Technologies

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10 pages, 222 KiB

Open AccessEditorial

Guest Editorial on 10th Anniversary of Technologies—Recent Advances and Perspectives

by Manoj Gupta, Eugene Wong and Gwanggil Jeon

Technologies 2024, 12(10), 177; https://doi.org/10.3390/technologies12100177 - 29 Sep 2024

Viewed by 1380

Abstract

In 2022, Technologies (ISSN: 2227-7080) celebrated its 10th anniversary [...] Full article

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

Research

Jump to: Editorial, Review, Other

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 1667

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)

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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 1972

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)

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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 2555

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)

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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 2906

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)

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13 pages, 460 KiB

Open AccessArticle

Privacy and Explainability: The Effects of Data Protection on Shapley Values

by Aso Bozorgpanah, Vicenç Torra and Laya Aliahmadipour

Technologies 2022, 10(6), 125; https://doi.org/10.3390/technologies10060125 - 1 Dec 2022

Cited by 7 | Viewed by 2406

Abstract

There is an increasing need to provide explainability for machine learning models. There are different alternatives to provide explainability, for example, local and global methods. One of the approaches is based on Shapley values. Privacy is another critical requirement when dealing with sensitive [...] Read more.

There is an increasing need to provide explainability for machine learning models. There are different alternatives to provide explainability, for example, local and global methods. One of the approaches is based on Shapley values. Privacy is another critical requirement when dealing with sensitive data. Data-driven machine learning models may lead to disclosure. Data privacy provides several methods for ensuring privacy. In this paper, we study how methods for explainability based on Shapley values are affected by privacy methods. We show that some degree of protection still permits to maintain the information of Shapley values for the four machine learning models studied. Experiments seem to indicate that among the four models, Shapley values of linear models are the most affected ones. Full article

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

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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 2257

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)

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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 2282

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)

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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 2695

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)

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10 pages, 299 KiB

Open AccessArticle

Evaluation Based on the Distance from the Average Solution Approach: A Derivative Model for Evaluating and Selecting a Construction Manager

by Phuong Thanh Phan and Phong Thanh Nguyen

Technologies 2022, 10(5), 107; https://doi.org/10.3390/technologies10050107 - 14 Oct 2022

Cited by 1 | Viewed by 1938

Abstract

In the current market of integration and globalization, the competition between engineering and construction companies is increasing. Construction contractors can improve their competitiveness by evaluating and selecting qualified personnel for the construction engineering manager position for their company’s civil engineering projects. However, most [...] Read more.

In the current market of integration and globalization, the competition between engineering and construction companies is increasing. Construction contractors can improve their competitiveness by evaluating and selecting qualified personnel for the construction engineering manager position for their company’s civil engineering projects. However, most personnel evaluation and selection models in the construction industry rely on qualitative techniques, which leads to unsuitable decisions. To overcome this problem, this paper presents evaluation criteria and proposes a new model for selecting construction managers based on the evaluation based on the distance from the average solution approach (EDASA). The research results showed that EDASA has many strengths, such as solving the problem faster when the number of evaluation criteria or the number of alternatives is increased. Full article

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

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 6231

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)

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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 2698

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)

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12 pages, 1832 KiB

Open AccessArticle

Extraction and Characterization of β-Viginin Protein Hydrolysates from Cowpea Flour as a New Manufacturing Active Ingredient

by Taline S. Almeida, Caio A. da Cruz Souza, Mariana B. de Cerqueira e Silva, Fabiana P. R. Batista, Ederlan S. Ferreira, André L. S. Santos, Laura N. Silva, Carlisson R. Melo, Cristiane Bani, M. Lucia Bianconi, Juliana C. Cardoso, Ricardo L. C. de Albuquerque-Júnior, Raquel de Melo Barbosa, Matheus M. Pereira, Eliana B. Souto, Cleide M. F. Soares and Patrícia Severino

Technologies 2022, 10(4), 89; https://doi.org/10.3390/technologies10040089 - 21 Jul 2022

Cited by 2 | Viewed by 2967

Abstract

The increased mortality rates associated with antibiotic resistance has become a significant public health problem worldwide. Living beings produce a variety of endogenous compounds to defend themselves against exogenous pathogens. The knowledge of these endogenous compounds may contribute to the development of improved [...] Read more.

