Group emotionGroup emotion refers to the moods, emotions and dispositional affects of a group of people. It can be seen as either an emotional entity influencing individual members' emotional states (top down) or the sum of the individuals' emotional states (bottom up). This view sees the group's dynamic processes as responsible for an elusive feeling state which influences the members' feelings and behavior. This view, that groups have an existence as entities beyond the characters that comprise them, has several angles.
Affective neuroscienceAffective neuroscience is the study of how the brain processes emotions. This field combines neuroscience with the psychological study of personality, emotion, and mood. The basis of emotions and what emotions are remains an issue of debate within the field of affective neuroscience. The term "affective neuroscience" was coined by neuroscientist Jaak Panksepp, at a time when cognitive neuroscience focused on parts of psychology that did not include emotion, such as attention or memory.
Affect control theoryIn control theory, affect control theory proposes that individuals maintain affective meanings through their actions and interpretations of events. The activity of social institutions occurs through maintenance of culturally based affective meanings. Besides a denotative meaning, every concept has an affective meaning, or connotation, that varies along three dimensions: evaluation – goodness versus badness, potency – powerfulness versus powerlessness, and activity – liveliness versus torpidity.
Physical neural networkA physical neural network is a type of artificial neural network in which an electrically adjustable material is used to emulate the function of a neural synapse or a higher-order (dendritic) neuron model. "Physical" neural network is used to emphasize the reliance on physical hardware used to emulate neurons as opposed to software-based approaches. More generally the term is applicable to other artificial neural networks in which a memristor or other electrically adjustable resistance material is used to emulate a neural synapse.
Speech recognitionSpeech recognition is an interdisciplinary subfield of computer science and computational linguistics that develops methodologies and technologies that enable the recognition and translation of spoken language into text by computers. It is also known as automatic speech recognition (ASR), computer speech recognition or speech to text (STT). It incorporates knowledge and research in the computer science, linguistics and computer engineering fields. The reverse process is speech synthesis.
Facial recognition systemA facial recognition system is a technology potentially capable of matching a human face from a or a video frame against a database of faces. Such a system is typically employed to authenticate users through ID verification services, and works by pinpointing and measuring facial features from a given image. Development began on similar systems in the 1960s, beginning as a form of computer application. Since their inception, facial recognition systems have seen wider uses in recent times on smartphones and in other forms of technology, such as robotics.
Digital audioDigital audio is a representation of sound recorded in, or converted into, digital form. In digital audio, the sound wave of the audio signal is typically encoded as numerical samples in a continuous sequence. For example, in CD audio, samples are taken 44,100 times per second, each with 16-bit sample depth. Digital audio is also the name for the entire technology of sound recording and reproduction using audio signals that have been encoded in digital form.
Aneutronic fusionAneutronic fusion is any form of fusion power in which very little of the energy released is carried by neutrons. While the lowest-threshold nuclear fusion reactions release up to 80% of their energy in the form of neutrons, aneutronic reactions release energy in the form of charged particles, typically protons or alpha particles. Successful aneutronic fusion would greatly reduce problems associated with neutron radiation such as damaging ionizing radiation, neutron activation, reactor maintenance, and requirements for biological shielding, remote handling and safety.
Theory of constructed emotionThe theory of constructed emotion (formerly the conceptual act model of emotion) is a theory in affective science proposed by Lisa Feldman Barrett to explain the experience and perception of emotion. The theory posits that instances of emotion are constructed predictively by the brain in the moment as needed. It draws from social construction, psychological construction, and neuroconstruction.
Video codecA video codec is software or hardware that compresses and decompresses digital video. In the context of video compression, codec is a portmanteau of encoder and decoder, while a device that only compresses is typically called an encoder, and one that only decompresses is a decoder. The compressed data format usually conforms to a standard video coding format. The compression is typically lossy, meaning that the compressed video lacks some information present in the original video.
Inertial confinement fusionInertial confinement fusion (ICF) is a fusion energy process that initiates nuclear fusion reactions by compressing and heating targets filled with fuel. The targets are small pellets, typically containing deuterium (2H) and tritium (3H). Energy is deposited in the target's outer layer, which explodes outward. This produces a reaction force in the form of shock waves that travel through the target. The waves compress and heat it. Sufficiently powerful shock waves generate fusion.
Predictive codingIn neuroscience, predictive coding (also known as predictive processing) is a theory of brain function which postulates that the brain is constantly generating and updating a "mental model" of the environment. According to the theory, such a mental model is used to predict input signals from the senses that are then compared with the actual input signals from those senses. With the rising popularity of representation learning, the theory is being actively pursued and applied in machine learning and related fields.
