Assessment of Vigilance Level during Work: Fitting a Hidden Markov Model to Heart Rate Variability

This study aimed to enhance the real-time performance and accuracy of vigilance assessment by developing a hidden Markov model (HMM). Electrocardiogram (ECG) signals were collected and processed to remove noise and baseline drift. A group of 20 volunteers participated in the study. Their heart rate variability (HRV) was measured to train...

Design knowledge graph-aided conceptual product design approach based on joint entity and relation extraction

Design knowledge is critical to creating ideas in the conceptual design stage of product development for innovation. Fragmentary design data, massive multidisciplinary knowledge call for the development of a novel knowledge acquisition approach for conceptual product design. This study proposes a Design Knowledge Graph-aided (DKG-aided)...

Using knowledge graphs and deep learning algorithms to enhance digital cultural heritage management

Cultural heritage management poses significant challenges for museums due to fragmented data, limited intelligent frameworks, and insufficient applications. In response, a digital cultural heritage management approach based on knowledge graphs and deep learning algorithms is proposed to address the above challenges. A joint entity-relation...

Chemical signal regulated injectable coacervate hydrogels

In the quest for stimuli-responsive materials with specific, controllable functions, coacervate hydrogels have become a promising candidate, featuring sensitive responsiveness to environmental signals enabling control over sol-gel transitions. However, conventional coacervation-based materials are regulated by relatively non-specific signals,...

Conductive Co-based metal organic framework nanostructures for excellent potassium- and lithium-ion storage: Kinetics and mechanism studies

Thanks to the low cost and earth's abundant potassium resources, potassium ion batteries (PIBs) have attracted much interest as alternative energy storage devices. However, there is still a great challenge to develop suitable anode materials for PIBs with high specific capacity, fast charge/discharge and stable ion storage. Nowadays,...

Evaluation of short-term streamflow prediction methods in Urban river basins

Efficient and accurate streamflow predictions are important for urban water management. Data-driven models, especially neural network (NN) models can predict streamflow fast, while the results are uncertain in some complex river systems. Physically based models can reveal the underlying physics, but it is relatively slow and computationally...

Microchannel Thermal Management System with Two-Phase Flow for Power Electronics over 500 W/cm²Heat Dissipation

In this article, a microchannel thermal management system (MTMS) with the two-phase flow using the refrigerant R1234yf with low global warming potential is presented. The thermal test vehicles (TTVs) were made of either single or multiple thermal test chips embedded in the substrates, which were then attached to the MTMS. The system included...