This chapter explores artificial intelligence (AI) auditing and its role in enhancing customer experience and building trust, reliability, and credibility in the digital marketing environment. It emphasizes the adoption and implementation of practices by global and international auditing firms such as Deloitte, PwC, Ernst & Young, and KPMG. The chapter employs a systematic review of academic literature and professional reports, analyzing studies related to AI applications in customer experience, algorithmic auditing practices, and AI governance frameworks. However, the chapter's findings reveal a research gap: the limited integration of AI auditing and customer experience in current literature. The chapter concludes by proposing

Mauddud Formation (Albian stage-the Early Cretaceous) is an important oil reservoir in Ratawi field of southern Iraq. Four wells, R T-2, R T-3, R T-6, and R T-7, located 70 km northwest of Basra, were selected to study microfacies properties and petrophysical associations with the probability of oil production. Seventy-seven core samples are collected, and thin sections for petrographic analysis. The self-potential, Gamma-ray, resistivity, and porosity logs are used to determine the top and bottom of the Mauddud Formation. Water saturation of the invaded and uninvaded zones, shale volume, and porosity were calculated. The study area results showed that the quantity of shale is less than 15% for most of the wells, and the dominant po

Oil recovery could be impacted by the relation between vertical permeability (K_v) and horizontal permeability (K_h) (K_v/K_h). 4816 plugs that have been getting hold of 18 wells of Mishrif formation in the West Qurna oilfield were used. K_v/K_h data provided some scatter, but the mean is ~1. K_v/K_h =1 was used for the Petrel model before upscaling according to the heterogeneity of each layer.

K_v/K_h values for Mishrif Formation in West Qurna Oilfield are 0.8 for relatively homogeneous, 0.4 for heterogeneous rock, and 0.1 for cap rocks (CRII).

   Eclipse ^TM was used for reservoir simulation. PVT and SCAL data e

Fresh water resources in terms of water quality is a crucial issue worldwide. In Egypt, the Nile River is the main source of fresh water in the country and monitoring its water quality is a major task on governments and research levels. In the present case study, the physical, chemical and algal distribution in Nile River was monitored over two seasons (winter and summer) in 2019. The aims of the study were to check the seasonal variation among the different water parameters and also to check the correlations between those parameters. Water samples were collected from the Nile in Cairo governorate in EGYPT. The different physiochemical and microbiological properties in water samples were assessed. The studied parameters were included: te

Huwaiza marsh is considered the largest marsh in the southern part of Iraq. It is located between 31° and 31.75° latitude and extends over the Iraqi-Iranian border; but the largest part lies in Iraq. It is located to the east of Tigris River in Messan and Basra governorates.
In this research, the variation of some water quality parameters at different locations of Huwaiza marsh were studied to find out its efficacy in the treatment of the contamination coming from the wastewater outfall of Kahlaa brokendown sewage treatment plant which lies on the Kahlaa River. This rive is the main feeder of Huwaiza marsh. Ten water quality sampling locations were chosen in this marsh. The water samples were taken during 2009 for three months; Janu

OpenStreetMap (OSM), recognised for its current and readily accessible spatial database, frequently serves regions lacking precise data at the necessary granularity. Global collaboration among OSM contributors presents challenges to data quality and uniformity, exacerbated by the sheer volume of input and indistinct data annotation protocols. This study presents a methodological improvement in the spatial accuracy of OSM datasets centred over Baghdad, Iraq, utilising data derived from OSM services and satellite imagery. An analytical focus was placed on two geometric correction methods: a two-dimensional polynomial affine transformation and a two-dimensional polynomial conformal transformation. The former involves twelve coefficients for ad

Due to the easily access to the satellite images, Google Earth (GE) images have become more popular than other online virtual globes. However, the popularity of GE is not an indication of its accuracy. A considerable amount of literature has been published on evaluating the positional accuracy of GE data; however there are few studies which have investigated the subject of improving the GE accuracy. In this paper, a practical method for enhancing the horizontal positional accuracy of GE is suggested by establishing ten reference points, in University of Baghdad main campus, using different Global Navigation Satellite System (GNSS) observation techniques: Rapid Static, Post-Processing Kinematic, and Network. Then, the GE image for the study