arXiv subjects

Yong Wang

Publications and source records attributed to Yong Wang.

At least 577 records · Page 32Linked to original sources

arXiv2017

Semicrystalline block copolymers in rigid confining nanopores

We have investigated PLLA crystallization in lamellae-forming PS-b-PLLA confined to straight cylindrical nanopores under weak confinement (nanopore diameter D / equilibrium PS-b-PLLA period L0 larger than 4.8). Molten PS-b-PLLA predominantly forms concentric lamellae along the nanopores, but intertwined helices occur even for D/L0 = 7.3. Quenching PS-b-PLLA melts below TG(PS) results in PLLA cold crystallization strictly confined by the vitrified PS domains. Above TG(PS), PLLA crystallization is templated by the PS-b-PLLA melt domain structure in the nanopore centers, while adsorption on the nanopore walls stabilizes the outermost cylindrical PS-b-PLLA shell. In between, the nanoscopic PS-b-PLLA melt domain structure apparently ripens to reduce frustrations transmitted from the outermost immobilized PS-b-PLLA layer. The onset of PLLA crystallization catalyzes the ripening while transient ripening states are arrested by advancing PLLA crystallization. Certain helical structure motifs persist PLLA crystallization even if PS is soft. The direction of fastest PLLA crystal growth is preferentially aligned with the nanopore axes to the same degree as for PLLA homopolymer, independent of whether PS is vitreous or soft.

cond-mat.soft↗

arXiv2017

Advanced SERS sensor based on capillarity-assisted preconcentration through gold nanoparticles-decorated porous nanorods

A preconcentrating surface-enhanced Raman scattering (SERS) sensor for the analysis of liquid-soaked tissue, tiny liquid droplets and thin liquid films without the necessity to collect the analyte is reported. The SERS sensor is based on a blockcopolymer membrane containing a spongy-continuous pore system. The sensor's upper side is an array of porous nanorods having tips functionalized with Au nanoparticles. Capillarity in combination with directional evaporation drives the analyte solution in contact with the flat yet nanoporous underside of the SERS sensor through the continuous nanopore system toward the nanorod tips where non-volatile components of the analyte solution precipitate at the Au nanoparticles. The nanorod architecture increases the sensor surface in the detection volume and facilitates analyte preconcentration driven by directional solvent evaporation. The model analyte 5,5'-dithiobis(2-nitrobenzoic acid) can be detected in a 1 x 10-3 m solution about 300 ms after the sensor is brought into contact with the solution. Moreover, a sensitivity of 0.1 ppm for the detection of the dissolved model analyte is achieved.

cond-mat.mes-hall↗

arXiv2017

A Many-Objective Evolutionary Algorithm with Angle-Based Selection and Shift-Based Density Estimation

Evolutionary many-objective optimization has been gaining increasing attention from the evolutionary computation research community. Much effort has been devoted to addressing this issue by improving the scalability of multiobjective evolutionary algorithms, such as Pareto-based, decomposition-based, and indicator-based approaches. Different from current work, we propose a novel algorithm in this paper called AnD, which consists of an angle-based selection strategy and a shift-based density estimation strategy. These two strategies are employed in the environmental selection to delete the poor individuals one by one. Specifically, the former is devised to find a pair of individuals with the minimum vector angle, which means that these two individuals share the most similar search direction. The latter, which takes both the diversity and convergence into account, is adopted to compare these two individuals and to delete the worse one. AnD has a simple structure, few parameters, and no complicated operators. The performance of AnD is compared with that of seven state-of-the-art many-objective evolutionary algorithms on a variety of benchmark test problems with up to 15 objectives. The experimental results suggest that AnD can achieve highly competitive performance. In addition, we also verify that AnD can be readily extended to solve constrained many-objective optimization problems.

cs.NE↗

arXiv2017

Truly Concurrent Process Algebra with Timing

We extend truly concurrent process algebra APTC with timing related properties. Just like ACP with timing, APTC with timing also has four parts: discrete relative timing, discrete absolute timing, continuous relative timing and continuous absolute timing.

