Impact of Climate Change on Future Flood Susceptibility: an Evaluation Based on Deep Learning Algorithms and GCM Model

Floods are common and recurring natural hazards which damages is the destruction for society. Several regions of the world with different climatic conditions face the challenge of floods in different magnitudes. Here we estimate flood susceptibility based on Analytical neural network (ANN), Deep learning neural network (DLNN) and Deep boost (DB) algorithm approach. We also attempt to estimate the future rainfall scenario, using the General circulation model (GCM) with its ensemble. The Representative concentration pathway (RCP) scenario is employed for estimating the future rainfall in more an authentic way. The validation of all models was done with considering different indices and the results show that the DB model is most optimal as compared to the other models. According to the DB model, the spatial coverage of very low, low, moderate, high and very high flood prone region is 68.20%, 9.48%, 5.64%, 7.34% and 9.33% respectively. The approach and results in this research would be beneficial to take the decision in managing this natural hazard in a more efficient way.

     

The effect of overload on the fatigue crack propagation in metastable beta Ti-V alloys

The effects of overload on the fatigue crack propagation behavior of two Ti-V alloys having different deformation mechanisms were studied. The results are explained in terms of residual stress effects associated with the overload and the removal of these stresses during post-overload cycling. An additional effect occurs during multiple cycle overload when the deformation structure representative of the strain amplitude is believed to form in the overload reverse plastic zone. This structure must be rearranged during cycling at ΔK _b before the baseline FCGR is reached and the process is responsible for part of the delay period. Formerly Research Scientist at Georgia Institute of Technology.     

Correction to: An improved binary sparrow search algorithm for feature selection in data classification

Neural Computing and Applications -     

An Improved Jellyfish Algorithm for Multilevel Thresholding of Magnetic Resonance Brain Image Segmentations

Image segmentation is vital when analyzing medical images, especially magnetic resonance (MR) images of the brain. Recently, several image segmentation techniques based on multilevel thresholding have been proposed for medical image segmentation; however, the algorithms become trapped in local minima and have low convergence speeds, particularly as the number of threshold levels increases. Consequently, in this paper, we develop a new multilevel thresholding image segmentation technique based on the jellyfish search algorithm (JSA) (an optimizer). We modify the JSA to prevent descents into local minima, and we accelerate convergence toward optimal solutions. The improvement is achieved by applying two novel strategies: Ranking-based updating and an adaptive method. Ranking-based updating is used to replace undesirable solutions with other solutions generated by a novel updating scheme that improves the qualities of the removed solutions. We develop a new adaptive strategy to exploit the ability of the JSA to find a best-so-far solution; we allow a small amount of exploration to avoid descents into local minima. The two strategies are integrated with the JSA to produce an improved JSA (IJSA) that optimally thresholds brain MR images. To compare the performances of the IJSA and JSA, seven brain MR images were segmented at threshold levels of 3, 4, 5, 6, 7, 8, 10, 15, 20, 25, and 30. IJSA was compared with several other recent image segmentation algorithms, including the improved and standard marine predator algorithms, the modified salp and standard salp swarm algorithms, the equilibrium optimizer, and the standard JSA in terms of fitness, the Structured Similarity Index Metric (SSIM), the peak signal-to-noise ratio (PSNR), the standard deviation (SD), and the Features Similarity Index Metric (FSIM). The experimental outcomes and the Wilcoxon rank-sum test demonstrate the superiority of the proposed algorithm in terms of the FSIM, the PSNR, the objective values, and the SD; in terms of the SSIM, IJSA was competitive with the others.     

The effect of ion implantation on cyclic stress-strain response of polycrystalline copper

The effect of aluminum and boron ion implantation on strain-controlled (low cycle) and stress-controlled (high cycle) fatigue behavior of polycrystalline copper was investigated. The cyclic stress-strain, strain-life and stress-life relations, cyclic slip and crack nucleation behavior of implanted copper are compared with those of unimplanted copper.Under strain control, ion-implanted samples show a lower degree of cyclic hardening and longer fatigue lives than their non-implanted counterparts. Aluminum implantation has a larger effect than boron implantation. Under stress control the fatigue life and the fatigue limit are observed to increase for the aluminum-implanted samples compared with their non-implanted counterparts. These changes in fatigue behavior are associated with changes in deformation behavior in the surface region and surface residual stresses created by ion implantation.     

