• Journal of Food Hygiene and Safety
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• v.27 no.4
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• pp.466-472
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• 2012

In this study, ribulose bisphosphate carboxylase (rbcL), RNApolymeraseC (rpoC1), intergenic spacer (psbA-trnH), and second internal transcribed spacer (ITS2) as identification markers for discrimination of P. mirifica in foods were selected. To be primer design, we obtained 719 bp, 520 bp, 348 bp, and 507 bp amplicon using universal primers from selected regions of P. mirifica. The regions of rbcL, rpoC1, and psbA-trnH were not proper for design primers because of high homology about P. mirifica, P. lobata, and B. superba. But, we had designed 4 pairs of oligonucleotide primers from ITS2 gene. Predicted amplicon from P. mirifica were obtained 137 bp and 216 bp using finally designed primers SFI12-miri-6F/SFI12-miri-7R and SFI12-miri-6F/SFI12-miri-8R, respectively. The species-specific primers distinguished P. mirifica from related species were able to apply food materials and processed foods. The developed PCR method would be applicable to food safety management for illegally distributed products in markets and internet shopping malls.

• Korean journal of food and cookery science
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• v.19 no.4
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• pp.529-538
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• 2003

The objectives of this study were to measure customers' cognition and overall satisfaction, and to identify relatively important attributes for the overall satisfaction, of home-delivered meals. Questionnaires were distributed to 243 customers. The statistical data analyses were completed by x$^2$-tests, ANOV A, factor analysis, reliability analysis and regression analysis using SPSS version 10. 56.6% of customers get obtained information from the internet, with 31.3% of these using this method at least once a week, but 72.9% of customers used this method less than once per years. The major reasons for ordering home-delivered meals were tired of cooking, more economical and no time to cook. The results were significantly different in relation to age, occupation and monthly income. The major reasons for hesitation about ordering home-delivered meals were meals should be prepared in households, not sanitary and the use of too many artificial flavors. The results for this factor were significantly different in relation to gender, age and monthly income(p<0.01). The most preferred kinds of home-delivery meals were Korean soup (guk), stew, soup (tang), speciality dishes and party dishes. The customer's cognition of kindness of the delivery staff was highest, with food temperature being the lowest among the options. The food and service level factors were derived from a factor based analysis of customer's cognition towards home-delivered meals. The customer's cognition of food taste, food quantity, kindness of delivery staff and packaging container shape were significantly different according to the use frequency and use period. The packaging method, sanitation, kindness of delivery staff, price and taste were the most relatively important attributes for overall satisfaction with home-delivered meals.

• The Korean Journal of Archival Studies
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• no.1
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• pp.23-76
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• 2000

In this paper, I examined what have been researched and determined about preservation strategy and selection of preservation media in the western archival community. Archivists have primarily been concerned with 'preservation' and 'use' of archival materials worth of being preserved permanently. In the new information era, preservation and use of archival materials were faced with new challenge. Life expectancy of paper records was shortened due to acidification and brittleness of the modem papers. Also emergence of information technology affects the traditional way of preservation and use of archival materials. User expectations are becoming so high technology-oriented and so complicated as to make archivists act like information managers using computer technology rather than traditional archival handicraft. Preservation strategy plays an important role in archival management as well as information management. For a cost-effective management of archives and archival institutions, preservation strategy is a must. The preservation strategy encompasses all aspects of archival preservation process and practices, from selection of archives, appraisal, inventorying, arrangement, description, conservation, microfilming or digitization, archival buildings, and access service. Those archival functions should be considered in their relations to each other to ensure proper preservation of archival materials. In the integrated preservation strategy, 'preservation' and 'use' should be combined and fulfilled without sacrificing the other. Preservation strategy planning is essential to determine the policies of archives to preserve their holdings safe and provide people with a maximum access in most effective ways. Preservation microfilming is to ensure permanent preservation of information held in important archival materials. To do this, a detailed standardization has been developed to guarantee the permanence of microfilm as well as its product quality. Silver gelatin film can last up to 500 years in the optimum storage environment and the most viable option for permanent preservation media. ISO and ANIS developed such standards for the quality of microfilms and microfilming technology. Preservation microfilming guidelines was also developed to ensure effective archival management and picture quality of microfilms. It is essential to assess the need of preservation microfilming. Limit in resources always put a restraint on preservation management. Appraisal (and selection) of what to be preserved was the most important part of preservation microfilming. In addition, microfilms with standard quality can be scanned to produce quality digital images for instant use through internet. As information technology develops, archivists began to utilize information technology to make preservation easier and more economical, and to promote use of archival materials through computer communication network. Digitization was introduced to provide easy and universal access to unique archives, and its large capacity of preserving archival data seems very promising. However, digitization, i.e., transferring images of records to electronic codes, still, needs to be standardized. Digitized data are electronic records, and st present electronic records are very unstable and not to be preserved permanently. Digital media including optical disks materials have not been proved as reliable media for permanent preservation. Due to their chemical coating and physical character using light, they are not stable and can be preserved at best 100 years in the optimum storage environment. Most CD-R can last only 20 years. Furthermore, obsolescence of hardware and software makes hard to reproduce digital images made from earlier versions. Even if when reformatting is possible, the cost of refreshing or upgrading of digital images is very expensive and the very process has to be done at least every five to ten years. No standard for this obsolescence of hardware and software has come into being yet. In short, digital permanence is not a fact, but remains to be uncertain possibility. Archivists must consider in their preservation planning both risk of introducing new technology and promising possibility of new technology at the same time. In planning digitization of historical materials, archivists should incorporate planning for maintaining digitized images and reformatting them in the coming generations of new applications. Without the comprehensive planning, future use of the expensive digital images will become unavailable. And that is a loss of information, and a final failure of both 'preservation' and 'use' of archival materials. As peter Adelstein said, it is wise to be conservative when considerations of conservations are involved.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.3
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• pp.175-186
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• 2019

