Visibility improvement of underwater turbid image using hybrid restoration network with weighted filter

Due to the attenuation of light passes through water, the captured underwater images suffer from low-contrast, halo artifacts, etc. To address this issue, the hybrid network with a weighted filter is proposed to improve the visibility of the obscured (turbid) images. In the captured image, the brighter pixels (near-to-source) are called foreground regions and the darker pixels (far-from-source) are called background regions. In order to ensure the adaptability of the proposed algorithm, the considered datasets are collected on different atmospheric light such as pond, lake, and fisheries tank. The foreground area of an image can be enhanced using the thresholding and masking technique. The background hazy region can be recovered by a hybrid Dehazenet called Generative Adversarial Network and Convolutional Neural Network. With this, the transmission map with high accuracy and color deviation can be addressed. Then both the regions are blended and the Amended Unsharp Mask filter is used to toughen the distorted edges. Finally, the blended restored image is weighted with a contrast factor to obtain the visibility improved image. The subjective and objective evaluation is done on considering the standard non-reference metric called Underwater Image Quality Measure comprises measures of color, sharpness, and contrast for a variety of water types with different atmospheric light. It is observed that the proposed technique showed a metric improvement of 57% compared to other existing techniques in an average manner. Overall, it is inferred that the proposed technique produces better results in both subjective and objective evaluation, thus it outperforms other state-of-the-art techniques.

     

Si diffusion in GaAs

Theoretical studies are carried out to ascertain the dominant mechanism of Si diffusion in GaAs. Lattice dynamical model calculations have shown that the most probable diffusion mechanism is through a single vacancy even though several experiments cannot fix the mechanism as substitutional, substitutional-interstitial pair or neutral defect pair.     

Parallel pattern identification in biological sequences on clusters

Tandem repeats are ubiquitous sequence features in both prokaryotic and eukaryotic genomes. They are known to cause several inherited neurological diseases in humans. Identifying these patterns is a highly computation-intensive process. Previous parallel implementations use straightforward domain decomposition based on existing sequential algorithms and rely on parallel machines with low-latency interconnection network and fast hardware support for processor synchronization. Our research exploits the superior cost effectiveness and flexibility achieved through low-cost clusters to speed up biological computations by designing communication-efficient parallel algorithms for pattern identification. This paper presents a low communication-overhead parallel algorithm for pattern identification in biological sequences. Given a biological sequence of length n and a pattern of length m, we conclude an algorithm with five computation/communication phases, each requiring O(n) computation time and only O(p) message units. The low communication overhead of the algorithm is essential in achieving reasonable speedups on clusters, where the interprocessor communication latency is usually higher.     

The Final Case of the Decoding Delay Problem for Maximum Rate Complex Orthogonal Designs

Complex orthogonal space-time block codes (COSTBCs) based on generalized complex orthogonal designs (CODs) have been successfully implemented in wireless systems with multiple transmit antennas and single or multiple receive antennas. It has been shown that for a maximum rate COD with 2m-1 or 2m columns, a lower bound on decoding delay is (_m-1 ^2m) and this delay is achievable when the number of columns is congruent to 0, 1 , or 3 modulo 4. In this paper, the final case is addressed, and it is shown that when the number of columns is congruent to 2 modulo 4, the lower bound on decoding delay cannot be achieved. In this case, the shortest decoding delay a maximum rate COD can achieve is twice the lower bound. New techniques for analyzing CODs are introduced with connections to binary vector spaces.     

Optimization of hybrid laser–TIG welding of 316LN stainless steel using genetic algorithm

Determination of optimum hybrid laser–TIG welding process variables for achieving the maximum depth of penetration (DOP) in type 316LN stainless steel has been carried out using a genetic algorithm (GA). Nd:YAG pulsed laser and the TIG heat source were coupled at the weld pool to carry out hybrid welding. Design of experiments approach was used to generate the experimental design matrix. Bead-on-plate welds were carried out based on the design matrix. The input variables considered were laser power, pulse frequency, pulse duration, and TIG current. The response variable considered was the DOP. Multiple-regression model was developed correlating the process variables with the DOP using the generated data. The regression model was used for evaluating the objective function in GA. GA-based model was developed and it produced a set of solutions. Tournament and roulette wheel selection methods were used during the execution of GA. It was found that both the selection methods identified similar welding process parameters for achieving the maximum DOP. Excellent agreement was observed between the target DOP and the DOP values obtained in the validation experiments during hybrid laser–TIG welding.     

Synthesis of novel Cu doped anatase TiO<Subscript>2</Subscript> catalysts and assessment of the influence of Nb concentration on the photocatalytic and electrochemical properties

