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Modern computer technology has opened up new opportunities for the development of digital signal processing methods. The applications of digital signal processing have expanded significantly and today include audio and speech processing, sonar, radar, and other sensor array processing, spectral density estimation, statistical signal processing, digital image processing, signal processing for telecommunications, control systems, biomedical engineering, and seismology, among others. This Special Issue is aimed at wide coverage of the problems of digital signal processing, from mathematical modeling to the implementation of problem-oriented systems. The basis of digital signal processing is digital filtering. Wavelet analysis implements multiscale signal processing and is used to solve applied problems of de-noising and compression. Processing of visual information, including image and video processing and pattern recognition, is actively used in robotic systems and industrial processes control today. Improving digital signal processing circuits and developing new signal processing systems can improve the technical characteristics of many digital devices. The development of new methods of artificial intelligence, including artificial neural networks and brain-computer interfaces, opens up new prospects for the creation of smart technology. This Special Issue contains the latest technological developments in mathematics and digital signal processing. The stated results are of interest to researchers in the field of applied mathematics and developers of modern digital signal processing systems.

digital filter --- finite field algebra --- conversion device --- module --- memory device --- residue --- feedback regulation --- digital signal analysis --- control efficacy --- residue number system --- redundant residue number system --- modular division --- fraction --- algorithm --- mathematical models of digital signal processing --- digital filtering --- maximum correntropy --- impulsive noise --- sparse channel estimation --- discrete wavelet transform --- medical imaging --- 3D image processing --- quantization noise --- harmonic wavelets --- classification --- kNN-algorithm --- deep neural networks --- machine learning --- Fourier transform --- short-time Fourier transform --- wavelet transform --- spectrogram --- confusion matrix --- ROC curve --- 3D model --- prosthetic design --- orientation --- positioning --- reconstruction --- speech enhancement --- adaptive filter --- microphone array --- sub-band processing --- filter bank --- posture classification --- skeleton detection --- motion capture --- exercise classification --- virtual rehabilitation --- wood defect --- CNN --- ELM --- genetic algorithm --- detection

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Very recently, a great deal of attention has been paid by researchers and technologists to trying to eliminate metal materials in the design of products and processes in favor of plastics and composites. After a few years, it is possible to state that metal materials are even more present in our lives and this is especially thanks to their ability to evolve. This Special Issue is focused on the recent evolution of metals and alloys with the scope of presenting the state of the art of solutions where metallic materials have become established, without a doubt, as a successful design solution thanks to their unique properties.

Technology: general issues --- material properties prediction --- experimental data analysis --- ductile/spheroidal cast iron (SGI) --- compact graphite cast iron (CGI) --- Machine Learning (RF) --- pattern recognition --- Random Forest (RF) --- Artificial Neural Network (NN) --- k-nearest neighbours (kNN) --- tribology --- wear --- slurry erosion --- coating --- cermet --- spheroidal graphite cast iron --- pack aluminizing --- microstructure --- high-temperature oxidation resistance --- hybrid composite --- wear performance --- ZA27 alloy --- deflection --- plates --- stiffeners --- numerical simulation --- Constructal Design --- austenitic stainless steel --- tensile properties --- artificial neural network --- MIV analysis --- pallet rack --- moment-rotation curve --- connection --- experiment --- numerical analysis --- thermomechanical processing --- grain growth --- forging --- retained austenite --- bainitic microstructure --- extended finite element method (xFEM) --- polarization curve --- long-term operated metals --- hybrid materials --- fatigue crack growth --- stress intensity factors (SIF) --- linear regression --- micromagnetic testing --- hardness --- case hardening depth --- phase-field modeling --- modified damage model --- large-strain plasticity --- S355J2+N steel --- ductile fracture --- two-stage yield function --- copper coatings --- pulsating current (PC) --- composite hardness models --- creep resistance --- n/a

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Open data and policy implications coming from data-aware planning entail collection and pre- and postprocessing as operations of primary interest. Before these steps, making data available to people and their decision-makers is a crucial point. Referring to the relationship between data and energy, public administrations, governments, and research bodies are promoting the construction of reliable and robust datasets to pursue policies coherent with the Sustainable Development Goals, as well as to allow citizens to make informed choices. Energy engineers and planners must provide the simplest and most robust tools to collect, process, and analyze data in order to offer solid data-based evidence for future projections in building, district, and regional systems planning. This Special Issue aims at providing the state-of-the-art on open-energy data analytics; its availability in the different contexts, i.e., country peculiarities; and its availability at different scales, i.e., building, district, and regional for data-aware planning and policy-making. For all the aforementioned reasons, we encourage researchers to share their original works on the field of open data and energy analytics. Topics of primary interest include but are not limited to the following: 1. Open data and energy sustainability; 2. Open data science and energy planning; 3. Open science and open governance for sustainable development goals; 4. Key performance indicators of data-aware energy modelling, planning, and policy; 5. Energy, water, and sustainability database for building, district, and regional systems; 6. Best practices and case studies.

