• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.57-76
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• 2017

Recently, consumer needs are diversifying as information technologies are evolving rapidly. A lot of IT devices such as smart phones and tablet PCs are launching following the trend of information technology. While IT devices focused on the technical advance and improvement a few years ago, the situation is changed now. There is no difference in functional aspects, so companies are trying to differentiate IT devices in terms of appearance design. Consumers also consider design as being a more important factor in the decision-making of smart phones. Smart phones have become a fashion items, revealing consumers' own characteristics and personality. As the design and appearance of the smartphone become important things, it is necessary to examine consumer values from the design and appearance of IT devices. Furthermore, it is crucial to clarify the mechanisms of consumers' design evaluation and develop the design evaluation model based on the mechanism. Since the influence of design gets continuously strong, various and many studies related to design were carried out. These studies can classify three main streams. The first stream focuses on the role of design from the perspective of marketing and communication. The second one is the studies to find out an effective and appealing design from the perspective of industrial design. The last one is to examine the consumer values created by a product design, which means consumers' perception or feeling when they look and feel it. These numerous studies somewhat have dealt with consumer values, but they do not include product attributes, or do not cover the whole process and mechanism from product attributes to consumer values. In this study, we try to develop the holistic design evaluation model based on consumer values based on three-step approach from product attributes, perceived attributes, to consumer values. Product attributes means the real and physical characteristics each smart phone has. They consist of bezel, length, width, thickness, weight and curvature. Perceived attributes are derived from consumers' perception on product attributes. We consider perceived size of device, perceived size of display, perceived thickness, perceived weight, perceived bezel (top - bottom / left - right side), perceived curvature of edge, perceived curvature of back side, gap of each part, perceived gloss and perceived screen ratio. They are factorized into six clusters named as 'Size,' 'Slimness,' 'No-Frame,' 'Roundness,' 'Screen Ratio,' and 'Looseness.' We conducted qualitative research to find out consumer values, which are categorized into two: look and feel values. We identified the values named as 'Silhouette,' 'Neatness,' 'Attractiveness,' 'Polishing,' 'Innovativeness,' 'Professionalism,' 'Intellectualness,' 'Individuality,' and 'Distinctiveness' in terms of look values. Also, we identifies 'Stability,' 'Comfortableness,' 'Grip,' 'Solidity,' 'Non-fragility,' and 'Smoothness' in terms of feel values. They are factorized into five key values: 'Sleek Value,' 'Professional Value,' 'Unique Value,' 'Comfortable Value,' and 'Solid Value.' Finally, we developed the holistic design evaluation model by analyzing each relationship from product attributes, perceived attributes, to consumer values. This study has several theoretical and practical contributions. First, we found consumer values in terms of design evaluation and implicit chain relationship from the objective and physical characteristics to the subjective and mental evaluation. That is, the model explains the mechanism of design evaluation in consumer minds. Second, we suggest a general design evaluation process from product attributes, perceived attributes to consumer values. It is an adaptable methodology not only smart phone but also other IT products. Practically, this model can support the decision-making when companies initiative new product development. It can help product designers focus on their capacities with limited resources. Moreover, if its model combined with machine learning collecting consumers' purchasing data, most preferred values, sales data, etc., it will be able to evolve intelligent design decision support system.

• Journal of Nutrition and Health
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• v.41 no.6
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• pp.561-572
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• 2008

Currently, Korea is facing dramatic nutrition transition among children, which may increase risk of degenerative diseases due to excessive intakes of fats, sugars and sodium. Promotion of eating healthier foods among children is difficult because the present nutrition label is not easily understood. Therefore, to promote healthier foods this study was aimed at developing guidance of standard amounts of high, medium and low levels of sugars, sodium, fats and other components contained in foods or drinks that are promoted to or formulated for consumption by children. Multipronged approach was used to collecting information, including key word searches in Medline and other databases, internet searches, reports from world organization, and contact of key individuals who work in organizations. We reviewed dietary reference intakes for Koreans, nutrient reference values, nutrient content claims of nutrition labeling, guideline daily amounts of United Kingdom, dietary guidelines and consumption data of nutrients, and selected components for labeling. And we decided goals of guideline daily amounts for children and nutrient criteria to underpin the high, medium and low content of each component. Then we collected data on processed foods sold at 12 middle schools and 11 high schools in Seoul, and classified processed foods into food category. Sales per one student per day were in the order of snacks, breads, and non-carbonated drinks. One hundred forty five mostly consumed products were selected and classified into criteria of high, medium and low total fat or sodium. Eighty five(58.6%) were classified into high fat food and only 11(7.6%) into high sodium food, in case that the base is chosen per 100 g or 100 mL. In conclusion, the nutrient criteria and choice of 100 g base, which we suggest in this study, need to be tested by simulation with more processed foods and refined in view of the practical issues suggested by stakeholders in future.

