Lidar-based mapping of leaf area index and its use for validating GLOBCARBON satellite LAI product in a temperate forest of the southern USA

Lidar provides enhanced abilities to remotely map leaf area index (LAI) with improved accuracies. We aim to further explore the capability of discrete-return lidar for estimating LAI over a pine-dominated forest in East Texas, with a secondary goal to compare the lidar-derived LAI map and the GLOBCARBON moderate-resolution satellite LAI product. Specific problems we addressed include (1) evaluating the effects of analysts and algorithms on in-situ LAI estimates from hemispherical photographs (hemiphoto), (2) examining the effectiveness of various lidar metrics, including laser penetration, canopy height and foliage density metrics, to predict LAI, (3) assessing the utility of integrating Quickbird multispectral imagery with lidar for improving the LAI estimate accuracy, and (4) developing a scheme to co-register the lidar and satellite LAI maps and evaluating the consistency between them. Results show that the use of different analysts or algorithms in analyzing hemiphotos caused an average uncertainty of 0.35 in in-situ LAI, and that several laser penetration metrics in logarithm models were more effective than other lidar metrics, with the best one explaining 84% of the variation in the in-situ LAI (RMSE = 0.29 LAI). The selection of plot size and height threshold in calculating laser penetration metrics greatly affected the effectiveness of these metrics. The combined use of NDVI and lidar metrics did not significantly improve estimation over the use of lidar alone. We also found that mis-registration could induce a large artificial discrepancy into the pixelwise comparison between the coarse-resolution satellite and fine-resolution lidar-derived LAI maps. By compensating for a systematic sub-pixel shift error, the correlation between two maps increased from 0.08 to 0.85 for pines (n = 24 pixels). However, the absolute differences between the two LAI maps still remained large due to the inaccuracy in accounting for clumping effects. Overall, our findings imply that lidar offers a superior tool for mapping LAI at local to regional scales as compared to optical remote sensing, accuracies of lidar-estimate LAI are affected not only by the choice of models but also by the absolute accuracy of in-situ reference LAI used for model calibration, and lidar-derived LAI maps can serve as reliable references for validating moderate-resolution satellite LAI products over large areas.     

Relaxing PWQ Lyapunov stability criteria for PWA systems

The note addresses the calculation of piecewise quadratic (PWQ) Lyapunov functions for PWA (piecewise affine) systems. New LMI relaxations are proposed. These relaxations have been found to be effective in cases where the traditional relaxations fail.     

Discrete‐time sector based hands‐off control for nonlinear system

This article presents a hands‐off control design for discrete‐time nonlinear system with a special type of nonlinear sector termed as “discrete‐time sector.” The design method to define the boundary of a discrete‐time sector is done with control‐Lyapunov function. The generalization of nonlinear system is viewed in the perspective of a comparison function. By means of a proposed sector, a switching control is designed such that no control action is experienced inside the sector thus, saving unnecessary control efforts. However, to study the robustness for discrete‐time system, a hands‐off control is modified to ensure the monotonic decrease in the energy of the system. Finally, the proposed approach is verified with the simulation results.     

A smart healthcare reward model for resource allocation in smart city

Today, cities face many significant challenges, and the smart city concept is a promising means to address typical traditional city problems. The wireless e-health technologies is an evolving topic in the area of telemedicine nowadays. Mobile telecommunication and the use of multimedia technologies are the core of providing better access to healthcare personnel on the move. These technologies provide equal access to medical information and expert care leading to a better and a more efficient use of resources. Mobile and Fog computing technologies can also cope with many challenges in smart healthcare resources of mobility, scalability, efficiency, and reliability. Optimal healthcare systems are particularly critical in cities, due to the highly concentrated populations. This high population increases the potential for harm and damage in the case of negligence or improper treatment. This can lead to infections and disease outbreaks, which could become epidemic situations and require containment, which is very costly. Motivated by the need for better usage and management of healthcare resources, which is crucial for reliable healthcare delivery, this paper introduces a model that can provide improved delivery and utilization of resources. The quality reward-based model was developed to study and react to the satisfaction factors of healthcare systems, and proposes an optimization-based algorithm called the Maximum Reward Algorithm (MRA), that enhances the use and delivery of healthcare resources. The algorithm has been tested with multiple experiments and simulations, and has proved that it can provide reliability, efficiency and achieves 50.1% to 77.2% performance improvement.

