arXiv subjects

Chao Chen

Publications and source records attributed to Chao Chen.

At least 919 records · Page 51Linked to original sources

arXiv2013

Design and Implementation of a Wireless Sensor and Actuator Network for Energy Measurement and Control at Home

This paper describes the design, implementation, and testing of a wireless sensor and actuator network for monitoring the energy use of electric appliances in a home environment. The network includes energy measurement nodes and a central server, where the nodes read the energy use of connected appliance, and wirelessly report their readings to the central server for processing. The server displays the readings from these nodes via a user visual interface in real time. Through this system, users can easily understand their electricity usage patterns and adapt their behavior to reduce their energy consumption and costs. Moreover, users are able to remotely power on/off individual devices to actively control the power use of certain appliances. The system allows for inexpensive monitoring of home energy use and illustrates a practical way to control the energy consumption through user interaction.

cs.NI↗

arXiv2012

Layered Subspace Codes for Network Coding

Subspace codes were introduced by Kötter and Kschischang for error control in random linear network coding. In this paper, a layered type of subspace codes is considered, which can be viewed as a superposition of multiple component subspace codes. Exploiting the layered structure, we develop two decoding algorithms for these codes. The first algorithm operates by separately decoding each component code. The second algorithm is similar to the successive interference cancellation (SIC) algorithm for conventional superposition coding, and further permits an iterative version. We show that both algorithms decode not only deterministically up to but also probabilistically beyond the error-correction capability of the overall code. Finally we present possible applications of layered subspace codes in several network coding scenarios.

cs.IT↗

arXiv2012

The Most Persistent Soft-Clique in a Set of Sampled Graphs

When searching for characteristic subpatterns in potentially noisy graph data, it appears self-evident that having multiple observations would be better than having just one. However, it turns out that the inconsistencies introduced when different graph instances have different edge sets pose a serious challenge. In this work we address this challenge for the problem of finding maximum weighted cliques. We introduce the concept of most persistent soft-clique. This is subset of vertices, that 1) is almost fully or at least densely connected, 2) occurs in all or almost all graph instances, and 3) has the maximum weight. We present a measure of clique-ness, that essentially counts the number of edge missing to make a subset of vertices into a clique. With this measure, we show that the problem of finding the most persistent soft-clique problem can be cast either as: a) a max-min two person game optimization problem, or b) a min-min soft margin optimization problem. Both formulations lead to the same solution when using a partial Lagrangian method to solve the optimization problems. By experiments on synthetic data and on real social network data, we show that the proposed method is able to reliably find soft cliques in graph data, even if that is distorted by random noise or unreliable observations.

cs.LG↗

arXiv2012

Ultrafast Spontaneous Motion of Nanodroplets

Making liquid droplets move spontaneously on solid surfaces is a key challenge in lab-on-chip and heat exchanger technologies. The best-known mechanism, a wettability gradient, does not generally move droplets rapidly enough and cannot drive droplets smaller than a critical size. Here we report how a curvature gradient is particularly effective at accelerating small droplets, and works for both hydrophilic and hydrophobic surfaces. Experiments for water droplets on tapered surfaces with curvature radii in the sub-millimeter range show a maximum speed of 0.28 m/s, two orders of magnitude higher than obtained by wettability gradient. We show that the force exerted on a droplet scales as the surface curvature gradient. Using molecular dynamics simulations, we observe nanoscale droplets moving spontaneously at over 100 m/s on tapered surfaces.

