• Korean Journal of Acupuncture
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• v.40 no.1
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• pp.1-12
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• 2023

Objectives : This study aims to provide information regarding the status and quality of mobile applications (MAs) using self-acupressure by performing a systematic review. Methods : We conducted comprehensive searching on five international databases and two app markets from inception to July 31, 2022 to identify MAs using self-acupressure. We analyzed the characteristics of each MA regarding the name of the MA, registered app markets, target symptoms, developers, the year and country of development, cost, target age, media function, and expertise. We assessed the quality of each MA using Mobile Application Rating Scale (MARS). Results : We identified a total of 30 MAs using self-acupressure (25 MAs from the app market and 6 MAs from clinical studies, with 1 MA in common). 17 out of 24 MAs from the app market provided self-acupressure regimens for various symptoms and the others provided regimens for specific symptoms such as memory, anxiety, depression, asthma, allergy, low back pain, and headache. 14 developers were reported. 23 MAs were developed after 2013. The largest number of MAs were developed in the United States. The target age group of 12 MAs was above the age of 3, and that of 11 MAs was above the age of 12. 14 MAs provided multimedia functions such as videos. 13 MAs provided information of expertise. From clinical studies, only 3 out of 6 MAs were accessible through the app market. 4 MAs were developed by the researchers of the study. In terms of MARS, the score of MAs from the app market was higher than that of MAs from clinical studies in both objective and subjective evaluation areas. Conclusions : This study summarizes the characteristics of MAs using self-acupressure. More MAs using self-acupressure should be developed and further clinical research for MA on each symptom and disease is warranted for the diversification of MA fields using self-acupressure.

• International journal of advanced smart convergence
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• v.12 no.3
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• pp.89-103
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• 2023

Obstructive sleep apnea (OSA) is one of the most prevalent sleep disorders that can lead to serious consequences, including hypertension and/or cardiovascular diseases, if not treated promptly. Continuous positive airway pressure (CPAP) is widely recognized as the most effective treatment for OSA, which needs the proper titration of airway pressure to achieve the most effective treatment results. However, the process of CPAP titration can be time-consuming and cumbersome. There is a growing importance in predicting personalized CPAP pressure before CPAP treatment. The primary objective of this study was to optimize the CPAP titration process for obstructive sleep apnea patients through EEG feature engineering with machine learning techniques. We aimed to identify and utilize the most critical EEG features to forecast key OSA predictive indicators, ultimately facilitating more precise and personalized CPAP treatment strategies. Here, we analyzed 126 OSA patients' PSG datasets before and after the CPAP treatment. We extracted 29 EEG features to predict the features that have high importance on the OSA prediction index which are AHI and SpO2 by applying the Shapley Additive exPlanation (SHAP) method. Through extracted EEG features, we confirmed the six EEG features that had high importance in predicting AHI and SpO2 using XGBoost, Support Vector Machine regression, and Random Forest Regression. By utilizing the predictive capabilities of EEG-derived features for AHI and SpO2, we can better understand and evaluate the condition of patients undergoing CPAP treatment. The ability to predict these key indicators accurately provides more immediate insight into the patient's sleep quality and potential disturbances. This not only ensures the efficiency of the diagnostic process but also provides more tailored and effective treatment approach. Consequently, the integration of EEG analysis into the sleep study protocol has the potential to revolutionize sleep diagnostics, offering a time-saving, and ultimately more effective evaluation for patients with sleep-related disorders.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.30-31
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• 2009

