Applied Sciences

36 pages, 4947 KiB

Open AccessArticle

The Potential of Gas Switching Partial Oxidation Using Advanced Oxygen Carriers for Efficient H₂ Production with Inherent CO₂ Capture

by Carlos Arnaiz del Pozo, Schalk Cloete, Ángel Jiménez Álvaro, Felix Donat and Shahriar Amini

Appl. Sci. 2021, 11(10), 4713; https://doi.org/10.3390/app11104713 - 20 May 2021

Cited by 4 | Viewed by 3185

Abstract

The hydrogen economy has received resurging interest in recent years, as more countries commit to net-zero CO₂ emissions around the mid-century. “Blue” hydrogen from natural gas with CO₂ capture and storage (CCS) is one promising sustainable hydrogen supply option. Although conventional [...] Read more.

The hydrogen economy has received resurging interest in recent years, as more countries commit to net-zero CO₂ emissions around the mid-century. “Blue” hydrogen from natural gas with CO₂ capture and storage (CCS) is one promising sustainable hydrogen supply option. Although conventional CO₂ capture imposes a large energy penalty, advanced process concepts using the chemical looping principle can produce blue hydrogen at efficiencies even exceeding the conventional steam methane reforming (SMR) process without CCS. One such configuration is gas switching reforming (GSR), which uses a Ni-based oxygen carrier material to catalyze the SMR reaction and efficiently supply the required process heat by combusting an off-gas fuel with integrated CO₂ capture. The present study investigates the potential of advanced La-Fe-based oxygen carrier materials to further increase this advantage using a gas switching partial oxidation (GSPOX) process. These materials can overcome the equilibrium limitations facing conventional catalytic SMR and achieve direct hydrogen production using a water-splitting reaction. Results showed that the GSPOX process can achieve mild efficiency improvements relative to GSR in the range of 0.6–4.1%-points, with the upper bound only achievable by large power and H₂ co-production plants employing a highly efficient power cycle. These performance gains and the avoidance of toxicity challenges posed by Ni-based oxygen carriers create a solid case for the further development of these advanced materials. If successful, results from this work indicate that GSPOX blue hydrogen plants can outperform an SMR benchmark with conventional CO₂ capture by more than 10%-points, both in terms of efficiency and CO₂ avoidance. Full article

(This article belongs to the Special Issue Thermodynamics and Sustainable Development)

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12 pages, 3683 KiB

Open AccessArticle

On the Estimation of the Moving Mass of a TMD Installed on a Lively Structure

by Alvaro Magdaleno, Cesar Pelaez, Alvaro Iglesias-Pordomingo and Antolin Lorenzana

Appl. Sci. 2021, 11(10), 4712; https://doi.org/10.3390/app11104712 - 20 May 2021

Viewed by 2230

Abstract

Tuned Mass Dampers are devices which can be assimilated to single-degree-of-freedom systems with a certain amount of moving mass, a natural frequency and a damping ratio intended to be installed on lively structures to reduce the contribution of a certain mode to their [...] Read more.

Tuned Mass Dampers are devices which can be assimilated to single-degree-of-freedom systems with a certain amount of moving mass, a natural frequency and a damping ratio intended to be installed on lively structures to reduce the contribution of a certain mode to their response. Once placed on the structure, the movement of the mass damper couples to the structural response and determines its properties as an isolated system becomes challenging. The authors have previously presented a methodology to estimate the natural frequency and damping ratio of an SDOF system installed on a structure and not necessarily tuned to a certain mode. It was based on a transmissibility function and, thus, the moving mass could not be estimated. With this work, the authors go one step further and present a novel procedure to estimate the moving mass value by means of the same transmissibility function and two well selected frequency response functions. The methodology is applied to estimate the properties of a real single-degree-of-freedom system placed on a lively timber platform. The results are compared with the mass modification technique to show that the proposed methodology provides better estimations in a more efficient way. Full article

(This article belongs to the Section Civil Engineering)

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13 pages, 2116 KiB

Open AccessFeature PaperArticle

Anti-Inflammatory and Antioxidant Effects of Soroseris hirsuta Extract by Regulating iNOS/NF-κB and NRF2/HO-1 Pathways in Murine Macrophage RAW 264.7 Cells

by Woo Jin Lee, Wan Yi Li, Sang Woo Lee and Sung Keun Jung

Appl. Sci. 2021, 11(10), 4711; https://doi.org/10.3390/app11104711 - 20 May 2021

Cited by 5 | Viewed by 3191

Abstract

Until now, the physiological effects of Soroseris hirsuta were primarily unknown. Here we have evaluated the anti-inflammatory and antioxidant effects of Soroseris hirsuta extract (SHE) on lipopolysaccharide (LPS)-activated murine macrophages RAW 264.7 cells. SHE inhibited nitric oxide expression and inducible nitric [...] Read more.

Until now, the physiological effects of Soroseris hirsuta were primarily unknown. Here we have evaluated the anti-inflammatory and antioxidant effects of Soroseris hirsuta extract (SHE) on lipopolysaccharide (LPS)-activated murine macrophages RAW 264.7 cells. SHE inhibited nitric oxide expression and inducible nitric oxide synthase expression in RAW 264.7 cells treated with LPS. Moreover, SHE suppressed LPS-induced phosphorylation of IκB kinase, inhibitor of kappa B, p65, p38, and c-JUN N-terminal kinase. Western blot and immunofluorescence analyses showed that SHE suppressed p65 nuclear translocation induced by LPS. Furthermore, SHE inhibited the reactive oxygen species in LPS-treated RAW 264.7 cells. SHE significantly increased heme oxygenase-1 expression and the nuclear translocation of nuclear factor erythroid 2-related factor 2. SHE suppressed LPS-induced interleukin-1β mRNA expression in RAW 264.7 cells. Thus, SHE is a promising nutraceutical as it displays anti-inflammatory and antioxidant properties. Full article

(This article belongs to the Special Issue Application of Natural Products with Antioxidant, Anti-inflammatory and Antimicrobial Potentials)

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11 pages, 15359 KiB

Open AccessArticle

Immunohistochemical Expression Patterns of Tight Junction Proteins, Pro-Apoptotic and Anti-Apoptotic Factors on Progression of Intestinal Mucositis of Onco-Hematological Patients under Epirubicin-Based Chemotherapy

by Coralia Cotoraci, Alciona Sasu, Eftimie Miutescu, Dana Iovanescu, Sami Gharbia, Alina Ciceu, Hildegard Herman and Anca Hermenean

Appl. Sci. 2021, 11(10), 4710; https://doi.org/10.3390/app11104710 - 20 May 2021

Viewed by 2556

Abstract

Chemotherapy and radiation are often accompanied by complications such as intestinal mucositis. The aim of this study was to assess by immunohistochemical assay the consequences of epirubicin-based therapy applied to onco-hematological patients, on the mucosal cells that undergo apoptosis and on the tight [...] Read more.

