Search results for "Tree"
showing 10 items of 1841 documents
Spectral clustering with the probabilistic cluster kernel
2015
Abstract This letter introduces a probabilistic cluster kernel for data clustering. The proposed kernel is computed with the composition of dot products between the posterior probabilities obtained via GMM clustering. The kernel is directly learned from the data, is parameter-free, and captures the data manifold structure at different scales. The projections in the kernel space induced by this kernel are useful for general feature extraction purposes and are here exploited in spectral clustering with the canonical k-means. The kernel structure, informative content and optimality are studied. Analysis and performance are illustrated in several real datasets.
WiHAR : From Wi-Fi Channel State Information to Unobtrusive Human Activity Recognition
2020
A robust and unobtrusive human activity recognition system is essential to a multitude of applications, such as health care, active assisted living, robotics, sports, and tele-immersion. Existing well-performing activity recognition methods are either vision- or wearable sensor-based. However, they are not fully passive. In this paper, we develop WiHAR—an unobtrusive Wi-Fi-based activity recognition system. WiHAR uses the Wi-Fi network interface card to capture the channel state information (CSI) data. These CSI data are effectively processed, and then amplitude and phase information is used to obtain the spectrogram. In the subsequent step, the time-variant mean Doppler shift (MDS) caused …
Deep Learning for Resource-Limited Devices
2020
In recent years, deep neural networks have revolutionized the development of intelligent systems and applications in many areas. Despite their numerous advantages and potentials, these intelligent models still suffer from several issues. Among them, the fact that they became very complex with millions of parameters. That is, requiring more resources and time, and being unsuitable for small restricted devices. To contribute in this direction, this paper presents (1) some state-of-the-art lightweight architectures that were specifically designed for small-sized devices, and (2) some recent solutions that have been proposed to optimize/compress classical deep neural networks to allow their dep…
An Agents and Artifacts Approach to Distributed Data Mining
2013
This paper proposes a novel Distributed Data Mining (DDM) approach based on the Agents and Artifacts paradigm, as implemented in CArtAgO [9], where artifacts encapsulate data mining tools, inherited from Weka, that agents can use while engaged in collaborative, distributed learning processes. Target hypothesis are currently constrained to decision trees built with J48, but the approach is flexible enough to allow different kinds of learning models. The twofold contribution of this work includes: i) JaCA-DDM: an extensible tool implemented in the agent oriented programming language Jason [2] and CArtAgO [10,9] to experiment DDM agent-based approaches on different, well known training sets. A…
An Intralingual Parallel Corpus of Translations into German Easy Language (Geasy Corpus): What Sentence Alignments Can Tell Us About Translation Stra…
2021
Parallel corpora are traditionally interlingual and contain source and target texts in different languages. However, intralingual translations into Easy Language (EL) become more and more common in various countries. First intralingual corpora have been built up and investigated in terms of linguistic and structural features, but a translation-driven corpus linguistic approach is still missing to empirically describe the strategies of Easy Language translation, the characteristics of translated texts as well as to make these parallel corpora usable for professionalising and automatising translation processes. In this paper, we introduce an intralingual parallel corpus of translations into G…
Automated quality control of next generation sequencing data using machine learning
2019
AbstractControlling quality of next generation sequencing (NGS) data files is a necessary but complex task. To address this problem, we statistically characterized common NGS quality features and developed a novel quality control procedure involving tree-based and deep learning classification algorithms. Predictive models, validated on internal data and external disease diagnostic datasets, are to some extent generalizable to data from unseen species. The derived statistical guidelines and predictive models represent a valuable resource for users of NGS data to better understand quality issues and perform automatic quality control. Our guidelines and software are available at the following …
Street Food and Street Vendors, a Culinary Heritage?
2018
This paper examines the theoretical discourse surrounding street food and tells how street food is multidimensional and spatially contingent, but also tackles food safety and aspects related to street vendors’ issues. The street food sector offers to the guests various dishes and drinks prepared at the place of sale or only marketed by itinerant merchants or by vendors with stationary carts, either on the streets or in other public places that may be of interest for tourists. Fast food is generally associated with globalization, so present in high income per capita countries. This paper aims to present a radiography of street food marketing, an image that defines a particular region or coun…
Ultraviolet radiation protection by a beach umbrella.
2010
A beach umbrella intercepts all direct UV irradiance, but only part of the diffuse component. Using a simple sky view factor model, we have determined the fraction of the hemispheric diffuse irradiance that is not intercepted by the umbrella. Assuming a sensor at the surface and close to the center of the umbrella, isotropic diffuse irradiance and for an umbrella of 80 cm radius and 100 cm high, our results show that approximately 34% of the incident horizontal irradiance is not intercepted by the umbrella. These results agree with irradiance measurements conducted with and without the umbrella. The model is next extended to examine receipt of UV radiation by a human figure in a vertical po…
Analysing urban development with decision tree based cellular automata. Toward an automatic transition rule creation process.
2016
International audience
Electrical treeing in EVA-bohemite and EVA-montmorillonite nanocomposites
2009
The present experimental work focuses on the growth of electrical treeing inside different Ethylene-vinyl acetate (EVA) nanocomposites containing Bohemite (an aluminum oxide hydroxide) and Montmorillonite (a phyllosilicate clay mineral) nanoparticles. Bohemite and Montmorillonite particles have different aspect ratios: the first one has a nanometric cube-like symmetry, while the latter has a typical layered structure. The results evidence that the growth of the electrical treeing inside the original polymer can be altered significantly by the dispersion of inorganic nanoparticles.