Technologies

18 pages, 36905 KB

Open AccessEditor’s ChoiceArticle

MINA: A Robotic Assistant for Hospital Fetching Tasks

by Harish Ram Nambiappan, Stephanie Arevalo Arboleda, Cody Lee Lundberg, Maria Kyrarini, Fillia Makedon and Nicholas Gans

Technologies 2022, 10(2), 41; https://doi.org/10.3390/technologies10020041 - 12 Mar 2022

Cited by 5 | Viewed by 6690

Abstract

In this paper, a robotic Multitasking Intelligent Nurse Aid (MINA) is proposed to assist nurses with everyday object fetching tasks. MINA consists of a manipulator arm on an omni-directional mobile base. Before the operation, an augmented reality interface was used to place waypoints. [...] Read more.

In this paper, a robotic Multitasking Intelligent Nurse Aid (MINA) is proposed to assist nurses with everyday object fetching tasks. MINA consists of a manipulator arm on an omni-directional mobile base. Before the operation, an augmented reality interface was used to place waypoints. Waypoints can indicate the location of a patient, supply shelf, and other locations of interest. When commanded to retrieve an object, MINA uses simultaneous localization and mapping to map its environment and navigate to the supply shelf waypoint. At the shelf, MINA builds a 3D point cloud representation of the shelf and searches for barcodes to identify and localize the object it was sent to retrieve. Upon grasping the object, it returns to the user. Collision avoidance is incorporated during the mobile navigation and grasping tasks. We performed experiments to evaluate MINA’s efficacy including with obstacles along the path. The experimental results showed that MINA can repeatedly navigate to the specified waypoints and successfully perform the grasping and retrieval task. Full article

(This article belongs to the Collection Selected Papers from the PETRA Conference Series)

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18 pages, 4030 KB

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 9 | Viewed by 4156

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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12 pages, 3271 KB

Open AccessEditor’s ChoiceArticle

Parasitic Coupling in 3D Sequential Integration: The Example of a Two-Layer 3D Pixel

by Petros Sideris, Arnaud Peizerat, Perrine Batude, Gilles Sicard and Christoforos Theodorou

Technologies 2022, 10(2), 38; https://doi.org/10.3390/technologies10020038 - 28 Feb 2022

Cited by 1 | Viewed by 5058

Abstract

In this paper, we present a thorough analysis of parasitic coupling effects between different electrodes for a 3D Sequential Integration circuit example comprising stacked devices. More specifically, this study is performed for a Back-Side Illuminated, 4T–APS, 3D Sequential Integration pixel with both its [...] Read more.

In this paper, we present a thorough analysis of parasitic coupling effects between different electrodes for a 3D Sequential Integration circuit example comprising stacked devices. More specifically, this study is performed for a Back-Side Illuminated, 4T–APS, 3D Sequential Integration pixel with both its photodiode and Transfer Gate at the bottom tier and the other parts of the circuit on the top tier. The effects of voltage bias and 3D inter-tier contacts are studied by using TCAD simulations. Coupling-induced electrical parameter variations are compared against variations due to temperature change, revealing that these two effects can cause similar levels of readout error for the top-tier readout circuit. On the bright side, we also demonstrate that in the case of a rolling shutter pixel readout, the coupling effect becomes nearly negligible. Therefore, we estimate that the presence of an inter-tier ground plane, normally used for electrical isolation, is not strictly mandatory for Monolithic 3D pixels. Full article

(This article belongs to the Special Issue MOCAST 2021)

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13 pages, 1030 KB

Open AccessEditor’s ChoiceArticle

Lightweight Neural Network for COVID-19 Detection from Chest X-ray Images Implemented on an Embedded System

by Theodora Sanida, Argyrios Sideris, Dimitris Tsiktsiris and Minas Dasygenis

Technologies 2022, 10(2), 37; https://doi.org/10.3390/technologies10020037 - 25 Feb 2022

Cited by 28 | Viewed by 6114

Abstract

At the end of 2019, a severe public health threat named coronavirus disease (COVID-19) spread rapidly worldwide. After two years, this coronavirus still spreads at a fast rate. Due to its rapid spread, the immediate and rapid diagnosis of COVID-19 is of utmost [...] Read more.

At the end of 2019, a severe public health threat named coronavirus disease (COVID-19) spread rapidly worldwide. After two years, this coronavirus still spreads at a fast rate. Due to its rapid spread, the immediate and rapid diagnosis of COVID-19 is of utmost importance. In the global fight against this virus, chest X-rays are essential in evaluating infected patients. Thus, various technologies that enable rapid detection of COVID-19 can offer high detection accuracy to health professionals to make the right decisions. The latest emerging deep-learning (DL) technology enhances the power of medical imaging tools by providing high-performance classifiers in X-ray detection, and thus various researchers are trying to use it with limited success. Here, we propose a robust, lightweight network where excellent classification results can diagnose COVID-19 by evaluating chest X-rays. The experimental results showed that the modified architecture of the model we propose achieved very high classification performance in terms of accuracy, precision, recall, and f1-score for four classes (COVID-19, normal, viral pneumonia and lung opacity) of 21.165 chest X-ray images, and at the same time meeting real-time constraints, in a low-power embedded system. Finally, our work is the first to propose such an optimized model for a low-power embedded system with increased detection accuracy. Full article

(This article belongs to the Special Issue MOCAST 2021)

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24 pages, 1663 KB

Open AccessEditor’s ChoiceArticle

Sovereign Digital Consent through Privacy Impact Quantification and Dynamic Consent

by Arno Appenzeller, Marina Hornung, Thomas Kadow, Erik Krempel and Jürgen Beyerer

Technologies 2022, 10(1), 35; https://doi.org/10.3390/technologies10010035 - 21 Feb 2022

Cited by 7 | Viewed by 4237

Abstract

Digitization is becoming more and more important in the medical sector. Through electronic health records and the growing amount of digital data of patients available, big data research finds an increasing amount of use cases. The rising amount of data and the imposing [...] Read more.

Digitization is becoming more and more important in the medical sector. Through electronic health records and the growing amount of digital data of patients available, big data research finds an increasing amount of use cases. The rising amount of data and the imposing privacy risks can be overwhelming for patients, so they can have the feeling of being out of control of their data. Several previous studies on digital consent have tried to solve this problem and empower the patient. However, there are no complete solution for the arising questions yet. This paper presents the concept of Sovereign Digital Consent by the combination of a consent privacy impact quantification and a technology for proactive sovereign consent. The privacy impact quantification supports the patient to comprehend the potential risk when sharing the data and considers the personal preferences regarding acceptance for a research project. The proactive dynamic consent implementation provides an implementation for fine granular digital consent, using medical data categorization terminology. This gives patients the ability to control their consent decisions dynamically and is research friendly through the automatic enforcement of the patients’ consent decision. Both technologies are evaluated and implemented in a prototypical application. With the combination of those technologies, a promising step towards patient empowerment through Sovereign Digital Consent can be made. Full article

(This article belongs to the Collection Selected Papers from the PETRA Conference Series)

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15 pages, 7368 KB

Open AccessEditor’s ChoiceArticle

Self-Supervised Human Activity Representation for Embodied Cognition Assessment

by Mohammad Zaki Zadeh, Ashwin Ramesh Babu, Ashish Jaiswal and Fillia Makedon

Technologies 2022, 10(1), 33; https://doi.org/10.3390/technologies10010033 - 17 Feb 2022

Cited by 6 | Viewed by 3807

Abstract

Physical activities, according to the embodied cognition theory, are an important manifestation of cognitive functions. As a result, in this paper, the Activate Test of Embodied Cognition (ATEC) system is proposed to assess various cognitive measures. It consists of physical exercises with different [...] Read more.

Physical activities, according to the embodied cognition theory, are an important manifestation of cognitive functions. As a result, in this paper, the Activate Test of Embodied Cognition (ATEC) system is proposed to assess various cognitive measures. It consists of physical exercises with different variations and difficulty levels designed to provide assessment of executive and motor functions. This work focuses on obtaining human activity representation from recorded videos of ATEC tasks in order to automatically assess embodied cognition performance. A self-supervised approach is employed in this work that can exploit a small set of annotated data to obtain an effective human activity representation. The performance of different self-supervised approaches along with a supervised method are investigated for automated cognitive assessment of children performing ATEC tasks. The results show that the supervised learning approach performance decreases as the training set becomes smaller, whereas the self-supervised methods maintain their performance by taking advantage of unlabeled data. Full article

(This article belongs to the Collection Selected Papers from the PETRA Conference Series)

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27 pages, 3415 KB

Open AccessEditor’s ChoiceReview

Mechanical Properties of Sustainable Metal Matrix Composites: A Review on the Role of Green Reinforcements and Processing Methods

by Sankaranarayanan Seetharaman, Jayalakshmi Subramanian, Ramachandra Arvind Singh, Wai Leong Eugene Wong, Mui Ling Sharon Nai and Manoj Gupta

Technologies 2022, 10(1), 32; https://doi.org/10.3390/technologies10010032 - 16 Feb 2022

Cited by 48 | Viewed by 10410

Abstract

Growing concerns like depleting mineral resources, increased materials wastage, and structural light-weighting requirements due to emission control regulations drive the development of sustainable metal matrix composites. Al and Mg based alloys with relatively lower melting temperatures qualify for recycling applications and hence are [...] Read more.

Growing concerns like depleting mineral resources, increased materials wastage, and structural light-weighting requirements due to emission control regulations drive the development of sustainable metal matrix composites. Al and Mg based alloys with relatively lower melting temperatures qualify for recycling applications and hence are considered as the matrix material for developing sustainable composites. The recent trend also explores various industrial by-products and agricultural wastes as green reinforcements, and this article presents insights on the properties of Al and Mg based sustainable metal matrix composites with special emphasis on green reinforcements and processing methods. Full article

(This article belongs to the Special Issue Commemorative Issue in Honor of Prof. Dr. Manoj Gupta on the Occasion of 60th Birthday)

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18 pages, 1305 KB

Open AccessEditor’s ChoiceArticle

Visible Light Communications for Internet of Things: Prospects and Approaches, Challenges, Solutions and Future Directions

by Stephen S. Oyewobi, Karim Djouani and Anish Matthew Kurien

Technologies 2022, 10(1), 28; https://doi.org/10.3390/technologies10010028 - 5 Feb 2022

Cited by 83 | Viewed by 10305

Abstract

Visible light communications (VLC) is an emerging and promising concept that is capable of solving the major challenges of 5G and Internet of Things (IoT) communication systems. Moreover, due to the usage of light-emitting diodes (LEDs) in almost every aspect of our daily [...] Read more.

