Z. -T. Han - Nankai Univ.

Z. -T. Han
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Name
Z. -T. Han
Affiliation
Nankai Univ.
Country
China

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Computer Science - Information Theory (10)
 
Mathematics - Information Theory (10)
 
Computer Science - Networking and Internet Architecture (9)
 
Computer Science - Computer Science and Game Theory (8)
 
Astrophysics of Galaxies (5)
 
High Energy Physics - Phenomenology (4)
 
Physics - Mesoscopic Systems and Quantum Hall Effect (4)
 
Computer Science - Computer Vision and Pattern Recognition (3)
 
Physics - Materials Science (3)
 
Physics - Optics (3)
 
Quantum Physics (3)
 
Computer Science - Distributed; Parallel; and Cluster Computing (3)
 
Solar and Stellar Astrophysics (3)
 
Statistics - Applications (1)
 
Mathematics - Analysis of PDEs (1)
 
Physics - Disordered Systems and Neural Networks (1)
 
Computer Science - Learning (1)
 
Computer Science - Computers and Society (1)
 
Physics - Superconductivity (1)
 
Computer Science - Cryptography and Security (1)
 
Computer Science - Data Structures and Algorithms (1)
 
High Energy Astrophysical Phenomena (1)
 
Physics - Strongly Correlated Electrons (1)
 
Mathematics - Combinatorics (1)
 
Statistics - Machine Learning (1)

Publications Authored By Z. -T. Han

Benefited from the widely deployed infrastructure, the LTE network has recently been considered as a promising candidate to support the vehicle-to-everything (V2X) services. However, with a massive number of devices accessing the V2X network in the future, the conventional OFDM-based LTE network faces the congestion issues due to its low efficiency of orthogonal access, resulting in significant access delay and posing a great challenge especially to safety-critical applications. The non-orthogonal multiple access (NOMA) technique has been well recognized as an effective solution for the future 5G cellular networks to provide broadband communications and massive connectivity. Read More

In many industrial applications of big data, the Jaccard Similarity Computation has been widely used to measure the distance between two profiles or sets respectively owned by two users. Yet, one semi-honest user with unpredictable knowledge may also deduce the private or sensitive information (e.g. Read More

Because of the limitations of matrix factorization, such as losing spatial structure information, the concept of low-rank tensor factorization (LRTF) has been applied for the recovery of a low dimensional subspace from high dimensional visual data. The low-rank tensor recovery is generally achieved by minimizing the loss function between the observed data and the factorization representation. The loss function is designed in various forms under different noise distribution assumptions, like $L_1$ norm for Laplacian distribution and $L_2$ norm for Gaussian distribution. Read More

DV UMa is an eclipsing dwarf nova with an orbital period of $\sim2.06$ h, which lies just at the bottom edge of the period gap. To detect its orbital period changes we present 12 new mid-eclipse times by using our CCD photometric data and archival data. Read More

We present the photometric results of the eclipsing cataclysmic variable (CV) WZ Sge near the period minimum ($P_{min}$). Eight new mid-eclipse times were determined and the orbital ephemeris was updated. Our result shows that the orbital period of WZ Sge is decreasing at a rate of $\dot{P}=-2. Read More

GSC 4560-02157 is a new eclipsing cataclysmic variable with an orbital period of $0.265359$ days. By using the published $V-$ and $R-$band data together with our observations, we discovered that the $O-C$ curve of GSC 4560-02157 may shows a cyclic variation with the period of $3. Read More

New eclipse timings of the Z Cam-type dwarf nova AY Psc were measured and the orbital ephemeris was revised. Based on the long-term AAVSO data, moreover, the outburst behaviors were also explored. Our analysis suggests that the normal outbursts are quasi-periodic, with an amplitude of $\sim2. Read More

EX Dra is a long-period eclipsing dwarf nova with $\sim2-3$ mag amplitude outbursts. This star has been monitored photometrically from November, 2009 to March, 2016 and 29 new mid-eclipse times were obtained. By using new data together with the published data, the best fit to the $O-C$ curve indicate that the orbital period of EX Dra have an upward parabolic change while undergoing double-cyclic variations with the periods of 21. Read More

