• Journal of the Korean Society of Marine Environment & Safety
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• v.12 no.2 s.25
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• pp.151-155
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• 2006

In these days, welding is the most commonly used metallic connection technology and also is the fundamental production technology of the modem industrial, which is used in various areas of the industrial fields, such as shipbuilding, automobiles, airplanes and plant facilities. However welding process produces strong light, electric currents, and fume gases etc., and the welding automation is not so easy compared to the other works of manufacturing industries which produce the standardized products in large quantities. So it is difficult to weld and detect the all kinds of seams automatically by a specific sensor. In this paper the sensor applying strain gauges is used to detect the seams of triangular wave form. With the auto carriage having the sensor we proposed the experiment to weld and track the seam automatically.

• Journal of Digital Convergence
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• v.19 no.10
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• pp.295-301
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• 2021

Individual mental fatigue not only reduces cognitive ability and work performance, but also becomes a major factor in large and small accidents occurring in daily life. In this paper, a CNN model for EEG-based mental fatigue discrimination was proposed. To this end, EEG in the resting state and task state were collected and applied to the proposed CNN model, and then the model performance was analyzed. All subjects who participated in the experiment were right-handed male students attending university, with and average age of 25.5 years. Spectral analysis was performed on the measured EEG in each state, and the performance of the CNN model was compared and analyzed using the raw EEG, absolute power, and relative power as input data of the CNN model. As a result, the relative power of the occipital lobe position in the alpha band showed the best performance. The model accuracy is 85.6% for training data, 78.5% for validation, and 95.7% for test data. The proposed model can be applied to the development of an automated system for mental fatigue detection.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.9
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• pp.339-348
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• 2021

In recent software defect prediction research, defect prediction between cross projects and cross-version projects are actively studied. Cross-version defect prediction studies assume WP(Within-Project) so far. However, in the CV(Cross-Version) environment, the previous work does not consider the distribution difference between project versions is important. In this study, we propose an automated Bayesian optimization framework that considers distribution differences between different versions. Through this, it automatically selects whether to perform transfer learning according to the difference in distribution. This framework is a technique that optimizes the distribution difference between versions, transfer learning, and hyper-parameters of the classifier. We confirmed that the method of automatically selecting whether to perform transfer learning based on the distribution difference is effective through experiments. Moreover, we can see that using our optimization framework is effective in improving performance and, as a result, can reduce software inspection effort. This is expected to support practical quality assurance activities for new version projects in a cross-version project environment.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.6
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• pp.1449-1461
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• 2018

As the number of software vulnerabilities grows year by year, attacks on software are also taking place a lot. As a result, the security administrator must identify and patch vulnerabilities in the software. However, it is important to prioritize the patches because patches for all vulnerabilities are realistically hard. In this paper, we propose a scoring system that expands the scale of risk assessment metric by taking into consideration attack patterns or weaknesses cause vulnerabilities with the vulnerability information provided by the NIST(National Institute of Standards and Technology). The proposed scoring system is expanded based on the CWSS and uses only public vulnerability information to utilize easily for any company. In this paper, we applied the automated scoring system to software vulnerabilities, and showed the expanded metrics with consideration for influence of attack pattern and weakness are meaningful.

• Journal of Convergence for Information Technology
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• v.8 no.6
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• pp.201-207
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• 2018

A genome contains all genetic information of an organism. Within a specific species, unique traits appear for each individual, which can be identified by analyzing nucleotide sequences. Many Genome-Wide Associations Studies have been carried out to find genetic associations and cause of diseases from slightly different base among the individuals. It is important to identify occurrence of slight variations for polymorphisms of individuals. In this paper, we introduce an analysis and visualization tool for specific variation pattern identification of polymorphisms in nucleotide sequences and show the validity of the tool by applying it to analyzing nucleotide sequences of subcultured pOka strain of varicella-zoster virus. The tool is expected to help efficiently explore allele frequency variations and genetic factors within a species.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.3
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• pp.519-529
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• 2019