Early detection of schedule delay in field construction activities is vital to project management. It provides the opportunity to initiate remedial actions and increases the chance of controlling such overruns or minimizing their impacts. This entails project managers to design, implement, and maintain a systematic approach for progress monitoring to promptly identify, process and communicate discrepancies between actual and as-planned performances as early as possible. Despite importance, systematic implementation of progress monitoring is challenging: (1) Current progress monitoring is time-consuming as it needs extensive as-planned and as-built data collection; (2) The excessive amount of work required to be performed may cause human-errors and reduce the quality of manually collected data and since only an approximate visual inspection is usually performed, makes the collected data subjective; (3) Existing methods of progress monitoring are also non-systematic and may also create a time-lag between the time progress is reported and the time progress is actually accomplished; (4) Progress reports are visually complex, and do not reflect spatial aspects of construction; and (5) Current reporting methods increase the time required to describe and explain progress in coordination meetings and in turn could delay the decision making process. In summary, with current methods, it may be not be easy to understand the progress situation clearly and quickly. To overcome such inefficiencies, this research focuses on exploring application of unsorted daily progress photograph logs - available on any construction site - as well as IFC-based 4D models for progress monitoring. Our approach is based on computing, from the images themselves, the photographer's locations and orientations, along with a sparse 3D geometric representation of the as-built scene using daily progress photographs and superimposition of the reconstructed scene over the as-planned 4D model. Within such an environment, progress photographs are registered in the virtual as-planned environment, allowing a large unstructured collection of daily construction images to be interactively explored. In addition, sparse reconstructed scenes superimposed over 4D models allow site images to be geo-registered with the as-planned components and consequently, a location-based image processing technique to be implemented and progress data to be extracted automatically. The result of progress comparison study between as-planned and as-built performances can subsequently be visualized in the D4AR - 4D Augmented Reality - environment using a traffic light metaphor. In such an environment, project participants would be able to: 1) use the 4D as-planned model as a baseline for progress monitoring, compare it to daily construction photographs and study workspace logistics; 2) interactively and remotely explore registered construction photographs in a 3D environment; 3) analyze registered images and quantify as-built progress; 4) measure discrepancies between as-planned and as-built performances; and 5) visually represent progress discrepancies through superimposition of 4D as-planned models over progress photographs, make control decisions and effectively communicate those with project participants. We present our preliminary results on two ongoing construction projects and discuss implementation, perceived benefits and future potential enhancement of this new technology in construction, in all fronts of automatic data collection, processing and communication.

• Journal of Korea Society of Industrial Information Systems
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• v.15 no.5
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• pp.137-148
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• 2010

In this paper, a mobile office support. system which consists of mobile devices and servers is proposed. An efficient mobile office support system is required to study since the existing mobile office support systems may face the serious problems such as an absence of interoperability, difficulties of data synchronization and device management in the near future, especially when a company has a large number of outdoor service employees. In this paper, a mobile office support system requirements for a company with a large number of outdoor service employees is proposed. And then, the methods to satisfy the requirements using a remote data synchronization and a remote device management technologies are proposed. The mobile office support system proposed in this paper synchronizes remotely a large number of various mobile devices of employees with centralized servers located in the company. In addition, it manages the mobile devices remotely for the employees. This paper proposes a mobile office support system based on OMA(Open Mobile Alliance) DS(Data Synchronization) and DM(Device Management) protocols. As OMA DS and DM protocols are de facto international standards, the interoperability between the mobile office support systems can be guaranteed.

• Journal of Korea Trade
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• v.27 no.3
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• pp.21-42
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• 2023

