Energy efficiency is a significant aspect in designing robust routing protocols for wireless sensor networks (WSNs). A reliable routing protocol has to be energy efficient and adaptive to the network size. To achieve high energy conservation and data aggregation, there are two major techniques, clusters and chains. In clustering technique, sensor networks are often divided into non-overlapping subsets called clusters. In chain technique, sensor nodes will be connected with the closest two neighbors, starting with the farthest node from the base station till the closest node to the base station. Each technique has its own advantages and disadvantages which motivate some researchers to come up with a hybrid routing algorit

An intrusion detection system (IDS) is key to having a comprehensive cybersecurity solution against any attack, and artificial intelligence techniques have been combined with all the features of the IoT to improve security. In response to this, in this research, an IDS technique driven by a modified random forest algorithm has been formulated to improve the system for IoT. To this end, the target is made as one-hot encoding, bootstrapping with less redundancy, adding a hybrid features selection method into the random forest algorithm, and modifying the ranking stage in the random forest algorithm. Furthermore, three datasets have been used in this research, IoTID20, UNSW-NB15, and IoT-23. The results are compared with the three datasets men

In the present work studies were carried out to extract a cationic dye (Methylene Blue MB) from an aqueous solution using emulsion liquid membrane process (ELM). The organic phase (membrane phase) consists of Span 80 as emulsifier, sulfuric acid solution as stripping agent and hexane as diluent. 

In this study, important factors influencing the extraction of methylene blue dye were studied. These factors include H₂SO₄ concentration in the stripping phase, agitation speed in the dye permeation stage, Initial dye concentration and diluent type.

   More than (98%) of Methylene blue dye was extracted at the following conditions: H₂SO₄ concentration (1.25) M, agitation

Electro coagulation treatment was used for zinc removal from electroplating wastewater of the State Company for Electrical Industries . This wastewater, here consists zinc ions with maximum concentration in solution of 90 ppm .

The parameters that influenced the wastewater treatment are: current density in the range  1-1.4 mA/cm2, pH  in the range 5-10, temperature in the range 25-45°C and time in the range 10-180 minute.

The research is a laboratory experimental type using batch system for electrical process with direct current. The cell comprised of aluminum electrode as anode and stainless steel electrode as cathode. Thirty experiments and one hundred fifty sample lab tests were carried out in this research

   The removal of Ibuprofen antibiotics (IBU) by photo-degradation UV/H₂O₂/Fe⁺² system was investigated in a batch reactor under different initial concentrations of H₂O₂ (100-500) mg/L, Fe⁺² (10-40) mg/L, pH (3-9) and initial concentrations of IBU (10-80) mg/L, and their relationship with the degradation efficiency were studied. The result demonstrated that the maximum elimination of IBU was 85.54% achieved at 300 mg/L of H₂O₂, 30 mg/L of Fe⁺², pH=3, and irradiation time of 150 min, for 10 mg/L of IBU. The results have shown that the oxidation reagent H₂O₂ plays a very important role in IBU degradation.

In this paper, the speed control of the real DC motor is experimentally investigated using nonlinear PID neural network controller. As a simple and fast tuning algorithm, two optimization techniques are used; trial and error method and particle swarm optimization PSO algorithm in order to tune the nonlinear PID neural controller's parameters and to find best speed response of the DC motor. To save time in the real system, a Matlab simulation package is used to carry out these algorithms to tune and find the best values of the nonlinear PID parameters. Then these parameters are used in the designed real time nonlinear PID controller system based on LabVIEW package. Simulation and experimental results are compared with each other and showe

Determining the face of wearing a mask from not wearing a mask from visual data such as video and still, images have been a fascinating research topic in recent decades due to the spread of the Corona pandemic, which has changed the features of the entire world and forced people to wear a mask as a way to prevent the pandemic that has calmed the entire world, and it has played an important role. Intelligent development based on artificial intelligence and computers has a very important role in the issue of safety from the pandemic, as the Topic of face recognition and identifying people who wear the mask or not in the introduction and deep education was the most prominent in this topic. Using deep learning techniques and the YOLO (”You on

For businesses that provide delivery services, the efficiency of the delivery process in terms of punctuality is very important. In addition to increasing customer trust, efficient route management, and selection are required to reduce vehicle fuel costs and expedite delivery. Some small and medium businesses still use conventional methods to manage delivery routes. Decisions to manage delivery schedules and routes do not use any specific methods to expedite the delivery settlement process. This process is inefficient, takes a long time, increases costs and is prone to errors. Therefore, the Dijkstra algorithm has been used to improve the delivery management process. A delivery management system was developed to help managers and drivers

Pilot-scale dead end microfiltration membranes were carried out to determine the feasibility of the process for treating the oily wastewater which discharge from some Iraqi factories such as power station of south of Baghdad and the general company of petrochemical industries. Polypropylene membranes (cylindrical shape) with different pore diameters (1 and 5 micron) were used to conduct the study on micromembrane process. The variables studied are oil concentration (100 – 1000 ppm), feed flow rate (20 – 40 l/h), operating temperature (31 – 50°C) and time (0 – 3 h). It was found that the flux increases with increasing feed flow rate, temperature and pore size of membrane, and decreases with increasing oil concentration and operating