Scotogenic models were proposed by some authors where the tiny Dirac neutrino mass terms arise at loop level. In prototype models, two $ad$ $hoc$ discrete symmetries were introduced, one is responsible for the absence of SM Yukawa couplings $\bar{\nu}_L\nu_R\overline{\phi^0}$ and the other for the stability of intermediate fields as dark matter(DM). In this paper, we construct the one-loop and two-loop scotogenic models for Dirac neutrino mass generation in the context of $U(1)_{B-L}$ extensions of standard model. Read More

Atomically-thin 2D semiconducting materials integrated into van der Waals heterostructures have enabled architectures that hold great promise for next generation nanoelectronics. However, challenges still remain to enable their full acceptance as compliant materials for integration in logic devices. Two key-components to master are the barriers at metal/semiconductor interfaces and the mobility of the semiconducting channel, which endow the building-blocks of ${pn}$ diode and field effect transistor. Read More

Early polarization observations on Type Ia supernovae (SNe Ia) may reveal the geometry of supernova ejecta, and then put constraints on their explosion mechanism and their progenitor model. We performed a literature search of SNe Ia with polarization measurements and determined the polarization and relative equivalent width (REW) of Si II 635.5-nm absorption feature at -5 days after the maximum light. Read More

Understanding semantic similarity among images is the core of a wide range of computer vision applications. An important step towards this goal is to collect and learn human perceptions. Interestingly, the semantic context of images is often ambiguous as images can be perceived with emphasis on different aspects, which may be contradictory to each other. Read More

This paper studies physical layer security in a wireless ad hoc network with numerous legitimate transmitter-receiver pairs and eavesdroppers. A hybrid full-/half-duplex receiver deployment strategy is proposed to secure legitimate transmissions, by letting a fraction of legitimate receivers work in the full-duplex (FD) mode sending jamming signals to confuse eavesdroppers upon their information receptions, and letting the other receivers work in the half-duplex mode just receiving their desired signals. The objective of this paper is to choose properly the fraction of FD receivers for achieving the optimal network security performance. Read More

By enabling wireless devices to be charged wirelessly and remotely, radio frequency energy harvesting (RFEH) has become a promising technology to power the unattended Internet of Things (IoT) low-power devices. To enable this, in future IoT networks, besides the conventional data access points (DAPs) responsible for collecting data from IoT devices, energy access points (EAPs) should be deployed to transfer radio frequency (RF) energy to IoT devices to maintain their sustainable operations. In practice, the DAPs and EAPs may be operated by different operators and a DAP should provide certain incentives to motivate the surrounding EAPs to charge its associated IoT device(s) to assist its data collection. Read More

With the emerging sensing technologies such as mobile crowdsensing and Internet of Things (IoT), people-centric data can be efficiently collected and used for analytics and optimization purposes. This data is typically required to develop and render people-centric services. In this paper, we address the privacy implication, optimal pricing, and bundling of people-centric services. Read More

Mobile crowdsensing has emerged as an efficient sensing paradigm which combines the crowd intelligence and the sensing power of mobile devices, e.g.,~mobile phones and Internet of Things (IoT) gadgets. Read More

Round-robin-differential-phase (RRDPS) quantum key distribution (QKD) protocol has attracted intensive studies due to its distinct security characteristic, e.g., information leakage in RRDPS can be bounded without learning error rate of key bits. Read More

We performed angle-resolved photoemission spectroscopy studies on a series of FeTe$_{1-x}$Se$_{x}$ monolayer films grown on SrTiO$_{3}$. The superconductivity of the films is robust and rather insensitive to the variations of the band position and effective mass caused by the substitution of Se by Te. However, the band gap between the electron- and hole-like bands at the Brillouin zone center decreases towards band inversion and parity exchange, which drive the system to a nontrivial topological state predicted by theoretical calculations. Read More

We present a transfer-free preparation method for graphene on hexagonal boron nitride (h-BN) crystals by chemical vapor deposition of graphene via a catalytic proximity effect, i.e. activated by a Cu catalyst close-by . Read More

