• Proceedings of the Korean Institute of Interior Design Conference
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• 2005.10a
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• pp.223-226
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• 2005

The latest trend of our medical industry seems to have a raise on more expectation and interest in mystical therapeutics of herb medicine and its efficiency especially for the disease such as chronicity and other obstinacy that used to be impossibie to be cured with only Western medical treatment. potentiality of ideal medical treatment through interchanging of medical study between Eastern and Western is becoming an issue today. Herb medicine is our native ethnic medicine and is based on the friendly-nature and human oriented under one of the classification of natural medicine. The point of this medicine has a strong connection with the conceptional trait of Health-Care that is been newly paid a lot of attention in Western medical science. This 'Y'Oriental Medical Clinic Interior Design is to grant a new possibility of global recognition of herb medicine getting over from a limited ethnic medicine by correcting the existing problems and expanding its scope to a part of natural medicine and to newly establish its meaning as a space for Health-Care utilizing a concept of nature.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.22 no.1
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• pp.1-8
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• 2012

Objectives: The aim of this study is to review occupational hygiene activities, including work environment measurement as required by the industrial safety and health laws of Korea, and suggest improvements required to establish an effective exposure surveillance system. Methods: The controversial limitations of exposure surveillance examining the work-association of several types of cancers in semiconductor workers were reviewed. Results: The bulk of the exposure surveillance system was found to focus purely on work environment measurements without providing other important exposure surrogates, such as job title, operation, exposure duration, etc. The current work environment measurement system is limited in terms of the efficient assessment of the exposure status of workers due to a lack of exposure information. Conclusion: The introduction of a national standard classification of occupations and job titles into the exposure and health effect surveillance system should be discussed in order to retrospectively assess exposure characteristics.

• Journal of the Korea Computer Industry Society
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• v.9 no.2
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• pp.93-98
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• 2008

In this study, analyzed principle about stream cipher that is formed to Cellular Automata foundation. Cellular Automata can embody complicated and various principle with simple identifying marks that is State, Neighborhood, Transition Rules originally. Cellular Automata is hinting that can handle encipherment smoothly using transition rule. Create binary pad (key stream) by Cellular Automata's transition rule 30 applications in treatise that see therefore, and experimented ability of encryption and decryption because using stream cipher of symmetric key encryption way of password classification.

• Annual Conference of KIPS
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• 2015.10a
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• pp.1846-1848
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• 2015

가스를 사용하는 산업 영역이 지속적으로 확장됨에 따라, 가스작업의 안전 관리 문제가 중요하게 대두되고 있다. 이는 특히 최근 발전 중인 사물네트워크(이하 IoT)를 활용하여 작업안전관리를 보다 용이하게 이루어가는 방향으로 연구되고 있다. 본 논문에서는 국내외에서 개발 중인 가스 시설 안전을 위한 IoT 시스템과 작업자를 효과적으로 연동시킬 수 있는 모바일 앱의 설계 방안을 모색하기 위해 우선적으로 작업자의 사용 용이성을 확보하기 위한 설계 방향을 설정하고, 이를 기준으로 석유화학산업에서 이루어지는 작업을 분류하여 배치하였다.

• Advances in environmental research
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• v.3 no.2
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• pp.131-149
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• 2014

Two different model selection indices, the Akaike information criterion (AIC) and the coefficient of determination ($R^2$), are used to discriminate competing isotherm equations for aqueous pollutant removal systems. The former takes into account model accuracy and complexity while the latter considers model accuracy only. The five types of isotherm shape in the Brunauer-Deming-Deming-Teller (BDDT) classification are considered. Sorption equilibrium data taken from the literature were correlated using isotherm equations with fitting parameters ranging from two to five. For the isotherm shapes of types I (favorable) and III (unfavorable), the AIC favors two-parameter equations which can easily track these simple isotherm shapes with high accuracy. The $R^2$ indicator by contrast recommends isotherm equations with more than two parameters which can provide marginally better fits than two-parameter equations. To correlate the more intricate shapes of types II (multilayer), IV (two-plateau) and V (S-shaped) isotherms, both indices favor isotherm equations with more than two parameters.

