• KIPS Transactions on Software and Data Engineering
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• v.5 no.12
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• pp.653-662
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• 2016

This paper describes a test case generation algorithm for Simulink/Stateflow models based on the Rapidly exploring Random Tree (RRT) algorithm that has been successfully applied to path finding. An important factor influencing the performance of the RRT algorithm is the metric used for calculating the distance between the nodes in the RRT space. Since a test case for a Simulink/Stateflow (SL/SF) model is an input sequence to check a specific condition (called a test target in this paper) at a specific status of the model, it is necessary to drive the model to the status before checking the condition. A status maps to a node of the RRT. It is usually necessary to check various conditions at a specific status. For example, when the specific status represents an SL/SF model state from which multiple transitions are made, we must check multiple conditions to measure the transition coverage. We propose a unique distance calculation metric, based on the observation that the test targets are gathered around some specific status such as an SL/SF state, named key nodes in this paper. The proposed metric increases the probability that an RRT is extended from key nodes by imposing penalties to non-key nodes. A test case generation algorithm utilizing the proposed metric is proposed. Three models of Electrical Control Units (ECUs) embedded in a commercial vehicle are used for the performance evaluation. The performances are evaluated in terms of penalties and compared with those of the algorithm using a typical RRT algorithm.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.6
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• pp.315-320
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• 2017

Estimating the correct pose of augmented objects on the real camera view efficiently is one of the most important questions in image tracking area. In computer vision, Homography is used for camera pose estimation in augmented reality system with markerless. To estimating Homography, several algorithm like SURF features which extracted from images are used. Based on extracted features, Homography is estimated. For this purpose, RANSAC algorithm is well used to estimate homography and DCS-RANSAC algorithm is researched which apply constraints dynamically based on Constraint Satisfaction Problem to improve performance. In DCS-RANSAC, however, the dataset is based on pattern of feature distribution of images manually, so this algorithm cannot classify the input image, pattern of feature distribution is not recognized in DCS-RANSAC algorithm, which lead to reduce it's performance. To improve this problem, we suggest the KCS-RANSAC algorithm using K-means clustering in CS-RANSAC to cluster the images automatically based on pattern of feature distribution and apply constraints to each image groups. The suggested algorithm cluster the images automatically and apply the constraints to each clustered image groups. The experiment result shows that our KCS-RANSAC algorithm outperformed the DCS-RANSAC algorithm in terms of speed, accuracy, and inlier rate.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.12
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• pp.491-498
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• 2019

Digital twin is a technology that virtualizes physical objects of the real world on a computer. It is used by collecting sensor data through IoT, and using the collected data to connect physical objects and virtual objects in both directions. It has an advantage of minimizing risk by tuning an operation of virtual model through simulation and responding to varying environment by exploiting experiments in advance. Recently, artificial intelligence and machine learning technologies have been attracting attention, so that tendency to virtualize a behavior of physical objects, observe virtual models, and apply various scenarios is increasing. In particular, recognition of each robot's motion is needed to build digital twin for co-robot which is a heart of industry 4.0 factory automation. Compared with modeling based research for recognizing motion of co-robot, there are few attempts to predict motion based on sensor data. Therefore, in this paper, an experimental environment for collecting current and inertia data in co-robot to detect the motion of the robot is built, and a motion prediction model based on the collected sensor data is proposed. The proposed method classifies the co-robot's motion commands into 9 types based on joint position and uses current and inertial sensor values to predict them by accumulated learning. The data used for accumulating learning is the sensor values that are collected when the co-robot operates with margin in input parameters of the motion commands. Through this, the model is constructed to predict not only the nine movements along the same path but also the movements along the similar path. As a result of learning using SVM, the accuracy, precision, and recall factors of the model were evaluated as 97% on average.

