• Journal of Biomedical Engineering Research
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• v.42 no.4
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• pp.175-185
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• 2021

Purpose: Vital sign are used to help assess the general physical health of a person, give clues to possible diseases, and show progress toward recovery. Researchers are using vital sign data and AI(artificial intelligence) to manage a variety of diseases and predict mortality. In order to analyze vital sign data using AI, it is important to select and extract vital sign data suitable for research purposes. Methods: We developed a method to visualize vital sign and early warning scores by processing retrospective vital sign data collected from EMR(electronic medical records) and patient monitoring devices. The vital sign data used for development were obtained using the open EMR big data MIMIC-III and the wearable patient monitoring device(CareTaker). Data processing and visualization were developed using Python. We used the development results with machine learning to process the prediction of mortality in ICU patients. Results: We calculated NEWS(National Early Warning Score) to understand the patient's condition. Vital sign data with different measurement times and frequencies were sampled at equal time intervals, and missing data were interpolated to reconstruct data. The normal and abnormal states of vital sign were visualized as color-coded graphs. Mortality prediction result with processed data and machine learning was AUC of 0.892. Conclusion: This visualization method will help researchers to easily understand a patient's vital sign status over time and extract the necessary data.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.3
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• pp.83-90
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• 2022

Diabetes is a common disease today, and there are also many cases of developing into serious complications called Diabetic Foot Ulcers(DFU). Diagnosis and prevention of DFU in advance is an important task, and this paper proposes the method. Based on existing studies introduced in the paper, it can be seen that foot pressure and temperature information are deeply correlated with DFU. Introduce the process and architecture of SmarTinsole, an IoT device that measures these indicators. Also, the paper describes the preprocessing process for AI-based diagnosis of DFU. Through the comparison of the measured pressure graph and the actual human step distribution, it presents the results that multiple information collected in real-time from SmarTinsole are more efficient and reliable than the previous study.

• Journal of the Korea Convergence Society
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• v.13 no.4
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• pp.53-61
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• 2022

Accidents are steadily occurring due to machine defects and carelessness during LNG storage operations. In previous studies, an environmental sensor module capable of measuring pressure, temperature, gas concentration, and flow to detect danger in advance was developed and the response speed according to the amount of leaked gas was measured. This paper proposes the development of a wired and wireless communication module that transmits data measured by the environmental sensor module to embedded devices connected to wired and wireless networks of SPI, UART, and LTE. First, a data communication module capable of interworking with an environmental sensor is designed. Design a protocol between devices in the Local Control Part and wired and wireless protocols in the Local Control Part and Remote Control Part. Ethernet, WiFi, and LTE communication modules were designed, and UART and SPI channels that can be linked with embedded controllers were designed. As a result, it was confirmed through a UI (User Interface) that each embedded device transmits data measured by the environmental sensor module while simultaneously communicating on a wired and wireless basis.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.6
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• pp.897-906
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• 2022

In this paper, we propose a novel MAC protocol based on the harmonic transmission of ACK, called HAT-LoRa, for improving the reliability and the utilization in multiple gateway LoRa Networks. LoRa is basically vulnerable to collision due to the primitive pure ALOHA-like MAC. Whereas data frame delivery can be guaranteed by the transparent bridge of multiple receiving gateways, ACK is still transmitted by a single gateway in LoRa Network. HAT-LoRa provides the augmented reception opportunity of ACK via the simultaneous transmissions of identical ACK in multiple spreading factors. The proposed method reduces the expected transmission times of ACK double gateway environment as well as single gateway environment, by 55 and 60% in maximum, by 35% and 40% in average, in a single- and double-gateway environment, respectively. Especially, it outperforms under the environment where the distance between end device and gateways are similar to each other.

• Journal of Digital Policy
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• v.1 no.2
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• pp.61-69
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• 2022

The paper is a study to develop and verify a blood glucose level prediction model based on biosignals obtained from photoplethysmography (PPG) sensors, ICT technology and data. Blood glucose prediction used the MLP architecture of machine learning. The input layer of the machine learning model consists of 10 input nodes and 5 hidden layers: heart rate, heart rate variability, age, gender, VLF, LF, HF, SDNN, RMSSD, and PNN50. The results of the predictive model are MSE=0.0724, MAE=1.1022 and RMSE=1.0285, and the coefficient of determination (R²) is 0.9985. A blood glucose prediction model using bio-signal data collected from digital devices and machine learning was established and verified. If research to standardize and increase accuracy of machine learning datasets for various digital devices continues, it could be an alternative method for individual blood glucose management.

