• Archives of design research
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• v.19 no.2 s.64
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• pp.121-128
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• 2006

The elements to enhance preference in symbol design are mainly related to consumers' response and aesthetic elements. Because certain aesthetic elements in design affect consumers' response and it is actually presented through (the different level of) preference. This study through surveying case studies examines whether a certain aesthetic element in symbol design gives rise to much preference. According to the result of study, high preference in symbolic design depends on high level of Rhythm, Balance, Harmony, Elaboration, Round, Gestalt, Organic, and Artificial/Natural among aesthetic elements. In comparison, it is founded that Simplicity/complexity, Objective/Abstract, depth, and symmetry should be designed at the moderate level, and proportion, repetition of elements be at the low level. Additionally(or Besides) this study makes out that symbol design cases with high preference have shapes from natural material or patterns of traditional culture, while cases with low preference have shapes from geometric figures. On the basis of these results, a guideline of symbol design could De offered(or suggested) to fit preference of consumers. But, this study is mostly concerned with only affect among emotional reactions of consumer in a scope of study, and is considered only in the aspect of form excluding color and texture.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2009.06a
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• pp.205-209
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• 2009

Recently, the increase of the size of GNP and the expansion of the foreign tour opportunities by the common 5 days work system in a week, reaction of the burden for visiting foreign countries, and expansion of airlines caused the rapid increase of overseas tour but slow increase in the number of foreign tourists, due to the price rise which might impact on the competitive power, and lack of tour infrastructure and attractiveness. As the wide area along the east coast of GyeongBuk Province has great amount of cultural, ocean and natural resources, it helps to get focused the tour industries and maximize the synergy effect through the mutual development coupling the resources and regions. On the basis of the potentials for the growth of east coast area to the international level and the development of local resources, a ocean tour and resort complex for four seasons, which has s strong connection to the local areas resulting the wide tour bond, could help to improve the local economy and balance the development of local province, and furthermore, jump to the level of the center in the East Coast area in the international society. Through the investigation and analysis of the ocean space development status and usage at the advanced foreign countries, the new meaning of the ocean space at the tour and resort complex would be proposed to the relevant local government in fit.

• The Journal of Natural Sciences
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• v.12 no.1
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• pp.85-101
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• 2002

Landscape civilization in Korea originated in Cochosun(Ancient Chosun) era, this again succeeding to the period of the Three States - Koguryo, Baekje and Silla. The distribution of this culture showed great progress with the association of two particular religions - Buddhism and Confucianism.. Landscape development in Korea has greatly changed during specific times of both cultural and political upheaval in various societies. Religion has had a great deal of influence on landscape development. Traditionally Korean people have had a tendency to favor more natural landscape than man-made structures in landscape : This trend was a quite different concept from that of other oriental countries, not to mention of western countries. In particular, Buddhism influenced natural landscape, far from artificial craftsmanship in landscape. Oriental garden is a typical 'tabloid edition' of natural landscape which consists lakes, islands, ponds, stone monuments, and fruit trees, quite often raising animal in parks and courtyard style house. This style of garden influenced in Chosun Dynasty landscape. Landscaping was usually for royal gardens, cemetery parks or high level of officer's residence. However, landscaping in Chosun Dynasty which had established Confucianism as a state religion gave us a specific designation. It was neither ethnic imitation of the garden style of both China and Japan : People were used to enjoy nature-friendly landscape or sink into the ecstasy of natural scenery itself. The trend that landscape or establishing garden had been aimed at royal family- or bureaucrat-centered formatives was to become an obstacle to the development of landscape techniques in Korea. An example represented in a beautiful garden with fabulous decoration which established in places. This was completely not fit for the nation's feeling.

• Journal of Internet Computing and Services
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• v.22 no.2
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• pp.59-68
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• 2021

As artificial intelligence(AI) technologies, which have made rapid growth recently, began to be applied to the marine environment such as ships, there have been active researches on the application of CNN-based models specialized for digital videos. In E-Navigation service, which is combined with various technologies to detect floating objects of clash risk to reduce human errors and prevent fires inside ships, real-time processing is of huge importance. More functions added, however, mean a need for high-performance processes, which raises prices and poses a cost burden on shipowners. This study thus set out to propose a method capable of processing information at a high rate while maintaining the accuracy by applying Quantization techniques of a deep learning model. First, videos were pre-processed fit for the detection of floating matters in the sea to ensure the efficient transmission of video data to the deep learning entry. Secondly, the quantization technique, one of lightweight techniques for a deep learning model, was applied to reduce the usage rate of memory and increase the processing speed. Finally, the proposed deep learning model to which video pre-processing and quantization were applied was applied to various embedded boards to measure its accuracy and processing speed and test its performance. The proposed method was able to reduce the usage of memory capacity four times and improve the processing speed about four to five times while maintaining the old accuracy of recognition.

