Applied Sciences

24 pages, 2907 KiB

Open AccessArticle

BassNet: A Variational Gated Autoencoder for Conditional Generation of Bass Guitar Tracks with Learned Interactive Control

by Maarten Grachten, Stefan Lattner and Emmanuel Deruty

Appl. Sci. 2020, 10(18), 6627; https://doi.org/10.3390/app10186627 - 22 Sep 2020

Cited by 5 | Viewed by 5612

Abstract

Deep learning has given AI-based methods for music creation a boost by over the past years. An important challenge in this field is to balance user control and autonomy in music generation systems. In this work, we present BassNet, a deep learning model [...] Read more.

Deep learning has given AI-based methods for music creation a boost by over the past years. An important challenge in this field is to balance user control and autonomy in music generation systems. In this work, we present BassNet, a deep learning model for generating bass guitar tracks based on musical source material. An innovative aspect of our work is that the model is trained to learn a temporally stable two-dimensional latent space variable that offers interactive user control. We empirically show that the model can disentangle bass patterns that require sensitivity to harmony, instrument timbre, and rhythm. An ablation study reveals that this capability is because of the temporal stability constraint on latent space trajectories during training. We also demonstrate that models that are trained on pop/rock music learn a latent space that offers control over the diatonic characteristics of the output, among other things. Lastly, we present and discuss generated bass tracks for three different music fragments. The work that is presented here is a step toward the integration of AI-based technology in the workflow of musical content creators. Full article

(This article belongs to the Special Issue Deep Learning for Applications in Acoustics: Modeling, Synthesis, and Listening)

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20 pages, 701 KiB

Open AccessArticle

Taylor Bird Swarm Algorithm Based on Deep Belief Network for Heart Disease Diagnosis

by Afnan M. Alhassan and Wan Mohd Nazmee Wan Zainon

Appl. Sci. 2020, 10(18), 6626; https://doi.org/10.3390/app10186626 - 22 Sep 2020

Cited by 19 | Viewed by 3163

Abstract

Contemporary medicine depends on a huge amount of information contained in medical databases. Thus, the extraction of valuable knowledge, and making scientific decisions for the treatment of disease, has progressively become necessary to attain effective diagnosis. The obtainability of a large amount of [...] Read more.

Contemporary medicine depends on a huge amount of information contained in medical databases. Thus, the extraction of valuable knowledge, and making scientific decisions for the treatment of disease, has progressively become necessary to attain effective diagnosis. The obtainability of a large amount of medical data leads to the requirement of effective data analysis tools for extracting constructive knowledge. This paper proposes a novel method for heart disease diagnosis. Here, the pre-processing of medical data is done using log-transformation that converts the data to its uniform value range. Then, the feature selection process is performed using sparse fuzzy-c-means (FCM) for selecting significant features to classify medical data. Incorporating sparse FCM for the feature selection process provides more benefits for interpreting the models, as this sparse technique provides important features for detection, and can be utilized for handling high dimensional data. Then, the selected features are given to the deep belief network (DBN), which is trained using the proposed Taylor-based bird swarm algorithm (Taylor-BSA) for detection. Here, the proposed Taylor-BSA is designed by combining the Taylor series and bird swarm algorithm (BSA). The proposed Taylor-BSA–DBN outperformed other methods, with maximal accuracy of 93.4%, maximal sensitivity of 95%, and maximal specificity of 90.3%, respectively. Full article

(This article belongs to the Special Issue Medical Informatics and Data Analysis)

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22 pages, 2099 KiB

Open AccessArticle

Hybrid Harmony Search-Simulated Annealing Algorithm for Location-Inventory-Routing Problem in Supply Chain Network Design with Defect and Non-Defect Items

by Farahanim Misni, Lai Soon Lee and Hsin-Vonn Seow

Appl. Sci. 2020, 10(18), 6625; https://doi.org/10.3390/app10186625 - 22 Sep 2020

Cited by 17 | Viewed by 3446

Abstract

This paper considers a location-inventory-routing problem (LIRP) that integrates the strategic, tactical, and operational decision planning in supply chain network design. Both defect and non-defect items of returned products are considered in the cost of reverse logistics based on the economic production quantity [...] Read more.

This paper considers a location-inventory-routing problem (LIRP) that integrates the strategic, tactical, and operational decision planning in supply chain network design. Both defect and non-defect items of returned products are considered in the cost of reverse logistics based on the economic production quantity model. The objective of the LIRP is to minimize the total cost of location-allocation of established depots, the cost of inventory, including production setup and holding cost, as well as the cost of travelled distance by the vehicles between the open depots and assigned customers. A Hybrid Harmony Search-Simulated Annealing (HS-SA) algorithm is proposed in this paper. This algorithm incorporates the dynamic values of harmony memory considering rate and pitch adjustment rate with the local optimization techniques to hybridize with the idea of probabilistic acceptance rule from simulated annealing, to avoid the local extreme points. Computational experiments on popular benchmark data sets show that the proposed hybrid HS-SA algorithm outperforms a standard HS and an improved HS for all cases. Full article

(This article belongs to the Special Issue Harmony Search Algorithm - Theoretical Background and Practical Applications)

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15 pages, 5333 KiB

Open AccessArticle

Follow-Up Control and Image Recognition of Neck Level for Standard Metal Gauge

by Chenquan Hua, Chengjin Xie and Xuan Xu

Appl. Sci. 2020, 10(18), 6624; https://doi.org/10.3390/app10186624 - 22 Sep 2020

Cited by 3 | Viewed by 2348

Abstract

An image recognition technique is proposed for determining optimal neck levels for standard metal gauges, in the process of validating pipe provers. A camera-level follow-up control system was designed to achieve automated tracking of fluid levels by a camera, thereby preventing errors from [...] Read more.

An image recognition technique is proposed for determining optimal neck levels for standard metal gauges, in the process of validating pipe provers. A camera-level follow-up control system was designed to achieve automated tracking of fluid levels by a camera, thereby preventing errors from inclined viewing angles. An orange background plate was placed behind the tube to reduce background interference, and highlight scale numbers/lines and concave meniscus. A segmentation algorithm, based on edge detection and K-means clustering, was used to segment indicator tubes and scales in the acquired images. The concave meniscus reconstruction algorithm and curve-fitting algorithm were proposed to better identify the lowest point of the meniscus. A characteristic edge detection model was used to identify centimeter-scale lines corresponding to the meniscus. A binary tree multiclass support vector machine (MCSVM) classifier was then used to identify scale numbers corresponding to scale lines and determine the optimal neck level for standard metal gauges. Experimental results showed that measurement errors were within ±0.1 mm compared to a ground truth acquired manually using Vernier calipers. The recognition time, including follow-up control, was less than 10 s, which is much lower than the switching time required between measuring individual tanks. This automated measurement approach for gauge neck levels can effectively reduce measurement times, decrease manmade errors in liquid level readings, and improve the efficiency of pipe prover validation. Full article

(This article belongs to the Section Applied Industrial Technologies)

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18 pages, 4145 KiB

Open AccessArticle

Extraction of Irregularly Shaped Coal Mining Area Induced Ground Subsidence Prediction Based on Probability Integral Method

by Xianfeng Tan, Bingzhong Song, Huaizhi Bo, Yunwei Li, Meng Wang and Guohong Lu

Appl. Sci. 2020, 10(18), 6623; https://doi.org/10.3390/app10186623 - 22 Sep 2020

Cited by 15 | Viewed by 2913

Abstract

Underground coal mining-induced ground subsidence (or major ground vertical settlement) is a major concern to the mining industry, government and people affected. Based on the probability integral method, this paper presents a new ground subsidence prediction method for predicting irregularly shaped coal mining [...] Read more.

