• Journal of the Society of Disaster Information
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• v.18 no.4
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• pp.806-816
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• 2022

Purpose: In this study, the luminance measurement analysis results of the smoke generation state are considered for visual signal display light color for real-time escape guidance in the underground common area. Method: We will analyze the scattering characteristics of light in the atmosphere and optical technology based on the visibility theory, and try to classify the elemental technology as a guidance function through a prototype of a visual signal display device for evacuation guidance. Result: In the experiment conducted under the smoke-generating condition, the results were derived with low luminance ratio and good visibility in the order of red, green, and yellow. However, this result is different from general lighting in which color rendering is considered, and is limited to signals for signals and detection. Conclusion: A conclusions were drawn by reflecting both the luminance measurement results in the smoke generation situation and the preference survey results conducted in previous studies for the light color of the visual signal for signal and detection. When events such as smoke occur, it is better to use the escape guidance visual signal in red or green.

• The Korean Journal of Nuclear Medicine Technology
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• v.26 no.2
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• pp.37-42
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• 2022

Purpose Since 1985, the Korean society of nuclear medicine technology (KSNMT) has been engaged in academic activities related to nuclear medicine imaging. From 2017 to 2021, the papers published in the journal were classified by the specific fields to examine the trends in the research and the direction of nuclear medicine in comparison with the papers submitted to the Korean Society of Nuclear Medicine (KSNM) during the same period. Materials and Methods From 2017 to 2021, papers submitted to KSNMT and KSNM were classified and databaseization using the Excel program by submission type, examination equipment, and examination field. Through this data, the number of papers published in journals by year, the number of papers submitted by detailed fields, and key words by era were analyzed and compared. Results The papers included by journal was 57 KSNMT and 280 KSNM. The major large classification of equipment, PET, Planar and SPECT was 26.3%, 21.1%, 19.3% in the KSNMT, KSNM was 49.6%, 6.4%, and 9.3%, with 66.7% and 65.3%, respectively. the major medium classification of equipment, industrial safety, urogenital system, nervous system, and quality control accounted for 54.4% of the total papers of the total ratio in the KSNMT, while the medium classification of oncology, endocrine system, urogenital system, therapy, and nervous system accounted for 61.1% of KSNM. In the major small classification of image acquisition, improvement effect, and exposure management accounted for 70.2% in KSNMT, while the items of image acquisition, report, and improvement effect accounted for 60.7% in KSNM. The major keywords except for equipment-related keywords such as PET/CT, PET/MR, and SPECT were SUV, Planar Image, and Respiration Gating Method in KSNMT and Ga68, Thyroid, and Lymphoma in the KSNM. Conclusion When checking the last 5 years of submissions, we can see that KSNMT is mainly concerned with image acquisition using existing radiotracers, while KSNM has focused on new radiotracers such as ⁶⁸Ga, ¹⁷⁷Lu, etc., and new medical technologies of theranostic. It has been confirmed that more PET-related papers than other examination equipment will account for a greater number of papers, and it is believed that future submissions will also account for a higher proportion of PET-related papers than other equipment.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.211-227
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• 2023

Personal service robots, a type of social robot that has emerged with the aging population and technological advancements, are undergoing a transformation centered around technologies that can extend independent living for older adults in their homes. For older adults to accept and use social robot innovations in their daily lives on a long-term basis, it is crucial to have a deeper understanding of user perspectives, contexts, and emotions. This research aims to comprehensively understand older adults by utilizing a mixed-method approach that integrates quantitative and qualitative data. Specifically, we employ the Van Kaam phenomenological methodology to group conversations into nine categories based on emotional cues and conversation participants as key variables, using voice conversation records between older adults and social robots. We then personalize the conversations based on frequency and weight, allowing for user segmentation. Additionally, we conduct profiling analysis using demographic data and health indicators obtained from pre-survey questionnaires. Furthermore, based on the analysis of conversations, we perform K-means cluster analysis to classify older adults into three groups and examine their respective characteristics. The proposed model in this study is expected to contribute to the growth of businesses related to understanding users and deriving insights by providing a methodology for segmenting older adult s, which is essential for the future provision of social robots with caregiving functions in everyday life.

