• Journal of Information Technology and Architecture
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• v.10 no.4
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• pp.435-449
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• 2013

The performance of Enterprise Architecture (EA) in the Korea's public IT domain produces mixed results and responses. On the one hand, EA earns positive remarks and enthusiasm as a central government-wide IT governance framework with its significant IT budget saving records. At the same time, however, the response to EA at the department and agency level is tainted with disappointment, fatigue, and reluctance. This essay suggests that this is perhaps caused by the sterile lackluster concept of EA Business Architecture employed in the current EA practice of the enterprise. The possibility for liberating and reviving the concept of EA Business Architecture is explored. Various conceptual axes and branches of EA Business Architecture are identified based upon extensive EA field experience and observations, and discussions are made on how the concept of EA Business Architecture can be expanded and amplified on those conceptual axes and branched. The resulting EA Business Architecture conceptualization is consolidated into an illustrative typology for EA Business Architecture. In the end the theoretical and practical implications of the research are discussed along with its contribution and limitation.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.27 no.1
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• pp.46-58
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• 2017

Objectives: Particulate matter (PM) at construction sites mostly originates from either construction activities or the atmospheric environment. This study was conducted to evaluate the exposure level to PM and the contribution ratio of atmosphere sources at construction sites. Methods: We reviewed literature and governmental systems related to PM exposure in occupational settings and summarized them. In the field evaluation, five construction sites and one golf course were selected: two from Gyeonggi-do Province and four from North Gyeongsang-do Province. For each site, personal samples from outdoor construction workers and area samples from the outdoor area around the construction site office were collected according to construction work types. PM concentrations reported from nearby National Ambient Air Monitoring Stations were recorded. Respirable dust concentrations, respirable silica concentrations, and several metal concentrations including Cd, Cr, Pb, and As were monitored over four months. In the end we suggested how to manage particulate matter exposure at construction sites. Results: There was little literature reporting on exposure levels of construction workers to PM. Respirable dust concentrations measured in Gyeonggi-do Province were higher than those measured in North Gyeongsang-do Province. The geometric means of respirable dust concentrations in personal samples and area samples were $37.89{\mu}g/m^3$ and $92.86{\mu}g/m^3$, respectively. The respirable dust concentrations were higher than the PM concentrations reported from nearby National Ambient Air Monitoring Station. The geometric means of respirable silica concentrations of personal samples and area samples were $1.3{\mu}g/m^3$ and $1.1{\mu}g/m^3$, respectively. All metal concentrations were lower than 10% of individual Korean occupational exposure limits. Conclusions: Assuming that personal samples consisted of ambient PM and dust originating from work activities and area samples only collected ambient PM, we concluded that the dust exposure of outdoor construction workers originated 40.8% from the atmosphere and 59.2% from construction activities. PM exposure at construction sites should be controlled by employers, as in the case of outdoor heat stress. The Korean government needs to consider setting an occupational exposure limit for respirable dust.

• Fire Science and Engineering
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• v.26 no.4
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• pp.55-62
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• 2012

The suppression mechanisms of carbon dioxide ($CO_2$) as a representative fire suppression agent were revisited using a counterflow diffusion flame which could be applied the concept of a local application system. To end this, the low strain rate $CH_4$/air counterflow diffusions with $CO_2$ addition in either fuel or oxidizer stream were examined numerically using detailed-kinetic chemistry. Radiative heat loss due to radiating gas species including $CO_2$ added was considered by the optically thin model (OTM). As a result, the critical $CO_2$ volume fractions in the oxidizer stream required to extinguish the flame were in good agreement with the experimental data reported in the literature, while somewhat under-prediction was observed with $CO_2$ added in the fuel stream. The surrogate agents were adopted to estimate the quantitative contribution with changing in global strain rate ($a_g$) on the flame extinguishment among pure dilution effect, thermal effects including radiation heat loss and chemical effect due to the $CO_2$ fire suppression agent.

