Zainab M. Al-Bahrani Department of Oral Diagnosis, College of Dentistry, University of Baghdad, Baghdad, Iraq.Corresponding author: Zainab M. Al-Bahra...

Genetic algorithms (GA) are a helpful instrument for planning and controlling the activities of a project. It is based on the technique of survival of the fittest and natural selection. GA has been used in different sectors of construction and building however that is rarely documented. This research aimed to examine the utilisation of genetic algorithms in construction project management. For this purpose, the research focused on the benefits and challenges of genetic algorithms, and the extent to which genetic algorithms is utilised in construction project management. Results showed that GA provides an ability of generating near optimal solutions which can be adopted to reduce complexity in project management and resolve difficult problem

Construction projects are characterized as projects with multi phases and activities, complex, unique, and have many different parties and stakeholders. Risks could appear at one or more of the construction project stages and may affect the achievement of project objectives. Therefore, one of the key elements in the planning phase of any project is the risk management process (RMP). This study attempts to understand the terminology of risk in general, risk management, and response to risk in particular. This study is mainly a review of thirty-eight studies that have been published between 1997 and 2020 that demonstrate the importance of the crucial phase of risk response from the risk management process and its impact on

The loss of dental hard tissue as a result of odontoclastic activity is known as root resorption. It is unwanted and pathological in permanent teeth. Root resorption may happen within the root canal called internal root resorption or on the outer surface of the root called external root resorption. Regardless of where it occurs, root resorption is irreparable, can cause pain for the patient, necessitates treatment, and in some circumstances, resulting in the early loss of the affected tooth. It might be challenging to precisely diagnose and treat root resorption. There is limited information within literatures on root resorption therefore this review aims to understand the radiological and clinical characteristics of r

Four different spectrophotometric methods are used in this study for the determination of Sulfamethoxazole and sulfanilamide drugs in pharmaceutical compounds, synthetic samples, and in their pure forms. The work comprises four chapters which are shown in the following: Chapter One: Includes a brief for Ultraviolet-Visible (UV-VIS) Absorption spectroscopy, antibacterial drugs and sulfonamides with some methods for their determination. The chapter lists two methods for optimization; univariate method and multivariate method. The later includes different types, two of these were mentioned; simplex method and design of experiment method. Chapter Two: Includes reaction of the two studied drugs with sodium nitrite and hydrochloric acid for diazo

Objectives: The demand for orthodontic treatment is nowadays increasing significantly for aesthetic improvement and to correct various kinds of malocclusion, yet the prolonged treatment time remains the main obstacle. This review aimed to demonstrate various orthodontic techniques and highlight the evidence-based successful approaches used for acceleration of orthodontic tooth movement. Materials and Methods: Data and sources of information pertaining to accelerated orthodontic tooth movement premised on English-written articles were searched using electronic databases including Google Scholar, Scopus, PubMed and MEDLINE. Results: This review demonstrated the availability of different surgical and non-surgical methods to enhance tooth movem

Human skin detection, which usually performed before image processing, is the method of discovering skin-colored pixels and regions that may be of human faces or limbs in videos or photos. Many computer vision approaches have been developed for skin detection. A skin detector usually transforms a given pixel into a suitable color space and then uses a skin classifier to mark the pixel as a skin or a non-skin pixel. A skin classifier explains the decision boundary of the class of a skin color in the color space based on skin-colored pixels. The purpose of this research is to build a skin detection system that will distinguish between skin and non-skin pixels in colored still pictures. This performed by introducing a metric that measu

This paper introduces a novel nonparametric hybrid cyber-intelligence-based statistical process control and anomaly detection framework in time series data. It is developed to overcome the shortcomings of the classical control schemes in dealing with complex, abnormal, and noisy input data, especially when it is autocorrelated. The proposed methodology combines three technical pillars: First, it utilizes a bidirectional long-short-term memory architecture (Bi-LSTM) to capture long-term time dependency and learn nonlinear patterns, leaving only true deviations as residuals that remove trends and noises from the market. Second, it adopts the Golden Eagle Optimizer (GEO) algorithm for optimal parameter selection. This intelligent algor