Machine scheduling problems (MSP) are     considered as one of the most important classes of combinatorial optimization problems. In this paper, the problem of job scheduling on a single machine is studied to minimize the multiobjective and multiobjective objective function. This objective function is: total completion time, total lead time and maximum tardiness time, respectively, which are formulated as  are formulated. In this study, a mathematical model is created to solve the research problem. This problem can be divided into several sub-problems and simple algorithms have been found to find the solutions to these sub-problems and compare them with efficient solutions. For this problem, some rules that provide efficient solutio

Autonomous motion planning is important area of robotics research. This type of planning relieves human operator from tedious job of motion planning. This reduces the possibility of human error and increase efficiency of whole process.

This research presents a new algorithm to plan path for autonomous mobile robot based on image processing techniques by using wireless camera that provides the desired image for the unknown environment . The proposed algorithm is applied on this image to obtain a optimal path for the robot. It is based on the observation and analysis of the obstacles that lying in the straight path between the start and the goal point by detecting these obstacles, analyzing and studying their shapes, positions and

Android operating system, since its first start, is growing very fast and takes a large space in smart devices market. It is built and developed on Linux and designed basically for touch screen devices such as, mobiles, tablets, etc. Mobile devices are markedly complicated and feature-rich; therefore they are prone to reliability of software and performance problems. Because of the small resources, smart devices, such as CPU, RAM, suffer from problems. One of these problems is Software Aging (SA). SA is recognized in long running OSs as a shortage in resources, performance retreating, and finally failure. SA is looked at from two sides, namely the poor response time of application which represents the end user side and the shortage in me

Coronavirus disease (COVID-19) is an acute disease that affects the respiratory system which initially appeared in Wuhan, China. In Feb 2019 the sickness began to spread swiftly throughout the entire planet, causing significant health, social, and economic problems. Time series is an important statistical method used to study and analyze a particular phenomenon, identify its pattern and factors, and use it to predict future values. The main focus of the research is to shed light on the study of SARIMA, NARNN, and hybrid models, expecting that the series comprises both linear and non-linear compounds, and that the ARIMA model can deal with the linear component and the NARNN model can deal with the non-linear component. The models

In this paper we generalize some of the results due to Bell and Mason on a near-ring N admitting a derivation D , and we will show that the body of evidence on prime near-rings with derivations have the behavior of the ring. Our purpose in this work is to explore further this ring like behavior. Also, we show that under appropriate additional hypothesis a near-ring must be a commutative ring.

This research presents a new algorithm for classification the
shadow and water bodies for high-resolution satellite images (4-
meter) of Baghdad city, have been modulated the equations of the
color space components C1-C2-C3. Have been using the color space
component C3 (blue) for discriminating the shadow, and has been
used C1 (red) to detect the water bodies (river). The new technique
was successfully tested on many images of the Google earth and
Ikonos. Experimental results show that this algorithm effective to
detect all the types of the shadows with color, and also detects the
water bodies in another color. The benefit of this new technique to
discriminate between the shadows and water in fast Matlab pro

     Agriculture improvement is a national economic issue that extremely depends on productivity. The explanation of disease detection in plants plays a significant role in the agriculture field. Accurate prediction of the plant disease can help treat the leaf as early as possible, which controls the economic loss. This paper aims to use the Image processing techniques with Convolutional Neural Network (CNN). It is one of the deep learning techniques to classify and detect plant leaf diseases. A publicly available Plant village dataset was used, which consists of 15 classes, including 12 diseases classes and 3 healthy classes.  The data augmentation techniques have been used. In addition to dropout and weight reg

This study introduced the effect of using magnetic abrasive finishing method (MAF) for finishing flat surfaces. The results of experiment allow considering the MAF method as a perspective for finishing flat surfaces, forming optimum physical mechanical properties of surfaces layer, removing the defective layers and decreasing the height of micro irregularities. Study the characteristics which permit judgment parameters of surface quality after MAF method then comparative with grinding

The present work deals with an experimental investigation of charging and discharging processes in thermal storage system using a phase change material PCM. Paraffin wax was used as the PCM which is formed in spherical capsules and packed in a cylindrical packed column which acted as an energy storage system. Air was used as the heat transfer fluid HTF in thermal storage unit. The effect of flow rate and inlet temperature of HTF on the time of charging and discharging process were studied. The results showed that the faster storage of thermal energy can be made by high flow rate of heat transfer fluid HTF and high inlet temperature of heat transfer fluid. It was found that at 65°C HTF inlet temperature, the melting and solidification pr