• Asian Pacific Journal of Cancer Prevention
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• v.13 no.3
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• pp.927-930
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• 2012

Background and Objectives: Artificial neural networks (ANNs) are flexible and nonlinear models which can be used by clinical oncologists in medical research as decision making tools. This study aimed to predict distant metastasis (DM) of colorectal cancer (CRC) patients using an ANN model. Methods: The data of this study were gathered from 1219 registered CRC patients at the Research Center for Gastroenterology and Liver Disease of Shahid Beheshti University of Medical Sciences, Tehran, Iran (January 2002 and October 2007). For prediction of DM in CRC patients, neural network (NN) and logistic regression (LR) models were used. Then, the concordance index (C index) and the area under receiver operating characteristic curve (AUROC) were used for comparison of neural network and logistic regression models. Data analysis was performed with R 2.14.1 software. Results: The C indices of ANN and LR models for colon cancer data were calculated to be 0.812 and 0.779, respectively. Based on testing dataset, the AUROC for ANN and LR models were 0.82 and 0.77, respectively. This means that the accuracy of ANN prediction was better than for LR prediction. Conclusion: The ANN model is a suitable method for predicting DM and in that case is suggested as a good classifier that usefulness to treatment goals.

• Journal of the Korea Society for Simulation
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• v.15 no.1
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• pp.11-17
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• 2006

This paper shows a case study of designing a PLC logic simulator that was developed to simulate and verify PLC control programs for nuclear plant systems. The nuclear control system requires strict restrictions rather than normal process control system does, as it works with a high-risky and dangerous nuclear plant. One is that it should assure the safeness of the control programs by exploiting severe testing. The other restriction is that the control programs should be executed fast enough such that they could control multi devices concurrently in real-time. To cope with these restrictions, we devised a logic compiler which generates C-code programs from given PLC logic programs. Once the logic program was translated into C-code, the program could be analyzed by conventional software analysis tools and could be used to construct a fast logic simulator after cross-compiling, in fact, that is a kind of compiled-code simulator.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.4
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• pp.807-819
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• 2019

Greybox fuzzing is known as an effective method to discover unknown security flaws reside in software and has been actively researched today. However, most of greybox fuzzing tools require an executable file. Because of this, a library, which cannot be executed by itself requires an additional executable file for greybox fuzzing. Generating such an executable file is challengeable because it requires both understanding of the library and fuzzing. In this research, we suggest the approach to generate an executable file automatically for a library and implement this approach as a tool based on the LLVM framework. This tool shows that executable files and seed files can be generated automatically by static/dynamic analysis of a unit test in the target project. A generated executable file is compatible with various greybox fuzzers like AFL because it has a common interface for greybox fuzzers. We show the performance of this tool as code coverage and discovered unknown security bugs using generated executable files and seed files from open source projects through this tool.

• Journal of KIBIM
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• v.13 no.3
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• pp.21-29
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• 2023

ChatGPT, a chatbot based on GPT large language models, has gained immense popularity among the general public as well as domain professionals. To assess its proficiency in specialized fields, ChatGPT was tested on mainstream exams like the bar exam and medical licensing tests. This study evaluated ChatGPT's ability to answer questions related to Building Information Modeling (BIM) by testing it on Korea's BIM expertise exam, focusing primarily on multiple-choice problems. Both GPT-3.5 and GPT-4 were tested by prompting them to provide the correct answers to three years' worth of exams, totaling 150 questions. The results showed that both versions passed the test with average scores of 68 and 85, respectively. GPT-4 performed particularly well in categories related to 'BIM software' and 'Smart Construction technology'. However, it did not fare well in 'BIM applications'. Both versions were more proficient with short-answer choices than with sentence-length answers. Additionally, GPT-4 struggled with questions related to BIM policies and regulations specific to the Korean industry. Such limitations might be addressed by using tools like LangChain, which allow for feeding domain-specific documents to customize ChatGPT's responses. These advancements are anticipated to enhance ChatGPT's utility as a virtual assistant for BIM education and modeling automation.

