In aspect-based sentiment analysis ABSA, implicit aspects extraction is a fine-grained task aim for extracting the hidden aspect in the in-context meaning of the online reviews. Previous methods have shown that handcrafted rules interpolated in neural network architecture are a promising method for this task. In this work, we reduced the needs for the crafted rules that wastefully must be articulated for the new training domains or text data, instead proposing a new architecture relied on the multi-label neural learning. The key idea is to attain the semantic regularities of the explicit and implicit aspects using vectors of word embeddings and interpolate that as a front layer in the Bidirectional Long Short-Term Memory Bi-LSTM. First, we

Roughness length is one of the key variables in micrometeorological studies and environmental studies in regards to describing development of cities and urban environments. By utilizing the three dimensions ultrasonic anemometer installed at Mustansiriyah university, we determined the rate of the height of the rough elements (trees, buildings and bridges) to the surrounding area of the university for a radius of 1 km. After this, we calculated the zero-plane displacement length of eight sections and calculated the length of surface roughness. The results proved that the ranges of the variables above are Z_H (9.2-13.8) m, Z_d (4.3-8.1) m and Z_o (0.24-0.48) m.

Background. “Polyetheretherketone (PEEK)” is a biocompatible, high-strength polymer that is well-suited for use in dental applications due to its unique properties. However, achieving good adhesion between PEEK and hydrophilic materials such as dental adhesives or cement can be challenging. Also, this hydrophobicity may affect the use of PEEK as an implant material. Surface treatment or conditioning is often necessary to improve surface properties. The piranha solution is the treatment of choice to be explored for this purpose. Methods. PEEK disks of 10 mm diameter and 2 mm thickness were used in this study. Those samples were divided into five groups (each group has five samples). The first is the control group, in which no

Highly Modified Asphalt (HiMA) binders have garnered significant attention due to their superior resistance to rutting, fatigue cracking, and thermal distress under heavy traffic loads and extreme environmental conditions. While elastomeric polymers such as Styrene- Butadiene-Styrene (SBS) have been extensively used in HiMA applications, the potential of plastomeric polymers, including Polyethylene (PE) and Ethylene Vinyl Acetate (EVA), remains largely unexplored. This study aims to evaluate the performance of reference binder (RB) modified with plastomeric HiMA asphalt in comparison to SBS-modified binders and determine the optimal polymer dosage for achieving an optimal balance between rutting resistance and fatigue durability. The experi

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

Coffee bean contains bioactive compounds including caffeine and chlorogenic acid (CGA) that have a stimulant effect and are used for combating fatigue and drowsiness, and enhancing alertness. However, when the coffee bean was processed in the form of green coffee bean (GCB) extract, it has an unpleasant flavour and limitations instability, activity, and bioavailability. This study aimed to produce microcapsules of the GCB (Coffea canephora) ethanolic extract containing considerable amounts of the bioactive compounds for nutraceutical supplements. The GCB ethanolic extract was microencapsulated by spray drying using a whey protein concentrate (WPC) biopolimer. The particle size (PSA), morphology (SEM), and physicochemical charact

n Segmented Optical Telescope (NGST) with hexagonal segment of spherical primary mirror can provide a 3 arc minutes field of view. Extremely Large Telescopes (ELT) in the 100m dimension would have such unprecedented scientific effectiveness that their construction would constitute a milestone comparable to that of the invention of the telescope itself and provide a truly revolutionary insight into the universe. The scientific case and the conceptual feasibility of giant filled aperture telescopes was our interested. Investigating the requirements of these imply for possible technical options in the case of a 100m telescope. For this telescope the considerable interest is the correction of the optical aberrations for the coming wavefront, th

Incremental sheet forming (ISF) is a metal forming technology in which small incremental deformations determine the final shape. The sheet is deformed by a hemispherical tool that follows the required shape contour to deform the sheet into the desired geometry. In this study, single point incremental sheet forming (SPIF) has been implemented in dentistry to manufacture a denture plate using two types of stainless steel, 304 and 316L, with an initial thickness of 0.5mm and 0.8mm, respectively. Stainless steel was selected due to its biocompatibility and reasonable cost. A three-dimensional (3D) analysis procedure was conducted to evaluate the manufactured part's geometrical accuracy and thickness distribution. The obtained results confirm