arXiv subjects

Peng Cheng

Publications and source records attributed to Peng Cheng.

At least 289 records · Page 16Linked to original sources

arXiv2018

Quality-Assured Synchronized Task Assignment in Crowdsourcing

With the rapid development of crowdsourcing platforms that aggregate the intelligence of Internet workers, crowdsourcing has been widely utilized to address problems that require human cognitive abilities. Considering great dynamics of worker arrival and departure, it is of vital importance to design a task assignment scheme to adaptively select the most beneficial tasks for the available workers. In this paper, in order to make the most efficient utilization of the worker labor and balance the accuracy of answers and the overall latency, we a) develop a parameter estimation model that assists in estimating worker expertise, question easiness and answer confidence; b) propose a \textit{quality-assured synchronized task assignment scheme} that executes in batches and maximizes the number of potentially completed questions (MCQ) within each batch. We prove that MCQ problem is NP-hard and present two greedy approximation solutions to address the problem. The effectiveness and efficiency of the approximation solutions are further evaluated through extensive experiments on synthetic and real datasets. The experimental results show that the accuracy and the overall latency of the MCQ approaches outperform the existing online task assignment algorithms in the synchronized task assignment scenario.

cs.DB↗

arXiv2018

Focal Loss Dense Detector for Vehicle Surveillance

Deep learning has been widely recognized as a promising approach in different computer vision applications. Specifically, one-stage object detector and two-stage object detector are regarded as the most important two groups of Convolutional Neural Network based object detection methods. One-stage object detector could usually outperform two-stage object detector in speed; However, it normally trails in detection accuracy, compared with two-stage object detectors. In this study, focal loss based RetinaNet, which works as one-stage object detector, is utilized to be able to well match the speed of regular one-stage detectors and also defeat two-stage detectors in accuracy, for vehicle detection. State-of-the-art performance result has been showed on the DETRAC vehicle dataset.

cs.CV↗

arXiv2018

FROG: A Fast and Reliable Crowdsourcing Framework (Technical Report)

For decades, the crowdsourcing has gained much attention from both academia and industry, which outsources a number of tasks to human workers. Existing works considered improving the task accuracy through voting or learning methods, they usually did not fully take into account reducing the latency of the task completion. When a task requester posts a group of tasks (e.g., sentiment analysis), and one can only obtain answers of all tasks after the last task is accomplished. As a consequence, the time delay of even one task in this group could delay the next step of the task requester's work from minutes to days, which is quite undesirable for the task requester. Inspired by the importance of the task accuracy and latency, in this paper, we will propose a novel crowdsourcing framework, namely Fast and Reliable crOwdsourcinG framework (FROG), which intelligently assigns tasks to workers, such that the latencies of tasks are reduced and the expected accuracies of tasks are met. Specifically, our FROG framework consists of two important components, task scheduler and notification modules. For the task scheduler module, we formalize a FROG task scheduling (FROG-TS) problem, in which the server actively assigns workers with tasks with high reliability and low latency. We prove that the FROG-TS problem is NP-hard. Thus, we design two heuristic approaches, request-based and batch-based scheduling. For the notification module, we define an efficient worker notifying (EWN) problem, which only sends task invitations to those workers with high probabilities of accepting the tasks. To tackle the EWN problem, we propose a smooth kernel density estimation approach to estimate the probability that a worker accepts the task invitation. Through extensive experiments, we demonstrate the effectiveness and efficiency of our proposed FROG platform on both real and synthetic data sets.

cs.DB↗

arXiv2018

Consensus-based Privacy-preserving Data Aggregation

Privacy-preserving data aggregation in ad hoc networks is a challenging problem, considering the distributed communication and control requirement, dynamic network topology, unreliable communication links, etc. Different from the widely used cryptographic approaches, in this paper, we address this challenging problem by exploiting the distributed consensus technique. We first propose a secure consensus-based data aggregation (SCDA) algorithm that guarantees an accurate sum aggregation while preserving the privacy of sensitive data. Then, we prove that the proposed algorithm converges accurately and is $(ε, σ)$-data-privacy, and the mathematical relationship between $ε$ and $σ$ is provided. Extensive simulations have shown that the proposed algorithm has high accuracy and low complexity, and they are robust against network dynamics.

eess.SY↗

arXiv2018

Calculation of Dissociation Temperature of Nucleon Using Gaussian Expansion Method

The first study of the dissociation temperature of nucleon in hot QCD medium in the framework of constituent quark model is presented. The temperature-dependent potential energy of the three quark system, taking as the internal energy of the system are obtained from the free energy of the system, and the temperature-dependent free energy is derived based on Debye-Hückel theory. The lattice QCD results of the free energy for heavy three-quark system are employed and extended to the light three-quark system. The Schrödinger equation for nucleon is solved with the help of Gaussian expansion method and the dissociation temperature of the nucleon is determined according to the temperature dependence of binding energy and radii. Comparing with the dissociation temperature of $J/ψ$, the dissociation temperature of nucleon is higher. So, nucleon is more difficult to melt than Charmonium.

