• Journal of Intelligence and Information Systems
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• v.20 no.3
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• pp.45-58
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• 2014

The Korean Culture Contents spread out to Worldwide, because the Korean wave is sweeping in the world. The contents stand in the middle of the Korean wave that we are used it. Each country is ongoing to keep their Culture industry improve the national brand and High added value. Performing contents is important factor of arousal in the enterprise industry. To improve high arousal confidence of product and positive attitude by populace is one of important factor by advertiser. Culture contents is the same situation. If culture contents have trusted by everyone, they will give information their around to spread word-of-mouth. So, many researcher study to measure for person's arousal analysis by statistical survey, physiological response, body movement and facial expression. First, Statistical survey has a problem that it is not possible to measure each person's arousal real time and we cannot get good survey result after they watched contents. Second, physiological response should be checked with surround because experimenter sets sensors up their chair or space by each of them. Additionally it is difficult to handle provided amount of information with real time from their sensor. Third, body movement is easy to get their movement from camera but it difficult to set up experimental condition, to measure their body language and to get the meaning. Lastly, many researcher study facial expression. They measures facial expression, eye tracking and face posed. Most of previous studies about arousal and interest are mostly limited to reaction of just one person and they have problems with application multi audiences. They have a particular method, for example they need room light surround, but set limits only one person and special environment condition in the laboratory. Also, we need to measure arousal in the contents, but is difficult to define also it is not easy to collect reaction by audiences immediately. Many audience in the theater watch performance. We suggest the system to measure multi-audience's reaction with real-time during performance. We use difference image analysis method for multi-audience but it weaks a dark field. To overcome dark environment during recoding IR camera can get the photo from dark area. In addition we present Multi-Audience Engagement Index (MAEI) to calculate algorithm which sources from sound, audience' movement and eye tracking value. Algorithm calculates audience arousal from the mobile survey, sound value, audience' reaction and audience eye's tracking. It improves accuracy of Multi-Audience Engagement Index, we compare Multi-Audience Engagement Index with mobile survey. And then it send the result to reporting system and proposal an interested persons. Mobile surveys are easy, fast, and visitors' discomfort can be minimized. Also additional information can be provided mobile advantage. Mobile application to communicate with the database, real-time information on visitors' attitudes focused on the content stored. Database can provide different survey every time based on provided information. The example shown in the survey are as follows: Impressive scene, Satisfied, Touched, Interested, Didn't pay attention and so on. The suggested system is combine as 3 parts. The system consist of three parts, External Device, Server and Internal Device. External Device can record multi-Audience in the dark field with IR camera and sound signal. Also we use survey with mobile application and send the data to ERD Server DB. The Server part's contain contents' data, such as each scene's weights value, group audience weights index, camera control program, algorithm and calculate Multi-Audience Engagement Index. Internal Device presents Multi-Audience Engagement Index with Web UI, print and display field monitor. Our system is test-operated by the Mogencelab in the DMC display exhibition hall which is located in the Sangam Dong, Mapo Gu, Seoul. We have still gotten from visitor daily. If we find this system audience arousal factor with this will be very useful to create contents.

• Journal of the Korean Society of Food Science and Nutrition
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• v.46 no.3
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• pp.358-367
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• 2017

Preservatives, as food additives, are occasionally intrinsic to natural raw materials or sometimes generated during the fermentation process as reported in many research articles. Preservative compounds in raw food materials may persist in the final food product, which is not supposed to include such preservative compounds. In this study, we validated an analytical method for preservative compounds in raw materials of functional foods. Quantification of benzoic acid and sorbic acid was determined using HPLC-PDA analysis after distillation, whereas propionic acid was quantified with GC-FID. A significant set of validation data (accuracy, precision, linearity, recovery, etc) was acquired. A total of 212 samples were collected for analysis of naturally occurred preservatives, and preservatives were detected in 85 samples. Most of the detected samples showed less 10 mg/kg of preservatives. The results of this study provide fundamental data on naturally occurring preservatives in raw materials of functional foods. Moreover, building up a database of naturally occurring preservatives could solve problems in the current scientific data.

