Recent Submissions

  • Improved Bi-Angle Aerosol Optical Depth Retrieval Algorithm from AHI Data Based on Particle Swarm Optimization

    Jin, Chunlin; Jiang, Xingxing; Sun, Yuxin; Wu, Shuhui; Xue, Yong; China University of Mining and Technology, Xuzhou 221116, China; University of Derby (MDPI AG, 2021-11-20)
    The Advanced Himawari Imager (AHI) aboard the Himawari-8, a new generation of geostationary meteorological satellite, has high-frequency observation, which allows it to effectively capture atmospheric variations. In this paper, we have proposed an Improved Bi-angle Aerosol optical depth (AOD) retrieval Algorithm (IBAA) from AHI data. The algorithm ignores the aerosol effect at 2.3 μm and assumes that the aerosol optical depth does not change within one hour. According to the property that the reflectivity ratio K of two observations at 2.3 μm does not change with wavelength, we constructed the equation for two observations of AHI 0.47 μm band. Then Particle Swarm Optimization (PSO) was used to solve the nonlinear equation. The algorithm was applied to the AHI observations over the Chinese mainland (80°–135°E, 15°–60°N) between April and June 2019 and hourly AOD at 0.47 μm was retrieved. We validated IBAA AOD against the Aerosol Robotic Network (AERONET) sites observation, including surrounding regions as well as the Chinese mainland, and compared it with the AHI L3 V030 hourly AOD product. Validation with AERONET of 2079 matching points shows a correlation coefficient R = 0.82, root-mean-square error RMSE = 0.27, and more than 62% AOD retrieval results within the expected error of ±(0.05 + 0.2 × AODAERONET). Although IBAA does not perform very well in the case of coarse-particle aerosols, the comparison and validation demonstrate it can estimate AHI AOD with good accuracy and wide coverage over land on the whole
  • A review of the generation of requirements specification in natural language using objects UML models and domain ontology

    Abdalazeima, Alaa; Meziane, Farid; University of Bahri, Sudan; University of Derby (Elsevier, 2021-07-14)
    In the software development life cycle, requirements engineering is the main process that is derived from users by informal interviews written in natural language by requirements engineers (analysts). The requirements may suffer from incompleteness and ambiguity when transformed into formal or semi-formal models that are not well understood by stakeholders. Hence, the stakeholder cannot verify if the formal or semi-formal models satisfy their needs and requirements. Another problem faced by requirements is that when code and/or designs are updated, it is often the case that requirements and specifically the requirements document are not updated. Hence ending with a requirements document not reflecting the implemented software.Generating requirements from the design and/or implementation document is seen by many researchers as a way to address the latter issue. This paper presents a survey of some works undertaken in the field of generation natural language specifications from object UML model using the support of an ontology. and analyzing the robustness and limitations of these existing approaches. This includes studying the generation of natural language from a formal model, review the generation of natural language from ontologies, and finally reviews studies about check to generate natural language from OntoUML.
  • Numerical analysis of shock interaction with a spherical bubble

    Onwuegbu, Solomon; Yang, Zhiyin; University of Derby (AIP Publishing, 2022-02-11)
    Two-dimensional and three-dimensional computational fluid dynamics studies of a spherical bubble impacted by a supersonic shock wave (Mach 1.25) have been performed to fully understand the complex process involved in shock–bubble interaction (SBI). The unsteady Reynolds-averaged Navier–Stokes computational approach with a coupled level set and volume of fluid method has been employed in the present study. The predicted velocities of refracted wave, transmitted wave, upstream interface, downstream interface, jet, and vortex ring agree very well with the relevant available experimental data. The predicted non-dimensional bubble and vortex velocities are also in much better agreement with the experiment data than values computed from a simple model of shock-induced Rayleigh–Taylor instability (the Richtmyer–Meshkov instability). Comprehensive flow visualization has been presented and analyzed to elucidate the SBI process from the beginning of bubble compression (continuous reflection and refraction of the acoustic wave fronts as well as the location of the incident, refracted and transmitted waves at the bubble compression stage) up to the formation of vortex rings as well as the production and distribution of vorticity. Furthermore, it is demonstrated that turbulence is generated with some small flow structures formed and more intensive mixing, i.e., turbulent mixing of helium with air starts to develop at the later stage of SBI.
  • Hydrogeophysical Characterization of Fractured Aquifers for Groundwater Exploration in the Federal District of Brazil