• Journal of KIISE:Software and Applications
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• v.26 no.11
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• pp.1372-1380
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• 1999

본 논문에서는 자연언어 문장의 객관적 정량적인 질 측정 방법의 구축에 대해 설명하고, 이를 문장 퇴고 시스템의 사례에 적용해 본다. 문장의 질을 평가한다는 것은 본질적으로 주관적이고 정량화가 어려운 작업이기 때문에, 이 과정에서 질의 객관적 계량화가 가능한지 여부가 가장 중요한 문제가 된다. 이 논문에서는 이러한 문제를 해결하기 위해 유전자 알고리즘을 이용한 진화적 접근 방법을 통해 객관적이고 정량적인 질의 측정 공식을 유도하는 방법론을 제시하였다. 이 논문에서 제시한 방법론의 핵심은 간단히 말해서 사람이 행하는 정성적인 판단을, 이에 가장 근접하는 정량적 측정 체계로 전환시키는 것이라고 보면 된다. 이것을 위해 정량화 문제를 문장의 단순 언어 특징들의 변화값을 이용한 최적화 문제로 환원시키고, 다시 이 최적화 문제를 유전자 알고리즘을 이용해 해결함으로써 문제를 효과적으로 해결할 수 있었다. 실험 결과를 보면, 본 논문에서 제시한 최적화 방법은 주어진 훈련용 예제와 검증용 예제 중 각각 99.84%, 99.88%를 만족시키는 해를 찾아내었으므로 정량적 질 평가 공식의 유도에 매우 효과적임을 알 수 있었다. 또한 도출된 측정 공식을 이용해서 실제 퇴고 시스템 평가에 적용한 결과 문장 질의 측정에 매우 유용하게 이용될 수 있음을 알 수 있었다. 이와 같이 질의 정량적 평가가 가능하다는 사실이 갖는 또 한가지 중요한 의미는 최종 사용자의 구매 의사나 개발자의 공학적 의사 결정을 위한 객관적 성능 평가 자료의 제공에 이 방법이 유용하게 사용될 수 있다는 점이다.Abstract This paper describes a method of building a quantitative measure of the quality of natural language sentences, particularly produced by document revision systems. Evaluating the quality of natural language sentences is intrinsically subjective, so what is most important as to the evaluation is whether the quality can be measured objectively. To solve such problem of objective measurability, genetic algorithm, an evolutionary learning method, is employed in this paper. The underlying standpoint of this approach is that building the quality measures is a task of constructing a formulae that produces as close results as can to the qualitative decisions made by humans. For doing this, the problem of measurability has been simply reduced to an optimization problem using the change of the values of simple linguistic parameters found in sentences, and the reduced problem has been solved effectively by the genetic algorithm. Experimental result shows that the optimization task satisfied 99.84% and 99.88% of the given objectives for training and validation samples, respectively, which means the method is quite effective in constructing the quantitative measure of the quality of natural language sentences. The actual evaluation result of a revision system shows that the measure is useful to quantize the quality of sentences. Another important contribution of this measure would be to provide an objective performance evaluation data of natural language systems on a basis of which end-users and developers can make their decision to fit their own needs.

• 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.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.5
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• pp.574-583
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• 2021

Predicting shipping markets is an important issue. Such predictions form the basis for decisions on investment methods, fleet formation methods, freight rates, etc., which greatly affect the profits and survival of a company. To this end, in this study, we propose a shipping freight rate prediction model for container ships using gated recurrent units (GRUs) and long short-term memory structure. The target of our freight rate prediction is the China Container Freight Index (CCFI), and CCFI data from March 2003 to May 2020 were used for training. The CCFI after June 2020 was first predicted according to each model and then compared and analyzed with the actual CCFI. For the experimental model, a total of six models were designed according to the hyperparameter settings. Additionally, the ARIMA model was included in the experiment for performance comparison with the traditional analysis method. The optimal model was selected based on two evaluation methods. The first evaluation method selects the model with the smallest average value of the root mean square error (RMSE) obtained by repeating each model 10 times. The second method selects the model with the lowest RMSE in all experiments. The experimental results revealed not only the improved accuracy of the deep learning model compared to the traditional time series prediction model, ARIMA, but also the contribution in enhancing the risk management ability of freight fluctuations through deep learning models. On the contrary, in the event of sudden changes in freight owing to the effects of external factors such as the Covid-19 pandemic, the accuracy of the forecasting model reduced. The GRU1 model recorded the lowest RMSE (69.55, 49.35) in both evaluation methods, and it was selected as the optimal model.

