Electrothermal energy storage (ETES) provides bulk electricity storage based on heat pump and heat engine technologies. A subcritical ETES is described in this paper. Based on the extremum principle of entransy dissipation, a geometry model is developed for heat transfer optimization for subcritical ETES. The exergy during the heat transfer process is deduced in terms of entropy production. The...

Abstract—Medical images are important to help identifying different diseases, for example, Magnetic resonance imaging (MRI) can be used to investigate the brain, spinal cord, bones, joints, breasts, blood vessels, and heart. Image segmentation, in medical image analysis, is usually the first step to find out some characteristics with similar color, intensity or texture so that the diagnosis cou...

Supply chain is an organized combination of inbound logistics, production plants and multiechelon distribution network. Decentralized distribution networks are common and prone to exogenous and endogenous uncertainties. Information uncertainty from the downstream customer and material uncertainty from the upstream supplier makes the supply chain behavior more complex. Previous attempts made to ...

Data mining is the process of extracting hidden patterns from huge data. Among the various clustering algorithms, k-means is the one of most widely used clustering technique in data mining. The performance of k-means clustering depends on the initial clusters and might converge to local optimum. K-means does not guarantee the unique clustering because it generates different results with randoml...

Fifty years ago, the optimization of thermoelectric devices was analyzed by considering the relation between optimal performances and local entropy production. Entropy is produced by the irreversible processes in thermoelectric devices. If these processes could be eliminated, entropy production would be reduced to zero, and the limiting Carnot efficiency or coefficient of performance would be o...

The objective of image segmentation is to extract meaningful objects. A meaningful segmentation selects the proper threshold values to optimize a criterion using entropy. The conventional multilevel thresholding methods are efficient for bi-level thresholding. However, they are computationally expensive when extended to multilevel thresholding since they exhaustively search the optimal threshol...

Weight based clustering has become the mainstream clustering algorithm in low-speed Ad hoc networks because of its excellent cluster stability. However, due to the dynamic topology changing in high-speed Ad hoc network, the cluster stability (network stability) decreased and the cluster maintenance costs increased sharply. To solve the problem, we propose a dynamic entropy based combination wei...

We study optimization methods for source-initiated energyefficient broadcast in all-wireless networks. The minimum energy broadcast (MEB) problem in wireless networks proved to be NP-complete [1,4]. Past studies on MEB problem [1,2,5,8,9] focus on deterministic optimization to construct energy-efficient broadcast tree. In this paper, we present a probabilistic optimization approach, the Randomi...

Certifying function nonnegativity is a ubiquitous problem in computational mathematics, with especially notable applications optimization. We study the question of certifying signomials based on recently proposed approach Sums-of-AM/GM-Exponentials (SAGE) decomposition due to second author and Shah. The existence SAGE sufficient condition for signomial, it can be verified by solving tractable c...