• Journal of Convergence for Information Technology
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• v.8 no.1
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• pp.9-14
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• 2018

The purpose of this study was to privide basic data for footwear development according to walking mechanics by comparing gait cycle difference between barefoot walking and walking shoes. The walking period was measured in 30 normal adult women with no foot deformity and abnormality. The first subject walked in sneakers and measured the cycle. And then, the subjects walked barefoot and the period was measured to obtain data. The data were taken form corresponding paired T-test. The results were as follows: In barefoot walking, the stance phase left side(p <.001), right side(p <.005), the loading response left side(p <.009), right side(p <.002) ), the pre-swing left side(p <.002), right side (p <.011), the double stance phase(p <.004) were increased and the mid-stance left side (p <.016), right side(p. 001), the swing phase left side(p<.001) was decreased. This suggests that barefoot walking increases the input of various senses of the foot, which makes stable walking possible. It is necessary to improve shoes based on the walking cycle in the future.

• Journal of Convergence for Information Technology
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• v.8 no.5
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• pp.77-83
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• 2018

A modular robot that memorizes motion can be easily created and operated because it expresses by hand. However, since there is not enough storage space in the module to store the user-created operation, it is impossible to reuse the created operation, and when the modular robot again memorizes the operation, it changes to another operation. There is no main controller capable of operating a plurality of modular robots at the same time, and thus there is a disadvantage that the user must input directly to the modular robot. To overcome these disadvantages, a remote controller has been proposed that can be operated in the surrounding smart devices by designing web server and component based software using wired and wireless network. In the proposed method, various types of structures are created by connecting to a modular robot, and the reconstructed operation is performed again after storing, and the usefulness is confirmed by regenerating the stored operation effectively. In addition, the reliability of the downloaded trajectory data is verified by analyzing the difference between the trajectory data and the actual trajectory. In the future, the trajectory stored in the remote controller will be standardized using the artificial intelligence technique, so that the operation of the modular robot will be easily implemented.

• Journal of Technology Innovation
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• v.25 no.4
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• pp.263-284
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• 2017

The purpose of this research is to analyze the performance of national R&D projects and to find out measures to improve the performance indicators, focusing on energy HRD projects. The main analysis target is 86 energy manpower projects supported since 2010. The performance indicators of the energy HRD projects are related to the research capacity, the number of emission workers, industry-university linkage, job creation and so on, and analyzed by using the 11 indicators of human resource performance index called KPI index. As a result of analyzing the attainment level of the proposed target by task, the index with the highest achievement level is the corporation linkage rate, and the index with the lowest achievement level is the participating company employment. As a result of examining the effects of job creation in company - linked activities, it was found that the greater the number of participating companies in the business, the greater the employment creation effect of the number of internships. As a result of the above analysis, the following policy alternatives are proposed. First, it is necessary to consider adding indicators that can express the quality performance of the business and performance indicators that can express actual business linkages. Second, it is necessary to strengthen the management of differentiated performance indicators according to policy performance targets and major target groups. Third, it is necessary to improve information input and accumulation system along with improvement of performance index.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.36 no.5
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• pp.805-817
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• 2016

This study considered the existing approximation theories of solitary wave for stable generation of it with different waveforms in a hydraulic/numerical wave tank for coping with the tsunami. Based on the approximation theory equations, two methods were proposed to estimate various waveforms of solitary wave. They estimate different waveforms and flow rates by applying waveform distribution factor and virtual depth factor with the original approximate expressions of solitary wave. Newly proposed estimation methods of solitary wave were applied in the wave generation of hydraulic/numerical wave tank. In the result, it was able to estimate the positional information signal of wave generator in the hydraulic wave tank and to find that the signal was very similar to an input signal of existing hydraulic model experiment. The waveform and velocity of solitary wave was applied to the numerical wave tank in order to generate wave, which enabled generate waveform of tsunami that was not reproduced with existing solitary wave approximation theory and found that the result had high conformity with existing experiment result. Therefore, it was able to validate and verify the two proposed estimation methods to generate stable tsunami in the hydraulic/numerical wave tank.

