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.
Neural network technique has been recently preferred in textile sector for the prediction task because the traditional mathematical and statistical methods can be inadequate to derive complex relations within textile datasets. Meanwhile ensemble learning has become a popular machine learning approach in recent years due to the high prediction performance it provides. Therefore, this study proposes...
In this study, a system has been developed to provide meaning and classification of e-mails according to their contents. The aim of the work is to develop an intelligent inbox to assist in awareness of information security. In the designed system, a client is developed that can connect to the server and receive e-mails. A two-step analysis is performed on the received e-mails. For both stage analysis,...
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...
Clustering is an important unsupervised data analysis technique, which divides data objects into clusters based on similarity. Clustering has been studied and applied in many different fields, including pattern recognition, data mining, decision science and statistics. Clustering algorithms can be mainly classified as hierarchical and partitional clustering approaches. Partitioning around medoids...
The paper is dedicated to the systemic botany domain and analyzes the degree of affinity between the species, genera and families based on fractal theory. The research is conducted on the image information from Gentianaceae family plant, in order to determine their membership to the recognized genera Gentiana, Gentianella and Gentianopsis which were previously tagged into a single genus. Some concepts...
The paper proposes an algorithm to process Alpha activity in real-time electroencephalogram signal using LabVIEW for mental state detection. The electroencephalogram signals from occipital region have direct relationship with the state of mind which can be utilized by physically challenged individuals to control their surrounding environment, providing an extent of independency. Being independent...
Web spam is a big problem for search engine users in World Wide Web. They use deceptive techniques to achieve high rankings. Although many researchers have presented the different approach for classification and web spam detection still it is an open issue in computer science. Analyzing and evaluating these websites can be an effective step for discovering and categorizing the features of these websites...
Digital libraries can provide information services for users with diverse needs. Due to a large amount of data that exists in digital library systems, including text and multimedia resources, with different cohorts of users, and the challenges with existing digital library systems in terms of maintaining privacy and confidentiality, it is very difficult to provide personalised library services and...
The handwritten digit recognition problem becomes one of the most famous problems in machine learning and computer vision applications. Many machine learning techniques have been employed to solve the handwritten digit recognition problem. This paper focuses on Neural Network (NN) approaches. The most three famous NN approaches are deep neural network (DNN), deep belief network (DBN) and convolutional...
Unemployment, poverty and similar problems that have come to the fore with the increase in population in our country have caused the municipalities to take charge in the field of social assistance and social services. For this purpose, it is very important that the municipalities that undertake social assistance and social service tasks are able to use the present data quickly during distribution...
DDoS attacks bring huge threaten to network, how to effectively detect DDoS is a hot topic of information security. Currently, there are some methods designed to detect DDoS attacks, but the detection rate of them is low. Moreover, DDoS detection is easily misled by flash crowd traffic. In this paper, a new method to detect DDoS attacks based on RDF-SVM algorithm is proposed. By considering the importance...
Image classification is one of the important problems in the field of machine learning. Deep learning architectures are used in many machine learning applications such as image classification and object detection. The ability to manipulate large image clusters and implement them quickly makes deep learning a popular method in classifying images. This study points out the success of the convolutional...
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...
Current hierarchical clustering algorithms face the risk of privacy leakage during the clustering process for big dataset. While differential privacy is a relatively recent development in the field of privacy-preserving data mining, offering more robust privacy guarantees. In the paper, BIRCH algorithm under differential privacy is studied and analyzed. Firstly, Diff-BIRCH algorithm which directly...
With the progress of the network and technology, the perfect combination of mobile intelligent terminal and internet, people are increasingly dependent on intelligent terminals. So, it was very necessary of a model for assessing the security performance of mobile intelligent terminals, especially to establish the objective model of the security performance of mobile intelligent terminal. In this paper,...
Modern healthcare service records, called Claims, record the medical treatments by a Provider (Doctor/Clinic), medication advised etc., along with the charges, and payments to be made by the patient and the Payer (insurance provider). Denial and rejection of healthcare claims is a significant administrative burden and source of loss to various healthcare providers and payers as well. Automating the...
This paper proposes an intelligent fault diagnosis technique to detect and classify possible faults occurring in Photovoltaic strings, based on the analysis of the symptoms observed in the I-V characteristic. The technique consists of two algorithms: The first one allows the classification of faults that have not the same symptoms evolution; whi le for the second one, two Artificial Neural Networks...
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...
Ensemble learning is a method created by using different combinations of experts. Using different combinations has a great potential to get better results in pattern classification problems. In this study, ensemble learning was used for the aim of PAF screening, i.e. finding whether a person is PAF patient or not from his/her ectopic-free ECG records. Both hierarchical and parallel structures of ensemble...
Machine learning has its tentacles spread over all major areas of science. The current rise in the amount of data being generated as necessitated its adoption in virtually all aspects including chemoinformatics. Several machine learning methods have been applied to the drug discovery process due to the importance of prediction of bioactivity before the release of drug into the market. The need for...
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.