Green nanotechnology is a thrilling and rising place of technology and generation that bracesthe ideas of inexperienced chemistry with ability advantages for sustainability, protection, andthe general protection from the race human. The inexperienced chemistry method introduces aproper technique for the production, processing, and alertness of much less dangerous chemicalsubstances to lessen threats to human fitness and the environment. The technique calls for inintensity expertise of the uncooked materials, particularly in phrases in their creation intonanomaterials and the resultant bioactivities that pose very few dangerous outcomes for peopleand the environment. In the twenty-first century, nanotechnology has become a systematic

This presented study is to make comparison of cross sections to produce 71As, 72As, 73As and 74As via different reactions with particle incident energy up to 60 MeV of alpha 100 MeV of proton as a part of systematic studies on particle-induced activations on enriched Ge, Ga, Rb and Nb targets and neutron capture. Theoretical calculation of production yield, and suggestion of optimum reaction to produce 71As, 72As, 73As and 74As, based on the main published and approved experimental results of excitation functions were calculated.

In this work, functionally graded materials were synthesized by centrifugal technique at different
volume fractions 0.5, 1, 1.5, and 2% Vf with a rotation speed of 1200 rpm and a constant rotation time, T
= 6 min . The mechanical properties were characterized to study the graded and non-graded nanocomposites
and the pure epoxy material. The mechanical tests showed that graded and non-graded added alumina
(Al2O3) nanoparticles enhanced the effect more than pure epoxy. The maximum difference in impact strength
occurred at (FGM), which was loaded from the rich side of the nano-alumina where the maximum value was
at 1% Vf by 133.33% of the sample epoxy side. The flexural strength and Young modulus of the fu

Two unsupervised classifiers for optimum multithreshold are presented; fast Otsu and k-means. The unparametric methods produce an efficient procedure to separate the regions (classes) by select optimum levels, either on the gray levels of image histogram (as Otsu classifier), or on the gray levels of image intensities(as k-mean classifier), which are represent threshold values of the classes. In order to compare between the experimental results of these classifiers, the computation time is recorded and the needed iterations for k-means classifier to converge with optimum classes centers. The variation in the recorded computation time for k-means classifier is discussed.

The support vector machine, also known as SVM, is a type of supervised learning model that can be used for classification or regression depending on the datasets. SVM is used to classify data points by determining the best hyperplane between two or more groups. Working with enormous datasets, on the other hand, might result in a variety of issues, including inefficient accuracy and time-consuming. SVM was updated in this research by applying some non-linear kernel transformations, which are: linear, polynomial, radial basis, and multi-layer kernels. The non-linear SVM classification model was illustrated and summarized in an algorithm using kernel tricks. The proposed method was examined using three simulation datasets with different sample

People’s ability to quickly convey their thoughts, or opinions, on various services or items has improved as Web 2.0 has evolved. This is to look at the public perceptions expressed in the reviews. Aspect-based sentiment analysis (ABSA) deemed to receive a set of texts (e.g., product reviews or online reviews) and identify the opinion-target (aspect) within each review. Contemporary aspect-based sentiment analysis systems, like the aspect categorization, rely predominantly on lexicon-based, or manually labelled seeds that is being incorporated into the topic models. And using either handcrafted rules or pre-labelled clues for performing implicit aspect detection. These constraints are restricted to a particular domain or language which is

This research is concerned with a new type of ferrocement characterized by its lower density and enhanced thermal insulation. Lightweight ferrocement plates have many advantages, low weight, low cost, thermal insulation, environmental conservation. This work contain two group experimental : first different of layer ferrocement, second different of ratio aggregate to cement. The experiments were made to determined the optimum proportion of cement and lightweight aggregate (recycle thermestone ). A low W/C ratio of 0.4 was used with super plasticizer conforming to ASTM 494 Type G. The compressive strength of the mortar mixes is 20-25 MPa. The work also involved the determination of thermal properties .Thermal conductivity value of thi