arXiv subjects

Jie Bao

Publications and source records attributed to Jie Bao.

52 records · Page 3Linked to original sources

arXiv2021

Few-Shot Text Ranking with Meta Adapted Synthetic Weak Supervision

The effectiveness of Neural Information Retrieval (Neu-IR) often depends on a large scale of in-domain relevance training signals, which are not always available in real-world ranking scenarios. To democratize the benefits of Neu-IR, this paper presents MetaAdaptRank, a domain adaptive learning method that generalizes Neu-IR models from label-rich source domains to few-shot target domains. Drawing on source-domain massive relevance supervision, MetaAdaptRank contrastively synthesizes a large number of weak supervision signals for target domains and meta-learns to reweight these synthetic "weak" data based on their benefits to the target-domain ranking accuracy of Neu-IR models. Experiments on three TREC benchmarks in the web, news, and biomedical domains show that MetaAdaptRank significantly improves the few-shot ranking accuracy of Neu-IR models. Further analyses indicate that MetaAdaptRank thrives from both its contrastive weak data synthesis and meta-reweighted data selection. The code and data of this paper can be obtained from https://github.com/thunlp/MetaAdaptRank.

cs.IR↗

arXiv2021

Control Contraction Metric Synthesis for Discrete-time Nonlinear Systems

Flexible manufacturing has been the trend in the area of the modern chemical process nowadays. One of the essential characteristics of flexible manufacturing is to track time-varying target trajectories (e.g. diversity and quantity of products). A possible tool to achieve time-varying targets is contraction theory. However, the contraction theory was developed for continuous time systems and there lacks analysis and synthesis tools for discrete-time systems. This article develops a systematic approach to discrete-time contraction analysis and control synthesis using Discrete-time Control Contraction Metrics (DCCM) which can be implemented using Sum of Square (SOS) programming. The proposed approach is demonstrated by illustrative example.

eess.SY↗

arXiv2021

Behavioural Approach to Distributed Control of Interconnected Systems

This paper formulates a framework for the analysis and distributed control of interconnected systems from the behavioural perspective. The discussions are carried out from the viewpoint of set theory and the results are completely representation-free. The core of a dynamical system can be represented as the set of all trajectories admissible through the system and interconnections are interpreted as constraints on the choice of trajectories. We develop a structure in which the interconnected behaviour can be directly built from the behaviours of the subsystems in an explicit way without any presumed forms of representations. We show that the interconnected behaviour can also be fully obtained from local observations of the subsystem. Furthermore, we develop the necessary and sufficient conditions for the existence of distributed controller behaviours and their explicit construction. Due to the entirely representation-free nature of this framework, it unites various representations and descriptions of features of dynamical systems (e.g. models, dissipativity, data, etc.) as behaviours, allowing for the formation of a unified platform for the analysis and distributed control for interconnected systems.

eess.SY↗

arXiv2021

Back-n White Neutron Source at CSNS and its Applications

Back-streaming neutrons from the spallation target of the China Spallation Neutron Source (CSNS) that emit through the incoming proton channel were exploited to build a white neutron beam facility (the so-called Back-n white neutron source), which was completed in March 2018. The Back-n neutron beam is very intense, at approximately 2*10^7 n/cm^2/s at 55 m from the target, and has a nominal proton beam with a power of 100 kW in the CSNS-I phase and a kinetic energy of 1.6 GeV and a thick tungsten target in multiple slices with modest moderation from the cooling water through the slices. In addition, the excellent energy spectrum spanning from 0.5 eV to 200 MeV, and a good time resolution related to the time-of-flight measurements make it a typical white neutron source for nuclear data measurements; its overall performance is among that of the best white neutron sources in the world. Equipped with advanced spectrometers, detectors, and application utilities, the Back-n facility can serve wide applications, with a focus on neutron-induced cross-section measurements. This article presents an overview of the neutron beam characteristics, the experimental setups, and the ongoing applications at Back-n.

