• 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.

• Korean Journal of Agricultural Science
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• v.49 no.4
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• pp.845-855
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• 2022

The purpose of this study is to develop a self-propelled underground crop harvester and its performance was evaluated by measuring the load during actual potato harvesting operations. This study was conducted at a constant working speed of 1 km·h^-1. A load measurement system was installed to measure the actual load and the required working power was analyzed. A hydraulic pressure sensor was also installed to measure the hydraulic pressure. The required hydraulic power was calculated using the hydraulic pressure and flow rate. The results showed that the engine speed, torque, and power during harvesting operation were in the range of 845 - 1,423 rpm, 95 - 228 Nm, and 9 - 31 kW, respectively. Traction power, excluding the hydraulic pump of the tractor and power take-off (PTO) output, was in the range of 9 - 28 kW, and it was confirmed that it occupies a ratio of 16.2 to 50% of the engine rated output. The engine can supply the minimum required traction power to move the vehicle. This means that the engine used in this study could be down-sized to be suitable for an underground crop harvester. In this study, the gear stages of the tractor were not considered. This research thus shows the possibility of developing a self-propelled underground crop harvester.

• Journal of Sensor Science and Technology
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• v.32 no.6
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• pp.441-446
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• 2023

Electrical and optical characteristics of the GaN-based light-emitting diode (LED) with the improved multi-quantum well (MQW) structure have been studied for light source in bio-sensing systems. Novel GaN/In_0.1GaN/In_0.2GaN/In_0.1GaN/GaN and Al_0.1GaN/GaN/In_0.2GaN/GaN/Al_0.1GaN (MQW) structures were suggested, and their radiative recombination rate, light output power, electroluminescence, and external quantum efficiency were compared with those of the conventional GaN/In_0.2GaN/GaN MQW structure using device simulation. The LED with the GaN/In_0.1GaN/In_0.2GaN/In_0.1GaN/GaN MQW structure showed an excellent recombination rate of 5.57 × 10²⁸ cm^-3·s^-1 that was more than one order improvement over that of the conventional LED. In addition, the efficiency droop was relieved by the suggested stepped MQW structure.

• PNF and Movement
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• v.22 no.1
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• pp.43-54
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• 2024

Purpose: Falls among persons older than 65 years are a significant concern due to their frequency and severity. This study aimed to develop a vest-type embedded artificial intelligence (AI) system capable of detecting and predicting falls in various scenarios. Methods: In this study, we established and developed a vest-type embedded AI system to judge and predict falls in various directions and situations. To train the AI, we collected data using acceleration and gyroscope values from a six-axis sensor attached to the seventh cervical and the second sacral vertebrae of the user, considering accurate motion analysis of the human body. The model was constructed using a neural network-based AI prediction algorithm to anticipate the direction of falls using the collected pedestrian data. Results: We focused on developing a lightweight and efficient fall prediction model for integration into an embedded AI algorithm system, ensuring real-time network optimization. Our results showed that the accuracy of fall occurrence and direction prediction using the trained fall prediction model was 89.0% and 78.8%, respectively. Furthermore, the fall occurrence and direction prediction accuracy of the model quantized for embedded porting was 87.0 % and 75.5 %, respectively. Conclusion: The developed fall detection and prediction system, designed as a vest-type with an embedded AI algorithm, offers the potential to provide real-time feedback to pedestrians in clinical settings and proactively prepare for accidents.

