arXiv subjects

Yu Zhang

Publications and source records attributed to Yu Zhang.

At least 1,603 records · Page 89Linked to original sources

arXiv2016

Grant-free Rateless Multiple Access: A Novel Massive Access Scheme for Internet of Things

Rateless Multiple Access (RMA) is a novel non-orthogonal multiple access framework that is promising for massive access in Internet of Things (IoT) due to its high efficiency and low complexity. In the framework, after certain \emph{registration}, each active user respectively transmits to the access point (AP) randomly based on an assigned random access control function (RACf) until receiving an acknowledgement (ACK). In this work, by exploiting the intrinsic access pattern of each user, we propose a grant-free RMA scheme, which no longer needs the registration process as in the original RMA, thus greatly reduces the signalling overhead and system latency. Furthermore, we propose a low-complexity joint iterative detection and decoding algorithm in which the channel estimation, active user detection, and information decoding are done simultaneously. Finally, we propose a method based on density evolution (DE) to evaluate the system performance.

cs.IT↗

arXiv2016

Proactive Decision Support using Automated Planning

Proactive decision support (PDS) helps in improving the decision making experience of human decision makers in human-in-the-loop planning environments. Here both the quality of the decisions and the ease of making them are enhanced. In this regard, we propose a PDS framework, named RADAR, based on the research in Automated Planning in AI, that aids the human decision maker with her plan to achieve her goals by providing alerts on: whether such a plan can succeed at all, whether there exist any resource constraints that may foil her plan, etc. This is achieved by generating and analyzing the landmarks that must be accomplished by any successful plan on the way to achieving the goals. Note that, this approach also supports naturalistic decision making which is being acknowledged as a necessary element in proactive decision support, since it only aids the human decision maker through suggestions and alerts rather than enforcing fixed plans or decisions. We demonstrate the utility of the proposed framework through search-and-rescue examples in a fire-fighting domain.

cs.HC↗

arXiv2016

Exploit Bounding Box Annotations for Multi-label Object Recognition

Convolutional neural networks (CNNs) have shown great performance as general feature representations for object recognition applications. However, for multi-label images that contain multiple objects from different categories, scales and locations, global CNN features are not optimal. In this paper, we incorporate local information to enhance the feature discriminative power. In particular, we first extract object proposals from each image. With each image treated as a bag and object proposals extracted from it treated as instances, we transform the multi-label recognition problem into a multi-class multi-instance learning problem. Then, in addition to extracting the typical CNN feature representation from each proposal, we propose to make use of ground-truth bounding box annotations (strong labels) to add another level of local information by using nearest-neighbor relationships of local regions to form a multi-view pipeline. The proposed multi-view multi-instance framework utilizes both weak and strong labels effectively, and more importantly it has the generalization ability to even boost the performance of unseen categories by partial strong labels from other categories. Our framework is extensively compared with state-of-the-art hand-crafted feature based methods and CNN based methods on two multi-label benchmark datasets. The experimental results validate the discriminative power and the generalization ability of the proposed framework. With strong labels, our framework is able to achieve state-of-the-art results in both datasets.

cs.CV↗

arXiv2016

Limit theorems for maximum flows on a lattice

We independently assign a non-negative value, as a capacity for the quantity of flows per unit time, with a distribution F to each edge on the Z^d lattice. We consider the maximum flows through the edges of two disjoint sets, that is from a source to a sink, in a large cube. In this paper, we show that the ratio of the maximum flow and the size of source is asymptotic to a constant. This constant is denoted by the flow constant.

math.PR↗

arXiv2016

An Overview of Transmission Theory and Techniques of Large-scale Antenna Systems for 5G Wireless Communications