• Journal of Korean Home Economics Education Association
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• v.19 no.2
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• pp.35-49
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• 2007

The purpose of this research was to analyze the contents of Housing Studies in Home Economics Education of Secondary School published in master's or doctorial theses and journals since 1985. The 24 research papers were analyzed by the type and time of publication, research subjects, data collecting methods, respondents & sample size, and statistical methods. The data were presented by tables with frequencies. The results showed that the most Housing educational research has been done as a type of theses and the number of published papers on Housing has been increased in somewhat. Over time there were two main theme of Housing educational research: general perception of housing and teaching - learning plans. Research methods, respondents and sample size, and statistical methods were obviously differed by the two research theme of Housing educational studies. This research suggested to broaden the research subjects as well as research methods beside to increase the number of studies on Housing area in Home Economics Education.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.67-101
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• 2014

The use of new technology greatly shapes the marketing strategies used by companies to engage their consumers. Among these new technologies, social media is used to reach out to the organization's audience online. One of the most popular social media channels to date is the microblogging platform Twitter. With 500 million tweets sent on average daily, the microblogging platform is definitely a rich source of data for researchers, and a lucrative marketing medium for companies. Nonetheless, one of the challenges for companies in developing an effective Twitter campaign is the limited theoretical and empirical evidence on the proper organizational usage of Twitter despite its potential advantages for a firm's external communications. The current study aims to provide empirical evidence on how firms can utilize Twitter effectively in their marketing communications using the association between brand personality and brand engagement that several branding researchers propose. The study extends Aaker's previous empirical work on brand personality by applying the Brand Personality Scale to explore whether Twitter brand communities convey distinctive brand personalities online and its influence on the communities' level or intensity of consumer engagement and sentiment quality. Moreover, the moderating effect of the product involvement construct in consumer engagement is also measured. By collecting data for a period of eight weeks using the publicly available Twitter application programming interface (API) from 23 accounts of Twitter-verified business-to-consumer (B2C) brands, we analyze the validity of the paper's hypothesis by using computerized content analysis and opinion mining. The study is the first to compare Twitter marketing across organizations using the brand personality concept. It demonstrates a potential basis for Twitter strategies and discusses the benefits of these strategies, thus providing a framework of analysis for Twitter practice and strategic direction for companies developing their use of Twitter to communicate with their followers on this social media platform. This study has four specific research objectives. The first objective is to examine the applicability of brand personality dimensions used in marketing research to online brand communities on Twitter. The second is to establish a connection between the congruence of offline and online brand personalities in building a successful social media brand community. Third, we test the moderating effect of product involvement in the effect of brand personality on brand community engagement. Lastly, we investigate the sentiment quality of consumer messages to the firms that succeed in communicating their brands' personalities on Twitter.

• The Journal of Engineering Geology
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• v.14 no.1
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• pp.29-46
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• 2004

