The Combined Economic Emission Dispatch (CEED) problem is crucial for optimizing power system operation by minimizing costs and emissions while ensuring grid stability and meeting demand. This paper addresses the complex, nonlinear, and nonconvex nature of CEED, arising from factors like valve-point effects and transmission losses, which necessitates efficient metaheuristic algorithms. We introduce an Improved Zebra Optimization Algorithm (IMZOA), an enhanced bio-inspired technique integrating advanced adaptive foraging and dynamic defense mechanisms, along with a cubic function for CEED modeling, to improve search efficiency and convergence. IMZOA demonstrates significant numerical improvements, achieving up to a 0.80 % cost reduction for

Recently, detecting dynamic patterns for growing communities in social networks have attracted significant attention. The objective of dynamic community detection is to analyze and identify clusters in complex networks that change over time. Different optimization algorithms, including both single-objective and multi-objective approaches, have been employed to address the challenge of dynamic community detection. Although current evolutionary algorithms for identifying community structure can traverse extensive areas of partition space, they often become stuck in local minima. In addition, limited studies have addressed this issue by integrating local search strategies with evolutionary algorithms for community identification. This paper in

Utilizing the modern technologies in agriculture such as subsurface water retention techniques were developed to improve water storage capacities in the root zone depth. Moreover, this technique was maximizing the reduction in irrigation losses and increasing the water use efficiency. In this paper, a polyethylene membrane was installed within the root zone of okra crop through the spring growing season 2017 inside the greenhouse to improve water use efficiency and water productivity of okra crop. The research work was conducted in the field located in the north of Babylon Governorate in Sadat Al Hindiya Township seventy-eight kilometers from Baghdad city. Three treatments plots were used for the comparison using surface

Background: zirconium (Zr) implants are known for having an aesthetically pleasing tooth-like colour Unlike the grey cervical collar that develops over time when titanium (Ti) implants are used in thin gingival biotypes. However, the surface qualities of Zr implants can be further improved. This present study examined using thermal vapour deposition (TVD) to coat Zr implants with germanium (Ge) to improve its physical and chemical characteristics and enhance soft and hard tissue responses. Materials and methods: Zr discs were divided into two groups; the uncoated (control) group was only grit-blasted with alumina particles while the coated (experimental) group was grit-blasted then coated with Ge via TVD. Field emission scanning ele

Statement of the Problem. The use of orthodontic fixed appliances may adversely affect oral health leading to demineralizing lesions and the development of gingival problems. Aims of the Study. The study aimed to coat orthodontic archwires with chlorhexidine hexametaphosphate nanoparticles (CHX-HMP NPs) and to evaluate the elusion of CHX from CHX-HMP NPs. Materials and Methods. A solution of CHX-HMP nanoparticles with an overall concentration of 5 mM for both CHX and HMP was prepared, characterized (using atomic force microscope and Fourier transformation infrared spectroscopy), and used to coat orthodontic stainless steel (SSW) and NiTi archwires (NiTiW). The coated segments were characterized (using scanning electron microscopy

Titanium alloy (Ti-6Al-4V or Gr.23) was widely used as a dental alloy. In the current study, polymerization of eugenol (PE) on Gr.23 titanium alloys was conducted by an electrochemical process before and after being treated by Micro Arc Oxidation (MAO). The formed films were characterized by scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS), and X-ray diffraction (XRD). The corrosion behavior of Gr.23 alloy in an artificial saliva environment at a temperature range of 293–323 K has been studied and assessed by means of electrochemical polarization and impedance spectroscopy techniques. Three cases are taken into consideration; bare Gr.23, Gr.23 coated by PE, and Gr.23 coated by PE after MAO treatment. The maxi

The slurry infiltrated fiber concrete (SIFCON) is nowadays considered a special type of high fiber content concrete; it is high strength and high performance material. This paper investigates the effect of spread steel fiber into the slurry mortar on some properties of SIFCON. According to fiber distribution, two sets were used in this investigation. The first set consisted of randomly distributing fibers inside the slurry. The second set was by placing the fibers in an orderly manner inside the slurry. Crimped steel fibers with an aspect ratio of (60) were used. Two different volume fractions percentage of (7% and 9%) by volume of mold were used in both sets for this study. Also, a w/c ratio of (0.35) and superplasticiz

Luminescent solar concentrator (LSC) are used to enhance       photoresponsivity of solar cell. The Quantumdots luminescent solar concentrator (QDLSC) consists of CdSe/CdS core/shell nanoparticles embedded in polyacrylamide polymer matrix positioned on the top surface of the silicon solar cell. This procedure improves the conversion efficiency of the bare silicon solar cell. The conversion efficiency of the solar cell has increased from 7.3% to 10.3%.  this improvement is referred to the widening of the response spectral region window  of the a- Si. Solar cell.

This paper proposes a new structure of the hybrid neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Weight parameters of the hybrid neural structure with its serial-parallel configuration are adapted by using the Back propagation learning algorithm. The ability of the proposed hybrid neural structure for nonlinear system has achieved a fast learning with minimum number