• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.177-190
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• 2021

Due to the development of the fourth industrial revolution technology, efforts are being made to improve areas that humans cannot handle by utilizing artificial intelligence techniques such as machine learning. Although on-demand production companies also want to reduce corporate risks such as delays in delivery by predicting total production time for orders, they are having difficulty predicting this because the total production time is all different for each order. The Theory of Constraints (TOC) theory was developed to find the least efficient areas to increase order throughput and reduce order total cost, but failed to provide a forecast of total production time. Order production varies from order to order due to various customer needs, so the total production time of individual orders can be measured postmortem, but it is difficult to predict in advance. The total measured production time of existing orders is also different, which has limitations that cannot be used as standard time. As a result, experienced managers rely on persimmons rather than on the use of the system, while inexperienced managers use simple management indicators (e.g., 60 days total production time for raw materials, 90 days total production time for steel plates, etc.). Too fast work instructions based on imperfections or indicators cause congestion, which leads to productivity degradation, and too late leads to increased production costs or failure to meet delivery dates due to emergency processing. Failure to meet the deadline will result in compensation for delayed compensation or adversely affect business and collection sectors. In this study, to address these problems, an entity that operates an order production system seeks to find a machine learning model that estimates the total production time of new orders. It uses orders, production, and process performance for materials used for machine learning. We compared and analyzed OLS, GLM Gamma, Extra Trees, and Random Forest algorithms as the best algorithms for estimating total production time and present the results.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.127-146
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• 2022

Recently, as word embedding has shown excellent performance in various tasks of deep learning-based natural language processing, researches on the advancement and application of word, sentence, and document embedding are being actively conducted. Among them, cross-language transfer, which enables semantic exchange between different languages, is growing simultaneously with the development of embedding models. Academia's interests in vector alignment are growing with the expectation that it can be applied to various embedding-based analysis. In particular, vector alignment is expected to be applied to mapping between specialized domains and generalized domains. In other words, it is expected that it will be possible to map the vocabulary of specialized fields such as R&D, medicine, and law into the space of the pre-trained language model learned with huge volume of general-purpose documents, or provide a clue for mapping vocabulary between mutually different specialized fields. However, since linear-based vector alignment which has been mainly studied in academia basically assumes statistical linearity, it tends to simplify the vector space. This essentially assumes that different types of vector spaces are geometrically similar, which yields a limitation that it causes inevitable distortion in the alignment process. To overcome this limitation, we propose a deep learning-based vector alignment methodology that effectively learns the nonlinearity of data. The proposed methodology consists of sequential learning of a skip-connected autoencoder and a regression model to align the specialized word embedding expressed in each space to the general embedding space. Finally, through the inference of the two trained models, the specialized vocabulary can be aligned in the general space. To verify the performance of the proposed methodology, an experiment was performed on a total of 77,578 documents in the field of 'health care' among national R&D tasks performed from 2011 to 2020. As a result, it was confirmed that the proposed methodology showed superior performance in terms of cosine similarity compared to the existing linear vector alignment.

• Journal of Nutrition and Health
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• v.56 no.4
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• pp.419-438
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• 2023

Purpose: This study examines the effectiveness of personalized goal setting and smartphone-based nutrition counseling among adults in their 20s and 30s. Methods: Nutrition counseling was conducted for a total of 30 adults through a 1:1 chat room of a mobile instant messenger, once a week for 8 weeks. The first week of counseling included a preliminary online questionnaire survey and a dietary intake survey. Based on the results of the preliminary survey, 2 dietary goals were set in the second week and the participants were asked to record their achievements on a daily checklist. From the third week onwards, counselors sent feedback messages based on the checklist and provided information on dietary guidelines in a card news format every week. Post-counseling questionnaires and dietary intake surveys were conducted in the seventh week. Changes in dietary habits during the counseling were reviewed in the eighth week, followed by a questionnaire survey on the evaluation of the counseling process. Results: The nutrition quotient (NQ) scores and self-efficacy scores were significantly higher after nutrition counseling. The NQ scores of consumption frequencies of fruits, milk and dairy products, nuts, fast food, Ramyeon, sweet and greasy baked products, sugarsweetened beverages, the number of vegetable dishes at meals, and breakfast frequency were significantly higher after nutrition counseling. The intake of protein, vitamin A, thiamin, riboflavin, folate, calcium, and iron, and the index of nutritional quality of vitamin A, riboflavin, folate, calcium, and iron were higher after nutrition education. The participants were satisfied with the nutrition counseling program and the provided nutrition information. Conclusion: Personalized goal setting and smartphone-based nutrition counseling were found to be effective in improving the quality of diet and self-efficacy in young adults. Similar results were obtained in both the underweight/normal weight and the overweight/obese groups.

