Search results for "performance"
showing 10 items of 4457 documents
Extraversion and performance approach goal orientation : An integrative approach to personality
2019
Abstract Research shows that extraversion is unrelated to performance approach goal orientation, both at the trait- and the state-level. However, since previous studies have either focused on the trait- or the state-level, such a conclusion may be premature. Building upon the idea that acting against one’s trait consumes self-control resources, we reason that within-person deviations from one’s level of trait extraversion might negatively relate to performance approach goal orientation. Using experience sampling data from 47 employees across 10 days (N = 307), we found that deviations from one’s trait extraversion levels are associated with lower levels of performance approach goal orientat…
Bayesian forecasting of demand time-series data with zero values
2013
This paper describes the development of a Bayesian procedure to analyse and forecast positive demand time-series data with a proportion of zero values and a high level of variability for the non-zero data. The resulting forecasts play decisive roles in organisational planning, budgeting, and performance monitoring. Exponential smoothing methods are widely used as forecasting techniques in industry and business. However, they can be unsuitable for the analysis of non-negative demand time-series data with the aforementioned features. In this paper, an unconstrained latent demand underlying the observed demand is introduced into the linear heteroscedastic model associated with the Holt-Winters…
Studies of polyamines transport through liquid membranes with D2EHPA as a carrier.
2008
The transport of polyamines through the liquid membranes with di‐2‐ethylhexyl phosphoric acid (D2EHPA) was investigated. The study was performed in three main steps: liquid–liquid extraction (LLE), bulk liquid membrane (BLM) extraction, and supported liquid membrane (SLM) extraction. Equilibrium distribution experiments allowed determining the extraction constants and stoichiometric coefficients for each polyamine. It turned out that one amino group binds two molecules of carrier (one D2EHPA dimer) and the extractability of polyamine rises with the increase in number of function groups in the molecule. The BLM and SLM experiments showed that despite considerable differences in distribution …
Vigor F7 projekta ietekme uz redzes funkcijām
2017
Maģistra darbs ir uzrakstīts angļu valodā uz 38 lapām. Tas satur 12 attēlus, 9 tabulas, 26 atsauces uz literatūras avotiem un 4 pielikumus. Galvenais darba mērķis ir nodemonstrēt F7 ierīces ietekmi uz redzes sistēmu un tās funkcijām. Tika veikti divi eksperimenti: Eksperiments I (30 dalībnieki, 10 – 40 g.v.), lai izvērtētu Vigor F7 ierīces ietekmi uz redzes funkcijām; Eksperiments II (20 dalībnieki, sportisti, 14 – 48 g.v.), lai izvērtētu Vigor F7 ierīces ietekmi uz dinamisko iemaņu efektivitāti. Abos eksperimentos novēroja statistiski nozīmīgi atšķirīgus rezultātus gan redzes funkcijām, gan dinamiskajām iemaņām, ja izmantoja F7 ierīci.
Fenibuta piemaisījumu kvantitatīvas noteikšanas metodes optimizācija un validācija
2021
Kokina. P., zinātniskie vadītāji: Dr. ķīm. V. Bartkevičs (LU), Dr. ķīm. A. Bolotin (AS Olainfarm). Maģistra darbs, 147 lappuses, 184 attēli, 75 tabulas, 15 literatūras avoti, 16 pielikumi. Latviešu valodā. Maģistra darbā ir veikta divu piemaisījumu(4-amino-3-fenilbutānskābes etilestera hidrohlorīds un 4-fenil-2-pirrolidons) kvantitatīvas noteikšanas analīzes metodes optimizācija un validācija farmaceitiskā preperāta Noofen® aktīvajai farmaceitiskai vielai (AFV) fenibuts. Metodes optimizācija un validācija bija nepieciešama farmaceitiskā preparāta Noofen® kvalitātes kontroles vajadzībām. Fenibuta paraugi tika analizēti ar augsti efektīvo šķidruma hromatogrāfiju (AEŠH). Optimizācija tika vērs…
Probing the origin of cosmic-rays with extremely high energy neutrinos using the IceCube Observatory
2013
We have searched for extremely high energy neutrinos using data taken with the IceCube detector between May 2010 and May 2012. Two neutrino induced particle shower events with energies around 1 PeV were observed, as reported previously. In this work, we investigate whether these events could originate from cosmogenic neutrinos produced in the interactions of ultra-high energy cosmic-rays with ambient photons while propagating through intergalactic space. Exploiting IceCube's large exposure for extremely high energy neutrinos and the lack of observed events above 100 PeV, we can rule out the corresponding models at more than 90% confidence level. The model independent quasi-differential 90% …
AnySeq: A High Performance Sequence Alignment Library based on Partial Evaluation
2020
Sequence alignments are fundamental to bioinformatics which has resulted in a variety of optimized implementations. Unfortunately, the vast majority of them are hand-tuned and specific to certain architectures and execution models. This not only makes them challenging to understand and extend, but also difficult to port to other platforms. We present AnySeq - a novel library for computing different types of pairwise alignments of DNA sequences. Our approach combines high performance with an intuitively understandable implementation, which is achieved through the concept of partial evaluation. Using the AnyDSL compiler framework, AnySeq enables the compilation of algorithmic variants that ar…
ASR performance prediction on unseen broadcast programs using convolutional neural networks
2018
In this paper, we address a relatively new task: prediction of ASR performance on unseen broadcast programs. We first propose an heterogenous French corpus dedicated to this task. Two prediction approaches are compared: a state-of-the-art performance prediction based on regression (engineered features) and a new strategy based on convolutional neural networks (learnt features). We particularly focus on the combination of both textual (ASR transcription) and signal inputs. While the joint use of textual and signal features did not work for the regression baseline, the combination of inputs for CNNs leads to the best WER prediction performance. We also show that our CNN prediction remarkably …
Analyzing Learned Representations of a Deep ASR Performance Prediction Model
2018
This paper addresses a relatively new task: prediction of ASR performance on unseen broadcast programs. In a previous paper, we presented an ASR performance prediction system using CNNs that encode both text (ASR transcript) and speech, in order to predict word error rate. This work is dedicated to the analysis of speech signal embeddings and text embeddings learnt by the CNN while training our prediction model. We try to better understand which information is captured by the deep model and its relation with different conditioning factors. It is shown that hidden layers convey a clear signal about speech style, accent and broadcast type. We then try to leverage these 3 types of information …
Sparsity-Driven Digital Terrain Model Extraction
2020
We here introduce an automatic Digital Terrain Model (DTM) extraction method. The proposed sparsity-driven DTM extractor (SD-DTM) takes a high-resolution Digital Surface Model (DSM) as an input and constructs a high-resolution DTM using the variational framework. To obtain an accurate DTM, an iterative approach is proposed for the minimization of the target variational cost function. Accuracy of the SD-DTM is shown in a real-world DSM data set. We show the efficiency and effectiveness of the approach both visually and quantitatively via residual plots in illustrative terrain types.