Chemotherapy and radiation are often accompanied by complications such as intestinal mucositis. The aim of this study was to assess by immunohistochemical assay the consequences of epirubicin-based therapy applied to onco-hematological patients, on the mucosal cells that undergo apoptosis and on the tight junction proteins, immediately before and after a short time of chemotherapy administration. We assessed the protein expression and distribution of the pro-apoptotic Bax, anti-apoptotic Bcl-2 and effector Caspase-3 as key proteins in apoptosis pathways and the changes in immunopositivity of Claudin-1 and ZO-1 tight junction proteins. Results show that the Bcl-2 family is involved in intestinal damage via Caspase-3 dependent apoptosis of epithelial cells. Additionally, the intestinal mucositis activates other injurious pathways through a dramatic drop in Claudin-1 and ZO-1 expressions, contributing for a while to a structural and functional integrity disruption of the intestinal epithelium. Full article

(This article belongs to the Special Issue New Research Trends in Hematology and Cancerous Tumours)

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13 pages, 4564 KiB

Open AccessArticle

Numerical Simulation and Experimental Study on Axial Stiffness and Stress Deformation of the Braided Corrugated Hose

by Dacheng Huang and Jianrun Zhang

Appl. Sci. 2021, 11(10), 4709; https://doi.org/10.3390/app11104709 - 20 May 2021

Cited by 4 | Viewed by 3711

Abstract

To explore the mechanical properties of the braided corrugated hose, the space curve parametric equation of the braided tube is deduced, specific to the structural features of the braided tube. On this basis, the equivalent braided tube model is proposed based on the [...] Read more.

To explore the mechanical properties of the braided corrugated hose, the space curve parametric equation of the braided tube is deduced, specific to the structural features of the braided tube. On this basis, the equivalent braided tube model is proposed based on the same axial stiffness in order to improve the calculational efficiency. The geometric model and the Finite Element Model of the DN25 braided corrugated hose is established. The numerical simulation results are analyzed, and the distribution of the equivalent stress and frictional stress is discussed. The maximum equivalent stress of the braided corrugated hose occurs at the braided tube, with the value of 903MPa. The maximum equivalent stress of the bellows occurs at the area in contact with the braided tube, with the value of 314MPa. The maximum frictional stress between the bellows and the braided tube is 88.46MPa. The tensile experiment of the DN25 braided corrugated hose is performed. The simulation results are in good agreement with test data, with a maximum error of 9.4%, verifying the rationality of the model. The study is helpful to the research of the axial stiffness of the braided corrugated hose and provides the base for wear and life studies on the braided corrugated hose. Full article

(This article belongs to the Section Mechanical Engineering)

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20 pages, 14302 KiB

Open AccessArticle

Reliability-Based Design Optimization of Structures Using Complex-Step Approximation with Sensitivity Analysis

by Junho Chun

Appl. Sci. 2021, 11(10), 4708; https://doi.org/10.3390/app11104708 - 20 May 2021

Cited by 13 | Viewed by 3446

Abstract

Structural optimization aims to achieve a structural design that provides the best performance while satisfying the given design constraints. When uncertainties in design and conditions are taken into account, reliability-based design optimization (RBDO) is adopted to identify solutions with acceptable failure probabilities. This [...] Read more.

Structural optimization aims to achieve a structural design that provides the best performance while satisfying the given design constraints. When uncertainties in design and conditions are taken into account, reliability-based design optimization (RBDO) is adopted to identify solutions with acceptable failure probabilities. This paper outlines a method for sensitivity analysis, reliability assessment, and RBDO for structures. Complex-step (CS) approximation and the first-order reliability method (FORM) are unified in the sensitivity analysis of a probabilistic constraint, which streamlines the setup of optimization problems and enhances their implementation in RBDO. Complex-step approximation utilizes an imaginary number as a step size to compute the first derivative without subtractive cancellations in the formula, which have been observed to significantly affect the accuracy of calculations in finite difference methods. Thus, the proposed method can select a very small step size for the first derivative to minimize truncation errors, while achieving accuracy within the machine precision. This approach integrates complex-step approximation into the FORM to compute sensitivity and assess reliability. The proposed method of RBDO is tested on structural optimization problems across a range of statistical variations, demonstrating that performance benefits can be achieved while satisfying precise probabilistic constraints. Full article

(This article belongs to the Section Civil Engineering)

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22 pages, 29337 KiB

Open AccessArticle

Path Planning for Localization of Radiation Sources Based on Principal Component Analysis

by Takuya Kishimoto, Hanwool Woo, Ren Komatsu, Yusuke Tamura, Hideki Tomita, Kenji Shimazoe, Atsushi Yamashita and Hajime Asama

Appl. Sci. 2021, 11(10), 4707; https://doi.org/10.3390/app11104707 - 20 May 2021

Cited by 13 | Viewed by 3796

Abstract

In this paper, we propose a path planning method for the localization of radiation sources using a mobile robot equipped with an imaging gamma-ray detector, which has a field of view in all directions. The ability to detect and localize radiation sources is [...] Read more.

In this paper, we propose a path planning method for the localization of radiation sources using a mobile robot equipped with an imaging gamma-ray detector, which has a field of view in all directions. The ability to detect and localize radiation sources is essential for ensuring nuclear safety, security, and surveillance. To enable the autonomous localization of radiation sources, the robot must have the ability to automatically determine the next location for gamma ray measurement instead of following a predefined path. The number of incident events is approximated to be the squared inverse proportional to the distance between the radiation source and the detector. Therefore, the closer the distance to the source, the shorter the time required to obtain the same radiation counts measured by the detector. Hence, the proposed method is designed to reduce this distance to a position where a sufficient number of gamma-ray events can be obtained; then, a path to surround the radiation sources is generated. The proposed method generates this path by performing principal component analysis based on the results obtained from previous measurements. Both simulations and actual experiments demonstrate that the proposed method can automatically generate a measurement path and accurately localize radiation sources. Full article

(This article belongs to the Section Robotics and Automation)

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19 pages, 10943 KiB

Open AccessArticle

Machine Learning Approach to Real-Time 3D Path Planning for Autonomous Navigation of Unmanned Aerial Vehicle

by Abera Tullu, Bedada Endale, Assefinew Wondosen and Ho-Yon Hwang

Appl. Sci. 2021, 11(10), 4706; https://doi.org/10.3390/app11104706 - 20 May 2021

Cited by 29 | Viewed by 6655

Abstract

The need for civilian use of Unmanned Aerial Vehicles (UAVs) has drastically increased in recent years. Their potential applications for civilian use include door-to-door package delivery, law enforcement, first aid, and emergency services in urban areas, which put the UAVs into obstacle collision [...] Read more.

