• KIISE Transactions on Computing Practices
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• v.20 no.9
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• pp.519-524
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• 2014

The operating systems in the system architecture, which is integrated several applications and modular electronic devices in the same computing device, demand partitioning technology for safety. Thus, operation system requires partition scheduler for partition scheduling. When we design partition scheduler in embedded system, which has small memory and low performance, such as space system, we must consider not only performance but also memory. In this paper, we introduces a linux-based memory efficient partition scheduler using partition bitmap. This partition scheduler demands small memory space and produce low partition switching overhead. The prototype was executed on a LEON4 processor, which is the Next Generation Multicore Processor (NGMP) in the space sector. In evaluation, this prototype shows accuracy, additional memory space and low partition switching overhead.

• KIISE Transactions on Computing Practices
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• v.21 no.1
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• pp.29-39
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• 2015

When new inertial navigation systems for an unmanned aerial vehicles are being developed and tested, construction of a fault-tolerant system is required because of various types of hazards caused by S/W and H/W faults. In this paper, a new fault-tolerant flight system that can be deployed into one or more FCCs (Flight Control Computers) is introduced, based on a partition scheme wherein each OFP (Operational Flight Program) partition uses an independent CPU and memory slot. The new fault-tolerant navigation system utilizes one or two FCCs, and executes a primary navigation OFP under development and a stable shadow OFP partition on each node. The fault-tolerant navigation system based on a single FCC can be used for UAVs with small payloads. For larger UAVs, an additional FCC with two OFP partitions can be used to provide both H/W and S/W fault-tolerance. The developed fault-tolerant navigation system significantly removes various hazards in testing new navigation S/Ws for UAVs.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.4B
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• pp.377-384
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• 2009

In order to reduce computing time significantly for a large matrix in EFEM of linear waves propagation over ripple beds, each of which is approximated to a multi-step topography, a partition method is presented to calculate reflection coefficients. By use of 10 evanescent modes in the model, the most accurate numerical solutions have been obtained up to date, which show different behaviors of computed reflection coefficient in some cases against the existing results. Both computing time and memory of the present partition model for solving a large matrix are still so much demanding that it is needed to develop an efficient method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.5
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• pp.2674-2697
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• 2019

Identity authentication is a crucial line of defense for network security, and passwords are still the mainstream of identity authentication. So far trawling password attacking has been extensively studied, but the research related with personal information is always sporadic. Probabilistic context-free grammar (PCFG) and Markov chain-based models perform greatly well in trawling guessing. In this paper we propose a systematic targeted attacking model based on structure partition and string reorganization by migrating the above two models to targeted attacking, denoted as TG-SPSR. In structure partition phase, besides dividing passwords to basic structure similar to PCFG, we additionally define a trajectory-based keyboard pattern in the basic grammar and introduce index bits to accurately characterize the position of special characters. Moreover, we also construct a BiLSTM recurrent neural network classifier to characterize the behavior of password reuse and modification after defining nine kinds of modification rules. Extensive experimental results indicate that in online attacking, TG-SPSR outperforms traditional trawling attacking algorithms by average about 275%, and respectively outperforms its foremost counterparts, Personal-PCFG, TarGuess-I, by about 70% and 19%; In offline attacking, TG-SPSR outperforms traditional trawling attacking algorithms by average about 90%, outperforms Personal-PCFG and TarGuess-I by 85% and 30%, respectively.

• Journal of Computing Science and Engineering
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• v.9 no.2
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• pp.51-72
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• 2015

Time predictability is crucial in hard real-time and safety-critical systems. Cache memories, while useful for improving the average-case memory performance, are not time predictable, especially when they are shared in multicore processors. To achieve time predictability while minimizing the impact on performance, this paper explores several time-predictable scratch-pad memory (SPM) based architectures for multicore processors. To support these architectures, we propose the dynamic memory objects allocation based partition, the static allocation based partition, and the static allocation based priority L2 SPM strategy to retain the characteristic of time predictability while attempting to maximize the performance and energy efficiency. The SPM based multicore architectural design and the related allocation methods thus form a comprehensive solution to hard real-time multicore based computing. Our experimental results indicate the strengths and weaknesses of each proposed architecture and the allocation method, which offers interesting on-chip memory design options to enable multicore platforms for hard real-time systems.

