COVID-19 Vaccine and Booster Shots Compatibility Analyzer using CMOS-based Monochrome Encoding

The continuous increase in COVID-19 positive cases in the Philippines might further weaken the local healthcare system. As such, an efficient system must be implemented to further improve the immunization efforts of the country. In this paper, a contactless digital electronic device is proposed to assess the vaccine and booster brand compatibility. Using Logisim 2.7.1, the logic diagrams were designed and simulated with the help of truth tables and Boolean functions. Moreover, the finalized logic circuit design was converted into its equivalent complementary metal-oxide semiconductor (CMOS) and stick diagrams to help contextualize how the integrated circuits will be designed. Results have shown that the proposed device was able to accept three inputs of the top three COVID-19 vaccine brands (Sinovac, AstraZeneca, and Pfizer) and assess the compatibility of heterologous vaccinations. With the successful results of the circuit, it can be concluded that this low-power device can be used to manufacture a physical prototype for use in booster vaccination sites. © 2022 IEEE.

Capturing complexity over space and time via deep learning: An application to real-time delay prediction in railways

Predictive analytics is an increasingly popular tool for enhancing decision-making processes but is in many business settings based on rule-based models. These rule-based models reach their limits in complex settings. This study compares the performance of a rule-based system with a customised LSTM encoder-decoder deep learning model for predicting train delays. For this, we use a purposefully built real-world dataset on railway transportation, where trains' interdependence over the network makes delay prediction more difficult. Results show that the deep learning model, which incorporates rich spatiotemporal interdependency information in real-time, outperforms the rule-based system by 18%, with the difference increasing to above 23% with higher complexity. The study also dissects the performance difference across different settings: dense versus rural areas, peak versus off-peak hours, low versus high delay, and before versus during the COVID-19 pandemic. The deep learning model is implemented as a proof of concept for decision support within Belgium's railway infrastructure company Infrabel. © 2023 Elsevier B.V.

A Low-cost Handheld Reconfigurable Impedimetric Readout System for Diagnostics of Viral Infections

This paper presents a portable impedimetric biosensor for detecting infectious diseases such as SARS-CoV-2 Infections. A bio-ready sensing electrode functionalized with SARS-CoV-2 nucleocapsid antibody was employed to quantitatively convert the concentration of nucleocapsid protein (N-protein) into impedance changes. In this paper, we proposed a readout system with a dynamic input range of 200 Ωto 1 MΩmagnitude and 0 to 180°phase. The resolution of this device is 1% and 6.5°for measuring the magnitude and phase, respectively. Herein we demonstrate and discuss the proposed system’s functionality, sensitivity, and selectivity using the clinical swab samples. As per these results, this readout system is suitable for the detection of N-protein ranging up to 10,000 pg/mL with a resolution of 56 fg/mL. The proposed impedimetric sensing system can be adopted for the detection of infectious diseases in the future. This low-cost (<$80) device using off-the-shelf is a unique candidate for batch production purposes during urgent pandemic situations. IEEE

A parallel approach to the fractional time delay model for predicting the spread of COVID-19

Due to the importance of forecast accuracy for diseases such as COVID-19, the existence of a mathematical model is particularly important. In this research, first, a model to describe the spread of the COVID-19 pandemic is examined. This model is based on a fractional ordinary differential equation. Then the predictor-corrector numerical method is presented to solve this model. Due to the computational challenge of numerically solving fractional models, a task-parallel approach with coarse granularity is presented to solve this model on shared memory systems. The initial data for testing the proposed approach is the data reported on December 31, 2019 by the Wuhan Municipal Commission of the outbreak of the COVID-19 pandemic in the city of Wuhan, China. The numerical results obtained from the proposed parallel approach show that the speedup of the parallel method compared to the sequential method reaches 2.76 in the prediction of 1000 days. © 2022 IEEE.

