Post-yield response of cold-cambered wide flange steel beams

The post-yield response of steel beams is important in steel fabrication particularly for setting cambers. A commonly used cambering process known as “cold cambering” consists of bending the girder about its strong axis using single or dual symmetrically applied concentrated loads. This paper recasts available solutions for wide flange steel beams relating loads to permanent deformation in parametric form to determine the effect of cross-sectional geometry and load position on its post-yield response. Sensitivity analyses were then conducted to identify appropriate values of these key parameters and their impact on alternative cambering set-ups. This allows optimization of the cold cambering operation for single- and dual-load systems. The analysis shows that dual-load systems offer significant benefits over single-load systems as they develop the required camber profile at smaller loads without overstraining the steel section. The best results are obtained if the spacing between the two loads is kept within one-third to one-quarter of the span.     

Magnetic resonance image denoising using nonlocal maximum likelihood paradigm in DCT‐framework

The data acquired by magnetic resonance (MR) imaging system are inherently degraded by noise that has its origin in the thermal Brownian motion of electrons. Denoising can enhance the quality (by improving the SNR) of the acquired MR image, which is important for both visual analysis and other post processing operations. Recent works on maximum likelihood (ML) based denoising shows that ML methods are very effective in denoising MR images and has an edge over the other state‐of‐the‐art methods for MRI denoising. Among the ML based approaches, the Nonlocal maximum likelihood (NLML) method is commonly used. In the conventional NLML method, the samples for the ML estimation of the unknown true pixel are chosen in a nonlocal fashion based on the intensity similarity of the pixel neighborhoods. Euclidean distance is generally used to measure this similarity. It has been recently shown that computing similarity measure is more robust in discrete cosine transform (DCT) subspace, compared with Euclidean image subspace. Motivated by this observation, we integrated DCT into NLML to produce an improved MRI filtration process. Other than improving the SNR, the time complexity of the conventional NLML can also be significantly reduced through the proposed approach. On synthetic MR brain image, an average improvement of 5% in PSNR and 86%reduction in execution time is achieved with a search window size of 91 × 91 after incorporating the improvements in the existing NLML method. On an experimental kiwi fruit image an improvement of 10% in PSNR is achieved. We did experiments on both simulated and real data sets to validate and to demonstrate the effectiveness of the proposed method. © 2015 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 25, 256–264, 2015     

Concrete crack detection using context‐aware deep semantic segmentation network

Computer‐vision and deep‐learning techniques are being increasingly applied to inspect, monitor, and assess infrastructure conditions including detection of cracks. Traditional vision‐based methods to detect cracks lack accuracy and generalization to work on complicated infrastructural conditions. This paper presents a novel context‐aware deep convolutional semantic segmentation network to effectively detect cracks in structural infrastructure under various conditions. The proposed method applies a pixel‐wise deep semantic segmentation network to segment the cracks on images with arbitrary sizes without retraining the prediction network. Meanwhile, a context‐aware fusion algorithm that leverages local cross‐state and cross‐space constraints is proposed to fuse the predictions of image patches. This method is evaluated on three datasets: CrackForest Dataset (CFD) and Tomorrows Road Infrastructure Monitoring, Management Dataset (TRIMMD) and a Customized Field Test Dataset (CFTD) and achieves Boundary F1 (BF) score of 0.8234, 0.8252, and 0.7937 under 2‐pixel error tolerance margin in CFD, TRIMMD, and CFTD, respectively. The proposed method advances the state‐of‐the‐art performance of BF score by approximately 2.71% in CFD, 1.47% in TRIMMD, and 4.14% in CFTD. Moreover, the averaged processing time of the proposed system is 0.7 s on a typical desktop with Intel^® Quad‐Core? i7‐7700 CPU@3.6 GHz Processor, 16GB RAM and NVIDIA GeForce GTX 1060 6GB GPU for an image of size 256 × 256 pixels.     

Partial replacement of carbon black with graphene in natural rubber/butadiene rubber based tire compound: Investigation of critical properties

Journal of Polymer Research - In this study, we prepared graphene oxide-based styrene/acrylic elastomeric disks (GSAE) from sugarcane bagasse/ferrocene (GO) and styrene/acrylic emulsion (SAE) to...     

