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.

Hollow Structures Based on Prussian Blue and Its Analogs for Electrochemical Energy Storage and Conversion.

Abstract: Due to their special structural characteristics, hollow structures grant fascinating physicochemical properties and widespread applications, especially in electrochemical energy storage and conversion. Recently, the research of Prussian blue (PB) and its analog (PBA) related nanomaterials has emerged and has drawn considerable attention because of their low cost, facile preparation, intrinsic open framework, and tunable composition. Here, the recent progress in the study of PB- and PBA-based hollow structures for electrochemical energy storage and conversion are summarized and discussed. First, some remarkable examples in the synthesis of hollow structures from PB- and PBA-based materials are illustrated in terms of the structural architectures, i.e., closed single-shelled hollow structures, open hollow structures, and complex hollow structures. Thereafter, their applications as potential electrode materials for lithium-/sodium-ion batteries, hybrid supercapacitors, and electrocatalysis are demonstrated. Finally, the current achievements in this field together with the limits and urgent challenges are summarized. Some perspectives on the potential solutions and possible future trends are also provided.

A-STAR: A Mobile Ad Hoc Routing Strategy for Metropolis Vehicular Communications

Abstract: One of the major issues that affect the performance of Mobile Ad hoc NETworks (MANET) is routing. Recently, position-based routing for MANET is found to be a very promising routing strategy for inter-vehicular communication systems (IVCS). However, position-based routing for IVCS in a built-up city environment faces greater challenges because of potentially more uneven distribution of vehicular nodes, constrained mobility, and difficult signal reception due to radio obstacles such as high-rise buildings. This paper proposes a new position-based routing scheme called Anchor-based Street and Traffic Aware Routing (A-STAR), designed specifically for IVCS in a city environment. Unique to A-STAR is the usage of information on city bus routes to identify an anchor path with high connectivity for packet delivery. Along with a new recovery strategy for packets routed to a local maximum, the proposed protocol shows significant performance improvement in a comparative simulation study with other similar routing approaches.

Pre-Service Teachers' Attitudes towards Computer Use: A Singapore Survey.

Abstract: The aim of this study is to examine the attitudes towards use of computers among pre-service teachers. A sample of 139 pre-service teachers was assessed for their computer attitudes using a Likert type questionnaire with four factors: affect (liking), perceived usefulness, perceived control, and behavioural intention to use the computer. The results of this study showed no gender or age differences among pre-service teachers on computer attitudes. However, there were significant differences for computer attitudes by the subject areas that pre-service teachers had been trained during their university education: Humanities, Sciences, Languages and General (Primary). Correlation analyses revealed significant associations between years of computer use and level of confidence, and computer attitudes. Implications for teacher training and suggestions for further research are provided.

What are Extreme Learning Machines? Filling the Gap Between Frank Rosenblatt’s Dream and John von Neumann’s Puzzle

Abstract: The emergent machine learning technique—extreme learning machines (ELMs)—has become a hot area of research over the past years, which is attributed to the growing research activities and significant contributions made by numerous researchers around the world. Recently, it has come to our attention that a number of misplaced notions and misunderstandings are being dissipated on the relationships between ELM and some earlier works. This paper wishes to clarify that (1) ELM theories manage to address the open problem which has puzzled the neural networks, machine learning and neuroscience communities for 60 years: whether hidden nodes/neurons need to be tuned in learning, and proved that in contrast to the common knowledge and conventional neural network learning tenets, hidden nodes/neurons do not need to be iteratively tuned in wide types of neural networks and learning models (Fourier series, biological learning, etc.). Unlike ELM theories, none of those earlier works provides theoretical foundations on feedforward neural networks with random hidden nodes; (2) ELM is proposed for both generalized single-hidden-layer feedforward network and multi-hidden-layer feedforward networks (including biological neural networks); (3) homogeneous architecture-based ELM is proposed for feature learning, clustering, regression and (binary/multi-class) classification. (4) Compared to ELM, SVM and LS-SVM tend to provide suboptimal solutions, and SVM and LS-SVM do not consider feature representations in hidden layers of multi-hidden-layer feedforward networks either.

Defect Engineering in Two Common Types of Dielectric Materials for Electromagnetic Absorption Applications

Abstract: Financial supports from the NSFC (Grant Nos. 11575085, 51602154, 11472131, and 11622218), the Aeronautics Science Foundation of China (Grant No. 2017ZF52066), the Qing Lan Project, Six talent peaks project in Jiangsu Province (Project No. XCL-035), the Jiangsu NSF (BK20160037), the program of China Scholarships Council (Grant No. 201806830013), Funding for Outstanding Doctoral Dissertation in NUAA (BCXJ 18-07), the Open Research Fund of Jiangsu Provincial Key Laboratory for Nanotechnology of Nanjing University, and the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD) are gratefully acknowledged.