• Journal of Biosystems Engineering
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• v.28 no.6
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• pp.517-524
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• 2003

There have been worldwide research and development efforts to automate various processes of bio-production and those efforts will be expanded with priority given to tasks which require high intensive labor or produce high value-added product and tasks under hostile environment. In the field of bio-production capabilities of the versatility and robustness of automated system have been major bottlenecks along with economical efficiency. This paper introduces a new concept of automation based on tole-operation, which can provide solutions to overcome inherent difficulties in automating bio-production processes. Operator(farmer), computer, and automatic machinery share their roles utilizing their maximum merits to accomplish given tasks successfully. Among processes of greenhouse watermelon cultivation tasks such as pruning, watering, pesticide application, and harvest with loading were chosen based on the required labor intensiveness and functional similarities to realize the proposed concept. The developed system was composed of 5 major hardware modules such as wireless remote monitoring and task control module, wireless remote image acquisition and data transmission module, gantry system equipped with 4 d.o.f. Cartesian type robotic manipulator, exchangeable modular type end-effectors, and guided watermelon loading and storage module. The system was operated through the graphic user interface using touch screen monitor and wireless data communication among operator, computer, and machine. The proposed system showed practical and feasible way of automation in the field of volatile bio-production process.

• Journal of KIISE:Computing Practices and Letters
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• v.7 no.6
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• pp.641-652
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• 2001

Most of current internet auction systems are single auction server program that partly automates the function of the conventional auction house. So these systems do not provide sufficient independence, distribution and parallelism between the functions of the conventional auction house. In these suction systems, only some of suction management facilities are automated by the server program, but still users need to execute a repetitive task to monitor the dynamic progress of a certain auction, decide the proper bid price, and submit the bid. Another problem is that they support only the single auctions such as English suction and Dutch auction, but they do not support the double auctions that are superior to the single auction in terms of speed, efficiency, and the fair distribution of profit. In this paper, we present are design and implement of an agent-based continuous double auction system, called CoDABot, in order to overcome the limitations of current auction systems. CoDABot supports the continuous double auction, provides various bidding agents for users to select, and has been implemented with a multi-agent system to realize more independent, and parallel subsystems.

• Journal of KIISE:Software and Applications
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• v.32 no.12
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• pp.1217-1228
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• 2005

Recently, since DNA computing has been widely studied for various applications, DNA sequence design which is the most basic and important step for DNA computing has been highlighted. In previous works, DNA sequence design has been formulated as a multi-objective optimization task, and solved by elitist non-dominated sorting genetic algorithm (NSGA-II). However, NSGA-II needed lots of computational time. Therefore, we use an $\varepsilon$- multiobjective evolutionarv algorithm ($\varepsilon$-MOEA) to overcome the drawbacks of NSGA-II in this paper. To compare the performance of two algorithms in detail, we apply both algorithms to the DTLZ2 benchmark function. $\varepsilon$-MOEA outperformed NSGA-II in both convergence and diversity, $70\%$ and $73\%$ respectively. Especially, $\varepsilon$-MOEA finds optimal solutions using small computational time. Based on these results, we redesign the DNA sequences generated by the previous DNA sequence design tools and the DNA sequences for the 7-travelling salesman problem (TSP). The experimental results show that $\varepsilon$-MOEA outperforms the most cases. Especially, for 7-TSP, $\varepsilon$-MOEA achieves the comparative results two tines faster while finding $22\%$ improved diversity and $92\%$ improved convergence in final solutions using the same time.

• Journal of the Korea Society of Computer and Information
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• v.12 no.3
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• pp.165-175
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• 2007

The mobile agent executes a given task by which the agent code moves to the server directly. Therefore, node migration method becomes an important factor which impact on the whole performance of distributed system. In this paper, we propose an adaptive migration path technique of mobile agent using the metadata of naming agent. In this proposed technique, node selection for migration depends on the content of referenced metadata, and the reliability of migrated information is determined by the metadata updating method and cooperative operations of individual agents in multi-agents system. For these, we design the metadata using by the number of hit documents, hit ratio, node processing time and network delay time, and describe the methods for creating, using and updating metadata for which determine the adaptive node migration path of mobile agent according to the cooperation of individual agents and number of hit documents using by designed metadata. And results of evaluated performance for proposed adaptive migration path technique through the proper experiment and analysis gain rate of high effective information earning, because of high hit ratio(72%) about of fathered documents by case of applying metadata move to the 13 nodes. But, in case of non-applying metadata is hit ratio(46%) of gathered documents and rate of effective information earning about of 26 nodes is 36.8%.

