• Journal of the Korean Association of Geographic Information Studies
• /
• v.22 no.3
• /
• pp.82-98
• /
• 2019

The importance of spatial information is rapidly rising. In particular, 3D spatial information construction and modeling for Real World Objects, such as smart cities and digital twins, has become an important core technology. The constructed 3D spatial information is used in various fields such as land management, landscape analysis, environment and welfare service. Three-dimensional modeling with image has the hig visibility and reality of objects by generating texturing. However, some texturing might have occlusion area inevitably generated due to physical deposits such as roadside trees, adjacent objects, vehicles, banners, etc. at the time of acquiring image Such occlusion area is a major cause of the deterioration of reality and accuracy of the constructed 3D modeling. Various studies have been conducted to solve the occlusion area. Recently the researches of deep learning algorithm have been conducted for detecting and resolving the occlusion area. For deep learning algorithm, sufficient training data is required, and the collected training data quality directly affects the performance and the result of the deep learning. Therefore, this study analyzed the ability of detecting the occlusion area of the image using various image quality to verify the performance and the result of deep learning according to the quality of the learning data. An image containing an object that causes occlusion is generated for each artificial and quantified image quality and applied to the implemented deep learning algorithm. The study found that the image quality for adjusting brightness was lower at 0.56 detection ratio for brighter images and that the image quality for pixel size and artificial noise control decreased rapidly from images adjusted from the main image to the middle level. In the F-measure performance evaluation method, the change in noise-controlled image resolution was the highest at 0.53 points. The ability to detect occlusion zones by image quality will be used as a valuable criterion for actual application of deep learning in the future. In the acquiring image, it is expected to contribute a lot to the practical application of deep learning by providing a certain level of image acquisition.

• Journal of Intelligence and Information Systems
• /
• v.25 no.1
• /
• pp.43-61
• /
• 2019

Development of technologies in artificial intelligence has been rapidly increasing with the Fourth Industrial Revolution, and researches related to AI have been actively conducted in a variety of fields such as autonomous vehicles, natural language processing, and robotics. These researches have been focused on solving cognitive problems such as learning and problem solving related to human intelligence from the 1950s. The field of artificial intelligence has achieved more technological advance than ever, due to recent interest in technology and research on various algorithms. The knowledge-based system is a sub-domain of artificial intelligence, and it aims to enable artificial intelligence agents to make decisions by using machine-readable and processible knowledge constructed from complex and informal human knowledge and rules in various fields. A knowledge base is used to optimize information collection, organization, and retrieval, and recently it is used with statistical artificial intelligence such as machine learning. Recently, the purpose of the knowledge base is to express, publish, and share knowledge on the web by describing and connecting web resources such as pages and data. These knowledge bases are used for intelligent processing in various fields of artificial intelligence such as question answering system of the smart speaker. However, building a useful knowledge base is a time-consuming task and still requires a lot of effort of the experts. In recent years, many kinds of research and technologies of knowledge based artificial intelligence use DBpedia that is one of the biggest knowledge base aiming to extract structured content from the various information of Wikipedia. DBpedia contains various information extracted from Wikipedia such as a title, categories, and links, but the most useful knowledge is from infobox of Wikipedia that presents a summary of some unifying aspect created by users. These knowledge are created by the mapping rule between infobox structures and DBpedia ontology schema defined in DBpedia Extraction Framework. In this way, DBpedia can expect high reliability in terms of accuracy of knowledge by using the method of generating knowledge from semi-structured infobox data created by users. However, since only about 50% of all wiki pages contain infobox in Korean Wikipedia, DBpedia has limitations in term of knowledge scalability. This paper proposes a method to extract knowledge from text documents according to the ontology schema using machine learning. In order to demonstrate the appropriateness of this method, we explain a knowledge extraction model according to the DBpedia ontology schema by learning Wikipedia infoboxes. Our knowledge extraction model consists of three steps, document classification as ontology classes, proper sentence classification to extract triples, and value selection and transformation into RDF triple structure. The structure of Wikipedia infobox are defined as infobox templates that provide standardized information across related articles, and DBpedia ontology schema can be mapped these infobox templates. Based on these mapping relations, we classify the input document according to infobox categories which means ontology classes. After determining the classification of the input document, we classify the appropriate sentence according to attributes belonging to the classification. Finally, we extract knowledge from sentences that are classified as appropriate, and we convert knowledge into a form of triples. In order to train models, we generated training data set from Wikipedia dump using a method to add BIO tags to sentences, so we trained about 200 classes and about 2,500 relations for extracting knowledge. Furthermore, we evaluated comparative experiments of CRF and Bi-LSTM-CRF for the knowledge extraction process. Through this proposed process, it is possible to utilize structured knowledge by extracting knowledge according to the ontology schema from text documents. In addition, this methodology can significantly reduce the effort of the experts to construct instances according to the ontology schema.

