• Smart Structures and Systems
• /
• 제20권6호
• /
• pp.683-696
• /
• 2017

In this study, the reliability of nonlinear ultrasonic modulation based fatigue crack detection is improved using a feature-level data fusion approach. When two ultrasonic inputs at two distinct frequencies are applied to a specimen with a fatigue crack, modulation components at the summation and difference of these two input frequencies appear. First, the spectral amplitudes of the modulation components and their spectral correlations are defined as individual features. Then, a 2D feature space is constructed by combining these two features, and the presence of a fatigue crack is identified in the feature space. The effectiveness of the proposed fatigue crack detection technique is experimentally validated through cyclic loading tests of aluminum plates, full-scale steel girders and a rotating shaft component. Subsequently, the improved reliability of the proposed technique is quantitatively investigated using receiver operating characteristic analysis. The uniqueness of this study lies in (1) improvement of nonlinear ultrasonic modulation based fatigue crack detection reliability using feature-level data fusion, (2) reference-free fatigue crack diagnosis without using the baseline data obtained from the intact condition of the structure, (3) application to full-scale steel girders and shaft component, and (4) quantitative investigation of the improved reliability using receiver operating characteristic analysis.

• Structural Engineering and Mechanics
• /
• 제71권1호
• /
• pp.57-63
• /
• 2019

During the last two decades, much joint research regarding vibration based methods has been done, leading to developing various algorithms and techniques. These algorithms and techniques can be divided into modal methods and signal methods. Although modal methods have been widely used for health monitoring and damage detection, signal methods due to higher efficiency have received considerable attention in various fields, including aerospace, mechanical and civil engineering. Signal-based methods are derived directly from the recorded responses through signal processing algorithms to detect damage. According to different signal processing techniques, signal-based methods can be divided into three categories including time domain methods, frequency domain methods, and time-frequency domain methods. The frequency domain methods are well-known and interest in using them has increased in recent years. To determine dynamic behaviours, to identify systems and to detect damages of bridges, different methods and algorithms have been proposed by researchers. In this study, a new algorithm to detect seismic damage in the bridge's piers is suggested. To evaluate the algorithm, an analytical model of a bridge with simple spans is used. Based on the algorithm, before and after damage, the bridge is excited by a sine force, and the piers' responses are measured. The dynamic specifications of the bridge are extracted by Power Spectral Density function. In addition, the Least Square Method is used to detect damage in the bridge's piers. The results indicate that the proposed algorithm can identify the seismic damage effectively. The algorithm is output-only method and measuring the excitation force is not needed. Moreover, the proposed approach does not need numerical models.

• Journal of Microbiology and Biotechnology
• /
• 제29권3호
• /
• pp.454-464
• /
• 2019

Salmonellosis is a highly contagious bacterial disease that threatens both human and poultry health. Tests that can detect Salmonella in the field are urgently required to facilitate disease control and for epidemiological investigations. Here, we combined loop-mediated isothermal amplification (LAMP) with a chromatographic lateral flow dipstick (LFD) to rapidly and accurately detect Salmonella. LAMP primers were designed to target the Salmonella invA gene. LAMP conditions were optimized by adjusting the ratio of inner to outer primers, $MgSO_4$ concentration, dNTP mix concentration, amplification temperature, and amplification time. We evaluated the specificity of our novel LAMP-LFD method using six Salmonella species and six related non-Salmonella strains. All six of the Salmonella strains, but none of the non-Salmonella strains, were amplified. LAMP-LFD was sensitive enough to detect concentrations of Salmonella enterica subsp. enterica serovar Pullorum genomic DNA as low as $89fg/{\mu}l$, which is 1,000 times more sensitive than conventional PCR. When artificially contaminated feed samples were analyzed, LAMP-LFD was also more sensitive than PCR. Finally, LAMP-LFD gave no false positives across 350 chicken anal swabs. Therefore, our novel LAMP-LFD assay was highly sensitive, specific, convenient, and fast, making it a valuable tool for the early diagnosis and monitoring of Salmonella infection in chickens.

