Nanyang Technological University

About: Nanyang Technological University is a education organization based out in Singapore, Singapore. It is known for research contribution in the topics: Computer science & Catalysis. The organization has 48003 authors who have published 112815 publications receiving 3294199 citations. The organization is also known as: NTU & Universiti Teknologi Nanyang.

Antibacterial Activity of Graphite, Graphite Oxide, Graphene Oxide, and Reduced Graphene Oxide: Membrane and Oxidative Stress

Abstract: Health and environmental impacts of graphene-based materials need to be thoroughly evaluated before their potential applications. Graphene has strong cytotoxicity toward bacteria. To better understand its antimicrobial mechanism, we compared the antibacterial activity of four types of graphene-based materials (graphite (Gt), graphite oxide (GtO), graphene oxide (GO), and reduced graphene oxide (rGO)) toward a bacterial model—Escherichia coli. Under similar concentration and incubation conditions, GO dispersion shows the highest antibacterial activity, sequentially followed by rGO, Gt, and GtO. Scanning electron microscope (SEM) and dynamic light scattering analyses show that GO aggregates have the smallest average size among the four types of materials. SEM images display that the direct contacts with graphene nanosheets disrupt cell membrane. No superoxide anion (O2•–) induced reactive oxygen species (ROS) production is detected. However, the four types of materials can oxidize glutathione, which serves ...

RefineNet: Multi-path Refinement Networks for High-Resolution Semantic Segmentation

Abstract: Recently, very deep convolutional neural networks (CNNs) have shown outstanding performance in object recognition and have also been the first choice for dense classification problems such as semantic segmentation. However, repeated subsampling operations like pooling or convolution striding in deep CNNs lead to a significant decrease in the initial image resolution. Here, we present RefineNet, a generic multi-path refinement network that explicitly exploits all the information available along the down-sampling process to enable high-resolution prediction using long-range residual connections. In this way, the deeper layers that capture high-level semantic features can be directly refined using fine-grained features from earlier convolutions. The individual components of RefineNet employ residual connections following the identity mapping mindset, which allows for effective end-to-end training. Further, we introduce chained residual pooling, which captures rich background context in an efficient manner. We carry out comprehensive experiments and set new state-of-the-art results on seven public datasets. In particular, we achieve an intersection-over-union score of 83.4 on the challenging PASCAL VOC 2012 dataset, which is the best reported result to date.

A survey of mobile cloud computing: architecture, applications, and approaches

Abstract: Together with an explosive growth of the mobile applications and emerging of cloud computing concept, mobile cloud computing (MCC) has been introduced to be a potential technology for mobile services. MCC integrates the cloud computing into the mobile environment and overcomes obstacles related to the performance (e.g., battery life, storage, and bandwidth), environment (e.g., heterogeneity, scalability, and availability), and security (e.g., reliability and privacy) discussed in mobile computing. This paper gives a survey of MCC, which helps general readers have an overview of the MCC including the definition, architecture, and applications. The issues, existing solutions, and approaches are presented. In addition, the future research directions of MCC are discussed. Copyright © 2011 John Wiley & Sons, Ltd.

Graphene-Based Materials: Synthesis, Characterization, Properties, and Applications

Abstract: Graphene, a two-dimensional, single-layer sheet of sp(2) hybridized carbon atoms, has attracted tremendous attention and research interest, owing to its exceptional physical properties, such as high electronic conductivity, good thermal stability, and excellent mechanical strength. Other forms of graphene-related materials, including graphene oxide, reduced graphene oxide, and exfoliated graphite, have been reliably produced in large scale. The promising properties together with the ease of processibility and functionalization make graphene-based materials ideal candidates for incorporation into a variety of functional materials. Importantly, graphene and its derivatives have been explored in a wide range of applications, such as electronic and photonic devices, clean energy, and sensors. In this review, after a general introduction to graphene and its derivatives, the synthesis, characterization, properties, and applications of graphene-based materials are discussed.

Atomic‐Layer Graphene as a Saturable Absorber for Ultrafast Pulsed Lasers

Abstract: The optical conductance of monolayer graphene is defined solely by the fine structure constant, α = (where e is the electron charge, is Dirac's constant and c is the speed of light). The absorbance has been predicted to be independent of frequency. In principle, the interband optical absorption in zero-gap graphene could be saturated readily under strong excitation due to Pauli blocking. Here, use of atomic layer graphene as saturable absorber in a mode-locked fiber laser for the generation of ultrashort soliton pulses (756 fs) at the telecommunication band is demonstrated. The modulation depth can be tuned in a wide range from 66.5% to 6.2% by varying the graphene thickness. These results suggest that ultrathin graphene films are potentially useful as optical elements in fiber lasers. Graphene as a laser mode locker can have many merits such as lower saturation intensity, ultrafast recovery time, tunable modulation depth, and wideband tunability.