• Mycobiology
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• 제49권6호
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• pp.559-581
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• 2021

The coastal marine ecosystems of Vietnam are one of the global biodiversity hotspots, but the biodiversity of marine fungi is not well known. To fill this major gap of knowledge, we assessed the genetic diversity (ITS sequence) of 75 fungal strains isolated from 11 surface coastal marine and deeper waters in Nha Trang Bay and Van Phong Bay using a culture-dependent approach and 5 OTUs (Operational Taxonomic Units) of fungi in three representative sampling sites using next-generation sequencing. The results from both approaches shared similar fungal taxonomy to the most abundant phylum (Ascomycota), genera (Candida and Aspergillus) and species (Candida blankii) but were different at less common taxa. Culturable fungal strains in this study belong to 3 phyla, 5 subdivisions, 7 classes, 12 orders, 17 families, 22 genera and at least 40 species, of which 29 species have been identified and several species are likely novel. Among identified species, 12 and 28 are new records in global and Vietnamese marine areas, respectively. The analysis of enzyme activity and the checklist of trophic mode and guild assignment provided valuable additional biological information and suggested the ecological function of planktonic fungi in the marine food web. This is the largest dataset of marine fungal biodiversity on morphology, phylogeny and enzyme activity in the tropical coastal ecosystems of Vietnam and Southeast Asia. Biogeographic aspects, ecological factors and human impact may structure mycoplankton communities in such aquatic habitats.

• 인터넷정보학회논문지
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• 제24권4호
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• pp.37-45
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• 2023

Adaptive has gained significant attention in Education Technology (EdTech), with personalized learning experiences becoming increasingly important. Next-generation chatbots, including models like ChatGPT, are emerging in the field of education. These advanced tools show great potential for delivering personalized and adaptive learning experiences. This paper reviews previous research on adaptive learning and the role of chatbots in education. Based on this, the paper explores current and future chatbot technologies to propose a framework for using ChatGPT or similar chatbots in adaptive learning. The framework includes personalized design, targeted resources and feedback, multi-turn dialogue models, reinforcement learning, and fine-tuning. The proposed framework also considers learning attributes such as age, gender, cognitive ability, prior knowledge, pacing, level of questions, interaction strategies, and learner control. However, the proposed framework has yet to be evaluated for its usability or effectiveness in practice, and the applicability of the framework may vary depending on the specific field of study. Through proposing this framework, we hope to encourage learners to more actively leverage current technologies, and likewise, inspire educators to integrate these technologies more proactively into their curricula. Future research should evaluate the proposed framework through actual implementation and explore how it can be adapted to different domains of study to provide a more comprehensive understanding of its potential applications in adaptive learning.

• BMB Reports
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• 제56권9호
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• pp.514-519
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• 2023

Methyltransferase-like 3 (METTL3), a key component of the m⁶A methyltransferase complex, regulates the splicing, nuclear transport, stability, and translation of its target genes. However, the mechanism underlying the regulation of METTL3 expression by alternative splicing (AS) remains unknown. We analyzed the expression pattern of METTL3 after AS in human tissues and confirmed the expression of an isoform retaining introns 8 and 9 (METTL3-IR). We confirmed the different intracellular localizations of METTL3-IR and METTL3 proteins using immunofluorescence microscopy. Furthermore, the endogenous expression of METTL3-IR at the protein level was different from that at the mRNA level. We found that 3'-UTR generation by intron retention (IR) inhibited the export of METTL3-IR mRNA to the cytoplasm, which in turn suppressed protein expression. To the best of our knowledge, this is the first study to confirm the regulation of METTL3 gene expression by AS, providing evidence that the suppression of METTL3 protein expression by IR is an integral part of the mechanism by which 3'-UTR generation regulates protein expression via inhibition of RNA export to the cytoplasm.

• 한국차세대컴퓨팅학회논문지
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• 제13권6호
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• pp.21-30
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• 2017

피지컬 컴퓨팅은 단순 컴퓨터 입출력이 아닌 현실세계와 상호작용을 통해 이루어지므로 학생들의 컴퓨팅적 사고와 소양을 기르는데 적합하다. 또한 이를 블록형 코딩 개발환경에서 개발한다면 사용자는 훨씬 더 직관적이고 쉽게 개발을 할 수 있을 것이다. 그러나 기존 블록형 코딩 개발환경은 물리기기가 컴퓨터에 지속적으로 연결되어 있어야 한다는 번거로움이 있다. Blockly는 코드 개념을 나타내는 그래픽 블록이 연동되어 웹과 안드로이드 애플리케이션에 시각적 코드 에디터를 추가하는 오픈소스 라이브러리이다. 본 논문에서는 오픈소스 Blockly 기반으로 기존의 블록형 개발환경에 피지컬 컴퓨팅 기능을 추가하고 이를 무선통신으로 동작시킬 수 있는 모바일용 피지컬 컴퓨팅 개발환경의 구축 내용에 대해 기술한다.