    Hussain, Yawar; Campos, José Eloi Guimarães; Borges, Welitom Rodrigues; Uagoda, Rogério Elias Soares; Hamza, Omar; Havenith, Hans-Balder; University of Liege, 4000 Liege, Belgium; University of Brasilia, Brasilia 70910-900, Brazil; University of Derby (MDPI AG, 2022-02-28)
    The present study applies a geophysical approach to the Federal district of Brazil, a challenging hydrogeologic setting that requires improved investigation to enhance groundwater prospecting to meet the rising water demand. The geophysical characterization of a complex hard-rock aquifer sub-system was conducted using direct current (DC) electrical resistivity tomography (ERT) integrated with surface geological information. With a total of twenty-seven ERT profiles, the resistivity acquisition was carried out using a dipole-dipole array of electrodes with an inter-electrode spacing of 10 m. Based on resistivity ranges, the interpretation of the inverted resistivity values indicated a ground profile consisting of upper dry soil, saprolite, weathered, and fresh bedrock. Along with this layered subsurface stratigraphy, the approach allowed us to map the presence of significant hydrogeological features sharp contrasting anomalies that may suggest structural controls separating high-resistivity (≥7000 Ω m) and low-resistivity (<7000 Ω m) conducting zones in the uppermost 10 m of the ground. The assumed impacts of these features on groundwater development are discussed in light of the Brasilia aquifer settings
  • Estimation of the PM2.5 and PM10 Mass Concentration over Land from FY-4A Aerosol Optical Depth Data

    Xue, Yong; University of Derby (MDPI AG, 2021-10-24)
    The purpose of this study is to estimate the particulate matter (PM2.5 and PM10) in China using the improved geographically and temporally weighted regression (IGTWR) model and Fengyun (FY-4A) aerosol optical depth (AOD) data. Based on the IGTWR model, the boundary layer height (BLH), relative humidity (RH), AOD, time, space, and normalized difference vegetation index (NDVI) data are employed to estimate the PM2.5 and PM10. The main processes of this study are as follows: firstly, the feasibility of the AOD data from FY-4A in estimating PM2.5 and PM10 mass concentrations were analysed and confirmed by randomly selecting 5–6 and 9–10 June 2020 as an example. Secondly, hourly concentrations of PM2.5 and PM10 are estimated between 00:00 and 09:00 (UTC) each day. Specifically, the model estimates that the correlation coefficient R2 of PM2.5 is 0.909 and the root mean squared error (RMSE) is 5.802 μg/m3, while the estimated R2 of PM10 is 0.915, and the RMSE is 12.939 μg/m3. Our high temporal resolution results reveal the spatial and temporal characteristics of hourly PM2.5 and PM10 concentrations on the day. The results indicate that the use of data from the FY-4A satellite and an improved time–geographically weighted regression model for estimating PM2.5 and PM10 is feasible, and replacing land use classification data with NDVI facilitates model improvement
  • Comparative Analysis of Three Structures of Second-Order Generalized Integrator and Its Application to Phase-Locked Loop of Linear Kalman Filter

    Zeng, Bo; Sun, Yuxiang; Xie, Shaojun; Nanjing University of Aeronautics and Astronautics, Nanjing City 211106, China; University of Derby (Hindawi Limited, 2022-02-12)
    The present work explores the power quality problems of a microgrid in the aviation field, such as frequency offset or waveform distortion, caused by voltage imbalance and nonlinear load, to ensure the efficient and stable flight of aircraft, unmanned aerial vehicles, and other aircraft. There are many problems such as excessive harmonics, voltage imbalance, and direct current (DC) component in aviation variable frequency power supply voltage in microgrid under different conditions. Therefore, three kinds of second-order generalized integrators (SOGIs) with different structures are combined with linear Kalman filter phase-locked loops (PLLs). Besides, intelligent sensors are utilized for signal processing. Finally, simulation experiments are conducted to compare three SOGIs. The results show that the system is stable when the parameters k1 = 738.9553, k2 = 1092108.98405, k3 = 1477.91, and Ts = 0.000125 s and k ranges in [0.5, 3]. The angular frequency of PLL output is very low under the problems of many harmonics, three-phase voltage imbalance, and DC component . The angular frequency output by the PLL finally changes linearly with a change rate of 400 πrad/s2, so that the output phase angle reaches a stable state. Thus, the proposed steady-state linear Kalman filter phase locking can accurately phase-lock the aviation variable frequency power supply. It provides an important reference for the power supply module in the microgrid to select the appropriate second-order generalized integrator to realize the accurate phase locking of the phase-locked loop under different conditions.
  • Creep-Fatigue Behaviours of Sn-Ag-Cu Solder Joints in Microelectronics Applications