• Journal of Platform Technology
• /
• 제9권3호
• /
• pp.36-43
• /
• 2021

뇌졸중 질환은 전세계적으로 가장 중요한 사망원인 중 하나이며, 특히 고령자에게 장애의 원인이 되는 가장 중요한 질환이다. 뇌졸중 질환이 발생하면 사망 또는 심각한 장애를 유발하기 때문에, 적극적인 일차 예방과 전조증상의 빠른 발견이 매우 중요하다. 특히, 일상생활에서의 뇌졸중 전조증상 발병을 감지 및 정확히 예측하여 전문가의 신속한 진단을 유도할 수 있어야 한다. 최근까지의 연구에서는 뇌졸중 환자의 전조증상을 예측하는 방법론으로 CT(Computed Tomography)나 MRI(Magnetic Resonance Imaging)와 같은 영상 분석이 대부분이었으나, 이러한 접근에는 오랜 검사 시간과 높은 검사 비용 등에 대한 한계점을 가지고 있다. 본 논문에서는 고령자의 뇌졸중 질환 발병이 보행 시 족압(Foot Pressure)에 어떤 영향을 미치는지 임상 데이터를 이용해 실험하였다. 실험 결과, 보행 중에 뇌졸중 고령자와 일반 고령자 간에 12개의 셀에서 * p < .05 인 유의미한 차가 있음을 분석 및 검증하였다. 결과적으로 고령의 뇌졸중 환자와 일반 고령자의 일상생활의 보행 패턴에 유의미한 차이를 발견했다는 것에 그 의미가 크다고 할 수 있다.

• 농촌계획
• /
• 제27권1호
• /
• pp.9-20
• /
• 2021

In order to develop practical indicator that can diagnose the regional conditions and characteristics of fishing villages, this study reviewed domestic and foreign researches and selected the diagnostic indicator of fishing villages by spatial unit. The major categories are divided into population and society, economic conditions, and living conditions. The middle categories consists of population, household, industry, tourism, settlement, environment, safety, health and welfare, education, and culture and leisure. The indicator were selected with reference to the existence of statistical data officially provided according to the spatial range(Si/Gun, eup/myeon, village). Based on the selected indicator, the test evaluation was conducted in Jindo-gun, Jeollanam-do by applying data that can be obtained from KOSIS and web GIS. It is judged that the diagnostic indicator developed through this research can be used in various ways from the planning stage to the implementation stage of the regional development project, such as grasping the current conditions, setting improvement targets, promotion and evaluation/monitoring of the project. In addition, it is expected that it will be possible to carry out regional diagnosis for each spatial unit and to plan and implement regional development projects by giving priority to areas where the level of each department is insufficient.

• 한국정보통신학회:학술대회논문집
• /
• 한국정보통신학회 2022년도 춘계학술대회
• /
• pp.406-409
• /
• 2022

최근 몇 년 동안, AI 시스템, 블록체인, VR/AR, 3D 프린팅, 로봇 공학, 나노 기술과 같은 기술의 발전은 바로 우리 눈앞에서 건강 관리의 미래를 재편하고 있습니다. 또한, 의료는 소비자의 요구에 초점을 맞춘 예방 중심의 의학으로 패러다임이 전환되었습니다. Covid-19와 같은 전염병의 확산으로 의료 및 치료 시설의 정의가 변경되어 병원의 물리적 환경을 재설계하고 사회적 거리 두기 요구사항을 해결하도록 통신 모델을 조정하고 가상 의료 솔루션을 구현하고 새로운 임상 프로토콜을 수립하기 위한 즉각적인 조치가 필요하게 되었습니다. 전통적으로 의료 시스템의 허브 역할을 해 온 병원은 이러한 환경에 맞서 스스로를 재정립하는 것을 추구하거나 강요당하고 있습니다. 미래의 건강관리는 질병을 치료하는 것뿐만 아니라 건강과 예방에 초점을 맞출 것으로 예상됩니다. 개인화된 진료에서는 장기적인 예방 전략, 원격 모니터링, 조기 진단 및 탐지가 매우 중요합니다. 이러한 현대 기술로 정의되는 스마트 헬스케어에 대한 관심이 높아짐에 따라, 본 연구는 스마트 헬스케어의 정의와 서비스 종류를 조사했습니다. 스마트 병원의 배경과 기술적 측면도 문헌 검토를 통해 탐구했습니다.