The effect of microstructure on the deformation modes and mechanical properties of Ti-6Al-2Nb-1Ta-0.8Mo: Part I. Widmanstätten structures

An alpha + beta Ti-6Al-2Nb-lTa-0.8Mo alloy with an initial Widmanstätten structure was thermally treated to produce a wide range of microstructures. The effects of individual microstructural parameters on deformation behavior and mechanical properties were investigated. The results show that the Widmanstätten colony boundaries are major barriers to slip. However, the slip distance can be decreased to a distance equal to the thickness of acicular alpha by transforming the beta phase in the Widmanstätten structure to martensite by quenching from 950°C. The decrease in slip distance is accompanied by a 25 pct increase in yield strength with no loss in ductility. A large decrease in ductility occurs after excursions above the beta-transus. The development of both equiaxed beta grains during heating in the beta phase field and continuous grain boundary alpha during cooling in the alpha + beta phase field leads to strain localization along prior beta grain boundaries.     

Microstructure-property relationships of two AI-3Li-2Cu-0.2Zr-XCd alloys

The microstructure and tensile properties of two A1-3 wt pct Li-2 wt pct Cu-0.2 wt pct Zr alloys, one Cd-free and one containing 0.2 wt pct Cd, have been investigated. The Cd-free alloy remained unrecrystallized for all solutionizing treatments studied, whereas a special treatment had to be developed to prevent recrystallization during solutionizing of the 0.2 wt pct Cd alloy. In combination with cadmium, zirconium either enters into, or nucleates on, the course Al₇Cu₂Fe and T₂ phases during high temperature annealing. This reduces the volume fraction of small coherent Al₃Zr particles in the matrix which normally inhibits recrystallization. Consequently, a low temperature anneal to precipitate Al₃Zr is necessary prior to high temperature solutionizing in order to prevent recrystallization in the Cd-containing alloy. Unlike its effect in lower lithium, higher copper content aluminum alloys, cadmium does not significantly affect the nucleation of the strengthening precipitates. If anything, cadmium has a detrimental effect on the age hardening response of this alloy, since it increases the formation of coarse Al-Cu-Li equilibrium phases at grain and subgrain boundaries and thus removes some of the copper and lithium from participating in the formation of the strengthening precipitates T₁ and δ′. Subgrain boundary fracture occurred during tensile tests of both alloys in the unrecrystallized condition; however, transgranular fracture occurred in tests of the partially recrystallized 0.2 wt pct Cd alloy. Both types of fractures are believed due to a form of strain localization associated with precipitate free zones and shearable precipitates. Formerly with the Fracture and Fatigue Research Laboratory, Georgia Institute of Technology, Atlanta, GA     

Multi‐mode resource‐constrained project scheduling using modified variable neighborhood search heuristic

This paper aims at providing a fast near‐optimum solution to the multi‐mode resource‐constrained project scheduling problems (MRCPSPs), for projects with activities that have known deterministic renewable and nonrenewable resource requirements. The MRCPSP is known to be nondeterministic polynomial‐time hard and has been solved using various exact, heuristic, and meta‐heuristic procedures. In this paper, a modified variable neighborhood search heuristic algorithm is used as an advanced optimization technique that suits scheduling problems. For the experimental study, we have considered a standard set of 3929 multi‐mode benchmark instances from the project scheduling library with a range of projects comprising 10–30 activities. Moreover, for a better comparison, this research also considers a standard set of 4320 newly developed multi‐mode instances from MMLIB50, MMLIB100, and MMLIB+ datasets. With the limit of 50,000 schedules on these datasets, our proposed algorithm provides better makespan for 106, 34, and 1601 instances, respectively, which justifies the efficiency of the proposed algorithm, particularly for projects with a larger number of activities. The results reported in this paper can be used as a benchmark for other researchers to compare and improve.     

A two-species model of a two-dimensional sandpile surface: a case of asymptotic roughening

We present and analyze a model of an evolving sandpile surface in (2 + 1) dimensions where the dynamics of mobile grains (ρ(x, t)) and immobile clusters (h(x, t)) are coupled. Our coupling models the situation where the sandpile is flat on average, so that there is no bias due to gravity. We find anomalous scaling: the expected logarithmic smoothing at short length and time scales gives way to roughening in the asymptotic limit, where novel and non-trivial exponents are found.