• International Journal of Advanced Culture Technology
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• v.7 no.2
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• pp.13-18
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• 2019

Comorbidity isthe simultaneous presence of two chronic diseases or conditions in a patient. As part of a larger research study, the aims of this study were to explore comorbid conditions in intensive care unit (ICU) patients and to compare the comorbidity across different demographic groups, and to determine what comorbid health problems coexisted in the patients with hospital-acquired pressure injury (HAPI). The average number of comorbid conditions was 6.4 with range from 0-20 in the ICU patients. African American patients had significantly more comorbid health problems than other race/ethnicity groups. Asian and Hispanic female patients showed higher comorbidity than male patients across age. The patients with HAPIs had significantly more comorbid health problems than the patients without HAPIs -- the average numbers were almost two-fold. We found comorbid health problems that existed with HAPI in ICU patients. 'Other diseases of lung' and 'Disorders of fluid, electrolyte, and acid-base balance' were most frequently coexisting health problems in the ICU patients with HAPI. Exploratory plots are helpful to discover patterns or hypotheses relevant to clinical management in critical care. Inclusion of patients' comorbid health problems to ICU HAPI risk assessment may be helpful. Identification of patients at a high risk for the development of HAPI and the early preventative interventions can help reduce length of stay as well as costly complications.

• Electronics and Telecommunications Trends
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• v.34 no.4
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• pp.43-54
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• 2019

Currently, a majority of artificial intelligence is used to secure big data; however, it is concentrated in a few of major companies. Therefore, automatic data augmentation and efficient learning algorithms for small-scale data will become key elements in future artificial intelligence competitiveness. In addition, it is necessary to develop a technique to learn meanings, correlations, and time-related associations of complex modal knowledge similar to that in humans and expand and transfer semantic prediction/knowledge inference about unknown data. To this end, a neural memory model, which imitates how knowledge in the human brain is processed, needs to be developed to enable knowledge expansion through modality cooperative learning. Moreover, declarative and procedural knowledge in the memory model must also be self-developed through human interaction. In this paper, we reviewed this essential methodology and briefly described achievements that have been made so far.

• International journal of advanced smart convergence
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• v.8 no.1
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• pp.159-165
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• 2019

'4th Industrial Revolution' is accelerating as a core part of creating new growth engines and enhancing competitiveness of businesses. The fourth industrial revolution means the transformation of society and industries that are brought by IoT (Internet of Things), big data analysis, AI (Artificial Intelligence), and robot technology. Information and Communication Technology (ICT), which is a major factor, is affecting production and manufacturing systems and as ICT technologies become more advanced, intelligent information technology is generally utilized in all areas of society, leading to hyper-connected society where new values are created and developed. ICT technology is not just about connecting devices and systems and making smart, it is about constantly converging and harmonizing new technologies in a number of fields and driving innovation and change. It is no exception to the agro-fisheries trade. In particular, ICT technology is applied to the agricultural sector, reducing labor, providing optimal environment for crops, and increasing productivity. Due to the nature of agriculture, which is a labor-intensive industry, it is predicted that the ripple effects of ICT technologies will become bigger. We are expected to use the Smart Concentration using ICT convergence technology as a useful resource for changing smart farms, and to help develop new service markets.

• Journal of Platform Technology
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• v.6 no.4
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• pp.49-58
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• 2018

Complex disasters make greater damage and higher losses unexpected than the past. To prevent these disasters, it needs to prepare a plan for handling unexpected results. Especially an accident at a facility like an atomic power plant makes a big problem cause of climate change. A simulation needs to do preliminary researches based on diverse situations. In this research we define the basic component techniques to design and implement the disaster management system. Basically a hierarchical system design method is to build on the resources provided from high performance computing(HPC) and large-scale storage systems. To develop the system, it is considered middleware as well as application studies, data studies and decision making services in convergence areas.

• Journal of the Korea Society of Computer and Information
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• v.24 no.6
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• pp.125-133
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• 2019

This study aimed to investigate the political system related to the Electronic Government Law by analyzing the process of the common initiative of the law. To achieve the goal, this study applied the method of social analysis and sugessted the proper role of the assembly for realizing the electronic government and its control. The data were gathered from the bill information service of the national assembly. Netminer 4.0 was used for refining and analyzing data. The results are as follows. First, by analyzing three centrality(degree, betweenness, and eigenvector) of assembly member, the network effect of the powered party and reelected members were revealed as strong in the network. Second, through the component analysis, 5 sub-network has shown in total. The sub-networks showed two distinctive difference between two big parties. By the difference, members in two parties showed different characteristics in constituting communities and the effect of the powered party revealed as strong and clear. Based on the result, this study demonstrated the necessity of social solidarity rather than solipsism in committing common initiative. And a chronological research is need to anlayze $18^{th}$ and $19^{th}$ assembly to verify the effect of the powered party in prospect study.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.01a
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• pp.359-360
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• 2019

