The aim of human lower limb rehabilitation robot is to regain the ability of motion and to strengthen the weak muscles. This paper proposes the design of a force-position control for a four Degree Of Freedom (4-DOF) lower limb wearable rehabilitation robot. This robot consists of a hip, knee and ankle joints to enable the patient for motion and turn in both directions. The joints are actuated by Pneumatic Muscles Actuators (PMAs). The PMAs have very great potential in medical applications because the similarity to biological muscles. Force-Position control incorporating a Takagi-Sugeno-Kang- three- Proportional-Derivative like Fuzzy Logic (TSK-3-PD) Controllers for position control and three-Proportional (3-P) controllers for force control. They are designed and simulated to improve the desired joints position specifications such as minimum overshoot, minimum oscillation, minimum steady state error, and disturbance rejection during tracking the desired position medical trajectory. Ant Colony Optimization (ACO) is used to tune the gains of position and force parts of the Force-Position controllers to get the desired position trajectory according to the required specification. A comparison between the force-position controllers tuned manually and tuned by ACO shows an enhancement in the results of the second type as compared with the first one with an average of 39%.
In this paper we proposes the philosophy of the Darwinian selection as synthesis method called Genetic algorithm ( GA ), and include new merit function with simple form then its uses in other works for designing one of the kinds of multilayer optical filters called high reflection mirror. Here we intend to investigate solutions for many practical problems. This work appears designed high reflection mirror that have good performance with reduction the number of layers, which can enable one to controlling the errors effect of the thickness layers on the final product, where in this work we can yield such a solution in a very shorter time by controlling the length of the chromosome and optimal genetic operators . Res
... Show MoreWireless Body Area Network (WBAN) is a tool that improves real-time patient health observation in hospitals, asylums, especially at home. WBAN has grown popularity in recent years due to its critical role and vast range of medical applications. Due to the sensitive nature of the patient information being transmitted through the WBAN network, security is of paramount importance. To guarantee the safe movement of data between sensor nodes and various WBAN networks, a high level of security is required in a WBAN network. This research introduces a novel technique named Integrated Grasshopper Optimization Algorithm with Artificial Neural Network (IGO-ANN) for distinguishing between trusted nodes in WBAN networks by means of a classifica
... Show MoreThe study intends to explore the obstacles that encounter a program of rehabilitating released prisoners as perceived by prisoners themselves in tubas' province. To this end, the researcher used a questionnaire as an instrument which was applied on (150) prisoner had chosen randomly to collect the study data. The findings revealed no significant differences among obstacles the encounter program regarding to the following variables: age, detention period, and number of detention, additionally, the findings found that there is a variance of obstacles mean according to the prisoners themselves, rehabilitation program, and the facility of that program.
Objectives: to assess nurses' knowledge toward infection control measures for hepatitis a virus in hemodialysis
units and to detemine the relationship between nurses' knowledge and their demographical characteristics.
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A non-probability `tturposive" sample of (51) nurses, who were working in hemodialysis units were selected
from Baghdad teaching hosphals. The data were collected through the use of constructed questionnaire, which
consists of two parts (I) Demographic data fom that consists of 10 items and (2) Nurses' knowledge form that
consists of 6 sections contain 79 items, by means of direct interview techniq
The evolution in the field of Artificial Intelligent (AI) with its training algorithms make AI very important in different aspect of the life. The prediction problem of behavior of dynamical control system is one of the most important issue that the AI can be employed to solve it. In this paper, a Convolutional Multi-Spike Neural Network (CMSNN) is proposed as smart system to predict the response of nonlinear dynamical systems. The proposed structure mixed the advantages of Convolutional Neural Network (CNN) with Multi -Spike Neural Network (MSNN) to generate the smart structure. The CMSNN has the capability of training weights based on a proposed training algorithm. The simulation results demonstrated that the proposed
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