The need for civilian use of Unmanned Aerial Vehicles (UAVs) has drastically increased in recent years. Their potential applications for civilian use include door-to-door package delivery, law enforcement, first aid, and emergency services in urban areas, which put the UAVs into obstacle collision risk. Therefore, UAVs are required to be equipped with sensors so as to acquire Artificial Intelligence (AI) to avoid potential risks during mission execution. The AI comes with intensive training of an on-board machine that is responsible to autonomously navigate the UAV. The training enables the UAV to develop humanoid perception of the environment it is to be navigating in. During the mission, this perception detects and localizes objects in the environment. It is based on this AI that this work proposes a real-time three-dimensional (3D) path planner that maneuvers the UAV towards destination through obstacle-free path. The proposed path planner has a heuristic sense of

A^{⋆}

algorithm, but requires no frontier nodes to be stored in a memory unlike

A^{⋆}

. The planner relies on relative locations of detected objects (obstacles) and determines collision-free paths. This path planner is light-weight and hence a fast guidance method for real-time purposes. Its performance efficiency is proved through rigorous Software-In-The-Loop (SITL) simulations in constrained-environment and preliminary real flight tests. Full article

(This article belongs to the Special Issue Unmanned Aerial Vehicles)

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17 pages, 10293 KiB

Open AccessArticle

Improvement of a Stitching Operation in the Stitching Linear-Scan Method for Measurement of Cylinders in a Small Dimension

by Qiaolin Li, Yuki Shimizu, Toshiki Saito, Hiraku Matsukuma, Yindi Cai and Wei Gao

Appl. Sci. 2021, 11(10), 4705; https://doi.org/10.3390/app11104705 - 20 May 2021

Cited by 7 | Viewed by 2267

Abstract

Attempts are made in this paper to improve the quality of the stitching between adjacent arc-profiles in the stitching linear-scan method for the roundness measurement of a cylinder in a small dimension. The data in the edge region of an arc-profile, which could [...] Read more.

Attempts are made in this paper to improve the quality of the stitching between adjacent arc-profiles in the stitching linear-scan method for the roundness measurement of a cylinder in a small dimension. The data in the edge region of an arc-profile, which could be influenced by the pressure angle of the measurement probe of a linear-scan stylus profiler, are eliminated in the stitching process to improve the quality of stitching. The effectiveness of the elimination of the edge region of an arc-profile is evaluated by employing the cross-correlation coefficient of two adjacent arc-profiles as an evaluation index. Furthermore, a modification is made to the experimental setup to reduce the misalignment of a workpiece along its axial direction with respect to the scanning probe. Experiments are carried out by using the modified setup to demonstrate the feasibility of the stitching linear-scan method for the roundness measurement of a small cylinder, which is difficult to measure by the conventional rotary-scan method. Full article

(This article belongs to the Special Issue New Trends in Manufacturing Metrology)

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10 pages, 1399 KiB

Open AccessArticle

Viñamecum: A Computer-Aided Method for Diagnoses of Pests and Diseases in the Vineyard

by Juan Ignacio García-García, Daniel Marín-Aragón, Hanael Maciá and Ana Jiménez-Cantizano

Appl. Sci. 2021, 11(10), 4704; https://doi.org/10.3390/app11104704 - 20 May 2021

Cited by 1 | Viewed by 2577

Abstract

Information and telecommunication technologies (ICTs) offer new opportunities to provide more timely information services to farmers. This work aims to present a progressive web app (PWA) for mobile devices, which incorporates updated technical information on the pests and diseases of grapevines. In its [...] Read more.

Information and telecommunication technologies (ICTs) offer new opportunities to provide more timely information services to farmers. This work aims to present a progressive web app (PWA) for mobile devices, which incorporates updated technical information on the pests and diseases of grapevines. In its development, it generated a database with content related to and photographs of grapevine pests and diseases for access by users using mobile devices. In addition, using an Expert System, the application allows the diagnosis of pathologies and the identification of pests by answering questions that are asked. This PWA is mainly addressed to technicians, students, and winegrowers who want to implement more environmentally friendly crop management strategies. Viñamecum is currently freely. Full article

(This article belongs to the Special Issue Agriculture 4.0 – the Future of Farming Technology)

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13 pages, 4535 KiB

Open AccessArticle

Behavior of Traffic Congestion and Public Transport in Eight Large Cities in Latin America during the COVID-19 Pandemic

by Renato Andara, Jesús Ortego-Osa, Melva Inés Gómez-Caicedo, Rodrigo Ramírez-Pisco, Luis Manuel Navas-Gracia, Carmen Luisa Vásquez and Mercedes Gaitán-Angulo

Appl. Sci. 2021, 11(10), 4703; https://doi.org/10.3390/app11104703 - 20 May 2021

Cited by 13 | Viewed by 4381

Abstract

This comparative study analyzes the impact of the COVID-19 pandemic on motorized mobility in eight large cities of five Latin American countries. Public institutions and private organizations have made public data available for a better understanding of the contagion process of the pandemic, [...] Read more.

This comparative study analyzes the impact of the COVID-19 pandemic on motorized mobility in eight large cities of five Latin American countries. Public institutions and private organizations have made public data available for a better understanding of the contagion process of the pandemic, its impact, and the effectiveness of the implemented health control measures. In this research, data from the IDB Invest Dashboard were used for traffic congestion as well as data from the Moovit© public transport platform. For the daily cases of COVID-19 contagion, those published by Johns Hopkins Hospital University were used. The analysis period corresponds from 9 March to 30 September 2020, approximately seven months. For each city, a descriptive statistical analysis of the loss and subsequent recovery of motorized mobility was carried out, evaluated in terms of traffic congestion and urban transport through the corresponding regression models. The recovery of traffic congestion occurs earlier and faster than that of urban transport since the latter depends on the control measures imposed in each city. Public transportation does not appear to have been a determining factor in the spread of the pandemic in Latin American cities. Full article

(This article belongs to the Special Issue CITIES: Energetic Efficiency, Sustainability; Infrastructures, Energy and the Environment; Mobility and IoT; Governance and Citizenship)

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22 pages, 44471 KiB

Open AccessArticle

A Novel Maneuver-Based Driving Envelope Generation Approach for Driving Safety Assessment

by Bohan Jiang, Xiaohui Li, Yujun Zeng and Daxue Liu

Appl. Sci. 2021, 11(10), 4702; https://doi.org/10.3390/app11104702 - 20 May 2021

Cited by 2 | Viewed by 2793

Abstract

It is of utmost importance for advanced driver assistance systems to evaluate the risk of the current situation and make continuous decisions about what kind of evasive maneuver can be initiated. The purpose of this paper is to establish efficient indicators to evaluate [...] Read more.

