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.
Person re-identification plays a key role in video monitoring. Aiming for current person re-identifications for numerical complexity and extraction difficulty, we propose a simple and fast multi-feature. On the basis of analysis of difference excitation and orientation of Weber Local Descriptors, showing graphic texture features by difference excitation of circular field, showing graphic edge orientation...
Object-based audio techniques are becoming popular as they provide the flexibility for personalized rendering. For encoding multiple audio objects, a recent approach based on the intra-object sparsity was proposed. However, the allocation strategy of the number of preserved time-frequency (TF) instants (NPTF) utilized in this approach usually leads to an unbalanced perceptual quality for the decoded...
Although some security threats were taken into consideration in the IPv6 design, DDoS attacks still exist in the IPv6 networks. The main difficulty to counter the DDoS attacks is to trace the source of such attacks, as the attackers often use spoofed source IP addresses to hide their identity. This makes the IP traceback schemes very relevant to the security of the IPv6 networks. Given that most of...
The influence of social networks among people and at the same time inevitable spread of commercial use of them. Accordingly, in order to sell products, recommender systems designed based on user behavior on social networks, providing a variety of commercial offers tailored to the user. The accuracy of recommender systems that make recommendations to users, and how many of the proposals are accepted...
Graph-based semi-supervised learning method has been influential in the data mining and machine learning fields. The key is to construct an effective graph to capture the intrinsic data structure, which further benefits for propagating the unlabeled data over the graph. The existing methods have shown the effectiveness of a graph regularization term on measuring the similarities among samples, which...
Given a large bipartite graph that represents objects and their properties, how can we automatically extract semantic information that provides an overview of the data and -- at the same time -- enables us to drill down to specific parts for an in-depth analysis? In this work, we propose extracting a taxonomy that models the relation between the properties via an is a hierarchy. The extracted taxonomy...
Many organizations, including businesses, government agencies and research organizations, are collecting vast amounts of data, which are stored, processed and analyzed to mine interesting patterns and knowledge to support efficient and quality decision making. In order to improve data quality and to facilitate further analysis, many application domains require information from multiple sources to...
Bioacoustic monitoring, such as surveys of animal populations and migration, needs efficient data mining methods to extract information from large datasets covering multi-year and multi-location recordings. This paper introduces a method for sparsecoding of bioacoustic recordings in order to efficiently compress and automatically extract patterns in data. We demonstrate the proposed method on the...
Online discussion forums make up a significant bulk in the type of opinion information that represents a valuable source for many real-world applications. However, conducting comprehensive opinion analysis of threaded discussions is a challenging task because it requires not only an aggregation of opinions over the multi-level thread structures, but also effective methods for exploring the complex...
The Needleman-Wunsch algorithm (NW) marked the genesis of a new field of research known as sequence alignment. Its inception was motivated by the growing need for automated methods to find homologous biological sequences. Subsequently, sequence alignment has established itself as a standard approach in bioinformatics, and has also been applied to other domains, including sequences of temporal events...
Since asynchronous circuits consume power only when activities actually happen, the conventional serial communication scheme where the embedded clock is always transmitted and the clock and data recovery (CDR) circuit is continuously working is very wasteful for connecting asynchronous circuit cores. This paper proposes a new serial communication scheme for asynchronous circuits where the power consumption...
Pharmacovigilance is the field of science devoted to the collection, analysis, and prevention of Adverse Drug Reactions (ADRs). Efficient strategies for the extraction of information about ADRs from free text sources are essential to support the important task of detecting and classifying unexpected pathologies, possibly related to (therapy-related) drug use. Narrative ADR descriptions may be collected...
Compressive sensing has been successfully used for optimized operations in wireless sensor networks. However, raw data collected by sensors may be neither originally sparse nor easily transformed into a sparse data representation. This paper addresses the problem of transforming source data collected by sensor nodes into a sparse representation with a few nonzero elements. Our contributions that address...
Automatic Manifold identification is currently a challenging problem in Machine Learning. This process consists on separating a dataset blindly, according to the form defined by the data instances in the space. Data are discriminated in groups defined by their form. These approaches are usually focused on continuity-based methods where the manifold follows a continuity criterion. Currently, clustering...
This paper presents a pipeline for multilingual analysis of contentious social behaviour. Its basic functionalities include news articles extraction from a variety of multilingual news sources (in Bulgarian, French, Polish, Russian, Spanish, and Swedish), protest event selection and an ontology-based event annotation. The results are output in CSV format. An evaluation of protest event selection and...
Aimed at solving the problem that traditional clustering methods are vulnerable to the sparsity feature of the high dimensional data, a spectral clustering algorithm is proposed based on K-SVD dictionary learning. The algorithm firstly learns a dictionary by K-SVD and obtains sparse representation coefficients of all data samples in the dictionary by l1 sparse optimization. Then the similarity matrix...
Number of security vulnerabilities in web application has grown with the tremendous growth of web application in last two decades. As the domain of Web Applications is maturing, large number of empirical studies has been reported in web applications to address the solution of vulnerable web application. However, before advancing towards finding new approaches of web applications security vulnerability...
Public software repositories offer a great opportunity for researchers. GitHub is a repository with more than 10 million projects. GitHub has an implementation of a defect tracking system. This paper describes the process developed to extract defects from GitHub repository, one of the most widely used public repositories. In this work, besides of the process, it is presented the appeared difficulties,...
In this paper, we outline the recent efforts of our research in defense against Distributed Denial of Service (DDoS) attacks. In particular, we present a novel approach to IP traceback, namely Unique Flow Marking (UFM), and we evaluate UFM against other marking schemes. Our results show that the UFM can reduce the number of marked packets compared to the other marking schemes, while achieving a better...
GitHub is a social coding platform that enables developers to efficiently work on projects, connect with other developers, collaborate and generally "be seen: by the community. This visibility also extends to prospective employers and HR personnel who may use GitHub to learn more about a developer's skills and interests. We propose a pipeline that automatizes this process and automatically suggests...
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.