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.
In this study, we apply machine learning algorithms to predict technical failures that can be encountered in Oracle databases and related services. In order to train machine learning algorithms, data from log files are collected hourly from Oracle database systems and labeled with two classes; normal or abnormal. We use several data science approaches to preprocess and transform the input data from...
Positioning applications become more popular with the advancement of location aware services. Global Positioning System is a successful solution for outdoors whereas it is not suitable for indoor environments due to the lack of line of sight for radio frequency signals. Therefore, various systems have been developed to solve the indoor positioning problem. Enhancing the performance of these systems...
Recently many industries and companies are developing machine learning algorithms and services, and they are publishing them on the internet. However, because most of people who want to use the machine learning services to analyze data are familiar with sheet data rather than programming language, it is difficult to use those services written in programming language. For the reason, we developed a...
SVM (Support Vector Machine), a state of the art classifier model is implemented on a computational mobile platform and its performances are evaluated against a low complexity classifier such as SFSVC (Super Fast Vector Support Classifier) on the same platform. For a better comparison, similar implementation for the two architectures are considered, such as using the same basic linear algebra library...
Ethnicity is one of the most salient clues to face identity. Analysis of ethnicity-specific facial data is a challenging problem and predominantly carried out using computer-based algorithms. Current published literature focusses on the use of frontal face images. We addressed the challenge of binary (British Pakistani or other ethnicity) ethnicity classification using profile facial images. The proposed...
Music emotions recognition (MER) is a challenging field of studies addressed in multiple disciplines such as musicology, cognitive science, physiology, psychology, arts and affective computing. In this paper, music emotions are classified into four types known as those of pleasing, angry, sad and relaxing. MER is formulated as a classification problem in cognitive computing where 548 dimensions of...
In this paper, we present an application designed to analyze news articles from Romanian mass media and extract opinions about political entities relevant to the major political stage. The application was created with the desire to study media polarization around important political events, such as legislative or presidential elections. The application uses different crawlers to extract the data from...
Linear Discriminant Regression Classification (LDRC) is an effective method developed in the recent years on aim of providing enhancement to the accuracy of Face Recognition (FR) based systems. The visible general problems in face recognition are fraudulent faces and the factors affecting recognition accuracy such as noise, diversions in the angle, poses and expression. These problems are the main...
Proposed algorithm is a face recognition algorithm from video using Generalized mean Deep Learning Neural Network. Generalized mean provides fast convergence of the feature set and Deep learning neural network is enhanced using wavelet transform as it improves the classification efficiency of the neural network. The performance of the proposed algorithm is evaluated on PaSC and Youtube dataset. The...
Facial expression has made significant progress in recent years with many commercial systems are available for real-world applications. It gains strong interest to implement a facial expression system on a portable device such as tablet and smart phone device using the camera already integrated in the devices. It is very common to see face recognition phone unlocking app in new smart phones which...
In this paper, the brief survey of data mining classification by using the machine learning techniques is presented. The machine learning techniques like decision tree and support vector machine play the important role in all the applications of artificial intelligence. Decision tree works efficiently with discrete data and SVM is capable of building the nonlinear boundaries among the classes. Both...
Information needs of the users have grown exponentially with the advent of advancements in information and communication technology. The traditional ways of searching information from the online resources has been evolved and the tendency is geared more towards getting quality contents. In healthcare domain, the clinical researchers and physicians are even more interested to find quality information...
This paper presents comparative analysis of various machine learning algorithms in order to evaluate their predictive performance for screening of cervical cancer by characterization and classification of Pap smear images. Papanicolaou smear (also referred to as Pap smear) is a microscopic examination of samples of human cells scraped from the lower, narrow part of the uterus, called cervix. The sample...
A waybill is a document that accompanies the freight during transportation. The document contains essential information such as, origin and destination of the freight, involved actors, and the type of freight being transported. We believe, the information from a waybill, when presented in an electronic format, can be utilized for building knowledge about the freight movement. The knowledge may be...
Machine learning has been applied in image processing system for object recognition, inspection and measurement. It assumes that the provided training objects are representative enough to the real objects. However in real application, new (unlearned) objects always emerge over time, which may deviate from the trained (learned) objects. The conventional image processing system using machine learning...
A great deal of effort is being made to increase accuracy and reliability of Condition Based Maintenance systems; for instance, by improved feature selection strategies or optimization approaches of classifier parameters. In this work a novel classification methodology is presented, covering from the characterization of the acquired physical magnitudes to the configuration of the classification algorithms...
Instance selection also named sample selection is an important preprocessing step for pattern classification. Almost all of the existing instance selection methods are developed for specific classifiers, such as nearest neighbor (NN) classifier, support vector machine (SVM) classifier. Few of them are designed for single hidden layer feed-forward neural networks (SLFNs) classifier. Based on sample...
Principal Component Analysis (PCA) is one of the most widely used subspace projection technique for face recognition. In subspace methods like PCA, feature selection is fundamental to obtain better face recognition. However, the problem of finding a subset of features from a high dimensional feature set is NP-hard. Therefore, to solve the feature selection problem, heuristic methods such as evolutionary...
Nowadays, we can see an increasing number of studies in genomics that try to find out ways to detect diseases and also better prevention methods. The public would gain a lot of benefits from the studies. With the rapid development of genotyping technology, it creates opportunity to the researchers to go depth to the genetic and look into the variants. Most of the time, researchers would found different...
In this paper, we focus on the issue of building up a training set for the task of image classification at minimal labeling costs. It is a topic that has attracted the considerable attention in the recent years. We propose a novel active learning algorithm with optimal distribution. In order to solve the problems of the noisy distribution and the sampling bias in the actively sampling process, the...
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.