• Journal of the Korean Society of Food Science and Nutrition
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• v.44 no.6
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• pp.904-911
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• 2015

The objective of this study was to investigate the quality characteristics of traditional wine using an radio-frequency identification (RFID) system annexed to a fermenter. In this study, we proposed an RFID-based data transmission scheme for monitoring fermentation of traditional alcoholic beverages. The pH, total acidity, total sugar, soluble sugar, free sugar, alcohol content, and organic acids of were investigated and subjected to fermentation of traditional alcoholic beverages three times. The pH ranged from 7.98, 7.95, and 7.68 at day 0, decreased drastically to 3.31~2.96 at day 2, and then slowly increased to the end point, finally reaching 3.34 at day 20. Acidity tended to increase quickly with time, especially for all samples after day 2. The fermentation environment induced a sudden increase acidity in reactants and indicated a low pH. The total sugars during fermentation quickly decreased to the range of 20.3, 22.43, and 19.2% at day 2, and the slope of reduction steadily decreased to 5.1, 6.1, and 4.8% at day 10. On the other hand, the alcohol content showed the reverse trend as total sugars. The alcohol content also showed the same pattern as total acids, showing the highest alcohol content of 17.3% (v/v) on day 20. In this study on traditional wine fermentation using an RFID system, we showed that pH, soluble sugar, and alcohol content can be adopted as key indicators for quality control and standardization of traditional wine manufacturing.

• Korean Chemical Engineering Research
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• v.60 no.1
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• pp.86-92
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• 2022

Recently, the bio-healthcare market is enlarging worldwide due to various reasons such as the COVID-19 pandemic. Among them, biometric measurement and analysis technology are expected to bring about future technological innovation and socio-economic ripple effect. Existing systems require a large-capacity battery to drive signal processing, wireless transmission part, and an operating system in the process. However, due to the limitation of the battery capacity, it causes a spatio-temporal limitation on the use of the device. This limitation can act as a cause for the disconnection of data required for the user's health care monitoring, so it is one of the major obstacles of the health care device. In this study, we report the concept of a standalone healthcare monitoring module, which is based on both triboelectric effects and electromagnetic effects, by converting biomechanical energy into suitable electric energy. The proposed system can be operated independently without an external power source. In particular, the wireless foot pressure measurement monitoring system, which is rationally designed triboelectric sensor (TES), can recognize the user's walking habits through foot pressure measurement. By applying the triboelectric effects to the contact-separation behavior that occurs during walking, an effective foot pressure sensor was made, the performance of the sensor was verified through an electrical output signal according to the pressure, and its dynamic behavior is measured through a signal processing circuit using a capacitor. In addition, the biomechanical energy dissipated during walking is harvested as electrical energy by using the electromagnetic induction effect to be used as a power source for wireless transmission and signal processing. Therefore, the proposed system has a great potential to reduce the inconvenience of charging caused by limited battery capacity and to overcome the problem of data disconnection.

• Korean Journal of Remote Sensing
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• v.39 no.6_2
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• pp.1565-1576
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• 2023

An atmospheric correction algorithm based on the radiative transfer model is required to obtain remote-sensing reflectance (R_rs) from the Geostationary Ocean Color Imager-II (GOCI-II) observed at the top-of-atmosphere. This R_rs derived from the atmospheric correction is utilized to estimate various marine environmental parameters such as chlorophyll-a concentration, total suspended materials concentration, and absorption of dissolved organic matter. Therefore, an atmospheric correction is a fundamental algorithm as it significantly impacts the reliability of all other color products. However, in clear waters, for example, atmospheric path radiance exceeds more than ten times higher than the water-leaving radiance in the blue wavelengths. This implies atmospheric correction is a highly error-sensitive process with a 1% error in estimating atmospheric radiance in the atmospheric correction process can cause more than 10% errors. Therefore, the quality assessment of R_rs after the atmospheric correction is essential for ensuring reliable ocean environment analysis using ocean color satellite data. In this study, a Quality Assurance (QA) algorithm based on in-situ R_rs data, which has been archived into a database using Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Bio-optical Archive and Storage System (SeaBASS), was applied and modified to consider the different spectral characteristics of GOCI-II. This method is officially employed in the National Oceanic and Atmospheric Administration (NOAA)'s ocean color satellite data processing system. It provides quality analysis scores for R_rs ranging from 0 to 1 and classifies the water types into 23 categories. When the QA algorithm is applied to the initial phase of GOCI-II data with less calibration, it shows the highest frequency at a relatively low score of 0.625. However, when the algorithm is applied to the improved GOCI-II atmospheric correction results with updated calibrations, it shows the highest frequency at a higher score of 0.875 compared to the previous results. The water types analysis using the QA algorithm indicated that parts of the East Sea, South Sea, and the Northwest Pacific Ocean are primarily characterized as relatively clear case-I waters, while the coastal areas of the Yellow Sea and the East China Sea are mainly classified as highly turbid case-II waters. We expect that the QA algorithm will support GOCI-II users in terms of not only statistically identifying R_rs resulted with significant errors but also more reliable calibration with quality assured data. The algorithm will be included in the level-2 flag data provided with GOCI-II atmospheric correction.

