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 design,analysis, and cost estimation of a generic adder and subtractor using the layered T (LT) logic reduction methodology with a quantum-dot cellular-automata-based approach

The quantum-dot cellular automata (QCA) is considered to be one of the ground-breaking nanotechnologies developed over the last two decades. A layered T (LT) logic cell library is constructed herein, and the methodology is extended to generic adder and subtractor module designs. The two proposed algorithms lead to more efficient QCA layout designs for an n-bit ripple carry adder (RCA) and subtractor based on an effective clock zone assignment approach. The suggested one-, four-, and eight-bit RCAs and subtractors surpass most of their existing counterparts by offering lower effective area and cell complexity. A comparative analysis is presented regarding the complexity, irreversible power dissipation, and Cost_α of the proposed n-bit layouts from a cost estimation purview.

     

Developing a Dynamic Cluster Quantization based Lossless Audio Compression (DCQLAC)

In this paper, an approach has been made to produce a compressed audio without losing any information. The proposed scheme is fabricated with the help of dynamic cluster quantization followed by Burrows Wheeler Transform (BWT) and Huffman coding. The encoding algorithm has been designed in two phases, i.e., dynamic cluster selection (of sampled audio) followed by dynamic bit selection for determining quantization level of individual cluster. Quantization level of each cluster is selected dynamically based on mean square quantization error (MSQE). Bit stream is further compressed by applying Burrows Wheeler Transform (BWT) and Huffman code respectively. Experimental results are supported with current state-of-the-art in audio quality analysis (like statistical parameters (compression ratio, space savings, SNR, PSNR) along with other parameters (encoding time, decoding time, Mean Opinion Score (MOS) and entropy) and compared with other existing techniques.

     

Catalytic Vicinal Diacylation of Epoxidized Triglycerides in Canola Oil

The epoxy ring opening and vicinal diacylation of fatty acids in vegetable oils was found to be promising reaction to synthesize stable biolubricants and bioplasticizers. The current research investigation is emphasized on the synthesis of a value added product vicinally diacylated canola oil by sulfated‐ZrO₂. The two‐step research approach employed includes: (i) epoxidation, and (ii) epoxy ring opening and vicinal diacylation of epoxidized triglycerides in the canola oil. Sulfated‐ZrO₂ was prepared and characterized to measure the physico‐chemical properties required for the effective catalysis. The Taguchi (L16 orthogonal array) statistical design method was employed to optimize the process conditions for the maximum formation of diacylated canola oil. Sulfated‐ZrO₂ demonstrated promising activity for the epoxy ring opening and vicinal diacylation of canola oil, and 99 % conversion was achieved at the optimum process conditions of temperature 130 °C, epoxy to acetic anhydride molar ratio (1:1.25), 16 wt% of catalyst loading and reaction time of 1 h which were inferred from the Taguchi analyses. The products were characterized and confirmed with FT‐IR, ¹H NMR and sodium spray mass spectroscopy. Spectroscopic analysis also confirmed the absence of intermediate products. The statistical analyses was undertaken to determine the order, rank and interactions among the process variables. The reaction followed Langmuir–Hinshelwood–Hougen–Watson type mechanism and the kinetic data was fitted in overall second order equation. Calculated apparent activation energy was 23.1 kcal/mol.     

Physical and mathematical modelling of flow and residence time distributions in different tundish designs

A steady state, three‐dimensional, turbulent flow model has been developed in‐house for analysis of melt flow and residence time distribution phenomena in steelmaking tundish system. The governing equations of flow, turbulence and tracer dispersion were derived in terms of the Cartesian co‐ordinate systems and solved numerically with their associated boundary conditions adapting a control volume based finite difference procedure. In the numerical solution scheme, the pressure‐velocity coupling was treated via the popular Simple (semi implicit method for pressure linked equations) algorithm. Prior to carrying out elaborate numerical predictions for tundish geometry, the model was applied to several standard test problems and evaluated against corresponding bench mark results. Thus, several typical test problems such as, flows in a cubic cavity, flows in ducts of rectangular cross‐section, flow over flat plate and so on were simulated numerically to assess the adequacy and appropriateness of the computational procedure developed. Results thus obtained together with the bench mark solutions indicated that the mathematical model is internally consistent and sufficiently robust. Accordingly, the turbulent flow model was applied to simulate flow and Residence Time Distributions (RTD) in four different tundish designs . These included, a single strand and a two strand slab casting tundish systems, a six strand rectangular shaped tundish and a six strand delta shaped billet casting tundish. Various RTD parameters (e.g., minimum break through time, t_min, time at which peak concentration occurs, t_peak and average residence time, t_av) were computed numerically in the four tundish systems and these were subsequently compared with corresponding experimental measurements derived from equivalent water model tundish systems. Except for the single strand tundish system, large differences between measurements and prediction (particularly on t_min and t_peak) were noted for the other three tundish geometries. Furthermore, the extent of such discrepancy was found to be relatively more pronounced for the multi‐strand tundish system. The possible reasons for such discrepancy is discussed in the text and it was shown computationally that relatively better agreement between theory and measurement can be achieved if, instead of the high Reynolds number k‐ε turbulence model, a low Reynolds number turbulence model is applied in the computational procedure.     

