• Journal of the Economic Geographical Society of Korea
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• v.25 no.1
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• pp.1-22
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• 2022

The purpose of this study is to analyze key concepts of Entrepreneurial Ecosystems and to suggest implications for economic geographical studies. The definition and concept of entrepreneurship as well as changes of its research trends were examined. By combining entrepreneurship and geography, Entrepreneurial Ecosystems, which have recently emerged as important concepts and theories, were examined with the focus on the key concepts such as 'actors and factors', 'productive' and 'territory'. It is important that the individual, organizational and institutional components such as entrepreneurs, start-ups, existing companies, institutions and cultural elements are interconnected to build communities through 'entrepreneurial recycling'. Entrepreneurial Ecosystems support to create innovative high-growth start-ups based on entrepreneurial culture in the local region. Despite conceptual limitations, theoretical and empirical analyses should be conducted from economic geographical perspectives in order to reveal the geographical and spatial processes of productive entrepreneurship and to suggest policy implications for region-based start-up ecosystems.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.4
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• pp.556-561
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• 2022

In this paper, we present a block media communication (BMC) system which employs powerline communication to the equipments used in the welding process for ship-assembly and uses metal block as a communication medium. Inductive couplers are installed on digital feeder and pin jig. Information signal is added to the current generated by the welding gun, and applied to the block. When the welding operation starts, information generated in the field is transmitted to the monitoring server in real-time. The field test on the BMC system confirms that the transmitted data are correctly received at the server. Since the proposed system can be built without any changes to the existing welding process, it is helpful to increase competitiveness of the shipbuilding industry through smart factory of shipyards. It is also possible to quickly respond to emergency situations that may occur to workers in an electromagnetic wave shielding environment or a closed space, the effect of preventing industrial accidents will be great.

• Journal of Internet Computing and Services
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• v.23 no.1
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• pp.87-93
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• 2022

Since 99% of PCs operating in the defense domain use the Windows operating system, detection and response of Window-based malware is very important to keep the defense cyberspace safe. This paper proposes a model capable of detecting malware in a Windows PE (Portable Executable) format. The detection model was designed with an emphasis on rapid update of the training model to efficiently cope with rapidly increasing malware rather than the detection accuracy. Therefore, in order to improve the training speed, the detection model was designed based on a Bidirectional LSTM (Long Short Term Memory) network that can detect malware with minimal sequence data without complicated pre-processing. The experiment was conducted using the EMBER2018 dataset, As a result of training the model with feature sets consisting of three type of sequence data(Byte-Entropy Histogram, Byte Histogram, and String Distribution), accuracy of 90.79% was achieved. Meanwhile, it was confirmed that the training time was shortened to 1/4 compared to the existing detection model, enabling rapid update of the detection model to respond to new types of malware on the surge.

• Journal of the Korea Society of Computer and Information
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• v.27 no.4
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• pp.19-26
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• 2022

With the recent development of intelligent transportation systems, car license plate recognition systems are being used in various fields. Such systems need to guarantee real-time performance to recognize the license plate of a driving car. Also, they should keep a high recognition rate even in problematic situations such as small license plates in low-resolution and unclear image due to distortion. In this paper, we propose a real-time car license plate recognition system that improved processing speed using object detection algorithm based on anchor-free method and text recognition algorithm based on Convolutional Neural Network(CNN). In addition, we used Spatial Transformer Network to increase the recognition rate on the low resolution or distorted images. We confirm that the proposed system is faster than previously existing car license plate recognition systems and maintains a high recognition rate in a variety of environment and quality images because the proposed system's recognition rate is 93.769% and the processing speed per image is about 0.006 seconds.

• The Journal of the Korea Contents Association
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• v.22 no.10
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• pp.103-113
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• 2022

As globalization progresses and localization takes place, interest in local culture is increasing. In line with this trend, the Cultural Heritage Administration has been promoting the Cultural Heritage Night Tour Project as a night-type cultural property tourism content since 2016. Cultural property nightlife, part of the regional regeneration project, creates new added value by converging and combining various historical and cultural-related contents centered on local cultural heritage. Although the "cultural nightlife" has been greatly activated, it is judged that changes are needed to continue. This is because fixed nightlife programs are positive in terms of establishing a nationwide network, but there is a limitation in that they cannot be standardized and expanded to various forms. Therefore, in this study, the meaning and limitations of nightlife programs were identified, and cognitive theory applicable to nightlife programs was considered. Through this process, it was confirmed that cognitive poetry's 'circular for dynamic semantic composition', 'surreal foreground', and 'adventures in time and space' can be applied to nightlife programs. As a result of combining cognitive poetry with nightlife programs, it was possible to present a strategy for implementing nightlife programs differentiated from existing nightlife programs.