A Novel RFET Sensor for Label-Free Biomolecule Detection

Silicon - In the current scenario, COVID-19 has created a havoc negative impact on the lives of the people, which have triggered the research interest on the design and development of sensitive,...     

Photopolymerization kinetics of bis-aromatic based urethane acrylate macromonomers in the presence of reactive diluent

The present work deals with the photopolymerization of bis-aromatic based urethane acrylate macromonomers in the presence of excess end capping agent as reactive diluent and estimation of their kinetic parameters. Formulations were made by independently homogenizing the macromonomers with photoinitiators of three different classes. Three different compositions of photoinitiators were used to study the effect of concentration of photoinitiator on cure kinetics. These compositions obtained were tested for photo curing performance using photo DSC under polychromatic radiation. The heat flows against time were recorded for all formulations under isothermal condition and the rates of polymerization, peak maximum times as well as the percentage conversions were estimated. It was observed that due to a longer timescale for reaction diffusion, formulations with macromonomer containing propoxylated backbone showed higher conversions than the corresponding ethoxylated analogue. The photopolymerization and kinetic estimations of the formulations including evaluation of kinetic model are discussed.     

Fractality of tics as a quantitative assessment tool for Tourette syndrome

Tics manifest as brief, purposeless and unintentional movements or noises that, for many individuals, can be suppressed temporarily with effort. Previous work has hypothesized that the chaotic temporal nature of tics could possess an inherent fractality, that is, have neighbour-to-neighbour correlation at all levels of timescale. However, demonstrating this phenomenon has eluded researchers for more than two decades, primarily because of the challenges associated with estimating the scale-invariant, power law exponent—called the fractal dimension D_f—from fractional Brownian noise. Here, we confirm this hypothesis and establish the fractality of tics by examining two tic time series datasets collected 6–12 months apart in children with tics, using random walk models and directional statistics. We find that D_f is correlated with tic severity as measured by the YGTTS total tic score, and that D_f is a sensitive parameter in examining the effect of several tic suppression conditions on the tic time series. Our findings pave the way for using the fractal nature of tics as a robust quantitative tool for estimating tic severity and treatment effectiveness, as well as a possible marker for differentiating typical from functional tics.     

Cooperative energy management in distributed wireless real-time systems

This work is based on the observation that existing energy management techniques for mobile devices, such as Dynamic Voltage Scaling (DVS), are non-cooperative in the sense that they reduce the energy consumption of a single device, disregarding potential consequences for other constraints (e.g., end-to-end deadlines) and/or other devices (e.g., energy consumption on neighboring devices). This paper argues that energy management in distributed wireless real-time systems has to be end-to-end in nature, requiring a coordinated approach among communicating devices. A cooperative distributed energy management technique (Co-DVS) is proposed that (1) adapts and maintains end-to-end latencies within specified timeliness requirements (deadlines) and (2) enhances energy savings at the devices with the highest pay-off factors that represent the relative benefits or significance of conserving energy at a device. The proposed technique employs a feedback-based approach to dynamically distribute end-to-end slack among the devices based on their pay-off factors.     

Information-Lossless Space–Time Block Codes From Crossed-Product Algebras

It is known that the Alamouti code is the only complex orthogonal design (COD) which achieves capacity and that too for the case of two transmit and one receive antenna only. Damen proposed a design for two transmit antennas, which achieves capacity for any number of receive antennas, calling the resulting space-time block code (STBC) when used with a signal set an information-lossless STBC. In this paper, using crossed-product central simple algebras, we construct STBCs for arbitrary number of transmit antennas over an a priori specified signal set. Alamouti code and quasi-orthogonal designs are the simplest special cases of our constructions. We obtain a condition under which these STBCs from crossed-product algebras are information-lossless. We give some classes of crossed-product algebras, from which the STBCs obtained are information-lossless and also of full rank. We present some simulation results for two, three, and four transmit antennas to show that our STBCs perform better than some of the best known STBCs and also that these STBCs are approximately 1 dB away from the capacity of the channel with quadrature amplitude modulation (QAM) symbols as input