• Journal of the Korea Society of Computer and Information
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• v.19 no.11
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• pp.53-61
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• 2014

In this paper, we propose a method using an image received by the depth camera in order to separate the wall in a three-dimensional space indoor environment. Results of the paper may be used to provide valuable information on the three-dimensional space. For example, they may be used to recognize the indoor space, to detect adjacent objects, or to project a projector on the wall. The proposed method first detects a normal vector at each point by using the three dimensional coordinates of points. The normal vectors are then clustered into several groups according to similarity. The RANSAC algorithm is applied to separate out planes. The domain knowledge helps to determine the wall among planes in an indoor environment. This paper concludes with experimental results that show performance of the proposed method in various experimental environment.

• Hwankyungkyoyuk
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• v.13 no.1
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• pp.1-13
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• 2000

The purpose of this study is to formulate the direction lot improvement of the curriculum on environmental education teacher training. The results of this study are summarized as follows: First, the nature of the courses related to subject matter education should be changed from the course of teaching profession into the course of special study, Second, the combination of the courses related to environmental education and environmental science is needed, Third, the curriculum should sufficiently include the contents of the 7th curriculum, Fourth, the curriculum should contain the courses of environmental science which can help the pre-service teachers to understand the fundamentals and concepts of ecology, This curriculum should also include the courses which can improve the pre-service teacher's ability to teach for the development of student's affirmative environmental value and attitude, Fifth, the curriculum should include the courses which are useful for the pre-service teachers to learn teaching method such as case study and simulation for the education of environmental knowledge and of cognitive domain about environmental issues. Sixth, the curriculum should reflect the contents of the regulation for teacher certificate which was renewed in Jan. of 2000.

• International Journal of Computer Science & Network Security
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• v.21 no.8
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• pp.1-12
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• 2021

An operation of an organization is currently using a digital environment which opens to potential cyber-attacks. These phenomena become worst as the cyberattack landscape is changing rapidly. The impact of cyber-attacks varies depending on the scope of the organization and the value of assets that need to be protected. It is difficult to assess the damage to an organization from cyberattacks due to a lack of understanding of tools, metrics, and knowledge on the type of attacks and their impacts. Hence, this paper aims to identify domains and sub-domains of cyber-attack taxonomy to facilitate the understanding of cyber-attacks. Four phases are carried in this research: identify existing cyber-attack taxonomy, determine and classify domains and sub-domains of cyber-attack, and construct the enhanced cyber-attack taxonomy. The existing cyber-attack taxonomies are analyzed, domains and sub-domains are selected based on the focus and objectives of the research, and the proposed taxonomy named AVOIDITALS Cyber-attack Taxonomy is constructed. AVOIDITALS consists of 8 domains, 105 sub-domains, 142 sub-sub-domains, and 90 other sub-sub-domains that act as a guideline to assist administrators in determining cyber-attacks through cyber-attacks pattern identification that commonly occurred on digital infrastructure and provide the best prevention method to minimize impact. This research can be further developed in line with the emergence of new types and categories of current cyberattacks and the future.

• Journal of Korea Multimedia Society
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• v.21 no.11
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• pp.1305-1316
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• 2018

Graphical user interface(GUI) has a very important role to interact with software users. However, designing and coding of GUI are tedious and pain taking processes. In many studies, the researchers are trying to convert GUI elements or widgets to code or describe formally their structures by help of domain knowledge of stochastic methods. In this paper, we propose the GUI elements detection approach based on object detection strategy using deep neural networks(DNN). Object detection with DNN is the approach that integrates localization and classification techniques. From the experimental result, if we selected the appropriate object detection model, the results can be used for automatic code generation from the sketch or capture images. The successful GUI elements detection can describe the objects as hierarchical structures of elements and transform their information to appropriate code by object description translator that will be studied at future.

• BMB Reports
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• v.51 no.12
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• pp.613-622
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• 2018

RNA helicases DDX5 and DDX17 are multitasking proteins that regulate gene expression in different biological contexts through diverse activities. Special attention has long been paid to their function as coregulators of transcription factors, providing insight about their functional association with a number of chromatin modifiers and remodelers. However, to date, the variety of described mechanisms has made it difficult to understand precisely how these proteins work at the molecular level, and the contribution of their ATPase domain to these mechanisms remains unclear as well. In light of their association with long noncoding RNAs that are key epigenetic regulators, an emerging view is that DDX5 and DDX17 may act through modulating the activity of various ribonucleoprotein complexes that could ensure their targeting to specific chromatin loci. This review will comprehensively describe the current knowledge on these different mechanisms. We will also discuss the potential roles of DDX5 and DDX17 on the 3D chromatin organization and how these could impact gene expression at the transcriptional and post-transcriptional levels.

