This paper proposes a novel meta-heuristic optimization algorithm called the fine-tuning meta-heuristic algorithm (FTMA) for solving global optimization problems. In this algorithm, the solutions are fine-tuned using the fundamental steps in meta-heuristic optimization, namely, exploration, exploitation, and randomization, in such a way that if one step improves the solution, then it is unnecessary to execute the remaining steps. The performance of the proposed FTMA has been compared with that of five other optimization algorithms over ten benchmark test functions. Nine of them are well-known and already exist in the literature, while the tenth one is proposed by the authors and introduced in this article. One test trial was shown t

Testing is a vital phase in software development, and having the right amount of test data is an important aspect in speeding up the process. As a result of the integrationist optimization challenge, extensive testing may not always be practicable. There is also a shortage of resources, expenses, and schedules that impede the testing process. One way to explain combinational testing (CT) is as a basic strategy for creating new test cases. CT has been discussed by several scholars while establishing alternative tactics depending on the interactions between parameters. Thus, an investigation into current CT methods was started in order to better understand their capabilities and limitations. In this study, 97 publications were evalua

The subject of the research seeks to indicate the level of influence of emotional intelligence in the empowerment of workers in the Ministry of Industry and Minerals General Company for Food Products. The research problem is illustrated by knowing all of the following:

• The level of the relationship between emotional intelligence in promoting the empowerment of employees of the Ministry of Industry and Minerals.
• The impact of emotional intelligence on the empowerment of workers in the ministry.
• Recognize the interest of the management of the Ministry of Industry and Minerals in emotional intelligence and the

      Detecting protein complexes in protein-protein interaction (PPI) networks is a challenging problem in computational biology. To uncover a PPI network into a complex structure, different meta-heuristic algorithms have been proposed in the literature. Unfortunately, many of such methods, including evolutionary algorithms (EAs), are based solely on the topological information of the network rather than on biological information. Despite the effectiveness of EAs over heuristic methods, more inherent biological properties of proteins are rarely investigated and exploited in these approaches. In this paper, we proposed an EA with a new mutation operator for complex detection problems. The proposed mutation operator is formulate

Background: Excision repair cross-complementing group 2 gene (ERCC2) polymorphisms have been linked as being a risk factor for colorectal cancer (CRC) emergence. However, data from several studies are contradictory. To validate genetic biomarkers of the CRC; the impact of the following ERCC2 polymorphism (rs1799793 and rs238406) was examined on CRC susceptibility among sample of Iraqi population. Methods: A total of 126 subjects were enrolled in this case control study; 78 CRC patients and 48 apparently healthy individuals who are age, gender, smoking status and BMI matched. Polymerase chain reaction (PCR) was used for genotyping, followed by sequencing then the association between genetic polymorphisms and CRC risk was investigate

Five rice (Oryza sativa L.) cultivars (N22, Amber, Moroberekan, Kinandang Patong, and Azucena) underwent path coefficient analysis across three plant spacings (15 cm × 15 cm, 20 cm × 20 cm, and 25 cm× 25 cm) in the summer of 2017 at the College of Agricultural Engineering Sciences, University of Baghdad, Al-Jadriya, Iraq. The experiment proceeded in a randomized complete block design (RCBD) with a split-plot arrangement and three replications. The main plots included three planting distances, and the subplot comprised five varieties. The traits studied were plant height, flag leaf area, number of tillers, panicle number, length and branches, grains per panicle, 1000-grain weight, and the percentage of unfilled grains. The results

Artificial neural networks usage, as a developed technique, increased in many fields such as Auditing business. Contemporary auditor should cope with the challenges of the technology evolution in the business environment by using computerized techniques such as Artificial neural networks, This research is the first work made in the field of modern techniques of the artificial neural networks in the field of auditing; it is made by using thesample of neural networks as a sample of the artificial multi-layer Back Propagation neural networks in the field of detecting fundamental mistakes of the financial statements when making auditing. The research objectives at offering a methodology for the application of theartificial neural networks wi

The authentic traditional architecture proved that it is very convenient to the environmental and social regulations where it appeared and lasted for hundred of years.

This traditional architecture got the intelligence in providing thermal comfort for their occupants by the intelligent usage of the building materials and the intelligent planning and designs which took in consideration the climatic condition and the aerodynamics of the whole city as one ecological system starting from the cold breeze passing through its narrow streets till it enters the dwelling units and glides out through the wind catchers.

This architecture had been neglected and replaced by modern imported architecture which had collap