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12 results on 'LN cat08778a'

1. Advances in the Field of Electrical Machines and Drives.

Author

Karlis, Athanasios and Karlis, Athanasios

Subjects
Technology: general issues, History of engineering & technology, fault size, inter-laminar fault, localized losses, thermographic measurement, thermal-electric coupling, axial flux, demagnetization, finite element analysis, permanent magnet, static eccentricity, synchronous generator, power loss minimization, speed control drive systems, efficiency measurement, IPMSM, additive manufacturing, three-dimensional printing, topology optimization, magnetic materials, soft magnetic materials, permanent magnets, electrical machines, torque ripple, 6th harmonic, induction motor, AC machine, PWM inverter, space phasor modulation, electric motor, interior permanent magnet, reluctance, MMF-permeance, winding function, predictive maintenance, digital twin, artificial intelligence, Industry 4.0, data handling, life cycle, electric machines, electromagnetic analysis, electromagnetic measurements, core losses, rotor flux linkage, modular stator, oriented steel, flux-injecting probes, insulation system, partial discharges, capacitive model, MATLAB/Simulink, flashover voltage, epoxy resin, matrix-converter, input AC filter design, PMSM, predictive control, electrical drives, energy efficiency, energy-saving, power quality, current signals, stray flux signals, LDA, automatic fault diagnosis, broken rotor bars, soft-starters
Abstract

Summary: Electrical machines and drives dominate our everyday lives. This is due to their numerous applications in industry, power production, home appliances, and transportation systems such as electric and hybrid electric vehicles, ships, and aircrafts. Their development follows rapid advances in science, engineering, and technology. Researchers around the world are extensively investigating electrical machines and drives because of their reliability, efficiency, performance, and fault-tolerant structure. In particular, there is a focus on the importance of utilizing these new trends in technology for energy saving and reducing greenhouse gas emissions. This Special Issue will provide the platform for researchers to present their recent work on advances in the field of electrical machines and drives, including special machines and their applications; new materials, including the insulation of electrical machines; new trends in diagnostics and condition monitoring; power electronics, control schemes, and algorithms for electrical drives; new topologies; and innovative applications.

2. Systems Engineering: Availability and Reliability.

Author

Antosz, Katarzyna, Machado, Jose, Mazurkiewicz, Dariusz, Antonelli, Dario, Soares, Filomena, and Antosz, Katarzyna

Subjects
Technology: general issues, History of engineering & technology, Quality check, bike frame, mathematical model, graphical user interface, risk management, safety assurance, medical parallel robot, robotic assisted cancer treatment, risk performance reasoning, hidden Markov model, Handy bauxite carrier, process safety, performance evaluation, safety, coupling correlation, risk assessment, multi-dimensional theory, precision steel tape, tape transportation, roller-tape interactions, roller-tape contact pair, reliability, truck unloading system, petroleum equipment, preventive maintenance, cork-rubber composites, compression, apparent compression modulus, Young's modulus, bonded condition, importance measure, cost, inventory systems, air compression system, nitrogen generation system, utility module, availability, sensitivity analysis, predictive maintenance, Industry 4.0, Internet of Things, artificial intelligence, machine learning, maintenance, predictive scheduling, flow shop, job shop, ant colony optimisation, on-line monitoring, collaborative robots, human robot collaboration, time between failure (TBF), common beta hypothesis (CBH) test, meta-analysis, level of heterogeneity, mean time between failure (MTBF), text mining, network-based distributed manufacturing systems, moth flame optimization algorithm, support vector machines, Naive Bayes, random forest, decision trees, supplier classification, machining centre, DSM, Copula function, fault propagation intensity, fault propagation behaviour, lubricity, gear oil, wear, operational reliability, n/a
Abstract

Summary: Current trends in Industry 4.0 are largely related to issues of reliability and availability. As a result of these trends and the complexity of engineering systems, research and development in this area needs to focus on new solutions in the integration of intelligent machines or systems, with an emphasis on changes in production processes aimed at increasing production efficiency or equipment reliability. The emergence of innovative technologies and new business models based on innovation, cooperation networks, and the enhancement of endogenous resources is assumed to be a strong contribution to the development of competitive economies all around the world. Innovation and engineering, focused on sustainability, reliability, and availability of resources, have a key role in this context. The scope of this Special Issue is closely associated to that of the ICIE'2020 conference. This conference and journal's Special Issue is to present current innovations and engineering achievements of top world scientists and industrial practitioners in the thematic areas related to reliability and risk assessment, innovations in maintenance strategies, production process scheduling, management and maintenance or systems analysis, simulation, design and modelling.

