322 research outputs found
Hybrid Tractable Classes of Binary Quantified Constraint Satisfaction Problems
In this paper, we investigate the hybrid tractability of binary Quantified
Constraint Satisfaction Problems (QCSPs). First, a basic tractable class of
binary QCSPs is identified by using the broken-triangle property. In this
class, the variable ordering for the broken-triangle property must be same as
that in the prefix of the QCSP. Second, we break this restriction to allow that
existentially quantified variables can be shifted within or out of their
blocks, and thus identify some novel tractable classes by introducing the
broken-angle property. Finally, we identify a more generalized tractable class,
i.e., the min-of-max extendable class for QCSPs
Population Density-based Hospital Recommendation with Mobile LBS Big Data
The difficulty of getting medical treatment is one of major livelihood issues
in China. Since patients lack prior knowledge about the spatial distribution
and the capacity of hospitals, some hospitals have abnormally high or sporadic
population densities. This paper presents a new model for estimating the
spatiotemporal population density in each hospital based on location-based
service (LBS) big data, which would be beneficial to guiding and dispersing
outpatients. To improve the estimation accuracy, several approaches are
proposed to denoise the LBS data and classify people by detecting their various
behaviors. In addition, a long short-term memory (LSTM) based deep learning is
presented to predict the trend of population density. By using Baidu
large-scale LBS logs database, we apply the proposed model to 113 hospitals in
Beijing, P. R. China, and constructed an online hospital recommendation system
which can provide users with a hospital rank list basing the real-time
population density information and the hospitals' basic information such as
hospitals' levels and their distances. We also mine several interesting
patterns from these LBS logs by using our proposed system
Positive Steady State Solutions of a Diffusive Leslie-Gower Predator-Prey Model with Holling Type II Functional Response and Cross-Diffusion
In this paper we consider a diffusive Leslie Gower predator prey model with Holling type II functional response and cross-diffusion under zero Dirichlet boundary condition. By using topological degree theory, bifurcation theory, energy estimates and asymptotic behavior analysis, we prove the existence, uniqueness and multiplicity of positive steady states solutions under certain conditions on the parameters
LS-DTKMS: A Local Search Algorithm for Diversified Top-k MaxSAT Problem
The Maximum Satisfiability (MaxSAT), an important optimization problem, has a range of applications, including network routing, planning and scheduling, and combinatorial auctions. Among these applications, one usually benefits from having not just one single solution, but k diverse solutions. Motivated by this, we study an extension of MaxSAT, named Diversified Top-k MaxSAT (DTKMS) problem, which is to find k feasible assignments of a given formula such that each assignment satisfies all hard clauses and all of them together satisfy the maximum number of soft clauses. This paper presents a local search algorithm, LS-DTKMS, for DTKMS problem, which exploits novel scoring functions to select variables and assignments. Experiments demonstrate that LS-DTKMS outperforms the top-k MaxSAT based DTKMS solvers and state-of-the-art solvers for diversified top-k clique problem
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