Search results for "link"

showing 10 items of 1973 documents

Scalable Hierarchical Clustering: Twister Tries with a Posteriori Trie Elimination

2015

Exact methods for Agglomerative Hierarchical Clustering (AHC) with average linkage do not scale well when the number of items to be clustered is large. The best known algorithms are characterized by quadratic complexity. This is a generally accepted fact and cannot be improved without using specifics of certain metric spaces. Twister tries is an algorithm that produces a dendrogram (i.e., Outcome of a hierarchical clustering) which resembles the one produced by AHC, while only needing linear space and time. However, twister tries are sensitive to rare, but still possible, hash evaluations. These might have a disastrous effect on the final outcome. We propose the use of a metaheuristic algor…

ta113Theoretical computer scienceBrown clusteringComputer scienceCorrelation clusteringSingle-linkage clusteringHierarchical clusteringCURE data clustering algorithmhierrchial clusteringCanopy clustering algorithmHierarchical clustering of networksCluster analysisclustering2015 IEEE Symposium Series on Computational Intelligence
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Biased graph walks for RDF graph embeddings

2017

Knowledge Graphs have been recognized as a valuable source for background information in many data mining, information retrieval, natural language processing, and knowledge extraction tasks. However, obtaining a suitable feature vector representation from RDF graphs is a challenging task. In this paper, we extend the RDF2Vec approach, which leverages language modeling techniques for unsupervised feature extraction from sequences of entities. We generate sequences by exploiting local information from graph substructures, harvested by graph walks, and learn latent numerical representations of entities in RDF graphs. We extend the way we compute feature vector representations by comparing twel…

ta113graph embeddingsGraph kernelComputer scienceVoltage graphComparability graphdata mining02 engineering and technologycomputer.software_genre020204 information systemsyhdistetty avoin tietolinked open data0202 electrical engineering electronic engineering information engineeringTopological graph theoryGraph (abstract data type)020201 artificial intelligence & image processingData miningtiedonlouhintaGraph propertyNull graphLattice graphavoin tietocomputerProceedings of the 7th International Conference on Web Intelligence, Mining and Semantics
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Effects of Temperature and Humidity on Radio Signal Strength in Outdoor Wireless Sensor Networks

2015

Many wireless sensor networks operating outdoors are exposed to changing weather conditions, which may cause severe degradation in system performance. Therefore, it is essential to explore the factors affecting radio link quality in order to mitigate their impact and to adapt to varying conditions. In this paper, we study the effects of temperature and humidity on radio signal strength in outdoor wireless sensor networks. Experimental measurements were performed using Atmel ZigBit 2.4GHz wireless modules, both in summer and wintertime. We employed all the radio channels specified by IEEE 802.15.4 for 2.4GHz ISM frequency band with two transmit power levels. The results show that changes in …

ta113ta213radio signal strengthComputer scienceFrequency bandbusiness.industryRadio Link ProtocolhumiditytemperatureTransmitter power outputTemperature measurementlaw.inventionlawMobile wireless sensor networkElectronic engineeringWirelesslämpötilaTelecommunicationsbusinesswireless sensor networksWireless sensor networkDiversity scheme
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Higher-order Nonnegative CANDECOMP/PARAFAC Tensor Decomposition Using Proximal Algorithm

2019

Tensor decomposition is a powerful tool for analyzing multiway data. Nowadays, with the fast development of multisensor technology, more and more data appear in higherorder (order > 4) and nonnegative form. However, the decomposition of higher-order nonnegative tensor suffers from poor convergence and low speed. In this study, we propose a new nonnegative CANDECOM/PARAFAC (NCP) model using proximal algorithm. The block principal pivoting method in alternating nonnegative least squares (ANLS) framework is employed to minimize the objective function. Our method can guarantee the convergence and accelerate the computation. The results of experiments on both synthetic and real data demonstrate …

ta113ta213signaalinkäsittelyComputationproximal algorithmnonnegative CAN-DECOMP/PARAFACalternating nonnegative least squares010103 numerical & computational mathematics01 natural sciencesLeast squares03 medical and health sciences0302 clinical medicinetensor decompositionblock principal pivotingConvergence (routing)Decomposition (computer science)Tensor decompositionOrder (group theory)0101 mathematicsMulti way analysisAlgorithm030217 neurology & neurosurgeryBlock (data storage)Mathematics
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Towards Mitigating the Impact of UAVs on Cellular Communications

