148 research outputs found
Optimizing Equitable Resource Allocation in Parallel Any-Scale Queues with Service Abandonment and its Application to Liver Transplant
We study the problem of equitably and efficiently allocating an arriving
resource to multiple queues with customer abandonment. The problem is motivated
by the cadaveric liver allocation system of the United States, which includes a
large number of small-scale (in terms of yearly arrival intensities) patient
waitlists with the possibility of patients abandoning (due to death) until the
required service is completed (matched donor liver arrives). We model each
waitlist as a GI/MI/1+GI queue, in which a virtual server receives a donor
liver for the patient at the top of the waitlist, and patients may abandon
while waiting or during service. To evaluate the performance of each queue, we
develop a finite approximation technique as an alternative to fluid or
diffusion approximations, which are inaccurate unless the queue's arrival
intensity is large. This finite approximation for hundreds of queues is used
within an optimization model to optimally allocate donor livers to each
waitlist. A piecewise linear approximation of the optimization model is shown
to provide the desired accuracy. Computational results show that solutions
obtained in this way provide greater flexibility, and improve system
performance when compared to solutions from the fluid models. Importantly, we
find that appropriately increasing the proportion of livers allocated to
waitlists with small scales or high mortality risks improves the allocation
equity. This suggests a proportionately greater allocation of organs to smaller
transplant centers and/or those with more vulnerable populations in an
allocation policy. While our motivation is from liver allocation, the solution
approach developed in this paper is applicable in other operational contexts
with similar modeling frameworks.Comment: 48 Page
On the number of frequency hypercubes
A frequency -cube is an -dimensional array filled by s and s such that each line contains exactly two s.
We classify the frequency -cubes , find a testing set of size
for , and derive an upper bound on the number of .
Additionally, for any greater than , we construct an that
cannot be refined to a latin hypercube, while each of its sub-
can.
Keywords: frequency hypercube, frequency square, latin hypercube, testing
set, MDS cod
Boosting Feedback Efficiency of Interactive Reinforcement Learning by Adaptive Learning from Scores
Interactive reinforcement learning has shown promise in learning complex
robotic tasks. However, the process can be human-intensive due to the
requirement of large amount of interactive feedback. This paper presents a new
method that uses scores provided by humans, instead of pairwise preferences, to
improve the feedback efficiency of interactive reinforcement learning. Our key
insight is that scores can yield significantly more data than pairwise
preferences. Specifically, we require a teacher to interactively score the full
trajectories of an agent to train a behavioral policy in a sparse reward
environment. To avoid unstable scores given by human negatively impact the
training process, we propose an adaptive learning scheme. This enables the
learning paradigm to be insensitive to imperfect or unreliable scores. We
extensively evaluate our method on robotic locomotion and manipulation tasks.
The results show that the proposed method can efficiently learn near-optimal
policies by adaptive learning from scores, while requiring less feedback
compared to pairwise preference learning methods. The source codes are publicly
available at https://github.com/SSKKai/Interactive-Scoring-IRL.Comment: Accepted by IEEE/RSJ International Conference on Intelligent Robots
and Systems (IROS 2023
The Cost-Effectiveness of Lowering Permissible Noise Levels Around U.S. Airports
Aircraft noise increases the risk of cardiovascular diseases and mental illness. The allowable limit for sound in the vicinity of an airport is 65 decibels (dB) averaged over a 24-h ‘day and night’ period (DNL) in the United States. We evaluate the trade-off between the cost and the health benefits of changing the regulatory DNL level from 65 dB to 55 dB using a Markov model. The study used LaGuardia Airport (LGA) as a case study. In compliance with 55 dB allowable limit of aircraft noise, sound insulation would be required for residential homes within the 55 dB to 65 dB DNL. A Markov model was built to assess the cost-effectiveness of installing sound insulation. One-way sensitivity analyses and Monte Carlo simulation were conducted to test uncertainty of the model. The incremental cost-effectiveness ratio of installing sound insulation for residents exposed to airplane noise from LGA was 93,054/QALY gained). Changing the regulatory standard for noise exposure around airports from 65 dB to 55 dB comes at a very good value
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Optimising the cost-effectiveness of speed limit enforcement cameras
Background Using the 140 speed cameras in New York City (NYC) as a case study, we explore how to optimise the number of cameras such that the most lives can be saved at the lowest cost.
Methods A Markov model was built to explore the economic and health impacts of speed camera installations in NYC as well as the optimal number and placement. Both direct and indirect medical savings associated with speed cameras are weighed against their cost. Health outcomes are measured in terms of quality-adjusted life years (QALYs).
Results Over the lifetime of an average NYC resident, the existing 140 speed cameras increase QALYs by 0.00044 units (95% credible interval (CrI) 0.00027 to 0.00073) and reduce costs by US21 to US147 (95% CrI US221) compared with existing speed cameras. Overall, this increase in cameras would save 7000 QALYs and US$1.2 billion over the lifetime of the current cohort of New Yorkers.