It is of utmost importance for advanced driver assistance systems to evaluate the risk of the current situation and make continuous decisions about what kind of evasive maneuver can be initiated. The purpose of this paper is to establish efficient indicators to evaluate the risk of candidate driving maneuvers for a human-in-the-loop vehicle. A novel safe driving envelope generation method is proposed, which takes various constraints into consideration, including the human operation, vehicle motion limits, and collision avoidance with road boundary and obstacles. The efficiency of the proposed method is validated by simulation experiments and real vehicle tests. The results show that the feasibility of candidate driving maneuvers can be efficiently determined by computing the driving envelope, and the proposed driving envelope method can be easily implemented for real-time applications. Full article

(This article belongs to the Section Robotics and Automation)

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20 pages, 14051 KiB

Open AccessArticle

Using Fuzzy Control for Feed Rate Scheduling of Computer Numerical Control Machine Tools

by Cheng-Jian Lin, Chun-Hui Lin and Shyh-Hau Wang

Appl. Sci. 2021, 11(10), 4701; https://doi.org/10.3390/app11104701 - 20 May 2021

Cited by 10 | Viewed by 2627

Abstract

In industrial processing, workpiece quality and processing time have recently become important issues. To improve the machining accuracy and reduce the cutting time, the cutting feed rate will have a significant impact. Therefore, how to plan a dynamic cutting feed rate is very [...] Read more.

In industrial processing, workpiece quality and processing time have recently become important issues. To improve the machining accuracy and reduce the cutting time, the cutting feed rate will have a significant impact. Therefore, how to plan a dynamic cutting feed rate is very important. In this study, a fuzzy control system for feed rate scheduling based on the curvature and curvature variation is proposed. The proposed system is implemented in actual cutting, and to verify the data an optical three-dimensional scanner is used to measure the cutting trajectory of the workpiece. Experimental results prove that the proposed fuzzy control system for dynamic cutting feed rate scheduling increases the cutting accuracy by 41.8% under the same cutting time; moreover, it decreases the cutting time by 50.8% under approximately the same cutting accuracy. Full article

(This article belongs to the Collection The Development and Application of Fuzzy Logic)

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13 pages, 864 KiB

Open AccessArticle

Saddle Point Approximation of Mutual Information for Finite-Alphabet Inputs over Doubly Correlated MIMO Rayleigh Fading Channels

by Yuyu Liu, Jinbao Zhang and Dan Zhang

Appl. Sci. 2021, 11(10), 4700; https://doi.org/10.3390/app11104700 - 20 May 2021

Cited by 2 | Viewed by 2057

Abstract

Given the mutual information of finite-alphabet inputs cannot be calculated concisely and accurately over fading channels, this paper proposes a new method to calculate the mutual information. First, the applicability of the saddle point method is studied, and then the mutual information is [...] Read more.

Given the mutual information of finite-alphabet inputs cannot be calculated concisely and accurately over fading channels, this paper proposes a new method to calculate the mutual information. First, the applicability of the saddle point method is studied, and then the mutual information is estimated by the saddle point approximation method with known channel state information. Furthermore, we induce the expectation of mutual information over doubly correlated multiple-input multiple-output (MIMO) Rayleigh fading channels. The validity of the saddle point approximation method is verified by comparing the numerical results of the Monte Carlo method and the saddle point approximation method under different doubly correlated MIMO fading channel scenarios. Full article

(This article belongs to the Special Issue Wireless Communication: Applications, Security and Reliability)

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17 pages, 4631 KiB

Open AccessArticle

Revisiting Label Smoothing Regularization with Knowledge Distillation

by Jiyue Wang, Pei Zhang, Qianhua He, Yanxiong Li and Yongjian Hu

Appl. Sci. 2021, 11(10), 4699; https://doi.org/10.3390/app11104699 - 20 May 2021

Cited by 9 | Viewed by 4066

Abstract

Label Smoothing Regularization (LSR) is a widely used tool to generalize classification models by replacing the one-hot ground truth with smoothed labels. Recent research on LSR has increasingly focused on the correlation between the LSR and Knowledge Distillation (KD), which transfers the knowledge [...] Read more.

Label Smoothing Regularization (LSR) is a widely used tool to generalize classification models by replacing the one-hot ground truth with smoothed labels. Recent research on LSR has increasingly focused on the correlation between the LSR and Knowledge Distillation (KD), which transfers the knowledge from a teacher model to a lightweight student model by penalizing their output’s Kullback–Leibler-divergence. Based on this observation, a Teacher-free Knowledge Distillation (Tf-KD) method was proposed in previous work. Instead of a real teacher model, a handcrafted distribution similar to LSR was used to guide the student learning. Tf-KD is a promising substitute for LSR except for its hard-to-tune and model-dependent hyperparameters. This paper develops a new teacher-free framework LSR-OS-TC, which decomposes the Tf-KD method into two components: model Output Smoothing (OS) and Teacher Correction (TC). Firstly, the LSR-OS extends the LSR method to the KD regime and applies a softer temperature to the model output softmax layer. Output smoothing is critical for stabilizing the KD hyperparameters among different models. Secondly, in the TC part, a larger proportion is assigned to the uniform distribution teacher’s right class to provide a more informative teacher. The two-component method was evaluated exhaustively on the image (dataset CIFAR-100, CIFAR-10, and CINIC-10) and audio (dataset GTZAN) classification tasks. The results showed that LSR-OS can improve LSR performance independently with no extra computational cost, especially on several deep neural networks where LSR is ineffective. The further training boost by the TC component showed the effectiveness of our two-component strategy. Overall, LSR-OS-TC is a practical substitution of LSR that can be tuned on one model and directly applied to other models compared to the original Tf-KD method. Full article

(This article belongs to the Section Computing and Artificial Intelligence)

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16 pages, 8664 KiB

Open AccessArticle

Performance Prediction and Design of Stratospheric Propeller

by Cong Xie, Guoquan Tao and Zhe Wu

Appl. Sci. 2021, 11(10), 4698; https://doi.org/10.3390/app11104698 - 20 May 2021

Cited by 2 | Viewed by 3217

Abstract

In this paper, a performance prediction method is proposed for the design of a stratospheric propeller. The Spalart–Allmaras (S–A) model was used to calculate the airfoil performance of FX63, and the polynomial fitting method was utilized to establish the airfoil database of the [...] Read more.