• The Korean Journal of Applied Statistics
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• v.34 no.3
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• pp.427-438
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• 2021

Two-stage sampling allows us to estimate population characteristics by both unit and cluster level together. Given a complex auxiliary information, integrated calibration weighting would better reflect the level-wise characteristics as well as multivariate characteristics between levels. This paper explored the integrated calibration weighting methods by Estevao and Särndal (2006) and Kim (2019) through a simulation study, where the efficiency of those weighting methods was compared using an artificial population data. Two weighting methods among others are shown efficient: single step calibration at the unit level with stacked individualized auxiliary information and iterative integrated calibration at each level. Under both methods, cluster calibrated weights are defined as the average of the calibrated weights of the unit(s) within cluster. Both were very good in terms of the goodness-of-fit of estimating the population totals of mutual auxiliary information between clusters and units, and showed small relative bias and relative mean square root errors for estimating the population totals of survey variables that are not included in calibration adjustments.

• Journal of Korean Library and Information Science Society
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• v.53 no.1
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• pp.231-263
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• 2022

The understanding and capability to utilize artificial intelligence (AI) incorporated technology has become a required basic skillset for the people living in today's information age, and various members of the university have also increasingly become aware of the need for AI education. Amidst such shifting societal demands, both domestic and international university libraries have recognized the users' need for educational content centered on AI, but a user-centered service that aims to provide personalized recommendations of digital AI educational content is yet to become available. It is critical while the demand for AI education amongst university students is progressively growing that university libraries acquire a clear understanding of user intention towards an AI educational content recommender system and the potential factors contributing to its success. This study intended to ascertain the factors affecting acceptance of such system, using the Extended Technology Acceptance Model with added variables - innovativeness, self-efficacy, social influence, system quality and task-technology fit - in addition to perceived usefulness, perceived ease of use, and intention to use. Quantitative research was conducted via online research surveys for university students, and quantitative research was conducted through written interviews of university librarians. Results show that all groups, regardless of gender, year, or major, have the intention to use the AI-related Educational Content Recommendation System, with the task suitability factor being the most dominant variant to affect use intention. University librarians have also expressed agreement about the necessity of the recommendation system, and presented budget and content quality issues as realistic restrictions of the aforementioned system.

• The Journal of Korean Academy of Prosthodontics
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• v.62 no.1
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• pp.6-19
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• 2024

With the advancement of Computer-Aided Design/Computer-Aided Manufacturing (CAD-CAM) technology, fabrication of dentures using this technology has gained popularity. As one of CAD-CAM technologies, digital complete denture system has been introduced, which fabricates complete dentures using subtractive manufacturing of monolithic block containing both the color of a denture base and an artificial tooth. In this case, two pairs of upper and lower dentures were fabricated for two patients. Two pairs of complete dentures were fabricated for a 74-year-old male and a 73-year-old female respectively by conventional denture fabrication method and digital method of milling. To obtain a digital complete denture, monolithic block (Ivotion, Ivoclar Vivadent, Schaan, Liechtenstein) was chosen for the materials to fabricate the digital complete dentures. An individual tray was designed using CAD software and manufactured by 3D printing technique. The final impression and interocclusal relationship were recorded using the fabricated individual tray. The final impression was scanned, and the complete denture design and try-in denture were 3D printed using CAD-CAM software. Subsequently, the monolithic block was milled, and the final dentures were fabricated and tried on patients. Previously mentioned two patient cases compared and analyzed stability, fit, speaking, mastication, aesthetics, and patient satisfaction of two pairs of dentures: one fabricated using CAD-CAM system and the other using traditional methods. This was performed to evaluate and report the findings from both denture-making approaches.

• The Journal of Bigdata
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• v.4 no.2
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• pp.1-12
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• 2019

As Artificial Intelligence (AI) technology develops, it is applied to various fields such as image, voice, and text. AI has shown fine results in certain areas. Researchers have tried to predict the stock market by utilizing artificial intelligence as well. Predicting the stock market is known as one of the difficult problems since the stock market is affected by various factors such as economy and politics. In the field of AI, there are attempts to predict the ups and downs of stock price by studying stock price patterns using various machine learning techniques. This study suggest a way of predicting stock price patterns based on the Convolutional Neural Network(CNN) among machine learning techniques. CNN uses neural networks to classify images by extracting features from images through convolutional layers. Therefore, this study tries to classify candlestick images made by stock data in order to predict patterns. This study has two objectives. The first one referred as Case 1 is to predict the patterns with the images made by the same-day stock price data. The second one referred as Case 2 is to predict the next day stock price patterns with the images produced by the daily stock price data. In Case 1, data augmentation methods - random modification and Gaussian noise - are applied to generate more training data, and the generated images are put into the model to fit. Given that deep learning requires a large amount of data, this study suggests a method of data augmentation for candlestick images. Also, this study compares the accuracies of the images with Gaussian noise and different classification problems. All data in this study is collected through OpenAPI provided by DaiShin Securities. Case 1 has five different labels depending on patterns. The patterns are up with up closing, up with down closing, down with up closing, down with down closing, and staying. The images in Case 1 are created by removing the last candle(-1candle), the last two candles(-2candles), and the last three candles(-3candles) from 60 minutes, 30 minutes, 10 minutes, and 5 minutes candle charts. 60 minutes candle chart means one candle in the image has 60 minutes of information containing an open price, high price, low price, close price. Case 2 has two labels that are up and down. This study for Case 2 has generated for 60 minutes, 30 minutes, 10 minutes, and 5minutes candle charts without removing any candle. Considering the stock data, moving the candles in the images is suggested, instead of existing data augmentation techniques. How much the candles are moved is defined as the modified value. The average difference of closing prices between candles was 0.0029. Therefore, in this study, 0.003, 0.002, 0.001, 0.00025 are used for the modified value. The number of images was doubled after data augmentation. When it comes to Gaussian Noise, the mean value was 0, and the value of variance was 0.01. For both Case 1 and Case 2, the model is based on VGG-Net16 that has 16 layers. As a result, 10 minutes -1candle showed the best accuracy among 60 minutes, 30 minutes, 10 minutes, 5minutes candle charts. Thus, 10 minutes images were utilized for the rest of the experiment in Case 1. The three candles removed from the images were selected for data augmentation and application of Gaussian noise. 10 minutes -3candle resulted in 79.72% accuracy. The accuracy of the images with 0.00025 modified value and 100% changed candles was 79.92%. Applying Gaussian noise helped the accuracy to be 80.98%. According to the outcomes of Case 2, 60minutes candle charts could predict patterns of tomorrow by 82.60%. To sum up, this study is expected to contribute to further studies on the prediction of stock price patterns using images. This research provides a possible method for data augmentation of stock data.

