• Journal of East-West Nursing Research
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• v.27 no.2
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• pp.153-165
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• 2021

Purpose: The aim of study was to identify ranges of Korean nurses' competency in disaster nursing. Methods: A scoping review was conducted using the Joanna Briggs Institute methodology. The review used information from four databases: RISS, ScienceON, EBSCO Discovery Service, and CINAHL. In this review, key words were 'disaster', 'nurs*', 'competenc*', 'ability' and 'preparedness'. Inclusion and exclusion criteria were identified as strategies to use in this review. The inclusion criteria for this review focused on the following: Korean nurse, articles related to disaster nursing competency, peer-review articles published in the full text in Korean and English. Review articles were excluded. Results: Nineteen studies were eligible for result extraction. A total of 10 categories of disaster nursing competency were identified: Knowledge of disaster nursing, crisis management, disaster preparation, information collection and sharing, nursing record and document management, communication, disaster plan, nursing activities in disaster response, infection management, and chemical, biological, radiation, nuclear, and explosive management. Conclusion: It is necessary to distinguish between Korean nurses' common disaster nursing competency, professional disaster nursing competency, and disaster nursing competency required in nursing practice. Therefore, future research will be needed to explore and describe disaster nursing competency.

• Journal of the Korea Society of Computer and Information
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• v.24 no.3
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• pp.29-39
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• 2019

In this study, we introduce a model that satisfies energy efficiency and economical efficiency by introducing and demonstrating cogeneration generators in industrial complexes using various actual data collected at the site. The proposed model is composed of three scenarios, ie, full - time operation, scenario operated according to demand, and a fusion type. In this study, the power generation profit and surplus thermal energy are measured according to the operation of the generator, and the thermal energy is traded according to the demand of the customer to calculate the profit and loss including the heat and evaluate the economic efficiency. As a result of the study, it is relatively profitable to reduce the generation of the generator under the condition that the electricity rate is low and the gas rate is high, while the basic charge is not increased. On the contrary, if the electricity rate is high and the gas rate is low, The more you start up, the more profit you can see. These results show that even a cogeneration power plant with a low economic efficiency due to a low "spark spread" has sufficient economic value if it can sell more than a certain amount of heat energy from a nearby customer and adjust the applied power through peak management.

• The Journal of Information Systems
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• v.28 no.2
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• pp.73-92
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• 2019

Purpose This study conducted an empirical study on the influence of institutional mechanisms on the formation of customer trust among leading online businesses. This study focused on the construct of PEEIM(Perceived Effectiveness of e-Commerce Institutional Mechanisms) which is the perceived recognition of institutional mechanisms for e-Commerce in general and the construct of PEIS which is the perceived recognition of institutional mechanisms that are implemented by vendors. Design/methodology/approach The online and offline surveys were conducted for the leading online shopping vendors in Korea and 292 data were used for the empirical analysis. The research model was tested using partial least squares structural equation modeling (PLS-SEM) in this study. The full measurement model including the formative second-order constructs was examined with the exploratory factor analysis. The structural model was analyzed via a two-stage approach. To analyze the research model this study used Smart PLS 2.0 program. Findings The findings showed that PEEIM negatively moderates the relationship between satisfaction in vender and trust in vender, but had no moderating effect between trust in vender and repurchase intention. In addition, the institutional mechanisms of vendors(PEIS) have been shown to have a direct impact on the vender's trust.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.6
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• pp.3165-3181
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• 2019

Spherical videos, which are also called 360-degree videos, have become increasingly popular due to the rapid development of virtual reality technology. However, the large amount of data in such videos is a huge challenge for existing transmission system. To use the existing encode framework, it should be converted into a 2D image plane by using a specific projection format, e.g. the equi-rectangular projection (ERP) format. The existing high-efficiency video coding standard (HEVC) can effectively compress video content, but its enormous computational complexity makes the time spent on compressing high-frame-rate and high-resolution 360-degree videos disproportionate to the benefits of compression. Focusing on the ERP format characteristics of 360-degree videos, this work develops a fast decision algorithm for predicting the coding unit depth interval and adaptive mode decision for intra prediction mode. The algorithm makes full use of the video characteristics of the ERP format by dealing with pole and equatorial areas separately. It sets different reference blocks and determination conditions according to the degree of stretching, which can reduce the coding time while ensuring the quality. Compared with the original reference software HM-16.16, the proposed algorithm can reduce time consumption by 39.3% in the all-intra configuration, and the BD-rate increases by only 0.84%.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.8
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• pp.3821-3841
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• 2019

Cloud radio access networks (C-RANs) have been regarded in recent times as a promising concept in future 5G technologies where all DSP processors are moved into a central base band unit (BBU) pool in the cloud, and distributed remote radio heads (RRHs) compress and forward received radio signals from mobile users to the BBUs through radio links. In such dynamic environment, automatic decision-making approaches, such as artificial intelligence based deep reinforcement learning (DRL), become imperative in designing new solutions. In this paper, we propose a generic framework of autonomous cell activation and customized physical resource allocation schemes for energy consumption and QoS optimization in wireless networks. We formulate the problem as fractional power control with bandwidth adaptation and full power control and bandwidth allocation models and set up a Q-learning model to satisfy the QoS requirements of users and to achieve low energy consumption with the minimum number of active RRHs under varying traffic demand and network densities. Extensive simulations are conducted to show the effectiveness of our proposed solution compared to existing schemes.