Dombi Bonferroni Mean Operators under Bipolar Complex Fuzzy Environment and Their Applications in Internet World

Internet is almost a necessary facility and tool to solve daily life problems in every field life. Whether at the individual level or national and international level sale purchase of any kind of object has always been of much importance, especially after Corona Pandemic, when online business is at its peak. Because of the enhancement of online sales and purchases, various businessmen are looking for suitable internet websites for their businesses, and the selection of the most suitable internet websites is one of the multi-attribute decision-making (MADM) dilemmas. Thus, in this script, we take benefits of three various concepts that are Bonferroni mean (BM) operator which is a significant technique to catch the interrelatedness among any number of inputs, Dombi operations which are based on Dombi t-norm and t-conorm and the ability to create an aggregation procedure more flexible because of the parameter, bipolar complex fuzzy set (BCFS) which is an outstanding model for tackling two-dimensional information with negative aspect and interpret bipolar complex fuzzy (BCF) Dombi Bonferroni mean (BCFDBM), BCF weighted Dombi Bonferroni mean (BCFWDBM), BCF Dombi geometric Bonferroni mean (BCFDGBM), and BCF weighted Dombi geometric Bonferroni mean (BCFWDGBM) operators. After ward, in this script, for tackling MADM dilemmas in the setting of BCFS, we investigate a MADM procedure based on the investigated operators and solve a MADM dilemma (selection of a suitable internet website for businessmen). Further, to display the superiority and efficiency of our work, we compare our approach and operators with a few current approaches and operators. Author

Monitoring of the Social Distance between Passengers in Real-time through Video Analytics and Deep Learning in Railway Stations for Developing the Highest Efficiency

Near the end of December 2019, the globe was hit with a major crisis, which is nothing but the coronavirus-based pandemic. The authorities at the train station should also keep in mind the need to limit the spread of the covid virus in the event of a global pandemic. When it comes to controlling the COVID-19 epidemic, public transportation facilities like train stations play a pivotal role because of the proximity of so many people who may be exposed to the virus. Using common place CCTV cameras and deep learning with simple online and real-time (DeepSORT) methods, this study develops social distance monitoring using a YOLOv4 identification of a Surveillance Object Model. Based on experiments conducted with a minicomputer equipped with an Intel 11th Gen Intel(R) Core(TM) i3-1115G4 at 3.00GHz, 2995 Mhz, two Core(s), four Logical processor, four gigabytes of random-access memory (RAM), this paper makes use of CCTV surveillance, which was put into practice at the Guindy railway station, Chennai, Tamilnadu in India in order to detect the violation of social distancing. © 2022 IEEE.

Flexible Printed Circuitry on Fabric for Wearable Electronics Applications

Health awareness has increased worldwide since the COVID 2019 pandemic, creating a strong demand for wearable electronics. Wearable sensors for monitoring a patient's health are prevalent to reduce medical costs and decrease in-person clinic visits. Integrating electronics into clothes is challenging because most fabrics are porous and incompatible with the existing manufacturing methods, such as screen printing. The indirect printing method was employed to fabricate electrical circuitry on a textile substrate by printing it on a heat transfer polymer (HTP) and attaching it to the target cloths by stitching or glueing. Such a fabrication process has the potential to lead the way in developing new intelligent clothes. However, the durability of the printed circuitry in this manufacturing process on a cloth is still unknown and requires investigation. Therefore, this paper's objective is to study the durability of printed circuitries on fabric by applying constant cyclic loading. The test vehicle is a printed conductive silver interdigitating circuitry on fabric. Another test vehicle on a polyethylene terephthalate (PET) substrate was fabricated for a benchmark. A constant cyclic loading at 1Hz at a 50% duty cycle was applied to the test vehicles 100,000 times. The printed circuitry was monitored by logging the voltage in an electrical voltage divider configuration while the sensor was pressed and released. The result indicates that the fabric test vehicle can still function after the 100,000 cycles of the cyclic loading test and is comparable to that on the PET substrate. The recorded voltage-to-force values of the printed sensor on the fabric drifted upward and downward up to 3% over the loading cycles. The optical microscope observation on the cyclic loading samples showed signs of shear stresses on the printed silver and electrically conductive films, which could cause the tips of the silver interdigitating fingers to shatter. The study indicates that the properly manufactured circuits on fabric can be reliable and utilized for wearable applications. © 2022 IEEE.

Stability and Bifurcation Analysis of the Caputo Fractional-Order Asymptomatic COVID-19 Model with Multiple Time-Delays

Throughout the last few decades, fractional-order models have been used in many fields of science and engineering, applied mathematics, and biotechnology. Fractional-order differential equations are beneficial for incorporating memory and hereditary properties into systems. Our paper proposes an asymptomatic COVID-19 model with three delay terms τ1,τ2,τ3 and fractional-order α. Multiple constant time delays are included in the model to account for the latency of infection in a vector. We study the necessary and sufficient criteria for stability of steady states and Hopf bifurcations based on the three constant time-delays, τ1, τ2, and τ3. Hopf bifurcation occurs in the addressed model at the estimated bifurcation points τ10, τ20, τ30, and τ10*. The numerical simulations fit to real observations proving the effectiveness of the theoretical results. Fractional-order and time-delays successfully enhance the dynamics and strengthen the stability condition of the asymptomatic COVID-19 model. © 2023 World Scientific Publishing Company.

