Technologies

15 pages, 1994 KiB

Open AccessEditor’s ChoiceArticle

Visual Performance and Perceptual–Motor Skills of Late Preterm Children and Healthy Controls Using the TVPS-3rd and VMI-6th Editions

by Danjela Ibrahimi, Jorge D. Mendiola Santibañez and Juvenal Rodríguez-Reséndiz

Technologies 2023, 11(2), 53; https://doi.org/10.3390/technologies11020053 - 4 Apr 2023

Cited by 2 | Viewed by 2607

Abstract

Background: The visual system is key to the learning process, preterm births are commonly followed by visual dysfunctions and other neurological conditions. Objective: to measure, analyze and compare the visual efficacy, visual–perceptual, and visual–motor skills of 20 late preterm children (34–36 weeks) born [...] Read more.

Background: The visual system is key to the learning process, preterm births are commonly followed by visual dysfunctions and other neurological conditions. Objective: to measure, analyze and compare the visual efficacy, visual–perceptual, and visual–motor skills of 20 late preterm children (34–36 weeks) born by caesarean section and appropriate weight for gestational age with 20 healthy controls born at full term by natural birth, age 5 to 12 years, from Querétaro, México. Methods: This was an observational, transverse, and prospective study. Parametric and non-parametric tests were performed using the SPSS 25.0. The visual acuity at distance and near, the phoria state, and the degree of stereopsis were analyzed. The Test of Visual-Perceptual Skills, Third Edition, was used to assess the overall performance, basic, sequencing, and complex processes. Fine motor skills were evaluated using the Visual–Motor Integration Test of Beery, Sixth Edition. Results: Visual acuity at distance and near (

p < 0.001

), stereopsis (

p < 0.001

), and the amount of exophoria at distance (

p = 0.01

) showed statistically significant differences between the groups. The overall performance (

p = 0.006

), basic processes (

p = 0.001

), sequencing processes (

p = 0.02

), and General and Motor VMI (

p < 0.001

and

0.002

, respectively) presented lower values in children born preterm. Conclusion: This research showed that even late preterm children present visual deficiencies and are at risk of delays on perceptual–motor skills. Early evaluation of their visual and motor abilities should be considered in order to help improve their cognitive functioning. Full article

(This article belongs to the Special Issue Smart Systems (SmaSys2022))

► Show Figures

Figure 1

11 pages, 4140 KiB

Open AccessEditor’s ChoiceCommunication

HAIS: Highways Automated-Inspection System

by Hossam A. Gabbar, Abderrazak Chahid, Manir U. Isham, Shashwat Grover, Karan Pal Singh, Khalid Elgazzar, Ahmad Mousa and Hossameldin Ouda

Technologies 2023, 11(2), 51; https://doi.org/10.3390/technologies11020051 - 1 Apr 2023

Cited by 4 | Viewed by 2833

Abstract

A smart city is a trending concept describing a new generation of cities operated intelligently with minimal human intervention. It promotes energy sustainability, minimal environmental impact, and better governance. In transportation, the remote highway infrastructure monitoring will enhance the driver’s safety, continuously report [...] Read more.

A smart city is a trending concept describing a new generation of cities operated intelligently with minimal human intervention. It promotes energy sustainability, minimal environmental impact, and better governance. In transportation, the remote highway infrastructure monitoring will enhance the driver’s safety, continuously report road conditions, and identify potential hazardous incidents such as accidents, floods, or snow storms. In addition, it facilitates the integration of future cuttingedge technologies such as self-driving vehicles. This paper presents a general introduction to a smart monitoring system for automated real-time road condition inspection. The proposed solution includes hardware devices/nodes and software applications for data processing, road condition inspection using hybrid algorithms based on digital signal processing, and artificial intelligence technologies. The proposed system has an interactive web interface for real-time data sharing, infrastructure monitoring, visualization, and management of inspection reports which can improve the maintenance process. Full article

(This article belongs to the Topic Emerging Technologies for Grid-Interactive Efficient Buildings and Communities)

► Show Figures

Figure 1

18 pages, 1984 KiB

Open AccessEditor’s ChoiceArticle

Forecasting by Combining Chaotic PSO and Automated LSSVR

by Wei-Chang Yeh and Wenbo Zhu

Technologies 2023, 11(2), 50; https://doi.org/10.3390/technologies11020050 - 30 Mar 2023

Cited by 4 | Viewed by 1630

Abstract

An automatic least square support vector regression (LSSVR) optimization method that uses mixed kernel chaotic particle swarm optimization (CPSO) to handle regression issues has been provided. The LSSVR model is composed of three components. The position of the particles (solution) in a chaotic [...] Read more.

An automatic least square support vector regression (LSSVR) optimization method that uses mixed kernel chaotic particle swarm optimization (CPSO) to handle regression issues has been provided. The LSSVR model is composed of three components. The position of the particles (solution) in a chaotic sequence with good randomness and ergodicity of the initial characteristics is taken into consideration in the first section. The binary particle swarm optimization (PSO) used to choose potential input characteristic combinations makes up the second section. The final step involves using a chaotic search to narrow down the set of potential input characteristics before combining the PSO-optimized parameters to create CP-LSSVR. The CP-LSSVR is used to forecast the impressive datasets testing targets obtained from the UCI dataset for purposes of illustration and evaluation. The results suggest CP-LSSVR has a good predictive capability discussed in this paper and can build a projected model utilizing a limited number of characteristics. Full article

(This article belongs to the Special Issue 10th Anniversary of Technologies—Recent Advances and Perspectives)

► Show Figures

Figure 1

19 pages, 11909 KiB

Open AccessEditor’s ChoiceArticle

Image-Based Quantification of Color and Its Machine Vision and Offline Applications

by Woo Sik Yoo, Kitaek Kang, Jung Gon Kim and Yeongsik Yoo

Technologies 2023, 11(2), 49; https://doi.org/10.3390/technologies11020049 - 29 Mar 2023

Cited by 2 | Viewed by 3842

Abstract

Image-based colorimetry has been gaining relevance due to the wide availability of smart phones with image sensors and increasing computational power. The low cost and portable designs with user-friendly interfaces, and their compatibility with data acquisition and processing, are very attractive for interdisciplinary [...] Read more.

Image-based colorimetry has been gaining relevance due to the wide availability of smart phones with image sensors and increasing computational power. The low cost and portable designs with user-friendly interfaces, and their compatibility with data acquisition and processing, are very attractive for interdisciplinary applications from art, the fashion industry, food science, medical science, oriental medicine, agriculture, geology, chemistry, biology, material science, environmental engineering, and many other applications. This work describes the image-based quantification of color and its machine vision and offline applications in interdisciplinary fields using specifically developed image analysis software. Examples of color information extraction from a single pixel to predetermined sizes/shapes of areas, including customized regions of interest (ROIs) from various digital images of dyed T-shirts, tongues, and assays, are demonstrated. Corresponding RGB, HSV, CIELAB, Munsell color, and hexadecimal color codes, from a single pixel to ROIs, are extracted for machine vision and offline applications in various fields. Histograms and statistical analyses of colors from a single pixel to ROIs are successfully demonstrated. Reliable image-based quantification of color, in a wide range of potential applications, is proposed and the validity is verified using color quantification examples in various fields of applications. The objectivity of color-based diagnosis, judgment and control can be significantly improved by the image-based quantification of color proposed in this study. Full article

(This article belongs to the Special Issue Image and Signal Processing)

► Show Figures

Figure 1

19 pages, 10511 KiB

Open AccessEditor’s ChoiceArticle

Mobilenetv2_CA Lightweight Object Detection Network in Autonomous Driving

by Peicheng Shi, Long Li, Heng Qi and Aixi Yang

Technologies 2023, 11(2), 47; https://doi.org/10.3390/technologies11020047 - 23 Mar 2023

Cited by 2 | Viewed by 1915

Abstract

A lightweight network target detection algorithm was proposed, based on MobileNetv2_CA, focusing on the problem of high complexity, a large number of parameters, and the missed detection of small targets in the target detection network based on candidate regions and regression methods in [...] Read more.

A lightweight network target detection algorithm was proposed, based on MobileNetv2_CA, focusing on the problem of high complexity, a large number of parameters, and the missed detection of small targets in the target detection network based on candidate regions and regression methods in autonomous driving scenarios. First, Mosaic image enhancement technology is used in the data pre-processing stage to enhance the feature extraction of small target scenes and complex scenes; second, the Coordinate Attention (CA) mechanism is embedded into the Mobilenetv2 backbone feature extraction network, combined with the PANet and Yolo detection heads for multi-scale feature fusion; finally, a Lightweight Object Detection Network is built. The experimental test results show that the designed network obtained the highest average detection accuracy of 81.43% on the Voc2007 + 2012 dataset, and obtained the highest average detection accuracy of 85.07% and a detection speed of 31.84 FPS on the KITTI dataset. The total amount of network parameters is only 39.5 M. This is beneficial to the engineering application of MobileNetv2 network in automatic driving. Full article

(This article belongs to the Special Issue Image and Signal Processing)

► Show Figures

Figure 1

17 pages, 2022 KiB

Open AccessEditor’s ChoiceReview

How to Bell the Cat? A Theoretical Review of Generative Artificial Intelligence towards Digital Disruption in All Walks of Life

by Subhra Mondal, Subhankar Das and Vasiliki G. Vrana

Technologies 2023, 11(2), 44; https://doi.org/10.3390/technologies11020044 - 17 Mar 2023

Cited by 79 | Viewed by 15087

Abstract

Generative Artificial Intelligence (GAI) has brought revolutionary changes to the world, enabling businesses to create new experiences by combining virtual and physical worlds. As the use of GAI grows along with the Metaverse, it is explored by academics, researchers, and industry communities for [...] Read more.

Generative Artificial Intelligence (GAI) has brought revolutionary changes to the world, enabling businesses to create new experiences by combining virtual and physical worlds. As the use of GAI grows along with the Metaverse, it is explored by academics, researchers, and industry communities for its endless possibilities. From ChatGPT by OpenAI to Bard AI by Google, GAI is a leading technology in physical and virtual business platforms. This paper focuses on GAI’s economic and societal impact and the challenges it poses. Businesses must rethink their operations and strategies to create hybrid physical and virtual experiences using GAI. This study proposes a framework that can help business managers develop effective strategies to enhance their operations. It analyzes the initial applications of GAI in multiple sectors to promote the development of future customer solutions and explores how GAI can help businesses create new value propositions and experiences for their customers, and the possibilities of digital communication and information technology. A research agenda is proposed for developing GAI for business management to enhance organizational efficiency. The results highlight a healthy conversation on the potential of GAI in various business sectors to improve customer experience. Full article

(This article belongs to the Section Information and Communication Technologies)

► Show Figures

Figure 1

10 pages, 753 KiB

Open AccessEditor’s ChoicePerspective

Developments and Applications of Artificial Intelligence in Music Education

by Xiaofei Yu, Ning Ma, Lei Zheng, Licheng Wang and Kai Wang

Technologies 2023, 11(2), 42; https://doi.org/10.3390/technologies11020042 - 16 Mar 2023

Cited by 55 | Viewed by 16168

Abstract

With the continuous developments of information technology, advanced computer technology and information technology have been promoted and used in the field of music. As one of the products of the rapid development of information technology, Artificial Intelligence (AI) involves many interdisciplinary subjects, adding [...] Read more.

