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1.
29th IEEE International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2022 ; 2022.
Article in English | Scopus | ID: covidwho-2063267

ABSTRACT

This paper evaluates the integration of the UV ray applied to disinfection in food industry with an automatic packaging machine, instead of traditional methods. This systematic review allows to evaluate the most appropriate solution to the selection of the automatic process and devices involved, in order to reduce the bacterial and virus with UV treatment by a schematic development and its verification through modeling and simulation software. The results obtained demonstrate the ability to control the intensity of UV rays emitted by an OSRAM TYPE UVC lamp with a range between 200-280 nm. It is appropriated for a complete disinfection of food products. And also, that the Proportional-Integrative Control system regulates the set-point in a rise time of 24 ms, settlement of 87.8 ms and overshoot of 13.8%. Our findings are the the control time, efficiency, accuracy and uniformity to be integrated into the packaging process;compared to thermal disinfection methods;with a settlement error of ± 1.48 and its ability to counteract Covid-19. © 2022 IEEE.

2.
2022 IEEE International Conference on Electrical, Computer, and Energy Technologies, ICECET 2022 ; 2022.
Article in English | Scopus | ID: covidwho-2063233

ABSTRACT

The rapidly growing market of eSports has become a lucrative industry. Sim racing is one of the traditional sports that gain increasing popularity in eSports. With raising profits, lucrative sponsoring contracts, and competitive price money, incentives for fraud are also on the upraise. This is further facilitated by the COVID-19 pandemic, which led to the substitution of live eSport events by virtual formats. Particularly, in sim racing it becomes increasingly challenging to verify the contestants identity in virtual events. Here, we propose and evaluate a generic workflow to identify personal driving style by transforming raw racing data (including measurements extracted from the simulation software and connected simulator hardware) into a comparable representation (fingerprint). As data base we used an extensive collection of telemetry data recorded from the racing simulation Assetto Corsa on 3 immersive motion simulators. The set contains over 2,000 laps of seven player recorded in weekly sessions. The experiments demonstrate the feasibility to distinguish players using the proposed method on different tracks, car models, and motion simulators. Due to the extensive experiments, we could achieve a driver separation score of up to 89%. The raw data and the raw results are made publicly available on Github. © 2022 IEEE.

3.
48th International Conference on Very Large Data Bases, VLDB 2022 ; 15(12):3606-3609, 2022.
Article in English | Scopus | ID: covidwho-2056499

ABSTRACT

Kernel density visualization (KDV) has been widely used in many geospatial analysis tasks, including traffic accident hotspot detection, crime hotspot detection, and disease outbreak detection. Although KDV can be supported by many scientific, geographical, and visualization software tools, none of these tools can support high-resolution KDV with large-scale datasets. Therefore, we develop the first versatile programming library, called LIBKDV, based on the set of our complexity-optimized algorithms. Given the high efficiency of these algorithms, LIBKDV not only accelerates the KDV computation but also enriches KDV-based geospatial analytics, including bandwidth-tuning analysis and spatiotemporal analysis, which cannot be natively and feasibly supported by existing software tools. In this demonstration, participants will be invited to use our programming library to explore interesting hotspot patterns on large-scale traffic accident, crime, and COVID-19 datasets. © 2022, VLDB Endowment. All rights reserved.

4.
Disease Surveillance ; 37(6):802-806, 2022.
Article in Chinese | GIM | ID: covidwho-2055475

ABSTRACT

Objective: To introduce the principle and method ofa-Sutte model, establish a a-Sutte model by using software R, compare the fitting and prediction effects of thea-Sutte model and multiple seasonal autoregressive integrated moving average model, SARIMA model and provides reference for the application of thea-Sutte model in epidemic prediction.

5.
6th International Conference on Virtual and Augmented Reality Simulations, ICVARS 2022 ; : 106-114, 2022.
Article in English | Scopus | ID: covidwho-2053364

ABSTRACT

Under such severe circumstances, accurately predicting the development trend of the epidemic is of great significance for subsequent intervention and control. This paper proposes an improved SEIRS dynamic model based on the infectious disease prediction model (SEIR model), which can accurately predict the development trend of the new coronavirus pneumonia. First, the Python simulation technology combined with the SEIRS model was used to predict the spread of Wuhan in the 40 days since the outbreak, and compared with the real data in Wuhan. After fully verifying the correctness and applicability of the model, the model was applied to Shanghai. Next, use Python simulation technology to predict the spread and end time of the epidemic in Shanghai, and set different control intensities by changing the parameter , and analyze the impact of different control start times and different control intensities on the new crown pneumonia epidemic. Finally, the experimental results are analyzed to propose corresponding epidemic prevention and control measures, and the model in this paper is extended to a wider range of application scenarios. © 2022 ACM.

