Deep reinforcement learningDeep reinforcement learning (deep RL) is a subfield of machine learning that combines reinforcement learning (RL) and deep learning. RL considers the problem of a computational agent learning to make decisions by trial and error. Deep RL incorporates deep learning into the solution, allowing agents to make decisions from unstructured input data without manual engineering of the state space. Deep RL algorithms are able to take in very large inputs (e.g.
Artificial neural networkArtificial neural networks (ANNs, also shortened to neural networks (NNs) or neural nets) are a branch of machine learning models that are built using principles of neuronal organization discovered by connectionism in the biological neural networks constituting animal brains. An ANN is based on a collection of connected units or nodes called artificial neurons, which loosely model the neurons in a biological brain. Each connection, like the synapses in a biological brain, can transmit a signal to other neurons.
Thermal resistanceThermal resistance is a heat property and a measurement of a temperature difference by which an object or material resists a heat flow. Thermal resistance is the reciprocal of thermal conductance. (Absolute) thermal resistance R in kelvins per watt (K/W) is a property of a particular component. For example, a characteristic of a heat sink. Specific thermal resistance or thermal resistivity Rλ in kelvin–metres per watt (K⋅m/W), is a material constant.
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.
Generative artificial intelligenceGenerative artificial intelligence (AI) is artificial intelligence capable of generating text, images, or other media, using generative models. Generative AI models learn the patterns and structure of their input training data and then generate new data that has similar characteristics. In the early 2020s, advances in transformer-based deep neural networks enabled a number of generative AI systems notable for accepting natural language prompts as input.
Seasonal thermal energy storageSeasonal thermal energy storage (STES), also known as inter-seasonal thermal energy storage, is the storage of heat or cold for periods of up to several months. The thermal energy can be collected whenever it is available and be used whenever needed, such as in the opposing season. For example, heat from solar collectors or waste heat from air conditioning equipment can be gathered in hot months for space heating use when needed, including during winter months.
Wireless sensor networkWireless sensor networks (WSNs) refer to networks of spatially dispersed and dedicated sensors that monitor and record the physical conditions of the environment and forward the collected data to a central location. WSNs can measure environmental conditions such as temperature, sound, pollution levels, humidity and wind. These are similar to wireless ad hoc networks in the sense that they rely on wireless connectivity and spontaneous formation of networks so that sensor data can be transported wirelessly.
AI alignmentIn the field of artificial intelligence (AI), AI alignment research aims to steer AI systems towards humans' intended goals, preferences, or ethical principles. An AI system is considered aligned if it advances the intended objectives. A misaligned AI system pursues some objectives, but not the intended ones. It can be challenging for AI designers to align an AI system because it can be difficult for them to specify the full range of desired and undesired behaviors.
Thermal conductivityThe thermal conductivity of a material is a measure of its ability to conduct heat. It is commonly denoted by , , or . Heat transfer occurs at a lower rate in materials of low thermal conductivity than in materials of high thermal conductivity. For instance, metals typically have high thermal conductivity and are very efficient at conducting heat, while the opposite is true for insulating materials like mineral wool or Styrofoam.
Learning organizationIn business management, a learning organization is a company that facilitates the learning of its members and continuously transforms itself. The concept was coined through the work and research of Peter Senge and his colleagues. Learning organizations may develop as a result of the pressures facing modern organizations; this enables them to remain competitive in the business environment. There are many definitions of a learning organization as well as typologies of kinds of learning organizations.
Business performance managementBusiness performance management (BPM), also known as corporate performance management (CPM) enterprise performance management (EPM), organizational performance management, or simply performance management are a set of management and analytic processes that ensure activities and outputs meet an organization's goals in an effective and efficient manner. Business performance management is contained within approaches to business process management.
Architectural modelAn architectural model is a type of scale model made to study aspects of an architectural design or to communicate design intent. They are made using a variety of materials including paper, plaster, plastic, resin, wood, glass, and metal. Models are built either with traditional handcraft techniques or via 3D printing technologies such as stereolithography, fused filament fabrication, and selective laser sintering. The use of architectural models dates to pre-history. Some of the oldest standing models were found in Malta at Tarxien Temples.
