• KIPS Transactions on Software and Data Engineering
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• v.2 no.7
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• pp.471-478
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• 2013

This paper proposes a black-box based test case generation method for Simulink/Stateflow model utilizing the RRT algorithm which is a method to efficiently solve the path planning for complicated systems. The proposed method in the paper tries to solve the reachability problem with the RRT algorithm, which has to be solved for black-box based test case generations. A major problem of the RRT based test case generation algorithms is that the cost such as running time and required memory size is too much for complicated Stateflow model. The typical RRT algorithm expands rapidly-exploring random tree (RRT) in a single state space. But the proposed method expands it in dynamic state space based on the state of Simulink model, consequently reducing the cost. In the paper, a new definition of RRT state space, a distance measure and a test case generation algorithm are proposed. The performance of proposed method is verified through the experiment against Stateflow model.

• Journal of KIISE:Software and Applications
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• v.31 no.9
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• pp.1246-1257
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• 2004

To find an optimal solution with genetic algorithm, it is desirable to maintain the population sire as large as possible. In some cases, however, the cost to evaluate each individual is relatively high and it is difficult to maintain large population. To solve this problem we propose a novel genetic algorithm based on fuzzy clustering, which considerably reduces evaluation number without any significant loss of its performance by evaluating only one representative for each cluster. The fitness values of other individuals are estimated from the representative fitness values indirectly. We have used fuzzy c-means algorithm and distributed the fitness using membership matrix, since it is hard to distribute precise fitness values by hard clustering method to individuals which belong to multiple groups. Nine benchmark functions have been investigated and the results are compared to six hard clustering algorithms with Euclidean distance and Pearson correlation coefficients as fitness distribution method.

• Journal of KIISE:Software and Applications
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• v.28 no.9
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• pp.662-668
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• 2001

Since the problem of disproving a tautology is as hard as the problem of proving it, no polynomial time algorithm for falsification(or testing invalidity) is feasible. Previous algorithms are mostly based on either divide-and-conquer or graph representation. Most of them demonstrated satisfactory results on a variety of input under certain constraints. However, they have experienced difficulties dealing with big input. We propose a new falsification algorithm using a Merge Rule to produce a counterexample by constructing a minterm which is not satisfied by an input expression in DNF(Disjunctive Normal Form). We also show that the algorithm is consistent and sound. The algorithm is based on a greedy method which would seek to maximize the number or terms falsified by the assignment made at each step of the falsification process. Empirical results show practical performance on big input to falsify randomized nontautological problem instances, consuming O(nm$^2$) time, where n is the number of variables and m is number of terms.

• Journal of KIISE:Software and Applications
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• v.31 no.9
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• pp.1161-1170
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• 2004

This paper proposes to segment skin color areas using a clustering algorithm. Most of previously proposed clustering algorithms have some difficulties, since they generally detect hyperspherical clusters, run in a batch mode, and predefine a number of clusters. In this paper, we use a well-known elliptical clustering algorithm, an EM algorithm, and modify it to learn on-line and find automatically the number of clusters, called to an EAM algorithm. The effectiveness of the EAM algorithm is demonstrated on a task of skin color region segmentation. Experimental results present the EAM algorithm automatically finds a right number of clusters in a given image without any information on the number. Comparing with the EM algorithm, we achieved better segmentation results with the EAM algorithm. Successful results were achieved to detect and segment skin color regions using a conditional probability on a region. Also, we applied to classify images with persons and got good classification results.

• Journal of KIISE:Software and Applications
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• v.27 no.3
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• pp.201-209
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• 2000

Recent works regarding video shot change detection algorithms show that abrupt shot changes are detected fairly well. However, gradual shot changes including wipes and dissolves are often missed or falsely detected. A robust shot change detection system, therefore, must include a shot verification step to further enhance the overall system performance. In this paper, we introduce the concept of the visual rhythm which is a single image, a subsampled version of a full video. On the visual rhythm, the different video edit effects such as cuts, wipes and dissolves manifest themselves as different patterns. Using this characteristic, it becomes possible, without sequentially playing the entire video, to find false positive shots as well as undetected shots. Thus, inclusion of the visual rhythm in the shot boundary verification process will aid the operator to exclude falsely detected shots as well as to find undetected shots fast and efficiently. For this purpose we have developed a new tool, a shot verifier incorporating the visual rhythm. The usefulness of the visual rhythm during the shot verification process will be presented.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.45 no.11
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• pp.951-966
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• 2017

