The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Electroencephalographic (EEG) patterns are electrical signals generated in association with neural activities. Most anomalies in brain functioning manifest with their signature characteristics in EEG pattern. Epileptic seizure, which is a brain abnormality well-studied through EEG analysis, is an abnormal harmonious neural activity in the brain characterized by the presence of spikes in EEG. An automated...
Support Vector Machine (SVM) is a popular machine learning technique for classification. SVM is computationally infeasible with large dataset due to its large training time. In this paper we compare three different methods for training time reduction of SVM. Different combination of Decision Tree (DT), Fisher Linear Discriminant (FLD), QR Decomposition (QRD) and Modified Fisher Linear Discriminant...
Sentiment classification of Twitter data has been successfully applied in finding predictions in a variety of domains. However, using sentiment classification to predict stock market variables is still challenging and ongoing research. The main objective of this study is to compare the overall accuracy of two machine learning techniques (logistic regression and neural network) with respect to providing...
Extreme learning machine (ELM) is an efficient learning algorithm which can be easily used with least human intervene. But when ELM is applied as multiclass classifier, the results of some classes are not satisfactory and it's hard to adjust the parameters for these classes without affecting other classes. To overcome these limitations, a novel method is proposed. In proposed approach, binary ELM...
Rainfall prediction is an important part of weather prediction. Compared to conventional methods predicting rainfall rate, the approach applying historical records and data mining technology shows obviously advantage in computing cost. Many excellent works have been done attempting to build predicting model with data mining methods, however, most of them just test the predicting accuracy on data set...
This paper presents a generalized pruning extreme learning machine (GP-ELM) algorithm which can generate a compact single-hidden-layer neural network (SLNN) by automatically pruning the number of hidden nodes iteratively while keep high accuracy. The proposed GP-ELM algorithm initializes a SLNN by using extreme learning algorithm (ELM) algorithm given superfluous number of hidden nodes. The following...
Author attribution has grown into an area that is more challenging from the past decade. It has become an inevitable task in many sectors like forensic analysis, law, journalism and many more as it helps to detect the author in every documentation. Here unigram/bigram features along with latent semantic features from word space were taken and the similarity of a particular document was tested using...
This paper addresses the problem of recognizing handwritten numerals for Gujarati Language. Three methods are presented for feature extraction. One belongs to the spatial domain and other two belongs to the transform domain. In first technique, a new method has been proposed for spatial domain which is based on Freeman chain code. This method obtains the global direction by considering n × n neighbourhood...
Pittsburgh compound B Positron Emission Tomography (PiB PET) imaging is a new technique to detect amyloid-beta (Aβ). Aβ is a pathological bio-data which appears distinctly in most neuro-degeneration diseases, such as Alzheimer's disease (AD). Although PiB PET imaging is relative mature, the accurate diagnosis of AD based on PiB PET images still remains a challenge for radiologists. To solve above...
For the purpose of discovering White Dwarf + Main Sequence (WDMS) from massive spectra, in this paper, an unsupervised learning algorithm for Nonlinear Dimensionality Reduction (NLDR) named Isometric Feature Mapping (Isomap) is discussed. The applicability of Isomap to Sloan Digital Sky Survey Data Release 10 (SDSS-DR10) is confirmed. Furthermore, Particle Swarm Optimization (PSO) is implemented to...
Human Computer Interaction would be much more smooth with the implementation of rapid recognition, the aim of which is to recognize the hand gesture before it is completed. In this paper, a rapid recognition for dynamic hand gestures using leap motion is proposed. The database contains the three-dimensional motion trajectory of the numbers and the alphabet (36 gestures in total) which captured by...
When binary tree SVM is used for multi-class fault diagnosis, inner-class distance or between-class distance is always used to decide the classification hierarchy, but these methods cannot take the comprehensive separability information between classes into account, which leads to decrease the accuracy of fault diagnosis easily, so an improved binary tree SVM method is proposed. Combining the separability...
This paper introduces a novel approach to predict human motion for the Non-binding Lower Extremity Exoskeleton (NBLEX). Most of the exoskeletons must be attached to the pilot, which exists potential security problems. In order to solve these problems, the NBLEX is studied and designed to free pilots from the exoskeletons. Rather than applying Electromyography (EMG) and Ground Reaction Force (GFR)...
System call analysis is a behavioral malware detection technique that is popular due to its promising detection results and ease of implementation. This study describes a system that uses system call analysis to detect malware that evade traditional defenses. The system monitors executing processes to identify compromised hosts in production environments. Experimental results compare the effectiveness...
As the number of cyber attacks have increased, detecting the intrusion in networks become a very tough job. For network intrusion detection system (NIDS), many data mining and machine learning techniques are used. However, for evaluation, most of the researchers used KDD Cup 99 data set, which has widely criticized for not showing current network situation. In this paper we used a new labelled network...
The main objective of this work is to classify Hindi and Telugu stories based on their structure into three genres: Fable, Folk-tale and Legend. In this work, each story is divided into three parts: (i) introduction, (ii) main and (iii) climax. The objective of this work is to explore how story genre information is embedded in different parts of the story. We are proposing a framework for story classification...
Use of modern technological advances in real-time biomedical analysis is very crucial. Current work focuses on glottal pathology discrimination based on non-invasive speech analysis techniques. Primary set back in developing such method is irregular performance depreciation of several state of the art acoustic features. To excuse such problems, we have used glottal to noise excitation ratio, which...
Today people use social media (eg, Twitter) to express their views on different topics. Many political parties have utilized such social media platforms for their election campaigns. Twitter data may provide a lot of information about a users personality. We study how the personality and interest of an individual is linked with his/her political associations. We have used the data set of two political...
In digital retinal images, positive means of texture feature detection around the macula region with specified radius is still an open issue. Diabetic macular edema is a complication caused due to Diabetic Retinopathy (DR) and is the true cause of blindness and visual loss. In this paper, we have presented a computerized method for texture feature extraction around the specified radius taking macula...
Malware analysis on the Android platform has been an important issue as the platform became prevalent. The paper proposes a malware detection approach based on static analysis and machine learning techniques. By conducting SVM training on two different feature sets, malicious-preferred features and normal-preferred features, we built a hybrid-model classifier to improve the detection accuracy. With...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.