Efforts have been made to introduce the climate smart agriculture (CSA) for adaptation to future climate conditions, which would require collection and management of site specific meteorological data. The objectives of this study were to identify requirements for construction of agricultural meteorology information service system (AMISS) using technologies that lead to the fourth industrial revolution, e.g., internet of things (IoT), artificial intelligence, and cloud computing. The IoT sensors that require low cost and low operating current would be useful to organize wireless sensor network (WSN) for collection and analysis of weather measurement data, which would help assessment of productivity for an agricultural ecosystem. It would be recommended to extend the spatial extent of the WSN to a rural community, which would benefit a greater number of farms. It is preferred to create the big data for agricultural meteorology in order to produce and evaluate the site specific data in rural areas. The digital climate map can be improved using artificial intelligence such as deep neural networks. Furthermore, cloud computing and fog computing would help reduce costs and enhance the user experience of the AMISS. In addition, it would be advantageous to combine environmental data and farm management data, e.g., price data for the produce of interest. It would also be needed to develop a mobile application whose user interface could meet the needs of stakeholders. These fourth industrial revolution technologies would facilitate the development of the AMISS and wide application of the CSA.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.145-165
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• 2023

Recommendation system plays a significant role on relieving difficulties of selecting information among rapidly increasing amount of information caused by the development of the Internet and on efficiently displaying information that fits individual personal interest. In particular, without the help of recommendation system, E-commerce and OTT companies cannot overcome the long-tail phenomenon, a phenomenon in which only popular products are consumed, as the number of products and contents are rapidly increasing. Therefore, the research on recommendation systems is being actively conducted to overcome the phenomenon and to provide information or contents that are aligned with users' individual interests, in order to induce customers to consume various products or contents. Usually, collaborative filtering which utilizes users' historical behavioral data shows better performance than contents-based filtering which utilizes users' preferred contents. However, collaborative filtering can suffer from cold-start problem which occurs when there is lack of users' historical behavioral data. In this paper, hybrid music recommendation system, which can solve cold-start problem, is proposed based on the playlist data of Melon music streaming service that is given by Kakao Arena for music playlist continuation competition. The goal of this research is to use music tracks, that are included in the playlists, and metadata of music tracks and playlists in order to predict other music tracks when the half or whole of the tracks are masked. Therefore, two different recommendation procedures were conducted depending on the two different situations. When music tracks are included in the playlist, LightFM is used in order to utilize the music track list of the playlists and metadata of each music tracks. Then, the result of Item2Vec model, which uses vector embeddings of music tracks, tags and titles for recommendation, is combined with the result of LightFM model to create final recommendation list. When there are no music tracks available in the playlists but only playlists' tags and titles are available, recommendation was made by finding similar playlists based on playlists vectors which was made by the aggregation of FastText pre-trained embedding vectors of tags and titles of each playlists. As a result, not only cold-start problem can be resolved, but also achieved better performance than ALS, BPR and Item2Vec by using the metadata of both music tracks and playlists. In addition, it was found that the LightFM model, which uses only artist information as an item feature, shows the best performance compared to other LightFM models which use other item features of music tracks.

