• The Korean Journal of Physiology and Pharmacology
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• v.26 no.1
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• pp.15-24
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• 2022

The development of selective targeting of drug molecules towards the mitochondria is an important issue related to therapy efficacy. In this study, we report that gallic acid (GA)-mitochondria targeting sequence (MTS)-H₃R₉ exhibits a dual role as a mitochondria-targeting vehicle with antioxidant activity for disease therapy. In viability assays, GA-MTS-H₃R₉ showed a better rescue action compared to that of MTS-H₃R₉. GA-MTS-H₃R₉ dramatically exhibited cell penetration and intercellular uptake compared to MTS and fit escape from lysosome release to the cytosol. We demonstrated the useful targeting of GA-MTS-H₃R₉ towards mitochondria in AC16 cells. Also, we observed that the antioxidant properties of mitochondrial-accrued GA-MTS-H₃R₉ alleviated cell damage by reactive oxygen species production and disrupted mitochondrial membrane potential. GA-MTS-H₃R₉ showed a very increased cytoprotective effect against anticancer activity compared to that of MTS-H₃R₉. We showed that GA-MTS-H₃R₉ can act as a vehicle for mitochondria-targeting and as a reagent for therapeutic applications intended for cardiovascular disease treatment.

• Journal of Sensor Science and Technology
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• v.33 no.4
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• pp.230-236
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• 2024

This study aimed to analyze the environmental factors affecting tomato growth by examining the correlation between weather and growth environment sensor data from P Smart Farm located in Gwangseok-myeon, Nonsan-si, Chungcheongnam-do. Key environmental variables such as the temperature, humidity, sunlight hours, solar radiation, and daily light integral (DLI) significantly affect tomato growth. The optimal temperature and DLI conditions play crucial roles in enhancing tomato growth and the photosynthetic efficiency. In this study, we developed a model to correct and predict the time-series variations in internal environmental sensor data using external weather sensor data. A linear regression analysis model was employed to estimate the external temperature variations and internal DLI values of P Smart Farm. Then, regression equations were derived based on these data. The analysis verified that the estimated variations in external temperature and internal DLI are explained effectively by the regression models. In this research, we analyzed and monitored smart-farm growth environment data based on weather sensor data. Thereby, we obtained an optimized model for the temperature and light conditions crucial for tomato growth. Additionally, the study emphasizes the importance of sensor-based data analysis in dynamically adjusting the tomato growth environment according to the variations in weather and growth conditions. The observations of this study indicate that analytical solutions using public weather data can provide data-driven operational experiences and productivity improvements for small- and medium-sized facility farms that cannot afford expensive sensors.

• Information Systems Review
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• v.24 no.2
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• pp.41-66
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• 2022

With the development of IT, mobile apps and the expansion of contactless services due to COVID-19, "smart orders" have recently been activated in the food and beverage service. Even in recent years, when sales have declined, the number of orders made by smart orders has been steadily increasing, and this ordering method can accumulate customer data, enabling effective customized services in the future. In the present study, satisfaction with smart orders and continuous use intention were studied based on the technology acceptance model (TAM). And it focused on whether there is a difference in personality when using smart orders. For this purpose, a survey was conducted on 317 smart order users, and the hypothesis was verified by structural equation model analysis. Perceived benefits had a significant effect on satisfaction; also, satisfaction had a significant effect on continuous use intention. There is a significant disparity between introvert and extrovert type. As a consequence, the introverted type has a greater intention to perceive usefulness of smart orders and continuously use them. These results suggest that the customer's personality type should be considered in future customer customization strategies.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.5
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• pp.409-415
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• 2016

Recently several techniques for disaster prevention based on IoT(Internet of Things) are being developed. In this paper, a new smart pattern classification method for electric loads is proposed. CT(Current Transformer) data are extracted from electric loads, and then the sampled CT data are converted using FFT and MFCC. FFT and FMCC data are used for the input data of neural networks. Experiments were conducted using FFT and MFCC data for 7 kinds of electric loads. Experiments results indicate the superiority of MFCC in comparison to FFT.

• Journal of Korea Multimedia Society
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• v.21 no.3
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• pp.415-422
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• 2018

Advances of telecommunication technology bring various changes in journalism field. Reporters started to gather, edit, and transmit content to main server in media company using hand-held smart media and notebook computer. This paper tried to testify valid bit-rate of visual news content using LTE network and mobile phone. Field news like natural disasters need real-time transmission of video content. But broadcasting company normally use heavy ENG system and transmission satellite trucks. We prepared and experimented different types of visual content that has different bit-rates. Transmission tool was LU-60HD mobile system of LiveU Corporation. Transmission result shows that bit-rate of 2Mbps news content is not suitable for broadcasting and VBR (Variable Bit Rate) transmission has better definition quality than CBR (Constant Bit Rate) method. Three different bit-rate of VBR transmission result shows that 5Mbps clip has better quality than 1Mbps and 3Mbps. The higher bit-rate, the better video quality. But if the content has much movements, that cause delay and abnormal quality of video. So optimizing the balance between stability of signal and quality of bit-rate is crucial factor of real-time broadcasting news gathering business.