Stability analysis of a fractional-order SEIR epidemic model with general incidence rate and time delay

In this paper, we investigate the qualitative behavior of a class of fractional SEIR epidemic models with a more general incidence rate function and time delay to incorporate latent infected individuals. We first prove positivity and boundedness of solutions of the system. The basic reproduction number (Formula presented.) of the model is computed using the method of next generation matrix, and we prove that if (Formula presented.), the healthy equilibrium is locally asymptotically stable, and when (Formula presented.), the system admits a unique endemic equilibrium which is locally asymptotically stable. Moreover, using a suitable Lyapunov function and some results about the theory of stability of differential equations of delayed fractional-order type, we give a complete study of global stability for both healthy and endemic steady states. The model is used to describe the COVID-19 outbreak in Algeria at its beginning in February 2020. A numerical scheme, based on Adams–Bashforth–Moulton method, is used to run the numerical simulations and shows that the number of new infected individuals will peak around late July 2020. Further, numerical simulations show that around 90% of the population in Algeria will be infected. Compared with the WHO data, our results are much more close to real data. Our model with fractional derivative and delay can then better fit the data of Algeria at the beginning of infection and before the lock and isolation measures. The model we propose is a generalization of several SEIR other models with fractional derivative and delay in literature. © 2023 John Wiley & Sons, Ltd.

POCT detection device based on thermal convection fluorescence PCR amplification

This article is based on the principle of thermal convection PCR and nucleic acid fluorescence intensity detection technology. The principle of thermal convection PCR is to form a temperature difference by separately controlling the upper temperature and the bottom temperature of the reaction tube. The lower temperature liquid at the upper part has relatively high density or specific gravity, and the upper and lower liquids will produce convection, which drives the flow of molecules in the tubular chamber. The reaction solution is formed into thermal convection in the reaction test tube and subjected to different temperatures, so as to meet the required conditions for the reaction of different enzymes, and realize the pre-denaturation, annealing and extension processes in the nucleic acid PCR amplification in a short time. Nucleic acid fluorescence intensity detection technology involves embedded system design for device control and signal analysis, optical system design for optical signal filtering and collection, and differential amplifier circuit design. The embedded system design is based on the development of precise temperature control system, motion system and signal analysis system based on Stm32 single-chip microcomputer. The temperature control system includes independent temperature control to control the heaters at the bottom of the reaction tube and the top of the reaction tube respectively;the motion system includes sample switching and switching of the light source in the imaging system. The optical system design includes 540nm FAM excitation light source, 570nm CY3 excitation light source and spherical lens focusing excitation system. This device uses a photodiode to convert the optical signal into an electrical signal, and then amplifies the collected electrical signal with a two-stage operational amplifier through a two-color light differential amplifier circuit, and then uses the signal analysis system to record and display the electrical signal changes in real time, and Make a qualitative analysis. This device not only has the advantages of low cost and high sensitivity, but also solves the key problem of the long time (more than 2 hours) of the whole process of real-time fluorescent quantitative PCR in the detection of new crown nucleic acid and cannot be screened quickly on site. The PCR time of this device is from 2 The hour is reduced to 30 minutes, which is suitable for POCT inspections, and achieves rapid screening goals for crowds of people, which is conducive to responding to acute nucleic acid detection and large-scale nucleic acid detection. This device is currently used with COVID-19 detection reagents to detect new coronaviruses, and realize the detection of 20 copies of nucleic acid sensitivity within 30 minutes. Four samples can be processed in batches at a time, and the sample size for single processing can be increased appropriately according to needs. This device provides rapid and sensitive screening methods for global epidemic prevention and control, and is of great significance to improve human health. This device can also be applied to other rapid nucleic acid detection fields. With different nucleic acid detection reagents, this device can detect different gene loci, and has a broad development space and application fields. © 2023 SPIE.

