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Volume 11, February-1

Appl. Sci., Volume 11, Issue 4 (February-2 2021) – 621 articles

Cover Story (view full-size image): Polymeric bioresorbable stents (BRS) are designed to mitigate the side effects of traditional inert metallic stents, such as chronic inflammation and late thrombosis, but are not bioactive. To improve their biointegration, it is crucial that stents undergo autologous luminal endothelialization. Moreover, the current fabrication techniques of stents, extrusion of tubes and laser cutting, do not allow performing customizable stents addressed to patients with special needs. This article investigates the effect of different functionalization strategies onto solvent-cast poly(L-lactic acid) surfaces with the capacity to accelerate the surface endothelialization and the fabrication of 3D-printed BRS via the solvent-cast direct writing technique. View this paper
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Open AccessArticle
An Empirical Investigation of Software Customization and Its Impact on the Quality of Software as a Service: Perspectives from Software Professionals
Appl. Sci. 2021, 11(4), 1677; https://0-doi-org.brum.beds.ac.uk/10.3390/app11041677 - 26 Feb 2021
Viewed by 639
Abstract
Although customization plays a significant role in the provision of software as a service (SaaS), delivering a customizable SaaS application that reflects the tenant’s specific requirements with acceptable level of quality is a challenge. Drawing on a pr-developed software customization model for SaaS [...] Read more.
Although customization plays a significant role in the provision of software as a service (SaaS), delivering a customizable SaaS application that reflects the tenant’s specific requirements with acceptable level of quality is a challenge. Drawing on a pr-developed software customization model for SaaS quality, two fundamental objectives of this study were to determine whether different software customization approaches have direct impacts on SaaS quality, and also to assess the construct reliability and construct validity of the model. A questionnaire-based survey was used to collect data from 244 software professionals with experience in SaaS development. Structural equation modeling was employed to test the construct reliability, construct validity, and research hypotheses. The measurement model assessment suggested that the six-construct model with 39 items exhibited good construct reliability and construct validity. The findings of the structural model assessment show that all customization approaches other than the integration approach significantly influence the quality of SaaS applications. The findings also indicate that both configuration and composition approaches have positive impacts on SaaS quality, while the impacts of the other approaches are negative. The empirical assessment and evaluation of this model, which features a rich set of information, provides considerable benefits to both researchers and practitioners. Full article
(This article belongs to the Special Issue Requirements Engineering: Practice and Research)
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Open AccessArticle
Plume Divergence and Discharge Oscillations of an Accessible Low-Power Hall Effect Thruster
Appl. Sci. 2021, 11(4), 1973; https://0-doi-org.brum.beds.ac.uk/10.3390/app11041973 - 23 Feb 2021
Viewed by 412
Abstract
Hall effect thrusters (HETs) are an increasingly utilized proportion of electric propulsion devices due to their high thrust-to-power ratio. To enable an accessible research thruster, our team used inexpensive materials and simplified structures to fabricate the 44-mm-diameter Western Hall Thruster (WHT44). Anode flow, [...] Read more.
Hall effect thrusters (HETs) are an increasingly utilized proportion of electric propulsion devices due to their high thrust-to-power ratio. To enable an accessible research thruster, our team used inexpensive materials and simplified structures to fabricate the 44-mm-diameter Western Hall Thruster (WHT44). Anode flow, discharge voltage, magnet current, and cathode flow fraction (CFF) were independently swept while keeping all other parameters constant. Simultaneously, a Faraday probe was used to test plume properties at a variety of polar coordinate distances, and an oscilloscope was used to capture discharge oscillation behavior. Plasma plume divergence angle at a fixed probe distance of 4.5 thruster diameters increased with increasing anode flow, varying from 36.7° to 37.4°. Moreover, divergence angle decreased with increasing discharge voltage, magnet current, and CFF, by 0.3°, 0.2°, and 8°, respectively, over the span of the swept parameters. Generally, the thruster exhibited a strong oscillation near 90 kHz, which is higher than a similarly sized HET (20–60 kHz). The WHT44 noise frequency spectra became more broadband and the amplitude increased at a CFF of less than 1.5% and greater than 26%. Only the low flow and low voltage operating conditions showed a quiescent sinusoidal discharge current; otherwise, the discharge current probability distribution was Gaussian. This work demonstrates that the WHT44 thruster, designed for simplicity of fabrication, is a viable tool for research and academic purposes. Full article
(This article belongs to the Special Issue Plasmas for Space Propulsion)
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Open AccessArticle
An Immersive Serious Game for the Behavioral Assessment of Psychological Needs
Appl. Sci. 2021, 11(4), 1971; https://0-doi-org.brum.beds.ac.uk/10.3390/app11041971 - 23 Feb 2021
Viewed by 458
Abstract
Motivation is an essential component in mental health and well-being. In this area, researchers have identified four psychological needs that drive human behavior: attachment, self-esteem, orientation and control, and maximization of pleasure and minimization of distress. Various self-reported scales and interviews tools have [...] Read more.
Motivation is an essential component in mental health and well-being. In this area, researchers have identified four psychological needs that drive human behavior: attachment, self-esteem, orientation and control, and maximization of pleasure and minimization of distress. Various self-reported scales and interviews tools have been developed to assess these dimensions. Despite the validity of these, they are showing limitations in terms of abstractation and decontextualization and biases, such as social desirability bias, that can affect responses veracity. Conversely, virtual serious games (VSGs), that are games with specific purposes, can potentially provide more ecologically valid and objective assessments than traditional approaches. Starting from these premises, the aim of this study was to investigate the feasibility of a VSG to assess the four personality needs. Sixty subjects participated in five VSG sessions. Results showed that the VSG was able to recognize attachment, self-esteem, and orientation and control needs with a high accuracy, and to a lesser extent maximization of pleasure and minimization of distress need. In conclusion, this study showed the feasibility to use a VSG to enhance the assessment of psychological behavioral-based need, overcoming biases presented by traditional assessment. Full article
(This article belongs to the Special Issue Applications of Virtual, Augmented, and Mixed Reality)
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Open AccessArticle
Impact of the Sub-Grid Scale Turbulence Model in Aeroacoustic Simulation of Human Voice
Appl. Sci. 2021, 11(4), 1970; https://0-doi-org.brum.beds.ac.uk/10.3390/app11041970 - 23 Feb 2021
Viewed by 485
Abstract
In an aeroacoustic simulation of human voice production, the effect of the sub-grid scale (SGS) model on the acoustic spectrum was investigated. In the first step, incompressible airflow in a 3D model of larynx with vocal folds undergoing prescribed two-degree-of-freedom oscillation was simulated [...] Read more.