In this paper, a performance prediction method is proposed for the design of a stratospheric propeller. The Spalart–Allmaras (S–A) model was used to calculate the airfoil performance of FX63, and the polynomial fitting method was utilized to establish the airfoil database of the lift and drag coefficient. A computational fluid dynamics (CFD) model was applied at different altitudes to prove the feasibility of the method. The CFD results were compared with the results of the vortex theory and prediction; the prediction result accuracy was improved compared with that of the vortex theory over a greater range of advance ratios. The airfoil performance data requirements and the number of iterative calculations were reduced. These results indicate that the proposed propeller design meets the requirements of stratospheric airship propulsion systems. Full article

(This article belongs to the Section Aerospace Science and Engineering)

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19 pages, 376 KiB

Open AccessArticle

Explainable Internet Traffic Classification

by Christian Callegari, Pietro Ducange, Michela Fazzolari and Massimo Vecchio

Appl. Sci. 2021, 11(10), 4697; https://doi.org/10.3390/app11104697 - 20 May 2021

Cited by 8 | Viewed by 2701

Abstract

The problem analyzed in this paper deals with the classification of Internet traffic. During the last years, this problem has experienced a new hype, as classification of Internet traffic has become essential to perform advanced network management. As a result, many different methods [...] Read more.

The problem analyzed in this paper deals with the classification of Internet traffic. During the last years, this problem has experienced a new hype, as classification of Internet traffic has become essential to perform advanced network management. As a result, many different methods based on classical Machine Learning and Deep Learning have been proposed. Despite the success achieved by these techniques, existing methods are lacking because they provide a classification output that does not help practitioners with any information regarding the criteria that have been taken to the given classification or what information in the input data makes them arrive at their decisions. To overcome these limitations, in this paper we focus on an “explainable” method for traffic classification able to provide the practitioners with information about the classification output. More specifically, our proposed solution is based on a multi-objective evolutionary fuzzy classifier (MOEFC), which offers a good trade-off between accuracy and explainability of the generated classification models. The experimental results, obtained over two well-known publicly available data sets, namely, UniBS and UPC, demonstrate the effectiveness of our method. Full article

(This article belongs to the Special Issue Explainable Artificial Intelligence (XAI))

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17 pages, 3163 KiB

Open AccessArticle

The Long-Term Consequences of Forest Fires on the Carbon Fluxes of a Tropical Forest in Africa

by Rico Fischer

Appl. Sci. 2021, 11(10), 4696; https://doi.org/10.3390/app11104696 - 20 May 2021

Cited by 14 | Viewed by 3763

Abstract

Tropical forests are an important component of the global carbon cycle, as they store large amounts of carbon. In some tropical regions, the forests are increasingly influenced by disturbances such as fires, which lead to structural changes but also alter species composition, forest [...] Read more.

Tropical forests are an important component of the global carbon cycle, as they store large amounts of carbon. In some tropical regions, the forests are increasingly influenced by disturbances such as fires, which lead to structural changes but also alter species composition, forest succession, and carbon balance. However, the long-term consequences on forest functioning are difficult to assess. The majority of all global forest fires are found in Africa. In this study, a forest model was extended by a fire model to investigate the long-term effects of forest fires on biomass, carbon fluxes, and species composition of tropical forests at Mt. Kilimanjaro (Tanzania). According to this modeling study, forest biomass was reduced by 46% by fires and even by 80% when fires reoccur. Forest regeneration lasted more than 100 years to recover to pre-fire state. Productivity and respiration were up to 4 times higher after the fire than before the fire, which was mainly due to pioneer species in the regeneration phase. Considering the full carbon balance of the regrowing forest, it takes more than 150 years to compensate for the carbon emissions caused by the forest fire. However, functional diversity increases after a fire, as fire-tolerant tree species and pioneer species dominate a fire-affected forest area and thus alter the forest succession. This study shows that forest models can be suitable tools to simulate the dynamics of tropical forests and to assess the long-term consequences of fires. Full article

(This article belongs to the Special Issue Fires and Modelling for Succession in Forests)

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9 pages, 5492 KiB

Open AccessArticle

Several Aspects of Application of Nanodiamonds as Reinforcements for Metal Matrix Composites

by Vladimir Popov

Appl. Sci. 2021, 11(10), 4695; https://doi.org/10.3390/app11104695 - 20 May 2021

Cited by 11 | Viewed by 2431

Abstract

After detonation synthesis, primary nanodiamond particles are around 4–6 nm in size. However, they join into agglomerates with larger parameters and weak bonds between particles. The introduction of agglomerates into a metal matrix can lead to the weakness of composites. This paper demonstrates [...] Read more.

After detonation synthesis, primary nanodiamond particles are around 4–6 nm in size. However, they join into agglomerates with larger parameters and weak bonds between particles. The introduction of agglomerates into a metal matrix can lead to the weakness of composites. This paper demonstrates the possibility of obtaining a non-agglomerated distribution of nanodiamonds inside a metal matrix. The fabrication method was based on mechanical alloying to create additional stresses and deformations by phase transformations during treatment in a planetary mill. According to the findings, the starting temperature of the reaction between the non-agglomerated nanodiamonds and aluminium matrix reduces to 450 °C. Furthermore, the paper shows that existing methods (annealing for the transformation of a diamond structure into graphitic material and cleaning from this graphitic material) cannot reduce the sizes of nanodiamonds in the agglomerated state. Agglomerated nanodiamonds transform into carbon onions (graphitic material) during annealing in a vacuum in the following way: the nanodiamonds located in the surface layers of the agglomerate are the first to undergo the complete transformation followed by the transformation of nanoparticles in its deeper layers. In the intermediate state, the agglomerate has a graphitic surface layer and a core from nanodiamonds: cleaning from graphite cannot reduce nanodiamond particle size. Full article

(This article belongs to the Special Issue Metal Matrix Composites)

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15 pages, 4386 KiB

Open AccessEditor’s ChoiceArticle

Geometry and Distortion Prediction of Multiple Layers for Wire Arc Additive Manufacturing with Artificial Neural Networks

by Christian Wacker, Markus Köhler, Martin David, Franziska Aschersleben, Felix Gabriel, Jonas Hensel, Klaus Dilger and Klaus Dröder

Appl. Sci. 2021, 11(10), 4694; https://doi.org/10.3390/app11104694 - 20 May 2021

Cited by 32 | Viewed by 4384

Abstract

Wire arc additive manufacturing (WAAM) is a direct energy deposition (DED) process with high deposition rates, but deformation and distortion can occur due to the high energy input and resulting strains. Despite great efforts, the prediction of distortion and resulting geometry in additive [...] Read more.

