• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.6
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• pp.506-514
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• 2022

This paper is about developing an intravenous injection management system that can provide nurses with information related to intravenous injection in real-time to compensate for possible instability factors during intravenous injection. The intravenous injection management system consists of an app-based user S/W and a web-based administrator S/W. User S/W is implemented to provide users with the ability to identify patients who need intravenous injection through smartphones, tablet PCs, and nursing PDAs, recognize information codes given to patients, and enter and share treatment contents and treatment items after intravenous injection. As a result of intravenous injection treatment uploaded through the user app, the manager S/W can check the records of intravenous injection treatment items, perform user management functions, emergency notification registration and management functions, and data upload functions. The implemented system has not yet been tested on the EMR system used in the actual hospital. Therefore, through further research, S/W will be optimized and actual environmental application tests will be conducted through cooperation with hospitals.

• Journal of Science Education
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• v.46 no.1
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• pp.17-29
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• 2022

The purpose of this study is to look qualitatively into how efficiently and reasonably a computer can learn themes related to the Nature of Science (NOS). In this regard, a corpus has been constructed focusing on literature (920 abstracts) related to NOS, and factors of the optimized Word2Vec (CBOW, Skip-gram) were confirmed. According to the four dimensions (Inquiry, Thinking, Knowledge and STS) of NOS, the comparative evaluation on the word-level word embedding was conducted. As a result of the study, according to the previous studies and the pre-evaluation on performance, the CBOW model was determined to be 200 for the dimension, five for the number of threads, ten for the minimum frequency, 100 for the number of repetition and one for the context range. And the Skip-gram model was determined to be 200 for the number of dimension, five for the number of threads, ten for the minimum frequency, 200 for the number of repetition and three for the context range. The Skip-gram had better performance in the dimension of Inquiry in terms of types of words with high similarity by model, which was checked by applying it to the four dimensions of NOS. In the dimensions of Thinking and Knowledge, there was no difference in the embedding performance of both models, but in case of words with high similarity for each model, they are sharing the name of a reciprocal domain so it seems that it is required to apply other models additionally in order to learn properly. It was evaluated that the dimension of STS also had the embedding performance that was not sufficient to look into comprehensive STS elements, while listing words related to solution of problems excessively. It is expected that overall implications on models available for science education and utilization of artificial intelligence could be given by making a computer learn themes related to NOS through this study.

• Journal of Korea Entertainment Industry Association
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• v.14 no.7
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• pp.161-173
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• 2020

In-depth interview in the field of hospitality industry services was conducted in COVID- 19. Introduction of kiosks for non-face-to-face services using untact technology, reservation, pay systems, self-service, service improvement using room service should be carried out. It is also necessary to implement Instagram, Facebook, YouTube, P-blogs, online broadcasting and live commerce through the establishment of m-channel system through untact marketing sales channels in the hospitality industry now that the product composition to solve the pro -blem of untact marketing is drawing attention due to diversification of online sales channe -ls. Now, the recognition of important elements of service education and a establishment of differentiated system of untact marketing, expansion of untact sale channel, implementation of non-face-to-face counseling service and introduction of pre-booking, telecommuting were recognized as urgent parts. In particular, a service differentiation and importance of human services, which were recognized free of charge, have re-recognized as premium, and quality service aspect of the hospitality industry in untact and the direction to diversify marketing channels are presented.