cond-mat.soft↗

arXiv2012

Annotating Simplices with a Homology Basis and Its Applications

Let $K$ be a simplicial complex and $g$ the rank of its $p$-th homology group $H_p(K)$ defined with $Z_2$ coefficients. We show that we can compute a basis $H$ of $H_p(K)$ and annotate each $p$-simplex of $K$ with a binary vector of length $g$ with the following property: the annotations, summed over all $p$-simplices in any $p$-cycle $z$, provide the coordinate vector of the homology class $[z]$ in the basis $H$. The basis and the annotations for all simplices can be computed in $O(n^ω)$ time, where $n$ is the size of $K$ and $ω<2.376$ is a quantity so that two $n\times n$ matrices can be multiplied in $O(n^ω)$ time. The pre-computation of annotations permits answering queries about the independence or the triviality of $p$-cycles efficiently. Using annotations of edges in 2-complexes, we derive better algorithms for computing optimal basis and optimal homologous cycles in 1-dimensional homology. Specifically, for computing an optimal basis of $H_1(K)$, we improve the time complexity known for the problem from $O(n^4)$ to $O(n^ω+n^2g^{ω-1})$. Here $n$ denotes the size of the 2-skeleton of $K$ and $g$ the rank of $H_1(K)$. Computing an optimal cycle homologous to a given 1-cycle is NP-hard even for surfaces and an algorithm taking $2^{O(g)}n\log n$ time is known for surfaces. We extend this algorithm to work with arbitrary 2-complexes in $O(n^ω)+2^{O(g)}n^2\log n$ time using annotations.

cs.CG↗

arXiv2012

Driving Droplets by Curvi-Propulsion

How to make small liquid droplets move spontaneously and directionally on solid surfaces is a challenge in lab-on-chip technologies, DNA analysis, and heat exchangers. The best-known mechanism, a wettability gradient, does not move droplets rapidly enough for most purposes and cannot move droplets smaller than a critical size defined by the contact angle hysteresis. Here we report on a mechanism using curvature gradients, which we show is particularly effective at accelerating small droplets, and works for both hydrophilic and hydrophobic surfaces. Experiments for water droplets on glass cones in the sub-millimeter range show a maximum speed of 0.28 m/s, two orders of magnitude higher than obtained by wettability gradient. From simple considerations of droplet surface area change, we show that the force exerted on a droplet on a conical surface scales as the curvature gradient. This force therefore diverges for small droplets near the tip of a cone. We illustrate this using molecular dynamics simulations, and describe nanometer-scale droplets moving spontaneously at over 100 m/s on nano-cones.

physics.flu-dyn↗

arXiv2011

Ultrafast Drop Movements Arising from Curvature Gradient

We report experimental observation of a kind of fast spontaneous movements of water drops on surfaces of cones with diameters from 0.1 to 1.5 mm. The observed maximum speed (0.22 m/s) under ambient conditions were at least two orders of magnitude higher than that resulting from any known single spontaneous movement mechanism, for example, Marangoni effect due to gradient of surface tension. We trapped even higher spontaneous movement speeds (up to 125 m/s) in virtual experiments for drops on nanoscale cones by using molecular dynamics simulations. The underlying mechanism is found to be universally effective - drops on any surface either hydrophilic or hydrophobic with varying mean curvature are subject to driving forces toward the gradient direction of the mean curvature. The larger the mean curvature of the surface and the lower the contact angle of the liquid are, the stronger the driving force will be. This discovery can lead to more effective techniques for transporting droplets.

physics.chem-ph↗

arXiv2011

The generalized quadratic covariation for fractional Brownian motion with Hurst index less than 1/2

Let $B^H$ be a fractional Brownian motion with Hurst index $0<H<1/2$. In this paper we study the {\it generalized quadratic covariation} $[f(B^H),B^H]^{(W)}$ defined by $$ [f(B^H),B^H]^{(W)}_t=\lim_{ε\downarrow 0}\frac{2H}{ε^{2H}}\int_0^t\{f(B^{H}_{s+ε})-f(B^{H}_s)\}(B^{H}_{s+ε}- B^{H}_s)s^{2H-1}ds, $$ where the limit is uniform in probability and $x\mapsto f(x)$ is a deterministic function. We construct a Banach space ${\mathscr H}$ of measurable functions such that the generalized quadratic covariation exists in $L^2$ and the Bouleau-Yor identity takes the form $$ [f(B^H),B^H]_t^{(W)}=-\int_{\mathbb {R}}f(x){\mathscr L}^{H}(dx,t) $$ provided $f\in {\mathscr H}$, where ${\mathscr L}^{H}(x,t)$ is the weighted local time of $B^H$. This allows us to write the fractional Itô formula for absolutely continuous functions with derivative belonging to ${\mathscr H}$. These are also extended to the time-dependent case.

