Amputation of the upper limb significantly hinders the ability of patients to perform activities of daily living. To address this challenge, this paper introduces a novel approach that combines non-invasive methods, specifically Electroencephalography (EEG) and Electromyography (EMG) signals, with advanced machine learning techniques to recognize upper limb movements. The objective is to improve the control and functionality of prosthetic upper limbs through effective pattern recognition. The proposed methodology involves the fusion of EMG and EEG signals, which are processed using time-frequency domain feature extraction techniques. This enables the classification of seven distinct hand and wrist movements. The experiments conducted in this study utilized the Binary Grey Wolf Optimization (BGWO) algorithm to select optimal features for the proposed classification model. The results demonstrate promising outcomes, with an average classification accuracy of 93.6% for three amputees and five individuals with intact limbs. The accuracy achieved in classifying the seven types of hand and wrist movements further validates the effectiveness of the proposed approach. By offering a non-invasive and reliable means of recognizing upper limb movements, this research represents a significant step forward in biotechnical engineering for upper limb amputees. The findings hold considerable potential for enhancing the control and usability of prosthetic devices, ultimately contributing to the overall quality of life for individuals with upper limb amputations.
Cost is the essence of any production process for it is one of the requirements for the continuity of activities so as to increase the profitability of the economic unit and to support the competitive situation in the market. Therefore, there should be an overall control to reduce the cost without compromising the product quality; to achieve this, the management should have detailed credible and reliable information about the cost to be measured, collected, understood and to analyze the causes for the spread of deviations and obstacles the management faces, and to search for the factors that trigger the emergence of these deviations and obstacles
This mixed method research analyses urban heritage and identity management concerning Karbala, and important spiritual and historical center. Homing in on particular spatial issues germane to Muharram’s rites, this study explores spiritual activities for the remembrance of the martyrdoms of Imam Hussein (A) and his brother Abbas (A), and their followers (RA), and identifies the way in which such activities construct urban identity in Karbala. Furthermore, this study contemplates the deployment of contemporary AR and VR technologies for urban identity. After reviewing extensive studies on religious, cultural, and urban heritage, a field survey of the Muharram pilgrimage in Karbala was conducted, spatially analyzing pilgrims’ movements in
... Show MoreIn this study, active knife and fixed knife of single-row disc silage machine has three different clearance C1, C2 and C3 (1, 3 and 5 mm) and it is tried in three different working speed V1, V2 and V3 (1.8, 2.5 and 3.7 km / h) and PTO speed (540 min-1) and machine's fuel consumption (l/h), average power consumption (kW), field energy consumption (kW/da), product energy consumption (kW/t), field working capacity (da/h), product working capacity (t/h) and Chopping size distribution characteristics of the fragmented material were determined. It has been found that knife-counter knife clearances smaller than 3 mm (1 mm) and larger (5 mm) have a negative effect on machine performance in general. In terms of fuel and power consumptions, the m
... Show MoreClean energy applications widely recognize Proton Exchange Membrane Fuel Cells (PEMFCs) for their high efficiency and environmental compatibility. Accurate parameter identification of PEMFC models is essential for enhancing system performance and reliability, particularly under dynamic operating conditions. This paper presents a novel optimization-based approach called Heterogeneous Comprehensive Learning-Bald Eagle Search (HCLBES) with enhanced exploration and exploitation capabilities for the effective modeling of PEMFC. The algorithm combines the exploration strength of the Bald Eagle Search with comprehensive learning and heterogeneity mechanisms to achieve a balanced global and local search space. In this algorithm, the number
... Show MoreBP algorithm is the most widely used supervised training algorithms for multi-layered feedforward neural net works. However, BP takes long time to converge and quite sensitive to the initial weights of a network. In this paper, a modified cuckoo search algorithm is used to get the optimal set of initial weights that will be used by BP algorithm. And changing the value of BP learning rate to improve the error convergence. The performance of the proposed hybrid algorithm is compared with the stan dard BP using simple data sets. The simulation result show that the proposed algorithm has improved the BP training in terms of quick convergence of the solution depending on the slope of the error graph.
The business environment is witnessing tremendous developments in the field of production and technology, which requires the development of production methods to go in line with these developments and the increasing competition, which has gone beyond the economic aspects to extend to the environmental aspects, as economic units tended to adopt a cleaner production strategy and through what they achieve by producing environmentally friendly products and achieving economic efficiency. Reducing costs, providing a safe and clean environment for workers, and reducing waste from production operations.
Objective: To determine the effectiveness of an Educational Program in Enhancing Nurse’s Knowledge about Occupational Health Hazards at Medical City Hospitals in Baghdad City.
Methodology: The present study employed a quasi-experimental design held at Medical City Hospitals in Baghdad City. A non-probability sample (convenience sample) consisted of (60) nurse. Data were collected by using a self-report questionnaire which consisted of six parts (a) socio-demographic characteristics (b) physical hazards knowledge (c) chemical hazards knowledge (d) biological hazards knowledge (e) psychological hazards knowledge and (f) mechanical hazards knowledge. Data were analyzed using the statistical packag
... Show MoreMoisture-induced damage is one of the primary causes of premature distress in asphalt pavements, leading to reduced service life and increased maintenance costs. Although nanomaterials have shown potential in enhancing asphalt performance, the underlying composite interaction mechanisms among nanomaterials, asphalt binder, and aggregate phases under moisture exposure are still not fully understood. In addition, comparative evaluations under consistent experimental conditions remain limited. This study investigates the influence of five nanomaterials: nano-silica (NS), nano-alumina (NA), nano-titanium dioxide (NT), nano-zinc oxide (NZ), and carbon nanotubes (CNT) on the physical and mechanical properties of asphalt binders and mixtur
... Show MoreB Saleem, H Alwan, L Khalid, Journal of Engineering, 2011 - Cited by 2