• Journal of Korea Technology Innovation Society
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• v.21 no.3
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• pp.1155-1178
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• 2018

Future automobiles are evolving into movable living spaces capable of eco-friendly autonomous driving. The role of electrically processing, controlling, and commanding various information in the vehicle is essential. It is expected that the automotive semiconductor will play a key role in the future automobile such as self-driving and eco-friendly automobile. In order to foster the automotive semiconductor industry, it is necessary to grasp technology trends and to acquire technology and quality that reflects the requirements in advance, thereby achieving technological innovation with industrial competitiveness. However, there is a lack of systematic analysis of technology trends to date. In this study, we analyzed the technology trends of automotive semiconductors using patent analysis and topic model, and confirmed technologies such as electric cars, driving assistance, and digital manufacturing. The technology trends showed that element technology and technical characteristics change according to technology convergence, market needs, and government regulations. Through this research, it is expected that it will help to make R&D policy for automotive semiconductor industry and to make decision for industrial technology strategy establishment. In addition, it is expected that it will be used effectively in detail research direction and patent strategy establishment by providing detailed classification of technology and trend analysis result of technology.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.25 no.1
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• pp.25-38
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• 2022

Urban problems are constantly occurring around the world due to rapid industrialization and population decline. In particular, as the number of vacant houses is gradually increasing as the population decreases, it is necessary to prepare countermeasures. A plan to utilize vacant houses has emerged to restore the natural environment of the urban ecosystem where forest destruction, damage to habitats of wild animals and plants, and disconnection have occurred due to large-scale development. Through connectivity analysis, it is possible to understand the overall ecosystem flow based on the movement of species and predict the effect when vacant houses are converted into green spaces. Therefore, this study analyzed the green area network to confirm the possibility of greening of vacant houses neglected in Jeonju based on circuit theory. Using Circuitscape and Least-cost path, we tried to identify the connectivity of green areas and propose an ecological axis based on the analysis. In order to apply the resistance values required for analysis based on previous studies, the 2020 subdivision land cover data were integrated into the major classification evaluation items. When the eight forests in the target site were analyzed as the standard, the overall connectivity and connectivity between forests in the area were high, so it is judged that the existing green areas can perform various functions, such as species movement and provision of habitats. Based on the results of the connectivity analysis, the importance of vacant houses was calculated and the top 20 vacant houses were identified, and it was confirmed that the higher the ranking, the more positive the degree of landscape connectivity was when converted to green areas. In addition, it was confirmed that the results of analyzing the least-cost path based on the resistance values such as connectivity analysis and the existing conceptual map showed some differences when comparing the ecological axes in the form. As a result of checking the vacant houses corresponding to the relevant axis based on the width standards of the main and sub-green areas, a total of 30 vacant houses were included in the 200m width and 6 vacant houses in the 80m width. It is judged that the conversion of vacant houses to green space can contribute to biodiversity conservation as well as connectivity between habitats of species as it is coupled with improved green space connectivity. In addition, it is expected to help solve the problem of vacant houses in the future by showing the possibility of using vacant houses.

• Korean Journal of Clinical Laboratory Science
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• v.53 no.2
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• pp.143-150
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• 2021

The recent spread of novel and highly variant pathogenic viruses, including the coronavirus (SARS-CoV-2), has increased the demand for diagnostic testing for rapid confirmation. This has resulted in investigating the functional capability of each space, and preparing facility guidelines to secure the safety of medical technologists. During viral evaluations, there is a requirement of negative pressure facilities along with thread separation, during pre-treatment of samples and before nucleic acid amplification. Space composition therefore needs to be planned by considering unidirectional air flow. This classification of safety management facilities is designated as biosafety level 2, and personal protective equipment is placed accordingly. In case of handling dangerous materials, they need to be carried out of the biosafety cabinet, and sterilizers are required for suitable disposal of infectious agents. A common feature of domestic laboratories is maintenance of the sample pre-treatment space at a negative pressure of -2.5 Pa or less, and arranging separate pre-treatment and reagent preparation spaces during the test process. We believe that the data generated in this study is meaningful, and offers an efficient direction and detailed flow for separation of the inspection process and space functions. Moreover, this study introduces construction of the laboratory by applying the safety management standards.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.40 no.4
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• pp.58-66
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• 2022

Biophilic design is an approach that attempts to connect people with nature to promote health, recovery and restoration processes. The purpose of this study was to systematically analyze restorative factors and characteristics of Soswaewon by applying a biophilic design analysis framework. To this end, a biophilic design classification system was established and content analysis and frequency analysis were conducted for 『Soswaewon 48 Young』. the ratio of plant words including bamboo, pine, and plum was the highest, and words related to dynamic water flow or interaction with water as well as various water types such as streams, waterfalls, and ponds were also high. appeared in rank. In addition, multisensory factors, seasonal changes, microclimatic factors, emotional elements that allow people to indirectly experience nature were expressed in various ways. The space layout and circulation provide opportunities to appreciate and experience the rich sensory resources of Soswaewon. In conclusion, this study confirmed the healing and restorative value of Soswaewon from the perspective of biophilic design, and it needs further research on the restorative factors of traditional spaces.