• Archives of design research
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• v.20 no.1 s.69
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• pp.5-20
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• 2007

The aim of this research is to find out the flows of mega-trends and design trends by analyzing the factors that influence trend and design trends in the late 20th century. Moreover, it is to forecast and recommend design color trends by evaluating color trends in design trends for the near future. Secondary and primary research were used in parallel. In the late 20th century, mega-trends were analyzed from secondary research based on PEST. Design trends were analyzed from case studies in fashion, space, product and visual design. On this basis, design color trends were analyzed. Also, color trends were forecast for the near future. The results are as follows. Firstly, the main trends in the late 20th century were 'female thinking', 'back to the nature' and 'heaven of peace'. Second, main design trends in the 1970s were modernism, post-modernism and high-tech. In the 1980s, with those of the 1970s, ecology was introduced In the late 1980s. In the 1990s, modernism rose again and ecology had an influence. The trends of 'female thinking' and 'back to the nature' controled the design in the early 2000s. Third, design colors in the late 20th century changed from Red to Purple Blue. Tones changed from 'grayish' to 'dull' Finally, it was forecast that Purple Blue, Yellow Red and Green colors with 'grayish', 'dull' and 'deep' tones were going to be used mainly in the near future. Also, achromatic colors with female and warm nuances would be reflected in design parts. This research will be very useful in that it has built a concrete database reflected on design trends forecasting in the near future by organizing academically a methodology to identify trends reflected on design and identifying relation between mega-trends and design trends based on analyzing factors that influence trend.

• Korean Journal of Environmental Biology
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• v.32 no.3
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• pp.168-175
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• 2014

In order to understand the phytoplankton community structure based on their cell size duringlow water temperature periods, we studied 10 stations in the East Sea, Korea on March, 2012. The minimum standing crops of total phytoplankton were $3.4{\times}10^6cells\;L^{-1}$ at the station 5. The maximum values were $7.6{\times}10^6cells\;L^{-1}$ at the station 8, which is two times the amount of the minimum. The carbon mass at the station 4 ($6.3{\times}10^8pg\;L^{-1}$) was more than forty times higher compared with station 5 ($0.08{\times}10^8pg\;L^{-1}$). From these results, we found a significant difference between standing crops and carbon mass which might have caused due to their differences in community structure and cell size. Therefore, we considered the types of plankton biomass to estimate the primary product in the specific location and/or time. The phytoplankton communities were classified in 3 types: microplankton (> $20{\mu}m$), nanoplankton (< $20{\mu}m$) and picoplankton (< $2{\mu}m$). In the case of picoplankton, various morphological types were observed during the study period. These various picoplankton species were further classified as S (spherical), SF (spherical&flagella), O (oval), OF (oval&flagella) or R (rod) type, and we analyzed their community structure based on these categories. The picoplankton was found to be the most dominant type at 8 stations and S type as the most popular. The picoplankton seems to be the significant organism in the marine ecology during low water temperature periods in the coastal waters of East Sea. Therefore, picoplankton \;-with scientific surveys can be considered as the database for their identification. In conclusion, we suggest that cell size of the phytoplankton would be the best criteria to accurately analyze their community structure and to reveal groups having more ecological influence.

• Journal of Life Science
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• v.14 no.4
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• pp.650-656
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• 2004

Oryza grandiglumis (CCDD, 2n=48), one of the wild rice species, has been known to possess fungal-,bacterial-, and insect-resistance against sheath blight, rice blast, bacterial leaf blight and brown plant hopper (Nilaparvata lugens). To rapidly isolate differentially expressed genes responding to fungal and wounding stress, wounding and yeast extract were treated to O. grandiglumis for 24 hrs. Suppression subtractive hybridization (SSH) method was used to obtain differentially expressed genes from yeast extract and wounding treated plants. Seven hundreds and seventy six clones were obtained by subcloning PCR product, and colony array and screening were carried out using radio-isotope labeled cDNA probes prepared from the wounding and yeast extract treated plants. One hundred and fifteen colonies were confirmed as true positive ones. Average insert size of the clones were ranged from 400 bp to 700 bp and all the inserts were sequenced. To decide the identity of those clones, sequences were analyzed by sequence homology via GenBank database. The homology search result showed that 68 clones were matched to the genes with known function; 16 were related to primary metabolism, 5 to plant retrotransposons, 5 to defense related metallothionein-like genes. In addition to that, others were matched to various genes with known function in amino acid synthesis and processing, membrane transport, and signal transduction, so on. In northern blot analysis, induced expressions of ogwfi-161, ogwfi-646, ogwfi-663, and ogwfi-695 by wounding and yeast extract treatments were confirmed. The result indicates that SSH method is very efficient for rapid screening of differentially expressed genes.