     

Load-Balanced Sparse Matrix–Vector Multiplication on Parallel Computers

We considered the load-balanced multiplication of a large sparse matrix with a large sequence of vectors on parallel computers. We propose a method that combines fast load-balancing with efficient message-passing techniques to alleviate computational and inter-node communications challenges. The performance of the proposed method was evaluated on benchmark as well as on synthetically generated matrices and compared with the current work. It is shown that, by using our approach, a tangible improvement over prior work can be obtained, particularly for very sparse and skewed matrices. Moreover, it is also shown that I/O overhead for this problem can be efficiently amortized through I/O latency hiding and overall load-balancing.     

Generic fitted shapes (GFS): Volumetric object segmentation in service robotics

In this paper, a simultaneous 3D volumetric segmentation and reconstruction method, based on the so-called Generic Fitted Shapes (GFS) is proposed. The aim of this work is to cope with the lack of volumetric information encountered in visually controlled mobile manipulation systems equipped with stereo or RGB-D cameras. Instead of using primitive volumes, such as cuboids or cylinders, for approximating objects in point clouds, their volumetric structure has been estimated based on fitted generic shapes. The proposed GFSs can capture the shapes of a broad range of object classes without the need of large a-priori shape databases. The fitting algorithm, which aims at determining the particular geometry of each object of interest, is based on a modified version of the active contours approach extended to the 3D Cartesian space. The proposed volumetric segmentation system produces comprehensive closed object surfaces which can be further used in mobile manipulation scenarios. Within the experimental setup, the proposed technique has been evaluated against two state-of-the-art methods, namely superquadrics and 3D Object Retrieval (3DOR) engines.     

Tunable single-mode fiber reflective grating filter

A single-mode fiber tunable reflective filter is demonstrated by translating a fan-shaped grating structure through the evanescent field of a side-polished fiber. Filter linewidths of about 1 nm were measured over tuning ranges in excess of 65 nm. Reflectivities as high as 88 percent were observed. Using the fiber filter as a feedback element, a multimode semiconductor laser was observed to oscillate in a single mode which could be discretely turned over a wavelength range of 26 nm.     

Argus: Low-Cost, Comprehensive Error Detection in Simple Cores

Argus, a novel approach for detecting errors in simple processor cores, dynamically verifies the correctness of the four tasks performed by a von Neumann core: control flow, data flow, computation, and memory access. Argus detects transient and permanent errors, with far lower impact on performance and chip area than previous techniques.     

Integration of diamond in fully-depleted silicon-on-insulator technology as buried insulator: A theoretical analysis

We examine here by electro-thermal simulation tools (SILVACO's Atlas) a configuration of Silicon-On-Insulator substrate for Fully-Depleted MOSFET architectures, incorporating diamond as buried insulator, and compare it with traditional silicon dioxide BOX for the future technological nodes of the ITRS (90 nm and below). Our aim is to give major trends to be followed in order to optimize diamond integration from electrical and thermal points of view, constraints that must be kept in mind in parallel with the technological work on thin diamond films. In this theoretical study, we perform a benchmarking between SiO₂ and diamond BOX. We first point out that the BOX thickness should not be more than few hundred nanometers to maintain electrical performances. From thermal point of view, we demonstrate that the replacement of 100 nm thick buried oxide by a 100 nm thick diamond layer can lead to about 50% reduction of the temperature when only 33% decrease can be obtained with Ultra Thin SiO₂ BOX (20 nm). Furthermore, thick diamond BOX avoids the parasitic capacitances issue that reduces Ultra Thin BOX devices working frequency.     

An arithmetical hierarchy in propositional dynamic logic

We prove that any alternation of modalities in PDL adds to its expressive power. The proof uses Turing machine models where PDL formulas define the arithmetical hierarchy of sets. As a by-product, we obtain a theorem of Berman and Paterson.