Implementation of VLSI on Signal Processing-Based Digital Architecture Using AES Algorithm

Continuous improvements in very-large-scale integration (VLSI) technology and design software have significantly broadened the scope of digital signal processing (DSP) applications. The use of application-specific integrated circuits (ASICs) and programmable digital signal processors for many DSP applications have changed, even though new system implementations based on reconfigurable computing are becoming more complex. Adaptable platforms that combine hardware and software programmability efficiency are rapidly maturing with discrete wavelet transformation (DWT) and sophisticated computerized design techniques, which are much needed in today’s modern world. New research and commercial efforts to sustain power optimization, cost savings, and improved runtime effectiveness have been initiated as initial reconfigurable technologies have emerged. Hence, in this paper, it is proposed that the DWT method can be implemented on a field-programmable gate array in a digital architecture (FPGA-DA). We examined the effects of quantization on DWT performance in classification problems to demonstrate its reliability concerning fixed-point math implementations. The Advanced Encryption Standard (AES) algorithm for DWT learning used in this architecture is less responsive to resampling errors than the previously proposed solution in the literature using the artificial neural networks (ANN) method. By reducing hardware area by 57%, the proposed system has a higher throughput rate of 88.72%, reliability analysis of 95.5% compared to the other standard methods.     

Disassembly Sequencing Using Tabu Search

End-of-life disassembly has developed into a major research area within the sustainability paradigm, resulting in the emergence of several algorithms and structures proposing heuristics techniques such as Genetic Algorithm (GA), Ant Colony Optimization (ACO) and Neural Networks (NN). The performance of the proposed methodologies heavily depends on the accuracy and the flexibility of the algorithms to accommodate several factors such as preserving the precedence relationships during disassembly while obtaining near- optimal and optimal solutions. This paper improves a previously proposed Genetic Algorithm model for disassembly sequencing by utilizing a faster metaheuristic algorithm, Tabu search, to obtain the optimal solution. The objectives of the proposed algorithm are to minimize (1) the traveled distance by the robotic arm, (2) the number of disassembly method changes, and (3) the number of robotic arm travels by combining the identical-material components together and hence eliminating unnecessary disassembly operations. In addition to improving the quality of optimum sequence generation, a comprehensive statistical analysis comparing the previous Genetic Algorithm and the proposed Tabu Search Algorithm is also included     

Array algorithms for H∞ estimation

We develop array algorithms for H^∞ filtering. These algorithms can be regarded as the Krein space generalizations of H ² array algorithms, which are currently the preferred method fur implementing H² filters. The array algorithms considered include two main families: square-root array algorithms, which are typically numerically more stable than conventional ones, and fast array algorithms which, when the system is time-invariant, typically offer an order of magnitude reduction in the computational effort. Both have the interesting feature that one does not need to explicitly check for the positivity conditions required for the existence of H^∞ filters, as these conditions are built into the algorithms themselves. However, since H^∞ square-root algorithms predominantly use J-unitary transformations, rather than the unitary transformations required in the H² case, further investigation is needed to determine the numerical behavior of such algorithms     

A fast and compact elimination method of empty elements from a double‐array structure

A double‐array is a well‐known data structure to implement the trie. However, the space efficiency of the double‐array degrades with the number of key deletions because the double‐array keeps empty elements produced by the key deletion. This paper presents a fast and compact elimination method of empty elements using properties of the trie nodes that have no siblings. The present elimination method is implemented by C language. From simulation results for large sets of keys, the present elimination method is about 30–330 times faster than the conventional elimination method and maintains high space efficiency. Copyright © 2003 John Wiley & Sons, Ltd.     

Green Synthesis of Silymarin–Chitosan Nanoparticles as a New Nano Formulation with Enhanced Anti-Fibrotic Effects against Liver Fibrosis

