141 research outputs found
Herding Effect based Attention for Personalized Time-Sync Video Recommendation
Time-sync comment (TSC) is a new form of user-interaction review associated
with real-time video contents, which contains a user's preferences for videos
and therefore well suited as the data source for video recommendations.
However, existing review-based recommendation methods ignore the
context-dependent (generated by user-interaction), real-time, and
time-sensitive properties of TSC data. To bridge the above gaps, in this paper,
we use video images and users' TSCs to design an Image-Text Fusion model with a
novel Herding Effect Attention mechanism (called ITF-HEA), which can predict
users' favorite videos with model-based collaborative filtering. Specifically,
in the HEA mechanism, we weight the context information based on the semantic
similarities and time intervals between each TSC and its context, thereby
considering influences of the herding effect in the model. Experiments show
that ITF-HEA is on average 3.78\% higher than the state-of-the-art method upon
F1-score in baselines.Comment: ACCEPTED for ORAL presentation at IEEE ICME 201
Non-communicable diseases sustained high call: China's health care model should be transformed as soon as possible
Background: There is sufficient evidence that the prevalence of non-communicable diseases (NCDs) in China is increasing rapidly. Results from the Fourth China National Health Services Survey (2008) show that compared to 2003, the prevalence of chronic diseases in China increased by 5%, while results from the Fifth National Health Services Survey (2013) showed an increase of 9% since 2008. As the world's most populous country and in the face of the rapid rise of non-communicable diseases, China lacks effective measures to achieve significant results on aspects of tobacco use, unhealthy diet, lack of exercise, harmful alcohol use and other risk factors. Of more concern is that the Chinese health care model is still stuck in the "medical services" stage. The "therapy" of health care models not only cause China to experience high health costs - there is also a steady increase in adverse health outcomes, with a failure to timely and effectively respond to the challenges of NCDs. Purpose: This article aims to analyze health care inputs and outputs since Chinese health care reform, and to provide a useful reference to improve Chinese future health care policies
Consensus seeking in multi-agent systems with an active leader and communication delays
summary:In this paper, we consider a multi-agent consensus problem with an active leader and variable interconnection topology. The dynamics of the active leader is given in a general form of linear system. The switching interconnection topology with communication delay among the agents is taken into consideration. A neighbor-based estimator is designed for each agent to obtain the unmeasurable state variables of the dynamic leader, and then a distributed feedback control law is developed to achieve consensus. The feedback parameters are obtained by solving a Riccati equation. By constructing a common Lyapunov function, some sufficient conditions are established to guarantee that each agent can track the active leader by assumption that interconnection topology is undirected and connected. We also point out that some results can be generalized to a class of directed interaction topologies. Moreover, the input-to-state stability (ISS) is obtained for multi-agent system with variable interconnection topology and communication delays in a disturbed environment
Prototypical Kernel Learning and Open-set Foreground Perception for Generalized Few-shot Semantic Segmentation
Generalized Few-shot Semantic Segmentation (GFSS) extends Few-shot Semantic
Segmentation (FSS) to simultaneously segment unseen classes and seen classes
during evaluation. Previous works leverage additional branch or prototypical
aggregation to eliminate the constrained setting of FSS. However,
representation division and embedding prejudice, which heavily results in poor
performance of GFSS, have not been synthetical considered. We address the
aforementioned problems by jointing the prototypical kernel learning and
open-set foreground perception. Specifically, a group of learnable kernels is
proposed to perform segmentation with each kernel in charge of a stuff class.
Then, we explore to merge the prototypical learning to the update of base-class
kernels, which is consistent with the prototype knowledge aggregation of
few-shot novel classes. In addition, a foreground contextual perception module
cooperating with conditional bias based inference is adopted to perform
class-agnostic as well as open-set foreground detection, thus to mitigate the
embedding prejudice and prevent novel targets from being misclassified as
background. Moreover, we also adjust our method to the Class Incremental
Few-shot Semantic Segmentation (CIFSS) which takes the knowledge of novel
classes in a incremental stream. Extensive experiments on PASCAL-5i and
COCO-20i datasets demonstrate that our method performs better than previous
state-of-the-art.Comment: Accepted by ICCV202
MATMPC - A MATLAB Based Toolbox for Real-time Nonlinear Model Predictive Control
In this paper we introduce MATMPC, an open source software built in MATLAB
for nonlinear model predictive control (NMPC). It is designed to facilitate
modelling, controller design and simulation for a wide class of NMPC
applications. MATMPC has a number of algorithmic modules, including automatic
differentiation, direct multiple shooting, condensing, linear quadratic program
(QP) solver and globalization. It also supports a unique Curvature-like Measure
of Nonlinearity (CMoN) MPC algorithm. MATMPC has been designed to provide
state-of-the-art performance while making the prototyping easy, also with
limited programming knowledge. This is achieved by writing each module directly
in MATLAB API for C. As a result, MATMPC modules can be compiled into MEX
functions with performance comparable to plain C/C++ solvers. MATMPC has been
successfully used in operating systems including WINDOWS, LINUX AND OS X.
Selected examples are shown to highlight the effectiveness of MATMPC
Cystatin C and risk of new-onset depressive symptoms among individuals with a normal creatinine-based estimated glomerular filtration rate: A prospective cohort study
The association between cystatin C and depressive symptoms in the general population has not been thoroughly elucidated to date. We investigated the association of cystatin C with new-onset depressive symptoms among individuals with normal creatinine-based estimated glomerular filtration rates (eGFR). In the China Health and Retirement Longitudinal Study, 5111 participants without depressive symptoms or renal dysfunction (eGFR \u3c 60 ml/min/1.73
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