Wire arc additive manufacturing (WAAM) is a direct energy deposition (DED) process with high deposition rates, but deformation and distortion can occur due to the high energy input and resulting strains. Despite great efforts, the prediction of distortion and resulting geometry in additive manufacturing processes using WAAM remains challenging. In this work, an artificial neural network (ANN) is established to predict welding distortion and geometric accuracy for multilayer WAAM structures. For demonstration purposes, the ANN creation process is presented on a smaller scale for multilayer beads on plate welds on a thin substrate sheet. Multiple concepts for the creation of ANNs and the handling of outliers are developed, implemented, and compared. Good results have been achieved by applying an enhanced ANN using deformation and geometry from the previously deposited layer. With further adaptions to this method, a prediction of additive welded structures, geometries, and shapes in defined segments is conceivable, which would enable a multitude of applications for ANNs in the WAAM-Process, especially for applications closer to industrial use cases. It would be feasible to use them as preparatory measures for multi-segmented structures as well as an application during the welding process to continuously adapt parameters for a higher resulting component quality. Full article

(This article belongs to the Special Issue Metal Additive Manufacturing and its Applications: From the Material to Components Service Life)

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36 pages, 6608 KiB

Open AccessFeature PaperReview

Cellulose Recovery from Agri-Food Residues by Effective Cavitational Treatments

by Federico Verdini, Emanuela Calcio Gaudino, Giorgio Grillo, Silvia Tabasso and Giancarlo Cravotto

Appl. Sci. 2021, 11(10), 4693; https://doi.org/10.3390/app11104693 - 20 May 2021

Cited by 32 | Viewed by 4872

Abstract

Residual biomass from agri-food production chain and forestry are available in huge amounts for further valorisation processes. Delignification is usually the crucial step in the production of biofuels by fermentation as well as in the conversion of cellulose into high added-value compounds. High-intensity [...] Read more.

Residual biomass from agri-food production chain and forestry are available in huge amounts for further valorisation processes. Delignification is usually the crucial step in the production of biofuels by fermentation as well as in the conversion of cellulose into high added-value compounds. High-intensity ultrasound (US) and hydrodynamic cavitation (HC) have been widely exploited as effective pretreatment techniques for biomass conversion and in particular for cellulose recovery. Due to their peculiar mechanisms, cavitational treatments promote an effective lignocellulosic matrix dismantling with delignification at low temperature (35–50 °C). Cavitation also promotes cellulose decrystallization due to a partial depolymerization. The aim of this review is to highlight recent advances in US and HC-assisted delignification and further cellulose recovery and valorisation. Full article

(This article belongs to the Special Issue Cellulose Isolation from Agri-Food Residues)

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15 pages, 4677 KiB

Open AccessArticle

The Effect of Dust Transport on the Concentration of Chlorophyll-A in the Surface Layer of the Black Sea

by Alla V. Varenik and Darya V. Kalinskaya

Appl. Sci. 2021, 11(10), 4692; https://doi.org/10.3390/app11104692 - 20 May 2021

Cited by 11 | Viewed by 2294

Abstract

This paper focuses on the atmospheric dust transport effect on the changes in chlorophyll-A concentration in the Black Sea surface layer. In order to assess the input of nutrients with atmospheric precipitations at the Crimean coast of the Black Sea, the collected samples [...] Read more.

This paper focuses on the atmospheric dust transport effect on the changes in chlorophyll-A concentration in the Black Sea surface layer. In order to assess the input of nutrients with atmospheric precipitations at the Crimean coast of the Black Sea, the collected samples were analyzed for the content of inorganic nitrogen, phosphates, and silicon. The samples were taken into a wet-only sampler and into a permanently open one, to assess the effect of dust on the nutrients concentration in dry depositions. Cases of multi-fold excess of the nutrients content in the open sampler collected precipitation over that in the wet-only sampler were identified. For such high concentration cases, the 7-day back-trajectories analyses was carried out using the model of the international network AERONET and the HYSPLIT model. The results of our research showed that the influx of nutrients with the atmospheric depositions can result in increasing of chlorophyll-A concentration in 11–36% in the surface layer of the Black Sea. After atmospheric depositions, concentration of phosphates in the surface layer can increase more than five times compared with the background concentration. The increase of silicon concentration can reach 30%. The influx of atmospheric precipitation containing significant amounts of nutrients into the bay can shifts the Redfield ratio compared with background value up to three times. Full article

(This article belongs to the Special Issue Climate Change and Aquatic Ecosystems: Impacts, Mitigation and Adaptation)

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14 pages, 5924 KiB

Open AccessFeature PaperArticle

Trimethoxycinnamates and Their Cholinesterase Inhibitory Activity

by Jiri Kos, Tomas Strharsky, Sarka Stepankova, Katarina Svrckova, Michal Oravec, Jan Hosek, Ales Imramovsky and Josef Jampilek

Appl. Sci. 2021, 11(10), 4691; https://doi.org/10.3390/app11104691 - 20 May 2021

Cited by 5 | Viewed by 2607

Abstract

A series of twelve nature-inspired 3,4,5-trimethoxycinnamates were prepared and characterized. All compounds, including the starting 3,4,5-trimethoxycinnamic acid, were tested for their ability to inhibit acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) in vitro; the selectivity index (SI) was also determined. 2-Fluororophenyl (2E)-3-(3,4,5-trimethoxyphenyl)-prop-2-enoate demonstrated [...] Read more.

A series of twelve nature-inspired 3,4,5-trimethoxycinnamates were prepared and characterized. All compounds, including the starting 3,4,5-trimethoxycinnamic acid, were tested for their ability to inhibit acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) in vitro; the selectivity index (SI) was also determined. 2-Fluororophenyl (2E)-3-(3,4,5-trimethoxyphenyl)-prop-2-enoate demonstrated the highest SI (1.71) in favor of BChE inhibition. 2-Chlorophenyl (2E)-3-(3,4,5-trimethoxyphenyl)prop-2-enoate showed the highest AChE-inhibiting (IC₅₀ = 46.18 µM) as well as BChE-inhibiting (IC₅₀ = 32.46 µM) activity with an SI of 1.42. The mechanism of action of the most potent compound was determined by the Lineweaver–Burk plot as a mixed type of inhibition. An in vitro cell viability assay confirmed the insignificant cytotoxicity of the discussed compounds on the two cell lines. Trends between structure, physicochemical properties and activity were discussed. Full article

(This article belongs to the Special Issue Plants: From Farm to Food and Biomedical Applications)

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22 pages, 4192 KiB

Open AccessArticle

Optimization of 3-DoF Manipulators’ Parasitic Motion with the Instantaneous Restriction Space-Based Analytic Coupling Relation

by Hassen Nigatu and Doik Kim

Appl. Sci. 2021, 11(10), 4690; https://doi.org/10.3390/app11104690 - 20 May 2021

Cited by 6 | Viewed by 3729

Abstract

This paper presents a velocity-level approach to optimizing the parasitic motion of 3-degrees of freedom (DoFs) parallel manipulators. To achieve this objective, we first systematically derive an analytical velocity-level parasitic motion equation as a primary step for the optimization. The paper utilizes an [...] Read more.

