Continuous escalation of the cost of generating energy is preceded by the fact of scary depletion of the energy reserve of the fossil fuels and pollution of the environment as developed and developing countries burn these fuels. To meet the challenge of the impending energy crisis, renewable energy has been growing rapidly in the last decade. Among the renewable energy sources, solar energy is the most extensively available energy, has the least effect on the environment, and is very efficient in terms of energy conversion. Thus, solar energy has become one of the preferred sources of renewable energy. Flat-plate solar collectors are one of the extensively-used and well-known types of solar collectors. However, the effectiveness of the coll

In this study, gold nanoparticles were synthesized in a single step biosynthetic method using aqueous leaves extract of thymus vulgaris L. It acts as a reducing and capping agent. The characterizations of nanoparticles were carried out using UV-Visible spectra, X-ray diffraction (XRD) and FTIR. The surface plasmon resonance of the as-prepared gold nanoparticles (GNPs) showed the surface plasmon resonance centered at 550[Formula: see text]nm. The XRD pattern showed that the strong four intense peaks indicated the crystalline nature and the face centered cubic structure of the gold nanoparticles. The average crystallite size of the AuNPs was 14.93[Formula: see text]nm. Field emission scanning electron microscope (FESEM) was used to s

The growing use of tele

This paper presents a new secret diffusion scheme called Round Key Permutation (RKP) based on the nonlinear, dynamic and pseudorandom permutation for encrypting images by block, since images are considered particular data because of their size and their information, which are two-dimensional nature and characterized by high redundancy and strong correlation. Firstly, the permutation table is calculated according to the master key and sub-keys. Secondly, scrambling pixels for each block to be encrypted will be done according the permutation table. Thereafter the AES encryption algorithm is used in the proposed cryptosystem by replacing the linear permutation of ShiftRows step with the nonlinear and secret pe

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

                The characteristics of sulfur nanoparticles were studied by using atomic force microscope (AFM) analysis. The atomic force microscope (AFM) measurements showed that the average size of sulfur nanoparticles synthesized using thiosulfate sodium solution through the extract of cucurbita pepo extra was 93.62 nm. Protecting galvanized steel from corrosion in salt media was achieved by using sulfur nanoparticles in different temperatures. The obtained data of thermodynamic in the presence of sulfur nanoparticles referred to high value as compares to counterpart in the absence of sulfur nanoparticles, the high inhibition efficiency (%IE) and corrosion resistance were at high temperature, the corrosion rate or weig

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

Many objective optimizations (MaOO) algorithms that intends to solve problems with many objectives (MaOP) (i.e., the problem with more than three objectives) are widely used in various areas such as industrial manufacturing, transportation, sustainability, and even in the medical sector.  Various approaches of MaOO algorithms are available and employed to handle different MaOP cases. In contrast, the performance of the MaOO algorithms assesses based on the balance between the convergence and diversity of the non-dominated solutions measured using different evaluation criteria of the quality performance indicators. Although many evaluation criteria are available, yet most of the evaluation and benchmarking of the MaOO with state-of-art a