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.

Recent advances in differential evolution – An updated survey

Abstract: Differential Evolution (DE) is arguably one of the most powerful and versatile evolutionary optimizers for the continuous parameter spaces in recent times. Almost 5 years have passed since the first comprehensive survey article was published on DE by Das and Suganthan in 2011. Several developments have been reported on various aspects of the algorithm in these 5 years and the research on and with DE have now reached an impressive state. Considering the huge progress of research with DE and its applications in diverse domains of science and technology, we find that it is a high time to provide a critical review of the latest literatures published and also to point out some important future avenues of research. The purpose of this paper is to summarize and organize the information on these current developments on DE. Beginning with a comprehensive foundation of the basic DE family of algorithms, we proceed through the recent proposals on parameter adaptation of DE, DE-based single-objective global optimizers, DE adopted for various optimization scenarios including constrained, large-scale, multi-objective, multi-modal and dynamic optimization, hybridization of DE with other optimizers, and also the multi-faceted literature on applications of DE. The paper also presents a dozen of interesting open problems and future research issues on DE.

Co3O4 Nanowire@MnO2 Ultrathin Nanosheet Core/Shell Arrays: A New Class of High‐Performance Pseudocapacitive Materials

Abstract: With the ever-increasing power and energy needs in applications ranging from next-generation plug-in hybrid electric vehicles (PHEVs) and modern consumer electronics to microand nanoelectromechanical systems, recent research and development has focused on new electrode materials for advanced energy storage devices. [ 1–5 ] Of the various power source devices, supercapacitors, also known as electrochemical capacitors (ECs), have attracted great interest due to a number of desirable properties, including fast charging and discharging, long cycle life, and the ability to deliver up to ten times more power than conventional batteries. [ 6–10 ] In addition, ECs play an important role in complementing fuel cells in future all-electric vehicles based on clean and renewable energy media. [ 11 ] There are three major types of electrode materials reported for ECs: carbonaceous materials, [ 12 ] metal oxides/hydroxides, [ 13 ] and conducting polymers. [ 14 ] Carbon-based materials store charge electrostatically from the reversible adsorption of ions onto their surfaces, leading to high power delivery at the cost of low energy density. By contrast, metal oxides/hydroxides and conducting polymers store charge in a faradic or redox-type process similar to batteries, which enables high energy density but is in general kinetically unfavorable. To bridge the performance gap between these materials, attempts at novel electrode design have been extensively made. Despite a huge number of publications, nearly all of them can be clarifi ed into one general concept, that is, the use of pseudocapacitive material–conductive matrix hybrid nanostructures. [ 15 , 16 ] In this regard, materials presenting high pseudocapacitence (metal oxides) are incorporated directly into highly conductive nanostructured carbons (carbon nanotubes, [ 17–20 ]

Spatio-Temporal LSTM with Trust Gates for 3D Human Action Recognition

Abstract: 3D action recognition – analysis of human actions based on 3D skeleton data – becomes popular recently due to its succinctness, robustness, and view-invariant representation. Recent attempts on this problem suggested to develop RNN-based learning methods to model the contextual dependency in the temporal domain. In this paper, we extend this idea to spatio-temporal domains to analyze the hidden sources of action-related information within the input data over both domains concurrently. Inspired by the graphical structure of the human skeleton, we further propose a more powerful tree-structure based traversal method. To handle the noise and occlusion in 3D skeleton data, we introduce new gating mechanism within LSTM to learn the reliability of the sequential input data and accordingly adjust its effect on updating the long-term context information stored in the memory cell. Our method achieves state-of-the-art performance on 4 challenging benchmark datasets for 3D human action analysis.

Novel genetic associations for blood pressure identified via gene-alcohol interaction in up to 570K individuals across multiple ancestries

Abstract: Heavy alcohol consumption is an established risk factor for hypertension; the mechanism by which alcohol consumption impact blood pressure (BP) regulation remains unknown. We hypothesized that a genome-wide association study accounting for gene-alcohol consumption interaction for BP might identify additional BP loci and contribute to the understanding of alcohol-related BP regulation. We conducted a large two-stage investigation incorporating joint testing of main genetic effects and single nucleotide variant (SNV)-alcohol consumption interactions. In Stage 1, genome-wide discovery meta-analyses in ≈131K individuals across several ancestry groups yielded 3,514 SNVs (245 loci) with suggestive evidence of association (P < 1.0 x 10-5). In Stage 2, these SNVs were tested for independent external replication in ≈440K individuals across multiple ancestries. We identified and replicated (at Bonferroni correction threshold) five novel BP loci (380 SNVs in 21 genes) and 49 previously reported BP loci (2,159 SNVs in 109 genes) in European ancestry, and in multi-ancestry meta-analyses (P < 5.0 x 10-8). For African ancestry samples, we detected 18 potentially novel BP loci (P < 5.0 x 10-8) in Stage 1 that warrant further replication. Additionally, correlated meta-analysis identified eight novel BP loci (11 genes). Several genes in these loci (e.g., PINX1, GATA4, BLK, FTO and GABBR2) have been previously reported to be associated with alcohol consumption. These findings provide insights into the role of alcohol consumption in the genetic architecture of hypertension.