In an aeroacoustic simulation of human voice production, the effect of the sub-grid scale (SGS) model on the acoustic spectrum was investigated. In the first step, incompressible airflow in a 3D model of larynx with vocal folds undergoing prescribed two-degree-of-freedom oscillation was simulated by laminar and Large-Eddy Simulations (LES), using the One-Equation and Wall-Adaptive Local-Eddy (WALE) SGS models. Second, the aeroacoustic sources and the sound propagation in a domain composed of the larynx and vocal tract were computed by the Perturbed Convective Wave Equation (PCWE) for vowels [u:] and [i:]. The results show that the SGS model has a significant impact not only on the flow field, but also on the spectrum of the sound sampled 1 cm downstream of the lips. With the WALE model, which is known to handle the near-wall and high-shear regions more precisely, the simulations predict significantly higher peak volumetric flow rates of air than those of the One-Equation model, only slightly lower than the laminar simulation. The usage of the WALE SGS model also results in higher sound pressure levels of the higher harmonic frequencies. Full article
(This article belongs to the Special Issue Computational Methods and Engineering Solutions to Voice II)
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Open AccessFeature PaperArticle
Climate Change Impacts on Salt Marsh Blue Carbon, Nitrogen and Phosphorous Stocks and Ecosystem Services
Appl. Sci. 2021, 11(4), 1969; https://0-doi-org.brum.beds.ac.uk/10.3390/app11041969 - 23 Feb 2021
Viewed by 425
Abstract
Salt marshes are valuable ecosystems, as they provide food, shelter, and important nursery areas for fish and macroinvertebrates, and a wide variety of ecosystem services for human populations. These ecosystem services heavily rely on the floristic composition of the salt marshes with different [...] Read more.
Salt marshes are valuable ecosystems, as they provide food, shelter, and important nursery areas for fish and macroinvertebrates, and a wide variety of ecosystem services for human populations. These ecosystem services heavily rely on the floristic composition of the salt marshes with different species conferring different service values and different adaptation and resilience capacities towards ecosystem stressors. Blue carbon, nitrogen, and phosphorous stocks are no exception to this, and rely on the interspecific differences in the primary production metabolism and physiological traits. Furthermore, these intrinsic physiological characteristics also modulate the species response to any environmental stressor, such as the ones derived from ongoing global changes. This will heavily shape transitional ecosystem services, with significant changes of the ecosystem value of the salt marshes in terms of cultural, provisioning, regulating, and supporting ecosystem services, with a special emphasis on the possible alterations of the blue carbon, nitrogen, and phosphorous stocks retained in these key environments. Thus, the need to integrate plant physiological characteristics and feedbacks towards the expected climate change-driven stressors becomes evident to accurately estimate the ecosystem services of the salt marsh community, and transfer these fundamental services into economic assets, for a fluid communication of the ecosystems value to stakeholders, decision and policy makers, and environmental management entities. Full article
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Open AccessArticle
Effects of Tooth Surface Crack Propagation on Meshing Stiffness and Vibration Characteristic of Spur Gear System
Appl. Sci. 2021, 11(4), 1968; https://0-doi-org.brum.beds.ac.uk/10.3390/app11041968 - 23 Feb 2021
Viewed by 368
Abstract
Tooth surface cracks are considered as the early stage of the development of tooth surface spalling failure. Understanding the excitation mechanism of surface cracks has a great significance in the early diagnosis of spalling faults. However, there are few studies on the dynamic [...] Read more.
Tooth surface cracks are considered as the early stage of the development of tooth surface spalling failure. Understanding the excitation mechanism of surface cracks has a great significance in the early diagnosis of spalling faults. However, there are few studies on the dynamic modelling of surface cracks, and the influence mechanism of surface cracking on the dynamic characteristics of a gear system is also not yet clear during its propagation process. Thus, an analytical calculation model of the meshing stiffness of gear with tooth surface crack is developed. Then, a dynamic model of a spur gear system with six degrees of freedom (DOF) is established based on the proposed surface crack calculation model. The effects of surface crack propagation on the meshing stiffness and dynamic characteristics of gear system are investigated. The results show that the side frequencies of dynamic transmission error (DTE) are more sensitive than those of the acceleration responses during the surface crack propagation, which is more favorable to the surface crack fault diagnosis. Compared to the traditional spalling fault model, the proposed model can accurately characterize the dynamic characteristics of a gear system with the early spalling defect. Full article
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Open AccessArticle
Diagnosis of Sepsis by AI-Aided Proteomics Using 2D Electrophoresis Images of Patient Serum Incorporating Transfer Learning for Deep Neural Networks
Appl. Sci. 2021, 11(4), 1967; https://0-doi-org.brum.beds.ac.uk/10.3390/app11041967 - 23 Feb 2021
Viewed by 434
Abstract
An accuracy of ≥98% was achieved in sepsis diagnosis using serum samples from 30 sepsis patients and 68 healthy individuals and a high-performance two-dimensional polyacrylamide gel electrophoresis (HP-2D-PAGE) method developed here with deep learning and transfer learning algorithms. In this method, small-scale target [...] Read more.
