This study explores the integration of ChatGPT, OpenAI’s conversational AI, into English as a Foreign Language (EFL) classrooms at Korean universities, focusing on student interactions and language learning strategy preferences. It categorises interactions using the Strategy Inventory for Language Learning (SILL) and Strategic Self-Regulation (S2R) frameworks to evaluate the pedagogical effectiveness of AIassisted learning. Ninety-nine university students participated in training sessions with ChatGPT prompts tailored to different learning strategies. Data were collected through surveys, chat transcripts, and qualitative feedback. Results indicate frequent student interactions with ChatGPT, averaging 4.49 strategies in initial training chats. Compensatory strategies like error correction and adaptive difficulty received high ratings, while social strategies were rated lowest. Metacognitive strategies, especially planning and summarising, were also well-received. The study concludes that ChatGPT supports diverse learning strategies, enhancing linguistic competence and promoting self-regulated learning. However, limitations such as AI accuracy and authenticity issues highlight the need for continued human interaction in language education.

현재 존재하는 인공지능 기반 음악 생성에 관한 여러 모델과 연구는 수동 텍스트(Text) 기반 음악 생성에 대해 다루고 있다. 본 논문은 사용자의 편의성을 높이고, 창의적인 음악 생성 과정 을 더욱 원활하게 할 수 있도록 텍스트(TEXT) 프롬프트(Prompt) 자동화를 통한 음악 생성시 스템 방안을 제안한다. 그 방안으로 음원 파일을 통해 수집한 음악 분석 및 데이터화와 가사 정보에서 추출한 키워드를 기반한 장르, 가수, 앨범 등의 정보가 포함된 데이터셋(Dataset)을 구축 후, 파이썬(Python)의 자연어 처리 방법인 Konlpy를 사용하여 가사 데이터를 토큰화하고, TF-IDF(Term Frequency-Inverse Document Frequency) 벡터화를 통해 중요한 단어를 추 출한다. 또한, MFCC, 템포 등의 특징 데이터셋을 통하여 모델을 통한 감정을 예측하고, CNN 모델 및 Chatgpt를 활용한 텍스트 프롬프트를 자동생성하는 방법을 구현하여, MusicGen 모델 을 사용한 자동화 생성 프롬프트 기반 음악을 생성한다. 본 텍스트 프롬프트 자동 생성 화를 통한 음악 생성 연구의 결과는 음악 데이터 분석 및 생성 분야에 기여될 것으로 기대한다.

According to Article 4 and 5 of the Nuclear Safety and Security Commission (NSSC) Notice No. 2020-6, radioactive waste packages should be classified by radioactive levels, and finally permanently shipped to underground or surface disposal facilities. The level of the radioactive waste package is determined based on the concentrations of the radionuclides suggested in Article 8 of NSSC Notice No. 2021-26. Since most of the radionuclides in radioactive wastes are beta nuclides, chemical separation and quantification of the target nuclides are essential. Conventional methods to classify chemically non-volatile radionuclides such as Tc-99, Sr-90, Nb- 94, Fe-55 take a lot of time (about 5 days) and have low efficiency. An automated non-volatile nuclide analysis system based on the continuous chemical separation method of radionuclides has been developed to compensate for this disadvantages of the conventional method in this study. The features of the automated non-volatile nuclide separation system are as follows. First, the amount of secondary waste generated during the chemical separation process is very small. That is, by adopting an open-bed resin column method instead of a closed-bed resin column method, additional fittings and connector are unnecessary during the chemical separation. In addition, because the peristaltic pump is supplied for the sample and solution respectively, it is great effective to prevent cross-contamination between radioactive samples and the acid stock solution for analysis. Second, the factors that may affect results, such as solution amount, operating time and flow rate, are almost constant. By mechanically controlling the flow rate precisely, the operating time and additional factors required during the separation process can be adjusted and predicted in advance, and the uncertainty of the chemical separation process can be significantly reduced. Finally, it is highly usable not only in the continuous separation process but also in the individual separation process. It can be applied to the individual separation process because the user can set the individual sequence using the program. As a result of the performance evaluation of the automation system, recovery rates of about 80–90% and reproducibility within 5% were secured for all of the radionuclides. Furthermore, it was confirmed that the actual work time was reduced by more than 50% compared to the previous manual method. (It was confirmed that the operation time required during the separation process was reduced from 6 days to 3 days.) Based on these results, the automation system is expected to improve the safety of workers in radiation exposure, reduce human error, and improve data reliability.

The purpose of this study was to examine the relative effectiveness of immediate feedback and informational prompt on safe sitting behaviors that may cause VDT syndromes. Participants were three white color workers and an ABCB within-subject design was adopted. Safety Posture System was developed specifically for the present study. The system could detect participants' unsafe sitting postures using sensors and provide feedback and prompt on the computer monitors. The results indicated that both immediate feedback and informational prompt considerably increased safe sitting behaviors. More importantly, the immediate feedback was more effective than the informational prompt in increasing safe sitting behaviors.