hep-ph↗

arXiv2017

Experimental realization of graphene-like borophene

We report a successful preparation of a purely honeycomb, graphene-like borophene, by using an Al(111) surface as the substrate and molecular beam epitaxy (MBE) growth in ultrahigh vacuum. Our scanning tunneling microscopy (STM) reveals perfect monolayer borophene with planar, non-buckled honeycomb lattice similar as graphene. Theoretical calculations show that the honeycomb borophene on Al(111) is energetically stable. Remarkably, nearly one electron charge is transferred to each boron atom from the Al(111) substrate and stabilizes the honeycomb borophene structure, in contrast to the little charge transfer in borophene/Ag(111) case. This work demonstrates that the borophene lattice can be manipulated by controlling the charge transfer between the substrate and the borophene film.

cond-mat.mes-hall↗

arXiv2017

Unique catalytic decomposition and reduction of hydrogen peroxide and organic peroxides on magnesia (001) promoted by oxide-metal hybrid nanostructure

The detection, removal and reduction of hydrogen peroxide is of significant importance for its increasing application in the areas of environment, food, electrochemistry and clinical laboratory. Herein the dissociative adsorption behavior of hydrogen peroxide on ultrathin magnesia (001) films deposited on transition metal is uncovered for the first time by employing periodic density-functional theory calculations with van der Waals corrections. The hydrogen peroxide is dissociated smoothly and reduced to surface hydroxyls on MgO(001)/TM, and the dissociative adsorption energies of all the considered fragmentation configurations are substantially negative, demonstrating dissociation and reduction of hydrogen peroxide on MgO(001)/TM is thermodynamically favorable. The dissociative adsorption energy decreases monotonously with increasing film thickness, demonstrating the lower reactivity of thick oxide films. Moreover, we examined the suitability of several transition metal slabs (molybdenum, silver, vanadium, tungsten and gold) combined with magnesia for splitting hydrogen peroxide. The dissociative adsorption energies enhance when the lattice constants of substrate slabs increase, indicating the chemisorption strength can be tuned by category of metal slabs as well as thickness of oxide film. The mechanism of reactivity enhancement for energetically and dynamically favorable decomposition of hydrogen peroxide on supported magnesia is elucidated by characterizing the geometric structures and electronic properties. The fragmentation and reduction of diethyl peroxide and peroxyacetone are also studied to reveal the catalytic activity of ultrathin magnesia toward splitting organic peroxides. The results are wished to provide useful clue for detecting and reducing hydrogen peroxide and organic peroxides by employing oxide-metal hybrid nanostructure.

physics.chem-ph↗

arXiv2017

Direct evidences of pentagonal silicon chains and magic clusters

Pentagon is one of the most beautiful geometric structures in nature, but it is rarely seen simply because five-fold symmetry is mathematically forbidden in a 2D or 3D periodic lattices. Fortunately, pentagon as a structural element is allowed in 1D or 0D systems, since translational symmetry is not necessary there. However, in these systems pentagons only compose a small portion of the structure. So far, 1D or 0D systems consisting of purely pentagons are still rare. Here, combing high resolution non-contact atomic force microscopy and tip-enhanced Raman spectroscopy, we have directly visualized the pentagon-ring structure in self-assembled Si nanoribbons and magic clusters on Ag(110) substrate. Moreover, chemical fingerprint of Si pentagon was detected in individual Si nanoribbon and clusters by tip-enhanced Raman spectroscopy. This work demonstrates that Si pentagon can be an important element in building silicon nanostructures, which may find potential applications in future nanoelectronics based on silicon.

cond-mat.mes-hall↗

arXiv2017

A Co(II)-based Molecular Magnet with a 6 T Coercive Field

Hard magnets with high coercivity, such as Nd2Fe14B and SmCo5 alloys, can maintain magnetisation under a high reverse external magnetic field and have therefore become irreplaceable parts in many practical applications. Molecular magnets are promising alternatives, owing to their precise and designable chemical structures, tuneable functionalities and controllable synthetic methods. Here, we demonstrate that an unusually large coercive field can be achieved in a single-chain magnet. Systematic characterisations, including magnetic susceptibility, heat capacity and neutron diffraction measurements, show that the observed giant coercive field originates from the spin dynamics along the one-dimensional chain of the compound because of the strong exchange coupling between Co(II) centres and radicals.