physics.acc-ph↗

arXiv2020

Towards Better Bus Networks: A Visual Analytics Approach

Bus routes are typically updated every 3-5 years to meet constantly changing travel demands. However, identifying deficient bus routes and finding their optimal replacements remain challenging due to the difficulties in analyzing a complex bus network and the large solution space comprising alternative routes. Most of the automated approaches cannot produce satisfactory results in real-world settings without laborious inspection and evaluation of the candidates. The limitations observed in these approaches motivate us to collaborate with domain experts and propose a visual analytics solution for the performance analysis and incremental planning of bus routes based on an existing bus network. Developing such a solution involves three major challenges, namely, a) the in-depth analysis of complex bus route networks, b) the interactive generation of improved route candidates, and c) the effective evaluation of alternative bus routes. For challenge a, we employ an overview-to-detail approach by dividing the analysis of a complex bus network into three levels to facilitate the efficient identification of deficient routes. For challenge b, we improve a route generation model and interpret the performance of the generation with tailored visualizations. For challenge c, we incorporate a conflict resolution strategy in the progressive decision-making process to assist users in evaluating the alternative routes and finding the most optimal one. The proposed system is evaluated with two usage scenarios based on real-world data and received positive feedback from the experts.

cs.HC↗

arXiv2020

Efficient Suspected Infected Crowds Detection Based on Spatio-Temporal Trajectories

Virus transmission from person to person is an emergency event facing the global public. Early detection and isolation of potentially susceptible crowds can effectively control the epidemic of its disease. Existing metrics can not correctly address the infected rate on trajectories. To solve this problem, we propose a novel spatio-temporal infected rate (IR) measure based on human moving trajectories that can adequately describe the risk of being infected by a given query trajectory of a patient. Then, we manage source data through an efficient spatio-temporal index to make our system more scalable, and can quickly query susceptible crowds from massive trajectories. Besides, we design several pruning strategies that can effectively reduce calculations. Further, we design a spatial first time (SFT) index, which enables us to quickly query multiple trajectories without much I/O consumption and data redundancy. The performance of the solutions is demonstrated in experiments based on real and synthetic trajectory datasets that have shown the effectiveness and efficiency of our solutions.

cs.DB↗

arXiv2020

Measurement of the neutron beam profile of the Back-n white neutron facility at CSNS with a Micromegas detector

The Back-n white neutron beam line, which uses back-streaming white neutrons from the spallation target of the China Spallation Neutron Source, is used for nuclear data measurements. A Micromegas-based neutron detector with two variants was specially developed to measure the beam spot distribution for this beam line. In this article, the design, fabrication, and characterization of the detector are described. The results of the detector performance tests are presented, which include the relative electron transparency, the gain and the gain uniformity, and the neutron beam profile reconstruction capability. The result of the first measurement of the Back-n neutron beam spot distribution is also presented.

physics.ins-det↗

arXiv2019

Measurements of differential and angle-integrated cross sections for the $^{10}$B($n, α$)$^{7}$Li reaction in the neutron energy range from 1.0 eV to 2.5 MeV