• Journal of Space Technology and Applications
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• v.1 no.1
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• pp.7-22
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• 2021

In this paper, we describe the results of the docking phase test in the ground environment of the rendezvous/docking technology verification satellite under development for the first time in Korea. rendezvous/docking technology is a high-level technology in space technology, which is also very important for accessing and performing tasks on relative objects in space orbit. In this paper, we describe the ground test results that the chaser finally docks the fixed target using an air bearing device. Based on the thrust control algorithm in the docking phase and the relative object recognition and relative distance estimation algorithm using visual-based sensors validated in this paper, we intend to use them for later expansion to rendezvous/docking algorithms in three-dimensional space for testing in space.

• Journal of the Society of Disaster Information
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• v.17 no.4
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• pp.802-816
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• 2021

Purpose: In this paper, we propose a direction of future research and development to be carried out in the passive tracking field by deriving a white space with enhanced search formula of patent analysis. Method: In this paper, we derive a white space by identifying the direction and the flow of technology change and by matrixing the object and solution through extensive patent search with enhanced search formula and analysis in the field of passive tracking technology. Result: By the proposed scheme, 'multi-target positioning and tracking' and '3D positioning technology' using artificial intelligence, adaptive/hybrid positioning technology, and radar/antenna were derived as white space technologies and confirmed with absence of any services or products. Conclusion: The derived white space technologies from this paper are the areas where patent applications are not active and there are not many prior patents, thus it is necessary to secure the rights through more active R&D and patent application activities.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.4
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• pp.99-105
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• 2023

In this paper, an intelligent CCTV was designed and experimentally developed by using an IOT device, Raspberry Pi, and artificial intelligence technology. Object Detection technology was used to detect the number of people on the CCTV screen, and Action Detection technology provided by OpenPose was used to detect emergency situations. The proposed system has a structure of CCTV, server and client. CCTV uses Raspberry Pi and USB camera, server uses Linux, and client uses iPhone. Communication between each subsystem was implemented using the MQTT protocol. The system developed as a prototype could transmit images at 2.7 frames per second and detect emergencies from images at 0.2 frames per second.

• Korean Journal of Childcare and Education
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• v.19 no.2
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• pp.61-85
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• 2023

Objective: This study aims to investigate whether science teaching attitude of early childhood teachers mediates the relationship between the professional learning environment of institutions and their intention to accept artificial intelligence (AI) technology, and whether the experience of using smart and digital devices moderates the effect of science teaching attitude. Methods: An online survey was conducted targeting 118 teachers with more than 1 year of experience in kindergarten and day care center settings. Descriptive statistical analysis, correlation analysis, and The Process macro model 4, 14 were performed using SPSS 27.0 and The Process macro 3.5. Results: First, the science teaching attitude of early childhood teachers served as a mediator between the professional learning environment of institutions and teachers' intention to accept AI technology. Second, the experience of using smart and digital devices was found to moderate the effect of teachers' science teaching attitude on their intention to accept AI technology. Conclusion/Implications: This results showed that an institutional environment that supports teachers' professionalism development and provides rich experience is crucial for promoting teachers' active acceptance of AI technology. The findings highlight the importance of creating a supportive institutional envionment for teacher's professional growth, enhancing science teaching attitudes, and facilitating the use of various devices.

• The Journal of the Korea Contents Association
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• v.22 no.5
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• pp.491-502
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• 2022

Voice technology allows consumers to make purchases through smart devices, and the interest in voice-driven conversational commerce has significantly expanded. In this study, we explored the continuance use intention of voice commerce, and the adoption of a value-attitude-behavior model. An online survey was conducted on 360 individuals who used an artificial intelligence assistant device in a voice commerce environment. We used Amos 23.0 and SPSS 25.0 for descriptive, confirmatory, and structural equation modeling analyses. These results indicated that functional value was the highest influencing variable on satisfaction of voice commerce, while social, emotional, and epistemic values significantly influenced it as well. Additionally, satisfaction of voice commerce significantly influenced the continuance use intention of voice commerce. These findings could help us understand the characteristics of voice commerce users and the diversity value in voice commerce environment.