A Simplified Scheme of Estimation and Cancellation of Companding Noise for Companded Multicarrier Transmission Systems

Nonlinear companding transform is an efficient method to reduce the high peak-to-average power ratio (PAPR) of multicarrier transmission systems. However, the introduced companding noise greatly degrades the bit-error-rate (BER) performance of the companded multicarrier systems. In this paper, a simplified but effective scheme of estimation and cancellation of companding noise for the companded multicarrier transmission system is proposed. By expressing the companded signals as the summation of original signals added with a companding noise component, and subtracting this estimated companding noise from the received signals, the BER performance of the overall system can be significantly improved. Simulation results well confirm the great advantages of the proposed scheme over other conventional decompanding or no decompanding schemes under various situations

The applications of building information modelling for the lifecycle performance of green buildings: a systematic literature review

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Antimagnetic Rotation Band in Nuclei: A Microscopic Description

Covariant density functional theory and the tilted axis cranking method are used to investigate antimagnetic rotation (AMR) in nuclei for the first time in a fully self-consistent and microscopic way. The experimental spectrum as well as the B(E2) values of the recently observed AMR band in 105Cd are reproduced very well. This gives a further strong hint that AMR is realized in specific bands in nuclei.Comment: 10 pages, 4 figure

An Invariance Principle of G-Brownian Motion for the Law of the Iterated Logarithm under G-expectation

The classical law of the iterated logarithm (LIL for short)as fundamental limit theorems in probability theory play an important role in the development of probability theory and its applications. Strassen (1964) extended LIL to large classes of functional random variables, it is well known as the invariance principle for LIL which provide an extremely powerful tool in probability and statistical inference. But recently many phenomena show that the linearity of probability is a limit for applications, for example in finance, statistics. As while a nonlinear expectation--- G-expectation has attracted extensive attentions of mathematicians and economists, more and more people began to study the nature of the G-expectation space. A natural question is: Can the classical invariance principle for LIL be generalized under G-expectation space? This paper gives a positive answer. We present the invariance principle of G-Brownian motion for the law of the iterated logarithm under G-expectation

Multi-Estimator Full Left Ventricle Quantification through Ensemble Learning

Cardiovascular disease accounts for 1 in every 4 deaths in United States. Accurate estimation of structural and functional cardiac parameters is crucial for both diagnosis and disease management. In this work, we develop an ensemble learning framework for more accurate and robust left ventricle (LV) quantification. The framework combines two 1st-level modules: direct estimation module and a segmentation module. The direct estimation module utilizes Convolutional Neural Network (CNN) to achieve end-to-end quantification. The CNN is trained by taking 2D cardiac images as input and cardiac parameters as output. The segmentation module utilizes a U-Net architecture for obtaining pixel-wise prediction of the epicardium and endocardium of LV from the background. The binary U-Net output is then analyzed by a separate CNN for estimating the cardiac parameters. We then employ linear regression between the 1st-level predictor and ground truth to learn a 2nd-level predictor that ensembles the results from 1st-level modules for the final estimation. Preliminary results by testing the proposed framework on the LVQuan18 dataset show superior performance of the ensemble learning model over the two base modules.Comment: Jiasha Liu, Xiang Li and Hui Ren contribute equally to this wor

Petrologic and In Situ Geochemical Constraints on Diogenite Genesis

Diogenites, members of the howardite, eucrite and diogenite (HED) clan, are orthopyroxenite, harzburgite and dunite meteorites [1-3]. Most are breccias, but remnant textures indicate they were originally coarse-grained rocks, with grain sizes of order of cm. Their petrography and compositions support an origin as crustal cumulates from a differentiated asteroid. Astronomical observations, and surface mineralogy and composition of Vesta determined by the Dawn spacecraft suggest that asteroid (4) Vesta is the parent object for HED meteorites [4-6]. The origin of diogenites is an unsettled issue. It is difficult to fit their bulk compositional characteristics into global magma ocean models that successfully describe the compositions of basaltic and cumulate eucrites [7]. Compositional analyses of acid-leached bulk samples have led to the hypothesis that many diogenites were formed late by interaction of their parent melts with a eucritic crust [8]. Those observations may alternatively be explained by subsolidus equilibration of trace elements between orthopyroxene and minor/ accessory phases in the rocks such as plagioclase and phosphate [7]. These competing hypotheses can be tested through in situ measurements of trace and minor elements in orthopyroxene. Our new petrologic observations and in situ minor and trace element data for a suite of diogenites are used to discuss the petrologic evolution of diogenites. Our preliminary data on two diogenites are consistent with the hypothesis that subsolidus element mobilization processes caused unusual trace element signatures seen in some diogenites [7]. We cannot stress strongly enough, however, that the sample set is too small and that additional data are required before definitive conclusions can be made