Tunable Assembly of sp3 Cross‐Linked 3D Graphene Monoliths: A First‐Principles Prediction

One of the biggest challenges in graphene applications is how one can fabricate 3D architectures comprising graphene sheets in which the resulting architectures have inherited graphene's excellent intrinsic properties but have overcome its shortcomings. Two series of 3D graphene monoliths (GMs) using zigzag or armchair graphene nanoribbons as building blocks and sp³ carbon chains as junction nodes are constructued, and calculations based on first principles are performed in order to predict their mechanical and electronic properties. The perfect match between sp² nanoribbons and sp³ linkers results in favorable energy and mechanical/dynamic stability. Owing to their tailored motifs, wine‐rack‐like pores, and rigid sp³ linkers, these GMs possess high surface areas, appreciable mechanical strength, and tunable band gaps. Negative linear compressibilities in a wide range are found for the zigzag GMs. By solving the problems of zero gap and dimensionality of graphene sheets simultaneously, these GMs offer a viable strategy towards many applications, e.g., microelectronic devices, energy storage, molecular sieves, sensitive pressure detectors, and telecommunication line systems.     

Conjunctive Management of Large-Scale Pressurized Water Distribution and Groundwater Systems in Semi-Arid Area with Parallel Genetic Algorithm

This study develops a production well management model for the conjunctive management of water resources in semi-arid areas. The management model integrates a large-scale pressurized water distribution system and a three-dimensional groundwater model under an optimization framework. The well pump operations optimization problem is formulated as a Boolean integer nonlinear programming (BINLP) problem to optimize the periodic 24-h pump on/off operations over a 1-week operation horizon. The management model considers multiple objectives and is solved by a parallel genetic algorithm (PGA) to overcome the difficulty of solving the BINLP problem. The PGA significantly reduces computation time for a case study in Chandler, Arizona. The Chandler water distribution model is built based on EPANET, and the Chandler three-dimension groundwater model is developed using MODFLOW. The high performance computing (HPC) of the genetic algorithm makes it possible to obtain 24-h real-time operations in the 7-day forecast model. The tank reliability, resilience, and vulnerability (R-R-V) are evaluated to infer the system reliability. The Pareto curve provides compromise solutions between the two competing objectives of energy reduction and pressure violation reduction.     

Performance analysis of a variable‐gain amplify‐and‐forward relayed mixed RF‐FSO system

In this work, an amplify‐and‐forward variable‐gain relayed mixed RF‐FSO system is studied. The considered dual‐hop system consists of a radio frequency (RF) link followed by a free space optical (FSO) channel. The RF link is affected by short‐term multipath fading and long‐term shadowing effects and is assumed to follow the generalized‐K fading distribution that approximates accurately several important distributions often used to model communication channels. The FSO channel experiences fading caused by atmospheric turbulence that is modeled by the gamma‐gamma distribution characterizing moderate and strong turbulence conditions. The FSO channel also suffers path loss and pointing error induced misalignment fading. The performance of the considered system is analyzed under the collective influence of distribution shaping parameters, pointing errors that result in misalignment fading, atmospheric turbulence, and path loss. The moment‐generating function of the Signal power to noise power ratio measured end‐to‐end for this system is derived. The cumulative distribution function for the Signal power to noise power ratio present between the source and destination receiver is also evaluated. Further, we investigate the error and outage performance and the average channel capacity for this system. The analytical expressions in closed form for the outage probability, symbol and bit error rate considering different modulation schemes and channel capacity are also derived. The mathematical expressions obtained are also demonstrated by numerical plots.     

GRAIL: a scalable index for reachability queries in very large graphs

Given a large directed graph, rapidly answering reachability queries between source and target nodes is an important problem. Existing methods for reachability tradeoff indexing time and space versus query time performance. However, the biggest limitation of existing methods is that they do not scale to very large real-world graphs. We present a simple yet scalable reachability index, called GRAIL, that is based on the idea of randomized interval labeling and that can effectively handle very large graphs. Based on an extensive set of experiments, we show that while more sophisticated methods work better on small graphs, GRAIL is the only index that can scale to millions of nodes and edges. GRAIL has linear indexing time and space, and the query time ranges from constant time to being linear in the graph order and size. Our reference C++ implementations are open source and available for download at http://www.code.google.com/p/grail/.     