math.PR↗

arXiv2011

Viscous damping of nanobeam resonators: humidity, thermal noise and the paddling effect

The nanobeam resonator is the key mechanical component in the nano-electromechanical system. In addition to its high frequency originating from its low dimension, the performance is significantly influenced by the circumstances, especially at nanoscale where a large surface area of the material is exposed. Molecular dynamics simulations and theoretical analysis are used for a quantitative prediction on the damping behavior, such as the critical damping condition and lifetime, of nanobeam resonators that directly maps the fluid-structure properties and interaction information into dynamical behaviors. We show here how the humidity defines the critical damping condition through viscous forces, marking the transition from under-damping to over-damping regime at elevated humidity. Novel phenomena such as the thermal fluctuation and paddling effects are also discussed.

cond-mat.mtrl-sci↗

arXiv2011

Existence of Steady Subsonic Euler Flows through Infinitely Long Periodic Nozzles

In this paper, we study the global existence of steady subsonic Euler flows through infinitely long nozzles which are periodic in $x_1$ direction with the period $L$. It is shown that when the variation of Bernoulli function at some given section is small and mass flux is in a suitable regime, there exists a unique global subsonic flow in the nozzle. Furthermore, the flow is also periodic in $x_1$ direction with the period $L$. If, in particular, the Bernoulli function is a constant, we also get the existence of subsonic-sonic flows when the mass flux takes the critical value.

math.AP↗

arXiv2011

Curvature Gradient Driving Droplets in Fast Motion

Earlier works found out spontaneous directional motion of liquid droplets on hydrophilic conical surfaces, however, not hydrophobic case. Here we show that droplets on any surface may take place spontaneous directional motion without considering contact angle property. The driving force is found to be proportional to the curvature gradient of the surface. Fast motion can be lead at surfaces with small curvature radii. The above discovery can help to create more effective transportation technology of droplets, and better understand some observed natural phenomena.

physics.chem-ph↗

arXiv2010

Surface Curvature-Induced Directional Movement of Water Droplets

Here we report a surface curvature-induced directional movement phenomenon, based on molecular dynamics simulations, that a nanoscale water droplet at the outer surface of a graphene cone always spontaneously moves toward the larger end of the cone, and at the inner surface toward the smaller end. The analysis on the van der Waals interaction potential between a single water molecule and a curved graphene surface reveals that the curvature with its gradient does generate the driving force resulting in the above directional motion. Furthermore, we found that the direction of the above movement is independent of the wettability, namely is regardless of either hydrophobic or hydrophilic of the surface. However, the latter surface is in general leading to higher motion speed than the former. The above results provide a basis for a better understanding of many reported observations, and helping design of curved surfaces with desired directional surface water transportation.

physics.class-ph↗

arXiv2010

Characterizing Internet Worm Infection Structure

Internet worm infection continues to be one of top security threats and has been widely used by botnets to recruit new bots. In this work, we attempt to quantify the infection ability of individual hosts and reveal the key characteristics of the underlying topology formed by worm infection, i.e., the number of children and the generation of the worm infection family tree. Specifically, we first apply probabilistic modeling methods and a sequential growth model to analyze the infection tree of a wide class of worms. We analytically and empirically find that the number of children has asymptotically a geometric distribution with parameter 0.5. As a result, on average half of infected hosts never compromise any vulnerable host, over 98% of infected hosts have no more than five children, and a small portion of infected hosts have a large number of children. We also discover that the generation follows closely a Poisson distribution and the average path length of the worm infection family tree increases approximately logarithmically with the total number of infected hosts. Next, we empirically study the infection structure of localized-scanning worms and surprisingly find that most of the above observations also apply to localized-scanning worms. Finally, we apply our findings to develop bot detection methods and study potential countermeasures for a botnet (e.g., Conficker C) that uses scan-based peer discovery to form a P2P-based botnet. Specifically, we demonstrate that targeted detection that focuses on the nodes with the largest number of children is an efficient way to expose bots. For example, our simulation shows that when 3.125% nodes are examined, targeted detection can reveal 22.36% bots. However, we also point out that future botnets may limit the maximum number of children to weaken targeted detection, without greatly slowing down the speed of worm infection.

