arXiv subjects

Jun Li

Publications and source records attributed to Jun Li.

At least 829 records · Page 46Linked to original sources

arXiv2018

The Reincarnation of Grille Cipher: A Generative Approach

In order to keep the data secret, various techniques have been implemented to encrypt and decrypt the secret data. Cryptography is committed to the security of content, i.e. it cannot be restored with a given ciphertext. Steganography is to hiding the existence of a communication channel within a stego. However, it has been difficult to construct a cipher (cypher) that simultaneously satisfy both channel and content security for secure communication. Inspired by the Cardan grille, this paper presents a new generative framework for grille cipher. A digital cardan grille is used for message encryption and decryption. The ciphertext is directly sampled by a powerful generator without an explicit cover. Message loss and prior loss are proposed for penalizing message extraction error and unrealistic ciphertext. Jensen-Shannon Divergence is introduced as new criteria for channel security. A simple practical data-driven grille cipher is proposed using semantic image inpainting and generative adversarial network. Experimental results demonstrate the promising of the proposed method.

cs.CR↗

arXiv2018

TiEV: The Tongji Intelligent Electric Vehicle in the Intelligent Vehicle Future Challenge of China

TiEV is an autonomous driving platform implemented by Tongji University of China. The vehicle is drive-by-wire and is fully powered by electricity. We devised the software system of TiEV from scratch, which is capable of driving the vehicle autonomously in urban paths as well as on fast express roads. We describe our whole system, especially novel modules of probabilistic perception fusion, incremental mapping, the 1st and the 2nd planning and the overall safety concern. TiEV finished 2016 and 2017 Intelligent Vehicle Future Challenge of China held at Changshu. We show our experiences on the development of autonomous vehicles and future trends.

cs.RO↗

arXiv2018

Energy-Efficient Wireless Powered Secure Transmission with Cooperative Jamming for Public Transportation

In this paper, wireless power transfer and cooperative jamming (CJ) are combined to enhance physical security in public transportation networks. First, a new secure system model with both fixed and mobile jammers is proposed to guarantee secrecy in the worst-case scenario. All jammers are endowed with energy harvesting (EH) capability. Following this, two CJ based schemes, namely B-CJ-SRM and B-CJ-TPM, are proposed, where SRM and TPM are short for secrecy rate maximization and transmit power minimization, respectively. They respectively maximize the secrecy rate (SR) with transmit power constraint and minimize the transmit power of the BS with SR constraint, by optimizing beamforming vector and artificial noise covariance matrix. To further reduce the complexity of our proposed optimal schemes, their low-complexity (LC) versions, called LC-B-CJ-SRM and LC-B-CJ-TPM are developed. Simulation results show that our proposed schemes, B-CJ-SRM and B-CJ-TPM, achieve significant SR performance improvement over existing zero-forcing and QoSD methods. Additionally, the SR performance of the proposed LC schemes are close to those of their original versions.

cs.CR↗

arXiv2018

Electronic phase separation in iron selenide (Li, Fe)OHFeSe superconductor system

The phenomenon of phase separation into antiferromagnetic (AFM) and superconducting (SC) or normal-state regions has great implication for the origin of high-temperature (high-Tc) superconductivity. However, the occurrence of an intrinsic antiferromagnetism above the Tc of (Li, Fe)OHFeSe superconductor is questioned. Here we report a systematic study on a series of (Li, Fe)OHFeSe single crystal samples with Tc up to ~41 K. We observe an evident drop in the static magnetization at Tafm ~125 K, in some of the SC (Tc < ~38 K, cell parameter c < ~9.27 Å) and non-SC samples. We verify that this AFM signal is intrinsic to (Li, Fe)OHFeSe. Thus, our observations indicate mesoscopic-to-macroscopic coexistence of an AFM state with the normal (below Tafm) or SC (below Tc) state in (Li, Fe)OHFeSe. We explain such coexistence by electronic phase separation, similar to that in high-Tc cuprates and iron arsenides. However, such an AFM signal can be absent in some other samples of (Li, Fe)OHFeSe, particularly it is never observed in the SC samples of Tc > ~38 K, owing to a spatial scale of the phase separation too small for the macroscopic magnetic probe. For this case, we propose a microscopic electronic phase separation. It is suggested that the microscopic static phase separation reaches vanishing point in high-Tc (Li, Fe)OHFeSe, by the occurrence of two-dimensional AFM spin fluctuations below nearly the same temperature as Tafm reported previously for a (Li, Fe)OHFeSe (Tc ~42 K) single crystal. A complete phase diagram is thus established. Our study provides key information of the underlying physics for high-Tc superconductivity.