Pressure Prediction System in Lung Circuit Using Deep Learning

A massive number of patients infected with SARS-CoV2 and Delta variant of COVID-19 have generated acute respiratory distress syndrome (ARDS) which needs intensive care, which includes mechanical ventilation. But due to the huge no of patients, the workload and stress on healthcare infrastructure and related personnel have grown exponentially. This has resulted in huge demand for innovation in the field of automated health care which can help reduce the stress on the current healthcare infrastructure. This work gives a solution for the issue of pressure prediction in mechanical ventilation. The algorithm suggested by the researchers tries to predict the pressure in the respiratory circuit for various lung conditions. Prediction of pressure in the lungs is a type of sequence prediction problem. Long short-term memory (LSTM) is the most efficient solution to the sequence prediction problem. Due to its ability to selectively remember patterns over the long term, LSTM has an edge over normal RNN. RNN is good for short-term patterns but for sequence prediction problems, LSTM is preferred. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

The moderating role of market turbulence beyond the Covid-19 pandemic and Russia-Ukraine crisis on the relationship between intellectual capital and business sustainability

This paper examines the role of Intellectual Capital (IC) and its contribution to Business Sustainability (BS) among Large Manufacturing Firms (LMF) in Malaysia. It seeks to explain the relationship between them under turbulent market conditions. The study used the survey method to collect data from 203 large companies, and the hypotheses were tested using Partial-Least Squares-Structural Equation Modeling. Based on the findings, two dimensions of IC, namely Human capital (HC) and Structural Capital (SC), had a significant effect on business sustainability, but Relational Capital (RC) did not. Also results indicate that Market Turbulence (MT) moderates the relationship between two IC dimensions, HC and RC but not that between SC and BS. The study findings can be used as guidelines by CEOs of LMFs, policy makers and researchers to comprehend positive the influence of MT and IC on BS. © 2022

Digitalizing the Speed Control Circuit of Three-Phase Induction Motor Based on Pulse-Width Modulation using Proteus Software

The practice course about electric motor controlling is essential in establishing undergraduate students' skills in many electronics and electrical engineering majors. However, due to the current COVID-19 situation, teaching this practical subject has become unlearnable in the laboratory room. Therefore, the urgent requirement is to find a solution to virtualize many electrical-motor control lessons for online learning during the distant social period. In this paper, we propose a potential solution to online practical electrical motor control coursework based on Proteus software. Unlike the common Matlab Simulink approach, the Proteus has the advantage of digitizing both the Arduino device and the electric circuits. We demonstrate the usefulness of Proteus 8.2 software by implementing a circuit to control a 3-phase asynchronous motor using the pulse width control method, named sine PWM. Through the learning on Proteus software, students not only review the theoretical knowledge of electrical motors but also learn how to apply the theory through simulating virtualized Arduino devices and building a control circuit with the control block to control the motor in real-Time. Furthermore, Proteus also supports printing out the control circuit board for the user. Proteus is, therefore, a suitable solution for online teaching of practice subjects for related majors. © 2022 IEEE.

COVID-19 Lung CT Images Recognition with Superscalar Winograd Circuit Based on VGG19

In this paper, we proposed COVID-19 lung CT (computed tomography) images recognition with superscalar winograd circuit based on VGG19. We adopt the VGG-19 machine learning architecture to recognize lung CT images and speed up neural network operations through Superscalar Winograd Circuit. After a series of experiments, our proposed method has a high pneumonia recognition rate and high computational efficiency. © 2022 IEEE.

All quiet on the COVID-19 front-Real experience must be bought for power electronics beginners-Real e

This paper introduces some actual efforts of our laboratory in power electronics education, especially for newly assigned undergraduate students, even during COVID-19 pandemic. The real hands-on experience is still important as a 'first step' before introducing model-based power electronics circuit design and analysis, which will become increasingly important in the future. © 2022 IEEE.