It is important to identify geometries of fracture that act as a conduit of fluid flow for characterization of ground water flow in fractured rock. Fracture geometries control hydraulic conductivity and stream lines in a rock mass. However, we have difficulties to acquire whole geometric data of fractures in a field scale because of discontinuous distribution of outcrops and impossibility of continuous collecting of subsurface data. Therefore, it is needed to develop a method to describe whole feature of a target fracture geometry. This study suggests a new approach to develop a method to characterize on the whole feature of a target fracture geometry based on the Fourier transform. After sampling of specimens along a target fracture from borehole cores, effective frequencies among roughness components were selected by the Fourier transform on each specimen. Then, the selected effective frequencies were averaged on each frequency. Because the averaged spectrum includes all the frequency profiles of each specimen, it shows the representative components of the fracture roughness of the target fracture. The inverse Fourier transform is conducted to reconstruct an averaged whole roughness feature after low pass filtering. The reconstructed roughness feature also shows the representative roughness of the target subsurface fracture including the geometrical characteristics of each specimen. It also means that overall roughness feature by scaling up of a fracture. In order to identify the characteristics of permeability coefficients along the target fracture, fracture models were constructed based on the reconstructed roughness feature. The computation of permeability coefficient was performed by the homogenization analysis that can calculate accurate permeability coefficients with full consideration of fracture geometry. The results show a range between $10^{-4}{\;}and{\;}10^{-3}{\;}cm/sec$, indicating reasonable values of permeability coefficient along a large fracture. This approach will be effectively applied to the analysis of permeability characteristics along a large fracture as well as identification of the whole feature of a fracture in a field scale.

• 한국호스피스완화의료학회:학술대회논문집
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• 2004.07a
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• pp.100-102
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• 2004

Under the current medical system, a terminal patient and his/her family who are neglected inevitably face various aspects of crises including not only physical, but also psychological, social, economic, spiritual and legal problems. Nurses often look after many terminal patents with these types of complicated problems. Therefore, educating the nurses who will take care of such patents would greatly reduce stress so the patents end could their lives in peace and without losing their dignity. This research is a quasi experimental study of nonequivalent control group. A pretest-posttest design where a basic education program is developed for nurses, who frequently treat terminal patents, to understand the importance of the role of hospice and to apply their understandings to treat terminal lancer patents. A sample of the nurses were taken from those who were working in general wards at two general hospitals in Seoul during October, 2003${\sim}$December 2003. The study was composed of 46 experimental group and 43 control group. A basic hospice education program was developed by taking emphasized and overlapping parts from advanced practice hospice nurses education course, short-term education course, an extensive literature survey and by consulting three professionals as well. With the group of 5 professors with vast experiences in oncolgy, 5 nursing administrator, 3 nursing practitioner, the tentative first version of the program was developed and reviewed. Afterwards, by utilizing person to person interviews with 2 head nurses experienced with terminal patients, 1 nurse in charge of hospice, 1 nurse on the contents of the program, and a person to person rating on the educating medium by a nurse were performed. The final version of a basic education program was developed after the second revision. The hospice basic education program consists of introduction to hospice, hospice and commucation, management of pain for terminal cancer patients, physical management for terminal cancer patients, socio-psycological caring of terminal cancer patients and management of death and separation. Total education time was four hours organized into 50 minutes of instruction and 10 minutes of break. $Powerpoint^{(R)}$ software was used as the education medium. As research tools, "Knowledge on Hospice" was developed by the author after receiving a review from one expert. "Attitude of Hospice Nursing" was revised Kim(2001)'s attitude measuring tool which was based on Wang(1998), Kwon(1989), Park and Sung(1991)'s tool. "Liability on nursing terminal patients" was used as developed by Zarits(1980) and Mongomory(1985) translated by Lee(1985). For collecting data, preliminary investigation prior to 1 week of the hospice basic education program and post-investigations after 1 week and 4 weeks of the education were carried out for the nurses at a general ward who understood and agreed on the purpose of the program. Collected data were analyzed throughout t-test, $x^2-test$, Manova test and Bonferroni correction in $SAS^{(R)}$ program. The summary of the investigation is as follows: Hypothesis 1: "Educated experimental group would possess more knowledge on hospice compared to the un-educated control group" was supported after 1 (F=12.14, p=.00) and 4 (F=5.3, p=.02) weeks of education. Hypothesis 2: "Educated experimental group would take a positive attitude toward hospice nursing compared to the un-educated control group" was supported after 1(F=3.92, p=.05) and 4(F=5.05, p=.02) weeks of education. Hypothesis 3: "Educated experimental poop would feel less liability compared to the un-educated control group in nursing terminal cancer patients' was rejected. In this study, it was found that knowledge on hospice was significantly important. By applying hospice basic education programs to nurses, the education program helped nurses to take a positive attitude toward terminal patients. It was, however, seen that the education program had no effect on alleviating liability in nursing terminal patients. Therefore, it is expected that this educational program would help hospices and nurses at general wards to understand the concept and the role of hospice so that terminal patents, now neglected under current medical system, would be able to end their lives in peace.

