Workflow engineA workflow engine is a software application that manages business processes. It is a key component in workflow technology and typically makes use of a database server. A workflow engine manages and monitors the state of activities in a workflow, such as the processing and approval of a loan application form, and determines which new activity to transition to according to defined processes (workflows). The actions may be anything from saving an application form in a document management system to sending a reminder e-mail to users or escalating overdue items to management.
Signal-to-noise ratioSignal-to-noise ratio (SNR or S/N) is a measure used in science and engineering that compares the level of a desired signal to the level of background noise. SNR is defined as the ratio of signal power to noise power, often expressed in decibels. A ratio higher than 1:1 (greater than 0 dB) indicates more signal than noise. SNR is an important parameter that affects the performance and quality of systems that process or transmit signals, such as communication systems, audio systems, radar systems, imaging systems, and data acquisition systems.
CloudIn meteorology, a cloud is an aerosol consisting of a visible mass of miniature liquid droplets, frozen crystals, or other particles suspended in the atmosphere of a planetary body or similar space. Water or various other chemicals may compose the droplets and crystals. On Earth, clouds are formed as a result of saturation of the air when it is cooled to its dew point, or when it gains sufficient moisture (usually in the form of water vapor) from an adjacent source to raise the dew point to the ambient temperature.
Molecular biologyMolecular biology məˈlɛkjʊlər is the study of chemical and physical structure of biological macromolecules. It is a branch of biology that seeks to understand the molecular basis of biological activity in and between cells, including biomolecular synthesis, modification, mechanisms, and interactions. Molecular biology was first described as an approach focused on the underpinnings of biological phenomena—uncovering the structures of biological molecules as well as their interactions, and how these interactions explain observations of classical biology.
White noiseIn signal processing, white noise is a random signal having equal intensity at different frequencies, giving it a constant power spectral density. The term is used, with this or similar meanings, in many scientific and technical disciplines, including physics, acoustical engineering, telecommunications, and statistical forecasting. White noise refers to a statistical model for signals and signal sources, rather than to any specific signal.
Workflow management systemA workflow management system (WfMS or WFMS) provides an infrastructure for the set-up, performance and monitoring of a defined sequence of tasks, arranged as a workflow application. There are several international standards-setting bodies in the field of workflow management: Workflow Management Coalition World Wide Web Consortium Organization for the Advancement of Structured Information Standards WS-BPEL 2.0 (integration-centric) and WS-BPEL4People (human task-centric) published by OASIS Standards Body.
Phase noiseIn signal processing, phase noise is the frequency-domain representation of random fluctuations in the phase of a waveform, corresponding to time-domain deviations from perfect periodicity (jitter). Generally speaking, radio-frequency engineers speak of the phase noise of an oscillator, whereas digital-system engineers work with the jitter of a clock. Historically there have been two conflicting yet widely used definitions for phase noise.
Transformer (machine learning model)A transformer is a deep learning architecture that relies on the parallel multi-head attention mechanism. The modern transformer was proposed in the 2017 paper titled 'Attention Is All You Need' by Ashish Vaswani et al., Google Brain team. It is notable for requiring less training time than previous recurrent neural architectures, such as long short-term memory (LSTM), and its later variation has been prevalently adopted for training large language models on large (language) datasets, such as the Wikipedia corpus and Common Crawl, by virtue of the parallelized processing of input sequence.
Cirrus cloudCirrus (cloud classification symbol: Ci) is a genus of high cloud made of ice crystals. Cirrus clouds typically appear delicate and wispy with white strands. Cirrus are usually formed when warm, dry air rises, causing water vapor deposition onto rocky or metallic dust particles at high altitudes. Globally, they form anywhere between above sea level, with the higher elevations usually in the tropics and the lower elevations in more polar regions.
NanoparticleA nanoparticle or ultrafine particle is usually defined as a particle of matter that is between 1 and 100 nanometres (nm) in diameter. The term is sometimes used for larger particles, up to 500 nm, or fibers and tubes that are less than 100 nm in only two directions. At the lowest range, metal particles smaller than 1 nm are usually called atom clusters instead.
MicrofilamentMicrofilaments, also called actin filaments, are protein filaments in the cytoplasm of eukaryotic cells that form part of the cytoskeleton. They are primarily composed of polymers of actin, but are modified by and interact with numerous other proteins in the cell. Microfilaments are usually about 7 nm in diameter and made up of two strands of actin. Microfilament functions include cytokinesis, amoeboid movement, cell motility, changes in cell shape, endocytosis and exocytosis, cell contractility, and mechanical stability.
Online machine learningIn computer science, online machine learning is a method of machine learning in which data becomes available in a sequential order and is used to update the best predictor for future data at each step, as opposed to batch learning techniques which generate the best predictor by learning on the entire training data set at once. Online learning is a common technique used in areas of machine learning where it is computationally infeasible to train over the entire dataset, requiring the need of out-of-core algorithms.