• Annual Conference of KIPS
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• 2004.05a
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• pp.873-876
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• 2004

사람의 동작을 인식하는 것에 대한 연구는 게임, 유비쿼터스 컴퓨팅 등의 발전에 따라 그 중요성이 증가하고 있다. 그러나, 대부분의 기존 연구에서는 극히 소수의 동작만을 정의하거나 특정 부위의 동작만을 다루므로 실제 응용에 적용하기에는 적합하지 않다. 본 논문에서는 특정 도메인의 사용 없이, 카메라 영상 입력으로 취득된 동작 패턴 정보만을 이용하여 40종 전신 연속 동작을 구분하는 동작인식 방법을 연구하였다. 인식에 사용된 입력 데이터는 동작자 관절들의 위치 및 회전 값들이며, 다수의 동작들을 인식하기 위해서는 기존의 인식 알고리즘들인 특징기반 인식, HMM, 신경망(Neural Network)등을 사용하여 복합적인 인식 엔진을 구성하여야 했다. 입력 데이터별로 적합한 인식 모듈을 거치게 하기 위해서는, 동작에 의한 입력 데이터에서 동작자 움직임의 주요 신체 부위를 추출함으로써 입력 데이터가 해당 그룹의 인식 모듈로 자동적으로 분류되게 하는 방법을 사용한다. 이는 다층의 인식 레이어 중 복잡도가 증가하는 하위 레이어일수록 자동 분류에 의해 걸러진 데이터만을 취급하게 되므로 효과적이다. 전체 실험 결과 단계별로 약 79~97%의 인식률을 보였다. 이는 향후 특정 컨텍스트 정보와 결합할 때 매우 높은 인식률을 기대할 수 있게 하는 수치이다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.1961-1974
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• 2019

In this letter, a harmonic-mean-based dual-antenna selection scheme at relay node is proposed in two-way relaying networks (TWRNs). With well-designed distributed orthogonal concatenated Alamouti space-time block code (STBC), a dual-antenna selection problem based on the instantaneous achievable sum-rate criterion is formulated. We propose a low-complexity selection algorithm based on the harmonic-mean criterion with linearly complexity $O(N_R)$ rather than the directly exhaustive search with complexity $O(N^2_R)$. From the analysis of network outage performance, we show that the asymptotic diversity gain function of the proposed scheme achieves as $1/{\rho}{^{N_R-1}}$, which demonstrates one degree loss of diversity order compared with the full diversity. This slight performance gap is mainly caused by sacrificing some dual-antenna selection freedom to reduce the algorithm complexity. In addition, our proposed scheme can obtain an extra coding gain because of the combination of the well-designed orthogonal concatenated Alamouti STBC and the corresponding dual-antenna selection algorithm. Compared with the common-used selection algorithms in the state of the art, the proposed scheme can achieve the best performance, which is validated by numerical simulations.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.749-751
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• 2016

Due to the advent of virtual reality, the past communication method using images and video through the expansion into three-dimensional space has been provided more realistic and seamless interaction environment. Unlike reality, virtual reality is under a full human control and due to this benefit can be used as a substitute for reality therefore medicine and healthcare area has attracted attention in the prevention and treatment of dementia utilizing virtual reality. The research provided in this paper is aimed to design a virtual reality-based mild cognitive impairment prevention training system, focusing on the Symptoms of Alzheimer's precursor, mild cognitive impairment.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.719-723
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• 2014

Research acitivities of university scholars greatly contribute to the development of research literature in their own areas, thereby playing an essential role of accomplishing national values. In Korea, university researchers conduct studies focusing on basic and fundamental research with their great performance disseminated for industry competence of the country. In this study, we examine research fund and performance for drawing implications for future directions.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.12
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• pp.4664-4681
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• 2020

Modulation recognition (MR) plays a key role in cognitive radar, cognitive radio, and some other civilian and military fields. While existing methods can identify the signal modulation type by extracting the signal characteristics, the quality of feature extraction has a serious impact on the recognition results. In this paper, an end-to-end MR method based on long short-term memory (LSTM) and the gated recurrent unit (GRU) is put forward, which can directly predict the modulation type from a sampled signal. Additionally, the sliding window method is applied to fast-changing mixed-modulation signals for which the signal modulation type changes over time. The recognition accuracy on training datasets in different SNR ranges and the proportion of each modulation method in misclassified samples are analyzed, and it is found to be reasonable to select the evenly-distributed and full range of SNR data as the training data. With the improvement of the SNR, the recognition accuracy increases rapidly. When the length of the training dataset increases, the neural network recognition effect is better. The loss function value of the neural network decreases with the increase of the training dataset length, and then tends to be stable. Moreover, when the fast-changing period is less than 20ms, the error rate is as high as 50%. As the fast-changing period is increased to 30ms, the error rates of the GRU and LSTM neural networks are less than 5%.