Showing papers by "Southeast University published in 2012"

An Overview of Recent Progress in the Study of Distributed Multi-agent Coordination

Abstract: This article reviews some main results and progress in distributed multi-agent coordination, focusing on papers published in major control systems and robotics journals since 2006. Distributed coordination of multiple vehicles, including unmanned aerial vehicles, unmanned ground vehicles and unmanned underwater vehicles, has been a very active research subject studied extensively by the systems and control community. The recent results in this area are categorized into several directions, such as consensus, formation control, optimization, task assignment, and estimation. After the review, a short discussion section is included to summarize the existing research and to propose several promising research directions along with some open problems that are deemed important for further investigations.

Spongy Graphene as a Highly Efficient and Recyclable Sorbent for Oils and Organic Solvents

Abstract: In this work, spongy graphene (SG), a shape-mouldable and nanoporous material with a high specific surface area used as a versatile and recyclable sorbent material, is proposed and studied. SG shows highly efficient absorption of not only petroleum products and fats, but also toxic solvents such as toluene and chloroform (up to 86 times of its own weight), requiring no further pretreatment, which is tens of times higher than that of conventional absorbers. Moreover, SG can be regenerated (>10 times) by heat treatment, yielding the full release of adsorbates (>99%). The present work suggests SG a widespread potential for applications in industry as well as topics regarding environmental protection.

Bio-inspired variable structural color materials

Abstract: Natural structural color materials, especially those that can undergo reversible changes, are attracting increasing interest in a wide variety of research fields. Inspired by the natural creatures, many elaborately nanostructured photonic materials with variable structural colors were developed. These materials have found important applications in switches, display devices, sensors, and so on. In this critical review, we will provide up-to-date research concerning the natural and bio-inspired photonic materials with variable structural colors. After introducing the variable structural colors in natural creatures, we will focus on the studies of artificial variable structural color photonic materials, including their bio-inspired designs, fabrications and applications. The prospects for the future development of these fantastic variable structural color materials will also be presented. We believe this review will promote the communications among biology, bionics, chemistry, optical physics, and material science (196 references).

Coking- and Sintering-Resistant Palladium Catalysts Achieved Through Atomic Layer Deposition

Abstract: We showed that alumina (Al(2)O(3)) overcoating of supported metal nanoparticles (NPs) effectively reduced deactivation by coking and sintering in high-temperature applications of heterogeneous catalysts We overcoated palladium NPs with 45 layers of alumina through an atomic layer deposition (ALD) process that alternated exposures of the catalysts to trimethylaluminum and water at 200°C When these catalysts were used for 1 hour in oxidative dehydrogenation of ethane to ethylene at 650°C, they were found by thermogravimetric analysis to contain less than 6% of the coke formed on the uncoated catalysts Scanning transmission electron microscopy showed no visible morphology changes after reaction at 675°C for 28 hours The yield of ethylene was improved on all ALD Al(2)O(3) overcoated Pd catalysts

Energy metabolism of cancer: Glycolysis versus oxidative phosphorylation (Review)

Abstract: Metabolic activities in normal cells rely primarily on mitochondrial oxidative phosphorylation (OXPHOS) to generate ATP for energy. Unlike in normal cells, glycolysis is enhanced and OXPHOS capacity is reduced in various cancer cells. It has long been believed that the glycolytic phenotype in cancer is due to a permanent impairment of mitochondrial OXPHOS, as proposed by Otto Warburg. This view is challenged by recent investigations which find that the function of mitochondrial OXPHOS in most cancers is intact. Aerobic glycolysis in many cancers is the combined result of various factors such as oncogenes, tumor suppressors, a hypoxic microenvironment, mtDNA mutations, genetic background and others. Understanding the features and complexity of the cancer energy metabolism will help to develop new approaches in early diagnosis and effectively target therapy of cancer.

Dual Enzyme-like Activities of Iron Oxide Nanoparticles and Their Implication for Diminishing Cytotoxicity

Abstract: Iron oxide nanoparticles (IONPs) are frequently used in biomedical applications, yet their toxic potential is still a major concern. While most studies of biosafety focus on cellular responses after exposure to nanomaterials, little is reported to analyze reactions on the surface of nanoparticles as a source of cytotoxicity. Here we report that different intracellular microenvironment in which IONPs are located leads to contradictive outcomes in their abilities to produce free radicals. We first verified pH-dependent peroxidase-like and catalase-like activities of IONPs and investigated how they interact with hydrogen peroxide (H2O2) within cells. Results showed that IONPs had a concentration-dependent cytotoxicity on human glioma U251 cells, and they could enhance H2O2-induced cell damage dramatically. By conducting electron spin resonance spectroscopy experiments, we showed that both Fe3O4 and γ-Fe2O3 nanoparticles could catalyze H2O2 to produce hydroxyl radicals in acidic lysosome mimic conditions, wit...