2018

The next generation of Unmanned Aerial Vehicles (UAVs) will rely on mobile networks as a communication infrastructure. Several issues need to be addressed to enable the expected potentials from this communication. In particular, it was demonstrated that flying UAVs perceive a high number of base stations (BSs), consequently causing more interferences on non-serving BSs. This unfortunately results in decreased throughput for ground user equipments (UEs) already connected. Such a problem could be a limiting factor for mobile network-enabled UAVs, due to its consequences on the quality of experience (QoE) of served UEs. This underpins the focus of this article, wherein the effect of UAVs' comm…

ta213Computer scienceDistributed computing05 social sciencesComputerApplications_COMPUTERSINOTHERSYSTEMS050801 communication & media studies020206 networking & telecommunicationsThroughput02 engineering and technologyCellular communicationBase station0508 media and communicationsModels of communicationTelecommunications link0202 electrical engineering electronic engineering information engineeringCellular networkPath lossQuality of experience2018 IEEE Global Communications Conference (GLOBECOM)
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Yritysten taidekokoelmat Suomessa : keräilypolitiikat, taiteen esittämisen käytännöt ja merkitykset elinkeinoelämässä

2015

taiteentutkimuskuvataidekulttuuricollectors and collecting theorytaideohjelmatmarkkinointiviestintäyritysten vapaaehtoinen sosiaalinen yhteiskuntavastuukuvataideart historyyrityskokoelmatcorporate artSuomikeräilyyritysyhteistyötaidejärjestelmäelinkeinoelämätaidekokoelmatkuvanveistocorporate social responsibilityyhteiskuntavastuuyrityskuvapatronagekulttuurinen pääomayritystaidecorporate support for the artscultural heritagesemi-public collectionsinstitutionalismiinstitutionaalinen taideteoriayrityksetmaalaustaidecollectingtaidelaitoksetbränditmesenaatittaidehistoriakuvataiteen tukeminentaiteen tukeminenprofessions
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Deriving electrophysiological brain network connectivity via tensor component analysis during freely listening to music

2020

Recent studies show that the dynamics of electrophysiological functional connectivity is attracting more and more interest since it is considered as a better representation of functional brain networks than static network analysis. It is believed that the dynamic electrophysiological brain networks with specific frequency modes, transiently form and dissolve to support ongoing cognitive function during continuous task performance. Here, we propose a novel method based on tensor component analysis (TCA), to characterize the spatial, temporal, and spectral signatures of dynamic electrophysiological brain networks in electroencephalography (EEG) data recorded during free music-listening. A thr…

tensor decompositionQuantitative Biology::Neurons and CognitionComputer Science::Soundsignaalinkäsittelyfrequency-specific brain connectivitymusiikkifreely listening to musicoscillatory coherenceelectroencephalography (EEG)EEGkuunteleminen
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Sparse nonnegative tensor decomposition using proximal algorithm and inexact block coordinate descent scheme

2021

Nonnegative tensor decomposition is a versatile tool for multiway data analysis, by which the extracted components are nonnegative and usually sparse. Nevertheless, the sparsity is only a side effect and cannot be explicitly controlled without additional regularization. In this paper, we investigated the nonnegative CANDECOMP/PARAFAC (NCP) decomposition with the sparse regularization item using l1-norm (sparse NCP). When high sparsity is imposed, the factor matrices will contain more zero components and will not be of full column rank. Thus, the sparse NCP is prone to rank deficiency, and the algorithms of sparse NCP may not converge. In this paper, we proposed a novel model of sparse NCP w…

tensor decompositionsignaalinkäsittelyproximal algorithmalgoritmitMathematicsofComputing_NUMERICALANALYSISinexact block coordinate descentsparse regularizationnonnegative CANDECOMP/PARAFAC decomposition
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Ylivieskalaisten nuorten tupakointi ja päihteidenkäyttö ja niihin liittyvä terveyskasvatus yläasteella

1997

terveyskasvatustupakointialkoholinkäyttöpäihteidenkäyttö
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Porilaisten yhdeksäsluokkalaisten ja kasvattajien käsityksiä nuorten alkoholinkäytöstä ja alkoholinkäytön ehkäisystä

2004

Views of ninth graders, educators and parents in Pori, Finland on adolescent alcohol use and on preventing alcohol useThe purpose of this research was to examine, first, alcohol use by ninth grade comprehensive school students as part of adolescent culture and, second, health promotion related to preventing alcohol use as described by adolescents themselves, their parents, teachers and school nurses. For the purposes of this study, the availability of alcohol, attitudes, causes and effects concerning alcohol use as well as preventing alcohol use constituted alcohol use. The research goal was to obtain extensive background information to prepare recommendations for a strategy to prevent adol…

terveyskasvatusvanhemmatnuoreteducationehkäisykäsityksetnuorisokulttuuriPorikoululaisetalkoholinkäyttöalkoholikäyttö
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