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Technologies
Volume 10
Issue 2
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Technologies, Volume 10, Issue 2 (April 2022) – 17 articles

Cover Story (view full-size image): The detection and prevention of body-straining postures and other similar conditions within the work environment play a significant part in establishing occupational safety and well-being. We propose a deep-learning-based method for an online assessment of ergonomically suboptimal postures that impose increased physical strain on workers during work activities, using visual data acquired with low-cost sensors. The correlation and fusion of these estimations with time-synchronized worker heart rate data from wearable sensors have also been investigated with the aim of improving short-term forecasting of worker cardiovascular activity and ultimately training better predictive models for worker fatigue. A new multimodal dataset comprising video and heart rate data captured in a real manufacturing workplace is also introduced. View this paper.
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18 pages, 2046 KiB  
Review
Strategic Investment in Open Hardware for National Security
by Joshua M. Pearce
Technologies 2022, 10(2), 53; https://doi.org/10.3390/technologies10020053 - 18 Apr 2022
Cited by 8 | Viewed by 4516
Abstract
Free and open-source hardware (FOSH) development has been shown to increase innovation and reduce economic costs. This article reviews the opportunity to use FOSH as a sanction to undercut imports and exports from a target criminal country. A formal methodology is presented for [...] Read more.
Free and open-source hardware (FOSH) development has been shown to increase innovation and reduce economic costs. This article reviews the opportunity to use FOSH as a sanction to undercut imports and exports from a target criminal country. A formal methodology is presented for selecting strategic national investments in FOSH development to improve both national security and global safety. In this methodology, first the target country that is threatening national security or safety is identified. Next, the top imports from the target country as well as potentially other importing countries (allies) are quantified. Hardware is identified that could undercut imports/exports from the target country. Finally, methods to support the FOSH development are enumerated to support production in a commons-based peer production strategy. To demonstrate how this theoretical method works in practice, it is applied as a case study to a current criminal military aggressor nation, who is also a fossil-fuel exporter. The results show that there are numerous existing FOSH and opportunities to develop new FOSH for energy conservation and renewable energy to reduce fossil-fuel-energy demand. Widespread deployment would reduce the concomitant pollution, human health impacts, and environmental desecration as well as cut financing of military operations. Full article
(This article belongs to the Special Issue 10th Anniversary of Technologies—Recent Advances and Perspectives)
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44 pages, 6771 KiB  
Review
Flow Stress Description Characteristics of Some Constitutive Models at Wide Strain Rates and Temperatures
by Hyunho Shin, Yongwon Ju, Min Kuk Choi and Dong Ho Ha
Technologies 2022, 10(2), 52; https://doi.org/10.3390/technologies10020052 - 11 Apr 2022
Cited by 17 | Viewed by 5843 | Correction
Abstract
The commonly employed mathematical functions in constitutive models, such as the strain hardening/softening model, strain-rate hardening factor, and temperature-softening factor, are reviewed, and their prediction characteristics are illustrated. The results may assist one (i) to better understand the behavior of the constitutive model [...] Read more.
The commonly employed mathematical functions in constitutive models, such as the strain hardening/softening model, strain-rate hardening factor, and temperature-softening factor, are reviewed, and their prediction characteristics are illustrated. The results may assist one (i) to better understand the behavior of the constitutive model that employs a given mathematical function; (ii) to find the reason for deficiencies, if any, of an existing constitutive model; (iii) to avoid employing an inappropriate mathematical function in future constitutive models. This study subsequently illustrates the flow stress description characteristics of twelve constitutive models at wide strain rates (from 10−6 to 106 s−1) and temperatures (from absolute to melting temperatures) using the material parameters presented in the original studies. The phenomenological models considered herein include the Johnson–Cook, Shin–Kim, Lin–Wagoner, Sung–Kim–Wagoner, Khan–Huang–Liang, and Rusinek–Klepaczko models. The physically based models considered are the Zerilli–Armstrong, Voyiadjis–Abed, Testa et al., Steinberg et al., Preston–Tonks–Wallace, and Follansbee–Kocks models. The illustrations of the behavior of the foregoing constitutive models may be informative in (i) selecting an appropriate constitutive model; (ii) understanding and interpreting simulation results obtained using a given constitutive model; (iii) finding a reference material to develop future constitutive models. Full article
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13 pages, 7056 KiB  
Article
Rough-Set-Theory-Based Classification with Optimized k-Means Discretization
by Teguh Handjojo Dwiputranto, Noor Akhmad Setiawan and Teguh Bharata Adji
Technologies 2022, 10(2), 51; https://doi.org/10.3390/technologies10020051 - 8 Apr 2022
Cited by 7 | Viewed by 3460
Abstract
The discretization of continuous attributes in a dataset is an essential step before the Rough-Set-Theory (RST)-based classification process is applied. There are many methods for discretization, but not many of them have linked the RST instruments from the beginning of the discretization process. [...] Read more.