• The Journal of the Convergence on Culture Technology
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• v.9 no.1
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• pp.19-26
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• 2023

In this study, the public sensitivity of the 'MZ generation' was examined through the social media big data sensitivity analysis method. For the analysis, the consumer account SNS text was examined, and positive and negative emotional factors were presented by classifying external sensibilities and emotions of the MZ generation. In conclusion, the positive emotions of liking and interest in relation to the "MZ generation" were 72.1%, higher than the negative emotional ratio of 27.9%. In positive sensitivity, the older generation showed 'a favorable feeling for the individuality and dignifiedness of the MZ generation' and 'interest in the MZ generation with new values'. In contrast, the MZ generation has a favorable feeling for 'the fact that they are a generation of their own boldness, youthfulness and individuality' and 'small growthism'. Negative sensitivity outside the MZ generation was found to be 'A concern about the marriage avoidance, employment difficulties, debt investment, and resignation trends of the MZ generation', 'Hate the MZ generation who treats Kkondae' and 'Difficult to talk to the MZ generation'. On the other hand, the negative emotions felt by the MZ generation itself were 'Rejection of generalization', 'Rejection of generation and gender conflicts', 'Rejection of competition worse than the older generation', 'Relative failure of the rich era', and 'Sadness to live in a predicted climate disaster'. Therefore, the older generation should not look at the MZ generation in general, but as individuals, and should alleviate conflicts with intergenerational understanding and empathy. there is a need for community consideration to solve generational conflicts, gender conflicts, and environmental problems.

• Journal of the Korean Geotechnical Society
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• v.26 no.3
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• pp.59-68
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• 2010

Systematic risk management is necessary in grand scaled urban construction because of the existence of complicated and various risk factors. Problems of obstructions, adjacent structures, safety, environment, traffic and geotechnical properties need to be solved because urban construction is progressed in limited space not as general earthwork. Therefore the establishment of special risk management system is necessary to manage not only geotechnical properties but also social and cultural uncertainties. This research presents the technique analysis by the current state of risk management technique. Risk factors were noticed and the importance of each factor was estimated through survey. The systemically categorized database was established. Risk extraction module, matrix and score module were developed based on the database. Expected construction budget and time distribution can be computed by Monte Carlo analysis of probabilities and influences. Construction budgets and time distributions of before and after response can be compared and analyzed 80 the risks are manageable for entire whole construction time. This system will be the foundation of standardization and integration. Procurement, efficiency improvement, effective time and resource management are available through integrated management technique development and application. Conclusively decrease in cost and time is expected by systemization of project management.

• Knowledge Management Research
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• v.24 no.1
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• pp.147-172
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• 2023

This study aims to review the competitiveness of 'TVING', a Korean OTT player in Korean market. For this, this study extracts core business resources of TVING focusing on resource-based theory, and analyzes their competitiveness under VRIO framework. TVING has 4 tangible and intangible resources respectively and 1 human resource. Tangible resources of TVING are technology(recommendation, compression), content(original, exclusive, discriminative non-exclusive), production studio, and paid-subscribers. Intangible resources are content planing capability, distribution network(local, global), marketing promotion·PR, sales), brand preference. And human resource of TVING creates IP professionalism of the company. As a result of VRIO analysis, discriminative non-exclusive content, production studios, and domestic service channels are the most powerful resources of TVING to 'sustain competitive advantage'. Technology, original content, planning capability and IT professionalism bring 'temporary competitive advantage', while exclusive content, the number of paid-subscribers, global service network, and promotion capabilities are not core resources with staying in competitive rank stages. By the way, TVING has potential users for sales of KT and LGU+ thanks to partnership and M&A, but this is not effectively used at the organization level yet. The meaning of this study can be found in that this evaluated competitiveness by each resource of TVING and arranged its implications.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.1
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• pp.253-263
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• 2017