3. Energy Management of Prosumer Communities.

Author

Sierla, Seppo, Pourakbari-Kasmaei, Mahdi, and Sierla, Seppo

Subjects
Technology: general issues, Energy industries & utilities, power-to-heat, sector coupling, thermal storage, district heat, deep well heat pump, hierarchical agglomerative clustering, chronology, demand response, two-capacity building model, residential users, flexible loads shifting scenarios, community of prosumers, new consumption peak, shared PV plant, storage batteries, load factor, real-time pricing, prosumers, electricity price forecasting, particle swarm optimization, renewable energy, peer-to-peer, electricity market, economic dispatch, consensus + innovations, distributed energy resources, battery, reinforcement learning, simulation, frequency reserve, frequency containment reserve, timescale, artificial intelligence, real-time
Abstract

Summary: The penetration of distributed generation, energy storages and smart loads has resulted in the emergence of prosumers: entities capable of adjusting their electricity production and consumption in order to meet environmental goals and to participate profitably in the available electricity markets. Significant untapped potential remains in the exploitation and coordination of small and medium-sized distributed energy resources. However, such resources usually have a primary purpose, which imposes constraints on the exploitation of the resource; for example, the primary purpose of an electric vehicle battery is for driving, so the battery could be used as temporary storage for excess photovoltaic energy only if the vehicle is available for driving when the owner expects it to be. The aggregation of several distributed energy resources is a solution for coping with the unavailability of one resource. Solutions are needed for managing the electricity production and consumption characteristics of diverse distributed energy resources in order to obtain prosumers with more generic capabilities and services for electricity production, storage, and consumption. This collection of articles studies such prosumers and the emergence of prosumer communities. Demand response-capable smart loads, battery storages and photovoltaic generation resources are forecasted and optimized to ensure energy-efficient and, in some cases, profitable operation of the resources.

4. Industrial Applications: New Solutions for the New Era.

Author

de Sales Guerra Tsuzuki, Marcos, Pessoa, Marcosiris Amorim de Oliveira, Acácio de Andrade, Alexandre, and de Sales Guerra Tsuzuki, Marcos

Subjects
Technology: general issues, History of engineering & technology, induction machines, electrical machines, vector control, SVPWM modulation, frequency inverter, artificial intelligence, photovoltaics, fault detection, machine learning, operation and maintenance, renewable energy, water-in-crude oil emulsion, water content, ultrasound, propagation velocity, exoskeletons, test bench, industry, benchmarking, microgrid model-based systems engineering, service systems, goal-oriented requirements engineering, safety instrumented system, ventricular assist device Bayesian network, Petri net, control strategy, UAV, fuzzy, PID controller, ROS, Industry 4.0, database, data models, big data and analytics, asset administration shell, MLOps, digital twin, IoT, prediction, coordinate metrology, optical scanning, noise reduction, digital manufacturing, integrated inspection system, data analytics, uncertainty, convolutional neural networks, warehouse management, image classification, ensemble learning, synthetic data, depth image, electrical maintenance, COVID-19, thermography, fever, computer vision, intelligent systems
Abstract

Summary: This book reprints articles from the Special Issue "Industrial Applications: New Solutions for the New Age" published online in the open-access journal Machines (ISSN 2075-1702). This book consists of twelve published articles. This special edition belongs to the "Mechatronic and Intelligent Machines" section.

5. Alternative Sources of Energy Modeling, Automation, Optimal Planning and Operation.

Author

Stavrakakis, George S. and Stavrakakis, George S.

Subjects
Technology: general issues, History of engineering & technology, entrained flow coal gasification, ash melting point, operation temperature, Markov process, stochastic optimization model, genetic algorithm, gallium nitride, magnetic-free converters, module-level converters, parallel architecture, partial shading, photovoltaic systems, switched capacitor converters, hybrid energy storage system, supercapacitor, lead-acid battery, energy management system, battery degradation, depth of discharge, techno-economic analysis, hybrid power station, green island, energy storage, remote community, reserves, k-means, probabilistic dimensioning, dynamic dimensioning, balancing, wave energy converters, deep neural networks, renewable energy sources, spatial planning, sentinel satellite imagery, permanent magnet synchronous machines, generators, fault detection, demagnetization, artificial intelligence, data mining, machine learning, advanced deep learning, windspeed forecasting, solar irradiation forecasting, increased RES penetration, smart grid, scalability, replicability, FLEXITRANSTORE, Angolan economy, diversification, strategic alternative, biofuels
Abstract

