arXiv subjects

Xing Zhang

Publications and source records attributed to Xing Zhang.

At least 145 records · Page 8Linked to original sources

arXiv2019

An Improvement of PAA on Trend-Based Approximation for Time Series

Piecewise Aggregate Approximation (PAA) is a competitive basic dimension reduction method for high-dimensional time series mining. When deployed, however, the limitations are obvious that some important information will be missed, especially the trend. In this paper, we propose two new approaches for time series that utilize approximate trend feature information. Our first method is based on relative mean value of each segment to record the trend, which divide each segment into two parts and use the numerical average respectively to represent the trend. We proved that this method satisfies lower bound which guarantee no false dismissals. Our second method uses a binary string to record the trend which is also relative to mean in each segment. Our methods are applied on similarity measurement in classification and anomaly detection, the experimental results show the improvement of accuracy and effectiveness by extracting the trend feature suitably.

cs.LG↗

arXiv2019

Constraining the scalar-tensor gravity theories with and without screening mechanisms by combined observations

Screened modified gravity (SMG) and Brans-Dicke (BD) gravity are typical examples of scalar-tensor theories with and without screening mechanisms, which can suppress the scalar field in dense regions. In this paper, we investigate the tests of time-varying gravitational constant $G$, gravitational dipole radiation, and Nordtvedt effect in BD and SMG theories, respectively. We place new constraints on these theories by combining Cassini experiment, lunar laser ranging (LLR) measurements, and pulsar observations from PSRs J1738$+$0333 and J0348$+$0432. We find that screening mechanism has important influence on theoretical constraints. The strongest, second, and weakest constraints on BD are from Cassini, pulsar, and LLR tests, respectively. The most stringent constraint on SMG comes from LLR measurements and improves the previous best constraint by more than seven orders of magnitude. We derive the bounds on the cosmological evolution of the scalar background in these theories using the time variation of $G$. The results of all tests agree well with general relativity (GR) and give more stringent constraints on the deviations from GR. Finally, as an example, we consider the chameleon model and derive the constraints on the model parameters.

gr-qc↗

arXiv2019

Formulating Camera-Adaptive Color Constancy as a Few-shot Meta-Learning Problem

Digital camera pipelines employ color constancy methods to estimate an unknown scene illuminant, in order to re-illuminate images as if they were acquired under an achromatic light source. Fully-supervised learning approaches exhibit state-of-the-art estimation accuracy with camera-specific labelled training imagery. Resulting models typically suffer from domain gaps and fail to generalise across imaging devices. In this work, we propose a new approach that affords fast adaptation to previously unseen cameras, and robustness to changes in capture device by leveraging annotated samples across different cameras and datasets. We present a general approach that utilizes the concept of color temperature to frame color constancy as a set of distinct, homogeneous few-shot regression tasks, each associated with an intuitive physical meaning. We integrate this novel formulation within a meta-learning framework, enabling fast generalisation to previously unseen cameras using only handfuls of camera specific training samples. Consequently, the time spent for data collection and annotation substantially diminishes in practice whenever a new sensor is used. To quantify this gain, we evaluate our pipeline on three publicly available datasets comprising 12 different cameras and diverse scene content. Our approach delivers competitive results both qualitatively and quantitatively while requiring a small fraction of the camera-specific samples compared to standard approaches.

cs.CV↗

arXiv2019

Gravitational wave forms, polarizations, response functions and energy losses of triple systems in Einstein-Aether theory