The increased mortality rates associated with antibiotic resistance has become a significant public health problem worldwide. Living beings produce a variety of endogenous compounds to defend themselves against exogenous pathogens. The knowledge of these endogenous compounds may contribute to the development of improved bioactive ingredients with antimicrobial properties, useful against conventional antibiotic resistance. Cowpea is an herbaceous legume of great interest due to its high protein content and high productivity rates. The study of genetic homology of vicillin (7S) from cowpea (Vigna unguiculata L.) with vicilins from soybean and other beans, such as adzuki, in addition to the need for further studies about potential biological activities of this vegetable, led us to seek the isolation of the vicilin fraction from cowpea and to evaluate the potential in vitro inhibitory action of pathogenic microorganisms. The cowpea beta viginin protein was isolated, characterized, and hydrolyzed in silico and in vitro by two enzymes, namely, pepsin and chymotrypsin. The antimicrobial activity of the protein hydrolysate fractions of cowpea flour was evaluated against Staphylococcus aureus and Pseudomonas aeruginosa, confirming the potential use of the peptides as innovative antimicrobial agents. Full article

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

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19 pages, 7952 KiB

Open AccessArticle

Analysis and Hardware Architecture on FPGA of a Robust Audio Fingerprinting Method Using SSM

by Ignacio Algredo-Badillo, Brenda Sánchez-Juárez, Kelsey A. Ramírez-Gutiérrez, Claudia Feregrino-Uribe, Francisco López-Huerta and Johan J. Estrada-López

Technologies 2022, 10(4), 86; https://doi.org/10.3390/technologies10040086 - 19 Jul 2022

Cited by 1 | Viewed by 2387

Abstract

The significant volume of sharing of digital media has recently increased due to the pandemic, raising the number of unauthorized uses of these media, such as emerging unauthorized copies, forgery, the lack of copyright, and electronic fraud, among others. In particular, several applications [...] Read more.

The significant volume of sharing of digital media has recently increased due to the pandemic, raising the number of unauthorized uses of these media, such as emerging unauthorized copies, forgery, the lack of copyright, and electronic fraud, among others. In particular, several applications integrate services or products such as music distribution, content management, audiobooks, streaming, and so on, which require users to demonstrate and guarantee their audio ownership. The use of acoustic fingerprint technology has emerged as a solution that is widely used to secure audio applications. This technique extracts and analyzes certain information that identifies the inherent properties of a partial or complete audio file. In this paper, we introduce two audio fingerprinting hardware architectures with a feature extraction system based on spectrogram saliency maps (SSM) and a brute-force search. The first of these conducts a search in 33 saliency maps of 32 × 32 pixels in size. After analyzing the first algorithm, a second architecture is proposed, in which the saliency map is reduced to 27 × 25 pixels, requiring 75.67% fewer hardware resources, lowering the power consumption by 64.58%, and improving the efficiency by 3.19 times via a throughput reduction of 22.29%. Full article

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

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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 2979

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)

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23 pages, 1569 KiB

Open AccessArticle

Optimization of the Pick-Up and Delivery Technology in a Selected Company: A Case Study

by Ondrej Stopka, Patrik Gross, Jan Pečman, Jiří Hanzl, Mária Stopková and Martin Jurkovič

Technologies 2022, 10(4), 84; https://doi.org/10.3390/technologies10040084 - 14 Jul 2022

Viewed by 3268

Abstract

This article deals with pick-up and delivery activities in a selected company that focuses on the distribution of products in the gastronomic sector of the market and suggests how to make the present approach more efficient. The introductory part of the article clarifies [...] Read more.