cs.LO↗

arXiv2017

Research on Shape Mapping of 3D Mesh Models based on Hidden Markov Random Field and EM Algorithm

How to establish the matching (or corresponding) between two different 3D shapes is a classical problem. This paper focused on the research on shape mapping of 3D mesh models, and proposed a shape mapping algorithm based on Hidden Markov Random Field and EM algorithm, as introducing a hidden state random variable associated with the adjacent blocks of shape matching when establishing HMRF. This algorithm provides a new theory and method to ensure the consistency of the edge data of adjacent blocks, and the experimental results show that the algorithm in this paper has a great improvement on the shape mapping of 3D mesh models.

cs.GR↗

arXiv2017

An Algebra of Actors Based on True Concurrency

An algebra of actors $\textrm{A}π$ fully captures the properties of actors based on asynchronous $π$-calculus, but, it is based on the interleaving bisimulation semantics. We adjust $\textrm{A}π$ to $\textrm{A}π_{tc}$ to make $\textrm{A}π$ having a truly concurrent semantics. We give the syntax and operational semantics of $\textrm{A}π_{tc}$, and also the truly concurrent semantics model and algebraic laws of $\textrm{A}π_{tc}$.

cs.LO↗

arXiv2017

Learning Traffic as Images: A Deep Convolutional Neural Network for Large-Scale Transportation Network Speed Prediction

This paper proposes a convolutional neural network (CNN)-based method that learns traffic as images and predicts large-scale, network-wide traffic speed with a high accuracy. Spatiotemporal traffic dynamics are converted to images describing the time and space relations of traffic flow via a two-dimensional time-space matrix. A CNN is applied to the image following two consecutive steps: abstract traffic feature extraction and network-wide traffic speed prediction. The effectiveness of the proposed method is evaluated by taking two real-world transportation networks, the second ring road and north-east transportation network in Beijing, as examples, and comparing the method with four prevailing algorithms, namely, ordinary least squares, k-nearest neighbors, artificial neural network, and random forest, and three deep learning architectures, namely, stacked autoencoder, recurrent neural network, and long-short-term memory network. The results show that the proposed method outperforms other algorithms by an average accuracy improvement of 42.91% within an acceptable execution time. The CNN can train the model in a reasonable time and, thus, is suitable for large-scale transportation networks.

cs.LG↗

arXiv2017

A Calculus of Truly Concurrent Mobile Processes

We make a mixture of Milner's $π$-calculus and our previous work on truly concurrent process algebra, which is called $π_{tc}$. We introduce syntax and semantics of $π_{tc}$, its properties based on strongly truly concurrent bisimilarities. Also, we include an axiomatization of $π_{tc}$. $π_{tc}$ can be used as a formal tool in verifying mobile systems in a truly concurrent flavor.

cs.LO↗

arXiv2017

Diffraction-Free Bloch Surface Waves

In this letter, we demonstrate a novel diffraction-free Bloch surface wave (DF-BSW) sustained on all-dielectric multilayers that does not diffract after being passed through three obstacles or across a single mode fiber. It can propagate in a straight line for distances longer than 110 μm at a wavelength of 633 nm and could be applied as an in-plane optical virtual probe, both in air and in an aqueous environment. The ability to be used in water, its long diffraction-free distance, and its tolerance to multiple obstacles make this DF-BSW ideal for certain applications in areas such as the biological sciences, where many measurements are made on glass surfaces or for which an aqueous environment is required, and for high-speed interconnections between chips, where low loss is necessary. Specifically, the DF-BSW on the dielectric multilayer can be used to develop novel flow cytometry that is based on the surface wave, but not the free space beam, to detect the surface-bound targets.

physics.optics↗

arXiv2017

The Influence of Surface Topography and Surface Chemistry on the Anti-Adhesive Performance of Nanoporous Monoliths