Gravitationally bound hierarchies containing three or more components are very common in our Universe. In this paper we study {\em periodic} gravitational wave (GW) form, their polarizations, response function, its Fourier transform, and energy loss rate of a triple system through three different channels of radiation, the scalar, vector and tensor modes, in Einstein-aether theory of gravity. In the weak-field approximations and with the recently obtained constraints of the theory, we first analyze the energy loss rate of a binary system, and find that the dipole contributions from the scalar and vector modes could be of the order of ${\cal{O}}\left(c_{14}\right){\cal{O}}\left(G_Nm/d\right)^2$, where $c_{14} \; (\equiv c_{1} + c_{4})$ is constrained to $c_{14} \lesssim {\cal{O}}\left(10^{-5}\right)$ by current observations, where $c_i$'s are the four coupling constants of the theory. On the other hand, the "strong-field" effects for a binary system of neutron stars are about six orders lower than that of GR. So, in this paper we ignore these "strong-field" effects and first develop the general formulas to the lowest post-Newtonian order, by taking the coupling of the aether field with matter into account. Within this approximation, we find that the scalar breather mode and the scalar longitudinal mode are all suppressed by a factor of ${\cal{O}}\left(c_{14}\right)$ with respect to the transverse-traceless modes ($h_{+}$ and $h_{\times}$), while the vectorial modes $(h_{X}$ and $h_{Y}$) are suppressed by a factor of $c_{13} \lesssim {\cal{O}}\left(10^{-15}\right)$. Applying the general formulas to a triple system with periodic orbits, we find that the corresponding GW form, response function, and its Fourier transform depend sensitively on both the configuration of the triple system and their orientations with respect to the detectors.

astro-ph.GA↗

arXiv2018

Angular momentum loss for eccentric compact binary in screened modified gravity

Gravitational wave (GW) observations provide insight into the gravity regime. These observations relies on the comparison of the data to the GWs model, which depends on the orbital evolution of the binary systems. In this paper, we study the orbital evolution of eccentric compact binaries within screened modified gravity, which is a kind of scalar-tensor theory with screening mechanisms. According to the Noether's theorem, from the theory's GW action, we compute the angular momentum flux both as a function of the fields in the theory and as a function of the multipole moments of a N-body system. We specialize to the orbital parameters of eccentric compact binaries to express its orbital energy and angular momentum decay, and then derive the decay rates of its orbital eccentricity and semimajor axis. We find that these quantities decay faster than in General Relativity due to the presence of dipole radiation.

gr-qc↗

arXiv2018

Waveforms of compact binary inspiral gravitational radiation in screened modified gravity

Scalar-tensor gravity, with the screening mechanisms to avoid the severe constraints of the fifth force in the Solar System, can be described with a unified theoretical framework, the so-called screened modified gravity (SMG). Within this framework, in this paper we calculate the waveforms of gravitational-waves (GWs) emitted by inspiral compact binaries, which include four polarization modes, the plus $h_{+}$, cross $h_{\times}$, breathing $h_{b}$, and longitudinal $h_{L}$ modes. The scalar polarizations $h_b$ and $h_L$ are both caused by the scalar field of SMG, and satisfy a simple linear relation. With the stationary phase approximations, we obtain their Fourier transforms, and derive the correction terms in the amplitude, phase, and polarizations of GWs, relative to the corresponding results in general relativity. The corresponding parametrized post-Einsteinian parameters in the general SMG are also identified. Imposing the noise level of the ground-based Einstein Telescope, we find that GW detections from inspiral compact binaries composed of a neutron star and a black hole can place stringent constraints on the sensitivities of neutron stars, and the bound is applicable to any SMG theory. Finally, we apply these results to some specific theories of SMG, including chameleon, symmetron, dilaton and $f(R)$.

gr-qc↗

arXiv2018

Non-local NetVLAD Encoding for Video Classification

This paper describes our solution for the 2$^\text{nd}$ YouTube-8M video understanding challenge organized by Google AI. Unlike the video recognition benchmarks, such as Kinetics and Moments, the YouTube-8M challenge provides pre-extracted visual and audio features instead of raw videos. In this challenge, the submitted model is restricted to 1GB, which encourages participants focus on constructing one powerful single model rather than incorporating of the results from a bunch of models. Our system fuses six different sub-models into one single computational graph, which are categorized into three families. More specifically, the most effective family is the model with non-local operations following the NetVLAD encoding. The other two family models are Soft-BoF and GRU, respectively. In order to further boost single models performance, the model parameters of different checkpoints are averaged. Experimental results demonstrate that our proposed system can effectively perform the video classification task, achieving 0.88763 on the public test set and 0.88704 on the private set in terms of GAP@20, respectively. We finally ranked at the fourth place in the YouTube-8M video understanding challenge.

cs.CV↗

arXiv2018

Evidence of deviations from general relativity in binary pulsars?

