• Journal of Radiopharmaceuticals and Molecular Probes
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• v.2 no.2
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• pp.103-107
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• 2016

Solid phase extraction (SPE) purification method is the efficient and well-known tool for automated [$^{11}C$]acetate synthesis. A fully automated homemade module adopting the SPE method and 'pinch' valves was developed very economically with a universal interface board, a relay card and an open source programmable logic controller. The radiochemical yield of the optimized [$^{11}C$]acetate synthesis by this system was $58.8{\pm}2.1%$ (n=10, decay-corrected) from $15.5{\pm}0.19GBq$ of $[^{11}C]CO_2$ as starting activity, and total synthetic time was 15 minutes. HPLC analysis showed its high radiochemical purity as $97.4{\pm}1.1%$ without possible by-products.

• ETRI Journal
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• v.44 no.4
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• pp.613-623
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• 2022

Autism spectrum disorder (ASD) is a developmental disorder associated with cognitive and neurobehavioral disorders. It affects the person's behavior and performance. Autism affects verbal and non-verbal communication in social interactions. Early screening and diagnosis of ASD are essential and helpful for early educational planning and treatment, the provision of family support, and for providing appropriate medical support for the child on time. Thus, developing automated methods for diagnosing ASD is becoming an essential need. Herein, we investigate using various machine learning methods to build predictive models for diagnosing ASD in children using facial images. To achieve this, we used an autistic children dataset containing 2936 facial images of children with autism and typical children. In application, we used classical machine learning methods, such as support vector machine and random forest. In addition to using deep-learning methods, we used a state-of-the-art method, that is, automated machine learning (AutoML). We compared the results obtained from the existing techniques. Consequently, we obtained that AutoML achieved the highest performance of approximately 96% accuracy via the Hyperpot and tree-based pipeline optimization tool optimization. Furthermore, AutoML methods enabled us to easily find the best parameter settings without any human efforts for feature engineering.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.4
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• pp.785-802
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• 2017

As cyber threats using malicious code continue to increase, many security and vaccine companies are putting a lot of effort into analysis and detection of malicious codes. However, obfuscation techniques that make software analysis more difficult are applied to malicious codes, making it difficult to respond quickly to malicious codes. In particular, commercial obfuscation tools can quickly and easily generate new variants of malicious codes so that malicious code analysts can not respond to them. In order for analysts to quickly analyze the actual malicious behavior of the new variants, reverse obfuscation(=de-obfuscation) is needed to disable obfuscation. In this paper, general analysis methodology is proposed to de-obfuscate the software used by a commercial obfuscation tool, Themida. First, We describe operation principle of Themida by analyzing obfuscated executable file using Themida. Next, We extract original code and data information of executable from obfuscated executable using Pintool, DBI(Dynamic Binary Instrumentation) framework, and explain the implementation results of automated analysis tool which can deobfuscate to original executable using the extracted original code and data information. Finally, We evaluate the performance of our automated analysis tool by comparing the original executable with the de-obfuscated executable.

• The Transactions of the Korea Information Processing Society
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• v.2 no.2
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• pp.185-198
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• 1995

The development of automated quality evaluation tool is desperately needed to decrease the cost of maintenance, to measure quality of source program in developing course for the purpose of developing high quality software. Main goal in this paper is to develop the automated tool for software quality evaluation related with high quality and high reliability of software. In this paper, we proposed the four software quality model to evaluate software quality; functional -size model, understandability model, complexity model and object-oriented model. Also, we made a scanner and a parser to analyze the c and C＋＋ source program and to produce the metrics and function value. The measurement value is statistically analyzed for the distribution of the measurement value. we can extracted the characteristics of measurement value and this one is assisted to make scores of software quality evaluation. Finally, we made a software quality evaluation tool to support software evaluation activities.

• Journal of KIISE:Software and Applications
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• v.34 no.8
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• pp.752-762
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• 2007

The PSP (Personal Software Process) is developed to help developers make high-quality products through improving their personal process. With consistent measurement and analysis activity that the PSP suggests, developers can identify process deficiencies and make reliable estimates on effort and quality. However, due to the high-overhead and context-switching problem of manual data recording, developers have difficulties in collecting reliable data, which can lead wrong analysis results. On the other hand, the paper-based process guides of the PSP are inconvenient to navigate its process information and difficult to attach additional information. In this paper, we introduce a PSP supporting tool developed to handle these problems. The tool provides automated data collection facilities to help acquire reliable data, an EPG (Electronic Process Guide) for the PSP to provide easy access and navigation of the process information, and an experience repository to store development experience as additional information about the process.

• Journal of the Korea Safety Management & Science
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• v.8 no.6
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• pp.109-118
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• 2006

This paper proposes service layout strategy considering service characteristics by the use of benchmarking production system such as layout by P-Q chart, improvement tool, automated system, Toyota production system and lean production system. This paper represents operation methodology of statistical process control using control chart for service performance outcomes.

• Journal of Korea Multimedia Society
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• v.23 no.8
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• pp.986-1005
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• 2020

In this paper, we propose AnoVid, an automated video annotation tool based on deep neural networks, that automatically generates various meta data for each scene or shot in a long drama video containing rich elements. To this end, a novel meta data schema for drama video is designed. Based on this schema, the AnoVid video annotation tool has a total of six deep neural network models for object detection, place recognition, time zone recognition, person recognition, activity detection, and description generation. Using these models, the AnoVid can generate rich video annotation data. In addition, AnoVid provides not only the ability to automatically generate a JSON-type video annotation data file, but also provides various visualization facilities to check the video content analysis results. Through experiments using a real drama video, "Misaeing", we show the practical effectiveness and performance of the proposed video annotation tool, AnoVid.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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• pp.211-214
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• 2002

The detection of tool wear is very important in an automated manufacturing system. This paper presents a tool condition monitoring system based on the wavelet transform analysis of the AC servo motor current in a milling process. The current measurement is relatively simple and does not affect machining operations. The discrete wavelet transform was used to decompose the current of a spindle AC servo motor in the time and frequency domain. The feature vectors were extracted from the decomposed signals and compared to clarity normal and wear conditions. The results show the feasibility of the wavelet transform analysis for the tool condition monitoring.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.58 no.2
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• pp.95-100
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• 2009

Recent advances in computer technology have brought more dependence on software to railway systems. Hence, the safety assurance of the vital software running on the railway system is very critical task and yet, not many works have been done. While much efforts have been reported to improve electronic hardware's safety, not so much systematic approaches to evaluate software's safety. In this paper, we suggested an automated analysis tool for S/W change impact in railway system, and presented its result of implementation. The analysis items in the implemented tool had referred to the international standards in relation to the software for railway system, such as IEC 61508 and IEC 62279. In these international standards, 'change impact analysis' for railway system S/W has to be required mandatorily. The proposed tool can be utilized at the assessment stage and also the software development stage.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1992.04b
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• pp.299-308
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• 1992

Determining tool-approach directions is an important issue when an effort is made to transfer CAD data into manufacturing automatically. An algorithm is developed to determine whether a given part can be machined on a three-axis milling machine. lf a set of feasible tool-approach directions exists for a sculptured surface, the NC tool path and G-codes for machining the surface on a three-axis milling machine can be generated automatically by an NC tool path generation algorithm. The algorithm can be used for orientation and fixturing of the workpiece for interference free machining. The algorithm can also be applied to checking the translational separability of polyhedral parts in automatic assembly.