cs.CR↗

arXiv2010

Darknet-Based Inference of Internet Worm Temporal Characteristics

Internet worm attacks pose a significant threat to network security and management. In this work, we coin the term Internet worm tomography as inferring the characteristics of Internet worms from the observations of Darknet or network telescopes that monitor a routable but unused IP address space. Under the framework of Internet worm tomography, we attempt to infer Internet worm temporal behaviors, i.e., the host infection time and the worm infection sequence, and thus pinpoint patient zero or initially infected hosts. Specifically, we introduce statistical estimation techniques and propose method of moments, maximum likelihood, and linear regression estimators. We show analytically and empirically that our proposed estimators can better infer worm temporal characteristics than a naive estimator that has been used in the previous work. We also demonstrate that our estimators can be applied to worms using different scanning strategies such as random scanning and localized scanning.

cs.CR↗

arXiv2010

Implementing and Evaluating a Wireless Body Sensor System for Automated Physiological Data Acquisition at Home

Advances in embedded devices and wireless sensor networks have resulted in new and inexpensive health care solutions. This paper describes the implementation and the evaluation of a wireless body sensor system that monitors human physiological data at home. Specifically, a waist-mounted triaxial accelerometer unit is used to record human movements. Sampled data are transmitted using an IEEE 802.15.4 wireless transceiver to a data logger unit. The wearable sensor unit is light, small, and consumes low energy, which allows for inexpensive and unobtrusive monitoring during normal daily activities at home. The acceleration measurement tests show that it is possible to classify different human motion through the acceleration reading. The 802.15.4 wireless signal quality is also tested in typical home scenarios. Measurement results show that even with interference from nearby IEEE 802.11 signals and microwave ovens, the data delivery performance is satisfactory and can be improved by selecting an appropriate channel. Moreover, we found that the wireless signal can be attenuated by housing materials, home appliances, and even plants. Therefore, the deployment of wireless body sensor systems at home needs to take all these factors into consideration.

cs.OH↗

arXiv2008

Measuring Traffic

A traffic performance measurement system, PeMS, currently functions as a statewide repository for traffic data gathered by thousands of automatic sensors. It has integrated data collection, processing and communications infrastructure with data storage and analytical tools. In this paper, we discuss statistical issues that have emerged as we attempt to process a data stream of 2 GB per day of wildly varying quality. In particular, we focus on detecting sensor malfunction, imputation of missing or bad data, estimation of velocity and forecasting of travel times on freeway networks.

stat.ME↗

arXiv2008

Quantifying Homology Classes

We develop a method for measuring homology classes. This involves three problems. First, we define the size of a homology class, using ideas from relative homology. Second, we define an optimal basis of a homology group to be the basis whose elements' size have the minimal sum. We provide a greedy algorithm to compute the optimal basis and measure classes in it. The algorithm runs in $O(β^4 n^3 \log^2 n)$ time, where $n$ is the size of the simplicial complex and $β$ is the Betti number of the homology group. Third, we discuss different ways of localizing homology classes and prove some hardness results.

cs.CG↗

arXiv2007

Quantifying Homology Classes II: Localization and Stability

In the companion paper, we measured homology classes and computed the optimal homology basis. This paper addresses two related problems, namely, localization and stability. We localize a class with the cycle minimizing a certain objective function. We explore three different objective functions, namely, volume, diameter and radius. We show that it is NP-hard to compute the smallest cycle using the former two. We also prove that the measurement defined in the companion paper is stable with regard to small changes of the geometry of the concerned space.

cs.CG↗