• Proceedings of the Korea Information Processing Society Conference
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• 2001.04b
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• pp.743-746
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• 2001

자바는 객체지향 언어이고, 한번 작성된 프로그램은 자바 가상 기계가 있는 모든 곳에서 수정없이 실행될 수 있기 때문에 소프트웨어의 개발과 유지 보수에 많은 장점을 가진 언어이다. 이러한 특징으로 인하여 개발되는 제품들이 자바로 구현되는 경우가 많다. 그러나 아직 대다수 소프트웨어 개발자들은 주로 C 언어나 C++ 언어를 사용하고 있으며, 최근에는 C#이라는 언어를 사용하고 있다. 자바가 플랫폼에 독립적인 장점은 가지고 있지만, 다수의 개발자 및 사용자가 마이크로소프트 윈도우 운영체제를 사용하고 있다는 것을 감안한다면 그리 탁월한 장점만은 될 수 없다. 또한, 최근의 개발동향이 COM(Component Object Model)을 지향하고 있고, 이는 더 이상 개발자들에게 프로그래밍 언어에 구애를 받지 않고 오직 개발 제품에 대한 집중력을 가질 수 있는 환경을 제공할 수 있다면, 그 개발 효율에 있어서 상당한 이점을 가질 수 있다는 의미이다. 따라서, COL(Component Object Language)을 기반으로 하고 있는 C# (C sharp)언어를 사용하여 개발을 함에 있어서 자바의 언어를 C# 언어로 변환할 수 있다면, 신생 언어인 C#에 있어서 기존 자바로 되어 있는 유용한 개발 제품들을 보다 효율적으로 이용할 수 있을 것이다. 본 논문에서는 두 언어(자바, C#)를 하나로 잇는 교량(bridge)역할을 할 수 있도록 자바의 중간 언어인 Bytecode를 C#의 중간 언어인 MSIL(Microsoft Intermediate Language)로 바꿀 수 있는 중간 언어 번역기를 설계하고 구현하였다. 이를 위한 방법으로는 먼저, 자바 Bytecode 와 MSIL 의 어셈블리 형태에서의 명령어 매칭과정을 매핑 테이블을 이용하여 처리하였고, MSIL 에서 자바 Bytecode 의 함수와 같은 기능을 하는 메소드의 변환을 위하여 마크로 변환기법을 이용하여 해결하였다.I/O ratio 2.5). BTEX의 상대적 함량도 실내가 실외보다 높아 실내에도 발생원이 있음을 암시하고 있다. 자료 분석결과 유치원 실내의 벤젠은 실외로부터 유입되고 있었고, 톨루엔, 에틸벤젠, 크실렌은 실외뿐 아니라 실내에서도 발생하고 있었다. 정량한 8개 화합물 각각과 총 휘발성 유기화합물의 스피어만 상관계수는 벤젠을 제외하고는 모두 유의하였다. 이중 톨루엔과 크실렌은 총 휘발성 유기화합물과 좋은 상관성 (톨루엔 0.76, 크실렌, 0.87)을 나타내었다. 이 연구는 톨루엔과 크실렌이 총 휘발성 유기화합물의 좋은 지표를 사용될 있고, 톨루엔, 에틸벤젠, 크실렌 등 많은 휘발성 유기화합물의 발생원은 실외뿐 아니라 실내에도 있음을 나타내고 있다.>10)의 $[^{18}F]F_2$를 얻었다. 결론: $^{18}O(p,n)^{18}F$ 핵반응을 이용하여 친전자성 방사성동위원소 $[^{18}F]F_2$를 생산하였다. 표적 챔버는 알루미늄으로 제작하였으며 본 연구에서 연구된 $[^{18}F]F_2$가스는 친핵성 치환반응으로 방사성동위원소를 도입하기 어려운 다양한 방사성의 약품개발에 유용하게 이용될 수 있을 것이다.었으나 움직임 보정 후 영상을 이용하여 비교한 경우, 결합능 변화가 선조체 영역에서 국한되어 나타나며 그 유의성이 움직임 보정 전에 비하여 낮음을 알 수 있었다. 결론: 뇌활성화 과제 수행시에 동반되는 피험자의 머리 움직임에 의하여 도파민 유리가 과대평가되었으며 이는 이 연구에서 제안한 영상정합을 이용한 움직임 보정기법에 의해서 개선되었다. 답이 없는 문제, 문제 만들기, 일반화가 가능한 문제 등으로 보고, 수학적 창의성 중 특히 확산적 사고에 초점을 맞추어 개방형 문제가 확산적 사고의 요소인 유창성, 독창성, 유연성 등에 각각 어떤 영향을 미치는지 20주의 프로그램을 개발, 진행하여 그 효과를

• Journal of Biosystems Engineering
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• v.20 no.2
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• pp.162-172
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• 1995