Testing gravitational theories by binary pulsars nowadays becomes a key issue. For the general screened modified gravity (SMG), the post-Keplerian parameters in the neutron star (NS) - white dwarf (WD) binaries differ from those of general relativity (GR), and the differences are quantified by the scalar charge $ε_{\scriptscriptstyle\rm WD}$ of WD. After deriving the constraints on $ε_{\scriptscriptstyle\rm WD}$ from four different NS-WD binaries, we find that $ε_{\scriptscriptstyle\rm WD}$ is different from zero at the 2$σ$ level in all the cases studied, and there exists an inverse correlation between masses and scalar charges of low-mass WDs, which is consistent with the screening mechanisms. In particular, two independent binaries with measured radii of WDs follow the coincident constraints on the vacuum expectation value of the scalar field. These self-consistent results indicate that the observations in NS-WD binary pulsars seem in favor of SMG, rather than GR.

gr-qc↗

arXiv2017

Constraining f(R) gravity in solar system, cosmology and binary pulsar systems

The $f(R)$ gravity can be cast into the form of a scalar-tensor theory, and scalar degree of freedom can be suppressed in high-density regions by the chameleon mechanism. In this article, for the general $f(R)$ gravity, using a scalar-tensor representation with the chameleon mechanism, we calculate the parameterized post-Newtonian parameters $γ$ and $β$, the effective gravitational constant $G_{\rm eff}$, and the effective cosmological constant $Λ_{\rm eff}$. In addition, for the general $f(R)$ gravity, we also calculate the rate of orbital period decay of the binary system due to gravitational radiation. Then we apply these results to specific $f(R)$ models (Hu-Sawicki model, Tsujikawa model and Starobinsky model) and derive the constraints on the model parameters by combining the observations in solar system, cosmological scales and the binary systems.

astro-ph.CO↗

arXiv2017

Hybrid Fault diagnosis capability analysis of Hypercubes under the PMC model and MM* model

System level diagnosis is an important approach for the fault diagnosis of multiprocessor systems. In system level diagnosis, diagnosability is an important measure of the diagnosis capability of interconnection networks. But as a measure, diagnosability can not reflect the diagnosis capability of multiprocessor systems to link faults which may occur in real circumstances. In this paper, we propose the definition of $h$-edge tolerable diagnosability to better measure the diagnosis capability of interconnection networks under hybrid fault circumstances. The $h$-edge tolerable diagnosability of a multiprocessor system $G$ is the maximum number of faulty nodes that the system can guarantee to locate when the number of faulty edges does not exceed $h$,denoted by $t_h^{e}(G)$. The PMC model and MM model are the two most widely studied diagnosis models for the system level diagnosis of multiprocessor systems. The hypercubes are the most well-known interconnection networks. In this paper, the $h$-edge tolerable diagnosability of $n$-dimensional hypercube under the PMC model and MM$^{*}$ is determined as follows: $t_h^{e}(Q_n)= n-h$, where $1\leq h<n$, $n\geq3$.

cs.DC↗

arXiv2017

Testing Brans-Dicke gravity using the Einstein telescope

Gravitational radiation is an excellent field for testing theories of gravity in strong gravitational fields. The current observations on the gravitational-wave (GW) bursts by LIGO have already placed various constraints on the alternative theories of gravity. In this paper, we investigate the possible bounds which could be placed on the Brans-Dicke gravity using GW detection from inspiralling compact binaries with the proposed Einstein Telescope, a third-generation GW detector. We first calculate in details the waveforms of gravitational radiation in the lowest post-Newtonian approximation, including the tensor and scalar fields, which can be divided into the three polarization modes, i.e. "plus mode", "cross mode" and "breathing mode". Applying the stationary phase approximation, we obtain their Fourier transforms, and derive the correction terms in amplitude, phase and polarization of GWs, relative to the corresponding results in General Relativity. Imposing the noise level of Einstein Telescope, we find that the GW detection from inspiralling compact binaries, composed of a neutron star and a black hole, can place stringent constraints on the Brans-Dicke gravity. The bound on the coupling constant $ω_{\rm BD}$ depends on the mass, sky-position, orbital angle, polarization angle, luminosity distance, redshift distribution and total observed number $N_{\rm GW}$ of the binary systems. Taking into account all the burst events up to redshift $z=5$, we find that the bound could be $ω_{\rm BD}\gtrsim 10^{6}\times(N_{\rm GW}/10^4)^{1/2}$. Even for the conservative estimation with $10^{4}$ observed events, the bound is still more than one order tighter than the current limit from Solar System experiments. So, we conclude that Einstein Telescope will provide a powerful platform to test alternative theories of gravity.

