Search results for "SAMPLE"
showing 10 items of 2270 documents
Exemplification and Exemplars, Effects of
2008
The term “exemplification effect” describes the influence of illustrating and aggregating case descriptions in media presentations on the recipients' perceptions of issues. Aggregating case descriptions emerges whenever media coverage presents any kind of generalizing claim about natural or social phenomena and an arbitrarily selected sample of single cases to illustrate the issue at hand. General claims (e.g., “growing poverty in society”) often are supported by presenting quantitative information (so-called “base-rate information”) about a large number of cases (e.g., statistics about poverty; Statistics, Descriptive). Keywords: Communication Reception and Effects; Persuasion and Social …
Exopeptidase digestion in combination with field desorption mass spectrometry for amino acid sequence determination
1982
Numerous studies have been devoted in the last years to the development of mass spectrometric methods for the sequence determination of peptides [ 1,2]. Most advanced among this work has been so far the rigorous chemical derivatization of oligopeptides to achieve sufficient volatility for the application of conventional (electron impact, EI) mass spectrometry [2-41. For example, the analysis by gas chromatography-mass spectrometry (GC-MS) of mixtures of oligopeptide fragments derivatized after chemical or enzymatic hydrolysis of polypeptides has been successfully used for sequence determinations [2,5]. Major limitations of this approach are that only small peptide derivatives are amenable t…
Situational expectancies and task values: Associations with students' effort
2017
Abstract According to expectancy-value theory, expectancies and task values are precursors for investing effort into learning. To date, it remains largely unknown (1) to what extent expectancies and values change from one learning situation to another and (2) to what extent inter-individual findings reflect intra-individual motivational processes. We applied an intensive longitudinal design in a sample of 155 pre-service teacher students attending a lecture. Across ten lessons with varying topics, students reported three times per lesson on their situational effort, expectancies, task values (intrinsic, attainment, utility), and cost. We used multilevel structural equation modeling with lea…
A probabilistic estimation and prediction technique for dynamic continuous social science models: The evolution of the attitude of the Basque Country…
2015
In this paper, a computational technique to deal with uncertainty in dynamic continuous models in Social Sciences is presented.Considering data from surveys,the method consists of determining the probability distribution of the survey output and this allows to sample data and fit the model to the sampled data using a goodness-of-fit criterion based the χ2-test. Taking the fitted parameters that were not rejected by the χ2-test, substituting them into the model and computing their outputs, 95% confidence intervals in each time instant capturing the uncertainty of the survey data (probabilistic estimation) is built. Using the same set of obtained model parameters, a prediction over …
Helminth Microbiota Profiling Using Bacterial 16S rRNA Gene Amplicon Sequencing: From Sampling to Sequence Data Mining
2021
Symbiont microbial communities play important roles in animal biology and are thus considered integral components of metazoan organisms, including parasitic worms (helminths). Nevertheless, the study of helminth microbiomes has thus far been largely overlooked, and symbiotic relationships between helminths and their microbiomes have been only investigated in selected parasitic worms. Over the past decade, advances in next-generation sequencing technologies, coupled with their increased affordability, have spurred investigations of helminth-associated microbial communities aiming at enhancing current understanding of their fundamental biology and physiology, as well as of host-microbe intera…
Towards the evaluation of automatic simultaneous speech translation from a communicative perspective
2021
In recent years, automatic speech-to-speech and speech-to-text translation has gained momentum thanks to advances in artificial intelligence, especially in the domains of speech recognition and machine translation. The quality of such applications is commonly tested with automatic metrics, such as BLEU, primarily with the goal of assessing improvements of releases or in the context of evaluation campaigns. However, little is known about how the output of such systems is perceived by end users or how they compare to human performances in similar communicative tasks. In this paper, we present the results of an experiment aimed at evaluating the quality of a real-time speech translation engine…
A Review of Multiple Try MCMC algorithms for Signal Processing
2018
Many applications in signal processing require the estimation of some parameters of interest given a set of observed data. More specifically, Bayesian inference needs the computation of {\it a-posteriori} estimators which are often expressed as complicated multi-dimensional integrals. Unfortunately, analytical expressions for these estimators cannot be found in most real-world applications, and Monte Carlo methods are the only feasible approach. A very powerful class of Monte Carlo techniques is formed by the Markov Chain Monte Carlo (MCMC) algorithms. They generate a Markov chain such that its stationary distribution coincides with the target posterior density. In this work, we perform a t…
The entrepreneurial logic of startup software development : A study of 40 software startups
2021
Context: Software startups are an essential source of innovation and software-intensive products. The need to understand product development in startups and to provide relevant support are highlighted in software research. While state-of-the-art literature reveals how startups develop their software, the reasons why they adopt these activities are underexplored. Objective: This study investigates the tactics behind software engineering (SE) activities by analyzing key engineering events during startup journeys. We explore how entrepreneurial mindsets may be associated with SE knowledge areas and with each startup case. Method: Our theoretical foundation is based on causation and effectuatio…
Order-distance and other metric-like functions on jointly distributed random variables
2013
We construct a class of real-valued nonnegative binary functions on a set of jointly distributed random variables, which satisfy the triangle inequality and vanish at identical arguments (pseudo-quasi-metrics). These functions are useful in dealing with the problem of selective probabilistic causality encountered in behavioral sciences and in quantum physics. The problem reduces to that of ascertaining the existence of a joint distribution for a set of variables with known distributions of certain subsets of this set. Any violation of the triangle inequality or its consequences by one of our functions when applied to such a set rules out the existence of this joint distribution. We focus on…
Parsimonious adaptive rejection sampling
2017
Monte Carlo (MC) methods have become very popular in signal processing during the past decades. The adaptive rejection sampling (ARS) algorithms are well-known MC technique which draw efficiently independent samples from univariate target densities. The ARS schemes yield a sequence of proposal functions that converge toward the target, so that the probability of accepting a sample approaches one. However, sampling from the proposal pdf becomes more computationally demanding each time it is updated. We propose the Parsimonious Adaptive Rejection Sampling (PARS) method, where an efficient trade-off between acceptance rate and proposal complexity is obtained. Thus, the resulting algorithm is f…