It is generally accepted that there are two spectrophotometric techniques for quantifying ceftazidime (CFT) in bulk medications and pharmaceutical formulations.  The methods  are described as simple, sensitive, selective, accurate and efficient techniques. The first method used an alkaline medium to convert ceftazidime to its diazonium salt, which is then combined with the 1-Naphthol (1-NPT) and 2-Naphthol (2-NPT) reagents. The azo dye that was produced brown  and red in color with absorption intensities of ƛmax 585 and 545nm respectively. Beer's law was followed in terms of concentration ranging from  (3-40) µg .ml^-1 For (CFT-1-NPT) and (CFT-2-NPT), the detection limits were 1.0096 and 0.8017 µg.ml^-1, respec

The current research creates an overall relative analysis concerning the estimation of Meixner process parameters via the wavelet packet transform. Of noteworthy presentation relevance, it compares the moment method and the wavelet packet estimator for the four parameters of the Meixner process. In this paper, the research focuses on finding the best threshold value using the square root log and modified square root log methods with the wavelet packets in the presence of noise to enhance the efficiency and effectiveness of the denoising process for the financial asset market signal. In this regard, a simulation study compares the performance of moment estimation and wavelet packets for different sample sizes. The results show that wavelet p

This study explores the challenges in Artificial Intelligence (AI) systems in generating image captions, a task that requires effective integration of computer vision and natural language processing techniques. A comparative analysis between traditional approaches such as retrieval- based methods and linguistic templates) and modern approaches based on deep learning such as encoder-decoder models, attention mechanisms, and transformers). Theoretical results show that modern models perform better for the accuracy and the ability to generate more complex descriptions, while traditional methods outperform speed and simplicity. The paper proposes a hybrid framework that combines the advantages of both approaches, where conventional methods prod

Background: One of the most common complications of dentures is its ability to fracture, so the aim of this study was to reinforce the high impact denture base with carbon nanotubes in different concentrations to improve the mechanical and physical properties of the denture base. Materials and methods: Three concentrations of carbon nanotubes was used 0.5%, 1%, 1.5% in a pilot study to see the best values regarding transverse strength, impact, hardness and roughness test, 1 wt% was the best concentration, so new samples for control group and 1wt% carbon nanotubes and the previous tests were of course repeated. Results: There was a significant increase in impact strength and transverse strength when we add carbon nanotubes in 1wt%, compared

Semi-parametric models analysis is one of the most interesting subjects in recent studies due to give an efficient model estimation. The problem when the response variable has one of two values either 0 ( no response) or one – with response which is called the logistic regression model.

We compare two methods Bayesian and . Then the results were compared using MSe criteria.

A simulation had been used to study the empirical behavior for the Logistic model , with  different sample sizes and variances. The results using represent that the Bayesian method is better than the   at small samples sizes.

In this work, a new development of predictive voltage-tracking control algorithm for Proton Exchange Membrane Fuel Cell (PEMFCs) model, using a neural network technique based on-line auto-tuning intelligent algorithm was proposed. The aim of proposed robust feedback nonlinear neural predictive voltage controller is to find precisely and quickly the optimal hydrogen partial pressure action to control the stack terminal voltage of the (PEMFC) model for N-step ahead prediction. The Chaotic Particle Swarm Optimization (CPSO) implemented as a stable and robust on-line auto-tune algorithm to find the optimal weights for the proposed predictive neural network controller to improve system performance in terms of fast-tracking de

Background: Liver metastasis significantly complicates cancer prognosis, yet easily accessible markers for its early detection and monitoring remain crucial. This study aimed to comprehensively evaluate key hematological parameters as potential indicators for liver metastasis in Iraqi patients. Methods: We conducted a cross-sectional study comparing hematological profiles between 90 patients (presumably with liver metastasis) and 30 healthy controls. White Blood Cell (WBC) count, Lymphocyte percentage, Neutrophil percentage, and Neutrophil-to-Lymphocyte Ratio (NLR) were analyzed. Given non-normal data distributions (confirmed by the Shapiro-Wilk test), group comparisons were performed using the non-parametric Mann-Whitney U test.

Researching the effects of the research and technological development contract, determining its extent and demarcating the boundaries of the obligations imposed in it, is the cornerstone of economic growth and development, because defining these obligations removes the ambiguity and conflict between interests, by stating the rights owed to each party and even trying to reconcile them, or impose protection by specifying guarantees that are compatible with the essence of the R&D contract, For the purpose of studying the subject thoroughly, we will divide this research into two sections. The first is devoted to identifying the parties to the research and technological development contract. As for the other topic, we will explain the obligation