• The KIPS Transactions:PartD
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• v.8D no.5
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• pp.513-522
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• 2001

Active database execute an action of active rule defined in advance which is triggered automatically, whenever an event with the matching event specifications occurs, its condition is evaluated. Because these rules may in turn trigger other rules, the set of rules may be triggered each other indefinitely, Therefore, we propose a termination analysis method to guarantee termination. This proposed method considers composite event as well as rule execution time. Above all, the method not only uses deactivation graph combined to trigger graph for exact analysis, but also improves the complexity of analysis. Also the proposed method enhances accuracy of analysis result.

• The KIPS Transactions:PartD
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• v.15D no.2
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• pp.213-222
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• 2008

The existing approaches for the music application have not considered a real-time multi-tasking model. So, it suffers from a high complexity and a low flexibility in design as well as lack of predictability for the timely execution of critical tasks. In this paper, we design a new concurrent tasking architecture for a real-time embedded music system and examine if all real-time tasks can finish execution within their respective time constraints. The design is implemented on the Linux based Xhyper272 Board that uses the Intel Bulverde microprocessor.

• Journal of Computing Science and Engineering
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• v.5 no.1
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• pp.1-18
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• 2011

As the first step toward real-time multi-core computing, this paper presents a novel approach to bounding the worst-case performance for threads running on multi-core processors with shared L2 instruction caches. The idea of our approach is to compute the worst-case instruction access interferences between different threads based on the program control flow information of each thread, which can be statically analyzed. Our experiments indicate that the proposed approach can reasonably estimate the worst-case shared L2 instruction cache misses by considering the inter-thread instruction conflicts. Also, the worst-case execution time (WCET) of applications running on multi-core processors estimated by our approach is much better than the estimation by simply assuming all L2 instruction accesses are misses.

• Journal of the Korea Safety Management & Science
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• v.24 no.4
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• pp.149-156
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• 2022

Manufacturing process mining performs various data analyzes of performance on event logs that record production. That is, it analyzes the event log data accumulated in the information system and extracts useful information necessary for business execution. Process data analysis by process mining analyzes actual data extracted from manufacturing execution systems (MES) to enable accurate manufacturing process analysis. In order to continuously manage and improve manufacturing and manufacturing processes, there is a need to structure, monitor and analyze the processes, but there is a lack of suitable technology to use. The purpose of this research is to propose a manufacturing process analysis method using process mining and to establish a manufacturing process mining system by analyzing empirical data. In this research, the manufacturing process was analyzed by process mining technology using transaction data extracted from MES. A relationship model of the manufacturing process and equipment was derived, and various performance analyzes were performed on the derived process model from the viewpoint of work, equipment, and time. The results of this analysis are highly effective in shortening process lead times (bottleneck analysis, time analysis), improving productivity (throughput analysis), and reducing costs (equipment analysis).

• The Journal of the Korea Contents Association
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• v.10 no.5
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• pp.70-79
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• 2010

We perform static program analysis for the binary code. The reason you want to analyze at the level of binary code, installed on your local computer, run the executable file without source code. And the reason we want to perform static analysis, static program analysis is to understand what actions to perform on your local computer. In this paper, execution flow graph representing information such as the execution order among functions and the flow of control is generated. Using graph, User can find execution flow of binary file and calls of insecure functions at the same time, and the graph should facilitate the analysis of binary files. In addition, program to be run is ensured the safety by providing an automated way to search the flow of execution, and program to be downloaded and installed from outside is determined whether safe before running.

• Journal of the Korea Society of Computer and Information
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• v.15 no.5
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• pp.49-56
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• 2010

In this paper, we implement a Hadoop based cluster for cloud computing and evaluate the performance of this cluster based on application characteristics by executing RandomTextWriter, WordCount, and PI applications. A RandomTextWriter creates given amount of random words and stores them in the HDFS(Hadoop Distributed File System). A WordCount reads an input file and determines the frequency of a given word per block unit. PI application induces PI value using the Monte Carlo law. During simulation, we investigate the effect of data block size and the number of replications on the execution time of applications. Through simulation, we have confirmed that the execution time of RandomTextWriter was proportional to the number of replications. However, the execution time of WordCount and PI were not affected by the number of replications. Moreover, the execution time of WordCount was optimum when the block size was 64~256MB. Therefore, these results show that the performance of cloud computing system can be enhanced by using a scheduling scheme that considers application's characteristics.

• Journal of The Korean Association of Information Education
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• v.23 no.2
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• pp.107-116
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• 2019

The purpose of this study is to develop a Python sorting algorithm training program based on execution time as an educational method for enhancing the logical thinking power of elementary students and then to verify the effect. The education program was developed based on the results of the pre-demand analysis conducted on 100 elementary school teachers. In order to verify the effectiveness of the developed educational program, I teached 25 students of the volunteer sample of the elementary school education donation program conducted at ${\bigcirc}{\bigcirc}$ University conducted 42 hours, 7 days. The results of the pre-test and post-test were analyzed using the 'Group Assessment of Logical Thinking(GALT)' developed by the Korea Educational Development Institute. The results showed that the Python sorting algorithm training centered on execution time was effective in improving the logical thinking ability of elementary school students.

• Journal of the Korea Society of Computer and Information
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• v.21 no.1
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• pp.125-129
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• 2016

In this paper, we propose an efficient dynamic workload balancing strategy which improves the performance of high-performance computing system. The key idea of this dynamic workload balancing strategy is to minimize execution time of each job and to maximize the system throughput by effectively using system resource such as CPU, memory. Also, this strategy dynamically allocates job by considering demanded memory size of executing job and workload status of each node. If an overload node occurs due to allocated job, the proposed scheme migrates job, executing in overload nodes, to another free nodes and reduces the waiting time and execution time of job by balancing workload of each node. Through simulation, we show that the proposed dynamic workload balancing strategy based on CPU, memory improves the performance of high-performance computing system compared to previous strategies.

• Journal of KIISE:Software and Applications
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• v.32 no.8
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• pp.795-807
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• 2005

The classical approaches for computing Live Variable Analysis(LVA) use iterative algorithms across the entire programs based on the Data Flow Analysis framework. In case of Zephyr compiler, average execution time of LVA takes $7\%$ of the compilation time for the benchmark programs. The classical LVA algorithm has many aspects for improvement. The iterative algorithm for LVA scans useless basic blocks and calculates large sets of variables repeatedly. We propose the improvement of Iterative algorithm for LVA based on used variables' upward movement. Our algorithm produces the same result as the previous iterative algorithm. It is based on use-def chain. Reordering of applying the flow equation in DFA reduces the number of visiting basic blocks and redundant flow equation executions, which improves overall processing time. Experimental results say that our algorithm ran reduce $36.4\%\;of\;LVA\;execution\;time\;and\;2.6\%$ of overall computation time in Zephyr compiler with benchmark programs.

• Journal of The Korean Association of Information Education
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• v.24 no.3
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• pp.233-241
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• 2020

This study has developed and applied an elementary EPL education program centered on execution time as an educational method for improving Computational thinking of elementary school students, and then its effect has been verified. The education program was developed based on the results of preliminary demand analysis conducted on 48 elementary school students. In order to verify the effectiveness of the education program, 25 students were asked to participate in the class of elementary school students on a seven hours for six days. Using the "Korea Bebras Challenge 2018", educational effects were analyzed through the results of pre- and post-mortem examinations, and the analysis showed that elementary EPL education centered on performance time was effective in improving computational thinking of elementary school students