The discretization of continuous attributes in a dataset is an essential step before the Rough-Set-Theory (RST)-based classification process is applied. There are many methods for discretization, but not many of them have linked the RST instruments from the beginning of the discretization process. The objective of this research is to propose a method to improve the accuracy and reliability of the RST-based classifier model by involving RST instruments at the beginning of the discretization process. In the proposed method, a k-means-based discretization method optimized with a genetic algorithm (GA) was introduced. Four datasets taken from UCI were selected to test the performance of the proposed method. The evaluation of the proposed discretization technique for RST-based classification is performed by comparing it to other discretization methods, i.e., equal-frequency and entropy-based. The performance comparison among these methods is measured by the number of bins and rules generated and by its accuracy, precision, and recall. A Friedman test continued with post hoc analysis is also applied to measure the significance of the difference in performance. The experimental results indicate that, in general, the performance of the proposed discretization method is significantly better than the other compared methods. Full article
(This article belongs to the Special Issue Data Science and Big Data in Biology, Physical Science and Engineering)
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28 pages, 3361 KiB  
Article
The NESTORE e-Coach: Designing a Multi-Domain Pathway to Well-Being in Older Age
by Leonardo Angelini, Mira El Kamali, Elena Mugellini, Omar Abou Khaled, Christina Röcke, Simone Porcelli, Alfonso Mastropietro, Giovanna Rizzo, Noemi Boqué, Josep Maria del Bas, Filippo Palumbo, Michele Girolami, Antonino Crivello, Canan Ziylan, Paula Subías-Beltrán, Silvia Orte, Carlo Emilio Standoli, Laura Fernandez Maldonado, Maurizio Caon, Martin Sykora, Suzanne Elayan, Sabrina Guye and Giuseppe Andreoniadd Show full author list remove Hide full author list
Technologies 2022, 10(2), 50; https://doi.org/10.3390/technologies10020050 - 1 Apr 2022
Cited by 5 | Viewed by 4064
Abstract
This article describes the coaching strategies of the NESTORE e-coach, a virtual coach for promoting healthier lifestyles in older age. The novelty of the NESTORE project is the definition of a multi-domain personalized pathway where the e-coach accompanies the user throughout different structured [...] Read more.
This article describes the coaching strategies of the NESTORE e-coach, a virtual coach for promoting healthier lifestyles in older age. The novelty of the NESTORE project is the definition of a multi-domain personalized pathway where the e-coach accompanies the user throughout different structured and non-structured coaching activities and recommendations. The article also presents the design process of the coaching strategies, carried out including older adults from four European countries and experts from the different health domains, and the results of the tests carried out with 60 older adults in Italy, Spain and The Netherlands. Full article
(This article belongs to the Collection Selected Papers from the PETRA Conference Series)
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11 pages, 4132 KiB  
Article
Vacuum UV (VUV) Photo-Oxidation of Polyethersulfone (PES)
by Sarah Oakes, Ryan Keeley, Hunter Heineman, Tom Allston, Joel Shertok, Michael Mehan, Gregory K. Thompson and Gerald A. Takacs
Technologies 2022, 10(2), 49; https://doi.org/10.3390/technologies10020049 - 30 Mar 2022
Cited by 5 | Viewed by 2773
Abstract
International need for water quality is placing a high demand on separation technology to develop advanced oxidative processes for polyethersulfone (PES) membranes to help improve water purification. Therefore, VUV photo-oxidation with a low pressure Ar plasma was studied to improve the hydrophilicity of [...] Read more.