Conclusion Speed cameras rank among the most cost-effective social policies, saving both money and lives
A Novel Memristive Multilayer Feedforward Small-World Neural Network with Its Applications in PID Control
In this paper, we present an implementation scheme of memristor-based multilayer feedforward small-world neural network (MFSNN) inspirited by the lack of the hardware realization of the MFSNN on account of the need of a large number of electronic neurons and synapses. More specially, a mathematical closed-form charge-governed memristor model is presented with derivation procedures and the corresponding Simulink model is presented, which is an essential block for realizing the memristive synapse and the activation function in electronic neurons. Furthermore, we investigate a more intelligent memristive PID controller by incorporating the proposed MFSNN into intelligent PID control based on the advantages of the memristive MFSNN on computation speed and accuracy. Finally, numerical simulations have demonstrated the effectiveness of the proposed scheme
Deintercalation of Al from MoAlB by molten salt etching to achieve a Mo2AlB2 compound and 2D MoB nanosheets
Two-dimensional (2D) MoB metal borides (MoB MBene) have attracted much attention due to their fascinating properties and functional applications. So far, work on the synthesis of 2D MoB nanosheets by acid or alkaline etching of MoAlB has not been very successful. It has been proposed that the 2D MoB MBene may be fabricated by chemical etching of a Mo2AlB2 precursor, but further investigations were not performed possibly due to the difficult preparation of the metastable Mo2AlB2 compound at high temperatures by solid-state reactions. Here, we report on the successful synthesis of the Mo2AlB2 compound and 2D MoB nanosheets by the deintercalation of Al from MoAlB through a ZnCl2 molten salt etching approach at relatively low temperatures. The influence of etching temperature, etching time, and starting mixtures on the formation of desirable phases have been investigated. A pure Mo2AlB2 compound was synthesized at temperatures below 600 ℃, while the 2D MoB MBene nanosheets were obtained at 700 ℃ through the molten salt etching of MoAlB. In addition, the present work further confirms that the MoB MBene can be prepared by etching the as-synthesized Mo2AlB2 precursor in LiF–HCl solution. Our work demonstrates that the molten salt etching is an effective method to prepare 2D MoB MBene
Kinetic Analysis of Bio-Oil Aging by Using Pattern Search Method
Bio-oil derived from fast pyrolysis of lignocellulosic biomass is unstable, and aging would occur during its storage, handling, and transportation. The kinetic analysis of bio-oil aging is fundamental for the investigation of bio-oil aging mechanisms and the utilization of bio-oil as biofuels, biomaterials or biochemicals. The aging kinetic experiments of bio-oil from poplar wood pyrolysis were conducted at different aging temperatures of 303, 333, 353, and 363 K for different specified periods of time in capped glass vessels. The traditional method with two separate fittings was employed to fit experimental data, and the results indicated that the obtained kinetic parameters could not fit the experimental data well. An advanced approach for kinetic modeling of bio-oil aging has been developed by simultaneously processing experimental data at different aging temperatures and using the pattern search method. The aging kinetic model with the optimized parameters predicted the aging kinetic experimental data of the bio-oil sample very well for different aging temperatures
A new opportunity for the emerging tellurium semiconductor: making resistive switching devices
Abstract: The development of the resistive switching cross-point array as the next-generation platform for high-density storage, in-memory computing and neuromorphic computing heavily relies on the improvement of the two component devices, volatile selector and nonvolatile memory, which have distinct operating current requirements. The perennial current-volatility dilemma that has been widely faced in various device implementations remains a major bottleneck. Here, we show that the device based on electrochemically active, low-thermal conductivity and low-melting temperature semiconducting tellurium filament can solve this dilemma, being able to function as either selector or memory in respective desired current ranges. Furthermore, we demonstrate one-selector-one-resistor behavior in a tandem of two identical Te-based devices, indicating the potential of Te-based device as a universal array building block. These nonconventional phenomena can be understood from a combination of unique electrical-thermal properties in Te. Preliminary device optimization efforts also indicate large and unique design space for Te-based resistive switching devices
Anomalous stopping of laser-accelerated intense proton beam in dense ionized matter
Ultrahigh-intensity lasers (10-10W/cm) have opened up new
perspectives in many fields of research and application [1-5]. By irradiating a
thin foil, an ultrahigh accelerating field (10 V/m) can be formed and
multi-MeV ions with unprecedentedly high intensity (10A/cm) in short
time scale (ps) are produced [6-14]. Such beams provide new options in
radiography [15], high-yield neutron sources [16], high-energy-density-matter
generation [17], and ion fast ignition [18,19]. An accurate understanding of
the nonlinear behavior of beam transport in matter is crucial for all these
applications. We report here the first experimental evidence of anomalous
stopping of a laser-generated high-current proton beam in well-characterized
dense ionized matter. The observed stopping power is one order of magnitude
higher than single-particle slowing-down theory predictions. We attribute this
phenomenon to collective effects where the intense beam drives an decelerating
electric field approaching 1GV/m in the dense ionized matter. This finding will
have considerable impact on the future path to inertial fusion energy.Comment: 8 pages, 4 figure
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