A5100911787- Diverse Topics in Contemporary Research
- Data-Driven Disease Surveillance
- Local Government Finance and Decentralization
- COVID-19 epidemiological studies
- Anomaly Detection Techniques and Applications
- Non-Invasive Vital Sign Monitoring
- Consumer Perception and Purchasing Behavior
- RNA Interference and Gene Delivery
- Physical Activity and Health
- earthquake and tectonic studies
- Innovation in Digital Healthcare Systems
- Economic Zones and Regional Development
- Context-Aware Activity Recognition Systems
- Advanced biosensing and bioanalysis techniques
- Immunotherapy and Immune Responses
- Emotion and Mood Recognition
- SARS-CoV-2 and COVID-19 Research
- Korean Peninsula Historical and Political Studies
- Korean Urban and Social Studies
- Influenza Virus Research Studies
- Educational Systems and Policies
- Lipid Membrane Structure and Behavior
- Geochemistry and Geologic Mapping
- Human-Animal Interaction Studies
- Geological and Geochemical Analysis
Catholic University of Korea
2022-2025
Kyungdong University
2014
Infantile epileptic spasm syndrome (IESS) is characterized by clustered spasms and hypsarrhythmia on electroencephalography (EEG). This study aimed to investigate the temporal dynamics dynamic synchronization of neural networks in IESS using EEG microstate analysis interictal recordings from 49 healthy controls (HC) 42 patients with IESS. Five maps were identified, features including global explained variance (GEV), mean correlation, occurrence, time coverage, duration, transition...
Accelerometer data collected from wearable devices have recently been used to monitor physical activities (PAs) in daily life. While the intensity of PAs can be distinguished with a cut-off approach, it is important discriminate different behaviors similar accelerometry patterns estimate energy expenditure. We aim overcome imbalance problem that negatively affects machine learning-based PA classification by extracting well-defined features and applying undersampling oversampling methods....
Abstract Since the coronavirus pandemic, mRNA vaccines have revolutionized field of vaccinology. Lipid nanoparticles (LNPs) are proposed to enhance delivery efficiency; however, their design is suboptimal. Here, a rational method for designing LNPs explored, focusing on ionizable lipid composition and structural optimization using machine learning (ML) techniques. A total 213 analyzed random forest regression models trained with 314 features predict expression efficiency. The models, which...
한반도 남부 산청회장암체 내에는 철 티탄 광체와 고철질 백립암이 분포한다. 이들에 대한 상세한 야외 노두 스케치와 더불어 산상과 분포 특징을 기재하였다. 또한 암석학적 특정을 종합하여 광체를 분류하고 백립암 사이의 암석성인적 관련성을 해석하고자 하였다 철-티탄 광체는 모암인 회장암질암과의 경계 특성과 내부변형 정도에 따라, 규칙 관입광맥형과 불규칙 광맥군형으로 나누어진다. 전자는 회장암질암과 일정한 방향의 관입경계를 이루며 내부에는 뚜렷한 연성전단변형이 인지되는 반면, 후자는 구불구불하고 불규칙한 보이며 내부 연성전단변형은 거의 인지되지 않는다. 회장암질암의 엽리를 절 단하고 있으며 회장암을 포획하고 있어, 회장암질암 엽리의 생성 이후에 관입하였다. 백립암도 주변 회장암질암을 관입 포획하며 관입경계와 평행한 엽리가 관찰된다. 백립암은 광체들과 동일한 화학조성의 티탄철석을 함유하며 내부로 주입, 연장되어 광체로 변화됨이 이상의 사질들은 연구지역 광체의 모암임을 지시한다....
Animal activity recognition (AAR) using wearable sensor data has gained significant attention due to its applications in monitoring and understanding animal behavior. However, two major challenges hinder the development of robust AAR models: domain variability difficulty obtaining labeled datasets. To address this issue, study intensively investigates impact unsupervised adaptation (UDA) for AAR. We compared three distinct types UDA techniques: minimizing divergence-based, adversarial-based,...
<sec> <title>BACKGROUND</title> The number of confirmed coronavirus disease (COVID-19) cases is a crucial indicator policies and lifestyles. Previous studies have attempted to forecast using machine learning techniques that utilize previous case counts search engine queries predetermined by experts. However, they limitations in reflecting temporal variations associated with pandemic dynamics. </sec> <title>OBJECTIVE</title> We propose novel framework extract keywords highly COVID-19,...
The number of confirmed COVID-19 cases is a crucial indicator policies and lifestyles. Previous studies have attempted to forecast using machine learning techniques that use previous case counts search engine queries predetermined by experts. However, they limitations in reflecting temporal variations associated with pandemic dynamics.
Purpose - The study aims to investigate empirically the effects of flow an Internet shopping mall upon consumers' revisit intention and purchase intention. Research design, data, methodology subjects comprised customers malls. SPSS 19.0 for Windows was used verify models hypotheses. Frequency, factors, reliability, regression analysis were used. Results This classified behavior factors malls into four categories-skills, convenience, mutual reaction-to their influence on flow. Skills...