• Land and Housing Review
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• v.9 no.2
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• pp.1-7
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• 2018

The purpose of this study is to suggest diagnosis indicators and checklist for urban regeneration projects by Korea Land & Housing Corporation(LH). There are already deprivation indices in the Urban Regeneration Act but not any additional guidelines in the practical aspect. In order to use the diagnosis indicators, the central government should supply more specific checklist to the actors in the regeneration field. The key actor of many stakeholders is LH as an operator and implementer in the regeneration projects. So far, LH has developed housing and cities and there haven't been any obvious changes to realize public benefit in the deteriorated area. From now on, It has to plan, implement, and manage a lot of regeneration projects entirely. Therefore, It is necessary to develope and apply the diagnosis indicators and checklist based on projects. This paper came up with the 6 factors related with LH business field : housing, urban infrastructure, public service, private service, environment, and smart city. For these, 32 diagnosis indicators and 72 checklists were selected that can include both physical and qualitative indicators. These can be used not only for the selection of regeneration projects but also for the process monitoring such as planning and implementation.

• Proceedings of the Korea Information Processing Society Conference
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• 2014.11a
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• pp.833-836
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• 2014

화장품산업의 세계적 트렌드는 기능성화장품에서 개인별 맞춤 화장품 시장으로 발전하고 있다. 해외 유명 브랜드 제품들이, 발 빠른 대처로 보다 세분화되고 기능성을 갖춘 화장품을 생산하면서, 고가로 출시하고 있으나 개인의 다양한 피부 특성과 기호에 상응하는 맞춤 제품을 제공하진 못하고 있는 실정이다. 이러한 환경에K-Beauty의 영향을 고려하여 개인별 피부특성과 요구사항을 반영한 맞춤화장품 개발을 위해 국내에 거주하는 전국의 20대 여성들을 주 대상으로 자가 설문과 피부측정을 통해 피부특성을 분석하고 이에 따른 중요 요인들을 찾고자 하였다. 결과를 통해 국내의 20대 여성들은 지성타입의 피부와 민감성에 많은 분포를 가진 것으로 확인되었고, 선행연구의 내용과 상응하는 결과 외에 피부 타입과 민감성에는 적극적인 피부 관리를 위한 생활습관 등이 중요한 영향을 미치고 있음을 확인할 수 있었다.

• Journal of the Korean Society of Propulsion Engineers
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• v.26 no.6
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• pp.53-61
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• 2022

The estimation method of combustion efficiency has been introduced by using closed bomb test(CBT). The Noble-Abel equation of state was applied to consider the real gas effects to take account of high operation pressure about a couple of 100 atm. of CBT. The heat loss through the CBT wall was considered. The volume change of grain was calculated by applying form functions, which estimated combustion efficiency of 8 different gain shapes. The combustion estimation method proposed in this study was fairly validated by the comparision with the pressure-time history data of the CBT experiments. The effects of both grain shape and propellant loading density were analyzed.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.6
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• pp.203-213
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• 2021

A vehicle crash occurs due to various factors such as the geometry of the road section, traffic, and driver characteristics. A safety performance function has been used in many studies to estimate the relationship between vehicle crash and road factors statistically. And depends on the purpose of the analysis, various characteristic variables have been used. And various characteristic variables have been used in the studies depending on the purpose of analysis. The existing domestic studies generally reflect the average characteristics of the sections by quantifying the traffic volume in macro aggregate units such as the ADT, but this has a limitation that it cannot reflect the real-time changing traffic characteristics. Therefore, the need for research on effective aggregation units that can flexibly reflect the characteristics of the traffic environment arises. In this paper, we develop a safety performance function that can reflect the traffic characteristics in detail with an aggregate unit for one hour in addition to the daily model used in the previous studies. As part of the present study, we also perform a comparison and evaluation between models. The safety performance function for daily and hourly units is developed using a negative binomial regression model with the number of accidents as a dependent variable. In addition, the optimal negative binomial regression model for each of the hourly and daily models was selected, and their prediction performances were compared. The model and evaluation results presented in this paper can be used to determine the risk factors for accidents in the highway section considering the dynamic characteristics. In addition, the model and evaluation results can also be used as the basis for evaluating the availability and transferability of the hourly model.

• Journal of Internet Computing and Services
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• v.15 no.1
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• pp.103-112
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• 2014

In recent years, the rapid diffusion of smart devices and growth of internet usage and social media has led to a constant production of huge amount of valuable data set that includes personal information, buying patterns, location information and other things. IT and Production Infrastructure has also started to produce its own data with the vitalization of M2M (Machine-to-Machine) and IoT (Internet of Things). This analysis study researches the applicable effects of Structured and Unstructured Big Data in various business circumstances, and purposes to find out the value creation method for a corporation through the Structured and Unstructured Big Data case studies. The result demonstrates that corporations looking for the optimized big data utilization plan could maximize their creative values by utilizing Unstructured and Structured Big Data generated interior and exterior of corporations.