Purpose - This paper investigates the trade effect of the Korea-China Free Trade Agreement (KCFTA) which coincides with political conflicts between the two countries due to the deployment of the Terminal High Altitude Area Defense (THAAD) in Korea. The two events occurred in the same year and both are likely to affect trade between two countries but in opposite directions. Therefore, it is crucial to distinguish between the trade effects from the KCFTA event and those from the THAAD event to evaluate the true FTA effects. However, this would be difficult when using only annual data. Accordingly, ex post studies to examine the trade effects of KCFTA are lacking in trustworthiness while many ex ante studies that conjecture the positive trade effects neglect the THAAD deployment impact. This paper aims to fill that gap. Design/methodology - Given that the KCFTA and THAAD events occurred in the same year but in different months, we use the monthly data from 2000 to 2019 of Korea's exports to bracket this period. We employ the difference-in-difference (DID) method within a gravity equation specification that uses hi-dimensional fixed effects to address various endogeneity issues and seasonal effects. We identify the net impact of KCFTA ratification from these two near-simultaneous events to quantify the effects of trade liberalization between these two countries. Findings - After isolating the THAAD effects on trade, the analysis creates a positive and statistically significant coefficient estimate of the KCFTA impact. In contrast, failing to isolate the THAAD effect produced a negative and statistically significant coefficient estimate of the KCFTA impact. Our results indicate that KCFTA independently increased Korea's exports to China by 10.2%, but that this increase was fully mitigated by the THAAD event. Further, our results verify that unobserved heterogeneity and multilateral resistance are technically difficult to account for in those estimations as that rely solely upon annual data, as this type of data are inadequate to control for the potential for endogeneity. Originality/value - This paper is one of the first studies to carefully evaluate the net trade effects of the KCFTA on Korea's largest trading partner while isolating the impact of simultaneously occurred political events that may influence trade in opposing directions. Our findings indicate that the lack of prior evidence of positive trade effects of the KCFTA when using annual data may be attributed to a failure to identify the impact of each event separately. This analysis supports using the correct modeling specification to avoid misleading conclusions when evaluating any important international trade policy.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.1249-1249
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• 2022

The facade, an exterior material of a building, is one of the crucial factors that determine its morphological identity and its functional levels, such as energy performance, earthquake and fire resistance. However, regardless of the type of exterior materials, huge property and human casualties are continuing due to frequent exterior materials dropout accidents. The quality of the building envelope depends on the detailed design and is closely related to the back frames that support the exterior material. Detailed design means the creation of a shop drawing, which is the stage of developing the basic design to a level where construction is possible by specifying the exact necessary details. However, due to chronic problems in the construction industry, such as reducing working hours and the lack of design personnel, detailed design is not being appropriately implemented. Considering these characteristics, it is necessary to develop the detailed design process of exterior materials and works based on the domain-expert knowledge of the construction industry using artificial intelligence (AI). Therefore, this study aims to establish a detailed design automation algorithm for AI-based condition-responsive exterior wall panels and their back frames. The scope of the study is limited to "detailed design" performed based on the working drawings during the exterior work process and "stone panels" among exterior materials. First, working-level data on stone works is collected to analyze the existing detailed design process. After that, design parameters are derived by analyzing factors that affect the design of the building's exterior wall and back frames, such as structure, floor height, wind load, lift limit, and transportation elements. The relational expression between the derived parameters is derived, and it is algorithmized to implement a rule-based AI design. These algorithms can be applied to detailed designs based on 3D BIM to automatically calculate quantity and unit price. The next goal is to derive the iterative elements that occur in the process and implement a robotic process automation (RPA)-based system to link the entire "Detailed design-Quality calculation-Order process." This study is significant because it expands the design automation research, which has been rather limited to basic and implemented design, to the detailed design area at the beginning of the construction execution and increases the productivity by using AI. In addition, it can help fundamentally improve the working environment of the construction industry through the development of direct and applicable technologies to practice.

• (The) Research of the performance art and culture
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• no.43
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• pp.173-202
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• 2021

During the Korean War, China dispatched 'the Anti-US and Pro-Joseon Comfort' group to North Korea 3 times. The purpose of the comfort group was to comfort the Chinese People's Supporting Soldiers and Joseon People's Army fighting the US imperial forces and at the same time, inform them of China's situation to booster their morale. Another purpose was to promote the socialism construction projects in the new China. Namely, China wanted to propagate various heroic achievements of the Chinese soldiers and accuse the US imperialist soldiers and thereby, inspire Chinese people's international sense and patriotism for the new China to mobilize the people for the war and promote the construction of the new China effectively. The comfort group consisted of diverse classes (laborers, farmers, intellectuals, women, students, soldiers, etc.) in various areas such as politics, military, ethnic, society, culture, education, etc. Their activities were conducted in various forms such as consolation, legwork, meeting and performances. Their activities were full of anger and compassion, sacrifice and emotion, battle and romance, impression and comfort. Such emotion was delivered intact to the Chinese people through the comfort group's propaganda activities back home in China. The Anti-US and Pro-Joseon Comfort' group revealed their identity of socialists New China in terms of their organization and their specific performances. Their identity claimed for democracy and equality, internationalism empathizing world peace and solidarity of the proletariats, and patriotism supporting the communists regime. The comfort group played a role in propagating such identity of new China effectively by crossing the border. It was a political and cultural performance that stipulated the political meaning of the Anti-US and Pro-Joseon Chosun Comfort' group