Underground coal mining-induced ground subsidence (or major ground vertical settlement) is a major concern to the mining industry, government and people affected. Based on the probability integral method, this paper presents a new ground subsidence prediction method for predicting irregularly shaped coal mining area extraction-induced ground subsidence. Firstly, the Delaunay triangulation method is used to divide the irregularly shaped mining area into a series of triangular extraction elements. Then, the extraction elements within the calculation area are selected. Finally, the Monte Carlo method is used to calculate extraction element-induced ground subsidence. The proposed method was tested by two experimental data sets: the simulation data set and direct leveling-based subsidence observations. The simulation results show that the prediction error of the proposed method is proportional to mesh size and inversely proportional to the amount of generated random points within the auxiliary domain. In addition, when the mesh size is smaller than 0.5 times the minimum deviation of the inflection point of the mining area, and the amount of random points within an auxiliary domain is greater than 800 times the area of the extraction element, the difference between the proposed method-based subsidence predictions and the traditional probability integral method-based subsidence predictions is marginal. The measurement results show that the root-mean-square error of the proposed method-based subsidence predictions is smaller than 3 cm, the average of absolute deviations of the proposed method-based subsidence predictions is 2.49 cm, and the maximum absolute deviation is 4.05 cm, which is equal to 0.75% of the maximum direct leveling-based subsidence observation. Full article

(This article belongs to the Special Issue Land Subsidence: Monitoring, Prediction and Modeling)

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22 pages, 13127 KiB

Open AccessArticle

A New Challenge: Path Planning for Autonomous Truck of Open-Pit Mines in The Last Transport Section

by Ziyu Zhao and Lin Bi

Appl. Sci. 2020, 10(18), 6622; https://doi.org/10.3390/app10186622 - 22 Sep 2020

Cited by 19 | Viewed by 4913

Abstract

During the operation of open-pit mining, the loading position of a haulage truck often changes, bringing a new challenge concerning how to plan an optimal truck transportation path considering the terrain factors. This paper proposes a path planning method based on a high-precision [...] Read more.

During the operation of open-pit mining, the loading position of a haulage truck often changes, bringing a new challenge concerning how to plan an optimal truck transportation path considering the terrain factors. This paper proposes a path planning method based on a high-precision digital map. It contains two parts: (1) constructing a high-precision digital map of the cutting zone and (2) planning the optimal path based on the modified Hybrid A* algorithm. Firstly, we process the high-precision map based on different terrain feature factors to generate the obstacle cost map and surface roughness cost map of the cutting zone. Then, we fuse the two cost maps to generate the final cost map for path planning. Finally, we incorporate the contact cost between tire and ground to improve the node extension and path smoothing part of the Hybrid A* algorithm and further enhance the algorithm’s capability of avoiding the roughness. We use real elevation data with different terrain resolutions to perform random tests and the results show that, compared with the path without considering the terrain factors, the total transportation cost of the optimal path is reduced by 10%–20%. Moreover, the methods demonstrate robustness. Full article

(This article belongs to the Special Issue Recent Advances in Smart Mining Technology)

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15 pages, 6139 KiB

Open AccessArticle

Microseismic Signal Denoising and Separation Based on Fully Convolutional Encoder–Decoder Network

by Hang Zhang, Chunchi Ma, Veronica Pazzi, Yulin Zou and Nicola Casagli

Appl. Sci. 2020, 10(18), 6621; https://doi.org/10.3390/app10186621 - 22 Sep 2020

Cited by 17 | Viewed by 3599

Abstract

Denoising methods are a highly desired component of signal processing, and they can separate the signal of interest from noise to improve the subsequent signal analyses. In this paper, an advanced denoising method based on a fully convolutional encoder–decoder neural network is proposed. [...] Read more.

Denoising methods are a highly desired component of signal processing, and they can separate the signal of interest from noise to improve the subsequent signal analyses. In this paper, an advanced denoising method based on a fully convolutional encoder–decoder neural network is proposed. The method simultaneously learns the sparse features in the time–frequency domain, and the mask-related mapping function for signal separation. The results show that the proposed method has an impressive performance on denoising microseismic signals containing various types and intensities of noise. Furthermore, the method works well even when a similar frequency band is shared between the microseismic signals and the noises. The proposed method, compared to the existing methods, significantly improves the signal–noise ratio thanks to minor changes of the microseismic signal (less distortion in the waveform). Additionally, the proposed methods preserve the shape and amplitude characteristics so that it allows better recovery of the real waveform. This method is exceedingly useful for the automatic processing of the microseismic signal. Further, it has excellent potential to be extended to the study of exploration seismology and earthquakes. Full article

(This article belongs to the Special Issue New Advance of Acoustic Emission and Microseismic Monitoring Technologies in Civil Engineering)

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16 pages, 1916 KiB

Open AccessArticle

Gesture-Based User Interface for Vehicle On-Board System: A Questionnaire and Research Approach

by Krzysztof Małecki, Adam Nowosielski and Mateusz Kowalicki

Appl. Sci. 2020, 10(18), 6620; https://doi.org/10.3390/app10186620 - 22 Sep 2020

Cited by 8 | Viewed by 5488

Abstract

Touchless interaction with electronic devices using gestures is gaining popularity and along with speech-based communication offers their users natural and intuitive control methods. Now, these interaction modes go beyond the entertainment industry and are successfully applied in real-life scenarios such as a car [...] Read more.

Touchless interaction with electronic devices using gestures is gaining popularity and along with speech-based communication offers their users natural and intuitive control methods. Now, these interaction modes go beyond the entertainment industry and are successfully applied in real-life scenarios such as a car interior. In the paper, we analyse the potential of hand gesture interaction in the vehicle environment by physically challenged drivers. A survey conducted with potential users shows that the knowledge of gesture-based interaction and its practical use by people with disabilities is low. Based on these results we proposed a gesture-based system for vehicle on-board system. It has been developed on the available state-of-the-art solutions and investigated in terms of usability on a group of people with different physical limitations who drive a car on daily basis mostly using steering aid tools. The obtained results are compared with the performance of users without any disabilities. Full article

(This article belongs to the Special Issue Advances in Image Processing, Analysis and Recognition Technology 2021)

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21 pages, 6116 KiB

Open AccessArticle

Noise Prediction Using Machine Learning with Measurements Analysis

by Po-Jiun Wen and Chihpin Huang

Appl. Sci. 2020, 10(18), 6619; https://doi.org/10.3390/app10186619 - 22 Sep 2020

Cited by 7 | Viewed by 8290

Abstract

The noise prediction using machine learning is a special study that has recently received increased attention. This is particularly true in workplaces with noise pollution, which increases noise exposure for general laborers. This study attempts to analyze the noise equivalent level (Leq) at [...] Read more.

