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

This paper is concerned with the numerical solutions of the vorticity transport equation (VTE) in two-dimensional space with homogenous Dirichlet boundary conditions. Namely, for this problem, the Crank-Nicolson finite difference equation is derived.  In addition, the consistency and stability of the Crank-Nicolson method are studied. Moreover, a numerical experiment is considered to study the convergence of the Crank-Nicolson scheme and to visualize the discrete graphs for the vorticity and stream functions. The analytical result shows that the proposed scheme is consistent, whereas the numerical results show that the solutions are stable with small space-steps and at any time levels.

Renewable energy technology is growing fast especially photovoltaic (PV) system to move the conventional electricity generation and distribution towards smart grid. However, similar to monthly electricity bill, the PV energy producers can only monitor their energy PV generation once a month. Any malfuntion in PV system components may reduce the performance of the system without notice. Thus, developing a real-time monitoring system of PV production is very crucial for early detection. In addition, electricity consumption is also important to be monitored more frequently to increase energy savings awareness among consumers. Hardware based Internet-of-Thing (IoT) monitoring and control system is widely used. However, the implementation of

Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D

Segmentation is the process of partition digital images into different parts depending on texture, color, or intensity, and can be used in different fields in order to segment and isolate the area to be partitioned. In this work images of the Moon obtained through observations in Astronomy and space dep. College of science university of Baghdad by ( Toward space telescopes and widespread used of a CCD camera) . Different segmentation methods were used to segment lunar craters. Different celestial objects cause craters when they crash into the surface of the Moon like asteroids and meteorites. Thousands of craters appears on the Moon's surface with ranges in size from meter to many kilometers, it provide insights into the age and ge

Plant regeneration protocols were developed for medicinally important anise (Pimpinella anisum L.) that successfully achieved from seeds. Seeds were sterilized and inoculated on Murashige and Skoog (MS) medium with and without gibberellins (GA3) until full germination. The highest percentage of germination (100%) was recorded on MS medium treated with 2.0 mg/L GA3 after 7 days. For shoot proliferation, different concentrations of 6- benzyl adenine BA (1, 1.5, 2 mg/L) were used. To enhance shoot induction, 0.1 mg/L of naphthalene acetic acid (NAA) and 0.01 mg/L of thidiazuron (TDZ) were tested along with BA. Direct regenerated shoots were obtained on MS medium supplemented with BA alone (2mg/L) which gave (7shoot/explant), while the presence

The research aims to apply the novel forward osmosis (FO) process to recover pure water
from contaminated water. Phenol was used as organic substance in the feed solution, while sodium
chloride salt was used as draw solution. Membranes used in the FO process is the cellulose
triacetate (CTA) and polyamide (thin film composite (TFC)) membrane. Reverse osmosis process
was used to treatment the draw solution, the exterior from the forward osmosis process. In the FO
process the active layer of the membrane faces the feed solution and the porous support layer faces
the draw solution and this will show the effect of dilutive internal concentration polarization and
concentrative external concentration polarization.
In th

Background: Acute radiodermatitis is a common side effect during and after radiotherapy course in breast cancer patients treated by radiotherapy. This study assess the frequency of acute radiodermatitis and record the predictive factors for acute radiodermatitis. Patients and Methods: A descriptive case series study conducted at Baghdad, Iraq from August 2020 to September 2021. 70 female scheduled for radiotherapy sessions enrolled in this study. sociodemographic data were recorded and Skin examination before radiotherapy and weekly till the end of the radiotherapy sessions was done to report the frequency, risk factors, clinical picture and grades of acute radiodermatitis based on The National Cancer Institute’s Common Terminology Crite