This study aims to investigate the relationship between corporate governance (CG) and audit quality (AQ) in the adequacy of the value relevance of accounting information (VRAI). The study sample included Iraqi firms listed on the Iraqi Stock Exchange (ISE) from 2010 to 2022. Nineteen firms were a research sample selected from 44 firms listed on the ISE. They chose to use the model (Ohlson, 1995) in measuring VRAI, which is based on measuring the absolute value of the level of value relevance to earnings per share (EPS) the absolute value of the book value suitability level VRAI. CG was measured through five factors: board size, gender of board members, independence of the board from the chief executive officer (CEO), ownership perce

Building Information Modeling (BIM) and Lean Construction (LC) are two quickly growing applied research areas in construction management. This study focuses on identifying the most essential benefits and analyzing the most affecting constraints on the construction sector that construction players face as they attempt to combine BIM-LC in Iraqi construction. Experts assessed 30 benefits and 28 constraints from examining the previous literature, and a two-round Delphi survey formed the responses. Expert consensus analysis was utilized to elaborate and validate responses after descriptive statistical checks had been used for data processing.

According to the study's findings, the benefits include ensuring the most ef

Botnet detection develops a challenging problem in numerous fields such as order, cybersecurity, law, finance, healthcare, and so on. The botnet signifies the group of co-operated Internet connected devices controlled by cyber criminals for starting co-ordinated attacks and applying various malicious events. While the botnet is seamlessly dynamic with developing counter-measures projected by both network and host-based detection techniques, the convention techniques are failed to attain sufficient safety to botnet threats. Thus, machine learning approaches are established for detecting and classifying botnets for cybersecurity. This article presents a novel dragonfly algorithm with multi-class support vector machines enabled botnet

MB Mahmood, BN Dhannoon

Nowadays, information systems constitute a crucial part of organizations; by losing security, these organizations will lose plenty of competitive advantages as well. The core point of information security (InfoSecu) is risk management. There are a great deal of research works and standards in security risk management (ISRM) including NIST 800-30 and ISO/IEC 27005. However, only few works of research focus on InfoSecu risk reduction, while the standards explain general principles and guidelines. They do not provide any implementation details regarding ISRM; as such reducing the InfoSecu risks in uncertain environments is painstaking. Thus, this paper applied a genetic algorithm (GA) for InfoSecu risk reduction in uncertainty. Finally, the ef

Abstract

     Drug information resources are the information that is used in medications discovery, utilization, and management. Little information about different types of resources used by Iraqi community pharmacists is known. Therefore, the objectives were to determine drug information resources' type do the pharmacists used and the common drug information questions they faced during their work in community pharmacy. A cross-sectional descriptive study was conducted in different Iraqi provinces and online self-reported survey was introduced through Google Form Software to an appropriate sample of graduated pharmacists who were working in a private community pharmacy and having at least one

This paper develops a fuzzy multi-objective model for solving aggregate production planning problems that contain multiple products and multiple periods in uncertain environments. We seek to minimize total production cost and total labor cost. We adopted a new method that utilizes a Zimmermans approach to determine the tolerance and aspiration levels. The actual performance of an industrial company was used to prove the feasibility of the proposed model. The proposed model shows that the method is useful, generalizable, and can be applied to APP problems with other parameters.