• Journal of Technology Innovation
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• v.29 no.3
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• pp.33-62
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• 2021

This study compares and analyzes the efficiency of R&D activities of technology-innovative small and medium-sized enterprises(SMEs) between industries and proposes ways to improve efficiency. The research samples are 6,708 technology-innovative SMEs, which have received a guarantee by the KIBO from 2008 to 2011. Input variables are the level of R&D personnel, R&D investment, and output variables are patent applications, prototype. Efficiency is measured by the DEA model, and indirect comparisons that are individually measured by industry are performed. As a result of the analysis, the CCR for determining the optimal returns to scale is 0.19, the BCC for determining the optimal input distribution is 0.70, and the SE for determining the optimal output is 0.30. By industry type, the medium and low-tech industries have high CCR and BCC, while the high-end and high-tech industries have high SE. R&D activities need to be operated on an optimal scale through managing R&D performance because there is the inefficiency of scale across the industry. The contribution of the study is to analyze the R&D efficiency of each industry of technology-innovative SMEs by the technology evaluation data of the KIBO.

• The Journal of the Korea Contents Association
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• v.21 no.9
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• pp.125-135
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• 2021

Due to the lack of national consensus on the importance and value of the character industry and the lack of recognition of value as a national strategic industry, the development of the character industry is experiencing great difficulties. The purpose of this study is to analyze the economic effects of character industry in China to help establish policies and strategies for the character industry in the future. To this end, this study utilized the China 2017 Industrial Association Table. The analysis results are as follows. China's character industry has a lower production inducement effect than other industries with a column total of 3.45514, and a row total of 1.30015. This shows that China's character industry is still being produced by small and medium-sized companies with a low equity ratio. Second, in the character industry, the index of the sensitivity of dispersion representing the forward linkage effect is 0.01426 and the impact factor is 0.03790, which are all less than 1. Therefore, it can be said to be the final demand manufacturing type.Third, in China character industry's income induction is 0.47690 and the production tax induction effect is -0.04912. It can be seen that the character industry has less income induction and tax burden generated every time the final demand increases by one unit in the entire industry than in other industries.Despite the quantitative growth of the character industry in China, the impact on other industries is low and it is not playing a role as an income-generating industry. Structural improvement is needed for the qualitative development of China's character industry.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.9 no.5
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• pp.281-290
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• 2019

The study aims to analyze teachers' perception of the "personality" area, which can be subjective in the in-depth interview process of selecting gifted children and is easily shunned due to its weak immediate effect. To this end, First, when asked about their difficulties as gifted teachers, many of them answered "professionalism and workload" and cited personality as the most important area to address in-depth interviews in selecting gifted students. It also recognized that personality interviews are necessary for the most basic virtues of education and social contribution, and cited cooperation, consideration, and concession as the sub-components to be dealt with in the personality interview. It was necessary to check whether each student's capabilities were evaluated in a variety of ways in an in-depth interview of the teacher's observing and recommending system. And it needed to be supplemented by in-depth observations such as the development of a valid question, camp or debate in the evaluation of the personality area. In order to reflect the needs of the education field, it will be necessary to supplement the personality interview in the gifted children's selection. And there is also a need to continue to study how to guide the personality education of already selected gifted children.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.9
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• pp.551-557
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• 2019

Diagnosis of abnormal faults is essential for producing high quality products. The role of real-time diagnosis is quite increasing in the batch processes of producing high value-added products such as semiconductors, pharmaceuticals, and so forth. In this study, we evaluate the effect of variable selection and future-value estimation techniques on the performance of the diagnosis system, which is based on nonlinear classification and measurement data. The diagnostic performance can be improved by selecting only the variables that are important and have high contribution for diagnosis. Thus, the diagnostic performance of several variable selection techniques is compared and evaluated. In addition, missing data of a new batch, called future observations, should be estimated because the full data of a new batch is not available before the end of the cycle. In this work the use of different estimation techniques is analyzed. A case study on the polyvinyl chloride batch process was carried out so that optimal variable selection and estimation methods were obtained: maximum 21.9% and 13.3% improvement by variable selection and maximum 25.8% and 15.2% improvement by estimation methods.