In this article, the high accuracy and effectiveness of forecasting global gold prices are verified using a hybrid machine learning algorithm incorporating an Adaptive Neuro-Fuzzy Inference System (ANFIS) model with Particle Swarm Optimization (PSO) and Gray Wolf Optimizer (GWO). The hybrid approach had successes that enabled it to be a good strategy for practical use. The ARIMA-ANFIS hybrid methodology was used to forecast global gold prices. The ARIMA model is implemented on real data, and then its nonlinear residuals are predicted by ANFIS, ANFIS-PSO, and ANFIS-GWO. The results indicate that hybrid models improve the accuracy of single ARIMA and ANFIS models in forecasting. Finally, a comparison was made between the hybrid foreca

Image retrieval is used in searching for images from images database. In this paper, content – based image retrieval (CBIR) using four feature extraction techniques has been achieved. The four techniques are colored histogram features technique, properties features technique, gray level co- occurrence matrix (GLCM) statistical features technique and hybrid technique. The features are extracted from the data base images and query (test) images in order to find the similarity measure. The similarity-based matching is very important in CBIR, so, three types of similarity measure are used, normalized Mahalanobis distance, Euclidean distance and Manhattan distance. A comparison between them has been implemented. From the results, it is conclud

BP algorithm is the most widely used supervised training algorithms for multi-layered feedforward neural net works. However, BP takes long time to converge and quite sensitive to the initial weights of a network. In this paper, a modified cuckoo search algorithm is used to get the optimal set of initial weights that will be used by BP algorithm. And changing the value of BP learning rate to improve the error convergence. The performance of the proposed hybrid algorithm is compared with the stan dard BP using simple data sets. The simulation result show that the proposed algorithm has improved the BP training in terms of quick convergence of the solution depending on the slope of the error graph.

This study presents, for the first time, an innovative Jet Plasma-assisted technique for the green synthesis of TiO₂@Ag core–shell nanoparticles using chard leaf extract as a natural reducing and stabilizing agent. The Jet Plasma provides a highly energetic environment that accelerates nucleation and core–shell formation at low temperatures without toxic precursors. The synthesized nanoparticles exhibited uniform and stable structures, as confirmed by comprehensive characterization techniques including X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), ultraviolet–visible (UV–Vis) spectroscopy, transmission electron microscopy (TEM), and zeta potential analysis. XRD patterns confirmed the crystalline anatase

The wound healing process is incredibly intricate, consisting of a series of cellular activities. Although, this complex process has the potential to degenerate and result in chronic wound problems that are resistant to biological healing mechanisms. Nanoparticles can help to reduce inflammation, promote tissue regeneration, and accelerate wound healing. The proteolytic enzymes are believed to break down proteins and other molecules that can cause inflammation and impede the healing process. Wound was created in vivo using adult mice, and by taking blood samples the hematological parameters were evaluated to detected the effects of bromelain, silver nanoparticles and Br-AgNPs. The results shows an increased in white blood cells WBC, RBC, MC

Background: Deterioration of maxillofacial silicone properties due to microbial colonization is a common problem and leads to the replacement of the prosthesis. Incorporation of the antimicrobial agent into the silicone could be a solution. The purpose of this study was to evaluate the effect of silver-zinc zeolite addition on some mechanical properties of a maxillofacial silicone (VST-50). Materials and methods: Total 120 specimens were fabricated and divided into 3 groups: 40 specimens for tear strength test, 40 specimens for tensile and percentage of elongation tests and 40 specimens for Shore A hardness and surface roughness. Each group was divided into 4 subgroups according to the amount of zeolite added (0% “control”, 0.5%, 1% and

In the present work, silver nanoparticles were prepared. Nonlinear optical properties and
optical limiting of silver nanoparticles were investigated.Standard chemical synthesis method was used at
diffrent weight ratio(0.038, 0.058 and 0.078) of silver nitrate. Several testing were done to obtain the
characteristics of the sample. Z-Scan experiments were performed using 30 ns Q-switched Nd:YAG
laser at 1064 nm and 532 nm at different intensities. The results showed that the nonlinear refractive
index is directly proportional to the input intensities, which caused by the self-focusing of the material.
In addition, the optical limiting behavior has been studied. The results showed that the sample could be
used as an opt

This study aimed to identify the alterations of liver in the quail (Coturnix coturnix) exposed by nanosilver particles.45 quail (females) were collected from agriculture research center in Abu-Ghraib, divided into (6) groups including: T1(12 quails were exposed to 4ppm), T2 (12 quails were exposed to 8ppm) and T3 (12 quails were exposed to 12ppm) of silver nanoparticles solution for 60 days. As well as three groups for control (3 females for each). Birds were dissected to isolate livers for histological preperations after fixation with Bouin's fluid, Routine stains Hematoxyline and eosin were used. Histological study showed that the structure of liver in a control groups consist of hepatocytes arranged radially cords around the central vein