본 논문에서는 2018년에 성횡한 악성코드에 대한 피해 사례를 살펴본 후 이를 적극적으로 대응하기 위한 방안을 살펴본다. 특히 가상통화 거래소에 대한 해킹 사고 및 가상화폐에 대한 지속적인 해킹 시도가 탐지되면서 관련 소식들이 언론에 지속적으로 보도되었다. 또한 이와 관련하여 PC 및 서버 자원을 몰래 훔쳐 가상통화 채굴에 사용하는 크립토재킹 공격기법도 함께 주목받았다. 랜섬웨어 부문은 갠드크랩 관련 보도가 대부분을 차지할 정도로 국내에서 지속적으로 이슈가 되었다. 또한 미국 법무부에서 최초로 북한 해커조직의 일원을 재판에 넘기면서 해커 그룹에 대한 관심이 집중되기도 했다. 2018년 전반적으로 이러한 가상통화 거래소 해킹, 크립토재킹, 랜섬웨어, 해커 그룹의 4가지 키워드를 도출하였으며, 이 중 해커 그룹은 북한과 중국의 경우를 나누어 총 5가지 주제를 통해 악성코드에 대한 주요 이슈들을 살펴본다. 본 논문에서는 이러한 악성코드의 공격을 근본적으로 해결할 수 있는 방안으로 클라이언트 측에 USB형태의 BBS(Big Bad Stick) 하드웨어를 통하여 제안하는 환경을 제안하고 안전한 서비스가 제공됨을 증명하여 본 연구가 새로운 보안성을 갖춘 시스템임을 보인다.

• Journal of Convergence for Information Technology
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• v.9 no.8
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• pp.1-8
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• 2019

Dialog system is becoming a new dominant interaction way between human and computer. It allows people to be provided with various services through natural language. The dialog system has a common structure of a pipeline consisting of several modules (e.g., speech recognition, natural language understanding, and dialog management). In this paper, we tackle a task of domain classification for the natural language understanding module by employing machine learning models such as convolutional neural network and random forest. For our dataset of seven service domains, we showed that the random forest model achieved the best performance (F1 score 0.97). As a future work, we will keep finding a better approach for domain classification by investigating other machine learning models.

• Journal of Korea Society of Digital Industry and Information Management
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• v.15 no.3
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• pp.1-14
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• 2019

The 4th Industrial Revolution, intelligent automobile application technology is evolving beyond the limit of the mobile device to a variety of application software and multi-media collective technology with big data-based AI(artificial intelligence) technology. with the recent commercialization of 5G mobile communication service, artificial intelligent automobile technology, which is a fusion of automobile and IT technology, is evolving into more intelligent automobile service technology, and each multimedia platform service and application developed in such distributed environment is being developed Accordingly, application software technology developed with a single system SoC of a portable terminal device through various service technologies is absolutely required. In this paper, smart device design for ontology design of intelligent automobile open platform enables to design intelligent automobile middleware software design technology such as Android based SVC Codec and real time video and graphics processing that is not expressed in single ASIC application software technology as SoC based application designWe have experimented in smart device environment through researches, and newly designed service functions of various terminal devices provided as open platforms and application solutions in SoC environment and applied standardized interface analysis technique and proved this experiment.

• IEMEK Journal of Embedded Systems and Applications
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• v.14 no.5
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• pp.249-258
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• 2019

In the cyber-physical system, big data collected from numerous sensors and IoT devices is transferred to the Cloud for processing and analysis. When transferring data to the Cloud, merging data into one single file is more efficient than using the data in the form of split files. However, current merging and splitting operations are performed at the user-level and require many I / O requests to memory and storage devices, which is very inefficient and time-consuming. To solve this problem, this paper proposes kernel-level partitioning and combining operations. At the kernel level, splitting and merging files can be done with very little overhead by modifying the file system metadata. We have designed the proposed algorithm in detail and implemented it in the Linux Ext4 file system. In our experiments with the real Cloud storage system, our technique has achieved a transfer time of up to only 17% compared to the case of transferring split files. It also confirmed that the time required can be reduced by up to 0.5% compared to the existing user-level method.

• The Bulletin of The Korean Astronomical Society
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• v.43 no.2
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• pp.46.2-46.2
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• 2018

The active region NOAA AR 12673 is the most flare productive active region in the solar cycle 24. On 2017 September 07, it produced an X1.3 flare, three M-class, and several C-class flares. We successfully observed several C-class flares from 16:50 UT to 22:00 UT using the 1.6m Goode Solar Telescope (GST; formerly NST) at Big Bear Solar Observatory (BBSO). The GST provides us with unprecedented high-resolution data of the Sun since 2009. Interestingly, we observed the active region in He I D3 and 10830 lines simultaneously. The data shows several interesting features: (1) D3 emission seems to be much weaker than 10830 emission around 21:29 UT; (2) a small loop seen in 10830 is moving upward and is brightened around 21:16 UT, but it is not clear in D3; (3) there are waves in the penumbra seen in 10830 line center; (4) there is a jet with twisting motion. In this presentation, we will give the results of our analysis and interpretations.