Differential and angle-integrated cross sections for the $^{10}$B($n, α$)$^{7}$Li, $^{10}$B($n, α$$_{0}$)$^{7}$Li and $^{10}$B($n, α$$_{1}$)$^{7}$Li$^{*}$ reactions have been measured at CSNS Back-n white neutron source. Two enriched (90%) $^{10}$B samples 5.0 cm in diameter and ~85.0 $μ$g/cm$^{2}$ in thickness each with an aluminum backing were prepared, and back-to-back mounted at the sample holder. The charged particles were detected using the silicon-detector array of the Light-charged Particle Detector Array (LPDA) system. The neutron energy E$_{n}$ was determined by TOF (time-of-flight) method, and the valid $α$ events were extracted from the E$_{n}$-Amplitude two-dimensional spectrum. With 15 silicon detectors, the differential cross sections of $α$-particles were measured from 19.2° to 160.8°. Fitted with the Legendre polynomial series, the ($n, α$) cross sections were obtained through integration. The absolute cross sections were normalized using the standard cross sections of the $^{10}$B($n, α$)$^{7}$Li reaction in the 0.3 - 0.5 MeV neutron energy region. The measurement neutron energy range for the $^{10}$B($n, α$)$^{7}$Li reaction is 1.0 eV $\le$ En < 2.5 MeV (67 energy points), and for the $^{10}$B($n, α$$_{0}$)$^{7}$Li and $^{10}$B($n, α$$_{1}$)$^{7}$Li$^{*}$ reactions is 1.0 eV $\le$ En < 1.0 MeV (59 energy points). The present results have been analyzed by the resonance reaction mechanism and the level structure of the $^{11}$B compound system, and compared with existing measurements and evaluations.

nucl-ex↗

arXiv2019

Reward Advancement: Transforming Policy under Maximum Causal Entropy Principle

Many real-world human behaviors can be characterized as a sequential decision making processes, such as urban travelers choices of transport modes and routes (Wu et al. 2017). Differing from choices controlled by machines, which in general follows perfect rationality to adopt the policy with the highest reward, studies have revealed that human agents make sub-optimal decisions under bounded rationality (Tao, Rohde, and Corcoran 2014). Such behaviors can be modeled using maximum causal entropy (MCE) principle (Ziebart 2010). In this paper, we define and investigate a general reward trans-formation problem (namely, reward advancement): Recovering the range of additional reward functions that transform the agent's policy from original policy to a predefined target policy under MCE principle. We show that given an MDP and a target policy, there are infinite many additional reward functions that can achieve the desired policy transformation. Moreover, we propose an algorithm to further extract the additional rewards with minimum "cost" to implement the policy transformation.

cs.AI↗

arXiv2018

Human activity recognition based on time series analysis using U-Net

Traditional human activity recognition (HAR) based on time series adopts sliding window analysis method. This method faces the multi-class window problem which mistakenly labels different classes of sampling points within a window as a class. In this paper, a HAR algorithm based on U-Net is proposed to perform activity labeling and prediction at each sampling point. The activity data of the triaxial accelerometer is mapped into an image with the single pixel column and multi-channel which is input into the U-Net network for training and recognition. Our proposal can complete the pixel-level gesture recognition function. The method does not need manual feature extraction and can effectively identify short-term behaviors in long-term activity sequences. We collected the Sanitation dataset and tested the proposed scheme with four open data sets. The experimental results show that compared with Support Vector Machine (SVM), k-Nearest Neighbor (kNN), Decision Tree(DT), Quadratic Discriminant Analysis (QDA), Convolutional Neural Network (CNN) and Fully Convolutional Networks (FCN) methods, our proposal has the highest accuracy and F1-socre in each dataset, and has stable performance and high robustness. At the same time, after the U-Net has finished training, our proposal can achieve fast enough recognition speed.

cs.LG↗

arXiv2018

Energy-resolved fast neutron resonance radiography at CSNS

The white neutron beamline at the China Spallation Neutron Source will be used mainly for nuclear data measurements. It will be characterized by high flux and broad energy spectra. To exploit the beamline as a neutron imaging source, we propose a liquid scintillator fiber array for fast neutron resonance radiography. The fiber detector unit has a small exposed area, which will limit the event counts and separate the events in time, thus satisfying the requirements for single-event time-of-flight (SEToF) measurement. The current study addresses the physical design criteria for ToF measurement, including flux estimation and detector response. Future development and potential application of the technology are also discussed.

