Search results for "koneoppiminen"

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…

Channel Increment Strategy-Based 1D Convolutional Neural Networks for Seizure Prediction Using Intracranial EEG

2022

The application of intracranial electroencephalogram (iEEG) to predict seizures remains challenging. Although channel selection has been utilized in seizure prediction and detection studies, most of them focus on the combination with conventional machine learning methods. Thus, channel selection combined with deep learning methods can be further analyzed in the field of seizure prediction. Given this, in this work, a novel iEEG-based deep learning method of One-Dimensional Convolutional Neural Networks (1D-CNN) combined with channel increment strategy was proposed for the effective seizure prediction. First, we used 4-sec sliding windows without overlap to segment iEEG signals. Then, 4-sec …

Terveydenhuollon alustat ja tekoäly

2018

IBM-teknologioiden hyödyntäminen terveydenhuollossa

2018

Finnish 5th and 6th grade students' pre-instructional conceptions of artificial intelligence (AI) and their implications for AI literacy education

2022

In the present paper, we report the findings of a qualitative survey study of 195 Finnish 5th and 6th grade students' pre-instructional conceptions of artificial intelligence (AI). An exploration of these initial conceptions provides insight into students' preliminary understanding of the topic and informs curriculum designers and teachers about misconceptions that might jeopardize student learning. The findings suggest that students' initial conceptions of AI are varied and often uninformed. For instance, references to the role of data in training AI applications were practically nonexistent. Instead, AI was often described as an anthropomorphic technology that possesses cognitive qualitie…

Oppiva tekoäly syvien neuroverkkojen avulla

2017

Tämä työ on toteutettu kirjallisuuskatsauksena. Tavoitteena oli selvittää neuroverkkopohjaisen tekoälyn toteutustavoista ja sen käyttötarkoituksista kuinka siitä voi tehdä oppivan. Löytämieni artikkeleiden perusteella oppiva tekoäly on mahdollinen hyvinkin monimutkaisille ongelmille, mutta rajoittava tekijä on laajuus. This work is done as literature review. The aim was to find out how to implement the neural network-based artificial intelligence and its uses. Based on the articles I found, learning artificial intelligence is possible for very complex problems, but the limiting factor is the scope.

Feature extraction for supervised learning in knowledge discovery systems

2005

Tiedon louhinnalla pyritään paljastamaan tietokannasta tietomassaan sisältyviä säännönmukaisuuksia, joiden olemassaolosta ei vielä olla tietoisia. Kun tietokantaan sisältyvät tiedot ovat kovin moniulotteisia, yksittäisten tapausten sisältäessä lukuisia piirteitä, monen koneoppimisen menetelmän suorituskyky heikkenee ratkaisevasti. Tätä ilmiötä nimitetään ”moniulotteisuuden kiroukseksi”, koska se johtaa usein sekä koneellisen käsittelyn monimutkaisuuden että käsittelyn yhteydessä syntyvien luokitusvirheiden kasvuun. Toisaalta tietokantaan mahdollisesti sisältyvät epärelevantit tai vain epäsuorasti relevantit piirteet tarjoavat heikon esitysavaruuden tietokannan käsiterakenteen kuvaamiseen. P…

Tiedon louhinta myynnin, markkinoinnin ja asiakkuuksien hallinnassa

2001

Hybrid vibration signal monitoring approach for rolling element bearings

2019

New approach to identify different lifetime stages of rolling element bearings, to improve early bearing fault detection, is presented. We extract characteristic features from vibration signals generated by rolling element bearings. This data is first pre-labelled with an unsupervised clustering method. Then, supervised methods are used to improve the labelling. Moreover, we assess feature importance with each classifier. From the practical point of view, the classifiers are compared on how early emergence of a bearing fault is being suggested. The results show that all of the classifiers are usable for bearing fault detection and the importance of the features was consistent. peerReviewed

Radio frequency fingerprinting for outdoor user equipment localization

2017

The recent advancements in cellular mobile technology and smart phone usage have opened opportunities for researchers and commercial companies to develop ubiquitous low cost localization systems. Radio frequency (RF) fingerprinting is a popular positioning technique which uses radio signal strength (RSS) values from already existing infrastructures to provide satisfactory user positioning accuracy in indoor and densely built outdoor urban areas where Global Navigation Satellite System (GNSS) signal is poor and hard to reach. However a major requirement for the RF fingerprinting to maintain good localization accuracy is the collection and updating of large training database. The Minimization…