cond-mat.supr-con↗

arXiv2018

VeriTable: Fast Equivalence Verification of Multiple Large Forwarding Tables

Due to network practices such as traffic engineering and multi-homing, the number of routes---also known as IP prefixes---in the global forwarding tables has been increasing significantly in the last decade and continues growing in a super linear trend. One of the most promising solutions is to use smart Forwarding Information Base (FIB) aggregation algorithms to aggregate the prefixes and convert a large table into a small one. Doing so poses a research question, however, i.e., how can we quickly verify that the original table yields the same forwarding behaviors as the aggregated one? We answer this question in this paper, including addressing the challenges caused by the longest prefix matching (LPM) lookups. In particular, we propose the VeriTable algorithm that can employ a single tree/trie traversal to quickly check if multiple forwarding tables are forwarding equivalent, as well as if they could result in routing loops or black holes. The VeriTable algorithm significantly outperforms the state-of-the-art work for both IPv4 and IPv6 tables in every aspect, including the total running time, memory access times and memory consumption.

cs.NI↗

arXiv2018

Im2Struct: Recovering 3D Shape Structure from a Single RGB Image

We propose to recover 3D shape structures from single RGB images, where structure refers to shape parts represented by cuboids and part relations encompassing connectivity and symmetry. Given a single 2D image with an object depicted, our goal is automatically recover a cuboid structure of the object parts as well as their mutual relations. We develop a convolutional-recursive auto-encoder comprised of structure parsing of a 2D image followed by structure recovering of a cuboid hierarchy. The encoder is achieved by a multi-scale convolutional network trained with the task of shape contour estimation, thereby learning to discern object structures in various forms and scales. The decoder fuses the features of the structure parsing network and the original image, and recursively decodes a hierarchy of cuboids. Since the decoder network is learned to recover part relations including connectivity and symmetry explicitly, the plausibility and generality of part structure recovery can be ensured. The two networks are jointly trained using the training data of contour-mask and cuboid structure pairs. Such pairs are generated by rendering stock 3D CAD models coming with part segmentation. Our method achieves unprecedentedly faithful and detailed recovery of diverse 3D part structures from single-view 2D images. We demonstrate two applications of our method including structure-guided completion of 3D volumes reconstructed from single-view images and structure-aware interactive editing of 2D images.

cs.CV↗

arXiv2018

Tighter monogamy relations in multipartite systems

Monogamy relations characterize the distributions of entanglement in multipartite systems. We investigate monogamy relations related to the concurrence C, the entanglement of formation E, negativity Nc and Tsallis-q entanglement Tq. Monogamy relations for the $α$th power of entanglement have been derived, which are tighter than the existing entanglement monogamy relations for some classes of quantum states. Detailed examples are presented.

quant-ph↗

arXiv2018

Secure SWIPT for Directional Modulation Aided AF Relaying Networks

Secure wireless information and power transfer based on directional modulation is conceived for amplify-and-forward (AF) relaying networks. Explicitly, we first formulate a secrecy rate maximization (SRM) problem, which can be decomposed into a twin-level optimization problem and solved by a one-dimensional (1D) search and semidefinite relaxation (SDR) technique. Then in order to reduce the search complexity, we formulate an optimization problem based on maximizing the signal-to-leakage-AN-noise-ratio (Max-SLANR) criterion, and transform it into a SDR problem. Additionally, the relaxation is proved to be tight according to the classic Karush-Kuhn-Tucker (KKT) conditions. Finally, to reduce the computational complexity, a successive convex approximation (SCA) scheme is proposed to find a near-optimal solution. The complexity of the SCA scheme is much lower than that of the SRM and the Max-SLANR schemes. Simulation results demonstrate that the performance of the SCA scheme is very close to that of the SRM scheme in terms of its secrecy rate and bit error rate (BER), but much better than that of the zero forcing (ZF) scheme.

cs.IT↗

arXiv2018

Convergence Analysis and Design of Multi-block ADMM via Switched Control Theory

We consider three challenges in multi-block Alternating Direction Method of Multipliers (ADMM): building convergence conditions for ADMM with any block (variable) sequence, finding available block sequences to be fit for ADMM, and designing useful parameter controllers for ADMM with unfixed parameters. To address these challenges, we develop a switched control framework for studying multi-block ADMM. First, since ADMM recursively and alternately updates the block-variables, it is converted into a discrete-time switched dynamical system. Second, we study exponential stability and stabilizability of the switched system for linear convergence analysis and design of ADMM by employing switched Lyapunov functions. Moreover, linear matrix inequalities conditions are proposed to ensure convergence of ADMM under arbitrary sequence, to find convergent sequences, and to design the fixed parameters. These conditions are checked and solved by employing semidefinite programming. Numerical experiments further verify the effectiveness of our proposed theories.

