W
Woochul Kang
Researcher at Incheon National University
Publications - 46
Citations - 815
Woochul Kang is an academic researcher from Incheon National University. The author has contributed to research in topics: Quality of service & Deep learning. The author has an hindex of 11, co-authored 46 publications receiving 746 citations. Previous affiliations of Woochul Kang include University of Illinois at Urbana–Champaign & Electronics and Telecommunications Research Institute.
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Proceedings ArticleDOI
LUSTER: wireless sensor network for environmental research
Leo Selavo,Anthony D. Wood,Qiuhua Cao,Tamim Sookoor,Hengchang Liu,A. Srinivasan,Yafeng Wu,Woochul Kang,John A. Stankovic,D. Young,John H. Porter +10 more
TL;DR: LUSTER---Light Under Shrub Thicket for Environmental Research---is a system that meets the challenges of EWSNs using a hierarchical architecture that includes distributed reliable storage, delay-tolerant networking, and deployment time validation techniques.
Journal ArticleDOI
RDDS: A Real-Time Data Distribution Service for Cyber-Physical Systems
TL;DR: This paper discusses the semantics-aware communication mechanism of RDDS that not only reduces the computation and communication overhead, but also enables the subscribers to access data in a timely and reliable manner when the network is slow or unstable and extended to achieve robustness against unpredictable workloads.
Journal ArticleDOI
Classification and Morphological Analysis of Vector Mosquitoes using Deep Convolutional Neural Networks.
TL;DR: This study investigated the capability of state-of-the-art deep learning models in classifying mosquito species having high inter-species similarity and intra-species variations and demonstrated that more than 97% classification accuracy can be achieved by fine-tuning general features if proper data augmentation techniques are applied together.
Journal ArticleDOI
Design, Implementation, and Evaluation of a QoS-Aware Real-Time Embedded Database
TL;DR: QeDB uses a novel feedback control scheme to support QoS in such embedded systems without requiring all data to reside in main memory and is based on simultaneous control of both I/O and CPU resources to guarantee the desired timeliness.
Proceedings ArticleDOI
I/O-Aware Deadline Miss Ratio Management in Real-Time Embedded Databases
TL;DR: This paper presents an I/O-aware deadline miss ratio management scheme in real-time embedded databases whose secondary storage is flash memory, and proposes an adaptive I/ o deadline assignment scheme, in which I/o deadlines are derived from up-to-date system status.