• Asia pacific journal of information systems
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• 제30권1호
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• pp.31-52
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• 2020

Stock markets are popular investment avenues to people who plan to receive premium returns compared to other financial instruments, but they are highly volatile and risky due to the complex financial dynamics and poor understanding of the market forces involved in the price determination. A system that can forecast, predict the stock prices and automatically create a portfolio of top performing stocks is of great value to individual investors who do not have sufficient knowledge to understand the complex dynamics involved in evaluating and predicting stock prices. In this paper the authors propose a Stock prediction, Portfolio Generation and Selection model based on Machine learning algorithms, Artificial neural networks (ANNs) are used for stock price prediction, Mathematical and Statistical techniques are used for Portfolio generation and Un-Supervised Machine learning based on K-Means Clustering algorithms are used for Portfolio Evaluation and Selection which take in to account the Portfolio Return and Risk in to consideration. The model presented here is limited to predicting stock prices on a long term basis as the inputs to the model are based on fundamental attributes and intrinsic value of the stock. The results of this study are quite encouraging as the stock prediction models are able predict stock prices at least a financial quarter in advance with an accuracy of around 90 percent and the portfolio selection classifiers are giving returns in excess of average market returns.

• 한국정보처리학회논문지
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• 제4권9호
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• pp.2280-2288
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• 1997

에이전트는 자율성, 사회성, 반응성, 지속성을 갖는 독립된 프로그램으로 지식과 추론 능력을 바탕으로 사용자의 작업을 대신해 준다. 여러 영역들을 포함하는 복잡한 문제를 효과적으로 해결하기 위해서 멀티에이전트 기반구조에 대한 연구가 활발히 진행되어 왔다. 그러나 이런 기반구조에서도 사용자의 질의는 상당히 애매하고 그에 대한 문제 해결에 대한 절차가 바로 생성되지 못하는 문제점이 있다. 이를 위해 멀티에이전트 기반구조에 계획 생성모듈을 추가시켜 좀더 지능을 갖춘 멀티에이전트의 개발이 요구된다. 본 논문에서는 OAA (Open Agent Architecture)를 이용한 에이전트 시스템이 사용자의 의도 파악과 작업수행을 위한 절차를 생성하고, 분산되어 독립적으로 흩어져 사용되고 있는 지식처리 시스템을 통합하여 상호의 지식을 공유하면서 서로 협동 가능하도록 OAA를 이용한 에이전트 시스템에 계획생성 모듈 추가방법을 제안한다. 또한 이방법의 유용성을 검증하기 위해 여행일정 에이전트 시스템에 적용하였다. 이러한 결과로 OAA를 이용한 에이전트 시스템을 사용하는 사용자는 컴퓨터 네트워크 상에서 제공되는 서비스의 제공과 사용에 있어서 좀더 편리한 인터페이스 환경을 제공 받을 수 있게 되었다. 또한 현재 독립적으로 흩어져 사용되고 있는 지식처리 시스템인 전문가 시스템이나 계획기를 통합하여 상호의 지식을 공유하면서 서로 협동으로 일을 처리할 수 있는 환경을 제공한다.

• 한국진공학회:학술대회논문집
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• 한국진공학회 2015년도 제49회 하계 정기학술대회 초록집
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• pp.64-64
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• 2015

Control of plasma processing methodologies can only occur by obtaining a thorough understanding of the physical and chemical properties of plasmas. However, all plasma processes are currently used in the industry with an incomplete understanding of the coupled chemical and physical properties of the plasma involved. Thus, they are often 'non-predictive' and hence it is not possible to alter the manufacturing process without the risk of considerable product loss. Only a more comprehensive understanding of such processes will allow models of such plasmas to be constructed that in turn can be used to design the next generation of plasma reactors. Developing such models and gaining a detailed understanding of the physical and chemical mechanisms within plasma systems is intricately linked to our knowledge of the key interactions within the plasma and thus the status of the database for characterizing electron, ion and photon interactions with those atomic and molecular species within the plasma and knowledge of both the cross-sections and reaction rates for such collisions, both in the gaseous phase and on the surfaces of the plasma reactor. The compilation of databases required for understanding most plasmas remains inadequate. The spectroscopic database required for monitoring both technological and fusion plasmas and thence deriving fundamental quantities such as chemical composition, neutral, electron and ion temperatures is incomplete with several gaps in our knowledge of many molecular spectra, particularly for radicals and excited (vibrational and electronic) species. However, the compilation of fundamental atomic and molecular data required for such plasma databases is rarely a coherent, planned research program, instead it is a parasitic process. The plasma community is a rapacious user of atomic and molecular data but is increasingly faced with a deficit of data necessary to both interpret observations and build models that can be used to develop the next-generation plasma tools that will continue the scientific and technological progress of the late 20th and early 21st century. It is therefore necessary to both compile and curate the A&M data we do have and thence identify missing data needed by the plasma community (and other user communities). Such data may then be acquired using a mixture of benchmarking experiments and theoretical formalisms. However, equally important is the need for the scientific/technological community to recognize the need to support the value of such databases and the underlying fundamental A&M that populates them. This must be conveyed to funders who are currently attracted to more apparent high-profile projects.

