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.
This article shows the solution to the problem of designing a neuronetwork component of industrial technical system. This solution lets to provide nominal accuracy of information processing, when technical system is working under conditions of destabilizing factors. Base of designing a neuronetwork component is algorithms of elimination of influence of external and internal noise of artificial neural...
Gender recognition has important applications in apparel design, social security, and human-computer interaction systems. In this paper, we investigate gender-recognition technologies using 3-D human body shape. The front and side silhouettes from 459 female subjects and 107 male subjects were extracted and then modeled using normalized Elliptic Fourier descriptors. Principal Component Analysis (PCA)...
The presence of metallic particles can adversely affect the reliability of Gas-Insulated Substation (GIS) by initiating partial discharges (PDs). Therefore, the investigation of PD characteristics and particle size and position on the spacer surface are the significant steps toward the reliability improvement of the GIS equipments. This paper presents the use of Back-Propagation Artificial Neural...
This thesis presents a malicious-degree decision system based on dynamic fuzzy neural network. Integrated with fuzzy reasoning and neural network in artificial intelligence, this system gives a comprehensive evaluation such as malicious-degree by analyzing the behaviors of unknown code. This method is compared with simple and multiple Bayes in the end. The experimental results and comparison show...
In this paper, we introduce a method to find useful markers from sensor arrays which have massive sensing points and diagnose liver cancer based on machine learning algorithms which are neural network and fuzzy neural network. We obtain reliable results by using a learning ability and n-fold cross validation. For the verification of the proposed method, raw data of serums from 314 normal and 81 patients...
The sleep apnea is a sleep disorder characterized by cessation of respiratory flow (apnea) or a reduction in the flow (hypopnea). This disorder is often invalidating and may in some cases lead to death. During the night, symptoms can include nocturnal choking, heavy snoring, sweating, restless sleep, impotence, and witnessed apnea. As the sleep centers for apnea detection are usually overloaded and...
Predicting students' academic achievement with high accuracy has an important vital role in many academic disciplines. Most recent studies indicate the important role of the data type selection. They also attempt to understand individual students more deeply by analyzing questionnaire for a particular purpose. The present study uses free-style comments written by students after each lesson, to predict...
One way to predict the behavior of smart home lighting is by using machine learning. Currently many methods of supervised learning that used for this problem, one of them is decision tree method. Very Fast Decision Tree (VFDT) as one of the decision tree method that has advantages in online machine learning that may useful in smart home, but there are still some room of improvisation that can improve...
In cognitive radio networks (CRNs), the cognitive Engine (CE) is responsible for decision making. This is quite a challenging task as it requires finding the balance between prediction accuracy and efficient learning for optimal configuration settings for the CRN. Artificial neural networks (ANNs) have been widely used as predictive tools in cognitive radio. In this paper, random neural networks (RNNs)...
In the automotive industry the issue of safety remains a major priority. This aspect is not focused just on the driver but also on the other participants of the traffic like the pedestrians. This paper describes a pedestrian detection system where three different classification methods are used for detecting pedestrians with a far infrared camera. The three methods are tested and compared on variable...
The design of Artificial Neural Network (ANN) is a typical task as it is depends on human experience. There are few techniques like the Back-Propagation algorithm and nature inspired meta-heuristic are one of the most widely used and popular technique for optimizing feed forward neural network training. Artificial Bee Colony (ABC) algorithm is nature inspired meta-heuristic approach based on behavior...
Glaucoma is an eye disease which damages the optic nerve of the eye and becomes severe over time. It is caused due to buildup of pressure inside the eye. Glaucoma tends to be inherited and may not show up until later in life. The detection of glaucomatous progression is one of the most important and most challenging aspects of primary open angle glaucoma (OAG) management. The early detection of glaucoma...
A critical issue in recognition of mathematical expressions is the identification of the spatial relations of the symbols or/and sub-expressions that comprise the entire mathematical formula. This paper addresses the problem of structural analysis of mathematical expressions by constructing appropriate feature vectors to represent the spatial affinity of the objects (mathematical symbols or sub-expressions)...
A bug in a software application may be a requirement bug, development bug, testing bug or security bug, etc. To prediet the bug numbers accurately is a challenging task. Advance knowledge about bug numbers will help the software managers to take decision on resource allocation and effort investments. The developers will be aware of the number of bugs in advance and can take effective steps to reduce...
Human Activity Recognition (HAR) have been developed for recognize context generated from human. In real environment system required multi -sensor for support large area and get more accuracy result. Using multi-sensor make high dimensional data which inefficacious for classification model. This paper is concerned with developing classification model that supports high dimensional data and reducing...
Current state-of-the art supervised vessel segmentation methods require large number of feature vectors to construct a good model. In this paper, we propose a framework to optimally search for optimal features as inputs to Artificial Neural Network (ANN) trained by Scaled Conjugate Gradient (SCG). SCG is known to speed-up the learning stage in a supervised learning especially when error reduction...
A system using electroencephalography (EEG) signals could enhance the detection of mental fatigue while driving a vehicle. This paper examines the classification between fatigue and alert states using an autoregressive (AR) model-based power spectral density (PSD) as the features extraction method and fuzzy particle swarm optimization with cross mutated of artificial neural network (FPSOCM-ANN) as...
Previously, we investigated the prediction of total effort and errors for embedded software development projects using an artificial neural network (ANN). In addition, we proposed a method for reducing this margin of error. However, methods using ANNs have reached their improvement limits, since an appropriate value is estimated using what is known as point estimation in statistics. In this paper,...
The present study proposes prediction approaches of student's grade based on their comments data. Students describe their learning attitudes, tendencies and behaviors by writing their comments freely after each lesson. The main difficulty of this research is to predict students' performance by separately using two class data in each lesson. Although students learn the same subject, there exist differences...
Gaze tracking is the process of measuring gaze point or the motion of an eye relative to the head. Gaze tracking technique provides us a brand new way of human computer interaction. In addition, eye gaze tracking can be also applied to support seriously disabled people in using computer. In this paper, we explored the use of eye gaze tracking technology on a tablet device, designed and implemented...
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.