Computer performanceIn computing, computer performance is the amount of useful work accomplished by a computer system. Outside of specific contexts, computer performance is estimated in terms of accuracy, efficiency and speed of executing computer program instructions. When it comes to high computer performance, one or more of the following factors might be involved: Short response time for a given piece of work. High throughput (rate of processing work). Low utilization of computing resource(s). Fast (or highly compact) data compression and decompression.
Inter-rater reliabilityIn statistics, inter-rater reliability (also called by various similar names, such as inter-rater agreement, inter-rater concordance, inter-observer reliability, inter-coder reliability, and so on) is the degree of agreement among independent observers who rate, code, or assess the same phenomenon. Assessment tools that rely on ratings must exhibit good inter-rater reliability, otherwise they are not valid tests. There are a number of statistics that can be used to determine inter-rater reliability.
Performance engineeringPerformance engineering encompasses the techniques applied during a systems development life cycle to ensure the non-functional requirements for performance (such as throughput, latency, or memory usage) will be met. It may be alternatively referred to as systems performance engineering within systems engineering, and software performance engineering or application performance engineering within software engineering.
Intraclass correlationIn statistics, the intraclass correlation, or the intraclass correlation coefficient (ICC), is a descriptive statistic that can be used when quantitative measurements are made on units that are organized into groups. It describes how strongly units in the same group resemble each other. While it is viewed as a type of correlation, unlike most other correlation measures, it operates on data structured as groups rather than data structured as paired observations.
Time seriesIn mathematics, a time series is a series of data points indexed (or listed or graphed) in time order. Most commonly, a time series is a sequence taken at successive equally spaced points in time. Thus it is a sequence of discrete-time data. Examples of time series are heights of ocean tides, counts of sunspots, and the daily closing value of the Dow Jones Industrial Average. A time series is very frequently plotted via a run chart (which is a temporal line chart).
Gestalt psychologyGestalt psychology, gestaltism, or configurationism is a school of psychology that emerged in the early twentieth century in Austria and Germany as a theory of perception that was a rejection of basic principles of Wilhelm Wundt's and Edward Titchener's elementalist and structuralist psychology. As used in Gestalt psychology, the German word Gestalt (gəˈʃtaelt,-'Stɑːlt,-ˈʃtɔːlt,-ˈstɑːlt,-ˈstɔːlt ɡəˈʃtalt; meaning "form") is interpreted as "pattern" or "configuration".
SaccadeA saccade (səˈkɑːd , French for jerk) is a quick, simultaneous movement of both eyes between two or more phases of fixation in the same direction. In contrast, in smooth pursuit movements, the eyes move smoothly instead of in jumps. The phenomenon can be associated with a shift in frequency of an emitted signal or a movement of a body part or device. Controlled cortically by the frontal eye fields (FEF), or subcortically by the superior colliculus, saccades serve as a mechanism for fixation, rapid eye movement, and the fast phase of optokinetic nystagmus.
Subliminal stimuliSubliminal stimuli (sʌbˈlɪmᵻnəl; sub- literally "below" or "less than") are any sensory stimuli below an individual's threshold for conscious perception, in contrast to supraliminal stimuli (above threshold). A 2012 review of functional magnetic resonance imaging (fMRI) studies showed that subliminal stimuli activate specific regions of the brain despite participants' unawareness. Visual stimuli may be quickly flashed before an individual can process them, or flashed and then masked to interrupt processing.
Least-squares spectral analysisLeast-squares spectral analysis (LSSA) is a method of estimating a frequency spectrum based on a least-squares fit of sinusoids to data samples, similar to Fourier analysis. Fourier analysis, the most used spectral method in science, generally boosts long-periodic noise in the long and gapped records; LSSA mitigates such problems. Unlike in Fourier analysis, data need not be equally spaced to use LSSA.
Informal learningInformal learning is characterized "by a low degree of planning and organizing in terms of the learning context, learning support, learning time, and learning objectives". It differs from formal learning, non-formal learning, and self-regulated learning, because it has no set objective in terms of learning outcomes, but an intent to act from the learner's standpoint (e.g., to solve a problem). Typical mechanisms of informal learning include trial and error or learning-by-doing, modeling, feedback, and reflection.
