A particle swarm optimization algorithm and neural network like self-tuning PID controller for CSTR system is presented. The scheme of the discrete-time PID control structure is based on neural network and tuned the parameters of the PID controller by using a particle swarm optimization PSO technique as a simple and fast training algorithm. The proposed method has advantage that it is not necessary to use a combined structure of identification and decision because it used PSO. Simulation results show the effectiveness of the proposed adaptive PID neural control algorithm in terms of minimum tracking error and smoothness control signal obtained for non-linear dynamical CSTR system.
Using the Neural network as a type of associative memory will be introduced in this paper through the problem of mobile position estimation where mobile estimate its location depending on the signal strength reach to it from several around base stations where the neural network can be implemented inside the mobile. Traditional methods of time of arrival (TOA) and received signal strength (RSS) are used and compared with two analytical methods, optimal positioning method and average positioning method. The data that are used for training are ideal since they can be obtained based on geometry of CDMA cell topology. The test of the two methods TOA and RSS take many cases through a nonlinear path that MS can move through that region. The result
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The removal of SO2 from simulated gas stream (SO2 + air) in a fixed bed reactor using Modified Activated Carbon (MAC) catalysts was investigated. All the experiments were conducted at atmospheric pressure, initial SO2 concentration of 2500 ppm and bed temperature of 90oC. MAC was prepared by loading a series of nickel and copper oxides 1, 3, 5, 7, and 10 w
... Show MoreThe transmitting and receiving of data consume the most resources in Wireless Sensor Networks (WSNs). The energy supplied by the battery is the most important resource impacting WSN's lifespan in the sensor node. Therefore, because sensor nodes run from their limited battery, energy-saving is necessary. Data aggregation can be defined as a procedure applied for the elimination of redundant transmissions, and it provides fused information to the base stations, which in turn improves the energy effectiveness and increases the lifespan of energy-constrained WSNs. In this paper, a Perceptually Important Points Based Data Aggregation (PIP-DA) method for Wireless Sensor Networks is suggested to reduce redundant data before sending them to the
... Show MoreThe traction property is one of the important mechanical properties, especially the rotary parts which are subjected to constant and variable loads There are many methods used to improve this property, and the shoot peening by metal balls is considered the most critical one. the study focuses on this characteristic of steel CK35 used in many engineering applications as the rotating shafts and railway This study shows that the fatigue strength is improved by14% after shoot peening with metal balls. The study includs the rehabilitation of damaged samples as a result of fatigue corrosion. The standard solution adopted was 36% MgCl2 with a 30 days immersion period. These samples has been improved by 6% after it decreased by18% d
... Show Moreيؤدي عرض معلومات مضللة او محرفة ضمن القوائم المالية والتي تعد أهم مصادر المعلومات الموثوقة التي يُعول عليها لاتخاذ القرارات السليمة الى عدم قدرتها على عكس نتيجة النشاط والمركز المالي لها او اعمال الوحدة الاقتصادية لتلك الفترات الزمنية بصورة صادقة وعادلة نتيجة لنوعية المعلومات المفصح عنها في القوائم المالية لذلك زاد الاهتمام بتطوير الممارسات المحاسبية لتتضمن افصاحات كافية بغرض اعطائهم صورة صادقة وعادلة
... Show MoreEarly detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze med
... Show MoreThe inverse kinematic equation for a robot is very important to the control robot’s motion and position. The solving of this equation is complex for the rigid robot due to the dependency of this equation on the joint configuration and structure of robot link. In light robot arms, where the flexibility exists, the solving of this problem is more complicated than the rigid link robot because the deformation variables (elongation and bending) are present in the forward kinematic equation. The finding of an inverse kinematic equation needs to obtain the relation between the joint angles and both of the end-effector position and deformations variables. In this work, a neural network has been proposed to solve the problem of inverse kinemati
... Show MoreThe aim of this study was to determine the effect on using the McCarthy Model (4MAT) for developing creative writing skills and reflective thinking among undergraduate students. The quasi-experimental approach was adopted. And, in order to achieve the study objective, the educational content of Teaching Ethics (Approach 401), for the plan for the primary grades teacher preparation program was dealt with by using a teaching program based on the McCarthy Model (4MAT) was used.
The study which was done had been based on the academic achievement test for creative writing skills, and the reflective thinking test. The validity and reliability of the study tools were also confirmed. The study was applied to a sample consisting of
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