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Volume 2, ECSA-7 2020

Eng. Proc., 2020, IEC 2020

1st International Electronic Conference—Futuristic Applications on Electronics

Online| 1–30 November 2020

Volume Editor: Flavio Canavero

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Cover Story (view full-size image): The 1st International Electronic Conference - Futuristic Applications on Electronics was successfully held online from 1 to 30 November 2020 and the publication of the conference proceedings is [...] Read more.
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Research

Open AccessProceedings
Novel and Compact Ultra-Wideband Wearable Band-Notch Antenna Design for Body Sensor Networks and Mobile Healthcare System
Eng. Proc. 2020, 3(1), 1; https://0-doi-org.brum.beds.ac.uk/10.3390/IEC2020-06973 - 30 Oct 2020
Viewed by 101
Abstract
The development and study of a novel and very miniaturized ultra-wideband (UWB) wearable band-notch antenna for body sensor networks (BSNs) and mobile healthcare system have been presented in this paper. A very user-friendly and reliable software Computer Simulation Technology (CST)TM Microwave Studio [...] Read more.
The development and study of a novel and very miniaturized ultra-wideband (UWB) wearable band-notch antenna for body sensor networks (BSNs) and mobile healthcare system have been presented in this paper. A very user-friendly and reliable software Computer Simulation Technology (CST)TM Microwave Studio was used for the modeling and simulation purpose of this antenna. The antenna is a textile-based UWB notch antenna, as it was printed on jeans’ textile substrate. The simulated performance parameters, such as return loss, bandwidth, gain, radiation efficiency and radiation patterns of this antenna are demonstrated and analyzed. The main aim of this paper was to design a textile-based compact UWB antenna with the characteristics of band notch in X-band to reject the down link band (7.25 GHz–7.75 GHz) of satellite communication in the UWB frequency ranges of 3.1 to 10.6 GHz in order to avoid interference. The simulated results show that this antenna has very well band notch characteristics in the frequency range of 7.25–7.75 GHz. The overall dimension of the antenna is 25 mm in length and 16 mm in width, which is very compact. The antenna is printed on 1 mm Jeans’ textile with the dielectric constant of 1.7. This antenna shows very good results; it has compact size and is printed on textile material, and has band notch characteristics to avoid interference. Due to all these attractive characteristics, it will be a good candidate for body sensor networks for a mobile healthcare system. Full article
Open AccessProceedings
The Tap-Length Associated with the Blind Adaptive Equalization/Deconvolution Problem
Eng. Proc. 2020, 3(1), 2; https://0-doi-org.brum.beds.ac.uk/10.3390/IEC2020-06968 - 30 Oct 2020
Viewed by 70
Abstract
The step-size parameter and the equalizer’s tap length are the system parameters in the blind adaptive equalization design. Choosing a large step-size parameter causes the equalizer to converge faster compared with applying a smaller value for the step size parameter. However, a higher [...] Read more.
The step-size parameter and the equalizer’s tap length are the system parameters in the blind adaptive equalization design. Choosing a large step-size parameter causes the equalizer to converge faster compared with applying a smaller value for the step size parameter. However, a higher step-size parameter leaves the system with a higher residual inter-symbol-interference (ISI) than does a lower step-size parameter. The equalizer’s tap length should be set large enough to compensate for the channel distortions. However, since the channel parameters are unknown, the required equalizer’s tap length is also unknown. The system parameters are usually designed via simulation trials, in such a way that the equalizer’s performance from the residual ISI point of view reaches a system desired residual ISI level. Recently, a closed-form approximated expression was derived for the residual ISI as a function of the system parameters, input sequence statistics and channel power. This expression was obtained under the assumption having a value for the equalizer’s tap length that is sufficient to compensate for the channel distortions. Based on this approximated expression, the outcome from the step-size parameter multiplied by the equalizer’s tap length can be derived when the residual ISI is given. By choosing a step-size parameter, we automatically have also the value for the equalizer’s tap length which might now not be large enough to compensate for the channel distortions and thus leaving the system with a higher residual ISI than the required one. In this work, we derive an expression that sets a condition on the equalizer’s tap length based on the input sequence statistics, on the chosen equalizer’s characteristics and required residual ISI. In addition, highlights are supplied on how to set the equalizer’s tap length for different channel cases based on this new derived expression. The findings are accompanied by simulation results. Full article
Open AccessProceedings
