• 제목/요약/키워드: prompt

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UK Civil Nuclear Decommissioning, a Blueprint for Korea's Nuclear Decommissioning Future?: Part II - UK's Progress and Implications for Korea

  • Foster, Richard I.;Park, June Kyung;Lee, Keunyoung;Seo, Bum-Kyoung
    • 방사성폐기물학회지
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    • 제20권1호
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    • pp.65-98
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    • 2022
  • The nuclear legacy that remains in the United Kingdom (UK) is complex and diverse. Consisting of legacy ponds and silos, redundant reprocessing plants, research facilities, and non-standard or one-off reactor designs, the clean-up of this legacy is under the stewardship of the Nuclear Decommissioning Authority (NDA). Through a mix of prompt and delayed decommissioning strategies, the NDA has made great strides in dealing with the UK's nuclear legacy. Fuel debris and sludge removal from the legacy ponds and silos situated at Sellafield, as part of a prompt decommissioning strategy for the site, has enabled intolerable risks to be brought under control. Reactor defueling and waste retrievals across the Magnox fleet is enabling their transition to a period of care and maintenance; accelerated through the adopted 'Lead and Learn' approach. Bespoke decommissioning methods implemented by the NDA have also enabled the relevant site licence companies to tackle non-standard reactor designs and one-off wastes. Such approaches have potential to influence and shape nuclear decommissioning decision making activities globally, including in Korea.

Neutronic design of pulsed neutron facility (PNF) for PGNAA studies of biological samples

  • Oh, Kyuhak
    • Nuclear Engineering and Technology
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    • 제54권1호
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    • pp.262-268
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    • 2022
  • This paper introduces a novel concept of the pulsed neutron facility (PNF) for maximizing the production of the thermal neutrons and its application to medical use based on prompt gamma neutron activation analysis (PGNAA) using Monte Carlo simulations. The PNF consists of a compact D-T neutron generator, a graphite pile, and a detection system using Cadmium telluride (CdTe) detector arrays. The configuration of fuel pins in the graphite monolith and the design and materials for the moderating layer were studied to optimize the thermal neutron yields. Biological samples - normal and cancerous breast tissues - including chlorine, a trace element, were used to investigate the sensitivity of the characteristic γ-rays by neutron-trace material interactions and the detector responses of multiple particles. Around 90 % of neutrons emitted from a deuterium-tritium (D-T) neutron generator thermalized as they passed through the graphite stockpile. The thermal neutrons captured the chlorines in the samples, then the characteristic γ-rays with specific energy levels of 6.12, 7.80 and 8.58 MeV were emitted. Since the concentration of chlorine in the cancerous tissue is twice that in the normal tissue, the count ratio of the characteristic g-rays of the cancerous tissue over the normal tissue is approximately 2.

Determining PGAA collimator plug design using Monte Carlo simulation

  • Jalil, A.;Chetaine, A.;Amsil, H.;Embarch, K.;Benchrif, A.;Laraki, K.;Marah, H.
    • Nuclear Engineering and Technology
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    • 제53권3호
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    • pp.942-948
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    • 2021
  • The aim of this work is to help inform the decision for choosing a convenient material for the PGAA (Prompt Gamma Activation Analysis) collimator plug to be installed at the tangential channel of the Moroccan Triga Mark II Research Reactor. Two families of materials are usually used for collimator construction: a mixture of high-density polyethylene (HDPE) with boron, which is commonly used to moderate and absorb neutrons, and heavy materials, either for gamma absorption or for fast neutron absorption. An investigation of two different collimator designs was performed using N-Particle Monte Carlo MCNP6.2 code with the ENDF/B-VII.1 and MCLIP84 libraries. For each design, carbon steel and lead materials were used separately as collimator heavy materials. The performed study focused on both the impact on neutron beam quality and the neutron-gamma background at the exit of the collimator beam tube. An analysis and assessment of the principal findings is presented in this paper, as well as recommendations.

