Search results for "202"
showing 10 items of 5810 documents
Life Cycle Assessment of an Ambitious Renovation of a Norwegian Apartment Building to nZEB Standard
2018
Author's accepted manuscript. The upgrading of building infrastructure to modern standards represents a key tool for reducing global energy demand and emissions from buildings. In Norway, building upgrades have been prioritized despite the relatively low carbon intensity of the Norwegian energy mix through various incentive programs and continual improvement in building standards. Prioritizing upgrades is important as up to 90% of the existing Norwegian building stock is expected to remain standing by the year 2050. The overall impact of upgrading buildings is expected to be a net benefit to the environment but this is primarily in operation, and many studies on energy do not include the ma…
Extended Natural Numbers and Counters
2020
Summary This article introduces extended natural numbers, i.e. the set ℕ ∪ {+∞}, in Mizar [4], [3] and formalizes a way to list a cardinal numbers of cardinals. Both concepts have applications in graph theory.
A Hardware and Secure Pseudorandom Generator for Constrained Devices
2018
Hardware security for an Internet of Things or cyber physical system drives the need for ubiquitous cryptography to different sensing infrastructures in these fields. In particular, generating strong cryptographic keys on such resource-constrained device depends on a lightweight and cryptographically secure random number generator. In this research work, we have introduced a new hardware chaos-based pseudorandom number generator, which is mainly based on the deletion of an Hamilton cycle within the $N$ -cube (or on the vectorial negation), plus one single permutation. We have rigorously proven the chaotic behavior and cryptographically secure property of the whole proposal: the mid-term eff…
Investigating the Impact of Radiation-Induced Soft Errors on the Reliability of Approximate Computing Systems
2020
International audience; Approximate Computing (AxC) is a well-known paradigm able to reduce the computational and power overheads of a multitude of applications, at the cost of a decreased accuracy. Convolutional Neural Networks (CNNs) have proven to be particularly suited for AxC because of their inherent resilience to errors. However, the implementation of AxC techniques may affect the intrinsic resilience of the application to errors induced by Single Events in a harsh environment. This work introduces an experimental study of the impact of neutron irradiation on approximate computing techniques applied on the data representation of a CNN.
Sequential Mining Classification
2017
Sequential pattern mining is a data mining technique that aims to extract and analyze frequent subsequences from sequences of events or items with time constraint. Sequence data mining was introduced in 1995 with the well-known Apriori algorithm. The algorithm studied the transactions through time, in order to extract frequent patterns from the sequences of products related to a customer. Later, this technique became useful in many applications: DNA researches, medical diagnosis and prevention, telecommunications, etc. GSP, SPAM, SPADE, PrefixSPan and other advanced algorithms followed. View the evolution of data mining techniques based on sequential data, this paper discusses the multiple …
Medical Data Mining for Heart Diseases and the Future of Sequential Mining in Medical Field
2018
Data Mining in general is the act of extracting interesting patterns and discovering non-trivial knowledge from a large amount of data. Medical data mining can be used to understand the events happened in the past, i.e. studying a patients vital signs to understand his complications and discover why he has died, or to predict the future by analyzing the events that had happened. In this chapter we are presenting an overview on studies that use data mining to predict heart failure and heart diseases classes. We will also focus on one of the trendiest data-mining field, namely the Sequential Mining, which is a very promising paradigm. Due to its important results in many fields, this chapter …
Overview on Sequential Mining Algorithms and Their Extensions
2018
The main purpose of data mining is to extract hidden, important and nontrivial information from a database. Sequential Pattern Mining is a data mining technique that aims to obtain and analyze frequent subsequences from sequences of events or items with or without time constraint. The importance of a sequence can be measured based on different factors such as the frequency of their occurrence, their length and also their profit. The pattern mining or the discovery of important and unexpected patterns and information was first introduced in 1990 with the well-known Apriori algorithm. Then, and after many studies on frequent pattern mining, a new approach appeared: Sequential Pattern Mining. …
Hop: Histogram of patterns for human action representation
2017
This paper presents a novel method for representing actions in terms of multinomial distributions of frequent sequential patterns of different length. Frequent sequential patterns are series of data descriptors that occur many times in the data. This paper proposes to learn a codebook of frequent sequential patterns by means of an apriori-like algorithm, and to represent an action with a Bag-of-Frequent-Sequential-Patterns approach. Preliminary experiments of the proposed method have been conducted for action classification on skeletal data. The method achieves state-of-the-art accuracy value in cross-subject validation.
Ietvarprogramma Apvārsnis 2020 un jaunākās Open Access nostādnes Eiropā
2012
Ziņojumā, kas sagatavots Open Access nedēļas semināram " Brīvpieejas e-resursu puiblicēšana: iespējas un attīstība" (2012.g. 26.oktobris), sniegta informācija par Eiropas Komisijas 2011. gadā publicētajos ieteikumos un paziņojumos ietvertajām Open Access nostādnēm saistībā ar jauno ES pētniecības un inovāciju finansēšanas programmu 2014.-2020. gadam Apvārsnis 2020. Prezentācijā iekļauts arī programmas Apvārsnis 2020 raksturojums un tajā paredzētās prasības zinātnisko rakstu publicēšanai brīvpieejā.
A calcined clay fixed bed adsorption studies for the removal of heavy metals from aqueous solutions
2021
Abstract A natural clay material from southern Tunisia was used as a low cost sorbent in a column-wise removal of metal pollutants. This is fundamentally important for a sustainable wastewater treatment strategy. This work has been performed within the framework of a project aiming to the valorization of natural geomaterials, from Tunisia, in several environmental applications. Column adsorption experiments were carried out for a better production of cleaner effluents and further understanding of the main mechanisms involved in the removal process, through a dynamic methodology, that would allow an industrial scale treatment. A calcined clay sample was used as an adsorbent for the removal o…