This article deals with pick-up and delivery activities in a selected company that focuses on the distribution of products in the gastronomic sector of the market and suggests how to make the present approach more efficient. The introductory part of the article clarifies the meanings of basic concepts related to the issue of optimizing the logistics processes in the company. The crucial goal is to analyze the existing pick-up and delivery technology and then, in the application part of the article, to propose adequate measures in the context of streamlining these activities with their technical and economic evaluation. An analysis of current delivery routes, which are used for the distribution of gastronomic products, is first performed. Thereafter, the routes are optimized with the aim of minimizing the total distance traveled by using the Operations Research methods, namely: the Hungarian method, Vogel approximation method, nearest neighbor method and the Routin route planner which is based on a principle of the Greedy algorithm. At the end of the article, a technical and economical evaluation of the findings is discussed, wherein the individual results of optimization through selected methods are first compared and then, new optimized routes are selected. Full article

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

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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 3305

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)

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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 2793

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)

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7 pages, 533 KiB

Open AccessCommunication

Exciting of Strong Electrostatic Fields and Electromagnetic Resonators at the Plasma Boundary by a Power Electromagnetic Beam

by O. M. Gradov

Technologies 2022, 10(4), 78; https://doi.org/10.3390/technologies10040078 - 29 Jun 2022

Viewed by 1852

Abstract

The interaction of an electromagnetic beam with a sharp boundary of a dense cold semi-limited plasma was considered in the case of a normal wave incidence on the plasma surface. The possibility of the appearance of an electrostatic field outside the plasma was [...] Read more.

The interaction of an electromagnetic beam with a sharp boundary of a dense cold semi-limited plasma was considered in the case of a normal wave incidence on the plasma surface. The possibility of the appearance of an electrostatic field outside the plasma was revealed, the intensity of which decreased according to the power law with a distance from the plasma and the center of the beam. It was possible to form cavities with a reduced electron density, being each electromagnetic resonators, which probed deeply into the dense plasma and couldexist in a stable state for a long period. Full article

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

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35 pages, 4322 KiB

Open AccessArticle

Solving Dual-Channel Supply Chain Pricing Strategy Problem with Multi-Level Programming Based on Improved Simplified Swarm Optimization

by Wei-Chang Yeh, Zhenyao Liu, Yu-Cheng Yang and Shi-Yi Tan

Technologies 2022, 10(3), 73; https://doi.org/10.3390/technologies10030073 - 11 Jun 2022

Cited by 5 | Viewed by 3152

Abstract

With the evolution of the Internet and the introduction of third-party platforms, a diversified supply chain has gradually emerged. In contrast to the traditional single sales channel, companies can also increase their revenue by selling through multiple channels, such as dual-channel sales: adding [...] Read more.

With the evolution of the Internet and the introduction of third-party platforms, a diversified supply chain has gradually emerged. In contrast to the traditional single sales channel, companies can also increase their revenue by selling through multiple channels, such as dual-channel sales: adding a sales channel for direct sales through online third-party platforms. However, due to the complexity of the supply chain structure, previous studies have rarely discussed and analyzed the capital-constrained dual-channel supply chain model, which is more relevant to the actual situation. To solve more complex and realistic supply chain decision problems, this paper uses the concept of game theory to describe the pricing negotiation procedures among the capital-constrained manufacturers and other parties in the dual-channel supply chain by applying the Stackelberg game theory to describe the supply chain structure as a hierarchical multi-level mathematical model to solve the optimal pricing strategy for different financing options to achieve the common benefit of the supply chain. In this study, we propose a Multi-level Improved Simplified Swarm Optimization (MLiSSO) method, which uses the improved, simplified swarm optimization (iSSO) for the Multi-level Programming Problem (MLPP). It is applied to this pricing strategy model of the supply chain and experiments with three related MLPPs in the past studies to verify the effectiveness of the method. The results show that the MLiSSO algorithm is effective, qualitative, and stable and can be used to solve the pricing strategy problem for supply chain models; furthermore, the algorithm can also be applied to other MLPPs. Full article

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

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8 pages, 2145 KiB

Open AccessArticle

Patterns Simulations Using Gibbs/MRF Auto-Poisson Models

by Stelios Zimeras

Technologies 2022, 10(3), 69; https://doi.org/10.3390/technologies10030069 - 6 Jun 2022

Cited by 1 | Viewed by 1929

Abstract

Pattern analysis is the process where characteristics of big data can be recognized using specific methods. Recognition of the data, especially images, can be achieved by applying spatial models, explaining the neighborhood structure of the patterns. These models can be introduced by Markov [...] Read more.

