350 research outputs found
Two Cases of Dermatitis Herpetiformis Successfully Treated with Tetracycline and Niacinamide
No abstract available.</p
Two Cases of Dermatitis Herpetiformis Successfully Treated with Tetracycline and Niacinamide
No abstract available.</p
Vector Autoregressive Evolution for Dynamic Multi-Objective Optimisation
Dynamic multi-objective optimisation (DMO) handles optimisation problems with
multiple (often conflicting) objectives in varying environments. Such problems
pose various challenges to evolutionary algorithms, which have popularly been
used to solve complex optimisation problems, due to their dynamic nature and
resource restrictions in changing environments. This paper proposes vector
autoregressive evolution (VARE) consisting of vector autoregression (VAR) and
environment-aware hypermutation to address environmental changes in DMO. VARE
builds a VAR model that considers mutual relationship between decision
variables to effectively predict the moving solutions in dynamic environments.
Additionally, VARE introduces EAH to address the blindness of existing
hypermutation strategies in increasing population diversity in dynamic
scenarios where predictive approaches are unsuitable. A seamless integration of
VAR and EAH in an environment-adaptive manner makes VARE effective to handle a
wide range of dynamic environments and competitive with several popular DMO
algorithms, as demonstrated in extensive experimental studies. Specially, the
proposed algorithm is computationally 50 times faster than two widely-used
algorithms (i.e., TrDMOEA and MOEA/D-SVR) while producing significantly better
results
Dissipation induced extended-localized transition
Mobility edge (ME), representing the critical energy that distinguishes
between extended and localized states, is a key concept in understanding the
transition between extended (metallic) and localized (insulating) states in
disordered and quasiperiodic systems. Here we explore the impact of dissipation
on a quasiperiodic system featuring MEs by calculating steady-state density
matrix and analyzing quench dynamics with sudden introduction of dissipation,
and demonstrate that dissipation can lead the system into specific states
predominantly characterized by either extended or localized states,
irrespective of the initial state. Our results establish the use of dissipation
as a new avenue for inducing transitions between extended and localized states,
and for manipulating dynamic behaviors of particles
Handling Dynamic Multiobjective Optimization Environments via Layered Prediction and Subspace-Based Diversity Maintenance
Peer reviewedPostprin
Achievable Diversity Order of HARQ-Aided Downlink NOMA Systems
The combination between non-orthogonal multiple access (NOMA) and hybrid
automatic repeat request (HARQ) is capable of realizing ultra-reliability, high
throughput and many concurrent connections particularly for emerging
communication systems. This paper focuses on characterizing the asymptotic
scaling law of the outage probability of HARQ-aided NOMA systems with respect
to the transmit power, i.e., diversity order. The analysis of diversity order
is carried out for three basic types of HARQ-aided downlink NOMA systems,
including Type I HARQ, HARQ with chase combining (HARQ-CC) and HARQ with
incremental redundancy (HARQ-IR). The diversity orders of three HARQ-aided
downlink NOMA systems are derived in closed-form, where an integration domain
partition trick is developed to obtain the bounds of the outage probability
specially for HARQ-CC and HARQ-IR-aided NOMA systems. The analytical results
show that the diversity order is a decreasing step function of transmission
rate, and full time diversity can only be achieved under a sufficiently low
transmission rate. It is also revealed that HARQ-IR-aided NOMA systems have the
largest diversity order, followed by HARQ-CC-aided and then Type I HARQ-aided
NOMA systems. Additionally, the users' diversity orders follow a descending
order according to their respective average channel gains. Furthermore, we
expand discussions on the cases of power-efficient transmissions and imperfect
channel state information (CSI). Monte Carlo simulations finally confirm our
analysis
A many-objective evolutionary algorithm based on rotated grid
Evolutionary optimization algorithms, a meta-heuristic approach, often encounter considerable challenges in many-objective optimization problems (MaOPs). The Pareto-based dominance loses its effectiveness in MaOPs, which are defined as having more than three objectives. Therefore, a more valid selection method is proposed to balance convergence and distribution. This paper proposes an algorithm using rotary grid technology to solve MaOPs (denoted by RGridEA). The algorithm uses the rotating grid to partition the objective space. Instead of using the Pareto non-dominated sorting strategy to layer the population a novel stratified method is used to enhance convergence effectively and make use of the grid to improve distribution and uniformity. Finally, with the other seven algorithm was tested on the test function DTLZ series analysis, confirming RGridEA is effective in resolving MaOPs
Outage Performance and Optimal Design of MIMO-NOMA Enhanced Small Cell Networks With Imperfect Channel-State Information
This paper focuses on boosting the performance of small cell networks (SCNs)
by integrating multiple-input multiple-output (MIMO) and non-orthogonal
multiple access (NOMA) in consideration of imperfect channel-state information
(CSI). The estimation error and the spatial randomness of base stations (BSs)
are characterized by using Kronecker model and Poisson point process (PPP),
respectively. The outage probabilities of MIMO-NOMA enhanced SCNs are first
derived in closed-form by taking into account two grouping policies, including
random grouping and distance-based grouping. It is revealed that the average
outage probabilities are irrelevant to the intensity of BSs in the
interference-limited regime, while the outage performance deteriorates if the
intensity is sufficiently low. Besides, as the channel uncertainty lessens, the
asymptotic analyses manifest that the target rates must be restricted up to a
bound to achieve an arbitrarily low outage probability in the absence of the
inter-cell interference.Moreover, highly correlated estimation error
ameliorates the outage performance under a low quality of CSI, otherwise it
behaves oppositely. Afterwards, the goodput is maximized by choosing
appropriate precoding matrix, receiver filters and transmission rates. In the
end, the numerical results verify our analysis and corroborate the superiority
of our proposed algorithm
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