Use of an Active Learning Strategy Based on Gaussian Process Regression for the Uncertainty Quantification of Electronic Devices
Eng. Proc. 2020, 3(1), 3; https://0-doi-org.brum.beds.ac.uk/10.3390/IEC2020-06967 - 30 Oct 2020
Viewed by 70
Abstract
This paper presents a preliminary version of an active learning (AL) scheme for the sample selection aimed at the development of a surrogate model for the uncertainty quantification based on the Gaussian process regression. The proposed AL strategy iteratively searches for new candidate [...] Read more.
This paper presents a preliminary version of an active learning (AL) scheme for the sample selection aimed at the development of a surrogate model for the uncertainty quantification based on the Gaussian process regression. The proposed AL strategy iteratively searches for new candidate points to be included within the training set by trying to minimize the relative posterior standard deviation provided by the Gaussian process regression surrogate. The above scheme has been applied for the construction of a surrogate model for the statistical analysis of the efficiency of a switching buck converter as a function of seven uncertain parameters. The performance of the surrogate model constructed via the proposed active learning method is compared with that provided by an equivalent model built via a Latin hypercube sampling. The results of a Monte Carlo simulation with the computational model are used as reference. Full article
Open AccessProceedings
Electronic Systems and Offsite Touristic Activities Based on Geological Concepts: A Speculative Discussion
Eng. Proc. 2020, 3(1), 4; https://0-doi-org.brum.beds.ac.uk/10.3390/IEC2020-06969 - 30 Oct 2020
Viewed by 92
Abstract
The COVID-19 pandemic has caused havoc in many economic areas such as those related to tourism. This creates the need for alternative activities in this sector, especially given that it is not clear when the present emergency will end and there could be [...] Read more.
The COVID-19 pandemic has caused havoc in many economic areas such as those related to tourism. This creates the need for alternative activities in this sector, especially given that it is not clear when the present emergency will end and there could be new situations of this kind. We consider here two main possibilities (virtual models and remote observations) for tourism related to geological objects (including those used by humans) and processes. These approaches could help to promote remote-operated tourism in other celestial bodies, helping to promote this kind of enterprise. These activities could be prepared with variable connection to education (for publics with diverse age ranges), prompting their use at any time of the year (hence minimizing the issue of seasonality). Our discussion suggests that remote observations will be the most interesting option since they could potentially give the users an unlimited diversity of experiences, it might give higher returns to local communities (but also higher loads on local environments) and they could find additional value in other geological applications. While our analysis is certainly very speculative at present, it can be submitted to falsification by the financial results. Full article
Open AccessProceedings
A System-Level Modelling of Noise in Coupled Resonating MEMS Sensors
Eng. Proc. 2020, 3(1), 5; https://0-doi-org.brum.beds.ac.uk/10.3390/IEC2020-06971 - 30 Oct 2020
Viewed by 122
Abstract
This paper presents realistic system-level modeling of effective noise sources in a coupled resonating mode-localized MEMS sensors. A governing set of differential equations are used to build a numerical model of a mechanical noise source in a coupled-resonator sensor and an effective thermo-mechanical [...] Read more.
This paper presents realistic system-level modeling of effective noise sources in a coupled resonating mode-localized MEMS sensors. A governing set of differential equations are used to build a numerical model of a mechanical noise source in a coupled-resonator sensor and an effective thermo-mechanical noise is quantified through the simulation performed via SIMULINK. On a similar note, an effective noise that stems from the electronic readout used for the coupled resonating MEMS sensors is also quantified. Various noise sources in electronic readout are identified and the contribution of each is quantified. A comparison between an effective mechanical and electronic noise in a sensor system aids in identifying the dominant noise source in a sensor system. A method to optimize the system noise floor for an amplitude-based readout is presented. The proposed models present a variety of operating conditions, such as finite quality factor, varying coupled electrostatic spring strength, and operation with in-phase and out-of-phase mode. The proposed models aim to study the impact of fundamental noise processes that govern the ultimate resolution into a coupled resonating system used for various sensing applications. Full article
Open AccessProceedings
Design and Analysis of a Compact UWB Band Notch Antenna for Wireless Communication
Eng. Proc. 2020, 3(1), 6; https://0-doi-org.brum.beds.ac.uk/10.3390/IEC2020-06974 - 30 Oct 2020
Viewed by 80
Abstract