Pattern analysis is the process where characteristics of big data can be recognized using specific methods. Recognition of the data, especially images, can be achieved by applying spatial models, explaining the neighborhood structure of the patterns. These models can be introduced by Markov random field (MRF) models where conditional distribution of the pixels may be defined by a specific distribution. Various spatial models could be introduced, explaining the real patterns of the data; one class of these models is based on the Poisson distribution, called auto-Poisson models. The main advantage of these models is the consideration of the local characteristics of the image. Based on the local analysis, various patterns can be introduced and models that better explain the real data can be estimated, using advanced statistical techniques like Monte Carlo Markov Chains methods. These methods are based on simulations where the proposed distribution must converge to the original (final) one. In this work, an analysis of a MRF model under Poisson distribution would be defined and simulations would be illustrated based on Monte Carlo Markov Chains (MCMC) process like Gibbs sampler. Results would be illustrated using simulated and real patterns data. Full article

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

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7 pages, 1174 KiB

Open AccessCommunication

An a Priori Discussion of the Fill Front Stability in Semisolid Casting

by Anders E. W. Jarfors, Qing Zhang and Stefan Jonsson

Technologies 2022, 10(3), 67; https://doi.org/10.3390/technologies10030067 - 30 May 2022

Viewed by 3625

Abstract

Metal casting is an industrially important manufacturing process offering a superior combination of design flexibility, productivity and cost-effectiveness, but has limitations due to filling related defects. Several semisolid casting processes are available capable of casting at a range of solid fractions to overcome [...] Read more.

Metal casting is an industrially important manufacturing process offering a superior combination of design flexibility, productivity and cost-effectiveness, but has limitations due to filling related defects. Several semisolid casting processes are available capable of casting at a range of solid fractions to overcome this. The current communication aims to review the filling front behaviour and give a new perspective to the gate design in semisolid processing compared to conventional high-pressure die-casting. It is shown that solid fraction and gate widths are critical to avoid instability and spraying. Full article

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

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12 pages, 11814 KiB

Open AccessArticle

Electrospinning for the Modification of 3D Objects for the Potential Use in Tissue Engineering

by Laura Bauer, Lisa Brandstäter, Mika Letmate, Manasi Palachandran, Fynn Ole Wadehn, Carlotta Wolfschmidt, Timo Grothe, Uwe Güth and Andrea Ehrmann

Technologies 2022, 10(3), 66; https://doi.org/10.3390/technologies10030066 - 29 May 2022

Cited by 5 | Viewed by 2739

Abstract

Electrospinning is often investigated for biotechnological applications, such as tissue engineering and cell growth in general. In many cases, three-dimensional scaffolds would be advantageous to prepare tissues in a desired shape. Some studies thus investigated 3D-printed scaffolds decorated with electrospun nanofibers. Here, we [...] Read more.

Electrospinning is often investigated for biotechnological applications, such as tissue engineering and cell growth in general. In many cases, three-dimensional scaffolds would be advantageous to prepare tissues in a desired shape. Some studies thus investigated 3D-printed scaffolds decorated with electrospun nanofibers. Here, we report on the influence of 3D-printed substrates on fiber orientation and diameter of a nanofiber mat, directly electrospun on conductive and isolating 3D-printed objects, and show the effect of shadowing, taking 3D-printed ears with electrospun nanofiber mats as an example for potential and direct application in tissue engineering in general. Full article

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

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12 pages, 2388 KiB

Open AccessArticle

Study of Joint Symmetry in Gait Evolution for Quadrupedal Robots Using a Neural Network

by Zainullah Khan, Farhat Naseer, Yousuf Khan, Muhammad Bilal and Muhammad A. Butt

Technologies 2022, 10(3), 64; https://doi.org/10.3390/technologies10030064 - 22 May 2022

Cited by 3 | Viewed by 2756

Abstract

Bio-inspired legged robots have the potential to traverse uneven terrains in a very efficient way. The effectiveness of the robot gait depends on the joint symmetry of the robot; variations in joint symmetries can result in different types of gaits suitable for different [...] Read more.