• Proceedings of the Korean Vacuum Society Conference
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• 2012.08a
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• pp.311-312
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• 2012

본 발표에서는 광학적 분석 시스템에 적용 가능한 발광소자(광원)과 수광소자(광센서)를 집적화시키는 모듈(수 발광 집적모듈) 기술을 제시하고자 한다. 이러한 수-발광 집적모듈은 다양한 응용 분야에 적용 될 수 있다. 예를 들어, 광신호 감지를 위한 광통신용 송-수신 모듈(optical communication), 의료/진단 분야에서 단백질/DNA/박테리아 등의 검출 및 분석에 관한 바이오 센서(bio-sensor), 그리고 대기(가스)/수질 모니터링에 관한 환경센서 등 매우 광범위한 분야에 해당되는 요소 기술이라 할 수 있다. 특히, 이들 분야들 중 바이오 물질을 분석하고 검출하는 광학적 바이오 센서 기술은 높은 경제적 가치와 산업적 성장 잠재력으로 인해 오랫동안 활발한 연구가 진행되어 오고 있다. 이러한 광학적 바이오 센서에서 가장 범용적인 방법 중 하나가 항온-항체 면역반응을 기반으로 하는 형광 검출(fluorescence detection) 기법이다. 이러한 시스템은 전체적으로 광원, 광학계, 그리고 센서로 구성되는데 기존에 일반적으로 사용되고 있는 형광 현미경의 경우는 민감도가 우수하다는 장점은 있으나 상당히 고가이고 부피가 크며 복잡한 광학구성으로 이루어져 있다는 한계점을 가지고 있다. 이러한 맥락에서 고민감도를 확보하면서 휴대성, 고속처리, 저가 등의 특성을 가진 시스템에 대한 요구가 갈수록 증가하고 있다. 이를 해결하기 위한 핵심기술 중의 하나가 수-발광 부분을 집적화 시키는 기술이라 할 수 있다. 본 연구에서는 바이오 센서 기술의 하나로서 형광을 측정하여 혈액내의 진단 지표인자를 검출할 수 있는 휴대용 혈액진단기기에 적용되는 소형 수 발광 집적 모듈을 개발하였다. 혈액내의 검출 성분의 양에 따라 형광의 세기가 변화하게 됨으로써 정량적인 검출이 가능한 원리이다. 모듈의 구조는 크게 광원(발광소자), 광학계, 그리고 광센서(수광소자) 세 영역으로 나누어 진다. 광원은 635 nm 적색 레이저다이오드로서 형광체(Alexa Fluor 647/발광파장: 668 nm)를 여기 시키는 기능을 하며 장착된 볼렌즈 의해 샘플의 형광체 영역으로 집광된다. 광학계는 크게 시준렌즈(collimating lens)와 광학필터로 구성됨으로써 샘플로부터 발생되는 광을 적절하게 수광소자로 전달하는 기능을 하게 된다. 여기서 광학필터의 경우는 기본적으로 Distributed Bragg's Reflector(DBR) 구조로써 실리콘(Si) 포토다이오드 상부에 모노리식(monolithic)하게 형성되며 검출 샘플로부터 진행되는 레이저 광(잡음의 주원인)은 차단하고 형광(광신호)만 통과 시키는 기능을 하게 된다. 따라서 신호 대 잡음비(S/N ratio)를 향상시키기 위해서는 정밀한 광 필터링 기능이 요구됨으로써 박막의 세밀한 공정 조건과 구조적-광학적 특성 분석이 수행되었다. 마지막으로 포토다이오드 소자는 일반적인 구조 이외에 중앙에 원형 구멍이 형성된 특별한 구조가 적용된다. 이것은 포토다이오드 구조에 변화를 줌으로써 모듈 구조를 효율적으로 응용할 수 있다는 의미를 갖는다. 또한 포토다이오드의 전기적-광학적 측정 분석을 통해 잡음 및 감도 특성이 세부적으로 조사되며 형광신호를 효과적으로 측정할 수 있음을 확인하였다. 최종적으로 제작된 모듈은 약 $1{\times}1{\times}1cm^3$ 내외 정도의 크기를 갖는다. 요약하자면 본 발표에서는 광학적 바이오센서에 적용할 수 있는 소형 수-발광 소자 집적모듈을 소개한다. 전체 모듈 설계는 최소한의 부피를 가짐과 동시에 측정의 정밀성을 향상시키는데 초점을 맞추어 진행하였다. 세부요소인 광학필터와 포트다이오드의 경우 잡음 및 민감도에 미치는 중요성 때문에 세밀한 공정 및 특성분석이 수행되었다. 결론적으로 독자적인 설계 및 공정을 통해 휴대성 및 정밀성 등의 목적에 부합한 경쟁력 있는 수-발광 소자 집적모듈 제작 기술을 확보하였다.

