• Journal of the Korea Society of Computer and Information
• /
• v.27 no.2
• /
• pp.33-42
• /
• 2022

In this paper, we proposed a deep learning model based on multi-scale dilated convolution feature fusion for the segmentation of black ice region in road image to send black ice warning to drivers in real time. In the proposed multi-scale dilated convolution feature fusion network, different dilated ratio convolutions are connected in parallel in the encoder blocks, and different dilated ratios are used in different resolution feature maps, and multi-layer feature information are fused together. The multi-scale dilated convolution feature fusion improves the performance by diversifying and expending the receptive field of the network and by preserving detailed space information and enhancing the effectiveness of diated convolutions. The performance of the proposed network model was gradually improved with the increase of the number of dilated convolution branch. The mIoU value of the proposed method is 96.46%, which was higher than the existing networks such as U-Net, FCN, PSPNet, ENet, LinkNet. The parameter was 1,858K, which was 6 times smaller than the existing LinkNet model. From the experimental results of Jetson Nano, the FPS of the proposed method was 3.63, which can realize segmentation of black ice field in real time.

• Journal of Intelligence and Information Systems
• /
• v.29 no.3
• /
• pp.249-265
• /
• 2023

Recently, the satellite industry has been paying attention to the private-led 'New Space' paradigm, which is a departure from the traditional government-led industry. The space industry, which is considered to be the next food industry, is still receiving relatively little attention in Korea compared to the global market. Therefore, the purpose of this study is to explore future signals that can help determine the market entry strategies of private companies in the domestic satellite industry. To this end, this study utilizes the theoretical background of future signal theory and the Keyword Portfolio Map method to analyze keyword potential in patent document data based on keyword growth rate and keyword occurrence frequency. In addition, news data was collected to categorize future signals into first symptom and early information, respectively. This is utilized as an interpretive indicator of how the keywords reveal their actual potential outside of patent documents. This study describes the process of data collection and analysis to explore future signals and traces the evolution of each keyword in the collected documents from a weak signal to a strong signal by specifically visualizing how it can be used through the visualization of keyword maps. The process of this research can contribute to the methodological contribution and expansion of the scope of existing research on future signals, and the results can contribute to the establishment of new industry planning and research directions in the satellite industry.

• 한국체육학회지인문사회과학편
• /
• v.55 no.6
• /
• pp.661-676
• /
• 2016

The purpose of this study is to draw a systematic access method of career intervention for dance majors. This study conducted Delphi survey and Analytic Hierarchy Process(AHP). As a result of study, 16 elements of career intervention were produced in total 4 areas. Results show that vocational guidance puts emphasis on the understanding of the various vocations, career education on the career planning and goal, career counseling on the macro-narrative to the life and career intervention network on the dance job fair and workshop. In the complex weight of all factors, ratings of weight show that dance vocation guidance and career education are demanded significantly. Results show that expansion of career alternatives, application of diversified dance career development road map to the curriculum, development of test tool and outcome standard, dance educators' systematic career intervention education and systematization of network for career support were suggested as measures for dance career intervention. This study discussed about dynamic reality and systematic access method for dance majors based on theories of Holland(1997), Super(1990), and Savickas(2005).

• 한국공간정보시스템학회:학술대회논문집
• /
• 2004.12a
• /
• pp.169-181
• /
• 2004

SK Telecom has already constructed GIMS system as the base common framework of LBS/GIS service system based on OGC(OpenGIS Consortium)'s international standard for the first mobile vector map service in 2002, But as service content appears more complex, renovation has been needed to satisfy multi-purpose, multi-function and maximum efficiency as requirements have been increased. This research is for preparation ion of GML3-based platform to upgrade service from GML2 based GIMS system. And with this, it will be possible for variety of application services to provide location and geographic data easily and freely. In GML 3.0, it has been selected animation, event handling, resource for style mapping, topology specification for 3D and telematics services for mobile LBS multimedia service. And the schema and transfer protocol has been developed and organized to optimize data transfer to MS(Mobile Stat ion) Upgrade to GML 3.0-based GIMS system has provided innovative framework in the view of not only construction but also service which has been implemented and applied to previous research and system. Also GIMS channel interface has been implemented to simplify access to GIMS system, and service component of GIMS internals, WFS and WMS, has gotten enhanded and expanded function.

• Cartoon and Animation Studies
• /
• s.19
• /
• pp.127-143
• /
• 2010

The purpose of this study is to aesthetically approach a game, which was popular at home, through microscopic analysis on World of Warcraft. World of Warcraft(hereunder called WOW), which improved a game method of MMORPG that had been popular conventionally at home, from several angles, is suggesting new paradigm of MMORPG game. This study aims to propose new vision on game analysis by approaching this new method from the perspective of player. For this, it divided WOW into shift method, instruction implementation method, and communication configuration method, and analyzed this, respectively, by introducing a concept of empty time, empty space, and non-place, which was borrowed from Zygmunt Bauman's "Liquid Modernity". WOW's shifting method rather extends empty time, that is, the waiting time, contrary to the conventional MMORPG, which used a method of removing. Instead of maximally reducing boring, which becomes disturbance of a game, it is what overwhelmingly enlarges time that needs to be waited, thereby being what induces a sense of time, which a player experiences daily life, to the inside of a game. WOW's instruction implementation method offers one of hugely single map instead of zone-system necessary for map loading in the discontinued form. This minutely implements even a greatly insignificant place in playing a game, thereby stirring up a sense of travel, which explores there in reality. Finally, WOW's community configuration method makes a hunting-targeted group clear, which added a concept of hunting called the raid to the existing gild system. The raid, which is a large party of being bound to the inside of Instant Dungeon, clearly gives a performance role to each of party members, thereby allowing the identity in character to be connected directly to the identity of player. Through this, the player filled the suggested 'space' with experience, thereby being able to change it into 'place' that is significant to an individual.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.37 no.3
• /
• pp.199-208
• /
• 2019