• Korean Journal of Environment and Ecology
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• v.23 no.1
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• pp.30-40
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• 2009

Employing the Numata-type life form, the paper analyzed changes of plants for 4 years at the Human-made Wetlands along Boknaecheon of Juam Lake since its creation. The number of the species planted at the Human-made Wetlands along Boknaecheon of Juam Lake, which was completed in December 2002, were 15 in total including, 10 families, 13 genera, 12 species and 3 varieties. As for the three-featured life forms of the planted species, there were 6 perennial hydatophytes, recording the biggest number of species in dormancy form; species each of $R_5$, $R_3$, $R_{2-3}$ respectively in radicoid from; 20 species of geomantic dissenminule form ($D_1$) in disseminule form and erecred type(e) existed the most in growth form. With regard to the 3 features of life form identified during the final year of the monitoring that lasted 5 years after the completion of the Wetlands, the number of species and individuals was found to have increased but there was no significant change of tendency as against the composition ration(%) of life form. There were 43 species of therophytes (Th) that covered 24.29% in dormancy form, while $R_5$ was prevalent in radicoid form and $D_4$, $D_1$, and $D_{1,4}$ comprosed 77.39% of the whole disseminule form. Growth form was surveyed in the order of erected type (e), bunch type (t), temporal rosette type (pr), branch type (b) and straight rosette type (ps) and these species comprised 64.97% of the whole flora. Consequently, in case of the artificial wetlands along the Boknaecheon of Juam Lake, it turned out that the vegetation type in which pioneer species of succession, or gradually stabilized perennial vegetation favoring Wetlands because the higher dormancy form has its perennial plants' composition ratio getting, the more its succession is progressing. Even though single grained plants ($R_5$) belonging to radicoid in breeding form, succession is predicted to take place considering the fact that they actually belong to ~ plants like Phragmites japonica that form a connection on the surface of the earth. In addition, it is judged that geomantic disseminule form ($D_1$) conveyed by water and gravitational disseminule form favored by the development of waterside woody plants ($D_4$) seem to be better fit to this area in desseminule form. As for growth form, bunch type (t) is judged to become prevalent on the Wetlands while a good variety of phanerophytes will coexist on the earth due to artificial as well as natural disturbances.

• Geophysics and Geophysical Exploration
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• v.8 no.3
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• pp.224-231
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• 2005

In geophysical field surveys, commercial equipments often fail to resolve the subsurface target or even sometimes fail to be applied because they do not fit to the various field situations or the physical properties of the medium or target. We developed a geophysical measurement system, which can be easily adapted for the various field situations and targets. The system based on PXI with A/D converter and some stand alone equipment such as Network Analyzer was applied to borehole radar survey, borehole sonic measurement and electromagnetic noise measurement. The system for borehole radar survey consists of PXI, Network Analyzer, dipole antennas, GPIB interface is used for PXI to control Network Analyzer. The system for borehole sonic measurement consists of PXI, 24 Bit A/D converter, high voltage pulse generator, transmitting and receiving piezoelectric sensors. The electromagnetic noise measurement system consists of PXI, 24 Bit A/D converter, 2 horizontal component electric field sensors and 2 horizontal and 1 vertical component magnetic filed sensors. The borehole radar system has been successfully applied to detect the width of the artificial tunnel through which the borehole pass and to image buried steel pipe, while the commercial borehole radar equipment failed. The borehole sonic system was tested to detect the width of artificial tunnel and showed a reasonable result. The characteristic of electromagnetic noise was grasped at an urban area with the data from the electromagnetic noise measurement system. The system is also applied to characterize the signal distortion by induction between the electric cables in resistivity survey. The system can be applied various geophysical problems with a simple modification of the system and sensors.