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An Optimized Approach for Industrial IoT Based on Edge Computing
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The Internet of Things (IoT) is an information network that connects gadgets and sensors to allow new autonomous tasks. The Industrial Internet of Things (IIoT) refers to the integration of IoT with industrial applications. Some vital infrastructures, such as water delivery networks, use IIoT. The scattered topology of IIoT and resource limits of edge computing provide new difficulties to traditional data storage, transport, and security protection with the rapid expansion of the IIoT. In this paper, a recovery mechanism to recover the edge network failure is proposed by considering repair cost and computational demands. The NP-hard problem was divided into interdependent major and minor problems that could be solved in polynomial time by using the Benders decomposition technique and cutting plane approximation. To ensure the nonincreasing character of the Benders upper limit, a local branching method was also added to improve the convergence. Simulation results indicated that the proposed method is superior to the existing method and has better overall performance.

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Publication Date
Mon Jul 01 2019
Journal Name
Iop Conference Series: Materials Science And Engineering
On Estimation of the Stress – Strength Reliability Based on Lomax Distribution
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Abstract<p>The present paper concerns with the problem of estimating the reliability system in the stress – strength model under the consideration non identical and independent of stress and strength and follows Lomax Distribution. Various shrinkage estimation methods were employed in this context depend on Maximum likelihood, Moment Method and shrinkage weight factors based on Monte Carlo Simulation. Comparisons among the suggested estimation methods have been made using the mean absolute percentage error criteria depend on MATLAB program.</p>
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Publication Date
Tue Dec 15 2020
Journal Name
Al-academy
Aesthetic and Functional Dimensions of the Industrial Product and their Influence on Construction of Consumer's Visual Impression: جاسم احمد زيدان
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  The visual impression represents a compound process of a group of concepts that might be secondary and interrelated to constitute, in reality, a cognitive image stored in the memory that can be retrieved according the implications of the situation in which the individual lives in his environment, as it awakens in him an image from the sub consciousness, thus it gets stimulated, and it is among the tangible things.
Since we live in our contemporary world under the development of knowledge, micro and wide technology of the devices, tools, materials, mechanisms, current developments and openness… etc. this transformation created visual impressions that the individual in general and the consumer in specific enjoys concerning his

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Publication Date
Thu Jan 25 2024
Journal Name
Iraqi Journal Of Agricultural Sciences
EFFECTS OF MINERAL FERTILIZATION AND SPRAYING WITH SALICYLIC ACID AND AMINO ACIDS ON THE GROWTH AND PRODUCTIVITY OF INDUSTRIAL POTATOES
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This experiment was carried out at a private field in the eastern Radwaniyah Baghdad for the fall season 2020/2021 and spring 2021 to study the effects of adding mineral fertilizers, spraying salicylic acid and amino acids on some growth traits and yield of industrial potato plants. 200 kg N h-1 , 100 kg P2O5 h-1, 100 kg K2O h-1 and F2 consist of 275 kg N h-1, 180 kg P2O5 h-1, 200 K2O h-1 and F3 consist of 350 kg N h-1, 360 kg P2O5 h-1, 300 K2O h-1 and salicylic acid in three concentrations of 0,50 and 100 mg L-1 ( S1, S2, S3) and amino acids in three concentrations of 0, 1.25 and 2.5 ml L-1 ( A1, A2 , A3) It was carried out as a factorial split plot experiment, where the fertilizer levels (F1, F2 and F3) are in the main plot and th

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Publication Date
Sat Jul 08 2017
Journal Name
Neural Computing And Applications
A new algorithm of modified binary particle swarm optimization based on the Gustafson-Kessel for credit risk assessment
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Publication Date
Tue Sep 08 2020
Journal Name
Baghdad Science Journal
Modified BFGS Update (H-Version) Based on the Determinant Property of Inverse of Hessian Matrix for Unconstrained Optimization
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The study presents the modification of the Broyden-Flecher-Goldfarb-Shanno (BFGS) update (H-Version) based on the determinant property of inverse of Hessian matrix (second derivative of the objective function), via updating of the vector s ( the difference between the next solution and the current solution), such that the determinant of the next inverse of Hessian matrix is equal to the determinant of the current inverse of Hessian matrix at every iteration. Moreover, the sequence of inverse of Hessian matrix generated by the method would never  approach a near-singular matrix, such that the program would never break before the minimum value of the objective function is obtained. Moreover, the new modification of BFGS update (H-vers