Nowadays, intelligent Android malware applies anti-analysis techniques to hide malicious behaviors and make it difficult for anti-virus vendors to detect its presence. Malware can use background components to hide harmful operations, use activity-alias to get around with automation script, or wipe the logcat to avoid forensics. During our study, several static analysis tools can not extract these hidden components like main activity, and dynamic analysis tools also have problem with code coverage due to partial execution of android malware. In this paper, we design and implement a system to analyze intelligent malware that uses anti-analysis techniques to improve detection rate of evasive malware. It extracts the hidden components of malware, runs background components like service, and generates all the intent events defined in the app. We also implemented a real-time logging system that uses modified logcat to block deleting logs from malware. As a result, we improve detection rate from 70.9% to 89.6% comparing other container based dynamic analysis platform with proposed system.

• Journal of Convergence for Information Technology
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• v.9 no.3
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• pp.8-15
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• 2019

Recently, the importance of pre-shipment quality inspection has been emphasized due to the increase of STB supply. In this paper, we propose a method to support automation of quality inspection through simultaneous multi-channel input of STB video signal. The proposed method extracts a fingerprint using the center scan line of the image after stable video shot boundary detection using CeLDP combining color information and LDP code and performs synchronization between input video channels. The proposed method shows stronger shot boundary detection performance than the conventional shot detection method. Through the experiments applied to the real environment, it is possible to secure reliability and real-time quality check for synchronization between multi-channel inputs required for STB quality inspection. Also, based on the proposed method, we intend to study a large-scale quality inspection method in the future and propose a more effective quality inspection system.

• Journal of Convergence for Information Technology
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• v.9 no.7
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• pp.33-40
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• 2019

As aerospace industry has been activated recently, it is required to commercialize composite analysis software. Until now, commercial software has been mainly used for analyzing composites, but it has been difficult to use due to high price and limited functions. In order to solve this problem, automatic analysis software for both in-plane and corner radius strength, which are all made on-line and generalized, has recently been developed. However, these have the disadvantage that they can not be analyzed simultaneously with multiple failure criteria. In this paper, we propose a method to greatly improve the processing speed while simultaneously handling the analysis of multiple failure criteria using a parallel processing platform that only works with a GPU equipped with a CUDA core. We have obtained satisfactory results when the analysis speed is experimented on the vast structure data.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.4
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• pp.531-540
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• 2019

Existing dozer productivity computation models use different input variables, formulas, productivity correction factors, and experimental data source. This paper presents a method that characterizes the productivity outputs obtained by the PLS model and the Caterpillar model that are accepted as industry standards. The method identifies the input variables to be collected from the site, the performance charts to be referenced, and the formulas and implements them in a single computational tool. This study verifies that the PLS model may replace the manual computational process of Caterpillar model by eliminating reliance on graphics manipulation. Replacing the Caterpillar model with the PLS model and implementing the process as a function contributes to assess the productivity of a dozer timely by encouraging to utilize real-time information collected directly from the site. This study allows researchers and practitioners to effectively deal with the values of productivity correction factors collected from the job site and to control the productivity. The practicality and effectiveness of the method have been validated by applying to a project case.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.2
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• pp.127-132
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• 2019

In this paper, we propose a visual inspection method of automotive parts for injection molding to improve the appearance quality and productivity of automotive parts. Exterior inspection of existing injection molding automobile parts was generally done by manual sampling inspection by human. First, we applied the edge-tolerance vision inspection algorithm ([1] - [4]) for vision inspection of electronic components (TFT-LCD and PCB) And we propose a new visual inspection method to overcome the problem. In the proposed visual inspection, the inspection images of the parts to be inspected are aligned on the basis of the reference image of good quality. Then, after partial adaptive binarization, the binary block matching algorithm is used to compare the good binary image and the test binary image. We verified the effectiveness of the edge-tolerance vision check algorithm and the proposed appearance vision test method through various comparative experiments using actual developed equipment.