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This paper aims at the classification of hand gestures using electromyographic signals (EMG) obtained through a MyoTM armband, which has eight medical grade electrodes. Each electrode provides information regarding muscles contraction performed during the execution of the movement. From these electrodes signals are extracted seven features for each one of eight electrodes. After extraction of the...
Heart disease is a deadly disease that large population of people around the world suffers from. When considering death rates and large number of people who suffers from heart disease, it is revealed how important early diagnosis of heart disease. Traditional way of diagnosis is not sufficient for such an illness. Developing a medical diagnosis system based on machine learning for prediction of heart...
Analysis of electromyography (EMG) signals of normal physical actions have found to be important in order to detect certain abnormalities of the musculoskeletal system and diagnose abnormalities in patient behavior. This paper presents the results of the development of an Artificial Neural Network (ANN) for classification of EMG signals, according to the type of human behavior. The developed ANN is...
How to develop an intelligent ventilator and control it well to provide a better experience and treatment effect for respiratory patients is still a difficult task needed to be solved. The existing problems focus on the control algorithm and the mechanical structure. Dedicated to these two problems, the paper proposes a design of CPAP ventilator based on the ANN algorithm. Firstly, the paper introduces...
Security of today communication networks depends also on effective hash function. A cryptographic hash function is used to realize a transformation of input to a fixed-size value. This value is called the hash value. One way hash function could be generated also by an artificial neural network (ANN). Theoretical analysis of the possibility of using artificial neural network and chaotic maps for hashing...
The paper considers the results of MATLAB modeling of artificial neural networks trained to perform basic logical operations: AND, OR, XOR and NOT. Below is a description of implementation of these artificial neural networks on a microcontroller by Texas Instruments family MSP430G2x, which is marketed by the manufacturer as an ultra-low power consumption device. Implementation of artificial neural...
Hausa sign language (HSL) is the main communication medium among deaf-mute Hausas in northern Nigeria. HSL is so unique that a deaf-mute individual from other part of the country can rarely understand it. HSL includes static and dynamic hand gesture recognitions. In this paper we present an intelligent recognition of static, manual and nonmanual HSL using an enhanced Fourier descriptor. A Red Green...
Artificial neural networks (ANN) is increasingly being used to solve engineering problems. Successful welding operations are at the top of engineering problems. The friction stir welding method, which is used to combine the materials under the melting temperature, is also a method that can be analyzed with ANN. In this study, Al-7075 workpieces (with and without aging treatment) were joined by the...
This paper presents a series of experiments on the classification of emergency phone conversation records using artificial neural networks (ANNs). Input data which were processed by ANNs were the features of callers and events taken from emergency phone calls. The authors analyzed four variants of classification: the groups of callers which have specified features, the groups of events which have...
Pregnancy is an important moment of growth of the human being. In many case women do not know that she is being pregnant, this is one of the causes of miscarriage. For healthy pregnancy also need to be guarded by knowing abnormalities early in pregnancy. There are several early pregnancy disorder among others hyperemesis gravidarum, pre-eclampsia and eclampsia, hydatidiform mole, and ectopic pregnancy...
This paper presents harmonic current estimation using neural network for a power electronic converter. Three types of popular neural architectures namely single hidden layered Feedforward architecture, multi hidden layered Feedforward neural architecture, cascade architecture are considered for investigation. The non-linear load namely diode bridge uncontrolled rectifier with resistive inductive (RL)...
In recent years, the strong growth in solar power generation industries is requiring an increasing need to predict the profile of solar power production over the day, in order to develop high efficient and optimized stand-alone and grid connected photovoltaic systems. Moreover, the opportunities offered by battery energy storage systems coupled with PV systems, require the load power to be forecasted...
In this paper, the artificial neural network (ANN) method is proposed in magnetic optic image (MOI) test. In the MOI test, it uses the rotation polarized light to detect the magnetic field which is induced by the crack. In the specimen, the magnetic field distribution depends on the shape of the crack. In the detection, the influences of the magnetic domain spots make it difficult to identify the...
The main aim of this paper is to implement a Artificial Neural Network to recognize and predict Handwritten digits from 0 to 9. A dataset comprises 5000 samples of number digits with different strokes are taken for our work. The dataset was trained using gradient descent Back-propagation algorithm and further tested using the Feed-forward algorithm. The system performance is observed by varying regularization...
Breathing is one of the human physiological activities that catch the interest of researchers especially in the area of medical diagnosis and human physiological performance. Apart from conventional measurement using intake or outflow of air, breathing characteristics could also be assessed through human respiratory muscles with the analysis on Electromyography (EMG) signal. In this paper, EMG signal...
This paper makes an attempt to predict the movement of the stock price for the following day using Artificial Neural Network (ANN). For the purpose of this research, two companies from each industry have been chosen that is, TATA Motors and Honda Motors from the Automobile industry and Cadila Pharmaceuticals Ltd. and Glenmark Pharmaceuticals from the Pharmaceutical industry. The historical prices...
The breast cancer is one of the most popular cause of death among women. It is also one of the diseases that can be cured and has high healing chances when it is detected in the early stages [1]. Detecting the cancer and differentiating between the diagnosis that affirm whether a patient has breast cancer or not has been considered as a big challenge. In order to have an accurate diagnosis, Support...
This paper proposes a classification algorithm based on ensemble neural networks. In the training phase, the proposed algorithm uses a random number of training data to develop multiple random artificial neural network (ANN) models until those ANN models converge. Those models with lower accuracy than the threshold are filtered out. The remaining highly accurate models will be used to predict the...
Artificial Neural networks (ANN) are used to solve various problems which are difficult to be solved by traditional linear methods or even not solved. In practice, ANN are used in two ways — as software running on conventional computer and as a specialized hardware and software systems. For the control system the signal processing is required to be performed in real time and that can be achieved only...
We modeled in this paper the variation of wind speed as a renewable energy in Mediterranean Sea of Libya (North of Africa) using an artificial neural network (ANN). We developed multi-layer, feed-forward, back-propagation artificial neural networks for prediction monthly mean wind speed. The monthly mean wind speed data of 25 cities in Libya were monitored during the period of six years from 2010...
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