An accuracy of ≥98% was achieved in sepsis diagnosis using serum samples from 30 sepsis patients and 68 healthy individuals and a high-performance two-dimensional polyacrylamide gel electrophoresis (HP-2D-PAGE) method developed here with deep learning and transfer learning algorithms. In this method, small-scale target domain data, which are collected to achieve our objective, are inputted directly into a model constructed with source domain data which are collected from a different domain from the target; target vectors are estimated with the outputted target domain data and applied to refine the model. Recognition performance of small-scale data is improved by reusing all layers, including the output layers of the neural network. Proteomics is generally considered the ultimate bio-diagnostic technique and provides extremely high information density in its two-dimensional electrophoresis images, but extracting the data has posed a basic problem. The present study is expected to solve that problem and will be an important breakthrough for practical utilization and future perspectives of proteomics in clinics after evaluation in clinical settings. Full article
(This article belongs to the Special Issue AI Proteomics: Technologies and Their Potential)
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Open AccessArticle
Review on Quality Control Methods in Metal Additive Manufacturing
Appl. Sci. 2021, 11(4), 1966; https://0-doi-org.brum.beds.ac.uk/10.3390/app11041966 - 23 Feb 2021
Viewed by 433
Abstract
Metal additive manufacturing (AM) has several similarities to conventional metal manufacturing, such as welding and cladding. During the manufacturing process, both metal AM and welding experience repeated partial melting and cooling, referred to as deposition. Owing to deposition, metal AM and welded products [...] Read more.
Metal additive manufacturing (AM) has several similarities to conventional metal manufacturing, such as welding and cladding. During the manufacturing process, both metal AM and welding experience repeated partial melting and cooling, referred to as deposition. Owing to deposition, metal AM and welded products often share common product quality issues, such as layer misalignment, dimensional errors, and residual stress generation. This paper comprehensively reviews the similarities in quality monitoring methods between metal AM and conventional metal manufacturing. It was observed that a number of quality monitoring methods applied to metal AM and welding are interrelated; therefore, they can be used complementarily with each other. Full article
(This article belongs to the Special Issue Additive Manufacturing and System: From Methods to Applications)
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Open AccessArticle
Region-of-Interest-Based Cardiac Image Segmentation with Deep Learning
Appl. Sci. 2021, 11(4), 1965; https://0-doi-org.brum.beds.ac.uk/10.3390/app11041965 - 23 Feb 2021
Cited by 1 | Viewed by 430
Abstract
Despite the promising results obtained by deep learning methods in the field of medical image segmentation, lack of sufficient data always hinders performance to a certain degree. In this work, we explore the feasibility of applying deep learning methods on a pilot dataset. [...] Read more.
Despite the promising results obtained by deep learning methods in the field of medical image segmentation, lack of sufficient data always hinders performance to a certain degree. In this work, we explore the feasibility of applying deep learning methods on a pilot dataset. We present a simple and practical approach to perform segmentation in a 2D, slice-by-slice manner, based on region of interest (ROI) localization, applying an optimized training regime to improve segmentation performance from regions of interest. We start from two popular segmentation networks, the preferred model for medical segmentation, U-Net, and a general-purpose model, DeepLabV3+. Furthermore, we show that ensembling of these two fundamentally different architectures brings constant benefits by testing our approach on two different datasets, the publicly available ACDC challenge, and the imATFIB dataset from our in-house conducted clinical study. Results on the imATFIB dataset show that the proposed approach performs well with the provided training volumes, achieving an average Dice Similarity Coefficient of the whole heart of 89.89% on the validation set. Moreover, our algorithm achieved a mean Dice value of 91.87% on the ACDC validation, being comparable to the second best-performing approach on the challenge. Our approach provides an opportunity to serve as a building block of a computer-aided diagnostic system in a clinical setting. Full article
(This article belongs to the Special Issue Soft Computing in Applied Sciences and Industrial Applications)
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Open AccessArticle
Design and Validation of an Adjustable Large-Scale Solar Simulator
Appl. Sci. 2021, 11(4), 1964; https://0-doi-org.brum.beds.ac.uk/10.3390/app11041964 - 23 Feb 2021
Viewed by 321
Abstract
This work presents an adjustable large-scale solar simulator based on metal halide lamps. The design procedure is described with regards to the construction and spatial arrangement of the lamps and the designed optical system. Rotation and translation of the lamp array allow setting [...] Read more.
This work presents an adjustable large-scale solar simulator based on metal halide lamps. The design procedure is described with regards to the construction and spatial arrangement of the lamps and the designed optical system. Rotation and translation of the lamp array allow setting the direction and the intensity of the luminous flux on the horizontal plane. To validate the built model, irradiance nonuniformity and temporal instability tests were carried out assigning Class A, B, or C for each test, according to the International Electrotechnical Commission (IEC) standards requirements. The simulator meets the Class C standards on a 200 × 90 cm test plane, Class B on 170 × 80 cm, and Class A on 80 × 40 cm. The temporal instability returns Class A results for all the measured points. Lastly, a PV panel is characterized by tracing the I–V curve under simulated radiation, under outdoor natural sunlight, and with a numerical method. The results show a good approximation. Full article
(This article belongs to the Section Energy)
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Open AccessArticle
Robust Long-Term Visual Object Tracking via Low-Rank Sparse Learning for Re-Detection
Appl. Sci. 2021, 11(4), 1963; https://0-doi-org.brum.beds.ac.uk/10.3390/app11041963 - 23 Feb 2021
Viewed by 352
Abstract
The Discriminative Correlation Filter (DCF) has been universally recognized in visual object tracking, thanks to its excellent accuracy and high speed. Nevertheless, these DCF-based trackers perform poorly in long-term tracking. The reasons include the following aspects—first, they have low adaptability to significant appearance [...] Read more.