Bio-inspired legged robots have the potential to traverse uneven terrains in a very efficient way. The effectiveness of the robot gait depends on the joint symmetry of the robot; variations in joint symmetries can result in different types of gaits suitable for different scenarios. In the literature, symmetric and asymmetric gaits have been synthesized for legged robots; however, no relation between the gait effectiveness and joint symmetry has been studied. In this research work, the effect of joint symmetry on the robot gait is studied. To test the suggested algorithm, spider-like robot morphology was created in a simulator. The simulation environment was set to a flat surface where the robots could be tested. The simulations were performed on the PyroSim software platform, a physics engine built on top of the Open Dynamics Engine. The quadrupedal robot was created with eight joints, and it is controlled using an artificial neural network. The artificial neural network was optimized using a genetic algorithm. Different robot symmetries were tested, i.e., diagonal joint symmetry, diagonal joint reverse symmetry, adjacent joint symmetry, adjacent joint reverse symmetry and random joint symmetry or joint asymmetry. The robot controllers for each joint symmetry were evolved for a set number of generations and the robot controllers were evaluated using a fitness function that we designed. Our results showed that symmetry in joint movement could help in generating optimal gaits for our test terrain, and joint symmetry produced gaits that were already present in nature. Moreover, our results also showed that certain joint symmetries tended to perform better than others in terms of stability, speed, and distance traveled. Full article

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

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13 pages, 11230 KiB

Open AccessEditor’s ChoiceArticle

Application of 3D Virtual Prototyping Technology to the Integration of Wearable Antennas into Fashion Garments

by Evridiki Papachristou and Hristos T. Anastassiu

Technologies 2022, 10(3), 62; https://doi.org/10.3390/technologies10030062 - 17 May 2022

Cited by 11 | Viewed by 5068

Abstract

A very large number of scientific papers have been published in the literature on wearable antennas of several types, structure and functionality. The main focus is always antenna efficiency from an engineering point of view. However, antenna integration into actual, realistic garments is [...] Read more.

A very large number of scientific papers have been published in the literature on wearable antennas of several types, structure and functionality. The main focus is always antenna efficiency from an engineering point of view. However, antenna integration into actual, realistic garments is seldom addressed. In this paper, 2D pattern and 3D virtual prototyping technology is utilized to develop regular clothing, available in the market, in which wearable antennas are incorporated in an automated manner, reducing the chances of compromising the garment elegance or comfort. The functionality of various commercial software modules is described, and particular design examples are implemented, proving the efficiency of the procedure and leading the way for more complex configurations. Full article

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

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15 pages, 2999 KiB

Open AccessEditor’s ChoiceArticle

A Comparative Analysis on Suicidal Ideation Detection Using NLP, Machine, and Deep Learning

by Rezaul Haque, Naimul Islam, Maidul Islam and Md Manjurul Ahsan

Technologies 2022, 10(3), 57; https://doi.org/10.3390/technologies10030057 - 29 Apr 2022

Cited by 60 | Viewed by 8457

Abstract

Social networks are essential resources to obtain information about people’s opinions and feelings towards various issues as they share their views with their friends and family. Suicidal ideation detection via online social network analysis has emerged as an essential research topic with significant [...] Read more.

Social networks are essential resources to obtain information about people’s opinions and feelings towards various issues as they share their views with their friends and family. Suicidal ideation detection via online social network analysis has emerged as an essential research topic with significant difficulties in the fields of NLP and psychology in recent years. With the proper exploitation of the information in social media, the complicated early symptoms of suicidal ideations can be discovered and hence, it can save many lives. This study offers a comparative analysis of multiple machine learning and deep learning models to identify suicidal thoughts from the social media platform Twitter. The principal purpose of our research is to achieve better model performance than prior research works to recognize early indications with high accuracy and avoid suicide attempts. We applied text pre-processing and feature extraction approaches such as CountVectorizer and word embedding, and trained several machine learning and deep learning models for such a goal. Experiments were conducted on a dataset of 49,178 instances retrieved from live tweets by 18 suicidal and non-suicidal keywords using Python Tweepy API. Our experimental findings reveal that the RF model can achieve the highest classification score among machine learning algorithms, with an accuracy of 93% and an F1 score of 0.92. However, training the deep learning classifiers with word embedding increases the performance of ML models, where the BiLSTM model reaches an accuracy of 93.6% and a 0.93 F1 score. Full article