Visible light communications (VLC) is an emerging and promising concept that is capable of solving the major challenges of 5G and Internet of Things (IoT) communication systems. Moreover, due to the usage of light-emitting diodes (LEDs) in almost every aspect of our daily life VLC is providing massive connectivity for various types of massive IoT communications ranging from machine-to-machine, vehicle-to-infrastructure, infrastructure-to-vehicle, chip-to-chip as well as device-to-device. In this paper, we undertake a comprehensive review of the prospects of implementing VLC for IoT. Moreover, we investigate existing and proposed approaches implemented in the application of VLC for IoT. Additionally, we look at the challenges faced in applying VLC for IoT and offer solutions where applicable. Then, we identify future research directions in the implementation of VLC for IoT. Full article

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18 pages, 5237 KB

Open AccessEditor’s ChoiceArticle

Reliable IoT-Based Monitoring and Control of Hydroponic Systems

by Konstantinos Tatas, Ahmad Al-Zoubi, Nicholas Christofides, Chrysostomos Zannettis, Michael Chrysostomou, Stavros Panteli and Anthony Antoniou

Technologies 2022, 10(1), 26; https://doi.org/10.3390/technologies10010026 - 2 Feb 2022

Cited by 54 | Viewed by 21632

Abstract

This paper presents the design and implementation of iPONICS: an intelligent, low-cost IoT-based control and monitoring system for hydroponics greenhouses. The system is based on three types of sensor nodes. The main (master) node is responsible for controlling the pump, monitoring the quality [...] Read more.

This paper presents the design and implementation of iPONICS: an intelligent, low-cost IoT-based control and monitoring system for hydroponics greenhouses. The system is based on three types of sensor nodes. The main (master) node is responsible for controlling the pump, monitoring the quality of the water in the greenhouse and aggregating and transmitting the data from the slave nodes. Environment sensing slave nodes monitor the ambient conditions in the greenhouse and transmit the data to the main node. Security nodes monitor activity (movement in the area). The system monitors water quality and greenhouse temperature and humidity, ensuring that crops grow under optimal conditions according to hydroponics guidelines. Remote monitoring for the greenhouse keepers is facilitated by monitoring these parameters via connecting to a website. An innovative fuzzy inference engine determines the plant irrigation duration. The system is optimized for low power consumption in order to facilitate off-grid operation. Preliminary reliability analysis indicates that the system can tolerate various transient faults without requiring intervention. Full article

(This article belongs to the Special Issue MOCAST 2021)

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16 pages, 2472 KB

Open AccessEditor’s ChoiceArticle

Performance Analysis of 2D and 3D Bufferless NoCs Using Markov Chain Models

by Konstantinos Tatas

Technologies 2022, 10(1), 27; https://doi.org/10.3390/technologies10010027 - 2 Feb 2022

Cited by 1 | Viewed by 3045

Abstract

Performance analysis and design space exploration of bufferless Networks-on-Chip is done mainly through time-consuming cycle-accurate simulation, due to the chaotic nature of packet deflections, which have thus far prevented the development of an accurate analytical model. In order to raise the level of [...] Read more.

Performance analysis and design space exploration of bufferless Networks-on-Chip is done mainly through time-consuming cycle-accurate simulation, due to the chaotic nature of packet deflections, which have thus far prevented the development of an accurate analytical model. In order to raise the level of abstraction as well as capture the inherently probabilistic behavior of deflection routing, this paper presents a methodology for employing Markov chain models in the analysis of the behavior of bufferless Networks-on-Chip. A formal way of describing a bufferless NoC topology as a set of discrete-time Markov chains is presented. It is demonstrated that by combining this description with the network average distance, it is possible to obtain the expectation of the number of hops between any pair of nodes in the network as a function of the flit deflection probability. Comparisons between the proposed model and cycle-accurate simulation demonstrate the accuracy achieved by the model, with negligible computational cost. The useful range of the proposed model is quantified, demonstrating that it has an error of less than 10% for a significant proportion (between 33 and 75%) of the injection rate range below saturation. Finally, a simple equation for comparing mesh topologies with a “back-of-the-envelope” calculation is introduced. Full article

(This article belongs to the Special Issue MOCAST 2021)

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17 pages, 2806 KB

Open AccessEditor’s ChoiceArticle

User-Centric Design Methodology for mHealth Apps: The PainApp Paradigm for Chronic Pain

by Yiannis Koumpouros

Technologies 2022, 10(1), 25; https://doi.org/10.3390/technologies10010025 - 31 Jan 2022

Cited by 18 | Viewed by 7142

Abstract

The paper presents a user-centric methodology in order to design successful mobile health (mHealth) applications. In addition to the theoretical background, such an example is presented with an application targeting chronic pain. The pain domain was decided due to its significance in many [...] Read more.

The paper presents a user-centric methodology in order to design successful mobile health (mHealth) applications. In addition to the theoretical background, such an example is presented with an application targeting chronic pain. The pain domain was decided due to its significance in many aspects: its complexity, dispersion in the population, the financial burden it causes, etc. The paper presents a step-by-step plan in order to build mobile health applications. Participatory design and interdisciplinarity are only some of the critical issues towards the desired result. In the given example (development of the PainApp), a participatory design was followed with a team of seventeen stakeholders that drove the design and development phases. Three physicians, one behavioral scientist, three IT and UX experts, and ten patients collaborated together to develop the final solution. The several features implemented in the PainApp solution are presented in details. The application is threefold: it supports the management, reporting, and treatment effectiveness monitoring. The paper is giving details on the methodological approach while presenting insights on the actual plan and the steps followed for having a patient-centric solution. Key success factors and barriers to mobile health applications that support the need for such an approach are also presented. Full article

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

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10 pages, 1457 KB

Open AccessEditor’s ChoiceArticle

Results of Preliminary Studies on the Perception of the Relationships between Objects Presented in a Cartesian Space

by Ira Woodring and Charles Owen

Technologies 2022, 10(1), 20; https://doi.org/10.3390/technologies10010020 - 30 Jan 2022

Viewed by 2561

Abstract

Visualizations often use the paradigm of a Cartesian space for the presentation of objects and information. Unified Modeling Language (UML) is a visual language used to describe relationships in processes and systems and is heavily used in computer science and software engineering. Visualizations [...] Read more.

Visualizations often use the paradigm of a Cartesian space for the presentation of objects and information. Unified Modeling Language (UML) is a visual language used to describe relationships in processes and systems and is heavily used in computer science and software engineering. Visualizations are a powerful development tool, but are not necessarily accessible to all users, as individuals may differ in their level of visual ability or perceptual biases. Sonfication methods can be used to supplement or, in some cases, replace visual models. This paper describes two studies created to determine the ability of users to perceive relationships between objects in a Cartesian space when presented in a sonified form. Results from this study will be used to guide the creation of sonified UML software. Full article

(This article belongs to the Collection Selected Papers from the PETRA Conference Series)

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14 pages, 2847 KB

Open AccessEditor’s ChoiceArticle

On the Exploration of Automatic Building Extraction from RGB Satellite Images Using Deep Learning Architectures Based on U-Net

by Anastasios Temenos, Nikos Temenos, Anastasios Doulamis and Nikolaos Doulamis

Technologies 2022, 10(1), 19; https://doi.org/10.3390/technologies10010019 - 29 Jan 2022

Cited by 19 | Viewed by 5039

Abstract

Detecting and localizing buildings is of primary importance in urban planning tasks. Automating the building extraction process, however, has become attractive given the dominance of Convolutional Neural Networks (CNNs) in image classification tasks. In this work, we explore the effectiveness of the CNN-based [...] Read more.

Detecting and localizing buildings is of primary importance in urban planning tasks. Automating the building extraction process, however, has become attractive given the dominance of Convolutional Neural Networks (CNNs) in image classification tasks. In this work, we explore the effectiveness of the CNN-based architecture U-Net and its variations, namely, the Residual U-Net, the Attention U-Net, and the Attention Residual U-Net, in automatic building extraction. We showcase their robustness in feature extraction and information processing using exclusively RGB images, as they are a low-cost alternative to multi-spectral and LiDAR ones, selected from the SpaceNet 1 dataset. The experimental results show that U-Net achieves a

91.9 %

accuracy, whereas introducing residual blocks, attention gates, or a combination of both improves the accuracy of the vanilla U-Net to

93.6 %

,

94.0 %

, and

93.7 %

, respectively. Finally, the comparison between U-Net architectures and typical deep learning approaches from the literature highlights their increased performance in accurate building localization around corners and edges. Full article

(This article belongs to the Collection Selected Papers from the PETRA Conference Series)

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18 pages, 1780 KB

Open AccessEditor’s ChoiceArticle

Stacking-Based Ensemble Learning Method for Multi-Spectral Image Classification

by Tagel Aboneh, Abebe Rorissa and Ramasamy Srinivasagan

Technologies 2022, 10(1), 17; https://doi.org/10.3390/technologies10010017 - 26 Jan 2022

Cited by 39 | Viewed by 7087

Abstract

Higher dimensionality, Hughes phenomenon, spatial resolution of image data, and presence of mixed pixels are the main challenges in a multi-spectral image classification process. Most of the classical machine learning algorithms suffer from scoring optimal classification performance over multi-spectral image data. In this [...] Read more.

