Search results for "Machine"
showing 10 items of 2592 documents
Ordered fuzzy rules generation based on incremental dataset
2021
This paper proposes a novel approach for building transparent knowledge-based systems by generating interpretable fuzzy rules that allow for present dependences between quantitative variables by accounting for uncertainty and the dynamics of their values. In the approach, IF-THEN rules are used to show the conditional relationship between the ordered fuzzy numbers, which contain additional information about the tendencies of variables' value changes. This paper elaborates an approach of mining ordered fuzzy rules from numerical data included in an incremental database. This approach develops the ability to record uncertainty and its change in the context of rapidly changing data. In additio…
Application of the Information Bottleneck method to discover user profiles in a Web store
2018
The paper deals with the problem of discovering groups of Web users with similar behavioral patterns on an e-commerce site. We introduce a novel approach to the unsupervised classification of user sessions, based on session attributes related to the user click-stream behavior, to gain insight into characteristics of various user profiles. The approach uses the agglomerative Information Bottleneck (IB) algorithm. Based on log data for a real online store, efficiency of the approach in terms of its ability to differentiate between buying and non-buying sessions was validated, indicating some possible practical applications of the our method. Experiments performed for a number of session sampl…
Automatic evaluation of information provider reliability and expertise
2013
Published version of an article in the journal: World Wide Web. Also available from the publisher at: http://dx.doi.org/10.1007/s11280-013-0249-x Q&A social media have gained a lot of attention during the recent years. People rely on these sites to obtain information due to a number of advantages they offer as compared to conventional sources of knowledge (e.g., asynchronous and convenient access). However, for the same question one may find highly contradicting answers, causing an ambiguity with respect to the correct information. This can be attributed to the presence of unreliable and/or non-expert users. These two attributes (reliability and expertise) significantly affect the quality o…
Damping Provision by Different Virtual Synchronous Machine Schemes
2020
The adoption of virtual synchronous machine (VSM) schemes for the control of power converters is gaining more and more attention both in academia and industry. The VSM control strategies fall into the category of grid-forming converter controls, and they are intended for a range of different applications, providing specific services and different kinds of support to the grid. The paper investigates the possibility of damping provision to the system by VSM power converters. Different schemes are considered and compared, showing the opportunity of the investigated solutions through combined modal and time domain analyses. A specific modification of the power synchronization loop is recognized…
Sensitivity Analysis and Frequency Dynamics of Grid-Connected Converters with Virtual Inertia
2021
For the participation in the frequency control of the system, power converters can be controlled with different strategies and methods, sharing the common concept of virtual inertia capability. In this work, a sensitivity analysis of two main categories of converter controls with virtual inertia is presented. The considered schemes are a grid-following current vector control with additional virtual inertia block and a grid-forming control scheme based on virtual synchronous machine concept. A proper basis for the comparison is first assessed providing an analytical correlation between the control parameters of the two schemes. For the two control strategies, the sensitivity analysis of the …
H&E Multi-Laboratory Staining Variance Exploration with Machine Learning
2022
In diagnostic histopathology, hematoxylin and eosin (H&E) staining is a critical process that highlights salient histological features. Staining results vary between laboratories regardless of the histopathological task, although the method does not change. This variance can impair the accuracy of algorithms and histopathologists’ time-to-insight. Investigating this variance can help calibrate stain normalization tasks to reverse this negative potential. With machine learning, this study evaluated the staining variance between different laboratories on three tissue types. We received H&E-stained slides from 66 different laboratories. Each slide contained kidney, skin, and colon tissue sampl…
Anomaly detection using one-class SVM with wavelet packet decomposition
2011
Anomaly detection has become a popular research topic in the field of machine learning. Support vector machine is one anomaly detection technique and it is coming one the most widely used. In this research, anomaly detection is applied to road condition monitoring, especially pothole detection, using accelerometer data. The proposed concept includes data preprocessing, feature extraction, feature selection and classification. Accelerometer data was first filtered and segmented, after which features were extracted with frequency- and time-domain functions, with genetic programming and with wavelet packet decomposition. A classification model was built using support vector machine and the cal…
Music adviser : emotion-driven music recommendation ecosystem
2017
In respect of the big amounts of music available in the web, people met the problem of choice. From another side, practically unlimited resources can bring us new opportunities in the music context. Efficient data management engines which are smart and self managed are in demand nowadays in the music industry to handle music sources amounts of which are coming towards to infinity continuously. This study demonstrates feasibility of the emotional based personalization of music recommendation system. There is still gap between human and artificial intelligence, robotics do not have intuition and emotions which represent critical point of recommendations. Taking into account significant influe…
Learn to Cache: Machine Learning for Network Edge Caching in the Big Data Era
2018
The unprecedented growth of wireless data traffic not only challenges the design and evolution of the wireless network architecture, but also brings about profound opportunities to drive and improve future networks. Meanwhile, the evolution of communications and computing technologies can make the network edge, such as BSs or UEs, become intelligent and rich in terms of computing and communications capabilities, which intuitively enables big data analytics at the network edge. In this article, we propose to explore big data analytics to advance edge caching capability, which is considered as a promising approach to improve network efficiency and alleviate the high demand for the radio resou…
Miten konesydän sykkii? Ruotsalainen Hubotit – melkein ihmisiä ei pelkää kysyä isoja kysymyksiä.
2013
Hubotit - melkein ihmisiä (Äkta Människor, Ruotsi 2011-) tuo pohjoismaiseen televisiofiktioon tieteisfiktion tutut teemat kuten ihmisen ja koneen risteymät sekä kuolemattomuuden. Teknologisen kehityksen takana tieteisfiktiossa piilee usein, ellei jopa aina, kysymyksiä kehityksen vaikutuksesta ihmisyyteen. Myös Hubotit - melkein ihmisiä esittää näitä suuria kysymyksiä: Mitä meille tapahtuu teknologian kehittyessä? Voimmeko muuttua joksikin paremmaksi teknologian avulla, vai onko ihmisyys jotain, jota ei voi teknologian avulla luoda tai laajentaa? Millainen voisi olla ihmismielen, -sydämen ja -sielun ohjelmakoodi? nonPeerReviewed