data envelopment analysis --- Kohonen self-organizing maps --- factor analysis --- multiple regression --- energy efficiency --- social media --- energy-consuming activities --- energy consumption --- machine learning --- ontology --- energy performance certificate --- heating energy demand --- buildings --- data mining --- classification --- regression --- decision tree --- support vector machine --- random forest --- artificial neural network --- open data --- electrification modelling --- Malawi --- OnSSET --- MESSAGEix --- reproducibility --- collaborative work --- open modelling and data --- data-handling --- integrated assessment modelling --- data pre- and post-processing --- space heating --- domestic hot water --- market assessment --- EU28 --- district heating --- data analytics --- big data --- forecasting --- energy --- polygeneration --- clustering --- kNN --- pattern recognition --- heating --- building stock --- heat map --- spatial analysis --- heat density map --- building performance simulation --- parametric modelling --- energy management --- model calibration --- Passive House --- energy planning --- energy potential mapping --- urban energy atlas --- urban energy transition --- energy data --- data-aware planning --- spatial planning --- open data analytics --- smart cities --- open energy governance --- urban database --- energy mapping --- building dataset --- energy modelling

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Very recently, a great deal of attention has been paid by researchers and technologists to trying to eliminate metal materials in the design of products and processes in favor of plastics and composites. After a few years, it is possible to state that metal materials are even more present in our lives and this is especially thanks to their ability to evolve. This Special Issue is focused on the recent evolution of metals and alloys with the scope of presenting the state of the art of solutions where metallic materials have become established, without a doubt, as a successful design solution thanks to their unique properties.

material properties prediction --- experimental data analysis --- ductile/spheroidal cast iron (SGI) --- compact graphite cast iron (CGI) --- Machine Learning (RF) --- pattern recognition --- Random Forest (RF) --- Artificial Neural Network (NN) --- k-nearest neighbours (kNN) --- tribology --- wear --- slurry erosion --- coating --- cermet --- spheroidal graphite cast iron --- pack aluminizing --- microstructure --- high-temperature oxidation resistance --- hybrid composite --- wear performance --- ZA27 alloy --- deflection --- plates --- stiffeners --- numerical simulation --- Constructal Design --- austenitic stainless steel --- tensile properties --- artificial neural network --- MIV analysis --- pallet rack --- moment-rotation curve --- connection --- experiment --- numerical analysis --- thermomechanical processing --- grain growth --- forging --- retained austenite --- bainitic microstructure --- extended finite element method (xFEM) --- polarization curve --- long-term operated metals --- hybrid materials --- fatigue crack growth --- stress intensity factors (SIF) --- linear regression --- micromagnetic testing --- hardness --- case hardening depth --- phase-field modeling --- modified damage model --- large-strain plasticity --- S355J2+N steel --- ductile fracture --- two-stage yield function --- copper coatings --- pulsating current (PC) --- composite hardness models --- creep resistance --- n/a

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Open data and policy implications coming from data-aware planning entail collection and pre- and postprocessing as operations of primary interest. Before these steps, making data available to people and their decision-makers is a crucial point. Referring to the relationship between data and energy, public administrations, governments, and research bodies are promoting the construction of reliable and robust datasets to pursue policies coherent with the Sustainable Development Goals, as well as to allow citizens to make informed choices. Energy engineers and planners must provide the simplest and most robust tools to collect, process, and analyze data in order to offer solid data-based evidence for future projections in building, district, and regional systems planning. This Special Issue aims at providing the state-of-the-art on open-energy data analytics; its availability in the different contexts, i.e., country peculiarities; and its availability at different scales, i.e., building, district, and regional for data-aware planning and policy-making. For all the aforementioned reasons, we encourage researchers to share their original works on the field of open data and energy analytics. Topics of primary interest include but are not limited to the following: 1. Open data and energy sustainability; 2. Open data science and energy planning; 3. Open science and open governance for sustainable development goals; 4. Key performance indicators of data-aware energy modelling, planning, and policy; 5. Energy, water, and sustainability database for building, district, and regional systems; 6. Best practices and case studies.

Research & information: general --- data envelopment analysis --- Kohonen self-organizing maps --- factor analysis --- multiple regression --- energy efficiency --- social media --- energy-consuming activities --- energy consumption --- machine learning --- ontology --- energy performance certificate --- heating energy demand --- buildings --- data mining --- classification --- regression --- decision tree --- support vector machine --- random forest --- artificial neural network --- open data --- electrification modelling --- Malawi --- OnSSET --- MESSAGEix --- reproducibility --- collaborative work --- open modelling and data --- data-handling --- integrated assessment modelling --- data pre- and post-processing --- space heating --- domestic hot water --- market assessment --- EU28 --- district heating --- data analytics --- big data --- forecasting --- energy --- polygeneration --- clustering --- kNN --- pattern recognition --- heating --- building stock --- heat map --- spatial analysis --- heat density map --- building performance simulation --- parametric modelling --- energy management --- model calibration --- Passive House --- energy planning --- energy potential mapping --- urban energy atlas --- urban energy transition --- energy data --- data-aware planning --- spatial planning --- open data analytics --- smart cities --- open energy governance --- urban database --- energy mapping --- building dataset --- energy modelling