According to the importance of the conveyor systems in various industrial and service lines, it is very desirable to make these systems as efficient as possible in their work. In this paper, the speed of a conveyor belt (which is in our study a part of an integrated training robotic system) is controlled using one of the artificial intelligence methods, which is the Artificial Neural Network (ANN). A visions sensor will be responsible for gathering information about the status of the conveyor belt and parts over it, where, according to this information, an intelligent decision about the belt speed will be taken by the ANN controller. ANN will control the alteration in speed in a way that gives the optimized energy efficiency through the conveyor belt motion. An optimal speed controlling mechanism of the conveyor belt is presented by detecting smartly the parts' number and weights using the vision sensor, where the latter will give sufficient visualization about the system. Then image processing will deliver the important data to ANN, which will optimally decide the best conveyor belt speed. This decided speed will achieve the aim of power saving in belt motion. The proposed controlling system will optimally switch the speed of the conveyor belt system to ON, OFF and idle status in order to minimize the consumption of energy in the conveyor belt. As the conveyor belt is fully loaded it moves at its maximum speed. But if the conveyor is partially loaded, the speed will be adjusted accordingly by the ANN. If no loading existed, the conveyor will be stopped. By this way, a very significant energy amount in addition to cost will be saved. The developed conveyor belt system will modernize industrial manufacturing lines, besides reducing energy consumption and cost and increasing the conveyor belts lifetime
It is often needed to have circuits that can display the decimal representation of a binary number and specifically in this paper on a 7-segment display. In this paper a circuit that can display the decimal equivalent of an n-bit binary number is designed and it’s behavior is described using Verilog Hardware Descriptive Language (HDL).
This HDL program is then used to configure an FPGA to implement the designed circuit.
تعد المبارزة أحد الألعاب الرياضية التي يتأثر فيها الأداء بتطور القدرات الخاصة بالأداء ومنها تحمل (سرعة وقوة الأداء ),وأن أكثر الأساليب السابقة في تدريب تطوير تحمل(سرعة وقوة الأداء) بالمبارزة تكون على ارض صلبة مثل الخشب والألمنيوم آو الإسفلت وفي بعض القاعات يكون التارتان, وظل هذا الأسلوب لفترات طويلة في العراق ،حيث تستخدم تدريبات الإثقال التي تعمل على تنمية تحمل القوة . أما في الوقت الحاضر فقد ظهر اتجاه حديث في
... Show MoreAutorías: Mariam Liwa Abdel Fattah, Liqaa Abdullah Ali. Localización: Revista iberoamericana de psicología del ejercicio y el deporte. Nº. 4, 2023. Artículo de Revista en Dialnet.
Recently, there has been a major trend towards environmental issues and concern for the green product because traditional products cause serious environmental impacts such as reduced resources, global warming, energy consumption, emissions and other environmental damage. Under these developments, economic units are looking for cost-effective technologies that reduce the cost of a green product that has four main dimensions: reducing energy, reducing resource consumption, preventing pollution, and using renewable energy while not compromising quality and satisfying customers in order to enhance competitive advantage.
This research will address one of the most important cost-effective green technologies, Gr
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Robust controller design requires a proper definition of uncertainty bounds. These uncertainty bounds are commonly selected randomly and conservatively for certain stability, without regard for controller performance. This issue becomes critically important for multivariable systems with high nonlinearities, as in Active Magnetic Bearings (AMB) System. Flexibility and advanced learning abilities of intelligent techniques make them appealing for uncertainty estimation. The aim of this paper is to describe the development of robust H2/H∞ controller for AMB based on intelligent estimation of uncertainty bounds using Adaptive Neuro Fuzzy Inference System (ANFIS). Simulatio
... Show MoreIn light of the developments and intense competition that the world has witnessed, the need to search for a sustainable and continuous competitive advantage for economic units has emerged, as the economic units must not lose sight of their interest in the activities they perform to achieve that advantage, and it can be said that the goal of the research is to identify the theoretical dimensions of the green value chain represented by: (Green research and development, green design, green manufacturing, green marketing, green services) and the dimensions of the sustainable competitive advantage represented by (quality, creativity, innovation, cost, response to the customer), as well as identifyi
... Show MoreThis paper proposes improving the structure of the neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Two learning algorithms are used to adjust the parameters weight of the hybrid neural structure with its serial-parallel configuration; the first one is supervised learning algorithm based Back Propagation Algorithm (BPA) and the second one is an intelligent algorithm n
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