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

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18 pages, 4030 KiB

Open AccessEditor’s ChoiceArticle

An Optimized Enhanced Phase Locked Loop Controller for a Hybrid System

by Amritha Kodakkal, Rajagopal Veramalla, Narasimha Raju Kuthuri and Surender Reddy Salkuti

Technologies 2022, 10(2), 40; https://doi.org/10.3390/technologies10020040 - 11 Mar 2022

Cited by 6 | Viewed by 3382

Abstract

The use of renewable energy sources is the need of the hour, but the highly intermittent nature of the wind and solar energies demands an efficient controller be connected with the system. This paper proposes an adept control algorithm for an isolated system [...] Read more.

The use of renewable energy sources is the need of the hour, but the highly intermittent nature of the wind and solar energies demands an efficient controller be connected with the system. This paper proposes an adept control algorithm for an isolated system connected with renewable energy sources. The system under consideration is a hybrid power system with a wind power harnessing unit associated with a solar energy module. A controller that works with enhanced phase locked loop (EPLL) algorithm is provided to maintain the quality of power at the load side and ensure that the source current is not affected during the load fluctuations. EPLL is very simple, precise, stable, and highly efficient in maintaining power quality. The double-frequency error which is the drawback of standard phase locked loop is eliminated in EPLL. Optimization techniques are used here to tune the values of the PI controller gains in the controlling algorithm. Tuning of the controller is an important process, as the gains of the controllers decide the quality of the output. The system is designed using MATLAB/SIMULINK. Codes are written in MATLAB for the optimization. Out of the three different optimization techniques applied, the salp swarm algorithm is found to give the most suitable gain values for the proposed system. Solar power generation is made more efficient by implementing maximum power point tracking. Perturb and observe is the method adopted for MPPT. Full article

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

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Review

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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 45 | Viewed by 6261

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)

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34 pages, 5160 KiB

Open AccessReview

Risk Assessment of Heterogeneous IoMT Devices: A Review

by Pritika, Bharanidharan Shanmugam and Sami Azam

Technologies 2023, 11(1), 31; https://doi.org/10.3390/technologies11010031 - 14 Feb 2023

Cited by 25 | Viewed by 5172

Abstract

The adaptation of the Internet of Medical Things (IoMT) has provided efficient and timely services and has transformed the healthcare industry to a great extent. Monitoring patients remotely and managing hospital records and data have become effortless with the advent of IoMT. However, [...] Read more.

The adaptation of the Internet of Medical Things (IoMT) has provided efficient and timely services and has transformed the healthcare industry to a great extent. Monitoring patients remotely and managing hospital records and data have become effortless with the advent of IoMT. However, security and privacy have become a significant concern with the growing number of threats in the cyber world, primarily for personal and sensitive user data. In terms of IoMT devices, risks appearing from them cannot easily fit into an existing risk assessment framework, and while research has been done on this topic, little attention has been paid to the methodologies used for the risk assessment of heterogeneous IoMT devices. This paper elucidates IoT, its applications with reference to in-demand sectors, and risks in terms of their types. By the same token, IoMT and its application area and architecture are explained. We have also discussed the common attacks on IoMT. Existing papers on IoT, IoMT, risk assessment, and frameworks are reviewed. Finally, the paper analyzes the available risk assessment frameworks such as NIST, ISO 27001, TARA, and the IEEE213-2019 (P2413) standard and highlights the need for new approaches to address the heterogeneity of the risks. In our study, we have decided to follow the functions of the NIST and ISO 270001 frameworks. The complete framework is anticipated to deliver a risk-free approach for the risk assessment of heterogeneous IoMT devices benefiting its users. Full article

