Ensemble learningIn statistics and machine learning, ensemble methods use multiple learning algorithms to obtain better predictive performance than could be obtained from any of the constituent learning algorithms alone. Unlike a statistical ensemble in statistical mechanics, which is usually infinite, a machine learning ensemble consists of only a concrete finite set of alternative models, but typically allows for much more flexible structure to exist among those alternatives.
Interactive mediaInteractive media normally refers to products and services on digital computer-based systems which respond to the user's actions by presenting content such as text, , animation, video and audio. Since its early conception, various forms of interactive media have emerged with impacts on educational and commercial markets. With the rise of decision-driven media, concerns surround the impacts of cybersecurity and societal distraction. Interactive media is a method of communication in which the output from the media comes from the input of the users.
Rule-based machine learningRule-based machine learning (RBML) is a term in computer science intended to encompass any machine learning method that identifies, learns, or evolves 'rules' to store, manipulate or apply. The defining characteristic of a rule-based machine learner is the identification and utilization of a set of relational rules that collectively represent the knowledge captured by the system. This is in contrast to other machine learners that commonly identify a singular model that can be universally applied to any instance in order to make a prediction.
Cultural diversityCultural diversity is the quality of diverse or different cultures, as opposed to monoculture. It has a variety of meanings in different contexts, sometimes applying to cultural artefacts like music recordings or art works in museums, and sometimes applying to the variety of human cultures or traditions in a specific region, or in the world as a whole. It can also refer to the inclusion of different cultural perspectives in an organization or society.
Expected utility hypothesisThe expected utility hypothesis is a popular concept in economics that serves as a reference guide for decision making when the payoff is uncertain. The theory describes which options rational individuals should choose in a situation with uncertainty, based on their risk aversion. The expected utility hypothesis states an agent chooses between risky prospects by comparing expected utility values (i.e. the weighted sum of adding the respective utility values of payoffs multiplied by their probabilities).
Anomaly detectionIn data analysis, anomaly detection (also referred to as outlier detection and sometimes as novelty detection) is generally understood to be the identification of rare items, events or observations which deviate significantly from the majority of the data and do not conform to a well defined notion of normal behaviour. Such examples may arouse suspicions of being generated by a different mechanism, or appear inconsistent with the remainder of that set of data.
Virtual assistantA virtual assistant (VA) is a software agent that can perform a range of tasks or services for a user based on user input such as commands or questions, including verbal ones. Such technologies often incorporate chatbot capabilities to simulate human conversation, such as via online chat, to facilitate interaction with their users. The interaction may be via text, graphical interface, or voice - as some virtual assistants are able to interpret human speech and respond via synthesized voices.
Location awarenessLocation awareness refers to devices that can passively or actively determine their location. Navigational instruments provide location coordinates for vessels and vehicles. Surveying equipment identifies location with respect to a well-known location wireless communications device. The term applies to navigating, real-time locating and positioning support with global, regional or local scope. The term has been applied to traffic, logistics, business administration and leisure applications.
Generalized linear mixed modelIn statistics, a generalized linear mixed model (GLMM) is an extension to the generalized linear model (GLM) in which the linear predictor contains random effects in addition to the usual fixed effects. They also inherit from GLMs the idea of extending linear mixed models to non-normal data. GLMMs provide a broad range of models for the analysis of grouped data, since the differences between groups can be modelled as a random effect. These models are useful in the analysis of many kinds of data, including longitudinal data.
COVID-19 pandemicThe COVID-19 pandemic, also known as the coronavirus pandemic, is a global pandemic of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The novel virus was first identified in an outbreak in the Chinese city of Wuhan in December 2019. Attempts to contain it there failed, allowing the virus to spread to other areas of Asia and later worldwide in 2020. The World Health Organization (WHO) declared the outbreak a public health emergency of international concern (PHEIC) on 30 January 2020.
Augmented realityAugmented reality (AR) is an interactive experience that combines the real world and computer-generated content. The content can span multiple sensory modalities, including visual, auditory, haptic, somatosensory and olfactory. AR can be defined as a system that incorporates three basic features: a combination of real and virtual worlds, real-time interaction, and accurate 3D registration of virtual and real objects. The overlaid sensory information can be constructive (i.e. additive to the natural environment), or destructive (i.
