<p class="Abstract">This New learning educational methods, which depending on Learning Management System (LMS), have been used by universities in the top education universities in the world. However, most of the Iraqi universities use the traditional education methods in the classroom. The purpose of this study was to examine the benefit of using LMS in higher education.  This study shows how to implement and use modern educational techniques in Engineering College of Wasit University. This paper shows that using modern education tools in the class lead to increase the productivity of student, save time with less effort for instructors with high accuracy of exam results. In addition, using LMS system allows students to obtain more information in a short time. Moreover, this system gives students an opportunity to interact with the instructor and among themselves. The findings show the benefits of integrating LMS in higher education and recommend other institutions to implement it.</p>

<p>Du to the raising  number  of  using Internet of Things (I O T) for personal and commercial devices and applications, as well as the continues needs for improving the quality of the performance for the internet – connected devices enhance the researchers to investigate solutions for managing the data through the network Because of the fact that  the internet-connected devices needs addresses for each sensor node uses the IP-network and a large number of electronic modules is fabricated to be compatible with IPv4 only like NodeMcu, ESP8266, Arduino WIFI, and ESP32  with knowing that the IPv4 has a limited addresses number that will not be enough for the needs of  IOT developments, Many researchers turned to IPv6. In the  proposed system, another solution is suggested instead of the IPV6. The proposed idea is based on Non-IP Wireless Sensor Network (WSN) by connecting many sensing nodes to the sink-node that has an IP to forward the data to the server to be visualized in a web-portal. By this method, it is able to connect more than one node to the internet over only one IP, there for the data rate that are needed will be decreased. In addition, by using the non-IP network, the data rate and the power consuming by the sensor nodes have been reduced, the practical results are discussed for connecting four nodes over one IP4 and how it will reduce the data rate and the power consuming. In this work, the esp33 has been used as a Sink-node, and the wireless transceiver module( NRF24) has been utilized to transmit the data from nodes to esp32.</p>

<p>In recent years, the Internet of things has become an urgent need in all of things that a person needs with least  effort and time. It covers in several areas, including controlling traffic and parking, following up on general and private buildings that  what you need of  periodic maintenance, and reducing energy through using  lighting Smart. In this paper, we focus on important thing and widespread in Iraq  , collection of solid waste in the streets without treatment, which causes environmental and psychological damage to the citizen.in addition , the solid waste deposal need set up sensors(RFID,GPS, ultrasonic, GSM,…etc), connecting them to Arduino Uno to accomplish specific intelligent processing that we need. Moreover, the system provides waste containers and warns the concerned departments in the city of the need to empty them when they reach a certain level, which makes the streets healthier, more attractive and free from rodents.</p>

Liver disease counts to be one of the most prevalent diseases in the worldwide. Therefore, this paper is aim to address the problem of predicting liver disease progression. As the existing predictive models focus on predicting the label of disease; the probability of developing the disease is still obscure. This paper, therefore, has proposed a model to predict the probability occurrence of liver diseases. The proposed predictive model used logistic regression abilities to predict the probability of liver disease occurrence. ILPD dataset was used to analyze the performance of the model. The predictive model has shown outstanding performance with a prediction accuracy rate of 72.4%, the sensitivity of 90.3%, the specificity of 78.3 %, Type I Error of 9.7 %, Type II Error of 21.7 %, and ROC of 0.758%. The model has furthermore confirmed the feasibility of the laboratory tests such as as (Age; Direct Bilirubin (DB), Alamine_Aminotransferase (SGPT), Total_Protiens (TP), Albumin (ALB)) to predict the disease progression. The predictive model will be helpful to patients and doctors to realize the progression of the disease and make a suitable timely intervention.

This paper presents an automated car license plate recognition system applied for Iraqi vehicle plate number that developed and applied to be used in control and law enforcement related applications. In this work, the proposed license plate recognition consists of three basic stages (preprocessing, license plate localization, license plate recognition). The license plate images are pre-processed through convert image to grayscale and apply morphological transformation filter not convert the result to binary image. Then, blurs the binary image using Gaussian filter and find all contour in image using OpenCV library. In the license plate localization KNN (k-Nearest Neighbors) algorithm are used to find all possible characters in the image. The last step is done by Crop the part of image with highest candidate license plate and apply the preprocessing and license plate localization again to find and recognize all part of license plate in the cropped image.