• Journal of Venture Innovation
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• v.5 no.1
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• pp.91-106
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• 2022

Cryptocurrency, stood out the sharp cost rising of Bitcoin has been spotlighted by means of the solution for stagflation because it is decentralized with an existing currency differently. Especially getting into 4th industrial revolution, technologies using block chain and internet of things have been used in the many fields, and the power of influence is also widespread. Nevertheless like a remark of Elon Musk of Tesla CEO, the problems of environmental contamination for cryptocurrency have been pointed out continuously and the most representative of them is an enormous electric usage as the use of fossil fuels. Also the amount generated of carbon dioxide result in the acceleration of global warming mainly based on the climate changes of earth if the existing mining method is continued. On the other hand, review researches have been conducted restrictively as the connection with environmental contamination as the mining of cryptocurrency. In this study, it intended to review problems for environmental contamination as the diversification of ecological system of cryptocurrency concretely. Upon investigation existing prior documents on the putting recent data first, the mining of cryptocurrency has affected on the environmental contamination conflicting with carbon neutrality as increasement of the electric usage and electronic wastes. And POS method without the mining process appeared, but it had a demerit collapsing a decentralization and then we met turning point on appearing various environmental-friendly cryptocurrency. Finally the appearance of cryptocurrency using new renewable energy acted on the opportunity of the usage maximization of energy storage apparatus and the birth of national government intervention. Based on these results, we mention clearly that hereafter cryptocurrency will regress if not go abreast the value of currency as well as environmental approach.

• Information Systems Review
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• v.22 no.2
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• pp.137-166
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• 2020

While South Koreans overseas travelling rate has been increased every year, domestic travelling rate has been at a standstill for several years. The purpose of this study is to analyze domestic traveling styles of Koreans according to their generations in order to provide generation-specific traveling services. For this purpose, we categorized the survey respondents into four different generations, which are Millennium (age 19~34), X generation (35~54), Baby Boomer (55~64) and senior by following the criterions of the Korea National Tourism Organization. After then, we analyze factors related to travel preparation process, the actual traveling activities and satisfaction after the travel. In this study, 16,713 data collected by the Ministry of Culture, Sports and Tourism are used. The results of this study show that Korean people tends to acquire domestic traveling information from their own or acquaintances past experiences. Also, they do not prefer the organized trip for domestic travels, thus do not buy package products a lot. In addition, natural scenery, rich in cultural heritage, and convenient accommodation are the most important determinant factors affecting the overall travel satisfaction of level for all generations. The traveling characteristics for each generation are as follows. Millennium get traveling information from the internet a lot, and more specifically, they refer portal sites and social network services (SNS) in many cases. Also, they tend to travel in summer peak season to popular destinations and pursues active traveling experiences. Generation X has similar traveling patterns with Millennium, however they major transportation method is using their own car. Also, transportation convenience and satisfactory leisure activity are important factors affecting the overall satisfaction level to Generation X. On the other hand, Baby boomer generation has a greater emphasis on appreciation of nature, visiting famous restaurants, and relaxation, rather than actively participating experiencing programs. They travel evenly in summer and spring/fall season to many different areas instead of focusing on popular tourist spots. In addition, shopping and eating delicious food are the important factors affecting the overall satisfaction level for them. Lastly, Senior generation has similar characteristics with Baby boomer in many ways, however, they travel a lot on the same day using public transportations or car rental service. They prefer spring and autumn trips rather than summer peak season, and tend to buy packaged travel products a lot compared with other generations. If these different traveling characteristics of each generation are considered for organizing and customizing tourism services, it is expected that domestic tourism satisfaction level will be ultimately increased.

• Asia pacific journal of information systems
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• v.22 no.4
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• pp.101-123
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• 2012