With the continuous developments of information technology, advanced computer technology and information technology have been promoted and used in the field of music. As one of the products of the rapid development of information technology, Artificial Intelligence (AI) involves many interdisciplinary subjects, adding new elements to music education. By analyzing the advantages of AI in music education, this paper systematically summarizes the application of AI in music education and discusses the development prospects of AI in music education. With the aid of AI, the combination of intelligent technology and on-site teaching solves the lack of individuation in the traditional mode and enhances students’ interest in learning. Full article

(This article belongs to the Special Issue 10th Anniversary of Technologies—Recent Advances and Perspectives)

► Show Figures

Figure 1

14 pages, 277 KiB

Open AccessEditor’s ChoiceReview

A Review of Deep Transfer Learning and Recent Advancements

by Mohammadreza Iman, Hamid Reza Arabnia and Khaled Rasheed

Technologies 2023, 11(2), 40; https://doi.org/10.3390/technologies11020040 - 14 Mar 2023

Cited by 158 | Viewed by 26538

Abstract

Deep learning has been the answer to many machine learning problems during the past two decades. However, it comes with two significant constraints: dependency on extensive labeled data and training costs. Transfer learning in deep learning, known as Deep Transfer Learning (DTL), attempts [...] Read more.

Deep learning has been the answer to many machine learning problems during the past two decades. However, it comes with two significant constraints: dependency on extensive labeled data and training costs. Transfer learning in deep learning, known as Deep Transfer Learning (DTL), attempts to reduce such reliance and costs by reusing obtained knowledge from a source data/task in training on a target data/task. Most applied DTL techniques are network/model-based approaches. These methods reduce the dependency of deep learning models on extensive training data and drastically decrease training costs. Moreover, the training cost reduction makes DTL viable on edge devices with limited resources. Like any new advancement, DTL methods have their own limitations, and a successful transfer depends on specific adjustments and strategies for different scenarios. This paper reviews the concept, definition, and taxonomy of deep transfer learning and well-known methods. It investigates the DTL approaches by reviewing applied DTL techniques in the past five years and a couple of experimental analyses of DTLs to discover the best practice for using DTL in different scenarios. Moreover, the limitations of DTLs (catastrophic forgetting dilemma and overly biased pre-trained models) are discussed, along with possible solutions and research trends. Full article

(This article belongs to the Special Issue Data Science and Big Data in Biology, Physical Science and Engineering)

► Show Figures

Figure 1

23 pages, 5488 KiB

Open AccessEditor’s ChoiceArticle

Non-Contact In-Vehicle Occupant Monitoring System Based on Point Clouds from FMCW Radar

by Yixuan Chen, Yunlong Luo, Jianhua Ma, Alex Qi, Runhe Huang, Francesco De Paulis and Yihong Qi

Technologies 2023, 11(2), 39; https://doi.org/10.3390/technologies11020039 - 13 Mar 2023

Cited by 4 | Viewed by 3193

Abstract

In order to reduce the probability of automobile safety incidents, the in-vehicle occupant monitoring is indispensable. However, occupant monitoring using frequency-modulated continuous wave (FMCW) radar can be challenging due to the interference from passengers’ posture, movement, and the presence of multiple people. This [...] Read more.

In order to reduce the probability of automobile safety incidents, the in-vehicle occupant monitoring is indispensable. However, occupant monitoring using frequency-modulated continuous wave (FMCW) radar can be challenging due to the interference from passengers’ posture, movement, and the presence of multiple people. This paper proposes an improved method for generating point clouds using FMCW radar. The approach involves point cloud clustering, post-processing operations such as segmentation, merging, and filtering of the clustered point cloud to match the actual in-vehicle environment, and a state machine combination step. Experimental results show that the proposed method can achieve high recognition accuracy in scenarios with multiple passengers who are moving and sitting in a relaxed manner. Full article

(This article belongs to the Section Information and Communication Technologies)

► Show Figures

Figure 1

15 pages, 3882 KiB

Open AccessEditor’s ChoiceReview

Aging Mechanism and Models of Supercapacitors: A Review

by Ning Ma, Dongfang Yang, Saleem Riaz, Licheng Wang and Kai Wang

Technologies 2023, 11(2), 38; https://doi.org/10.3390/technologies11020038 - 3 Mar 2023

Cited by 44 | Viewed by 6117

Abstract

Electrochemical supercapacitors are a promising type of energy storage device with broad application prospects. Developing an accurate model to reflect their actual working characteristics is of great research significance for rational utilization, performance optimization, and system simulation of supercapacitors. This paper presents the [...] Read more.

Electrochemical supercapacitors are a promising type of energy storage device with broad application prospects. Developing an accurate model to reflect their actual working characteristics is of great research significance for rational utilization, performance optimization, and system simulation of supercapacitors. This paper presents the fundamental working principle and applications of supercapacitors, analyzes their aging mechanism, summarizes existing supercapacitor models, and evaluates the characteristics and application scope of each model. By examining the current state and limitations of supercapacitor modeling research, this paper identifies future development trends and research focuses in this area. Full article

(This article belongs to the Special Issue 10th Anniversary of Technologies—Recent Advances and Perspectives)

► Show Figures

Figure 1

29 pages, 2313 KiB

Open AccessEditor’s ChoiceArticle

Reconstruction of Industrial and Historical Heritage for Cultural Enrichment Using Virtual and Augmented Reality

by Lukas Paulauskas, Andrius Paulauskas, Tomas Blažauskas, Robertas Damaševičius and Rytis Maskeliūnas

Technologies 2023, 11(2), 36; https://doi.org/10.3390/technologies11020036 - 25 Feb 2023

Cited by 19 | Viewed by 4742

Abstract

Because of its benefits in providing an engaging and mobile environment, virtual reality (VR) has recently been rapidly adopted and integrated in education and professional training. Augmented reality (AR) is the integration of VR with the real world, where the real world provides [...] Read more.

Because of its benefits in providing an engaging and mobile environment, virtual reality (VR) has recently been rapidly adopted and integrated in education and professional training. Augmented reality (AR) is the integration of VR with the real world, where the real world provides context and the virtual world provides or reconstructs missing information. Mixed reality (MR) is the blending of virtual and physical reality environments allowing users to interact with both digital and physical objects at the same time. In recent years, technology for creating reality-based 3D models has advanced and spread across a diverse range of applications and research fields. The purpose of this paper is to design, develop, and test VR for kinaesthetic distance learning in a museum setting. A VR training program has been developed in which learners can select and perform pre-made scenarios in a virtual environment. The interaction in the program is based on kinaesthetic learning characteristics. Scenarios with VR controls simulate physical interaction with objects in a virtual environment for learners. Learners can grasp and lift objects to complete scenario tasks. There are also simulated devices in the virtual environment that learners can use to perform various actions. The study’s goal was to compare the effectiveness of the developed VR educational program to that of other types of educational material. Our innovation is the development of a system for combining their 3D visuals with rendering capable of providing a mobile VR experience for effective heritage enhancement. Full article

(This article belongs to the Special Issue Immersive Technologies and Applications on Arts, Culture and Tourism)

► Show Figures

Figure 1

15 pages, 14241 KiB

Open AccessEditor’s ChoiceArticle

Dual-Band Rectifier Circuit Design for IoT Communication in 5G Systems

by Ioannis D. Bougas, Maria S. Papadopoulou, Achilles D. Boursianis, Spyridon Nikolaidis and Sotirios K. Goudos

Technologies 2023, 11(2), 34; https://doi.org/10.3390/technologies11020034 - 24 Feb 2023

Cited by 5 | Viewed by 2847

Abstract

Radio-frequency (RF) energy harvesting (EH) is emerging as a reliable and constantly available free energy source. The primary factor determining whether this energy can be utilized is how efficiently it can be collected. In this work, an RF EH system is presented. More [...] Read more.

Radio-frequency (RF) energy harvesting (EH) is emerging as a reliable and constantly available free energy source. The primary factor determining whether this energy can be utilized is how efficiently it can be collected. In this work, an RF EH system is presented. More particularly, we designed a dual-band RF to DC rectifier circuit at sub-6 GHz in the 5G bands, able to supply low-power sensors and microcontrollers used in agriculture, the military, or health services. The system operates at

3.5

GHz and 5 GHz in the 5G cellular network’s frequency band FR1. Numerical results reveal that the system provides maximum power conversion efficiency (PCE) equal to 53% when the output load (sensor or microcontroller) is

1.74

kΩ and the input power is 12 dBm. Full article

(This article belongs to the Special Issue Intelligent Reflecting Surfaces for 5G and Beyond)

► Show Figures

Figure 1

28 pages, 1321 KiB

Open AccessEditor’s ChoiceArticle

A Layer-Wise Coupled Thermo-Elastic Shell Model for Three-Dimensional Stress Analysis of Functionally Graded Material Structures

by Salvatore Brischetto, Domenico Cesare and Roberto Torre

Technologies 2023, 11(2), 35; https://doi.org/10.3390/technologies11020035 - 24 Feb 2023

Cited by 6 | Viewed by 1931

Abstract

In this work, a coupled 3D thermo-elastic shell model is presented. The primary variables are the scalar sovra-temperature and the displacement vector. This model allows for the thermal stress analysis of one-layered and sandwich plates and shells embedding Functionally Graded Material (FGM) layers. [...] Read more.