• Journal of the Korean Society of Food Science and Nutrition
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• v.37 no.2
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• pp.217-222
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• 2008

The aim of the present study was to evaluate the effect of marination with mixed salt (NaCl, $CaCl_2$, and phosphate) and kiwi juice and of different cooking methods for pork loin-based products in order to establish the basic database for increasing the consumption of pork loin in Korea. Diced chilled pork loin ($2{\times}2{\times}2\;cm$) was marinated in 4 different treatments: no additives (T1), salt mix only (T2), kiwi juice only (T3), and salt mix+kiwi juice (T4). The mixed salt was prepared by the addition of NaCl, $CaCl_2$, and phosphate dissolved in water (10% of pork loin weight) at concentrations of 0.5, 0.5, and 0.3% per pork loin weight, respectively. The amount of kiwi juice was 10% of pork loin weight. After marination for 24 hrs at $4^{\circ}C$, the samples were cooked with different methods including roasting with Kimchi, pan broiling, and simmering. After simmering, pH of pork loin of T1 and T2 was higher than that of T3 and T4 (p<0.05), while that of roasted with Kimchi and pan broiled did not show any difference. Water holding capacity of T4 after pan broiling was higher than that of T1, T2, and T3 (p<0.001) and shear force of T4 was lower than other treatments. Also flavor and acceptability of T4 after pan broiling were scored higher by 11 sensory panelists (p<0.05). From this result, the pork loin-based products marinated with mixed salt and kiwi juice with pan broiling would be preferred by consumers as one of the methods to promote the consumption of pork loin in Korea.

• Korea Science and Art Forum
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• v.31
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• pp.21-32
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• 2017

Local festivals form the regional cultures and atmosphere of communication; they increase the demand of domestic tourism businesses and thus, have an important role in ripple effects (e.g. regional image improvement, tourist influx, job creation, regional contents development, and local product sales) and economic revitalization. IoT (Internet of Thing) technologies have been developed especially, beacon-one of the IoT services has been applied as plenty of types and forms both domestically and internationally. However, notwithstanding expansion of current digital mobile technologies, it still remains as difficult for the individual to track the information about all the local festivals and to fulfill the tourists' needs of enjoying festivals given the weak strategic approaches and advertisement activities. Furthermore, current festival-related mobile applications don't function well as delivering information and have numerous contents issues (e.g. ways of information delivery within the festival places, independent application usage for each festival, one time usage due to one time event). This research, based on the background mentioned above, aims to develop the local festival mobile application and data analysis system applying beacon technology. First of all, three algorithms were developed, namely, 'festival crowding algorithm', 'visitor stats algorithm', and 'customized information algorithm', and then beta test was followed with the developed application and data analysis system. As a result, they could form the database of visitors' types and behaviors, and provide functions and services, such as personalized information, waiting time for festival contents, and 'hot place' function. Besides, in Google Play store, they also got the titles given with more than 13,000 downloads within first three months and as the most exposed application related with festivals; and, thus, got credited with their marketability and excellence. This research follows this order: chapter 2 shows the literature review of local festival related with technology development, beacon service, and festival application. In Chapter 3, design plans and conditions are described of developing local festival mobile application and data analysis system with beacon. Chapter 4 evaluates the results of the beta performance test to verify applicability of the developed application and data analysis system, and lastly, chapter 5 explains the conclusion and suggests the future research.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.123-139
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• 2019

The job classification system of major job sites differs from site to site and is different from the job classification system of the 'SQF(Sectoral Qualifications Framework)' proposed by the SW field. Therefore, a new job classification system is needed for SW companies, SW job seekers, and job sites to understand. The purpose of this study is to establish a standard job classification system that reflects market demand by analyzing SQF based on job offer information of major job sites and the NCS(National Competency Standards). For this purpose, the association analysis between occupations of major job sites is conducted and the association rule between SQF and occupation is conducted to derive the association rule between occupations. Using this association rule, we proposed an intelligent job classification system based on data mapping the job classification system of major job sites and SQF and job classification system. First, major job sites are selected to obtain information on the job classification system of the SW market. Then We identify ways to collect job information from each site and collect data through open API. Focusing on the relationship between the data, filtering only the job information posted on each job site at the same time, other job information is deleted. Next, we will map the job classification system between job sites using the association rules derived from the association analysis. We will complete the mapping between these market segments, discuss with the experts, further map the SQF, and finally propose a new job classification system. As a result, more than 30,000 job listings were collected in XML format using open API in 'WORKNET,' 'JOBKOREA,' and 'saramin', which are the main job sites in Korea. After filtering out about 900 job postings simultaneously posted on multiple job sites, 800 association rules were derived by applying the Apriori algorithm, which is a frequent pattern mining. Based on 800 related rules, the job classification system of WORKNET, JOBKOREA, and saramin and the SQF job classification system were mapped and classified into 1st and 4th stages. In the new job taxonomy, the first primary class, IT consulting, computer system, network, and security related job system, consisted of three secondary classifications, five tertiary classifications, and five fourth classifications. The second primary classification, the database and the job system related to system operation, consisted of three secondary classifications, three tertiary classifications, and four fourth classifications. The third primary category, Web Planning, Web Programming, Web Design, and Game, was composed of four secondary classifications, nine tertiary classifications, and two fourth classifications. The last primary classification, job systems related to ICT management, computer and communication engineering technology, consisted of three secondary classifications and six tertiary classifications. In particular, the new job classification system has a relatively flexible stage of classification, unlike other existing classification systems. WORKNET divides jobs into third categories, JOBKOREA divides jobs into second categories, and the subdivided jobs into keywords. saramin divided the job into the second classification, and the subdivided the job into keyword form. The newly proposed standard job classification system accepts some keyword-based jobs, and treats some product names as jobs. In the classification system, not only are jobs suspended in the second classification, but there are also jobs that are subdivided into the fourth classification. This reflected the idea that not all jobs could be broken down into the same steps. We also proposed a combination of rules and experts' opinions from market data collected and conducted associative analysis. Therefore, the newly proposed job classification system can be regarded as a data-based intelligent job classification system that reflects the market demand, unlike the existing job classification system. This study is meaningful in that it suggests a new job classification system that reflects market demand by attempting mapping between occupations based on data through the association analysis between occupations rather than intuition of some experts. However, this study has a limitation in that it cannot fully reflect the market demand that changes over time because the data collection point is temporary. As market demands change over time, including seasonal factors and major corporate public recruitment timings, continuous data monitoring and repeated experiments are needed to achieve more accurate matching. The results of this study can be used to suggest the direction of improvement of SQF in the SW industry in the future, and it is expected to be transferred to other industries with the experience of success in the SW industry.

