Upper limb amputation is a condition that severely limits the amputee’s movement. Patients who have lost the use of one or more of their upper extremities have difficulty performing activities of daily living. To help improve the control of upper limb prosthesis with pattern recognition, non-invasive approaches (EEG and EMG signals) is proposed in this paper and are integrated with machine learning techniques to recognize the upper-limb motions of subjects. EMG and EEG signals are combined, and five features are utilized to classify seven hand movements such as (wrist flexion (WF), outward part of the wrist (WE), hand open (HO), hand close (HC), pronation (PRO), supination (SUP), and rest (RST)). Experiments demonstrate that using mean absolute value (MAV), waveform length (WL), Wilson Amplitude (WAMP), Sine Slope Changes (SSC), and Cardinality features of the proposed algorithm achieves a classification accuracy of 89.6% when classifying seven distinct types of hand and wrist movement. Index Terms— Human Robot Interaction, Bio-signals Analysis, LDA classifier.
World statistics proved that the most of work dangerous accidents, which causes death, are occurred in the construction works. These accidents related to many causes such as loss of workers experience and ignoring rules of safety requirements, especially young workers. Due to the risk of accidents that may occur in the site of work, the idea of this study crystallized to show the relationship between the age of worker and number of injuries and accidents, to identify the causes of these injuries, and to put the appropriate solutions to avoid or reduce the risk of work injuries. Also, the research shows the main principles of safety requirements to forming a clear picture about the subject of the study. A questioner form was prepared to c
... Show MoreThe chemical additives used to enhance the properties of drilling mud cause damage to humans and the environment. Therefore, it is necessary to search for alternative additives to add them to the drilling mud. Thus, this study investigates the effects of pomegranate peel and grape seed powders as natural waste when added to un-weighted water-based mud. The test includes measurements of the rheological properties and filtration, as well as the alkanity and density of the drilling mud. The results showed a decrease in PH values with an increase in the concentrations of pomegranate peel or grapeseed, and a decrease in mud density with an increase in powders of pomegranate peel and grape seed concentrations that resulted f
... Show MoreThe current study aimed to evaluate the effect of the heavy metals copper, cadmium and cobalt when added individually, in combination and in combination on the growth and reproduction of the aquatic fungus Saprolegnia hypogyna.
The emergence of COVID-19 has resulted in an unprecedented escalation in different aspects of human activities, including medical education. Students and educators across academic institutions have confronted various challenges in following the guidelines of protection against the disease on one hand and accomplishing learning curricula on the other hand. In this short view, we presented our experience in implementing e-learning to the undergraduate nursing students during the present COVID-19 pandemic emphasizing the learning content, barriers, and feedback of students and educators. We hope that this view will trigger the preparedness of nursing faculties in Iraq to deal with this new modality of learning and improve it should t
... Show MoreThe aim of this work is to produce samples from Iraqi raw materials like Husyniat Bauxite (raw and burnt) and to study the effect of some additives like white Doekhla kaolin clays and alumina on that material properties were using sodium silica as a binding material. Five mixtures were prepared from Bauxite (raw and burnt) and kaolin clays, with an additive of (40) ml from sodium silica and alumina of (2.5, 5, 7.5,10 wt %) percentage as a binding material. the size grading was through sieving. The formation of all specimens was conducted by a measured gradually semi-dry pressing method under a compression force of (10) Tons and humidity ratio ranging from (5-10) % from mixture weight. Drying all specimens was done and then they were burn
... Show MoreThe study area is witnessing divergence where I am North wind North East wind as we find that the north wind is getting replicated as we move from the south, The reason can be attributed to the nature of the surface of the region, with at least repeat this wind the northern region to the presence of mountain ranges, while we find that energizes the surface in the center and south helped to increase repeat this wind gusts, It also finds that the North wind East prevail in the northern region and least replicated as we move from the north to the south and to the fact that North stations are within blowing this wind sites for the circles near the display of high pressure located centers to the north-east, north and distancing itself from pa
... Show MoreThis experiment was conducted in the season 2001-2000 in station Ishaqi the company's general industrial crops to plant livestock Vigna radala deleted (Khadrawi) carried out the experiment design panels splinter and order in RCBD with three balls two factors are levels nitrogen fertilizer (120 and, 100.0 kg urea / ha)nitrogen ratio of 46%, which put in the main panels mAIN PLOT and Alkiavat three levels that were placed in secondary panels .....
Prediction of daily rainfall is important for flood forecasting, reservoir operation, and many other hydrological applications. The artificial intelligence (AI) algorithm is generally used for stochastic forecasting rainfall which is not capable to simulate unseen extreme rainfall events which become common due to climate change. A new model is developed in this study for prediction of daily rainfall for different lead times based on sea level pressure (SLP) which is physically related to rainfall on land and thus able to predict unseen rainfall events. Daily rainfall of east coast of Peninsular Malaysia (PM) was predicted using SLP data over the climate domain. Five advanced AI algorithms such as extreme learning machine (ELM), Bay
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