• Korean Journal of Heritage: History & Science
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• v.55 no.1
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• pp.305-321
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• 2022

The stone chamber tomb in Eungpyeong-ri, Buyeo, is a joint tomb that contains the bodies of two individuals. This paper investigates the relationship between the buried persons and the characteristics of the stone chamber tomb. Based on the geographical location, relics, and the excavated human bones, it was determined that the tomb was built during the Sabi Period of the Baekje Dynasty and that the buried individuals were most probably residents of high stature or government officials. To study the excavated bones, the remains were carefully collected and conservation was carried out. Before collecting samples from the human bones for the analytical research, the results of near-infrared analysis were used to collect the samples for the isotope analysis and DNA analysis. The most important issue when handling the excavation site was the reinforcing agent and the concentration of the agent used. In situations like this, Paraloid B-72 is the most suitable agent. When the shape of human bones was difficult to distinguish from the soil, conservation was performed using X-ray and CT imaging data. The same chemical used for the reinforcement of the site was used to complete a minimum level of conservation to the surface areas where the conservation treatment of removing foreign substances, the reinforcement areas, and bonded areas were carried out. The collagen yield from the sample obtained at selected position was 3.8% to 6.1%. The results of analyzing the stable isotopes of carbon and nitrogen found in the extracted collagen showed that the stable isotope ratios came out to δ¹³C -18.3‰±0.1‰, -19.0‰±0.1‰ for EBW and δ¹⁵N 10.7‰±0.5‰, 10.6‰±0.1‰ for EBE. It is believed the two individuals consumed small amounts of minor cereals, mainly from C₃ plants, and protein was obtained from eating terrestrial animals. What's more, the deviations in data obtained from the two individuals were so small that it could be inferred that the individuals ate similar foods. Considering the preservation state of the sample, amplifying DNA for the DNA analysis would have been very difficult since the amount of surviving DNA was so deficient. For DNA analysis, it is anticipated that the results could be derived by applying improved extraction methods that will be developed in the future. In this research, any association between scientific analysis(DNA and stable isotope ratio) and near-infrared spectroscopy was difficult to establish. Further research is needed on the utilization of near-infrared analysis for gathering samples from human bones.

• Journal of The Korean Society of Grassland and Forage Science
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• v.41 no.4
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• pp.287-294
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• 2021

The objective of this study was conducted to calculate the damage of whole crop maize in accordance with abnormal climate using the forage yield prediction model through machine learning. The forage yield prediction model was developed through 8 machine learning by processing after collecting whole crop maize and climate data, and the experimental area was selected as Gyeonggi-do. The forage yield prediction model was developed using the DeepCrossing (R²=0.5442, RMSE=0.1769) technique of the highest accuracy among machine learning techniques. The damage was calculated as the difference between the predicted dry matter yield of normal and abnormal climate. In normal climate, the predicted dry matter yield varies depending on the region, it was found in the range of 15,003~17,517 kg/ha. In abnormal temperature, precipitation, and wind speed, the predicted dry matter yield differed according to region and abnormal climate level, and ranged from 14,947 to 17,571, 14,986 to 17,525, and 14,920 to 17,557 kg/ha, respectively. In abnormal temperature, precipitation, and wind speed, the damage was in the range of -68 to 89 kg/ha, -17 to 17 kg/ha, and -112 to 121 kg/ha, respectively, which could not be judged as damage. In order to accurately calculate the damage of whole crop maize need to increase the number of abnormal climate data used in the forage yield prediction model.