The noise prediction using machine learning is a special study that has recently received increased attention. This is particularly true in workplaces with noise pollution, which increases noise exposure for general laborers. This study attempts to analyze the noise equivalent level (Leq) at the National Synchrotron Radiation Research Center (NSRRC) facility and establish a machine learning model for noise prediction. This study utilized the gradient boosting model (GBM) as the learning model in which past noise measurement records and many other features are integrated as the proposed model makes a prediction. This study analyzed the time duration and frequency of the collected Leq and also investigated the impact of training data selection. The results presented in this paper indicate that the proposed prediction model works well in almost noise sensors and frequencies. Moreover, the model performed especially well in sensor 8 (125 Hz), which was determined to be a serious noise zone in the past noise measurements. The results also show that the root-mean-square-error (RMSE) of the predicted harmful noise was less than 1 dBA and the coefficient of determination (R²) value was greater than 0.7. That is, the working field showed a favorable noise prediction performance using the proposed method. This positive result shows the ability of the proposed approach in noise prediction, thus providing a notification to the laborer to prevent long-term exposure. In addition, the proposed model accurately predicts noise future pollution, which is essential for laborers in high-noise environments. This would keep employees healthy in avoiding noise harmful positions to prevent people from working in that environment. Full article

(This article belongs to the Special Issue Machine Learning and Signal Processing for IOT Applications)

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28 pages, 13696 KiB

Open AccessArticle

Measuring Quality of Service in a Robotized Comprehensive Geriatric Assessment Scenario

by Adrián Romero-Garcés, Jesús Martínez-Cruz, Juan F. Inglés-Romero, Cristina Vicente-Chicote, Rebeca Marfil and Antonio Bandera

Appl. Sci. 2020, 10(18), 6618; https://doi.org/10.3390/app10186618 - 22 Sep 2020

Cited by 8 | Viewed by 2946

Abstract

Comprehensive Geriatric Assessment (CGA) is an integrated clinical process to evaluate frail elderly people in order to create therapy plans that improve their quality and quantity of life. The whole process includes the completion of standardized questionnaires or specific movements, which are performed [...] Read more.

Comprehensive Geriatric Assessment (CGA) is an integrated clinical process to evaluate frail elderly people in order to create therapy plans that improve their quality and quantity of life. The whole process includes the completion of standardized questionnaires or specific movements, which are performed by the patient and do not necessarily require the presence of a medical expert. With the aim of automatizing these parts of the CGA, we have designed and developed CLARC (smart CLinic Assistant Robot for CGA), a mobile robot able to help the physician to capture and manage data during the CGA procedures, mainly by autonomously conducting a set of predefined evaluation tests. Using CLARC to conduct geriatric tests will reduce the time medical professionals have to spend on purely mechanical tasks, giving them more time to develop individualised care plans for their patients. In fact, ideally, CLARC will perform these tests on its own. In parallel with the effort to correctly address the functional aspects, i.e., the development of the robot tasks, the design of CLARC must also deal with non-functional properties such as the degree of interaction or the performance. We argue that satisfying user preferences can be a good way to improve the acceptance of the robot by the patients. This paper describes the integration into the software architecture of the CLARC robot of the modules that allow these properties to be monitored at run-time, providing information on the quality of its service. Experimental evaluation illustrates that the defined quality of service metrics correctly capture the evolution of the aspects of the robot’s activity and its interaction with the patient covered by the non-functional properties that have been considered. Full article

(This article belongs to the Special Issue Cognitive Robotics)

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19 pages, 5350 KiB

Open AccessArticle

Precoded Generalized Spatial Modulation for Downlink MIMO Transmissions in Beyond 5G Networks

by João Pedro Pavia, Vasco Velez, Bernardo Brogueira, Nuno Souto and Américo Correia

Appl. Sci. 2020, 10(18), 6617; https://doi.org/10.3390/app10186617 - 22 Sep 2020

Cited by 2 | Viewed by 3324

Abstract

The design of multiple input multiple output (MIMO) schemes capable of achieving both high spectral and energy efficiency constitutes a challenge for next-generation wireless networks. MIMO schemes based on generalized spatial modulations (GSM) have been widely considered as a powerful technique to achieve [...] Read more.

The design of multiple input multiple output (MIMO) schemes capable of achieving both high spectral and energy efficiency constitutes a challenge for next-generation wireless networks. MIMO schemes based on generalized spatial modulations (GSM) have been widely considered as a powerful technique to achieve that purpose. In this paper, a multi-user (MU) GSM MIMO system is proposed, which relies on the transmission of precoded symbols from a base station to multiple receivers. The precoder’s design is focused on the removal of the interference between users and allows the application of single-user GSM detection at the receivers, which is accomplished using a low-complexity iterative algorithm. Link level and system level simulations of a cloud radio access network (C-RAN) comprising several radio remote units (RRUs) were run in order to evaluate the performance of the proposed solution. Simulation results show that the proposed GSM MU-MIMO approach can exploit efficiently a large number of antennas deployed at the transmitter. Moreover, it can also provide large gains when compared to conventional MU-MIMO schemes with identical spectral efficiencies. In fact, regarding the simulated C-RAN scenario with perfect channel estimation, system level results showed potential gains of up to 155% and 139% in throughput and coverage, respectively, compared to traditional cellular networks. The introduction of imperfect channel estimation reduces the throughput gain to 125%. Full article

(This article belongs to the Special Issue Transmission Techniques for 5G and Beyond)

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17 pages, 2683 KiB

Open AccessArticle

A New Architectural Approach to Monitoring and Controlling AM Processes

by Muhammad Adnan, Yan Lu, Albert Jones, Fan-Tien Cheng and Ho Yeung

Appl. Sci. 2020, 10(18), 6616; https://doi.org/10.3390/app10186616 - 22 Sep 2020

Cited by 13 | Viewed by 3515

Abstract

The abilities to both monitor and control additive manufacturing (AM) processes in real-time are necessary before the routine production of quality AM parts will be possible. Currently, neither ability exist! The major reason is that AM processes are different from traditional manufacturing processes [...] Read more.

