• Journal of the Korean Society of Food Science and Nutrition
• /
• v.44 no.3
• /
• pp.347-355
• /
• 2015

Oxidative stress is one of the key mechanisms involved in neuronal damage. Neuroprotective effects and underlying mechanisms of action of several wild vegetables, Cirsium setidens (CS), Pleurospermum kamtschaticumin (PK), and Allium victorials (AV), against oxidative stress induced by hydrogen peroxide in SK-N-SH cells were investigated. CS and AV up to $400{\mu}g/mL$ showed no detectable effects on cell viability of human SK-N-SH neuro-blastoma cells compared with control. Incubation of SK-N-SH cells with hydrogen peroxide resulted in significant induction of cell death and reaction oxygen species (ROS) production, whereas treatment of cells with CS and AV significantly reduced cell death and ROS production, respectively. Among the wild vegetables tested, CS and PK showed more effective DPPH radical scavenging activity than AV, whereas PK showed strong cytotoxicity in SK-N-SH cells compared with the control. CS showed much higher inhibitory effects on cell death and ROS generation against oxidative stress than AV. Thus, CS was selected for subsequent experiments. Ethyl acetate (EA), hexane, butanol, aqueous, and chloroform extracts from CS significantly inhibited cell death and ROS generation in SK-N-SH cells induced by oxidative stress. EA extract from CS (CS-EA) showed the highest DPPH radical-scavenging activity, intra-cellular ROS-scavenging activity, and neuroprotective effects. CS-EA attenuated apoptosis signal-regulating p38 activation by inhibiting phosphorylation. The findings suggest that CS-EA protects neuronal cells through antioxidant activity and inhibition of phosphorylation of p38 in brain neural cells.

• Journal of Energy Engineering
• /
• v.23 no.4
• /
• pp.61-72
• /
• 2014

This paper analyzed transition pathways toward a low carbon society in Korea to meet global $2^{\circ}C$ climate target. Lower economic growth, industrial structure change, enhance of energy demand management, decarbonization of power sector, and replacement of low carbon fuel could reduce greenhouse gas (GHG) emission from fuel combustion in 2050 by 67% against in 2011, or by 74% against in BAU (Business-As-Usual). Lower economic growth contributes to 13% of cumulative emission reduction relative to BAU, industrial structure change 9%, enhance of energy demand management 72%, decarbonization of power sector 5% and replacement of low carbon fuel 1% respectively. Final energy consumption in 2050 needs to be reduced to 50% relative to 2011, or to 41% relative to BAU. Nuclear, coal and renewable energy represent 31%, 40%, 2% respectively among electricity generation in 2011, but 38%, 2%, 32% in 2050. CCS represents 23% of total generation in 2050. Emission intensity of electricity in 2050 was decreased to 19% relative to 2011, or to 24% relative to BAU. Primary energy in 2050 was decreased to 64% compared to 2011, or to 44% compared to BAU. Final energy consumption, primary energy supply and GHG emission from fuel combustion from 1990 to 2011 increased by 176%, 197%, 146%. Radical change from historical trend is required to transit toward a low carbon society by 2050. Appropriate economic growth, structural change to non-energy intensive industries, energy technology research, development and deployment (RD&D) in terms of enhancement of energy efficiency and low carbon energy supply technologies, and fuel change to electricity and renewable energy are key instruments.

