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As a member of the European Union, Hungary face different challenges, of which the most important are the transformation of the healthcare system, the Social Security and pension system and the system of taxation. These economic and social challenges require long-term governmental strategies, which should be modelled, tested, verified in some way. It is for this challenge that we find an efficient...
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...
Image-Based Rendering (IBR) allows good-quality free-viewpoint navigation in urban scenes, but suffers from artifacts on poorly reconstructed objects, e.g., reflective surfaces such as cars. To alleviate this problem, we propose a method that automatically identifies stock 3D models, aligns them in the 3D scene and performs morphing to better capture image contours. We do this by first adapting learning-based...
Palmprint has rich texture information, and palmprint recognition is a very promising biometric identification technology. To study online palmprint identification technology under non-contact mode, a novel and simple method for online palmprint identification technology is presented, and a palmprint recognition simulation system is designed in this paper. Firstly, based on the coordinate position...
We propose a Convolutional Neural Network model to learn spatial footstep features end-to-end from a floor sensor system for biometric applications. Our model's generalization performance is assessed by independent validation and evaluation datasets from the largest footstep database to date, containing nearly 20,000 footstep signals from 127 users. We report footstep recognition performance as Equal...
Recent research has demonstrated the negative impact of pupil dilation on iris recognition performance. Apart from light intensity changes, several factors such as alcohol, drugs, age, disease and psychology, are known to affect the size of the pupil. This work (1) analyzes the impact of drugs on pupil dilation, (2) proposes the use of a biomechanical nonlinear iris normalization scheme along with...
In cases of emergency situations many agencies and authorities need to exchange information between their departments in order to provide fast and accurate first aid to the people in need. In many cases medical teams go on the field with no information what to expect and sometimes the people providing help are in danger because of shortage of information prior to depart on the crisis scene. IMPRESS...
We consider the problem of daily human activity recognition (HAR) using multiple wireless inertial sensors, and specifically, HAR systems with a very low number of sensors, each one providing an estimation of the performed activities. We propose new Bayesian models to combine the output of the sensors. The models are based on a soft outputs combination of individual classifiers to deal with the small...
Modeling Heart Rate Variability (HRV) data has become important for clinical applications and as a research tool. These data exhibit long memory and time-varying conditional variance (volatility). In HRV, volatility is traditionally estimated by recursive least squares combined with short memory AutoRegressive (AR) models. This work considers a parametric approach based on long memory Fractionally...
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...
Biometric technologies are used to grant specific users access to services and data. The access control is usually performed at the start of a session that spans over a period of time. Continuous authentication aims at insuring the identity of the user over this period of time, and not only at its start. Multi-biometrics aims at increasing the accuracy, robustness and usability of biometrics systems...
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...
We demonstrate that classical quadratic forms are not able to solve the problem of recognizing high-dimensional images. The “deep” Galushkin-Hinton neural networks can solve the problem of high-dimensional image recognition, but their training has exponential computational complexity. It is technically impossible to train and retrain a “deep” neural network rapidly. For mobile “artificial nose” systems...
Iris liveness detection methods have been developed to overcome the vulnerability of iris biometric systems to spoofing attacks. In the literature, it is typically assumed that a known attack modality will be perpetrated. Then liveness models are designed using labelled samples from both real/live and fake/spoof distributions, the latter derived from the assumed attack modality. In this work it is...
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...
Digital Ecosystem (DE) is a concept emerged from the natural existence of business ecosystem, which in turn is taken from the concept of biological ecological systems. On the other hand, System of Information Systems (SoIS) are special type of System of Systems (SoS) that deals with several Information Systems producing overwhelming amount of information. In this paper we aim to define the concepts...
Electrocardiogram signal is prone to noise interference. Processing noisy signals in an automated system such as biometric systems negatively affects its performance. In this paper, we developed a real-time abnormal electrocardiogram heartbeat detection and removal. The proposed technique eliminates outliers in real-time while subjects data are being collected. We used Gaussian mixture model to model...
Gait refers to the walking style of every individual person. Recent days gait is emerged as a supporting biometric using machine vision technique. This Work aims to develop a system capable of Human gait recognition by using model free approach. The gait database consists of silhouettes ie. outer frame of the human body. These silhouettes are affected by noises and discontinuities. So preprocessing...
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