• BMB Reports
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• v.54 no.9
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• pp.451-457
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• 2021

Over the last decades, research has focused on the role of pleckstrin homology (PH) domain leucine-rich repeat protein phosphatases (PHLPPs) in regulating cellular signaling via PI3K/Akt inhibition. The PKB/Akt signaling imbalances are associated with a variety of illnesses, including various types of cancer, inflammatory response, insulin resistance, and diabetes, demonstrating the relevance of PHLPPs in the prevention of diseases. Furthermore, identification of novel substrates of PHLPPs unveils their role as a critical mediator in various cellular processes. Recently, researchers have explored the increasing complexity of signaling networks involving PHLPPs whereby relevant information of PHLPPs in metabolic diseases was obtained. In this review, we discuss the current knowledge of PHLPPs on the well-known substrates and metabolic regulation, especially in liver, pancreatic beta cell, adipose tissue, and skeletal muscle in relation with the stated diseases. Understanding the context-dependent functions of PHLPPs can lead to a promising treatment strategy for several kinds of metabolic diseases.

• ETRI Journal
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• v.43 no.1
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• pp.40-52
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• 2021

DNS (Domain Name System) tunnels almost obscure the true network activities of users, which makes it challenging for the gateway or censorship equipment to identify malicious or unpermitted network behaviors. An efficient way to address this problem is to conduct a temporal-spatial analysis on the tunnel traffic. Nevertheless, current studies on this topic limit the DNS tunnel to those with a single protocol, whereas more than one protocol may be used simultaneously. In this paper, we concentrate on the refined identification of two protocols mixed in a DNS tunnel. A feature set is first derived from DNS query and response flows, which is incorporated with deep neural networks to construct a regression model. We benchmark the proposed method with captured DNS tunnel traffic, the experimental results show that the proposed scheme can achieve identification accuracy of more than 90%. To the best of our knowledge, the proposed scheme is the first to estimate the ratios of two mixed protocols in DNS tunnels.

• Electronics and Telecommunications Trends
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• v.36 no.1
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• pp.109-119
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• 2021

The Korean government recently announced a plan of the Carbon Neutral policy in addition to the Green New Deal of the Korean New Deal and the Renewable Energy 3020. The energy sector is entering the era of major transformation involving the expansion of decarbonization, decentralization, and digitalization. DNA-oriented ICT technology will be incorporated into the sector. Further, new energy industries and services are being realized via efficient and smart operation and by appropriately managing the energy-environment changes. Recently, ETRI presented a technology development map for 2035 comprising 12 new concepts in four major fields(personal, social, industrial and public) of national intelligence. This map includes the concept of "Energy Maestro" associated with the field of public intelligence for human sustainability. This paper briefly introduces this concept and ETRI's Energy-R&D status. Based on the domain knowledge and the experience acquired through the R&D, ETRI will lead to a new paradigm with respect to the creation of new energy services and industries via the incorporation of the new ICT technologies including AI and big-data into the energy sector.

• International Journal of Contents
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• v.17 no.1
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• pp.1-10
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• 2021

Visual analytics is an emerging research field that combines the strength of electronic data processing and human intuition-based social background knowledge. This study demonstrates useful visual analytics with Tableau in conjunction with semantic network analysis using examples of sentiment flow and strategic communication strategies via Twitter in a blockchain domain. We comparatively investigated the sentiment flow over time and language usage patterns between companies with a good reputation and firms with a poor reputation. In addition, this study explored the relations between reputation and marketing communication strategies. We found that cryptocurrency firms more actively produced information when there was an increased public demand and increased transactions and when the coins' prices were high. Emotional language strategies on social media did not affect cryptocurrencies' reputations. The pattern in semantic representations of keywords was similar between companies with a good reputation and firms with a poor reputation. However, the reputable firms communicated on a wide range of topics and used more culturally focused strategies, and took more advantages of social media marketing by expanding their outreach to other social media networks. The visual big data analytics provides insights into business intelligence that helps informed policies.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.4
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• pp.1166-1186
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• 2022

Artistic font design has become an integral part of visual media. However, without prior knowledge of the font domain, it is difficult to create distinct font styles. When the number of characters is limited, this task becomes easier (e.g., only Latin characters). However, designing CJK (Chinese, Japanese, and Korean) characters presents a challenge due to the large number of character sets and complexity of the glyph components in these languages. Numerous studies have been conducted on automating the font design process using generative adversarial networks (GANs). Existing methods rely heavily on reference fonts and perform font style conversions between different fonts. Additionally, rather than capturing style information for a target font via multiple style images, most methods do so via a single font image. In this paper, we propose a network architecture for generating multilingual font sets that makes use of geometric structures as content. Additionally, to acquire sufficient style information, we employ multiple style images belonging to a single font style simultaneously to extract global font style-specific information. By utilizing the geometric structural information of content and a few stylized images, our model can generate an entire font set while maintaining the style. Extensive experiments were conducted to demonstrate the proposed model's superiority over several baseline methods. Additionally, we conducted ablation studies to validate our proposed network architecture.