• Journal of Broadcast Engineering
• /
• v.24 no.1
• /
• pp.118-131
• /
• 2019

In order to provide 8K UHD contents of terrestrial broadcasting with a large capacity, the terrestrial broadcasting system has various problems such as limited bandwidth and so on. To solve these problems, UHD contents transmission technology has been actively studied, and an 8K UHD broadcasting system using terrestrial broadcasting network and communication network has been proposed. The proposed technique is to solve the limited bandwidth problem of terrestrial broadcasting network by segmenting 8K UHD contents and transmitting them to heterogeneous networks through hierarchical separation. Through the terrestrial broadcasting network, the base layer corresponding to FHD and the additional enhancement layer data for 4K UHD are transmitted, and the additional enhancement layer data corresponding to 8K UHD is transmitted through the communication network. When 8K UHD contents are provided in such a way, user can receive up to 4K UHD broadcasting by terrestrial channels, and also can receive up to 8K UHD additional communication networks. However, in order to transmit the 4K UHD contents within the allocated bit rate of the domestic terrestrial UHD broadcasting, the compression rate is increased, so a certain level of image deterioration occurs inevitably. Due to the nature of UHD contents, video quality should be considered as a top priority over other factors, so that video quality should be guaranteed even within a limited bit rate. This requires packet scheduling of content generators in the broadcasting system. Since the multiplexer sends out the packets received from the content generator in order, it is very important to make the transmission time and the transmission rate of the process from the content generator to the multiplexer constant and accurate. Therefore, we propose a variable transmission scheduler between the content generator and the multiplexer to guarantee the image quality of a certain level of UHD contents in this paper.

• Journal of the Korean Institute of Landscape Architecture
• /
• v.49 no.5
• /
• pp.151-162
• /
• 2021

The recent trend of using ornamental grasses as essential landscaping plants has become more prominent, while the demands for today's gardens are to solve the challenges of climate change, biodiversity loss, and urban ecosystem services. Nowadays, the interest in ornamental grasses in South Korea is dramatically increasing, as is the number of available species and varieties. To find the better use of ornamental grasses in urban green spaces, more research should be conducted to understand the current state of ornamental grasses and their characteristics in South Korea. and a practical way of applying ornamental grasses to urban gardens should be devised. For that purpose, this research carried out a survey on the current state of ornamental grasses distributed in the landscaping plants market in South Korea. The grasses were analyzed according to the growing conditions, including habitats, ecological, and horticultural growth characteristics. As a result, 40 genera, 104 species, and 264 taxa of ornamental grasses were verified to be distributed in the market for garden plants in South Korea in August 2021. Poaceae and Cyperaceae are 69.7% and 28.4% among them, respectively. Juncaceae and Typhaceae are of little importance. No Restionaceae is supplied yet. Most of the Poaceae ornamental grasses prefer sunny open land, but others from various habitats are used too. The majority of the Cyperaceae ornamental grasses originate from woodlands, woodland edges, water's edges, and marshes. The market supplies fourteen genera of cool-season and sixteen genera of warm-season grasses. According to life-types of grasses, thirty-eight species are evergreens or semi-evergreens. Thirty-four species are deciduous. Seven species are summer-dormant. According to the growth habits of the grasses, thirty-three species are runners and fifty-one species are clumpers. There are fifteen taxa of ornamental grasses recently selected that have become native grasses.