We designed spongy monoliths allowing liquid delivery to their surfaces through continuous nanopore systems (mean pore diameter ca. 40 nm). These nanoporous monoliths were flat or patterned with microspherical structures a few 10 microns in diameter, and their surfaces consisted of aprotic polymer or of TiO2 coatings. Liquid may reduce adhesion forces FAd; possible reasons include screening of solid-solid interactions and poroelastic effects. Softening-induced deformation of flat polymeric monoliths upon contact formation in the presence of liquids enhanced the work of separation WSe. On flat TiO2-coated monoliths, WSe was under wet conditions smaller than under dry conditions, possibly because of liquid-induced screening of solid-solid interactions. Under dry conditions, WSe is larger on flat TiO2-coated monoliths than on flat monoliths with polymeric surface. However, under wet conditions liquid-induced softening results in larger WSe on flat monoliths with polymeric surface than on flat monoliths with oxidic surface. Monolithic microsphere arrays show anti-adhesive properties; FAd and WSe are reduced by at least one order of magnitude as compared to flat nanoporous counterparts. On nanoporous monolithic microsphere arrays, capillarity (WSe is larger under wet than under dry conditions) and solid-solid interactions (WSe is larger on oxide than on polymer) dominate contact mechanics. Thus, the microsphere topography reduces the impact of softening-induced surface deformation and screening of solid-solid interactions associated with liquid supply. Overall, simple modifications of surface topography and chemistry combined with delivery of liquid to the contact interface allow adjusting WSe and FAd over at least one order of magnitude. (...)

cond-mat.soft↗

arXiv2017

An Adaptive Framework to Tune the Coordinate Systems in Evolutionary Algorithms

In the evolutionary computation research community, the performance of most evolutionary algorithms (EAs) depends strongly on their implemented coordinate system. However, the commonly used coordinate system is fixed and not well suited for different function landscapes, EAs thus might not search efficiently. To overcome this shortcoming, in this paper we propose a framework, named ACoS, to adaptively tune the coordinate systems in EAs. In ACoS, an Eigen coordinate system is established by making use of the cumulative population distribution information, which can be obtained based on a covariance matrix adaptation strategy and an additional archiving mechanism. Since the population distribution information can reflect the features of the function landscape to some extent, EAs in the Eigen coordinate system have the capability to identify the modality of the function landscape. In addition, the Eigen coordinate system is coupled with the original coordinate system, and they are selected according to a probability vector. The probability vector aims to determine the selection ratio of each coordinate system for each individual, and is adaptively updated based on the collected information from the offspring. ACoS has been applied to two of the most popular EA paradigms, i.e., particle swarm optimization (PSO) and differential evolution (DE), for solving 30 test functions with 30 and 50 dimensions at the 2014 IEEE Congress on Evolutionary Computation. The experimental studies demonstrate its effectiveness.

cs.NE↗

arXiv2017

Interlayer coupling in commensurate and incommensurate bilayer structures of transition metal dichalcogenides

The interlayer couplings in commensurate and incommensurate bilayer structures of transition metal dichalcogenides are investigated with perturbative treatment. The interlayer coupling in \pm K valleys can be decomposed into a series of hopping terms with distinct phase factors. In H-type and R-type commensurate bilayers, the interference between the three main terms leads to a sensitive dependence of the interlayer coupling strength on the translation. The magnitudes of the main hopping terms are found to some dozen of meV by fitting to the ab initio results. The interlayer couplings in Γvalley of valence band and Q valley of conduction band are also studied. The obtained strong coupling strengths of several hundred meV can play important roles in mediating the ultrafast interlayer charge transfer in heterobilayers of transition metal dichalcogenides.

cond-mat.mes-hall↗

arXiv2017

Challenge of Multi-Camera Tracking

Multi-camera tracking is quite different from single camera tracking, and it faces new technology and system architecture challenges. By analyzing the corresponding characteristics and disadvantages of the existing algorithms, problems in multi-camera tracking are summarized and some new directions for future work are also generalized.

