• Journal of KIISE
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• v.43 no.9
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• pp.974-982
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• 2016

Mutation analysis (or software mutation analysis) generates variants of a target program by injecting systematic code changes to the target program, and utilizes the variants to analyze the target program behaviors. Effective mutation analyses require adequate mutation operators that generate diverse variants for use in the analysis. However, the current mutation analysis tools for Java programs have limitations, since they support only limited types of mutation operators and do not support recent language features such as Java8. In this study, we present Mutagen4J, a new mutant generation tool for Java programs. Mutagen4J additionally supports mutation operators recently shown to generate various mutants and fully supports recent Java language features. The experimental results show that Mutagen4J generates useful mutants for analyses 2.3 times more than the existing Java mutation tools used for the study.

• Journal of Korean Society for Geospatial Information Science
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• v.22 no.1
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• pp.47-54
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• 2014

Precise Point Positioning (PPP) algorithms using GPS code pseudo-range measurements were developed and their accuracy was validated for the purpose of implementing them on a portable device. The group delay, relativistic effect, and satellite-antenna phase center offset models were applied as fundamental corrections for PPP. GPS satellite orbit and clock offsets were taken from the International GNSS Service official products which were interpolated using the best available algorithms. Tropospheric and ionospheric delays were obtained by applying mapping functions to the outputs from scientific GPS data processing software and Global Ionosphere Maps, respectively. When the developed algorithms were tested for four days of data, the horizontal and vertical positioning accuracies were 0.8-1.6 and 1.6-2.2 meters, respectively. This level of performance is comparable to that of Differential GPS, and further improvements and fine-tuning of this suite of PPP algorithms and its implementation at a portable device should be utilized in a variety of surveying and Location-Based Service applications.

• Journal of KIISE:Software and Applications
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• v.33 no.8
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• pp.692-702
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• 2006

In this study, a weighted fuzzy min-max (WFMM) neural network model for pattern classification is proposed. The model has a modified structure of FMM neural network in which the weight concept is added to represent the frequency factor of feature values in a learning data set. First we present in this paper a new activation function of the network which is defined as a hyperbox membership function. Then we introduce a new learning algorithm for the model that consists of three kinds of processes: hyperbox creation/expansion, hyperbox overlap test, and hyperbox contraction. A weight adaptation rule considering the frequency factors is defined for the learning process. Finally we describe a feature analysis technique using the proposed model. Four kinds of relevance factors among feature values, feature types, hyperboxes and patterns classes are proposed to analyze relative importance of each feature in a given problem. Two types of practical applications, Fisher's Iris data and Cleveland medical data, have been used for the experiments. Through the experimental results, the effectiveness of the proposed method is discussed.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.11
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• pp.124-129
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• 2013

This paper proposes a high-performance vector inner product calculation circuit for real-time object recognition based on SVM algorithm. SVM algorithm shows a higher detection rate than other object recognition algorithms. However, it requires a huge amount of computational efforts. Since vector inner product calculation is one of the major operations of SVM algorithm, it is important to implement a high-performance vector inner product calculation circuit for real-time object recognition capability. The proposed circuit adopts the pipeline architecture with six stages to increase the operating speed and makes it possible to recognize objects in real time based on SVM. The proposed circuit was described in Verilog HDL at RTL. For silicon verification, an MPW chip was fabricated using TSMC 180nm standard cell library. The operation of the implemented MPW chip was verified on the test board with test application software developed for the chip verification.

• The KIPS Transactions:PartA
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• v.13A no.6 s.103
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• pp.481-488
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• 2006

FRP(Functional Reactive Programming) is a kind of embedded language in Haskell, it declaratively program reactive system based on two essential high-order types named behavior and events. This Paper design and implementation RT-FRP(Real-time Functional Reactive Programming) translator for using FRP in embedded systems with many constraints. The RT-FRP translator generates a C Program from an RT-FRP program according to the operational semantics of the RT-FRP language. To show the effectiveness of the RT-FRP translator, we loaded and executed the test program generated by the translator onto a real embedded system, LEGO Mindstorm. According to the experimental result, the reactive system software can be programmed more concisely using RT-FRP than using an imperative counter part although the size of the binary code is rather increased.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.9
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• pp.433-440
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• 2016

Railway point machines act as actuators that provide different routes to trains by driving switchblades from the current position to the opposite one. Since point failure can significantly affect railway operations with potentially disastrous consequences, early stress detection of point machine is critical for monitoring and managing the condition of rail infrastructure. In this paper, we propose a stress detection method for point machine in railway condition monitoring systems using sound data. The system enables extracting sound feature vector subset from audio data with reduced feature dimensions using feature subset selection, and employs support vector machines (SVMs) for early detection of stress anomalies. Experimental results show that the system enables cost-effective detection of stress using a low-cost microphone, with accuracy exceeding 98%.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2017.05a
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• pp.560-562
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• 2017

This paper presents the development and test results of a test rig for confirming the hover performance of the coaxial propeller which is applied to the drone in order to carry out the mission that requires high payload such as the development of the courier drones. the performance of each propeller was measured by varying the thrust and torque according to the H/D ratio. the Thrust sensor and torque sensor were used to measure the thrust and torque generated when the propeller rotated, and a photo sensor was used to measure the rpm. it used the data acquisition system to acquire data from each sensor, and used the Labview softwaer to control data storage, monitoring and BLDC motor control. In the test, each propeller meansured the figure of mefit according to the chansge of the interval at the same rpm.

• Journal of the Korea Society of Computer and Information
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• v.13 no.2
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• pp.203-210
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• 2008

Home networking has been noticed as a key technology for the home automation because it is possible to remotely monitor and control the in-house appliances and devices through the network. Wireless home networking method is easily applied to the conventional houses compared to the wired home networking method because of low cost and small effort due to no extra wired works. Especially, home networking using the ZigBee protocol is one of the most attractive technologies in the wireless networking area because of its low cost and low power consumption characteristics. However, there are a lot of practical problems to be solved in implementing the ZigBee module and constructing the wireless network. In this paper, one of the practical structures of the hardware and software modules for implementing the ZigBee protocol is proposed. Moreover, problems in constructing the home networking with the proposed ZigBee module are introduced, and the effective solutions to solve these problems are described through various tests.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2007.11a
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• pp.929-933
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• 2007

Concrete Pavement Cutting Operation have Labor-intensive features. And Cutting Operation quality and productivity is influenced by operator's experience. Moreover Workers have risk of safety concerns. Therefore we need Concrete Pavement Cutting Operation automation system and system support software development on the economics. First of all we have to develop driving Path Planning for Concrete Pavement Cutting automation system. If result of Path Planning connect with automation system, Weak points is a complement to the existing Path Planning and we can obtain effective automation system. Consequently this paper suggest method of Autonomous Driving Path Planning for Concrete Pavement Cutting Operation And the Path Planning system application.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.5
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• pp.341-346
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• 2013

In this paper, we propose a rule extraction method using a modified Fuzzy Min-Max (FMM) neural network. The suggested method supplements the hyperbox definition with a frequency factor of feature values in the learning data set. We have defined a relevance factor between features and pattern classes. The proposed model can solve the ambiguity problem without using the overlapping test process and the contraction process. The hyperbox membership function based on the fuzzy partitions is defined for each dimension of a pattern class. The weight values are trained by the feature range and the frequency of feature values. The excitatory features and the inhibitory features can be classified by the proposed method and they can be used for the rule generation process. From the experiments of sign language recognition, the proposed method is evaluated empirically.