To meet the future demand for huge traffic volume of wireless data service, the research on the fifth generation (5G) mobile communication systems has been undertaken in recent years. It is expected that the spectral and energy efficiencies in 5G mobile communication systems should be ten-fold higher than the ones in the fourth generation (4G) mobile communication systems. Therefore, it is important to further exploit the potential of spatial multiplexing of multiple antennas. In the last twenty years, multiple-input multiple-output (MIMO) antenna techniques have been considered as the key techniques to increase the capacity of wireless communication systems. When a large-scale antenna array (which is also called massive MIMO) is equipped in a base-station, or a large number of distributed antennas (which is also called large-scale distributed MIMO) are deployed, the spectral and energy efficiencies can be further improved by using spatial domain multiple access. This paper provides an overview of massive MIMO and large-scale distributed MIMO systems, including spectral efficiency analysis, channel state information (CSI) acquisition, wireless transmission technology, and resource allocation.

cs.IT↗

arXiv2016

Slow Auger Recombination of Charged Excitons in Nonblinking Perovskite Nanocrystals without Spectral Diffusion

Over the last two decades, intensive research efforts have been devoted to the suppressions of photoluminescence (PL) blinking and Auger recombination in metal-chalcogenide nanocrystals (NCs), with significant progresses being made only very recently in several specific heterostructures. Here we show that nonblinking PL is readily available in the newly-synthesized perovskite CsPbI3 (cesium lead iodide) NCs, and their Auger recombination of charged excitons is greatly slowed down, as signified by a PL lifetime about twice shorter than that of neutral excitons. Moreover, spectral diffusion is completely absent in single CsPbI3 NCs at the cryogenic temperature, leading to a resolution-limited PL linewidth of ~200 μeV.

cond-mat.mtrl-sci↗

arXiv2016

Electroweak radiative corrections to triple photon production at the ILC

In this paper, we present the precision predictions for three photon production in the standard model (SM) at the ILC including the full next-to-leading (NLO) electroweak (EW) corrections, high order initial state radiation (h.o.ISR) contributions and beamstrahlung effects. We present the LO and the NLO EW+h.o.ISR+beamstrahlung corrected total cross sections for various colliding energy when $\sqrt s \ge 200 {\rm GeV}$ and the kinematic distributions of final photons with $\sqrt s = 500 {\rm GeV}$ at ILC, and find that the NLO EW corrections, the h.o.ISR contributions and the beamstrahlung effects are important in exploring the process $e^+e^- \to γγγ$.

hep-ph↗

arXiv2016

Frequency-Domain Response Based Timing Synchronization: A Near Optimal Sampling Phase Criterion for TDS-OFDM

In time-domain synchronous OFDM (TDS-OFDM) system for digital television terrestrial multimedia broadcasting (DTMB) standard, the baseband OFDM signal is upsampled and shaping filtered by square root raised cosine (SRRC) filter before digital-to-analog converter (DAC). Much of the work in the area of timing synchronization for TDS-OFDM focuses on frame synchronization and sampling clock frequency offset recovery, which does not consider the sampling clock phase offset due to the upsampling and SRRC filter. This paper evaluates the bit-error-rate (BER) effect of sampling clock phase offset in TDS-OFDM system. First, we provide the BER for M-order quadrature amplitude modulation (M-QAM) in uncoded TDS-OFDM system. Second, under the condition of the optimal BER criterion and additive white Gaussian noise (AWGN) channel, we propose a near optimal sampling phase estimation criterion based on frequency-domain response. Simulations demonstrate that the proposed criterion also has good performance in actual TDS-OFDM system with channel coding over multipath channels, and it is superior to the conventional symbol timing recovery methods for TDS-OFDM system.

cs.IT↗

arXiv2016

Direct experimental evidence of pi magnetism of a single atomic vacancy in graphene

The pristine graphene is strongly diamagnetic. However, graphene with single carbon atom defects could exhibit paramagnetism with local magnetic moments ~ 1.5 per vacancy1-6. Theoretically, both the electrons and electrons of graphene contribute to the magnetic moment of the defects, and the pi magnetism is characterizing of two spin-split DOS (density-of-states) peaks close to the Dirac point1,6. Since its prediction, many experiments attempt to study this pi magnetism in graphene, whereas, only a notable resonance peak has been observed around the atomic defects6-9, leaving the pi magnetism experimentally so elusive. Here, we report direct experimental evidence of the pi magnetism by using scanning tunnelling microscope. We demonstrate that the localized state of the atomic defects is split into two DOS peaks with energy separations of several tens meV and the two spin-polarized states degenerate into a profound peak at positions with distance of ~ 1 nm away from the monovacancy. Strong magnetic fields further increase the energy separations of the two spin-polarized peaks and lead to a Zeeman-like splitting. The effective g-factors geff around the atomic defect is measured to be about 40. Such a giant enhancement of the g-factor is attributed to the strong spin polarization of electron density and large electron-electron interactions near the atomic vacancy.

