• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2000.11a
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• pp.31-35
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• 2000

We investigate the groundwater distribution and chemical characteristics for 3 or 5 districts every year and make the hydrogeologic map on a scale of 1:50,000. We draw the hydrogeologic digital map based on "The Handbook for the Drawing and Management of Hydrogeologic Map" which was published by MOCT and KOWACO in 1998. But, the Stiff diagram and well's notation are difficult to be presented in the digital map using the commercial Arcview GIS tools. So we develop the script file with Avenue language to represent them in Arcview GIS tool. At first, we design the database for the chemical analysis result of groundwater and well identification, and make the program code with Avenue language to display them on the digital map. And next we test the usefulness of the program code. As a result, we find that the script file is very useful for drawing the symbols and diagrams in hydrogeologic digital map using ArcView GIS.

• Genomics & Informatics
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• v.17 no.2
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• pp.15.1-15.7
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• 2019

Automatically detecting mentions of pharmaceutical drugs and chemical substances is key for the subsequent extraction of relations of chemicals with other biomedical entities such as genes, proteins, diseases, adverse reactions or symptoms. The identification of drug mentions is also a prior step for complex event types such as drug dosage recognition, duration of medical treatments or drug repurposing. Formally, this task is known as named entity recognition (NER), meaning automatically identifying mentions of predefined entities of interest in running text. In the domain of medical texts, for chemical entity recognition (CER), techniques based on hand-crafted rules and graph-based models can provide adequate performance. In the recent years, the field of natural language processing has mainly pivoted to deep learning and state-of-the-art results for most tasks involving natural language are usually obtained with artificial neural networks. Competitive resources for drug name recognition in English medical texts are already available and heavily used, while for other languages such as Spanish these tools, although clearly needed were missing. In this work, we adapt an existing neural NER system, NeuroNER, to the particular domain of Spanish clinical case texts, and extend the neural network to be able to take into account additional features apart from the plain text. NeuroNER can be considered a competitive baseline system for Spanish drug and CER promoted by the Spanish national plan for the advancement of language technologies (Plan TL).

• Journal of the Korean Chemical Society
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• v.52 no.3
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• pp.315-321
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• 2008

The posters are the tools to communicate authors' idea with others by visual image and a little word. Every discipline has its own sign with specific meaning shared by the members of the discipline. Chemists and students learning chemistry, therefore, will communicate with each other by specific chemical signs (codes). The Korean Chemical Society has held the feast of drawing chemistry posters by students nationwide since 2004. In 2004 and 2005, more than three thousands of posters were submitted, and about one hundred and fifty posters were selected as the prize winners. The award was divided by the grade levels of elementary, middle, and high school. This study explores the codes of chemistry used in students' posters. With the analysis of the visual elements and the verbal elements of posters, 7 chemical codes were found such as the liquid, the experiment apparatus, the graduations, the chemical language, scientists, the earth and environment, and things around us. In addition, the differences were investigated on the grade levels, on awarded or non-awarded poster, and on the years. Educational implications of these findings are discussed.

• Asian Journal of Innovation and Policy
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• v.10 no.3
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• pp.294-315
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• 2021

Since the division of South and North Korea in 1945, there has been little exchange in science and technology, despite some interchange in a few fields including the chemistry area. Accordingly, the difference in scientific and technological terminology between the two Koreas has become intensified. This is because North Korea carried out a campaign to purify the Korean language and blocked the inflow of foreign words. They also tried to convert into their own North Korean terms in many fields. This circumstance in North Korea aggravated the heterogeneity of inter-Korean scientific and technological terms. In particular, the heterogeneity of chemical terminology has worsened due to the different characteristics of the technology donor countries such as the United States and Japan in South Korea, and China and the Soviet Union in North Korea between the two Koreas and the different way of technological development. The purpose of this study is to collect chemical terminology data used in two Koreas and analyze similarities and differences. Through comparative analysis of inter-Korean terminology in the chemical field, it can be possible to recognize how the chemical terms between the two Koreas have changed since the division and the degree of heterogeneity based on different technical systems and language policies. The outcome of this study would present basic data on the unification of chemical terminology in preparation for before and after unification, and contribute to communication and academic exchange between researchers in the inter-Korean scientific and technological fields, including chemistry.