physics.chem-ph↗

arXiv2017

Discovery of two-dimensional Dirac nodal line fermions in monolayer Cu2Si

Topological nodal line semimetals, a novel quantum state of materials, possess topologically nontrivial valence and conduction bands that touch at a line near the Fermi level. The exotic band structure can lead to various novel properties, such as long-range Coulomb interaction and flat Landau levels. Recently, topological nodal lines have been observed in several bulk materials, such as PtSn4, ZrSiS, TlTaSe2 and PbTaSe2. However, in two-dimensional materials, experimental research on nodal line fermions is still lacking. Here, we report the discovery of two-dimensional Dirac nodal line fermions in monolayer Cu2Si based on combined theoretical calculations and angle-resolved photoemission spectroscopy measurements. The Dirac nodal lines in Cu2Si form two concentric loops centred around the Γ point and are protected by mirror reflection symmetry. Our results establish Cu2Si as a new platform to study the novel physical properties in two-dimensional Dirac materials and provide new opportunities to realize high-speed low-dissipation devices.

cond-mat.mtrl-sci↗

arXiv2017

Strain-Induced Band Engineering in Monolayer Stanene on Sb(111)

Two-dimensional (2D) allotrope of tin with low buckled honeycomb structure, named as stanene, is proposed to be an ideal 2D topological insulator with a nontrivial gap larger than 0.1 eV. Theoretical works also pointed out the topological property of stanene occurs by strain tuning. In this letter, we report the successful realization of high quality, monolayer stanene film as well as monolayer stanene nanoribbons on Sb(111) surface by molecular beam epitaxy, providing an ideal platform to the study of stanene. More importantly, we observed a continuous evolution of the electronic bands of stanene across a nanoribbon, which are related to the strain field gradient in stanene. Our work experimentally confirmed that strain is an effective method for band engineering in stanene, which is important for fundamental research and application of stanene.

cond-mat.mtrl-sci↗

arXiv2017

Remarkably strong chemisorption of nitric oxide on insulating oxide films promoted by hybrid structure

The remarkably strong chemical adsorption behaviors of nitric oxide on magnesia (001) film deposited on metal substrate have been investigated by employing periodic density functional calculations with Van der Waals corrections. The molybdenum supported magnesia (001) show significantly enhanced adsorption properties and the nitric oxide is chemisorbed strongly and preferably trapped in flat adsorption configuration on metal supported oxide film, due to the substantially large adsorption energies and transformation barriers. The analysis of Bader charges, projected density of states, differential charge densities, electron localization function, highest occupied orbital and particular orbital with largest Mg-NO-Mg bonding coefficients, are applied to reveal the electronic adsorption properties and characteristics of bonding between nitric oxide and surface as well as the bonding within the hybrid structure. The strong chemical binding of nitric oxide on magnesia deposited on molybdenum slab offers new opportunities for toxic gas detection and treatment. We anticipate that hybrid structure promoted remarkable chemical adsorption of nitric oxide on magnesia in this study will provide versatile strategy for enhancing chemical reactivity and properties of insulating oxide.

physics.chem-ph↗

arXiv2017

Synthesis of Borophene Nanoribbons on Ag(110) Surface

We present the successful synthesis of single-atom-thick borophene nanoribbons (BNRs) by self-assembly of boron on Ag(110) surface. The scanning tunneling microscopy (STM) studies reveal high quality BNRs: all the ribbons are along the [-110] direction of Ag(110), and can run across the steps on the surface. The width of ribbons is distributed in a narrow range around 10.3 nm. High resolution STM images revealed four ordered surface structures in BNRs. Combined with DFT calculations, we found that all the four structures of boron nanoribbons consist of the boron chains with different width, separated by hexagonal hole arrays. The successful synthesis of BNRs enriches the low dimensional allotrope of boron and may promote further applications of borophene

cond-mat.mtrl-sci↗

arXiv2017

Prediction-Based Task Assignment in Spatial Crowdsourcing (Technical Report)

Spatial crowdsourcing refers to a system that periodically assigns a number of location-based workers with spatial tasks nearby (e.g., taking photos or videos at some spatial locations). Previous works on the spatial crowdsourcing usually designed task assignment strategies that maximize some assignment scores, which are however only based on available workers/tasks in the system at the time point of assigning workers/tasks. These strategies may achieve local optimality, due to the neglect of future workers/tasks that may join the system. In contrast, in this paper, we aim to achieve "globally" optimal task assignments, by considering not only those present, but also future (via predictions), workers/tasks. Specifically, we formalize an important problem, namely prediction-based spatial crowdsourcing (PB-SC), which expects to obtain a "globally" optimal strategy for worker-and-task assignments, over both present and predicted task/worker locations, such that the total assignment quality score is maximized under the constraint of the traveling budget. In this paper, we design an effective grid-based prediction method to estimate spatial distributions of workers/tasks in the future, and then utilize the predicted ones in our procedure of task assignments. We prove that the PB-SC problem is NP-hard, and thus intractable. Therefore, we propose efficient approximate algorithms to tackle the PB-SC problem, including greedy and divide-and-conquer (D&C) approaches, which can efficiently assign workers to spatial tasks with high quality scores and low budget consumptions, by considering both current and future task/worker distributions. Through extensive experiments, we demonstrate the efficiency and effectiveness of our PB-SC processing approaches on real/synthetic data.