eess.SY↗

arXiv2018

Geometrical pluripotential theory on Sasaki manifolds

We extend profound results in pluripotential theory on Kahler manifolds to Sasaki setting via its transverse Kahler structure. As in Kahler case, these results form a very important piece to solve the existence of Sasaki metrics with constant scalar curvature (cscs) in terms of properness of K-energy. One main result is to generalize T. Darvas' theory on the geometric structure of the space of Kahler potentials in Sasaki setting. Along the way we extend most of corresponding results in pluripotential theory to Sasaki setting via its transverse Kahler structure.

math.DG↗

arXiv2018

Uncertainty relation based on Wigner-Yanase-Dyson skew information with quantum memory

We present uncertainty relations based on Wigner--Yanase--Dyson skew information with quantum memory. Uncertainty inequalities both in product and summation forms are derived. \mbox{It is} shown that the lower bounds contain two terms: one characterizes the degree of compatibility of two measurements, and the other is the quantum correlation between the measured system and the quantum memory. Detailed examples are given for product, separable and entangled states.

quant-ph↗

arXiv2018

Elliptical vortex and oblique vortex lattice in the FeSe superconductor based on the nematicity and mixed superconducting orders

The electronic nematic phase is characterized as an ordered state of matter with rotational symmetry breaking, and has been well studied in the quantum Hall system and the high-$T_c$ superconductors, regardless of cuprate or pnictide family. The nematic state in high-$T_c$ systems often relates to the structural transition or electronic instability in the normal phase. Nevertheless, the electronic states below the superconducting transition temperature is still an open question. With high-resolution scanning tunneling microscope measurements, direct observation of vortex core in FeSe thin films revealed the nematic superconducting state by Song \emph{et al}. Here, motivated by the experiment, we construct the extended Ginzburg-Landau free energy to describe the elliptical vortex, where a mixed \emph{s}-wave and \emph{d}-wave superconducting order is coupled to the nematic order. The nematic order induces the mixture of two superconducting orders and enhances the anisotropic interaction between the two superconducting orders, resulting in a symmetry breaking from $C_4$ to $C_2$. Consequently, the vortex cores are stretched into an elliptical shape. In the equilibrium state, the elliptical vortices assemble a lozenge-like vortex lattice, being well consistent with experimental results.

cond-mat.supr-con↗

arXiv2018

Adversarial Metric Learning

In the past decades, intensive efforts have been put to design various loss functions and metric forms for metric learning problem. These improvements have shown promising results when the test data is similar to the training data. However, the trained models often fail to produce reliable distances on the ambiguous test pairs due to the distribution bias between training set and test set. To address this problem, the Adversarial Metric Learning (AML) is proposed in this paper, which automatically generates adversarial pairs to remedy the distribution bias and facilitate robust metric learning. Specifically, AML consists of two adversarial stages, i.e. confusion and distinguishment. In confusion stage, the ambiguous but critical adversarial data pairs are adaptively generated to mislead the learned metric. In distinguishment stage, a metric is exhaustively learned to try its best to distinguish both the adversarial pairs and the original training pairs. Thanks to the challenges posed by the confusion stage in such competing process, the AML model is able to grasp plentiful difficult knowledge that has not been contained by the original training pairs, so the discriminability of AML can be significantly improved. The entire model is formulated into optimization framework, of which the global convergence is theoretically proved. The experimental results on toy data and practical datasets clearly demonstrate the superiority of AML to the representative state-of-the-art metric learning methodologies.

cs.LG↗

arXiv2018

Power Allocation Strategy of Maximizing Secrecy Rate for Secure Directional Modulation Networks

In this paper, given the beamforming vector of confidential messages and artificial noise (AN) projection matrix and total power constraint, a power allocation (PA) strategy of maximizing secrecy rate (Max-SR) is proposed for secure directional modulation (DM) networks. By the method of Lagrange multiplier, the analytic expression of the proposed PA strategy is derived. To confirm the benefit from the Max-SR-based PA strategy, we take the null-space projection (NSP) beamforming scheme as an example and derive its closed-form expression of optimal PA strategy. From simulation results, we find the following facts: in the medium and high signal-to-noise-ratio (SNR) regions, compared with three typical PA parameters such $β=0.1, 0.5$, and $0.9$, the optimal PA shows a substantial SR performance gain with maximum gain percent up to more than $60\%$. Additionally, as the PA factor increases from 0 to 1, the achievable SR increases accordingly in the low SNR region whereas it first increases and then decreases in the medium and high SNR regions, where the SR can be approximately viewed as a convex function of the PA factor. Finally, as the number of antennas increases, the optimal PA factor becomes large and tends to one in the medium and high SNR region. In other words, the contribution of AN to SR can be trivial in such a situation.