Summary: An economic development model analyzes the adoption of alternative strategy capable of leveraging the economy, based essentially on RES. The combination of wind turbine, PV installation with new technology battery energy storage, DSM network and RES forecasting algorithms maximizes RES integration in isolated islands. An innovative model of power system (PS) imbalances is presented, which aims to capture various features of the stochastic behavior of imbalances and to reduce in average reserve requirements and PS risk. Deep learning techniques for medium-term wind speed and solar irradiance forecasting are presented, using for first time a specific cloud index. Scalability-replicability of the FLEXITRANSTORE technology innovations integrates hardware-software solutions in all areas of the transmission system and the wholesale markets, promoting increased RES. A deep learning and GIS approach are combined for the optimal positioning of wave energy converters. An innovative methodology to hybridize battery-based energy storage using supercapacitors for smoother power profile, a new control scheme and battery degradation mechanism and their economic viability are presented. An innovative module-level photovoltaic (PV) architecture in parallel configuration is introduced maximizing power extraction under partial shading. A new method for detecting demagnetization faults in axial flux permanent magnet synchronous wind generators is presented. The stochastic operating temperature (OT) optimization integrated with Markov Chain simulation ascertains a more accurate OT for guiding the coal gasification practice.

6. Advances of Machine Design in Italy 2022.

Author

Ceccarelli, Marco, Carbone, Giuseppe, Gasparetto, Alessandro, and Ceccarelli, Marco

Subjects
Technology: general issues, History of engineering & technology, Mechanical engineering & materials, precision agriculture, mobile manipulation, motion planning, analytic Jacobian, inverse kinematics, manipulability, history of mms, italian history of mechanism design, models of mechanisms, history of teaching, italian mechanism collections, kinematics, planar mechanism, instant center, singular configuration, machine design, drone-based package delivery, UAV transportation, embedded payload, packaging, quick-release system, hypoid gears, friction, wear, elasto-hydrodynamic lubrication, automatic machines, planar parallel mechanism, five bar linkage, design optimization, vibration reduction, lightweight gears, finite-element analysis, multibody simulation, design space exploration, transmission error, squeeze film damper, seal instability, rotor dynamics, lubrication, UGVs, reconfigurable robots, mechatronic design, field robotics, path and trajectory planning, rollover detection, heavy vehicles, off-road applications, predictive algorithms, artificial intelligence, load transfer ratio, gas micro-turbine, discriminant analysis, vibrational analysis, diesel blends, kerosene, biofuel, statistical index, accelerometer, confusion matrix, Cohen's kappa, human-robot collaboration, human-in-the-loop, virtual reality, obstacle avoidance, configuration-dependent substructuring, dynamics of linkages, three-points linkage, vibrations, feeding, rotary device, functional synthesis, mechanical design, applied mechanics, tribology, Boundary Elements Methods, n/a
Abstract

Summary: This reprint contains a Special Issue of the MDPI journal Machines on Italian advances in mechanism and machines science through a collection of selected papers from the Fourth International Conference of IFToMM Italy, IFIT 2022. The included papers belong to a broad range of disciplines in MMS, with research and design results that can be of interest not only to scholars in the field of MMS and mechanical engineering but also to professionals and even students, broadening their understanding of the problems and solutions under development, mainly, but not only, from the Italian community.

7. Advances in Public Transport Platform for the Development of Sustainability Cities.

Author

Corchado, Juan M., Larriba-Pey, Josep L., Chamoso, Pablo, De la Prieta, Fernando, and Corchado, Juan M.