• Proceedings of the KOR-BRONCHOESO Conference
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• 1987.05a
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• pp.6-6
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• 1987

만성중이염은 현재 그 빈도가 줄어드는 추세에 있으나 아직도 이과 영역에서 큰 비중을 차지하는 질환이다. 또한 청력개선, 정상구조의 보존, 병변 제거의 목적을 위하여 대부분 수술적 요법이 필요하게 된다. 이에 저자들은 본 병원에서 시행한 만성 중이염 451예, 남자 238예, 여자 213예. 진주종성 중이염 170예, 비진주종성 중이염 273예에 대한 수술시 소견에 대한 임상 통계적 관찰을 한 바, 다음과 같은 결과를 얻었다. 1) 관찰대상을 술식별로 분류하면 진주종성 중이염과 비진주종성 중이염의 비가 $\circled1$ Myningoplasty ; 19.1% : 0%, $\circled2$ Tympanoplasty without mastoidectomy ; 34.5% : 14.4%, $\circled3$ Tympanoplasty with mastoidectomy ; 3.0% :12.1% 이었다. 2) 고막천공부위는, 진주종성 중이염과 비진주종성 중이염의 비가 변연부천공이 10.1% : 5.5%, 상고실천공이 38.8% : 1.4%, 중심부천증이 12.9% : 47.3%, 전천공이 32.5% : 39.6%, 고막유착이 5.6% : 6.2% 을 보였다. 3) 이소골의 상태는 진주종성중이염과 비진주종성 중이염의 비가, 모든 이소골의 손실은 26.6% : 4.3%, 모든 이소골이 정상에 가까운 예는 16.6% : 69.3%, 가장 병변이 심했던 침골 이상은 76.9% : 24.8% 를 보였다. 4) 중이강 점막소견은 진주종성 중이염과 비진주종성 중이염의 비가, 정상에 가까운 예가 16.7% : 47.0%, 병적 소견을 보인 예가 83.3% : 53.0% 이었다. 5) 진주종성 중이염과, 비진주종성 중이염에서의 안면신경관노출은 2.2% : 0.3%, 뇌막노출은 9.5% : 2.9%, 횡정맥동노출은 5.0% : 1.1%, 미로누공은 1.7% : 0% 이었다.lant, engineering service business can be said "The Software of Total Industry." Engineering service is what is called a higher business which offers specialized engineering know-how and experience. Engineering service compaines offer Its specialized knowledge and experience to government, industry and commerce. Whether the task is to modernize plant equipment, to design a building or to manage construction, an engineering company will develop and implement the most appropriate and cost effective solution. Clients use the engineering service of firm knowing that the engineer′s professional judgement is not influenced or biased by other commercial affiliations. While benefiting from the diverse experience that professional engineers can apply to a specific problem, government and industry also reduce the need for permanent in-house engineering staff. Engineering firms may be specialized or multi-disciplinary.도말표본에서와 같이 제 14 일 이전에는 호중구가, 그 이후에는 단핵구가 주종을 이루었다.>18.9dB

• Journal of Distribution Science
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• v.15 no.6
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• pp.77-96
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• 2017

Purpose - This study aims to develop correspondence strategies to the environment change in domestic retail store types. Recently, new types of retails have emerged in retail industries. Therefore, trade area platform has developed focusing on the speed of data, no longer trade area from district border. Besides, 'trade area smart' brings about change in retail types with the development of giga internet. Thus, context shopping is changing the way of consumers' purchase pattern through data capture, technology capability, and algorithm development. For these reasons, the sales estimation model has been shown to be flawed using the notion of former scale and time, and it is necessary to construct a new model. Research design, data, and methodology - This study focuses on measuring retail change in large multi-shopping mall for the outlook for retail industry and competition for trade area with the theoretical background understanding of retail store types and overall domestic retail conditions. The competition among retail store types are strong, whereas the borders among them are fading. There is a greater need to analyze on a new model because sales expectation can be hard to get with business area competition. For comprehensive research, therefore, the research method based on the statistical analysis was excluded, and field survey and literature investigation method were used to identify problems and propose an alternative. In research material, research fidelity has improved with complementing research data related with retail specialists' as well as department stores. Results - This study analyzed trade area survival and its pattern through sales estimation and empirical studies on trade areas. The sales estimation, based on Huff model system, counts the number of households shopping absorption expectation from trade areas. Based on the results, this paper estimated sales scale, and then deducted modified probability model. Conclusions - In times of retail store chain destruction and off-line store reorganization, modified Huff model has problems in estimating sales. Transformation probability model, supplemented by the existing problems, was analyzed to be more effective in competitiveness business condition. This study offers a viable alternative to figure out related trade areas' sale estimation by reconstructing new-modified probability model. As a result, the future task is to enlarge the borders from IT infrastructure with data and evidence based business into DT infrastructure.

