify multiple data, but these changes in the file system are not atomically written to disk. Thus, for the consistency of the file system, conventional journaling guarantees crash consistency instead of sacrificing the system performance. It is known that using non-volatile memory as a journal space can alleviate performance degradation due to low latency and byte-level accessibility of non-volatile memory. However, none of the journaling techniques considering non-volatile memory provide scalability. In this paper, journal space on non-volatile memory is divided into multiple regions for scalable journaling, thus dispersing concentrated operations in one region. Second, the journal area-specific operator structure is used to accelerate data write operations to storage devices. We apply the proposed technique to JFS to evaluate it on multi-core servers equipped with high-performance storage devices. The evaluation results show that the proposed technique performs better than the existing technique of the NVM-based journaling file system.

• Nuclear Engineering and Technology
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• v.51 no.3
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• pp.807-817
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• 2019

Airborne Gamma Ray Spectrometry (AGRS) with its important applications such as gathering radiation information of ground surface, geochemistry measuring of the abundance of Potassium, Thorium and Uranium in outer earth layer, environmental and nuclear site surveillance has a key role in the field of nuclear science and human life. The Broyden-Fletcher-Goldfarb-Shanno (BFGS), with its advanced numerical unconstrained nonlinear optimization in collaboration with Artificial Neural Networks (ANNs) provides a noteworthy opportunity for modern AGRS. In this study a new AGRS system empowered by ANN-BFGS has been proposed and evaluated on available empirical AGRS data. To that effect different architectures of adaptive ANN-BFGS were implemented for a sort of published experimental AGRS outputs. The selected approach among of various training methods, with its low iteration cost and nondiagonal scaling allocation is a new powerful algorithm for AGRS data due to its inherent stochastic properties. Experiments were performed by different architectures and trainings, the selected scheme achieved the smallest number of epochs, the minimum Mean Square Error (MSE) and the maximum performance in compare with different types of optimization strategies and algorithms. The proposed method is capable to be implemented on a cost effective and minimum electronic equipment to present its real-time process, which will let it to be used on board a light Unmanned Aerial Vehicle (UAV). The advanced adaptation properties and models of neural network, the training of stochastic process and its implementation on DSP outstands an affordable, reliable and low cost AGRS design. The main outcome of the study shows this method increases the quality of curvature information of AGRS data while cost of the algorithm is reduced in each iteration so the proposed ANN-BFGS is a trustworthy appropriate model for Gamma-ray data reconstruction and analysis based on advanced novel artificial intelligence systems.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.68 no.1
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• pp.27-35
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• 2019

There is a growing interest in various microgrid solutions that supply electricity 24 hours a day to off-grid areas where are not connected with the main grid, and Korea has many positive effects by constructing overseas microgrids as a country operating the emission trading scheme. Since it is not clear how to obtain load curves that is one of the inputs of the HOMER used to design a microgrid optimization plan, or it is necessary to examine whether electricity is supplied to the peak load level of the areas where have not received the electricity benefits from the viewpoint of the demand management, a methodology should be developed to know the load composition ratio and the shape of the daily load curve. In this paper, the relative coefficient and average load information for each load group obtained from the survey are used besides peak load and total average load. A mathematical model is proposed to derive the load composition ratio in the form of a Quadratic Programming and the load forecasting is performed using simple linear regression with future indicators. The effectiveness of the proposed method is confirmed for the Philippine island region supported by Korea Energy Agency and the Asian Development Bank.

• Structural Monitoring and Maintenance
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• v.5 no.4
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• pp.463-488
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• 2018

In the last decades, research efforts have been spent to investigate the effect of prestressing on the dynamic behaviour of prestressed concrete (PSC) beams. Whereas no agreement has been reached among the achievements obtained by different Researchers and among the theoretical and the experimental results for simply supported beams, very few researches have addressed this problem in continuous PSC beams. This topic is, indeed, worthy of consideration bearing in mind that many relevant bridges and viaducts in the road and railway networks have been designed and constructed with this structural scheme. In this paper the attention is, thus, focused on the dynamic features of continuous PSC bridges taking into account the effect of prestressing. This latter, in fact, contributes to the modification of the distribution of the bending stress along the beam, also by means of the secondary moments, and influences the flexural stiffness of the beam itself. The dynamic properties of a continuous, two spans bridge connected by a nonlinear spring have been extracted by solving an eigenvalue problem in different linearized configurations corresponding to different values of the prestress force. The stiffness of the nonlinear spring has been calculated considering the mechanical behaviour of the PSC beam in the uncracked and in the cracked stage. The application of the proposed methodology to several case studies indicates that the shift from the uncracked to the cracked stage due to an excessive prestress loss is clearly detectable looking at the variation of the dynamic properties of the beam. In service conditions, this shift happens for low values of the prestress losses (up to 20%) for structure with a high value of the ratio between the permanent load and the total load, as happens for instance in long span, continuous box bridges. In such conditions, the detection of the dynamic properties can provide meaningful information regarding the structural state of the PSC beam.