The abilities to both monitor and control additive manufacturing (AM) processes in real-time are necessary before the routine production of quality AM parts will be possible. Currently, neither ability exist! The major reason is that AM processes are different from traditional manufacturing processes in many ways and so are the sensors and the monitoring data collected from them. In traditional manufacturing, that data is mostly numeric in nature. To that numeric data, AM monitoring data add large volumes of a variety of in situ, high-speed, image data. Collecting, fusing, and analyzing all that AM data and making the necessary control decisions is not possible using traditional, rigid, hierarchical-control architectures. Therefore, researchers are proposing to use real-time, machine-learning algorithms to analyze the data and to execute the other control functions. This paper identifies those control functions and proposes a new architecture to integrate them. This paper also shows an example of using that architecture to analyze the melt-pool, shape analysis using a clustering method. Full article

(This article belongs to the Special Issue Emerging Paradigms and Architectures for Industry 4.0 Applications)

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14 pages, 7808 KiB

Open AccessArticle

The Shear Strength of Granite Weathered Soil Under Different Hydraulic Paths

by Youqian Lu, Guoqing Cai and Chenggang Zhao

Appl. Sci. 2020, 10(18), 6615; https://doi.org/10.3390/app10186615 - 22 Sep 2020

Cited by 4 | Viewed by 3231

Abstract

At present, there is no clear understanding of the influence of differences in soil mineral composition, particle size grading, and hydraulic paths on the shear strength of unsaturated soil, and the related strength models are not applicable. The shear strength characteristics of different [...] Read more.

At present, there is no clear understanding of the influence of differences in soil mineral composition, particle size grading, and hydraulic paths on the shear strength of unsaturated soil, and the related strength models are not applicable. The shear strength characteristics of different saturation specimens under different hydraulic paths were studied on two granite weathered soils. The experimental results show that the shear strength index of the prepared specimen is “arched” with the increase of saturation, and the dehydration specimen decreases linearly with the saturation. As considering the cementation of free oxides in soils and the interaction among soil particles at different saturations, it is assumed that there are three different contact modes among soil particles: direct contact, meniscus contact, and cement contact. The difference in contact modes will reflect the different laws of shear strength. A shear strength model capable of distinguishing between the capillary effect and the adsorptive effect was established. The model predicted and verified the shear strength data of granite weathered soil under different hydraulic paths well, and then theoretically explained the evolution law of the shear strength of granite weathering soil under the change of saturation. Full article

(This article belongs to the Section Civil Engineering)

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24 pages, 2848 KiB

Open AccessFeature PaperReview

Electrochemical Biosensors Based on Conducting Polymers: A Review

by Boris Lakard

Appl. Sci. 2020, 10(18), 6614; https://doi.org/10.3390/app10186614 - 22 Sep 2020

Cited by 120 | Viewed by 9471

Abstract

Conducting polymers are an important class of functional materials that has been widely applied to fabricate electrochemical biosensors, because of their interesting and tunable chemical, electrical, and structural properties. Conducting polymers can also be designed through chemical grafting of functional groups, nanostructured, or [...] Read more.

Conducting polymers are an important class of functional materials that has been widely applied to fabricate electrochemical biosensors, because of their interesting and tunable chemical, electrical, and structural properties. Conducting polymers can also be designed through chemical grafting of functional groups, nanostructured, or associated with other functional materials such as nanoparticles to provide tremendous improvements in sensitivity, selectivity, stability and reproducibility of the biosensor’s response to a variety of bioanalytes. Such biosensors are expected to play a growing and significant role in delivering the diagnostic information and therapy monitoring since they have advantages including their low cost and low detection limit. Therefore, this article starts with the description of electroanalytical methods (potentiometry, amperometry, conductometry, voltammetry, impedometry) used in electrochemical biosensors, and continues with a review of the recent advances in the application of conducting polymers in the recognition of bioanalytes leading to the development of enzyme based biosensors, immunosensors, DNA biosensors, and whole-cell biosensors. Full article

(This article belongs to the Special Issue Advanced Electrochemical Biosensors)

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14 pages, 3505 KiB

Open AccessArticle

Intersection Routing Based on Fuzzy Multi-Factor Decision for VANETs

by Zhenbo Cao, Bhagya Nathali Silva, Muhammad Diyan, Jilong Li and Kijun Han

Appl. Sci. 2020, 10(18), 6613; https://doi.org/10.3390/app10186613 - 22 Sep 2020

Cited by 6 | Viewed by 2684

Abstract

Vehicular ad hoc network (VANET) is a special form of mobile ad hoc network (MANET), which plays a key role in the intelligent transportation system (ITS). Though many outstanding geographic routing protocols are designed for VANETs, a majority of them use parameters that [...] Read more.

Vehicular ad hoc network (VANET) is a special form of mobile ad hoc network (MANET), which plays a key role in the intelligent transportation system (ITS). Though many outstanding geographic routing protocols are designed for VANETs, a majority of them use parameters that only affect routing performance. In this article, we propose an intersection routing based on fuzzy multi-factor decision (IRFMFD), which utilizes several features. The scheme is divided into two parts, namely vehicular decision management and intersection decision management. In the vehicular component, candidate vehicles between two static nodes (SNs) located at two intersections derive potential routing paths considering distance, neighbor quantity, and relative velocity. In the intersection component, the candidate SN was chosen from the current intersection’s 2-hop neighbors which were connected with the current intersection by a route that was decided on in part one. To get the best scheme, we also introduced other factors to estimate the number of hops in each link and link lifetime. The simulation shows that the IRFMFD outperforms on delivery ratio and end-to-end delay compared with AODV (Ad hoc on-demand distance vector), GPSR (Greedy perimeter stateless routing) and GeOpps (Geographical opportunistic routing). Full article

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

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21 pages, 6802 KiB

Open AccessArticle

Optimal Design and Control of a Two-Speed Planetary Gear Automatic Transmission for Electric Vehicle

by Wei Huang, Jianfeng Huang and Chengliang Yin

Appl. Sci. 2020, 10(18), 6612; https://doi.org/10.3390/app10186612 - 22 Sep 2020

Cited by 14 | Viewed by 9195

Abstract

Multispeed transmissions are helpful for improvement of the economy and drivability of electric vehicles (EVs). In this paper, we propose a two-speed transmission based on dual planetary gear mechanism, in which shifts are realized by torque transfer between two brakes located on ring [...] Read more.