We show that every set $\mathcal{P}$ of $n$ non-collinear points in the plane contains a point incident to at least $\lceil\frac{n}{3}\rceil+1$ of the lines determined by $\mathcal{P}$. Read More

Transferring graphene flakes onto hexagonal boron nitride (h-BN) has been the most popular approach for the fabrication of graphne/h-BN heterostructures so far. The orientation between graphene and h-BN lattices, however, are not controllable and the h-BN/graphene interfaces are prone to be contaminated during this elaborate process. Direct synthesis of graphene on h-BN is an alternative and rapidly growing approach. Read More

Recently, the concept of fog computing which aims at providing time-sensitive data services has become popular. In this model, computation is performed at the edge of the network instead of sending vast amounts of data to the cloud. Thus, fog computing provides low latency, location awareness to end users, and improves quality-of-services (QoS). Read More

Fog computing is a promising architecture to provide economic and low latency data services for future Internet of things (IoT)-based network systems. It relies on a set of low-power fog nodes that are close to the end users to offload the services originally targeting at cloud data centers. In this paper, we consider a specific fog computing network consisting of a set of data service operators (DSOs) each of which controls a set of fog nodes to provide the required data service to a set of data service subscribers (DSSs). Read More

2017Jan

The neutrinophilic two-Higgs-doublet model ($\nu$2HDM) provides a natural way to generate tiny neutrino mass from interactions with the new doublet scalar $\Phi_\nu$ ($H^\pm,~H,~A$) and singlet neutrinos $N_R$ of TeV scale. In this paper, we perform detailed simulations for the lepton number violating (LNV) signatures at LHC arising from cascade decays of the new scalars and neutrinos with the mass order $m_{N_R}Read More

This paper presents a comprehensive literature review on applications of economic and pricing models for resource management in cloud networking. To achieve sustainable profit advantage, cost reduction, and flexibility in provisioning of cloud resources, resource management in cloud networking requires adaptive and robust designs to address many issues, e.g. Read More

How to enhance the communication efficiency and quality on vehicular networks is one critical important issue. While with the larger and larger scale of vehicular networks in dense cities, the real-world datasets show that the vehicular networks essentially belong to the complex network model. Meanwhile, the extensive research on complex networks has shown that the complex network theory can both provide an accurate network illustration model and further make great contributions to the network design, optimization and management. Read More

One significant challenge in cognitive radio networks is to design a framework in which the selfish secondary users are obliged to interact with each other truthfully. Moreover, due to the vulnerability of these networks against jamming attacks, designing anti-jamming defense mechanisms is equally important. %providing the security defense is also of great importance. Read More

Simultaneously information and power transfer in mobile relay networks have recently emerged, where the relay can harvest the radio frequency (RF) energy and then use this energy for data forwarding and system operation. Most of the previous works do not consider that the relay may have its own objectives, such as using the harvested energy for its own transmission instead of maximizing transmission of the network. Therefore, in this paper, we propose a Nash bargaining approach to balance the information transmission efficiency of source-destination pairs and the harvested energy of the relay in a wireless powered relay network with multiple source-destination pairs and one relay. Read More

If neutrinos are Dirac fermions, certain new physics beyond the standard model should exist to account for the smallness of neutrino mass. With two additional scalars and a heavy intermediate fermion, in this paper, we systematically study the general mechanism that can natrally generate the tiny Dirac neutrino mass at tree and in one-loop level. For tree level models, we focus on natural ones, in which the additional scalars develop small vacuum expectation values without fine-tuning. Read More

The concept of device-to-device (D2D) communications underlaying cellular networks opens up potential benefits for improving system performance but also brings new challenges such as interference management. In this paper, we propose a pricing framework for interference management from the D2D users to the cellular system, where the base station (BS) protects itself (or its serving cellular users) by pricing the crosstier interference caused from the D2D users. A Stackelberg game is formulated to model the interactions between the BS and D2D users. Read More

We propose a novel stacked generalization (stacking) method as a dynamic ensemble technique using a pool of heterogeneous classifiers for node label classification on networks. The proposed method assigns component models a set of functional coefficients, which can vary smoothly with certain topological features of a node. Compared to the traditional stacking model, the proposed method can dynamically adjust the weights of individual models as we move across the graph and provide a more versatile and significantly more accurate stacking model for label prediction on a network. Read More