cs.DB↗

arXiv2017

Privacy-preserving Average Consensus: Privacy Analysis and Optimal Algorithm Design

Privacy-preserving average consensus aims to guarantee the privacy of initial states and asymptotic consensus on the exact average of the initial value. In existing work, it is achieved by adding and subtracting variance decaying and zero-sum random noises to the consensus process. However, there is lack of theoretical analysis to quantify the degree of the privacy protection. In this paper, we introduce the maximum disclosure probability that the other nodes can infer one node's initial state within a given small interval to quantify the privacy. We develop a novel privacy definition, named $(ε, δ)$-data-privacy, to depict the relationship between maximum disclosure probability and estimation accuracy. Then, we prove that the general privacy-preserving average consensus (GPAC) provides $(ε, δ)$-data-privacy, and provide the closed-form expression of the relationship between $ε$ and $δ$. Meanwhile, it is shown that the added noise with uniform distribution is optimal in terms of achieving the highest $(ε, δ)$-data-privacy. We also prove that when all information used in the consensus process is available, the privacy will be compromised. Finally, an optimal privacy-preserving average consensus (OPAC) algorithm is proposed to achieve the highest $(ε, δ)$-data-privacy and avoid the privacy compromission. Simulations are conducted to verify the results.

eess.SY↗

arXiv2016

Micro-burst in Data Centers: Observations, Implications, and Applications

Micro-burst traffic is not uncommon in data centers. It can cause packet dropping, which results in serious performance degradation (e.g., Incast problem). However, current solutions that attempt to suppress micro-burst traffic are extrinsic and ad hoc, since they lack the comprehensive and essential understanding of micro-burst's root cause and dynamic behavior. On the other hand, traditional studies focus on traffic burstiness in a single flow, while in data centers micro-burst traffic could occur with highly fan-in communication pattern, and its dynamic behavior is still unclear. To this end, in this paper we re-examine the micro-burst traffic in typical data center scenarios. We find that evolution of micro-burst is determined by both TCP's self-clocking mechanism and bottleneck link. Besides, dynamic behaviors of micro-burst under various scenarios can all be described by the slope of queue length increasing. Our observations also implicate that conventional solutions like absorbing and pacing are ineffective to mitigate micro-burst traffic. Instead, senders need to slow down as soon as possible. Inspired by the findings and insights from experimental observations, we propose S-ECN policy, which is an ECN marking policy leveraging the slope of queue length increasing. Transport protocols utilizing S-ECN policy can suppress the sharp queue length increment by over 50%, and reduce the 99th percentile of query completion time by ~20%.

cs.NI↗

arXiv2016

Analytical and exact critical phenomena of $d$-dimensional singly spinning Kerr-AdS black holes

In the extended phase space, the $d$-dimensional singly spinning Kerr-AdS black holes exhibit the van der Waals's phase transition and reentrant phase transition. Since the black hole system is a single characteristic parameter thermodynamic system, we show that the form of the critical point can be uniquely determined by the dimensional analysis. When $d=4$, we get the analytical critical point. The coexistence curve and phase diagrams are obtained. The result shows that the fitting form of the coexistence curve in the reduced parameter space is independent of the angular momentum. When $d=5$---$9$, the exact critical points are numerically solved. It demonstrates that when $d\geq6$, there are two critical points. However, the small one does not participate in the phase transition. Moreover, the exact critical reentrant phase transition points are also obtained. All the critical points are obtained without any approximation.

gr-qc↗

arXiv2016

Critical phenomena in the extended phase space of Kerr-Newman-AdS black holes

Treating the cosmological constant as a thermodynamic pressure, we investigate the critical behavior of a Kerr-Newman-AdS black hole system. The critical points for the van der Waals like phase transition are numerically solved. The highly accurate fitting formula for them is given and is found to be dependent of the charge $Q$ and angular momentum $J$. In the reduced parameter space, we find that the temperature, Gibbs free energy, and coexistence curve depend only on the dimensionless angular momentum-charge ratio $ε=J/Q^2$ rather than $Q$ and $J$. Moreover, when varying $ε$ from 0 to $\infty$, the coexistence curve will continuously change from that of the Reissner-Nordström-AdS black hole to the Kerr-AdS black hole. These results may guide us to study the critical phenomena for other thermodynamic systems with two characteristic parameters.

gr-qc↗