cond-mat.mtrl-sci↗

arXiv2016

Plan Explicability and Predictability for Robot Task Planning

Intelligent robots and machines are becoming pervasive in human populated environments. A desirable capability of these agents is to respond to goal-oriented commands by autonomously constructing task plans. However, such autonomy can add significant cognitive load and potentially introduce safety risks to humans when agents behave unexpectedly. Hence, for such agents to be helpful, one important requirement is for them to synthesize plans that can be easily understood by humans. While there exists previous work that studied socially acceptable robots that interact with humans in "natural ways", and work that investigated legible motion planning, there lacks a general solution for high level task planning. To address this issue, we introduce the notions of plan {\it explicability} and {\it predictability}. To compute these measures, first, we postulate that humans understand agent plans by associating abstract tasks with agent actions, which can be considered as a labeling process. We learn the labeling scheme of humans for agent plans from training examples using conditional random fields (CRFs). Then, we use the learned model to label a new plan to compute its explicability and predictability. These measures can be used by agents to proactively choose or directly synthesize plans that are more explicable and predictable to humans. We provide evaluations on a synthetic domain and with human subjects using physical robots to show the effectiveness of our approach

cs.AI↗

arXiv2016

Sensitivity study of (10,100) GeV gamma-ray bursts with double shower front events from ARGO-YBJ

ARGO-YBJ, located at the YangBaJing Cosmic Ray Observatory (4300 m a.s.l., Tibet, China), is a full coverage air shower array, with an energy threshold of 300 GeV for gamma-ray astronomy. Most of the recorded events are single front showers, satisfying the trigger requirement of at least 20 particles detected in a given time window. However, in 13% of the events, two randomly arriving showers may be recorded in the same time window, and the second one, in generally smaller, does not need to satisfy the trigger condition. These events are called double front shower events. By using these small showers, well under the trigger threshold, the detector primary energy threshold can be lowered to a few tens of GeV. In this paper, the angular resolution that can be achieved with these events is evaluated by a full Monte Carlo simulation. The ARGO-YBJ sensitivity in detecting gamma-ray bursts (GRBs) by using double front shower events is also studied for various cutoff energies, time durations, and zenith angles of GRBs in the field view of ARGO.

astro-ph.HE↗

arXiv2016

Recurrent Neural Network Encoder with Attention for Community Question Answering

We apply a general recurrent neural network (RNN) encoder framework to community question answering (cQA) tasks. Our approach does not rely on any linguistic processing, and can be applied to different languages or domains. Further improvements are observed when we extend the RNN encoders with a neural attention mechanism that encourages reasoning over entire sequences. To deal with practical issues such as data sparsity and imbalanced labels, we apply various techniques such as transfer learning and multitask learning. Our experiments on the SemEval-2016 cQA task show 10% improvement on a MAP score compared to an information retrieval-based approach, and achieve comparable performance to a strong handcrafted feature-based method.

cs.CL↗

arXiv2016

The variance of the incipient infinite cluster in two-dimensional percolation

Consider bond percolation on the square lattice. Let ${\cal C}$ be the incipient infinite cluster with the incipient measure $ν$. If a one-arm path exponent exists and equals $5/48$, it is well known that $E_ν|{\cal C}\cup [-n,n]^2| = n^{ 91/48+o(1)}$. In this paper, we focus on the variance of $|{\cal C}\cup [-n,n]^2|$ and show that $σ^2_ν(|{\cal C}\cup [-n,n]^2|)= n^{91/24+o(1)}$.

math.PR↗

arXiv2016

Mobile-service based Max-Min Fairness Resource Scheduling for Heterogeneous Vehicular Networks