In the present study, Cu doped (Ti_0.8Cu_xO_2?x/2) and (Cu, Nb) co-doped (Ti_0.8Cu_x?y Nb_yO_2?(x?y/2+y)) TiO₂ photocatalysts were fabricated by sol–gel method. The catalysts were polycrystalline in nature with preferential orientation along (101) plane answering to anatase phase of TiO₂. Higher Nb concentration results in the formation of secondary phase (Nb₂O₅). A decrease in average crystallite size was noticed with the addition of Nb concentration in Cu doped TiO₂ photocatalyst. The formation of anatase phase was also fixed by Raman spectra. The TEM photograph confirmed the co-doped TiO₂ photocatalyst in nanometer range of about 15 nm and the particles were in hexagonal shape. The doping of Nb⁵⁺ ions inspired a shift in the absorption threshold towards the visible spectral range (red shift) compared to Cu doped TiO₂ catalyst. The photocatalysts have direct bandgaps of 3.253 to 2.974 eV. Semiconducting properties were investigated through electrochemical impedance spectroscopy. The results indicate that the presence of Nb⁵⁺ ions into Cu doped TiO₂ has enhanced the efficiency of electrochemical conductivity. Photocatalytic performance was assessed from the sample degradation by illuminating methylene blue dye under visible light exposure. It is found that TCN3 photocatalyst bleaches MB much faster than all others. Also it exhibits great improvement of photocatalytic activity (96.86%) within 120 min. The photocatalytic degradation process is explained using the pseudo first order kinetics and it fits well with higher correlation coefficient. All these analyses elucidate that the incorporation of Nb⁵⁺ ions might tune the structural, optical, electrochemical and phocatalytic properties of Cu doped TiO₂ photocatalysts.     

2D-titanium carbide (MXene) based selective electrochemical sensor for simultaneous detection of ascorbic acid,dopamine and uric acid

Two-dimensional (2D) titanium carbide (MXene) nanosheets exhibited excellent conductivity,flexibility,high volumetric capacity,hydrophilic surface,thermal stability,etc.So,it has been exploited in various applications.Herein,we report synthesis of mixed phase 2D MXene as a catalytic material for simultaneous detection of important biomolecules such as ascorbic acid (AA),dopamine (DA) and uric acid (UA),Crystalline structure,surface morphology and elemental composition of mixed phase titanium carbide (Ti-C-Tx) MXene (Tx =-F,-OH,or-O) nanosheets were confirmed by X-ray diffraction (XRD),Raman spectroscopy,high-resolution transmission electron microscopy (HR-TEM),high-resolution scanning electron microscopy (HR-SEM) and Energy-dispersive X-ray spectroscopy (EDS) mapping analysis.Furthermore,Ti-C-Tx modified glassy carbon electrode (GCE) was prepared and its electrochemical properties are studied by cyclic voltammetry (CV) and differential pulse voltammetry (DPV).It was found that Ti-C-Tx modified GCE (Ti-C-Tx/GCE) showed excellent electrocatalytic activity and separated oxidation peaks of important biomolecules such as AA (at 0.01 V),DA (at 0.21 V) and UA (at 0.33 V).Also,Ti-C-Tx/GCE sensor is enabled their simultaneous detection in physiological pH from 100 to 1000 μM for AA,0.5-50 μM for DA and 0.5-4 μM & 100-1500 μM for UA.The limit ofdetection's (LOD) was estimated as 4.6 μM,0.06 μM and 0.075 μM for AA,DA and UA,respectively.Moreover,real sample analysis indicated that spiked AA,DA and UA can be determined accurately by Ti-C-Tx/GCE with the recovery ratio in the range between 100.5％-103％ in human urine samples.The proposed Ti-C-Tx modified electrode exhibited good stability,selectivity and reproducibility as an electrochemical sensor for the detection ofAA,DA and UA molecules.     

Effect of microarc oxidised layer thickness on plain fatigue and fretting fatigue behaviour of Al–Mg–Si alloy

The objective of this work was to investigate the performance of microarc oxide coatings of two different thicknesses (40 and 100 μm) on Al–Mg–Si alloy samples under plain fatigue and fretting fatigue loadings. Tensile residual stress present in the substrate of 40 μm thick coated samples induced early crack initiation in the substrate and so their plain fatigue lives were shorter than those of untreated specimens. Presence of more pores and tensile surface residual stress in 100 μm thick coated samples caused early crack initiation at the surface leading to their inferior plain fatigue lives compared with 40 μm thick coated samples. While the differences between the lives of coated and uncoated specimens were significant under plain fatigue loading, this was not the case under fretting fatigue loading. This may be attributed to relatively higher surface hardness of coated specimens. The performance of 40 μm thick coated samples was better than that of 100 μm thick coated specimens under both plain fatigue and fretting fatigue loadings.     

Additive Number Theory via Automata Theory

Theory of Computing Systems - We show how some problems in additive number theory can be attacked in a novel way, using techniques from the theory of finite automata. We start by recalling the...     

Optimal Parallel Randomized Algorithms for the Voronoi Diagram of Line Segments in the Plane

Abstract. We present an optimal parallel randomized algorithm for the Voronoi diagram of a set of n nonintersecting (except possibly at endpoints) line segments in the plane. Our algorithm runs in O(log n) time with high probability using O(n) processors on a CRCW PRAM. This algorithm is optimal in terms of work done since the sequential time bound for this problem is Ω(n log n) . Our algorithm improves by an O(log n) factor the previously best known deterministic parallel algorithm, given by Goodrich, ó'Dúnlaing, and Yap, which runs in O( log ² n) time using O(n) processors. We obtain this result by using a new ``two-stage' random sampling technique. By choosing large samples in the first stage of the algorithm, we avoid the hurdle of problem-size ``blow-up' that is typical in recursive parallel geometric algorithms. We combine the two-stage sampling technique with efficient search and merge procedures to obtain an optimal algorithm. This technique gives an alternative optimal algorithm for the Voronoi diagram of points as well (all other optimal parallel algorithms for this problem use the transformation to three-dimensional half-space intersection).