MM ABDUL-WAHHAB, SA AHMED, International Journal of Pharmaceutical Research, 2020 - Cited by 2

Elzaki Transform Adomian decomposition technique (ETADM), which an elegant combine, has been employed in this work to solve non-linear Riccati matrix differential equations. Solutions are presented to demonstrate the relevance of the current approach. With the use of figures, the results of the proposed strategy are displayed and evaluated. It is demonstrated that the suggested approach is effective, dependable, and simple to apply to a range of related scientific and technical problems.

The aim of this research is to adopt a close range photogrammetric approach to evaluate the pavement surface condition, and compare the results with visual measurements. This research is carried out on the road of Baghdad University campus in AL-Jaderiyiah for evaluating the scaling, surface texture for Portland cement concrete and rutting, surface texture for asphalt concrete pavement. Eighty five stereo images of pavement distresses were captured perpendicular to the surface using a DSLR camera. Photogrammetric process was carried out by using ERDAS IMAGINE V.8.4. The results were modeled by using a relationship between the photogrammetric and visual techniques and selected the highest coefficient of determination (R2). The first techniqu

The aim of this research is to adopt a close range photogrammetric approach to evaluate the pavement surface condition, and compare the results with visual measurements. This research is carried out on the road of Baghdad University campus in AL-Jaderiyiah for evaluating the scaling, surface texture for Portland cement concrete and rutting, surface texture for asphalt concrete pavement. Eighty five stereo images of pavement distresses were captured perpendicular to the surface using a DSLR camera. Photogrammetric process was carried out by using ERDAS IMAGINE V.8.4.  The results were modeled by using a relationship between the photogrammetric and visual techniques and selected the highest coefficient of determinatio

HM Al-Dabbas, RA Azeez, AE Ali, IRAQI JOURNAL OF COMPUTERS, COMMUNICATIONS, CONTROL AND SYSTEMS ENGINEERING, 2023

Estimating the semantic similarity between short texts plays an increasingly prominent role in many fields related to text mining and natural language processing applications, especially with the large increase in the volume of textual data that is produced daily. Traditional approaches for calculating the degree of similarity between two texts, based on the words they share, do not perform well with short texts because two similar texts may be written in different terms by employing synonyms. As a result, short texts should be semantically compared. In this paper, a semantic similarity measurement method between texts is presented which combines knowledge-based and corpus-based semantic information to build a semantic network that repre

Research summary

This research discloses the study of the methodology of one of the notables of the followers, which is: (Abi Mijlis Al-Basri), who had a clear impact on many commentators after him, especially in the field of interpretation by impact. This study included two topics:

The first: his biography and scientific

The second: his methodology in the traditional interpretation.

A fuzzy logic approach (FLA) application in the process of stud arc welding environment was implemented under the condition of fuzziness input data. This paper is composed of the background of FLA, related research work review and points for developing in stud welding manufacturing. Then, it investigates thecase of developingstud arc welding process on the controversial certaintyof available equipment and human skills.Five parameters (welding time, sheet thickness, type of coating, welding current and stud shape) were studied.A pair of parameter was selected asiteration whichis welding current and welding time and used fo

   Regarding to the computer system security, the intrusion detection systems are fundamental components for discriminating attacks at the early stage. They monitor and analyze network traffics, looking for abnormal behaviors or attack signatures to detect intrusions in early time. However, many challenges arise while developing flexible and efficient network intrusion detection system (NIDS) for unforeseen attacks with high detection rate. In this paper, deep neural network (DNN) approach was proposed for anomaly detection NIDS. Dropout is the regularized technique used with DNN model to reduce the overfitting. The experimental results applied on NSL_KDD dataset. SoftMax output layer has been used with cross entropy loss funct