Multispeed transmissions are helpful for improvement of the economy and drivability of electric vehicles (EVs). In this paper, we propose a two-speed transmission based on dual planetary gear mechanism, in which shifts are realized by torque transfer between two brakes located on ring gears. To synthesize the dynamic and economic performances of the vehicle, a multiobjective optimization problem is constructed for gear ratio optimization and Pareto-optimal solutions of gear ratio combinations are obtained by Nondominated sorting genetic algorithm-II (NSGA-II). In particular, the minimum electric energy consumption of the EV is calculated with a fast Dynamic Programming (DP) in each iteration. Following this, a constant-output-torque control (COTC) scheme is adopted for the torque phase and inertia phase of gearshift process to ensure constant output torque on the wheel. To enhance transient responses, the feedforward–feedback controller structure is applied and a disturbance observer is integrated to improve robustness. Simulation results demonstrate that the two-speed transmission has much better performance in terms of acceleration time and energy economy compared to the fixed-ratio transmission, and the proposed gearshift control method is able to achieve fast and smooth gear shift robustly while maintaining constant output torque. Full article

(This article belongs to the Special Issue Electric (Hybrid) Vehicles: Optimization Techniques, Control Systems and Powertrain Modeling - selected papers from conference EVER2021)

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21 pages, 401 KiB

Open AccessArticle

Scheduling in Heterogeneous Distributed Computing Systems Based on Internal Structure of Parallel Tasks Graphs with Meta-Heuristics

by Apolinar Velarde Martinez

Appl. Sci. 2020, 10(18), 6611; https://doi.org/10.3390/app10186611 - 22 Sep 2020

Cited by 7 | Viewed by 3072

Abstract

The problem of scheduling parallel tasks graphs (PTGs) represented by directed acyclic graphs (DAGs) in heterogeneous distributed computing systems (HDCSs) is considered an nondeterministic polynomial time (NP) problem due to the diversity of characteristics and parameters, generally opposed, intended to be optimized. The [...] Read more.

The problem of scheduling parallel tasks graphs (PTGs) represented by directed acyclic graphs (DAGs) in heterogeneous distributed computing systems (HDCSs) is considered an nondeterministic polynomial time (NP) problem due to the diversity of characteristics and parameters, generally opposed, intended to be optimized. The PTGs are scheduled by a scheduler that determines the best location for the sub-tasks that constitute the PTGs and is responsible for allocating the resources of the HDCS to the sub-tasks of the PTGs. To optimize scheduling and allocations, the scheduler extracts characteristics from the internal structure of the PTGs. The prevailing characteristic in existing research is the critical path (CP), which is limited to providing execution paths of PTGs; considering this limitation, we extend the array method proposed in Velarde, which extracts two additional characteristics to the CP: the layering and the density of the graph for scheduling. These characteristics are represented as integer values of the PTGs to be scheduled; the values obtained from the characteristics are stored in arrays representing populations that are evaluated with the heuristic univariate marginal distribution algorithm (UMDA) and in terms of comparison with the genetic algorithm. With the best allocations produced by the algorithms, two performance parameters are evaluated: makespan and waiting time. The results indicate that when more PTGs characteristics are considered, resource allocations are optimized, and scheduling times are reduced. The results obtained with the heuristic algorithms show that UMDA provides shorter scheduling and allocation times compared with the genetic algorithm; UMDA widely distributes the sub-tasks in the clusters, whereas the genetic algorithm compacts the assignments of the PTGs in the clusters with a longer convergence time that translates into longer scheduling and allocation times. Extensive explanations of these conclusions are provided in this work, based on the conducted experiments. Full article

(This article belongs to the Special Issue Interdisciplinary Artificial Intelligence: Methods and Applications of Nature-Inspired Computing)

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18 pages, 7923 KiB

Open AccessArticle

Quantitative Demonstration of Wear Rate and Dissipation Energy during Tension–Torsion Cyclic Loading of Steel Wires with Fretting Contact in Different Environmental Media

by Dagang Wang, Xiangru Wang, Guozheng Xie and Huilong Zhu

Appl. Sci. 2020, 10(18), 6610; https://doi.org/10.3390/app10186610 - 22 Sep 2020

Cited by 2 | Viewed by 2501

Abstract

The wear rate and dissipation energy during tension–torsion cyclic loading of steel wires with fretting contact in different environmental media were explored in this study. Hysteresis loops of tangential force versus displacement amplitude (Ft-D) and torque versus torsion angle (T-θ [...] Read more.

The wear rate and dissipation energy during tension–torsion cyclic loading of steel wires with fretting contact in different environmental media were explored in this study. Hysteresis loops of tangential force versus displacement amplitude (Ft-D) and torque versus torsion angle (T-θ), and their dissipation energies were obtained employing the self-made test rig. Morphologies of wear scars of steel wires were observed employing the white light interference surface morphology. The quantitative demonstration of the coefficient of cyclic wear of steel wire was carried out combining polynomial fitting, reconstruction of three-dimensional geometric model of wear scar and Archard’s equation. The results show that F_t-D curves reveal both decreases of the relative slip and dissipation energy in the order: corrosive media, deionized water and air. Increases of contact load and crossing angle caused overall decreases in the relative slip and dissipation energy, while the relative slip and dissipation energy both increased with increasing torsion angle. T-θ curves indicated the largest and smallest dissipation energies in cases of acid solution and deionized water, respectively. Increases of contact load, crossing angle and torsion angle caused increases in relative slip and dissipation energy due to cyclic torsional loading with fretting contact. The wear coefficient in cases of distinct environmental media decreased in this order: air, corrosive media and deionized water. Increases of the contact load, torsion angle and crossing angle all induced increases in the wear coefficient. Full article

(This article belongs to the Section Mechanical Engineering)

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14 pages, 5814 KiB

Open AccessArticle

From the Point Cloud to BIM Methodology for the Ideal Reconstruction of a Lost Bastion of the Cáceres Wall

by Pablo Alejandro Cruz Franco, Adela Rueda Márquez de la Plata and Jesús Cruz Franco

Appl. Sci. 2020, 10(18), 6609; https://doi.org/10.3390/app10186609 - 22 Sep 2020

Cited by 16 | Viewed by 2953

Abstract

Thanks to the use of non-invasive techniques and remote sensing in a 19th century building, it was possible to demonstrate that said building is a lost part of the Cáceres wall. This wall was believed to maintain the straight line from a known [...] Read more.

Thanks to the use of non-invasive techniques and remote sensing in a 19th century building, it was possible to demonstrate that said building is a lost part of the Cáceres wall. This wall was believed to maintain the straight line from a known section, but remote sensing makes it clear that at that point the wall makes a break creating a door of which there was no record. Once this premise was confirmed, an ideal reconstruction hypothesis was developed. For this, the work base was taken on the data collected in an exhaustive data collection process, which launched millions of control points and facilitated in theorizing the original state of this lost section. The HBIM methodology greatly facilitated the process, and will allow for possible modifications with an IFC file as advances are made in that area. Finally, the research proposes an architectural project path that takes into account the data obtained remotely, and that achieves the inclusion of this part of the city in cultural interest and, of course, in a protected and cataloged area. Full article

(This article belongs to the Special Issue Theory and Modelling of Historic Masonry Architecture)

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16 pages, 1159 KiB

Open AccessArticle

Assessing Significant Factors Affecting Risky Riding Behaviors of Motorcyclists

by Wins Cott Goh, Lee Vien Leong and Richard Jun Xian Cheah

Appl. Sci. 2020, 10(18), 6608; https://doi.org/10.3390/app10186608 - 22 Sep 2020

Cited by 10 | Viewed by 3386

Abstract

This study was conducted in Malaysia, where motorcycle traffic accidents represent a high percentage of fatality among overall traffic accidents. Studies have shown that risk perception and positive outcome of risky riding behavior have a significant impact on a rider’s decision making. Therefore, [...] Read more.