The Discriminative Correlation Filter (DCF) has been universally recognized in visual object tracking, thanks to its excellent accuracy and high speed. Nevertheless, these DCF-based trackers perform poorly in long-term tracking. The reasons include the following aspects—first, they have low adaptability to significant appearance changes in long-term tracking and are prone to tracking failure; second, these trackers lack a practical re-detection module to find the target again after tracking failure. In our work, we propose a new long-term tracking strategy to solve these issues. First, we make the best of the static and dynamic information of the target by introducing the motion features to our long-term tracker and obtain a more robust tracker. Second, we introduce a low-rank sparse dictionary learning method for re-detection. This re-detection module can exploit a correlation among these training samples and alleviate the impact of occlusion and noise. Third, we propose a new reliability evaluation method to model an adaptive update, which can switch expediently between the tracking module and the re-detection module. Massive experiments demonstrate that our proposed approach has an obvious improvement in precision and success rate over these state-of-the-art trackers. Full article
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Open AccessArticle
Formulation and Thermomechanical Characterization of Functional Hydrogels Based on Gluten Free Matrices Enriched with Antioxidant Compounds
Appl. Sci. 2021, 11(4), 1962; https://0-doi-org.brum.beds.ac.uk/10.3390/app11041962 - 23 Feb 2021
Viewed by 346
Abstract
Native starch from potatoes and hybrid carrageenans from the red alga Mastocarpus stellatus have been used as gluten-free gelling matrices to obtain functional hydrogels. The enrichment of gelling matrices with antioxidant compounds from natural sources is an increasing market trend. In this context, [...] Read more.
Native starch from potatoes and hybrid carrageenans from the red alga Mastocarpus stellatus have been used as gluten-free gelling matrices to obtain functional hydrogels. The enrichment of gelling matrices with antioxidant compounds from natural sources is an increasing market trend. In this context, this work is aimed at the formulation and thermo-rheological characterization of functional hydrogels using potato starch from agro-industrial waste and kappa–iota hybrid carrageenans extracted from the above seaweed, enriched with antioxidant compounds from different agro-industrial products, such as waste coming from the pruning of green tea and two varieties of hops used in the brewing industry. Environmentally friendly technologies such as microwave hydrodiffusion and gravity, microwave-assisted extraction, ultrasounds and autohydrolysis were used for the recovery of antioxidant compounds. The results point out that functional hydrogels based on potato starch and hybrid carrageenans with a wide range of viscoelastic features can be achieved, with the particularity of being suitable for people with celiac disease. The incorporation of selected antioxidant extracts from vegetable by-products involved the drop (about tenfold) of the viscous and elastic properties of the formulated gels. The sequential combination of the above treatments could even further expand the thermo-rheological properties of formulated hydrogels, with potential application in functional foodstuffs and novel gluten-free goods. Full article
(This article belongs to the Special Issue Gluten-Free Foods)
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Open AccessArticle
Vibration Isolation of a Surveillance System Equipped in a Drone with Mode Decoupling
Appl. Sci. 2021, 11(4), 1961; https://0-doi-org.brum.beds.ac.uk/10.3390/app11041961 - 23 Feb 2021
Viewed by 354
Abstract
Vibration isolation with mode decoupling plays a crucial role in the design of an intelligent robotic system. Specifically, a coupled multi-degree-of-freedom (multi-DOF) model accurately predicts responses of system dynamics; hence, it is useful for vibration isolation and control with mode decoupling. This study [...] Read more.
Vibration isolation with mode decoupling plays a crucial role in the design of an intelligent robotic system. Specifically, a coupled multi-degree-of-freedom (multi-DOF) model accurately predicts responses of system dynamics; hence, it is useful for vibration isolation and control with mode decoupling. This study presents a vibration isolation method with mode decoupling based on system identification, including a coupled multi-DOF model to design intelligent robotic systems. Moreover, the entire procedure is described, including the derivation of the governing equation of the coupled multi-DOF model, estimation of the frequency response function, and parameter estimation using least squares approximation. Furthermore, the suggested methods were applied for a mobile surveillance system suffering from resonances with mode coupling; it made the monitoring performance of the surveillance camera deteriorate. The resonance problem was mitigated by installing vibration isolators, but limited to eliminate the coupling effects of natural frequency deterioration performances of vibration isolation. More seriously, system identification with a simple decoupled model limits the prediction of this phenomenon. Hence, it is difficult to enhance the performance of vibration isolators. In contrast, the presented method can accurately predict the vibration phenomenon and plays a critical role in vibration isolation. Therefore, dynamic characteristics were predicted based on a vibration isolator using the coupled three-DOF model, and a final suggestion is presented here. The experiments demonstrated that the suggested configuration decreased vibration up to 98.3%, 94.0%, and 94.5% in the operational frequency range, i.e., 30–85 Hz, compared to the original surveillance system in the fore-after, side-by-side, and vertical directions, respectively. The analysis suggests that the present method and procedure effectively optimize the vibration isolation performances of a drone containing a surveillance system. Full article
(This article belongs to the Special Issue Noise Reduction and Vibration Isolation)
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Open AccessArticle
Theoretical Analysis and Design of an Innovative Coil Structure for Transcranial Magnetic Stimulation
Appl. Sci. 2021, 11(4), 1960; https://0-doi-org.brum.beds.ac.uk/10.3390/app11041960 - 23 Feb 2021
Viewed by 290
Abstract
Previous research showed that pulsed functional magnetic stimulation can activate brain tissue with optimum intensity and frequency. Conventional stimulation coils are always set as a figure-8 type or Helmholtz. However, the magnetic fields generated by these coils are uniform around the target, and [...] Read more.
Previous research showed that pulsed functional magnetic stimulation can activate brain tissue with optimum intensity and frequency. Conventional stimulation coils are always set as a figure-8 type or Helmholtz. However, the magnetic fields generated by these coils are uniform around the target, and their magnetic stimulation performance still needs improvement. In this paper, a novel type of stimulation coil is proposed to shrink the irritative zone and strengthen the stimulation intensity. Furthermore, the electromagnetic field distribution is calculated and measured. Based on numerical simulations, the proposed coil is compared to traditional coil types. Moreover, the influential factors, such as the diameter and the intersection angle, are also analyzed. It was demonstrated that the proposed coil has a better performance in comparison with the figure-8 coil. Thus, this work suggests a new way to design stimulation coils for transcranial magnetic stimulation. Full article
(This article belongs to the Section Electrical, Electronics and Communications Engineering)
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Open AccessArticle
Data Assimilation of AOD and Estimation of Surface Particulate Matters over the Arctic
Appl. Sci. 2021, 11(4), 1959; https://0-doi-org.brum.beds.ac.uk/10.3390/app11041959 - 23 Feb 2021
Viewed by 381
Abstract
In this study, more accurate information on the levels of aerosol optical depth (AOD) was calculated from the assimilation of the modeled AOD based on the optimal interpolation method. Additionally, more realistic levels of surface particulate matters over the Arctic were estimated using [...] Read more.
