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Min Chen

Publications and source records attributed to Min Chen.

At least 253 records · Page 14Linked to original sources

Gate-controlled magnonic-assisted switching of magnetization in ferroelectric/ferromagnetic junctions

Interfacing a ferromagnet with a polarized ferroelectric gate generates a non-uniform, interfacial spin density coupled to the ferroelectric polarization allowing so for an electric field control of effective transversal field to magnetization. Here we study the dynamic magnetization switching behavior of such a multilayer system based on the Landau-Lifshitz-Baryakhtar equation, demonstrating that interfacial magnetoelectric coupling is utilizable as a highly localized and efficient tool for manipulating magnetism.

cond-mat.str-el↗

Energy and coverage efficiency trade-off in 5G small cell networks

When small cells are densely deployed in the fifth generation (5G) cellular networks, the base stations (BSs) switch-off strategy is an effective approach for saving energy consumption considering changes of traffic load. In general, the loss of coverage efficiency is an inevitable cost for cellular networks adopting BSs switch-off strategies. Based on the BSs switch-off strategy, an optimized energy density efficiency of hard core point process (HCPP) small cell networks is proposed to trade off the energy and coverage efficiency. Simulation results imply that the minimum active BS distance used for the BSs switch-off strategy is recommended as 150 meters to achieve a tradeoff between energy and coverage efficiency in 5G small cell networks.

cs.NI↗

Detecting Small Signs from Large Images

In the past decade, Convolutional Neural Networks (CNNs) have been demonstrated successful for object detections. However, the size of network input is limited by the amount of memory available on GPUs. Moreover, performance degrades when detecting small objects. To alleviate the memory usage and improve the performance of detecting small traffic signs, we proposed an approach for detecting small traffic signs from large images under real world conditions. In particular, large images are broken into small patches as input to a Small-Object-Sensitive-CNN (SOS-CNN) modified from a Single Shot Multibox Detector (SSD) framework with a VGG-16 network as the base network to produce patch-level object detection results. Scale invariance is achieved by applying the SOS-CNN on an image pyramid. Then, image-level object detection is obtained by projecting all the patch-level detection results to the image at the original scale. Experimental results on a real-world conditioned traffic sign dataset have demonstrated the effectiveness of the proposed method in terms of detection accuracy and recall, especially for those with small sizes.

cs.CV↗

Brain Intelligence: Go Beyond Artificial Intelligence

Artificial intelligence (AI) is an important technology that supports daily social life and economic activities. It contributes greatly to the sustainable growth of Japan's economy and solves various social problems. In recent years, AI has attracted attention as a key for growth in developed countries such as Europe and the United States and developing countries such as China and India. The attention has been focused mainly on developing new artificial intelligence information communication technology (ICT) and robot technology (RT). Although recently developed AI technology certainly excels in extracting certain patterns, there are many limitations. Most ICT models are overly dependent on big data, lack a self-idea function, and are complicated. In this paper, rather than merely developing next-generation artificial intelligence technology, we aim to develop a new concept of general-purpose intelligence cognition technology called Beyond AI. Specifically, we plan to develop an intelligent learning model called Brain Intelligence (BI) that generates new ideas about events without having experienced them by using artificial life with an imagine function. We will also conduct demonstrations of the developed BI intelligence learning model on automatic driving, precision medical care, and industrial robots.

cs.CV↗

Persistent Spread Measurement for Big Network Data Based on Register Intersection

Persistent spread measurement is to count the number of distinct elements that persist in each network flow for predefined time periods. It has many practical applications, including detecting long-term stealthy network activities in the background of normal-user activities, such as stealthy DDoS attack, stealthy network scan, or faked network trend, which cannot be detected by traditional flow cardinality measurement. With big network data, one challenge is to measure the persistent spreads of a massive number of flows without incurring too much memory overhead as such measurement may be performed at the line speed by network processors with fast but small on-chip memory. We propose a highly compact Virtual Intersection HyperLogLog (VI-HLL) architecture for this purpose. It achieves far better memory efficiency than the best prior work of V-Bitmap, and in the meantime drastically extends the measurement range. Theoretical analysis and extensive experiments demonstrate that VI-HLL provides good measurement accuracy even in very tight memory space of less than 1 bit per flow.

