Showing papers by "Nanyang Technological University published in 2011"

Differential Evolution: A Survey of the State-of-the-Art

Abstract: Differential evolution (DE) is arguably one of the most powerful stochastic real-parameter optimization algorithms in current use. DE operates through similar computational steps as employed by a standard evolutionary algorithm (EA). However, unlike traditional EAs, the DE-variants perturb the current-generation population members with the scaled differences of randomly selected and distinct population members. Therefore, no separate probability distribution has to be used for generating the offspring. Since its inception in 1995, DE has drawn the attention of many researchers all over the world resulting in a lot of variants of the basic algorithm with improved performance. This paper presents a detailed review of the basic concepts of DE and a survey of its major variants, its application to multiobjective, constrained, large scale, and uncertain optimization problems, and the theoretical studies conducted on DE so far. Also, it provides an overview of the significant engineering applications that have benefited from the powerful nature of DE.

Domain Adaptation via Transfer Component Analysis

Abstract: Domain adaptation allows knowledge from a source domain to be transferred to a different but related target domain. Intuitively, discovering a good feature representation across domains is crucial. In this paper, we first propose to find such a representation through a new learning method, transfer component analysis (TCA), for domain adaptation. TCA tries to learn some transfer components across domains in a reproducing kernel Hilbert space using maximum mean miscrepancy. In the subspace spanned by these transfer components, data properties are preserved and data distributions in different domains are close to each other. As a result, with the new representations in this subspace, we can apply standard machine learning methods to train classifiers or regression models in the source domain for use in the target domain. Furthermore, in order to uncover the knowledge hidden in the relations between the data labels from the source and target domains, we extend TCA in a semisupervised learning setting, which encodes label information into transfer components learning. We call this extension semisupervised TCA. The main contribution of our work is that we propose a novel dimensionality reduction framework for reducing the distance between domains in a latent space for domain adaptation. We propose both unsupervised and semisupervised feature extraction approaches, which can dramatically reduce the distance between domain distributions by projecting data onto the learned transfer components. Finally, our approach can handle large datasets and naturally lead to out-of-sample generalization. The effectiveness and efficiency of our approach are verified by experiments on five toy datasets and two real-world applications: cross-domain indoor WiFi localization and cross-domain text classification.

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 ...

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.

Differences Between Tight and Loose Cultures: A 33-Nation Study

Abstract: With data from 33 nations, we illustrate the differences between cultures that are tight (have many strong norms and a low tolerance of deviant behavior) versus loose (have weak social norms and a high tolerance of deviant behavior). Tightness-looseness is part of a complex, loosely integrated multilevel system that comprises distal ecological and historical threats (e.g., high population density, resource scarcity, a history of territorial conflict, and disease and environmental threats), broad versus narrow socialization in societal institutions (e.g., autocracy, media regulations), the strength of everyday recurring situations, and micro-level psychological affordances (e.g., prevention self-guides, high regulatory strength, need for structure). This research advances knowledge that can foster cross-cultural understanding in a world of increasing global interdependence and has implications for modeling cultural change.

Multiobjective evolutionary algorithms: A survey of the state of the art

Abstract: A multiobjective optimization problem involves several conflicting objectives and has a set of Pareto optimal solutions. By evolving a population of solutions, multiobjective evolutionary algorithms (MOEAs) are able to approximate the Pareto optimal set in a single run. MOEAs have attracted a lot of research effort during the last 20 years, and they are still one of the hottest research areas in the field of evolutionary computation. This paper surveys the development of MOEAs primarily during the last eight years. It covers algorithmic frameworks such as decomposition-based MOEAs (MOEA/Ds), memetic MOEAs, coevolutionary MOEAs, selection and offspring reproduction operators, MOEAs with specific search methods, MOEAs for multimodal problems, constraint handling and MOEAs, computationally expensive multiobjective optimization problems (MOPs), dynamic MOPs, noisy MOPs, combinatorial and discrete MOPs, benchmark problems, performance indicators, and applications. In addition, some future research issues are also presented.