    Depiver, Joshua Adeniyi; Sabuj, Mallik; Amalu, Emeka H; Lu, Yiling; University of Derby (Taylor and Francis, 2021)
    Electronic manufacturing is one of the dynamic industries in the world in terms of leading in technological advancements. At the heart of electronic assembly lies the 'soldering technology' and the 'solder joints' between electronic components and substrate. During the operation of electronic products, solder joints experience harsh environmental conditions in terms of cyclic change of temperature and vibration and exposure to moisture and chemicals. Due to the cyclic application of loads and higher operational temperature, solder joints fail primarily through creep and fatigue failures. This paper presents the creep-fatigue behaviours of solder joints in a ball grid array (BGA), soldered on a printed circuit board (PCB). Using finite element (FE) simulation, the solder joints were subjected to thermal cycling and isothermal ageing. Accelerated thermal cycling (ATC) was carried out using a temperate range from 40℃ to 150℃, and isothermal ageing was done at -40,25,75 and 150℃ temperatures for 45 days (64,800 mins). The solders studied are lead-based eutectic Sn63Pb37 and lead-free SAC305, SAC387, SAC396 and SAC405. The results were analysed using the failure criterion of equivalent stress, strain rate, deformation rate, and the solders' strain energy density. The SAC405 and SAC396 are found to possess the least stress magnitude, strain rate, deformation rate, and strain energy density damage than the lead-based eutectic Sn63Pb37 solder; they have the highest fatigue lives based on the damage mechanisms. This research provides a technique for determining the preventive maintenance time of BGA components in mission-critical systems. Furthermore, it proposes developing a new life prediction model based on a combination of the damage parameters for improved prediction.
  • Mobility Analysis during the 2020 Pandemic in a Touristic city: the Case of Cagliari

    Ferrara, Enrico; Uras, Marco; Atzori, Luigi; Bagdasar, Ovidiu; Liotta, Antonio; University of Derby; University of Cagliari; Free University of Bozen-Bolzano, Italy (IEEE, 2021-09-20)
    The impact of the 2020 COVID-19 pandemic has been significant on every aspect of life and has drastically changed our habits. Here we analyze an extensive set of traffic traces in Cagliari, one of the most touristic cities in the Mediterranean, to quantify how the different phases of the pandemic have affected not only traffic volumes but also their patterns. We put traffic in relation to different restriction levels, finding a non-linear relation. Following a 76% traffic reduction on the first lockdown, subsequent restrictions have lead to less sudden changes. We then use the official tourist-presence figures to pinpoint the traffic stations that are influenced by tourists’ mobility the most. All in all, our analysis shows that although the absolute traffic volumes roughly followed the pandemic evolution, the weekly traffic patterns changed drastically over the time, whereas the daily ones maintained more consistency.
  • Relations Between Entropy and Accuracy Trends in Complex Artificial Neural Networks

    Cavallaro, Lucia; Grassia, Marco; Fiumara, Giacomo; Mangioni, Giuseppe; De Meo, Pasquale; Carchiolo, Vincenza; Bagdasar, Ovidiu; Liotta, Antonio; University of Derby; Università degli Studi di Catania, Italy; et al. (Springer, 2022-01-01)
    Training Artificial Neural Networks (ANNs) is a non-trivial task. In the last years, there has been a growing interest in the academic community in understanding how those structures work and what strategies can be adopted to improve the efficiency of the trained models. Thus, the novel approach proposed in this paper is the inclusion of the entropy metric to analyse the training process. Herein, indeed, an investigation on the accuracy computation process in relation to the entropy of the intra-layers’ weights of multilayer perceptron (MLP) networks is proposed. From the analysis conducted on two well-known datasets with several configurations of the ANNs, we discovered that there is a connection between those two metrics (i.e., accuracy and entropy). These promising results can be helpful in defining, in the future, new criteria to evaluate the training process goodness in real-time by optimising it and allow faster detection of its trend.
  • Embedded Data Imputation for Environmental Intelligent Sensing: A Case Study