In this work, a coupled 3D thermo-elastic shell model is presented. The primary variables are the scalar sovra-temperature and the displacement vector. This model allows for the thermal stress analysis of one-layered and sandwich plates and shells embedding Functionally Graded Material (FGM) layers. The 3D equilibrium equations and the 3D Fourier heat conduction equation for spherical shells are put together into a set of four coupled equations. They automatically degenerate in those for simpler geometries thanks to proper considerations about the radii of curvature and the use of orthogonal mixed curvilinear coordinates

α

,

β

, and z. The obtained partial differential governing the equations along the thickness direction are solved using the exponential matrix method. The closed form solution is possible assuming simply supported boundary conditions and proper harmonic forms for all the unknowns. The sovra-temperature amplitudes are directly imposed at the outer surfaces for each geometry in steady-state conditions. The effects of the thermal environment are related to the sovra-temperature profiles through the thickness. The static responses are evaluated in terms of displacements and stresses. After a proper and global preliminary validation, new cases are presented for different thickness ratios, geometries, and temperature values at the external surfaces. The considered FGM is metallic at the bottom and ceramic at the top. This FGM layer can be embedded in a sandwich configuration or in a one-layered configuration. This new fully coupled thermo-elastic model provides results that are coincident with the results proposed by the uncoupled thermo-elastic model that separately solves the 3D Fourier heat conduction equation. The differences are always less than 0.5% for each investigated displacement, temperature, and stress component. The differences between the present 3D full coupled model and the the advantages of this new model are clearly shown. Both the thickness layer and material layer effects are directly included in all the conducted coupled thermal stress analyses. Full article

(This article belongs to the Special Issue 10th Anniversary of Technologies—Recent Advances and Perspectives)

► Show Figures

Figure 1

14 pages, 955 KiB

Open AccessEditor’s ChoiceArticle

On the Sliding Mode Control Applied to a DC-DC Buck Converter

by Sandra Huerta-Moro, Oscar Martínez-Fuentes, Victor Rodolfo Gonzalez-Diaz and Esteban Tlelo-Cuautle

Technologies 2023, 11(2), 33; https://doi.org/10.3390/technologies11020033 - 23 Feb 2023

Cited by 3 | Viewed by 3045

Abstract

This work shows the voltage regulation of a DC–DC buck converter by applying sliding mode control using three different cases of sliding surfaces. The DC–DC buck converter is modeled by ordinary differential equations (ODEs) that are solved by applying numerical methods. The ODEs [...] Read more.

This work shows the voltage regulation of a DC–DC buck converter by applying sliding mode control using three different cases of sliding surfaces. The DC–DC buck converter is modeled by ordinary differential equations (ODEs) that are solved by applying numerical methods. The ODEs describe two state variables that are associated to the capacitor voltage and the inductor current. The state variable associated to voltage is regulated by applying two well-known sliding surfaces and a third one that is introduced herein to improve the response of the sliding mode control. The stability of the proposed sliding surface is verified by using a Lyapunov theorem to guarantee closed-loop stability. Finally, simulation results show the improvement of voltage regulation when applying the proposed sliding surface compared to already reported approaches. Full article

► Show Figures

Figure 1

33 pages, 11421 KiB

Open AccessEditor’s ChoiceArticle

Identifying Historic Buildings over Time through Image Matching

by Kyriaki A. Tychola, Stamatis Chatzistamatis, Eleni Vrochidou, George E. Tsekouras and George A. Papakostas

Technologies 2023, 11(1), 32; https://doi.org/10.3390/technologies11010032 - 17 Feb 2023

Viewed by 2900

Abstract

The buildings in a city are of great importance. Certain historic buildings are landmarks and indicate the city’s architecture and culture. The buildings over time undergo changes because of various factors, such as structural changes, natural disaster damages, and aesthetic interventions. The form [...] Read more.

The buildings in a city are of great importance. Certain historic buildings are landmarks and indicate the city’s architecture and culture. The buildings over time undergo changes because of various factors, such as structural changes, natural disaster damages, and aesthetic interventions. The form of buildings in each period is perceived and understood by people of each generation, through photography. Nevertheless, each photograph has its own characteristics depending on the camera (analog or digital) used for capturing it. Any photo, even depicting the same object, is impossible to capture in the same way in terms of illumination, viewing angle, and scale. Hence, to study two or more photographs depicting the same object, first they should be identified and then properly matched. Nowadays, computer vision contributes to this process by providing useful tools. In particular, for this purpose, several feature detection and description algorithms of homologous points have been developed. In this study, the identification of historic buildings over time through feature correspondence techniques and methods is investigated. Especially, photographs from landmarks of Drama city, in Greece, on different dates and conditions (weather, light, rotation, scale, etc.), were gathered and experiments on 2D pairs of images, implementing traditional feature detectors and descriptors algorithms, such as SIFT, ORB, and BRISK, were carried out. This study aims to evaluate the feature matching procedure focusing on both the algorithms’ performance (accuracy, efficiency, and robustness) and the identification of the buildings. SIFT and BRISK are the most accurate algorithms while ORB and BRISK are the most efficient. Full article

(This article belongs to the Special Issue Image and Signal Processing)

► Show Figures

Figure 1

15 pages, 1059 KiB

Open AccessEditor’s ChoiceArticle

FogTrust: Fog-Integrated Multi-Leveled Trust Management Mechanism for Internet of Things

by Abdul Rehman, Kamran Ahmad Awan, Ikram Ud Din, Ahmad Almogren and Mohammed Alabdulkareem

Technologies 2023, 11(1), 27; https://doi.org/10.3390/technologies11010027 - 7 Feb 2023

Cited by 9 | Viewed by 2505

Abstract

The Internet of Things (IoT) is widely used to reduce human dependence. It is a network of interconnected smart devices with internet connectivity that can send and receive data. However, the rapid growth of IoT devices has raised security and privacy concerns, with [...] Read more.

The Internet of Things (IoT) is widely used to reduce human dependence. It is a network of interconnected smart devices with internet connectivity that can send and receive data. However, the rapid growth of IoT devices has raised security and privacy concerns, with the identification and removal of compromised and malicious nodes being a major challenge. To overcome this, a lightweight trust management mechanism called FogTrust is proposed. It has a multi-layer architecture that includes edge nodes, a trusted agent, and a fog layer. The trust agent acts as an intermediary authority, communicating with both IoT nodes and the fog layer for computation. This reduces the burden on nodes and ensures a trustworthy environment. The trust agent calculates the trust degree and transmits it to the fog layer, which uses encryption to maintain integrity. The encrypted value is shared with the trust agent for aggregation to improve the trust degree’s accuracy. The performance of the FogTrust approach was evaluated against various potential attacks, including On-off, Good-mouthing, and Bad-mouthing. The simulation results demonstrate that it effectively assigns low trust degrees to malicious nodes in different scenarios, even with varying percentages of malicious nodes in the network. Full article

(This article belongs to the Special Issue 10th Anniversary of Technologies—Recent Advances and Perspectives)

► Show Figures

Figure 1

25 pages, 4600 KiB

Open AccessEditor’s ChoiceArticle

A Comprehensive Methodology for the Development of an Open Source Experimental Platform for Control Courses

by Marcos Aviles, Juvenal Rodríguez-Reséndiz, Juan Pérez-Ospina and Oscar Lara-Mendoza

Technologies 2023, 11(1), 25; https://doi.org/10.3390/technologies11010025 - 3 Feb 2023

Cited by 4 | Viewed by 2088

Abstract

This article presents the methodology for developing a control laboratory project that provides practical experience based on the ABET criteria. The project is structured around a portable and cheap ball and beam whose integrated system is made using printed circuit boards as the [...] Read more.

This article presents the methodology for developing a control laboratory project that provides practical experience based on the ABET criteria. The project is structured around a portable and cheap ball and beam whose integrated system is made using printed circuit boards as the first task. For the expression of the plant, students are guided to execute the essential stages of the control system design, from system modeling, through the design of the basic or advanced control strategy in the MATLAB and Arduino environment, to the implementation and validation of the closed loop. The proposed methods are clear and direct, greatly fostering the understanding of feedback control techniques and enabling students to gain extensive knowledge in practical implementations of control systems. The methodology is easy to interpret and modify in order to adopt it to any computer, allowing for the implementation of new practical tasks in control courses. Additionally, application examples and student-focused comments are included. This paper describes, in detail, the implementation and development of six laboratory practices for control courses, which have been developed based on ESP32 and other existing equipment. Full article

(This article belongs to the Special Issue Smart Systems (SmaSys2022))

► Show Figures

Figure 1

24 pages, 2335 KiB

Open AccessEditor’s ChoiceArticle

An Advanced Decision Tree-Based Deep Neural Network in Nonlinear Data Classification

by Mohammad Arifuzzaman, Md. Rakibul Hasan, Tasnia Jahan Toma, Samia Binta Hassan and Anup Kumar Paul

Technologies 2023, 11(1), 24; https://doi.org/10.3390/technologies11010024 - 1 Feb 2023

Cited by 9 | Viewed by 5611

Abstract

Deep neural networks (DNNs), the integration of neural networks (NNs) and deep learning (DL), have proven highly efficient in executing numerous complex tasks, such as data and image classification. Because the multilayer in a nonlinearly separable data structure is not transparent, it is [...] Read more.

Deep neural networks (DNNs), the integration of neural networks (NNs) and deep learning (DL), have proven highly efficient in executing numerous complex tasks, such as data and image classification. Because the multilayer in a nonlinearly separable data structure is not transparent, it is critical to develop a specific data classification model from a new and unexpected dataset. In this paper, we propose a novel approach using the concepts of DNN and decision tree (DT) for classifying nonlinear data. We first developed a decision tree-based neural network (DTBNN) model. Next, we extend our model to a decision tree-based deep neural network (DTBDNN), in which the multiple hidden layers in DNN are utilized. Using DNN, the DTBDNN model achieved higher accuracy compared to the related and relevant approaches. Our proposal achieves the optimal trainable weights and bias to build an efficient model for nonlinear data classification by combining the benefits of DT and NN. By conducting in-depth performance evaluations, we demonstrate the effectiveness and feasibility of the proposal by achieving good accuracy over different datasets. Full article

(This article belongs to the Special Issue Data Science and Big Data in Biology, Physical Science and Engineering)

► Show Figures

Figure 1

20 pages, 7629 KiB

Open AccessEditor’s ChoiceArticle

Application and Analysis of Modified Metal-Oxide Memristor Models in Electronic Devices

by Valeri Mladenov

Technologies 2023, 11(1), 20; https://doi.org/10.3390/technologies11010020 - 28 Jan 2023

Cited by 5 | Viewed by 3771

Abstract

The design of memristor-based electronic circuits and devices gives researchers opportunities for the engineering of CMOS-memristor-based electronic integrated chips with ultra-high density and various applications. Metal-oxide memristors have good compatibility with the present CMOS integrated circuits technologies. The analysis of new electronic circuits [...] Read more.

The design of memristor-based electronic circuits and devices gives researchers opportunities for the engineering of CMOS-memristor-based electronic integrated chips with ultra-high density and various applications. Metal-oxide memristors have good compatibility with the present CMOS integrated circuits technologies. The analysis of new electronic circuits requires suitable software and fast-functioning models. The main purpose of this paper is to propose the application of several modified, simplified, and improved metal-oxide memristor models in electronic devices and provide a comparison of their behavior, basic characteristics, and properties. According to this, LTSPICE is utilized in this paper because it is a free software product with good convergence. Several memristor-based electronic circuits, such as non-volatile passive and hybrid memory crossbars, a neural network, and different reconfigurable devices–filters, an amplifier, and a generator are analyzed in the LTSPICE environment, applying several standards and modified metal-oxide memristor models. After a comparison of the operation of the considered schemes, the main advantages of the modified metal-oxide memristor models, according to their standard analogs, are expressed, including fast operation, good accuracy, respectable convergence, switching properties, and successful applicability in complex electronic circuits. Full article

(This article belongs to the Special Issue MOCAST 2022)

► Show Figures

Figure 1

16 pages, 5064 KiB

Open AccessEditor’s ChoiceArticle

Floating Interleaved Boost Converter with Zero-Ripple Input Current Using Variable Inductor

by Hector Hidalgo, Nimrod Vázquez, Rodolfo Orosco, Hector Huerta-Ávila, Sergio Pinto and Leonel Estrada

Technologies 2023, 11(1), 21; https://doi.org/10.3390/technologies11010021 - 28 Jan 2023

Cited by 5 | Viewed by 2458

Abstract

A zero-ripple input current is known to improve the lifetime of battery sets and fuel cells and to assure maximum power point tracking in PV panels. To perform current ripple elimination in a floating interleaved boost converter (FIBC), one of the typical linear [...] Read more.

