• Journal of Internet Computing and Services
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• v.23 no.4
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• pp.35-43
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• 2022

Makeup is the most common way to improve a person's appearance. However, since makeup styles are very diverse, there are many time and cost problems for an individual to apply makeup directly to himself/herself.. Accordingly, the need for makeup automation is increasing. Makeup transfer is being studied for makeup automation. Makeup transfer is a field of applying makeup style to a face image without makeup. Makeup transfer can be divided into a traditional image processing-based method and a deep learning-based method. In particular, in deep learning-based methods, many studies based on Generative Adversarial Networks have been performed. However, both methods have disadvantages in that the resulting image is unnatural, the result of makeup conversion is not clear, and it is smeared or heavily influenced by the makeup style face image. In order to express the clear boundary of makeup and to alleviate the influence of makeup style facial images, this study divides the makeup area and calculates the loss function using HoG (Histogram of Gradient). HoG is a method of extracting image features through the size and directionality of edges present in the image. Through this, we propose a makeup transfer network that performs robust learning on edges.By comparing the image generated through the proposed model with the image generated through BeautyGAN used as the base model, it was confirmed that the performance of the model proposed in this study was superior, and the method of using facial information that can be additionally presented as a future study.

• Convergence Security Journal
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• v.22 no.5
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• pp.69-80
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• 2022

Now that climate change and food resource security are becoming issues around the world, smart farms are emerging as an alternative to solve them. In addition, changes in the production environment in the primary industry are a major concern for people engaged in all primary industries (agriculture, livestock, fishery), and the resulting food shortage problem is an important problem that we all need to solve. In order to solve this problem, in the primary industry, efforts are made to solve the food shortage problem through productivity improvement by introducing smart farms using the 4th industrial revolution such as ICT and BT and IoT big data and artificial intelligence technologies. This is done through the public and private sectors.This paper intends to consider the minimum requirements for the smart farm data collection system for the development and utilization of smart farms, the establishment of a sustainable agricultural management system, the sequential system construction method, and the purposeful, efficient and usable data collection system. In particular, we analyze and improve the problems of the data collection system for building a Korean smart farm standard model, which is facing limitations, based on in-depth investigations in the field of livestock and livestock (pig farming) and analysis of various cases, to establish an efficient and usable big data collection system. The goal is to propose a method for collecting big data.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.1D
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• pp.129-136
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• 2008

Along with the development in cutting-edge digital technology, the street space is also being changed. Mobile telecommunication units and internet give a big change in a human being's lifestyle. And the ubiquitous computing is proceeding with expanding its application range from the indoor space to the street space. As the street furniture is the convenient facility that allows a human being's life in street space to be abundant, it is getting advanced. First of all, in terms of such phenomenon, this study analyzed the cases of a research on application of street space and the actual condition of a change in the number of individuals for the street furniture, through a literature research of ubiquitous. Also, it researched into the realities of using the street furniture of the walking-desired streets at Daehac-ro and Hongdae district, where are two representative places related to digital generation. The next was carried out FGI (Focus Group Interview) with users of the street space in front of Hongik University and managers of the street furniture, and was researched into the use & management behavior, and recognition level on the street furniture. Thus, the key elements were extracted such as interchange of information for cultural activities, automation for interaction variability in function. Finally the core elements for future vision of street furniture in this digital era were extracted in 3I, namely, Information, Intellectualization, and Integration. This is considered to be applied to the establishment of direction in the process of high-tech digitalization in street furniture related to information hereafter.

• Journal of Internet of Things and Convergence
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• v.10 no.2
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• pp.85-91
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• 2024

In this paper, we studied projection mapping, which is being utilized as a digital canvas beyond space and time for theme parks, mega events, and exhibition performances. Since the existing projection technology used for fixed objects has the limitation that it is difficult to map moving objects in terms of utilization, it is urgent to develop a technology that can track and map moving objects and a real-time dynamic projection mapping system based on dynamically moving objects so that it can respond to various markets such as performances, exhibitions, and theme parks. In this paper, we propose a system that can track real-time objects in real time and eliminate the delay phenomenon by developing hardware and performing high-speed image processing. Specifically, we develop a real-time object image analysis and projection focusing control unit, an integrated operating system for a real-time object tracking system, and an image processing library for projection mapping. This research is expected to have a wide range of applications in the technology-intensive industry that utilizes real-time vision machine-based detection technology, as well as in the industry where cutting-edge science and technology are converged and produced.