• Journal of the Korean Institute of Landscape Architecture
• /
• v.49 no.2
• /
• pp.89-100
• /
• 2021

This study evaluated the degree of interaction between the people and the environment using perceived naturalness measure. The seventh-grade index of Hemeroby was divided into subclasses of land cover according to degrees of human influence. The grade was standardized for each indicator to evaluate the current state of urban parks in Seoul by applying probability density function and weight. User evaluation was conducted on six distinctive parks selected. In the results, three implications were found between spatial evaluation according to the perceived naturalness. First, park users evaluated highly for the spaces such as broad-leaved forest, coniferous forest and mixed forest evaluated highly in the Hemeroby grade index. Park users generally recognized that various types of trees in the area had high naturalness. The density of trees is one of the factors in perceived naturalness. Second, water spaces were highly evaluated for naturalness in the Hemeroby grade index. However, the perceived naturalness of water spaces such as inland wetlands, pond and reservoir evaluated in various ways depending on environmental conditions around the park. Third, perceived naturalness is easily evaluated through vertical landscape elements such as trees rather than horizontal landscapes such as grassland. The perceived naturalness is similar to the naturalness evaluation using land cover. However the study found the perceived naturalness for a specific space was different from the Hemeroby index. Perceived naturalness by the user includes the content that the individual sees, hears, and experiences. Park users are usually structuring naturalness through evaluating the value of urban green spaces based on personal perception. Therefore there is no absolute standard criterion for evaluating the naturalness of urban green spaces. A deeper study is needed that considers user bundles or user groups with conflicting interests on the perceived naturalness in urban parks. These studies will be essential data on the direction of naturalness urban park service should provide.

• Journal of IKEEE
• /
• v.25 no.1
• /
• pp.156-167
• /
• 2021

In this paper, we propose a digital transceiver unit design for in-building of 5G optical repeaters that extends the coverage of 5G mobile communication network services and connects to a stable wireless network in a building. The digital transceiver unit for driving the proposed 5G optical repeater is composed of 4 blocks: a signal processing unit, an RF transceiver unit, an optical input/output unit, and a clock generation unit. The signal processing unit plays an important role, such as a combination of a basic operation of the CPRI interface, a 4-channel antenna signal, and response to external control commands. It also transmits and receives high-quality IQ data through the JESD204B interface. CFR and DPD blocks operate to protect the power amplifier. The RF transmitter/receiver converts the RF signal received from the antenna to AD, is transmitted to the signal processing unit through the JESD204B interface, and DA converts the digital signal transmitted from the signal processing unit to the JESD204B interface and transmits the RF signal to the antenna. The optical input/output unit converts an electric signal into an optical signal and transmits it, and converts the optical signal into an electric signal and receives it. The clock generator suppresses jitter of the synchronous clock supplied from the CPRI interface of the optical input/output unit, and supplies a stable synchronous clock to the signal processing unit and the RF transceiver. Before CPRI connection, a local clock is supplied to operate in a CPRI connection ready state. XCZU9CG-2FFVC900I of Xilinx's MPSoC series was used to evaluate the accuracy of the digital transceiver unit for driving the 5G optical repeater proposed in this paper, and Vivado 2018.3 was used as the design tool. The 5G optical repeater digital transceiver unit proposed in this paper converts the 5G RF signal input to the ADC into digital and transmits it to the JIG through CPRI and outputs the downlink data signal received from the JIG through the CPRI to the DAC. And evaluated the performance. The experimental results showed that flatness, Return Loss, Channel Power, ACLR, EVM, Frequency Error, etc. exceeded the target set value.