This paper presents a velocity-level approach to optimizing the parasitic motion of 3-degrees of freedom (DoFs) parallel manipulators. To achieve this objective, we first systematically derive an analytical velocity-level parasitic motion equation as a primary step for the optimization. The paper utilizes an analytic structural constraint equation that describes the manipulator’s restriction space to formulate the parasitic motion equation via the task variable coupling relation. Then, the relevant geometric variables are identified from the analytic coupling equation. The Quasi-Newton method is used for the direction-specific minimization, i.e., optimizing either the x-axis or y-axis parasitic motion. The pattern-search algorithm is applied to optimize all parasitic terms from the workspace. The proposed approach equivalently describes the 3-PhRS, 3-PvRS, 3RPS manipulators. Moreover, other manipulators within a similar category can be equivalently expressed by the proposed method. Finally, the paper presents the resulting optimum configurations and numerical simulations to demonstrate the approach. Full article

(This article belongs to the Section Robotics and Automation)

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13 pages, 1760 KiB

Open AccessArticle

3D Skeletal Joints-Based Hand Gesture Spotting and Classification

by Ngoc-Hoang Nguyen, Tran-Dac-Thinh Phan, Soo-Hyung Kim, Hyung-Jeong Yang and Guee-Sang Lee

Appl. Sci. 2021, 11(10), 4689; https://doi.org/10.3390/app11104689 - 20 May 2021

Cited by 6 | Viewed by 3206

Abstract

This paper presents a novel approach to continuous dynamic hand gesture recognition. Our approach contains two main modules: gesture spotting and gesture classification. Firstly, the gesture spotting module pre-segments the video sequence with continuous gestures into isolated gestures. Secondly, the gesture classification module [...] Read more.

This paper presents a novel approach to continuous dynamic hand gesture recognition. Our approach contains two main modules: gesture spotting and gesture classification. Firstly, the gesture spotting module pre-segments the video sequence with continuous gestures into isolated gestures. Secondly, the gesture classification module identifies the segmented gestures. In the gesture spotting module, the motion of the hand palm and fingers are fed into the Bidirectional Long Short-Term Memory (Bi-LSTM) network for gesture spotting. In the gesture classification module, three residual 3D Convolution Neural Networks based on ResNet architectures (3D_ResNet) and one Long Short-Term Memory (LSTM) network are combined to efficiently utilize the multiple data channels such as RGB, Optical Flow, Depth, and 3D positions of key joints. The promising performance of our approach is obtained through experiments conducted on three public datasets—Chalearn LAP ConGD dataset, 20BN-Jester, and NVIDIA Dynamic Hand gesture Dataset. Our approach outperforms the state-of-the-art methods on the Chalearn LAP ConGD dataset. Full article

(This article belongs to the Special Issue Deep Learning-Based Action Recognition)

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21 pages, 17868 KiB

Open AccessArticle

Nonlinear Dynamic Response of a Concrete Rectangular Liquid Storage Tank on Rigid Soil Subjected to Three-Directional Ground Motion

by Chae-Been Lee and Jin-Ho Lee

Appl. Sci. 2021, 11(10), 4688; https://doi.org/10.3390/app11104688 - 20 May 2021

Cited by 13 | Viewed by 3599

Abstract

The dynamic responses of a concrete rectangular liquid storage tank on the surface of rigid soil subjected to three-directional earthquake ground motion are investigated with material nonlinearity taken into consideration. Material nonlinearity in concrete is considered using the concrete damage plasticity model. The [...] Read more.

The dynamic responses of a concrete rectangular liquid storage tank on the surface of rigid soil subjected to three-directional earthquake ground motion are investigated with material nonlinearity taken into consideration. Material nonlinearity in concrete is considered using the concrete damage plasticity model. The hydrodynamic pressure due to earthquake ground motion is considered using a finite-element solution of the governing equation for an inviscid and incompressible ideal fluid with the fluid–structure interaction taken into consideration. It was observed from the dynamic analyses that the effects of material nonlinearity and directionality significantly affect the earthquake responses of the considered system. The relative displacement of the structure increased significantly by the nonlinearity of the material. Inclined cracks due to the increased displacement were observed on the long-sided walls. The hydrodynamic pressure can be reduced significantly by the material nonlinearity and is influenced by the directionality of an earthquake’s ground motion. The base shear and overturning moment due to the hydrodynamic pressure and the resulting impulsive mass and corresponding height for a simplified mass-spring analogy are also affected. Because the directionality was observed to have a significant influence on the peak value of the sloshing height, it must be estimated with the directionality considered. Full article

(This article belongs to the Section Civil Engineering)

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18 pages, 2802 KiB

Open AccessArticle

Central Non-Linear Model-Based Predictive Vehicle Dynamics Control

by Philipp Maximilian Sieberg and Dieter Schramm

Appl. Sci. 2021, 11(10), 4687; https://doi.org/10.3390/app11104687 - 20 May 2021

Cited by 5 | Viewed by 2943

Abstract

Considering automated driving, vehicle dynamics control systems are also a crucial aspect. Vehicle dynamics control systems serve as an important influence factor on safety and ride comfort. By reducing the driver’s responsibility through partially or fully automated driving functions, the occupants’ perception of [...] Read more.

