Software testing is a vital part of the software development life cycle. In many cases, the system under test has more than one input making the testing efforts for every exhaustive combination impossible (i.e. the time of execution of the test case can be outrageously long). Combinatorial testing offers an alternative to exhaustive testing via considering the interaction of input values for every t-way combination between parameters. Combinatorial testing can be divided into three types which are uniform strength interaction, variable strength interaction and input-output based relation (IOR). IOR combinatorial testing only tests for the important combinations selected by the tester. Most of the researches in combinatorial testing applied the uniform and the variable interaction strength, however, there is still a lack of work addressing IOR. In this paper, a Jaya algorithm is proposed as an optimization algorithm engine to construct a test list based on IOR in the proposed combinatorial test list generator strategy into a tool called CTJ. The result of applying the Jaya algorithm in input-output based combinatorial testing is acceptable since it produces a nearly optimum number of test cases in a satisfactory time range.
The current research aims to determine the intellectual security and the psychological resilience of Secondary school students and how these two variables are related to each other. The study also seeks the extent to which psychological resilience contributes to intellectual security
The research sample consisted of (420) students from the Secondary stage in the Directorate of Education of Baghdad / Rusafa III. Two scales were administered to the participants to collect the needed data. As for the analysis of data, Pearson correlation coefficient, T-test, and the Regression analysis were employed, the results revealed:
- The members of the sample have an intellectual Security.
- The members of the sample have
The study attempts to measure the level of shyness; the level of psychological isolation; to identify the relationship between shyness and psychological isolation; and to identify the differences between shyness and psychological isolation among first-intermediate students. To this end, a random sample comprised (187) male and female students was chosen for the academic year (2016-2017) from Baghdad \ Al-Rasafa. To measure the shyness and psychological isolation, the researcher designed two scales: one to measure the shyness composed of (37) items divided into four domains; and the other to measure the psychological isolation made of (56) items divided into three domains. The study concluded that the sample has a medium level of shyness;
... Show MoreDiabetic Nephropathy(DN) is a complex disease manifested by persistence microalbuminuria occurring due to the interaction between hemodynamic and metabolic pathway that activates the local renin-angiotensin-aldosterone system resulting in a decline in renal functions.
This study aimed to quantify the associations between serum aldosterone concentration and fetuin- A as a marker of calcification in type 2 diabetic patients with and without microalbuminuria from one side, and study the possible relationship between aldosterone and fetuin-A with glycemic indices, serum electrolyte, renal function and microalbuminuria and body mass index from the other side.
A case-control study involved eighty-six adult subjects
... Show MoreThe aim of this study was to measure the effectiveness of a proposed program to develop the creative abilities of the students of Tabuk University and its impact on the creative output of the NEOM project. The sample of the study consisted of (50) university students divided into two groups: an experimental group of 25 students who receive the proposed training program, and control group of (25) students.
To achieve these objectives, the researcher designed and developed tools to collect the required data, which were verified their validity and reliability.
The descriptive statistics of mean, standard deviations, correlation coefficient, T test for the associated sample were used in the analysis of the results of th
... Show MoreChoosing 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.
... Show More This paper describes the application of consensus optimization for Wireless Sensor Network (WSN) system. Consensus algorithm is usually conducted within a certain number of iterations for a given graph topology. Nevertheless, the best Number of Iterations (NOI) to reach consensus is varied in accordance with any change in number of nodes or other parameters of . graph topology. As a result, a time consuming trial and error procedure will necessary be applied
to obtain best NOI. The implementation of an intellig ent optimization can effectively help to get the optimal NOI. The performance of the consensus algorithm has considerably been improved by the inclusion of Particle Swarm Optimization (PSO). As a case s
Recently Genetic Algorithms (GAs) have frequently been used for optimizing the solution of estimation problems. One of the main advantages of using these techniques is that they require no knowledge or gradient information about the response surface. The poor behavior of genetic algorithms in some problems, sometimes attributed to design operators, has led to the development of other types of algorithms. One such class of these algorithms is compact Genetic Algorithm (cGA), it dramatically reduces the number of bits reqyuired to store the poulation and has a faster convergence speed. In this paper compact Genetic Algorithm is used to optimize the maximum likelihood estimator of the first order moving avergae model MA(1). Simulation results
... Show MoreThis paper discusses an optimal path planning algorithm based on an Adaptive Multi-Objective Particle Swarm Optimization Algorithm (AMOPSO) for two case studies. First case, single robot wants to reach a goal in the static environment that contain two obstacles and two danger source. The second one, is improving the ability for five robots to reach the shortest way. The proposed algorithm solves the optimization problems for the first case by finding the minimum distance from initial to goal position and also ensuring that the generated path has a maximum distance from the danger zones. And for the second case, finding the shortest path for every robot and without any collision between them with the shortest time. In ord
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