• 대한디지털의료영상학회논문지
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• 제16권1호
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• pp.43-47
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• 2014

Sens of insecutity of the public and professionals about harmful effects of radiation is increasing in an accident at the Chernobyl and Fkushima nuclear power plant.Anxiety was amplified to lack of information about radiation majority of people. To target the middle and high school in the region of Daegu and Gyeongsangbuk-do, to investigate the radiation recognition of the next generation, it is intended to present a model of education for the safe use of radiation. The High School of the six metropolitan cities, city, town through the questionnaire and needs to be educational experience of radiation and use knowledge level of radiation, experience in daily life, understanding of man-made radiation and natural radiation, information channel on radiation, the radiation Distribute the total 800 parts of, to recover the 629 unit, was analyzed for 155 females 474 males. Many people 75.36% of the people, to 24.64% female subjects of this investigation, was constant, respectively from 13 to 18 years age. It is a large number and 30.37% of the respondents as "normal" level of knowledge of radiation, for the type of radiation, most knew. You have answer for risk experience of the medical radiation was higher, touching a lot of information via the broadcast medium in general, and the accuracy is low. I thought we wanted to be educated three or more twice a year, as an educator,about 71.37% and radiation-related understanding of knowledge and background in accordance with the diversification of information channels, the regional differences between urban and rural areas. But I considered the difference age (grade) for each is displayed, intended for junior high school students, the target surface and use the occurrence of radiation, high school students, the need for education about risk and application of radiation through this study.

• 디지털융복합연구
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• 제13권9호
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• pp.439-444
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• 2015

본 의학적 효능연구는 전통고의서 문헌에 나타난 닭관련 약처방을 분석 정리하여 재래닭의 의학적 효능을 구명하는데 목표를 두고 고려시대에서 조선시대에 이르는 필사본 한의서를 중심으로 재래닭 관련 처방을 번역하고 정리 하고자 한다. 주지하다시피 필사본 고의서는 당대의 명의가 숱한 시행착오를 거쳐 정립된 자신만의 고유처방을 출판술이 발달되지 않은 시대적 상황에서 직접 기술하여 자손대대로 전래한 처방중심 고의서이다. 전국에 산재되어 있는 처방중심의 고의서는 관리부실에 의한 손망실로 거의 원형을 찾아보기 어렵고, 또 소실로 인해 그 존재조차 확인되지 않고 있다. 현존하는 한의서에 기술된 다양한 닭처방과 약리작용을 분석하여 대체의학을 위한 자료를 정리하고자 한다. 이러한 연구는 분석된 내용을 구분 정리하여 DB를 구축하고 처방 및 혼합약재에 대한 치료방법을 유용성 평가를 통해 다양한 기능성식품개발의 근거로 마련하고자한다. 현존하는 재래닭 관련 지식정보의 관리체계가 미흡하여 국가 지식 자원의 지속적인 확충과 전문인력양성 및 지식문화 관련 사업의 부가가치 창출을 통한 미래 신성장 동력산업 육성에도 일익하고자 한다. 고의서에 나타난 재래닭관련 처방지식을 정제화하여 다학제간의 융복합연구 시스템을 통한 재래닭의 약리작용 연구와 유용성을 평가하고 기능성식품이나 대체의학의 실용화 방안 역시 제시하고자 한다.

• 한국융합학회논문지
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• 제12권10호
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• pp.63-70
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• 2021

고해상도 심층신경망을 이용하여 기상데이터를 초해상화하면 보다 더 정밀한 연구와 실생활에 유용한 서비스를 제공할 수 있다. 본 논문에서는 고해상도 심층신경망 학습에 사용하기 위한 개선된 훈련자료 생산기술을 최초로 제안한다. 기상전문 지식으로 고해상도 기상 자료를 생성하기 위해, 전문 기관의 관측자료와 ERA5 재분석장 자료를 바탕으로 람베르트 정각원추도법과 객관분석을 적용했다. 그 결과, 기상 전문 지식 기반의 기온 및 습도 분석자료는 기존 배경장 대비 RMSE 값이 각각 최대 42%, 46% 개선되었다. 다음으로, 기상 전문 기술을 이용한 수동적인 데이터 생성 기법을 자동화하기 위해 인공지능 기술 중 하나인 SRGAN을 이용했고, 10 km 해상도를 가지는 전지구모델자료로부터 1 km 해상도를 가지는 고해상도 자료를 생성하는 실험을 진행했다. 최종적으로, SRGAN으로 생성한 결과는 전지구모델입력자료에 비해 높은 해상도를 가지며 수동으로 생성한 고해상도 분석자료와 유사한 분석 패턴을 보이면서도 부드러운 경계를 보였다.