International need for water quality is placing a high demand on separation technology to develop advanced oxidative processes for polyethersulfone (PES) membranes to help improve water purification. Therefore, VUV photo-oxidation with a low pressure Ar plasma was studied to improve the hydrophilicity of PES by flowing oxygen over the surface during treatment. X-ray photoelectron spectroscopy (XPS) detected a decrease in the C at% (4.4 ± 1.7 at%), increase in O at% (3.7 ± 1.0 at%), and a constant S at% (5.4 ± 0.2 at%). Curve fitting of the XPS spectra showed a decrease in sp2 C-C aromatic group bonding, and an increase in C-O, C-S, O=C-OH, sulphonate (-SO3) and sulphate (-SO4) functional groups with treatment time. The water contact angle decreased from 71.9° for untreated PES down to a saturation level of 41.9° with treatment. Since scanning electron microscopy (SEM) showed no major changes in surface roughness, the increase in hydrophilicity was mainly due to oxidation of the surface. Washing the VUV photo-oxidized PES samples with water or ethanol increased the water contact angle saturation level up to 66° indicating the formation of a weak boundary layer. Full article
(This article belongs to the Section Environmental Technology)
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14 pages, 29620 KiB  
Article
Verifiable Surface Disinfection Using Ultraviolet Light with a Mobile Manipulation Robot
by Alan G. Sanchez and William D. Smart
Technologies 2022, 10(2), 48; https://doi.org/10.3390/technologies10020048 - 29 Mar 2022
Cited by 3 | Viewed by 3205
Abstract
Robots are being increasingly used in the fight against highly-infectious diseases such as the Novel Coronavirus (SARS-CoV-2). By using robots in place of human health care workers in disinfection tasks, we can reduce the exposure of these workers to the virus and, as [...] Read more.
Robots are being increasingly used in the fight against highly-infectious diseases such as the Novel Coronavirus (SARS-CoV-2). By using robots in place of human health care workers in disinfection tasks, we can reduce the exposure of these workers to the virus and, as a result, often dramatically reduce their risk of infection. Since healthcare workers are often disproportionately affected by large-scale infectious disease outbreaks, this risk reduction can profoundly affect our ability to fight these outbreaks. Many robots currently available for disinfection, however, are little more than mobile platforms for ultraviolet lights, do not allow fine-grained control over how the disinfection is performed, and do not allow verification that it was done as the human supervisor intended. In this paper, we present a semi-autonomous system, originally designed for the disinfection of surfaces in the context of Ebola Virus Disease (EVD) that allows a human supervisor to direct an autonomous robot to disinfect contaminated surfaces to a desired level, and to subsequently verify that this disinfection has taken place. We describe the overall system, the user interface, how our calibration and modeling allows for reliable disinfection, and offer directions for future work to address open space disinfection tasks. Full article
(This article belongs to the Collection Selected Papers from the PETRA Conference Series)
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18 pages, 5635 KiB  
Article
Fall Detection Using Multi-Property Spatiotemporal Autoencoders in Maritime Environments
by Iason Katsamenis, Nikolaos Bakalos, Eleni Eirini Karolou, Anastasios Doulamis and Nikolaos Doulamis
Technologies 2022, 10(2), 47; https://doi.org/10.3390/technologies10020047 - 29 Mar 2022
Cited by 6 | Viewed by 3214
Abstract
Man overboard is an emergency in which fast and efficient detection of the critical event is the key factor for the recovery of the victim. Its severity urges the utilization of intelligent video surveillance systems that monitor the ship’s perimeter in real time [...] Read more.
