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| 1 | RNN-Based Demand Awareness in Smart Library Using CRFID显示文摘To provide more intelligence service in the smart library, we need to better perceive the reader’s preferences. In addition to perceiving online records based on readers’ search history and borrowing records, advanced information technologies give us more chance to perceive the behavior of readers in the actual reading process and further discover the need for reading. In this paper, we use CRFID and RNN deep learning network to recognize book motions in the reading process, so as to judge readers’ need degree for the book, which can provide a basis for library book purchases and readers personalized service. In order to improve the recognition accuracy, we use the RSS as well as acceleration magnitude gathered from CRFID as the input data for RNN, and design a new encoding scheme. We trained and tested the deep learning network using real-world data, recorded during actual reading in our lab environment which mimics a typical reading room, from the experimental results, we conclude that our approach is feasible to recognize different reading phase to perceiving the needs of the readers. | Ruiqin Bai Jumin Zhao Dengao Li Xiaoyu Lv Qiang Wang Biaokai Zhu | 2020 | China Communications2020，17，5： | 7 |
| 2 | Dark matter direct search sensitivity of the PandaX-4T experiment显示文摘The Panda X-4T experiment, a 4-ton scale dark matter direct detection experiment, is being planned at the China Jinping Underground Laboratory. In this paper we present a simulation study of the expected background in this experiment. In a 2.8-ton fiducial mass and the signal region between 1-10 keV electron equivalent energy, the total electron recoil background is found to be 4.9 × 10^(-5) kg^(-1) d^(-1) keV^(-1). The nuclear recoil background in the same region is 2.8 × 10^(-7) kg^(-1) d^(-1) keV^(-1). With an exposure of 5.6 ton-years, the sensitivity of Panda X-4 T could reach a minimum spin-independent dark matter-nucleon cross section of 6 × 10^(-48) cm^2 at a dark matter mass of 40 Ge V/c^2. | HongGuang Zhang Abdusalam Abdukerim Wei Chen Xun Chen YunHua Chen XiangYi Cui BinBin Dong DeQing Fang ChangBo Fu Karl Giboni Franco Giuliani LinHui Gu XuYuan Guo ZhiFan Guo Ke Han ChangDa He ShengMing He Di Huang XingTao Huang Zhou Huang Peng Ji XiangDong Ji YongLin Ju ShaoLi Li Yao Li Heng Lin HuaXuan Liu JiangLai Liu YuGang Ma YaJun Mao KaiXiang Ni JinHua Ning XiangXiang Ren Fang Shi AnDi Tan AnQing Wang Cheng Wang HongWei Wang Meng Wang QiuHong Wang SiGuang Wang XiuLi Wang XuMing Wang Zhou Wang MengMeng Wu ShiYong Wu JingKai Xia MengJiao Xiao PengWei Xie BinBin Yan JiJun Yang Yong Yang ChunXu Yu JuMin Yuan JianFeng Yue Dan Zhang Tao Zhang Li Zhao QiBin Zheng JiFang Zhou Ning Zhou XiaoPeng Zhou | 2019 | Science China(Physics,Mechanics & Astronomy)2019，62，3： | 6 |
| 3 | An Improved Space-Time Joint Anti-jamming Algorithm Based on Variable Step LMS显示文摘In wireless communication,the space-time anti-jamming method is widely applied because it shows better performance than the pure airspace and pure temporal anti-jamming methods.However,its application is limited by its computational complexity,and it cannot suppress narrowband interference that is in the same direction as the navigation signal.To solve these problems,we propose improved frequency filter to filter the narrowband interference from the desired signal direction in advance,meanwhile,an improved variable step Least Mean Square(LMS) method is proposed to complete the space-time array weights with fast iteration,thereby reducing computational complexity.The simulation results show that,compared with conventional methods,the anti-jamming capability of the proposed algorithm is significantly enhanced; and its complexity is significantly reduced. | Dengao Li Jinqiang Liu Jumin Zhao Gang Wu Xiaofang Zhao | 2017 | Tsinghua Science and Technology2017，22，5： | 2 |