• Journal of the Korean Society of Propulsion Engineers
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• v.22 no.5
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• pp.125-131
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• 2018

Some propellants in a liquid rocket engine are burned in the pre-burner of a staged combustion cycle engine, resulting hot gas drives the turbine. The burned gas passing through the turbine is supplied to the combustor at high temperature and pressure. The form of the gas can be fuel rich or oxidizer rich dependent upon the mixture ratio or the engine scheme. When the cycle works at oxidizer-rich condition, the metal pipes composing the engine can be ignited or even exploded by an impact of very a small particle. In this study, we developed the powder combination and processes for an anti-oxidation coating through the analysis of various coating materials.

• Journal of IKEEE
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• v.23 no.3
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• pp.852-857
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• 2019

In order to manage the demand resources of project participants and to provide appropriate strategies in the virtual power plant's power trading platform for consumers or operators who want to participate in the distributed resource collective trading market, it is very important to forecast the next day's demand of individual participants and the overall system's electricity demand. This paper developed a power demand forecasting model for the next day. For the model, we used LSTM algorithm of deep learning technique in consideration of time series characteristics of power demand forecasting data, and new scheme is applied by applying one-hot encoding method to input/output values such as power demand. In the performance evaluation for comparing the general DNN with our LSTM forecasting model, both model showed 4.50 and 1.89 of root mean square error, respectively, and our LSTM model showed high prediction accuracy.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.4
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• pp.453-461
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• 2019

In this paper, we focus on the study of multi-node rendezvous on one common channel among multiple channels before transmitting in CRAHNs (Cognitive Radio Ad-hoc Networks) for the efficient use of inefficient frequency resources. Most existing researches have dealt with the channel rendezvous between two nodes. But, it can be time-consuming to apply them to three or more nodes. In addition, it cab be impossible to communicate with each other. Therefore, in this paper, we propose a Multi-Node Sequence (MNSEQ), which allows three or more nodes to rendezvous on a single common channel in a short period of time. And, CSMA/CA was applied for data exchange after rendezvous. By performance evaluation through very extensive simulations, we have demonstrated that the proposed MNSEQ outperforms the existing scheme in terms of communication completion time and transmission efficiency.

• Convergence Security Journal
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• v.21 no.2
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• pp.29-35
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• 2021

UART (Universal asynchronous receiver/transmitter) is a hardware device that converts data into serial format and transmits it, and is widely used for system diagnosis and debugging in most embedded systems. Hackers can access system memory or firmware by using the functions of UART, and can take over the system by acquiring administrator rights of the system. In this paper, we studied secure UART to protect against hacker attacks through UART. In the proposed scheme, only authorized users using the promised UART communication protocol are allowed to access UART and unauthorized access is not allowed. In addition, data is encrypted and transmitted to prevent protocol analysis through sniffing. The proposed UART technique was implemented in an embedded Linux system and performance evaluation was performed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.10
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• pp.1337-1344
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• 2021

This paper presents an interactive educational game design procedure using the DGBL (Digital Game-based Learning) methodology that will help developers to design a multipurpose educational game. The DGBL consists of five stages, which are Analysis, Design, Development, Quality Assurance, and Implementation & Evaluation. This paper is focusing only on the specific technologies included in the Analysis and Design stages based on the DGBL. The first Analysis stage consists of gathering requirements, determining game ideation and learning objectives, and the second Design stage consists of defining the game architecture and database scheme. In this paper, we have designed a lecturers introduction game for a new student or freshmen as a case study to apply the Analysis and Design stages based on DGBL, as well as showing the prototype result in the form of a storyboard.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.5
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• pp.959-968
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• 2019

In the agricultural industry, wireless sensor network technology has being applied by utilizing various sensors and embedded systems. In particular, a lot of researches are being conducted to diagnose diseases of crops early by using sensor network. There are some difficulties on traditional research how to diagnose crop diseases is not practical for agriculture. This paper proposes the algorithm which enables to investigate and analyze the crop leaf image taken by image camera and detect the infected area within the image. We applied the enhanced k-means clustering method to the images captured at horticulture facility and categorized the areas in the image. Then we used the edge detection and edge tracking scheme to decide whether the extracted areas are located in inside of leaf or not. The performance was evaluated using the images capturing tomato leaves. The results of performance evaluation shows that the proposed algorithm outperforms the traditional algorithms in terms of classification capability.