• Journal of Broadcast Engineering
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• v.11 no.4 s.33
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• pp.386-395
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• 2006

Multi-view video coding technology demands the very high efficient coding technologies, because it has to encode a number of video sequences which are achieved from a number of video cameras. For this purpose, multi-view video coding introduces the inter-view prediction scheme between different views, but it shows a limitation of coding performance enhancement by adopting only new prediction method. Accordingly, we are going to achieve the more coding performance by enhancing dequantizer perfermance. Multi-view video coding is implemented basically based on H.264/AVC and uses the same quantization/de-quantization method as H.264/AVC does. The conventional quantizer and dequantizer is designed with the assumption that input residual signal follows the Laplacian PDF. However, it doesn't follow the fixed PDF type always. This mismatch between assumption and real data causes degradation of coding performance. To solve this problem, we propose the efficient de-quantization method based on quantized coefficients distribution at decoder without extra information. The extensive simulation results show that the proposed algorithm produces maximum $1.5\;dB{\sim}0.6\;dB$ at high bitrate compared with that of conventional method.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.12
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• pp.1150-1158
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• 2010

In this study, the Polynomial-based Radial Basis Function Neural Networks is proposed as one of the recognition part of overall face recognition system that consists of two parts such as the preprocessing part and recognition part. The design methodology and procedure of the proposed pRBFNNs are presented to obtain the solution to high-dimensional pattern recognition problem. First, in preprocessing part, we use a CCD camera to obtain a picture frame in real-time. By using histogram equalization method, we can partially enhance the distorted image influenced by natural as well as artificial illumination. We use an AdaBoost algorithm proposed by Viola and Jones, which is exploited for the detection of facial image area between face and non-facial image area. As the feature extraction algorithm, PCA method is used. In this study, the PCA method, which is a feature extraction algorithm, is used to carry out the dimension reduction of facial image area formed by high-dimensional information. Secondly, we use pRBFNNs to identify the ID by recognizing unique pattern of each person. The proposed pRBFNNs architecture consists of three functional modules such as the condition part, the conclusion part, and the inference part as fuzzy rules formed in 'If-then' format. In the condition part of fuzzy rules, input space is partitioned with Fuzzy C-Means clustering. In the conclusion part of rules, the connection weight of pRBFNNs is represented as three kinds of polynomials such as constant, linear, and quadratic. Coefficients of connection weight identified with back-propagation using gradient descent method. The output of pRBFNNs model is obtained by fuzzy inference method in the inference part of fuzzy rules. The essential design parameters (including learning rate, momentum coefficient and fuzzification coefficient) of the networks are optimized by means of the Particle Swarm Optimization. The proposed pRBFNNs are applied to real-time face recognition system and then demonstrated from the viewpoint of output performance and recognition rate.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.36C no.10
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• pp.17-28
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• 1999

In this paper, an ASIC emulation system called ACE (ASIC Emulator) is proposed. It can produce the prototype of target ASIC in a short time and verify the function of ASIC circuit immediately The ACE is consist of emulation software in which there are EDIF reader, library translator, technology mapper, circuit partitioner and LDF generator and emulation hardware including emulation board and logic analyzer. Technology mapping is consist of three steps such as circuit partitioning and extraction of logic function, minimization of logic function and grouping of logic function. During those procedures, the number of basic logic blocks and maximum levels are minimized by making the output to be assigned in a same block sharing product-terms and input variables as much as possible. Circuit partitioner obtain chip-level netlists satisfying some constraints on routing structure of emulation board as well as the architecture of FPGA chip. A new partitioning algorithm whose objective function is the minimization of the number of interconnections among FPGA chips and among group of FPGA chips is proposed. The routing structure of emulation board take the advantage of complete graph and partial crossbar structure in order to minimize the interconnection delay between FPGA chips regardless of circuit size. logic analyzer display the waveform of probing signal on PC monitor that is designated by user. In order to evaluate the performance of the proposed emulation system, video Quad-splitter, one of the commercial ASIC, is implemented on the emulation board. Experimental results show that it is operated in the real time of 14.3MHz and functioned perfectly.