• Journal of the Korea Convergence Society
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• v.13 no.2
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• pp.151-166
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• 2022

Museum is the carrier and symbol of history and cultural accumulation, and the museum cultural relics are clues with the spirit of history. Moreover, the museum cultural and creative products are portable history. Museum has changed form the traditional "object-basic" model to the modern "people-basic" model, which pays more attention to its living inheritance. Therefor, the museum cultural and creative products is also the way of expression of its living inheritance. This paper analyzes the opportunities and difficulties of cultural and creative products of Chinese museums by means of network survey, field survey and expert interview. In order to improve the design method of cultural and creative products. By exploring the cultural connotation, broadening the functional factors, innovating the design factors and creating the empathy factor between products and people to explore and the verify. Trying to make up the imperfect design methods of cultural and creative products in small and medium-sized museums which leads to the lack of function, innovation and communication of cultural and creative products. We try to attract more people's attention, spread traditional culture and realize the resonance between people and objects.

• Korean Journal of Remote Sensing
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• v.39 no.1
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• pp.77-86
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• 2023

Ship detection is widely used in areas such as maritime security, maritime traffic, fisheries management, illegal fishing, and border control, and ship detection is important for rapid response and damage minimization as ship accident rates increase due to recent increases in international maritime traffic. Currently, according to a number of global and national regulations, ships must be equipped with automatic identification system (AIS), which provide information such as the location and speed of the ship periodically at regular intervals. However, most small vessels (less than 300 tons) are not obligated to install the transponder and may not be transmitted intentionally or accidentally. There is even a case of misuse of the ship'slocation information. Therefore, in this study, ship detection was performed using high-resolution optical satellite images that can periodically remotely detect a wide range and detectsmallships. However, optical images can cause false-alarm due to noise on the surface of the sea, such as waves, or factors indicating ship-like brightness, such as clouds and wakes. So, it is important to remove these factors to improve the accuracy of ship detection. In this study, false alarm wasreduced, and the accuracy ofship detection wasimproved by removing wake.As a ship detection method, ship detection was performed using machine learning-based random forest (RF), and convolutional neural network (CNN) techniquesthat have been widely used in object detection fieldsrecently, and ship detection results by the model were compared and analyzed. In addition, in this study, the results of RF and CNN were combined to improve the phenomenon of ship disconnection and the phenomenon of small detection. The ship detection results of thisstudy are significant in that they improved the limitations of each model while maintaining accuracy. In addition, if satellite images with improved spatial resolution are utilized in the future, it is expected that ship and wake simultaneous detection with higher accuracy will be performed.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.3D
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• pp.423-429
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• 2008

The object of the present study is to estimate the potential effects of climate change and land use on soil erosion in the mid-east Korea. Simulated precipitation by CCCma climate model during 2030-2050 is used to model predicted soil erosion, and results are compared to observation. Simulation results allow relative comparison of the impact of climate change on soil erosion between current and predicted future condition. Expected land use changes driven by socio-economic change and plant growth driven by the increase of temperature and are taken into accounts in a comprehensive way. Mean precipitation increases by 17.7% (24.5%) for A2 (B2) during 2030-2050 compared to the observation period (1966-1998). In general predicted soil erosion for the B2 scenario is larger than that for the A2 scenario. Predicted soil erosion increases by 48%~90% under climate change except the scenario 1 and 2. Predicted soil erosion under the influence of temperature-induced fast plant growth, higher evapotranspiration rate, and fertilization effect (scenario 5 and 6) is approximately 25% less than that in the scenario 3 and 4. On the basis of the results it is said that precipitation and the corresponding soil erosion is likely to increase in the future and care needs to be taken in the study area.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.1-25
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• 2020

