In every country in the world, there are a number of amputees who have been exposed to some accidents that led to the loss of their upper limbs. The aim of this study is to suggest a system for real-time classification of five classes of shoulder girdle motions for high-level upper limb amputees using a pattern recognition system. In the suggested system, the wavelet transform was utilized for feature extraction, and the extreme learning machine was used as a classifier. The system was tested on four intact-limbed subjects and one amputee, with eight channels involving five electromyography channels and three-axis accelerometer sensor. The study shows that the suggested pattern recognition system has the ability to classify the shoulder girdle motions for high-level upper limb motions with 88.4% average classification accuracy for four intact-limbed subjects and 92.8% classification accuracy for one amputee by combining electromyography and accelerometer channels. The outcomes of this study may suggest that the proposed pattern recognition system can help to provide control signals to drive a prosthetic arm for high-level upper limb amputees.
The research aims to enhance the level of evaluation of the performance of banking transactions control policies and procedures. The research is based on the following hypothesis: efficient transactions control policies and procedures contribute enhancing financial reporting, by assessing non-application gap of those policies and procedures in a manner that helps to prevent, discover, and correct material misstatements. The researchers designed an examination list that includes the control policies and procedures related to the transactions, as a guide to the bank audit program prepared by the Federal Financial Supervision Bureau. The research methodology is
... Show MoreAccurate emotion categorization is an important and challenging task in computer vision and image processing fields. Facial emotion recognition system implies three important stages: Prep-processing and face area allocation, feature extraction and classification. In this study a new system based on geometric features (distances and angles) set derived from the basic facial components such as eyes, eyebrows and mouth using analytical geometry calculations. For classification stage feed forward neural network classifier is used. For evaluation purpose the Standard database "JAFFE" have been used as test material; it holds face samples for seven basic emotions. The results of conducted tests indicate that the use of suggested distances, angles
... Show MoreThe availability of different processing levels for satellite images makes it important to measure their suitability for classification tasks. This study investigates the impact of the Landsat data processing level on the accuracy of land cover classification using a support vector machine (SVM) classifier. The classification accuracy values of Landsat 8 (LS8) and Landsat 9 (LS9) data at different processing levels vary notably. For LS9, Collection 2 Level 2 (C2L2) achieved the highest accuracy of (86.55%) with the polynomial kernel of the SVM classifier, surpassing the Fast Line-of-Sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) at (85.31%) and Collection 2 Level 1 (C2L1) at (84.93%). The LS8 data exhibits similar behavior. Conv
... Show MoreIn this work, satellite images for Razaza Lake and the surrounding area
district in Karbala province are classified for years 1990,1999 and
2014 using two software programming (MATLAB 7.12 and ERDAS
imagine 2014). Proposed unsupervised and supervised method of
classification using MATLAB software have been used; these are
mean value and Singular Value Decomposition respectively. While
unsupervised (K-Means) and supervised (Maximum likelihood
Classifier) method are utilized using ERDAS imagine, in order to get
most accurate results and then compare these results of each method
and calculate the changes that taken place in years 1999 and 2014;
comparing with 1990. The results from classification indicated that
Nowadays, people's expression on the Internet is no longer limited to text, especially with the rise of the short video boom, leading to the emergence of a large number of modal data such as text, pictures, audio, and video. Compared to single mode data ,the multi-modal data always contains massive information. The mining process of multi-modal information can help computers to better understand human emotional characteristics. However, because the multi-modal data show obvious dynamic time series features, it is necessary to solve the dynamic correlation problem within a single mode and between different modes in the same application scene during the fusion process. To solve this problem, in this paper, a feature extraction framework of
... Show MoreThe rapid sprawl in urban areas caused by excessive production and consumption of goods (as driven by local poor social choices) has inevitably resulted in a major burden due to environmental degradation worldwide. Unfortunately, these traditional models of urban planning fail to properly account for the intricacies that permeate a modern city and are deficient in terms of their approach as they shape themselves within an environment largely divorced from natural systems, resulting in vast mismanagement of resources, guiding cities down trajectories where growth destroys both physical and cultural landscapes. As cities suffer from increasing scarcity, we advocate for regeneration and resilience to be embedded in advanced urban design approa
... Show MoreAt different stages of the evolution of the modern Iraqi state ears last century did not receive the industrial sectors importance in great domestic production (GDP) and that the limited resources available in the initial stage and the dominance of public sector industry in the late stage , so the continued decline in the contribution of the private industrial sector in GDP , and this is why imbalance in the labor market and reduced demand for manpower in this sector despite the high rates of labor supply and the various skills and levels of investments, their human and the different geographical distribution , and direction of labor to other economic sectors most requested of the l
... Show MoreThe objective of the current research is to find an optimum design of hybrid laminated moderate thick composite plates with static constraint. The stacking sequence and ply angle is required for optimization to achieve minimum deflection for hybrid laminated composite plates consist of glass and carbon long fibers reinforcements that impeded in epoxy matrix with known plates dimension and loading. The analysis of plate is by adopting the first-order shear deformation theory and using Navier's solution with Genetic Algorithm to approach the current objective. A program written with MATLAB to find best stacking sequence and ply angles that give minimum deflection, and the results comparing with ANSYS.