A zero-ripple input current is known to improve the lifetime of battery sets and fuel cells and to assure maximum power point tracking in PV panels. To perform current ripple elimination in a floating interleaved boost converter (FIBC), one of the typical linear inductors is substituted by a variable inductor, and phases of the converter have complementary duty cycles. This variable inductor is controlled using a switched current-source converter, which adjusts the input current ripple. An equivalent model for the variable inductor is presented, including uncertainties in the component description. To achieve current stabilization, a variable inductor controller was designed using the sliding modes approach via fixed frequency. An experimental prototype is implemented and tested with an output voltage controller to compare with the conventional FIBC. The results demonstrate that the input current ripple of the proposed converter is eliminated without significantly decreasing the efficiency. Full article

(This article belongs to the Section Environmental Technology)

► Show Figures

Figure 1

19 pages, 4927 KiB

Open AccessEditor’s ChoiceArticle

Evaluation of a Remote-Controlled Drone System for Bedridden Patients Using Their Eyes Based on Clinical Experiment

by Yoshihiro Kai, Yuuki Seki, Riku Suzuki, Atsunori Kogawa, Ryuichi Tanioka, Kyoko Osaka, Yueren Zhao and Tetsuya Tanioka

Technologies 2023, 11(1), 15; https://doi.org/10.3390/technologies11010015 - 17 Jan 2023

Cited by 1 | Viewed by 3190

Abstract

With the aging of the population in Japan, the number of bedridden patients who need long-term care is increasing. The Japanese government has been promoting the creation of an environment that enables everyone, including bedridden patients, to enjoy travel, based on the principle [...] Read more.

With the aging of the population in Japan, the number of bedridden patients who need long-term care is increasing. The Japanese government has been promoting the creation of an environment that enables everyone, including bedridden patients, to enjoy travel, based on the principle of normalization. However, it is difficult for bedridden patients to enjoy the scenery of distant places and to talk with the local people because they need support from helpers to travel to distant places using travel agencies. Therefore, to enhance their quality of life (QOL), we developed a remote-controlled drone system, which involves using only the eyes. We believe that bedridden patients are able to operate the system’s drone in a distant place, to easily view the scenery of the distant place with a camera installed on the drone, and to talk with the local people. However, we have never evaluated whether actual bedridden patients can operate the drone in a distant place, to see the scenery, and to talk with the local people. In this paper, we presented clinical experimental results to verify the effectiveness of this drone system. Findings showed that, not only subjects with relatively high levels of independence in activities of daily living, but also bedridden subjects, could operate the drone at a distant place with only their eyes and communicate with others. Full article

(This article belongs to the Section Assistive Technologies)

► Show Figures

Figure 1

25 pages, 2599 KiB

Open AccessEditor’s ChoiceArticle

Estimation of Energy Consumption and Flight Time Margin for a UAV Mission Based on Fuzzy Systems

by Luis H. Manjarrez, Julio C. Ramos-Fernández, Eduardo S. Espinoza and Rogelio Lozano

Technologies 2023, 11(1), 12; https://doi.org/10.3390/technologies11010012 - 12 Jan 2023

Cited by 6 | Viewed by 2841

Abstract

An essential aspect to achieving safety with a UAV is that it operates within the limits of its capabilities, the available flight time being a key aspect when planning and executing a mission. The flight time will depend on the relationship between the [...] Read more.

An essential aspect to achieving safety with a UAV is that it operates within the limits of its capabilities, the available flight time being a key aspect when planning and executing a mission. The flight time will depend on the relationship between the available energy and the energy required by the UAV to complete the mission. This paper addresses the problem of estimating the energy required to perform a mission, for which a fuzzy Takagi–Sugeno system was implemented, whose premises were developed using fuzzy C-means to estimate the power required in the different stages of the mission. The parameters used in the fuzzy C-means algorithm were optimized using particle swarm optimization. On the other hand, an equivalent circuit model of a battery was used, for which fuzzy modeling was employed to determine the relationship between the open-circuit voltage and the state of charge of the battery, which in conjunction with an extended Kalman filter allows determining the battery charge. In addition, we developed a methodology to determine the minimum allowable battery charge level. From this, it is possible to determine the available flight time at the end of a mission defined as the flight time margin. In order to evaluate the developed methodology, a physical experiment was performed using an hexarotor UAV obtaining a maximum prediction error equivalent to the energy required to operate for 7 s, which corresponds to 2% of the total mission time. Full article

(This article belongs to the Special Issue 10th Anniversary of Technologies—Recent Advances and Perspectives)

► Show Figures

Figure 1

22 pages, 6361 KiB

Open AccessEditor’s ChoiceArticle

Investigation of Surface Layer Condition of SiAlON Ceramic Inserts and Its Influence on Tool Durability When Turning Nickel-Based Superalloy

by Sergey N. Grigoriev, Marina A. Volosova and Anna A. Okunkova

Technologies 2023, 11(1), 11; https://doi.org/10.3390/technologies11010011 - 12 Jan 2023

Cited by 3 | Viewed by 2325

Abstract

SiAlON is one of the problematic and least previously studied but prospective cutting ceramics suitable for most responsible machining tasks, such as cutting sophisticated shapes of aircraft gas turbine engine parts made of chrome–nickel alloys (Inconel 718 type) with increased mechanical and thermal [...] Read more.

SiAlON is one of the problematic and least previously studied but prospective cutting ceramics suitable for most responsible machining tasks, such as cutting sophisticated shapes of aircraft gas turbine engine parts made of chrome–nickel alloys (Inconel 718 type) with increased mechanical and thermal loads (semi-finishing). Industrially produced SiAlON cutting inserts are replete with numerous defects (stress concentrators). When external loads are applied, the wear pattern is difficult to predict. The destruction of the cutting edge, such as the tearing out of entire conglomerates, can occur at any time. The complex approach of additional diamond grinding, lapping, and polishing combined with an advanced double-layer (CrAlSi)N/DLC coating was proposed here for the first time to minimize it. The criterion of failure was chosen to be 0.4 mm. The developed tri-nitride coating sub-layer plays a role of improving the main DLC coating adhesion. The microhardness of the DLC coating was 28 ± 2 GPa, and the average coefficient of friction during high-temperature heating (up to 800 °C) was ~0.4. The average durability of the insert after additional diamond grinding, lapping, polishing, and coating was 12.5 min. That is superior to industrial cutting inserts and those subjected to (CrAlSi)N/DLC coating by 1.8 and 1.25 times, respectively. Full article

(This article belongs to the Special Issue Advanced Processing Technologies of Innovative Materials)

► Show Figures

Figure 1

17 pages, 3857 KiB

Open AccessEditor’s ChoiceArticle

An Efficient Hybrid CNN Classification Model for Tomato Crop Disease

by Maria Vasiliki Sanida, Theodora Sanida, Argyrios Sideris and Minas Dasygenis

Technologies 2023, 11(1), 10; https://doi.org/10.3390/technologies11010010 - 4 Jan 2023

Cited by 17 | Viewed by 4399

Abstract

Tomato plants are vulnerable to a broad number of diseases, each of which has the potential to cause significant damage. Diseases that affect crops substantially negatively impact the quantity and quality of agricultural products. Regarding quality crop maintenance, the importance of a timely [...] Read more.

Tomato plants are vulnerable to a broad number of diseases, each of which has the potential to cause significant damage. Diseases that affect crops substantially negatively impact the quantity and quality of agricultural products. Regarding quality crop maintenance, the importance of a timely and accurate diagnosis cannot be overstated. Deep learning (DL) strategies are now a critical research field for crop disease diagnoses. One independent system that can diagnose plant illnesses based on their outward manifestations is an example of an intelligent agriculture solution that could address these problems. This work proposes a robust hybrid convolutional neural network (CNN) diagnostic tool for various disorders that may affect tomato leaf tissue. A CNN and an inception module are the two components that make up this hybrid technique. The dataset employed for this study consists of nine distinct categories of tomato diseases and one healthy category sourced from PlantVillage. The findings are promising on the test set, with 99.17% accuracy, 99.23% recall, 99.13% precision, 99.56% AUC, and 99.17% F1-score, respectively. The proposed methodology offers a solution that boasts high performance for the diagnostics of tomato crops in the actual agricultural setting. Full article

(This article belongs to the Section Assistive Technologies)

► Show Figures

Figure 1

21 pages, 7053 KiB

Open AccessEditor’s ChoiceArticle

Electrical Discharge Machining of Alumina Using Cu-Ag and Cu Mono- and Multi-Layer Coatings and ZnO Powder-Mixed Water Medium

by Anna A. Okunkova, Marina A. Volosova, Khaled Hamdy and Khasan I. Gkhashim

Technologies 2023, 11(1), 6; https://doi.org/10.3390/technologies11010006 - 27 Dec 2022

Cited by 3 | Viewed by 2369

Abstract

The paper aims to extend the current knowledge on electrical discharge machining of insulating materials, such as cutting ceramics used to produce cutting inserts to machine nickel-based alloys in the aviation and aerospace industries. Aluminum-based ceramics such as Al₂O₃, [...] Read more.

The paper aims to extend the current knowledge on electrical discharge machining of insulating materials, such as cutting ceramics used to produce cutting inserts to machine nickel-based alloys in the aviation and aerospace industries. Aluminum-based ceramics such as Al₂O₃, AlN, and SiAlON are in the most demand in the industry but present a scientific and technical problem in obtaining sophisticated shapes. One of the existing solutions is electrical discharge machining using assisting techniques. Using assisting Cu-Ag and Cu mono- and multi-layer coatings of 40–120 µm and ZnO powder-mixed deionized water-based medium was proposed for the first time. The developed coatings were subjected to tempering and testing. It was noticed that Ag-adhesive reduced the performance when tempering had a slight effect. The unveiled relationship between the material removal rate, powder concentration, and pulse frequency showed that performance was significantly improved by adding assisting powder up to 0.0032–0.0053 mm³/s for a concentration of 14 g/L and pulse frequency of 2–7 kHz. Further increase in concentration leads to the opposite trend. The most remarkable results corresponded to the pulse duration of 1 µs. The obtained data enlarged the knowledge of texturing insulating cutting ceramics using various powder-mixed deionized water-based mediums. Full article

(This article belongs to the Special Issue Advanced Processing Technologies of Innovative Materials)

► Show Figures

Figure 1

23 pages, 5762 KiB

Open AccessEditor’s ChoiceArticle

A Conceptual Framework for Data Sensemaking in Product Development—A Case Study

by Tommy Langen, Haytham B. Ali and Kristin Falk

Technologies 2023, 11(1), 4; https://doi.org/10.3390/technologies11010004 - 22 Dec 2022

Viewed by 2902

Abstract

The industry acknowledges the value of using data and digitalization approaches to improve their systems. However, companies struggle to use data effectively in product development. This paper presents a conceptual framework for Data Sensemaking in Product Development, exemplified through a case study of [...] Read more.