    Erhan, Laura; Di Mauro, Mario; Anjum, Ashiq; Bagdasar, Ovidiu; Song, Wei; Liotta, Antonio; University of Derby; University of Salerno, 84084 Fisciano, Italy; University of Leicester; University of Alba Iulia, 510009 Alba Iulia, Romania; et al. (MDPI AG, 2021-11-23)
    Recent developments in cloud computing and the Internet of Things have enabled smart environments, in terms of both monitoring and actuation. Unfortunately, this often results in unsustainable cloud-based solutions, whereby, in the interest of simplicity, a wealth of raw (unprocessed) data are pushed from sensor nodes to the cloud. Herein, we advocate the use of machine learning at sensor nodes to perform essential data-cleaning operations, to avoid the transmission of corrupted (often unusable) data to the cloud. Starting from a public pollution dataset, we investigate how two machine learning techniques (kNN and missForest) may be embedded on Raspberry Pi to perform data imputation, without impacting the data collection process. Our experimental results demonstrate the accuracy and computational efficiency of edge-learning methods for filling in missing data values in corrupted data series. We find that kNN and missForest correctly impute up to 40% of randomly distributed missing values, with a density distribution of values that is indistinguishable from the benchmark. We also show a trade-off analysis for the case of bursty missing values, with recoverable blocks of up to 100 samples. Computation times are shorter than sampling periods, allowing for data imputation at the edge in a timely manner.
  • Sound Level Monitoring at Live Events, Part 2 - Regulations, Practices, and Preferences

    Hill, Adam J.; Mulder, Johannes; Burton, Jon; Kok, Marcel; Lawrence, Michael; University of Derby; The Australian National University; Rational Acoustics; dBcontrol (Audio Engineering Society, 2022-01-23)
    This paper considers existing regulations, practices, and preferences regarding the measurement, monitoring, and management of sound levels at live music events. It brings together a brief overview of current regulations with the outcomes of a recent international survey of live sound engineers and evaluation of three datasets of sound measurement at live music events. The paper reveals the benefit of a 15-min time frame for the definition of equivalent continuous sound level limits in comparison to longer or shorter time frames. The paper also reveals support from the live sound engineering community for the application of sound level limits and development of a global certification system for live sound engineers.
  • Sound Level Monitoring at Live Events, Part 3 - Improved Tools and Procedures

    Hill, Adam J.; Mulder, Johannes; Burton, Jon; Kok, Marcel; Lawrence, Michael; University of Derby; The Australian National University; Rational Acoustics; dBcontrol (Audio Engineering Society, 2022-01-23)
    This is the final installment in a series of three papers looking into the subject of sound level monitoring at live events. The first two papers revealed how practical shortcomings and audience and neighbor considerations (in the form of sound level limits) can impact the overall live experience. This paper focuses on an improved set of tools for sound engineers to ensure a high-quality and safe live event experience while maintaining compliance with local sound level limits. This includes data processing tools to predict future limit violations and guidelines for improved user interface design. Practical procedures, including effective sound level monitoring practice, alongside resourceful mixing techniques are presented to provide a robust toolset that can allow sound engineers to perform their best without compromising the listening experience in response to local sound level limits.
  • Empowering digital supply chain transformation by utilizing Industry 4.0, Smart Factories, Standards, Smart Contracts and Blockchains

    Takhar, Sukhraj; University of Derby (2022-01-20)
    Companies that place products onto the marketplace, whether they are internally manufactured or sourced from a supply chain, are often faced with ever increasing demands for data from a diverse set of stakeholders, requiring a multitude of different data reporting needs to be identified and requested from suppliers, ranging from: the identification of raw materials; number of products in WIP state within facilities; finished stock levels in storage; demand needs from customers; numerous what-if scenarios; exposure analysis; safe use and disposal instructions; through to obligatory reporting data under chemical regulation to identify the presence of any hazardous chemicals on finished products; through to the emerging Environmental, Social, and Governance data reporting needs in order to gain access to future sources of funding. Blockchains are often mistakenly viewed as being solely related to recording transactional data related to some form of electronic payment mechanism. Smart contracts enable contracts between buyers and suppliers to create contract terms in an electronic manner and processed in an efficient and automated manner. This paper contributes to existing literature by identifying a research gap in transforming the currently diverse manually intensive data collection tasks, via digital technologies such as supply chain collection of reporting tasks embedded into smart contracts, with digital data flows supporting IPC-CFX and IPC technical standards, recording data collection requests and responses in real-time within a blockchain, which is then verified by applicable supply chain actors, to ensure data consistency, accuracy and verification. The proposed design enables companies to address existing state supply chain data collection tasks using as structured framework, enabling appropriate risks to be identified and managed accordingly in a more timely and consistent manner. The design may then be expanded in a consistent manner as new supply chain reporting needs arise.
  • Estimation of total groundwater reserves and delineation of weathered/fault zones for aquifer potential: A case study from the Federal District of Brazil

