A new hybrid algorithm for global optimization and slope stability evaluation

A new hybrid optimization algorithm was presented by integrating the gravitational search algorithm （GSA） with the sequential quadratic programming （SQP）, namely GSA-SQP, for solving global optimization problems and minimization of factor of safety in slope stability analysis. The new algorithm combines the global exploration ability of the GSA to converge rapidly to a near optimum solution. In addition, it uses the accurate local exploitation ability of the SQP to accelerate the search process and find an accurate solution. A set of five well-known benchmark optimization problems was used to validate the performance of the GSA-SQP as a global optimization algorithm and facilitate comparison with the classical GSA. In addition, the effectiveness of the proposed method for slope stability analysis was investigated using three ease studies of slope stability problems from the literature. The factor of safety of earth slopes was evaluated using the Morgenstern-Price method. The numerical experiments demonstrate that the hybrid algorithm converges faster to a significantly more accurate final solution for a variety of benchmark test functions and slope stability problems.     

Preparation, Characterization and Thermal Degradation of Polyimide (4-APS/BTDA)/SiO(2) Composite Films

Polyimide/SiO(2) composite films were prepared from tetraethoxysilane (TEOS) and poly(amic acid) (PAA) based on aromatic diamine (4-aminophenyl sulfone) (4-APS) and aromatic dianhydride (3,3,4,4-benzophenonetetracarboxylic dianhydride) (BTDA) via a sol-gel process in N-methyl-2-pyrrolidinone (NMP). The prepared polyimide/SiO(2) composite films were characterized using X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), scanning electron microscope (SEM) and thermogravimetric analysis (TGA). The FTIR results confirmed the synthesis of polyimide (4-APS/BTDA) and the formation of SiO(2) particles in the polyimide matrix. Meanwhile, the SEM images showed that the SiO(2) particles were well dispersed in the polyimide matrix. Thermal stability and kinetic parameters of the degradation processes for the prepared polyimide/SiO(2) composite films were investigated using TGA in N(2) atmosphere. The activation energy of the solid-state process was calculated using Flynn-Wall-Ozawa's method without the knowledge of the reaction mechanism. The results indicated that thermal stability and the values of the calculated activation energies increased with the increase of the TEOS loading and the activation energy also varied with the percentage of weight loss for all compositions.     

Extraction,transesterification and process control in biodiesel production from Jatropha curcas

Biodiesel has gained worldwide popularity as an alternative energy source due to its renewable, non‐toxic, biodegradable and non‐flammable properties. It also has low emission profiles and is environmentally beneficial. Biodiesel can be used either in pure form or blended with conventional petrodiesel in automobiles without any major engine modifications. Various non‐edible and edible oils can be used for the preparation of biodiesel. With no competition with food uses, the use of non‐edible oils as alternative source for engine fuel will be important. Among the non‐edible oils, such as Pongamia, Argemone and Castor, Jatropha curcas has tremendous potential for biodiesel production. J. curcas, growing mainly in tropical and sub‐tropical climates across the developing world, is a multipurpose species with many attributes and considerable potentials. In this article, we review the oil extraction and characterization, the role of different catalysts on transesterification, the current state‐of‐the‐art in biodiesel production, the process control and future potential improvement of biodiesel production from J. curcas.     

Recovery of neutron-irradiation-induced defects of Al2O3, Y2O3, and yttrium-aluminum garnet

SiC fiber-reinforced SiC matrix composites (SiC_f/SiC) are considered as one of the candidates for blanket materials in future fusion reactors and as an advanced fuel cladding material for next-generation fission reactors. Generally, the densification of SiC needs sintering additives and oxides such as Al₂O₃, Y₂O₃, and yttrium-aluminum garnet (YAG, Y₃Al₅O₁₂), which are frequently added to SiC. However, the effects of neutron irradiation on sintering additives are still unclear. In this study, we performed the neutron irradiation of Al₂O₃, Y₂O₃, and YAG at fluences up to 2.0–2.5 × 10²⁴ n/m² (E > 0.1 MeV) at 60–90 °C. The isochronal recovery of the macroscopic volume of Al₂O₃ against annealing temperature showed smooth and continuous shrinkage at a temperature of up to 1200 °C, and the volume slightly increased above that temperature. In contrast, the volume of Y₂O₃ showed quick shrinkage at the low temperature range, and slower and smooth recovery was observed up to ～1100 °C. In the case of YAG, the recovery of volume occurred in a step-wise manner at 600–750 °C, and continuous shrinkage occurred at temperatures lower and higher than that temperature range. The activation energies for the macroscopic volume recoveries of three oxides were obtained from the Arrhenius plots of the rate coefficients. Two-stage recovery was observed for Al₂O₃, whereas more complicated recovery processes were suggested for Y₂O₃ and YAG.     