The industry acknowledges the value of using data and digitalization approaches to improve their systems. However, companies struggle to use data effectively in product development. This paper presents a conceptual framework for Data Sensemaking in Product Development, exemplified through a case study of an Automated Parking System. The work is grounded in systems engineering, human centered-design, and data science theory. The resulting framework applies to practitioners and researchers in the early phase of product development. The framework combines conceptual models and data analytics, facilitating the range from human judgment and decision-making to verifications. The case study and feedback from several industrial actors suggest that the framework is valuable, usable, and feasible for more effective use of data in product development. Full article

(This article belongs to the Special Issue Human-Centered Cyber-Physical Systems)

► Show Figures

Figure 1

18 pages, 10341 KiB

Open AccessEditor’s ChoiceArticle

Design and Analysis of Guidance Function of Permanent Magnet Electrodynamic Suspension

by Yuqing Xiang, Zigang Deng, Hongfu Shi, Kaiwen Li, Ting Cao, Bin Deng, Le Liang and Jun Zheng

Technologies 2023, 11(1), 3; https://doi.org/10.3390/technologies11010003 - 21 Dec 2022

Cited by 2 | Viewed by 2177

Abstract

Inspired by the guidance principle in the electromagnetic levitation system, a new permanent magnet electrodynamic suspension (PM EDS) structure with ferromagnetic guidance track is proposed and analyzed in this paper. Considering the lack of effective guidance ability for the PM EDS system, we [...] Read more.

Inspired by the guidance principle in the electromagnetic levitation system, a new permanent magnet electrodynamic suspension (PM EDS) structure with ferromagnetic guidance track is proposed and analyzed in this paper. Considering the lack of effective guidance ability for the PM EDS system, we adopted the ferromagnetic guidance track as being mounted under the conductor plate. The guidance principle is studied and the implementation of the guidance function is also introduced, and the finite element method (FEM) is employed and its accuracy is confirmed via the PM EDS high-speed rotating experimental platform fabricated in our laboratory. The influence of longitudinal speed on the guidance force is taken into account, which shows that the guidance performance is enhanced more obviously at low speeds. Moreover, the influence of the guidance track parameters on the guidance performance is also analyzed, including the geometric parameters, section shape, installation position and material. The equivalent small-scale PM EDS system experimental prototype is carried out to validate the effectiveness of the ferromagnetic guidance. The proposed ferromagnetic guidance structure is demonstrated to improve the guidance performance of the PM EDS system effectively, which will offer a technical reference for the practical engineering application of the PM EDS system. Full article

(This article belongs to the Section Assistive Technologies)

► Show Figures

Figure 1

18 pages, 631 KiB

Open AccessEditor’s ChoiceArticle

HADD: High-Accuracy Detection of Depressed Mood

by Yu Liu, Kyoung-Don Kang and Mi Jin Doe

Technologies 2022, 10(6), 123; https://doi.org/10.3390/technologies10060123 - 29 Nov 2022

Cited by 6 | Viewed by 2184

Abstract

Depression is a serious mood disorder that is under-recognized and under-treated. Recent advances in mobile/wearable technology and ML (machine learning) have provided opportunities to detect the depressed moods of participants in their daily lives with their consent. To support high-accuracy, ubiquitous detection of [...] Read more.

Depression is a serious mood disorder that is under-recognized and under-treated. Recent advances in mobile/wearable technology and ML (machine learning) have provided opportunities to detect the depressed moods of participants in their daily lives with their consent. To support high-accuracy, ubiquitous detection of depressed mood, we propose HADD, which provides new capabilities. First, HADD supports multimodal data analysis in order to enhance the accuracy of ubiquitous depressed mood detection by analyzing not only objective sensor data, but also subjective EMA (ecological momentary assessment) data collected by using mobile devices. In addition, HADD improves upon the accuracy of state-of-the-art ML algorithms for depressed mood detection via effective feature selection, data augmentation, and two-stage outlier detection. In our evaluation, HADD significantly enhanced the accuracy of a comprehensive set of ML models for depressed mood detection. Full article

(This article belongs to the Section Assistive Technologies)

► Show Figures

Figure 1

20 pages, 2143 KiB

Open AccessEditor’s ChoiceArticle

Simulation Analysis of Signal Conditioning Circuits for Plants’ Electrical Signals

by Mirella Carneiro, Victor Oliveira, Fernanda Oliveira, Marco Teixeira and Milena Pinto

Technologies 2022, 10(6), 121; https://doi.org/10.3390/technologies10060121 - 25 Nov 2022

Cited by 1 | Viewed by 2206

Abstract

Electrical signals are generated and transmitted through plants in response to stimuli caused by external environment factors, such as touching, luminosity, and leaf burning. By analyzing a specific plant’s electrical responses, it is possible to interpret the impact of external aspects in the [...] Read more.

Electrical signals are generated and transmitted through plants in response to stimuli caused by external environment factors, such as touching, luminosity, and leaf burning. By analyzing a specific plant’s electrical responses, it is possible to interpret the impact of external aspects in the plasma membrane potential and, thus, determine the cause of the electrical signal. Moreover, these signals permit the whole plant structure to be informed almost instantaneously. This work presents a brief discussion of plants electrophysiology theory and low-cost signal conditioning circuits, which are necessary for the acquisition of plants’ electrical signals. Two signal conditioning circuits, which must be chosen depending on the signal to be measured, are explained in detail and electrical simulation results, performed in OrCAD Capture Software are presented. Furthermore, Monte Carlo simulations were performed to evaluate the impact of components variations on the accuracy and efficiency of the signal conditioning circuits. Those simulations showed that, even after possible component variations, the filters’ cut-off frequencies had at most 4% variation from the mean. Full article

(This article belongs to the Special Issue 10th Anniversary of Technologies—Recent Advances and Perspectives)

► Show Figures

Figure 1

18 pages, 2498 KiB

Open AccessEditor’s ChoiceArticle

Infrared Thermal Imaging and Artificial Neural Networks to Screen for Wrist Fractures in Pediatrics

by Olamilekan Shobayo, Reza Saatchi and Shammi Ramlakhan

Technologies 2022, 10(6), 119; https://doi.org/10.3390/technologies10060119 - 22 Nov 2022

Cited by 4 | Viewed by 2144

Abstract

Paediatric wrist fractures are commonly seen injuries at emergency departments. Around 50% of the X-rays taken to identify these injuries indicate no fracture. The aim of this study was to develop a model using infrared thermal imaging (IRTI) data and multilayer perceptron (MLP) [...] Read more.

Paediatric wrist fractures are commonly seen injuries at emergency departments. Around 50% of the X-rays taken to identify these injuries indicate no fracture. The aim of this study was to develop a model using infrared thermal imaging (IRTI) data and multilayer perceptron (MLP) neural networks as a screening tool to assist clinicians in deciding which patients require X-ray imaging to diagnose a fracture. Forty participants with wrist injury (19 with a fracture, 21 without, X-ray confirmed), mean age 10.50 years, were included. IRTI of both wrists was performed with the contralateral as reference. The injured wrist region of interest (ROI) was segmented and represented by the means of cells of 10 × 10 pixels. The fifty largest means were selected, the mean temperature of the contralateral ROI was subtracted, and they were expressed by their standard deviation, kurtosis, and interquartile range for MLP processing. Training and test files were created, consisting of randomly split 2/3 and 1/3 of the participants, respectively. To avoid bias of participant inclusion in the two files, the experiments were repeated 100 times, and the MLP outputs were averaged. The model’s sensitivity and specificity were 84.2% and 71.4%, respectively. Further work involves a larger sample size, adults, and other bone fractures. Full article

(This article belongs to the Special Issue Medical Imaging & Image Processing III)

► Show Figures

Figure 1

15 pages, 9713 KiB

Open AccessEditor’s ChoiceArticle

Friction Stir Welding of Ti-6Al-4V Using a Liquid-Cooled Nickel Superalloy Tool

by Sergei Tarasov, Alihan Amirov, Andrey Chumaevskiy, Nikolay Savchenko, Valery E. Rubtsov, Aleksey Ivanov, Evgeniy Moskvichev and Evgeny Kolubaev

Technologies 2022, 10(6), 118; https://doi.org/10.3390/technologies10060118 - 18 Nov 2022

Cited by 6 | Viewed by 2246

Abstract

Friction stir welding (FSW) of titanium alloy was carried out using liquid cooling of the FSW tool made of heat-resistant nickel superalloy. Cooling of the nickel superalloy tool was performed by means of circulating water inside the tool. The FSW joints were characterized [...] Read more.

Friction stir welding (FSW) of titanium alloy was carried out using liquid cooling of the FSW tool made of heat-resistant nickel superalloy. Cooling of the nickel superalloy tool was performed by means of circulating water inside the tool. The FSW joints were characterized by microstructures and mechanical strength. The mechanical strength of the joints was higher than that of the base metal. Full article

(This article belongs to the Special Issue 10th Anniversary of Technologies—Recent Advances and Perspectives)

► Show Figures

Figure 1

26 pages, 2625 KiB

Open AccessEditor’s ChoiceArticle

Towards a Modern Learning Organization: Human-Centered Digitalization of Lessons Learned Management for Complex Systems Development Projects

by YangYang Zhao and Henrik Jensen

Technologies 2022, 10(6), 117; https://doi.org/10.3390/technologies10060117 - 16 Nov 2022

Viewed by 2702

Abstract

The importance of learning from experience is incontrovertible; however, little is studied regarding the digitalization of in- and inter-project lessons learned in modern organizational practices. As a critical part of organizational knowledge, lessons learned are known to help organizations adapt to the ever-changing [...] Read more.