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Publication Date
Thu Jan 29 2026
Journal Name
Journal Of Interdisciplinary Mathematics
Efficient design of neural network based on modified LM training algorithm for solving nonlinear 4th order 3D-PDEs 
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Authors in this work design efficient neural networks, which are based on the modified Levenberg - Marquardt (LM) training algorithms to solve non-linear fourth - order three -dimensional partial differential equations in the two kinds in the periodic and in the non-periodic - Periodic. Software reliability growth models are essential tools for monitoring and evaluating the evolution of software reliability. Software defect detection events that occur during testing and operation are often treated as counting processes in many current models. However, when working with large software systems, the error detection process should be viewed as a random process with a continuous state space, since the number of faults found during testin

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Publication Date
Tue Apr 02 2019
Journal Name
Artificial Intelligence Research
A three-stage learning algorithm for deep multilayer perceptron with effective weight initialisation based on sparse auto-encoder
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A three-stage learning algorithm for deep multilayer perceptron (DMLP) with effective weight initialisation based on sparse auto-encoder is proposed in this paper, which aims to overcome difficulties in training deep neural networks with limited training data in high-dimensional feature space. At the first stage, unsupervised learning is adopted using sparse auto-encoder to obtain the initial weights of the feature extraction layers of the DMLP. At the second stage, error back-propagation is used to train the DMLP by fixing the weights obtained at the first stage for its feature extraction layers. At the third stage, all the weights of the DMLP obtained at the second stage are refined by error back-propagation. Network structures an

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Publication Date
Tue Mar 12 2024
Journal Name
Semiconductor Physics, Quantum Electronics And Optoelectronics
Numerical study of single-layer and interlayer grating polarizers based on metasurface structures for quantum key distribution systems
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Polarization is an important property of light, which refers to the direction of electric field oscillations. Polarization modulation plays an essential role for polarization encoding quantum key distribution (QKD). Polarization is used to encode photons in the QKD systems. In this work, visible-range polarizers with optimal dimensions based on resonance grating waveguides have been numerically designed and investigated using the COMSOL Multiphysics Software. Two structures have been designed, namely a singlelayer metasurface grating (SLMG) polarizer and an interlayer metasurface grating (ILMG) polarizer. Both structures have demonstrated high extinction ratios, ~1.8·103 and 8.68·104 , and the bandwidths equal to 45 and 55 nm for th

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Publication Date
Sun Jan 01 2023
Journal Name
Aip Conference Proceedings
Sliding mode control based on high-order extended state observer for flexible joint robot under time-varying disturbance
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Abstract. In this paper, a high order extended state observer (HOESO) based a sliding mode control (SMC) is proposed for a flexible joint robot (FJR) system in the presence of time varying external disturbance. A composite controller is integrated the merits of both HOESO and SMC to enhance the tracking performance of FJR system under the time varying and fast lumped disturbance. First, the HOESO estimator is constructed based on only one measured state to precisely estimate unknown system states and lumped disturbance with its high order derivatives in the FJR system. Second, the SMC scheme is designed based on such accurate estimations to govern the nominal FJR system by well compensating the estimation errors in the states and the lumped

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Publication Date
Mon Aug 01 2011
Journal Name
Journal Of Engineering
DAMAGE DETECTION AND LOCATION FOR IN AND OUT-OFPLANE CURVED BEAMS USING FUZZY LOGIC BASED ON FREQUENCY DIFFERENCE
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In this study, structures damage identification method based on changes in the dynamic characteristics
(frequencies) of the structure are examined, stiffness as well as mass matrices of the curved
(in and out-of-plane vibration) beam elements is formulated using Hamilton's principle. Each node
of both of them possesses seven degrees of freedom including the warping degree of freedom. The
curved beam element had been derived based on the Kang and Yoo’s thin-walled curved beam theory
in 1994. A computer program was developing to carry out free vibration analyses of the curved
beam as well as straight beam. Comparing with the frequencies for other researchers using the general
purpose program MATLAB. Fuzzy logic syste

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