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In this paper, we try to make an author identification of two ancient Arabic religious books dating from the 6th century: The holy Quran and the Hadith. The authorship identification process is achieved through four phases which are: documents collection, text preprocessing, features extraction and classification model building. Thus, two series of experiments are undergone and commented. The first...
Massive proliferation of social media has opened possibilities for perpetrator to conduct the crime of online child grooming. Because the pervasiveness of the problem scale, it may only be tamed effectively and efficiently by using an automatic grooming conversation detection system. Previously, Pranoto, Gunawan, and Soewito [1] had developed a logistic model for the purpose and the model was able...
Crackles, which are a kind of abnormal lung sounds, are used as indicators for the diagnosis of pulmonary diseases. In this paper, an automatic and noninvasive method is presented for crackles detecting. This method mainly comprises three steps: preprocessing, features extracting and crackles detecting based on support vector machines(SVM). The features are fmin/fmax of the frequency limbic signal,...
Feature extraction addresses the problem of finding the most compact and informative set of features. To maximize the effectiveness of each single feature extraction algorithm and to develop an efficient intrusion detection system, an ensemble of Linear Discriminant Analysis and Principle Component Analysis feature extraction algorithms is implemented. The experiments demonstrate that the ensemble...
Blind steganalysis is a method used to detect whether there is a hidden message in a media without having to know the steganography algorithm behind it. Digital image is converted into features using feature extraction algorithm subtractive pixel adjacency matrix. A model is built based on the resulting features using machine learning method support vector machine. The support vector machine method...
This paper presents a robust machine learning based computational solution for human detection. The proposed mechanism is specifically applicable for pose-variant situations in video frames. In order to address the pose variance problem, features are extracted using an improved variant of Histograms of Gradients (HoG) and local Binary Pattern features (LBP). The two feature sets are combined to form...
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 study in this paper an authorship attribution in Arabic poetry using text mining classification. Several features such as Characters, Poetry Sentence length; Word length, Rhyme, Meter and First word in the sentence are used as input data for text mining classification algorithms Naïve Bayes NB, Support Vector Machine SVM, and Sequential Minimal Optimization SMO. The data set of experiment was divided...
This paper presents novel architectures for machine learning based classifiers using stochastic logic. Two types of classifier architectures are presented. These include: linear support vector machine (SVM) and artificial neural network (ANN). Stochastic computing systems require fewer logic gates and are inherently fault-tolerant. Thus, these structures are well suited for nanoscale CMOS technologies...
Speaker recognition systems based on spectral features perform well in acoustically matched and noise-free conditions. Spectral features are unsuccessful to model information about the speaker at higher levels. Prosody which represents intonation, rhythm and stress of speech, better represents speaker characteristics at higher levels. Voice disguise is a common threat to automatic speaker identification...
Feature extraction addresses the problem of finding the most compact and informative set of features. To maximize the effectiveness of each single feature extraction algorithm and to develop an efficient intrusion detection system, an ensemble of Linear Discriminant Analysis (LDA) and Principle Component Analysis (PCA) feature extraction algorithms is implemented. This ensemble PCA-LDA method has...
Signal peptides are significant important in targeting the translocation of integral membrane proteins and secretory proteins. Due the high similarity between the transmembrane helices and signal peptides, classifiers have limit ability to discriminate the signal peptides from the transmembrane helices. To solve this problem, the protein functional domain information is applied in this method. For...
Bag-of-visual-word (BOW) model for object recognition has attracted much attention in recent years. The ambiguity of visual words is a key issue to limit its performance. This paper presents an effective BOW scheme by introducing spatial weights, which is dependent on the saliency map. Different from conventional visual attention regions based on segmentation, this saliency map is obtained from selected...
This paper investigates detection of patterns in brain waves while induced with mental stress. Electroencephalogram (EEG) is the most commonly used brain signal acquisition method as it is simple, economical and portable. An automatic EEG based stress recognition system is designed and implemented in this study with two effective stressors to induce different levels of mental stress. The Stroop colour-word...
This paper proposes an off-line automatic assessment system utilising novel combined feature extraction techniques. The proposed feature extraction techniques are 1) the proposed Water Reservoir, Loop, Modified Direction and Gaussian Grid Feature (WRL_MDGGF), 2) the proposed Gravity, Water Reservoir, Loop, Modified Direction and Gaussian Grid Feature (G_WRL_MDGGF). The proposed feature extraction...
We propose a Convolutional Neural Network model to learn spatial footstep features end-to-end from a floor sensor system for biometric applications. Our model's generalization performance is assessed by independent validation and evaluation datasets from the largest footstep database to date, containing nearly 20,000 footstep signals from 127 users. We report footstep recognition performance as Equal...
Face spoofing can be performed in a variety of ways such as replay attack, print attack, and mask attack to deceive an automated recognition algorithm. To mitigate the effect of spoofing attempts, face anti-spoofing approaches aim to distinguish between genuine samples and spoofed samples. The focus of this paper is to detect spoofing attempts via Haralick texture features. The proposed algorithm...
Diabetes, referred to as diabetes mellitus, describes a group of metabolic diseases in which the person has high blood glucose. Possible complications that can be caused by badly controlled diabetes: Eye complications, Foot complication, Skin complications, Heart problems, Hypertension, etc. Diabetic retinopathy (DR), a common complication of diabetes, affects the blood vessels in the retina. It is...
Recently electrocorticography (ECoG) has emerged as a potential tool for Brain Computer Interfacing applications. In this paper, a continuous wavelet transform (CWT) based method is proposed for classifying ECoG motor imagery signals corresponding to left pinky and tongue movement. The total experiment is carried out with the publicly available benchmark BCI competition III, data set I. The L2 norms...
Human iris can be used for detecting organ disorders based on iridology science. Nowadays, iridology diagnosis can be done automatically by computer using artificial intelligence approach. This research focused on cardiac diagnosis based on left iris map on clockwise direction around 2:00 to 3:00. The Principal Component Analysis (PCA) is used for feature extraction while the Support Vector Machine...
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