• Journal of Yeungnam Medical Science
• /
• 제40권4호
• /
• pp.402-411
• /
• 2023

Background: We hypothesized that fatty liver disease (FLD) is associated with a high prevalence of hearing loss (HL) owing to metabolic disturbances. This study aimed to evaluate the association between FLD and HL in a large sample of the Korean population. Methods: We used a dataset of adults who underwent routine voluntary health checkups (n=21,316). Fatty liver index (FLI) was calculated using Bedogni's equation. The patients were divided into two groups: the non-FLD (NFLD) group (n=18,518, FLI <60) and the FLD group (n=2,798, FLI ≥60). Hearing thresholds were measured using an automatic audiometer. The average hearing threshold (AHT) was calculated as the pure-tone average at four frequencies (0.5, 1, 2, and 3 kHz). HL was defined as an AHT of >40 dB. Results: HL was observed in 1,370 (7.4%) and 238 patients (8.5%) in the NFLD and FLD groups, respectively (p=0.041). Compared with the NFLD group, the odds ratio for HL in the FLD group was 1.16 (p=0.040) and 1.46 (p<0.001) in univariate and multivariate logistic regression analyses, respectively. Linear regression analyses revealed that FLI was positively associated with AHT in both univariate and multivariate analyses. Analyses using a propensity score-matched cohort showed trends similar to those using the total cohort. Conclusion: FLD and FLI were associated with poor hearing thresholds and HL. Therefore, active monitoring of hearing impairment in patients with FLD may be helpful for early diagnosis and treatment of HL in the general population.

• BioChip Journal
• /
• 제16권
• /
• pp.49-57
• /
• 2020

During living donor liver transplantation, a number of blood vessels and bile ducts are anastomosed while the liver and gallbladder are resected in the donor and recipient. Early detection and treatment of complications after surgery by evaluating the function of blood vessels and the biliary tract is crucial. A biosensing chip that can monitor patient health status from the bile excreted during the recovery process has been developed using a surface-enhanced Raman sensing chip. Surface-enhanced Raman spectroscopy signals of bile obtained from normal bile duct ligation and gallbladder damage mouse models using a cautery device were identified and analyzed. The surface-enhanced Raman chip with a nanometer-level porous structure can selectively separate the nanometer biomarkers and measure the Raman signal. Through the detection of nanometer biomarkers in the bile and comparative analysis of histopathology, the Raman signal in the damaged gallbladder was compared with that caused by liver damage due to bile duct ligation, showing that it becomes a biosensing chip for monitoring recovery.

• 근관절건강학회지
• /
• 제21권1호
• /
• pp.1-10
• /
• 2014

Purpose: The purpose of the study was to identify the attributes of self-help groups, their antecedents and consequences relating to self-help groups. Methods: We used the Walker and Avant (2010) method using the key word "self-help groups" the Korea Education and Research Information Service (www.riss4u.net), Pubmed, CINAHL and ProQuest for articles on this topic published between January 2000 and March 2013 were searched. Ultimately, 64 domestic and 21 foreign papers were selected for in-depth analysis. Results: The attributes of self-help groups are as follows: 1) members share common experiences and are supportive of each other; 2) members set goals for individual change; 3) groups are self-monitoring; 4) groups learn problem-solving processes through voluntary and active participation; and 5) groups are small and meet regularly. The antecedents of self-help groups are as follows: 1) an intervention by an expert; 2) a diagnosis of their illness; 3) motivation to change individuals' state; and 4) educational desire. The consequences of self-help groups are the relief of symptoms, the improvement of physiological parameters and quality of life, the decrease in depression, stress, and anxiety, the improvement of illness-related knowledge and self-help activity, and a change in beliefs. Conclusion: Self-help groups can be used as an intervention strategy to help people with chronic illness manage their own problems.

• 한국전산구조공학회논문집
• /
• 제34권1호
• /
• pp.25-33
• /
• 2021

머신러닝 기법의 발달과 함께 기계에서 발생하는 다양한 종류(진동, 온도, 유량 등)의 데이터를 활용하여 기계의 상태를 진단하고 이상 탐지 및 비정상 분류 연구도 활발히 진행되고 있다. 특히 진동 데이터를 활용한 회전 기계의 상태 진단은 전통적인 기계 상태 모니터링 분야로 오랜 기간 동안 연구가 진행되었고, 연구 방법 또한 매우 다양하다. 본 연구에서는 가정용 에어컨에 사용되는 로터리 압축기에 가속도계를 직접 설치하여 진동 데이터를 수집하는 실험을 진행하였다. 데이터 부족 문제를 해결하기 위해 데이터 분할을 수행하였으며, 시간 영역에서의 진동 데이터로부터 통계적, 물리적 특징들을 추출한 후, Chi-square 검증을 통해 고장 분류 모델의 주요 특징을 추출하였다. SVM(Support Vector Machine) 모델은 압축기의 정상 혹은 이상 유무를 분류하기 위해 개발되었으며, 파라미터 최적화를 통해 분류 정확도를 개선하였다.