• 국제학술발표논문집
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• The 8th International Conference on Construction Engineering and Project Management
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• pp.387-396
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• 2020

Wearable biosensors have the potential to non-invasively and continuously monitor seniors' stress in their daily interaction with the urban environment, thereby enabling to address the stress and ultimately advance their outdoor mobility. However, current wearable biosensor-based stress detection methods have several drawbacks in field application due to their dependence on batch-learning algorithms. First, these methods train a single classifier, which might not account for multiple subjects' different physiological reactivity to stress. Second, they require a great deal of computational power to store and reuse all previous data for updating the signle classifier. To address this issue, we tested the feasibility of online multi-task learning (OMTL) algorithms to identify multiple seniors' stress from electrodermal activity (EDA) collected by a wristband-type biosensor in a daily trip setting. As a result, OMTL algorithms showed the higher test accuracy (75.7%, 76.2%, and 71.2%) than a batch-learning algorithm (64.8%). This finding demonstrates that the OMTL algorithms can strengthen the field applicability of the wearable biosensor-based stress detection, thereby contributing to better understanding the seniors' stress in the urban environment and ultimately advancing their mobility.

• 정보처리학회논문지:소프트웨어 및 데이터공학
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• 제5권9호
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• pp.433-440
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• 2016

철도 선로전환기는 열차의 진로를 현재의 궤도에서 다른 궤도로 제어하는 장치이다. 선로전환기의 이상 상황은 탈선 등과 같은 심각한 문제를 발생할 수 있기 때문에, 선로전환기의 스트레스를 지속적으로 모니터링 하는 것은 매우 중요하다. 본 논문에서는 선로전환기가 작동할 때 발생하는 소리 정보를 이용하여 선로전환기의 스트레스를 탐지하는 시스템을 제안한다. 제안하는 시스템은 선로전환기의 동작 시 발생하는 소리 데이터로부터 자질 선택방법을 사용하여 스트레스 탐지에 유효한 감소된 차원의 자질 부분집합을 선택한 후, 기계학습의 대표적 모델인 SVM(Support Vector Machine)을 이용하여 선로전환기의 스트레스 상태 여부를 탐지한다. 테스트용 선로전환기를 실제 구동하며 수집한 소리 데이터를 이용하여, 본 논문에서 제안하는 시스템의 성능을 실험적으로 검증한 바 98%를 넘는 정확도를 확인하였다.

• Steel and Composite Structures
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• 제19권1호
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• pp.131-152
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• 2015

Easy detection and evaluation of defect in the tube structure is a continuous problem and remains a significant demand in tube inspection technologies. This study is aimed to automate defect detection using the pattern recognition approach based on the classification of high frequency stress wave signals. The stress wave signals from vibrational impact excitation on several tube conditions were captured to identify the defect in ASTM A179 seamless steel tubes. The variation in stress wave propagation was captured by a high frequency sensor. Stress wave signals from four tubes with artificial defects of different depths and one reference tube were classified using the autoregressive (AR) algorithm. The results were demonstrated using a dendrogram. The preliminary research revealed the natural arrangement of stress wave signals were grouped into two clusters. The stress wave signals from the healthy tube were grouped together in one cluster and the signals from the defective tubes were classified in another cluster. This approach was effective in separating different stress wave signals and allowed quicker and easier defect identification and interpretation in steel tubes.

• 농업과학연구
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• 제50권4호
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• pp.883-902
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• 2023

Water is critical to the health and productivity of fruit trees. Efficient monitoring of water stress is essential for optimizing irrigation practices and ensuring sustainable fruit production. Short-range sensing can be reliable, rapid, inexpensive, and used for applications based on well-developed and validated algorithms. This paper reviews the recent advancement in fruit tree water stress detection via short-range sensing, which can be used for irrigation scheduling in orchards. Thermal imagery, near-infrared, and shortwave infrared methods are widely used for crop water stress detection. This review also presents research demonstrating the efficacy of short-range sensing in detecting water stress indicators in different fruit tree species. These indicators include changes in leaf temperature, stomatal conductance, chlorophyll content, and canopy reflectance. Short-range sensing enables precision irrigation strategies by utilizing real-time data to customize water applications for individual fruit trees or specific orchard areas. This approach leads to benefits, such as water conservation, optimized resource utilization, and improved fruit quality and yield. Short-range sensing shows great promise for potentially changing water stress monitoring in fruit trees. It could become a useful tool for effective fruit tree water stress management through continued research and development.

• Journal of Biosystems Engineering
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• 제24권6호
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• pp.539-546
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• 1999