Currently, Social Media, it has widely a renown keyword and its related social trends and businesses have been fastly applied into various contexts. Social media has become an important research area for scholars interested in online technologies and cyber space and their social impacts. Social media is not only including web-based services but also mobile-based application services that allow people to share various style information and knowledge through online connection. Social media users have tendency to common identity- and bond-attachment through interactions such as 'thumbs up', 'reply note', 'forwarding', which may have driven from various factors and may result in delivering information, sharing knowledge, and specific experiences et al. Even further, almost of all social media sites provide and connect unknown strangers depending on shared interests, political views, or enjoyable activities, and other stuffs incorporating the creation of contents, which provides benefits to users. As fast developing digital devices including smartphone, tablet PC, internet based blogging, and photo and video clips, scholars desperately have began to study regarding diverse issues connecting human beings' motivations and the behavioral results which may be articulated by the format of antecedents as well as consequences related to contents that people create via social media. Social media such as Facebook, Twitter, or Cyworld users are more and more getting close each other and build up their relationships by a different style. In this sense, people use social media as tools for maintain pre-existing network, creating new people socially, and at the same time, explicitly find some business opportunities using personal and unlimited public networks. In terms of theory in explaining this phenomenon, social capital is a concept that describes the benefits one receives from one's relationship with others. Thereby, social media use is closely related to the form and connected of people, which is a bridge that can be able to achieve informational benefits of a heterogeneous network of people and common identity- and bonding-attachment which emphasizes emotional benefits from community members or friend group. Social capital would be resources accumulated through the relationships among people, which can be considered as an investment in social relations with expected returns and may achieve benefits from the greater access to and use of resources embedded in social networks. Social media using for their social capital has vastly been adopted in a cyber world, however, there has been little explaining the phenomenon theoretically how people may take advantages or opportunities through interaction among people, why people may interactively give willingness to help or their answers. The individual consciously express themselves in an online space, so called, common identity- or bonding-attachments. Common-identity attachment is the focus of the weak ties, which are loose connections between individuals who may provide useful information or new perspectives for one another but typically not emotional support, whereas common-bonding attachment is explained that between individuals in tightly-knit, emotionally close relationship such as family and close friends. The common identify- and bonding-attachment are mainly studying on-offline setting, which individual convey an impression to others that are expressed to own interest to others. Thus, individuals expect to meet other people and are trying to behave self-presentation engaging in opposite partners accordingly. As developing social media, individuals are motivated to disclose self-disclosures of open and honest using diverse cues such as verbal and nonverbal and pictorial and video files to their friends as well as passing strangers. Social media context, common identity- and bond-attachment for self-presentation seems different compared with face-to-face context. In the realm of social media, social users look for self-impression by posting text messages, pictures, video files. Under the digital environments, people interact to work, shop, learn, entertain, and be played. Social media provides increasingly the kinds of intention and behavior in online. Typically, identity and bond social capital through self-presentation is the intentional and tangible component of identity. At social media, people try to engage in others via a desired impression, which can maintain through performing coherent and complementary communications including displaying signs, symbols, brands made of digital stuffs(information, interest, pictures, etc,). In marketing area, consumers traditionally show common-identity as they select clothes, hairstyles, automobiles, logos, and so on, to impress others in any given context in a shopping mall or opera. To examine these social capital and attachment, we combined a social capital theory with an attachment theory into our research model. Our research model focuses on the common identity- and bond-attachment how they are formulated through social capitals: cognitive capital, structural capital, relational capital, and individual characteristics. Thus, we examined that individual online kindness, self-rated expertise, and social relation influence to build common identity- and bond-attachment, and the attachment effects make an impact on both the willingness to help, however, common bond seems not to show directly impact on information sharing. As a result, we discover that the social capital and attachment theories are mainly applicable to the context of social media and usage in the individual networks. We collected sample data of 256 who are using social media such as Facebook, Twitter, and Cyworld and analyzed the suggested hypotheses through the Structural Equation Model by AMOS. This study analyzes the direct and indirect relationship between the social network service usage and outcomes. Antecedents of kindness, confidence of knowledge, social relations are significantly affected to the mediators common identity-and bond attachments, however, interestingly, network externality does not impact, which we assumed that a size of network was a negative because group members would not significantly contribute if the members do not intend to actively interact with each other. The mediating variables had a positive effect on toward willingness to help. Further, common identity attachment has stronger significant on shared information.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.29-44
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• 2017