This study was conducted in Malaysia, where motorcycle traffic accidents represent a high percentage of fatality among overall traffic accidents. Studies have shown that risk perception and positive outcome of risky riding behavior have a significant impact on a rider’s decision making. Therefore, this study is targeted at further understanding of Malaysian motorcyclists within the locality of their home country. A questionnaire survey was conducted to gather motorcycle rider’s information, together with their perception of the three factors mentioned above. A reliability test of the findings was analyzed using Cronbach’s Alpha, while a PCA analysis was conducted to determine the linear combinations that have maximum variance. Subsequently, a statistical model was constructed based on the latent variables’ relations, the relation between the latent variables and observed variables, and also the hypothesis model. The model confirms that the positive affect of the risky behavior has a significant positive relationship with motorcyclists’ risk behavior (estimate coefficient = 1.016). Findings in the model also show that older motorcyclists are less likely to take part in risky riding behavior while riding on the road, with an estimate coefficient of −0.037 and a negative relationship with positive affect (estimate coefficient = −0.032). Full article

(This article belongs to the Section Civil Engineering)

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23 pages, 1157 KiB

Open AccessArticle

Proof of Adjourn (PoAj): A Novel Approach to Mitigate Blockchain Attacks

by Sarwar Sayeed and Hector Marco-Gisbert

Appl. Sci. 2020, 10(18), 6607; https://doi.org/10.3390/app10186607 - 22 Sep 2020

Cited by 21 | Viewed by 5033

Abstract

The blockchain is a distributed ledger technology that is growing in importance since inception. Besides cryptocurrencies, it has also crossed its boundary inspiring various organizations, enterprises, or business establishments to adopt this technology benefiting from the most innovative security features. The decentralized and [...] Read more.

The blockchain is a distributed ledger technology that is growing in importance since inception. Besides cryptocurrencies, it has also crossed its boundary inspiring various organizations, enterprises, or business establishments to adopt this technology benefiting from the most innovative security features. The decentralized and immutable aspects have been the key points that endorse blockchain as one of the most secure technologies at the present time. However, in recent times such features seemed to be faded due to new attacking techniques. One of the biggest challenges remains within the consensus protocol itself, which is an essential component to bring all network participants to an agreed state. Cryptocurrencies adopt suitable consensus protocols based on their mining requirement, and Proof of Work (PoW) is the consensus protocol that is being predominated in major cryptocurrencies. Recent consensus protocol-based attacks, such as the 51% attack, Selfish Mining, Miner Bribe Attack, Zero Confirmation Attack, and One Confirmation Attack have been demonstrated feasible. To overcome these attacks, we propose Proof of Adjourn (PoAj), a novel consensus protocol that provides strong protection regardless of attackers hashing capability. After analyzing the 5 major attacks, and current protection techniques indicating the causes of their failure, we compared the PoAj against the most widely used PoW, showing that PoAj is not only able to mitigate the 5 attacks but also attacks relying on having a large amount of hashing power. In addition, the proposed PoAj showed to be an effective approach to mitigate the processing time issue of large-sized transactions. PoAj is not tailored to any particular attack; therefore, it is effective against malicious powerful players. The proposed approach provides a strong barrier not only to current and known attacks but also to future unknown attacks based on different strategies that rely on controlling the majority of the hashing power. Full article

(This article belongs to the Special Issue Advances in Blockchain Technology and Applications II)

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20 pages, 3615 KiB

Open AccessArticle

Multidomain Simulation Model for Analysis of Geometric Variation and Productivity in Multi-Stage Assembly Systems

by Sergio Benavent Nácher, Pedro Rosado Castellano, Fernando Romero Subirón and José V. Abellán-Nebot

Appl. Sci. 2020, 10(18), 6606; https://doi.org/10.3390/app10186606 - 22 Sep 2020

Cited by 6 | Viewed by 2762

Abstract

Nowadays, the new era of industry 4.0 is forcing manufacturers to develop models and methods for managing the geometric variation of a final product in complex manufacturing environments, such as multistage manufacturing systems. The stream of variation model has been successfully applied to [...] Read more.

Nowadays, the new era of industry 4.0 is forcing manufacturers to develop models and methods for managing the geometric variation of a final product in complex manufacturing environments, such as multistage manufacturing systems. The stream of variation model has been successfully applied to manage product geometric variation in these systems, but there is a lack of research studying its application together with the material and order flow in the system. In this work, which is focused on the production quality paradigm in a model-based system engineering context, a digital prototype is proposed to integrate productivity and part quality based on the stream of variation analysis in multistage assembly systems. The prototype was modelled and simulated with OpenModelica tool exploiting the Modelica language capabilities for multidomain simulations and its synergy with SysML. A case study is presented to validate the potential applicability of the approach. The proposed model and the results show a promising potential for future developments aligned with the production quality paradigm. Full article

(This article belongs to the Special Issue Mechanical Tolerance Analysis in the Era of Industry 4.0)

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12 pages, 670 KiB

Open AccessArticle

Dosimetric Issues Associated with Percutaneous Ablation of Small Liver Lesions with ⁹⁰Y

by Marco D’Arienzo, Anna Sarnelli, Emilio Mezzenga, Laura Chiacchiararelli, Antonino Amato, Massimo Romanelli, Roberto Cianni, Marta Cremonesi and Giovanni Paganelli

Appl. Sci. 2020, 10(18), 6605; https://doi.org/10.3390/app10186605 - 22 Sep 2020

Cited by 3 | Viewed by 2607

Abstract

The aim of the present paper is twofold. Firstly, to assess the absorbed dose in small lesions using Monte Carlo calculations in a scenario of intratumoral injection of ⁹⁰Y (e.g., percutaneous ablation). Secondly, to derive a practical analytical formula for the calculation [...] Read more.