The Effects of Construal Levels to Charity Retailing Communication

  • LEE, Jeonghoon;LEE, Han-Suk
    • 유통과학연구
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    • 제19권8호
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    • pp.81-89
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    • 2021
  • Purpose: Traditional charity retail needs to change its communication in the online environment. This article examines the effectiveness of communication by online charity organizations in terms of the type of messages being delivered. Research design, data and methodology: Study 1 based on a sample of 120 Korean adults, we investigated whether charity asking messages for domestic people, compared to those for foreign people, prompt more favorable evaluations when framed with low (vs. high) construal levels. In Study 2, with 120 Korean adults sample, we tested whether emotional message appeals prompt a more favorable response than rational messages when framed in a socially close. Results: According to the result of Study 1, for the domestic recipients, donation messages situated in the near, compared to the distant, future induced more favorable reactions from potential donors. Moreover, in Study 2, emotional (vs. rational) message appeals generated more positive donation intentions when they were framed in the socially close situation. Conclusions: This research contributes that differing consumer construal have important implications for how marketing communication might best gain charitable support. This suggests that marketers who design a donation message should consider message's appeal and type to activate the potential donors' willingness to participate in the campaign.

긴급차량 우선신호시스템 운영상의 문제점 도출과 개선방안에 관한 델파이 연구 (Delphi studies on the operational problems of the Emergency Vehicle Priority Signal System and improvement measures)

  • 김진현
    • 한국응급구조학회지
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    • 제26권3호
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    • pp.185-199
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    • 2022
  • Purpose: Prompt arrival of emergency vehicles at the scene is important. Therefore, special cases for emergency vehicles are being applied. However, there remain obstacles that obstruct the prompt arrival during dispatch. Methods: First, a literature review revealed five categories of problems with the emergency vehicle priority signal system. Then, the first Delphi survey was conducted to confirm the validity of the five categories. Further, a second Delphi survey was conducted to identify additional problems, and we used a 5-point Likert scale for a third Delphi survey. Results: A total of 92 items were extracted from preceding studies. The validity of the five categories was confirmed in the first Delphi survey. Then, 123 additional items were derived from the second Delphi survey, and the final 50 items were selected from 93 items obtained from the third Delphi survey. Conclusion: This study revealed problems and improvement measures for improving the operation of the emergency vehicle priority signal system that were not proposed in previous studies.

Prompting 기반 매개변수 효율적인 Few-Shot 학습 연구 (Parameter-Efficient Prompting for Few-Shot Learning)

  • 박은환;;서대룡;전동현;강인호;나승훈
    • 한국정보과학회 언어공학연구회:학술대회논문집(한글 및 한국어 정보처리)
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    • 한국정보과학회언어공학연구회 2022년도 제34회 한글 및 한국어 정보처리 학술대회
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    • pp.343-347
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    • 2022
  • 최근 자연어처리 분야에서는 BERT, RoBERTa, 그리고 BART와 같은 사전 학습된 언어 모델 (Pre-trained Language Models, PLM) 기반 미세 조정 학습을 통하여 여러 하위 과업에서 좋은 성능을 거두고 있다. 이는 사전 학습된 언어 모델 및 데이터 집합의 크기, 그리고 모델 구성의 중요성을 보여주며 대규모 사전 학습된 언어 모델이 각광받는 계기가 되었다. 하지만, 거대한 모델의 크기로 인하여 실제 산업에서 쉽게 쓰이기 힘들다는 단점이 명백히 존재함에 따라 최근 매개변수 효율적인 미세 조정 및 Few-Shot 학습 연구가 많은 주목을 받고 있다. 본 논문은 Prompt tuning, Prefix tuning와 프롬프트 기반 미세 조정 (Prompt-based fine-tuning)을 결합한 Few-Shot 학습 연구를 제안한다. 제안한 방법은 미세 조정 ←→ 사전 학습 간의 지식 격차를 줄일 뿐만 아니라 기존의 일반적인 미세 조정 기반 Few-Shot 학습 성능보다 크게 향상됨을 보인다.

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Monte-Carlo simulation for detecting neutron and gamma-ray simultaneously with CdZnTe half-covered by gadolinium film

  • J. Byun ;J. Seo ;Y. Kim;J. Park;K. Shin ;W. Lee ;K. Lee ;K. Kim;B. Park
    • Nuclear Engineering and Technology
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    • 제55권3호
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    • pp.1031-1035
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    • 2023
  • Neutron is an indirectly ionizing particle without charge, which is normally measured by detecting reaction products. Neutron detection system based on measuring gadolinium-converted gamma-rays is a good way to monitor the neutron because the representative prompt gamma-rays of gadolinium have low energies (79, 89, 182, and 199 keV). Low energy gamma-rays and their high attenuation coefficient on materials allow the simple design of a detector easier to manufacture. Thus, we designed a cadmium zinc telluride detector to investigate feasibility of simultaneous detection of gamma-rays and neutrons by using the Monte-Carlo simulation, which was divided into two parts; first was gamma-detection part and second was gamma- and neutron-simultaneous detection part. Consequently, we confirmed that simultaneous detection of gamma-rays and neutrons could be feasible and valid, although further research is needed for adoption on real detection.