As the number of available satellites increases and technology advances, image information outputs are becoming increasingly diverse and a large amount of data is accumulating. In this study, we propose a change detection method for high-resolution satellite images that uses transfer learning and a deep learning network to overcome the limit caused by insufficient training data via the use of pre-trained information. The deep learning network used in this study comprises convolutional layers to extract the spatial and spectral information and convolutional long-short term memory layers to analyze the time series information. To use the learned information, the two initial convolutional layers of the change detection network are designed to use learned values from 40,000 patches of the ISPRS (International Society for Photogrammertry and Remote Sensing) dataset as initial values. In addition, 2D (2-Dimensional) and 3D (3-dimensional) kernels were used to find the optimized structure for the high-resolution satellite images. The experimental results for the KOMPSAT-3A (KOrean Multi-Purpose SATllite-3A) satellite images show that this change detection method can effectively extract changed/unchanged pixels but is less sensitive to changes due to shadow and relief displacements. In addition, the change detection accuracy of two sites was improved by using 3D kernels. This is because a 3D kernel can consider not only the spatial information but also the spectral information. This study indicates that we can effectively detect changes in high-resolution satellite images using the constructed image information and deep learning network. In future work, a pre-trained change detection network will be applied to newly obtained images to extend the scope of the application.

• Journal of Intelligence and Information Systems
• /
• v.25 no.1
• /
• pp.179-196
• /
• 2019

Recently, the "Smart Consumer" has been emerging. He or she is increasingly inclined to search for and purchase products by taking into account personal judgment or expert reviews rather than by relying on information delivered through manufacturers' advertising. This is especially true when purchasing cosmetics. Because cosmetics act directly on the skin, consumers respond seriously to dangerous chemical elements they contain or to skin problems they may cause. Above all, cosmetics should fit well with the purchaser's skin type. In addition, changes in global cosmetics consumer trends make it necessary to study this field. The desire to find one's own individualized cosmetics is being revealed to consumers around the world and is known as "Finding the Holy Grail." Many consumers show a deep interest in customized cosmetics with the cultural boom known as "K-Beauty" (an aspect of "Han-Ryu"), the growth of personal grooming, and the emergence of "self-culture" that includes "self-beauty" and "self-interior." These trends have led to the explosive popularity of cosmetics made in Korea in the Chinese and Southeast Asian markets. In order to meet the customized cosmetics needs of consumers, cosmetics manufacturers and related companies are responding by concentrating on delivering premium services through the convergence of ICT(Information, Communication and Technology). Despite the evolution of companies' responses regarding market trends toward customized cosmetics, there is no "Intelligent Data Platform" that deals holistically with consumers' skin condition experience and thus attaches emotions to products and services. To find the Holy Grail of customized cosmetics, it is important to acquire and analyze consumer data on what they want in order to address their experiences and emotions. The emotions consumers are addressing when purchasing cosmetics varies by their age, sex, skin type, and specific skin issues and influences what price is considered reasonable. Therefore, it is necessary to classify emotions regarding cosmetics by individual consumer. Because of its importance, consumer emotion analysis has been used for both services and products. Given the trends identified above, we judge that consumer emotion analysis can be used in our study. Therefore, we collected and indexed data on consumers' emotions regarding their cosmetics experiences focusing on consumers' language. We crawled the cosmetics emotion data from SNS (blog and Twitter) according to sales ranking ($1^{st}$ to $99^{th}$), focusing on the ample/serum category. A total of 357 emotional adjectives were collected, and we combined and abstracted similar or duplicate emotional adjectives. We conducted a "Consumer Sentiment Journey" workshop to build a "Consumer Sentiment Dictionary," and this resulted in a total of 76 emotional adjectives regarding cosmetics consumer experience. Using these 76 emotional adjectives, we performed clustering with the Self-Organizing Map (SOM) method. As a result of the analysis, we derived eight final clusters of cosmetics consumer sentiments. Using the vector values of each node for each cluster, the characteristics of each cluster were derived based on the top ten most frequently appearing consumer sentiments. Different characteristics were found in consumer sentiments in each cluster. We also developed a cosmetics experience pattern map. The study results confirmed that recommendation and classification systems that consider consumer emotions and sentiments are needed because each consumer differs in what he or she pursues and prefers. Furthermore, this study reaffirms that the application of emotion and sentiment analysis can be extended to various fields other than cosmetics, and it implies that consumer insights can be derived using these methods. They can be used not only to build a specialized sentiment dictionary using scientific processes and "Design Thinking Methodology," but we also expect that these methods can help us to understand consumers' psychological reactions and cognitive behaviors. If this study is further developed, we believe that it will be able to provide solutions based on consumer experience, and therefore that it can be developed as an aspect of marketing intelligence.