The ventilation in greenhouse have been important for such as adjustment of temperature, supplying of the oxygen, prevention of the overhumidity, density adjustment of $CO_2$, discharge of harmfulness gas, etc. However, the general ventilation which had been used the quantitative control method in discharge of a property of air mechanism in greenhouse, and caused mainly in waste of the heating energy and growth obstacle of the vegetable. Therefore, this study was peformed to obtain more scientific ventilation method using by analysis and measurement of the isothermal lines according to opening of window ventilation in greenhouse, and the results are summarized as follows. 1. The ventilating amount was more influenced by rather opening amount of window than the ventilating time. 2. In window ventilation, the temperature in greenhouse was mostly changed within 5 minutes after ventilating not regard to the spot of opening, after about 10 minutes temperature became to equilibrium state under the respective ventilating conditions. 3. In opening of the skylight only, isothermal lines were complicated, therefore, a tall vegetable may be possible to damage by a cold-weather from the lower central port in greenhouse. 4. Isothermal lines were a tendency to simply in opening of a side window that may be more effective ventilation in kinds of the short vegetable. 5. In conditions of internal temperature>setting temperature>external temperature, a skylight can be suitable to open 10~20cm in order to the optimum ventilation in greenhouse. 6. In conditions of internal temperature>external temperature>setting temperature, opening of all the windows or both the side windows that can be suitable in order to obtain the optimum ventilation in greenhouse. 7. An effect of ventilation was the most excellent to open of all the windows or both the side windows, and it were also found orderly excellent to open of the side window and the skylight or the skylight only, to open of the side window only. 8. Temperature was varied as the equation of T=Tc+ (To-Tc)e-at, and the ranges of (a) values were limited within 0.34~0.68. 9. A variations of humidity were similar to that of temperature, s.

• Journal of the Korea Society for Simulation
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• v.15 no.1
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• pp.35-42
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• 2006

Sensor network, that is an infrastructure of ubiquitous computing, consists of a number of sensor nodes of which hardware is very small. The network topology and routing scheme of the network should be determined according to its purpose, and its hardware and software may have to be changed as needed from time to time. Thus, the sensor network simulator being capable of verifying its behavior and estimating performance is required for better design. Sensor network simulators currently existing have been developed for specific hardwares or operating systems, so that they can only be used for such systems and do not provide any means to estimate the amount of power consumption and program execution time which are major issues for system design. In this study, we develop the sensor network simulator that can be used to design and verify various sensor networks without regarding to types of applications or operating systems, and also has the capability of predicting the amount of power consumption and program execution time. For this purpose, the simulator is developed by using machine instruction-level discrete-event simulation scheme. As a result, the simulator can be used to analyze program execution timings and related system behaviors in the actual sensor nodes in detail. Instruction traces used as workload for simulations are executable images produced by the cross-compiler for ATmega128L microcontroller.

• Journal of Biomedical Engineering Research
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• v.44 no.6
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• pp.404-413
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• 2023

In this research, we studied the development of a SUS304 microneedle array based on microfabrication technology and the applicability of Parylene-C thin film, a medical polymer material. First of all, four materials commonly used in the field of medical engineering (SUS304, Ti, PMMA, and PEEK) were selected and a 5 ㎛ Parylene-C thin film was deposited. The applicability of Parylene-C coating to each material was confirmed through SEM analysis, contact angle measurement, surface roughness(Ra) measurement, and adhesion test according to ASTM standards for each specimen. Parylene-C thin film was deposited based on chemical vapor deposition (CVD), and a 5 ㎛ Parylene-C deposition process was established through trial and error. Through characteristic experiments to confirm the applicability of Parylene-C, SUS304 material, which is the easiest to apply Parylene-C coating without pretreatment was selected to develop a microneedle array based on CNC micromachining technology. The CNC micromachining process was divided into a total of 5 steps, and a microneedle array consisting of 19 needles with an inner diameter of 200 ㎛, an outer diameter of 400 ㎛, and a height of 1.4 mm was designed and manufactured. Finally, a 5 ㎛ Parylene-C coated microneedle array was developed, which presented future research directions in the field of microneedle-based drug delivery systems.

• Radiation Oncology Journal
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• v.17 no.2
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• pp.172-178
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• 1999

Purpose : To measure the basic structural characteristics of radiation oncology facilities in Korea during 1997 and to compare personnel, equipments and patient loads between Korea and developed countries. Methods and Materials : Mail serveys we conducted in 1998 and data on treatment machines, personnel and peformed new patients were collected. Responses were obtained from the 100 percent of facilities. The consensus data of the whole country were summarized using Microsoft Excel program. Results: In Korea during 1997, 42 facilities delivered megavoltage radiation theraphy with 71 treatment machines, 100 radiation oncologists, 26 medical physicist, 205 technologists and 19,773 new patients. Eighty nine percent of facilities in Korea had linear accelators at least 6 MeV maximum photon energy. Ninety five percent of facilities had simulators while five percent of facilities had no simulator, Ninety one percent of facilities had computer planning systems and eighty three percent of facilities reported that they had a written quality assurance program. Thirty six percent of facilities had only one radiation oncologist and thirty eight percent of facilities had no medical physicists. The median of the distribution of annual patients load of a facility, patients load per a machine, patients load per a radiation oncologist, patients load per a therapist and therapists per a machine in Korea were 348 patients per a year, 263 patients per a machine, 171 patients per a radiation oncologist, 81 patients per a therapist, and 3 therapists per a machine respectively. Conclusions : The whole scale of the radiation oncology departments in Korea was smaller than Japan and USA in population ratio regard. In case of hardware level like linear accelerators, simulators and computer planning systems, there was no big differences between Korea and USA. The patients loads of radiation oncologists and therapists had no significant differences as compared with USA. However, it was desirable to consider the part time system in USA because there were a lot of hospitals which did not employ medical physicists.