• Journal of Energy Engineering
• /
• v.23 no.2
• /
• pp.125-148
• /
• 2014

This paper performs a historical analysis on the various factors contributing to the current carbon lock-in of Korean electricity industry by using techo-institutional complex. The possibilities of the industry's carbon lock-out toward more sustainable development are also investigated. It turns out that market, firm, consumer, and government factors are all responsible for the development of the carbon lock-in of Korean power industry; the Korean government consistently favoring large power plants based on the economy of scale; below-cost electricity tariff; inflation policy to suppress increases in power price; rapid demand growth in summer and winter seasons; rigidities of electricity tariff; and expansion of gas-fired and imported coal-fired large power plants. On the other hand, except for nuclear power generation and smart grid, environment laws and new and renewable energy laws are the other remaining factors contributing to the carbon lock-out. Considering three key points that Korea is an export-oriented economy, the generation mix is the most critical factor to decide the amounts of carbon emission in the power industry, and the share of industry and commercial power consumption is over 85%, it is unlikely that Korea will achieve the carbon lock-out of power industry in the near future. Therefore, there are needs for more integrated approaches from market, firm, consumer, and government all together in order to achieve the carbon lock-out in the electricity industry. Firstly, from the market perspective, it is necessary to persue more active new and renewable energy penetration and to guarantee consumer choices by mitigating the incumbent's monopoly power as in the OECD countries. Secondly, from the firm perspective, the promotion of distributed energy system is urgent, which includes new and renewable resources and demand resources. Thirdly, from the consumer perspective, more green choices in the power tariff and customer awareness on the carbon lock-out are needed. Lastly, the government shall urgently improve power planning frameworks to include the various externalities that were not properly reflected in the past such as environmental and social conflict costs.

• Journal of Environmental Impact Assessment
• /
• v.32 no.1
• /
• pp.1-14
• /
• 2023

When carrying out development projects around Ardeidae breeding habitats, we intend to devise a plan for sustainable coexistence by presenting measures to select and reduce key evaluation items so that conflicts can be prevented in advance at the environmental impact assessment stage. The results of the study are as follows. The main evaluation items are animal and plant items for preservation of Ardeidae breeding habitats and odor and noise items that can evaluate the effects of odors and noise in Ardeidae breeding habitats. First, the scope of the survey in animals and plants categories is not limited to legal guardian species, but includes egrets breeding and feeding grounds corresponding to major species breeding grounds and migratory birds, and preservation measures are established according to the reduction of the area of breeding and feeding grounds. Second, in the odor category, the irradiation period includes the period when the odor generation is the highest from the end of June to the end of July. The odor evaluation standard is based on the complex odor discharge standard, which is a concentration regulation, and the odor concentration felt by humans shall be 2 to 5OU/m³ and the frequency shall be 2% or less. Third, in the noise category, the timing of the survey is measured every month from May to August, including when the sound of egrets and young birds is combined to maximize noise generation. Since the noise of Ardeidae, a bird in summer, occurs only for a certain period of time, measures are taken to reduce noise by securing separation distances, securing buffer green areas, and installing construction rather than installing artificial structures such as soundproof walls. In order for existing Ardeidae breeding sites to maintain an appropriate density of populations and not move populations elsewhere, it is necessary to manage nesting tree and maintain stable habitat quantity and quality.

• Journal of Intelligence and Information Systems
• /
• v.22 no.4
• /
• pp.247-264
• /
• 2016

With the rapid acceleration of low-birth rate and population aging, the employment of the neglected groups of people including the middle aged class is a crucial issue in South Korea. In particular, in the 2010s, the number of the middle aged who want to find a new job after retirement age is significantly increasing with the arrival of the retirement time of the baby boom generation (born 1955-1963). Despite the importance of matching jobs to this emerging middle aged class, private job portals as well as the Korean government do not provide any online job service tailored for them. A gigantic amount of job information is available online; however, the current recruiting systems do not meet the demand of the middle aged class as their primary targets are young workers. We are in dire need of a specially designed recruiting system for the middle aged. Meanwhile, when users are searching the desired occupations on the Worknet website, provided by the Korean Ministry of Employment and Labor, users are experiencing discomfort to search for similar jobs because Worknet is providing filtered search results on the basis of exact matches of a preferred job code. Besides, according to our Worknet data analysis, only about 24% of job seekers had landed on a job position consistent with their initial preferred job code while the rest had landed on a position different from their initial preference. To improve the situation, particularly for the middle aged class, we investigate a soft job matching technique by performing the following: 1) we review a user behavior logs of Worknet, which is a public job recruiting system set up by the Korean government and point out key system design implications for the middle aged. Specifically, we analyze the job postings that include preferential tags for the middle aged in order to disclose what types of jobs are in favor of the middle aged; 2) we develope a new occupation classification scheme for the middle aged, Korea Occupation Classification for the Middle-aged (KOCM), based on the similarity between jobs by reorganizing and modifying a general occupation classification scheme. When viewed from the perspective of job placement, an occupation classification scheme is a way to connect the enterprises and job seekers and a basic mechanism for job placement. The key features of KOCM include establishing the Simple Labor category, which is the most requested category by enterprises; and 3) we design MOMA (Middle-aged Occupation Matching Algorithm), which is a hybrid job matching algorithm comprising constraint-based reasoning and case-based reasoning. MOMA incorporates KOCM to expand query to search similar jobs in the database. MOMA utilizes cosine similarity between user requirement and job posting to rank a set of postings in terms of preferred job code, salary, distance, and job type. The developed system using MOMA demonstrates about 20 times of improvement over the hard matching performance. In implementing the algorithm for a web-based application of recruiting system for the middle aged, we also considered the usability issue of making the system easier to use, which is especially important for this particular class of users. That is, we wanted to improve the usability of the system during the job search process for the middle aged users by asking to enter only a few simple and core pieces of information such as preferred job (job code), salary, and (allowable) distance to the working place, enabling the middle aged to find a job suitable to their needs efficiently. The Web site implemented with MOMA should be able to contribute to improving job search of the middle aged class. We also expect the overall approach to be applicable to other groups of people for the improvement of job matching results.

