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An interpretable reasoning network for multi-relation question answering

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arXiv 2018年

作者： Zhou, Mantong Huang, Minlie Zhu, Xiaoyan State Key Lab. of Intelligent Technology and Systems National Lab. for Information Science and Technology Dept. of Computer Science and Technology Tsinghua University Beijing China

Multi-relation Question Answering is a challenging task, due to the requirement of elab.rated analysis on questions and reasoning over multiple fact triples in knowledge base. In this paper, we present a novel model called Interpretable Reasoning Network that employs an interpretable, hop-by-hop reasoning process for question answering. The model dynamically decides which part of an input question should be analyzed at each hop;predicts a relation that corresponds to the current parsed results;utilizes the predicted relation to update the question representation and the state of the reasoning process;and then drives the next-hop reasoning. Experiments show that our model yields state-of-the-art results on two datasets. More interestingly, the model can offer traceable and observable intermediate predictions for reasoning analysis and failure diagnosis, thereby allowing manual manipulation in predicting the final answer. Copyright © 2018, The Authors. All rights reserved.

关键词： Knowledge based systems

Convexification of Neural Graph

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arXiv 2018年

作者： Xiao, Han State Key Lab. of Intelligent Technology and Systems National Lab. for Information Science and Technology Dept. of Computer Science and Technology Tsinghua University Beijing100084 China

Traditionally, most complex intelligence architectures are extremely non-convex, which could not be well performed by convex optimization. However, this paper decomposes complex structures into three types of nodes: operators, algorithms and functions. Iteratively, propagating from node to node along edge, we prove that "regarding the tree-structured neural graph, it is nearly convex in each variable, when the other variables are fixed." In fact, the non-convex properties stem from circles and functions, which could be transformed to be convex with our proposed scale mechanism. Experimentally, we justify our theoretical analysis by two practical applications. Copyright © 2018, The Authors. All rights reserved.

关键词： Trees (mathematics)

Research on the dispatch proportion of battery capacity in photovoltaic primary frequency control

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Research on the dispatch proportion of battery capacity in p...

IEEE Conference on Energy Internet and Energy system Integration (EI2)

作者： Zhijun Han Gang Luo Xinrui Song Caiming Yang Lizong Zhang Yanbing Jia Zhou Zhao Yuanwen Jin State Grid Zhejiang Power Co. Ltd. Hangzhou China State Grid Shaoxing Power Supply Company Shaoxing China Shanxi Key Lab. of Power System Operation and Control Taiyuan University of Technology Taiyuan China Shaoxing Jianyuan Power Group Co. Ltd. Shaoxing China

ISBN: (数字)9781728131375

ISBN: (纸本)9781728131382

It is an inevitable problem of frequency control with the increasing capacity of PV connected into large-scale grid. In order to resolve the problem of the contradiction between the increasing demand and dressing supply capacity of frequency control, the requirement of relevant technical for PV to take part in primary frequency control is put forward. The battery-assisted frequency control system is introduced, and the primary frequency control effect can be improved by using its fast response characteristic. In this paper, the ratio of battery output to all power output is used to analyze the primary frequency control gain of the battery participating in the frequency control of the PV plant. The simulation results show that the larger proportion of energy storage system output can bring better frequency control capacity, reduce frequency fluctuations and improve system stability.

关键词： Frequency control Batteries Photovoltaic systems Generators

Combination Effect of Cation Vacancies and O2 Adsorption on Ferromagnetism of Na0.5Bi0.5TiO3（100） Surface:ab initio Study

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Chinese Journal of Chemical Physics 2018年第2期31卷 177-183,245页

作者： Lin Ju Ying Dai Tong-shuai Xu Yong-jia Zhang Li Sun School of Physics and Electric Engineering Anyang Normal University Anyang 455000 China School of Physics State Key Laboratory of Crystal Materials Shandong University Jinan 250100 China Key Lab of Advanced Transducers and Intelligent Control System Ministry of Education Taiyuan University of Technology Taiyuan 030024 China

