Multi-Objective optimization can be used to produce regularized Electrical Impedance Tomography (EIT) images where the weight of the regularization term is not known a priori. This paper proposes a novel Multi-Objecti...
详细信息
ISBN:
(纸本)9781424492695
Multi-Objective optimization can be used to produce regularized Electrical Impedance Tomography (EIT) images where the weight of the regularization term is not known a priori. This paper proposes a novel Multi-Objective optimization algorithm based on Simulated Annealing tailored for EIT image reconstruction. Images are reconstructed from experimental data and compared with images from other Multi and Single Objective optimization methods. A significant performance enhancement from traditional techniques can be inferred from the results.
In this paper, we propose a continuous-time formulation for the AdaGrad, RMSProp, and Adam optimization algorithms by modeling them as first-order integro-differential equations. We perform numerical simulations of th...
详细信息
Feasibility of the novel utilization of a pressure switch mechanism for re-calibrating drifted implanted pressure sensors in-situ is demonstrated. We have designed and characterized the pressure response of a system, ...
详细信息
ISBN:
(纸本)9781509010134
Feasibility of the novel utilization of a pressure switch mechanism for re-calibrating drifted implanted pressure sensors in-situ is demonstrated. We have designed and characterized the pressure response of a system, which can quantify the offset of a sensor after it has been implanted. The benchtop device is constructed of a 25 pm thick titanium diaphragm with 10 mm working diameter. An optimization algorithm detected a characteristic change in the pressure response produced by the activation of a pressure switch. The repeatability of detection across three sensors is within ±0.23 mmHg over 8 pressurization cycles.
Much of the literature on optimal design of bandit algorithms is based on minimization of expected regret. It is well known that algorithms that are optimal over certain exponential families can achieve expected regre...
详细信息
This paper presents a linear FPT algorithm to find a tree decomposition with a 2-approximation of the treewidth with a significantly smaller exponential dependence on the treewidth in the running time than previously ...
详细信息
Cyberbullying has emerged as a serious societal and public health problem that demands accurate methods for the detection of cyberbullying instances in an effort to mitigate the consequences. While techniques to autom...
详细信息
ISBN:
(纸本)9781538646595
Cyberbullying has emerged as a serious societal and public health problem that demands accurate methods for the detection of cyberbullying instances in an effort to mitigate the consequences. While techniques to automatically detect cyberbullying incidents have been developed, the scalability and timeliness of existing cyberbullying detection approaches have largely been ignored. We address this gap by formulating cyberbullying detection as a sequential hypothesis testing problem. Based on this formulation, we propose a novel algorithm designed to reduce the time to raise a cyberbullying alert by drastically reducing the number of feature evaluations necessary for a decision to be made. We demonstrate the effectiveness of our approach using a real-world dataset from Twitter, one of the top five networks with the highest percentage of users reporting cyberbullying instances. We show that our approach is highly scalable while not sacrificing accuracy for scalability.
In the construction industry, a specialist subcontractor manages a taskforce of single-skilled laborers to work on multiple construction sites, aiming to minimize the total cost and stay profitable and competitive. Th...
详细信息
ISBN:
(纸本)9781424427086
In the construction industry, a specialist subcontractor manages a taskforce of single-skilled laborers to work on multiple construction sites, aiming to minimize the total cost and stay profitable and competitive. This paper presents a simulation-based approach to assist the subcontractor in scheduling the application of limited laborer resources to handle jobs over multiple concurring sites. Factoring in technological constraints, repetitive building cycles, alternative method options, and the limited quantity of skilled laborers, we resort to computer power (including simulation and optimization algorithms resulting from recent research) in search of the best combination of construction methods at individual sites along with the optimum size of labor force, aimed to find the least cost for completing the jobs at all sites. A case study of bar-bender scheduling over three sites by use of an in-house computer tool results in the optimum method combinations, the optimum crew size, and the optimum resource schedule.
This paper focuses on the deblurring and denoising of Poisson noise contaminated images acquired with a new imaging technique producing large 3D data sets: Light Sheet Fluorescence Microscopy. This paper details the o...
详细信息
ISBN:
(纸本)9781424441211
This paper focuses on the deblurring and denoising of Poisson noise contaminated images acquired with a new imaging technique producing large 3D data sets: Light Sheet Fluorescence Microscopy. This paper details the optimization algorithm used, which is based on the Alternating Direction Method of Multipliers, and its efficient implementation using GPU hardware. In practice, a 3D 100 million voxel image is deconvolved in five minutes, which is at least 25 times faster than a state-of-the-art MATLAB implementation.
Learning Tomography (LT) is a nonlinear optimization algorithm for computationally imaging three-dimensional (3D) distribution of the refractive index in semi-transparent samples. Since the energy function in LT is ge...
详细信息
ISBN:
(纸本)9781509041183
Learning Tomography (LT) is a nonlinear optimization algorithm for computationally imaging three-dimensional (3D) distribution of the refractive index in semi-transparent samples. Since the energy function in LT is generally non-convex, the solution it obtains is not guaranteed to be globally optimal. In this paper, we describe linear and nonlinear tomographic reconstruction methods and compare them numerically. We present a review of the LT and, in addition, we investigate the influence of the initialization and exemplify the effect of regularization on the convergence of the algorithm. In particular, we show that both are essential for high-quality imaging in strongly scattering scenarios.
Using directional antennas in wireless mesh networks (termed DMesh in this paper) is attractive due to its longer coverage range and spatial separation between transmissions of the same channel. However, the connectiv...
详细信息
ISBN:
(纸本)9781467309202
Using directional antennas in wireless mesh networks (termed DMesh in this paper) is attractive due to its longer coverage range and spatial separation between transmissions of the same channel. However, the connectivity in a DMesh is much lower than its omni-directional counterpart. This makes topology control (through beaming) a critical problem in DMesh. Because topology control coupled with routing decision, their joint optimization is critical to achieve the best performance. In this paper, we consider a multimedia DMesh with a certain traffic demand at each mesh router. We first formulate the joint topology control and routing assignment as an optimization problem and show that it is NP-hard. To address the problem, we propose a novel and efficient heuristic called TORA (Joint Topology Control and Routing Assignment), an ant-colony optimization algorithm which seeks to jointly optimize topology and routing for DMesh. Simulation results based on NS3 show that TORA performs substantially better in terms of loss rate, delay and throughput as compared with a recent scheme.
暂无评论