gr-qc↗

arXiv2017

Gravitational radiation from compact binary systems in screened modified gravity

Screened modified gravity (SMG) is a kind of scalar-tensor theory with screening mechanisms, which can suppress the fifth force in dense regions and allow theories to evade the solar system and laboratory tests. In this paper, we investigate how the screening mechanisms in SMG affect the gravitational radiation damping effects, calculate in detail the rate of the energy loss due to the emission of tensor and scalar gravitational radiations, and derive their contributions to the change in the orbital period of the binary system. We find that the scalar radiation depends on the screened parameters and the propagation speed of scalar waves, and the scalar dipole radiation dominates the orbital decay of the binary system. For strongly self-gravitating bodies, all effects of scalar sector are strongly suppressed by the screening mechanisms in SMG. By comparing our results to observations of binary system PSR J1738+0333, we place the stringent constraints on the screening mechanisms in SMG. As an application of these results, we focus on three specific models of SMG (chameleon, symmetron, and dilaton), and derive the constraints on the model parameters, respectively.

gr-qc↗

arXiv2017

A Survey on Mobile Edge Networks: Convergence of Computing, Caching and Communications

As the explosive growth of smart devices and the advent of many new applications, traffic volume has been growing exponentially. The traditional centralized network architecture cannot accommodate such user demands due to heavy burden on the backhaul links and long latency. Therefore, new architectures which bring network functions and contents to the network edge are proposed, i.e., mobile edge computing and caching. Mobile edge networks provide cloud computing and caching capabilities at the edge of cellular networks. In this survey, we make an exhaustive review on the state-of-the-art research efforts on mobile edge networks. We first give an overview of mobile edge networks including definition, architecture and advantages. Next, a comprehensive survey of issues on computing, caching and communication techniques at the network edge is presented respectively. The applications and use cases of mobile edge networks are discussed. Subsequently, the key enablers of mobile edge networks such as cloud technology, SDN/NFV and smart devices are discussed. Finally, open research challenges and future directions are presented as well.

cs.NI↗

arXiv2017

Distributed Edge Caching Scheme Considering the Tradeoff Between the Diversity and Redundancy of Cached Content

Caching popular contents at the edge of cellular networks has been proposed to reduce the load, and hence the cost of backhaul links. It is significant to decide which files should be cached and where to cache them. In this paper, we propose a distributed caching scheme considering the tradeoff between the diversity and redundancy of base stations' cached contents. Whether it is better to cache the same or different contents in different base stations? To find out this, we formulate an optimal redundancy caching problem. Our goal is to minimize the total transmission cost of the network, including cost within the radio access network (RAN) and cost incurred by transmission to the core network via backhaul links. The optimal redundancy ratio under given system configuration is obtained with adapted particle swarm optimization (PSO) algorithm. We analyze the impact of important system parameters through Monte-Carlo simulation. Results show that the optimal redundancy ratio is mainly influenced by two parameters, which are the backhaul to RAN unit cost ratio and the steepness of file popularity distribution. The total cost can be reduced by up to 54% at given unit cost ratio of backhaul to RAN when the optimal redundancy ratio is selected. Under typical file request pattern, the reduction amount can be up to 57%.