In this study, more accurate information on the levels of aerosol optical depth (AOD) was calculated from the assimilation of the modeled AOD based on the optimal interpolation method. Additionally, more realistic levels of surface particulate matters over the Arctic were estimated using the assimilated AOD based on the linear relationship between the particulate matters and AODs. In comparison to the MODIS observation, the assimilated AOD was much improved compared with the modeled AOD (e.g., increase in correlation coefficients from −0.15–0.26 to 0.17–0.76 over the Arctic). The newly inferred monthly averages of PM10 and PM2.5 for April–September 2008 were 2.18–3.70 μg m−3 and 0.85–1.68 μg m−3 over the Arctic, respectively. These corresponded to an increase of 140–180%, compared with the modeled PMs. In comparison to in-situ observation, the inferred PMs showed better performances than those from the simulations, particularly at Hyytiala station. Therefore, combining the model simulation and data assimilation provided more accurate concentrations of AOD, PM10, and PM2.5 than those only calculated from the model simulations. Full article
(This article belongs to the Special Issue Air Pollution II)
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Open AccessArticle
Performances Assessment of Tricalcium Aluminate as an Innovative Material for Thermal Energy Storage Applications
Appl. Sci. 2021, 11(4), 1958; https://0-doi-org.brum.beds.ac.uk/10.3390/app11041958 - 23 Feb 2021
Viewed by 314
Abstract
In this paper, tricalcium aluminate hexahydrate (Ca3Al2O6·6H2O), thanks to its appropriate features, was assessed as an innovative, low-cost and nontoxic material for thermochemical energy storage applications. The high dehydration heat and the occurring temperature (200–300 [...] Read more.
In this paper, tricalcium aluminate hexahydrate (Ca3Al2O6·6H2O), thanks to its appropriate features, was assessed as an innovative, low-cost and nontoxic material for thermochemical energy storage applications. The high dehydration heat and the occurring temperature (200–300 °C) suggest that this material could be more effective than conventional thermochemical storage materials operating at medium temperature. For these reasons, in the present paper, Ca3Al2O6·6H2O hydration/dehydration performances, at varying synthesis procedures, were assessed. Experimentally, a co-precipitation and a solid–solid synthesis were studied in order to develop a preparation method that better provides a performing material for this specific application field. Thermal analysis (TGA, DSC) and structural characterization (XRD) were performed to evaluate the thermochemical behavior at medium temperature of the prepared materials. Furthermore, reversibility of the dehydration process and chemical stability of the obtained materials were investigated through cycling dehydration/hydration tests. The promising results, in terms of de/hydration performance and storage density (≈200 MJ/m3), confirm the potential effectiveness of this material for thermochemical energy storage applications and encourage further developments on this topic. Full article
(This article belongs to the Special Issue Materials for Thermal Energy Storage-Volume II)
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Open AccessArticle
Viability of Cupola Slag as an Alternative Eco-Binder and Filler in Concrete and Mortars
Appl. Sci. 2021, 11(4), 1957; https://0-doi-org.brum.beds.ac.uk/10.3390/app11041957 - 23 Feb 2021
Viewed by 304
Abstract
Obtaining new materials capable of meeting society’s demands motivates the search for new solutions that are capable of satisfying twofold requirements: respect for the environment and obtaining more durable and resistant materials. Cupola slag is a by-product generated in the process of obtaining [...] Read more.
Obtaining new materials capable of meeting society’s demands motivates the search for new solutions that are capable of satisfying twofold requirements: respect for the environment and obtaining more durable and resistant materials. Cupola slag is a by-product generated in the process of obtaining ductile iron. When the slag undergoes rapid cooling, its vitrification is favored, leaving the silica in an amorphous structure and, thus, susceptible to reacting. Through reaction, the slag can develop cementing properties and cement can consequently be partially replaced with residue, providing savings in economic and environmental costs compared to traditional hydraulic binders. In this study, the physical and chemical properties of cupola slag and its recovery process are analyzed. Mortars that incorporate traditional admixtures (fly ash and limestone filler) have been manufactured and consistency and mechanical properties have been compared with mortars that incorporate cupola slag admixture. Mortars have also been manufactured with normalized sand and with Portland cement replacements (0, 10, 20, and 30% by weight) with cupola slag, and both the consistency and the mechanical properties have been compared at 7, 28, 60, and 90 days. The results obtained show the suitability of cupola slag as a binder and as an admixture, with respect to the traditional ones, and how the mechanical properties tend to converge for all of the replacement levels characterized, for ages close to 90 days of age. Full article
(This article belongs to the Special Issue Eco-Performance of Alternative Binder Systems)
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Open AccessEditorial
Special Issue: The State of the Art of Thermochemical Heat Storage
Appl. Sci. 2021, 11(4), 1956; https://0-doi-org.brum.beds.ac.uk/10.3390/app11041956 - 23 Feb 2021
Viewed by 278
Abstract
Nowadays, thermal energy storage (TES) is gaining a crucial role in the development of highly efficient thermal energy systems [...] Full article
(This article belongs to the Section Mechanical Engineering)
Open AccessArticle
Outlier Detection for Multivariate Time Series Using Dynamic Bayesian Networks
Appl. Sci. 2021, 11(4), 1955; https://0-doi-org.brum.beds.ac.uk/10.3390/app11041955 - 23 Feb 2021
Viewed by 343
Abstract
Outliers are observations suspected of not having been generated by the underlying process of the remaining data. Many applications require a way of identifying interesting or unusual patterns in multivariate time series (MTS), now ubiquitous in many applications; however, most outlier detection methods [...] Read more.