Extreme learning machines: a survey

Abstract: Computational intelligence techniques have been used in wide applications. Out of numerous computational intelligence techniques, neural networks and support vector machines (SVMs) have been playing the dominant roles. However, it is known that both neural networks and SVMs face some challenging issues such as: (1) slow learning speed, (2) trivial human intervene, and/or (3) poor computational scalability. Extreme learning machine (ELM) as emergent technology which overcomes some challenges faced by other techniques has recently attracted the attention from more and more researchers. ELM works for generalized single-hidden layer feedforward networks (SLFNs). The essence of ELM is that the hidden layer of SLFNs need not be tuned. Compared with those traditional computational intelligence techniques, ELM provides better generalization performance at a much faster learning speed and with least human intervene. This paper gives a survey on ELM and its variants, especially on (1) batch learning mode of ELM, (2) fully complex ELM, (3) online sequential ELM, (4) incremental ELM, and (5) ensemble of ELM.

Single‐Layer Semiconducting Nanosheets: High‐Yield Preparation and Device Fabrication

Abstract: The common featureof these materials is that the bulk material forms are layeredstructures with strong covalent bonding in each layer andweak van der Waals forces between the layers. Therefore,single or few-layer nanosheets of these materials can beobtained by using adhesive tapes for mechanical cleavage.

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 ]

Differential evolution algorithm with ensemble of parameters and mutation strategies

Abstract: Differential evolution (DE) has attracted much attention recently as an effective approach for solving numerical optimization problems. However, the performance of DE is sensitive to the choice of the mutation strategy and associated control parameters. Thus, to obtain optimal performance, time-consuming parameter tuning is necessary. Different mutation strategies with different parameter settings can be appropriate during different stages of the evolution. In this paper, we propose to employ an ensemble of mutation strategies and control parameters with the DE (EPSDE). In EPSDE, a pool of distinct mutation strategies along with a pool of values for each control parameter coexists throughout the evolution process and competes to produce offspring. The performance of EPSDE is evaluated on a set of bound-constrained problems and is compared with conventional DE and several state-of-the-art parameter adaptive DE variants.

Graphene-based nanomaterials for energy storage

Abstract: There is enormous interest in the use of graphene-based materials for energy storage. This article discusses the progress that has been accomplished in the development of chemical, electrochemical, and electrical energy storage systems using graphene. We summarize the theoretical and experimental work on graphene-based hydrogen storage systems, lithium batteries, and supercapacitors. Even though the research on the use of graphene for energy storage began very recently, the explosive growth of the research conducted in this area makes this minireview timely.

A Hybrid AC/DC Microgrid and Its Coordination Control

Abstract: This paper proposes a hybrid ac/dc micro grid to reduce the processes of multiple dc-ac-dc or ac-dc-ac conversions in an individual ac or dc grid. The hybrid grid consists of both ac and dc networks connected together by multi-bidirectional converters. AC sources and loads are connected to the ac network whereas dc sources and loads are tied to the dc network. Energy storage systems can be connected to dc or ac links. The proposed hybrid grid can operate in a grid-tied or autonomous mode. The coordination control algorithms are proposed for smooth power transfer between ac and dc links and for stable system operation under various generation and load conditions. Uncertainty and intermittent characteristics of wind speed, solar irradiation level, ambient temperature, and load are also considered in system control and operation. A small hybrid grid has been modeled and simulated using the Simulink in the MATLAB. The simulation results show that the system can maintain stable operation under the proposed coordination control schemes when the grid is switched from one operating condition to another.

Pathological Video Game Use Among Youths: A Two-Year Longitudinal Study

Abstract: OBJECTIVES: We aimed to measure the prevalence and length of the problem of pathological video gaming or Internet use, to identify risk and protective factors, to determine whether pathological gaming is a primary or secondary problem, and to identify outcomes for individuals who become or stop being pathological gamers. METHODS: A 2-year, longitudinal, panel study was performed with a general elementary and secondary school population in Singapore, including 3034 children in grades 3 ( N = 743), 4 ( N = 711), 7 ( N = 916), and 8 ( N = 664). Several hypothesized risk and protective factors for developing or overcoming pathological gaming were measured, including weekly amount of game play, impulsivity, social competence, depression, social phobia, anxiety, and school performance. RESULTS: The prevalence of pathological gaming was similar to that in other countries (∼9%). Greater amounts of gaming, lower social competence, and greater impulsivity seemed to act as risk factors for becoming pathological gamers, whereas depression, anxiety, social phobias, and lower school performance seemed to act as outcomes of pathological gaming. CONCLUSION: This study adds important information to the discussion about whether video game “addiction” is similar to other addictive behaviors, demonstrating that it can last for years and is not solely a symptom of comorbid disorders.