• Korean Journal of Remote Sensing
• /
• v.37 no.5_1
• /
• pp.1029-1042
• /
• 2021

As part of the next-generation Compact Advanced Satellite 500 (CAS500) project, CAS500-4 is scheduled to be launched in 2025 focusing on the remote sensing of agriculture and forestry. To obtain quantitative information on vegetation from satellite images, it is necessary to acquire surface reflectance through atmospheric correction. Thus, it is essential to develop an atmospheric correction method suitable for CAS500-4. Since the absorption and scattering characteristics in the atmosphere vary depending on the wavelength, it is needed to analyze the sensitivity of atmospheric correction parameters such as aerosol optical depth (AOD) and water vapor (WV) considering the wavelengths of CAS500-4. In addition, as CAS500-4 has only five channels (blue, green, red, red edge, and near-infrared), making it difficult to directly calculate key parameters for atmospheric correction, external parameter data should be used. Therefore, thisstudy performed a sensitivity analysis of the key parameters (AOD, WV, and O₃) using the simulated images based on Sentinel-2 satellite data, which has similar wavelength specifications to CAS500-4, and examined the possibility of using the products of GEO-KOMPSAT-2A (GK2A) as atmospheric parameters. The sensitivity analysisshowed that AOD wasthe most important parameter with greater sensitivity in visible channels than in the near-infrared region. In particular, since AOD change of 20% causes about a 100% error rate in the blue channel surface reflectance in forests, a highly reliable AOD is needed to obtain accurate surface reflectance. The atmospherically corrected surface reflectance based on the GK2A AOD and WV was compared with the Sentinel-2 L2A reflectance data through the separability index of the known land cover pixels. The result showed that two corrected surface reflectance had similar Seperability index (SI) values, the atmospheric corrected surface reflectance based on the GK2A AOD showed higher SI than the Sentinel-2 L2A reflectance data in short-wavelength channels. Thus, it is judged that the parameters provided by GK2A can be fully utilized for atmospheric correction of the CAS500-4. The research findings will provide a basis for atmospheric correction of the CAS500-4 in the future.

• Korean Journal of Culture and Social Issue
• /
• v.21 no.3
• /
• pp.551-573
• /
• 2015

The rise of single living has been one of the most important demographic shifts of recent decades. The solo household is a little less than 40% in Europe areas and that of Tokyo is over 45%. Being impacted this figure, the formation of single economy is the key word in World Economic Forum(WEF) 2008. Seoul' single household is increasing rapidly. Between 2000 and 2005, the growth of single person is around 34%, the population of single person reached 700,000 people. Now 20% of total household in Seoul is Single household. Living alone or solo living is not exceptional or special in Seoul Metropolitan City. The rise in single living will create pressures towards poverty and inequality and so on. Seoul should develop and prepare the urban policy for single household. We figured out the four key trends which composed of single household in Seoul. Four types of single person are like below : Gold Mr and Miss, Reserved labor forces, depressed single and silver generation. Gold group is amonst people aged 30 and 40 who is working in the area of white collar and professional. They are usually elective single person household who have chosen solo living. Reserved labor forces group is usually among 20s people who have not get the regular hob. For this group, job acquiring is the most important issue. Depressed single person household group is among people aged late 30s and 40s. Its group is the result from the broken family. The silver group is among aged over 65 that is the main issue of the aged society. In this research, we stressed that people living alone can be split into two types - elective single person households who have chosen single living, and forced single person household who have been constrained to this lifestyle by circumstances. Except gold group, the rest of the group is the forced single household who are faced to poverty. The monthly income of single person household is almost under 2 million won. Single person household is usually working in the blue collar job and service area. So, except gold group that is the smallest part of single person household, almost single person is not the target of private market, but the object of public policy.