• Journal of the Korean Association of Geographic Information Studies
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• v.26 no.2
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• pp.68-81
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• 2023

This study aims to establish a scenario based on the spacing and arrangement of the roadside trees to reduce heat waves and fine dust in cities that occurred during the urbanization process and to quantitatively analyze the degree of reduction. The ENVI-met 5.0.2v model, a micro-climate simulation program, was used to analyze the degree of improvement in the thermal environment and fine dust according to the roadside tree scenario. As a result of temperature analysis according to street tree spacing, the narrower the distance between roadside trees, the lower the temperature during the day as the number of planted trees increased, and a similar pattern was shown regardless of the distance between roadside trees in the morning and evening. In the case of fine dust emitted from the road, the concentration of fine dust increased slightly due to the increase in roadside trees, but the concentration of sidewalks where people walk increased slightly or there was no difference because of blocking fine dust on trees. The temperature according to the arrangement of street trees tended to decrease as the number of planted trees increased as the arrangement increased. However, not only the amount of trees but also the crown projected area was judged to have a significant impact on the temperature reduction because the temperature reduction was greater in the scenario of planting the same amount of trees and widening the interval of arrangement. In terms of the arrangement, the fine dust concentration showed a difference from the results according to the interval, suggesting that the fine dust concentration may change depending on the relationship between the main wind direction and the tree planting direction. By quantitatively analyzing the degree of thermal environment and fine dust improvement caused by roadside trees, this study is expected to promote policies and projects to improve the roadside environment efficiently, such as a basic plan for roadside trees and a project for wind corridor forests.

• Journal of Popular Narrative
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• v.25 no.3
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• pp.303-345
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• 2019

This article analyzes the multi-layered communication in the Webtoon Princess Pari, released on the Daum portal site, created (written and illustrated) by Kim Naim, through analyzing the narrative structure and comments with the qualitative / quantitative methodology. The webtoon Princess Pari is structured in an omnibus style in which unit narratives are intermittently articulated, multi-lined, and interconnected. As integrated narratives which link with unitary narratives, Pari's growth story as a shaman and a romance narrative are structured. The classical original story of the shaman was used as a prehistory corresponding to the prequel of the webtoon through a preview, and the writer restructured the narrative to overcome the contradictions of the gender asymmetry and the patriarchal ideology of the original text. The viewer then creates a conversational space by giving critical and reflective comments. According to a statistical analysis conducted through sampling, the types of comments can be classified as follows: Appreciation and criticism of the contents ≫ Emotional response ≫ Intuitive overall review ≫ Knowledge and reflection ≫ Comments on comments. In the process of creation and acceptance of the Webtoon, a multi-layered dialogue between classical and modern, content and audience, acceptance and creation has been at play. In the creation dimension, the writer used a device to fill the gap of mythical symbols of the contents. At the level of the audience, they formed a culture of sharing information, knowledge, and reflection about tradition/folk/culture through comments. This corresponds to classical and modern dialogue through the webtoon. The viewers form a sympathetic bond, attempt hermeneutical coordination, supplement the information, and search for a balanced angle through controversial conversation. In addition, by commenting on attitudes, views, and perspective, the commentators showed a behavioral pattern corresponding to meta-criticism in literature. The viewers' comments acted as feedback on the creation of the webtoons, so that the creation and acceptance itself influenced the production of the content of the webtoon. The webtoon Princess Pari, which was based on Korean classical narrative, has been reorganized onto 'moving and dynamic' content, which leads to sense, thinking, criticism and reflection through the formation of various dialogues.

• Journal of agriculture & life science
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• v.50 no.3
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• pp.1-11
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• 2016

With increasing interest, there have been studies on LiDAR(Light Detection And Ranging)-based DEM(Digital Elevation Model) to acquire three dimensional topographic information. For producing LiDAR DEM with better accuracy, Filtering process is crucial, where only surface reflected LiDAR points are left to construct DEM while non-surface reflected LiDAR points need to be removed from the raw LiDAR data. In particular, the changes of input values for filtering algorithm-constructing parameters are supposed to produce different products. Therefore, this study is aimed to contribute to better understanding the effects of the changes of the levels of GroundFilter Algrothm's Mean parameter(GFmn) embedded in FUSION software on the accuracy of the LiDAR DEM products, using LiDAR data collected for Hwacheon, Yangju, Gyeongsan and Jangheung watershed experimental area. The effect of GFmn level changes on the products' accuracy is estimated by measuring and comparing the residuals between the elevations at the same locations of a field and different GFmn level-produced LiDAR DEM sample points. In order to test whether there are any differences among the five GFmn levels; 1, 3, 5, 7 and 9, One-way ANOVA is conducted. In result of One-way ANOVA test, it is found that the change in GFmn level significantly affects the accuracy (F-value: 4.915, p<0.01). After finding significance of the GFmn level effect, Tukey HSD test is also conducted as a Post hoc test for grouping levels by the significant differences. In result, GFmn levels are divided into two subsets ('7, 5, 9, 3' vs. '1'). From the observation of the residuals of each individual level, it is possible to say that LiDAR DEM is generated most accurately when GFmn is given as 7. Through this study, the most desirable parameter value can be suggested to produce filtered LiDAR DEM data which can provide the most accurate elevation information.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.17 no.2
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• pp.23-42
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• 2006