| 4 | Optimal Data Transmission in Backscatter Communication for Passive Sensing Systems显示文摘Computational Radio Frequency IDentification (CRFID) is a device that integrates passive sensing and computing applications,which is powered by electromagnetic waves and read by the off-the-shelf Ultra High Frequency Radio Frequency IDentification (UHF RFID) readers.Traditional RFID only identifies the ID of the tag,and CRFID is different from traditional RFID.CRFID needs to transmit a large amount of sensing and computing data in the mobile sensing scene.However,the current Electronic Product Code,Class-1 Generation-2 (EPC C1G2)protocol mainly aims at the transmission of multi-tag and minor data.When a large amount of data need to be fed back,a more reliable communication mechanism must be used to ensure the efficiency of data exchange.The main strategy of this paper is to adjust the data frame length of the CRFID response dynamically to improve the efficiency and reliability of CRFID backscattering communication according to energy acquisition and channel complexity.This is done by constructing a dynamic data frame length model and optimizing the command set of the interface protocol.Then,according to the actual situation of the uplink,a dynamic data validation method is designed,which reduces the data transmission delay and the probability of retransmitting,and improves the throughput.The simulation results show that the proposed scheme is superior to the existing methods.Under different energy harvesting and channel conditions,the dynamic data frame length and verification method can approach the theoretical optimum. | Jumin Zhao Ji Li Dengao Li Haizhu Yang | 2020 | Tsinghua Science and Technology2020，25，5： | 2 |
| 5 | Mineralogical and compositional characteristics of Late Permian coals from an area of high lung cancer rate in Xuan Wei, Yunnan, China: Occurrence and origin of quartz and chamosite显示文摘 | Shifeng Dai Linwei Tian Chen-Lin Chou Yiping Zhou Mingquan Zhang Lei Zhao Jumin Wang Zong Yang Hongzhi Cao Deyi Ren | 2008 | International Journal of Coal Geology2008，，4： | 1 |
| 6 | An improved evaluation of the neutron background in the PandaX-Ⅱ experiment显示文摘In dark matter direct detection experiments,neutron is a serious source of background,which can mimic the dark matter-nucleus scattering signals.In this paper,we present an improved evaluation of the neutron background in the PandaX-II dark matter experiment by a novel approach.Instead of fully relying on the Monte Carlo simulation,the overall neutron background is determined from the neutron-induced high energy signals in the data.In addition,the probability of producing a dark-matter-like background per neutron is evaluated with a complete Monte Carlo generator,where the correlated emission of neutron(s)andγ(s)in the(α,n)reactions and spontaneous fissions is taken into consideration.With this method,the neutron backgrounds in the Run 9(26-ton-day)and Run 10(28-ton-day)data sets of PandaX-II are estimated to be(0.66±0.24)and(0.47±0.25)events,respectively. | QiuHong Wang Abdusalam Abdukerim Wei Chen Xun Chen YunHua Chen XiangYi Cui YingJie Fan DeQing Fang ChangBo Fu LiSheng Geng Karl Giboni Franco Giuliani LinHui Gu XuYuan Guo Ke Han ChangDa He Di Huang Yan Huang YanLin Huang Zhou Huang Peng Ji XiangDong Ji YongLin Ju YiHui Lai Kun Liang HuaXuan Liu JiangLai Liu WenBo Ma YuGang Ma YaJun Mao Yue Meng Parinya Namwongsa KaiXiang Ni JinHua Ning XuYang Ning XiangXiang Ren ChangSong Shang Lin Si AnDi Tan AnQing Wang HongWei Wang Meng Wang SiGuang Wang XiuLi Wang Zhou Wang MengMeng Wu ShiYong Wu JingKai Xia MengJiao Xiao PengWei Xie BinBin Yan JiJun Yang Yong Yang ChunXu Yu Jumin Yuan Dan Zhang HongGuang Zhang Tao Zhang Li Zhao QiBin Zheng JiFang Zhou Ning Zhou XiaoPeng Zhou | 2020 | Science China(Physics,Mechanics & Astronomy)2020，63，3： | 0 |