• International Journal of Computer Science & Network Security
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• v.23 no.1
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• pp.112-119
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• 2023

Traditionally used for networking computers and communications, the Internet has been evolving from the beginning. Internet is the backbone for many things on the web including social media. The concept of social networking which started in the early 1990s has also been growing with the internet. Social Networking Sites (SNSs) sprung and stayed back to an important element of internet usage mainly due to the services or provisions they allow on the web. Twitter and Facebook have become the primary means by which most individuals keep in touch with others and carry on substantive conversations. These sites allow the posting of photos, videos and support audio and video storage on the sites which can be shared amongst users. Although an attractive option, these provisions have also culminated in issues for these sites like posting offensive material. Though not always, users of SNSs have their share in promoting hate by their words or speeches which is difficult to be curtailed after being uploaded in the media. Hence, this article outlines a process for extracting user reviews from the Twitter corpus in order to identify instances of hate speech. Through the use of MPCA (Modified Principal Component Analysis) and ECNN, we are able to identify instances of hate speech in the text (Enhanced Convolutional Neural Network). With the use of NLP, a fully autonomous system for assessing syntax and meaning can be established (NLP). There is a strong emphasis on pre-processing, feature extraction, and classification. Cleansing the text by removing extra spaces, punctuation, and stop words is what normalization is all about. In the process of extracting features, these features that have already been processed are used. During the feature extraction process, the MPCA algorithm is used. It takes a set of related features and pulls out the ones that tell us the most about the dataset we give itThe proposed categorization method is then put forth as a means of detecting instances of hate speech or abusive language. It is argued that ECNN is superior to other methods for identifying hateful content online. It can take in massive amounts of data and quickly return accurate results, especially for larger datasets. As a result, the proposed MPCA+ECNN algorithm improves not only the F-measure values, but also the accuracy, precision, and recall.

• Journal of the Korean Institute of Landscape Architecture
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• v.43 no.1
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• pp.16-28
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• 2015

This study is suggested to enlarge the green area and to connect and improve the present green areas by deriving the lines of community greenway using living areas and community spaces close to the life of residence in Nam-gu. The purpose of this paper is to suggest the method of establishing greenway for the formation of community in which the residence can grow the community spirit and love their living space much more. Land-use status, green coverage ratio, and impermeability paving ratio are investigated. The community facilities are classified. The highest is educational facility, which is 7.7%, the green facility is 1.9% and the total area of community facilities which is 21.4%. The total area of Nam-gu is divided into 31 zones in total according to the administrative districts, the mail roads and reserved land of railroad and urban development. The total 20 lines of community greenway lines are chosen and the total length of lines is 18.2km. Finally, the characteristics of community greenway lines are analysed, the characteristics of community greenway lines are overall estimated according to the land-use, the street environment and the community facility. The classification system of community greenway is established on the basis on the function and purpose of greenway, the present status of land-use and the type of community facility. Based on the field investigation, the 6 greenway types are suggested considering the interconnection. The method of establishment of community greenway is suggested according to the principle of function and purpose, the principle of land-use and the principle of use of the facilities. Furthermore, the planting methods suitable to each greenway type are suggested in the building planting case of wall planting, roof planting, veranda planting, etc., and in the complex planting of parks, schools, roads, parking lots and other small areas.

• Journal of the Korean Institute of Landscape Architecture
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• v.45 no.6
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• pp.137-148
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• 2017

This study analyzed the opinions of residents for desirable urban regeneration and suggested an improvement plan for alley environments. This study conducted a questionnaire survey of the residents living in Alley Garden of Bisan 2,3-dong, Daegu Metropolitan City. In the analysis of the importance and satisfaction of Alley Garden components, items related to a safe, cleanly environment such as 'Lighting facility installation', 'Sewage and waste disposal' and 'CCTV installation' had a high level of importance. It was also found that items improved by the Residential Environment Improvement Project and Alley Garden such as 'Lighting facility installation', 'Quantity of herbaceous flowers' and 'Kinds of herbaceous flowers' had a high level of satisfaction. The IPA results showed that items such as 'Empty house maintenance', 'Rest facilities such as benches and pergolas', 'Space for resident interaction' and 'Public parking lot' had a high level of importance, but had a low level of satisfaction, which suggests that they should be improved by priority. As a result of factor analysis, Alley Garden components were classified into four factors: 'Safety and cleanliness', 'Greenness', 'Exchange and convenience facility' and 'Aesthetics renewal'. Based on this classification, a regression analysis was conducted regarding the effects of the four factors on overall satisfaction. Results showed that all four factors had a significant influence on the overall satisfaction and that 'Aesthetics renewal' and 'Safety and cleanliness', respectively showing levels of significance at 0.274 and 0.235, were highly influential to overall satisfaction. Therefore, it was concluded that spaces for resident interaction and rest facilities should be preferentially installed to improve the environment of alleys. For the improvement of the overall satisfaction of alley environments, it was also concluded that residents should be encouraged to engage in activities such as sculpture installation and mural drawing, along with the introduction of safety bells and crime prevention environment design and the implementation of alley beautification projects.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.41 no.4
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• pp.40-48
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• 2023

