The success of an organization is significantly influenced by strategic performance, a focal point in recent scholarly investigations and regulatory considerations. This study delves into the examination of the impact of strategy formulation, implementation, and evaluation on the strategic performance within the context of the oil industry in Iraq. Additionally, the research explores the moderating influence of leadership style on the relationship between strategy formulation, implementation, evaluation, and strategic performance in the Iraqi oil industry. Data collection involved the utilization of survey questionnaires distributed to selected employees of Iraqi oil companies. Statistical analysis, specifically SPSS-AMOS, was employed to s

The interest in the issue of capital movement as an economic phenomenon has increased because of its effects and effects and its ability to influence the economic balance and the effectiveness of monetary policy. All countries seek to attract capital and benefit from it because of its effects and results such as supporting economic development process and optimal allocation of economic resources. The problem of the financing gap that most countries suffer from, and others, but sometimes the movement of capital creates challenges for monetary policy makers in achieving their goals.

   After 2003, the Iraqi economy witnessed an openness and economic liberalization unlike previous years, which

<p>In combinatorial testing development, the fabrication of covering arrays is the key challenge by the multiple aspects that influence it. A wide range of combinatorial problems can be solved using metaheuristic and greedy techniques. Combining the greedy technique utilizing a metaheuristic search technique like hill climbing (HC), can produce feasible results for combinatorial tests. Methods based on metaheuristics are used to deal with tuples that may be left after redundancy using greedy strategies; then the result utilization is assured to be near-optimal using a metaheuristic algorithm. As a result, the use of both greedy and HC algorithms in a single test generation system is a good candidate if constructed correctly. T

Heart disease is a significant and impactful health condition that ranks as the leading cause of death in many countries. In order to aid physicians in diagnosing cardiovascular diseases, clinical datasets are available for reference. However, with the rise of big data and medical datasets, it has become increasingly challenging for medical practitioners to accurately predict heart disease due to the abundance of unrelated and redundant features that hinder computational complexity and accuracy. As such, this study aims to identify the most discriminative features within high-dimensional datasets while minimizing complexity and improving accuracy through an Extra Tree feature selection based technique. The work study assesses the efficac

Social media is known as detectors platform that are used to measure the activities of the users in the real world. However, the huge and unfiltered feed of messages posted on social media trigger social warnings, particularly when these messages contain hate speech towards specific individual or community. The negative effect of these messages on individuals or the society at large is of great concern to governments and non-governmental organizations. Word clouds provide a simple and efficient means of visually transferring the most common words from text documents. This research aims to develop a word cloud model based on hateful words on online social media environment such as Google News. Several steps are involved including data acq

Wireless Body Area Sensor Networks (WBASNs) have garnered significant attention due to the implementation of self-automaton and modern technologies. Within the healthcare WBASN, certain sensed data hold greater significance than others in light of their critical aspect. Such vital data must be given within a specified time frame. Data loss and delay could not be tolerated in such types of systems. Intelligent algorithms are distinguished by their superior ability to interact with various data systems. Machine learning methods can analyze the gathered data and uncover previously unknown patterns and information. These approaches can also diagnose and notify critical conditions in patients under monitoring. This study implements two s