Higher dimensionality, Hughes phenomenon, spatial resolution of image data, and presence of mixed pixels are the main challenges in a multi-spectral image classification process. Most of the classical machine learning algorithms suffer from scoring optimal classification performance over multi-spectral image data. In this study, we propose stack-based ensemble-based learning approach to optimize image classification performance. In addition, we integrate the proposed ensemble learning with XGBoost method to further improve its classification accuracy. To conduct the experiment, the Landsat image data has been acquired from Bishoftu town located in the Oromia region of Ethiopia. The current study’s main objective was to assess the performance of land cover and land use analysis using multi-spectral image data. Results from our experiment indicate that, the proposed ensemble learning method outperforms any strong base classifiers with 99.96% classification performance accuracy. Full article

(This article belongs to the Special Issue Multimedia Indexing and Retrieval)

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23 pages, 5508 KB

Open AccessEditor’s ChoiceArticle

Novel Benes Network Routing Algorithm and Hardware Implementation

by Dimitris Nikolaidis, Panos Groumas, Christos Kouloumentas and Hercules Avramopoulos

Technologies 2022, 10(1), 16; https://doi.org/10.3390/technologies10010016 - 25 Jan 2022

Cited by 8 | Viewed by 9419

Abstract

Benes/Clos networks constitute a particularly important part of interconnection networks and have been used in numerous areas, such as multi-processor systems, data centers and on-chip networks. They have also attracted great interest in the field of optical communications due to the increasing popularity [...] Read more.

Benes/Clos networks constitute a particularly important part of interconnection networks and have been used in numerous areas, such as multi-processor systems, data centers and on-chip networks. They have also attracted great interest in the field of optical communications due to the increasing popularity of optical switches based on these architectures. There are numerous algorithms aimed at routing these types of networks, with varying degrees of utility. Linear algorithms, such as Sun Tsu and Opferman, were historically the first attempt to standardize the routing procedure of this types of networks. They require matrix-based calculations, which are very demanding in terms of resources and in some cases involve backtracking, which impairs their efficiency. Parallel solutions, such as Lee’s algorithm, were introduced later and provide a different answer that satisfy the requirements of high-performance networks. They are, however, extremely complex and demand even more resources. In both cases, hardware implementations reflect their algorithmic characteristics. In this paper, we attempt to design an algorithm that is simple enough to be implemented on a small field programmable gate array board while simultaneously efficient enough to be used in practical scenarios. The design itself is of a generic nature; therefore, its behavior across different sizes (8 × 8, 16 × 16, 32 × 32, 64 × 64) is examined. The platform of implementation is a medium range FPGA specifically selected to represent the average hardware prototyping device. In the end, an overview of the algorithm’s imprint on the device is presented alongside other approaches, which include both hard and soft computing techniques. Full article

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

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12 pages, 1985 KB

Open AccessEditor’s ChoiceArticle

IoT Framework for Measurement and Precision Agriculture: Predicting the Crop Using Machine Learning Algorithms

by Kalaiselvi Bakthavatchalam, Balaguru Karthik, Vijayan Thiruvengadam, Sriram Muthal, Deepa Jose, Ketan Kotecha and Vijayakumar Varadarajan

Technologies 2022, 10(1), 13; https://doi.org/10.3390/technologies10010013 - 20 Jan 2022

Cited by 106 | Viewed by 12416

Abstract

IoT architectures facilitate us to generate data for large and remote agriculture areas and the same can be utilized for Crop predictions using this machine learning algorithm. Recommendations are based on the following N, P, K, pH, Temperature, Humidity, and Rainfall these attributes [...] Read more.

IoT architectures facilitate us to generate data for large and remote agriculture areas and the same can be utilized for Crop predictions using this machine learning algorithm. Recommendations are based on the following N, P, K, pH, Temperature, Humidity, and Rainfall these attributes decide the crop to be recommended. The data set has 2200 instances and 8 attributes. Nearly 22 different crops are recommended for a different combination of 8 attributes. Using the supervised learning method, the optimum model is attained using selected machine learning algorithms in WEKA. The Machine learning algorithm selected for classifying is multilayer perceptron rules-based classifier JRip, and decision table classifier. The main objective of this case study is to end up with a model which predicts the high yield crop and precision agriculture. The proposed system modeling incorporates the trending technology, IoT, and Agriculture needy measurements. The performance assessed by the selected classifiers is 98.2273%, the Weighted average Receiver Operator Characteristics is 1 with the maximum time taken to build the model being 8.05 s. Full article

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15 pages, 782 KB

Open AccessEditor’s ChoiceArticle

Efficient Stochastic Computing FIR Filtering Using Sigma-Delta Modulated Signals

by Nikos Temenos, Anastasis Vlachos and Paul P. Sotiriadis

Technologies 2022, 10(1), 14; https://doi.org/10.3390/technologies10010014 - 20 Jan 2022

Cited by 7 | Viewed by 3380

Abstract

This work presents a soft-filtering digital signal processing architecture based on sigma-delta modulators and stochastic computing. A sigma-delta modulator converts the input high-resolution signal to a single-bit stream enabling filtering structures to be realized using stochastic computing’s negligible-area multipliers. Simulation in the spectral [...] Read more.

This work presents a soft-filtering digital signal processing architecture based on sigma-delta modulators and stochastic computing. A sigma-delta modulator converts the input high-resolution signal to a single-bit stream enabling filtering structures to be realized using stochastic computing’s negligible-area multipliers. Simulation in the spectral domain demonstrates the filter’s proper operation and its roll-off behavior, as well as the signal-to-noise ratio improvement using the sigma-delta modulator, compared to typical stochastic computing filter realizations. The proposed architecture’s hardware advantages are showcased with synthesis results for two FIR filters using FPGA and synopsys tools, while comparisons with standard stochastic computing-based hardware realizations, as well as with conventional binary ones, demonstrate its efficacy. Full article

(This article belongs to the Special Issue MOCAST 2021)

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15 pages, 332 KB

Open AccessEditor’s ChoiceReview

A Review of Efficient Real-Time Decision Making in the Internet of Things

by Kyoung-Don Kang

Technologies 2022, 10(1), 12; https://doi.org/10.3390/technologies10010012 - 19 Jan 2022

Cited by 13 | Viewed by 6392

Abstract

Emerging applications of IoT (the Internet of Things), such as smart transportation, health, and energy, are envisioned to greatly enhance the societal infrastructure and quality of life of individuals. In such innovative IoT applications, cost-efficient real-time decision-making is critical to facilitate, for example, [...] Read more.

Emerging applications of IoT (the Internet of Things), such as smart transportation, health, and energy, are envisioned to greatly enhance the societal infrastructure and quality of life of individuals. In such innovative IoT applications, cost-efficient real-time decision-making is critical to facilitate, for example, effective transportation management and healthcare. In this paper, we formally define real-time decision tasks in IoT, review cutting-edge approaches that aim to efficiently schedule real-time decision tasks to meet their timing and data freshness constraints, review state-of-the-art approaches for efficient sensor data analytics in IoT, and discuss future research directions. Full article

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

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17 pages, 4039 KB

Open AccessEditor’s ChoiceArticle

Assistive Technologies for Supporting the Wellbeing of Older Adults

by Ioanna Dratsiou, Annita Varella, Evangelia Romanopoulou, Oscar Villacañas, Sara Cooper, Pavlos Isaris, Manex Serras, Luis Unzueta, Tatiana Silva, Alexia Zurkuhlen, Malcolm MacLachlan and Panagiotis D. Bamidis

Technologies 2022, 10(1), 8; https://doi.org/10.3390/technologies10010008 - 14 Jan 2022

Cited by 15 | Viewed by 6881

Abstract

As people age, they are more likely to develop multiple chronic diseases and experience a decline in some of their physical and cognitive functions, leading to the decrease in their ability to live independently. Innovative technology-based interventions tailored to older adults’ functional levels [...] Read more.

As people age, they are more likely to develop multiple chronic diseases and experience a decline in some of their physical and cognitive functions, leading to the decrease in their ability to live independently. Innovative technology-based interventions tailored to older adults’ functional levels and focused on healthy lifestyles are considered imperative. This work proposed a framework of active and healthy ageing through the integration of a broad spectrum of digital solutions into an open Pan-European technological platform in the context of the SHAPES project, an EU-funded innovation action. In conclusion, the SHAPES project can potentially engage older adults in a holistic technological ecosystem and, therefore, facilitate the maintenance of a high-quality standard of life. Full article

(This article belongs to the Section Assistive Technologies)

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22 pages, 13186 KB

Open AccessEditor’s ChoiceReview

3D Scanning/Printing: A Technological Stride in Sculpture

by G.-Fivos Sargentis, Evangelia Frangedaki, Michalis Chiotinis, Demetris Koutsoyiannis, Stephanos Camarinopoulos, Alexios Camarinopoulos and Nikos D. Lagaros

Technologies 2022, 10(1), 9; https://doi.org/10.3390/technologies10010009 - 14 Jan 2022

Cited by 23 | Viewed by 9940

Abstract

The creation of innovative tools, objects and artifacts that introduce abstract ideas in the real world is a necessary step for the evolution process and characterize the creative capacity of civilization. Sculpture is based on the available technology for its creation process and [...] Read more.

The creation of innovative tools, objects and artifacts that introduce abstract ideas in the real world is a necessary step for the evolution process and characterize the creative capacity of civilization. Sculpture is based on the available technology for its creation process and is strongly related to the level of technological sophistication of each era. This paper analyzes the evolution of basic sculpture techniques (carving, lost-wax casting and 3D scanning/printing), and their importance as a culture footprint. It also presents and evaluates the added creative capacities of each technological step and the different methods of 3D scanning/printing concerning sculpture. It is also an attempt to define the term “material poetics”, which is connected to sculpture artifacts. We conclude that 3D scanning/printing is an important sign of civilization, although artifacts lose a part of material poetics with additive manufacturing. Subsequently, there are various causes of the destruction of sculptures, leaving a hole in the history of art. Finally, this paper showcases the importance of 3D scanning/printing in salvaging cultural heritage, as it has radically altered the way we “backup” objects. Full article

(This article belongs to the Section Manufacturing Technology)

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10 pages, 4927 KB

Open AccessEditor’s ChoiceArticle

A Simulated Environment for Robot Vision Experiments

by Christos Sevastopoulos, Stasinos Konstantopoulos, Keshav Balaji, Mohammad Zaki Zadeh and Fillia Makedon

Technologies 2022, 10(1), 7; https://doi.org/10.3390/technologies10010007 - 12 Jan 2022

Cited by 6 | Viewed by 3659

Abstract

Training on simulation data has proven invaluable in applying machine learning in robotics. However, when looking at robot vision in particular, simulated images cannot be directly used no matter how realistic the image rendering is, as many physical parameters (temperature, humidity, wear-and-tear in [...] Read more.