• Information Systems Review
• /
• v.18 no.3
• /
• pp.209-233
• /
• 2016

Internet companies that utilize social network have increased in number. The introduction of diverse social media services facilitated innovative changes in e-business. Social network service (SNS), which is a domain of social media, is a web-based service designed to strengthen human relations in the Internet and build new social relations. The remarkable growth of social network services and the profit generation and perception of this service are the new growth engines of this digital age. Given this development, many global IT companies views SNS as the most powerful form of social media. Thus, they invest efforts to develop business models using SNS.2) This study verifies the impact of privacy exposure in SNS as a result of privacy invasion. This study examines the purpose of using the SNS and user's awareness of the significance of personal information, which are key factors that affect self-disclosure of personal information. This study utilizes theory of reasoned action (TRA) to provide a theoretical platform that describes the specific behavior and emotional response of individuals. This study presents a research model that considers negative attitude (negatude). In this model, self-disclosure in SNS is considered a TRA. TRA is a subjective norm, a behavioral intention, and a key variable of exposure behavior. A survey was conducted on college students at Y university in Seoul to empirically verify the research model. The students have experiences in using SNS. A total of 198 samples were collected. Path analysis was applied to analyze the relations of factors. The results of path analysis show the statistically insignificant impact of privacy invasion on negatude, subjective norm, behavioral intention, and exposure behavior. The impact of unrecognized privacy invasion was also considered insignificant. The impacts of intention to use SNS on negatude, subjective norm, behavioral intention, and exposure behavior was significant. A significant impact was also found for the significance of personal information on subjective norm, behavioral intention, and exposure behavior, whereas the impact on negatude was insignificant. The impact of subjective norm on behavioral intention was significant. Lastly, the impact of behavioral intention on exposure behavior was insignificant. These findings are significant because the study examined the process of self-disclosure by integrating psychological and social factors based on theoretical discussion.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.15 no.1
• /
• pp.285-301
• /
• 2020

Looking at the problem of aging in the nation from a demographic perspective, it is not a problem of the overall population, but of the structure of the population. It is the baby boomer and post-baby boomers, the largest population in the country. Baby boomers were born between 1955 and 1963, and currently have a population of 7001,333, which is 13.6 percent (as of 2015). The Post-Baby Boomer generation was born between 1964 and 1974, with a total population of 9,567,171, accounting for 18.8 percent of the total population. In particular, baby boomers and post-baby boomers (32.4% of the total population) have begun to retire or will retire soon. The average life expectancy continues to increase due to the development of medical technology, and the falling birth rate of newborns and the declining population of the production population are darkening the domestic economy. In a policy proposal aimed at easing the nation's falling economic growth rate, women's participation rate is as high as Sweden and men's efforts to increase it as high as Japan's, while the elderly rate is desirable to maintain Korea's high level. This is because the expansion of the elderly generation's participation in economic activities could ease a sharp drop in economic growth and reduce the burden of supporting the elderly population. The study, based on this social problem awareness and problem solving plan, looks at the relationship between career orientation and satisfaction in start-up education based on the diverse career base of active seniors, and also suggests the importance of customized start-up education on the diversity of active seniors by clarifying the relationship between them, and suggests the desirable direction of senior start-up policy design, funding, and start-up education. Based on the theoretical background, the concept of five factors was defined: active senior, career-oriented, satisfaction level of start-up education, willingness to start a business, and the concept definition of an active senior, which is particularly key to the baby boomers in their 50s and 60s, is generally regarded as a source of consumption or welfare benefits, but in this study, the concept of active start-up is reflected in the domestic start-up market by young people in their 40s, 50s and 60s. As a result of a hypothesis test. Hypothesis 1 and Hypothesis 5: Career orientation has been verified to affect the willingness to start a business and the behavior of preparation for a start-up. Hypothesis 3: The willingness to start a business has been verified as having an effect between startup preparation actions. Hypothesis 4: The satisfaction level of start-up education has been verified to affect start-up preparation behavior. However, hypothesis 2: The satisfaction level of education for start-ups does not affect the willingness to start a business. Such results can be inferred that satisfaction in start-up education does not have a direct effect on the will to start a business and increases the will to start a business through the influence of personal career orientation.

