이우친 교수

Underwater mobile sensor networks have recently been proposed as a way to explore and observe the ocean, providing 4D (space and time) monitoring of underwater environments. We consider a specialized geographic routing problem called pressure routing that directs a packet to any sonobuoy on the surface based on depth information available from on-board pressure gauges. The main challenge of pressure routing in sparse underwater networks has been the efficient handling of 3D voids. In this respec

A SEA Swarm (Sensor Equipped Aquatic Swarm) is a sensor "cloud" that drifts with water currents and enables 4D (space and time) monitoring of local underwater events such as contaminants, marine life and intruders. The swarm is escorted at the surface by drifting sonobuoys that collect the data from underwater sensors via acoustic modems and report it in real-time via radio to a monitoring center. The goal of this study is to design an efficient anycast routing algorithm for reliable underwater

A Sensor Equipped Aquatic (SEA) swarm is a sensor cloud that drifts with water currents and enables 4-D (space and time) monitoring of local underwater events such as contaminants, marine life, and intruders. The swarm is escorted on the surface by drifting sonobuoys that collect data from the underwater sensors via acoustic modems and report it in real time via radio to a monitoring center. The goal of this study is to design an efficient anycast routing algorithm for reliable underwater sensor

Mobile underwater networks with acoustic communications are confronted with several unique challenges such as long propagation delays, high transmission power consumption, and node mobility. In particular, slow signal propagation permits multiple packets to concurrently travel in the underwater channel, which must be exploited to improve the overall throughput. To this end, we propose the delay-aware opportunistic transmission scheduling (DOTS) protocol that uses passively obtained local informa

The average three-state prediction accuracy per protein (Q(3)) is estimated by cross-validation to be 77.07 +/- 0.26% with a segment overlap (Sov) score of 73.32 +/- 0.39%. The SVM performs similarly to the 'state-of-the-art' PSIPRED prediction method on a non-homologous test set of 121 proteins despite being trained on substantially fewer examples. A simple consensus of the SVM, PSIPRED and PROFsec achieves significantly higher prediction accuracy than the individual methods.

A SEA Swarm (Sensor Equipped Aquatic Swarm) is a collection of mobile underwater sensors that moves as a group with water current and enables 4D (space and time) monitoring of local underwater events such as contaminants and intruders. For prompt alert reporting, mobile sensors routes events to mobile sinks (i.e., autonomous underwater vehicles) via geographic routing that is known to be most efficient under mobility and scarce acoustic bandwidth. In order for a packet to be routed to the destin

Underwater Acoustic Sensor Networks (UW-ASNs) use acoustic links as a means of communications and are accordingly confronted with long propagation delays, low bandwidth, and high transmission power consumption. This unique situation, however, permits multiple packets to concurrently propagate in the underwater channel, which must be exploited in order to improve the overall throughput. To this end, we propose the Delay-aware Opportunistic Transmission Scheduling (DOTS) algorithm that uses passiv

Underwater environment represents a challenging and promising application scenario for sensor networks. Due to hard constraints imposed by acoustic communications and to high power consumption of acoustic modems, in underwater sensor networks (USN) energy saving becomes even more critical than in traditional sensor networks. In this paper the authors propose delay-tolerant data dolphin (DDD), an approach to apply delay-tolerant networking in the resource-constrained underwater environment. DDD e

We studied the association between objectively measured smartphone usage and objectively measured sleep quality and physical activity for seven consecutive days among Hong Kong adolescents and young adults aged 11-25 years (n = 357, 67% female). We installed an app that tracked the subjects' smartphone usage and had them wear an ActiGraph GT3X accelerometer on their wrist to measure their sleep quality and physical activity level. Smartphone usage data were successfully obtained from 187 partici

Mobile underwater networking is a developing technology for monitoring and exploring the Earth's oceans. For effective underwater exploration, multimedia communications such as sonar images and low resolution videos are becoming increasingly important. Unlike terrestrial RF communication, underwater networks rely on acoustic waves as a means of communication. Unfortunately, acoustic waves incur long propagation delays that typically lead to low throughput especially in protocols that require rec