In regression testing, Test case prioritization (TCP) is a technique to arrange all the available test cases. TCP techniques can improve fault detection performance which is measured by the average percentage of fault detection (APFD). History-based TCP is one of the TCP techniques that consider the history of past data to prioritize test cases. The issue of equal priority allocation to test cases is a common problem for most TCP techniques. However, this problem has not been explored in history-based TCP techniques. To solve this problem in regression testing, most of the researchers resort to random sorting of test cases. This study aims to investigate equal priority in history-based TCP techniques. The first objective is to implement

Permeability is one of the essential petrophysical properties of rocks, reflecting the rock's ability to pass fluids. It is considered the basis for building any model to predict well deliverability. Yamama formation carbonate rocks are distinguished by sedimentary cycles that separate formation into reservoir units and insulating layers, a very complex porous system caused by secondary porosity due to substitute and dissolution processes. Those factors create permeability variables and vary significantly. Three ways used for permeability calculation, the firstly was the classical method, which only related the permeability to the porosity, resulting in a weak relationship. Secondly, the flow zone indicator (FZI) was divided reservoir into

In this work, an inventive photovoltaic evaporative cooling (PV/EC) hybrid system was constructed and experimentally investigated. The PV/EC hybrid system has the prosperous advantage of producing electrical energy and cooling the PV panel besides providing cooled-humid air. Two cooling techniques were utilized: backside evaporative cooling (case #1) and combined backside evaporative cooling with a front-side water spray technique (case #2). The water spraying on the front side of the PV panel is intermittent to minimize water and power consumption depending on the PV panel temperature. In addition, two pad thicknesses of 5 cm and 10 cm were investigated at three different water flow rates of 1, 2, and 3 lpm. In Case #1,

Software Defined Networking (SDN) with centralized control provides a global view and achieves efficient network resources management. However, using centralized controllers has several limitations related to scalability and performance, especially with the exponential growth of 5G communication. This paper proposes a novel traffic scheduling algorithm to avoid congestion in the control plane. The Packet-In messages received from different 5G devices are classified into two classes: critical and non-critical 5G communication by adopting Dual-Spike Neural Networks (DSNN) classifier and implementing it on a Virtualized Network Function (VNF). Dual spikes identify each class to increase the reliability of the classification

Abstract

A sensitive, precise and reliable indirect spectrophotometric method for the determination of chlordiazepoxide (CDE) in pure and pharmaceutical dosage forms is described. The method is based on oxidative coupling reaction between amino group resulting from acidic decomposition of CDE with phenothiazine in the presence of sodium periodate to produce an intense green soluble dye that is stable and shows a maximum absorption at 602 nm. The calibration plot indicates that Beer’s law is obeyed over the concentration range of 0.1?50 µg/mL, with a molar absorptivity of 1×10⁴ L/mol cm and correlation coefficient of 0.9994.All the conditions that affecting on the stability and sensitivity of the fo

Background and Objectives: Dyspepsia is a disorder characterized by difficulty in digestion and represents a major health concern. Therefore, it is crucial to identify functional dyspepsia linked to Helicobacter pylori (H. pylori). This research aimed to determine the prevalence of H. pylori among patients with dyspepsia and to examine the potential risk factors associated with the infection. Materials and Methods: From August 14th to September 21st, 2024, a total of 105 patients with dyspepsia, who attended the Central Laboratory of Baghdad Medical City Complex (Iraq), were enrolled in this study. Data on nonsteroidal anti-inflam- matory drugs (NSAIDs), smoking, family history, fasting habits and frequent fast food consumption wer

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class