In this study, a traumatic spinal cord injury (TSCI) classification system is proposed using a convolutional neural network (CNN) technique with automatically learned features from electromyography (EMG) signals for a non-human primate (NHP) model. A comparison between the proposed classification system and a classical classification method (k-nearest neighbors, kNN) is also presented. Developing such an NHP model with a suitable assessment tool (i.e., classifier) is a crucial step in detecting the effect of TSCI using EMG, which is expected to be essential in the evaluation of the efficacy of new TSCI treatments. Intramuscular EMG data were collected from an agonist/antagonist tail muscle pair for the pre- and post-spinal cord lesi

 The aim of this paper, is to discuss several high performance training algorithms fall into two main categories. The first category uses heuristic techniques, which were developed from an analysis of the performance of the standard gradient descent algorithm. The second category of fast algorithms uses standard numerical optimization techniques such as: quasi-Newton . Other aim is to solve the drawbacks related with these training algorithms and propose an efficient training algorithm for FFNN

     Doubts arise about the originality of a document when noticing a change in its writing style. This evidence to plagiarism has made the intrinsic approach for detecting plagiarism uncover the plagiarized passages through the analysis of the writing style for the suspicious document where a reference corpus to compare with is absent.      The proposed work aims at discovering the deviations in document writing style through applying several steps: Firstly, the entire document is segmented into disjointed segments wherein each corresponds to a paragraph in the original document. For the entire document and for each segment, center vectors comprising average  weight of their word  are constructed. Second, the degree of cl

<span lang="EN-US">In the last years, the self-balancing platform has become one of the most common candidates to use in many applications such as flight, biomedical fields, and industry. In this paper, the physical prototype of a proposed self-balancing platform that described the self-balancing attitude in the (X-axis, Y-axis, or biaxial) under the influence of road disturbance has been introduced. In the physical prototype, the inertial measurement unit (IMU) sensor will sense the disturbance in (X-axis, Y-axis, and biaxial). With the determined error, the corresponding electronic circuit, DC servo motors, and the Arduino software, the platform overcame the tilt angle(disturbance). Optimization of the proportional-integral-

Authentication is the process of determining whether someone or something is, in fact, who or what it is declared to be. As the dependence upon computers and computer networks grows, the need for user authentication has increased. User’s claimed identity can be verified by one of several methods. One of the most popular of these methods is represented by (something user know), such as password or Personal Identification Number (PIN). Biometrics is the science and technology of authentication by identifying the living individual’s physiological or behavioral attributes. Keystroke authentication is a new behavioral access control system to identify legitimate users via their typing behavior. The objective of this paper is to provide user

Recent years have seen an explosion in graph data from a variety of scientific, social and technological fields. From these fields, emotion recognition is an interesting research area because it finds many applications in real life such as in effective social robotics to increase the interactivity of the robot with human, driver safety during driving, pain monitoring during surgery etc. A novel facial emotion recognition based on graph mining has been proposed in this paper to make a paradigm shift in the way of representing the face region, where the face region is represented as a graph of nodes and edges and the gSpan frequent sub-graphs mining algorithm is used to find the frequent sub-structures in the graph database of each emotion. T

The proper operation, and control of wastewater treatment plants, is receiving an increasing attention, because of the rising concern about environmental issues. In this research a mathematical model was developed to predict biochemical oxygen demand in the waste water discharged from Abu-Ghraib diary factory in Baghdad using Artificial Neural Network (ANN).In this study the best selection of the input data were selected from the recorded parameters of the wastewater from the factory. The ANN model developed was built up with the following parameters: Chemical oxygen demand, Dissolved oxygen, pH, Total dissolved solids, Total suspended solids, Sulphate, Phosphate, Chloride and Influent flow rate. The results indicated that the constructed A