Task Assignment on Spatial Crowdsourcing [Experiments and Analyses] (Technical Report)

Recently, with the rapid development of mobile devices and the crowdsourcing platforms, the spatial crowdsourcing has attracted much attention from the database community. Specifically, spatial crowdsourcing refers to sending a location-based request to workers according to their positions, and workers need to physically move to specified locations to conduct tasks. Many works have studied task assignment problems in spatial crowdsourcing, however, their problem settings are different from each other. Thus, it is hard to compare the performances of existing algorithms on task assignment in spatial crowdsourcing. In this paper, we present a comprehensive experimental comparison of most existing algorithms on task assignment in spatial crowdsourcing. Specifically, we first give general definitions about spatial workers and spatial tasks based on definitions in the existing works such that the existing algorithms can be applied on the same synthetic and real data sets. Then, we provide an uniform implementation for all the tested algorithms of task assignment problems in spatial crowdsourcing (open sourced). Finally, based on the results on both synthetic and real data sets, we discuss the strengths and weaknesses of tested algorithms, which can guide future research on the same area and practical implementations of spatial crowdsourcing systems.Comment: 17 page

Studies on the switching speed effect of the phase shift keying in SLED for generating high power microwave

SLAC energy doubler (SLED) type radio-frequency pulse compressors are widely used in large-scale particle accelerators for converting long-duration moderate-power input pulse into short-duration high-power output pulse. The phase shift keying (PSK) is one of the key components in SLED pulse compression systems. Performance of the PSK will influence the output characteristics of SLED, such as rise-time of the output pulse, the maximal peak power gain, and the energy efficiency. In this paper, high power microwave source based on power combining and pulse compression of conventional klystrons was introduced, the nonideal PSK with slow switching speed and without power output during the switching process were investigated, the experimental results with nonideal PSK agreed well with the analytical results

Radiative and pionic transitions from the Ds1(2460)D_{s1}(2460) to the Ds0∗(2317)D_{s0}^\ast(2317)

We estimate the partial widths for the radiative and pionic transitions from the $D_{s1}(2460)$ to the $D_{s0}(2317)$ in a molecule scenario, in which the $D_{s1}(2460)$ and $D_{s0}^\ast(2317)$ are considered as hadronic molecule states of $DK$ and $D^\ast K$, respectively. The partial widths for the $D_{s1}(2460) \to D_{s0}^\ast(2317) \pi^0$ and $D_{s1}(2460) \to D_{s0}^\ast(2317) \gamma$ are evaluated to be about $0.19 \sim 0.22$ keV and $3.0 \sim 3.1$ keV, respectively. In addition, the ratio of the $D_{s1}(2460) \to D_{s0}(2317) \gamma$ and $D_{s1}(2460) \to D_{s}^\ast \pi^0$ is estimated to be about $(6.6\sim 10.6) \times 10^{-2}$, which is safely under the measured upper limit.Comment: 8 pages, 8 figures, 2 tables, published versio

Semi-supervised Learning with Contrastive Predicative Coding

Semi-supervised learning (SSL) provides a powerful framework for leveraging unlabeled data when labels are limited or expensive to obtain. SSL algorithms based on deep neural networks have recently proven successful on standard benchmark tasks. However, many of them have thus far been either inflexible, inefficient or non-scalable. This paper explores recently developed contrastive predictive coding technique to improve discriminative power of deep learning models when a large portion of labels are absent. Two models, cpc-SSL and a class conditional variant~(ccpc-SSL) are presented. They effectively exploit the unlabeled data by extracting shared information between different parts of the (high-dimensional) data. The proposed approaches are inductive, and scale well to very large datasets like ImageNet, making them good candidates in real-world large scale applications.Comment: 6 pages, 4 figures, conferenc

Giant Magnetoresistance in Hubbard Chains

We use numerically unbiased methods to show that the one-dimensional Hubbard model with periodically distributed on-site interactions already contains the minimal ingredients to display the phenomenon of magnetoresistance; i.e., by applying an external magnetic field, a dramatic enhancement on the charge transport is achieved. We reach this conclusion based on the computation of the Drude weight and of the single-particle density of states, applying twisted boundary condition averaging to reduce finite-size effects. The known picture that describes the giant magnetoresistance, by interpreting the scattering amplitudes of parallel or antiparallel polarized currents with local magnetizations, is obtained without having to resort to different entities; itinerant and localized charges are indistinguishable.Comment: 6+4 pages 5+5 figures, as publishe

Event-triggered Online Proactive Network Association to Mobile Edge Computing for IoT