Subjects
Technology: general issues, History of engineering & technology, Environmental science, engineering & technology, optimization models, timetable, passenger waiting time, vehicle occupancy ratio, intelligent transportation systems, demand prediction, taxi recommendation, vehicle social network, ride-hailing, urban rail transit (URT), exploratory data analysis (EDA), data envelopment analysis (DEA), sustainable transport systems, intelligent transportation systems (ITS), big-data applications, dynamic bus travel time prediction, wide and deep, data fusion, attention, recurrent neural network, deep neural networks, intelligent transportation, railway, CPS, security, safety, critical infrastructure, carsharing, data analysis, delays, demand, public transit, taxi, complex network analysis, centrality measures, network robustness, ridership patterns, clustering analysis, passenger flow, Barcelona underground, artificial intelligence, Big Data analytics, forecasting systems, recommender system, Fintech, passenger traffic, artificial neural network, regression analysis, reputation algorithm, users' reputation, transport, software application, deep learning, energy consumption, sustainable cities, transfer learning, wastewater treatment plants, unmanned aerial vehicles (UAVs), multi-objective optimization, integer programming, GLPK, variable neighborhood search, search and rescue, learning recommender system, learning object, learning videos, content-based, collaborative filtering, users' profiling, data extraction, natural language processing, mapping application, time series forecasting, HTM, regression, machine intelligence, cyber-attack detection, IoT, trust, energy trading, trusted negotiations, n/a
Abstract

Summary: Modern societies demand high and varied mobility, which in turn requires a complex transport system adapted to social needs that guarantees the movement of people and goods in an economically efficient and safe way, but all are subject to a new environmental rationality and the new logic of the paradigm of sustainability. From this perspective, an efficient and flexible transport system that provides intelligent and sustainable mobility patterns is essential to our economy and our quality of life. The current transport system poses growing and significant challenges for the environment, human health, and sustainability, while current mobility schemes have focused much more on the private vehicle that has conditioned both the lifestyles of citizens and cities, as well as urban and territorial sustainability. Transport has a very considerable weight in the framework of sustainable development due to environmental pressures, associated social and economic effects, and interrelations with other sectors. The continuous growth that this sector has experienced over the last few years and its foreseeable increase, even considering the change in trends due to the current situation of generalized crisis, make the challenge of sustainable transport a strategic priority at local, national, European, and global levels. This Special Issue will pay attention to all those research approaches focused on the relationship between evolution in the area of transport with a high incidence in the environment from the perspective of efficiency.

8. Image and Video Processing and Recognition Based on Artificial Intelligence.

Author

Park, Kang Ryoung, Lee, Sangyoun, Kim, Euntai, and Park, Kang Ryoung

Subjects
Technology: general issues, emotion recognition, brain computer interface, bag of deep features, continuous wavelet transform, face image analysis, deep learning, face parsing, facial attributes classification, building extraction, convolutional neural networks, mask R-CNN, high-resolution remote sensing image, autoencoders, semi-supervised learning, computer vision, pathology, epidermis, skin, image processing, generative models, generative adversarial net, depth map, super-resolution, guidance, residual network, channel interaction, pose estimation, body orientation, multi-person, multi-task, surface defect detection, active learning, generative adversarial network, presentation attack detection, artificial image generation, presentation attack face images, ultrasound image, malignant thyroid nodule, artificial intelligence, weighted binary cross-entropy loss, infrared circumferential scanning system, target recognition, deep convolutional neural networks, data augmentation, transfer learning, bounding box regression, loss function, medical image fusion, convolutional neural network, image pyramid, multi-scale decomposition, armature, surface inspection, action recognition, social robotics, common spatial patterns, vehicle recognition, multi resolution network, optimization, semantic segmentation, global context, local context, fully convolutional networks, image-to-image conversion, image de-raining, label to photos, edges to photos, generative adversarial network (GAN), remote sensing, helicopter footage, crowd counting, multitask learning, normalized cross-correlation, Marr wavelets, entropy and response, graph matching, RANSAC, GC-LSTM model, typhoon, satellite image, prediction system, monocular depth estimation, feature distillation, joint attention, finger-vein recognition, camera position, finger position, lighting, unobserved database, heterogeneous database, domain adaptation, cycle-consistent adversarial networks, SDUMLA-HMT-DB, HKPolyU-DB, biometrics, face recognition, single-sample face recognition, binarized statistical image features, K-nearest neighbors, sparse coding, fast approximation, homotopy iterative hard thresholding, object recognition, character recognition, orthogonal polynomials, orthogonal moments, Krawtchouk polynomials, Tchebichef polynomials, support vector machine
Abstract

Summary: This book includes 23 published papers on Special issues of "Image and Video Processing and Recognition Based on Artificial Intelligence" in the journal Sensors. The purpose of this Special Issue was to invite high-quality and state-of-the-art academic papers on challenging issues in the field of AI-based image and video processing and recognition.