Generalized Extended State Observer Based Control for Systems With Mismatched Uncertainties

Abstract: The standard extended state observer based control (ESOBC) method is only applicable for a class of single-input-single-output essential-integral-chain systems with matched uncertainties. It is noticed that systems with nonintegral-chain form and mismatched uncertainties are more general and widely exist in practical engineering systems, where the standard ESOBC method is no longer available. To this end, it is imperative to explore new ESOBC approach for these systems to extend its applicability. By appropriately choosing a disturbance compensation gain, a generalized ESOBC (GESOBC) method is proposed for nonintegral-chain systems subject to mismatched uncertainties without any coordinate transformations. The proposed method is able to extend to multi-input-multi-output systems with almost no modification. Both numerical and application design examples demonstrate the feasibility and efficacy of the proposed method.

Speed Control for PMSM Servo System Using Predictive Functional Control and Extended State Observer

Abstract: The speed regulation problem for permanent magnet synchronous motor (PMSM) servo system is studied in this paper. In order to optimize the control performance of the PMSM servo system, the predictive functional control (PFC) method is introduced in the control design of speed loop. The PFC-based speed control design consists of two steps. A simplified model is employed to predict the future q -axis current of PMSM. Then, an optimal control law is obtained by minimizing a quadratic performance index. However, it is noted that the standard PFC method does not achieve a satisfying effect in the presence of strong disturbances. To this end, an improved PFC method, called the PFC+ESO method, is developed. It introduces extended state observer (ESO) to estimate the lumped disturbances and adds a feedforward compensation item based on the estimated disturbances to the PFC speed controller. Simulation and experiment comparisons are made for these PFC methods and proportional-integral method with antiwindup control method to verify the effectiveness of the proposed methods.

Real-time observation on dynamic growth/dissolution of conductive filaments in oxide-electrolyte-based ReRAM.

Abstract: Evolution of growth/dissolution conductive filaments (CFs) in oxide-electrolyte-based resistive switching memories are studied by in situ transmission electron microscopy. Contrary to what is commonly believed, CFs are found to start growing from the anode (Ag or Cu) rather than having to reach the cathode (Pt) and grow backwards. A new mechanism based on local redox reactions inside the oxide-electrolyte is proposed.

Synchronization Control for Nonlinear Stochastic Dynamical Networks: Pinning Impulsive Strategy

Abstract: In this paper, a new control strategy is proposed for the synchronization of stochastic dynamical networks with nonlinear coupling. Pinning state feedback controllers have been proved to be effective for synchronization control of state-coupled dynamical networks. We will show that pinning impulsive controllers are also effective for synchronization control of the above mentioned dynamical networks. Some generic mean square stability criteria are derived in terms of algebraic conditions, which guarantee that the whole state-coupled dynamical network can be forced to some desired trajectory by placing impulsive controllers on a small fraction of nodes. An effective method is given to select the nodes which should be controlled at each impulsive constants. The proportion of the controlled nodes guaranteeing the stability is explicitly obtained, and the synchronization region is also derived and clearly plotted. Numerical simulations are exploited to demonstrate the effectiveness of the pinning impulsive strategy proposed in this paper.

Meta-analysis identifies common variants associated with body mass index in east Asians

Abstract: Multiple genetic loci associated with obesity or body mass index (BMI) have been identified through genome-wide association studies conducted predominantly in populations of European ancestry We performed a meta-analysis of associations between BMI and approximately 24 million SNPs in 27,715 east Asians, which was followed by in silico and de novo replication studies in 37,691 and 17,642 additional east Asians, respectively We identified ten BMI-associated loci at genome-wide significance (P < 50 × 10(-8)), including seven previously identified loci (FTO, SEC16B, MC4R, GIPR-QPCTL, ADCY3-DNAJC27, BDNF and MAP2K5) and three novel loci in or near the CDKAL1, PCSK1 and GP2 genes Three additional loci nearly reached the genome-wide significance threshold, including two previously identified loci in the GNPDA2 and TFAP2B genes and a newly identified signal near PAX6, all of which were associated with BMI with P < 50 × 10(-7) Findings from this study may shed light on new pathways involved in obesity and demonstrate the value of conducting genetic studies in non-European populations

Synthesis of Ultralong Copper Nanowires for High-Performance Transparent Electrodes

Abstract: Cu nanowires hold great promise for the fabrication of low-cost transparent electrodes. However, their current synthesis is mainly performed in aqueous media with poor nanowire dispersibility. We report herein the novel synthesis of ultralong single-crystalline Cu nanowires with excellent dispersibility, providing an excellent candidate material for high-performance transparent electrode fabrication.