This paper investigates the resource scheduling for heterogeneous vehicular networks, where some moving vehicles are selected and scheduled as helping relays to assist information transmission between the roadside infrastructure and other moving vehicles. For such a system, we propose a mobile-service based max-min fairness resource scheduling scheme, where service amount which is more suitable for high mobility scenarios is adopted to characterize the information transmission capacity of the links and the max-min criteria is adopted to meet the fairness requirement of the moving vehicles. Simulation results demonstrate the effectiveness of our proposed scheme. It is shown that our proposed scheme archives higher throughput and better fairness compared with random scheduling scheme and non relaying scheme.

cs.NI↗

arXiv2016

Storm Detection by Visual Learning Using Satellite Images

Computers are widely utilized in today's weather forecasting as a powerful tool to leverage an enormous amount of data. Yet, despite the availability of such data, current techniques often fall short of producing reliable detailed storm forecasts. Each year severe thunderstorms cause significant damage and loss of life, some of which could be avoided if better forecasts were available. We propose a computer algorithm that analyzes satellite images from historical archives to locate visual signatures of severe thunderstorms for short-term predictions. While computers are involved in weather forecasts to solve numerical models based on sensory data, they are less competent in forecasting based on visual patterns from satellite images. In our system, we extract and summarize important visual storm evidence from satellite image sequences in the way that meteorologists interpret the images. In particular, the algorithm extracts and fits local cloud motion from image sequences to model the storm-related cloud patches. Image data from the year 2008 have been adopted to train the model, and historical thunderstorm reports in continental US from 2000 through 2013 have been used as the ground-truth and priors in the modeling process. Experiments demonstrate the usefulness and potential of the algorithm for producing more accurate thunderstorm forecasts.

cs.CV↗

arXiv2016

On Training Bi-directional Neural Network Language Model with Noise Contrastive Estimation

We propose to train bi-directional neural network language model(NNLM) with noise contrastive estimation(NCE). Experiments are conducted on a rescore task on the PTB data set. It is shown that NCE-trained bi-directional NNLM outperformed the one trained by conventional maximum likelihood training. But still(regretfully), it did not out-perform the baseline uni-directional NNLM.

cs.CL↗

arXiv2016

Automatic Generation of High-Coverage Tests for RTL Designs using Software Techniques and Tools

Register Transfer Level (RTL) design validation is a crucial stage in the hardware design process. We present a new approach to enhancing RTL design validation using available software techniques and tools. Our approach converts the source code of a RTL design into a C++ software program. Then a powerful symbolic execution engine is employed to execute the converted C++ program symbolically to generate test cases. To better generate efficient test cases, we limit the number of cycles to guide symbolic execution. Moreover, we add bit-level symbolic variable support into the symbolic execution engine. Generated test cases are further evaluated by simulating the RTL design to get accurate coverage. We have evaluated the approach on a floating point unit (FPU) design. The preliminary results show that our approach can deliver high-quality tests to achieve high coverage.

cs.SE↗

arXiv2016

Generalized holographic Ricci dark energy and generalized second law of thermodynamics in Bianchi Type I universe

Generalized second law of thermodynamics in the Bianchi type I universe with the generalized holographic Ricci dark energy model is studied in this paper. The behavior of dark energy's equation of state parameter indicates that it is matter-like in the early time of the universe but phantom-like in the future. By analysing the evolution of the deviations of state parameter and the total pressure of the universe, we find that for an anisotropic Bianchi type I universe, it transits from a high anisotropy stage to a more homogeneous stage in the near past. Using the normal entropy given by Gibbs' law of thermodynamics, it is proved that the generalized second law of thermodynamics does not always satisfied throughout the history of the universe when we assume the universe is enclosed by the generalized Ricci scalar radius $R_{gr}$. It becomes invalid in the near past to the future, and the formation of the galaxies will be helpful in explaining such phenomenon, for that the galaxies's formation is an entropy increase process. The negative change rates of the horizon entropy and internal entropy occur in different period indicates that the influences of galaxies formation is wiped from internal to the universe's horizon.

gr-qc↗