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.     

Effect of modifier concentration on the fracture behaviour of rubber-modified PMMA

Izod fracture surfaces of blends of PMMA with various amounts of a rubber modifier were studied using scanning electron microscopy. Attention was focused on modes of crack initiation and propagation and on the role of the modifier in the fracture process. It was found that the impact strength of this class of materials increased monotonically with an increase in modifier concentration, at least up to 40 wt% modifier. Unmodified PMMA was studied to provide a basis for understanding the morphological features on the fracture surfaces of the rubber-modified blends. It was confirmed that PMMA fractures through the formation and rupture of crazes. This phenomenon was also found to occur in blends containing 10 wt% modifier. However, blends with 20 wt% modifier crazed only in the later stages of the fracture process, when the crack speed had exceeded some critical value. No evidence of crazing was found in blends with 30 and 40 wt% modifier loadings, although extensive plastic deformation was observed on the fracture surfaces.     

Energy-efficient production of chilled water in industry

Current practices for operation of a water-chilling plant (WCP) in the cement product industry in Kuwait have been studied and evaluated under different load conditions. Experimental results and weather data are used to demonstrate deficiencies in the present design. An analysis has been conducted to arrive at the optimum use of a cooling tower (CT) and chillers for year-round application. A significantly larger cooling tower is recommended for technical and economic viability. Our case study may serve as a guide for optimizing the design and operation of other types of water-chilling plants.     

Video--EEG monitoring in intractable attacks of uncertain etiology

Video-EEG monitoring was done in 26 patients with paroxysmal intractable attacks of uncertain etiology to determine the nature and cause. Two broad categories were identified: Those with prominent motor activity and those with attacks of collapse/limpness. Events were recorded in 16 patients of which 11 showed no abnormality on the simultaneously recorded EEG, thus helping to confirm their diagnosis of pseudoseizures.     

Effects of regulation on the flow regime of the river Murray,Australia

The flow regime of the River Murray has changed markedly over the last century, and especially the last 50 years, through increased diversions, construction of dams, weirs and levees and changes in operational procedures. A model developed by the Murray–Darling Basin Commission is used to compare simulated natural (unregulated) flows at eight stations with those at seven consecutive stages in the development of regulation. Monthly and annual average flows and coefficients of variation and skewness were computed, and the flow-duration, peak-flow and low-flow characteristics curves plotted. The results confirm that average monthly and annual flows are now considerably lower than those which prevailed under natural conditions. The seasonal distribution of flows has changed in the upper Murray, owing to the influence of dams. Flow-duration characteristics now vary considerably along the river, whereas there was little change under natural conditions. The effect of regulation on flow-duration characteristics is minimal at Albury and becomes more pronounced downstream; it is most apparent in regard to flows exceeded 20–80% of the time. The magnitude of average annual floods (annual exceedance probability 50%) has been reduced by over 50% at all stations, but big floods (average recurrence interval 20 years or more) are little affected. Further, the low flows for a given annual non-exceedance probability are higher under regulated conditions than those under natural conditions. These changes have profound implications for communities of native plants and animals in both riverine and floodplain environments, and also for the long-term utility of the river as a resource.     

Optimal parallel algorithms for rectilinear link-distance problems

We provide optimal parallel solutions to several link-distance problems set in trapezoided rectilinear polygons. All our main parallel algorithms are deterministic and designed to run on the exclusive read exclusive write parallel random access machine (EREW PRAM). LetP be a trapezoided rectilinear simple polygon withn vertices. InO(logn) time usingO(n/logn) processors we can optimally compute:

1. Minimum réctilinear link paths, or shortest paths in theL ₁ metric from any point inP to all vertices ofP.
2. Minimum rectilinear link paths from any segment insideP to all vertices ofP.
3. The rectilinear window (histogram) partition ofP.
4. Both covering radii and vertex intervals for any diagonal ofP.
5. A data structure to support rectilinear link-distance queries between any two points inP (queries can be answered optimally inO(logn) time by uniprocessor).

Our solution to 5 is based on a new linear-time sequential algorithm for this problem which is also provided here. This improves on the previously best-known sequential algorithm for this problem which usedO(n logn) time and space.5 We develop techniques for solving link-distance problems in parallel which are expected to find applications in the design of other parallel computational geometry algorithms. We employ these parallel techniques, for example, to compute (on a CREW PRAM) optimally the link diameter, the link center, and the central diagonal of a rectilinear polygon.     

Controlled Element Specific Nanoscale Domains by Self-Assembly for High Performance Bifunctional Alkaline Water Splitting Catalyst

A stable bifunctional water-splitting catalyst can simplify the development of alkaline medium electrolyzers. In this study, a catalytic material with controlled nanoscale domains of Pt and Ni is formed by a self-assembly process at room temperature. The final structure of the catalyst is achieved through two-stage transformation, first is the formation of Pt-Ni nanoscale domains and then inducing Ni to higher oxidation states. The material has a nanowire-like morphology at the macroscale, which ensures rapid kinetics and mass transfer. The results prove that the nanoscale domains of Pt, Ni, and Ni²⁺ and Ni³⁺ with close interfacing are crucial for the performance of the electrocatalyst and ensure the presence of Ni in a high oxidation state, leading to both hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) activity. The catalyst has a low overpotential and ultralow Tafel slope for both HER and OER, 13.7 and 32 mV dec⁻¹, respectively, crucial for high power applications.     

A Comprehensive Neural Network Model for Colorization and Captioning of Images Along with IoT Deployment

The convergence of artificial neural networks and the internet of things (IoT) has gained popularity in the field of computer science research. In this work, an efficient neural network model for the image colorization problem is proposed along with deploying these models to the remote system using IoT deployment tools. Further, this work proposed two convolution neural network models namely the Alpha model and Beta model towards solving the image colorization of the grayscale format. An efficient combination of models is proposed and analyzed such that the loss rate is minimized as?~?0.005. Next, an efficient model for solving image captioning is proposed based on the bi-directional long short term memory model. Finally, the work discusses the merits and demerits of deploying the neural network model using the AWS Greengrass and Docker IoT environment on remote systems.