Outliers are observations suspected of not having been generated by the underlying process of the remaining data. Many applications require a way of identifying interesting or unusual patterns in multivariate time series (MTS), now ubiquitous in many applications; however, most outlier detection methods focus solely on univariate series. We propose a complete and automatic outlier detection system covering the pre-processing of MTS data that adopts a dynamic Bayesian network (DBN) modeling algorithm. The latter encodes optimal inter and intra-time slice connectivity of transition networks capable of capturing conditional dependencies in MTS datasets. A sliding window mechanism is employed to score each MTS transition gradually, given the DBN model. Two score-analysis strategies are studied to assure an automatic classification of anomalous data. The proposed approach is first validated in simulated data, demonstrating the performance of the system. Further experiments are made on real data, by uncovering anomalies in distinct scenarios such as electrocardiogram series, mortality rate data, and written pen digits. The developed system proved beneficial in capturing unusual data resulting from temporal contexts, being suitable for any MTS scenario. A widely accessible web application employing the complete system is publicly available jointly with a tutorial. Full article
(This article belongs to the Special Issue Machine Learning in Computer Engineering Applications)
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Open AccessArticle
Optimal Design and Experimental Verification of Ultrasonic Cutting Horn for Ceramic Composite Material
Appl. Sci. 2021, 11(4), 1954; https://0-doi-org.brum.beds.ac.uk/10.3390/app11041954 - 23 Feb 2021
Viewed by 275
Abstract
We developed and optimized a block-type ultrasonic horn that can be used for cutting hard materials. The proposed block-type sonotrode consists of an aluminum horn and a tungsten carbide blade to increase the cutting of hard materials. We designed an initial ultrasonic block [...] Read more.
We developed and optimized a block-type ultrasonic horn that can be used for cutting hard materials. The proposed block-type sonotrode consists of an aluminum horn and a tungsten carbide blade to increase the cutting of hard materials. We designed an initial ultrasonic block horn that has double slots and an exponential stepped profile. We developed a finite element model of the initial model and analyzed the characteristics of natural frequency and displacement. We formulated a DOE table and response surface to perform sensitivity analysis and analyze the correlation between the design variables and characteristics of the proposed block horn. The optimal ultrasonic block horn was derived via a multi-objective optimal design problem to maximize the amplitude uniformity of the proposed horn and frequency separation. We fabricated the optimal block horn and verified it experimentally. An ultrasonic cutting experiment was conducted to find the ultrasonic cutting force with hard ceramic composite materials. A cutting test with a conventional cutting machine under the same condition was also conducted to compare the cutting force. The proposed optimal ultrasonic cutter requires 70% less cutting force than the conventional cutter to cut a ceramic composite material and the cutting surface with the application of the proposed optimal ultrasonic cutter is much cleaner with no crack and delamination than that with the application of the conventional cutter. Full article
(This article belongs to the Special Issue Ultrasonic Transducers and Related Apparatus and Applications)
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Open AccessArticle
Semantic 3D Mapping from Deep Image Segmentation
Appl. Sci. 2021, 11(4), 1953; https://0-doi-org.brum.beds.ac.uk/10.3390/app11041953 - 23 Feb 2021
Viewed by 321
Abstract
The perception and identification of visual stimuli from the environment is a fundamental capacity of autonomous mobile robots. Current deep learning techniques make it possible to identify and segment objects of interest in an image. This paper presents a novel algorithm to segment [...] Read more.
The perception and identification of visual stimuli from the environment is a fundamental capacity of autonomous mobile robots. Current deep learning techniques make it possible to identify and segment objects of interest in an image. This paper presents a novel algorithm to segment the object’s space from a deep segmentation of an image taken by a 3D camera. The proposed approach solves the boundary pixel problem that appears when a direct mapping from segmented pixels to their correspondence in the point cloud is used. We validate our approach by comparing baseline approaches using real images taken by a 3D camera, showing that our method outperforms their results in terms of accuracy and reliability. As an application of the proposed algorithm, we present a semantic mapping approach for a mobile robot’s indoor environments. Full article
(This article belongs to the Special Issue Deep Image Semantic Segmentation and Recognition)
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Open AccessArticle
Analysis of the Aggregate Effect on the Compressive Strength of Concrete Using Dune Sand
Appl. Sci. 2021, 11(4), 1952; https://0-doi-org.brum.beds.ac.uk/10.3390/app11041952 - 23 Feb 2021
Viewed by 254
Abstract
In this study, the compressive strengths of concrete were investigated based on water content and aggregate volume fractions, comprising dune sand (DS), crushed sand (CS), and coarse aggregate (CA), for different ages. Experimental data were used to analyze the effects of the volume [...] Read more.
In this study, the compressive strengths of concrete were investigated based on water content and aggregate volume fractions, comprising dune sand (DS), crushed sand (CS), and coarse aggregate (CA), for different ages. Experimental data were used to analyze the effects of the volume fraction changes of aggregates on the compressive strength. The compressive strength of concrete increases until the volumetric DS to fine aggregate (FA) ratio (DS/FA ratio) reaches 20%, after which it decreases. The relationship between changes in compressive strength and aggregate volume fractions was analyzed considering the effect factor of each aggregate on the compressive strength and at 2 conditions: (1) 0 < DS < CS < CA and (2) 0 < CA < CS < DS. For condition (1), when the effect factor of CA = 1, those of DS and CS were within 0.04–0.83 and 0.72–0.92, respectively, for all mixtures. For condition (2), when the effect factor of DS = 1, those of CS and CA were within 0.68–0.80 and 0.02–0.79, respectively. Full article
(This article belongs to the Special Issue Advanced Fiber-Reinforced Cementitious Composites)
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Open AccessArticle
Entropy Generation and MHD Convection within an Inclined Trapezoidal Heated by Triangular Fin and Filled by a Variable Porous Media
Appl. Sci. 2021, 11(4), 1951; https://0-doi-org.brum.beds.ac.uk/10.3390/app11041951 - 23 Feb 2021
Viewed by 295
Abstract
Analyses of the entropy of a thermal system that consists of an inclined trapezoidal geometry heated by a triangular fin are performed. The domain is filled by variable porosity and permeability porous materials and the working mixture is Al2O3-Cu [...] Read more.