Remote Access Active Experiential Learning with Industrial Instruments

One of the grand challenges recently thrust on engineering education is providing active, experiential learning that can flex with significant global events such as pandemics and meet the needs of individual students. The COVID pandemic is a prominent driving force for change, but beyond that, meeting the needs of students with physical, economic, or temporal barriers, such as with professional learning, is critical for our education system. This is especially true for university laboratories, where hands-on nature is often more challenging to provide remote learning services to engineering students. In electrical engineering education, the immediate response to the pandemic-induced closure of university laboratories was to cancel laboratory learning, assemble hobbyist-type experimental kits, and ship the kits to students to learn fundamentals. This approach provided a flexible experimental arrangement for students but was limited due to a lack of student exposure to tools and processes used in the industry. These learnings are critical to students who want to excel in internships or their first regular employment. Here, we describe the development of a remote active, experiential training program based on industrial tools for students to learn at a distance with industrial-type laboratory equipment. A pedagogical electronic amplifier was set up in the laboratory. Instead of students attaching probe clips to various parts of the amplifier to test, electronic laboratory switches, controlled remotely by students, allowed them to probe salient parts of the amplifier and even substitute different electronic components. Based on newly available commercial software and hardware, the system will enable students access to a laboratory session, interact with other students via online chat, and conduct experiments. In this innovative practice full paper, we will review the method approach, experimental laboratory configurations, and the learning outcomes of this remote learning technique. This method is an innovative approach to remote learning. It is potentially extensible beyond electrical and electronic engineering to other engineering domains, such as photonics, mechatronics, civil, and perhaps chemical, where electronically controlled laboratory equipment is included in the student's experiential learning. © 2022 IEEE.

Overview of On-board IC Ticket Equipment System for Rolling Stock

West Japan Railway Company (hereinafter referred to as "JR West") introduced the IC card ticket system "JCOCA" and has expanded the use area of the IC card. For the local lines, the onboard type of ticket gate machine for the IC card ticket is introduced to allow to use the IC card. This type of ticket gate machine is also effective for reducing the burden on the train crew. The introduction of this on-board type of IC ticket gate is our effort to allow passengers to smoothly get on/off and to provide safe and secure transport service under the COVID-19 epidemic. © 2022 Japan Railway Engineers' Association. All rights reserved.

The Sustainability of the Supply Chain of the City of Meknes in Fruits and Vegetables Tested by the Covid-19

This article examines the sustainability of the supply chain of fruits and vegetables (SCF V), in Meknes, Morocco, in relation with Covid-19 pandemic. Our methodology is based on a theoretical framework associated with the dimensions of sustainability (economic, social, environmental, territorial and health). We mobilize a database resulting from 121 surveys conducted among producers, distributors and consumers. To process the collected data, we have chosen the method of weighting the sub-indicators by maximizing scores from the Data Envelopment Analysis (DEA) approach and the method of weighting by arithmetic means. The results show that the overall durability of SCFV/Meknes has improved considerably, especially during the strict containment related to COVID-19. © 2022 IEEE.

Timing analysis of the sanitization process due to the COVID-19 pandemic in an elementary school using simulation

The recent pandemic caused by the COVID-19 virus, forced all educational institutions in the Mexican national territory to close their doors to face-to-face classes during the month of March 2020. It was many months later, when the Ministry of Public Education announced the return to hybrid classes for the 2021-2022 school year. This represented a challenge for schools in this national territory, particularly those from primary level since all institutions must have had biosafety and disinfection protocols in order to receive all their students and safeguard their safety. For this reason, a primary school was chosen for this study and a discrete event simulation was performed;the main objective of the simulation was to analyze the time invested in the different sanitizing stations, as well as the establishment of new stations to choose the best option that can lead to a timely disinfection process that accommodates the total number of students without affecting the planned day-to-day academic activities. © 2022 The Authors.

Recycling Test Methods to Improve Test Capacity and Increase Chip Shipments

In this research, we quantified semiconductor fabrication capability parameters and test capability parameters and used a digital integrated circuit test model (DITM) to discuss the impact of the test guardband (TGB) on test yield. Furthermore, the DITM can be used to estimate the yield distribution trend of future semiconductor products using data from the IEEE International Roadmap for Devices and Systems (IRDS) 2021 Table. With the COVID-19 pandemic, the global semiconductor industry is facing chip and material shortages. Furthermore, test technology lags behind semiconductor manufacturing technology, and the test yield of production capacity is deteriorating, seriously affecting the entire semiconductor supply chain. Therefore, we proposed the recycling test method, extending the test time, moving TGB, and repeatedly looking for reliable products. These parameters were calculated using the estimated product parameters released by the IRDS 2021. We proved that the proposed recycling test method could improve the high-yield target of semiconductor testing. As long as test methods are used properly, not only can high-yield shipments be made, but also companies’overall profit will be significantly improved, and the problem of chip shortages will be solved. IEEE