• Korean Journal of Remote Sensing
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• v.38 no.5_2
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• pp.747-763
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• 2022

Ocean salinity affects ocean circulation on a global scale and low salinity water around coastal areas often has an impact on aquaculture and fisheries. Microwave satellite sensors (e.g., Soil Moisture Active Passive [SMAP]) have provided sea surface salinity (SSS) based on the dielectric characteristics of water associated with SSS and sea surface temperature (SST). In this study, a Light Gradient Boosting Machine (LGBM)-based model for generating high resolution SSS from Geostationary Ocean Color Imager (GOCI) data was proposed, having machine learning-based improved SMAP SSS by Jang et al. (2022) as reference data (SMAP SSS (Jang)). Three schemes with different input variables were tested, and scheme 3 with all variables including Multi-scale Ultra-high Resolution SST yielded the best performance (coefficient of determination = 0.60, root mean square error = 0.91 psu). The proposed LGBM-based GOCI SSS had a similar spatiotemporal pattern with SMAP SSS (Jang), with much higher spatial resolution even in coastal areas, where SMAP SSS (Jang) was not available. In addition, when tested for the great flood occurred in Southern China in August 2020, GOCI SSS well simulated the spatial and temporal change of Changjiang Diluted Water. This research provided a potential that optical satellite data can be used to generate high resolution SSS associated with the improved microwave-based SSS especially in coastal areas.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.1-21
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• 2020

With the rapid development of artificial intelligence technology, various techniques have been developed to extract meaningful information from unstructured text data which constitutes a large portion of big data. Over the past decades, text mining technologies have been utilized in various industries for practical applications. In the field of business intelligence, it has been employed to discover new market and/or technology opportunities and support rational decision making of business participants. The market information such as market size, market growth rate, and market share is essential for setting companies' business strategies. There has been a continuous demand in various fields for specific product level-market information. However, the information has been generally provided at industry level or broad categories based on classification standards, making it difficult to obtain specific and proper information. In this regard, we propose a new methodology that can estimate the market sizes of product groups at more detailed levels than that of previously offered. We applied Word2Vec algorithm, a neural network based semantic word embedding model, to enable automatic market size estimation from individual companies' product information in a bottom-up manner. The overall process is as follows: First, the data related to product information is collected, refined, and restructured into suitable form for applying Word2Vec model. Next, the preprocessed data is embedded into vector space by Word2Vec and then the product groups are derived by extracting similar products names based on cosine similarity calculation. Finally, the sales data on the extracted products is summated to estimate the market size of the product groups. As an experimental data, text data of product names from Statistics Korea's microdata (345,103 cases) were mapped in multidimensional vector space by Word2Vec training. We performed parameters optimization for training and then applied vector dimension of 300 and window size of 15 as optimized parameters for further experiments. We employed index words of Korean Standard Industry Classification (KSIC) as a product name dataset to more efficiently cluster product groups. The product names which are similar to KSIC indexes were extracted based on cosine similarity. The market size of extracted products as one product category was calculated from individual companies' sales data. The market sizes of 11,654 specific product lines were automatically estimated by the proposed model. For the performance verification, the results were compared with actual market size of some items. The Pearson's correlation coefficient was 0.513. Our approach has several advantages differing from the previous studies. First, text mining and machine learning techniques were applied for the first time on market size estimation, overcoming the limitations of traditional sampling based- or multiple assumption required-methods. In addition, the level of market category can be easily and efficiently adjusted according to the purpose of information use by changing cosine similarity threshold. Furthermore, it has a high potential of practical applications since it can resolve unmet needs for detailed market size information in public and private sectors. Specifically, it can be utilized in technology evaluation and technology commercialization support program conducted by governmental institutions, as well as business strategies consulting and market analysis report publishing by private firms. The limitation of our study is that the presented model needs to be improved in terms of accuracy and reliability. The semantic-based word embedding module can be advanced by giving a proper order in the preprocessed dataset or by combining another algorithm such as Jaccard similarity with Word2Vec. Also, the methods of product group clustering can be changed to other types of unsupervised machine learning algorithm. Our group is currently working on subsequent studies and we expect that it can further improve the performance of the conceptually proposed basic model in this study.