The aim of the present paper is twofold. Firstly, to assess the absorbed dose in small lesions using Monte Carlo calculations in a scenario of intratumoral injection of ⁹⁰Y (e.g., percutaneous ablation). Secondly, to derive a practical analytical formula for the calculation of the absorbed dose that incorporates the absorbed fractions for ⁹⁰Y. The absorbed dose per unit administered activity was assessed using Monte Carlo calculations in spheres of different size (diameter 0.5–20 cm). The spheres are representative of tumor regions and are assumed to be uniformly filled with ⁹⁰Y. Monte Carlo results were compared with the macrodosimetric approach used for dose calculation in liver radioembolization. The results of this analysis indicate that the use of the analytic model provides dose overestimates below 10% for lesions with diameter larger than approximately 2 cm. However, for lesions smaller than 2 cm the analytic model is likely to deviate significantly (>10%) from Monte Carlo results, providing dose overestimations larger than 50% for lesions of 0.5 cm diameter. In this paper an analytical formula derived from MC calculations that incorporates the absorbed fractions for ⁹⁰Y is proposed. In a scenario of intratumoral injection of microspheres, the proposed equation can be usefully employed in the treatment planning of spherical lesions of small size (down to 0.5 cm diameter) providing dose estimates in close agreement with Monte Carlo calculations (maximum deviation below 0.5%). Full article

(This article belongs to the Special Issue Applications of Medical Physics)

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28 pages, 4885 KiB

Open AccessArticle

Development and Implementation of a Novel Optimization Algorithm for Reliable and Economic Grid-Independent Hybrid Power System

by Mohammed Kharrich, Omar Hazem Mohammed, Salah Kamel, Ali Selim, Hamdy M. Sultan, Mohammed Akherraz and Francisco Jurado

Appl. Sci. 2020, 10(18), 6604; https://doi.org/10.3390/app10186604 - 21 Sep 2020

Cited by 36 | Viewed by 3806

Abstract

Recently, fast uptake of renewable energy sources (RES) in the world has introduced new difficulties and challenges; one of the most important challenges is providing economic energy with high efficiency and good quality. To reach this goal, many traditional and smart algorithms have [...] Read more.

Recently, fast uptake of renewable energy sources (RES) in the world has introduced new difficulties and challenges; one of the most important challenges is providing economic energy with high efficiency and good quality. To reach this goal, many traditional and smart algorithms have been proposed and demonstrated their feasibility in obtaining the optimal solution. Therefore, this paper introduces an improved version of Bonobo Optimizer (BO) based on a quasi-oppositional method to solve the problem of designing a hybrid microgrid system including RES (photovoltaic (PV) panels, wind turbines (WT), and batteries) with diesel generators. A comparison between traditional BO, the Quasi-Oppositional BO (QOBO), and other optimization techniques called Harris Hawks Optimization (HHO), Artificial Electric Field Algorithm (AEFA) and Invasive Weed Optimization (IWO) is carried out to check the efficiency of the proposed QOBO. The QOBO is applied to a stand-alone hybrid microgrid system located in Aswan, Egypt. The results show the effectiveness of the QOBO algorithm to solve the optimal economic design problem for hybrid microgrid power systems. Full article

(This article belongs to the Special Issue Microgrids/Nanogrids Implementation, Planning, and Operation)

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18 pages, 3458 KiB

Open AccessArticle

Frequent Microalgae in the Fountains of the Alhambra and Generalife: Identification and Creation of a Culture Collection

by Fernando Bolívar-Galiano, Clara Abad-Ruiz, Pedro Sánchez-Castillo, Maurizio Toscano and Julio Romero-Noguera

Appl. Sci. 2020, 10(18), 6603; https://doi.org/10.3390/app10186603 - 21 Sep 2020

Cited by 4 | Viewed by 3988

Abstract

Cyanobacteria, green algae and diatoms are significant factors in the biodeterioration of stone cultural heritage sites, and specifically fountain monuments, due to the constant presence of water. In this study, samples were taken from different fountains in the Alhambra and Generalife, which are [...] Read more.

Cyanobacteria, green algae and diatoms are significant factors in the biodeterioration of stone cultural heritage sites, and specifically fountain monuments, due to the constant presence of water. In this study, samples were taken from different fountains in the Alhambra and Generalife, which are among the Spanish monuments of greatest historical and artistic value and which together were declared a World Heritage Site by UNESCO in 1984. The aim was to identify which species of colonising microalgae are most frequent and to obtain monoalgal cultures from them. From a conservation point of view, it is interesting to identify which algae are growing in these fountains and how they behave in order to develop new methods to control their growth. The most abundant groups of algae in our samples were green algae and cyanobacteria. The most common genera in the former group were Bracteacoccus, Chlorosarcina, Chlorosarcinopsis, Apatococcus and Klebsormidium. As for cyanobacteria, the most abundant genera were Phormidium, Calothrix, Leptolyngbya, Chamaesiphon, Pleurocapsa and Chlorogloea. Using our collected samples, 10 genera of green algae and 13 genera of cyanobacteria were isolated, thereby constituting the base samples for the creation of a reference collection of living algae from the Alhambra and Generalife contexts, which can be used in subsequent studies to develop new types of treatment against biodeterioration. Full article

(This article belongs to the Special Issue Microbial Communities in Cultural Heritage and Their Control)

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23 pages, 4514 KiB

Open AccessArticle

A Finite State Method in the Performance Evaluation of the Bernoulli Serial Production Lines

by Neven Hadžić, Viktor Ložar and Filip Abdulaj

Appl. Sci. 2020, 10(18), 6602; https://doi.org/10.3390/app10186602 - 21 Sep 2020

Cited by 6 | Viewed by 2704

Abstract

Research on the performance measure evaluation of Bernoulli serial production lines is presented in this paper. Important aspects of the modeling and analysis using transition systems within the Markovian framework are addressed, including analytical and approximation methods. The “dimensionality curse” problems of the [...] Read more.

Research on the performance measure evaluation of Bernoulli serial production lines is presented in this paper. Important aspects of the modeling and analysis using transition systems within the Markovian framework are addressed, including analytical and approximation methods. The “dimensionality curse” problems of the large scale and dense transition systems in the production system engineering field are pointed out as one of the main research and development obstacles. In that respect, a new analytically-based finite state method is presented based on the proportionality property of the stationary probability distribution across the systems’ state space. Simple and differentiable expressions for the performance measures including the production rate, the work-in-process, and the probabilities of machine blockage and starvation are formulated. A finite state method’s accuracy and applicability are successfully validated by comparing the obtained results against the rigorous analytical solution. Full article

(This article belongs to the Section Mechanical Engineering)

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16 pages, 3280 KiB

Open AccessArticle

Research on Strength Prediction Model of Sand-like Material Based on Nuclear Magnetic Resonance and Fractal Theory

by Hongwei Deng, Guanglin Tian, Songtao Yu, Zhen Jiang, Zhiming Zhong and Yanan Zhang

Appl. Sci. 2020, 10(18), 6601; https://doi.org/10.3390/app10186601 - 21 Sep 2020

Cited by 30 | Viewed by 2806

Abstract

Micro-pore structure has a decisive effect on the physical and mechanical properties of porous materials. To further improve the composition of rock-like materials, the internal relationship between microscopic characteristics (porosity, pore size distribution) and macroscopic mechanical properties of materials needs to be studied. [...] Read more.

