Regression testing is a crucial phase in the software development lifecycle that makes sure that new changes/updates in the software system don’t introduce defects or don’t affect adversely the existing functionalities. However, as the software systems grow in complexity, the number of test cases in regression suite can become large which results into more testing time and resource consumption. In addition, the presence of redundant and faulty test cases may affect the efficiency of the regression testing process. Therefore, this paper presents a new Hybrid Framework to Exclude Similar & Faulty Test Cases in Regression Testing (ETCPM) that utilizes automated code analysis techniques and historical test execution data to

Renewable energy resources have become a promissory alternative to overcome the problems related to atmospheric pollution and limited sources of fossil fuel energy. The technologies in the field of renewable energy are used also to improve the ventilation and cooling in buildings by using the solar chimney and heat exchanger. This study addresses the design, construction and testing of a cooling system by using the above two techniques. The aim was to study the effects of weather conditions on the efficiency of this system which was installed in Baghdad for April and May 2020. The common weather in these months is hot in Baghdad. The test room of the design which has a size of 1 m3 was situated to face the geographical south. The te

There are many diseases that affect the arteries, especially those related to their elasticity and stiffness, and they can be guessed by estimating and calculating the modulus of elasticity. Hence, the accurate calculation of the elastic modulus leads to an accurate assessment of these diseases, especially in their early stages, which can contribute to the treatment of these diseases early. Most of the calculations used the one-dimensional (1D) modulus of elasticity. From a mechanical point of view, the stresses to which the artery is subjected are not one-dimensional, but three-dimensional. Therefore, estimating at least a two-dimensional (2D) modulus of elasticity will necessarily be more accurate. To the knowledge of researchers, there i

This paper presents the design, construction and investigates an experimental study of a parabolic Trough Solar Collector (PTSC). It is constructed of multi – piece glass mirror to form the parabolic reflector (1.8 m ? 2.8 m) its form were checked with help of a laser and carbon steel rectangular as receiver. Sun tracker has been developed (using two – axis) to track solar PTSC according to the direction of beam propagation of solar radiation. Using synthetic oil as a heat transfer its capability to heat transfer and load high temperature (?400 oc). The storage tank is fabricated with stainless steel of size 50 L. The experimental tests have been carried out in Baghdad climatic conditions (33.3o N, 44.4o E) during selective days of the

Choosing antimicrobials is a common dilemma when the expected rate of bacterial resistance is high. The observed resistance values in unequal groups of isolates tested for different antimicrobials can be misleading. This can affect the decision to recommend one antibiotic over the other. We analyzed recalled data with the statistical consideration of unequal sample groups. Data was collected concerning children suspected to have typhoid fever at Al Alwyia Pediatric Teaching Hospital in Baghdad, Iraq. The study period extended from September 2021 to September 2022. A novel algorithm was developed to compare the drug sensitivity among unequal numbers of Salmonella typhi (S. Typhi) isolates tested with different antibacterials.

 Data Driven Requirement Engineering (DDRE) represents a vision for a shift from the static traditional methods of doing requirements engineering to dynamic data-driven user-centered methods. Data available and the increasingly complex requirements of system software whose functions can adapt to changing needs to gain the trust of its users, an approach is needed in a continuous software engineering process. This need drives the emergence of new challenges in the discipline of requirements engineering to meet the required changes. The problem in this study was the method in data discrepancies which resulted in the needs elicitation process being hampered and in the end software development found discrepancies and could not meet the need

In this paper, we derive and prove the stability bounds of the momentum coefficient µ and the learning rate ? of the back propagation updating rule in Artificial Neural Networks .The theoretical upper bound of learning rate ? is derived and its practical approximation is obtained