Training on simulation data has proven invaluable in applying machine learning in robotics. However, when looking at robot vision in particular, simulated images cannot be directly used no matter how realistic the image rendering is, as many physical parameters (temperature, humidity, wear-and-tear in time) vary and affect texture and lighting in ways that cannot be encoded in the simulation. In this article we propose a different approach for extracting value from simulated environments: although neither of the trained models can be used nor are any evaluation scores expected to be the same on simulated and physical data, the conclusions drawn from simulated experiments might be valid. If this is the case, then simulated environments can be used in early-stage experimentation with different network architectures and features. This will expedite the early development phase before moving to (harder to conduct) physical experiments in order to evaluate the most promising approaches. In order to test this idea we created two simulated environments for the Unity engine, acquired simulated visual datasets, and used them to reproduce experiments originally carried out in a physical environment. The comparison of the conclusions drawn in the physical and the simulated experiments is promising regarding the validity of our approach. Full article

(This article belongs to the Collection Selected Papers from the PETRA Conference Series)

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11 pages, 2094 KB

Open AccessEditor’s ChoiceArticle

Traffic Flow Prediction for Smart Traffic Lights Using Machine Learning Algorithms

by Alfonso Navarro-Espinoza, Oscar Roberto López-Bonilla, Enrique Efrén García-Guerrero, Esteban Tlelo-Cuautle, Didier López-Mancilla, Carlos Hernández-Mejía and Everardo Inzunza-González

Technologies 2022, 10(1), 5; https://doi.org/10.3390/technologies10010005 - 10 Jan 2022

Cited by 98 | Viewed by 26988

Abstract

Nowadays, many cities have problems with traffic congestion at certain peak hours, which produces more pollution, noise and stress for citizens. Neural networks (NN) and machine-learning (ML) approaches are increasingly used to solve real-world problems, overcoming analytical and statistical methods, due to their [...] Read more.

Nowadays, many cities have problems with traffic congestion at certain peak hours, which produces more pollution, noise and stress for citizens. Neural networks (NN) and machine-learning (ML) approaches are increasingly used to solve real-world problems, overcoming analytical and statistical methods, due to their ability to deal with dynamic behavior over time and with a large number of parameters in massive data. In this paper, machine-learning (ML) and deep-learning (DL) algorithms are proposed for predicting traffic flow at an intersection, thus laying the groundwork for adaptive traffic control, either by remote control of traffic lights or by applying an algorithm that adjusts the timing according to the predicted flow. Therefore, this work only focuses on traffic flow prediction. Two public datasets are used to train, validate and test the proposed ML and DL models. The first one contains the number of vehicles sampled every five minutes at six intersections for 56 days using different sensors. For this research, four of the six intersections are used to train the ML and DL models. The Multilayer Perceptron Neural Network (MLP-NN) obtained better results (R-Squared and EV score of 0.93) and took less training time, followed closely by Gradient Boosting then Recurrent Neural Networks (RNNs), with good metrics results but the longer training time, and finally Random Forest, Linear Regression and Stochastic Gradient. All ML and DL algorithms scored good performance metrics, indicating that they are feasible for implementation on smart traffic light controllers. Full article

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

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16 pages, 2920 KB

Open AccessEditor’s ChoiceArticle

A Simplified Tantalum Oxide Memristor Model, Parameters Estimation and Application in Memory Crossbars

by Valeri Mladenov and Stoyan Kirilov

Technologies 2022, 10(1), 6; https://doi.org/10.3390/technologies10010006 - 10 Jan 2022

Cited by 6 | Viewed by 4609

Abstract

In this paper, an improved and simplified modification of a tantalum oxide memristor model is presented. The proposed model is applied and analyzed in hybrid and passive memory crossbars in LTSPICE environment and is based on the standard Ta₂O₅ memristor [...] Read more.

In this paper, an improved and simplified modification of a tantalum oxide memristor model is presented. The proposed model is applied and analyzed in hybrid and passive memory crossbars in LTSPICE environment and is based on the standard Ta₂O₅ memristor model proposed by Hewlett–Packard. The discussed modified model has several main enhancements—inclusion of a simplified window function, improvement of its effectiveness by the use of a simple expression for the i–v relationship, and replacement of the classical Heaviside step function with a differentiable and flat step-like function. The optimal values of coefficients of the tantalum oxide memristor model are derived by comparison of experimental current–voltage relationships and by using a procedure for parameter estimation. A simplified LTSPICE library model, correspondent to the analyzed tantalum oxide memristor, is created in accordance with the considered mathematical model. The improved and altered Ta₂O₅ memristor model is tested and simulated in hybrid and passive memory crossbars for a state near to a hard-switching operation. After a comparison of several of the best existing memristor models, the main pros of the proposed memristor model are highlighted—its improved implementation, better operating rate, and good switching properties. Full article

(This article belongs to the Special Issue MOCAST 2021)

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12 pages, 944 KB

Open AccessEditor’s ChoiceArticle

Artwork Style Recognition Using Vision Transformers and MLP Mixer

by Lazaros Alexios Iliadis, Spyridon Nikolaidis, Panagiotis Sarigiannidis, Shaohua Wan and Sotirios K. Goudos

Technologies 2022, 10(1), 2; https://doi.org/10.3390/technologies10010002 - 28 Dec 2021

Cited by 10 | Viewed by 5107

Abstract

Through the extensive study of transformers, attention mechanisms have emerged as potentially more powerful than sequential recurrent processing and convolution. In this realm, Vision Transformers have gained much research interest, since their architecture changes the dominant paradigm in Computer Vision. An interesting and [...] Read more.

Through the extensive study of transformers, attention mechanisms have emerged as potentially more powerful than sequential recurrent processing and convolution. In this realm, Vision Transformers have gained much research interest, since their architecture changes the dominant paradigm in Computer Vision. An interesting and difficult task in this field is the classification of artwork styles, since the artistic style of a painting is a descriptor that captures rich information about the painting. In this paper, two different Deep Learning architectures—Vision Transformer and MLP Mixer (Multi-layer Perceptron Mixer)—are trained from scratch in the task of artwork style recognition, achieving over 39% prediction accuracy for 21 style classes on the WikiArt paintings dataset. In addition, a comparative study between the most common optimizers was conducted obtaining useful information for future studies. Full article

(This article belongs to the Special Issue MOCAST 2021)

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10 pages, 2049 KB

Open AccessEditor’s ChoiceArticle

Encoding Two-Qubit Logical States and Quantum Operations Using the Energy States of a Physical System

by Dimitrios Ntalaperas and Nikos Konofaos

Technologies 2022, 10(1), 1; https://doi.org/10.3390/technologies10010001 - 22 Dec 2021

Cited by 7 | Viewed by 3965

Abstract

In this paper, we introduce a novel coding scheme, which allows single quantum systems to encode multi-qubit registers. This allows for more efficient use of resources and the economy in designing quantum systems. The scheme is based on the notion of encoding logical [...] Read more.

In this paper, we introduce a novel coding scheme, which allows single quantum systems to encode multi-qubit registers. This allows for more efficient use of resources and the economy in designing quantum systems. The scheme is based on the notion of encoding logical quantum states using the charge degree of freedom of the discrete energy spectrum that is formed by introducing impurities in a semiconductor material. We propose a mechanism of performing single qubit operations and controlled two-qubit operations, providing a mechanism for achieving these operations using appropriate pulses generated by Rabi oscillations. The above architecture is simulated using the Armonk single qubit quantum computer of IBM to encode two logical quantum states into the energy states of Armonk’s qubit and using custom pulses to perform one and two-qubit quantum operations. Full article

(This article belongs to the Special Issue MOCAST 2021)

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17 pages, 4910 KB

Open AccessEditor’s ChoiceArticle

Efficient Sandstorm Image Enhancement Using the Normalized Eigenvalue and Adaptive Dark Channel Prior

by Ho Sang Lee

Technologies 2021, 9(4), 101; https://doi.org/10.3390/technologies9040101 - 17 Dec 2021

Cited by 7 | Viewed by 2793

Abstract

A sandstorm image has features similar to those of a hazy image with regard to the obtaining process. However, the difference between a sand dust image and a hazy image is the color channel balance. In general, a hazy image has no color [...] Read more.

A sandstorm image has features similar to those of a hazy image with regard to the obtaining process. However, the difference between a sand dust image and a hazy image is the color channel balance. In general, a hazy image has no color cast and has a balanced color channel with fog and dust. However, a sand dust image has a yellowish or reddish color cast due to sand particles, which cause the color channels to degrade. When the sand dust image is enhanced without color channel compensation, the improved image also has a new color cast. Therefore, to enhance the sandstorm image naturally without a color cast, the color channel compensation step is needed. Thus, to balance the degraded color channel, this paper proposes the color balance method using each color channel’s eigenvalue. The eigenvalue reflects the image’s features. The degraded image and the undegraded image have different eigenvalues on each color channel. Therefore, if using the eigenvalue of each color channel, the degraded image can be improved naturally and balanced. Due to the color-balanced image having the same features as the hazy image, this work, to improve the hazy image, uses dehazing methods such as the dark channel prior (DCP) method. However, because the ordinary DCP method has weak points, this work proposes a compensated dark channel prior and names it the adaptive DCP (ADCP) method. The proposed method is objectively and subjectively superior to existing methods when applied to various images. Full article

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11 pages, 1148 KB

Open AccessEditor’s ChoiceArticle

Functional Model of a Self-Driving Car Control System

by Kirill Sviatov, Nadejda Yarushkina, Daniil Kanin, Ivan Rubtcov, Roman Jitkov, Vladislav Mikhailov and Pavel Kanin

Technologies 2021, 9(4), 100; https://doi.org/10.3390/technologies9040100 - 10 Dec 2021

Cited by 8 | Viewed by 5743

Abstract

The article describes a structural and functional model of a self-driving car control system, which generates a wide class of mathematical problems. Currently, control systems for self-driving cars are considered at several levels of abstraction and implementation: Mechanics, electronics, perception, scene recognition, control, [...] Read more.