Considering automated driving, vehicle dynamics control systems are also a crucial aspect. Vehicle dynamics control systems serve as an important influence factor on safety and ride comfort. By reducing the driver’s responsibility through partially or fully automated driving functions, the occupants’ perception of safety and ride comfort changes. Both aspects are focused even more and have to be enhanced. In general, research on vehicle dynamics control systems is a field that has already been well researched. With regard to the mentioned aspects, however, a central control structure features sufficient potential by exploiting synergies. Furthermore, a predictive mode of operation can contribute to achieve these objectives, since the vehicle can act in a predictive manner instead of merely reacting. Consequently, this contribution presents a central predictive control system by means of a non-linear model-based predictive control algorithm. In this context, roll, self-steering and pitch behavior are considered as control objectives. The active roll stabilization demonstrates an excellent control quality with a root mean squared error of

7.6953 \times 10^{- 3}

rad averaged over both validation maneuvers. Compared to a vehicle utilizing a conventional control approach combined with a skyhook damping, pitching movements are reduced by

19.75

%. Furthermore, an understeering behavior is maintained, which corresponds to the self-steering behavior of the passive vehicle. In general, the central predictive control, thus, increases both ride comfort and safety in a holistic way. Full article

(This article belongs to the Special Issue Performance and Safety Enhancement Strategies in Vehicle Dynamics and Ground Contact)

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18 pages, 2359 KiB

Open AccessArticle

A New Data Fusion Neural Network Scheme for Rainfall Retrieval Using Passive Microwave and Visible/Infrared Satellite Data

by Massimiliano Sist, Giovanni Schiavon and Fabio Del Frate

Appl. Sci. 2021, 11(10), 4686; https://doi.org/10.3390/app11104686 - 20 May 2021

Cited by 3 | Viewed by 2381

Abstract

A new data fusion technique based on Artificial Neural Networks (ANN) for the design of a rainfall retrieval algorithm is presented. The use of both VIS/IR (VISible and InfraRed) data from GEO (Geostationary Earth Orbit) satellite and of passive microwave data from LEO [...] Read more.

A new data fusion technique based on Artificial Neural Networks (ANN) for the design of a rainfall retrieval algorithm is presented. The use of both VIS/IR (VISible and InfraRed) data from GEO (Geostationary Earth Orbit) satellite and of passive microwave data from LEO (Low Earth Orbit) satellite can take advantage of both types of sensors reducing their limitations. The technique can reconstruct the surface rain field with the MSG-SEVIRI (Meteosat Second Generation–Spinning Enhanced Visible Infrared Imager) spatial and temporal resolution, which means 3 km at the sub satellite point and 5 km at mid-latitudes, every 15 min, respectively. Rainfall estimations are also compared with H-SAF (Hydrology Satellite Application Facility) PR-OBS3A operational product showing better performance both on the identification of rainy areas and on the retrieval of the amount of precipitation. In particular, in the considered test cases, results report an improvement in average of 83% in terms of probability of rainy areas detection, of 45% in terms of false alarm rate, and of 47% in terms of root mean square error in the retrieval of the amount of precipitation. Full article

(This article belongs to the Special Issue Satellite Earth Observation for Atmospheric Modeling)

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15 pages, 4481 KiB

Open AccessArticle

Nonlinear Nonsingular Fast Terminal Sliding Mode Control Using Deep Deterministic Policy Gradient

by Zefeng Xu, Wenkai Huang, Zexuan Li, Linkai Hu and Puwei Lu

Appl. Sci. 2021, 11(10), 4685; https://doi.org/10.3390/app11104685 - 20 May 2021

Cited by 20 | Viewed by 3000

Abstract

Background: As a control strategy of industrial robots, sliding mode control has the advantages of fast response and simple physical implementation, but it still has the problems of chattering and low tracking accuracy caused by chattering. This paper proposes a new sliding mode [...] Read more.

Background: As a control strategy of industrial robots, sliding mode control has the advantages of fast response and simple physical implementation, but it still has the problems of chattering and low tracking accuracy caused by chattering. This paper proposes a new sliding mode control strategy for the application of industrial robot control, which effectively solves these problems. Methods: In this paper, a deep deterministic policy gradient–nonlinear nonsingular fast terminal sliding mode control (DDPG–NNFTSMC) strategy is proposed for industrial robot control. In order to improve the tracking control accuracy and anti-interference ability, DDPG is used to approach the uncertainties of the system in real time, which ensures the robustness of the system in various uncertain environments. Lyapunov function is used to prove the stability and finite time convergence of the system. Compared with the nonsingular terminal sliding mode control (NTSMC), the time to reach the equilibrium point is shorter. With the help of MATLAB/Simulink, the tracking accuracy and control effects are compared with traditional terminal sliding mode control (TSMC), NTSMC and radial basis function–sliding mode control (RBF–SMC), the results showed that it had the advantages of nonsingularity, finite time convergence, small tracking error. The motion accuracy and anti-interference ability of the uncertain manipulator system was further improved, and the chattering problem of the system in the motion process is effectively eliminated. Full article

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18 pages, 26420 KiB

Open AccessArticle

A Novel Decomposition-Ensemble Learning Model Based on Ensemble Empirical Mode Decomposition and Recurrent Neural Network for Landslide Displacement Prediction

by Xiaoxu Niu, Junwei Ma, Yankun Wang, Junrong Zhang, Hongjie Chen and Huiming Tang

Appl. Sci. 2021, 11(10), 4684; https://doi.org/10.3390/app11104684 - 20 May 2021

Cited by 40 | Viewed by 3520

Abstract

As vital comments on landslide early warning systems, accurate and reliable displacement prediction is essential and of significant importance for landslide mitigation. However, obtaining the desired prediction accuracy remains highly difficult and challenging due to the complex nonlinear characteristics of landslide monitoring data. [...] Read more.

As vital comments on landslide early warning systems, accurate and reliable displacement prediction is essential and of significant importance for landslide mitigation. However, obtaining the desired prediction accuracy remains highly difficult and challenging due to the complex nonlinear characteristics of landslide monitoring data. Based on the principle of “decomposition and ensemble”, a three-step decomposition-ensemble learning model integrating ensemble empirical mode decomposition (EEMD) and a recurrent neural network (RNN) was proposed for landslide displacement prediction. EEMD and kurtosis criteria were first applied for data decomposition and construction of trend and periodic components. Second, a polynomial regression model and RNN with maximal information coefficient (MIC)-based input variable selection were implemented for individual prediction of trend and periodic components independently. Finally, the predictions of trend and periodic components were aggregated into a final ensemble prediction. The experimental results from the Muyubao landslide demonstrate that the proposed EEMD-RNN decomposition-ensemble learning model is capable of increasing prediction accuracy and outperforms the traditional decomposition-ensemble learning models (including EEMD-support vector machine, and EEMD-extreme learning machine). Moreover, compared with standard RNN, the gated recurrent unit (GRU)-and long short-term memory (LSTM)-based models perform better in predicting accuracy. The EEMD-RNN decomposition-ensemble learning model is promising for landslide displacement prediction. Full article

(This article belongs to the Special Issue Geohazards: Risk Assessment, Mitigation and Prevention)

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