| 7 | Constraining self-interacting dark matter with the full dataset of PandaX-II显示文摘Self-interacting dark matter(SIDM)is a leading candidate proposed to solve discrepancies between predictions of the prevailing cold dark matter theory and observations of galaxies.Many SIDM models predict the existence of a light force carrier that mediates strong dark matter self-interactions.If the mediator couples to the standard model particles,it could produce characteristic signals in dark matter direct detection experiments.We report searches for signals of SIDM models with a light mediator using the full dataset of the PandaX-II experiment,basing on a total exposure of 132 tonne-days.No significant excess over background is found,and our likelihood analysis leads to a strong upper limit on the dark matter-nucleon coupling strength.We further combine the PandaX-II constraints and those from observations of the light element abundances in the early universe,and show that direct detection and cosmological probes can provide complementary constraints on dark matter models with a light mediator. | Jijun Yang Abdusalam Abdukerim Wei Chen Xun Chen Yunhua Chen Chen Cheng Xiangyi Cui Yingjie Fan Deqing Fang Changbo Fu Mengting Fu Lisheng Geng Karl Giboni Linhui Gu Xuyuan Guo Ke Han Changda He Shengming He Di Huang Yan Huang Ran Huo Yanlin Huang Zhou Huang Xiangdong Ji Yonglin Ju Shuaijie Li Qing Lin Huaxuan Liu Jianglai Liu Xiaoying Lu Wenbo Ma Yugang Ma Yajun Mao Yue Meng Nasir Shaheed Kaixiang Ni Jinhua Ning Xuyang Ning Xiangxiang Ren Changsong Shang Guofang Shen Lin Si Andi Tan Anqing Wang Hongwei Wang Meng Wang QiuHong Wang Siguang Wang Wei Wang Xiuli Wang Zhou Wang Mengmeng Wu Shiyong Wu Weihao Wu Jingkai Xia Mengjiao Xiao Xiang Xiao Pengwei Xie Binbin Yan Yong Yang Chunxu Yu Hai-Bo Yu Jumin Yuan Ying Yuan Xinning Zeng Dan Zhang Tao Zhang Li Zhao Qibin Zheng Jifang Zhou Ning Zhou Xiaopeng Zhou | 2021 | Science China(Physics,Mechanics & Astronomy)2021，64，11： | 0 |
| 8 | Determination of Double Beta Decay Half-Life of 136Xe with the PandaX-4T Natural Xenon Detector显示文摘Precise measurement of two-neutrino double beta decay(DBD)half-life is an important step for the searches of Majorana neutrinos with neutrinoless double beta decay.We report the measurement of DBD half-life of 136xe using the Pandax-4T dual-phase Time Projection Chamber(TPC)with 3.7-tonne natural xenon and the first 94.9-day physics data release. | Lin Si Zhaokan Cheng Abdusalam Abdukerim Zihao Bo Wei Chen Xun Chen Yunhua Chen Chen Cheng Yunshan Cheng Xiangyi Cui Yingjie Fan Deqing Fang Changbo Fu Mengting Fu Lisheng Geng Karl Giboni Linhui Gu Xuyuan Guo Ke Han Changda He Jinrong He Di Huang Yanlin Huang Zhou Huang Ruquan Hou Xiangdong Ji Yonglin Ju Chenxiang Li Jiafu Li Mingchuan Li Shu Li Shuaijie Li Qing Lin Jianglai Liu Xiaoying Lu Lingyin Luo Yunyang Luo Wenbo Ma Yugang Ma Yujun Mao Yue Meng Nasir Shaheed Xiaofeng Shang Xuyang Ning Ningchun Qi Zhicheng Qian Xiangxiang Ren Changsong Shang Guofang Shen Wenliang Sun Andi Tan Yi Tao Anqing Wang Meng Wang Qiuhong Wang Shaobo Wang Siguang Wang Wei Wang Xiuli Wang Zhou Wang Yuehuan Wei Mengmeng Wu Weihao Wu Jingkai Xia Mengjiao Xiao Xiang Xiao Pengwei Xie Binbin Yan Xiyu Yan Yong Yang Chunxu Yu Jumin Yuan Ying Yuan Zhe Yuan Dan Zhang Minzhen Zhang Peng Zhang Shibo Zhang Shu Zhang Tao Zhang Li Zhao Qibin Zheng Jifang Zhou Ning Zhou Xiaopeng Zhou Yong Zhou | 2023 | Research2023，，2： | 0 |
| 9 | KTI-RNN:Recognition of Heart Failure from Clinical Notes显示文摘Although deep learning methods have recently attracted considerable attention in the medical field,analyzing large-scale electronic health record data is still a difficult task.In particular,the accurate recognition of heart failure is a key technology for doctors to make reasonable treatment decisions.This study uses data from the Medical Information Mart for Intensive Care database.Compared with structured data,unstructured data contain abundant patient information.However,this type of data has unsatisfactory characteristics,e.g.,many colloquial vocabularies and sparse content.To solve these problems,we propose the KTI-RNN model for