Preparation of novel 3D graphene networks for supercapacitor applications

Abstract: The supercapacitor is considered as a promising candidate for energy storage due to its high power performance, long life cycle, and low maintenance cost. [ 3 ] Pseudocapacitive materials, such as transition metal oxides, are being explored for use in supercapacitors with a large specifi c capacitance and high energy density. [ 4 ] However, pseudocapacitors often suffer from the low rate capability and poor stability, because the active materials are usually insulating or semiconducting, which hinders the fast electron transport required for high charge/discharge rates. As an ideal matrix, graphene is commonly used for growth of functional nanomaterials. [ 1a , 2c , 5 ] Recently, nanocomposites made by graphene and transition metal oxides have attracted wide attention in the fi eld of supercapacitors due to their synergetic effect, arising from the combination of the redox reaction of metal oxides with the high surface area/conductivity of graphene, to improve the electrochemical performance. [ 6 ]

Broadband graphene polarizer

Abstract: Scientists study the coupling, guiding and polarizing of electromagnetic waves in graphene and demonstrate a graphene-based fibre polarizer that exhibits a transverse-electric-pass polarization at an extinction ratio of up to ∼27 dB in the telecommunications band.

Robust Adaptive Control of Uncertain Nonlinear Systems in the Presence of Input Saturation and External Disturbance

Abstract: In this technical note, we consider adaptive control of single input uncertain nonlinear systems in the presence of input saturation and unknown external disturbance. By using backstepping approaches, two new robust adaptive control algorithms are developed by introducing a well defined smooth function and using a Nussbaum function. The Nussbaum function is introduced to compensate for the nonlinear term arising from the input saturation. Unlike some existing control schemes for systems with input saturation, the developed controllers do not require assumptions on the uncertain parameters within a known compact set and a priori knowledge on the bound of the external disturbance. Besides showing global stability, transient performance is also established and can be adjusted by tuning certain design parameters.

Pyridinic N doped graphene: synthesis, electronic structure, and electrocatalytic property

Abstract: Different C–N bonding configurations in nitrogen (N) doped carbon materials have different electronic structures. Carbon materials doped with only one kind of C–N bonding configuration are an excellent platform for studying doping effects on the electronic structure and physical/chemical properties. Here we report synthesis of single layer graphene doped with pure pyridinic N by thermal chemical vapour deposition of hydrogen and ethylene on Cu foils in the presence of ammonia. By adjusting the flow rate of ammonia, the atomic ratio of N and C can be modulated from 0 to 16%. The domain like distribution of N incorporated in graphene was revealed by the imaging of Raman spectroscopy and time-of-flight secondary ion mass spectrometry. The ultraviolet photoemission spectroscopy investigation demonstrated that the pyridinic N efficiently changed the valence band structure of graphene, including the raising of density of π states near the Fermi level and the reduction of work function. Such pyridinic N doping in carbon materials was generally considered to be responsible for their oxygen reduction reaction (ORR) activity. The 2e reduction mechanism of ORR on our CNxgraphene revealed by rotating disk electrode voltammetry indicated that the pyridinic N may not be an effective promoter for ORR activity of carbon materials as previously expected.

The Secrecy Capacity of the MIMO Wiretap Channel

Abstract: We consider the MIMO wiretap channel, that is a MIMO broadcast channel where the transmitter sends some confidential information to one user which is a legitimate receiver, while the other user is an eavesdropper. Perfect secrecy is achieved when the transmitter and the legitimate receiver can communicate at some positive rate, while insuring that the eavesdropper gets zero bits of information. In this paper, we compute the perfect secrecy capacity of the multiple antenna MIMO broadcast channel, where the number of antennas is arbitrary for both the transmitter and the two receivers. Our technique involves a careful study of a Sato-like upper bound via the solution of a certain algebraic Riccati equation.