Development and investigation of a miniaturized ultra-wideband band notch antenna is demonstrated in this paper. The antenna was modeled and simulated using Computer Simulation Technology (CST)TM Microwave Studio software. The simulated results of this antenna are presented and analyzed. The performance parameters [...] Read more.
Development and investigation of a miniaturized ultra-wideband band notch antenna is demonstrated in this paper. The antenna was modeled and simulated using Computer Simulation Technology (CST)TM Microwave Studio software. The simulated results of this antenna are presented and analyzed. The performance parameters such as return loss, gain, radiation efficiency, radiation patterns are simulation-based results provided here. The main objective of this paper was to obtain band notch characteristics at the Wireless Local Area Network (5.15–5.8 GHz) and WiMax (5.25–5.85 GHz) in the UWB frequency ranges of 3.1–10.6 GHz in order to avoid interference. Results and analysis show that the antenna meets the objective and shows very good results. It has very compact size as well which is attractive feature of this antenna that will make it suitable for ultra-wideband wireless communication systems. Full article
Open AccessProceedings
Evaluation of Generative Modeling Techniques for Frequency Responses
Eng. Proc. 2020, 3(1), 7; https://0-doi-org.brum.beds.ac.uk/10.3390/IEC2020-06970 - 30 Oct 2020
Viewed by 76
Abstract
During microwave design, it is of practical interest to obtain insight in the statistical variability of a device’s frequency response with respect to several sources of variation. Unfortunately, the frequency response acquisition can be particularly time-consuming or expensive. This makes uncertainty quantification unfeasible [...] Read more.
During microwave design, it is of practical interest to obtain insight in the statistical variability of a device’s frequency response with respect to several sources of variation. Unfortunately, the frequency response acquisition can be particularly time-consuming or expensive. This makes uncertainty quantification unfeasible when dealing with complex networks. Generative modeling techniques that are based on machine learning can reduce the computation load by learning the underlying stochastic process from few instances of the device response and generating new ones by executing an inexpensive sampling strategy. This way, an arbitrary number of frequency responses can be obtained that are drawn from a probability distribution that resembles the original one. The use of Gaussian Process Latent Variable Models (GP-LVM) and Variational Autoencoders (VAE) as modeling algorithms will be evaluated in a generative framework. The framework includes a Vector Fitting (VF) pre-processing step which guarantees stability and reciprocity of S-matrices by converting them into a suitable rational model. Both GP-LVM and VAE are tested on the S-parameter responses of two linear multi-port network examples. Full article
Open AccessProceedings
A Bayesian Optimisation Procedure for Estimating Optimal Trajectories in Electromagnetic Compliance Testing
Eng. Proc. 2020, 3(1), 8; https://0-doi-org.brum.beds.ac.uk/10.3390/IEC2020-06972 - 30 Oct 2020
Viewed by 93
Abstract
The need for accurate physical measurements is omnipresent in both scientific and engineering applications. Such measurements can be used to explore and characterize the behavior of a system over the parameters of interest. These procedures are often very costly and time-consuming, requiring many [...] Read more.
The need for accurate physical measurements is omnipresent in both scientific and engineering applications. Such measurements can be used to explore and characterize the behavior of a system over the parameters of interest. These procedures are often very costly and time-consuming, requiring many measurements or samples. Therefore, a suitable data collection strategy can be used to reduce the cost of acquiring the required samples. One important consideration which often surfaces in physical experiments, like near-field measurements for electromagnetic compliance testing, is the total path length between consecutively visited samples by the measurement probe, as the time needed to travel along this path is often a limiting factor. A line-based sampling strategy optimizes the sample locations in order to reduce the overall path length while achieving the intended goal. Previous research on line-based sampling techniques solely focused on exploring the measurement space. None of these techniques considered the actual measurements themselves despite these values hold the potential to identify interesting regions in the parameter space, such as an optimum, quickly during the sampling process. In this paper, we extend Bayesian optimization, a point-based optimization technique into a line-based setting. The proposed algorithm is assessed using an artificial example and an electromagnetic compatibility use-case. The results show that our line-based technique is able to find the optimum using a significantly shorter total path length compared to the point-based approach. Full article
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