Identification of Pb-Zn ore under the condition of low count rate detection of slim hole based on PGNAA technology

  • Haolong Huang;Pingkun Cai;Wenbao Jia;Yan Zhang
    • Nuclear Engineering and Technology
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    • 제55권5호
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    • pp.1708-1717
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    • 2023
  • The grade analysis of lead-zinc ore is the basis for the optimal development and utilization of deposits. In this study, a method combining Prompt Gamma Neutron Activation Analysis (PGNAA) technology and machine learning is proposed for lead-zinc mine borehole logging, which can identify lead-zinc ores of different grades and gangue in the formation, providing real-time grade information qualitatively and semi-quantitatively. Firstly, Monte Carlo simulation is used to obtain a gamma-ray spectrum data set for training and testing machine learning classification algorithms. These spectra are broadened, normalized and separated into inelastic scattering and capture spectra, and then used to fit different classifier models. When the comprehensive grade boundary of high- and low-grade ores is set to 5%, the evaluation metrics calculated by the 5-fold cross-validation show that the SVM (Support Vector Machine), KNN (K-Nearest Neighbor), GNB (Gaussian Naive Bayes) and RF (Random Forest) models can effectively distinguish lead-zinc ore from gangue. At the same time, the GNB model has achieved the optimal accuracy of 91.45% when identifying high- and low-grade ores, and the F1 score for both types of ores is greater than 0.9.

Over the Rainbow: How to Fly over with ChatGPT in Tourism

  • Taekyung Kim
    • Journal of Smart Tourism
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    • 제3권1호
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    • pp.41-47
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    • 2023
  • Tourism and hospitality have encountered significant changes in recent years as a result of the rapid development of information technology (IT). Customers now expect more expedient services and customized travel experiences, which has intensified competition among service providers. To meet these demands, businesses have adopted sophisticated IT applications such as ChatGPT, which enables real-time interaction with consumers and provides recommendations based on their preferences. This paper focuses on the AI support-prompt middleware system, which functions as a mediator between generative AI and human users, and discusses two operational rules associated with it. The first rule is the Information Processing Rule, which requires the middleware system to determine appropriate responses based on the context of the conversation using techniques for natural language processing. The second rule is the Information Presentation Rule, which requires the middleware system to choose an appropriate language style and conversational attitude based on the gravity of the topic or the conversational context. These rules are essential for guaranteeing that the middleware system can fathom user intent and respond appropriately in various conversational contexts. This study contributes to the planning and analysis of service design by deriving design rules for middleware systems to incorporate artificial intelligence into tourism services. By comprehending the operation of AI support-prompt middleware systems, service providers can design more effective and efficient AI-driven tourism services, thereby improving the customer experience and obtaining a market advantage.

퓨샷 개체명 인식을 위한 Maximal Marginal Relevance 기반의 라벨 단어 집합 생성 (Generating Label Word Set based on Maximal Marginal Relevance for Few-shot Name Entity Recognition)

  • 최효림;황현선;이창기
    • 한국정보과학회 언어공학연구회:학술대회논문집(한글 및 한국어 정보처리)
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    • 한국정보과학회언어공학연구회 2023년도 제35회 한글 및 한국어 정보처리 학술대회
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    • pp.664-671
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    • 2023
  • 최근 다양한 거대 언어모델(Large Language Model)들이 개발되면서 프롬프트 엔지니어링의 대한 다양한 연구가 진행되고 있다. 본 논문에서는 퓨삿 학습 환경에서 개체명 인식의 성능을 높이기 위해서 제안된 템플릿이 필요 없는 프롬프트 튜닝(Template-free Prompt Tuning) 방법을 이용하고, 이 방법에서 사용된 라벨 단어 집합 생성 방법에 Maximal Marginal Relevance 알고리즘을 적용하여 해당 개체명에 대해 보다 다양하고 구체적인 라벨 단어 집합을 생성하도록 개선하였다. 실험 결과, 'LOC' 타입을 제외한 나머지 개체명 타입에서 'PER' 타입은 0.60%p, 'ORG' 타입은 4.98%p, 'MISC' 타입은 1.38%p 성능이 향상되었고, 전체 개체명 인식 성능은 1.26%p 향상되었다. 이를 통해 본 논문에서 제안한 라벨 단어 집합 생성 기법이 개체명 인식 성능 향상에 도움이 됨을 보였다.

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