Distributed Adaptive Control of Synchronization in Complex Networks

Abstract: This technical note studies distributed adaptive control of synchronization in complex networks An effective distributed adaptive strategy to tune the coupling weights of a network is designed based on local information of node dynamics The analysis is then extended to the case where only a small fraction of coupling weights can be adjusted A general criterion is derived and it is found that synchronization can be reached if the subgraph consisting of the edges and nodes corresponding to the updated coupling weights is connected Finally, simulation examples are given to illustrate the theoretical analysis

Stability Analysis of Markovian Jump Stochastic BAM Neural Networks With Impulse Control and Mixed Time Delays

Abstract: This paper discusses the issue of stability analysis for a class of impulsive stochastic bidirectional associative memory neural networks with both Markovian jump parameters and mixed time delays. The jumping parameters are modeled as a continuous-time discrete-state Markov chain. Based on a novel Lyapunov-Krasovskii functional, the generalized Ito's formula, mathematical induction, and stochastic analysis theory, a linear matrix inequality approach is developed to derive some novel sufficient conditions that guarantee the exponential stability in the mean square of the equilibrium point. At the same time, we also investigate the robustly exponential stability in the mean square of the corresponding system with unknown parameters. It should be mentioned that our stability results are delay-dependent, which depend on not only the upper bounds of time delays but also their lower bounds. Moreover, the derivatives of time delays are not necessarily zero or smaller than one since several free matrices are introduced in our results. Consequently, the results obtained in this paper are not only less conservative but also generalize and improve many earlier results. Finally, two numerical examples and their simulations are provided to show the effectiveness of the theoretical results.

Intuitionistic Fuzzy Information Aggregation Using Einstein Operations

Abstract: Aggregation of fuzzy information is a new branch of Atanassov's intuitionistic fuzzy set (AIFS) theory, which has attracted significant interest from researchers in recent years. In this paper, we treat the intuitionistic fuzzy aggregation operators with the help of Einstein operations. We first introduce some new operations of AIFSs, such as Einstein sum, Einstein product, and Einstein scalar multiplication. Then, we develop some intuitionistic fuzzy aggregation operators, such as the intuitionistic fuzzy Einstein weighted averaging operator and the intuitionistic fuzzy Einstein ordered weighted averaging operator, which extend the weighted averaging operator and the ordered weighted averaging operator to aggregate Atanassov's intuitionistic fuzzy values, respectively. We further establish various properties of these operators and analyze the relations between these operators and the existing intuitionistic fuzzy aggregation operators. Moreover, we give some numerical examples to illustrate the developed aggregation operators. Finally, we apply the intuitionistic fuzzy Einstein weighted averaging operator to multiple attribute decision making with intuitionistic fuzzy information.

Consensus in multi-agent systems with communication constraints

Abstract: The problem of second-order consensus is investigated in this paper for a class of multi-agent systems with a fixed directed topology and communication constraints where each agent is assumed to share information only with its neighbors on some disconnected time intervals. A novel consensus protocol designed based on synchronous intermittent local information feedback is proposed to coordinate the states of agents to converge to second-order consensus under a fixed strongly connected topology, which is then extended to the case where the communication topology contains a directed spanning tree. By using tools from algebraic graph theory and Lyapunov control approach, it is proved that second-order consensus can be reached if the general algebraic connectivity of the communication topology is larger than a threshold value and the mobile agents communicate with their neighbors frequently enough as the network evolves. Finally, a numerical example is simulated to verify the theoretical analysis. Copyright © 2011 John Wiley & Sons, Ltd.

Quantitative Comparison of Flux-Switching Permanent-Magnet Motors With Interior Permanent Magnet Motor for EV, HEV, and PHEV Applications

Abstract: Permanent-magnet (PM) motors with both magnets and armature windings on the stator (stator PM motors) have attracted considerable attention due to their simple structure, robust configuration, high power density, easy heat dissipation, and suitability for high-speed operations. However, current PM motors in industrial, residential, and automotive applications are still dominated by interior permanent-magnet motors (IPM) because the claimed advantages of stator PM motors have not been fully investigated and validated. Hence, this paper will perform a comparative study between a stator-PM motor, namely, a flux switching PM motor (FSPM), and an IPM which has been used in the 2004 Prius hybrid electric vehicle (HEV). For a fair comparison, the two motors are designed at the same phase current, current density, and dimensions including the stator outer diameter and stack length. First, the Prius-IPM is investigated by means of finite-element method (FEM). The FEM results are then verified by experimental results to confirm the validity of the methods used in this study. Second, the FSPM design is optimized and investigated based on the same method used for the Prius-IPM. Third, the electromagnetic performance and the material mass of the two motors are compared. It is concluded that FSPM has more sinusoidal back-EMF hence is more suitable for BLAC control. It also offers the advantage of smaller torque ripple and better mechanical integrity for safer and smoother operations. But the FSPM has disadvantages such as low magnet utilization ratio and high cost. It may not be able to compete with IPM in automotive and other applications where cost constraints are tight.