Man overboard is an emergency in which fast and efficient detection of the critical event is the key factor for the recovery of the victim. Its severity urges the utilization of intelligent video surveillance systems that monitor the ship’s perimeter in real time and trigger the relative alarms that initiate the rescue mission. In terms of deep learning analysis, since man overboard incidents occur rarely, they present a severe class imbalance problem, and thus, supervised classification methods are not suitable. To tackle this obstacle, we follow an alternative philosophy and present a novel deep learning framework that formulates man overboard identification as an anomaly detection task. The proposed system, in the absence of training data, utilizes a multi-property spatiotemporal convolutional autoencoder that is trained only on the normal situation. We explore the use of RGB video sequences to extract specific properties of the scene, such as gradient and saliency, and utilize the autoencoders to detect anomalies. To the best of our knowledge, this is the first time that man overboard detection is made in a fully unsupervised manner while jointly learning the spatiotemporal features from RGB video streams. The algorithm achieved 97.30% accuracy and a 96.01% F1-score, surpassing the other state-of-the-art approaches significantly. Full article
(This article belongs to the Collection Selected Papers from the PETRA Conference Series)
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18 pages, 3213 KiB  
Article
Efficiently Mitigating Face-Swap-Attacks: Compressed-PRNU Verification with Sub-Zones
by Ali Hassani, Hafiz Malik and Jon Diedrich
Technologies 2022, 10(2), 46; https://doi.org/10.3390/technologies10020046 - 27 Mar 2022
Cited by 3 | Viewed by 3415
Abstract
Face-swap-attacks (FSAs) are a new threat to face recognition systems. FSAs are essentially imperceptible replay-attacks using an injection device and generative networks. By placing the device between the camera and computer device, attackers can present any face as desired. This is particularly potent [...] Read more.
Face-swap-attacks (FSAs) are a new threat to face recognition systems. FSAs are essentially imperceptible replay-attacks using an injection device and generative networks. By placing the device between the camera and computer device, attackers can present any face as desired. This is particularly potent as it also maintains liveliness features, as it is a sophisticated alternation of a real person, and as it can go undetected by traditional anti-spoofing methods. To address FSAs, this research proposes a noise-verification framework. Even the best generative networks today leave alteration traces in the photo-response noise profile; these are detected by doing a comparison of challenge images against the camera enrollment. This research also introduces compression and sub-zone analysis for efficiency. Benchmarking with open-source tampering-detection algorithms shows the proposed compressed-PRNU verification robustly verifies facial-image authenticity while being significantly faster. This demonstrates a novel efficiency for mitigating face-swap-attacks, including denial-of-service attacks. Full article
(This article belongs to the Special Issue The Applications and Challenges of Cybersecurity in Science, Healthcare and Medicine)
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31 pages, 7448 KiB  
Review
Material Design for Enhancing Properties of 3D Printed Polymer Composites for Target Applications
by Vinita V. Shinde, Yuyang Wang, Md Fahim Salek, Maria L. Auad, Lauren E. Beckingham and Bryan S. Beckingham
Technologies 2022, 10(2), 45; https://doi.org/10.3390/technologies10020045 - 23 Mar 2022
Cited by 15 | Viewed by 6057
Abstract
Polymer composites are becoming an important class of materials for a diversified range of industrial applications due to their unique characteristics and natural and synthetic reinforcements. Traditional methods of polymer composite fabrication require machining, manual labor, and increased costs. Therefore, 3D printing technologies [...] Read more.