9. Intelligent Sensors for Human Motion Analysis.

Author

Krzeszowski, Tomasz, Świtoński, Adam, Kepski, Michal, Calafate, Carlos Tavares, and Krzeszowski, Tomasz

Subjects
Technology: general issues, History of engineering & technology, gait recognition, biometrics, regularized discriminant analysis, particle swarm optimization, grey wolf optimization, whale optimization algorithm, FMCW, vital sign, XGBoost, MFCC, COVID-19, 3D human pose estimation, deep learning, generalization, optical sensing principle, modular sensing unit, plantar pressure measurement, gait parameters, 3D human mesh reconstruction, deep neural network, motion capture, neural networks, reconstruction, gap filling, FFNN, LSTM, BILSTM, GRU, pose estimation, movement tracking, computer vision, artificial intelligence, markerless motion capture, assessment, kinematics, development, machine learning, human action recognition, features fusion, features selection, recognition, fall risk detection, balance, Berg Balance Scale, human tracking, elderly, telemedicine, diagnosis, precedence indicator, knowledge measure, fuzzy inference, rule induction, posture detection, aggregation function, markerless, human motion analysis, gait analysis, data augmentation, skeletal data, time series classification, EMG, pattern recognition, robot, cyber-physical systems, RGB-D sensors, human motion modelling, F-Formation, Kinect v2, Azure Kinect, Zed 2i, socially occupied space, facial expression recognition, facial landmarks, action units, convolutional neural networks, graph convolutional networks, artifact classification, artifact detection, anomaly detection, 3D multi-person pose estimation, absolute poses, camera-centric coordinates, deep-learning, n/a
Abstract

Summary: The book, "Intelligent Sensors for Human Motion Analysis," contains 17 articles published in the Special Issue of the Sensors journal. These articles deal with many aspects related to the analysis of human movement. New techniques and methods for pose estimation, gait recognition, and fall detection have been proposed and verified. Some of them will trigger further research, and some may become the backbone of commercial systems.

10. Advances in Sustainable and Digitalized Factories: Manufacturing, Measuring Technologies and Systems.

Author

Calvo, Roque, Yagüe-Fabra, José A., Tosello, Guido, and Calvo, Roque

Subjects
Technology: general issues, History of engineering & technology, Industry 4.0, continuous improvement, lean manufacturing, lean production systems, lean 4.0, systematic literature review, tiny RFID, metallic electromagnetic isolation, analog manometer, Ansys HFSS simulator, passive digitization, ontology, production simulation, multi-agent, digital twin, augmented reality, industry 4.0, quality 4.0, metrology, assembly, turbine blades, re-manufacturing, uncertainty, robust scheduling, case-based reasoning, failure mode, effect and criticality analysis, knowledge-based system, nearest neighbor, reliability-centered maintenance, virtual reality, cyber physical system, OPC UA, CAD, industrial IoT, prototyping, retrofitting solutions, embedded solutions, low-cost, value chain, additive manufacturing, subtractive manufacturing, cost comparison, plant simulation, technology comparison, hybrid dependability modelling, production scheduling, dynamic failure rate, discrete event simulation, time-driven simulation, machine learning, manufacturing, artificial intelligence, smart manufacturing, digitization, smart surface, friction force field, under-actuation, feeding, simulation, material flow handling, intralogistics, robotic bin-picking, simulation model, ADAMS, pick-point determination, MATLAB/Simulink, 2-F robotic gripper, performance analysis, plastic injection molding, design of experiments, process optimization, facility layout problem, evolutionary algorithms, numerical modeling, multi-objective optimization, n/a
Abstract

Summary: The book is the reprint of the Special Issue 'Advances in Sustainable and Digitalized Factories: Manufacturing, Measuring Technologies and Systems' published in the journal Applied Science (MDPI). It contains 17 articles, including 1 Editorial, 14 Research Papers, and 2 Reviews.

