Seismic waveA seismic wave is a mechanical wave of acoustic energy that travels through the Earth or another planetary body. It can result from an earthquake (or generally, a quake), volcanic eruption, magma movement, a large landslide, and a large man-made explosion that produces low-frequency acoustic energy. Seismic waves are studied by seismologists, who record the waves using seismometers, hydrophones (in water), or accelerometers.
Energy StarEnergy Star (trademarked ENERGY STAR) is a program run by the U.S. Environmental Protection Agency (EPA) and U.S. Department of Energy (DOE) that promotes energy efficiency. The program provides information on the energy consumption of products and devices using different standardized methods. The Energy Star label is found on more than 75 different certified product categories, homes, commercial buildings, and industrial plants. In the United States, the Energy Star label is also shown on the Energy Guide appliance label of qualifying products.
S waveNOTOC In seismology and other areas involving elastic waves, S waves, secondary waves, or shear waves (sometimes called elastic S waves) are a type of elastic wave and are one of the two main types of elastic body waves, so named because they move through the body of an object, unlike surface waves. S waves are transverse waves, meaning that the direction of particle movement of a S wave is perpendicular to the direction of wave propagation, and the main restoring force comes from shear stress.
Energy conservationEnergy conservation is the effort to reduce wasteful energy consumption by using fewer energy services. This can be done by using energy more effectively (using less energy for continuous service) or changing one's behavior to use less service (for example, by driving less). Energy conservation can be achieved through efficient energy use, which has some advantages, including a reduction in greenhouse gas emissions and a smaller carbon footprint, as well as cost, water, and energy savings.
Terahertz metamaterialA terahertz metamaterial is a class of composite metamaterials designed to interact at terahertz (THz) frequencies. The terahertz frequency range used in materials research is usually defined as 0.1 to 10 THz. This bandwidth is also known as the terahertz gap because it is noticeably underutilized. This is because terahertz waves are electromagnetic waves with frequencies higher than microwaves but lower than infrared radiation and visible light.
Prime ministerA prime minister, premier or chief of cabinet is the head of the cabinet and the leader of the ministers in the executive branch of government, often in a parliamentary or semi-presidential system. Under those systems, a prime minister is not the head of state, but rather the head of government, serving as the principle administrator under either a monarch in a monarchy or under a president in a republican form of government.
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.
Love waveIn elastodynamics, Love waves, named after Augustus Edward Hough Love, are horizontally polarized surface waves. The Love wave is a result of the interference of many shear waves (S-waves) guided by an elastic layer, which is welded to an elastic half space on one side while bordering a vacuum on the other side. In seismology, Love waves (also known as Q waves (Quer: German for lateral)) are surface seismic waves that cause horizontal shifting of the Earth during an earthquake.
Feature learningIn machine learning, feature learning or representation learning is a set of techniques that allows a system to automatically discover the representations needed for feature detection or classification from raw data. This replaces manual feature engineering and allows a machine to both learn the features and use them to perform a specific task. Feature learning is motivated by the fact that machine learning tasks such as classification often require input that is mathematically and computationally convenient to process.
Energy efficiency in British housingDomestic housing in the United Kingdom presents a possible opportunity for achieving the 20% overall cut in UK greenhouse gas emissions targeted by the Government for 2010. However, the process of achieving that drop is proving problematic given the very wide range of age and condition of the UK housing stock. Although carbon emissions from housing have remained fairly stable since 1990 (due to the increase in household energy use having been compensated for by the 'dash for gas'), housing accounted for around 30% of all the UK's carbon dioxide emissions in 2004 (40 million tonnes of carbon) up from 26.
