Several recent approaches focused on the developing of traditional systems to measure the costs to meet the new environmental requirements, including Attributes Based Costing (ABCII). It is method of accounting is based on measuring the costs according to the Attributes that the product is designed on this basis and according to achievement levels of all the Attribute of the product attributes. This research provides the knowledge foundations of this approach and its role in the market-oriented compared to the Activity based costing as shown in steps to be followed to apply for this Approach. The research problem in the attempt to reach the most accurate Approach in the measurement of the cost of products from th

This study proposes a pioneering Ethical Artificial Intelligence (EAI) framework for advancing sustainable development in Iraq by integrating eight multidimensional sustainability indicators—administrative, technological, economic, environmental, social, legal, security, and governance. Utilizing data from 60 completed development projects, the framework combines SPSS statistical analysis, the SMART-AI model, and Artificial Neural Networks (ANN) to identify key determinants of project success and failure. Results reveal a 37% project failure rate, with administrative and technological deficiencies emerging as the most influential predictors. The SMART-AI model achieved an accuracy of 91.3% using stratified k-fold cross-validation. A bilin

The meniscus has a crucial function in human anatomy, and Magnetic Resonance Imaging (M.R.I.) plays an essential role in meniscus assessment. It is difficult to identify cartilage lesions using typical image processing approaches because the M.R.I. data is so diverse. An M.R.I. data sequence comprises numerous images, and the attributes area we are searching for may differ from each image in the series. Therefore, feature extraction gets more complicated, hence specifically, traditional image processing becomes very complex. In traditional image processing, a human tells a computer what should be there, but a deep learning (D.L.) algorithm extracts the features of what is already there automatically. The surface changes become valuable when

       In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from      Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial

Portland cement concrete is the most commonly used construction material in the world for decades. However, the searches in concrete technology are remaining growing to meet particular properties related to its strength, durability, and sustainability issue. Thus, several types of concrete have been developed to enhance concrete performance. Most of the modern concrete types have to contain supplementary cementitious materials (SCMs) as a partial replacement of cement. These materials are either by-products of waste such as fly ash, slag, rice husk ash, and silica fume or from a geological resource like natural pozzolans and metakaolin (MK). Ideally, the utilization of SCMs will enhance the concrete performance, minimize

Docetaxel is an effective treatment approved for many types of cancers, but its effectiveness in clinical practice can be compromised by significant occurrence of adverse drug reactions. The aim of the current study was to measure the distribution of adverse drug reactions of docetaxel reported in Iraq and to assess the causality, severity, seriousness, preventability, expectedness and outcome of these adverse reactions. A retrospective study conducted on individual case safety reports from the Iraqi Pharmacovigilance Center / Ministry of Health. The study included 118 individual case safety report containing 236 adverse drug reactions.
Most of the adverse drug reactions were related to skin and subcutaneous tissue disorders(26.7%), f

Objective: Aimed to asses the role of PT estimation in early diagnosis and predicting the extent and the outcome of head injury with ICerH and/ or Contusion
Method :PT was measured by Digiclot 818
Group –1: One hundred consecutive head injured patients admitted at Neurosurgical and Al Ramadi teaching hospitals were initially estimated for prothrombin time and subsequently scanned
Group-2 : Two hundred twenty five consecutive non scanned head injured patients admitted to Neurosurgical and Al Ramadi teaching hospitals were estimated with prothrombin time at the time of insult and subsequently for the next two weeks Al – Kindy Col Med J 2012; Vol. 8 No. 1 P: 54
Clinical and neurological evaluation (GCS) score in addition to

Due to the lack of statistical researches in studying with existing (p) of Exogenous Input variables, and there contributed in time series phenomenon as a cause, yielding (q) of Output variables as a result in time series field, to form conceptual idea similar to the Classical Linear Regression that studies the relationship between dependent variable with explanatory variables. So highlight the importance of providing such research to a full analysis of this kind of phenomena important in consumer price inflation in Iraq. Were taken several variables influence and with a direct connection to the phenomenon and analyzed after treating the problem of outliers existence in the observations by (EM) approach, and expand the sample size (n=36) to