• Proceedings of the Korean Vacuum Society Conference
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• 2012.08a
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• pp.375-375
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• 2012

Graphene is a sp2-hybridized carbon sheet with an atomic-level thickness and a wide range of graphene applications has been intensely investigated due to its unique electrical, optical, and mechanical properties. In particular, hybrid graphene structures combined with various nanomaterials have been studied in energy- and sensor-based applications due to the high conductivity, large surface area and enhanced reactivity of the nanostructures. Conventional metal-catalytic growth method, however, makes useful applications difficult since a transfer process, used to separate graphene from the metal substrate, should be required. Recently several papers have been published on direct graphene growth on the two dimensional planar substrates, but it is necessary to explore a direct growth of hierarchical nanostructures for the future graphene applications. In this study, uniform graphene layers were successfully synthesized on highly dense dielectric nanowires (NWs) without any external catalysts. We also demonstrated that the graphene morphology on NWs can be controlled by the growth parameters, such as temperature or partial pressure in chemical vapor deposition (CVD) system. This direct growth method can be readily applied to the fabrication of nanoscale graphene electrode with designed structures because a wide range of nanostructured template is available. In addition, we believe that the direct growth growth approach and morphological control of graphene are promising for the advanced graphene applications such as super capacitors or bio-sensors.

• Journal of the Korea Society of Computer and Information
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• v.25 no.3
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• pp.243-250
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• 2020

In this paper, we propose an effective software education scheme for universities. The key idea of this software education scheme is to analyze software curriculum of QS world university rankings Top 10, SW-oriented university, and regional main national university. And based on the results, we propose five improvements for the effective SW education method of universities. The first is to enhance the adaptability of the industry by developing courses based on the SW developer's job analysis in the curriculum development process. Second, it is necessary to strengthen the curriculum of the 4th industrial revolution core technologies(cloud computing, big data, virtual/augmented reality, Internet of things, etc.) and integrate them with various fields such as medical, bio, sensor, human, and cognitive science. Third, programming language education should be included in software convergence course after basic syntax education to implement projects in various fields. In addition, the curriculum for developing system programming developers and back-end developers should be strengthened rather than application program developers. Fourth, it offers opportunities to participate in industrial projects by reinforcing courses such as capstone design and comprehensive design, which enables product-based self-directed learning. Fifth, it is necessary to develop university-specific curriculum based on local industry by reinforcing internship or industry-academic program that can acquire skills in local industry field.