The importance of learning from experience is incontrovertible; however, little is studied regarding the digitalization of in- and inter-project lessons learned in modern organizational practices. As a critical part of organizational knowledge, lessons learned are known to help organizations adapt to the ever-changing world via the complex systems development projects they use to capitalize on and to develop their competitive advantage. In this paper, we introduce the concept of human-centered digitalization for this unique type of organizational knowledge and explain why this approach to managing lessons learned for complex systems development projects is necessary. Drawing from design thinking and systems thinking theories, we further outline the design principles for guiding actions and provide a case study of their implementation in automated systems projects for maritime industries. Full article

(This article belongs to the Special Issue Human-Centered Cyber-Physical Systems)

► Show Figures

Figure 1

20 pages, 8521 KiB

Open AccessEditor’s ChoiceArticle

Electrical Discharge Machining of Al₂O₃ Using Copper Tape and TiO₂ Powder-Mixed Water Medium

by Sergey N. Grigoriev, Anna A. Okunkova, Marina A. Volosova, Khaled Hamdy and Alexander S. Metel

Technologies 2022, 10(6), 116; https://doi.org/10.3390/technologies10060116 - 11 Nov 2022

Cited by 6 | Viewed by 3052

Abstract

Aluminum-based ceramics are used in industry to produce cutting tools that resist extreme mechanical and thermal load conditions during the machining of Ni-based and high-entropy alloys. There is wide field of application also in the aerospace industry. Microtexturing of cutting ceramics reduces contact [...] Read more.

Aluminum-based ceramics are used in industry to produce cutting tools that resist extreme mechanical and thermal load conditions during the machining of Ni-based and high-entropy alloys. There is wide field of application also in the aerospace industry. Microtexturing of cutting ceramics reduces contact loads and wear of cutting tools. However, most of the published works are related to the electrical discharge machining of alumina in hydrocarbons, which creates risks for the personnel and equipment due to the formation of chemically unstable dielectric carbides (methanide Al₃C₄ and acetylenide Al₂(C₂)₃). An alternative approach for wire electrical discharge machining Al₂O₃ in the water-based dielectric medium using copper tape of 40 µm thickness and TiO₂ powder suspension was proposed for the first time. The performance was evaluated by calculating the material removal rate for various combinations of pulse frequency and TiO₂ powder concentration. The obtained kerf of 54.16 ± 0.05 µm in depth demonstrated an increasing efficiency of more than 1.5 times with the closest analogs for the workpiece thickness up to 5 mm in height. The comparison of the performance (0.0083–0.0084 mm³/s) with the closest analogs shows that the results may correlate with the electrical properties of the assisting materials. Full article

(This article belongs to the Section Innovations in Materials Processing)

► Show Figures

Figure 1

21 pages, 15427 KiB

Open AccessEditor’s ChoiceArticle

Modelling the Trust Value for Human Agents Based on Real-Time Human States in Human-Autonomous Teaming Systems

by Chin-Teng Lin, Hsiu-Yu Fan, Yu-Cheng Chang, Liang Ou, Jia Liu, Yu-Kai Wang and Tzyy-Ping Jung

Technologies 2022, 10(6), 115; https://doi.org/10.3390/technologies10060115 - 8 Nov 2022

Cited by 1 | Viewed by 2641

Abstract

The modelling of trust values on agents is broadly considered fundamental for decision-making in human-autonomous teaming (HAT) systems. Compared to the evaluation of trust values for robotic agents, estimating human trust is more challenging due to trust miscalibration issues, including undertrust and overtrust [...] Read more.

The modelling of trust values on agents is broadly considered fundamental for decision-making in human-autonomous teaming (HAT) systems. Compared to the evaluation of trust values for robotic agents, estimating human trust is more challenging due to trust miscalibration issues, including undertrust and overtrust problems. From a subjective perception, human trust could be altered along with dynamic human cognitive states, which makes trust values hard to calibrate properly. Thus, in an attempt to capture the dynamics of human trust, the present study evaluated the dynamic nature of trust for human agents through real-time multievidence measures, including human states of attention, stress and perception abilities. The proposed multievidence human trust model applied an adaptive fusion method based on fuzzy reinforcement learning to fuse multievidence from eye trackers, heart rate monitors and human awareness. In addition, fuzzy reinforcement learning was applied to generate rewards via a fuzzy logic inference process that has tolerance for uncertainty in human physiological signals. The results of robot simulation suggest that the proposed trust model can generate reliable human trust values based on real-time cognitive states in the process of ongoing tasks. Moreover, the human-autonomous team with the proposed trust model improved the system efficiency by over

50 %

compared to the team with only autonomous agents. These results may demonstrate that the proposed model could provide insight into the real-time adaptation of HAT systems based on human states and, thus, might help develop new ways to enhance future HAT systems better. Full article

(This article belongs to the Special Issue 10th Anniversary of Technologies—Recent Advances and Perspectives)

► Show Figures

Figure 1

24 pages, 10290 KiB

Open AccessEditor’s ChoiceArticle

Modular Multi-Input DC/DC Converter for EV Fast Charging

by Hossam A. Gabbar and Abdalrahman Elshora

Technologies 2022, 10(6), 113; https://doi.org/10.3390/technologies10060113 - 7 Nov 2022

Cited by 1 | Viewed by 2758

Abstract

In this paper, a modular multi-input, single output DC/DC converter is proposed to enhance the energy management of a fast-charging station for electric vehicles (EVs). The proposed bidirectional converter can work in different modes of operation with fewer components and a modular design [...] Read more.

In this paper, a modular multi-input, single output DC/DC converter is proposed to enhance the energy management of a fast-charging station for electric vehicles (EVs). The proposed bidirectional converter can work in different modes of operation with fewer components and a modular design to extend the input power sources and increase the charging power rate. The converter has several merits compared to the conventional converters, such as centralizing the control, reducing power devices, and reducing power conversion stages. By using MATLAB/Simulink, the converter was tested in many operation modes and was used to charge a Nissan Leaf EV’s battery (350 V, 60 Ah) from hybrid sources simultaneously and individually in power up to (17 kW). In addition, it was tested on a hardware scale at a low power rate (100 W) for the validation of the simulation work and the topology concept. In addition, its different losses and efficiency were calculated during the different operation modes. Full article

► Show Figures

Figure 1

34 pages, 11931 KiB

Open AccessEditor’s ChoiceArticle

Open-Source Photovoltaic—Electrical Vehicle Carport Designs

by Nicholas Vandewetering, Koami Soulemane Hayibo and Joshua M. Pearce

Technologies 2022, 10(6), 114; https://doi.org/10.3390/technologies10060114 - 7 Nov 2022

Cited by 8 | Viewed by 6987

Abstract

Solar powering the increasing fleet of electrical vehicles (EV) demands more surface area than may be available for photovoltaic (PV)-powered buildings. Parking lot solar canopies can provide the needed area to charge EVs but are substantially costlier than roof- or ground-mounted PV systems. [...] Read more.

Solar powering the increasing fleet of electrical vehicles (EV) demands more surface area than may be available for photovoltaic (PV)-powered buildings. Parking lot solar canopies can provide the needed area to charge EVs but are substantially costlier than roof- or ground-mounted PV systems. To provide a low-cost PV parking lot canopy to supply EV charging, in this study, we provide a full mechanical and economic analysis of three novel PV canopy systems: (1) an exclusively wood, single-parking-spot spanning system, (2) a wood and aluminum double-parking-spot spanning system, and (3) a wood and aluminum cantilevered system for curbside parking. All three systems can be scaled to any amount of EV parking spots. The complete designs and bill of materials (BOM) of the canopies are provided, along with basic instructions, and are released with an open-source license that will enable anyone to fabricate them. Analysis results indicate that single-span systems provide cost savings of 82–85%, double-span systems save 43–50%, and cantilevered systems save 31–40%. In the first year of operation, PV canopies can provide 157% of the energy needed to charge the least efficient EV currently on the market if it is driven the average driving distance in London, ON, Canada. Full article

(This article belongs to the Topic Emerging Technologies for Grid-Interactive Efficient Buildings and Communities)

► Show Figures

Figure 1

8 pages, 362 KiB

Open AccessEditor’s ChoiceCommunication

Variance-Based Sensitivity Analysis of Fitting Parameters to Impact on Cycling Durability of Polymer Electrolyte Fuel Cells

by Victor A. Kovtunenko

Technologies 2022, 10(6), 111; https://doi.org/10.3390/technologies10060111 - 28 Oct 2022

Cited by 3 | Viewed by 1671

Abstract

Degradation of a catalyst layer in polymer electrolyte membrane fuel cells is considered, which is caused by electrochemical reactions of the platinum ion dissolution and oxide coverage. An accelerated stress test is applied, where the electric potential cycling is given by a non-symmetric [...] Read more.

Degradation of a catalyst layer in polymer electrolyte membrane fuel cells is considered, which is caused by electrochemical reactions of the platinum ion dissolution and oxide coverage. An accelerated stress test is applied, where the electric potential cycling is given by a non-symmetric square profile. Computer simulations of the underlying one-dimensional Holby–Morgan model predict durability of the fuel cell operating. A sensitivity analysis based on the variance quantifies how loss of the platinum mass subjected to the degradation is impacted by the variation of fitting parameters in the model. Full article

(This article belongs to the Section Environmental Technology)

► Show Figures

Figure 1

29 pages, 4740 KiB

Open AccessEditor’s ChoiceReview

Thermal Inkjet Printing: Prospects and Applications in the Development of Medicine

by Md Jasim Uddin, Jasmin Hassan and Dennis Douroumis

Technologies 2022, 10(5), 108; https://doi.org/10.3390/technologies10050108 - 21 Oct 2022

Cited by 19 | Viewed by 13174

Abstract

Over the last 10 years, inkjet printing technologies have advanced significantly and found several applications in the pharmaceutical and biomedical sector. Thermal inkjet printing is one of the most widely used techniques due to its versatility in the development of bioinks for cell [...] Read more.

Over the last 10 years, inkjet printing technologies have advanced significantly and found several applications in the pharmaceutical and biomedical sector. Thermal inkjet printing is one of the most widely used techniques due to its versatility in the development of bioinks for cell printing or biosensors and the potential to fabricate personalized medications of various forms such as films and tablets. In this review, we provide a comprehensive discussion of the principles of inkjet printing technologies highlighting their advantages and limitations. Furthermore, the review covers a wide range of case studies and applications for precision medicine. Full article

(This article belongs to the Special Issue 10th Anniversary of Technologies—Recent Advances and Perspectives)

► Show Figures

Figure 1

11 pages, 2490 KiB

Open AccessEditor’s ChoiceReview

Exploration of Educational Possibilities by Four Metaverse Types in Physical Education

by Ji-Eun Yu

Technologies 2022, 10(5), 104; https://doi.org/10.3390/technologies10050104 - 23 Sep 2022

Cited by 57 | Viewed by 9934

Abstract

The metaverse has been evolving the internet-based education represented by e-learning. Metaverse technology is currently being developed as a platform centered on content-based information industries. It can be classified into four categories: augmented reality, lifelogging, mirror worlds, and virtual worlds. Although current research [...] Read more.

