Search results for "iho"
showing 10 items of 2277 documents
Robustness, Stability, and Fidelity of Explanations for a Deep Skin Cancer Classification Model
2022
Skin cancer is one of the most prevalent of all cancers. Because of its being widespread and externally observable, there is a potential that machine learning models integrated into artificial intelligence systems will allow self-screening and automatic analysis in the future. Especially, the recent success of various deep machine learning models shows promise that, in the future, patients could self-analyse their external signs of skin cancer by uploading pictures of these signs to an artificial intelligence system, which runs such a deep learning model and returns the classification results. However, both patients and dermatologists, who might use such a system to aid their work, need to …
El viaje desde los cuestionarios Likert a los cuestionarios de elección forzosa: evidencia de la invarianza de los parámetros de los ítems
2019
Multidimensional forced-choice questionnaires are widely regarded in the personnel selection literature for their ability to control response biases. Recently developed IRT models usually rely on the assumption that item parameters remain invariant when they are paired in forced-choice blocks, without giving it much consideration. This study aims to test this assumption empirically on the MUPP-2PL model, comparing the parameter estimates of the forced-choice format to their graded-scale equivalent on a Big Five personality instrument. The assumption was found to hold reasonably well, especially for the discrimination parameters. In the cases in which it was violated, we briefly discuss the …
Testing Ikonos and Landsat 7 ETM+ Potential for Stand-Level Forest Type Mapping by Soft Supervised Approaches
2003
Forest types can be adopted as a suitable reference for classifying survey units within multipurpose forest resources inventories, at the properly considered level. This kind of hierarchical classification approach integrates an ecologically meaningful per-habitat perspective with practical survey, planning and management requirements. Advanced remote sensing technologies can be valuable tools for a cost-effective implementation of such an approach. In the present paper, data from high (Landsat 7 ETM+) and very high (Ikonos) spatial resolution satellite sensors were tested to understand their potential contribution supporting stand-level forest type mapping under Mediterranean conditions. I…
Gaisa aerosolu daļiņu mērījumi iekštelpās un āra vidē
2016
Gaisa aerosolu daļiņu mērījumi iekštelpās un āra vidē. Ivanovs V., zinātniskā vadītāja Doc., Dr. ķīm. Osīte A. Bakalaura darbs, 36 lappuses, 19 attēli, 0 tabulas, 27 literatūras avoti. Darbs uzrakstīts latviešu valodā. Literatūras apskatā ir apkopota literatūra par gaisa piesārņojumu, aerosola daļiņu, tas veidošanas avotiem un analīzes metodēm. Veikti gaisa aerosolu koncentrāciju mērījumi, izmantojot putekļu monitoru Grimm EDM107. Aerosolu koncentrāciju mērījumi bija veikti iekštelpās un āra vidē raksturojot dažādu sadzīvē pielietotu degšanas procesu rezultātā radušos aerosolu daļiņu koncentrācijas. Kā arī bija veikta Rīgas pilsētvidē ņemtu aerosolu analīze ar induktīvi saistītās plazmas ma…
Pašvadīta koučinga ietekme uz darba pašefektivitāti
2018
Pētījuma “Pašvadīta koučinga ietekme uz darba pašefektivitāti” mērķis bija noskaidrot pašvadīta koučinga ietekmi uz darba pašefektivitāti un tās saistību ar pamata pašnovērtējumu un gatavību mainīties. Pētījumā pieteicās 176 dalībnieki, kuri randomizēti tika iedalīti eksperimentālā un kontroles grupā ar mērķi paaugstināt dalībnieku darba pašefektivitāti vai laimes izjūtu. Tika veikti divi darba pašefektivitātes, pamata pašnovērtējuma un gatavības mainīties mērījumi. Otro mērījumu veica 75 dalībnieki. Pētījuma rezultāti norāda, ka neatkarīgi no dalības grupā, četru nedēļu pašvadīta koučinga programma paaugstina darba pašefektivitāti un norāda uz pozitīvu saistību starp darba pašefektivitāti,…
Model selection for penalized Gaussian Graphical Models
2013
High-dimensional data refers to the case in which the number of parameters is of one or more order greater than the sample size. Penalized Gaussian graphical models can be used to estimate the conditional independence graph in high-dimensional setting. In this setting, the crucial issue is to select the tuning parameter which regulates the sparsity of the graph. In this paper, we focus on estimating the "best" tuning parameter. We propose to select this tuning parameter by minimizing an information criterion based on the generalized information criterion and to use a stability selection approach in order to obtain a more stable graph. The performance of our method is compared with the state…
Detection of Signals in MC–CDMA Using a Novel Iterative Block Decision Feedback Equalizer
2022
This paper presents a technique to mitigate multiple access interference (MAI) in multicarrier code division multiple access (MC-CDMA) wireless communications systems. Although under normal circumstances the MC-CDMA system can achieve high spectral efficiency and resistance towards inter symbol interference (ISI) however when exposed to substantial nonlinear distortion the issue of MAI manifests. Such distortion results when the power amplifiers are driven into saturation or when the transmit signal experiences extreme adverse channel conditions. The proposed technique uses a modified iterative block decision feedback equalizer (IB-DFE) that uses a minimal mean square error (MMSE) receiver …
Model averaging estimation of generalized linear models with imputed covariates
2015
a b s t r a c t We address the problem of estimating generalized linear models when some covariate values are missing but imputations are available to fill-in the missing values. This situation generates a bias-precision trade- off in the estimation of the model parameters. Extending the generalized missing-indicator method proposed by Dardanoni et al. (2011) for linear regression, we handle this trade-off as a problem of model uncertainty using Bayesian averaging of classical maximum likelihood estimators (BAML). We also propose a block model averaging strategy that incorporates information on the missing-data patterns and is computationally simple. An empirical application illustrates our…
The ITS-2 of the nuclear rDNA as a molecular marker for populations, species, and phylogenetic relationships in Triatominae (Hemiptera: Reduviidae), …
2001
The nucleotide sequences of the rDNA second internal transcribed spacer (ITS-2) of 31 populations of 12 and 3 species of the two main Triatominae tribes Triatomini and Rhodniini, including the most important Chagas disease vectors, were obtained. Sequence comparisons and parsimony, distance, and maximum-likelihood analyses indicate that ITS-2 is a useful marker for resolving supraspecific, specific, subspecific, and even sometimes population-level relationships in Triatominae. Results were markedly different between species of Triatomini and Rhodniini, suggesting polyphyly. Phylogenetic trees support an old divergence between South American and North-Central American Triatomini and query th…
Phylogenetics of Anthyllis (Leguminosae: Papilionoideae: Loteae): Partial incongruence between nuclear and plastid markers, a long branch problem and…
2010
Abstract Phylogenetic relationships in the genus Anthyllis (Leguminosae: Papilionoideae: Loteae) were investigated using data from the nuclear ribosomal internal transcribed spacer regions (ITS) and three plastid regions (psbA–trnH intergenic spacer, petB–petD region and rps16 intron). Bayesian and maximum parsimony (MP) analysis of a concatenated plastid dataset recovered well-resolved trees that are topologically similar, with many clades supported by unique indels. MP and Bayesian analyses of the ITS sequence data recovered trees that have several well-supported topological differences, both among analyses, and to trees inferred from the plastid data. The most substantial of these concer…