• Journal of Internet Computing and Services
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• v.25 no.1
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• pp.189-198
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• 2024

AI is accepted not only in the private sector but also in the defense sector as a cutting-edge technology that must be introduced for the development of national defense. In particular, artificial intelligence has been selected as a key task in defense science and technology innovation, and the importance of data is increasing. As the national defense department shifts from a closed data policy to data sharing and activation, efforts are being made to secure high-quality data necessary for the development of national defense. In particular, we are promoting a review of the business budget system to secure data so that related procedures can be improved to reflect the unique characteristics of AI and big data, and research and development can begin with sufficient large quantities and high-quality data. However, there is a need to establish standardization and quality standards for structured data and unstructured data at the national defense level, but the defense department is still proposing standardization and quality standards for structured data, so this needs to be supplemented. In this paper, we propose an unstructured data set standard format for defense unstructured data sets, which are most needed in defense artificial intelligence, and based on this, we propose a standardization method for defense unstructured data sets.

• Information Systems Review
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• v.26 no.2
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• pp.155-167
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• 2024

This study recognized the importance of joint research in the field of artificial intelligence and analyzed the characteristics of the industry-academic-research technological cooperation ecosystem focusing on patents from the perspective of the Techno-Economic Segment (TES). To this end, economic entities such as companies, universities, and research institutes within the ecosystem were identified for 7,062 joint research projects out of 113,289 artificial intelligence patents over the past 10 years filed in IP5 countries since 2012. Next, this study identified the topics of technological cooperation and the characteristics of cooperation. As a result of the analysis, technological cooperation is increasing, and the frequency of all types of cooperation was high in industry-to-industry (40%) and industry-to-university (25.2%) relationships. Here, this study confirmed that the role of universities is being strengthened, with an increase in the ratio of companies with strengths in funding and analytical data, industry and universities with excellent research personnel (9.8%), and cooperation between universities (1.9%). In addition, as a result of identifying collaborative patent research areas of interest and collaborative relationships through topic modeling and network analysis, overall similar research interests were derived regardless of the type of cooperation, and applications such as autonomous driving, edge computing, cloud, marketing, and consumer behavior analysis were derived. It was confirmed that the scope of research was expanding, collaborating entities were becoming more diverse, and a large-scale network including Chinese-centered universities was emerging.

• Journal of Cadastre & Land InformatiX
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• v.47 no.1
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• pp.161-178
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• 2017

Whereas the demand for development of forested areas covering more than 60% of Korean territory, permission on the forest development has been still given from the perspective of effective land utilization rather than conservation. As the assessment of large forested areas usually focuses more on forest structure, it has its limitation of observing and analyzing the interior change in forest in this way. This study was aimed at computing landscape metrics using a presence vegetation map and FRAGTSTATS 4.2 and analyzing vegetation mosaics. Colonies in native vegetation were classified into a series of major groups and sub-groups based on the native species within the colonies. The colonies were investigated by analyzing a suite of landscape metrics - Core Area, Percentage of Landscape, Number of Patches, Patch Density, Largest Patch Index, Total Edge, Edge Density, Landscape Shape Index, Mean Patch Area, Euclidean Nearest Neighbor. In the Chungnam province major groups and sub-groups of colonies classified based on the proportion of pine and oak species, and pine species was the principal one in terms of distribution area. As for the competition between pines and oaks, while the coverage of pine-centered colonies were three times larger than those of oak-centered ones, pine colonies showed the greater number of patches and therefore higher fragmentation than oaks at the major group level. For the sub-groups, the largest coverage colonies were not only indicated by Pinus densiflora-Quesrcus mongolica colonies among P. densiflora-centered colonies, Q. accutissima colonies among Q. accutissima-centered ones, Q. accutissima-P. densiflora colonies among Q. accutissima-centered ones, Q. mongolica colonies among Q. mongolica-centered ones, P. thumbergii colonies among P. thumbergii-centered ones, and Q. serrata-Q. acutissima colonies among Q. serrata-centered ones, but also revealed more severely mosaicked than other smaller colonies. The overall mosaicking degree estimated by landscape metrics was considered useful for monitoring and investigating vegetation. However, in order to develop management strategy based on analyzing the reason for the mosaicking process and anticipating a trend in vegetation succession, it is essential to further study about ecological characteristics of each colony in the vegetation.

• Journal of Internet Computing and Services
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• v.25 no.1
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• pp.99-107
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• 2024

Along with economic growth and industrial development, there is an increasing demand for various electronic components and device production of semiconductor, SMT component, and electrical battery products. However, these products may contain foreign substances coming from manufacturing process such as iron, aluminum, plastic and so on, which could lead to serious problems or malfunctioning of the product, and fire on the electric vehicle. To solve these problems, it is necessary to determine whether there are foreign materials inside the product, and may tests have been done by means of non-destructive testing methodology such as ultrasound ot X-ray. Nevertheless, there are technical challenges and limitation in acquiring X-ray images and determining the presence of foreign materials. In particular Small-sized or low-density foreign materials may not be visible even when X-ray equipment is used, and noise can also make it difficult to detect foreign objects. Moreover, in order to meet the manufacturing speed requirement, the x-ray acquisition time should be reduced, which can result in the very low signal- to-noise ratio(SNR) lowering the foreign material detection accuracy. Therefore, in this paper, we propose a five-step approach to overcome the limitations of low resolution, which make it challenging to detect foreign substances. Firstly, global contrast of X-ray images are increased through histogram stretching methodology. Second, to strengthen the high frequency signal and local contrast, we applied local contrast enhancement technique. Third, to improve the edge clearness, Unsharp masking is applied to enhance edges, making objects more visible. Forth, the super-resolution method of the Residual Dense Block (RDB) is used for noise reduction and image enhancement. Last, the Yolov5 algorithm is employed to train and detect foreign objects after learning. Using the proposed method in this study, experimental results show an improvement of more than 10% in performance metrics such as precision compared to low-density images.

