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The categorical data that have natural ordering between categories are termed ordinal data, which are pervasive in numerous areas, including discrete sensor readings, metering data or preference options. Though aggregating such ordinal data from the population is facilitating plenty of crowdsourcing applications, contributing such data is privacy risky and may reveal sensitive information (e.g. locations,...
This paper presents a hardware realisation of a novel ECG baseline drift removal that preserves the ECG signal integrity. The microcontroller implementation detects the fiducial markers of the ECG signal and the baseline wander estimation is achieved through a weighted piecewise linear interpolation. This estimated drift is then removed to recover a “clean” ECG signal without significantly distorting...
The microbial diversity and taxonomic profiles of human microbiome carries indicative signals associated with several complex human diseases. Methods quantifying and differentiating profiles belonging to healthy/disease microbiomes have a potential to be used as non-invasive diagnostic tools. 16S rRNA sequencing is a currently popular and feasible technology to generate the required data for such...
In this paper a model devoted to the forecast of solar radiation and Photovoltaic (PV) power has been addressed. In particular, for what concerns the solar radiation prediction, the novelty of the approach stays in the use of the clear sky model proposed by Hottel fed by the output of a data driven algorithm. In this hybrid approach, key parameters are computed through the exploitation of a database...
Increasing interests in metabolomics have motivated the need for efficient and accurate metabolite profiling method. In this paper, we proposed a new method for targeted metabolite profiling. The approach relies on nonlinear least squares technique and a novel peak assignment algorithm. Peaks from experimental spectra are assigned to a reference compound library with the aid of mixed integer nonlinear...
Nowadays, face recognition systems are going to widespread in many fields of application, from automatic user login for financial activities and access to restricted areas, to surveillance for improving security in airports and railway stations, to cite a few. In such scenarios, several architectures based on both 2D image analysis and 3D reconstruction are investigated and proposed in literature...
Recently, polyhedral conic classifiers have become popular since they perform better compared to the Support Vector Machines (SVMs). Cone vertex of polyhedral conic classifiers is an important parameter and it is generally taken as the mean of positive data in literature. In this paper, we studied optimally estimating the cone vertex to improve the accuracy of the polyhedral conic classifiers. The...
In the present work, we proposed a novel approach which allows the estimation of actuator fault and its compensation correctly for switched hybrid system. So, to thwart the impact of the fault we extended and developed a fault tolerant control (FTC) for switched system. The synthesis of it needs to follow three important steps. The first step, is based on the use of the Data-based Projection Method...
Differential privacy is a formal mathematical standard for quantifying the degree of that individual privacy in a statistical database is preserved. To guarantee differential privacy, a typical method is adding random noise to the original data for data release. In this paper, we investigate the basic conditions of differential privacy considering the general random noise adding mechanism, and then...
Our aim is to evaluate fundamental parameters from the analysis of the electromagnetic spectra of stars. We may use 103–105 spectra; each spectrum being a vector with 102–104 coordinates. We thus face the so-called “curse of dimensionality”. We look for a method to reduce the size of this data-space, keeping only the most relevant information. As a reference method, we use principal component analysis...
In this paper, synthesising tango choreographies from tango dances is aimed. This system takes tango dance patterns performed by human dancers as input and produces choreographies that are represented in 3 dimensional virtual environment. Dance figures obtained by motion capture system are segmented automatically and analyzed with regard to weight center to form the dance database. Choreographies...
Indoor localization is a crucial topic for mobile computing and it has been attracting numerous research groups and labs around the world. Among the many techniques being proposed for indoor localization, fingerprinting based on the use of Wi-Fi signal has attracted continuous attention in academia because of pervasive penetration of wireless LANs (WLANs) and Wi-Fi enabled mobile devices. In the indoor...
Food related web services, such as recipe websites and food journaling apps, are rapidly gaining popularity. Data from service providers and that generated by users often coexist in these services. Compared to the former, the latter, due to its randomness and lack of organization, is often difficult to incorporate into common service features like recommendation making and associative searching. This...
Skew angle detection is one of the most important component of Optical Characters Recognition (OCR) systems and documents analysis. Taking documents by the blind and visually impaired people with a mobile phone always have a degree of inclination. In this paper, a novel and an efficient method based on extraction of Harris corner features points and Hough transform is presented to estimate skew angle...
We propose to demonstrate HDBExpDetector, a system for analysts to discover bursty events from a thirdparty web database by using nothing but the existing search interface of the web database to monitor and detect sudden changes to aggregates that satisfy certain user-defined conditions. Video https://youtu.be/7Pwd8o1h5CY.
The Unified Data Architecture (UDA) of Teradata is an inclusive multisystem data analytics solution. A key challenge for query optimization under the UDA is to find optimal plans for queries that access data on heterogeneous remote data stores. The challenge comes primarily from the lack of statistics for data stored on remote systems. In this paper, we present techniques implemented in Teradata Database...
We study a novel problem of influence maximization in trajectory databases that is very useful in precise locationaware advertising. It finds k best trajectories to be attached with a given advertisement and maximizes the expected influence among a large group of audience. We show that the problem is NP-hard and propose both exact and approximate solutions to find the best set of trajectories. We...
This work proposes a technique for predicting the pitch from Mel-frequency cepstral coefficients (MFCC) vectors. Previous pitch prediction methods are based on the statistical models such as Gaussian mixture models and hidden Markov models. In this paper, we propose a three-step method to estimate pitch from MFCC vectors. First the Mel-filterbank energies (MFBEs) are estimated from MFCC vectors. Secondly,...
In this paper, a new approach which serves firstly the estimation of the actuator fault and secondly its compensation for hybrid switched system is presented. The compensation of this fault is based on the use of the additive fault tolerant control. So, this paper extends an estimation method (Data-based Projection Method) for switched system to estimate the actuator fault. Then, the additive control...
The fundamental frequency is one of the prosodic parameters, and many algorithms have been developed for estimating the fundamental frequency of speech signals. Most of them provide good results on good quality speech signals, but their performance degrades when dealing with noisy signals. Moreover, although some provide a probability for the voicing decision, none of them indicate how reliable the...
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