NIPS 시스템은 중성자 핵반응 결과 방출되는 즉발 감마선을 정량적으로 측정하는 장치이며 고체 및 액체 폐기물 중 존재하는 다양한 원소를 비파괴적으로 분석할 수 있는 장점이 있다. 본 연구에서는 NIPS 시스템에 이용된 고순도반도체 검출기의 계측효율을 Ba 및 Eu 방사성 동위원소 선원과 Cl(n, ) Cl 핵반응 시 발생되는 즉발감마선을 이용하여 80 keV에서 8 MeV까지 넓은 영역에 대하여 구하였다. Cl(n, ) Cl 핵반응을 이용한 고에너지 감마선의 계측효율은 즉발감마선의 방사능 값을 정확히 알 수 없기 때문에 저 에너지 영역에서 정확히 알고 있는 검출기 효율곡선에 규격화시켜 전 에너지 영역에서의 효율보정곡선을 구하였다. 또한 KCl 표준용액에 Cf 중성자 선원을 조사시켜 표준용액으로부터 방출되는 즉발 감마선을 고순도반도체 검출기로 측정하고 광대역 계측효율 곡선을 이용하여 수용액 시료에서의 평균 열중성자 속을 예측하였다. NIPS 측정시스템은 주변 재료 물질의 핵반응으로 방출되는 감마선 background를 줄이기 위해 두 개의 고순도반도체 검출기를 이용한 동시계수 장치가 고안되었으며, 동시계수 모드에서의 계측효율도 함께 고려되었으며, 표준선원을 이용하여 전 계수 또는 동시계수모드에서의 background에 대한 측정감도를 비교하였다.다.

68Ga 방사성 핵종은 68Ge/68Ga 제너레이터에서 생산되는 양전자 방출핵종으로서 PET 검사에 이용되는 방사성 핵종이다. 68Ga은 67.8분의 반감기를 가지고 88.9 %의 β+ 붕괴와 11.1 %의 전자포획으로 68Zn으로 붕괴된다. β+ 붕괴 과정에서 87.7 %는 기저상태의 68Zn로 붕괴되며, 1.2 %는 여기상태의 68Zn로 붕괴된다. 여기상태의 68Zn은 1.077 Mev의 γ선을 방출하며 기저상태의 68Zn가 된다. 이때 방출되는 1.077 Mev의 γ선을 Prompt Gamma라 하며, Prompt Gamma-ray가 환자와 상호작용하게 되면 저에너지 γ선의 산란선이 발생되게 되는데 이 산란선이 PET의 동시계수 회로에 검출되어 질 수 있다. 이 연구의 목적은 68Ga을 이용하는 PET검사 중 신경내분비 종양진단에 사용되는 68Ga-DOTATOC PET/CT영상에 Prompt Gamma-ray 보정 전 후의 표준섭취계수(SUV)를 평가해 보고자 하였다. 68Ga-DOTATOC PET/CT를 시행한 15명의 환자에 대해서 병변부위(Pancreas, Liver, Thoracic Spine, Brain)와 정상으로 섭취되는 조직(Pituitary, Lung, Liver, Spleen, Kidney, Intestine)의 SUVmax와 SUVmean을 비교하였으며, 임상영상의 정량적 평가를 위해 Target to Background Ratio(TBR)을 산출하여 비교하였다. Prompt Gamma-ray 보정 후 Thoracic Spine을 제외한 병변부위와 Pituitary를 제외한 정상조직에서 SUVmax, SUVmean은 높은 값을 나타내었으며, TBR은 Prompt Gamma-ray 보정 전 후 각각 51.51±49.28, 55.50±53.12로 보정 후 높은 값을 나타냈다. (p<0.0001)

A prompt gamma-ray neutron activation (PGNA) system was simulated by the Monte Carlo N-Particle transport code (MCNP-4A) to estimate the level at which the scattered photon fluence rate, the absolute efficiency of the HPGe-detector, the volume of the concrete sample and the 35Cl(n,γ) reaction rate in this sample contribute to the count rate in the NaCl concentration measurement. The n-γ fluence rates at the ST-2 beam tube exit of the HANARO reactor were used as input data, and the GAMMA-X type HPGe detector was modeled to tally 1.1649 MeV γ-rays emitted from the 35Cl(n,γ) reaction in the concrete sample. For three cylindrical concrete samples of 13.8, 46.8 and 157.1 cm3 volumes, respectively, the relations between the NaCl weight fractions of 0.1, 1, 2 and 5 % in each of the concrete samples and the 1.1649 MeV pulses created in the HPGe detector model were studied. As a result, it was found that the count rate at the same NaCl concentration nearly depends on the volume of the samples in a simulated condition of the same NaCl concentration samples, and that the linearities of the NaCl concentration calibration curves were reasonable in the narrow range of the NaCl weight fraction.