Micro-pore structure has a decisive effect on the physical and mechanical properties of porous materials. To further improve the composition of rock-like materials, the internal relationship between microscopic characteristics (porosity, pore size distribution) and macroscopic mechanical properties of materials needs to be studied. This study selects portland cement, quartz sand, silica fume, and water-reducing agent as raw materials to simulate sandstone. Based on the Nuclear magnetic resonance (NMR) theory and fractal theory, the study explores the internal relationship between pore structure and mechanical properties of sandstone-like materials, building a compressive strength prediction model by adopting the proportion of macropores and the dimension of macropore pore size as dependent variables. Test results show that internal pores of the material are mainly macropores, and micropores account for the least. The aperture fractal dimension, the correlation coefficient of mesopores and macropores are quite different from those of micropores. Fractal characteristics of mesopores and macropores are obvious. The macropore pore volume ratio has a good linear correlation with fractal dimension and strength, and it has a higher correlation coefficient with pore volume ratio, pore fractal dimension and other variable factors. The compressive strength increases with the growth of pore size fractal dimension, but decreases with the growth of macropore pore volume ratio. The strength prediction model has a high correlation coefficient, credibility and prediction accuracy, and the predicted strength is basically close to the measured strength. Full article

(This article belongs to the Special Issue Advances in Design, Repair and Materials of Structural Concrete)

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17 pages, 1117 KiB

Open AccessArticle

A Comprehensive Approach in Medical Nutrition Therapy for Adults’ Weight Loss Management in Lebanon

by Marie-Therese Khalil, Joseph Matta, Mateja Videmšek, Damir Karpljuk and Maja Meško

Appl. Sci. 2020, 10(18), 6600; https://doi.org/10.3390/app10186600 - 21 Sep 2020

Cited by 1 | Viewed by 3498

Abstract

The objective of the research is to identify the different factors of Lebanese culture that interfere with weight loss therapy and assist the field of nutrition in homogenising in a standardised manner the protocol of Medical Nutrition Therapy (MNT). The first part of [...] Read more.

The objective of the research is to identify the different factors of Lebanese culture that interfere with weight loss therapy and assist the field of nutrition in homogenising in a standardised manner the protocol of Medical Nutrition Therapy (MNT). The first part of the study is based on a literature review, and, in the second part, quantitative analysis was used. The research was conducted on 514 Lebanese adults via questionnaire. The analysis was performed with the AMOS (Version 22, IBM®, Amonk, NY, USA) statistical tool. For the analysis of correlations, chi-square and non-parametric tests were used. Variables affecting weight loss management were identified with the aid of seven hypotheses using structural equation modelling (SEM). Body shape and Body Mass Index (BMI) were found to be inter-related to cognitive behaviours toward food, lifestyle practices, medical conditions, food and beverages. In parallel, and based on the research results, younger adults, in particular women, have better BMI and look better in terms of body shape. Ageing has a direct impact on weight gain. Older people have a lower activity level, which is more prevalent among women, and they also prefer to eat typical Lebanese food. Habits, such as smoking, drinking alcohol, are directly related to obesity and some medical conditions. Low physical activity influences the problems related to body shape. For further studies, one should also include types of physical activities in terms of intensity and number of hours. This would assist the study in being more specified and credible toward the effect of exercise on weight loss management. Full article

(This article belongs to the Section Applied Biosciences and Bioengineering)

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18 pages, 10270 KiB

Open AccessArticle

Shock-Absorber Rotary Generator for Automotive Vibration Energy Harvesting

by Tae Dong Kim and Jin Ho Kim

Appl. Sci. 2020, 10(18), 6599; https://doi.org/10.3390/app10186599 - 21 Sep 2020

Cited by 8 | Viewed by 6749

Abstract

The vibration energy derived from vehicle movement over a road surface was first converted to rotational energy during vehicle operation by installing blades in the suspension system. The rotational energy was converted to electrical energy using the rotational energy as the input value [...] Read more.

The vibration energy derived from vehicle movement over a road surface was first converted to rotational energy during vehicle operation by installing blades in the suspension system. The rotational energy was converted to electrical energy using the rotational energy as the input value of the rotary generator. The vibrations from the road’s surface were analyzed using CarSim-Simulink. The blades’ characteristics were analyzed using ANSYS Fluent. The T–ω curve was derived, and the power generation of the rotary generator was verified using the commercial electromagnetic analysis program, ANSYS MAXWELL. For high power generation, the design was optimized using PIAnO (process integration, automation, and optimization), a PIDO (process integration and design optimization) tool. The amount of power generation was 59.4562 W, which was a 122.47% increase compared to the initial model. The remaining problems were analyzed, and further studies were performed. This paper proposes the applicability and development direction of suspension with energy harvesting by installing blades on suspension. Full article

(This article belongs to the Special Issue Automobile Energy Harvesting Technologies)

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34 pages, 10305 KiB

Open AccessArticle

ERS-1/2 and Sentinel-1 SAR Data Mining for Flood Hazard and Risk Assessment in Lima, Peru

by Nancy Alvan Romero, Francesca Cigna and Deodato Tapete

Appl. Sci. 2020, 10(18), 6598; https://doi.org/10.3390/app10186598 - 21 Sep 2020

Cited by 10 | Viewed by 5757

Abstract

The coastline environment and urban areas of Peru overlooking the Pacific Ocean are among the most affected by El Niño-Southern Oscillation (ENSO) events, and its cascading hazards such as floods, landslides and avalanches. In this work, the complete archives of the European Space [...] Read more.

The coastline environment and urban areas of Peru overlooking the Pacific Ocean are among the most affected by El Niño-Southern Oscillation (ENSO) events, and its cascading hazards such as floods, landslides and avalanches. In this work, the complete archives of the European Space Agency (ESA)’s European Remote-Sensing (ERS-1/2) missions and European Commission’s Copernicus Sentinel-1 constellation were screened to select synthetic aperture radar (SAR) images covering the most severe and recent ENSO-related flooding events that affected Lima, the capital and largest city of Peru, in 1997–1998 and 2017–2018. Based on SAR backscatter color composites and ratio maps retrieved from a series of pre-, cross- and post-event SAR pairs, flooded areas were delineated within the Rímac River watershed. These are mostly concentrated along the riverbanks and plain, where low-lying topography and gentle slopes (≤5°), together with the presence of alluvial deposits, also indicate greater susceptibility to flooding. A total of 409 areas (58.50 km²) revealing change were mapped, including 197 changes (32.10 km²) due to flooding-related backscatter variations (flooded areas, increased water flow in the riverbed, and riverbank collapses and damage), and 212 (26.40 km²) due to other processes (e.g., new urban developments, construction of river embankments, other engineering works, vegetation changes). Urban and landscape changes potentially contributing, either detrimentally or beneficially, to flooding susceptibility were identified and considered in the overall assessment of risk. The extent of built-up areas within the basin was mapped by combining information from the 2011 Global Urban Footprint (GUF) produced by the German Aerospace Center (DLR), the Open Street Map (OSM) accessed from the Quantum GIS (QGIS) service, and 2011–2019 very high-resolution optical imagery from Google Earth. The resulting flooding risk map highlights the sectors of potential concern along the Rímac River, should flooding events of equal severity as those captured by SAR images occur in the future. Full article

(This article belongs to the Special Issue Advances in Remote Sensing and GIS for Natural Hazards Assessment)

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