11. Machine Learning in Tribology.

Author

Tremmel, Stephan, Marian, Max, and Tremmel, Stephan

Subjects
Technology: general issues, History of engineering & technology, artificial intelligence, machine learning, artificial neural networks, tribology, condition monitoring, semi-supervised learning, random forest classifier, self-lubricating journal bearings, reduced order modelling, dynamic friction, rubber seal applications, tensor decomposition, laser surface texturing, texturing during moulding, digital twin, PINN, reynolds equation, triboinformatics, databases, data mining, meta-modeling, monitoring, analysis, prediction, optimization, fault data generation, Convolutional Neural Network (CNN), Generative Adversarial Network (GAN), bearing fault diagnosis, unbalanced datasets, tribo-testing, tribo-informatics, natural language processing, tribAIn, BERT, amorphous carbon coatings, UHWMPE, total knee replacement, Gaussian processes, rolling bearing dynamics, cage instability, regression, neural networks, random forest, gradient boosting, evolutionary algorithms, rolling bearings, remaining useful life, feature engineering, structure-borne sound, n/a
Abstract

Summary: Tribology has been and continues to be one of the most relevant fields, being present in almost all aspects of our lives. The understanding of tribology provides us with solutions for future technical challenges. At the root of all advances made so far are multitudes of precise experiments and an increasing number of advanced computer simulations across different scales and multiple physical disciplines. Based upon this sound and data-rich foundation, advanced data handling, analysis and learning methods can be developed and employed to expand existing knowledge. Therefore, modern machine learning (ML) or artificial intelligence (AI) methods provide opportunities to explore the complex processes in tribological systems and to classify or quantify their behavior in an efficient or even real-time way. Thus, their potential also goes beyond purely academic aspects into actual industrial applications. To help pave the way, this article collection aimed to present the latest research on ML or AI approaches for solving tribology-related issues generating true added value beyond just buzzwords. In this sense, this Special Issue can support researchers in identifying initial selections and best practice solutions for ML in tribology.

12. Low Back Pain (LBP)

Author

Denaro, Vincenzo, Iavicoli, Sergio, Russo, Fabrizio, Vadalà, Gianluca, and Denaro, Vincenzo

Subjects
Technology: general issues, Environmental science, engineering & technology, low back pain (LBP), standing position, musculoskeletal pain, sedentary behaviour, back pain, Google Trends, infodemiology, seasonality, Wikipedia, back problems, Low Back Pain Scale, maximum voluntary isometric contraction, postural stability, unexpected external postural perturbations, disability, insurance, low back pain, lumbar decompression, lumbar fusion, musculoskeletal disorders, occupational health, pain, return to work, satisfaction, manual therapy, kinesiophobia, fear of pain, Australian method, Neurac, chronic, underserved, African American, Latino, older adults, workload, wearable assistive device, occupational back-support exoskeleton, EMG, handling task, lumbalgia, physical activity, prevention, public health, occupational safety and health, risk assessment, occupational disorder, knowledge, rehabilitation nurses, patient care, unemployment, gender difference, population attributable fraction, cross-sectional studies, orthopaedics, artificial intelligence, computer vision, digital image processing, deep learning, decision support systems, computer aided diagnosis, sub-threshold lumbar instability, non-radiological lumbar instability, lumbar instability, radiography, lumbar translation, lumbar rotation, screening tool, X-ray, sensitivity, specificity, workplace interventions, workers, work ability, systematic review, meta-analysis, cognitive behavioral therapy, mindfulness-based stress reduction, depression, fear-avoidance beliefs, absenteeism, epidemiology, workplace, epidural steroid injections, lumbosacral radicular pain, disk herniation, canal stenosis, review, pelvic incidence, hip-knee line, anthropometry, ROC curve, reliability, MRI, CT, bone metastasis, bone cancer, lung cancer, prostate cancer, machine learning, radiomics, signature, spinal load, core stability, ergonomics, low-back pain, lower extremity
Abstract

Summary: Low back pain (LBP) is a major public health problem, being the most commonly reported musculoskeletal disorder (MSD) and the leading cause of compromised quality of life and work absenteeism. Indeed, LBP is the leading worldwide cause of years lost to disability, and its burden is growing alongside the increasing and aging population. The etiology, pathogenesis, and occupational risk factors of LBP are still not fully understood. It is crucial to give a stronger focus to reducing the consequences of LBP, as well as preventing its onset. Primary prevention at the occupational level remains important for highly exposed groups. Therefore, it is essential to identify which treatment options and workplace-based intervention strategies are effective in increasing participation at work and encouraging early return-to-work to reduce the consequences of LBP. The present Special Issue offers a unique opportunity to update many of the recent advances and perspectives of this health problem. A number of topics will be covered in order to attract high-quality research papers, including the following major areas: prevalence and epidemiological data, etiology, prevention, assessment and treatment approaches, and health promotion strategies for LBP. We have received a wide range of submissions, including research on the physical, psychosocial, environmental, and occupational perspectives, also focused on workplace interventions.

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