This study aims to develop a recommendation engine methodology to enhance the model’s effectiveness and efficiency. The proposed model is commonly used to assign or propose a limited number of developers with the required skills and expertise to address and resolve a bug report. Managing collections within bug repositories is the responsibility of software engineers in addressing specific defects. Identifying the optimal allocation of personnel to activities is challenging when dealing with software defects, which necessitates a substantial workforce of developers. Analyzing new scientific methodologies to enhance comprehension of the results is the purpose of this analysis. Additionally, developer priorities were discussed, especially th

Energy savings are very common in IoT sensor networks because IoT sensor nodes operate with their own limited battery. The data transmission in the IoT sensor nodes is very costly and consume much of the energy while the energy usage for data processing is considerably lower. There are several energy-saving strategies and principles, mainly dedicated to reducing the transmission of data. Therefore, with minimizing data transfers in IoT sensor networks, can conserve a considerable amount of energy. In this research, a Compression-Based Data Reduction (CBDR) technique was suggested which works in the level of IoT sensor nodes. The CBDR includes two stages of compression, a lossy SAX Quantization stage which reduces the dynamic range of the

In this research article, an Iterative Decomposition Method is applied to approximate linear and non-linear fractional delay differential equation. The method was used to express the solution of a Fractional delay differential equation in the form of a convergent series of infinite terms which can be effortlessly computable.
The method requires neither discretization nor linearization. Solutions obtained for some test problems using the proposed method were compared with those obtained from some methods and the exact solutions. The outcomes showed the proposed approach is more efficient and correct.

Furosemide drug determination in pharmaceutical and biological urine samples using a novel continuous flow-injection analysis technique that is simple, rapid, sensitive and economical. The complex formed by the reaction of furosemide and O-phenylenediamine with oxidative agent K₃[Fe(CN)₆] to produce an orange-yellow colored product at 460 nm was the basis for the proposed method.  The proposed method’s linearity ranges (3-100) μg.mL^-1and (1-50) μg.mL^-1 for CFIA/merging zone methods and batch .The detection limit and Limit of quantification values were 2.7502 μg.mL^-1  and 9.1697 μg.mL^-1 the relative standard deviation was 0.7143 %, and the average recovery is 98.80%

Seventeen core samples were taken from Luhais and Tuba oil wells according to the presence of oil bearing formations. These wells were located in the province of Basra/southern Iraq. The formation that the samples are collected from Zubair and Mishrif formations. The core samples were taken from the wells at different depths. In the current study the ultrasonic technique was conducted to measure (Vp and Vs) as well as to determine some petrophysical properties for core samples and some elastic moduli such as (Young's modulus, Bulk modulus, Shear modulus, Poisson's ratio and Lame's constant) depending on the values of Vp and Vs as well as density. The relationships between seismic wave velocities with elastic moduli and petrophysical prop

Background: Parvovirus B19 is a human pathogenic virus associated with a wide range of clinical conditions. During pregnancy congenital infection with parvovirus B19 can be associated with poor outcome, including miscarriage, fetal anemia and non-immune hydrops.  

Objective: The study aimed to determine the prevalenceof Parvovirus B19 DNA in pregnant women attending the Military hospital in Khartoum, demonstrating the association between the virus and poor pregnancy outcomes.

Subjects and methods: This study was a cross sectional study, testing pregnant Sudanese women whole blood samples (n= 97) for the presence of Parvovirus B1

Background/Objectives: The purpose of current research aims to a modified image representation framework for Content-Based Image Retrieval (CBIR) through gray scale input image, Zernike Moments (ZMs) properties, Local Binary Pattern (LBP), Y Color Space, Slantlet Transform (SLT), and Discrete Wavelet Transform (DWT). Methods/Statistical analysis: This study surveyed and analysed three standard datasets WANG V1.0, WANG V2.0, and Caltech 101. The features an image of objects in this sets that belong to 101 classes-with approximately 40-800 images for every category. The suggested infrastructure within the study seeks to present a description and operationalization of the CBIR system through automated attribute extraction system premised on CN

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