In this paper, a self-tuning adaptive neural controller strategy for unknown nonlinear system is presented. The system considered is described by an unknown NARMA-L2 model and a feedforward neural network is used to learn the model with two stages. The first stage is learned off-line with two configuration serial-parallel model & parallel model to ensure that model output is equal to actual output of the system & to find the jacobain of the system. Which appears to be of critical importance parameter as it is used for the feedback controller and the second stage is learned on-line to modify the weights of the model in order to control the variable parameters that will occur to the system. A back propagation neural network is applied to learn the control structure for self-tuning PID type neuro-controller. Where the neural network is used to minimize the error function by adjusting the PID gains. Simulation results show that the self-tuning PID scheme can deal with a large unknown nonlinearity
DeepFake is a concern for celebrities and everyone because it is simple to create. DeepFake images, especially high-quality ones, are difficult to detect using people, local descriptors, and current approaches. On the other hand, video manipulation detection is more accessible than an image, which many state-of-the-art systems offer. Moreover, the detection of video manipulation depends entirely on its detection through images. Many worked on DeepFake detection in images, but they had complex mathematical calculations in preprocessing steps, and many limitations, including that the face must be in front, the eyes have to be open, and the mouth should be open with the appearance of teeth, etc. Also, the accuracy of their counterfeit detectio
... Show MoreThe research focuses on determination of best location of high elevated tank using the required head of pump as a measure for this purpose. Five types of network were used to find the effect of the variation in the discharge and the node elevation on the best location. The most weakness point was determined for each network. Preliminary tank locations were chosen for test along the primary pipe with same interval distance. For each location, the water elevation in tank and pump head was calculated at each hour depending on the pump head that required to achieve the minimum pressure at the most weakness point. Then, the sum of pump heads through the day was determined. The results proved that there is a most economical lo
... Show MorePID (proportional-integral-derivative) and Mu controllers are widely used in electro-hydraulic servo systems due to their effectiveness and ease of implementation. This paper explores using particle swarm optimization (PSO) for tuning traditional and robust PID controllers, along with D-K iteration for Mu controller tuning. Three controller types: conventional PID (CPID), robust PID (RPID), and structured singular value controllers are developed, while analyzing multiplicative uncertainty with six uncertain coefficients. Their findings indicated that both PID (CPID and RPID) and Mu controllers maintained system stability. Notably, the Mu controller can handle coefficient uncertainty without a pure integral term, while the RPID controller de
... Show MoreFerritin is a key organizer of protected deregulation, particularly below risky hyperferritinemia, by straight immune-suppressive and pro-inflammatory things. , We conclude that there is a significant association between levels of ferritin and the harshness of COVID-19. In this paper we introduce a semi- parametric method for prediction by making a combination between NN and regression models. So, two methodologies are adopted, Neural Network (NN) and regression model in design the model; the data were collected from مستشفى دار التمريض الخاص for period 11/7/2021- 23/7/2021, we have 100 person, With COVID 12 Female & 38 Male out of 50, while 26 Female & 24 Male non COVID out of 50. The input variables of the NN m
... Show MoreSampling is the selection of a representative portion of a material, and it’s as important as testing. The minimum weight of gravel field or lab sample depends on the nominal maximum particle size. The weight of the sample will always be greater than that portion required for testing. The approximate precision desired for the testing will control the weight of the gravel sample. In this study, gravel sample has been simulated by using multilinear approximated function for Fuller’s curve on the logarithmic scale. Gravel particles are divided into classes according to their medium diameter and each class was simulated separately. A stochastic analysis, by using 100 realizations in s
Fine aggregate (Sand) is a necessary material used in concrete construction purposes, it’s naturally available and it’s widely used around the world for different parts of construction in any building mainly for filling the voids between gravel. Sand gradation is important for different composite materials, and it gives good cohesion when compared with coarse sand that provides strength for the building. Therefore, sand is necessary to be tested before it is used and mixed with other building materials in construction and the specimen must be selected carefully to represent the real material in the field. The specimen weight must be larger than the required weight for test. When t
Praise be to God, Lord of the worlds, and prayers and peace be upon our master Muhammad and upon his family and companions as a whole.
The topic of attention was drawn to the attention of the speakers, as it made me ponder it carefully, and my goal in that is to know the reason for the interest of the speakers and their care for it, and to clarify from their books the purpose of making this topic one of the advanced investigations with them.
The idea of writing a paper on the subject of consideration was not absent from my thinking, because I saw the attention of speakers on this issue, as they made it one of the first issues that they deal with studying in their work
... Show MoreAg2O (Silver Oxide) is an important p-type (in chasm to most oxides which were n-type), with a high conductivity semiconductor. From the optical absorbance data, the energy gap value of the Ag2O thin films was 1.93 eV, where this value substantially depends on the production method, vacuum evaporation of silver, and optical properties of Ag2O thin films are also affected by the precipitation conditions. The n-type and p-type silicon substrates were used with porous silicon wafers to precipitate ±125 nm, as thick Ag2O thin film by thermal evaporation techniques in vacuum and via rapid thermal oxidation of 400oC and oxidation time 95 s, then characterized by measurement of
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