We study entire solutions to homogeneous reaction-diffusion equations in several dimensions with Fisher-KPP reactions. Any entire solution $02\sqrt{f'(0)}\,$.} \] When $f$ is $C^2$ and concave, our main result provides an almost complete characterization of transition fronts as well as transition solutions with bounded width within this class of solutions. Read More

Single photons with orbital angular momentum (OAM) have attracted substantial attention from researchers. A single photon can carry infinite OAM values theoretically. Thus, OAM photon states have been widely used in quantum information and fundamental quantum mechanics. Read More

KIC~8262223 is an eclipsing binary with a short orbital period ($P=1.61$ d). The {\it Kepler} light curves are of Algol-type and display deep and partial eclipses, ellipsoidal variations, and pulsations of Delta Scuti type. Read More

Employing tidally enhanced stellar wind, we studied in binaries the effects of metallicity, mass ratio of primary to secondary, tidal enhancement efficiency and helium abundance on the formation of blue hook (BHk) stars in globular clusters (GCs). A total of 28 sets of binary models combined with different input parameters are studied. For each set of binary model, we presented a range of initial orbital periods that is needed to produce BHk stars in binaries. Read More

In this paper, we explore the redundancy in convolutional neural network, which scales with the complexity of vision tasks. Considering that many front-end visual systems are interested in only a limited range of visual targets, the removing of task-specified network redundancy can promote a wide range of potential applications. We propose a task-specified knowledge distillation algorithm to derive a simplified model with pre-set computation cost and minimized accuracy loss, which suits the resource constraint front-end systems well. Read More

We report a novel approach for on-chip electrical detection of the radiation guided by dielectric-loaded surface plasmon polariton waveguides (DLSPPW) and DLSPPW-based components. The detection is realized by fabricating DLSPPW components on the surface of a gold (Au) pad supported by a silicon (Si) substrate supplied with aluminum pads facilitating electrical connections, with the gold pad being perforated in a specific locations below the DLSPPWs in order to allow a portion of the DLSPPW-guided radiation to leak into the Si-substrate, where it is absorbed and electrically detected. We present two-dimensional photocurrent maps obtained when the laser beam is scanning across the gold pad containing the fabricated DLSPPW components that are excited via grating couplers located at the DLSPPW tapered terminations. Read More

The unique optical and electronic properties of graphene allow one to realize active optical devices. While several types of graphene-based photonic modulators have already been demonstrated, the potential of combining the versatility of graphene with subwavelength field confinement of plasmonic/metallic structures is not fully realized. Here we report fabrication and study of hybrid graphene-plasmonic modulators. Read More

The arrival of small-scale distributed energy generation in the future smart grid has led to the emergence of so-called prosumers, who can both consume as well as produce energy. By using local generation from renewable energy resources, the stress on power generation and supply system can be significantly reduced during high demand periods. However, this also creates a significant challenge for conventional power plants that suddenly need to ramp up quickly when the renewable energy drops off. Read More

2016Sep
Affiliations: 1Nankai U., 2Nankai U., 3Nankai U., ITP, Beijing, CHEP, Peking U.

We analyse the testability of the type II radiative seesaw in which neutrino mass and dark matter (DM) are related at one-loop level. Under the constraints from DM relic density, direct and indirect detection, and invisible Higgs decays, we find three possible regions of DM mass $M_{s_1}$ that can survive the present and even the future experiments: (1) the Higgs resonance region with $M_{s_1}\sim M_h/2$, (2) the Higgs region with $M_{s_1}\sim M_h$, and (3) the coannihilation region with $M_{s_2}\sim M_{s_1}$. Here $s_{1,2}$ are two scalar singlets with the lighter $s_1$ being the DM candidate. Read More