In this work, numerical analyses are carried out and the behaviors are investigated for three types of double-acting oleo-pneumatic shock absorbers along with the mathematical models proposed in the part I of this work. After presenting each numerical algorithm corresponding to each model, the numerical algorithms are implemented as user-subroutines in MSC/ADAMS commercial multi-body dynamic software. By using the developed user-subroutines, numerical studies are carried out for compression/stretch test as well as drop test. From the comparative studies, we investigated the salient feature of each double-acting oleo-pneumatic shock absorber. Results identifies that it is possible to increase the absorbing efficiency in accordance with the requirements for aircraft landing conditions.

• Journal of Electrical Engineering and Technology
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• v.10 no.4
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• pp.1540-1551
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• 2015

The detection of position and speed in BLDC motors without using position sensors has meant many efforts for the last decades. The aim of this paper is to develop a sensorless technique for detecting the position and speed of BLDC motors, and to overcome the drawbacks of position sensor-based methods by improving the performance of traditional approaches oriented to motor phase voltage sensing. The position and speed information is obtained by computing the derivative of the terminal phase voltages regarding to a virtual neutral point. For starting-up the motor and implementing the algorithms of the detection technique, a FPGA board with a real-time processor is used. Also, a versatile hardware has been developed for driving BLDC motors through pulse width modulation (PWM) signals. Delta and wye winding motors have been considered for evaluating the performance of the designed hardware and software, and tests with and without load are performed. Experimental results for validating the detection technique were attained in the range 5-1500 rpm and 5-150 rpm under no-load and full-load conditions, respectively. Specifically, speed and position square errors lower than 3 rpm and between 10º-30º were obtained without load. In addition, the speed and position errors after full-load tests were around 1 rpm and between 10º-15º, respectively. These results provide the evidence that the developed technique allows to detect the position and speed of BLDC motors with low accuracy errors at starting-up and over a wide speed range, and reduce the influence of noise in position sensing, which suggest that it can be satisfactorily used as a reliable alternative to position sensors in precision applications.

• KIISE Transactions on Computing Practices
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• v.23 no.8
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• pp.466-472
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• 2017

Hardware Transactional Memory (HTM) has greatly changed the parallel programming paradigm for transaction processing. Since Intel has recently proposed Transactional Synchronization Extension (TSX), a number of studies based on HTM have been conducted. However, the existing studies support conflict prediction for a single cause of the transaction processing and provide a standardized TSX environment for all workloads. To solve the problems, we propose an efficient hardware transactional memory scheme for processing transactions in multi-core in-memory environment. First, the proposed scheme determines whether to use Software Transactional Memory (STM) or the serial execution as a fallback path of HTM by using a prediction matrix to collect the information of previously executed transactions. Second, the proposed scheme performs efficient transaction processing according to the characteristic of a given workload by providing a retry policy based on machine learning algorithms. Finally, through the experimental performance evaluation using Stanford transactional applications for multi-processing (STAMP), the proposed scheme shows 10~20% better performance than the existing schemes.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.8
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• pp.3076-3082
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• 2010

The techniques and the products which use various video compression codec are come out from army or civil field. In existing high-end PC environment, process of the video compression codec does not become a problem, but in embedded system environments which limited system resources, because the system load due to the high-resolution images compressed by high-density, issues of performance and utilization are highlighted. This paper proposes the DirectShow Filter interfaces which are a hardware method in order to solve the problem existing software algorithms for image compression performance and peripheral interfaces.

• Journal of KIISE:Software and Applications
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• v.37 no.4
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• pp.297-304
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• 2010

Clustering method which based on sentence type or document genre is a technique used to improve translation quality of SMT(statistical machine translation) by domain-specific translation. But there is no previous research using sentence type and document genre information simultaneously. In this paper, we suggest an integrated clustering method that classifying sentence type by syntactic structure similarity and document genre by word similarity information. We interpolated domain-specific models from clusters with general models to improve translation quality of SMT system. Kernel function and cosine measures are applied to calculate structural similarity and word similarity. With these similarities, we used machine learning algorithms similar to K-means to clustering. In Japanese-English patent translation corpus, we got 2.5% point relative improvements of translation quality at optimal case.