The metaverse has been evolving the internet-based education represented by e-learning. Metaverse technology is currently being developed as a platform centered on content-based information industries. It can be classified into four categories: augmented reality, lifelogging, mirror worlds, and virtual worlds. Although current research finds that the potential of the metaverse is not small in the education world, and metaverse technology is already being used in the sports world, concrete applications have not been investigated. The main aims of this study, which started with this purpose, can be summarized as follows. The metaverse environment is still in its rudimentary stage, and its use related to physical education subjects is only at the game level. In the future, the utilization of the metaverse by physical education subjects will be possible in universities only when more specialized technology is grafted into various sports. Ultimately, this study contributes to expanding the scope and depth of follow-up research by offering basic data showing the direction of metaverse-based physical education. Full article

(This article belongs to the Special Issue Human-Centered Cyber-Physical Systems)

► Show Figures

Figure 1

13 pages, 27820 KiB

Open AccessEditor’s ChoiceArticle

Design and Implementation of an Anthropomorphic Robotic Arm Prosthesis

by Valentina A. Yurova, Gleb Velikoborets and Andrei Vladyko

Technologies 2022, 10(5), 103; https://doi.org/10.3390/technologies10050103 - 21 Sep 2022

Cited by 10 | Viewed by 6109

Abstract

The development and manufacture of prosthetic limbs is one of the important tendencies of the development of medical techniques. Taking into account the development of modern electronic technology and automated systems and its mobility and compactness, the actual task is to create a [...] Read more.

The development and manufacture of prosthetic limbs is one of the important tendencies of the development of medical techniques. Taking into account the development of modern electronic technology and automated systems and its mobility and compactness, the actual task is to create a prosthesis that will be close to a fully functioning human limb in its anthropomorphic properties and will be capable of reproducing its basic actions with a high accuracy. The paper analyzes the main directions in the development of a control system for electronic limb prostheses. The description and results of the practical implementation of a prototype of an anthropomorphic prosthetic arm and its control system are presented in the paper. We developed an anthropomorphic multi-finger artificial hand for utilization in robotic research and teaching applications. The designed robotic hand is a low-cost alternative to other known 3D printed robotic hands and has 21 degrees of freedom—4 degrees of freedom for each finger, 3 degrees for the thumb and 2 degrees responsible for the position of the robotic hand in space. The open-source mechanical design of the presented robotic arm has mass-dimensional and motor parameters close to the human hand, with the possibility of autonomous battery operation, the ability to connect different control systems, such as from a computer, an electroencephalograph, a touch glove. Full article

(This article belongs to the Special Issue 10th Anniversary of Technologies—Recent Advances and Perspectives)

► Show Figures

Figure 1

9 pages, 1928 KiB

Open AccessEditor’s ChoiceArticle

A Machine-Learning-Based Approach to Critical Geometrical Feature Identification and Segmentation in Additive Manufacturing

by Alexandre Staub, Lucas Brunner, Adriaan B. Spierings and Konrad Wegener

Technologies 2022, 10(5), 102; https://doi.org/10.3390/technologies10050102 - 16 Sep 2022

Cited by 2 | Viewed by 2275

Abstract

Additive manufacturing (AM) processes offer a good opportunity to manufacture three- dimensional objects using various materials. However, many of the processes, notably laser Powder bed fusion, face limitations in manufacturing specific geometrical features due to their physical constraints, such as the thermal conductivity [...] Read more.

Additive manufacturing (AM) processes offer a good opportunity to manufacture three- dimensional objects using various materials. However, many of the processes, notably laser Powder bed fusion, face limitations in manufacturing specific geometrical features due to their physical constraints, such as the thermal conductivity of the surrounding medium, the internal stresses, and the warpage or weight of the part being manufactured. This work investigates the opportunity to use machine learning algorithms in order to identify hard-to-manufacture geometrical features. The segmentation of these features from the main body of the part permits the application of different manufacturing strategies to improve the overall manufacturability. After selecting features that are particularly problematic during laser powder bed fusion using stainless steel, an algorithm is trained using simple geometries, which permits the identification of hard-to-manufacture features on new parts with a success rate of 88%, showing the potential of this approach. Full article

(This article belongs to the Special Issue Advanced Processing Technologies of Innovative Materials)

► Show Figures

Figure 1

14 pages, 5549 KiB

Open AccessEditor’s ChoiceArticle

Solar Energy Management Using a V-Groove: An Approach Based on a Multiple Optical Path Algorithm

by Fadel Kawtharani, Bruno Serio, Geraldine Guida, Patrice Twardowski and Mohammad Hammoud

Technologies 2022, 10(5), 101; https://doi.org/10.3390/technologies10050101 - 12 Sep 2022

Viewed by 1925

Abstract

Angular and spectral separations of thermal radiation have become a key challenge in solar concentration or thermal management of sources radiating at extremely high or low temperatures. Reflections obtained from electromagnetic theory in an open cavity geometry increase the emission and absorption compared [...] Read more.

Angular and spectral separations of thermal radiation have become a key challenge in solar concentration or thermal management of sources radiating at extremely high or low temperatures. Reflections obtained from electromagnetic theory in an open cavity geometry increase the emission and absorption compared to a flat surface due to the cavity effect. In this paper, in order to obtain the directional emission of geometric surfaces (V-Grooves) using ray tracing and studying the propagation of light, a new algorithm is developed. The numerical simulations take into account the materials properties of both facets of the V-shape, thus simulating an original asymmetric and a multilayer V-shape and providing a very interesting directive thermal emission behavior. We evaluated the emission behavior from the reflection and emission coefficients of different rays at different angles for different parameters (materials properties, wavelength, and geometry). The simulations of a V-groove showed that due to the different reflections occurring inside an aluminum V-cavity with an aperture angle of 28°, the emissivity was well enhanced by 86% in the normal direction compared to a flat surface made of the same material. Moreover, using the original asymmetric opposite-sided materials (Al and Si) in a V- groove, it was possible to separate and control the emission by focusing the radiation or directing different spectral bands in different directions. Full article

► Show Figures

Figure 1

30 pages, 8357 KiB

Open AccessEditor’s ChoiceArticle

Digitization of Manufacturing Processes: From Sensing to Twining

by Panagiotis Stavropoulos

Technologies 2022, 10(5), 98; https://doi.org/10.3390/technologies10050098 - 30 Aug 2022

Cited by 16 | Viewed by 4071

Abstract

Zero-defect manufacturing and flexibility in production lines is driven from accurate Digital Twins (DT) which monitor, understand, and predict the behavior of a manufacturing process under different conditions while also adapting to them by deciding the right course of action in time intervals [...] Read more.

Zero-defect manufacturing and flexibility in production lines is driven from accurate Digital Twins (DT) which monitor, understand, and predict the behavior of a manufacturing process under different conditions while also adapting to them by deciding the right course of action in time intervals relevant to the captured phenomenon. During the exploration of the alternative approaches for the development of process twins, significant efforts should be made for the selection of acquisition devices and signal-processing techniques to extract meaningful information from the studied process. As such, in Industry 4.0 era, machine tools are equipped with embedded sensors that give feedback related to the process efficiency and machine health, while additional sensors are installed to capture process-related phenomena, feeding simulation tools and decision-making algorithms. Although the maturity level of some process mechanisms facilitates the representation of the physical world with the aid of physics-based models, data-driven models are proposed for complex phenomena and non-mature processes. This paper introduces the components of Digital Twin and gives emphasis on the steps that are required to transform obtained data into meaningful information that will be used in a Digital Twin. The introduced steps are identified in a case study from the milling process. Full article

(This article belongs to the Special Issue Advances and Innovations in Manufacturing Technologies)

► Show Figures

Figure 1

21 pages, 1475 KiB

Open AccessEditor’s ChoiceReview

Selected Techniques for Cutting SO_x Emissions in Maritime Industry

by Christos Papadopoulos, Marios Kourtelesis, Anastasia Maria Moschovi, Konstantinos Miltiadis Sakkas and Iakovos Yakoumis

Technologies 2022, 10(5), 99; https://doi.org/10.3390/technologies10050099 - 30 Aug 2022

Cited by 8 | Viewed by 5140

Abstract

Burning fuels with high sulfur content leads to SO_x emissions, especially SO₂, which leads to various environmental and health problems. The maritime sector is responsible for 13% of the global anthropogenic emissions of SO₂. Thus, the International Maritime [...] Read more.

Burning fuels with high sulfur content leads to SO_x emissions, especially SO₂, which leads to various environmental and health problems. The maritime sector is responsible for 13% of the global anthropogenic emissions of SO₂. Thus, the International Maritime Organization (IMO) has issued a protocol, known as MARPOL Annex VI, which aims to further limit SO₂ emissions derived from ships along with NO_x, particulate matter and volatile organic compound emissions. This has led ship owners and operators to choose between more expensive fuels with low sulfur content or to apply a DeSO_x solution, which still allows them to use the cheapest heavy fuel oil. The current work reviews the state-of-the-art DeSO_x solutions both for the maritime and land-based sector. Next, it proposes an alternative cheaper and environmentally friendly DeSO_x solution based on the selective reduction of SO₂ to elemental sulfur by utilizing a catalytic converter based on metal oxides, similar to the ones used in the automotive industry. Finally, it reviews the most promising metal oxide catalysts reported in the literature for the selective reduction of SO₂ towards elemental sulfur. Full article

(This article belongs to the Topic Advances in the Sustainability Assessment of Building and Infrastructure Projects)

► Show Figures

Figure 1

19 pages, 6708 KiB

Open AccessEditor’s ChoiceArticle

An Automatic, Contactless, High-Precision, High-Speed Measurement System to Provide In-Line, As-Molded Three-Dimensional Measurements of a Curved-Shape Injection-Molded Part

by Saeid Saeidi Aminabadi, Atae Jafari-Tabrizi, Dieter Paul Gruber, Gerald Berger-Weber and Walter Friesenbichler

Technologies 2022, 10(4), 95; https://doi.org/10.3390/technologies10040095 - 17 Aug 2022

Cited by 2 | Viewed by 2653

Abstract

In the manufacturing of injection-molded plastic parts, it is essential to perform a non-destructive (and, in some applications, contactless) three-dimensional measurement and surface inspection of the injection-molded part to monitor the part quality. The measurement method depends strongly on the shape and the [...] Read more.