Simultaneous Optimization of Luminance and Color Chromaticity of Phosphors Using a Nondominated Sorting Genetic Algorithm

Acquiring materials that simultaneously meet two or more conflicting requirements is very difficult. For instance, a situation wherein the color chromaticity and photoluminescence (PL) intensity of phosphors conflict with one another is a frequent problem. Therefore, identification of a good phosphor that simultaneously exhibits both desirable PL intensity and color chromaticity is a challenge. A high‐throughput synthesis and characterization strategy that was reinforced by a nondominated sorting genetic algorithm (NSGA)‐based optimization process was employed to simultaneously optimize both the PL intensity and color chromaticity of a MgO–ZnO–SrO–CaO–BaO–Al₂O₃–Ga₂O₃–MnO system. NSGA operations, such as Pareto sorting and niche sharing, and the ensuing high‐throughput synthesis and characterization resulted in identification of promising green phosphors, i.e., Mn²⁺‐doped AB₂O₄ (A = alkali earth, B = Al and Ga) spinel solid solutions, for use in either plasma display panels or cold cathode fluorescent lamps.     

Application of artificial neural network for the prediction of laser cladding process characteristics at Taguchi-based optimized condition

This paper presents an investigation on the optimization of multiple performance characteristics during CO₂ laser cladding process considering clad width and clad depth as performance characteristics. This optimization for multiple quality characteristics has been done using Taguchi’s quality loss function. The process model for laser cladding operation using various techniques like artificial neural network (ANN) has rarely been found in the literature review. In the present work, a number of experiments have been performed to establish the interrelationship between process variables and response variables using the back propagation method of ANN. The essential input process parameters are identified as laser power, scan speed of work table, and powder feed rate. Moreover, the analysis of variance is also employed to determine the contribution of each control parameter on clad bead quality. In order to validate the predicted result, an experiment as confirmatory test is carried out at the optimized cladding condition. It is observed that the confirmatory experimental result is showing a good agreement with the predicted one. However, it has been found that the optimum condition of the cladding parameters for multi-performance characteristics varies with the different combinations of weighting factors.     

Association and dissociation kinetics of bobwhite quail lysozyme with monoclonal antibody HyHEL-5

The anti-hen egg lysozyme monoclonal antibody HyHEL-5 and itscomplexes with various species-variant and mutant lysozymeshave been the subject of considerable experimental and theoreticalinvestigation. The affinity of HyHEL-5 for bobwhite quail lysozyme(BWQL) is over 1000-fold lower than its affinity for the originalantigen, hen egg lysozyme (HEL). This difference is believedto arise almost entirely from the replacement in BWQL of thestructural and energetic epitope residue Arg68 by lysine. Inthis study, the association and dissociation kinetics of BWQLwith HyHEL-5 were investigated under a variety of conditionsand compared with previous results for HEL. HyHEL-5–BWQLassociation follows a bimolecular mechanism and the dissociationof the antibody–antigen complex is a first-order process.Changes in ionic strength (from 27 to 500 mM) and pH (from 6.0to 10.0) produced about a 2-fold change in the association anddissociation rates. The effect of viscosity modifiers on theassociation reaction was also studied. The large differencein the HEL and BWQL affinities for HyHEL-5 is essentially dueto differences in the dissociation rate constant.     

Combined quality loss (CQL) concept in WPCA-based Taguchi philosophy for optimization of multiple surface quality characteristics of UNS C34000 brass in cylindrical grinding

The present study highlights a multi-objective optimization problem by applying Weighted Principal Component Analysis (WPCA) coupled with Taguchi method through a case study in cylindrical grinding of UNS C34000 Medium Leaded Brass. The study aimed at evaluating the best process environment which could simultaneously satisfy multiple requirements of surface quality. In view of the fact that traditional Taguchi method fails to solve a multi-objective optimization problem, to overcome this limitation, WPCA has been coupled with Taguchi method. Furthermore, to follow the basic assumption of Taguchi method, i.e., quality attributes should be uncorrelated or independent; which is not always satisfied in practical situation; the study applied WPCA to eliminate response correlation and to evaluate independent or uncorrelated quality indices called principal components which were aggregated by WPCA to compute overall quality index denoted as Multi-Response Performance Index. A combined quality loss was then estimated which was optimized (minimized) finally. The study combined WPCA and Taguchi method for predicting optimal setting. Optimal result was verified through confirmatory test. This indicates application feasibility of the aforesaid methodology proposed for multi-response optimization and off-line control of correlated multiple surface quality characteristics in cylindrical grinding.     

Error Detecting Dual Basis Bit Parallel Systolic Multiplication Architecture over GF（2^m）

An error tolerant hardware efficient verylarge scale integration （VLSI） architecture for bitparallel systolic multiplication over dual base, which canbe pipelined, is presented. Since this architecture has thefeatures of regularity, modularity and unidirectionaldata flow, this structure is well suited to VLSIimplementations. The length of the largest delay pathand area of this architecture are less compared to the bitparallel systolic multiplication architectures reportedearlier. The architecture is implemented using Austria Micro System＇s 0.35 μm CMOS （complementary metaloxide semiconductor） technology. This architecture canalso operate over both the dual-base and polynomialbase.