• 보건행정학회지
• /
• 제33권4호
• /
• pp.440-449
• /
• 2023

Background: This study aimed to analyze the prehospital process and reperfusion therapy process of acute ischemic stroke in Busan metropolitan area and examine the impact of living arrangement on the early management and functional outcomes of acute ischemic stroke (AIS). Methods: The patients who diagnosed with AIS and received reperfusion therapy at the Busan Regional Cardiovascular Center between September 2020 and May 2023 were selected. We investigated the patients' hospital arrival time (onset to door time) and utilization of 119 emergency ambulance services. Additionally, various time matrices related to reperfusion therapy after hospital were examined, along with the functional outcome at the 90-day after treatment. Results: Among the 753 AIS patients who underwent reperfusion therapy, 166 individuals (22.1%) were living alone. AIS patients living alone experienced significant delays in symptom detection (p<0.05) and hospital arrival compared to AIS patients with cohabitants (370.1 minutes vs. 210.2 minutes, p<0.001). There were no significant differences between the two groups in terms of 119 ambulance utilization and time metrics related with the reperfusion therapy. Independent predictors of prognosis in AIS patients were found to be age above 70, National Institutes of Health Stroke Scale score at admission, tissue plasminogen activator, living alone (odds ratio [OR], 1.785; 95% confidence interval [CI], 1.155-2.760) and interhospital transfer (OR, 1.898; 95% CI, 1.152-3.127). Delay in identification of AIS was shown significant correlation (OR, 2.440; 95% CI, 1.070-5.561) at living alone patients. Conclusion: This study revealed that AIS patients living alone in the Busan metropolitan region, requiring endovascular treatment, face challenges in the pre-hospital phase, which significantly impact their prognosis.

• Smart Structures and Systems
• /
• 제19권4호
• /
• pp.361-369
• /
• 2017

Electromechanical impedance method as an efficient tool in Structural Health Monitoring (SHM) utilizes the electromechanical impedance of piezoelectric materials which is directly related to the mechanical impedance of the host structure and will be affected by damages. In this paper, electromechanical impedance of piezoelectric patches attached to simply support rectangular plate is determined theoretically and experimentally in order to detect damage. A pairs of piezoelectric wafer active sensor (PWAS) patches are used on top and bottom of an aluminum plate to generate pure bending. The analytical model and experiments are carried out both for undamaged and damaged plates. To validate theoretical models, the electromechanical impedances of PWAS for undamaged and damaged plate using theoretical models are compared with those obtained experimentally. Both theoretical and experimental results demonstrate that by crack generation and intensifying this crack, natural frequency of structure decreases. Finally, in order to evaluate damage severity, damage metrics such as Root Mean Square Deviation (RMSD), Mean Absolute Percentage Deviation (MAPD), and Correlation Coefficient Deviation (CCD) are used based on experimental results. The results show that generation of crack and crack depth increasing can be detectable by CCD.

• 한국도서관정보학회지
• /
• 제52권1호
• /
• pp.79-108
• /
• 2021

헬스 분야에서 정보 검색의 어려움 중의 하나는 일반 사용자들이 전문적인 용어들을 이해하기가 어렵다는 점이다. 헬스와 관련된 전문 용어들은 일반 사용자들이 검색어로 사용하기 어렵기 때문에 이러한 전문 용어들이 자동적으로 검색어에 더해질 수 있다면 좀 더 검색의 효과를 높일 수 있을 것이다. 제안된 검색어 확장 모델은 전문 용어를 포함하는 MeSH(Medical Subject Headings)를 검색어 확장을 위한 단어 후보 군으로 이용하였다. 문서들은 MeSH용어들로 표현이 되고 이렇게 표현된 문서들의 집합에 대해서 LDA(Latent Dirichlet Analysis) 토픽들이 생성된 후, (검색어+초기 검색어에 의해 검색된 상위 k개 문서들)에 연관된 토픽 단어들이 원래의 검색어를 확장하는 데 쓰여졌다. MeSH로 구성된 토픽 단어들은 임의로 정해진 토픽 확률 임계값과 토픽을 구성하는 단어의 확률 임계값보다 높았을 때 초기의 검색어에 포함되었다. 특정수의 토픽을 갖는 LDA 모델에서 이러한 적절한 임계값의 설정을 통해 선택된 토픽 단어들은 검색어 확장에 이용되어 검색시에 infAP(inferred Average Precision)와 infNDCG(inferred Normalized Discounted Cumulative Gain)를 높이는데 효과적으로 작용하였다. 또한 토픽 확률값과 토픽 단어의 확률값을 곱하여 계산된 토픽 단어의 스코어가 높은 상위 k개의 단어를 검색어를 확장하는 데 이용하였을 때에도 검색의 성능이 향상될 수 있음을 확인하였다.