• Journal of Internet Computing and Services
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• v.14 no.6
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• pp.95-105
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• 2013

Recently, SME's Collaboration activities have become one of a vital factor for sustaining competitive edge. This is because of the rapidly changing and competitive market environment, and also to leverage performance by overcoming obstacles of having limited internal resources. Discussing about the effects and relationships of the firm's collaboration activities and its outputs are not new. However, as ICT and various technologies have been diffused into the traditional industries, boundaries and practice capabilities within the industries are becoming ambiguous. Thus contents of the products/services and their development methods are also go and come over the industries. Although many researchers suggested the relations of SME's collaboration activities and innovation performances, most of the previous literatures are focusing on broad perspectives of firm's environmental factors rather than considering various SME's idiosyncrasy factors such as their major product and customer types at once. Therefore, the purpose of this paper is to analyze how SME(Small Medium Enterprise)'s external collaboration activities by their idiosyncrasy act as an input to types of innovation performance. In order to analyze collaboration effects in detail, we defined factors that can represent the SME's business environment - Perceived importance of using external resources, Perceived importance of external partnership, Collaboration and Collaboration levels of Major Product types, Customer types and lastly the Firm Sizes. We have also specifically divided the performance of innovation types as product innovation and process innovation based on existing research. In this study, the empirical analysis is based on Probit Regression Model to observe the correlations with the impact of each SME's business environment and their activities. For the empirical data, 497 samples were collected which, this sample data was extracted from the 'Korean Open Innovation Survey' performed by ETRI(Korean Electronics Telecommunications Research Institute) in 2010. As a result, empirical test results indicated that the impact of collaboration varies depend on the innovation types (Product and Process Innovation). The Impact of the collaboration level for the product innovation tend to be more effective when SMEs are developing for a final product, targeting on for individual customers (B2C). But on the other hand, the analysis result of the Process innovation tend to be higher than the product innovation, when SMEs are developing raw materials for their partners or to other firms targeting on for manufacturing industries(B2B). Also perceived importance of using external resources has effected to both product and process innovation performance. But Perceived importance of external partnership was statistically insignificant. Interesting finding was that the service product has negative effects on for the process innovation performance. And Relationship between size of the firms and their external collaboration activities with their performance of the innovations indicated that the bigger firms(over 100 of employees) tend to have better for both product and process innovations. Finally, implications of the results can be suggested as performance of innovation can be varied depends on firm's unique business idiosyncrasy as well as levels of external collaboration activities. The Implication of this research can be considered for firms in selecting an appropriate strategy as well as for policy makers.

• Journal of Internet Computing and Services
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• v.16 no.2
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• pp.49-55
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• 2015

According to the statistics of traffic accidents over recent 5 years, traffic accidents during the night times happened more than the day times. There are various causes to occur traffic accidents and the one of the major causes is inappropriate or missing street lights that make driver's sight confused and causes the traffic accidents. In this paper, with smartphones, we designed and implemented a lane luminance measurement application which stores the information of driver's location, driving, and lane luminance into database in real time to figure out the inappropriate street light facilities and the area that does not have any street lights. This application is implemented under Native C/C++ environment using android NDK and it improves the operation speed than code written in Java or other languages. To measure the luminance of road, the input image with RGB color space is converted to image with YCbCr color space and Y value returns the luminance of road. The application detects the road lane and calculates the road lane luminance into the database sever. Also this application receives the road video image using smart phone's camera and improves the computational cost by allocating the ROI(Region of interest) of input images. The ROI of image is converted to Grayscale image and then applied the canny edge detector to extract the outline of lanes. After that, we applied hough line transform method to achieve the candidated lane group. The both sides of lane is selected by lane detection algorithm that utilizes the gradient of candidated lanes. When the both lanes of road are detected, we set up a triangle area with a height 20 pixels down from intersection of lanes and the luminance of road is estimated from this triangle area. Y value is calculated from the extracted each R, G, B value of pixels in the triangle. The average Y value of pixels is ranged between from 0 to 100 value to inform a luminance of road and each pixel values are represented with color between black and green. We store car location using smartphone's GPS sensor into the database server after analyzing the road lane video image with luminance of road about 60 meters ahead by wireless communication every 10 minutes. We expect that those collected road luminance information can warn drivers about safe driving or effectively improve the renovation plans of road luminance management.