• The Journal of the Korea Contents Association
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• v.22 no.9
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• pp.104-112
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• 2022

The pandemic caused by the COVID-19 virus, which has lasted for the past three years, has changed society and the way people live in many ways. These changes also affect cyberspace, so the pre-pandemic information security model and standards have limitations when applied to the current situation. In this paper, a new method to improve the information security model of public institutions was proposed in consideration of various situations in the new normal era. In other words, through the proposed information security model, the possibility of external intrusion is blocked in advance through the policy and technical supplementation of remote work, which is a weakness of the existing information security operation of public institutions. Also, how to prevent abnormal authentication attempts by building a secure VPN environment, how to prevent social engineering cyber attacks targeting fear and uncertainty caused by COVID-19, and how to use a smooth network and create a remote work environment. For this purpose, methods for securing service availability were additionally presented.

• Journal of the Korea Computer Graphics Society
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• v.27 no.3
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• pp.1-11
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• 2021

Slow sync is a photography technique where a user takes an image with long exposure and a camera flash to enlighten the foreground and background. Unlike short exposure with flash and long exposure without flash, slow sync guarantees the bright foreground and background in the dim environment. However, taking a slow sync image with a smartphone is difficult because the smartphone camera has continuous and weak flash and can not turn on flash if the exposure time is long. This paper proposes a deep learning method that input is a short exposure flash image and output is a slow sync image. We present a deep learning network with a weight map for spatially varying enlightenment. We also propose a dataset that consists of smartphone short exposure flash images and slow sync images for supervised learning. We utilize the linearity of a RAW image to synthesize a slow sync image from short exposure flash and long exposure no-flash images. Experimental results show that our method trained with our dataset synthesizes slow sync images effectively.

• Journal of the Korea Society of Computer and Information
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• v.27 no.8
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• pp.143-149
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• 2022

Since patent documents contain detailed results of research and development technologies, many studies on various patent analysis methods for effective technology analysis have been conducted. In particular, research on quantitative patent analysis by statistics and machine learning algorithms has been actively conducted recently. The most used patent data in quantitative patent analysis is technology keywords. Most of the existing methods for analyzing the keyword data were models based on the Gaussian probability distribution with random variable on real space from negative infinity to positive infinity. In this paper, we propose a model using gamma probability distribution to analyze the frequency data of patent keywords that can theoretically have values from zero to positive infinity. In addition, in order to determine the regression equation of the gamma-based regression model, two-mode network is constructed to visualize the technological association between keywords. Practical patent data is collected and analyzed for performance evaluation between the proposed method and the existing Gaussian-based analysis models.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.3
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• pp.99-104
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• 2022

In the age of convergent media, traditional media and network media are highly integrated, and benefits are shared, which promotes the increase of traditional culture communication channels, the change of communication methods, and the change of the mode of interaction with audiences. This article analyzes the difficulties of traditional culture dissemination by enumerating some excellent cultural programs in China. At the same time, combined with the current situation of convergence media, it discusses how to transform invisible traditional culture into visual digital content, and make it widely disseminated by means of convergence media. It provides reference for the development of traditional culture, and has enlightening significance for creating high-quality cultural programs and spreading mainstream culture.

• Journal of Broadcast Engineering
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• v.27 no.4
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• pp.487-498
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• 2022

Depth map is an image that contains distance information in 3D space on a 2D plane and is used in various 3D vision tasks. Many existing depth estimation studies mainly use narrow FoV images, in which a significant portion of the entire scene is lost. In this paper, we propose a technique for generating 360° omnidirectional RGBD images from a sparse set of narrow FoV images. The proposed generative adversarial network based image generation model estimates the relative FoV for the entire panoramic image from a small number of non-overlapping images and produces a 360° RGB and depth image simultaneously. In addition, it shows improved performance by configuring a network reflecting the spherical characteristics of the 360° image.