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

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23 pages, 1095 KiB

Open AccessReview

Production Technologies, Regulatory Parameters, and Quality Control of Vaccine Vectors for Veterinary Use

by Raquel de M. Barbosa, Amélia M. Silva, Classius F. da Silva, Juliana C. Cardoso, Patricia Severino, Lyghia M. A. Meirelles, Arnobio A. da Silva-Junior, César Viseras, Joel Fonseca and Eliana B. Souto

Technologies 2022, 10(5), 109; https://doi.org/10.3390/technologies10050109 - 21 Oct 2022

Cited by 3 | Viewed by 5863

Abstract

This paper presents a comprehensive review of the main types of vaccines approaching production technology, regulatory parameters, and the quality control of vaccines. Bioinformatic tools and computational strategies have been used in the research and development of new pharmaceutical products, reducing the time [...] Read more.

This paper presents a comprehensive review of the main types of vaccines approaching production technology, regulatory parameters, and the quality control of vaccines. Bioinformatic tools and computational strategies have been used in the research and development of new pharmaceutical products, reducing the time between supposed pharmaceutical product candidates (R&D steps) and final products (to be marketed). In fact, in the reverse vaccinology field, in silico studies can be very useful in identifying possible vaccine targets from databases. In addition, in some cases (subunit or RNA/ DNA vaccines), the in silico approach permits: (I) the evaluation of protein immunogenicity through the prediction of epitopes, (II) the potential adverse effects of antigens through the projection of similarity to host proteins, (III) toxicity and (IV) allergenicity, contributing to obtaining safe, effective, stable, and economical vaccines for existing and emerging infectious pathogens. Additionally, the rapid growth of emerging infectious diseases in recent years should be considered a driving force for developing and implementing new vaccines and reassessing vaccine schedules in companion animals, food animals, and wildlife disease control. Comprehensive and well-planned vaccination schedules are effective strategies to prevent and treat infectious diseases. Full article

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

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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 20 | Viewed by 13413

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)

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26 pages, 3481 KiB

Open AccessReview

Synthetic Micro/Nanomotors for Drug Delivery

by Eduardo Guzmán and Armando Maestro

Technologies 2022, 10(4), 96; https://doi.org/10.3390/technologies10040096 - 17 Aug 2022

Cited by 4 | Viewed by 3241

Abstract

Synthetic micro/nanomotors (MNMs) are human-made machines characterized by their capacity for undergoing self-propelled motion as a result of the consumption of chemical energy obtained from specific chemical or biochemical reactions, or as a response to an external actuation driven by a physical stimulus. [...] Read more.

Synthetic micro/nanomotors (MNMs) are human-made machines characterized by their capacity for undergoing self-propelled motion as a result of the consumption of chemical energy obtained from specific chemical or biochemical reactions, or as a response to an external actuation driven by a physical stimulus. This has fostered the exploitation of MNMs for facing different biomedical challenges, including drug delivery. In fact, MNMs are superior systems for an efficient delivery of drugs, offering several advantages in relation to conventional carriers. For instance, the self-propulsion ability of micro/nanomotors makes possible an easier transport of drugs to specific targets in comparison to the conventional distribution by passive carriers circulating within the blood, which enhances the drug bioavailability in tissues. Despite the promising avenues opened by the use of synthetic micro/nanomotors in drug delivery applications, the development of systems for in vivo uses requires further studies to ensure a suitable biocompatibility and biodegradability of the fabricated engines. This is essential for guaranteeing the safety of synthetic MNMs and patient convenience. This review provides an updated perspective to the potential applications of synthetic micro/nanomotors in drug delivery. Moreover, the most fundamental aspects related to the performance of synthetic MNMs and their biosafety are also discussed. Full article

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

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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 26 | Viewed by 8084

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)

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15 pages, 766 KiB

Open AccessReview

Explainable AI (XAI) Applied in Machine Learning for Pain Modeling: A Review

by Ravichandra Madanu, Maysam F. Abbod, Fu-Jung Hsiao, Wei-Ta Chen and Jiann-Shing Shieh

Technologies 2022, 10(3), 74; https://doi.org/10.3390/technologies10030074 - 14 Jun 2022

Cited by 12 | Viewed by 5286

Abstract

Pain is a complex term that describes various sensations that create discomfort in various ways or types inside the human body. Generally, pain has consequences that range from mild to severe in different organs of the body and will depend on the way [...] Read more.