The combination effect of cation vacancies and O2 adsorption on ferromagnetism of Na0.5Bi0.5TiO3（100） surface is studied by using density functional theory. An ideal Na0.5Bi0.5TiO3（100） surface is non-magnetic and the cation vacancy could induce the magnetism. By comparing the formation energies for Na, Bi and Ti vacancy, the Na vacancy is more stable than the others. Therefore, we focus on the configuration and electric structure for the system of O2 molecule adsorption on the Na0.5Bi0.5TiO3（100） surface with a Na vacancy. Among the five physisorption configurations we considered, the most likely adsorption position is Na vacancy. The O2 adsorption enhances the magnetism of the system. The contribution of spin polarization is mainly from the O 2p orbitals. The characteristics of exchange coupling are also calculated, which show that the ferromagnetic coupling is favorable. Compared with the previous calculation results, our calculations could explain the room-temperature ferromagnetism of Na0.5Bi0.5TiO3 nanocrytalline powders more reasonably, because of taking into account adsorbed oxygen and cation vacancies. Moreover, our results also show that adsorption of O2 molecule as well as introduction of cation vacancies may be a promising approach to improve multiferroic materials.

关键词： O2 adsorption Cation vacancies Ferromagnetism First-principles calculation

POSTER: STAR (Space-Time Adaptive and Reductive) Algorithms for Real-World Space-Time Optimality

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ACM SIGPLAN Notices 2017年第8期52卷 455-456页

作者： Tang, Yuan You, Ronghui School of Computer Science School of Software Fudan University Shanghai Key Lab. of Intelligent Information Processing State Key Lab. of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences China

It's important to hit a space-time balance for a real-world algorithm to achieve high performance on modern shared-memory multi-core or many-core systems. However, a large class of dynamic programs with more than $O(1)$ dependency achieve optimality either in space or time, but not both. In the literature, the problem is known as the fundamental space-time tradeoff. By exploiting properly on the runtime system, we show that our STAR (Space-Time Adaptive and Reductive) technique can help these dynamic programs to achieve sublinear parallel time bounds while still maintaining work-, space-, and cache-optimality in a processor- and cache-oblivious fashion. © 2017 ACM.

关键词： Real time systems

Relation mention extraction from noisy data with hierarchical reinforcement learning

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arXiv 2018年

作者： Feng, Jun Huang, Minlie Zhang, Yijie Yang, Yang Zhu, Xiaoyan State Key Lab. of Intelligent Technology and Systems National Lab. for Information Science and Technology Dept. of Computer Science and Technology Tsinghua University Beijing100084 China College of Computer Science and Technology Zhejiang University

In this paper we address a task of relation mention extraction from noisy data: extracting representative phrases for a particular relation from noisy sentences that are collected via distant supervision. Despite its significance and value in many downstream applications, this task is less studied on noisy data. The major challenges exists in 1) the lack of annotation on mention phrases, and more severely, 2) handling noisy sentences which do not express a relation at all. To address the two challenges, we formulate the task as a semi-Markov decision process and propose a novel hierarchical reinforcement learning model. Our model consists of a top-level sentence selector to remove noisy sentences, a low-level mention extractor to extract relation mentions, and a reward estimator to provide signals to guide data denoising and mention extraction without explicit annotations. Experimental results show that our model is effective to extract relation mentions from noisy data. Copyright © 2018, The Authors. All rights reserved.

关键词： Extraction

iSplit LBI: Individualized partial ranking with ties via split LBI

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arXiv 2019年

作者： Xu, Qianqian Sun, Xinwei Yang, Zhiyong Cao, Xiaochun Huang, Qingming Yao, Yuan Key Lab. of Intelligent Information Processing Institute of Computing Technology CAS Microsoft Research Asia State Key Laboratory of Information Security Institute of Information Engineering CAS School of Cyber Security University of Chinese Academy of Sciences School of Computer Science and Tech. University of Chinese Academy of Sciences Key Laboratory of Big Data Mining and Knowledge Management CAS Peng Cheng Laboratory Department of Mathematics Hong Kong University of Science and Technology Hong Kong

Due to the inherent uncertainty of data, the problem of predicting partial ranking from pairwise comparison data with ties has attracted increasing interest in recent years. However, in real-world scenarios, different individuals often hold distinct preferences. It might be misleading to merely look at a global partial ranking while ignoring personal diversity. In this paper, instead of learning a global ranking which is agreed with the consensus, we pursue the tie-aware partial ranking from an individualized perspective. Particularly, we formulate a unified framework which not only can be used for individualized partial ranking prediction, but also be helpful for abnormal user selection. This is realized by a variable splitting-based algorithm called iSplitLBI. Specifically, our algorithm generates a sequence of estimations with a regularization path, where both the hyperparameters and model parameters are updated. At each step of the path, the parameters can be decomposed into three orthogonal parts, namely, abnormal signals, personalized signals and random noise. The abnormal signals can serve the purpose of abnormal user selection, while the abnormal signals and personalized signals together are mainly responsible for individual partial ranking prediction. Extensive experiments on simulated and real-world datasets demonstrate that our new approach significantly outperforms state-of-the-art alternatives. The code is now availiable at https://***/qianqianxu010/ NeurIPS2019-iSplitLBI. Copyright © 2019, The Authors. All rights reserved.