The article describes a structural and functional model of a self-driving car control system, which generates a wide class of mathematical problems. Currently, control systems for self-driving cars are considered at several levels of abstraction and implementation: Mechanics, electronics, perception, scene recognition, control, security, integration of all subsystems into a solid system. Modern research often considers particular problems to be solved for each of the levels separately. In this paper, a parameterized model of the integration of individual components into a complex control system for a self-driving car is considered. Such a model simplifies the design and development of self-driving control systems with configurable automation tools, taking into account the specifics of the solving problem. The parameterized model can be used for CAD design in the field of self-driving car development. A full cycle of development of a control system for a self-driving truck was implemented, which was rub in the “Robocross 2021” competition. The software solution was tested on more than 40 launches of a self-driving truck. Parameterization made it possible to speed up the development of the control system, expressed in man-hours, by 1.5 times compared to the experience of the authors of the article who participated in the same competition in 2018 and 2019. The proposed parameterization was used in the development of individual CAD elements described in this article. Additionally, the implementation of specific modules and functions is a field for experimental research. Full article

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

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20 pages, 7877 KB

Open AccessEditor’s ChoiceArticle

On the Part Quality, Process Parameters and In-Die Pressures in Indirect Squeeze Casting

by Anders E. W. Jarfors, Jie Zhou, Andong Du, Jinchuan Zheng and Gegang Yu

Technologies 2021, 9(4), 95; https://doi.org/10.3390/technologies9040095 - 2 Dec 2021

Cited by 2 | Viewed by 3116

Abstract

Squeeze casting is a process that can produce the highest quality castings. In the current study, the effect of the process settings and the in-die conditions on rejection rates is studied through a full-scale experimental study. Factors affecting the as-cast part quality were [...] Read more.

Squeeze casting is a process that can produce the highest quality castings. In the current study, the effect of the process settings and the in-die conditions on rejection rates is studied through a full-scale experimental study. Factors affecting the as-cast part quality were investigated in the current study from two different viewpoints. The first part of the study was to investigate the influence of the process settings on the part rejection rate, and the second was to understand the conditions in the die and the effects on the part rejection rate to understand better the reasons and sensitivity of the squeeze casting process. Full article

(This article belongs to the Section Manufacturing Technology)

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15 pages, 29424 KB

Open AccessEditor’s ChoiceArticle

A Deep Learning-Based Dirt Detection Computer Vision System for Floor-Cleaning Robots with Improved Data Collection

by Daniel Canedo, Pedro Fonseca, Petia Georgieva and António J. R. Neves

Technologies 2021, 9(4), 94; https://doi.org/10.3390/technologies9040094 - 1 Dec 2021

Cited by 16 | Viewed by 12364

Abstract

Floor-cleaning robots are becoming increasingly more sophisticated over time and with the addition of digital cameras supported by a robust vision system they become more autonomous, both in terms of their navigation skills but also in their capabilities of analyzing the surrounding environment. [...] Read more.

Floor-cleaning robots are becoming increasingly more sophisticated over time and with the addition of digital cameras supported by a robust vision system they become more autonomous, both in terms of their navigation skills but also in their capabilities of analyzing the surrounding environment. This document proposes a vision system based on the YOLOv5 framework for detecting dirty spots on the floor. The purpose of such a vision system is to save energy and resources, since the cleaning system of the robot will be activated only when a dirty spot is detected and the quantity of resources will vary according to the dirty area. In this context, false positives are highly undesirable. On the other hand, false negatives will lead to a poor cleaning performance of the robot. For this reason, a synthetic data generator found in the literature was improved and adapted for this work to tackle the lack of real data in this area. This synthetic data generator allows for large datasets with numerous samples of floors and dirty spots. A novel approach in selecting floor images for the training dataset is proposed. In this approach, the floor is segmented from other objects in the image such that dirty spots are only generated on the floor and do not overlap those objects. This helps the models to distinguish between dirty spots and objects in the image, which reduces the number of false positives. Furthermore, a relevant dataset of the Automation and Control Institute (ACIN) was found to be partially labelled. Consequently, this dataset was annotated from scratch, tripling the number of labelled images and correcting some poor annotations from the original labels. Finally, this document shows the process of generating synthetic data which is used for training YOLOv5 models. These models were tested on a real dataset (ACIN) and the best model attained a mean average precision (mAP) of 0.874 for detecting solid dirt. These results further prove that our proposal is able to use synthetic data for the training step and effectively detect dirt on real data. According to our knowledge, there are no previous works reporting the use of YOLOv5 models in this application. Full article

(This article belongs to the Special Issue Smart Systems (SmaSys2021))

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23 pages, 9116 KB

Open AccessEditor’s ChoiceReview

Critical Overview of Visual Tracking with Kernel Correlation Filter

by Srishti Yadav and Shahram Payandeh

Technologies 2021, 9(4), 93; https://doi.org/10.3390/technologies9040093 - 30 Nov 2021

Cited by 8 | Viewed by 6827

Abstract

With the development of new methodologies for faster training on datasets, there is a need to provide an in-depth explanation of the workings of such methods. This paper attempts to provide an understanding for one such correlation filter-based tracking technology, Kernelized Correlation Filter [...] Read more.

With the development of new methodologies for faster training on datasets, there is a need to provide an in-depth explanation of the workings of such methods. This paper attempts to provide an understanding for one such correlation filter-based tracking technology, Kernelized Correlation Filter (KCF), which uses implicit properties of tracked images (circulant matrices) for training and tracking in real-time. It is unlike deep learning, which is data intensive. KCF uses implicit dynamic properties of the scene and movements of image patches to form an efficient representation based on the circulant structure for further processing, using properties such as diagonalizing in the Fourier domain. The computational efficiency of KCF, which makes it ideal for low-power heterogeneous computational processing technologies, lies in its ability to compute data in high-dimensional feature space without explicitly invoking the computation on this space. Despite its strong practical potential in visual tracking, there is a need for an in-depth critical understanding of the method and its performance, which this paper aims to provide. Here we present a survey of KCF and its method along with an experimental study that highlights its novel approach and some of the future challenges associated with this method through observations on standard performance metrics in an effort to make the algorithm easy to investigate. It further compares the method against the current public benchmarks such as SOTA on OTB-50, VOT-2015, and VOT-2019. We observe that KCF is a simple-to-understand tracking algorithm that does well on popular benchmarks and has potential for further improvement. The paper aims to provide researchers a base for understanding and comparing KCF with other tracking technologies to explore the possibility of an improved KCF tracker. Full article

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

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17 pages, 511 KB

Open AccessEditor’s ChoiceArticle

Incremental Lagrangian Relaxation Based Discrete Gate Sizing and Threshold Voltage Assignment

by Dimitrios Mangiras and Giorgos Dimitrakopoulos

Technologies 2021, 9(4), 92; https://doi.org/10.3390/technologies9040092 - 26 Nov 2021

Cited by 3 | Viewed by 3236

Abstract

Timing closure remains one of the most critical challenges of a physical synthesis flow, especially when the design operates under multiple operating conditions. Even if timing is almost closed at the end of the flow, last-mile placement and routing congestion optimizations may introduce [...] Read more.

Timing closure remains one of the most critical challenges of a physical synthesis flow, especially when the design operates under multiple operating conditions. Even if timing is almost closed at the end of the flow, last-mile placement and routing congestion optimizations may introduce new timing violations. Correcting such violations needs minimally disruptive techniques such as threshold voltage reassignment and gate sizing that affect only marginally the placement and routing of the almost finalized design. To this end, we transform a powerful Lagrangian-relaxation-based optimizer, used for global timing optimization early in the design flow, into a practical incremental timing optimizer that corrects small timing violations with fast runtime and without increasing the area/power of the design. The proposed approach was applied to already optimized designs of the ISPD 2013 benchmarks assuming that they experience new timing violations due to local wire rerouting. Experimental results show that in single corner designs, timing is improved by more than 36% on average, using 45% less runtime. Correspondingly, in a multicorner context, timing is improved by 39% when compared to the fully-fledged version of the timing optimizer. Full article

(This article belongs to the Special Issue MOCAST 2021)

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17 pages, 5585 KB

Open AccessEditor’s ChoiceArticle

An Interactive Task Conditioning System Featuring Personal Comfort Models and Non-Intrusive Sensing Techniques: A Field Study in Shanghai

by Siliang Lu and Erica Cochran Hameen

Technologies 2021, 9(4), 90; https://doi.org/10.3390/technologies9040090 - 21 Nov 2021

Cited by 4 | Viewed by 3394

Abstract

Heating, ventilation and air-conditioning (HVAC) systems play a key role in shaping office environments. However, open-plan office buildings nowadays are also faced with problems like unnecessary energy waste and an unsatisfactory shared indoor thermal environment. Therefore, it is significant to develop a new [...] Read more.

Heating, ventilation and air-conditioning (HVAC) systems play a key role in shaping office environments. However, open-plan office buildings nowadays are also faced with problems like unnecessary energy waste and an unsatisfactory shared indoor thermal environment. Therefore, it is significant to develop a new paradigm of an HVAC system framework so that everyone could work under their preferred thermal environment and the system can achieve higher energy efficiency such as task ambient conditioning system (TAC). However, current task conditioning systems are not responsive to personal thermal comfort dynamically. Hence, this research aims to develop a dynamic task conditioning system featuring personal thermal comfort models with machine learning and the wireless non-intrusive sensing system. In order to evaluate the proposed task conditioning system performance, a field study was conducted in a shared office space in Shanghai from July to August. As a result, personal thermal comfort models with indoor air temperature, relative humidity and cheek (side face) skin temperature have better performances than baseline models with indoor air temperature only. Moreover, compared to personal thermal satisfaction predictions, 90% of subjects have better performances in thermal sensation predictions. Therefore, personal thermal comfort models could be further implemented into the task conditioning control of TAC systems. Full article

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

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14 pages, 3803 KB

Open AccessEditor’s ChoiceArticle

Electrospun PVP/TiO₂ Nanofibers for Filtration and Possible Protection from Various Viruses like COVID-19

by Ankush Sharma, Dinesh Pathak, Deepak S. Patil, Naresh Dhiman, Viplove Bhullar and Aman Mahajan

Technologies 2021, 9(4), 89; https://doi.org/10.3390/technologies9040089 - 19 Nov 2021

Cited by 19 | Viewed by 6067

Abstract

In this study, TiO₂ nanofibers were prepared with Polyvinylpyrrolidone (PVP) polymer using sol-gel method via electrospinning technique. Owing to the advantages of small fiber diameter, tunable porosity, low cost, large surface to volume ratio, structure control, light-weight, and less energy consumption, electrospun [...] Read more.

