The grasping stability of robotic manipulators is crucial to enable autonomous manipulation in an environment where robots are facing obstacles in their route, where abrupt changes in the robot’s speed are induced. These speed variations will produce forces affecting the robotic manipulator, hence its grasping stability. In this research, the grasping stability of a robotic manipulator that functions according to a frictional self-locking mechanism is investigated statically and dynamically. Both theoretical and experimental results showed that the grasped object size, weight, and its orientation inside the gripper have a great effect on grasping stability. Both the theoretical and experimental results indicated that the grasping object parameters (diameter 25.5 mm–72 mm, weight 25 N–40 N) as well as its orientation inside the gripper influence the grasping stability. The configuration achieved which loaded 40 N, grasped an object of diameter 25.5 mm, and used an initial torque of 0.5N-m with rubber tube material showed optimal grasping stability of 98%. The dynamic test revealed that pulse disturbances (5 mm amplitude, 1.0 s duration) were stable without exceeding two degrees of vertical angular deviation.
In this paper, the human robotic leg which can be represented mathematically by single input-single output (SISO) nonlinear differential model with one degree of freedom, is analyzed and then a simple hybrid neural fuzzy controller is designed to improve the performance of this human robotic leg model. This controller consists from SISO fuzzy proportional derivative (FPD) controller with nine rules summing with single node neural integral derivative (NID) controller with nonlinear function. The Matlab simulation results for nonlinear robotic leg model with the suggested controller showed that the efficiency of this controller when compared with the results of the leg model that is controlled by PI+2D, PD+NID, and F
... Show MoreThe regressor-based adaptive control is useful for controlling robotic systems with uncertain parameters but with known structure of robot dynamics. Unmodeled dynamics could lead to instability problems unless modification of control law is used. In addition, exact calculation of regressor for robots with more than 6 degrees of freedom is hard to be calculated, and the task could be more complex for robots. Whereas the adaptive approximation control is a powerful tool for controlling robotic systems with unmodeled dynamics. The local (partitioned) approximation-based adaptive control includes representation of the uncertain matrices and vectors in the robot model as finite combinations of basis functions. Update laws for the weighting matri
... Show MoreIt is well known that the spread of cancer or tumor growth increases in polluted environments. In this paper, the dynamic behavior of the cancer model in the polluted environment is studied taking into consideration the delay in clearance of the environment from their contamination. The set of differential equations that simulates this epidemic model is formulated. The existence, uniqueness, and the bound of the solution are discussed. The local and global stability conditions of disease-free and endemic equilibrium points are investigated. The occurrence of the Hopf bifurcation around the endemic equilibrium point is proved. The stability and direction of the periodic dynamics are studied. Finally, the paper is ended with a numerical simul
... Show MoreIt is proposed and studied a prey-predator system with a Holling type II functional response that merges predation fear with a predator-dependent prey's refuge. Understanding the impact of fear and refuge on the system's dynamic behavior is one of the objectives. All conceivable steady-states are investigated for their stability. The persistence condition of the system has been established. Local bifurcation analysis is performed in the Sotomayor sense. Extensive numerical simulation with varied parameters was used to explore the system's global dynamics. A limit cycle and a point attractor are the two types of attractors in the system. It's also interesting to note that the system exhibits bi-stability between these 2 types of attractors.
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The research aims to examine the relationship between psychological flow, psychological well-being, and self-management among a sample of fine artists in the Makkah region and its governorates. The research also aims to examine the mean group differences in psychological flow, psychological well-being, and self-management due to demographic variables (sex and years of practicing arts). The sample consists of (110) male and female fine artists. The descriptive correlational approach was performed to collect the data by using the psychological flow scale developed by Payne et al (2011), which was translated by the researcher, the Oxford happiness questionnaire developed by Hills and Argyle (2002), it has t
... Show MoreThe study is carried out by using personal dosimeters (film badge). The films are irradiated to absorbed dose of range (0.01-10000 rad). The calibration curves are drawn by using the ordinary method taking into account the filtration effects in three regions (D (Pb/Sn),D(Du),D(300). The calibration films are stored in ambient condition. It is found that the optical density increases, which is attributed to the photodegradation of the films may induce localized states in the energy gap causing increasing in optical absorption, but optical density decreases, which attributed to the photodegradation of the films may cause some cracks at the film surface during the first month, whereas at the rest months we see clear stability in optical d
... Show MoreEarly and accurate detection of COVID-19 from chest computed tomography (CT) scans are becoming essential for effective clinical decision-making and disease control. This study is proposing a robust deep learning framework that integrates a convolutional self-attention network (CSAN), gamma correction for image enhancement, and a voting-based ensemble classifier to improving diagnostic performance. The model is being evaluated on a dataset of 2,271 CT images and is achieving an accuracy of 95.12%, sensitivity of 97.25%, specificity of 98.11%, F1-score of 96.46%, and area under the curve (AUC) of 0.977. Experimental results are demonstrating that the proposed method significantly surpasses baseline models, including standalone CSAN,
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The current study aims to identify the predictability of burnout in perceived self-competence among mothers of students with disabilities in the Sultanate of Oman. The study sample consists of (484) respondents who were mothers of students with disabilities. The researcher developed a burnout Scale which consists of (19) items and a perceived self-competence Scale which consists of (20) items. A correlation descriptive design was used. The results showed that the level of burnout was low (Mean= 2.30), while the level of burnout was high (Mean= 3.87). Regarding the correlation coefficient, the results showed that there was a significant negative correlation between burnout and perceived self-competence. A
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