This study is part of a foundational research effort aimed at developing a suitability index for breeding grounds related to avian activities along the domestic South and West coasts, including islands. Focus Group Interviews (FGI) and Analytic Hierarchy Process (AHP) analyses were conducted. The results are as follows. First, as a result of determining the value of the suitability of coastal bird breeding sites, the 'Natural Value(0.763)' was higher than the 'Artificial Value(0.237)'. Other artificial values were identified as sub-ranked except for 'Protected Areas' to ensure continuous integrity of breeding spaces. Second, as a result of re-establishing the 25 evaluation items classified in the two-time FGI as higher concepts, nine natural values and five artificial values were finally selected as a total of 14. Third, the results of the mid-classification evaluation of the importance of the suitability of coastal bird breeding sites were identified in the order of 'Ecological Value(0.392)', 'Topographic Value(0.251)', 'Passive Interference(0.124)', 'Geological Value(0.120)', and 'Active Interference(0.113)'. Fourth, the results of the priority of evaluation items of coastal bird breeding sites were in the order of 'Vegetation Distribution (0.187)', 'Area of Mudflats(0.118)', 'Presence or Absence of Mudflats(0.092)', 'Appearance of Natural Enemies(0.087)', 'Protected Areas(0.08)', 'Island Area (0.069)', 'Over-Breeding devastation(0.064)', 'Soil Composition Ratio(0.056)', 'Distance from Land(0.054)', 'Ocean farm area (0.045)', 'Cultivated land area(0.041)', 'Cultivation behavior(0.038)', 'Angle of the Surface(0.036)', and 'Land Use(0.033)'. It is judged that the weighting result value of the evaluation items derived in this study can be used for priority evaluation focusing on the coastal bird breeding area space. However, it seems that the correlation with the unique habitat suitability of bird individuals needs to be supplemented, and spatial analysis research incorporating species-specific characteristics will be left as a future task.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.1-23
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• 2018

From the 21st century, various high-quality services have come up with the growth of the internet or 'Information and Communication Technologies'. Especially, the scale of E-commerce industry in which Amazon and E-bay are standing out is exploding in a large way. As E-commerce grows, Customers could get what they want to buy easily while comparing various products because more products have been registered at online shopping malls. However, a problem has arisen with the growth of E-commerce. As too many products have been registered, it has become difficult for customers to search what they really need in the flood of products. When customers search for desired products with a generalized keyword, too many products have come out as a result. On the contrary, few products have been searched if customers type in details of products because concrete product-attributes have been registered rarely. In this situation, recognizing texts in images automatically with a machine can be a solution. Because bulk of product details are written in catalogs as image format, most of product information are not searched with text inputs in the current text-based searching system. It means if information in images can be converted to text format, customers can search products with product-details, which make them shop more conveniently. There are various existing OCR(Optical Character Recognition) programs which can recognize texts in images. But existing OCR programs are hard to be applied to catalog because they have problems in recognizing texts in certain circumstances, like texts are not big enough or fonts are not consistent. Therefore, this research suggests the way to recognize keywords in catalog with the Deep Learning algorithm which is state of the art in image-recognition area from 2010s. Single Shot Multibox Detector(SSD), which is a credited model for object-detection performance, can be used with structures re-designed to take into account the difference of text from object. But there is an issue that SSD model needs a lot of labeled-train data to be trained, because of the characteristic of deep learning algorithms, that it should be trained by supervised-learning. To collect data, we can try labelling location and classification information to texts in catalog manually. But if data are collected manually, many problems would come up. Some keywords would be missed because human can make mistakes while labelling train data. And it becomes too time-consuming to collect train data considering the scale of data needed or costly if a lot of workers are hired to shorten the time. Furthermore, if some specific keywords are needed to be trained, searching images that have the words would be difficult, as well. To solve the data issue, this research developed a program which create train data automatically. This program can make images which have various keywords and pictures like catalog and save location-information of keywords at the same time. With this program, not only data can be collected efficiently, but also the performance of SSD model becomes better. The SSD model recorded 81.99% of recognition rate with 20,000 data created by the program. Moreover, this research had an efficiency test of SSD model according to data differences to analyze what feature of data exert influence upon the performance of recognizing texts in images. As a result, it is figured out that the number of labeled keywords, the addition of overlapped keyword label, the existence of keywords that is not labeled, the spaces among keywords and the differences of background images are related to the performance of SSD model. This test can lead performance improvement of SSD model or other text-recognizing machine based on deep learning algorithm with high-quality data. SSD model which is re-designed to recognize texts in images and the program developed for creating train data are expected to contribute to improvement of searching system in E-commerce. Suppliers can put less time to register keywords for products and customers can search products with product-details which is written on the catalog.