• The Journal of the Convergence on Culture Technology
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• v.9 no.1
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• pp.361-372
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• 2023

In this study, three luxury fashion start-up platforms, Balaan, Trenbe, and Must-it, were selected as research subjects. The purpose of this study is to compare and analyze the marketing mix strategies of each of the three online sites. The results of our study are as follows. First of all, the product strategies of the three luxury platform companies are characterized by the composition of products from high-end brands to SPA brands, and product composition such as kids, home living, Used goods and art in addition to women's and men's wear. In addition, the pricing strategies of luxury platforms show price differences depending on the luxury platform even for the same product. It is shown as a structure that directly determines margin. Therefore, in order to secure an edge in price competitiveness, each platform provided discount coupons and savings that are not available in offline stores such as department stores, providing opportunities to purchase luxury goods at a lower price than offline stores.Lastly, the sales promotion strategies of the three luxury platform companies was used include price discount promotions such as price discounts, discount coupons, and regular sales, and value-added sales such as membership registration/review points, events, product information, delivery services, social contribution activities, and SNS utilization.

• The Journal of the Convergence on Culture Technology
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• v.9 no.1
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• pp.649-654
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• 2023

This paper proposes the design of a neural network structure search model using graph convolutional neural networks. Deep learning has a problem of not being able to verify whether the designed model has a structure with optimized performance due to the nature of learning as a black box. The neural network structure search model is composed of a recurrent neural network that creates a model and a convolutional neural network that is the generated network. Conventional neural network structure search models use recurrent neural networks, but in this paper, we propose GC-NAS, which uses graph convolutional neural networks instead of recurrent neural networks to create convolutional neural network models. The proposed GC-NAS uses the Layer Extraction Block to explore depth, and the Hyper Parameter Prediction Block to explore spatial and temporal information (hyper parameters) based on depth information in parallel. Therefore, since the depth information is reflected, the search area is wider, and the purpose of the search area of the model is clear by conducting a parallel search with depth information, so it is judged to be superior in theoretical structure compared to GC-NAS. GC-NAS is expected to solve the problem of the high-dimensional time axis and the range of spatial search of recurrent neural networks in the existing neural network structure search model through the graph convolutional neural network block and graph generation algorithm. In addition, we hope that the GC-NAS proposed in this paper will serve as an opportunity for active research on the application of graph convolutional neural networks to neural network structure search.

• The Journal of the Convergence on Culture Technology
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• v.9 no.1
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• pp.153-160
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• 2023

This research experiments on the workers' recognition of the fire alarm sound for sirens and portable loudspeakers in a small construction site. As a result of analyzing the siren alarm sound recognition from measuring on the 1st, 2nd, and 4th floors, the sound was more unrecognizable on the 4th floor than on the 1st, and 1 person on the 1st floor was unable to recognize all sounds. In the case of the 2nd floor, one person could not notice the alarm in the last 3rd trial, and another did not realize it all three times. For the 4th floor, 3 people demonstrated unrecognition in all 3 tests. As a result of analyzing the recognition of portable loudspeaker alarm sounds, 1 person could not recognize all sounds on the first floor. In the case of the 2nd floor, 2 people were confirmed to be unable to notice, and lastly, 4 people could not recognize all trials on the 4th floor. The subjects who didn't recognize the sound were unable to distinguish between portable loudspeaker alarm sound and work noise due to the workspace and obstacles.