From the canonical binary scenario, the majority of sdBs are produced from low-mass stars with degenerate cores where helium is ignited in a way of flashes. Due to numerical difficulties, the models of produced sdBs are generally constructed from more massive stars with non-degenerate cores, leaving several uncertainties on the exact characteristics of sdB stars. Employing MESA, we systematically studied the characteristics of sdBs produced from the common envelope (CE) ejection channel, and found that the sdB stars produced from the CE ejection channel appear to form two distinct groups on the effective temperature-gravity diagram. Read More

Backscatter wireless communication is an emerging technique widely used in low-cost and low-power wireless systems, especially in passive radio frequency identification (RFID) systems. Recently, the requirement of high data rates, data reliability, and security drives the development of RFID systems, which motivates our investigation on the physical layer security of a multiple-input multiple-output (MIMO) RFID system. In this paper, we propose a noise-injection precoding strategy to safeguard the system security with the resource-constrained nature of the backscatter system taken into consideration. Read More

Creating, detecting, and manipulating Majorana fermions (MFs) in condensed matters have attracted tremendous interest due to their relevance to topological quantum computing. A single-mode MF platform combining helical edge state of a quantum spin Hall insulator (QSHI), s-wave superconductor, and magnetic insulator was proposed early on, taking advantages of the spin-polarized single-mode dispersion and the absence of non-magnetic scattering inherent in the helical states. Moreover, the edge modes may be gapped out by nearby nanoscale magnetic insulator due to the breaking of time-reversal-symmetry (TRS), localizing a pair of Majorana bound states. Read More

Atomically thin layers of transition-metal dicalcogenides (TMDCs) are often known to be metastable in the ambient atmosphere. Understanding the mechanism of degradation is essential for their future applications in nanoelectronics, and thus has attracted intensive interest recently. Here, we demonstrate a systematic study of atomically thin WTe$_{2}$ in its low temperature quantum electronic transport properties. Read More

This paper provides a state-of-the-art literature review on economic analysis and pricing models for data collection and wireless communication in Internet of Things (IoT). Wireless Sensor Networks (WSNs) are the main component of IoT which collect data from the environment and transmit the data to the sink nodes. For long service time and low maintenance cost, WSNs require adaptive and robust designs to address many issues, e. Read More

In this paper, we introduce a new model for RF-powered cognitive radio networks with the aim to improve the performance for secondary systems. In our proposed model, when the primary channel is busy, the secondary transmitter is able either to backscatter the primary signals to transmit data to the secondary receiver or to harvest RF energy from the channel. The harvested energy then will be used to transmit data to the receiver when the channel becomes idle. Read More

Calibration of the polarization basis between the transmitter and receiver is an important task in quantum key distribution (QKD). An effective polarization-basis tracking scheme will decrease the quantum bit error rate (QBER) and improve the efficiency of a polarization encoding QKD system. In this paper, we proposed a polarization-basis tracking scheme using only unveiled sifted key bits while performing error correction by legitimate users, rather than introducing additional reference light or interrupting the transmission of quantum signals. Read More

With the rapid growth of sensor technology, smartphone sensing has become an effective approach to improve the quality of smartphone applications. However, due to time-varying wireless channels and lack of incentives for the users to participate, the quality and quantity of the data uploaded by the smartphone users are not always satisfying. In this paper, we consider a smartphone sensing system in which a platform publicizes multiple tasks, and the smartphone users choose a set of tasks to participate in. Read More

We study the entanglement in momentum space of a disordered one-dimensional fermion lattice model with attractive interaction. We observe that the many-body localization transition can be characterized by behaviors of two components in entanglement spectrum. One of the components is related to paired-fermion entanglement which contributes to the long-range correlation in position space, and the vanishing of it indicates the emerged many-body localized phase. Read More

This paper considers a compressive sensing (CS) approach for hyperspectral data acquisition, which results in a practical compression ratio substantially higher than the state-of-the-art. Applying simultaneous low-rank and joint-sparse (L&S) model to the hyperspectral data, we propose a novel algorithm to joint reconstruction of hyperspectral data based on loopy belief propagation that enables the exploitation of both structured sparsity and amplitude correlations in the data. Experimental results with real hyperspectral datasets demonstrate that the proposed algorithm outperforms the state-of-the-art CS-based solutions with substantial reductions in reconstruction error. Read More