This is a study of the digital archives of Culturecontent.com where 'Cultural Archetype Contents' are currently in service. One of the major purposes of our study is to point out problems in the current system and eventually propose improvements to the digital archives. The government launched a four-year project for developing the cultural archetype content sources and establishing its related business with the hope of enhancing the nation's competitiveness. More specifically, the project focuses on the production of source materials of cultural archetype contents in the subjects of Korea's history. tradition, everyday life. arts and general geographical books. In addition, through this project, the government also intends to establish a proper distribution system of digitalized culture contents and to control copyright issues. This paper analyzes the digital archives system that stores the culture content data that have been produced from 2002 to 2005 and evaluates the current system's weaknesses and strengths. The summary of our findings is as follows. First. the digital archives system does not contain a semantic search engine and therefore its full function is 1agged. Second, similar data is not classified into the same categories but into the different ones, thereby confusing and inconveniencing users. Users who want to find source materials could be disappointed by the current distributive system. Our paper suggests a better system of digital archives with text mining technology which consists of five significant intelligent process-keyword searches, summarization, clustering, classification and topic tracking. Our paper endeavors to develop the best technical environment for preserving and using culture contents data. With the new digitalized upgraded settings, users of culture contents data will discover a world of new knowledge. The technology we introduce in this paper will lead to the highest achievable digital intelligence through a new framework.

• Asia Marketing Journal
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• v.13 no.4
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• pp.29-54
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• 2012

Recently, as film has been admitted as the artistic merit and higher value-added business, the past studies on film have been lively carried on various fields. Especially, the film business is thought to be value-added business and has explored the causes of influencing spectators. However, there are no researches enough to explain what induces the choice and diffusion of the film. The film is not only hedonic products but also typical example of experiential products. So how to process film formation plays important roles in explaining the procedures of forming preference on the film and the movies spread more widely. But the great part of study of films has been concentrated on exploring hedonic factors of influencing spectator's choice. Until now there is not enough study for the relationship between experiential information processing and film preference. To explain film's preference, our study focuses on preference fluency and processing fluency that can provide an insight for our question about the relationship. In this article, to explain the procedures of processing experiential information and forming preference on the film, our study focuses on finding the relationship between film's processing fluency and film's preference fluency and explores the factors that affect film's processing fluency. To achieve the goal of this study, we distinguish factors of film's conceptual fluency from factors of film's perceptual fluency and explore the paths from the factors to film's preference fluency. The factors which have effects on perceptual fluency are hypothesized to be distinction of image expression, distinction of sound expression, correspondence between actors' image and their role. The factors which have effect on conceptual fluency are supposed to be well-organized story, suitability of lines expression. The experiments in which students were sampled at 'C' university were conducted in 2010 (december). Data collection was proceeded through questionnaires. We test the hypothesized model by using structural equation modeling(Amos 17.0). The fit indices for the model are as follows : x²=416.266(df=213, p=0.00), GFI=0.855, AGFI=0.812, RMSEA =0.069, IFI=O.925, CFI=0.920, TLI=0.905. According to the guidelines, there is evidence that our measurement model fits data. The results of empirical study are as follows. The path from film's perceptual fluency to film's preference fluency is supported(estimate: 0.223, C.R: 2.641). The path from film's conceptual fluency to film's preference fluency is supported(estimate: 0.397, C.R: 4.863). The path from distinction of image expression to film's perceptual fluency is not supported(estimate: 0.113, C.R: 1.665). The path from distinction of sound expression to film's perceptual fluency is supported (estimate: 0.190, C.R: 2.042). The path from correspondence between actors' image and their role to film's perceptual fluency is supported(estimate: 0.686, C.R: 5.566). The path from well-organized story to film's conceptual fluency is supported(estimate: 0.396, C.R: 4.023). The path from suitability of lines expression to film's conceptual fluency is supported(estimate: 0.536, C.R: 5.441). Concludingly, our study explored the influencing factors of film's processing fluency inducing film's Preference fluency. First, film's perceptual fluency and film's conceptual fluency have positive effects on film's preference fluency. Second, distinction of image expression is not significant on film's perceptual fluency, but distinction of sound expression and image's correspondence of actors' image and their role have positive effects on film's perceptual fluency. Lastly, well-organized story and suitability of lines expression have positive effects on film's conceptual fluency.