cs.NI↗

Underwater Optical Image Processing: A Comprehensive Review

Underwater cameras are widely used to observe the sea floor. They are usually included in autonomous underwater vehicles, unmanned underwater vehicles, and in situ ocean sensor networks. Despite being an important sensor for monitoring underwater scenes, there exist many issues with recent underwater camera sensors. Because of lights transportation characteristics in water and the biological activity at the sea floor, the acquired underwater images often suffer from scatters and large amounts of noise. Over the last five years, many methods have been proposed to overcome traditional underwater imaging problems. This paper aims to review the state-of-the-art techniques in underwater image processing by highlighting the contributions and challenges presented in over 40 papers. We present an overview of various underwater image processing approaches, such as underwater image descattering, underwater image color restoration, and underwater image quality assessments. Finally, we summarize the future trends and challenges in designing and processing underwater imaging sensors.

cs.CV↗

High quality electron beam acceleration by ionization injection in laser wakefields with mid-infrared dual-color lasers

For the laser wakefield acceleration, suppression of beam energy spread while keeping sufficient charge is one of the key challenges. In order to achieve this, we propose bichromatic laser ionization injection with combined laser wavelengths of $2.4\rm μm$ and $0.8\rm μm$ for wakefield excitation and for triggering electron injection via field ionization, respectively. A laser pulse at $2.4\rm μm$ wavelength enables one to drive an intense acceleration structure with relatively low laser power. To further reduce the requirement of laser power, we also propose to use carbon dioxide as the working gas medium, where carbon acts as the injection element. Our full three dimensional particle-in-cell simulations show that electron beams at the GeV energy level with both low energy spreads (around one percent) and high charges (several tens of picocoulomb) can be obtained by this scheme with laser parameters achievable in the near future.

physics.plasm-ph↗

POMDP-lite for Robust Robot Planning under Uncertainty

The partially observable Markov decision process (POMDP) provides a principled general model for planning under uncertainty. However, solving a general POMDP is computationally intractable in the worst case. This paper introduces POMDP-lite, a subclass of POMDPs in which the hidden state variables are constant or only change deterministically. We show that a POMDP-lite is equivalent to a set of fully observable Markov decision processes indexed by a hidden parameter and is useful for modeling a variety of interesting robotic tasks. We develop a simple model-based Bayesian reinforcement learning algorithm to solve POMDP-lite models. The algorithm performs well on large-scale POMDP-lite models with up to $10^{20}$ states and outperforms the state-of-the-art general-purpose POMDP algorithms. We further show that the algorithm is near-Bayesian-optimal under suitable conditions.

cs.AI↗

Valley-protected backscattering suppression in silicon photonic graphene

In this paper, we study valley degree of freedom in all dielectric silicon photonic graphene. Photonic band gap opening physics under inversion symmetry breaking is revisited by the viewpoint of nonzero valley Chern number. Bulk valley modes with opposite orbital angular momentum are unveiled by inspecting time-varying electric fields. Topological transition is well illustrated through photonic Dirac Hamiltonian. Valley dependent edge states and the associated valley-protected backscattering suppression around Z-shape bend waveguide have been demonstrated.

physics.optics↗

A compact tunable polarized X-ray source based on laser-plasma helical undulators

Laser wakefield accelerators have great potential as the basis for next generation compact radiation sources because their accelerating gradients are three orders of magnitude larger than traditional accelerators. However, X-ray radiation from such devices still lacks of tunability, especially the intensity and polarization distribution. Here we propose a tunable polarized radiation source from a helical plasma undulator based on plasma channel guided wakefield accelerator. When a laser pulse is initially incident with a skew angle relative to the channel axis, the laser and accelerated electrons experience collective spiral motions, which leads to elliptically polarized synchrotron-like radiation with flexible tunability on radiation intensity, spectra and polarization. We demonstrate that a radiation source with millimeter size and peak brilliance of $2\times10^{19} photons/s/mm^{2}/mrad^{2}/0.1%$ bandwidth can be made with moderate laser and electron beam parameters. This brilliance is comparable with the third generation of synchrotron radiation facilities running at similar photon energies, suggesting that laser plasma based radiation sources are promising for advanced applications.