    Hussain, Yawar; Borges, Welitom; Uagoda, Rogerio; Moura, Cristiane; Maciel, Susanne; Hamza, Omar; Havenith, Hans-Balder; Liège University; University of Derby; University of Brasilia (Walter de Gruyter GmbH, 2021-08-18)
    In the Federal District of Brazil, groundwater extraction is challenged by fractured aquifers with difficulty in identification of hydraulic traps and significant uncertainty in the estimation of recharge potential. This study aims to optimize the demarcation of new locations of tubular wells by the aid of geophysical investigation. In the first stage of this study, the total exploitable amount of groundwater were calculated from the information of the physical environment and the existing wells. Second, electrical resistivity tomography (ERT) method was carried out on the selected sites – based on their surficial characteristics. The possible hydraulic traps (where groundwater might exist) were identified from the inversion of the resistivity measured by the dipole–dipole array and from the delineation of the resultant conducting zones (including the weathered rocks and fractures). Using this approach, we predicted the position and number of tubular wells required and ranked them according to their potential productivity. The study provides a promising framework for investigating groundwater in fractured aquifers.
  • Cure mechanism and kinetic prediction of biobased glass/polyfurfuryl alcohol prepreg by model-free kinetics

    Odiyi, D.C.; Sharif, T.; Choudhry, R.S.; Mallik, S.; University of Derby (Elsevier BV, 2022-12-26)
    This paper explains the cure reaction mechanisms of a novel bio-based glass/Polyfurfuryl prepreg using an experimental and numerical approach. It suggests optimized parameters of rapid curing for isothermal curing conditions. Dynamic scanning calorimetry (DSC) under non-isothermal conditions was used to determine parameters for the two model-free kinetic methods Friedman and Ozawa Flynn Wall. The average activation energy (88.9 ± 4.9 kJ/mol) was found to be higher than that reported for neat resin in literature. The validated models were used to gain insight into reaction mechanisms and were used to predict the evolution of reaction time under isothermal conditions for the PFA prepreg. This suggested that the curing time can be reduced to half by rapidly heating and maintaining isothermal conditions at 160°C, which provides faster curing using hot-press. In addition, dynamic mechanical analysis (DMA) was carried out to compare the manufacturer recommended cure cycle with the rapid cycle suggested.
  • Mechanical Properties and Failure Mechanisms of Novel Resin-infused Thermoplastic and Conventional Thermoset 3D Fabric Composites

    Shah, Syed Zulfiqar Hussain; Megat-Yusoff, Puteri Sri Melor; Karuppanan, Saravanan; Choudhry, Rizwan Saeed; Ahmad, Faiz; Sajid, Zubair; Universiti Teknologi Petronas, Perak, Malaysia; University of Derby (Springer Science and Business Media LLC, 2021-10-16)
    This paper presents an extensive comparison of the mechanical properties and failure mechanisms of a recently developed thermoplastic (Elium ®) 3D fabric-reinforced composite (3D-FRC) with the conventional thermoset (epoxy) 3D-FRC. Experiments involved tensile tests, compression tests, V-notch shear tests, and short beam shear tests for specimens produced through the vacuum-assisted resin infusion process in each case. These tests were used for the determination of in-plane elastic constants, failure strengths and for investigating the failure mechanisms. A micro-mechanical model validated against these experiments was used to predict the remaining orthotropic elastic constants. This work enhances our understanding of the mechanics of infusible thermoplastic 3D-FRC as a new class of emerging materials and provides useful data which substantiates that this unconventional thermoplastic resin is also easier to recycle, uses similar manufacturing processes and can be a suitable replacement for conventional thermoset resins.
  • Advances in Manufacturing Technology XXXIV