Sentiment Analysis (SA) is a Natural Language Processing (NLP) task that analyzes the sentiments consumers or the public feel about an arbitrary object from written texts. Furthermore, Aspect-Based Sentiment Analysis (ABSA) is a fine-grained analysis of the sentiments towards each aspect of an object. Since having a more practical value in terms of business, ABSA is drawing attention from both academic and industrial organizations. When there is a review that says "The restaurant is expensive but the food is really fantastic", for example, the general SA evaluates the overall sentiment towards the 'restaurant' as 'positive', while ABSA identifies the restaurant's aspect 'price' as 'negative' and 'food' aspect as 'positive'. Thus, ABSA enables a more specific and effective marketing strategy. In order to perform ABSA, it is necessary to identify what are the aspect terms or aspect categories included in the text, and judge the sentiments towards them. Accordingly, there exist four main areas in ABSA; aspect term extraction, aspect category detection, Aspect Term Sentiment Classification (ATSC), and Aspect Category Sentiment Classification (ACSC). It is usually conducted by extracting aspect terms and then performing ATSC to analyze sentiments for the given aspect terms, or by extracting aspect categories and then performing ACSC to analyze sentiments for the given aspect category. Here, an aspect category is expressed in one or more aspect terms, or indirectly inferred by other words. In the preceding example sentence, 'price' and 'food' are both aspect categories, and the aspect category 'food' is expressed by the aspect term 'food' included in the review. If the review sentence includes 'pasta', 'steak', or 'grilled chicken special', these can all be aspect terms for the aspect category 'food'. As such, an aspect category referred to by one or more specific aspect terms is called an explicit aspect. On the other hand, the aspect category like 'price', which does not have any specific aspect terms but can be indirectly guessed with an emotional word 'expensive,' is called an implicit aspect. So far, the 'aspect category' has been used to avoid confusion about 'aspect term'. From now on, we will consider 'aspect category' and 'aspect' as the same concept and use the word 'aspect' more for convenience. And one thing to note is that ATSC analyzes the sentiment towards given aspect terms, so it deals only with explicit aspects, and ACSC treats not only explicit aspects but also implicit aspects. This study seeks to find answers to the following issues ignored in the previous studies when applying the BERT pre-trained language model to ACSC and derives superior ACSC models. First, is it more effective to reflect the output vector of tokens for aspect categories than to use only the final output vector of [CLS] token as a classification vector? Second, is there any performance difference between QA (Question Answering) and NLI (Natural Language Inference) types in the sentence-pair configuration of input data? Third, is there any performance difference according to the order of sentence including aspect category in the QA or NLI type sentence-pair configuration of input data? To achieve these research objectives, we implemented 12 ACSC models and conducted experiments on 4 English benchmark datasets. As a result, ACSC models that provide performance beyond the existing studies without expanding the training dataset were derived. In addition, it was found that it is more effective to reflect the output vector of the aspect category token than to use only the output vector for the [CLS] token as a classification vector. It was also found that QA type input generally provides better performance than NLI, and the order of the sentence with the aspect category in QA type is irrelevant with performance. There may be some differences depending on the characteristics of the dataset, but when using NLI type sentence-pair input, placing the sentence containing the aspect category second seems to provide better performance. The new methodology for designing the ACSC model used in this study could be similarly applied to other studies such as ATSC.

• The Korean Journal of Archival Studies
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• no.44
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• pp.51-99
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• 2015

The purpose of the archival appraisal has gradually changed from the selection of records to the documentation of the society. In particular, the qualitative and quantitative developments of the current digital technology and web have become the driving force that enables semantic acquisition, rather than physical one. Under these circumstances, the concept of 'documentary heritage' has been re-established internationally, led by UNESCO. Library and Archives Canada (LAC) reflects this trend. LAC has been trying to develop a new appraisal model and an acquisition model at the same time to revive the spirit of total archives, which is the 'Whole-of-society approach'. Features of this approach can be summarized in three main points. First, it is for documentary heritage and the acquisition refers to semantic acquisition, not the physical one. And because the object of management is documentary heritage, the cooperation between documentary heritage institutions has to be a prerequisite condition. Lastly, it cannot only documenting what already happened, it can documenting what is happening in the current society. 'Whole-of-society approach', as an appraisal method, is a way to identify social components based on social theories. The approach, as an acquisition method, is targeting digital recording, which includes 'digitized' heritage and 'born-digital' heritage. And it makes possible to the semantic acquisition of documentary heritage based on the data linking by mapping identified social components as metadata component and establishing them into linked open data. This study pointed out that it is hard to realize documentation of the society based on domestic appraisal system since the purpose is limited to selection. To overcome this limitation, we suggest a guideline applied with 'Whole-of-society approach'.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.38 no.9
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• pp.1029-1036
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• 2014

Several types of automatic 3D scanners are available for use in the 3D scanning industry, e.g., an automatic 3D scanner that uses a robot arm and one that uses an automatic rotary table. Specifically, these scanners are used to obtain a 3D shape using automatic assisting devices. Most of these scanners are required to perform numerous operations, such as merging, aligning, trimming, and filling holes. We are interested in developing an automatic 3D shape collection device using a spherical-coordinate-based guiding system. Then, the aim of the present study is to design an automatic guiding system that can automatically collect 3D shape data. We develop a 3D model of this system and measuring data which are collected by a personal computer. An optimal design of this system and the geometrical accuracy of the measured data are both evaluated using 3D modeling software. The developed system is then applied to an object having a highly complex shape and manifold sections. Our simulation results demonstrate that the developed system collects higher-quality 3D data than the conventional method.

