The administration on the basis of the activities designed to evaluate the performance of activities in terms of cost, time and quality by identifying activities that add value and those that are no add value and  enables the administration of making up their own continuous improvement in production, through lower costs and reduce the time and improve the quality   and reduce the incidence of spoilage and waste, y based search Ally premise that (the continuous improvement of the adoption of management style on the basis of the activities helps management in decision-making wise to reduce  costs) to prove the hypothesis has sought research to achieve its goal of  Alkadivh and Alkoppelan     &nb

 In this work the design and application of a fuzzy logic controller to DC-servomotor is investigated. The proposed strategy is intended to improve the performance of the original control system by use of a fuzzy logic controller (FLC) as the motor load changes. Computer simulation demonstrates that FLC is effective in position control of a DC-servomotor comparing with conventional one.

This paper addresses the use of adaptive sliding mode control for the servo actuator system with friction. The adaptive sliding mode control has several advantages over traditional sliding mode control method. Firstly, the magnitude of control effort is reduced to the minimal admissible level defined by the conditions for the sliding mode to exist. Secondly, the upper bounds of uncertainties are not required to be known in advance. Therefore, adaptive sliding mode control method can be effectively implemented. The numerical simulation via MATLAB 2014a for servo actuator system with friction is investigated to confirm the effectiveness of the proposed robust adaptive sliding mode control scheme. The results clarify, after

<p>The directing of a wheeled robot in an unknown moving environment with physical barriers is a difficult proposition. In particular, having an optimal or near-optimal path that avoids obstacles is a major challenge. In this paper, a modified neuro-controller mechanism is proposed for controlling the movement of an indoor mobile robot. The proposed mechanism is based on the design of a modified Elman neural network (MENN) with an effective element aware gate (MEEG) as the neuro-controller. This controller is updated to overcome the rigid and dynamic barriers in the indoor area. The proposed controller is implemented with a mobile robot known as Khepera IV in a practical manner. The practical results demonstrate that the propo

Abstract:

               Today, the financial and banking sector is witnessing a qualitative shift thanks to financial technology services, which provide their services to many individuals and companies in quick, easy and less expensive ways compared to traditional means. Financial technology is a new form of financial science that combines financial transactions and technological skills concerned with providing financial services and improving the work environment within Banking institutions, and financial technology provides many advantages such as lower transaction costs, instant payment, and saving more time and effort in conducting banking

Impact Resistance training with and against the trajectory of the motor in some physical abilities and the BioA 100-meter, mechanical racing run for young people. That Training Jogging for different distances Melt -Rubber ropes According to direction and reversed movement With Obligations To the border of scientific of components Pregnancy Training represents to a training trend Aimed To Events Developments In The link between Starting and running, According to the specific mechanical requirements Have It Of Development of force Explosive and quick and their components which To give Border To the level Special speed for Stages Sprint run 100 m and amounts Efforts Required instantaneous powers. Noted Researcher In That Over there Repeat For

The use of real-time machine learning to optimize passport control procedures at airports can greatly improve both the efficiency and security of the processes. To automate and optimize these procedures, AI algorithms such as character recognition, facial recognition, predictive algorithms and automatic data processing can be implemented. The proposed method is to use the R-CNN object detection model to detect passport objects in real-time images collected by passport control cameras. This paper describes the step-by-step process of the proposed approach, which includes pre-processing, training and testing the R-CNN model, integrating it into the passport control system, and evaluating its accuracy and speed for efficient passenger flow

Modeling data acquisition systems (DASs) can support the vehicle industry in the development and design of sophisticated driver assistance systems. Modeling DASs on the basis of multiple criteria is considered as a multicriteria decision-making (MCDM) problem. Although literature reviews have provided models for DASs, the issue of imprecise, unclear, and ambiguous information remains unresolved. Compared with existing MCDM methods, the robustness of the fuzzy decision by opinion score method II (FDOSM II) and fuzzy weighted with zero inconsistency II (FWZIC II) is demonstrated for modeling the DASs. However, these methods are implemented in an intuitionistic fuzzy set environment that restricts the ability of experts to provide mem