• Proceedings of the Korean Society of Computer Information Conference
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• 2014.01a
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• pp.9-13
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• 2014

The performance of large scale software applications has been automatically increasing for last few decades under the influence of Moore's law - the number of transistors on a microprocessor roughly doubled every eighteen months. However, on-chip transistors limitations and heating issues led to the emergence of multicore processors. The energy efficient ARM based System-on-Chip (SoC) processors are being considered for future high performance computing systems. In this paper, we present a case study of two widely used parallel programming models i.e. MPI and MapReduce on distributed memory cluster of ARM SoC development boards. The case study application, Black-Scholes option pricing equation, was parallelized and evaluated in terms of power consumption and throughput. The results show that the Hadoop implementation has low instantaneous power consumption that of MPI, but MPI outperforms Hadoop implementation by a factor of 1.46 in terms of total power consumption to execution time ratio.

• Structural Engineering and Mechanics
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• v.71 no.3
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• pp.317-327
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• 2019

The aim of this paper is to present the most important issues on the implementation, operation and maintenance of foundation for machines. The article presents the newest solutions both in terms of technology implementation as well as materials used in construction of such structures. Foundations for machines are special building structures used to transfer loads from an operating machine to the subsoil. The purpose of these foundations is not just to transfer loads, but also to reduce vibrations occurring during operation of the machine, i.e. their damping and preventing redistribution to other elements of the building. It should be noted that foundations for machines (particularly foundations for hammers) are the most dynamically loaded building structures. For these reasons, they require precise static and dynamic calculations, accuracy in their implementation and care for them after they have been made. Therefore, the paper in detail present the guidelines regarding: design, construction and maintenance of structures of this type. Furthermore, the most important parameters and characteristics of materials used for the construction of these foundations are described. As a result of the conducted analyzes, it was found that the concrete mix, in foundations for machines, should have a low water/binder ratio. For its execution, it is necessary to use broken aggregates from igneous rocks and binders modified with mineral additives and chemical admixtures. On the other hand, the reinforcement of composites should contain a large amount of structural reinforcement to prevent shrinkage cracks.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.12
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• pp.4364-4384
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• 2021

The dynamic network state and the mobility of the terminals make the service function chain (SFC) orchestration mechanisms based on static and deterministic assumptions hard to be applied in SDN/NFV mobile edge computing networks. Designing dynamic and online SFC orchestration mechanism can greatly improve the execution efficiency of compute-intensive and resource-hungry applications in mobile edge computing networks. In order to increase the overall profit of service provider and reduce the resource cost, the system running time is divided into a sequence of time slots and a dynamic orchestration scheme based on an improved column generation algorithm is proposed in each slot. Firstly, the SFC dynamic orchestration problem is formulated as an integer linear programming (ILP) model based on layered graph. Then, in order to reduce the computation costs, a column generation model is used to simplify the ILP model. Finally, a two-stage heuristic algorithm based on greedy strategy is proposed. Four metrics are defined and the performance of the proposed algorithm is evaluated based on simulation. The results show that our proposal significantly provides more than 30% reduction of run time and about 12% improvement in service deployment success ratio compared to the Viterbi algorithm based mechanism.

• Journal of the Korean Society of Systems Engineering
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• v.17 no.2
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• pp.49-60
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• 2021

The Core Protection Calculator System (CPCS) is vital for plant safety as it ensures the required Specified Acceptance Fuel Design Limit (SAFDL) are not exceeded. The CPCS generates trip signals when Departure from Nucleate Boiling Ratio (DNBR) and Local Power Density (LPD) exceeds their predetermined setpoints. These setpoints are established based on the operating margin from the analysis that produces the SAFDL values. The goal of this research is to create a simplified CPCS that optimizes operating margin for I-SMRs. Because the I-SMR is compact in design, instrumentation placement is a challenge, as it is with Ex-core detectors and RCP instrumentation. The proposed CPCS addresses the issue of power flux measurement with In-Core Instrumentation (ICI), while flow measurement is handled with differential pressure transmitters between Steam Generators (SG). Simplification of CPCS is based on a Look-Up-Table (LUT) for determining the CEA groups' position. However, simplification brings approximations that result in a loss of operational margin, which necessitates compensation. Appropriate compensation is performed based on the result of analysis. FPGAs (Field Programmable Gate Arrays) are presented as a way to compensate for the inadequacies of current systems by providing faster execution speeds and a lower Common Cause Failure rate (CCF).