Topologically Convergent and Divergent Structural Connectivity Patterns between Patients with Remitted Geriatric Depression and Amnestic Mild Cognitive Impairment

Abstract: Alzheimer's disease (AD) can be conceptualized as a disconnection syndrome. Both remitted geriatric depression (RGD) and amnestic mild cognitive impairment (aMCI) are associated with a high risk for developing AD. However, little is known about the similarities and differences in the topological patterns of white matter (WM) structural networks between RGD and aMCI. In this study, diffusion tensor imaging and deterministic tractography were used to map the human WM networks of 35 RGD patients, 38 aMCI patients, and 30 healthy subjects. Furthermore, graph theoretical methods were applied to investigate the alterations in the global and regional properties of the WM network in these patients. First, both the RGD and aMCI patients showed abnormal global topology in their WM networks (i.e., reduced network strength, reduced global efficiency, and increased absolute path length) compared with the controls, and there were no significant differences in these global network properties between the patient groups. Second, similar deficits of the regional and connectivity characteristics in the WM networks were primarily found in the frontal brain regions of RGD and aMCI patients compared with the controls, while a different nodal efficiency of the posterior cingulate cortex and several prefrontal brain regions were also observed between the patient groups. Together, our study provides direct evidence for the association of a great majority of convergent and a minority of divergent connectivity of WM structural networks between RGD and aMCI patients, which may lead to increasing attention in defining a population at risk of AD.

Flat metasurfaces to focus electromagnetic waves in reflection geometry.

Abstract: We show that a flat metasurface with a parabolic reflection-phase distribution can focus an impinging plane wave to a point image in reflection geometry. Our system is much thinner than conventional geometric-optics devices and does not suffer the energy-loss issues encountered by many metamaterial devices working in transmission geometry. We designed realistic microwave samples and performed near-field scanning experiments to verify the focusing effect. Experimental results are in good agreement with full wave simulations, model calculations, and theoretical analyses.

Classification of Fruits Using Computer Vision and a Multiclass Support Vector Machine

Abstract: Automatic classification of fruits via computer vision is still a complicated task due to the various properties of numerous types of fruits. We propose a novel classification method based on a multi-class kernel support vector machine (kSVM) with the desirable goal of accurate and fast classification of fruits. First, fruit images were acquired by a digital camera, and then the background of each image was removed by a split-and-merge algorithm; Second, the color histogram, texture and shape features of each fruit image were extracted to compose a feature space; Third, principal component analysis (PCA) was used to reduce the dimensions of feature space; Finally, three kinds of multi-class SVMs were constructed, i.e., Winner-Takes-All SVM, Max-Wins-Voting SVM, and Directed Acyclic Graph SVM. Meanwhile, three kinds of kernels were chosen, i.e., linear kernel, Homogeneous Polynomial kernel, and Gaussian Radial Basis kernel; finally, the SVMs were trained using 5-fold stratified cross validation with the reduced feature vectors as input. The experimental results demonstrated that the Max-Wins-Voting SVM with Gaussian Radial Basis kernel achieves the best classification accuracy of 88.2%. For computation time, the Directed Acyclic Graph SVMs performs swiftest.

Some issues on intuitionistic fuzzy aggregation operators based on Archimedean t-conorm and t-norm

Abstract: Archimedean t-conorm and t-norm are generalizations of a lot of other t-conorms and t-norms, such as Algebraic, Einstein, Hamacher and Frank t-conorms and t-norms or others, and some of them have been applied to intuitionistic fuzzy set, which contains three functions: the membership function, the non-membership function and the hesitancy function describing uncertainty and fuzziness more objectively. Recently, Beliakov et al. [3] constructed some operations about intuitionistic fuzzy sets based on Archimedean t-conorm and t-norm, from which an aggregation principle is proposed for intuitionistic fuzzy information. In this paper, we propose some other operations on intuitionistic fuzzy sets, study their properties and relationships, and based on which, we study the properties of the aggregation principle proposed by Beliakov et al. [3], and give some specific intuitionistic fuzzy aggregation operators, which can be considered as the extensions of the known ones. In the end, we develop an approach for multi-criteria decision making under intuitionistic fuzzy environment, and illustrate an example to show the behavior of the proposed operators.