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Roller element bearing fault diagnosis is crucial in industry to maintain that the machine is in good condition so that there is no delay of work due to machine breakdown. This paper discusses the use of Extreme Learning Machine (ELM) algorithm to classify bearing faults. The performance of ELM is compared with Back Propagation (BP) algorithm. It was found that the results show that the ELM has smaller...
Every organism emits energy around it which comprises UV-radiation, EM-radiation, infrared and thermal radiation. This energy around human body represents health condition of the subject under study. These energy fields are called as aura of the body under consideration. Several types of equipments are there to capture such energy. Kirlian camera captures the distribution of energy radiation around...
Now a day's recognition of satellite image authenticity has received too much attention due to the invention of various remote sensing image inpainting algorithms. Satellite image forgery can be referred as a technique in which fake satellite image is generated by the creation and alternation of new image contents. This paper proposes an algorithm for the identification of inpainted remote sensing...
This paper introduces to diagnosis of Dyslexia using computing system, considered people difficulties in reading, spelling, writing and speaking. Consequently, a computational analysis classifier will be achieved using dyslexia metrics techniques. Accordingly, Gibson test of brain skills will be used with effect of working memory, auditing (hearing and speech) and visual memory and cognition, visual...
The main objective of the spatial image classification is to extract information classes from a multiband raster spatial image. The network structure and number of inputs are the key factors in deciding the performance and accuracy of the traditional pixel based image classification techniques like Support Vector Machines (SVM), Artificial Neural Networks (ANN), Fuzzy logic, Decision Trees (DT) and...
To date, paper-based examinations are still in use worldwide on all levels of education levels (e.g. secondary, tertiary levels). However, literature regarding off-line automatic assessment systems employing off-line handwriting recognition is not numerous. This paper proposes an off-line automatic assessment system employing a hybrid feature extraction technique - a newly proposed Modified Direction...
We use query-by-example keyword spotting (QbyE-KWS) approach to solve the personalized wake-up word detection problem for small-footprint, low-computational cost on-device applications. QbyE-KWS takes keywords as templates, and matches the templates across an audio stream via DTW to see if the keyword is included. In this paper, we use neural networks as acoustic models to extract DNN/LSTM phoneme...
This paper presents a classification method for multi-class classification of electromyography (EMG) signals from eight hand movements. The data were collected from 15 subjects. The EMG signals were extracted using 16 time-domain feature extraction methods. The 16 features are reduced using principal component analysis (PCA) to enhance the classification accuracy. The features results from PCA are...
Roadside vegetation classification has recently attracted increasing attention, due to its significance in applications such as vegetation growth management and fire hazard identification. Existing studies primarily focus on learning visible feature based classifiers or invisible feature based thresholds, which often suffer from a generalization problem to new data. This paper proposes an approach...
According to skin specialist, skin texture has close relation to an individual's health, hormones, hydration, and allergic symptoms. So by procuring one's image texture sample and exposing it to the imaging device we can identify the skin health. Texture analysis is an important tool to analyze the skin texture. The existing means of skin analysis is applicable only for isotropic images. Isotropic...
Electrocardiogram (ECG) is used as one of the important diagnostic tool for the detection of the health of a heart. Growing number of heart patients has necessitated development of automatic detection techniques for detecting various abnormalities or arrhythmias of the heart to reduce pressure on physicians and share their load. The present work will help in developing a computer based system that...
Cardiotocography (CTG) is a monitoring technique that is used routinely during pregnancy and labor to assess fetal well-being. CTG consists of two signals which are fetal heart rate (FHR) and uterine contraction (UC). Twenty-one features representing the characteristic of FHR have been used in this work. The features are obtained from a large dataset consisting of 2126 records in UCI Machine Learning...
We have conducted a study of detection system for premature ventricular contraction (PVC) developed in an android mobile phone. The system utilizes artificial neural network (ANN) with electrocardiographic (ECG) features of RR interval and QRS width. RR Interval and QRS width is Interval in ECG waveform. The algorithms of the detection are implemented using JAVA Eclipse Juno. The system is examined...
This paper proposes an intellectual classification system to recognize normal and abnormal MRI brain images. Nowadays, decision and treatment of brain tumors is based on symptoms and radiological appearance. Magnetic resonance imaging (MRI) is a most important controlled tool for the anatomical judgment of tumors in brain. In the present investigation, various techniques were used for the classification...
During the last few eras, evolutionary algorithms have been adopted to tackle cyber-terrorism. Among them, genetic algorithms and genetic programming were popular choices. Recently, it has been shown that differential evolution was more successful in solving a wide range of optimization problems. However, a very limited number of research studies have been conducted for intrusion detection using differential...
One of the challenges in precision agriculture is the detection of diseased crops in agricultural environments. This paper presents a methodology to detect the Ceratocystis wilt disease in Eucalyptus crops. An unmanned aerial vehicle is used to obtain high-resolution RGB images of a predefined area. The methodology enables the extraction of visual features from image regions and uses several supervised...
Transformation of the initial feature in NSL-KDD dataset based on principal component analysis (PCA), generates the new features in smaller dimension. In that dimension, network scanning (Ra-Probe) has a characteristic sign of the average value that is different from the normal activity. The selection used the characteristics of these factors result in two-dimensional subset of the 75% rate reduction...
ECG refers to non-invasive bioelectrical recording of the heart. Under the clinical settings, the ECG is interpreted by cardiologists via conventional inspection techniques. The methods however are exposed to visual error which leads to inaccurate diagnosis of the heart condition. Hence, as an attempt towards an automated diagnostic system, the paper elaborates on arrhythmia modelling based on ECG...
Automated signature verification and forgery detection has many applications in the field of Bank-cheque processing, document authentication, ATM access etc. Handwritten signatures have proved to be important in authenticating a person's identity, who is signing the document. In this paper a Fuzzy Logic and Artificial Neural Network Based Off-line Signature Verification and Forgery Detection System...
This paper presents the improvement of vehicle classification in forward scattering radar (FSR) using a new classification technique. The technique is a combination between two methods which are Z-score and neural network (NN). The Zscore is used to extract the features of target signature while neural network is used as a classifier to classify the size of vehicles. The results of vehicle classification...
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