In Internet commerce, consumers are heavily influenced by product reviews written by other users who have already purchased the product. However, as the product reviews accumulate, it takes a lot of time and effort for consumers to individually check the massive number of product reviews. Moreover, product reviews that are written carelessly actually inconvenience consumers. Thus many online vendors provide mechanisms to identify reviews that customers perceive as most helpful (Cao et al. 2011; Mudambi and Schuff 2010). For example, some online retailers, such as Amazon.com and TripAdvisor, allow users to rate the helpfulness of each review, and use this feedback information to rank and re-order them. However, many reviews have only a few feedbacks or no feedback at all, thus making it hard to identify their helpfulness. Also, it takes time to accumulate feedbacks, thus the newly authored reviews do not have enough ones. For example, only 20% of the reviews in Amazon Review Dataset (Mcauley and Leskovec, 2013) have more than 5 reviews (Yan et al, 2014). The purpose of this study is to analyze the factors affecting the usefulness of online product reviews and to derive a forecasting model that selectively provides product reviews that can be helpful to consumers. In order to do this, we extracted the various linguistic, psychological, and perceptual elements included in product reviews by using text-mining techniques and identifying the determinants among these elements that affect the usability of product reviews. In particular, considering that the characteristics of the product reviews and determinants of usability for apparel products (which are experiential products) and electronic products (which are search goods) can differ, the characteristics of the product reviews were compared within each product group and the determinants were established for each. This study used 7,498 apparel product reviews and 106,962 electronic product reviews from Amazon.com. In order to understand a review text, we first extract linguistic and psychological characteristics from review texts such as a word count, the level of emotional tone and analytical thinking embedded in review text using widely adopted text analysis software LIWC (Linguistic Inquiry and Word Count). After then, we explore the descriptive statistics of review text for each category and statistically compare their differences using t-test. Lastly, we regression analysis using the data mining software RapidMiner to find out determinant factors. As a result of comparing and analyzing product review characteristics of electronic products and apparel products, it was found that reviewers used more words as well as longer sentences when writing product reviews for electronic products. As for the content characteristics of the product reviews, it was found that these reviews included many analytic words, carried more clout, and related to the cognitive processes (CogProc) more so than the apparel product reviews, in addition to including many words expressing negative emotions (NegEmo). On the other hand, the apparel product reviews included more personal, authentic, positive emotions (PosEmo) and perceptual processes (Percept) compared to the electronic product reviews. Next, we analyzed the determinants toward the usefulness of the product reviews between the two product groups. As a result, it was found that product reviews with high product ratings from reviewers in both product groups that were perceived as being useful contained a larger number of total words, many expressions involving perceptual processes, and fewer negative emotions. In addition, apparel product reviews with a large number of comparative expressions, a low expertise index, and concise content with fewer words in each sentence were perceived to be useful. In the case of electronic product reviews, those that were analytical with a high expertise index, along with containing many authentic expressions, cognitive processes, and positive emotions (PosEmo) were perceived to be useful. These findings are expected to help consumers effectively identify useful product reviews in the future.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.109-125
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• 2019

As interest on intelligent search engines increases, various studies have been conducted to extract and utilize the features related to products intelligencely. In particular, when users search for goods in e-commerce search engines, the 'color' of a product is an important feature that describes the product. Therefore, it is necessary to deal with the synonyms of color terms in order to produce accurate results to user's color-related queries. Previous studies have suggested dictionary-based approach to process synonyms for color features. However, the dictionary-based approach has a limitation that it cannot handle unregistered color-related terms in user queries. In order to overcome the limitation of the conventional methods, this research proposes a model which extracts RGB values from an internet search engine in real time, and outputs similar color names based on designated color information. At first, a color term dictionary was constructed which includes color names and R, G, B values of each color from Korean color standard digital palette program and the Wikipedia color list for the basic color search. The dictionary has been made more robust by adding 138 color names converted from English color names to foreign words in Korean, and with corresponding RGB values. Therefore, the fininal color dictionary includes a total of 671 color names and corresponding RGB values. The method proposed in this research starts by searching for a specific color which a user searched for. Then, the presence of the searched color in the built-in color dictionary is checked. If there exists the color in the dictionary, the RGB values of the color in the dictioanry are used as reference values of the retrieved color. If the searched color does not exist in the dictionary, the top-5 Google image search results of the searched color are crawled and average RGB values are extracted in certain middle area of each image. To extract the RGB values in images, a variety of different ways was attempted since there are limits to simply obtain the average of the RGB values of the center area of images. As a result, clustering RGB values in image's certain area and making average value of the cluster with the highest density as the reference values showed the best performance. Based on the reference RGB values of the searched color, the RGB values of all the colors in the color dictionary constructed aforetime are compared. Then a color list is created with colors within the range of ${\pm}50$ for each R value, G value, and B value. Finally, using the Euclidean distance between the above results and the reference RGB values of the searched color, the color with the highest similarity from up to five colors becomes the final outcome. In order to evaluate the usefulness of the proposed method, we performed an experiment. In the experiment, 300 color names and corresponding color RGB values by the questionnaires were obtained. They are used to compare the RGB values obtained from four different methods including the proposed method. The average euclidean distance of CIE-Lab using our method was about 13.85, which showed a relatively low distance compared to 3088 for the case using synonym dictionary only and 30.38 for the case using the dictionary with Korean synonym website WordNet. The case which didn't use clustering method of the proposed method showed 13.88 of average euclidean distance, which implies the DBSCAN clustering of the proposed method can reduce the Euclidean distance. This research suggests a new color synonym processing method based on RGB values that combines the dictionary method with the real time synonym processing method for new color names. This method enables to get rid of the limit of the dictionary-based approach which is a conventional synonym processing method. This research can contribute to improve the intelligence of e-commerce search systems especially on the color searching feature.