• The Journal of Engineering Geology
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• v.30 no.4
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• pp.557-575
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• 2020

Plasma blasting which is generated by high voltage arc discharge of electricity is applied to soil mass to improve permeability of soil and cleaning efficiency of oil contamination. A new high voltage generator was manufactured and three types of soil including silty sand, silty sand mixed with lime and silty sand mixed with cement were prepared. Small and large soil columns were produced using these types of soil and plasma blasting was performed within soil columns to investigate the variation of soil volume penetrated by fluid and permeability. Soil volume penetrated by fluid increased by 11~71% when plasma blasting was applied in soil. Although plasma blasting with low electricity voltage induced horizontal fracture and fluid penetrated along this weak plane, plasma blasting with high voltage induced spherical penetration of fluid. Plasma blasting increased the permeability of soil. Permeabilty of soils mixed with lime and cement increased by 450~1,052% with plasma blasting. Permeability of soil increased as discharge voltage increased when plasma blasing was applied once. However, several blastings with the same discharge voltage increase or decrease permeability of soil. Oil contaminated soil was prepared by adding diesel into soil artificially and plasma blasting was performed in these oil contaminated soil. Cleaning efficiency increased by average of 393% for soil located nearby the blasting and by average of 239% for soil located far from the blasting. Cleaning efficiency did not show any correlation with discharge voltage. All these results indicated that plasma blasting might be used for in-situ cleaning of oil contaminated soil because plasma blasting increased permeability of soil and cleaning efficiency.

• Journal of KIISE:Computer Systems and Theory
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• v.34 no.10
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• pp.493-501
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• 2007

The imprecise real-time system provides flexibility in scheduling time-critical tasks. Most scheduling problems of satisfying both 0/1 constraint and timing constraints, while the total error is minimized, are NP-complete when the optional tasks have arbitrary processing times. Liu suggested a reasonable strategy of scheduling tasks with the 0/1 constraint on uniprocessors for minimizing the total error. Song et at suggested a reasonable strategy of scheduling tasks with the 0/1 constraint on multiprocessors for minimizing the total error. But, these algorithms are all off-line algorithms. In the online scheduling, the NORA algorithm can find a schedule with the minimum total error for the imprecise online task system. In NORA algorithm, EDF strategy is adopted in the optional scheduling. On the other hand, for the task system with 0/1 constraint, EDF_Scheduling may not be optimal in the sense that the total error is minimized. Furthermore, when the optional tasks are scheduled in the ascending order of their required processing times, NORA algorithm which EDF strategy is adopted may not produce minimum total error. Therefore, in this paper, an online algorithm is proposed to minimize total error for the imprecise task system with 0/1 constraint. Then, to compare the performance between the proposed algorithm and NORA algorithm, a series of experiments are performed. As a conseqence of the performance comparison between two algorithms, it has been concluded that the proposed algorithm can produce similar total error to NORA algorithm when the optional tasks are scheduled in the random order of their required processing times but, the proposed algorithm can produce less total error than NORA algorithm especially when the optional tasks are scheduled in the ascending order of their required processing times.

• Journal of KIISE:Information Networking
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• v.32 no.3
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• pp.279-290
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• 2005

Recently, as the serious damage caused by DDoS attacks increases, the rapid detection and the proper response mechanisms are urgent. However, existing security mechanisms do not effectively defend against these attacks, or the defense capability of some mechanisms is only limited to specific DDoS attacks. In this paper, we propose a detection architecture against DDoS attack using data mining technology that can classify the latest types of DDoS attack, and can detect the modification of existing attacks as well as the novel attacks. This architecture consists of a Misuse Detection Module modeling to classify the existing attacks, and an Anomaly Detection Module modeling to detect the novel attacks. And it utilizes the off-line generated models in order to detect the DDoS attack using the real-time traffic. We gathered the NetFlow data generated at an access router of our network in order to model the real network traffic and test it. The NetFlow provides the useful flow-based statistical information without tremendous preprocessing. Also, we mounted the well-known DDoS attack tools to gather the attack traffic. And then, our experimental results show that our approach can provide the outstanding performance against existing attacks, and provide the possibility of detection against the novel attack.