• Journal of Environmental Impact Assessment
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• v.32 no.6
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• pp.450-462
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• 2023

This study suggested methodology of Citizen Science as a tool of ecosystem conservation and management to achieve Wetland Protected Area (WPA) Conservation Plan and examined whose applicability in 3 WPAs (Jangrok of Gwangju metropolitan city, Madongho of Goseong in South Gyeongsang Province, and Incheongang estuary of Gochang in North Jeolla Province). It consists of a) figuring out main interests and stakeholder or beneficiaries of WPA and their information demand based on conservation, utilization, and management target in the WPA Conservation Plan, b) conducting research activities to gain outcome to address stakeholder's demand, and c) returning the research outcome to citizen scientists and making diffusion to the society. Based on the suggested method and process, citizen scientists conducted ecosystem monitoring (plants including Invasive Alien Plants, terrestrial insects, traces of mammals, discovering unknown wetland). As a result, citizen scientists contributed to collecting species information of 16 plans, 43 species of terrestrial insects, 5 mammals including Lutra lutra (Endangered Species I) and Prionailurus bengalensis (Endangered Species II). The authors constructed and provided distribution map of Invasive Alien Plants, which included information of location and density which citizen scientists registered, for Environment Agencies and local governments who manage 3 WPAs to aid data-based ecosystem policy, In further studies, not only accumulating research data and outcomes acquired from citizen science to suffice the policy demands but also deliberate reviewing policy applicability and social·economic ripple effect should be processed for the suggested Citizen Science in WPA to be settled down as a tool of ecosystem conservation and management.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.123-138
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• 2017

Since the stock market is driven by the expectation of traders, studies have been conducted to predict stock price movements through analysis of various sources of text data. In order to predict stock price movements, research has been conducted not only on the relationship between text data and fluctuations in stock prices, but also on the trading stocks based on news articles and social media responses. Studies that predict the movements of stock prices have also applied classification algorithms with constructing term-document matrix in the same way as other text mining approaches. Because the document contains a lot of words, it is better to select words that contribute more for building a term-document matrix. Based on the frequency of words, words that show too little frequency or importance are removed. It also selects words according to their contribution by measuring the degree to which a word contributes to correctly classifying a document. The basic idea of constructing a term-document matrix was to collect all the documents to be analyzed and to select and use the words that have an influence on the classification. In this study, we analyze the documents for each individual item and select the words that are irrelevant for all categories as neutral words. We extract the words around the selected neutral word and use it to generate the term-document matrix. The neutral word itself starts with the idea that the stock movement is less related to the existence of the neutral words, and that the surrounding words of the neutral word are more likely to affect the stock price movements. And apply it to the algorithm that classifies the stock price fluctuations with the generated term-document matrix. In this study, we firstly removed stop words and selected neutral words for each stock. And we used a method to exclude words that are included in news articles for other stocks among the selected words. Through the online news portal, we collected four months of news articles on the top 10 market cap stocks. We split the news articles into 3 month news data as training data and apply the remaining one month news articles to the model to predict the stock price movements of the next day. We used SVM, Boosting and Random Forest for building models and predicting the movements of stock prices. The stock market opened for four months (2016/02/01 ~ 2016/05/31) for a total of 80 days, using the initial 60 days as a training set and the remaining 20 days as a test set. The proposed word - based algorithm in this study showed better classification performance than the word selection method based on sparsity. This study predicted stock price volatility by collecting and analyzing news articles of the top 10 stocks in market cap. We used the term - document matrix based classification model to estimate the stock price fluctuations and compared the performance of the existing sparse - based word extraction method and the suggested method of removing words from the term - document matrix. The suggested method differs from the word extraction method in that it uses not only the news articles for the corresponding stock but also other news items to determine the words to extract. In other words, it removed not only the words that appeared in all the increase and decrease but also the words that appeared common in the news for other stocks. When the prediction accuracy was compared, the suggested method showed higher accuracy. The limitation of this study is that the stock price prediction was set up to classify the rise and fall, and the experiment was conducted only for the top ten stocks. The 10 stocks used in the experiment do not represent the entire stock market. In addition, it is difficult to show the investment performance because stock price fluctuation and profit rate may be different. Therefore, it is necessary to study the research using more stocks and the yield prediction through trading simulation.