• Journal of KIISE:Computing Practices and Letters
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• v.8 no.1
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• pp.9-16
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• 2002

Join operation exert a great effect on the performance of system in temporal database as in the relational database. Especially, as for the temporal join, the optimization of interval partition decides the performance of query processing. In this paper, to improve the efficiency of parallel join query in temporal database. I proposed Minimum Interval Partition(MIP) scheme that time interval partitioning. The validity of this MIP algorithm that decides minimum breakpoint of the partition is proved by example scenario and I confirmed improved efficiency as compared with existing partition algorithm.

• Nuclear Engineering and Technology
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• v.54 no.4
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• pp.1495-1507
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• 2022

The improvement of thermal-hydraulic analysis techniques is essential to ensure the safety and reliability of nuclear power plants. The one-dimensional two-fluid model has been adopted in state-of-the-art thermal-hydraulic system codes. Current constitutive equations used in the system codes reach a mature level. Some exceptions are the partition method of wall friction in the momentum equation of the two-fluid model and the interfacial drag force model for a horizontal two-phase flow. This study is focused on deriving the partition method of wall friction in the momentum equation of the two-fluid model and modeling the interfacial drag force model for a horizontal bubbly flow. The one-dimensional momentum equation in the two-fluid model is derived from the local momentum equation. The derived one-dimensional momentum equation demonstrates that total wall friction should be apportioned to gas and liquid phases based on the phasic volume fraction, which is the same as that used in the SPACE code. The constitutive equations for the interfacial drag force are also identified. Based on the assessments, the Rassame-Hibiki correlation, Hibiki-Ishii correlation, Ishii-Zuber correlation, and Rassame-Hibiki correlation are recommended for computing the distribution parameter, interfacial area concentration, drag coefficient, and relative velocity covariance of a horizontal bubbly flow, respectively.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.4
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• pp.455-460
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• 2003

A new cluster validity index is proposed that determines the optimal partition and optimal number of clusters for fuzzy partitions obtained from the fuzzy c-means algorithm. The proposed validity index exploits an overlap measure and a separation measure between clusters. The overlap measure is obtained by computing an inter-cluster overlap. The separation measure is obtained by computing a distance between fuzzy clusters. A good fuzzy partition is expected to have a low degree of overlap and a larger separation distance. Testing of the proposed index and nine previously formulated indexes on well-known data sets showed the superior effectiveness and reliability of the proposed index in comparison to other indexes.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.21 no.46
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• pp.33-49
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• 1998

In order to improve the performance of relational databases, one has to reduce the number of disk accesses necessary to transfer data from disk to main memory. The paper proposes to reduce the number of disk I/O accesses by vertically partitioning relation into fragments and allowing attribute replication to fragments if necessary. When zero-one integer programming model is solved by the branch-and-bound method, it requires much computing time to solve a large sized problem. Therefore, heuristic solutions using genetic algorithm(GA) are presented. GA in this paper adapts a few ideas which are different from traditional genetic algorithms, for examples, a rank-based sharing fitness function, elitism and so on. In order to improve performance of GA, a set of optimal parameter levels is determined by the experiment and makes use of it. As relations are vertically partitioned allowing attribute replications and saved in disk, an attribute replicating vertical partition method by GA can attain less access cost than non-attribute-replication one and require less computing time than the branch-and-bound method in large-sized problems. Also, it can acquire a good solution similar to the optimum solution in small-sized problem.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.6
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• pp.2761-2781
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• 2018

With the continuous growth of data size and the use of compression technology, data reduction has great research value and practical significance. Aiming at the shortcomings of the existing semantic compression algorithm, this paper is based on the analysis of ItCompress algorithm, and designs a method of bidirectional order selection based on interval partitioning, which named An Optimized Iterative Semantic Compression Algorithm (Optimized ItCompress Algorithm). In order to further improve the speed of the algorithm, we propose a parallel optimization iterative semantic compression algorithm using GPU (POICAG) and an optimized iterative semantic compression algorithm using Spark (DOICAS). A lot of valid experiments are carried out on four kinds of datasets, which fully verified the efficiency of the proposed algorithm.