• Phonetics and Speech Sciences
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• v.6 no.2
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• pp.73-79
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• 2014

Alveolar fricative sounds /s/ and /s'/ are learned last for normal children in the speech development process for Koreans. These are especially difficult to articulate for hearing-impaired children often causing articulation errors. The acoustic phonetic evaluation uses testing tools to provide indirect and object information. These objective resources can be compared with standardized resources on speech when interpreting the results of a test. However, most previous studies in Korea did not consider acoustic studies that used the spectrum moment values of hearing-impaired children. Therefore, this study was conducted to compare the characteristics of hearing-impaired children's pronunciation of fricative sounds using spectrum moment values. For this purpose, the study selected a total of 10 hearing-impaired children (5 boys and 5 girls) currently in 3rd or 5th grade and attending one of the elementary schools in Seoul or Gyeonggi-do. For the selection process, their age, type of hearing aid, implantation of hearing aid (CI) before two years of age, hearing capacity (dB) before and after wearing the hearing aid, duration of speech rehabilitation, and time of learning alveolar fricative sounds were all considered. Also, 10 normal children (5 boys and 5 girls) were selected among 3rd or 5th grade students attending one of the elementary schools in Seoul or Gyeonggi-do. The subjects were asked to read the carrier sentence, "I say _______," including a list of 12 meaningless syllables composed of CV and VCV syllables, including alveolar fricative sounds /s/ and /s'/ and vowels /a/, /i/, and /u/. The recorded resources were processed through the Time-frequency Analysis Software Program to measure M1 (mean), M2 (variance), M3 (skewness), and M4 (kurtosis) of the fricative noise. No significant differences were found when comparing spectrum threshold values in the acoustic phonetic characteristics of hearing-impaired children and normal children in alveolar fricative sound pronunciation according to vowels /a/, /i/, and /u/, alveolar fricative sounds /s/ and /s'/, and syllable structure (CV, VCV) other than, for M3 in the comparison of groups according to disability. In the comparison of syllable structures, there were statistically significant differences in M1, M2, M3, and M4 with clinical significance. However, there was no significant difference in results when comparing the alveolar fricative sounds according to the vowels.

• The Journal of Korean Society for Radiation Therapy
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• v.29 no.2
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• pp.65-73
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• 2017

Purpose: Machine Performance Check (MPC) is a self-checking software based on the Electronic Portal Imaging Device (EPID) to measure daily beam outputs without external installation. The purpose of this study is to verify the usefulness of MPC by comparing and correlating daily beam output of QA Beamchecker PLUS. Materials and Methods: Linear accelerator (Truebeam 2.5) was used to measure 10 energies which are composed of photon beams(6, 10, 15 MV and 6, 10 MV-FFF) and electron beams(6, 9, 12, 16 and 20 MeV). A total of 80 cycles of data was obtained by measuring beam output measurement before treatment over five months period. The Pearson correlation coefficient was used to evaluate the consistency of the beam output between the MPC and the QA Beamchecker PLUS. In this study, if the Pearson correlation coefficient is; (1) 0.8 or higher, the correlation is very strong (2) between 0.6 and 0.79, the correlation is strong (3) between 0.4 and 0.59, the correlation is moderate (4) between 0.2 and 0.39, the correlation is weak (5) lower than 0.2, the correlation is very weak. Results: Output variations observed between MPC and QA Beamchecker PLUS were within 2 % for photons and electrons. The beam outputs variations of MPC were $0.29{\pm}0.26%$ and $0.30{\pm}0.26%$ for photon and electron beams, respectively. QA Beamchecker PLUS beam outputs were $0.31{\pm}0.24%$ and $0.33{\pm}0.24%$ for photon and electron beams, respectively. The Pearson correlation coefficient between MPC and QA Beamchecker PLUS indicated that photon beams were very strong at 15 MV, and strong at 6 MV, 10 MV, 6 MV-FFF and 10 MV-FFF. For electron beams, the Pearson correlation coefficient were strong at 16 MeV and 20 MeV, moderate at 9 MeV and 12 MeV, and very weak at 6 MeV. Conclusion: MPC showed significantly strong correlation with QA Beamchecker PLUS when testing with photon beams and high-energy electron beams in the evaluation of daily beam output, but the correlation when testing with low-energy electron beams (6 MeV) appeared to be low. However, MPC and QA Beamchecker PLUS are considered to be suitable for checking daily beam output, as they performed within 2 % of beam output consistency during the observation. MPC which can perform faster than the conventional daily beam output measurement tool, is considered to be an effective method for users.