오이를 공시재료로 하여, 생육중인 식물 잎으로부터 비교적 신속하게 생체정보 수집이 가능한 비파괴 계측기인 엽록소 측정기, 엽록소 형광측정기, 적외선 엽온측정기, 반사형 분광분석기를 이용하여 질소 결핍장해 오이의 조기 진단 가능성 여부와 그 유용한 정도를 파악하기 위하여 수행한 연구의 주요 결과는 다음과 같다. 1) 엽록소 측정기의 측정값으로서 질소 결핍장해 오이의 진단은 엽록소 함량 45 SPAD 이하 여부로서 판단할 수 있고, 이에 의한 질소 결핍 장해의 진단은 장해 발생 후 빠르면 3일 정도면 적중율 95%수준의 장해 진단이 가능하고 7∼10일 후엔 높은 정확도의 진단이 가능함을 알 수 있었다. 2) 엽록소 형광 측정에 의한 질소 결핍장해 오이의 진단은 장해 발생 후 빠르면 5일째부터 적중률 95%수준의 장해 진단이 가능하며, 이에 의한 오이의 질소 결핍장해 진단은 엽록소 함량 측정에 의한 진단보다는 우수하지 못하다. 그리고 대기-엽온차에 의해 질소 결핍장해 오이의 진단은 불가능한 것으로 판단되었다. 3) 분광분석기의 흡광도 분석에 의한 질소 결핍 진단의 민감 파장대는 562∼564 nm, 700∼724 nm, 1,886∼1,894 nm으로 분석되었다. 이러한 영역의 파장에 의한 질소 결핍장해 오이의 진단은 장해 발생후 3∼4일째부터 적중을 95%수준의 진단이 가능하며, 진단의 정확도는 본 연구에서 사용한 4가지 측정기 중 가장 우수하였다.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2021년도 추계학술대회
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• pp.613-617
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• 2021

서비스 산업의 성장과 함께 감정노동자의 스트레스가 사회적 문제로 인식되어 2018년 감정노동자 보호법이 시행되었다. 그러나 실질적인 감정노동자 보호 시스템의 부족으로 스트레스 관리를 위한 디지털 시스템이 필요한 시점이다. 본 논문에서는 대표적인 감정노동자인 고객 상담사를 위한 딥러닝 기반 스트레스 감지 시스템을 제안한다. 시스템은 실시간 얼굴검출 모듈, 한국인 감정 이미지 중심의 이미지 빅데이터를 딥러닝한 감정분류 FER 모듈, 마지막으로 스트레스 수치만을 시각화하는 모니터링 모듈로 구성된다. 이 시스템을 통하여 감정노동자의 스트레스 모니터링과 정신질환 예방을 목표로 설계하였다.

• 한국생물공학회:학술대회논문집
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• 한국생물공학회 2000년도 춘계학술발표대회
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• pp.355-356
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• 2000

Three 'stress probe' plasmids were constructed and characterized which utilize a green fluorescent protein (CFP) as a non-invasive reporter to elucidate Escherichia coli cellular stress responses in quiescent or 'resting' cells. Facile detection of cellular stress levels was achieved by fusion of three heat shock stress protein promoter elements, those of the heat shock transcription factor ${\sigma}^{32}$, pretense subunit ClpB, and chaperone DnaK, to the reporter gene $gfp_{uv}$. When perturbed by chemical or physical stress (such as heat shock, nutrient (amino acid) limitation, addition of IPTG, acetic acid, ethanol, phenol, antifoam, and salt (osmotic shock), the E. coli cells produced GFPuv which was easily detected from within the cells as emitted green fluorescence. A temporal and amplitudinal mapping of these responses was performed, demonstrating regions where quantitative delineation of cell stress was afforded.

• 전기학회논문지
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• 제59권6호
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• pp.1131-1135
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• 2010

The development of modern civilization result from the abundance of material. Yet modern people live with chronic mild stress. Excessive chronic mild stress leads to various diseases. From the risk of the disease in order to protect our bodies need to manage chronic mild stress. The purpose of this study is to inspection the effectiveness of detecting in chronic mild stress using the Multi-sensor system. The Multi-sensor system is designed that can be measure three kinds of vital signals of chronic mild stress for the detection. First Photoplethysmogram(PPG), second Electro Dermal Activity(EDA), third Skin Temperature(SKT). The ages and occupations exposed to chronic mild stress, people often use out of this system was applied to dairy products(Pen). In addition, vital signals that occur when the variety of noise was used to remove the accelerometer. Chronic mild stress by the analysis of measured vital signals from Multi-sensor system to the measurement information to a PC to a wireless transmission(Bluetooth). In this study, using Multi-sensor system writing conditions and a variety of situations in the movement to measure vital signals and measurement results verified the accuracy and reliability. Through this measure chronic mild stress in everyday life and managing to maintain will help more healthy lifestyle.

• Asian-Australasian Journal of Animal Sciences
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• 제28권4호
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• pp.592-598
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• 2015

Stress adversely affects the wellbeing of commercial chickens, and comes with an economic cost to the industry that cannot be ignored. In this paper, we first develop an inexpensive and non-invasive, automatic online-monitoring prototype that uses sound data to notify producers of a stressful situation in a commercial poultry facility. The proposed system is structured hierarchically with three binary-classifier support vector machines. First, it selects an optimal acoustic feature subset from the sound emitted by the laying hens. The detection and classification module detects the stress from changes in the sound and classifies it into subsidiary sound types, such as physical stress from changes in temperature, and mental stress from fear. Finally, an experimental evaluation was performed using real sound data from an audio-surveillance system. The accuracy in detecting stress approached 96.2%, and the classification model was validated, confirming that the average classification accuracy was 96.7%, and that its recall and precision measures were satisfactory.

• 비파괴검사학회지
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• 제11권1호
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• pp.23-30
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• 1991

In this study the bonding quality evaluation of FRP honeycomb structure was performed by the ultrasonic C-Scan method and stress wave factor measurements. These NDT techniques could be well applied to the disbonding detection of FRP honeycomb structures. Especially, stress wave factor (SWF) measurement is expected to be a useful technique in field applications.