Polymer composites are becoming an important class of materials for a diversified range of industrial applications due to their unique characteristics and natural and synthetic reinforcements. Traditional methods of polymer composite fabrication require machining, manual labor, and increased costs. Therefore, 3D printing technologies have come to the forefront of scientific, industrial, and public attention for customized manufacturing of composite parts having a high degree of control over design, processing parameters, and time. However, poor interfacial adhesion between 3D printed layers can lead to material failure, and therefore, researchers are trying to improve material functionality and extend material lifetime with the addition of reinforcements and self-healing capability. This review provides insights on different materials used for 3D printing of polymer composites to enhance mechanical properties and improve service life of polymer materials. Moreover, 3D printing of flexible energy-storage devices (FESD), including batteries, supercapacitors, and soft robotics using soft materials (polymers), is discussed as well as the application of 3D printing as a platform for bioengineering and earth science applications by using a variety of polymer materials, all of which have great potential for improving future conditions for humanity and planet Earth. Full article
(This article belongs to the Special Issue 3D Printing and Additive Manufacturing: Principles and Applications)
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8 pages, 3262 KiB  
Article
Negotiating Learning Goals with Your Future Learning-Self
by Konstantinos Tsiakas, Deborah Cnossen, Timothy H. C. Muyrers, Danique R. C. Stappers, Romain H. A. Toebosch and Emilia I. Barakova
Technologies 2022, 10(2), 44; https://doi.org/10.3390/technologies10020044 - 22 Mar 2022
Viewed by 2780
Abstract
This paper discusses the challenges towards designing an educational avatar which visualizes the future learning-self of a student in order to promote their self-regulated learning skills. More specifically, the avatar follows a negotiation-based interaction with the student during the goal-setting process of self-regulated [...] Read more.
This paper discusses the challenges towards designing an educational avatar which visualizes the future learning-self of a student in order to promote their self-regulated learning skills. More specifically, the avatar follows a negotiation-based interaction with the student during the goal-setting process of self-regulated learning. The goal of the avatar is to help the student get insights of their possible future learning-self based on their daily goals. Our approach utilizes a Recurrent Neural Network as the underlying prediction model for expected learning outcomes and goal feasibility. In this paper, we present our ongoing work and design process towards an explainable and personalized educational avatar, focusing both on the avatar design and the human-algorithm interactions. Full article
(This article belongs to the Collection Selected Papers from the PETRA Conference Series)
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13 pages, 2933 KiB  
Review
A Survey on GAN-Based Data Augmentation for Hand Pose Estimation Problem
by Farnaz Farahanipad, Mohammad Rezaei, Mohammad Sadegh Nasr, Farhad Kamangar and Vassilis Athitsos
Technologies 2022, 10(2), 43; https://doi.org/10.3390/technologies10020043 - 21 Mar 2022
Cited by 16 | Viewed by 6490
Abstract
Deep learning solutions for hand pose estimation are now very reliant on comprehensive datasets covering diverse camera perspectives, lighting conditions, shapes, and pose variations. While acquiring such datasets is a challenging task, several studies circumvent this problem by exploiting synthetic data, but this [...] Read more.
Deep learning solutions for hand pose estimation are now very reliant on comprehensive datasets covering diverse camera perspectives, lighting conditions, shapes, and pose variations. While acquiring such datasets is a challenging task, several studies circumvent this problem by exploiting synthetic data, but this does not guarantee that they will work well in real situations mainly due to the gap between the distribution of synthetic and real data. One recent popular solution to the domain shift problem is learning the mapping function between different domains through generative adversarial networks. In this study, we present a comprehensive study on effective hand pose estimation approaches, which are comprised of the leveraged generative adversarial network (GAN), providing a comprehensive training dataset with different modalities. Benefiting from GAN, these algorithms can augment data to a variety of hand shapes and poses where data manipulation is intuitively controlled and greatly realistic. Next, we present related hand pose datasets and performance comparison of some of these methods for the hand pose estimation problem. The quantitative and qualitative results indicate that the state-of-the-art hand pose estimators can be greatly improved with the aid of the training data generated by these GAN-based data augmentation methods. These methods are able to beat the baseline approaches with better visual quality and higher values in most of the metrics (PCK and ME) on both the STB and NYU datasets. Finally, in conclusion, the limitation of the current methods and future directions are discussed. Full article
(This article belongs to the Collection Selected Papers from the PETRA Conference Series)
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30 pages, 5249 KiB  
Article
Detection of Physical Strain and Fatigue in Industrial Environments Using Visual and Non-Visual Low-Cost Sensors
by Konstantinos Papoutsakis, George Papadopoulos, Michail Maniadakis, Thodoris Papadopoulos, Manolis Lourakis, Maria Pateraki and Iraklis Varlamis
Technologies 2022, 10(2), 42; https://doi.org/10.3390/technologies10020042 - 16 Mar 2022
Cited by 12 | Viewed by 5776
Abstract
The detection and prevention of workers’ body straining postures and other stressing conditions within the work environment, supports establishing occupational safety and promoting well being and sustainability at work. Developed methods towards this aim typically rely on combining highly ergonomic workplaces and expensive [...] Read more.