• Journal of Microbiology and Biotechnology
• /
• 제28권8호
• /
• pp.1247-1259
• /
• 2018

Raspberries are polyphenol-rich fruits with the potential to reduce the severity of the clinical signs associated with obesity, a phenomenon that may be related to changes in the gut microbiota. The aim of this study was to investigate the effect of raspberry supplementation on the fecal microbiota using an in vivo model of obesity. Obese diabetic db/db mice were used in this study and assigned to two experimental groups (with and without raspberry supplementation). Fecal samples were collected at the end of the supplementation period (8 weeks) and used for bacterial 16S rRNA gene profiling using a MiSeq instrument (Illumina). QIIME 1.8 was used to analyze the 16S data. Raspberry supplementation was associated with an increased abundance of Lachnospiraceae (p = 0.009), a very important group for gut health, and decreased abundances of Lactobacillus, Odoribacter, and the fiber degrader S24-7 family as well as unknown groups of Bacteroidales and Enterobacteriaceae (p < 0.05). These changes were enough to clearly differentiate bacterial communities accordingly to treatment, based on the analysis of UniFrac distance metrics. However, a predictive approach of functional profiles showed no difference between the treatment groups. Fecal metabolomic analysis provided critical information regarding the raspberry-supplemented group, whose relatively higher phytosterol concentrations may be relevant for the host health, considering the proven health benefits of these phytochemicals. Further studies are needed to investigate whether the observed differences in microbial communities (e.g., Lachnospiraceae) or metabolites relate to clinically significant differences that can prompt the use of raspberry extracts to help patients with obesity.

• Smart Structures and Systems
• /
• 제31권2호
• /
• pp.101-111
• /
• 2023

Structural health monitoring (SHM) covers a range of damage detection strategies for buildings. In real-time, SHM provides a basis for rapid decision making to optimise the speed and economic efficiency of post-event response. Previous work introduced an SHM method based on identifying structural nonlinear hysteretic parameters and their evolution from structural force-deformation hysteresis loops in real-time. This research extends and generalises this method to investigate the impact of a wide range of flag-shaped or pinching shape nonlinear hysteretic response and its impact on the SHM accuracy. A particular focus is plastic stiffness (K_p), where accurate identification of this parameter enables accurate identification of net and total plastic deformation and plastic energy dissipated, all of which are directly related to damage and infrequently assessed in SHM. A sensitivity study using a realistic seismic case study with known ground truth values investigates the impact of hysteresis loop shape, as well as added noise, on SHM accuracy using a suite of 20 ground motions from the PEER database. Monte Carlo analysis over 22,000 simulations with different hysteresis loops and added noise resulted in absolute percentage identification error (median, (IQR)) in K_p of 1.88% (0.79, 4.94)%. Errors were larger where five events (Earthquakes #1, 6, 9, 14) have very large errors over 100% for resulted K_p as an almost entirely linear response yielded only negligible plastic response, increasing identification error. The sensitivity analysis shows accuracy is reduces to within 3% when plastic drift is induced. This method shows clear potential to provide accurate, real-time metrics of non-linear stiffness and deformation to assist rapid damage assessment and decision making, utilising algorithms significantly simpler than previous non-linear structural model-based parameter identification SHM methods.