physics.plasm-ph↗

Plasma optical modulators for intense lasers

Optical modulators can be made nowadays with high modulation speed, broad bandwidth, while being compact, owing to the recent advance in material science and microfabrication technology. However, these optical modulators usually work for low intensity light beams. Here, we present an ultrafast, plasma-based optical modulator, which can directly modulate high power lasers with intensity up to 10^16 W/cm^2 level to produce an extremely broad spectrum with a fractional bandwidth over 100%, extending to the mid-infrared regime in the low-frequency side. This concept relies on two co-propagating laser beams in a sub-mm-scale underdense plasma, where a drive laser pulse first excites an electron plasma wave in its wake while a following carrier laser beam is modulated by the plasma wave. The laser and plasma parameters suitable for the modulator to work are presented. Such optical modulators may enable new applications in the high field physics.

physics.plasm-ph↗

Service-Oriented Architectures and Web Services: Course Tutorial and Lab Notes

This document presents a number of quick-step instructions to get started on writing mini-service-oriented web services-based applications using OpenESB 2.31, Tomcat 6, GlassFish 2.x/3.0.1 with BPEL support, and Java 1.6+ primarily in Scientific Linux 6.6 with user quota restrictions. While the tutorial notes are oriented towards the students taking the SOEN487 on service-oriented architectures (SOA) at Computer Science and Software Engineering (CSE) Department, Faculty of Engineering and Computer Science (ENCS), other may find some of it useful as well outside of CSE or Concordia. The notes are compiled mostly based on the students' needs and feedback.

cs.DC↗

RF-Based Charger Placement for Duty Cycle Guarantee in Battery-Free Sensor Networks

Battery-free sensor networks have emerged as a promising solution to conquer the lifetime limitation of battery-powered systems. In this paper, we study a sensor network built from battery-free sensor nodes which harvest energy from radio frequency (RF) signals transmitted by RF-based chargers, e.g., radio frequency identification (RFID) readers. Due to the insufficiency of harvested energy, the sensor nodes have to work in duty cycles to harvest enough energy before turning active and performing tasks. One fundamental issue in this kind of network design is how to deploy the chargers to ensure that the battery-free nodes can maintain a designated duty cycle for continuous operation. Based on a new wireless recharge model, we formulate the charger placement problem for node's duty cycle guarantee as a constrained optimization problem. We develop both greedy and efficient heuristics for solving the problem and validate our solutions through extensive simulations. The simulation results show that the proposed particle swarm optimization (PSO)-based divide-and-conquer approach can effectively reduce the number of chargers compared with the greedy approach.

cs.NI↗

Perturbed Hankel determinant, correlation functions and Painlevé equations

We continue with the study of the Hankel determinant, $$ D_{n}(t,α,β):=\det\left(\int_{0}^{1}x^{j+k}w(x;t,α,β)dx\right)_{j,k=0}^{n-1}, $$ generated by a Pollaczek-Jacobi type weight, $$ w(x;t,α,β):=x^α(1-x)^β{\rm e}^{-t/x}, \quad x\in [0,1], \quad α>0, \quad β>0, \quad t\geq 0. $$ This reduces to the "pure" Jacobi weight at $t=0.$ We may take $α\in \mathbb{R}$, in the situation while $t$ is strictly greater than $0.$ It was shown in Chen and Dai (2010), that the logarithmic derivative of this Hankel determinant satisfies a Jimbo-Miwa-Okamoto $σ$-form of Painlevé \uppercase\expandafter{\romannumeral5} (${\rm P_{\uppercase\expandafter{\romannumeral5}}}$). In fact the logarithmic of the Hankel determinant has an integral representation in terms of a particular ${\rm P_{\uppercase\expandafter{\romannumeral5}}}.$ \\ In this paper, we show that, under a double scaling, where $n$ the dimension of the Hankel matrix tends to $\infty$, and $t$ tends to $0^{+},$ such that $s:=2n^2t$ is finite, the double scaled Hankel determinant (effectively an operator determinant) has an integral representation in terms of a particular ${\rm P_{\uppercase\expandafter{\romannumeral3}'}}.$ Expansions of the scaled Hankel determinant for small and large $s$ are found. A further double scaling with $α=-2n+λ,$ where $n\rightarrow \infty$ and $t,$ tends to $0^{+},$ such that $s:=nt$ is finite. In this situation the scaled Hankel determinant has an integral representation in terms of a particular ${\rm P_{\uppercase\expandafter{\romannumeral5}}},$ %which can be degenerate to a particular ${\rm P_{\uppercase\expandafter{\romannumeral3}}}$ and its small and large $s$ asymptotic expansions are also found.

math.CA↗

What May Visualization Processes Optimize?