Spectral discrimination of healthy and Ganoderma-infected oil palms from hyperspectral data

Although hyperspectral remote sensing has been used to study many agricultural phenomena such as crop stress and diseases, the potential use of this technique for detecting Ganoderma disease infestations and damage to oil palms under field conditions has not been explored to date. This research was conducted to investigate the feasibility of using a portable hyperspectral remote-sensing instrument to identify spectral differences between oil-palm leaves with and without Ganoderma infections. Reflectance spectra of samples representative of three classes of disease severity were collected. The most significant bands for spectral discrimination were selected from reflectance spectra and first derivatives of reflectance spectra. The significant wavelengths were identified using one-way analysis of variance. Then, a Jeffries–Matusita (JM) distance measurement was used to determine spectral separability between the classes. A maximum likelihood classifier method was used to classify the three classes based on the most significant wavelength spectral responses, and an error matrix was finally used to assess the accuracy of the classification.     

Satellite remote sensing of deforestation in the Sungai Buloh Forest Reserve,Peninsular Malaysia

Deforestation has been a very critical environmental problem during the past few decades. Monitoring the Earth's surface conditions and their changes are essential to the management of this global environmental problem. Remote sensing can provide an effective 1001 for monitoring environmental changes on a global scale. This has focused attention on developing more effective and efficient techniques for the management and survey of forest areas. This study was designed to assess the feasibility of utilizing Landsat TM data in monitoring deforestation in the Sungai Buloh Forest Reserve. Detection of land cover change due to urbanization was performed using rnulti-tempora! data taken in 1988and 1991. An IDRISI image processing system was used to analyse the satellite data. Multi-temporal images were registered and spectral signatures of each point were directly compared. Correlation analysis was used to evaluate the similarity of two spectral signatures. A false colour composite image of bands 4, 5 and 3 (Red-Green-Blue) was used in unsupervised classification. For detection of land cover change, both multi-temporal images were overlaid and the area was calculated. The study revealed that the rate of deforestation in the Sungai Buloh Forest Reserve is about 182ha yr^-1 with an accuracy of 90·0 per cent.     

Four single-tooth implants as supernumerary premolars in the treatment of diastemas and microdontia: report of a case

The osseointegration concept involving single-tooth implants has become a valuable treatment component in many orthodontic situations. This case report illustrates the use of single-tooth implants as supernumerary teeth in the treatment of diastemas.     

Propagation of non-linear waves in a non-ideal relaxing gas

We have derived an evolution equation governing the far-field behaviour of small amplitude waves in a non-ideal relaxing gas for planar and converging flow. Asymptotic expansions of the flow variables for small amplitude waves have been used to derive the evolution equation. This equation turns out to be a generalized Burger's equation. The numerical solution of this equation is obtained by using the homotopy analysis method (HAM) proposed by Liao with two different initial conditions. Using the HAM, we have studied the effect of relaxation and nonlinearity. The convergence control parameter enables us to find a good approximate solution for such a complex flow problem. This method also confirms the capabilities and usefulness of convergence control parameter and HAM for complex and highly non-linear problems.     

Recent advancement in VM task allocation system for cloud computing: review from 2015 to2021

Cloud computing is new technology that has considerably changed human life at different aspect over the last decade. Especially after the COVID-19 pandemic, almost all life activity shifted into cloud base. Cloud computing is a utility where different hardware and software resources are accessed on pay per user ground base. Most of these resources are available in virtualized form and virtual machine (VM) is one of the main elements of visualization.VM used in data center for distribution of resource and application according to benefactor demand. Cloud data center faces different issue in respect of performance and efficiency for improvement of these issues different approaches are used. Virtual machine play important role for improvement of data center performance therefore different approach are used for improvement of virtual machine efficiency (i-e) load balancing of resource and task. For the improvement of this section different parameter of VM improve like makespan, quality of service, energy, data accuracy and network utilization. Improvement of different parameter in VM directly improve the performance of cloud computing. Therefore, we conducting this review paper that we can discuss about various improvements that took place in VM from 2015 to 20,201. This review paper also contain information about various parameter of cloud computing and final section of paper present the role of machine learning algorithm in VM as well load balancing approach along with the future direction of VM in cloud data center.