As needs for knowledge on Korean history and the attention of the people are rapidly increasing, various smartphone applications for learning the history have appeared during recent years. These applications provide multiple choice questions to users through their own problem banks. But, since these questions are selected from the fixed set of problems that are stored previously, the learning efficiency of users is inevitably decreased when they use the applications repeatedly. In this paper, we present a question generation system named K-History which generates multiple choice questions in an automatic way using the database on the history of Korea. In addition, we also describe the development of the application Korean History Infinite Challenge as a learning application for Korean history. To develop K-History, we classify typical types of learning problems through various problems based on Korean history learning materials, proposing algorithms to generate problems according to the types found. Through the developed techniques, various learning systems can reduce the cost for creating questions, while increasing the learning efficiency of users.

• Design Convergence Study
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• v.16 no.3
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• pp.103-118
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• 2017

It is expected that the integrated control service of the public sector will be increased for the safety of citizens in the future. Therefore, In this study, we analyzed the classification of CCTV control center and the characteristics of interior design. The survey was conducted at eight control centers in Seoul that were constructed since 2007 and analyzed according to the criteria of general matters, services, spatial basic information, spatial structure, and internal structure. The results of the survey are summarized as follows. Based on the results of the study, the Integrated Control Center is a space where the ratio of the physical environment is not high but performs important tasks for the citizens of the city, which are operated 24 hours a day, and security and security. It is characterized by the efficient space allocation for the treatment, the design of the moving line, and the connection according to the urgent work flow. The results of this study are expected to be used as basic data for other integrated control center environment.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.129-148
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• 2023

Bitcoin is a blockchain technology-based digital currency that has been recognized as a representative cryptocurrency and a financial investment asset. Due to its highly volatile nature, Bitcoin has gained a lot of attention from investors and the public. Based on this popularity, numerous studies have been conducted on price and trend prediction using machine learning and deep learning. This study employed LSTM (Long Short Term Memory) and CNN (Convolutional Neural Networks), which have shown potential for predictive performance in the finance domain, to enhance the classification accuracy in Bitcoin price trend prediction. XAI(eXplainable Artificial Intelligence) techniques were applied to the predictive model to enhance its explainability and interpretability by providing a comprehensive explanation of the model. In the empirical experiment, CNN was applied to technical indicators and Google trend data to build a Bitcoin price trend prediction model, and the CNN model using both technical indicators and Google trend data clearly outperformed the other models using neural networks, SVM, and LSTM. Then SHAP(Shapley Additive exPlanations) was applied to the predictive model to obtain explanations about the output values. Important prediction drivers in input variables were extracted through global interpretation, and the interpretation of the predictive model's decision process for each instance was suggested through local interpretation. The results show that our proposed research framework demonstrates both improved classification accuracy and explainability by using CNN, Google trend data, and SHAP.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.23-34
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• 2023

Wearable technology for military applications has received considerable attention as a means of personal status check and monitoring. Among many, an implementation to recognize specific motion states of a human is promising in that allows active management of troops by immediately collecting the operational status and movement status of individual soldiers. In this study, as an extension of military wearable application research, a new ankle wearable device is proposed that can glean the information of a soldier on the battlefield on which action he/she takes in which environment. Presuming a virtual situation, the soldier's upper limbs are easily exposed to uncertainties about circumstances. Therefore, a sensing module is attached to the ankle of the soldier that may always interact with the ground. The obtained data comprises 3-axis accelerations and 3-axis rotational velocities, which cannot be interpreted by hand-made algorithms. In this study, to discern the behavioral characteristics of a human using these dynamic data, a data-driven model is introduced; four features extracted from sliced data (minimum, maximum, mean, and standard deviation) are utilized as an input of the model to learn and classify eight primary military movements (Sitting, Standing, Walking, Running, Ascending, Descending, Low Crawl, and High Crawl). As a result, the proposed device could recognize a movement status of a solider with 95.16% accuracy in an arbitrary test situation. This research is meaningful since an effective way of motion recognition has been introduced that can be furtherly extended to various military applications by incorporating wearable technology and artificial intelligence.