In this paper, we present an abstract model of visualization and inference processes and describe an information-theoretic measure for optimizing such processes. In order to obtain such an abstraction, we first examined six classes of workflows in data analysis and visualization, and identified four levels of typical visualization components, namely disseminative, observational, analytical and model-developmental visualization. We noticed a common phenomenon at different levels of visualization, that is, the transformation of data spaces (referred to as alphabets) usually corresponds to the reduction of maximal entropy along a workflow. Based on this observation, we establish an information-theoretic measure of cost-benefit ratio that may be used as a cost function for optimizing a data visualization process. To demonstrate the validity of this measure, we examined a number of successful visualization processes in the literature, and showed that the information-theoretic measure can mathematically explain the advantages of such processes over possible alternatives.

cs.HC↗

Singular linear statistics of the Laguerre Unitary Ensemble and Painlevé III (${\rm P_{III}}$): Double scaling analysis

We continue with the study of the Hankel determinant, $$ D_{n}(t,α):=\det\left(\int_{0}^{\infty}x^{j+k}w(x;t,α)dx\right)_{j,k=0 }^{n-1}, $$ generated by singularly perturbed Laguerre weight, $$ w(x;t,α):=x^α{\rm e}^{-x}\:{\rm e}^{-t/x}, \quad 0\leq x<\infty,\;\;\;α>0,\;\;\;\;t>0, $$ obtained through a deformation of the Laguerre weight function, $$ w(x;0,α):=x^α{\rm e}^{-x},\quad 0\leq x<\infty,\;\; α>0, $$ via the multiplicative factor ${\rm e}^{-t/x}$. \\ An earlier investigation was made on the finite $n$ aspect of the problem, this has appeared in \cite{ci1}. There, it was found that the logarithm of the Hankel determinant has an integral representation in terms of a particular ${\rm P_{III}},$ and its derivative with $t.$ In this paper we show that, under a double scaling, where $n$, the order of the Hankel matrix tends to $\infty,$ and $t$, tends to $0$, the scaled---and therefore, in some sense, infinite dimensional---Hankel determinant, has an integral representation in terms of the $C$ potential, and its derivatives. The second order non-linear differential equation which the $C$ potential satisfies, after a minor change of variables, is another ${\rm P_{III}},$ albeit with fewer number of parameters. \\ Expansions of the double scaled determinant for small and large parameter are obtained.

math.CA↗

A Palmtop Synchrotron-like Radiation Source

Synchrotron radiation sources are immensely useful tools for scientific researches and many practical applications. Currently, the state-of-the-art synchrotrons rely on conventional accelerators, where electrons are accelerated in a straight line and radiate in bending magnets or other insertion devices. However, these facilities are usually large and costly. Here, we propose a compact all-optical synchrotron-like radiation source based on laser-plasma acceleration either in a straight or in a curved plasma channel. With the laser pulse off-axially injected in a straight channel, the centroid oscillation of the pulse causes a wiggler motion of the whole accelerating structure including the trapped electrons, leading to strong synchrotron-like radiations with tunable spectra. It is further shown that a ring-shaped synchrotron is possible in a curved plasma channel. Due to the intense acceleration and bending fields inside plasmas, the central part of the sources can be made within palm size. With its potential of high flexibility and tunability, such compact light sources once realized would find applications in wide areas and make up the shortage of large synchrotron radiation facilities.

physics.plasm-ph↗

Decomposition of Sparse Graphs into Forests: The Nine Dragon Tree Conjecture for $k \le 2$

For a loopless multigraph $G$, the fractional arboricity $Arb(G)$ is the maximum of $\frac{|E(H)|}{|V(H)|-1}$ over all subgraphs $H$ with at least two vertices. Generalizing the Nash-Williams Arboricity Theorem, the Nine Dragon Tree Conjecture asserts that if $Arb(G)\le k+\frac{d}{k+d+1}$, then $G$ decomposes into $k+1$ forests with one having maximum degree at most $d$. The conjecture was previously proved for $d=k+1$ and for $k=1$ when $d \le 6$. We prove it for all $d$ when $k \le 2$, except for $(k,d)=(2,1)$.

math.CO↗