• Journal of Intelligence and Information Systems
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• v.28 no.4
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• pp.1-25
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• 2022

After the first Covid-19 confirmed case occurred in Korea in January 2020, interest in personal transportation such as public bicycles not public transportation such as buses and subways, increased. The demand for 'Ddareungi', a public bicycle operated by the Seoul Metropolitan Government, has also increased. In this study, a demand prediction model of a GRU(Gated Recurrent Unit) was presented based on the rental history of public bicycles by time zone(2019~2021) in Seoul. The usefulness of the GRU method presented in this study was verified based on the rental history of Around Exit 1 of Yeouido, Yeongdengpo-gu, Seoul. In particular, it was compared and analyzed with multiple linear regression models and recurrent neural network models under the same conditions. In addition, when developing the model, in addition to weather factors, the Seoul living population was used as a variable and verified. MAE and RMSE were used as performance indicators for the model, and through this, the usefulness of the GRU model proposed in this study was presented. As a result of this study, the proposed GRU model showed higher prediction accuracy than the traditional multi-linear regression model and the LSTM model and Conv-LSTM model, which have recently been in the spotlight. Also the GRU model was faster than the LSTM model and the Conv-LSTM model. Through this study, it will be possible to help solve the problem of relocation in the future by predicting the demand for public bicycles in Seoul more quickly and accurately.

• The Journal of the Korea Contents Association
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• v.22 no.2
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• pp.22-34
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• 2022

This study examines the forms and current status of online performance content production in the field of the performing arts through diversified video media platforms. For this, it studied the leading case of Cirque du Soleil Entertainment and analyzed the unique brand value innovation elements of Cirque du Soleil, the background and current status of the digital hub platform of "Cirque Connect", and its various sub-contents that have diversified original contents. Digital platform applications and sub-content production in the field of the performing arts require an understanding of the needs of the public, who are familiar with media content appreciation, and strategic planning that takes into consideration everything from the initial stages of performance planning to the creation of varied sub-contents. This will promote the improvement of sub-content quality and increase the product value of digital contents in the performing arts through distinctions made from other various forms of cultural and artistic contents. environments in which information from various perspectives related to performance works can easily be accessed through online platforms will enhance the popularity of the performing arts field and allow the performing arts industry to expand its base in rapidly changing cultural enjoyment methods. For the performing arts field to be competitive within cultural trends that are being diversified, the most important tasks to be completed are gaining brand value innovation that enhances the artistic and cultural value of performance works and based on this, producing various sub-contents.

• Journal of the Korea Society for Simulation
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• v.18 no.4
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• pp.197-206
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• 2009

The medical information system is an effective medical diagnosis assistance system which offers an environment in which medial images and diagnosis information can be shared. However, this system can only stored and transmitted information without other functions. To resolve this problem and to enhance the efficiency of diagnostic activities, a medical image classification and retrieval system is necessary. The medical image classification and retrieval system can improve efficiency in a medical diagnosis by providing disease-related images and can be useful in various medical practices by checking diverse cases. However, it is difficult to understand the meanings contained in images because the existing image classification and retrieval system has handled superficial information only. Therefore, a medical image classification system which can classify medical images by analyzing the relation among the elements of the image as well as the superficial information has been required. In this paper, we propose the method for learning and classification of brain MRI, in which the superficial information as well as the spatial information extracted from images are used. The superficial information of images, which is color, shape, etc., is called low-level image information and the logical information of the image is called high-level image information. In extracting both low-level and high-level image information in this paper, the anatomical names and structure of the brain have been used. The low-level information is used to give an anatomical name in brain images and the high-level image information is extracted by analyzing the relation among the anatomical parts. Each information is used in learning and classification. In an experiment, the MRI of the brain including disease have been used.

• Journal of the Korean Association of Geographic Information Studies
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• v.26 no.1
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• pp.69-88
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• 2023

Efficient spatial planning is one of the necessary factors to successfully respond to climate change. And researchers often use LULC(Land-Use/Cover) data to conduct land use and spatial planning research. However, LULC data has a limited number of grades related to urban surface, so each different urban structure appearing in several cities is not easily analyzed with existing land cover products. This limitation of land cover data seems to be overcome through LCZ(Local Climate Zone) data used in the urban heat island field. Therefore, this study aims to first discuss whether LCZ data can be applied not only to urban heat island fields but also to other fields, and secondly, whether LCZ data still have problems with existing LULC data. Research methodology is largely divided into two categories. First, through literature review, studies in the fields of climate, land use, and urban spatial structure related to LCZ are synthesized to analyze what research LCZ data is currently being used, and how it can be applied and utilized in the fields of land use and urban spatial structure. Next, the GIS spatial analysis methodology is used to analyze whether LCZ still has several errors that are found in the LULC.