• Annual Conference on Human and Language Technology
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• 2023.10a
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• pp.522-524
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• 2023

화합물 관련 한국어 문서는 화합물 정보를 추출하여 그 용도를 발견할 수 있는 중요한 문서임에도 불구하고 자연어 처리를 위한 말뭉치의 구축이 되지 않아서 활용이 어려웠다. 이 연구에서는 최초로 한국 특허 문서에서 한국어 화합물 개체명 인식(Chemical Named Entity Recognition, CNER)을 위한 말뭉치를 구축하였다. 또한 구축된 CNER 말뭉치를 기본 모델인 Bi-LSTM과 KorBERT 사전학습 모델을 미세 조정하여 개체명 인식을 수행하였다. 한국어 CNER F1 성능은 Bi-LSTM 기반 모델이 83.71%, KoCNER 말뭉치를 활용하는 자연어 처리 기술들은 한국어 논문에 대한 화합물 개체명 인식으로 그 외연을 확대하고, 한국어로 작성된 화합물 관련 문서에서 화합물 명칭뿐만 아니라 물성, 반응 등의 개체를 추출하고 관계를 규명하는데 활용 될 수 있을 것이다.

• Journal of the Korean Chemical Society
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• v.64 no.3
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• pp.189-195
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• 2020

In the study, the effect of flipped classroom approach applied to chemistry I class in a foreign language high school was explored. Flipped classroom was applied to 176 grade 10 students (43 boys and 133 girls) from a foreign language high school located in a metropolitan city for one semester and its instructional effects were studied in terms of cognitive and affective aspects. Before the class, students were provided with guiding worksheets and asked to summarize contents. Within the class, various student-centered activities were adopted. After the flipped classroom for one semester, mid-term and final-term exam scores were analyzed, and students' attitude toward chemistry class and flipped classroom were surveyed. Analysis on the exam scores showed the possibility for positive impact on students' achievement and perceptions on chemistry class including flipped classroom approach. Moreover, some students mentioned flipped classroom was helpful for self-directed learning and meta-cognition. Based on these results, educational implications were discussed.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.31-34
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• 1995

The automated chemical analysis shop floor are developed for the environmental pollution problems in our chemical analysis center. This shop floor have the several equipments include weight, pour, dry, heater, boiler, mixture, spectroscopy etc. And the material handling components are made up by the stored stack, conveyore, turntables, robot etc. Computer simulation has been an important tool for these complete design problem. We have designed the arangement of chemical equipments and material flow systems by using the simulator "AutoModII". "AutoMoII" is one of the advanced simulator, CAD-like drawing tools with a powerful, engineering oriented language to model control logic and material flow. The result is the modeling of the chemical analysis system in accurate, three dimensional detail. We could designed the set able layout and scheduling system by using the AutoMoII simulator. AutoMoII simulator.

• International Journal of Advanced Culture Technology
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• v.6 no.3
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• pp.117-128
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• 2018

This study attempts to derive the possibility of literary therapy through addition and subtraction of emotional codons. It is presumed that the remnants of the emotions formed by the addition and subtraction of emotions will remain in the human body and cause chemical reactions. When this research is activated, cluster of emotional codons will be created by a combination of literary emotions. This is expected to accelerate therapeutic action of sentences by encoding certain emotional codons in AI.

• Journal of the Korean Institute of Gas
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• v.25 no.3
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• pp.9-15
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• 2021

In this paper, a study on the construction of a knowledge base based on natural language processing and the design of a chemical substance estimation system for the development of a knowledge service for a real-time sensor information fusion detection system and symptoms of contact with chemical substances in industrial sites. The information on 499 chemical substances contact symptoms from the Wireless Information System for Emergency Responders(WISER) program provided by the National Institutes of Health(NIH) in the United States was used as a reference. AllegroGraph 7.0.1 was used, input triples are Cas No., Synonyms, Symptom, SMILES, InChl, and Formula. As a result of establishing the knowledge base, it was confirmed that 39 symptoms based on ammonia (CAS No: 7664-41-7) were the same as those of the WISER program. Through this, a method of establishing was proposed knowledge base for the symptom extraction process of the chemical substance estimation system.

• Journal of the Korean Chemical Society
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• v.56 no.2
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• pp.195-200
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• 2012

In this study we present a new approach for computing the partial atomic charge derived from the wavefunctions of molecules. This charge, which we call the "y_charge", was calculated by taking into account the energy level and orbital populations in each molecular orbital (MO). The charge calculations were performed in the software, which was developed by us, developed using the C# programming language. Partial atomic charges cannot be calculated directly from quantum mechanics. According to a partitioning function, the electron density of constituent molecular atoms depends on the electrostatic attraction field of the nucleus. Taking into account the Boltzmann population of each MO as a function of its energy and temperature we obtain a formula of partial charges.