In this study, TiO₂ nanofibers were prepared with Polyvinylpyrrolidone (PVP) polymer using sol-gel method via electrospinning technique. Owing to the advantages of small fiber diameter, tunable porosity, low cost, large surface to volume ratio, structure control, light-weight, and less energy consumption, electrospun nanofibers are evolving as an adaptable material with a number of applications, in this case for filtration and environmental/virus protection. Different samples of TiO₂/PVP nanofibers have been prepared by changing the parameters to achieve the best result. As the polymer concentration was increased from 6 to 8 wt.% of PVP, diameter of the resultant fibers was seen to be increased, implying decrease in the pore-size of the fibers up to 1.4 nm. Surface morphology has been checked via Scanning Electron Microscope (SEM) images. Crystalline nature has been analyzed by X-ray Crystallography. Using the Bruanauer-Emmett-Teller (BET) test, surface area and porosity has been checked for the suitable application. The synthesized TiO₂/PVP nanofibers have tremendous practical potentials in filtration and environmental remediation applications. Full article

(This article belongs to the Special Issue Glass, Glass-Ceramics, and Ceramics for Nuclear Waste Immobilization and Other Environmental Applications)

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13 pages, 290 KB

Open AccessEditor’s ChoiceArticle

Smart Additive Manufacturing: The Path to the Digital Value Chain

by Nuno Araújo, Vânia Pacheco and Leonardo Costa

Technologies 2021, 9(4), 88; https://doi.org/10.3390/technologies9040088 - 17 Nov 2021

Cited by 24 | Viewed by 7430

Abstract

The aim of this article is to characterize the impacts of Smart Additive Manufacturing (SAM) on industrial production, digital supply chains (DSCs) and corresponding digital value chains (DVCs), logistics and inventory management. The method used consists of a critical review of the literature, [...] Read more.

The aim of this article is to characterize the impacts of Smart Additive Manufacturing (SAM) on industrial production, digital supply chains (DSCs) and corresponding digital value chains (DVCs), logistics and inventory management. The method used consists of a critical review of the literature, enriched by the authors’ field experience. The results show that digital transformation of manufacturing is affecting business models, from resource acquisition to the end user. Smart manufacturing is considered a successful improvement introduced by Industry 4.0. Additive Manufacturing (AM) plays a crucial role in this digital transformation, changing the way manufacturers think about the entire lifecycle of a product. SAM combines AM in a smart factory environment. SAM reduces the complexity of DSCs and contributes to a more flexible approach to logistics and inventory management. It has also spurred the growth and popularization of customized mass production as well as decentralized manufacturing, rapid prototyping, unprecedented flexibility in product design, production and delivery, and resource efficiency and sustainability. SAM technology impacts all five Fletcher’s stages in DVCs. However, the need for clear definitions and regulations on 3D printing of digital files and their reproduction, as well as product health, safety, and integrity issues, cannot be ignored. Furthermore, investment in this technology is still expensive and can be prohibitive for many companies, namely SMEs. Full article

(This article belongs to the Special Issue 3D Printing and Additive Manufacturing: Principles and Applications)

16 pages, 1360 KB

Open AccessEditor’s ChoiceArticle

Visual Robotic Perception System with Incremental Learning for Child–Robot Interaction Scenarios

by Niki Efthymiou, Panagiotis Paraskevas Filntisis, Gerasimos Potamianos and Petros Maragos

Technologies 2021, 9(4), 86; https://doi.org/10.3390/technologies9040086 - 15 Nov 2021

Cited by 5 | Viewed by 4201

Abstract

This paper proposes a novel lightweight visual perception system with Incremental Learning (IL), tailored to child–robot interaction scenarios. Specifically, this encompasses both an action and emotion recognition module, with the former wrapped around an IL system, allowing novel actions to be easily added. [...] Read more.

This paper proposes a novel lightweight visual perception system with Incremental Learning (IL), tailored to child–robot interaction scenarios. Specifically, this encompasses both an action and emotion recognition module, with the former wrapped around an IL system, allowing novel actions to be easily added. This IL system enables the tutor aspiring to use robotic agents in interaction scenarios to further customize the system according to children’s needs. We perform extensive evaluations of the developed modules, achieving state-of-the-art results on both the children’s action BabyRobot dataset and the children’s emotion EmoReact dataset. Finally, we demonstrate the robustness and effectiveness of the IL system for action recognition by conducting a thorough experimental analysis for various conditions and parameters. Full article

(This article belongs to the Collection Selected Papers from the PETRA Conference Series)

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21 pages, 4793 KB

Open AccessEditor’s ChoiceArticle

A Novel In Vitro Simulator to Investigate Promotion of Reconstruction of Damaged Neuronal Cell Colony Differentiated from iPS Cells with the Aid of Micro Dynamic Stimulation

by Tadashi Kosawada, Taku Kitsunai, Zhonggang Feng and Kaoru Goto

Technologies 2021, 9(4), 83; https://doi.org/10.3390/technologies9040083 - 4 Nov 2021

Viewed by 3060

Abstract

Neuronal cells are equipped with the function of a sensor that senses stimulation and elongates neurites to connect nearby neuronal cells in forming a neuronal network, as they are generally said to be hard to recover from physical damage, such as in the [...] Read more.

Neuronal cells are equipped with the function of a sensor that senses stimulation and elongates neurites to connect nearby neuronal cells in forming a neuronal network, as they are generally said to be hard to recover from physical damage, such as in the case of a spinal cord injury. Therefore, in this study, a novel in vitro simulator in which micro dynamic stimulations are applied to a damaged neuronal cell colony artificially is proposed to investigate the possibility of promoting the reconstruction of damaged neuronal cells on a colony basis. A neuronal cell colony differentiated from iPS cells is physically damaged by cutting off treatment, and micro dynamic stimulations are applied to the colony by utilizing a developed mini-vibration table system. NeuroFluor NeuO is used to establish a method for fluorescent staining of the living neuronal cells, and morphologies of the reconstructing neurons are analysed, revealing a relationship between the stimulation and the reconstructing process of the damaged neurons. It is found that significant differences are observed in the reconstructing efficiency between the statically cultured damaged neuronal cell colony and the dynamically stimulated one. The results suggest that applying appropriate micro dynamic stimulations is a promising approach to promote the reconstruction of a damaged neuronal cell colony. Full article

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22 pages, 501 KB

Open AccessEditor’s ChoiceArticle

Multiclass Confusion Matrix Reduction Method and Its Application on Net Promoter Score Classification Problem

by Ioannis Markoulidakis, Ioannis Rallis, Ioannis Georgoulas, George Kopsiaftis, Anastasios Doulamis and Nikolaos Doulamis

Technologies 2021, 9(4), 81; https://doi.org/10.3390/technologies9040081 - 2 Nov 2021

Cited by 150 | Viewed by 20377

Abstract

The current paper presents a novel method for reducing a multiclass confusion matrix into a

2 \times 2

version enabling the exploitation of the relevant performance metrics and methods such as the receiver operating characteristic and area under the curve for the assessment [...] Read more.

The current paper presents a novel method for reducing a multiclass confusion matrix into a

2 \times 2

version enabling the exploitation of the relevant performance metrics and methods such as the receiver operating characteristic and area under the curve for the assessment of different classification algorithms. The reduction method is based on class grouping and leads to a special type of matrix called the reduced confusion matrix. The developed method is then exploited for the assessment of state of the art machine learning algorithms applied on the net promoter score classification problem in the field of customer experience analytics indicating the value of the proposed method in real world classification problems. Full article

(This article belongs to the Collection Selected Papers from the PETRA Conference Series)

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26 pages, 2169 KB

Open AccessEditor’s ChoiceReview

3D Printing Polymeric Materials for Robots with Embedded Systems

by Ray Noel Medina Delda, Rex Balisalisa Basuel, Rodel Peralta Hacla, Dan William Carpiano Martinez, John-John Cabibihan and John Ryan Cortez Dizon

Technologies 2021, 9(4), 82; https://doi.org/10.3390/technologies9040082 - 2 Nov 2021

Cited by 32 | Viewed by 10587

Abstract

The fabrication of robots and their embedded systems is challenging due to the complexity of the interacting components. The integration of additive manufacturing (AM) to robotics has made advancements in robotics manufacturing through sophisticated and state-of-the-art AM technologies and materials. With the emergence [...] Read more.

The fabrication of robots and their embedded systems is challenging due to the complexity of the interacting components. The integration of additive manufacturing (AM) to robotics has made advancements in robotics manufacturing through sophisticated and state-of-the-art AM technologies and materials. With the emergence of 3D printing, 3D printing materials are also being considered and engineered for specific applications. This study reviews different 3D printing materials for 3D printing embedded robotics. Materials such as polyethylene glycol diacrylate (PEGDA), acrylonitrile butadiene styrene (ABS), flexible photopolymers, silicone, and elastomer-based materials were found to be the most used 3D printing materials due to their suitability for robotic applications. This review paper revealed that the key areas requiring more research are material formulations for improved mechanical properties, cost, and the inclusion of materials for specific applications. Future perspectives are also provided. Full article

(This article belongs to the Special Issue 3D Printing and Additive Manufacturing: Principles and Applications)

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10 pages, 497 KB

Open AccessEditor’s ChoiceArticle

Lifetime of Catalyst under Voltage Cycling in Polymer Electrolyte Fuel Cell Due to Platinum Oxidation and Dissolution

by Victor A. Kovtunenko and Larisa Karpenko-Jereb

Technologies 2021, 9(4), 80; https://doi.org/10.3390/technologies9040080 - 31 Oct 2021

Cited by 8 | Viewed by 3089

Abstract

The durability of a platinum catalyst in a polymer electrolyte membrane fuel cell is studied at various operating conditions with respect to the different electric potential difference (called voltage) applied in accelerated stress tests. The electrochemical reactions of Pt ion dissolution and Pt [...] Read more.