The LED block cipher

Abstract: We present a new block cipher LED. While dedicated to compact hardware implementation, and offering the smallest silicon footprint among comparable block ciphers, the cipher has been designed to simultaneously tackle three additional goals. First, we explore the role of an ultra-light (in fact non-existent) key schedule. Second, we consider the resistance of ciphers, and LED in particular, to related-key attacks: we are able to derive simple yet interesting AES-like security proofs for LED regarding related- or single-key attacks. And third, while we provide a block cipher that is very compact in hardware, we aim to maintain a reasonable performance profile for software implementation.

Nitrogen-containing microporous carbon nanospheres with improved capacitive properties

Abstract: We report the largely improved electrochemical capacitance of polypyrrole-derived microporous carbon nanospheres (MCNs, 80–100 nm in diameter) containing nitrogen functional groups. We have investigated the electrochemical properties of precursor polypyrrole nanospheres (PNs, with a high N/C ratio and low surface area) and as-derived carbon nanospheres (CNs, with a moderate N/C ratio and low surface area) prepared by carbonizing PNs at different temperatures, and MCNs (with a low N/C ratio and high surface area) obtained by chemical activation of CNs. The samples are thoroughly characterized by transmission electron microscopy (TEM), X-ray diffraction (XRD), Raman spectroscopy, thermogravimetric analysis (TGA), nitrogen sorption, elemental analysis, and X-ray photoelectron spectroscopy (XPS). It is found that MCNs with a high surface area and N-doping species exhibit much better capacitive performance compared to the PNs and CNs, and commercial carbon blacks (XC-72 and BP2000) as well. The MCN sample gives a reversible specific capacitance of ∼240 F g−1 for 3000 cycles in aqueous media as a result of combined advantages of high electrochemical activity of doped heteroatoms (N and O) and accessible well-developed porosity, demonstrating the promising use in high-energy-density supercapacitors.

Game Theory in Wireless and Communication Networks: Theory, Models, and Applications

Abstract: This unified treatment of game theory focuses on finding state-of-the-art solutions to issues surrounding the next generation of wireless and communications networks. Future networks will rely on autonomous and distributed architectures to improve the efficiency and flexibility of mobile applications, and game theory provides the ideal framework for designing efficient and robust distributed algorithms. This book enables readers to develop a solid understanding of game theory, its applications and its use as an effective tool for addressing wireless communication and networking problems. The key results and tools of game theory are covered, as are various real-world technologies including 3G networks, wireless LANs, sensor networks, dynamic spectrum access and cognitive networks. The book also covers a wide range of techniques for modeling, designing and analysing communication networks using game theory, as well as state-of-the-art distributed design techniques. This is an ideal resource for communications engineers, researchers, and graduate and undergraduate students.

Sparse reconstruction cost for abnormal event detection

Abstract: We propose to detect abnormal events via a sparse reconstruction over the normal bases. Given an over-complete normal basis set (e.g., an image sequence or a collection of local spatio-temporal patches), we introduce the sparse reconstruction cost (SRC) over the normal dictionary to measure the normalness of the testing sample. To condense the size of the dictionary, a novel dictionary selection method is designed with sparsity consistency constraint. By introducing the prior weight of each basis during sparse reconstruction, the proposed SRC is more robust compared to other outlier detection criteria. Our method provides a unified solution to detect both local abnormal events (LAE) and global abnormal events (GAE). We further extend it to support online abnormal event detection by updating the dictionary incrementally. Experiments on three benchmark datasets and the comparison to the state-of-the-art methods validate the advantages of our algorithm.

Chitosan-functionalized graphene oxide as a nanocarrier for drug and gene delivery.