In the manufacturing of injection-molded plastic parts, it is essential to perform a non-destructive (and, in some applications, contactless) three-dimensional measurement and surface inspection of the injection-molded part to monitor the part quality. The measurement method depends strongly on the shape and the optical properties of the part. In this study, a high-precision (±5 µm) and high-speed system (total of 24 s for a complete part dimensional measurement) was developed to measure the dimensions of a piano-black injection-molded part. This measurement should be done in real time and close to the part’s production time to evaluate the quality of the produced parts for future online, closed-loop, and predictive quality control. Therefore, a novel contactless, three-dimensional measurement system using a multicolor confocal sensor was designed and manufactured, taking into account the nominal curved shape and the glossy black surface properties of the part. This system includes one linear and one cylindrical moving axis, as well as one confocal optical sensor for radial R-direction measurements. A 6 DOF (degrees of freedom) robot handles the part between the injection molding machine and the measurement system. An IPC coordinates the communications and system movements over the OPC UA communication network protocol. For validation, several repeatability tests were performed at various speeds and directions. The results were compared using signal similarity methods, such as MSE, SSID, and RMS difference. The repeatability of the system in all directions was found to be in the range of ±5 µm for the desired speed range (less than 60 mm/s–60 degrees/s). However, the error increases up to ±10 µm due to the fixture and the suction force effect. Full article

(This article belongs to the Special Issue 10th Anniversary of Technologies—Recent Advances and Perspectives)

► Show Figures

Figure 1

29 pages, 10117 KiB

Open AccessEditor’s ChoiceReview

Multimodal Semantic Segmentation in Autonomous Driving: A Review of Current Approaches and Future Perspectives

by Giulia Rizzoli, Francesco Barbato and Pietro Zanuttigh

Technologies 2022, 10(4), 90; https://doi.org/10.3390/technologies10040090 - 25 Jul 2022

Cited by 24 | Viewed by 7918

Abstract

The perception of the surrounding environment is a key requirement for autonomous driving systems, yet the computation of an accurate semantic representation of the scene starting from RGB information alone is very challenging. In particular, the lack of geometric information and the strong [...] Read more.

The perception of the surrounding environment is a key requirement for autonomous driving systems, yet the computation of an accurate semantic representation of the scene starting from RGB information alone is very challenging. In particular, the lack of geometric information and the strong dependence on weather and illumination conditions introduce critical challenges for approaches tackling this task. For this reason, most autonomous cars exploit a variety of sensors, including color, depth or thermal cameras, LiDARs, and RADARs. How to efficiently combine all these sources of information to compute an accurate semantic description of the scene is still an unsolved task, leading to an active research field. In this survey, we start by presenting the most commonly employed acquisition setups and datasets. Then we review several different deep learning architectures for multimodal semantic segmentation. We will discuss the various techniques to combine color, depth, LiDAR, and other modalities of data at different stages of the learning architectures, and we will show how smart fusion strategies allow us to improve performances with respect to the exploitation of a single source of information. Full article

(This article belongs to the Special Issue 10th Anniversary of Technologies—Recent Advances and Perspectives)

► Show Figures

Figure 1

18 pages, 4518 KiB

Open AccessEditor’s ChoiceArticle

Efficient Supervised Machine Learning Network for Non-Intrusive Load Monitoring

by Muhammad Usman Hadi, Nik Hazmi Nik Suhaimi and Abdul Basit

Technologies 2022, 10(4), 85; https://doi.org/10.3390/technologies10040085 - 16 Jul 2022

Cited by 6 | Viewed by 2929

Abstract

From a single meter that measures the entire home’s electrical demand, energy disaggregation calculates appliance-by-appliance electricity consumption. Non-intrusive load monitoring (NILM), also known as energy disaggregation, tries to decompose aggregated energy consumption data and estimate each appliance’s contribution. Recently, methodologies based on Artificial [...] Read more.

From a single meter that measures the entire home’s electrical demand, energy disaggregation calculates appliance-by-appliance electricity consumption. Non-intrusive load monitoring (NILM), also known as energy disaggregation, tries to decompose aggregated energy consumption data and estimate each appliance’s contribution. Recently, methodologies based on Artificial Intelligence (AI) have been proposed commonly used in these models, which can be expensive to run on a server or prohibitive when the target device has limited capabilities. AI-based models are typically computationally expensive and require a lot of storage. It is not easy to reduce the computing cost and size of a neural network without sacrificing performance. This study proposed an efficient non-parametric supervised machine learning network (ENSML) architecture with a smaller size, and a quick inference time without sacrificing performance. The proposed architecture can maximise energy disaggregation performance and predict new observations based on past ones. The results showed that employing the ENSML model considerably increased the accuracy of energy prediction in 99 percent of cases. Full article

(This article belongs to the Special Issue 10th Anniversary of Technologies—Recent Advances and Perspectives)

► Show Figures

Figure 1

23 pages, 4284 KiB

Open AccessEditor’s ChoiceArticle

Demonstration of Resilient Microgrid with Real-Time Co-Simulation and Programmable Loads

by Hossam A. Gabbar, Yasser Elsayed, Manir Isham, Abdalrahman Elshora, Abu Bakar Siddique and Otavio Lopes Alves Esteves

Technologies 2022, 10(4), 83; https://doi.org/10.3390/technologies10040083 - 12 Jul 2022

Cited by 2 | Viewed by 3243

Abstract

In recent years, the foment for sustainable and reliable micro energy grid (MEG) systems has increased significantly, aiming mainly to reduce the dependency on fossil fuels, provide low-cost clean energy, lighten the burden, and increase the stability and reliability of the regional electrical [...] Read more.

In recent years, the foment for sustainable and reliable micro energy grid (MEG) systems has increased significantly, aiming mainly to reduce the dependency on fossil fuels, provide low-cost clean energy, lighten the burden, and increase the stability and reliability of the regional electrical grid by having interconnected and centralized clean energy sources, and ensure energy resilience for the population. A resilient energy system typically consists of a system able to control the energy flow effectively by backing up the intermittent output of renewable sources, reducing the effects of the peak demand on the grid side, considering the impact on dispatch and reliability, and providing resilient features to ensure minimum operation interruptions. This paper aims to demonstrate a real-time simulation of a microgrid capable of predicting and ensuring energy lines run correctly to prevent or shorten outages on the grid when it is subject to different disturbances by using energy management with a fail-safe operation and redundant control. In addition, it presents optimized energy solutions to enhance the situational awareness of energy grid operators based on a graphical and interactive user interface. To expand the MEG’s capability, the setup integrates real implemented hardware components with the emulated components based on real-time simulation using OPAL-RT OP4510. Most hardware components are implemented in the lab to be modular, expandable, and flexible for various test scenarios, including fault imitation. They include but are not limited to the power converter, inverter, battery charger controller, relay drivers, programmable AC and DC loads, PLC, and microcontroller-based controller. In addition, the real-time simulation offers a great variety of power sources and energy storage such as wind turbine emulators and flywheels in addition to the physical sources such as solar panels, supercapacitors, and battery packs. Full article

(This article belongs to the Special Issue 10th Anniversary of Technologies—Recent Advances and Perspectives)

► Show Figures

Figure 1

14 pages, 1826 KiB

Open AccessEditor’s ChoiceArticle

Distribution Path Optimization by an Improved Genetic Algorithm Combined with a Divide-and-Conquer Strategy

by Jiaqi Li, Yun Wang and Ke-Lin Du

Technologies 2022, 10(4), 81; https://doi.org/10.3390/technologies10040081 - 5 Jul 2022

Cited by 2 | Viewed by 2690

Abstract

The multivehicle routing problem (MVRP) is a variation of the classical vehicle routing problem (VRP). The MVRP is to find a set of routes by multiple vehicles that serve multiple customers at a minimal total cost while the travelling-time delay due to traffic [...] Read more.

The multivehicle routing problem (MVRP) is a variation of the classical vehicle routing problem (VRP). The MVRP is to find a set of routes by multiple vehicles that serve multiple customers at a minimal total cost while the travelling-time delay due to traffic congestion is tolerated. It is an NP problem and is conventionally solved by metaheuristics such as evolutionary algorithms. For the MVRP in a distribution network, we propose an optimal distribution path optimization method that is composed of a distribution sequence search stage and a distribution path search stage that exploits a divide-and-conquer strategy, inspired by the idea of dynamic programming. Several optimization objectives subject to constraints are defined. The search for the optimal solution of the number of distribution vehicles, distribution sequence, and path is implemented by using an improved genetic algorithm (GA), which is characterized by an operation for preprocessing infeasible solutions, an elitist’s strategy, a sequence-related two-point crossover operator, and a reversion mutation operator. The improved GA outperforms the simple GA in terms of total cost, route topology, and route feasibility. The proposed method can help to reduce costs and increase efficiency for logistics and transportation enterprises and can also be used for flow-shop scheduling by manufacturing enterprises. Full article

(This article belongs to the Special Issue 10th Anniversary of Technologies—Recent Advances and Perspectives)

► Show Figures

Figure 1

22 pages, 66210 KiB

Open AccessEditor’s ChoiceArticle

Evaluation of Machine Learning Algorithms for Classification of EEG Signals

by Francisco Javier Ramírez-Arias, Enrique Efren García-Guerrero, Esteban Tlelo-Cuautle, Juan Miguel Colores-Vargas, Eloisa García-Canseco, Oscar Roberto López-Bonilla, Gilberto Manuel Galindo-Aldana and Everardo Inzunza-González

Technologies 2022, 10(4), 79; https://doi.org/10.3390/technologies10040079 - 30 Jun 2022

Cited by 19 | Viewed by 8608

Abstract

In brain–computer interfaces (BCIs), it is crucial to process brain signals to improve the accuracy of the classification of motor movements. Machine learning (ML) algorithms such as artificial neural networks (ANNs), linear discriminant analysis (LDA), decision tree (D.T.), K-nearest neighbor (KNN), naive Bayes [...] Read more.

In brain–computer interfaces (BCIs), it is crucial to process brain signals to improve the accuracy of the classification of motor movements. Machine learning (ML) algorithms such as artificial neural networks (ANNs), linear discriminant analysis (LDA), decision tree (D.T.), K-nearest neighbor (KNN), naive Bayes (N.B.), and support vector machine (SVM) have made significant progress in classification issues. This paper aims to present a signal processing analysis of electroencephalographic (EEG) signals among different feature extraction techniques to train selected classification algorithms to classify signals related to motor movements. The motor movements considered are related to the left hand, right hand, both fists, feet, and relaxation, making this a multiclass problem. In this study, nine ML algorithms were trained with a dataset created by the feature extraction of EEG signals.The EEG signals of 30 Physionet subjects were used to create a dataset related to movement. We used electrodes C3, C1, CZ, C2, and C4 according to the standard 10-10 placement. Then, we extracted the epochs of the EEG signals and applied tone, amplitude levels, and statistical techniques to obtain the set of features. LabVIEW™2015 version custom applications were used for reading the EEG signals; for channel selection, noise filtering, band selection, and feature extraction operations; and for creating the dataset. MATLAB 2021a was used for training, testing, and evaluating the performance metrics of the ML algorithms. In this study, the model of Medium-ANN achieved the best performance, with an AUC average of 0.9998, Cohen’s Kappa coefficient of 0.9552, a Matthews correlation coefficient of 0.9819, and a loss of 0.0147. These findings suggest the applicability of our approach to different scenarios, such as implementing robotic prostheses, where the use of superficial features is an acceptable option when resources are limited, as in embedded systems or edge computing devices. Full article

(This article belongs to the Special Issue Image and Signal Processing)

► Show Figures

Figure 1

Journal Menu

Journal Browser

Editor’s Choice Articles

Further Information

Guidelines

MDPI Initiatives

Follow MDPI