Pain is a complex term that describes various sensations that create discomfort in various ways or types inside the human body. Generally, pain has consequences that range from mild to severe in different organs of the body and will depend on the way it is caused, which could be an injury, illness or medical procedures including testing, surgeries or therapies, etc. With recent advances in artificial-intelligence (AI) systems associated in biomedical and healthcare settings, the contiguity of physician, clinician and patient has shortened. AI, however, has more scope to interpret the pain associated in patients with various conditions by using any physiological or behavioral changes. Facial expressions are considered to give much information that relates with emotions and pain, so clinicians consider these changes with high importance for assessing pain. This has been achieved in recent times with different machine-learning and deep-learning models. To accentuate the future scope and importance of AI in medical field, this study reviews the explainable AI (XAI) as increased attention is given to an automatic assessment of pain. This review discusses how these approaches are applied for different pain types. Full article

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

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17 pages, 2911 KiB

Open AccessReview

Advanced Security Framework for Internet of Things (IoT)

by Abid Ali, Abdul Mateen, Abdul Hanan and Farhan Amin

Technologies 2022, 10(3), 60; https://doi.org/10.3390/technologies10030060 - 12 May 2022

Cited by 16 | Viewed by 6265

Abstract

The stimulus to carry out this research was to identify and propose a secure framework for the Internet of Things (IoT). Due to the massive accessibility and interconnection of IoT devices, systems are at risk of being exploited by hackers. Therefore, there is [...] Read more.

The stimulus to carry out this research was to identify and propose a secure framework for the Internet of Things (IoT). Due to the massive accessibility and interconnection of IoT devices, systems are at risk of being exploited by hackers. Therefore, there is a need to find an advanced security framework that covers data security, data confidentiality, and data integrity issues. The study uses a systematic literature review (SLR) technique and complete substantive literature is reviewed to find out the constructs and themes in the existing literature. We performed it in four steps, which were inclusion, eligibility, screening, and identification. We reviewed around 568 articles from well-reputable journals, and after exclusion, 260 articles and 54 reports were analyzed. We performed an analysis using MAXQDA in which the nodes and themes were first identified. After the classification, a qualitative model was generated using MAXQDA. The proposed model is supported by the literature so it will be useful for the IT managers, developers, and the users of IoT. Full article

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

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18 pages, 2046 KiB

Open AccessEditor’s ChoiceReview

Strategic Investment in Open Hardware for National Security

by Joshua M. Pearce

Technologies 2022, 10(2), 53; https://doi.org/10.3390/technologies10020053 - 18 Apr 2022

Cited by 8 | Viewed by 4482

Abstract

Free and open-source hardware (FOSH) development has been shown to increase innovation and reduce economic costs. This article reviews the opportunity to use FOSH as a sanction to undercut imports and exports from a target criminal country. A formal methodology is presented for [...] Read more.

Free and open-source hardware (FOSH) development has been shown to increase innovation and reduce economic costs. This article reviews the opportunity to use FOSH as a sanction to undercut imports and exports from a target criminal country. A formal methodology is presented for selecting strategic national investments in FOSH development to improve both national security and global safety. In this methodology, first the target country that is threatening national security or safety is identified. Next, the top imports from the target country as well as potentially other importing countries (allies) are quantified. Hardware is identified that could undercut imports/exports from the target country. Finally, methods to support the FOSH development are enumerated to support production in a commons-based peer production strategy. To demonstrate how this theoretical method works in practice, it is applied as a case study to a current criminal military aggressor nation, who is also a fossil-fuel exporter. The results show that there are numerous existing FOSH and opportunities to develop new FOSH for energy conservation and renewable energy to reduce fossil-fuel-energy demand. Widespread deployment would reduce the concomitant pollution, human health impacts, and environmental desecration as well as cut financing of military operations. Full article

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

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Other

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10 pages, 753 KiB

Open AccessPerspective

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 56 | Viewed by 16815

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)

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