Improved Merging Multi Convolutional Neural Networks Framework of Image Indexing and Retrieval

The effect of the aqueous extract of fenugreek seeds (Trigonella Foenum Graecum L.), Rhodium complex (?) with formula [RhL2CLH2O].1 1/2 ETOH and palladium (?) [pdl2].2ETOH,where L=2-hydroxy phenyl piperonalidine was studied on two cancer cell lines. The first cell line was intestine cancer of female albino mice (L20B), the second one was Rhabdomysarcomas (RD)cell line in human. The activity of the new complexes and the aqueous extract was compared to the well-known anticancer drug (cis-platin) by utilizing the in vitro system. The cell lines were treated with four concentrations of cis-platin 31.25,62.5,125 and 250 ?g/ml for 72 hour exposure time. The same concentrations were used with extract and the new complexes. This study showed that t

ABSTRACT Background: One of the major problems of all ceramic restorations is their probable fracture against the occlusal forces. The objective of this in vitro study was to evaluate the effect of two gingival finishing lines (90°shoulder and deep chamfer) on the fracture resistance of full contour CAD/CAM and heat press all-ceramic crowns. Materials and Methods: Thirty two maxillary first premolars were prepared to receive full contour CAD/CAM (zolid) and heat press (Cergo Kiss) ceramic crowns using a special paralleling device (Parallel-A-Prep). The teeth were divided into four groups according to the type of finishing line prepared. Each crown was cemented to its corresponding tooth using self-etch, self-adhesive dual cure resin ceme

This study proposes a hybrid predictive maintenance framework that integrates the Kolmogorov-Arnold Network (KAN) with Short-Time Fourier Transform (STFT) for intelligent fault diagnosis in industrial rotating machinery. The method is designed to address challenges posed by non-linear and non-stationary vibration signals under varying operational conditions. Experimental validation using the FALEX multispecimen test bench demonstrated a high classification accuracy of 97.5%, outperforming traditional models such as SVM, Random Forest, and XGBoost. The approach maintained robust performance across dynamic load scenarios and noisy environments, with precision and recall exceeding 95%. Key contributions include a hardware-accelerated K

<abstract><p>Many variations of the algebraic Riccati equation (ARE) have been used to study nonlinear system stability in the control domain in great detail. Taking the quaternion nonsymmetric ARE (QNARE) as a generalized version of ARE, the time-varying QNARE (TQNARE) is introduced. This brings us to the main objective of this work: finding the TQNARE solution. The zeroing neural network (ZNN) technique, which has demonstrated a high degree of effectiveness in handling time-varying problems, is used to do this. Specifically, the TQNARE can be solved using the high order ZNN (HZNN) design, which is a member of the family of ZNN models that correlate to hyperpower iterative techniques. As a result, a novel

    Adontomerus amygdali (Boucek, 1958) (Hymenoptera, Torymidae) is recorded for the first time in Iraq, parasitizing almond fruits wasp, Eurytoma amygdali Enderlein, 1907 (Hymenoptera, Eurytomidae) infesting fruits of almond trees Prunus dulcis (Mill.) D. A. Webb (=Amygdalus communis Linn.)   growing in Koysinjaq district, Erbil, Iraq. A short morphological description of this species is presented.

This research is seeks to state the role of Green Human Resources Management Practices and their dimensions (Green Employment and Selection, Green Performance Assessment, Green Training & Development and Green Compensation and Stimulation Systems) in strengthening the Strategic Positioning in the Nongovernmental Hospitals in Erbil city, and aims to analyze the relationship between Green Human Resources Management Practices and Strategic Positioning and to show the impact of Green Human Resources Management Practices in determining the Strategic Position.

            It is depended on a questionnaire as key tools for achieving data, as designed on

Wireless Multimedia Sensor Networks (WMSNs) are a type of sensor network that contains sensor nodes equipped with cameras, microphones; therefore the WMSNS are able to   produce multimedia data such as video and audio streams, still images, and scalar data from the surrounding environment. Most multimedia applications typically produce huge volumes of data, this leads to congestion. To address this challenge, This paper proposes Modify Spike Neural Network control for Traffic Load Parameter with Exponential Weight of Priority Based Rate Control algorithm (MSNTLP with EWBPRC). The Modify Spike Neural Network controller (MSNC) can calculate the appropriate traffi