20,713 research outputs found
Learning the Joint Representation of Heterogeneous Temporal Events for Clinical Endpoint Prediction
The availability of a large amount of electronic health records (EHR)
provides huge opportunities to improve health care service by mining these
data. One important application is clinical endpoint prediction, which aims to
predict whether a disease, a symptom or an abnormal lab test will happen in the
future according to patients' history records. This paper develops deep
learning techniques for clinical endpoint prediction, which are effective in
many practical applications. However, the problem is very challenging since
patients' history records contain multiple heterogeneous temporal events such
as lab tests, diagnosis, and drug administrations. The visiting patterns of
different types of events vary significantly, and there exist complex nonlinear
relationships between different events. In this paper, we propose a novel model
for learning the joint representation of heterogeneous temporal events. The
model adds a new gate to control the visiting rates of different events which
effectively models the irregular patterns of different events and their
nonlinear correlations. Experiment results with real-world clinical data on the
tasks of predicting death and abnormal lab tests prove the effectiveness of our
proposed approach over competitive baselines.Comment: 8 pages, this paper has been accepted by AAAI 201
Physical properties of CO-dark molecular gas traced by C
Neither HI nor CO emission can reveal a significant quantity of so-called
dark gas in the interstellar medium (ISM). It is considered that CO-dark
molecular gas (DMG), the molecular gas with no or weak CO emission, dominates
dark gas. We identified 36 DMG clouds with C emission (data from Galactic
Observations of Terahertz C+ (GOT C+) project) and HINSA features. Based on
uncertainty analysis, optical depth of HI of 1 is a reasonable
value for most clouds. With the assumption of , these clouds
were characterized by excitation temperatures in a range of 20 K to 92 K with a
median value of 55 K and volume densities in the range of
cm to cm with a median value of
cm. The fraction of DMG column density in the cloud ()
decreases with increasing excitation temperature following an empirical
relation +1.0. The relation
between and total hydrogen column density is given by
=. The values of in the
clouds of low extinction group ( mag) are consistent with the
results of the time-dependent, chemical evolutionary model at the age of ~ 10
Myr. Our empirical relation cannot be explained by the chemical evolutionary
model for clouds in the high extinction group ( mag). Compared to
clouds in the low extinction group ( mag), clouds in the high
extinction group ( mag) have comparable volume densities but
excitation temperatures that are 1.5 times lower. Moreover, CO abundances in
clouds of the high extinction group ( mag) are
times smaller than the canonical value in the Milky Way. #[Full version of
abstract is shown in the text.]#Comment: Accepted for publishing in Astronomy & Astrophysics. 13 pages, 8
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Event-triggered distributed H∞ state estimation with packet dropouts through sensor networks
This study is concerned with the event-triggered distributed H∞ state estimation problem for a class of discrete-time stochastic non-linear systems with packet dropouts in a sensor network. An event-triggered communication mechanism is adopted over the sensor network with hope to reduce the communication burden and the energy consumption, where the measurements on each sensor are transmitted only when a certain triggering condition is violated. Furthermore, a novel distributed state estimator is designed where the available innovations are not only from the individual sensor, but also from its neighbouring ones according to the given topology. The purpose of the problem under consideration is to design a set of distributed state estimators such that the dynamics of estimation errors is exponentially mean-square stable and also the prespecified H∞ disturbance rejection attenuation level is guaranteed. By utilising the property of the Kronecker product and the stochastic analysis approaches, sufficient conditions are established under which the addressed state estimation problem is recast as a convex optimisation one that can be easily solved via available software packages. Finally, a simulation example is utilised to illustrate the usefulness of the proposed design scheme of event-triggered distributed state estimators.This work was supported in part by Royal Society of the UK, the National Natural Science Foundation of China under Grants 61329301, 61203139, 61473076, 61374127 and 61422301, the Shanghai Rising-Star Program of China under Grant 13QA1400100, the ShuGuang project of Shanghai Municipal Education Commission and Shanghai Education Development Foundation under Grant 13SG34, the Fundamental Research Funds for the Central Universities, DHU Distinguished Young Professor Program, and the Alexander von Humboldt Foundation of Germany
Interval Estimation Methods for Discrete-Time Linear Time-Invariant Systems
International audienc
Can Marketization Improve Sustainable Development in Northeastern China? Evidence from the Perspective of Coupling Coordination Degree Model
With the acquisition of sustainable development, pursuing the coordinated development of social economy and ecological environment has been a critical approach of Northeastern China. Since the reform and opening-up, marketization has profoundly affected the regional social economy. However, what role will marketization play in regional sustainable development? Can marketization improve sustainable development measured by the coupling coordination degree? This paper adopts the coupling coordination degree model (CCDM) to estimate the coupling coordination degree and further explore the impact of marketization on the coupling coordination degree in Northeastern China from 1994 to 2019. The results show that the average values of the static coupling degree (SCD), dynamic coupling degree (DCD), and coupling coordination degree (CCD) remained in a tiny coordinated state, which indicated that the level of sustainable development in Northeastern China is presented still primary from 1990 to 2019. Marketization has a significant negative impact on the coupling coordination degree, which indicates that marketization should be considered in the process of sustainable development in Northeastern China
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