The durability of a platinum catalyst in a polymer electrolyte membrane fuel cell is studied at various operating conditions with respect to the different electric potential difference (called voltage) applied in accelerated stress tests. The electrochemical reactions of Pt ion dissolution and Pt oxide coverage of the catalyst lead to the degradation of platinum described by a one-dimensional Holby–Morgan model. The theoretical study of the underlying reaction–diffusion system with the nonlinear reactions is presented by numerical simulations which allow to predict a lifetime of the catalyst under applied voltage cycling. The computer simulation investigates how the Pt mass loss depends on the voltage slope and the upper potential level in cycles. Full article

(This article belongs to the Section Environmental Technology)

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13 pages, 4359 KB

Open AccessEditor’s ChoiceArticle

Robot Operations for Pine Tree Resin Collection

by Vladimir Gurau, Beau Ragland, Daniel Cox, Andrew Michaud and Lloyd Busby

Technologies 2021, 9(4), 79; https://doi.org/10.3390/technologies9040079 - 27 Oct 2021

Cited by 5 | Viewed by 4109

Abstract

A robotic technology consisting of an industrial robot mounted on an autonomous rover used to tap slash pine trees and collect their oleoresin for processing is introduced, and the technological challenges related to the robotic operations are discussed in detail. Unlike the case [...] Read more.

A robotic technology consisting of an industrial robot mounted on an autonomous rover used to tap slash pine trees and collect their oleoresin for processing is introduced, and the technological challenges related to the robotic operations are discussed in detail. Unlike the case of industrial automated manufacturing systems where the relative position between the tool and workpiece can be controlled within a few hundredths of a millimeter accuracy, when used in highly unstructured environments characteristic to forestry or agriculture, the positioning accuracy between the industrial robot and the target on which it operates can be much lower than the accuracy required for the operation of the industrial robot. The paper focuses on presenting the robotic operations necessary for drilling three converging boreholes in the pine tree, spraying the boreholes with chemicals, inserting a plastic tube with pre-attached collection bag in one borehole and inserting two plugs in other two boreholes. The challenges related to performing these robotic operations in conditions of large variations in the actual shape of the pine tree trunk and variations in the relative position between the robot and the pine tree after the autonomous vehicle positions itself in front of the tree are presented. The technical solutions used to address these challenges are also described. The strategies used to programmatically adjust the robot toolpath based on detection of the borehole entry points and on the measurement of the insertion force are presented. Full article

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

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18 pages, 4656 KB

Open AccessEditor’s ChoiceArticle

An Open-Source, Low-Cost Measurement System for Collecting Hydrometeorological Data in the Open Field

by Kenichi Tatsumi, Tomoya Yamazaki and Hirohiko Ishikawa

Technologies 2021, 9(4), 78; https://doi.org/10.3390/technologies9040078 - 22 Oct 2021

Cited by 2 | Viewed by 3724

Abstract

To realize precision agriculture at multiple locations in the field, a low-cost measurement system should be developed for easy collection of hydrometeorological data, such as temperature, moisture, and light. In this study, a compact and low-cost hydrometeorological measurement system with a simplified wire [...] Read more.

To realize precision agriculture at multiple locations in the field, a low-cost measurement system should be developed for easy collection of hydrometeorological data, such as temperature, moisture, and light. In this study, a compact and low-cost hydrometeorological measurement system with a simplified wire code, which is customizable according to the purpose of observation, was built using a circuit board that connects Arduino to the sensors, which was then implemented and analyzed. The developed system measures air and soil temperatures, soil water content, and photosynthetic photon flux density using a sensor connected to Arduino Uno and saves the continuous, high-temporal-resolution output to an SD card. The results obtained from continuous measurement showed that the data collected using this system was significantly better than those collected using commercially available equipment. Anyone can easily measure the weather environments by using this fully open, highly versatile, portable, and user-friendly system. This system can contribute to the growth and expansion of precision agriculture, field management, development of crop models, and laborsaving. It can also provide a global solution to ongoing agricultural issues and improve the efficiency of farming operations, particularly in developing and low-income countries. Full article

(This article belongs to the Topic Smart Technologies in Food Packaging and Sensors)

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33 pages, 2362 KB

Open AccessEditor’s ChoiceReview

A Review of 4IR/5IR Enabling Technologies and Their Linkage to Manufacturing Supply Chain

by Mokesioluwa Fanoro, Mladen Božanić and Saurabh Sinha

Technologies 2021, 9(4), 77; https://doi.org/10.3390/technologies9040077 - 21 Oct 2021

Cited by 32 | Viewed by 16630

Abstract

Over the last decade, manufacturing processes have undergone significant change. Most factory activities have been transformed through a set of features built into a smart manufacturing framework. The tools brought to bear by the fourth industrial revolution are critical enablers of such change [...] Read more.

Over the last decade, manufacturing processes have undergone significant change. Most factory activities have been transformed through a set of features built into a smart manufacturing framework. The tools brought to bear by the fourth industrial revolution are critical enablers of such change and progress. This review article describes the series of industrial revolutions and explores traditional manufacturing before presenting various enabling technologies. Insights are offered regarding traditional manufacturing lines where some enabling technologies have been included. The manufacturing supply chain is envisaged as enhancing the enabling technologies of Industry 4.0 through their integration. A systematic literature review is undertaken to evaluate each enabling technology and the manufacturing supply chain and to provide some theoretical synthesis. Similarly, obstacles are listed that must be overcome before a complete shift to smart manufacturing is possible. A brief discussion maps out how the fourth industrial revolution has led to novel manufacturing technologies. Likewise, a review of the fifth industrial revolution is given, and the justification for this development is presented. Full article

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10 pages, 7712 KB

Open AccessEditor’s ChoiceArticle

Heat Treatment Consideration in Structural Simulations of Machine Elements: Analysis of a Starter Clutch Barrel

by Domen Šeruga, Matija Kavčič, Jernej Klemenc and Marko Nagode

Technologies 2021, 9(4), 73; https://doi.org/10.3390/technologies9040073 - 9 Oct 2021

Viewed by 3267

Abstract

Consideration of heat treatment in simulations of structural components and its impact on predictions of behaviour during operation is analysed here. An automotive machine element with a complex geometry and dynamic load is analysed rather than a standard laboratory specimen under controlled conditions. [...] Read more.

Consideration of heat treatment in simulations of structural components and its impact on predictions of behaviour during operation is analysed here. An automotive machine element with a complex geometry and dynamic load is analysed rather than a standard laboratory specimen under controlled conditions. The heat treatment analysis of a starter clutch barrel has been performed in DANTE followed by a structural analysis in ANSYS 2019 R3 during operation simulating a load cycle due to the start of an internal combustion engine. The heat treatment simulation consisted of carburisation, quenching and tempering. First, the carbon content and its distribution have been simulated. Next, the hardness of the starter clutch barrel and its distribution have been analysed with respect to the carbon distribution and hardness-dependent material properties of the AISI/SAE 4142 steel. Finally, the stress field after the heat treatment and during the operation of the starter clutch barrel has been thoroughly evaluated and compared to the simulation without the consideration of the heat treatment. Results of the simulation show that the heat treatment introduces favourable compressive stresses at the critical location of the starter clutch barrel and reduces the effective amplitude of the equivalent stress during the operation. Furthermore, the results of the simulation prove that heat treatment should be considered already during the early stages of the R & D process as it can have a decisive effect on the operational behaviour of the structural component. Moreover, a non-consideration of the heat treatment can lead into erroneous conclusions regarding the suitability of machine elements. Full article

(This article belongs to the Section Manufacturing Technology)

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11 pages, 1148 KB

Open AccessFeature PaperEditor’s ChoiceReview

The Promise of Turning Induced Deformation Process for Synthesizing Magnesium Based Materials with Superior Mechanical Response

by Michael Johanes and Manoj Gupta

Technologies 2021, 9(4), 69; https://doi.org/10.3390/technologies9040069 - 22 Sep 2021

Cited by 4 | Viewed by 2607

Abstract

In recent times, an alternative synthesis pathway involving severe plastic deformation for Mg-based materials has been explored involving the generation of turnings according to a set of machining parameters and cold compaction into billets followed by hot extrusion. This is known as the [...] Read more.

In recent times, an alternative synthesis pathway involving severe plastic deformation for Mg-based materials has been explored involving the generation of turnings according to a set of machining parameters and cold compaction into billets followed by hot extrusion. This is known as the turning induced deformation (TID) method and has shown potential to alter the properties of resulting Mg-based materials for the better, not to mention economic benefits arising from this processing method. This work summarizes exploratory efforts involving this method for synthesis of Mg-based materials. The TID method resulted in overall superior properties compared to conventional processing methods, while two distinct parameters (high depth of cut and low cutting speed) were found to have significant positive influence on the final material properties, and as such are considered to be suitable basis on which further exploratory work in this field may be conducted. Full article

(This article belongs to the Special Issue Commemorative Issue in Honor of Prof. Dr. Manoj Gupta on the Occasion of 60th Birthday)

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18 pages, 3785 KB

Open AccessEditor’s ChoiceArticle

Open-Source Script for Design and 3D Printing of Porous Structures for Soil Science

by Romain Bedell, Alaa Hassan, Anne-Julie Tinet, Javier Arrieta-Escobar, Delphine Derrien, Marie-France Dignac, Vincent Boly, Stéphanie Ouvrard and Joshua M. Pearce

Technologies 2021, 9(3), 67; https://doi.org/10.3390/technologies9030067 - 15 Sep 2021

Cited by 2 | Viewed by 6834

Abstract

Three-dimensional (3D) printing in soil science is relatively rare but offers promising directions for research. Having 3D-printed soil samples will help academics and researchers conduct experiments in a reproducible and participatory research network and gain a better understanding of the studied soil parameters. [...] Read more.