    Shafik, Mahmoud; Case, Keith; University of Derby (IOS Press, 2021-09-07)
    The development of technologies and management of operations is key to sustaining the success of manufacturing businesses, and since the late 1970s, the International Conference on Manufacturing Research (ICMR) has been a major annual event for academics and industrialists engaged in manufacturing research. The conference is renowned as a friendly and inclusive platform that brings together a broad community of researchers who share a common goal. This book presents the proceedings of ICMR2021, the 18th International Conference on Manufacturing Research, incorporating the 35th National Conference on Manufacturing Research, and held in Derby, UK, from 7 to 10 September 2021. The theme of the ICMR2021 conference is digital manufacturing. Within the context of Industrial 4.0, ICMR2021 provided a platform for researchers, academics and industrialists to share their vision, knowledge and experience, and to discuss emerging trends and new challenges in the field. The 60 papers included in the book are divided into 10 parts, each covering a different area of manufacturing research. These are: digital manufacturing, smart manufacturing; additive manufacturing; robotics and industrial automation; composite manufacturing; machining processes; product design and development; information and knowledge management; lean and quality management; and decision support and production optimization. The book will be of interest to all those involved in developing and managing new techniques in manufacturing industry.
  • WHAM: To Asymmetry and Beyond!

    Dring, Mark; Wiggins, Bruce; University of Derby (Institute of Acoustics, 2021-11-18)
    Auralisation of acoustic spaces is a tool used in many industries. To provide a truly representative result, the systems used must capture and deliver critical, dynamic, psychoacoustic cues that react to the listeners head position. The WHAM (Webcam Head-tracked Ambisonics) website ( utilises webcams to provide auralisation that reacts to head rotation via the browser using standard HRTF data; visitors to the site can experience very high order horizontal only Ambisonic to binaural presentation of room responses. In its initial inception, orders were limited to 7th order asymmetry for the final binaural presentation, which previous research has shown to fall below a transparent perceptual threshold compared to orders up to 31st. This paper documents the developments to deliver beyond 7th order and improvements in functionality made to the WHAM website and open-source JS Ambisonics software library, that continue to make it a useful remote resource for acoustic auralisation purposes.
  • Shape optimisation of cold roll formed sections considering effects of cold working

    Qadir, Sangar; Nguyen, Van Bac; Hajirasouliha, Iman; Ceranic, Boris; Tracada, Eleni; English, Martin; University of Derby; University of Sheffield; Hadley Industries plc (Elsevier, 2021-11-06)
    The design development of new cold roll formed sections can lead to a significant reduction in material costs if the sections are optimised for strength performance considering the effect of shapes and change of material properties by cold working during the manufacturing process. In this paper, the buckling and ultimate strengths of cold roll formed channel and zed sections with intermediate stiffeners under distortional bending were studied using experimentally validated Finite Element (FE) models. The section strength was optimised using FE modelling and optimisation based on Design Of Experiments (DOE) and response surface methodology. A nonlinear FE model was first developed for a referenced section subject to four-point bending tests and the section’s dimensions and material properties were defined as geometric parameters using the DOE technique. A response surface was then used to determine the influences of the stiffeners’ location, shape, size, and cold working at the section corners and stiffener bends during the manufacturing process. A multi-objective genetic algorithm method was deployed to obtain optimal shapes for the sections with maximum buckling and ultimate strengths while keeping the same amount of material used. The results revealed that the ultimate bending moment capacities could be enhanced up to 17% and 25% for the channel and zed sections, respectively. Including the cold working effect had considerable enhancement in the ultimate moment capacities, with a maximum increase of 5%. The results of this study clearly demonstrated an efficient and effective approach to optimise design for strength performance of cold roll formed sections.
  • Sound Level Monitoring at Live Events, Part 1–Live Dynamic Range

    Hill, Adam J.; Mulder, Johannes; Burton, Jon; Kok, Marcel; Lawrence, Michael; University of Derby; The National University of Australia; dBcontrol; Rational Acoustics (Audio Engineering Society, 2021-11-08)
    Musical dynamics are often central within pieces of music and are therefore likely to be fundamental to the live event listening experience. While metrics exist in broadcasting and recording to quantify dynamics, such measures work on high-resolution data. Live event sound level monitoring data is typically low-resolution (logged at one second intervals or less), which necessitates bespoke musical dynamics quantification. Live dynamic range (LDR) is presented and validated here to serve this purpose, where measurement data is conditioned to remove song breaks and sound level regulation-imposed adjustments to extract the true musical dynamics from a live performance. Results show consistent objective performance of the algorithm, as tested on synthetic data as well as datasets from previous performances.

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