关键词： Forecasting

Ablation characteristics of hybrid target materials for laser triggered vacuum switches

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Ablation characteristics of hybrid target materials for lase...

International Conference on Mechanical, Electric and Industrial Engineering, MEIE 2018

作者： Hui, Chen State Key Laboratory of Advanced Electromagnetic Engineering and Technology Huazhong University of Science and Technology Wuhan Hubei430074 China Hubei Collaborative Innovation Center for High-efficiency Utilization of Solar Energy Hubei University of Technology Wuhan430068 China Hubei Key Lab. for High-efficiency Utiliz. of Solar Ener. and Oper. Control of Energy Storage System Hubei University of Technology Wuhan430068 China

The key difference of laser triggered vacuum switch (LTVS) and electrical triggered vacuum switch (ETVS) is the different triggered way, because the initial plasmas were generated by laser irradiation target material of LTVS, which generates different impact on the triggered characteristics of LTVS with different target materials. There are three laser wavelength (1064nm, 532nm and 266nm) which are tested the triggered characteristics of target materials, with decreased conduction time delay under the condition of increasing laser energy. © Published under licence by IOP Publishing Ltd.

关键词： Hybrid materials

Magnetic Modulation of Terahertz Waves via Spin-Polarized Electron Tunneling Based on Magnetic Tunnel Junctions

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Physical Review Applied 2020年第1期14卷 014032-014032页

作者： Zuanming Jin Jugeng Li Wenjie Zhang Chenyang Guo Caihua Wan Xiufeng Han Zhenxiang Cheng Chao Zhang Alexey V. Balakin Alexander P. Shkurinov Yan Peng Guohong Ma Yiming Zhu Jianquan Yao Songlin Zhuang Terahertz Technology Innovation Research Institute Terahertz Spectrum and Imaging Technology Cooperative Innovation Center Shanghai Key Lab of Modern Optical System University of Shanghai for Science and Technology 516 JunGong Road Shanghai 200093 China Department of Physics Shanghai University 99 Shangda Road Shanghai 200444 China Shanghai Institute of Intelligent Science and Technology Tongji University Shanghai 200092 China Beijing National Laboratory for Condensed Matter Physics Institute of Physics University of Chinese Academy of Sciences Chinese Academy of Sciences Beijing 100190 China Institute for Superconducting and Electronic Materials University of Wollongong Wollongong New South Wales 2500 Australia School of Physics University of Wollongong Wollongong New South Wales 2522 Australia Department of Physics and International Laser Center Lomonosov Moscow State University Leninskie Gory 1 Moscow 19991 Russia STU & SIOM Joint Laboratory for Superintense Lasers and Applications Shanghai 201210 China College of Precision Instrument and Optoelectronics Engineering Tianjin University Tianjin 300110 China

Magnetic tunnel junctions (MTJs) are a key technology in modern spintronics because they are the basis of read-heads of modern hard disk drives, nonvolatile magnetic random access memories, and sensor applications. In this paper, we demonstrate that tunneling magnetoresistance can influence terahertz (THz) wave propagation through a MTJ. In particular, various magnetic configurations between parallel state and antiparallel state of the magnetizations of the ferromagnetic layers in the MTJ have the effect of changing the conductivity, making a functional modulation of the propagating THz electromagnetic fields. Operating in the THz frequency range, a maximal modulation depth of 60% is reached for the parallel state of the MTJ with a thickness of 77.45 nm, using a magnetic field as low as 30 mT. The THz conductivity spectrum of the MTJ is governed by spin-dependent electron tunneling. It is anticipated that the MTJ device and its tunability scheme will have many potential applications in THz magnetic modulators, filtering, and sensing.

关键词： Magnetoresistance Photoconductivity Ultrafast magnetic effects Magnetic tunnel junctions Terahertz time-domain spectroscopy