Background: Silymarin (SIL) has long been utilized to treat a variety of liver illnesses, but due to its poor water solubility and low membrane permeability, it has a low oral bioavailability, limiting its therapeutic potential. Aim: Design and evaluate hepatic-targeted delivery of safe biocompatible formulated SIL-loaded chitosan nanoparticles (SCNPs) to enhance SIL’s anti-fibrotic effectiveness in rats with CCl₄-induced liver fibrosis. Methods: The SCNPs and chitosan nanoparticles (CNPs) were prepared by ionotropic gelation technique and are characterized by physicochemical parameters such as particle size, morphology, zeta potential, and in vitro release studies. The therapeutic efficacy of successfully formulated SCNPs and CNPs were subjected to in vivo evaluation studies. Rats were daily administered SIL, SCNPs, and CNPs orally for 30 days. Results: The in vivo study revealed that the synthesized SCNPs demonstrated a significant antifibrotic therapeutic action against CCl₄-induced hepatic injury in rats when compared to treated groups of SIL and CNPs. SCNP-treated rats had a healthy body weight, with normal values for liver weight and liver index, as well as significant improvements in liver functions, inflammatory indicators, antioxidant pathway activation, and lipid peroxidation reduction. The antifibrotic activities of SCNPs were mediated by suppressing the expression of the main fibrosis mediators TGFβR1, COL3A1, and TGFβR2 by boosting the hepatic expression of protective miRNAs; miR-22, miR-29c, and miR-219a, respectively. The anti-fibrotic effects of SCNPs were supported by histopathology and immunohistochemistry (IHC) study. Conclusions: According to the above results, SCNPs might be the best suitable carrier to target liver cells in the treatment of liver fibrosis.     

Corrosion inhibition of steel by sodium sulphite

The corrosion inhibition of steel in a closed system containing sodium sulphite at room temperature has been established. Steady-state potential as well as weight loss measurements indicated that sodium sulphite did not only remove O₂ from the solution but also brought complete cathodic protection. It was found also that sodium sulphite could tolerate the presence of Cl^?, SO₄^2? and S^2?. In case of sulphite—sulphate or sulphite—chloride mixtures a concentration of 5 × 10^?3M Na₂SO₃ was required to tolerate a wide range of concentration of these aggressive ions. A linear relationship was found between log sulphite concentration and log maximum tolerated concentration of sulphide.     

Calculation of maximum surface settlement induced by EPB shield tunnelling and introducing most effective parameter

This study aims to predict ground surface settlement due to shallow tunneling and introduce the most affecting parameters on this phenomenon.Based on data collected from Shanghai LRT Line 2 project undertaken by TBM-EPB method,this research has considered the tunnel's geometric,strength,and operational factors as the dependent variables.At first,multiple regression(MR) method was used to propose equations based on various parameters.The results indicated the dependency of surface settlement on many parameters so that the interactions among different parameters make it impossible to use MR method as it leads to equations of poor accuracy.As such,adaptive neuro-fuzzy inference system(ANFIS),was used to evaluate its capabilities in terms of predicting surface settlement.Among generated ANFIS models,the model with all input parameters considered produced the best prediction,so as its associated R~2 in the test phase was obtained to be 0.957.The equations and models in which operational factors were taken into consideration gave better prediction results indicating larger relative effect of such factors.For sensitivity analysis of ANFIS model,cosine amplitude method(CAM) was employed; among other dependent variables,fill factor of grouting(n) and grouting pressure(P) were identified as the most affecting parameters.     

Synthesis and characterization of polyurethane – Treated waste milled light bulbs composites

In this study, polyurethane (PU)-milled light bulbs glass composites were synthesized and characterized. The main interest in this study that the polyurethane derived from renewable resources and waste glass are used to form the composite constituents as an attempt towards environmental preservation. Castor oil and polymeric diphenyl methane di-isocyanates (PMDI) were used in NCO/OH ratio = 2 for polyurethane synthesis. Milled glass with average particles size less than 300 μm were prepared based on waste light bulbs. Silane A1100 (as a compatibilizer) was used in order to improve the value of recycled milled glass beads. The adhesion force between polyurethane matrix and milled glass beads was evaluated using mechanical and physical tests. Scanning electron microscopy (SEM) was used to investigate dispersion and fracture surfaces of the composites. Infrared spectrum (IR), Differential scanning calorimetry (DSC) behavior, and Thermogravimetric analysis (TGA), were employed to characterize the developed composite materials in details. Chemical resistance (weight change, thickness swelling) was measured in oil, water and dilute acetic acid media. Furthermore, tensile strength and hardness were investigated using universal materials testing machines. A slight increase in the hardness values was reported along with the increasing in particulate fillers loading up to 10% as a considerable improvement has been detected when milled glass reached 20%. The DSC analysis showed the presence of treated milled glass beads influences the thermal behavior of pure PU and composites. This can be attributed to enhancing the physical bonding between PU and silica group. Waste milled glass showed a significant effect on the thermal degradation of the composites in the presence of coupling agent. Further analysis on the tensile strength of the composites indicated that such improved mechanical properties may be attributed to the presence of coupling agent.