• Journal of Food Hygiene and Safety
• /
• v.36 no.1
• /
• pp.68-76
• /
• 2021

Foodborne outbreaks frequently occur worldwide and result in huge economic losses. It is the therefore important to estimate the costs associated with foodborne diseases to minimize the economic damage. At the same time, it is difficult to accurately estimate the economic loss from foodborne disease due to a wide variety of cost components. In Korea, there are a limited number of analytical studies attempting to estimate such costs. In this study we investigated the components of economic cost used in foreign countries to better estimate the cost of foodborne disease in Korea. Seven recent studies investigated the cost components used to estimate the cost of foodborne disease in humans. This study categorized the economic loss into four types of cost: direct costs, indirect costs, food business costs, and government administration costs. The healthcare costs most often included were medical (outpatient) and hospital costs (inpatient). However, these cost components should be selected according to the systems and budgets of medical services by country. For non-healthcare costs, several other studies considered transportation costs to the hospital as an exception to the cost of inpatient care. So, further discussion is needed on whether to consider inpatient care costs. Among the indirect costs, premature mortality, lost productivity, lost leisure time, and lost quality of life/pain, grief and suffering costs were considered, but the opportunity costs for hospital visits were not considered in any of the above studies. As with healthcare costs, government administration costs should also be considered appropriate cost components due to the difference in government budget systems, for example. Our findings will provide fundamental information for economic analysis associated with foodborne diseases to improve food safety policy in Korea.

• Journal of Intelligence and Information Systems
• /
• v.27 no.1
• /
• pp.129-149
• /
• 2021

Recently, interest in social robots that can socially interact with humans is increasing. Thanks to the development of ICT technology, social robots have become easier to provide personalized services and emotional connection to individuals, and the role of social robots is drawing attention as a means to solve modern social problems and the resulting decline in the quality of individual lives. Along with the interest in social robots, the spread of social robots is also increasing significantly. Many companies are introducing robot products to the market to target various target markets, but so far there is no clear trend leading the market. Accordingly, there are more and more attempts to differentiate robots through the design of social robots. In particular, anthropomorphism has been studied importantly in social robot design, and many approaches have been attempted to anthropomorphize social robots to produce positive effects. However, there is a lack of research that systematically describes the mechanism by which anthropomorphism for social robots is formed. Most of the existing studies have focused on verifying the positive effects of the anthropomorphism of social robots on consumers. In addition, the formation of anthropomorphism of social robots may vary depending on the individual's motivation or temperament, but there are not many studies examining this. A vague understanding of anthropomorphism makes it difficult to derive design optimal points for shaping the anthropomorphism of social robots. The purpose of this study is to verify the mechanism by which the anthropomorphism of social robots is formed. This study confirmed the effect of the human-likeness of social robots(Within-subjects) and the construal level of consumers(Between-subjects) on the formation of anthropomorphism through an experimental study of 3×2 mixed design. Research hypotheses on the mechanism by which anthropomorphism is formed were presented, and the hypotheses were verified by analyzing data from a sample of 206 people. The first hypothesis in this study is that the higher the human-likeness of the robot, the higher the level of anthropomorphism for the robot. Hypothesis 1 was supported by a one-way repeated measures ANOVA and a post hoc test. The second hypothesis in this study is that depending on the construal level of consumers, the effect of human-likeness on the level of anthropomorphism will be different. First, this study predicts that the difference in the level of anthropomorphism as human-likeness increases will be greater under high construal condition than under low construal condition.Second, If the robot has no human-likeness, there will be no difference in the level of anthropomorphism according to the construal level. Thirdly,If the robot has low human-likeness, the low construal level condition will make the robot more anthropomorphic than the high construal level condition. Finally, If the robot has high human-likeness, the high construal levelcondition will make the robot more anthropomorphic than the low construal level condition. We performed two-way repeated measures ANOVA to test these hypotheses, and confirmed that the interaction effect of human-likeness and construal level was significant. Further analysis to specifically confirm interaction effect has also provided results in support of our hypotheses. The analysis shows that the human-likeness of the robot increases the level of anthropomorphism of social robots, and the effect of human-likeness on anthropomorphism varies depending on the construal level of consumers. This study has implications in that it explains the mechanism by which anthropomorphism is formed by considering the human-likeness, which is the design attribute of social robots, and the construal level of consumers, which is the way of thinking of individuals. We expect to use the findings of this study as the basis for design optimization for the formation of anthropomorphism in social robots.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.16 no.1
• /
• pp.71-85
• /
• 2021

