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Biometric authentication systems verify the identity of individuals based on what they are. As they are error prone, they can reject genuine individuals or accept impostors. Researchers of the field quantify the quality of their algorithm by benchmarking it on several databases. However, although the standard evaluation metrics state the performance of their system, they are unable to explain the...
Models are the cornerstone of Model-Driven Engineering (MDE). Their size is constantly growing, becoming one of the main problems when it comes to manipulating them, via model-to-model transformations, model-to-text transformations or simply parsing them. In this paper we propose a way of distributing Ecore models representing them as JSON and URLs as identifiers, since HTTP is one of the most successful...
Trust fosters cooperation in social interactions. It is widely studied in applied and academic disciplines. However, trust is a hard concept to define. Network analysis of the Web of Science citation databases shows it has multiple meanings and applications even within Computer Science. To date general models of trust are essentially conceptual, whereas workable proposals focus on special situations...
In this paper, we present a novel method for predicting gene functional interactions. We study the effectiveness of various raw and derived features from neural word embedding learned from biomedical literature. Our evaluation results demonstrate that the information captured in neural word embedding is very useful and our learned classification models are capable of predicting gene functional interactions...
Mathematical Models Database (MMD) is an online repository of mathematical models that can be easily used for research purposes, in teaching or in performing comparative tests. In a single free-of-charge, freely accessible Internet service all the data from the database is available with an expected (in its final form) several ready-to-use models, either purely mathematical or physics-based. Apart...
This paper describes large-scale full-wave analyses of electromagnetic fields using numerical human body models. Recently, medical equipment using electromagnetic fields including hyperthermia is spreading. During treatment, it is effective to focus the electromagnetic field onto the lesions inside the human body. The purpose of this research is to accurately calculate the electromagnetic field inside...
Quantitative research has been extensively applied in sociology. The traditional way of using data statistical computing tools of R, SPSS and Stata on the stand-alone machine can't deal with the challenges of big data; furthermore, the demand of complex computing in mobile condition is increasing due to the fieldwork characteristics of sociological researchers. Considering the computing needs of sociological...
While Model Driven Engineering is gaining more industrial interest, scalability issues when managing large models have become a major problem in current modeling frameworks. Scalable model persistence has been achieved by using NoSQL backends for model storage, but existing modeling framework APIs have not evolved accordingly, limiting NoSQL query performance benefits. In this paper we present the...
We are currently witnessing an explosion of advances in database technology, that cover all phases of database application design: non-functional requirements, conceptual modeling, logical modeling, deployment, physical design and exploitation. Researchers and engineers cooperate to integrate these advances in the database design. Their proposed solutions have to be confronted with similar studies...
Biological analysis applications are usually high demanding in terms of computational power required. Cloud Computing infrastructures can be of great value supporting those type of applications, thanks to the high flexibility and performing hardware provided. The merging of solutions based on MapReduce and distributed file systems services, allows the creation of scalable infrastructures and data...
Many scientific fields generate, and require manipulation of big data. Known scientific data analysis systems, as well as traditional DBMSs, follow a pull-based architectural design, where the executed queries mandate the data needed. This design, while suitable for traditional transaction-based workloads where number of queries retrieve small parts of data located at various places of the database,...
Augmented reality is becoming the future of e-commerce, throw their mobile devices, customers have access to all kind of information, going from weather, news papers, shops and so on. Today's mobiles devices are so powerful to the point that they can be used as a platform of virtual try-on systems. Over this paper we present a virtual eye glasses try-on system based on augmented reality and LBP for...
In the era of big data, data analytics, business intelligence database management plays a vital role from technical business management and research point of view. Over many decades, database management has been a topic of active research. There are different type of database management system have been proposed over a period of time but Relational Database Management System (RDBMS) is the one which...
The main purpose of this paper is to review the literatures on the adoption of Cloud Computing by SMEs in order to learn the current state of Cloud Computing studies and identify gaps for future research. Twenty-two articles were reviewed and analyzed from various journals and conference proceedings that were published on Cloud Computing adoption, acceptance, and diffusion. Findings revealed that...
This article provides an overview of the challenges of big data, in the aspects of data scale, data heterogeneity, data timeliness, and demand for deep analyzing, in correspondence with four features of big data. It also presents an overview of trends of big data analytics both in theory and technique, with the development of testing benchmark, visualization technology, advanced and mixed architecture,...
Monte Carlo (MC) simulations play a crucial role in nuclear medical imaging since they can provide the ground truth for clinical acquisitions, by integrating and quantifing all physical parameters that affect image quality. The last decade a number of realistic computational anthropomorphic models have been developed to serve imaging, as well as other biomedical engineering applications. The combination...
Spatio-temporal interesting points feature is a key technology for a wide class of computer vision approaches to recognize human actions. In this paper, a novel bio-inspired model based spatio-temporal interesting points (BIM-STIP) framework is proposed. Different from traditional STIP framework, the introduction of bio-inspired model provides a biological theory for interest points detection and...
Human gait recognition is a distance based second generation biometrics, which is unobtrusive. Human gait recognition is nothing but identifying a person from its walking style. Human Cooperation is not required in this biometric system. There are two approaches of gait recognition, which are model based and model free approaches. This paper provides a recent comprehensive survey of only model free...
Network theory has been used for modeling biological data as well as social networks, transportation logistics, business transcripts, and many other types of data sets. Identifying important features/parts of these networks for a multitude of applications is becoming increasingly significant as the need for big data analysis techniques grows. When analyzing a network of protein-protein interactions...
A biometric identification system determines the identity of a given biometric input data, among a set of gallery identities stored in the database. The existing identification techniques typically base the decision on the match scores representing the similarity between the query and the template of each gallery. The strategies proposed so far for combining different biometric identification systems...
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