• English Language & Literature Teaching
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• v.9 no.1
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• pp.153-171
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• 2003

The scores of TOEFL, TOEIC, and TEPS have been increasingly used for many purposes in Korea. In particular, these test scores are being used as a predictor for determining readiness for and success in college work, or as a measure of the testees' overall English proficiency. Nonetheless, studies have rarely proposed that the validity of the test scores is used for either purpose. As a preliminary step to explore the predictive validity of the test scores, we collected the scores of TOEFL, TOEIC, and TEPS from thirty students of a university as well as their cumulative grade point averages (GPAs). The correlations between the test scores and GPAs show that TOEFL will be most likely to have the highest validity coefficient as a predictor for determining success in college work as well as a measure of overall English proficiency. Although this study has a few limitations such as the small number of participants, their homogeneousness as a group, etc., it provides some insight into the use of the three tests for college admissions and measurement of overall English proficiency and suggests need for conducting further validation studies in these areas.

• The Journal of the Acoustical Society of Korea
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• v.16 no.1
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• pp.100-103
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• 1997

In this paper, we analyze the time delayed effect of speech feature. Here, the time delayed effect means that the current feature vector of speech is under the influence of the previous feature vectors. In this paper, we use a set of LPC driven cepstal coefficients and evaluate the time delayed effect of cepstrum with the performance of the speech recognition system. For the experiments, we used the speech database consisting of 22 words which uttered by 50 male speakers. The speech database uttered by 25 male speakers was used for training, and the other set was used for testing. The experimental results show that the time delayed effect is large in the lower orders of feature vector but small in the higher orders.

• Nuclear Engineering and Technology
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• v.50 no.5
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• pp.780-787
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• 2018

This article presents a security module based on a field programmable gate array (FPGA) to mitigate man-in-the-middle cyber attacks. Nowadays, the FPGA is considered to be the state of the art in nuclear power plants I&C systems due to its flexibility, reconfigurability, and maintainability of the FPGA technology; it also provides acceptable solutions for embedded computing applications that require cybersecurity. The proposed FPGA-based security module is developed to mitigate information-gathering attacks, which can be made by gaining physical access to the network, e.g., a man-in-the-middle attack, using a cryptographic process to ensure data confidentiality and integrity and prevent injecting malware or malicious data into the critical digital assets of a nuclear power plant data communication system. A model-based system engineering approach is applied. System requirements analysis and enhanced function flow block diagrams are created and simulated using CORE9 to compare the performance of the current and developed systems. Hardware description language code for encryption and serial communication is developed using Vivado Design Suite 2017.2 as a programming tool to run the system synthesis and implementation for performance simulation and design verification. Simple windows are developed using Java for physical testing and communication between a personal computer and the FPGA.

• Journal of Physiology & Pathology in Korean Medicine
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• v.21 no.3
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• pp.789-793
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• 2007

To evaluate the effectiveness of cupping and bloodletting therapy in the treatment of musculoskeletal diseases. Systematic searches were conducted on KSI, KISTI, DB Pia, KIOM Database, and Koreamed until January 2007 Hand-searches included conference proceedings and our own files. There were no restrictions regarding the language of journals published in Korea. Controlled trials of dry cupping, wet cupping, or blood letting for patients with musculoskeletal disease were considered for inclusion. Trials testing other forms of dry cupping therapy were included. Methodological quality was assessed by two doctors. 20 possibly relevant studies were identified and 5 studies were included. One trial tested wet cupping for ankle sprain and reported positive result. Two trials tested blood letting for low back pain, one was positive and the other one was neutral. One trial tested the types of dry cupping for low back pain, and Ki-gong cupping therapy was superior to other two types of cupping. One trial compared wet cupping with dry cupping for low back pain and the result was negative. The effectiveness of bloodletting plus acupuncture for treating patients with low back pain is superior to acupuncture in spite of low quality. One trial of wet cupping for ankle sprain had effects in reducing pain. However, I suggest that the rigorous RCTs of cupping and blood letting therapy will be conducted in well designed features.

• Phonetics and Speech Sciences
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• v.11 no.3
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• pp.1-7
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• 2019

Korean (L1)-English (L2) bilingual adults' and children's production of Korean and English stops was examined to determine the age effects and L2 experience on the development of L1 and L2 stop contrasts. Four groups of Seoul Korean speakers (experienced and inexperienced adult and child groups) and two groups of age-matched native English speakers participated. The overall results of voice onset time (VOT) and fundamental frequency (F0) of phrase-initial stops in Korean and word-intial stops in English showed a delay in the acquisition of L1 due to the dominant exposure to L2. Significantly longer VOT and lower F0 for aspirated stops as well as high temporal variability across repetitions of lenis stops were interpreted to indicate a strong effect of English on Korean stop contrasts for bilingual children. That is, the heavy use of VOT for Korean stop contrasts shows bilingual children's attention to the acoustic cue that are primarily employed in the dominant L2. Furthermore, inexperienced children, but not adults, were shown to create new L2 categories that are distinctive from the L1 within 6 months of L2 experience, suggesting greater independence between the two phonological systems. The implications of bilinguals' age at the time of testing to the degree and direction of L1-L2 interaction are further discussed.