Representative domestic start-up support organizations include the Business Incubator(BI), Korea Institute of Startup & Entrepreneurship Development(KISED), Techno Park(TP), and Center of Creative Economy Innovation(CCEI), and there are about 260 Business incubator nationwide. The Business incubator is operated by universities, research institutes, and private foundations or associations. The organization consists of the center director and the incubating professionals (hereinafter referred to as "manager"), etc., and performs tasks such as center operation management and incubation support services for tenant companies. Until now, research on the operation of Business Incubator has been mainly focused on the performance of tenant companies. Studies on whether the manager's competency characteristics directly or indirectly affect the performance of the tenant companies through psychological mediators such as self-efficacy and organizational commitment were very scarce. The purpose of this study is to explore various factors influencing organizational commitment and job performance by the competence characteristics of Business incubator managers, and to explain the causal relationship among those factors. In particular, the difference in perception was investigated by a manager's survey that influences organizational commitment and work performance at the Business incubator. Through this, we intend to present practical implications for the role of managers in the operation of Business incubators. This study is an exploratory study, and the subject of the study was a survey of about 600 managers working at Business incubator nationwide, of which 116 responses were analyzed. Data analysis included descriptive statistics, exploratory factor analysis, and reliability. Structural equation model analysis was performed for hypothesis tests. As a result of the analysis, it was found that the cognitive characteristics of the Business incubator manager, communication, and situational response as the behavioral characteristics had a positive effect on the manager's self-efficacy, and the behavioral characteristics had a greater effect on the self-efficacy. It was also found that the manager's cognitive and behavioral characteristics, and self-efficacy had a positive effect on organizational commitment and work performance. In particular, a manager's self-efficacy has a positive effect on organizational commitment and work performance. This result showed that the manager's competency characteristics increase the manager's self-efficacy as a mediating factor rather than directly affecting organizational commitment and work performance. This study explains that the manager's competency characteristics are transferred to organizational commitment and work performance. The results of the study are expected to reflect the job standard of the National Competency Standards (NCS) and basic vocational competency to the job competency of managers, and it also provides a guideline for the effective business incubator operation in terms of human resource management. In practice, it is expected that the results of the study can reflect the vocational basic skills of the Business Incubator manager's job competency in the National Competency Standards(NCS) section, and suggest directions for the operation of the Business Incubator and the manager's education and training.

• Journal of Intelligence and Information Systems
• /
• v.28 no.2
• /
• pp.191-206
• /
• 2022

Recently, it is a de-facto approach to utilize a pre-trained language model(PLM) to achieve the state-of-the-art performance for various natural language tasks(called downstream tasks) such as sentiment analysis and question answering. However, similar to any other machine learning method, PLM tends to depend on the data distribution seen during the training phase and shows worse performance on the unseen (Out-of-Distribution) domain. Due to the aforementioned reason, there have been many efforts to develop domain-specified PLM for various fields such as medical and legal industries. In this paper, we discuss the training of a finance domain-specified PLM for the Korean language and its applications. Our finance domain-specified PLM, KB-BERT, is trained on a carefully curated financial corpus that includes domain-specific documents such as financial reports. We provide extensive performance evaluation results on three natural language tasks, topic classification, sentiment analysis, and question answering. Compared to the state-of-the-art Korean PLM models such as KoELECTRA and KLUE-RoBERTa, KB-BERT shows comparable performance on general datasets based on common corpora like Wikipedia and news articles. Moreover, KB-BERT outperforms compared models on finance domain datasets that require finance-specific knowledge to solve given problems.