Adhesive lift method for patterning arbitrary-shaped thin ion-selective films in micro/nanofluidic device.

Micro/nanofluidic platforms with nanoporous films have been utilized as research tools for studying electrokinetic phenomena occurring not only in macro-scale systems such as electro-desalination but also in micro-scale systems such as bio-molecular preconcentrators. However, due to the limitations of fabrication techniques, studies with nanoporous films are mainly limited to vary the physicochemical properties of the films such as surface charge and pore size, despite the enormous effect of the membrane morphology on the phenomena that is to be expected. Therefore, we propose an economic and feasible nanofabrication method called the "adhesive lift method" for patterning thin arbitrarily-shaped nanoporous film to integrate it into micro/nanofluidic platforms.

DRER: Deep Learning-Based Driver's Real Emotion Recognizer.

In intelligent vehicles, it is essential to monitor the driver's condition; however, recognizing the driver's emotional state is one of the most challenging and important tasks. Most previous studies focused on facial expression recognition to monitor the driver's emotional state. However, while driving, many factors are preventing the drivers from revealing the emotions on their faces.