• Journal of Intelligence and Information Systems
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• v.19 no.1
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• pp.57-77
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• 2013

Social media has become one of the most popular media in web and mobile application. In 2011, social networks and blogs are still the top destination of online users, according to a study from Nielsen Company. In their studies, nearly 4 in 5active users visit social network and blog. Social Networks and Blogs sites rule Americans' Internet time, accounting to 23 percent of time spent online. Facebook is the main social network that the U.S internet users spend time more than the other social network services such as Yahoo, Google, AOL Media Network, Twitter, Linked In and so on. In recent trend, most of the companies promote their products in the Facebook by creating the "Facebook Page" that refers to specific product. The "Like" option allows user to subscribed and received updates their interested on from the page. The film makers which produce a lot of films around the world also take part to market and promote their films by exploiting the advantages of using the "Facebook Page". In addition, a great number of streaming service providers allows users to subscribe their service to watch and enjoy movies and TV program. They can instantly watch movies and TV program over the internet to PCs, Macs and TVs. Netflix alone as the world's leading subscription service have more than 30 million streaming members in the United States, Latin America, the United Kingdom and the Nordics. As the matter of facts, a million of movies and TV program with different of genres are offered to the subscriber. In contrast, users need spend a lot time to find the right movies which are related to their interest genre. Recent years there are many researchers who have been propose a method to improve prediction the rating or preference that would give the most related items such as books, music or movies to the garget user or the group of users that have the same interest in the particular items. One of the most popular methods to build recommendation system is traditional Collaborative Filtering (CF). The method compute the similarity of the target user and other users, which then are cluster in the same interest on items according which items that users have been rated. The method then predicts other items from the same group of users to recommend to a group of users. Moreover, There are many items that need to study for suggesting to users such as books, music, movies, news, videos and so on. However, in this paper we only focus on movie as item to recommend to users. In addition, there are many challenges for CF task. Firstly, the "sparsity problem"; it occurs when user information preference is not enough. The recommendation accuracies result is lower compared to the neighbor who composed with a large amount of ratings. The second problem is "cold-start problem"; it occurs whenever new users or items are added into the system, which each has norating or a few rating. For instance, no personalized predictions can be made for a new user without any ratings on the record. In this research we propose a clustering method according to the users' genre interest extracted from social network service (SNS) and user's movies rating information system to solve the "cold-start problem." Our proposed method will clusters the target user together with the other users by combining the user genre interest and the rating information. It is important to realize a huge amount of interesting and useful user's information from Facebook Graph, we can extract information from the "Facebook Page" which "Like" by them. Moreover, we use the Internet Movie Database(IMDb) as the main dataset. The IMDbis online databases that consist of a large amount of information related to movies, TV programs and including actors. This dataset not only used to provide movie information in our Movie Rating Systems, but also as resources to provide movie genre information which extracted from the "Facebook Page". Formerly, the user must login with their Facebook account to login to the Movie Rating System, at the same time our system will collect the genre interest from the "Facebook Page". We conduct many experiments with other methods to see how our method performs and we also compare to the other methods. First, we compared our proposed method in the case of the normal recommendation to see how our system improves the recommendation result. Then we experiment method in case of cold-start problem. Our experiment show that our method is outperform than the other methods. In these two cases of our experimentation, we see that our proposed method produces better result in case both cases.