Analyses of the entropy of a thermal system that consists of an inclined trapezoidal geometry heated by a triangular fin are performed. The domain is filled by variable porosity and permeability porous materials and the working mixture is Al2O3-Cu hybrid nanofluids. The porosity is varied exponentially with the smallest distance to the nearest wall and the permeability is depending on the particle diameter. Because of using the two energy equations model (LTNEM), sources of the entropy are entropy due to the transfer of heat of the fluid phase, entropy due to the fluid friction and entropy due to the porous phase transfer of heat. A computational domain with new coordinates (ξ,η) is created and Finite Volume Method (FVM) in case of the non-orthogonal grids is used to solve the resulting system. Various simulations for different values of the inclination angle, Hartmann number and alumina-copper concentration are carried out and the outcomes are presented in terms of streamlines, temperature, fluid friction entropy and Bejan number. It is remarkable that the increase in the inclination angle causes a diminishing of the heat transfer rate. Additionally, the irreversibility due to the temperature gradients is dominant near the heated fins, regardless of the values of the Hartmann number. Full article
(This article belongs to the Special Issue Nanofluids Application in Heat Transfer)
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Open AccessArticle
Automatic Identification of Peanut-Leaf Diseases Based on Stack Ensemble
Appl. Sci. 2021, 11(4), 1950; https://0-doi-org.brum.beds.ac.uk/10.3390/app11041950 - 23 Feb 2021
Cited by 1 | Viewed by 274
Abstract
Peanut is an important food crop, and diseases of its leaves can directly reduce its yield and quality. In order to solve the problem of automatic identification of peanut-leaf diseases, this paper uses a traditional machine-learning method to ensemble the output of a [...] Read more.
Peanut is an important food crop, and diseases of its leaves can directly reduce its yield and quality. In order to solve the problem of automatic identification of peanut-leaf diseases, this paper uses a traditional machine-learning method to ensemble the output of a deep learning model to identify diseases of peanut leaves. The identification of peanut-leaf diseases included healthy leaves, rust disease on a single leaf, leaf-spot disease on a single leaf, scorch disease on a single leaf, and both rust disease and scorch disease on a single leaf. Three types of data-augmentation methods were used: image flipping, rotation, and scaling. In this experiment, the deep-learning model had a higher accuracy than the traditional machine-learning methods. Moreover, the deep-learning model achieved better performance when using data augmentation and a stacking ensemble. After ensemble by logistic regression, the accuracy of residual network with 50 layers (ResNet50) was as high as 97.59%, and the F1 score of dense convolutional network with 121 layers (DenseNet121) was as high as 90.50. The deep-learning model used in this experiment had the greatest improvement in F1 score after the logistic regression ensemble. Deep-learning networks with deeper network layers like ResNet50 and DenseNet121 performed better in this experiment. This study can provide a reference for the identification of peanut-leaf diseases. Full article
(This article belongs to the Section Food Science and Technology)
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Open AccessArticle
Application of Artificial Intelligence to Determined Unconfined Compressive Strength of Cement-Stabilized Soil in Vietnam
Appl. Sci. 2021, 11(4), 1949; https://0-doi-org.brum.beds.ac.uk/10.3390/app11041949 - 23 Feb 2021
Viewed by 274
Abstract
Cement stabilized soil is one of the commonly used as ground reinforcement solutions in geotechnical engineering. In this study, the main object was to apply three machine learning (ML) methods namely gradient boosting (GB), artificial neural network (ANN) and support vector machine (SVM) [...] Read more.
Cement stabilized soil is one of the commonly used as ground reinforcement solutions in geotechnical engineering. In this study, the main object was to apply three machine learning (ML) methods namely gradient boosting (GB), artificial neural network (ANN) and support vector machine (SVM) to predict unconfined compressive strength (UCS) of cement stabilized soil. Soil samples were collected at Hai Duong city, Vietnam. A total of 216 soil–cement samples were mixed in the laboratory and compressed to determine the UCS. This data set is divided into two parts of the training data set (80%) and testing set (20%) to build and test the model, respectively. To verify the performance of ML model, various criteria named correlation coefficient (R), mean absolute error (MAE) and root mean square error (RMSE) were used. The results show that all three ML models were effective methods to predict the UCS of cement-stabilized soil. Amongst three model used in this study, optimized ANN model provided superior performance compare to two others models with performance indicator R = 0.925, RMSE = 419.82 and MAE = 292.2 for testing part. This study can provide an effective tool to quickly predict the UCS of cement stabilized soil with high accuracy. Full article
(This article belongs to the Section Civil Engineering)
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Open AccessArticle
Online Intelligent Perception of Pantograph and Catenary System Status Based on Parameter Adaptation
Appl. Sci. 2021, 11(4), 1948; https://0-doi-org.brum.beds.ac.uk/10.3390/app11041948 - 23 Feb 2021
Viewed by 280
Abstract
Online autonomous perception of pantograph catenary system status is of great significance for railway autonomous operation and maintenance (RIOM). Image sensors combined with an image processing algorithm can realize the automatic acquisition of the pantograph catenary condition; however, it is difficult to meet [...] Read more.
Online autonomous perception of pantograph catenary system status is of great significance for railway autonomous operation and maintenance (RIOM). Image sensors combined with an image processing algorithm can realize the automatic acquisition of the pantograph catenary condition; however, it is difficult to meet the demand of long-term stable condition acquisition, which restricts the implementation of online contact state feedback and the realization of railway automation. This paper proposes an online intelligent perception of the pantograph and catenary system (PCS) status based on parameter adaptation to realize fast and stable state analysis when the train is in long-term operation outdoors. First, according to the feature of the contact point, we used histogram of gradient (HoG) features and one-dimensional signal combined with a KCF tracker as the baseline method. Then, a result discriminator located by L1 and hash similarity constraints was used to construct a closed-loop parameter adaptive localization framework, which retrieves and updates parameters when tracking failure occurs. After that, a pruned RefineDet method was used to detect pantograph horns and sparks, which, together with the contact points localization method, ensure the long-term stability of feature localization in PCS images. Then, based on the stereo cameras model, the three-dimensional trajectory of the whole pantograph body can be reconstructed by the image features, and we obtained pantograph catenary contact parameters including the pantograph slide posture, contact line offset, arc detection, separation detection, etc. Our method has been tested on more than 16,000 collected image pairs and the results show that the proposed method has a better positioning effect than the state-of-art method, and realizes the online acquisition of pantograph catenary contact state, representing a significant contribution to RIOM. Full article
(This article belongs to the Special Issue Machine Learning in Computer Engineering Applications)
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Open AccessArticle
Application of the Segmented Correlation Technology in Seismic Communication with Morse Code
Appl. Sci. 2021, 11(4), 1947; https://0-doi-org.brum.beds.ac.uk/10.3390/app11041947 - 23 Feb 2021
Viewed by 247
Abstract
Seismic communication might promise to revolutionize the theory of seismic waves. However, one of the greatest challenges to its widespread adoption is the difficulty of signal extraction because the seismic waves in the vibration environments, such as seas, streets, city centers and subways, [...] Read more.