• Journal of Distribution Science
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• v.13 no.11
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• pp.101-109
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• 2015

Purpose - A traditional retail market is a place that offers economic opportunity to employees and employers alike it also is a place where the community can meet. The Korean government has invested three trillion won to improve physical and non-physical aspects in traditional retail markets since 2004. However, little research on this has been conducted. We explore this research gap that could lead to theory extension. We analyze consumption behavior with respect to traditional retail markets through an empirical analysis, thus overcoming limits in previous research. We empirically analyze policy effects of traditional retail market projects supported by the Korean government. Research design, data, and methodology - We propose a traditional retail market improvement plan via the relation between cause and effect resulting from the analysis. More specifically, logit analysis was carried out with 1,754 consumers in 16 cities nationwide. In order to analyze consumer consumption behaviors nationwide, the probability was analyzed using a logit model. This research analyzes the link between support and non-support by the Korean government using binary values. The dependent variable is whether Korean government support is implemented; the binomial logistic regression is used as the statistical estimation technique. The object variables are:1 (support) or 0 (nonsupport), and the prediction value is between 1 and 0. As a result of the factor analysis of questions related to attributes of service quality, four factors were extracted: convenience, product, facilities, and service. Results - The results indicate that convenience, product, and facilities have a significant influence on consumer satisfaction in accordance with the government's traditional retail market support. Additionally, the results reveal that convenience, product, facilities, and service all have a significant influence on consumer satisfaction in a traditional retail market's service quality and consumer satisfaction. Finally, the analysis indicates that the highly satisfied traditional retail market customer has a significant influence on revisit intention. Moreover, the results reveal that the highly satisfied traditional retail market customer has a significant influence on recommendation intention. Conclusions - This research focused on consumers nationwide to measure policy effects of traditional retail markets compared to previous research that focused on one traditional retail market or a specific area. We verified the relationship of service quality and customer satisfaction and consumer behavior based on service quality theory. The results indicate that consumer satisfaction of traditional retail markets supported by service quality factors has a significant impact. In a concrete form, the results indicate that these effects are from facility modernization projects and marketing support projects of the Korean government. The results also imply that these facility and management support effects from the Korean government have been consistent. We realize that the Korean government has to selectively support traditional retail markets in major cities and small and medium-sized cities. To that end, the Korean government needs to select a concentration strategy for the revitalization of traditional retail markets.

• Journal of Digital Convergence
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• v.16 no.2
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• pp.117-126
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• 2018

The threat to information security is growing globally. To this, organizations are increasing the weight of adapting and operating the more specialized information security policy and system. Information security requires participation from the employees who execute the security system and policy, and to increase the level of organization's internal security, requires organization's systematic support to improve employees' information security compliance intention. This research finds the mechanism for improving employee's information security compliance intention by applying justice theory and goal setting theory in information security. We use structural equation modeling to verify the research hypothesis, and conducted a survey on the employees of organization with information security policy. In other words, this research performs verification of the research model based hypothesis which claims that security policy goal setting has positive influence on employee's level of security related justice recognition, and claims that justice has positive influence on compliance intention. The object of study is the employees of the organization that adapts information security policy, and 383 valid samples were collected via survey. Structural equation modeling was performed to verify the research hypothesis. The result shows that security policy goal factor (goal difficulty, goal specificity) improves employee's security related justice recognition, and that security related justice (distribution, process, and information justice) has positive influence on compliance intention. The result suggests the strategic approach directions for improving employees' compliance intention on organization's security policy.

• Tunnel and Underground Space
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• v.30 no.5
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• pp.462-472
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• 2020

Rock classification is fundamental discipline of exploring geological and geotechnical features in a site, which, however, may not be easy works because of high diversity of rock shape and color according to its origin, geological history and so on. With the great success of convolutional neural networks (CNN) in many different image-based classification tasks, there has been increasing interest in taking advantage of CNN to classify geological material. In this study, a feasibility of the deep CNN is investigated for automatically and accurately identifying rock types, focusing on the condition of various shapes and colors even in the same rock type. It can be further developed to a mobile application for assisting geologist in classifying rocks in fieldwork. The structure of CNN model used in this study is based on a deep residual neural network (ResNet), which is an ultra-deep CNN using in object detection and classification. The proposed CNN was trained on 10 typical rock types with an overall accuracy of 84% on the test set. The result demonstrates that the proposed approach is not only able to classify rock type using images, but also represents an improvement as taking highly diverse rock image dataset as input.

• The Journal of Korean Academy of Prosthodontics
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• v.50 no.2
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• pp.85-91
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• 2012

Purpose: The object of this study was to determine if the low-priced alloy and metal UCLA abutment could be available for manufacturing bar-retained framework of implant prosthesis. Materials and methods: Bar structure was classified into 4 groups, The specimen of group 1 and 2 were based on casting high noble metal alloys and noble metal alloys with gold UCLA abutment. The specimen of group 3 and 4 were based on casting noble metal alloys and base metal alloys with metal UCLA abutment. Cast bar structure was installed in an acrylic resin model and only the screw on the hexed abutment side was tightened to 20 Ncm. On the opposite side, vertical discrepancy was measured with stereo microscope from front, back, and lateral side of the implant-abutment interface. One-way ANOVA was performed to analyze the marginal fit discrepancy. Results: One-way ANOVA test showed significant differences among all groups ($P$<.05) except for Group 1 and 3. Among them, difference between Group 1 and 2 was noticeable. Measured vertical discrepancies were all below $70{\mu}m$ except to Group 2. Conclusion: Base metal alloy and metal UCLA abutment could be used as an alternative to high-priced gold alloy for implant bar-retained framework.