unstructured data recognition.The proposed model overcomes sparse content and obtains good classification results.The term frequency-inverse word frequency(TF-IWF)model is used to extract the keyword set.The latent dirichlet allocation(LDA)model is adopted to extract the topic word set.These models enable the expansion of the medical record text content.Finally,we embed the global attention mechanism and gating mechanism between the bidirectional recurrent neural network(BiRNN)model and the output layer.We call it gated-attention-BiRNN(GA-BiRNN)and use it to identify heart failure from extensive medical texts.Results show that the F 1 score of the proposed KTI-RNN model is 85.57%,and the accuracy rate of the proposed KTI-RNN model is 85.59%. | Dengao Li Huiting Ma Wenjing Li Baofeng Zhao Jumin Zhao Yi Liu Jian Fu | 2023 | Tsinghua Science and Technology2023，28，1： | 0 |
| 10 | IQABC-Based Hybrid Deployment Algorithm for Mobile Robotic Agents Providing Network Coverage显示文摘Working as aerial base stations,mobile robotic agents can be formed as a wireless robotic network to provide network services for on-ground mobile devices in a target area.Herein,a challenging issue is how to deploy these mobile robotic agents to provide network services with good quality for more users,while considering the mobility of on-ground devices.In this paper,to solve this issue,we decouple the coverage problem into the vertical dimension and the horizontal dimension without any loss of optimization and introduce the network coverage model with maximum coverage range.Then,we propose a hybrid deployment algorithm based on the improved quick artificial bee colony.The algorithm is composed of a centralized deployment algorithm and a distributed one.The proposed deployment algorithm deploy a given number of mobile robotic agents to provide network services for the on-ground devices that are independent and identically distributed.Simulation results have demonstrated that the proposed algorithm deploys agents appropriately to cover more ground area and provide better coverage uniformity. | Shuang Xu Xiaojie Liu Dengao Li Jumin Zhao | 2024 | Tsinghua Science and Technology2024，29，2： | 0 |
| 11 | Intra-Patient and Inter-Patient Multi-Classification of Severe Cardiovascular Diseases Based on CResFormer显示文摘Severe cardiovascular diseases can rapidly lead to death.At present,most studies in the deep learning field using electrocardiogram(ECG)are performed on intra-patient experiments for the classification of coronary artery disease(CAD),myocardial infarction,and congestive heart failure(CHF).By contrast,actual conditions are inter-patient experiments.In this study,we proposed a deep learning network,namely,CResFormer,with dual feature extraction to improve accuracy in classifying such diseases.First,fixed segmentation of dual-lead ECG signals without preprocessing was used as input data.Second,one-dimensional convolutional layers performed moderate dimensionality reduction to accommodate subsequent feature extraction.Then,ResNet residual network block layers and transformer encoder layers sequentially performed feature extraction to obtain key associated abstract features.Finally,the Softmax function was used for classifications.Notably,the focal loss function is used when dealing with unbalanced datasets.The average accuracy,sensitivity,positive predictive value,and specificity of four classifications of severe cardiovascular diseases are 99.84%,99.68%,99.71%,and 99.90%in intra-patient experiments,respectively,and 97.48%,93.54%,96.30%,and 97.89%in inter-patient experiments,respectively.In addition,the model performs well in unbalanced datasets and shows good noise robustness.Therefore,the model has great application potential in diagnosing CAD,MI,and CHF in the actual clinical environment. | Dengao Li Changcheng Shi Jumin Zhao Yi Liu Chunxia Li | 2023 | Tsinghua Science and Technology2023，28，2： | 0 |
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