• Journal of Intelligence and Information Systems
• /
• v.25 no.2
• /
• pp.25-38
• /
• 2019

Selecting high-quality information that meets the interests and needs of users among the overflowing contents is becoming more important as the generation continues. In the flood of information, efforts to reflect the intention of the user in the search result better are being tried, rather than recognizing the information request as a simple string. Also, large IT companies such as Google and Microsoft focus on developing knowledge-based technologies including search engines which provide users with satisfaction and convenience. Especially, the finance is one of the fields expected to have the usefulness and potential of text data analysis because it's constantly generating new information, and the earlier the information is, the more valuable it is. Automatic knowledge extraction can be effective in areas where information flow is vast, such as financial sector, and new information continues to emerge. However, there are several practical difficulties faced by automatic knowledge extraction. First, there are difficulties in making corpus from different fields with same algorithm, and it is difficult to extract good quality triple. Second, it becomes more difficult to produce labeled text data by people if the extent and scope of knowledge increases and patterns are constantly updated. Third, performance evaluation is difficult due to the characteristics of unsupervised learning. Finally, problem definition for automatic knowledge extraction is not easy because of ambiguous conceptual characteristics of knowledge. So, in order to overcome limits described above and improve the semantic performance of stock-related information searching, this study attempts to extract the knowledge entity by using neural tensor network and evaluate the performance of them. Different from other references, the purpose of this study is to extract knowledge entity which is related to individual stock items. Various but relatively simple data processing methods are applied in the presented model to solve the problems of previous researches and to enhance the effectiveness of the model. From these processes, this study has the following three significances. First, A practical and simple automatic knowledge extraction method that can be applied. Second, the possibility of performance evaluation is presented through simple problem definition. Finally, the expressiveness of the knowledge increased by generating input data on a sentence basis without complex morphological analysis. The results of the empirical analysis and objective performance evaluation method are also presented. The empirical study to confirm the usefulness of the presented model, experts' reports about individual 30 stocks which are top 30 items based on frequency of publication from May 30, 2017 to May 21, 2018 are used. the total number of reports are 5,600, and 3,074 reports, which accounts about 55% of the total, is designated as a training set, and other 45% of reports are designated as a testing set. Before constructing the model, all reports of a training set are classified by stocks, and their entities are extracted using named entity recognition tool which is the KKMA. for each stocks, top 100 entities based on appearance frequency are selected, and become vectorized using one-hot encoding. After that, by using neural tensor network, the same number of score functions as stocks are trained. Thus, if a new entity from a testing set appears, we can try to calculate the score by putting it into every single score function, and the stock of the function with the highest score is predicted as the related item with the entity. To evaluate presented models, we confirm prediction power and determining whether the score functions are well constructed by calculating hit ratio for all reports of testing set. As a result of the empirical study, the presented model shows 69.3% hit accuracy for testing set which consists of 2,526 reports. this hit ratio is meaningfully high despite of some constraints for conducting research. Looking at the prediction performance of the model for each stocks, only 3 stocks, which are LG ELECTRONICS, KiaMtr, and Mando, show extremely low performance than average. this result maybe due to the interference effect with other similar items and generation of new knowledge. In this paper, we propose a methodology to find out key entities or their combinations which are necessary to search related information in accordance with the user's investment intention. Graph data is generated by using only the named entity recognition tool and applied to the neural tensor network without learning corpus or word vectors for the field. From the empirical test, we confirm the effectiveness of the presented model as described above. However, there also exist some limits and things to complement. Representatively, the phenomenon that the model performance is especially bad for only some stocks shows the need for further researches. Finally, through the empirical study, we confirmed that the learning method presented in this study can be used for the purpose of matching the new text information semantically with the related stocks.