• 치위생과학회지
• /
• 제23권3호
• /
• pp.193-198
• /
• 2023

Background: The nose is located at the center of the face, and it is possible to determine race, sex, and the like. Research using the nasal index (NI) classification method to classify the shape of the nose is currently in progress. However, domestic research is required as most research is being conducted abroad. In this study, we used a 3D program to confirm the ratio of the nose shape of Koreans. Methods: One hundred patients (50 males and 50 females) in their 20s were evaluated (IRB approval no. DKUDH IRB 2020-01-007). Cone beam computed tomography was performed using the Mimics ver.22 (Materialise Co., Leuven, Belgium) 3D program to model the patient's skull and soft tissues into three views: coronal, sagittal, and frontal. To confirm the ratio of measurement metrics, analysis was performed using the SPSS ver. 23.0 (IBM Co., Armonk, NY, USA) program. Results: Ten leptorrhine (long and narrow) type, 76 mesorrhine (moderate shape) type, and 14 platyrrhine (broad and short) type noses were observed. In addition, as a result of sex comparison, five males had the leptorrhine (long and narrow) type, 40 mesorrhine (moderate shape), and five platyrrhine (broad and short) types. For females, five patients had the leptorrhine (long and narrow) type, 36 patients had the mesorrhine (moderate shape) type, and nine patients had the platyrrhine (broad and short) type. Conclusion: This study will be helpful when performing nose-related surgeries and procedures in clinical practice and for similar studies in the future.

• Asian Journal of Atmospheric Environment
• /
• 제5권4호
• /
• pp.237-246
• /
• 2011

To explore the sources of carbonaceous material in the airborne particulate matter (PM), comprehensive PM sampling was performed (3 to 14 January 2010) at a traffic hot spot site (HS), Farm Gate, Dhaka using several samplers: AirMetrics MiniVol (for $PM_{10}$ and $PM_{2.5}$) and MOUDI (for size fractionated submicron PM). Long-term PM data (April 2000 to March 2006 and April 2000 to March 2010 in two size fractions ($PM_{2.2}$ and $PM_{2.2-10}$) obtained from two air quality-monitoring stations, one at Farm Gate (HS) and another at a semi-residential (SR) area (Atomic Energy Centre, Dhaka Campus, (AECD)), respectively were also analyzed. The long-term PM trend shows that fine particulate matter concentrations have decreased over time as a result of government policy interventions even with increasing vehicles on the road. The ratio of $PM_{2.5}/PM_{10}$ showed that the average $PM_{2.5}$ mass was about 78% of the $PM_{10}$ mass. It was also found that about 63% of $PM_{2.5}$ mass is $PM_1$. The total contribution of BC to $PM_{2.5}$ is about 16% and showed a decreasing trend over the years. It was observed that $PM_1$ fractions contained the major amount of carbonaceous materials, which mainly originated from high temperature combustion process in the $PM_{2.5}$. From the IMPROVE TOR protocol carbon fraction analysis, it was observed that emissions from gasoline vehicles contributed to $PM_1$ given the high abundance of EC1 and OC2 and the contribution of diesel to $PM_1$ is minimal as indicated by the low abundance of OC1 and EC2. Source apportionment results also show that vehicular exhaust is the largest contributors to PM in Dhaka. There is also transported $PM_{2.2}$from regional sources. With the increasing economic activities and recent GDP growth, the number of vehicles and brick kilns has significantly increased in and around Dhaka. Further action will be required to further reduce PM-related air pollution in Dhaka.