• Safety and Health at Work
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• v.13 no.4
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• pp.507-511
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• 2022

Law enforcement officers (LEOs) often encounter rapidly changing and uncontrolled situations that expose them to various hazards. A law enforcement agency requested an evaluation by the National Institute for Occupational Safety and Health (NIOSH) when multiple LEOs reported illness after executing a search warrant and taking a suspect into custody. NIOSH investigators interviewed LEOs and reviewed medical records, forensic laboratory results for collected evidence, and environmental testing results of samples taken after the operation. Two-thirds (25 of 38) of LEOs who participated in the operation reported ≥1 symptom. Eleven LEOs met a case definition for influenza-like illness (ILI). Members of one unit were more likely to have ILI than non-members (prevalence ratio (PR), 4.1; 95% confidence interval (CI): 1.3-13.0; p = 0.01). Influenza vaccination was associated with a lower prevalence of ILI (PR, 0.2; 95% CI, 0.1-0.9; p = 0.02). Preventing employees from working while ill and annual influenza vaccination might prevent similar occurrences.

• Korea Trade Review
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• v.42 no.3
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• pp.25-47
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• 2017

Forfaiting is a trade finance facility whereby financial institution purchases accounts receivable from exporters, on a without recourse basis. After the adoption of K-IFRS in 2011, accounting for simple borrowing as usual negotiation increases debt ratio which in turn, worsens financial soundness of a company. Hence, exporting companies have their interest in forfaiting that enables book-off in order to decrease the borrowing. Along with the execution of URF 800 at ICC and increasing the interest of exporting companies into forfaiting, foreign exchange banks in Korea expand the development of products related to forfaiting. Upon surveying all these national banks of this matter, this paper identified an appropriate solution for the forfaiting practice.

• Journal of KIISE:Databases
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• v.34 no.5
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• pp.379-388
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• 2007

Disordered streams may cause inaccurate or delayed results in window-based queries. Existing approaches usually leverage buffers to hand]e the streams. However, most of the approaches estimate the buffer size simply based on the maximum network delay in the streams, which tends to over-estimate the buffer size and result in high latency. In this paper, we propose a probabilistic approach to estimate the buffer size adaptively according to the fluctuated network delays. We first assume that intervals of tuple generations follow an exponential distribution and network delays have a normal distribution. Then, we derive an estimation function from the assumptions. The function takes a drop ratio as an input parameter, which denotes a percentage of tuple drops permissible during query execution. By describing the drop ratio in a query specification, users can control the quality of query results such as accuracy or latency according to application requirements. Our experimental results show that the proposed function has better adaptivity than the existing function based on the maximum network delay.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.2
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• pp.263-269
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• 2017

'Goal Model' is core knowledge of 'Autonomic Control System' suggested to minimize human interference in system management. 'Autonomic Control System' performs 'Monitoring-Analysis-Plan-Execution', that is the four step of 'Autonomic Control', based on 'Goal Model'. Therefore, it is necessary to quantify achievement ratio of 'Goal Model' of target system. Thus, this paper present 'Probabilistic Evaluation of Goal Model' for methodology how to quantify achievement ratio of 'Goal Model'. It comprises 3-steps including 'Goal modeling and weighting', 'Goal model monitoring', 'Goal model evaluation and analysis'. Through these research, we provide core knowledge for 'Autonomic Control system' and it is possible to increase the reliability of system by evaluating 'Goal model' with applying weight. As case study, we apply 'Goal model' to a 'Smart IoT Kit' and we demonstrate the validity of the suggested research.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.6
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• pp.485-492
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• 2016

A role of the binarization is very important in separating the foreground and the background in the field of the computer vision. In this study, an adaptive fuzzy binarization is proposed. An ${\alpha}$-cut control ratio is obtained by the distribution of grey level of pixels in a sliding window, and binarization is performed using the value. To obtain the ${\alpha}$-cut, existing thresholding methods which execution speed is fast are used. The threshold values are set as the center of each membership function and the fuzzy intervals of the functions are specified with the distribution of grey level of the pixel. Then ${\alpha}$-control ratio is calculated using the specified function and binarization is performed according to the membership degree of the pixels. The experimental results show the proposed method can segment the foreground and the background well than existing binarization methods and decrease loss of the foreground.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.2
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• pp.201-211
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• 2022

According to the recent change in the cybersecurity paradigm, research on anomaly detection methods using machine learning and deep learning techniques, which are AI implementation technologies, is increasing. In this study, a comparative study on data preprocessing techniques that can improve the anomaly detection performance of a GRU (Gated Recurrent Unit) neural network-based intrusion detection model using NGIDS-DS (Next Generation IDS Dataset), an open dataset, was conducted. In addition, in order to solve the class imbalance problem according to the ratio of normal data and attack data, the detection performance according to the oversampling ratio was compared and analyzed using the oversampling technique applied with DCGAN (Deep Convolutional Generative Adversarial Networks). As a result of the experiment, the method preprocessed using the Doc2Vec algorithm for system call feature and process execution path feature showed good performance, and in the case of oversampling performance, when DCGAN was used, improved detection performance was shown.