cs.NI↗

arXiv2017

An Approach for Spatial-temporal Traffic Modeling in Mobile Cellular Networks

The volume and types of traffic data in mobile cellular networks have been increasing continuously. Meanwhile, traffic data change dynamically in several dimensions such as time and space. Thus, traffic modeling is essential for theoretical analysis and energy efficient design of future ultra-dense cellular networks. In this paper, the authors try to build a tractable and accurate model to describe the traffic variation pattern for a single base station in real cellular networks. Firstly a sinusoid superposition model is proposed for describing the temporal traffic variation of multiple base stations based on real data in a current cellular network. It shows that the mean traffic volume of many base stations in an area changes periodically and has three main frequency components. Then, lognormal distribution is verified for spatial modeling of real traffic data. The spatial traffic distributions at both spare time and busy time are analyzed. Moreover, the parameters of the model are presented in three typical regions: park, campus and central business district. Finally, an approach for combined spatial-temporal traffic modeling of single base station is proposed based on the temporal and spatial traffic distribution of multiple base stations. All the three models are evaluated through comparison with real data in current cellular networks. The results show that these models can accurately describe the variation pattern of real traffic data in cellular networks.

cs.NI↗

arXiv2016

The unexpected thermal conductivity from graphene disk, carbon nanocone to carbon nanotube

Graphene and single-wall carbon nanotube (SWCNT) have attracted great attention because of their ultra-high thermal conductivity. However, there are few works exploring the relations of their thermal conductivity quantitatively. The carbon nanocone (CNC) is a graded structure fall in between graphene disk (GD) and SWCNT. We perform non-equilibrium molecular dynamics (NEMD) simulation to study the thermal conductivity of CNC with different apex angles, and then compare them with that of GD and SWCNT. Our results show that, different from the homogeneous thermal conductivity in SWCNT, the CNC also has a natural graded thermal conductivity which is similar to the GD. Unexpectedly, the graded rate keeps almost the same when the apex angle decreases from 180° (GD) to 19°, but then suddenly declines to zero when the apex angle decreases from 19° to 0° (SWCNT). What is more interesting, the graded effect is not diminished when the interatomic force constant is weakened and mean free path is shorten. That is, besides nanoscale, the graded effect can be observed in macroscale graphene or CNC structures.

cond-mat.mes-hall↗

arXiv2016

Extracting Actionability from Machine Learning Models by Sub-optimal Deterministic Planning

A main focus of machine learning research has been improving the generalization accuracy and efficiency of prediction models. Many models such as SVM, random forest, and deep neural nets have been proposed and achieved great success. However, what emerges as missing in many applications is actionability, i.e., the ability to turn prediction results into actions. For example, in applications such as customer relationship management, clinical prediction, and advertisement, the users need not only accurate prediction, but also actionable instructions which can transfer an input to a desirable goal (e.g., higher profit repays, lower morbidity rates, higher ads hit rates). Existing effort in deriving such actionable knowledge is few and limited to simple action models which restricted to only change one attribute for each action. The dilemma is that in many real applications those action models are often more complex and harder to extract an optimal solution. In this paper, we propose a novel approach that achieves actionability by combining learning with planning, two core areas of AI. In particular, we propose a framework to extract actionable knowledge from random forest, one of the most widely used and best off-the-shelf classifiers. We formulate the actionability problem to a sub-optimal action planning (SOAP) problem, which is to find a plan to alter certain features of a given input so that the random forest would yield a desirable output, while minimizing the total costs of actions. Technically, the SOAP problem is formulated in the SAS+ planning formalism, and solved using a Max-SAT based approach. Our experimental results demonstrate the effectiveness and efficiency of the proposed approach on a personal credit dataset and other benchmarks. Our work represents a new application of automated planning on an emerging and challenging machine learning paradigm.

cs.AI↗

arXiv2016

Social Computing for Mobile Big Data in Wireless Networks

Mobile big data contains vast statistical features in various dimensions, including spatial, temporal, and the underlying social domain. Understanding and exploiting the features of mobile data from a social network perspective will be extremely beneficial to wireless networks, from planning, operation, and maintenance to optimization and marketing. In this paper, we categorize and analyze the big data collected from real wireless cellular networks. Then, we study the social characteristics of mobile big data and highlight several research directions for mobile big data in the social computing areas.

cs.SI↗