Numerical evaluation of the Hankel transform by using linear Legendre multi-wavelets

An efficient algorithm for evaluating the Hankel transform Fn(p) of order n of a function f(r) is given. As the continuous Legendre multi-wavelets forms an orthonormal basis for L²(R); we expand the part rf(r) of the integrand in its wavelet series reducing the Hankel transform integral as a series of Bessel functions multiplied by the wavelet coefficients of the input function. Numerical examples are given to illustrate the efficiency of the proposed method.     

Peer to peer trade in HTM5 meta model for agent oriented cloud robotic systems

Cloud computing is a methodology and not a technology. Adaptation of cloud computing services for robotic applications is relatively straightforward while adaptation of underlying ideas will require a new design attitude. Cloud computing is a cost-effective and dynamic business model. Currently cloud robotics is understood as a client server methodology which enables robots utilize resources and services placed at centralized servers. These cloud servers treat robots as any other client computer offering them platform, infrastructure, process or algorithm as a service. HTM5 is an OMG MDA based multi-view meta-model for agent oriented development of cloud robotic systems. HTM5 encourages design of peer-to-peer service ecosystems based on an open registry and matchmaking mechanism. In peer-to-peer cloud robotics, a robot can trade its hardware, software and functional resources as a service to other robots in the ecosystem. The peer-to-peer trade in such systems may be driven by contracts and relationships between its member agents. This article discusses trade-view model of HTM5 methodology and its use in developing a cloud robotic ecosystem that implements peer-to-peer, contract based economy. The article also presents a case study with experiments that implement distributed artificial intelligence and peer-to-peer service oriented trade on simulated and real robot colonies.     

Automated classification of phonological errors in aphasic language

Using heuristically guided state space search, a prototype program has been developed to simulate and classify phonemic errors occurring in the speech of neurologically impaired patients. Simulations are based on an interchangeable rule/operator set of elementary errors which represent a theory of phonemic processing faults. This work is significant because it introduces and evaluates a novel approach to error simulation and classification, provides a prototype simulation tool for neurolinguistic research, and forms the initial phase of a larger research effort involving computer modelling of neurolinguistic processes.     

Matching two perspective views

A computational approach to image matching is described. It uses multiple attributes associated with each image point to yield a generally overdetermined system of constraints, taking into account possible structural discontinuities and occlusions. In the algorithm implemented, intensity, edgeness, and cornerness attributes are used in conjunction with the constraints arising from intraregional smoothness, field continuity and discontinuity, and occlusions to compute dense displacement fields and occlusion maps along the pixel grids. The intensity, edgeness, and cornerness are invariant under rigid motion in the image plane. In order to cope with large disparities, a multiresolution multigrid structure is employed. Coarser level edgeness and cornerness measures are obtained by blurring the finer level measures. The algorithm has been tested on real-world scenes with depth discontinuities and occlusions. A special case of two-view matching is stereo matching, where the motion between two images is known. The algorithm can be easily specialized to perform stereo matching using the epipolar constraint     

Superresolution and noise filtering using moving least squares.

An irregularly spaced sampling raster formed from a sequence of low-resolution frames is the input to an image sequence superresolution algorithm whose output is the set of image intensity values at the desired high-resolution image grid. The method of moving least squares (MLS) in polynomial space has proved to be useful in filtering the noise and approximating scattered data by minimizing a weighted mean-square error norm, but introducing blur in the process. Starting with the continuous version of the MLS, an explicit expression for the filter bandwidth is obtained as a function of the polynomial order of approximation and the standard deviation (scale) of the Gaussian weight function. A discrete implementation of the MLS is performed on images and the effect of choice of the two dependent parameters, scale and order, on noise filtering and reduction of blur introduced during the MLS process is studied.     

Performance analysis of stereo, vergence, and focus as depth cuesfor active vision

This paper compares the performances of the binocular cues of stereo and vergence, and the monocular cue of focus for range estimation using an active vision system. The performance of each cue is characterized in terms of sensitivity to errors in the imaging parameters. The effects of random, quantization errors are expressed in terms of the standard deviation of the resulting depth error. The effect of systematic, calibration errors on estimation using each cue is also studied. Performance characterization of each cue is utilized to evaluate the relative performance of the cues. Also discussed, based on such characterization, are ways to select a cue taking into account the computational and reliability aspects of the corresponding estimation process