cs.CV↗

arXiv2017

Transplantation of Data Mining Algorithms to Cloud Computing Platform when Dealing Big Data

This paper made a short review of Cloud Computing and Big Data, and discussed the portability of general data mining algorithms to Cloud Computing platform. It revealed the Cloud Computing platform based on Map-Reduce cannot solve all the Big Data and data mining problems. Transplanting the general data mining algorithms to the real-time Cloud Computing platform will be one of the research focuses in Cloud Computing and Big Data.

cs.DC↗

arXiv2017

Survey of modern Fault Diagnosis methods in networks

With the advent of modern computer networks, fault diagnosis has been a focus of research activity. This paper reviews the history of fault diagnosis in networks and discusses the main methods in information gathering section, information analyzing section and diagnosing and revolving section of fault diagnosis in networks. Emphasis will be placed upon knowledge-based methods with discussing the advantages and shortcomings of the different methods. The survey is concluded with a description of some open problems.

cs.AI↗

arXiv2017

A Theoretical Perspective of Solving Phaseless Compressed Sensing via Its Nonconvex Relaxation

As a natural extension of compressive sensing and the requirement of some practical problems, Phaseless Compressed Sensing (PCS) has been introduced and studied recently. Many theoretical results have been obtained for PCS with the aid of its convex relaxation. Motivated by successful applications of nonconvex relaxed methods for solving compressive sensing, in this paper, we try to investigate PCS via its nonconvex relaxation. Specifically, we relax PCS in the real context by the corresponding $\ell_p$-minimization with $p\in (0,1)$. We show that there exists a constant $p^\ast\in (0,1]$ such that for any fixed $p\in(0, p^\ast)$, every optimal solution to the $\ell_p$-minimization also solves the concerned problem; and derive an expression of such a constant $p^\ast$ by making use of the known data and the sparsity level of the concerned problem. These provide a theoretical basis for solving this class of problems via the corresponding $\ell_p$-minimization.

math.OC↗

arXiv2017

Optical selection rules for excitonic Rydberg series in the massive Dirac cones of hexagonal 2D materials

We investigate the optical transition selection rules for excitonic Rydberg series formed in massive Dirac cones. The entanglement of the exciton envelop function with the pseudospin texture leads to anomalous selection rules for one-photon generation of excitons, where $d$-orbitals can be excited with the opposite helicity selection rule from the $s$-orbitals in a given valley. The trigonal warping effects in realistic hexagonal lattices further renders more excited states bright, where $p$-orbitals can also be accessed by one-photon excitation with the opposite valley selection rules to the $s$-orbitals. The one-photon generation of exciton in the various states and the intra-excitonic transition between these states are both dictated by the discrete in-plane rotational symmetry of the lattices, and our results show that in hexagonal 2D materials the symmetry allowed transitions are enabled when trigonal warping effects are included in the massive Dirac fermion model. In monolayer transition metal dichalcogenides where excitons can be generated by visible light and intra-excitonic transitions can be induced by infrared light, we give the strength of these optical transitions, estimated using modified hydrogen-like envelope functions combined with the optical transition matrix elements between the Bloch states calculated at various $k$ points.

cond-mat.mes-hall↗

arXiv2017

Introduction to Tensor Variational Inequalities

In this paper, we introduce a class of variational inequalities, where the involved function is the sum of an arbitrary given vector and a homogeneous polynomial defined by a tensor; and we call it the tensor variational inequality (TVI). The TVI is a natural extension of the affine variational inequality and the tensor complementarity problem. We show that a class of multi-person noncooperative games can be formulated as a TVI. In particular, we investigate the global uniqueness and solvability of the TVI. To this end, we first introduce two classes of structured tensors and discuss some related properties; and then, we show that the TVI has the property of global uniqueness and solvability under some assumptions, which is different from the existed result for the general variational inequality.

math.OC↗