• Journal of the Korean earth science society
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• v.44 no.1
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• pp.47-61
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• 2023

Rather than an abstract discourse, the purpose of this study is to outline the core concepts in the 2015 revised curriculum as a concrete teaching and learning method in the school context. We interviewed eight secondary science teachers and reported their perceptions and perspectives on core concepts using a backward design model based on the cyclical process of the platform, deliberation, and design for developing teaching and learning materials to understand core concepts. The participants perceived these core concepts differently, such as big ideas corresponding to the ultimate principle, minimum science concepts required for daily life, and primary and significant key concepts. In addition, this affects the association of teaching and learning. When core concepts are understood as transferable and expandable big ideas, there is a tendency to focus on the relationship between concepts and design project learning in a specific direction. However, if core concepts are identified as minimum science concepts at the level of science literacy, that can be recalled within the context of life, there is a tendency to emphasize on activities that make a meaningful difference to the lives of students with focus on case studies that are relevant to everyday life. Once core concepts are identified as key scientific content elements, such as basic or significant concepts, teachers recognize that it is essential to emphasize concept changes by correcting misconceptions, acquiring accurate scientific knowledge, and developing problem-solving items through paper-and-pencil evaluation. As the 2015 revised curriculum is finalized and the 2022 revised curriculum is scheduled for release, effective policy support is required to ensure that the curriculum is revised, which emphasizes the purpose of big ideas by naming core concepts as core ideas, to be stably implemented in schools.

• Smart Media Journal
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• v.11 no.9
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• pp.30-38
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• 2022

It is important to grasp biometric data in real time for prompt action in the event of a safety accident at a work site where the risk of safety accidents exists. Among them, blood oxygen saturation is the most important factor in maintaining human life, so real-time oxygen saturation measurement and monitoring is necessary according to the situation as a preemptive response for worker safety management. By receiving real-time bio-signals from workers wearing health and life-risk protective clothing, and sharing and analyzing the worker's risk status in an external system, it is possible to diagnose the worker's current condition and efficiently respond to emergencies that may occur to the worker. In this paper, we propose a wearable oxygen saturation measurement platform technology that can monitor the risk of harmful gases and oxygen saturation of the wearer in real time and ensure the wearer's activity and safety in order to cope with emergency situations at the scene of an accident. If we overcome the limitations identified through the results of the proposed system later and apply improved biodata such as motion correction to the platform, we expect that it will be usable not only in hazardous gas environments, but also in hospitals and homes for emergency patients.

• Journal of the Korea Society of Computer and Information
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• v.28 no.10
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• pp.85-92
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• 2023

In this paper, we propose a method for automatically generating story-based abbreviated summaries from long-form dramas and movies. From the shooting stage, the basic premise was to compose a frame with illusion of depth considering the golden division as well as focus on the object of interest to focus the viewer's attention in terms of content delivery. To consider how to extract the appropriate frames for this purpose, we utilized elemental techniques that have been utilized in previous work on scene and shot detection, as well as work on identifying focus-related blur. After converting the videos shared on YouTube to frame-by-frame, we divided them into a entire frame and three partial regions for feature extraction, and calculated the results of applying Laplacian operator and FFT to each region to choose the FFT with relative consistency and robustness. By comparing the calculated values for the entire frame with the calculated values for the three regions, the target frames were selected based on the condition that relatively sharp regions could be identified. Based on the selected results, the final frames were extracted by combining the results of an offline change point detection method to ensure the continuity of the frames within the shot, and an edit decision list was constructed to produce an abbreviated summary of 62.77% of the footage with F1-Score of 75.9%