The detection and prevention of workers’ body straining postures and other stressing conditions within the work environment, supports establishing occupational safety and promoting well being and sustainability at work. Developed methods towards this aim typically rely on combining highly ergonomic workplaces and expensive monitoring mechanisms including wearable devices. In this work, we demonstrate how the input from low-cost sensors, specifically, passive camera sensors installed in a real manufacturing workplace, and smartwatches used by the workers can provide useful feedback on the workers’ conditions and can yield key indicators for the prevention of work-related musculo-skeletal disorders (WMSD) and physical fatigue. To this end, we study the ability to assess the risk for physical strain of workers online during work activities based on the classification of ergonomically sub-optimal working postures using visual information, the correlation and fusion of these estimations with synchronous worker heart rate data, as well as the prediction of near-future heart rate using deep learning-based techniques. Moreover, a new multi-modal dataset of video and heart rate data captured in a real manufacturing workplace during car door assembly activities is introduced. The experimental results show the efficiency of the proposed approach that exceeds 70% of classification rate based on the F1 score measure using a set of over 300 annotated video clips of real line workers during work activities. In addition a time lagging correlation between the estimated ergonomic risks for physical strain and high heart rate was assessed using a larger dataset of synchronous visual and heart rate data sequences. The statistical analysis revealed that imposing increased strain to body parts will results in an increase to the heart rate after 100–120 s. This finding is used to improve the short term forecasting of worker’s cardiovascular activity for the next 10 to 30 s by fusing the heart rate data with the estimated ergonomic risks for physical strain and ultimately to train better predictive models for worker fatigue. Full article
(This article belongs to the Collection Selected Papers from the PETRA Conference Series)
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18 pages, 36905 KiB  
Article
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 4833
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 KiB  
Article
An Optimized Enhanced Phase Locked Loop Controller for a Hybrid System
by Amritha Kodakkal, Rajagopal Veramalla, Narasimha Raju Kuthuri and Surender Reddy Salkuti
Technologies 2022, 10(2), 40; https://doi.org/10.3390/technologies10020040 - 11 Mar 2022
Cited by 6 | Viewed by 3387
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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14 pages, 905 KiB  
Article
A Switched Capacitor Memristor Emulator Using Stochastic Computing
by Carola de Benito, Oscar Camps, Mohamad Moner Al Chawa, Stavros G. Stavrinides and Rodrigo Picos
Technologies 2022, 10(2), 39; https://doi.org/10.3390/technologies10020039 - 2 Mar 2022
Cited by 3 | Viewed by 2841
Abstract
Due to the increased use of memristors and their many applications, the use of emulators has grown in parallel to avoid some of the difficulties presented by real devices, such as variability and reliability. In this paper, we present a memristive emulator designed [...] Read more.
Due to the increased use of memristors and their many applications, the use of emulators has grown in parallel to avoid some of the difficulties presented by real devices, such as variability and reliability. In this paper, we present a memristive emulator designed using a switched capacitor (SC), that is, an analog component/block and a control part or block implemented using stochastic computing (SCo) and therefore fully digital. Our design is thus a mixed signal circuit. Memristor equations are implemented using stochastic computing to generate the control signals necessary to work with the controllable resistor implemented as a switched capacitor. Full article
(This article belongs to the Special Issue MOCAST 2021)
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12 pages, 3271 KiB  
Article
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 4447
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 KiB  
Article
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 24 | Viewed by 5260
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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