Abstract: The covalent functionalization of graphene oxide (GO) with chitosan (CS) is successfully accomplished via a facile amidation process. The CS-grafted GO (GO-CS) sheets consist of about 64 wt.% CS, which imparts them with a good aqueous solubility and biocompatibility. Additionally, the physicochemical properties of GO-CS are studied. As a novel nanocarrier, GO-CS is applied to load a water-insoluble anticancer drug, camptothecin (CPT), via π-π stacking and hydrophobic interactions. It is demonstrated that GO-CS possesses a superior loading capacity for CPT, and the GO-CS-CPT complexes show remarkably high cytotoxicity in HepG2 and HeLa cell lines compared to the pure drug. At the same time, GO-CS is also able to condense plasmid DNA into stable, nanosized complexes, and the resulting GO-CS/pDNA nanoparticles exhibit reasonable transfection efficiency in HeLa cells at certain nitrogen/phosphate ratios. Therefore, the GO-CS nanocarrier is able to load and deliver both anticancer drugs and genes.

Event Detection in Twitter

Abstract: Twitter, as a form of social media, is fast emerging in recent years. Users are using Twitter to report real-life events. This paper focuses on detecting those events by analyzing the text stream in Twitter. Although event detection has long been a research topic, the characteristics of Twitter make it a non-trivial task. Tweets reporting such events are usually overwhelmed by high flood of meaningless “babbles”. Moreover, event detection algorithm needs to be scalable given the sheer amount of tweets. This paper attempts to tackle these challenges with EDCoW (Event Detection with Clustering of Wavelet-based Signals). EDCoW builds signals for individual words by applying wavelet analysis on the frequencybased raw signals of the words. It then filters away the trivial words by looking at their corresponding signal autocorrelations. The remaining words are then clustered to form events with a modularity-based graph partitioning technique. Experimental results show promising result of EDCoW.

CENTRIST: A Visual Descriptor for Scene Categorization

Abstract: CENsus TRansform hISTogram (CENTRIST), a new visual descriptor for recognizing topological places or scene categories, is introduced in this paper. We show that place and scene recognition, especially for indoor environments, require its visual descriptor to possess properties that are different from other vision domains (e.g., object recognition). CENTRIST satisfies these properties and suits the place and scene recognition task. It is a holistic representation and has strong generalizability for category recognition. CENTRIST mainly encodes the structural properties within an image and suppresses detailed textural information. Our experiments demonstrate that CENTRIST outperforms the current state of the art in several place and scene recognition data sets, compared with other descriptors such as SIFT and Gist. Besides, it is easy to implement and evaluates extremely fast.

Quasiemulsion-templated formation of α-Fe2O3 hollow spheres with enhanced lithium storage properties.

Abstract: α-Fe2O3 hollow spheres with sheet-like subunits are synthesized by a facile quasiemulsion-templated method. Glycerol is dispersed in water to form oil-in-water quasiemulsion microdroplets, which serve as soft templates for the deposition of the α-Fe2O3 shell. When tested as anode materials for lithium-ion batteries, these α-Fe2O3 hollow spheres manifest greatly enhanced Li storage properties.

A polycationic antimicrobial and biocompatible hydrogel with microbe membrane suctioning ability

Abstract: Despite advanced sterilization and aseptic techniques, infections associated with medical implants have not been eradicated. Most present coatings cannot simultaneously fulfil the requirements of antibacterial and antifungal activity as well as biocompatibility and reusability. Here, we report an antimicrobial hydrogel based on dimethyldecylammonium chitosan (with high quaternization)-graft-poly(ethylene glycol) methacrylate (DMDC-Q-g-EM) and poly(ethylene glycol) diacrylate, which has excellent antimicrobial efficacy against Pseudomonas aeruginosa, Escherichia coli, Staphylococcus aureus and Fusarium solani. The proposed mechanism of the antimicrobial activity of the polycationic hydrogel is by attraction of sections of anionic microbial membrane into the internal nanopores of the hydrogel, like an ‘anion sponge’, leading to microbial membrane disruption and then microbe death. We have also demonstrated a thin uniform adherent coating of the hydrogel by simple ultraviolet immobilization. An animal study shows that DMDC-Q-g-EM hydrogel coating is biocompatible with rabbit conjunctiva and has no toxicity to the epithelial cells or the underlying stroma.