Renewable energy technology is growing fast especially photovoltaic (PV) system to move the conventional electricity generation and distribution towards smart grid. However, similar to monthly electricity bill, the PV energy producers can only monitor their energy PV generation once a month. Any malfuntion in PV system components may reduce the performance of the system without notice. Thus, developing a real-time monitoring system of PV production is very crucial for early detection. In addition, electricity consumption is also important to be monitored more frequently to increase energy savings awareness among consumers. Hardware based Internet-of-Thing (IoT) monitoring and control system is widely used. However, the implementation of

Quality control is an effective statistical tool in the field of controlling the productivity to monitor and confirm the manufactured products to the standard qualities and the certified criteria for some products and services and its main purpose is to cope with the production and industrial development in the business and competitive market. Quality control charts are used to monitor the qualitative properties of the production procedures in addition to detecting the abnormal deviations in the production procedure. The multivariate Kernel Density Estimator control charts method was used which is one of the nonparametric methods that doesn’t require any assumptions regarding the distribution o

The aim of this research is controlling the amount of the robotic hand catching force using the artificial muscle wire as an actuator to achieve the desired response of the robotic hand in order to catch different things without destroying or dropping them; where the process is to be similar to that of human hand catching way. The proper selection of the amount of the catching force is achieved through out simulation using the fuzzy control technique. The mechanism of the arrangement of the muscle wires is proposed to achieve good force selections. The results indicate the feasibility of using this proposed technique which mimics human reasoning where as the weight of the caught peace increases, the force increases also with approximatel

An epidemiological study in Al-Mahmmodiya (50 km south Baghdad) to investigate a possible vector of Leishmaniasis were applied .This region is considered as a foci of Leishmaniasisaccording to the health association statistics. CDC light traps were used to collect the insects nightly. Insects were collected by Indoor application as human dwellings and animal shelters and Outdoor application as rodent's barrows and field trees. Sand flies were transported to the laboratory, isolated and identified according to the identification keys in Tropical Biological Researches Unit at the Collage of Science / University of Baghdad. Must of the collected sand flies were belonging to three species PhlebotomuspapatasiScopoli(45%), PhlebotomusalexandriSin

In recent years, the field of research around the congestion problem of 4G and 5G networks has grown, especially those based on artificial intelligence (AI). Although 4G with LTE is seen as a mature technology, there is a continuous improvement in the infrastructure that led to the emergence of 5G networks. As a result of the large services provided in industries, Internet of Things (IoT) applications and smart cities, which have a large amount of exchanged data, a large number of connected devices per area, and high data rates, have brought their own problems and challenges, especially the problem of congestion. In this context, artificial intelligence (AI) models can be considered as one of the main techniques that can be used to solve ne

Inefficient wastewater disposal and wastewater discharge problems in water bodies have led to increasing pollution in water bodies.  Pollutants in the river contribute to increasing the biological oxygen demand (BOD), total suspended solids (SS), total dissolved solids (TDS), chemical oxygen demand (COD), and toxic metals render this water unsuitable for consumption and even pose a significant risk to human health. Over the last few years, water conservation has been the subject of growing awareness and concern throughout the world, so this research focused on review studies of researches that studied the importance of water quality of wastewater treated disposal in water bodies and modern technology to management w

Nowadays, Wheeled Mobile Robots (WMRs) have found many applications as industry, transportation, inspection, and other fields. Therefore, the trajectory tracking control of the nonholonomic wheeled mobile robots have an important problem. This work focus on the application of model-based on Fractional Order  PI^aD^b (FOPID) controller for trajectory tracking problem. The control algorithm based on the errors in postures of mobile robot which feed to FOPID controller to generate correction signals that transport to  torque for each driven wheel, and by means of dynamics model of mobile robot these torques used to compute the linear and angular speed to reach the desired pose. In this work a dynamics model of

The hydraulic conditions of a flow previously proved to be changed when placing large-scale geometric roughness elements on the bed of an open channel. These elements impose more resistance to the flow.  The geometry of the roughness elements, the numbers used, and the configuration are parameters that can affect the hydraulic flow characteristics. The target is to use inclined block elements to control the salt wedge propagation pointed in most estuaries to prevent its negative effects. The Computational Fluid Dynamics CFD Software was used to simulate the two-phase flow in an estuary model. In this model, the used block elements are 2 cm by 3 cm cross-sections with an inclined face in the flow direction, with a length

Software Defined Networking (SDN) with centralized control provides a global view and achieves efficient network resources management. However, using centralized controllers has several limitations related to scalability and performance, especially with the exponential growth of 5G communication. This paper proposes a novel traffic scheduling algorithm to avoid congestion in the control plane. The Packet-In messages received from different 5G devices are classified into two classes: critical and non-critical 5G communication by adopting Dual-Spike Neural Networks (DSNN) classifier and implementing it on a Virtualized Network Function (VNF). Dual spikes identify each class to increase the reliability of the classification