Seismic communication might promise to revolutionize the theory of seismic waves. However, one of the greatest challenges to its widespread adoption is the difficulty of signal extraction because the seismic waves in the vibration environments, such as seas, streets, city centers and subways, are very complex. Here, we employ segmented correlation technology with Morse code (SCTMC), which extracts the target signal by cutting the collected data into a series of segments and makes these segments cross-correlate with the decoded signal to process the collected data. To test the effectiveness of the technology, a seismic communication system composed of vibroseis sources and geophones was built in an environment full of other vibration signals. Most notably, it improves the signal-to-noise ratio (SNR), extending the relay distance and suppressing other vibration signals by using technology to deal with seismic data generated by the system. Full article
(This article belongs to the Special Issue Advances in Applied Geophysics)
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Open AccessArticle
Optimizing a Reverse Supply Chain Network for Electronic Waste under Risk and Uncertain Factors
Appl. Sci. 2021, 11(4), 1946; https://0-doi-org.brum.beds.ac.uk/10.3390/app11041946 - 23 Feb 2021
Viewed by 285
Abstract
Minimizing the impact of electronic waste (e-waste) on the environment through designing an effective reverse supply chain (RSC) is attracting the attention of both industry and academia. To obtain this goal, this study strives to develop an e-waste RSC model where the input [...] Read more.
Minimizing the impact of electronic waste (e-waste) on the environment through designing an effective reverse supply chain (RSC) is attracting the attention of both industry and academia. To obtain this goal, this study strives to develop an e-waste RSC model where the input parameters are fuzzy and risk factors are considered. The problem is then solved through crisp transformation and decision-makers are given the right to choose solutions based on their satisfaction. The result shows that the proposed model provides a practical and satisfactory solution to compromise between the level of satisfaction of constraints and the objective value. This solution includes strategic and operational decisions such as the optimal locations of facilities (i.e., disassembly, repairing, recycling facilities) and the flow quantities in the RSC. Full article
(This article belongs to the Special Issue Electronic Waste: Management and Recovery Technologies)
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Open AccessArticle
Category-Theoretic Formulation of the Model-Based Systems Architecting Cognitive-Computational Cycle
Appl. Sci. 2021, 11(4), 1945; https://0-doi-org.brum.beds.ac.uk/10.3390/app11041945 - 23 Feb 2021
Viewed by 285
Abstract
We introduce the Concept→Model→Graph→View Cycle (CMGVC). The CMGVC facilitates coherent architecture analysis, reasoning, insight, and decision making based on conceptual models that are transformed into a generic, robust graph data structure (GDS). The GDS is then transformed into multiple views of the model, [...] Read more.
We introduce the Concept→Model→Graph→View Cycle (CMGVC). The CMGVC facilitates coherent architecture analysis, reasoning, insight, and decision making based on conceptual models that are transformed into a generic, robust graph data structure (GDS). The GDS is then transformed into multiple views of the model, which inform stakeholders in various ways. This GDS-based approach decouples the view from the model and constitutes a powerful enhancement of model-based systems engineering (MBSE). The CMGVC applies the rigorous foundations of Category Theory, a mathematical framework of representations and transformations. We show that modeling languages are categories, drawing an analogy to programming languages. The CMGVC architecture is superior to direct transformations and language-coupled common representations. We demonstrate the CMGVC to transform a conceptual system architecture model built with the Object Process Modeling Language (OPM) into dual graphs and a stakeholder-informing matrix that stimulates system architecture insight. Full article
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Open AccessArticle
In Situ Measurement of Sound Attenuation by Fish Schools (Japanese Horse Mackerel, Trachurus japonicus) at Mid-Frequency Bands
Appl. Sci. 2021, 11(4), 1944; https://0-doi-org.brum.beds.ac.uk/10.3390/app11041944 - 23 Feb 2021
Viewed by 363
Abstract
Acoustic waves are attenuated by fish schools as they propagate through the ocean. The attenuation by fish schools is not currently considered in fishery acoustics and sonar applications, especially at mid-frequency bands. In this study, fish school attenuation experiments were conducted with a [...] Read more.
Acoustic waves are attenuated by fish schools as they propagate through the ocean. The attenuation by fish schools is not currently considered in fishery acoustics and sonar applications, especially at mid-frequency bands. In this study, fish school attenuation experiments were conducted with a number of individual fish in situ in a net cage at mid-frequency bands (3–7 kHz). The target fish species was the Japanese horse mackerel (Trachurus japonicus), which typically forms fish schools in the coastal ocean of northeastern Asia. The attenuated acoustic waves were measured for the cases of non-net, only net (0), 100, 200, 300, 400, and 500 individual horse mackerels in the net cage. Results showed that the acoustic signal attenuation increased with the number of horse mackerels. The mean and maximum attenuation coefficients were approximately 6.0–15.4 dB/m and 6.5–21.8 dB/m for all frequencies, respectively. The measured attenuation coefficients were compared with the ones from previous studies to propose new regression models with normalized extinction cross-sections of weight and length of fish. This study confirmed that the fish school attenuation could not be ignored and compensated at mid-frequencies in the ocean. These results would be useful for fishery acoustics, especially in the development of scientific echo-sounder, and naval applications of sonar operations and analysis. Full article
(This article belongs to the Collection Fishery Acoustics)
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