• Asian Journal of Innovation and Policy
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• v.10 no.2
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• pp.159-176
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• 2021

Over the past two decades, smart cities have been attracting attention as a means of solving urban problems and as a model for securing urban sustainability. Many studies have been conducted in various fields such as conceptual definitions, classification, new technologies, case analysis, and civic participation of smart cities. In particular, applicable technologies and their importance have been highlighted so far. However, since a city is a complex and meta-systematic space, it is the overly optimistic prospect that technology, one of the smart city components, will lead to successful smart cities. This study elucidates the impediments to driving smart cities as a case study of South Korea, a leading country in smart technology and digital transformation. We examined three comprehensive national plans for promoting smart cities and conducted focus group interviews with experts in smart cities to analyze the obstacles to carrying smart cities. We classified the thirteen impediments into technological, industrial, governmental, and social factors as a result. Some of them are generic issues in policy establishment and enforcement, while others are specific to smart cities.

• Journal of information and communication convergence engineering
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• v.19 no.3
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• pp.166-174
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• 2021

A large volume of patient data is generated from various devices used in healthcare applications. With increase in the volume of data generated in the healthcare industry, more wellness monitoring is required. A cloud-enabled analysis of healthcare data that predicts patient risk factors is required. Machine learning techniques have been developed to address these medical care problems. A novel technique called the radix-trie-based Tanimoto kernel regressive infomax boost classification (RT-TKRIBC) technique is introduced to analyze the heterogeneous health data in the cloud to predict the health risks and send alerts. The infomax boost ensemble technique improves the prediction accuracy by finding the maximum mutual information, thereby minimizing the mean square error. The performance evaluation of the proposed RT-TKRIBC technique is realized through extensive simulations in the cloud environment, which provides better prediction accuracy and less prediction time than those provided by the state-of-the-art methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.6
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• pp.3219-3237
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• 2019

The Cloud Computing is growing rapidly in the current IT industry. Cloud computing has become a buzzword in relation to Grid & Utility computing. It provides on demand services to customers and customers will pay for what they get. Various "Cloud Service Provider" such as Microsoft Azure, Google Web Services etc. enables the users to access the cloud in cost effective manner. However, security, privacy and integrity of data is a major concern. In this paper various security challenges have been identified and the survey briefs the comprehensive overview of various security issues in cloud computing. The classification of security issues in cloud computing have been studied. In this paper we have discussed security challenges in cloud computing and also list recommended methods available for addressing them in the literature.

• Journal of Korea Multimedia Society
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• v.24 no.4
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• pp.519-527
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• 2021

Alzheimer's disease is one of the challenges to tackle in the coming aging era and is attempting to diagnose and predict through various biomarkers. While the application of various deep learning-based technologies as powerful imaging technologies has recently expanded across the medical industry, empirical design is not easy because there are various deep earning neural networks architecture and categorical hyperparameters that rely on problems and data to solve. In this paper, we show the possibility of optimizing a deep learning neural network structure and hyperparameters for Alzheimer's disease classification in amyloid brain images in a representative deep earning neural networks architecture using genetic algorithms. It was observed that the optimal deep learning neural network structure and hyperparameter were chosen as the values of the experiment were converging.

• Food Science and Industry
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• v.50 no.1
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• pp.57-66
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• 2017

Home meal replacements (HMR) are kinds of convenient foods as cooked or semi-cooked foods, which are produced outside of home, to eat directly or after simple cooking in substitution for traditional home meals. Recently the market size for HMR is expanding rapidly around the world due to the changes of global consumer trends, growth of single-person household, increase in economic participation of women, aging population, and so on. The Europe takes over 52.4% of the global market share for HMR in global HMR market, and North America, Asia-Pacific, and Africa-Middle East are following. The most popular HMR products in US and Europe are frozen foods, whereas the market share of chilled products in Asia including Japan, South Korea, and Vietnam are much higher than that in US and Europe. Currently, the trends in HMR is focus on the expansion of the list of products that replace for meals with simple cooking, but it is expected that nutrition-enforced HMR product for aged persons or patients who live alone are requested for the further growth of the HMR market.