Three-dimensional (3D) printing in soil science is relatively rare but offers promising directions for research. Having 3D-printed soil samples will help academics and researchers conduct experiments in a reproducible and participatory research network and gain a better understanding of the studied soil parameters. One of the most important challenges in utilizing 3D printing techniques for soil modeling is the manufacturing of a soil structure. Until now, the most widespread method for printing porous soil structures is based on scanning a real sample via X-ray tomography. The aim of this paper is to design a porous soil structure based on mathematical models rather than on samples themselves. This can allow soil scientists to design and parameterize their samples according to their desired experiments. An open-source toolchain is developed using a Lua script, in the IceSL slicer, with graphical user interface to enable researchers to create and configure their digital soil models, called monoliths, without using meshing algorithms or STL files which reduce the resolution of the model. Examples of monoliths are 3D-printed in polylactic acid using fused filament fabrication technology with a layer thickness of 0.20, 0.12, and 0.08 mm. The images generated from the digital model slicing are analyzed using open-source ImageJ software to obtain information about internal geometrical shape, porosity, tortuosity, grain size distribution, and hydraulic conductivities. The results show that the developed script enables designing reproducible numerical models that imitate soil structures with defined pore and grain sizes in a range between coarse sand (from 1 mm diameter) to fine gravel (up to 12 mm diameter). Full article

(This article belongs to the Special Issue Open Source Agriculture Technology)

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12 pages, 4449 KB

Open AccessFeature PaperEditor’s ChoiceArticle

Design, Construction and Tests of a Low-Cost Myoelectric Thumb

by Murat Ayvali, Inge Wickenkamp and Andrea Ehrmann

Technologies 2021, 9(3), 63; https://doi.org/10.3390/technologies9030063 - 3 Sep 2021

Cited by 4 | Viewed by 6038

Abstract

Myoelectric signals can be used to control prostheses or exoskeletons as well as robots, i.e., devices assisting the user or replacing a missing part of the body. A typical application of myoelectric prostheses is the human hand. Here, the development of a low-cost [...] Read more.

Myoelectric signals can be used to control prostheses or exoskeletons as well as robots, i.e., devices assisting the user or replacing a missing part of the body. A typical application of myoelectric prostheses is the human hand. Here, the development of a low-cost myoelectric thumb is described, which can either be used as an additional finger or as prosthesis. Combining 3D printing with inexpensive sensors, electrodes, and electronics, the recent project offers the possibility to produce an individualized myoelectric thumb at significantly lower costs than commercial myoelectric prostheses. Alternatively, a second thumb may be supportive for people with special manual tasks. These possibilities are discussed together with disadvantages of a second thumb and drawbacks of the low-cost solution in terms of mechanical properties and wearing comfort. The study shows that a low-cost customized myoelectric thumb can be produced in this way, but further research on controlling the thumb as well as improving motorization are necessarily to make it fully usable for daily tasks. Full article

(This article belongs to the Section Assistive Technologies)

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10 pages, 1695 KB

Open AccessEditor’s ChoiceCommunication

A Design Study of Orthotic Shoe Based on Pain Pressure Measurement Using Algometer for Calcaneal Spur Patients

by Dwi Basuki Wibowo, Agus Suprihanto, Wahyu Caesarendra, Adam Glowacz, Rudiansyah Harahap, Ryszard Tadeusiewicz, Eliasz Kańtoch and Pg Emeroylariffion Abas

Technologies 2021, 9(3), 62; https://doi.org/10.3390/technologies9030062 - 30 Aug 2021

Viewed by 3734

Abstract

The pressure pain threshold (PPT) is a useful tool for evaluating mechanical sensitivity in individuals suffering from various musculoskeletal disorders. The aim of this study is to investigate PPT at the heel area in order to assist in the design of orthotic shoes [...] Read more.

The pressure pain threshold (PPT) is a useful tool for evaluating mechanical sensitivity in individuals suffering from various musculoskeletal disorders. The aim of this study is to investigate PPT at the heel area in order to assist in the design of orthotic shoes for sufferers of heel pain due to a calcaneal spur. The size and location of the calcaneal spur was determined by x-ray images, with PPT data measured around the spur at five points by using algometer FDIX 25. The pain test experiment was conducted by pressing each point to obtain the pain minimum compressive pressure (PMCP) and its location. The information of shoe size, spur location and dimensions, and the PMCP location for each individual is used to obtain the exact point location for applying a softer material to the shoe in-sole, in order to reduce heel pain. The results are significant as it can be used by designers to design appropriate shoe in-soles for individuals suffering from heel pain. Full article

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37 pages, 5562 KB

Open AccessEditor’s ChoiceReview

Post-Processing of 3D-Printed Polymers

by John Ryan C. Dizon, Ciara Catherine L. Gache, Honelly Mae S. Cascolan, Lina T. Cancino and Rigoberto C. Advincula

Technologies 2021, 9(3), 61; https://doi.org/10.3390/technologies9030061 - 25 Aug 2021

Cited by 200 | Viewed by 28067

Abstract

Additive manufacturing, commonly known as 3D printing, is an advancement over traditional formative manufacturing methods. It can increase efficiency in manufacturing operations highlighting advantages such as rapid prototyping, reduction of waste, reduction of manufacturing time and cost, and increased flexibility in a production [...] Read more.

Additive manufacturing, commonly known as 3D printing, is an advancement over traditional formative manufacturing methods. It can increase efficiency in manufacturing operations highlighting advantages such as rapid prototyping, reduction of waste, reduction of manufacturing time and cost, and increased flexibility in a production setting. The additive manufacturing (AM) process consists of five steps: (1) preparation of 3D models for printing (designing the part/object), (2) conversion to STL file, (3) slicing and setting of 3D printing parameters, (4) actual printing, and (5) finishing/post-processing methods. Very often, the 3D printed part is sufficient by itself without further post-printing processing. However, many applications still require some forms of post-processing, especially those for industrial applications. This review focuses on the importance of different finishing/post-processing methods for 3D-printed polymers. Different 3D printing technologies and materials are considered in presenting the authors’ perspective. The advantages and disadvantages of using these methods are also discussed together with the cost and time in doing the post-processing activities. Lastly, this review also includes discussions on the enhancement of properties such as electrical, mechanical, and chemical, and other characteristics such as geometrical precision, durability, surface properties, and aesthetic value with post-printing processing. Future perspectives is also provided towards the end of this review. Full article

(This article belongs to the Special Issue 3D Printing and Additive Manufacturing: Principles and Applications)

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22 pages, 3163 KB

Open AccessEditor’s ChoiceArticle

Evaluation of Thoracic Equivalent Multiport Circuits Using an Electrical Impedance Tomography Hardware Simulation Interface

by Christos Dimas, Vassilis Alimisis, Ioannis Georgakopoulos, Nikolaos Voudoukis, Nikolaos Uzunoglu and Paul P. Sotiriadis

Technologies 2021, 9(3), 58; https://doi.org/10.3390/technologies9030058 - 9 Aug 2021

Cited by 4 | Viewed by 4490

Abstract

Electrical impedance tomography is a low-cost, safe, and high temporal resolution medical imaging modality which finds extensive application in real-time thoracic impedance imaging. Thoracic impedance changes can reveal important information about the physiological condition of patients’ lungs. In this way, electrical impedance tomography [...] Read more.

Electrical impedance tomography is a low-cost, safe, and high temporal resolution medical imaging modality which finds extensive application in real-time thoracic impedance imaging. Thoracic impedance changes can reveal important information about the physiological condition of patients’ lungs. In this way, electrical impedance tomography can be a valuable tool for monitoring patients. However, this technique is very sensitive to measurement noise or possible minor signal errors, coming from either the hardware, the electrodes, or even particular biological signals. Thus, the design of a good performance electrical impedance tomography hardware setup which properly interacts with the tissue examined is both an essential and a challenging concept. In this paper, we adopt an extensive simulation approach, which combines the system’s analogue and digital hardware, along with equivalent circuits of 3D finite element models that represent thoracic cavities. Each thoracic finite element model is created in MATLAB based on existing CT images, while the tissues’ conductivity and permittivity values for a selected frequency are acquired from a database using Python. The model is transferred to a multiport RLC network, embedded in the system’s hardware which is simulated at LT SPICE. The voltage output data are transferred to MATLAB where the electrical impedance tomography signal sampling and digital processing is also simulated. Finally, image reconstructions are performed in MATLAB, using the EIDORS library tool and considering the signal noise levels and different electrode and signal sampling configurations (ADC bits, sampling frequency, number of taps). Full article

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20 pages, 1163 KB

Open AccessEditor’s ChoiceArticle

Exploiting Biomedical Sensors for a Home Monitoring System for Paediatric Patients with Congenital Heart Disease

by Massimiliano Donati, Silvia Panicacci, Alessio Ruiu, Stefano Dalmiani, Pierluigi Festa, Lamia Ait-Ali, Francesca Mastorci, Alessandro Pingitore, Wanda Pennè, Luca Fanucci and Sergio Saponara

Technologies 2021, 9(3), 56; https://doi.org/10.3390/technologies9030056 - 31 Jul 2021

Cited by 5 | Viewed by 4102

Abstract

Congenital heart disease, the most frequent malformation at birth, is usually not fatal but leads to multiple hospitalisations and outpatient visits, with negative impact on the quality of life and psychological profile not only of children but also of their families. In this [...] Read more.

Congenital heart disease, the most frequent malformation at birth, is usually not fatal but leads to multiple hospitalisations and outpatient visits, with negative impact on the quality of life and psychological profile not only of children but also of their families. In this paper, we describe the entire architecture of a system for remotely monitoring paediatric/neonatal patients with congenital heart disease, with the final aim of improving quality of life of the whole family and reducing hospital admissions. The interesting vital parameters for the disease are ECG, heart rate, oxygen saturation, body temperature and body weight. They are collected at home using some biomedical sensors specifically selected and calibrated for the paediatric field. These data are then sent to the smart hub, which proceeds with the synchronisation to the remote e-Health care center. Here, the doctors can log and evaluate the patient’s parameters. Preliminary results underline the sensor suitability for children and infants and good usability and data management of the smart-hub technology (E@syCare). In the clinical trial, some patients from the U.O.C. Paediatric and Adult Congenital Cardiology- Monasterio Foundation are enrolled. They receive a home monitoring kit according to the group they belong to. The trial aims to evaluate the effects of the system on quality of life. Psychological data are collected through questionnaires filled in by parents/caregivers in self-administration via the gateway at the beginning and at the end of the study. Results highlight an overall improvement in well-being and sleep quality, with a consequent reduction in anxious and stressful situations during daily life thanks to telemonitoring. At the same time, users reported a good level of usability, ease of data transmission and management of the devices. Full article

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