• The Journal of the Convergence on Culture Technology
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• v.6 no.2
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• pp.437-447
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• 2020

The purpose of this study is to research the countermeasures and expected effects through the use of drones in the field of disaster prevention as a drone-based smart quarantine performance method. The environmental, market, and technological approaches to the review of the current quarantine performance task and its countermeasures are as follows. First, in terms of the environment, the effectiveness of the quarantine performance business using drone-based control is to broaden the utilization of forest, bird flu, livestock, facility areas, mosquito larvae, pests, and to simplify and provide various effective prevention systems such as AI and cholera. Second, in terms of market, the standardization of livestock and livestock quarantine laws and regulations according to the use of disinfection and quarantine missions using domestic standardized drones through the introduction of new technologies in the quarantine method, shared growth of related industries and discovery of new markets, and animal disease prevention It brings about the effect of annual budget savings. Third, the technical aspects are (1) on-site application of disinfection and prevention using multi-drone, a new form of animal disease prevention, (2) innovation in the drone industry software field, and (3) diversification of the industry with an integrated drone control / control system applicable to various markets. (4) Big data drone moving path 3D spatial information analysis precise drone traffic information ensures high flight safety, (5) Multiple drones can simultaneously auto-operate and fly, enabling low-cost, high-efficiency system deployment, (6) High precision that this was considered due to the increase in drone users by sector due to the necessity of airplane technology. This study was prepared based on literature surveys and expert opinions, and the future research field needs to prove its effectiveness based on empirical data on drone-based services. The expected effect of this study is to contribute to the active use of drones for disaster prevention work and to establish policies related to them.

• Journal of The Korean Association For Science Education
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• v.33 no.2
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• pp.405-424
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• 2013

The purpose of this study is to explore the characteristics of secondary science teachers' thoughts on 'good' science teaching and to find a concept that can represent the way the teachers think. Participants were twenty pre- and in-service teachers who were enrolled in a graduate course I taught at a university located in Seoul in the first semester, 2011. The participating teachers collected and analyzed a variety of data and created portfolios while they were trained, as part of the course, on qualitative research methods with the same research questions as those of this study. In the current study, the process in which the teachers and I found answers to the research questions was narratively reconstructed based on the teachers' portfolios and my field notes. It was revealed that science teaching was perceived as a task aiming at realizing some kind of values and that because the teachers pursued various values in the science classroom and there exist conflicting relationships among different values, it was hard to define 'good' science teaching. It was also discussed that science instruction was inherently accompanied with the ongoing process of selecting values as the relationships among the values were ever-changing within the contexts of the classroom. This multi-faceted and dynamic structure of the teachers' thoughts on 'good' science teaching was conceptualized analogically as 'Foucault's pendulum,' which has multiple planes of oscillation. Implications for science teacher education and science education research were suggested.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.11 no.6
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• pp.123-132
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• 2012

Gas sensors has been used very differently that depending on following purposes; Automotive (exhaust gas, fuel mixture gas, oxygen, particulates), agriculture / food industry (fresh, stored, CO2, humidity, NH3, nitrogen oxide gas, organic gas, toxic gas emitted from pesticides and insecticides), industrial / medical (chemical gas, hydrogen, oxygen and toxic gases), military (chemical weapon), environmental measurements (CO and other air pollution consisting of sulfur and nitrogen gas), residential (LNG, LPG, butane, indoor air, humidity). The types of industrial toxic substances are known about 700 species and many of these exist in gaseous form under normal conditions. he multi-gas detection sensors will be developed for casualties that detect the most important and find easy three kinds of gases in marine plant; carbon dioxide(CO2), carbon(CO), ammonia(NH3). Package block consists of gas sensing device minor ingredient, rf front end, zigbee chip. Develope interworking technology between the sensor and zigbee chip inside a package. Conduct a performance test through test jig about prototype zigbee sensor module with rf output power and unwanted emission test. This research task available early address when poisonous gas leaked from large industrial site and contribution for workers' safety at the enclosed space.

• The Journal of the Korea Contents Association
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• v.21 no.11
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• pp.135-144
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• 2021

Recently, data-driven decision-making technology has become a key technology leading the data industry, and machine learning technology for this requires high-quality training datasets. However, real-world data contains missing values for various reasons, which degrades the performance of prediction models learned from the poor training data. Therefore, in order to build a high-performance model from real-world datasets, many studies on automatically imputing missing values in initial training data have been actively conducted. Many of conventional machine learning-based imputation techniques for handling missing data involve very time-consuming and cumbersome work because they are applied only to numeric type of columns or create individual predictive models for each columns. Therefore, this paper proposes a new data imputation technique called 'Denoising Self-Attention Network (DSAN)', which can be applied to mixed-type dataset containing both numerical and categorical columns. DSAN can learn robust feature expression vectors by combining self-attention and denoising techniques, and can automatically interpolate multiple missing variables in parallel through multi-task learning. To verify the validity of the proposed technique, data imputation experiments has been performed after arbitrarily generating missing values for several mixed-type training data. Then we show the validity of the proposed technique by comparing the performance of the binary classification models trained on imputed data together with the errors between the original and imputed values.