• Journal of the Korean earth science society
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• v.44 no.6
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• pp.655-674
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• 2023

This study examined whether the "self-guided interpretation" media in the Yeoncheon area of the Hantangang River UNESCO Geopark are intelligible for visitors. Accordingly, two on-site investigations were conducted in the Hantangang River Global Geopark in September and November 2022. The Yeoncheon area, known for its diverse geological features and the era of geological attraction formation, was selected for analysis. We analyzed the readability levels, graphic characteristics, and alignment with science curriculum of the interpretive media specific to geological sites among a total of 36 self-guided interpretive media in the Yeoncheon area. Results indicated that information boards, primarily offering guidance on geological attractions, were the most prevalent type of interpretive media in the Yeoncheon area. The quantity of text in explanatory media surpassed that of a 12^th-grade science textbook. The average vocabulary grade was similar to that of 11^th- and 12^th-grade science textbooks, with somewhat reduced readability due to a high occurrence of complex sentences. Predominant graphic types included illustrative photographs, aiding comprehension of the geological formation process through multi-structure graphics. Regarding scientific terms used in the interpretive media, 86.3% of the terms were within the "Solid Earth" section of the 2015 revised curriculum, with the majority being at the 4^th-grade level. The 11^th-grade optional curriculum terms comprised the second largest portion, and 13.7% of all science terms were from outside the curriculum. Notably, variations in the scientific terminology's complexity was based on geological attractions. Specifically, the terminology level on the homepage tended to be generally higher than that on information boards. Through these findings, specific factors impeding visitor comprehension of geological attractions in the Yeoncheon area, based on the interpretation medium, were identified. We suggest further research to effect improvements in self-guided interpretation media, fostering geological resource education for general visitors and anticipating advancements in geology education.

• Journal of Venture Innovation
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• v.3 no.2
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• pp.41-76
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• 2020

This study confirmed factors affecting smart factory technology acceptance through empirical analysis. It is a study on what factors have an important influence on the introduction of the smart factory, which is the core field of the 4th industry. I believe that there is academic and practical significance in the context of insufficient research on technology acceptance in the field of smart factories. This research was conducted based on the Unified Theory of Acceptance and Use of Technology (UTAUT), whose explanatory power has been proven in the study of the acceptance factors of information technology. In addition to the four independent variables of the UTAUT : Performance Expectancy, Effort Expectancy, Social Influence, and Facilitating Conditions, Government Assistance Expectancy, which is expected to be an important factor due to the characteristics of the smart factory, was added to the independent variable. And, in order to confirm the technical factors of smart factory technology acceptance, the Task Technology Fit(TTF) was added to empirically analyze the effect on Behavioral Intention. Trust is added as a parameter because the degree of trust in new technologies is expected to have a very important effect on the acceptance of technologies. Finally, empirical verification was conducted by adding Innovation Resistance to a research variable that plays a role as a moderator, based on previous studies that innovation by new information technology can inevitably cause refusal to users. For empirical analysis, an online questionnaire of random sampling method was conducted for incumbents of domestic small and medium-sized enterprises, and 309 copies of effective responses were used for empirical analysis. Amos 23.0 and Process macro 3.4 were used for statistical analysis. For accurate statistical analysis, the validity of Research Model and Measurement Variable were secured through confirmatory factor analysis. Accurate empirical analysis was conducted through appropriate statistical procedures and correct interpretation for causality verification, mediating effect verification, and moderating effect verification. Performance Expectancy, Social Influence, Government Assistance Expectancy, and Task Technology Fit had a positive (+) effect on smart factory technology acceptance. The magnitude of influence was found in the order of Government Assistance Expectancy(β=.487) > Task Technology Fit(β=.218) > Performance Expectancy(β=.205) > Social Influence(β=.204). Both the Task Characteristics and the Technology Characteristics were confirmed to have a positive (+) effect on Task Technology Fit. It was found that Task Characteristics(β=.559) had a greater effect on Task Technology Fit than Technology Characteristics(β=.328). In the mediating effect verification on Trust, a statistically significant mediating role of Trust was not identified between each of the six independent variables and the intention to introduce a smart factory. Through the verification of the moderating effect of Innovation Resistance, it was found that Innovation Resistance plays a positive (+) moderating role between Government Assistance Expectancy, and technology acceptance intention. In other words, the greater the Innovation Resistance, the greater the influence of the Government Assistance Expectancy on the intention to adopt the smart factory than the case where there is less Innovation Resistance. Based on this, academic and practical implications were presented.