Search results for "LEARNING"

On Assessing Vulnerabilities of the 5G Networks to Adversarial Examples

2022

The use of artificial intelligence and machine learning is recognized as the key enabler for 5G mobile networks which would allow service providers to tackle the network complexity and ensure security, reliability and allocation of the necessary resources to their customers in a dynamic, robust and trustworthy way. Dependability of the future generation networks on accurate and timely performance of its artificial intelligence components means that disturbance in the functionality of these components may have negative impact on the entire network. As a result, there is an increasing concern about the vulnerability of intelligent machine learning driven frameworks to adversarial effects. In …

Big high-dimensional data analysis with diffusion maps

2013

High-dimensional Big Data processing with dictionary learning and diffusion maps

2015

Algorithms for modern Big Data analysis deal with both massive amount of sam- ples and a large number of features (high-dimension). One way to cope with these challenges is to assume and discover the existence of localization in the data by uncovering its intrinsic geometry. This approach suggests that different data segments can be analyzed separately and then unified in order to gain an understanding of the whole phenomenon. Methods that utilize efficiently local- ized data are attractive for high-dimensional big data analysis, because they can be parallelized, and thus the computational resources, which are needed for their utilization, are realistic and affordable. These methods can explo…

Agile Deep Learning UAVs Operating in Smart Spaces : Collective Intelligence Versus “Mission-Impossible”

2018

The environments, in which we all live, are known to be complex and unpredictable. The complete discovery of these environments aiming to take full control over them is a “mission-impossible”, however, still in our common agenda. People intend to make their living spaces smarter utilizing innovations from the Internet of Things and Artificial Intelligence. Unmanned aerial vehicles (UAVs) as very dynamic, autonomous and intelligent things capable to discover and control large areas are becoming important “inhabitants” within existing and future smart cities. Our concern in this paper is to challenge the potential of UAVs in situations, which are evolving fast in a way unseen before, e.g., em…

Kernels and Graphs on M25 + H

2023

Codes related to article "Graphs and Kernelized Learning Applied to Interactions of Hydrogen with Doped Gold Nanoparticle Electrocatalysts". There are two main types of codes: codes to transform a catalytic system of protected gold nanoparticle and a single hydrogen atom into a graph-based representation, and codes to run kernel-based machine learning methods to predict interaction energies between the nanoparticle and the hydrogen atom. This is a snapshot of the code dataset that has been taken on 06.06.2023. A more detailed description of the data and the address to the GitLab repository for the latest version of the code can be found from the parent dataset of this data publication.

Kernels and Graphs on M25 + H (parent repository)

2023

The repository contains codes related to article "Graphs and Kernelized Learning Applied to Interactions of Hydrogen with Doped Gold Nanoparticle Electrocatalysts". There are two main types of codes: codes to transform a catalytic system of protected gold nanoparticle and a single hydrogen atom into a graph-based representation, and codes to run kernel-based machine learning methods to predict interaction energies between the nanoparticle and the hydrogen atom. This is the metadata for the parent repository of the codes. Updates and possible corrections are documented in the GitLab project, where the material saved and shared. The GitLab project can be found and downloaded from the followin…

Supplementary data for the article "Machine Learning for Predicting Chemical Potentials of Multifunctional Organic Compounds in Atmospherically Relev…

2022

The data set contains the supplementary data of the article "Machine Learning for Predicting Chemical Potentials of Multifunctional Organic Compounds in Atmospherically Relevant Solutions" published in J. Phys. Chem. Lett., https://doi.org/10.1021/acs.jpclett.2c02612. The data includes: - A machine learning (EMLM) model for predicting chemical potentials of individual conformers of multifunctional organic compounds calculated by the COSMOtherm program - COSMO-files used for training and testing the EMLM model - Descriptors and chemical potentials used for the training and testing the model Artikkelin "Machine Learning for Predicting Chemical Potentials of Multifunctional Organic Compounds i…

Assessment of microalgae species, biomass and distribution from spectral images using a convolution neural network

2021

Artikkeliin "Assessment of microalgae species, biomass and distribution from spectral images using a convolution neural network" liittyvä aineisto koostuu seuraavista osista: 1.Transmittanssi-hyperspektrikuvat levänäytteistä kuvattuina 24-kuoppalevyllä 2.Biomassamääritykset elektronisella solulaskurilla 3.Opetus- ja validointiaineisto konvoluutioneuroverkolle 4.Testiaineisto konvoluutioneuroverkolle 5.Opetus-, validointi- ja testiaineiston käsittelyyn käytetty Python koodi 6.Seitsemään eri malliin käytetty Python koodi ja mallit itsessään The data and code related to the article "Assessment of microalgae species, biomass and distribution from spectral images using a convolution neural netwo…

Anomaly detection in wireless sensor networks

2016

Wireless Sensor Network can be defined as a network of integrated sensors responsible for environmental sensing, data processing and communication with other sensors and the base station while consuming low power. Today, WSNs are being used in almost every part of life. The cost effective nature of WSNs is beneficial for environmental monitoring, production facilities and security monitoring. At the same time WSNs are vulnerable to security breaches, attacks and information leakage. Anomaly detection techniques are used to detect such activities over the network that do not conform to the normal behavior of the network communication. Supervised Machine learning approach is one way to detect…

A case study : teaching conflict awareness in a Finnish lower secondary school

2018

TIIVISTELMÄ Salminen, Tanja. 2018. Tapaustutkimus: Konfliktitietoisuuden ja sovittelun opettaminen suomalaisessa yläkoulussa. Pro-Gradu -tutkielma. Jyväskylän yliopisto. Opettajankoulutuslaitos. 89 sivua. HundrED on suomalainen koulutusalan voittoa tavoittelematon järjestö, jonka tarkoituksena on etsiä ja jakaa tulevaisuuden koulutusinnovaatioita ja pyrkiä muuttamaan maailmaa koulutusta muuttamalla. Crisis Management Initiative (CMI) laati yhdessä HundrEDin kanssa materiaalipaketin, jonka erilaisten harjoitusten avulla yläkouluissa ja lukioissa voidaan opettaa konfliktinratkaisuja sovittelutaitoja. Kokeilun tavoitteena on edistää neutraalia ja faktoihin keskittyvää keskustelua ja tutkia syi…