cs.IT↗

arXiv2018

A Neighborhood-Assisted Hotelling's $T^2$ Test for High-Dimensional Means

Many tests have been proposed to remedy the classical Hotelling's $T^2$ test in the "large $p$, small $n$" paradigm, but the existence of an optimal sum-of-squares type test has not been explored. This paper shows that under certain conditions, the population Hotelling's $T^2$ test with the known $Σ^{-1}$ attains the best power among all the $L_2$-norm based tests with the data transformation by $Σ^η$ for $η\in (-\infty, \infty)$. To extend the result to the case of unknown $Σ^{-1}$, we propose a Neighborhood-Assisted Hotelling's $T^2$ statistic obtained by replacing the inverse of sample covariance matrix in the classical Hotelling's $T^2$ statistic with a regularized covariance estimator. Utilizing a regression model, we establish its asymptotic normality under mild conditions. We show that the proposed test is able to match the performance of the population Hotelling's $T^2$ test under certain conditions, and thus possesses certain optimality. Moreover, it can adaptively attain the best power by empirically choosing a neighborhood size to maximize its signal-to-noise ratio. Simulation experiments and case studies are given to demonstrate the empirical performance of the proposed test.

stat.ME↗

arXiv2018

Secure Directional Modulation to Enhance Physical Layer Security in IoT Networks

In this work, an adaptive and robust null-space projection (AR-NSP) scheme is proposed for secure transmission with artificial noise (AN)-aided directional modulation (DM) in wireless networks. The proposed scheme is carried out in three steps. Firstly, the directions of arrival (DOAs) of the signals from the desired user and eavesdropper are estimated by the Root Multiple Signal Classificaiton (Root-MUSIC) algorithm and the related signal-to-noise ratios (SNRs) are estimated based on the ratio of the corresponding eigenvalue to the minimum eigenvalue of the covariance matrix of the received signals. In the second step, the value intervals of DOA estimation errors are predicted based on the DOA and SNR estimations. Finally, a robust NSP beamforming DM system is designed according to the afore-obtained estimations and predictions. Our examination shows that the proposed scheme can significantly outperform the conventional non-adaptive robust scheme and non-robust NSP scheme in terms of achieving a much lower bit error rate (BER) at the desired user and a much higher secrecy rate (SR). In addition, the BER and SR performance gains achieved by the proposed scheme relative to other schemes increase with the value range of DOA estimation error.

cs.IT↗

arXiv2018

Magnitude of the Current in Two-Dimensional Interlayer Tunneling Devices

Using the Bardeen tunneling method with first-principles wave functions, computations are made of the tunneling current in graphene / hexagonal-boron-nitride / graphene (G/h-BN/G) vertical structures. Detailed comparison with prior experimental results is made, focusing on the magnitude of the achievable tunnel current. With inclusion of the effects of translational and rotational misalignment of the graphene and the h-BN, predicted currents are found to be about 15x larger than experimental values. A reduction in this discrepancy, to a factor of 2.5x, is achieved by utilizing a realistic size for the band gap of the h-BN, hence affecting the exponential decay constant for the tunneling.

cond-mat.mes-hall↗

arXiv2018

Quantum Image Processing and Its Application to Edge Detection: Theory and Experiment

Processing of digital images is continuously gaining in volume and relevance, with concomitant demands on data storage, transmission and processing power. Encoding the image information in quantum-mechanical systems instead of classical ones and replacing classical with quantum information processing may alleviate some of these challenges. By encoding and processing the image information in quantum-mechanical systems, we here demonstrate the framework of quantum image processing, where a pure quantum state encodes the image information: we encode the pixel values in the probability amplitudes and the pixel positions in the computational basis states. Our quantum image representation reduces the required number of qubits compared to existing implementations, and we present image processing algorithms that provide exponential speed-up over their classical counterparts. For the commonly used task of detecting the edge of an image, we propose and implement a quantum algorithm that completes the task with only one single-qubit operation, independent of the size of the image. This demonstrates the potential of quantum image processing for highly efficient image and video processing in the big data era.

quant-ph↗