physics.ins-det↗

arXiv2016

Nuclear Fusion in Laser-Driven Counter-Streaming Collisionless Plasmas

Nuclear fusion reactions are the most important processes in nature to power stars and produce new elements, and lie at the center of the understanding of nucleosynthesis in the universe. It is critically important to study the reactions in full plasma environments that are close to true astrophysical conditions. By using laser-driven counter-streaming collisionless plasmas, we studied the fusion D$+$D$\rightarrow n +^3$He in a Gamow-like window around 27 keV. The results show that astrophysical nuclear reaction yield can be modulated significantly by the self-generated electromagnetic fields and the collective motion of the plasma. This plasma-version mini-collider may provide a novel tool for studies of astrophysics-interested nuclear reactions in plasma with tunable energies in earth-based laboratories.

nucl-ex↗

arXiv2016

Neutron Beam Tests of Barium Fluoride Crystal for Dark Matter Direct Detection

In order to test the capabilities of Barium Fluoride (BaF2) Crystal for dark matter direct detection, nuclear recoils are studied with mono-energetic neutron beam. The energy spectra of nuclear recoils, quenching factors for elastic scattering neutrons and discrimination capability between neutron inelastic scattering events and γ events are obtained for various recoil energies of the F content in BaF2.

physics.ins-det↗

arXiv2016

Neutron Beam Tests of $CsI(Na)$ and $CaF_{2}(Eu)$ Crystals for Dark Matter Direct Search

In recent decades, inorganic crystals have been widely used in dark matter direct search experiments. To contribute to the understanding of the capabilities of $CsI(Na)$ and $CaF_{2}(Eu)$ crystals, a mono-energetic neutron beam is utilized to study the properties of nuclear recoils, which are expected to be similar to signals of dark matter direct detection. The quenching factor of nuclear recoils in $CsI(Na)$ and $CaF_{2}(Eu)$, as well as an improved discrimination factor between nuclear recoils and $γ$ backgrounds in $CsI(Na)$, are reported.

physics.ins-det↗

arXiv2013

High Resolution Gamma Ray Detection in a Dual Phase Xenon Time Projection Chamber

Dual phase Xenon Time Projection Chambers (XeTPCs) are being used by several experiments as a promising technique for direct detection of dark matter. We report on the design and performance of a small 3-D sensitive dual phase XeTPC. The position resolution is 2 mm in the center of detector, limited by the hole size of the mesh at the proportional scintillation region. An energy resolution of 1.6%(σ /E) for 662 keV gamma rays is achieved by combining the ionization and scintillation signals at a drift field of 0.5 kV/cm. This represents the best energy resolution achieved among liquid xenon detectors. The energy resolution is only slightly dependent on drift field. Better than 2% energy resolution (σ /E) for 662 keV gamma rays can be achieved for drift fields between 100 V/cm and 2 kV/cm. With high position and energy resolutions, a dual phase XeTPC has also potential applications in surveys for neutrinoless double-beta decay and in gamma ray imaging.

physics.ins-det↗

arXiv2012

Mutual or Unrequited Love: Identifying Stable Clusters in Social Networks with Uni- and Bi-directional Links

Many social networks, e.g., Slashdot and Twitter, can be represented as directed graphs (digraphs) with two types of links between entities: mutual (bi-directional) and one-way (uni-directional) connections. Social science theories reveal that mutual connections are more stable than one-way connections, and one-way connections exhibit various tendencies to become mutual connections. It is therefore important to take such tendencies into account when performing clustering of social networks with both mutual and one-way connections. In this paper, we utilize the dyadic methods to analyze social networks, and develop a generalized mutuality tendency theory to capture the tendencies of those node pairs which tend to establish mutual connections more frequently than those occur by chance. Using these results, we develop a mutuality-tendency-aware spectral clustering algorithm to identify more stable clusters by maximizing the within-cluster mutuality tendency and minimizing the cross-cluster mutuality tendency. Extensive simulation results on synthetic datasets as well as real online social network datasets such as Slashdot, demonstrate that our proposed mutuality-tendency-aware spectral clustering algorithm extracts more stable social community structures than traditional spectral clustering methods.

cs.SI↗