• 디지털융복합연구
• /
• 제17권1호
• /
• pp.239-247
• /
• 2019

감정을 정확히 예측하는 것은 환자중심의 의료디바이스 개발 및 감성관련 산업에서 매우 중요한 이슈이다. 감정예측에 관한 많은 연구 중 감정 예측에 심박 변동성과 뉴로-퍼지 접근법을 적용한 연구는 없다. 본 연구는 HRV를 이용한 ANFEP(Adaptive Neuro Fuzzy system for Emotion Prediction)을 제안한다. ANFEP의 핵심 기능은 인공 신경망과 퍼지시스템을 통합해 예측 모델을 학습하는 ANFIS(Adaptive Neuro-Fuzzy Inference System)에 기반한다. 제안 모형의 검증을 위해 50명의 실험자를 대상으로 청각자극으로 감정을 유발하고, 심박변이도를 구하여 ANFEP 모형에 입력하였다. STDRR과 RMSSD를 입력으로 하고 입력변수 당 2개의 소속함수로 하는 ANFEP모형이 가장 좋은 결과를 나타났다. 제안한 감정예측 모형을 선형회귀 분석, 서포트 벡터 회귀, 인공신경망, 랜덤 포레스트와 비교한 결과 본 제안모형이 가장 우수한 성능을 보였다. 연구 결과는 보다 적은 입력으로 신뢰성 높은 감정인식이 가능함을 입증했고, 이를 활용해 보다 정확하고 신뢰성 높은 감정인식 시스템 개발에 대한 연구가 필요하다.

• 지능정보연구
• /
• 제26권3호
• /
• pp.127-147
• /
• 2020

세계는 신형 코로나바이러스 감염증(COVID-19)으로 수 많은 인명 피해와 경제적 손실을 기록하고 있는 상황이다. 우리나라 정부는 연구개발(Research & Development)을 통해 국가 감염병 위기를 극복하려는 전략을 수립하고 실행하기 위한 투자방향을 수립하였다. 기존 기술분류나 과학기술 표준분류에 따른 통계를 활용하면 특정 R&D 분야의 특이점 및 변화를 발견하기 어렵다는 한계가 존재해왔다. 최근 우리나라 감염병 연구개발 과제를 대상으로 수요자의 목적에 맞게 분류체계를 수립하고 연구비 비교 분석을 통해 투자가 요구되는 연구 분야를 제시하는 연구들이 진행되었다. 하지만 현재 국가 보건 안보와 신성장 산업육성이라는 목표를 달성하기 위한 실행방안으로 요구되고 있는 전염병 연구분야의 국가간 협력전략 수립에 필요한 정보를 체계적으로 제공하고 있지 못한 상황이다. 따라서 국가 공동 연구개발 전략 수립을 위한 분류체계와 분류모델기반의 정보서비스에 대한 연구가 요구되고 있다. 우선 감염병관련 NTIS 과제데이터를 기반으로 정성분석을 통해 7개의 분류체계를 도출하였다. 스코퍼스(Scopus) 데이터와 양방향 RNN모델을 사용하여, 분류체계 모델을 학습시켰다. 최종적인 모델의 분류 성능은 90%이상의 높은 정확도와 강건성을 확보하였다. 실증연구를 위해 주요 국가의 코로나바이러스 연구개발 과제를 대상으로 전염병 분류체계를 적용하였다. 주요 국가의 감염병(코로나바이러스) 연구개발 과제를 분류체계별로 분석한 결과, 세계적으로 유행하는 바이러스의 예상치 못한 창궐이 확산되는 속도에 비해 백신과 치료제 개발이 제대로 이뤄지지 않는 원인의 배경을 간접적으로 확인할 수 있었다. 국가별 비교분석을 통해 미국과 일본은 상대적으로 모든 영역에 골고루 연구개발 투자를 하고 있는 것으로 나타난 반면, 유럽은 상대적으로 특정 연구분야에 많은 투자를 하는 집중화 전략을 취하는 것으로 나타났다. 동시에 주요 국가의 코로나 바이러스 주요 연구조직에 대한 정보를 분류체계별로 제공하여 국제 공동R&D 전략의 기초정보를 제공하였다. 본 연구 결과를 통해 세 가지 정책적 의미를 도출할 수 있다. 첫째, 데이터기반 과학기술정책 관점에서 수요자 관심분야에 대한 국가 R&D사업의 정보를 글로벌 기준으로 문서를 분류하는 방안을 제시하였다. 둘째, 감염병관련 국가 R&D사업 영역에 대한 정보분석 서비스 기획의 기반을 마련하였다. 마지막으로 국가 감염병 R&D 분류체계 수립을 통해 분류 체계의 궁극적 목표인 산업, 기업, 정책 정보를 제공할 수 있는 기반을 마련한 것이다.