Ultra-low latency communication for mobile machines emerges as a critical technology in Internet of Things (IoT). Proactive network association has been suggested to support ultra-low latency communication with the assistance of mobile edge computing. To resolve system dynamics and uncertainty, in this paper, an online proactive network association is proposed to minimize average task delay while considering time-average energy consumption constraints. Under distributed computing and networking environments, we formulate an event-triggered proactive network association model by semi-Markov task states and independent identically distributed (i.i.d.) random events. Then we facilitate the mobility-aware anticipatory network association to predictively consider handover effects caused by the mobility. Based on the Markov decision processes (MDP) and Lyapunov optimization, the two-stage online proactive network association (TOPNA) decision algorithm is proposed without the knowledge nor distribution of random events. Simulation results exhibit the effectiveness of the proposed algorithm.Comment: 6 pages, 4 figures, the paper submitted to IEEE GLOBECOM 201

A Multi-Agent Reinforcement Learning Method for Impression Allocation in Online Display Advertising

In online display advertising, guaranteed contracts and real-time bidding (RTB) are two major ways to sell impressions for a publisher. Despite the increasing popularity of RTB, there is still half of online display advertising revenue generated from guaranteed contracts. Therefore, simultaneously selling impressions through both guaranteed contracts and RTB is a straightforward choice for a publisher to maximize its yield. However, deriving the optimal strategy to allocate impressions is not a trivial task, especially when the environment is unstable in real-world applications. In this paper, we formulate the impression allocation problem as an auction problem where each contract can submit virtual bids for individual impressions. With this formulation, we derive the optimal impression allocation strategy by solving the optimal bidding functions for contracts. Since the bids from contracts are decided by the publisher, we propose a multi-agent reinforcement learning (MARL) approach to derive cooperative policies for the publisher to maximize its yield in an unstable environment. The proposed approach also resolves the common challenges in MARL such as input dimension explosion, reward credit assignment, and non-stationary environment. Experimental evaluations on large-scale real datasets demonstrate the effectiveness of our approach

Valley controlled propagation of pseudospin states in bulk metacrystal waveguides

Light manipulations such as spin-direction locking propagation, robust transport, quantum teleportation and reconfigurable electromagnetic pathways have been investigated at the boundaries of photonic systems. Recently by breaking Dirac cones in time-reversal invariant photonic crystals, valley-pseudospin coupled edge states have been employed to realize selective propagation of light. Here, without photonic boundaries, we realize the propagation of pseudospin states in three-dimensional bulk metacrystal waveguides by employing the ubiquitous valley degree of freedom. Valley-dependent pseudospin bands are achieved in three-dimensional metacrystal waveguides without Dirac cones. Reconfigurable photonic valley Hall effect is proposed after studying the variation of pseudospin states near K' and K valleys. Moreover, a prototype of photonic blocker is realized by cascading two inversion asymmetric metacrystal waveguides in which the pseudospin direction locking propagation exists. In addition, valley-dependent pseudospin bands are also discussed in a realistic metamaterials sample. These results show an alternative way towards molding the pseudospin flow in photonic systems.Comment: 26 pages, 7 figure

Large scale quantum key distribution: challenges and solutions

Quantum key distribution (QKD) together with one time pad encoding can provide information-theoretical security for communication. Currently, though QKD has been widely deployed in many metropolitan fiber networks, its implementation in a large scale remains experimentally challenging. This letter provides a brief review on the experimental efforts towards the goal of global QKD, including the security of practical QKD with imperfect devices, QKD metropolitan and backbone networks over optical fiber and satellite-based QKD over free space.Comment: 14 pages, 5 figures. An invited review article for Optics Express's 20th Anniversary celebratio

Understanding the ηcρ\eta_c\rho decay mode of Zc(′)Z_c^{(\prime)} via the triangle loop mechanism

Recently, the BESIII Collaboration reported a new measurement of the $\eta_c \rho$ decay mode of $Z_c^{(\prime)}$, which motivated us to study the inner structure of $Z_c^{(\prime)}$ via investigating the hidden charm decays of these two $Z_c$ states. We consider the {triangle loop mechanism} contribution in the hidden charm decays of $Z_c^{(\prime)}$. Our estimations indicate that the triangle loop mechanism plays an important role in the decays of the $Z_c^{(\prime)}$, where our results are in agreement with the experimental observations in a reasonable parameter range. Furthermore, we point out that the $Z_c^{(\prime)}$ can be interpreted as the hadronic molecules, while the tetraquark scenario is less favored