• Phonetics and Speech Sciences
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• v.12 no.4
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• pp.19-25
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• 2020

This study examined thirty-one Korean students' pronunciation of an English passage using a speech recognition application, Speechnotes, and two Canadian raters' evaluations of their speech according to the International English Language Testing System (IELTS) band criteria to assess the possibility of using the application as a teaching aid for pronunciation education. The results showed that the grand average percentage of correctly recognized words was 77.7%. From the moderate recognition rate, the pronunciation level of the participants was construed as intermediate and higher. The recognition rate varied depending on the composition of the content words and the function words in each given sentence. Frequency counts of unrecognized words by group level and word type revealed the typical pronunciation problems of the participants, including fricatives and nasals. The IELTS bands chosen by the two native raters for the rainbow passage had a moderately high correlation with each other. A moderate correlation was reported between the number of correctly recognized content words and the raters' bands, while an almost a negligible correlation was found between the function words and the raters' bands. From these results, the author concludes that the speech recognition application could constitute a partial aid for diagnosing each individual's or the group's pronunciation problems, but further studies are still needed to match human raters.

• Journal of Biomedical Engineering Research
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• v.42 no.4
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• pp.186-192
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• 2021

In this paper, we evaluated prediction accuracy of Euler angle spectrograph classification method using a convolutional neural networks (CNN) for hand gesture recognition in augmented reality (AR) cognitive rehabilitation system based on Leap Motion Controller (LMC). Hand gesture recognition methods using a conventional support vector machine (SVM) show 91.3% accuracy in multiple motions. In this paper, five hand gestures ("Promise", "Bunny", "Close", "Victory", and "Thumb") are selected and measured 100 times for testing the utility of spectral classification techniques. Validation results for the five hand gestures were able to be correctly predicted 100% of the time, indicating superior recognition accuracy than those of conventional SVM methods. The hand motion recognition using CNN meant to be applied more useful to AR cognitive rehabilitation training systems based on LMC than sign language recognition using SVM.

• International Journal of Computer Science & Network Security
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• v.23 no.8
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• pp.77-84
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• 2023

The utilization of GPUs on general-purpose computers is currently on the rise due to the increase in its programmability and performance requirements. The utility of tools like NVIDIA's CUDA have been designed to allow programmers to code algorithms by using C-like language for the execution process on the graphics processing units GPU. Unfortunately, many of the performance and correctness bugs will happen on parallel programs. The CUDA tool support for the parallel programs has not yet been actualized. The use of a dynamic analyzer to find performance and correctness bugs in CUDA programs facilitates the execution of sophisticated processes, especially in modern computing requirements. Any race conditions bug it will impact of program correctness and the share memory bank conflicts to improve the overall performance. The technique instruments the programs in a way that promotes accessibility of the memory locations accessed by different threads well as to check for any bugs in the code of a program. The instrumented source code will be used initiated directly in the device emulation code of CUDA to send report for the user about all errors. The current degree of automation helps programmers solve subtle bugs in highly complex programs or programs that cannot be analyzed manually.

• Journal of Information Technology Applications and Management
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• v.31 no.3
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• pp.149-163
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• 2024

As conversational AI systems such as ChatGPT have become more advanced, researchers are exploring ways to use them in education. However, we need effective ways to evaluate these systems before allowing them to help teach students. This study proposes a detailed framework for testing conversational AI across three important criteria as follow. First, specialized benchmarks that measure skills include giving clear explanations, adapting to context during long dialogues, and maintaining a consistent teaching personality. Second, adaptive standards check whether the systems meet the ethical requirements of privacy, fairness, and transparency. These standards are regularly updated to match societal expectations. Lastly, evaluations were conducted from three perspectives: technical accuracy on test datasets, performance during simulations with groups of virtual students, and feedback from real students and teachers using the system. This framework provides a robust methodology for identifying strengths and weaknesses of conversational AI before its deployment in schools. It emphasizes assessments tailored to the critical qualities of dialogic intelligence, user-centric metrics capturing real-world impact, and ethical alignment through participatory design. Responsible innovation by AI assistants requires evidence that they can enhance accessible, engaging, and personalized education without disrupting teaching effectiveness or student agency.

• International journal of advanced smart convergence
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• v.13 no.2
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• pp.205-213
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• 2024

This study uses a large language model (LLM) to identify Aristotle's rhetorical principles (ethos, pathos, and logos) in COVID-19 information on Naver Knowledge-iN, South Korea's leading question-and-answer community. The research analyzed the differences of these rhetorical elements in the most upvoted answers with random answers. A total of 193 answer pairs were randomly selected, with 135 pairs for training and 58 for testing. These answers were then coded in line with the rhetorical principles to refine GPT 3.5-based models. The models achieved F1 scores of .88 (ethos), .81 (pathos), and .69 (logos). Subsequent analysis of 128 new answer pairs revealed that logos, particularly factual information and logical reasoning, was more frequently used in the most upvoted answers than the random answers, whereas there were no differences in ethos and pathos between the answer groups. The results suggest that health information consumers value information including logos while ethos and pathos were not associated with consumers' preference for health information. By utilizing an LLM for the analysis of persuasive content, which has been typically conducted manually with much labor and time, this study not only demonstrates the feasibility of using an LLM for latent content but also contributes to expanding the horizon in the field of AI text extraction.