6.
3rd International Conference on Artificial Intelligence in Electronics Engineering, AIEE 2022 ; : 80-84, 2022.
Article in English | Scopus | ID: covidwho-2053338

ABSTRACT

This article presents the design and prototyping of an electronic mask as personal protective equipment for the virus pandemic known as COVID - 19. Needs were identified such as: tightness and comfort. Requirements for use for long periods of time;this was considered for the design, also it has an adjustable ventilation system. The mask was simulated and validated with Solidworks Flow Simulation software, in addition a PID control model was implemented, thereby, it was shown that enough flow is generated to vary the temperature in a range of 20 to 37.2 ° C inside the mask. The design considers an outlet duct and an inlet duct with filters that prevent the entry of polluting particles, providing adequate protection. The prototype was made by 3D printing, And the thermal stability was achieved with the implementation of the temperature regulation system. The results obtained were validated, and they allow to future research to provide greater efficiency to masks. © 2022 ACM.

7.
6th International Conference on Management in Emerging Markets, ICMEM 2021 ; 2021.
Article in English | Scopus | ID: covidwho-2052012

ABSTRACT

Radiology department at a tertiary referral hospital faces service operation challenges such as huge and various patient arrival, which can increase the probability of patient queuing. During COVID-19 pandemic, it is mandatory to apply social distancing protocol in the radiology department. A strategy to prevent accumulation of patients at one spot would be required. The aim of this study is to identify an alternative solution which can reduce the patient's waiting time in MRI services. Discrete event simulation (DES) is used for this study by constructing several improvement scenarios with Arenao simulation software. Statistical analysis is used to test the validity of base case scenario model, and to investigate performance of the improvement scenarios. The result of this study shows that the selected scenario is able to reduce 83.6% of patient's length of stay, which lead into a more efficient MRI services in radiology department, be able to serve patients more effectively, and thus increase the patient satisfaction. The result of the simulation can be used by the hospital management to improve the operational performance of the radiology department. © 2021 IEEE.

8.
19th IEEE International Conference on Mechatronics and Automation, ICMA 2022 ; : 581-586, 2022.
Article in English | Scopus | ID: covidwho-2052009

ABSTRACT

Due to the rapid spread of COVID-19 around the world, people's diet environment has also changed, and gastrointestinal diseases have become a common disease around us so far, and the prevalence is on the rise. But because traditional treatments for gastrointestinal diseases are unfriendly to patients, they often require the administration of anesthetics, which can cause side effects. Wireless capsule endoscope is a kind of medical robot that can alleviate the pain of patients, and the research on wireless capsule endoscope has been gradually mature at home and abroad, this paper designed a new four-page propeller-driven biopsy capsule robot. The optimal number of propeller pages is obtained by comparing the velocity of three different numbers of propeller blades in the pipeline. The three axis Helmholtz coil driving system and biopsy module based on CAM structure are also introduced. At the same time, the anchoring module used for precise biopsy of the robot is introduced, so as to ensure that the biopsy capsule robot can reach the specified position quickly and accurately and complete the biopsy task. Finally, we use simulation software to simulate the velocity and pressure of different propeller blades in the same liquid. © 2022 IEEE.

9.
Manufacturing Letters ; 33:970-981, 2022.
Article in English | Scopus | ID: covidwho-2049661

ABSTRACT

The pedagogy of a first-year engineering course in manufacturing is presented. This course entitled Manufacturing and Society involves collaboration with social science, is based on industrial robots as the central theme to attract students’ interests and utilizes the flipped classroom approach for delivery. We hypothesize that, in one semester, recent high school graduates will be able to gain knowledge in manufacturing by learning the computer-aided engineering (CAD) software, applying CAD to design a penholder, fabricating the penholder using additive manufacturing and computer-aided manufacturing (CAM) software, programming the robot to create a toolpath for the pen, drawing using the pen on the penholder guided by a robot, and elaborating on impacts of robotic painting on society from a social science perspective. This course is designed to give students, regardless of their intended major in engineering, broad knowledge in manufacturing via 10 engineering, 3 social science, and 10 technical communication lectures;8 labs;and 4 projects. The social science lectures and discussions focus on how knowledge about society can be used to inform design and manufacturing decisions, social science research methods for understanding how engineers and technology can impact people's lives, and changing trends in work, the workplace, and the future workforce as it relates to manufacturing. This course aimed to give undergraduate first-year engineering students a positive view of advanced manufacturing and its impact on society. Student evaluations and comments were positive and affirmed the learning objective of teaching manufacturing to the first-year engineering students. The flipped classroom approach was demonstrated to be ideal during the COVID-19 pandemic with limited capacity for in-person lectures and labs. The use of flipped classrooms allowed students to learn at their own pace, review and reinforce knowledge, have a closer interaction with instructors, and reduce the number of technical errors using simulation tools. This course with the support of flipped classroom pedagogy can be successfully implemented in the post-pandemic era, devoting the time of the class to answer questions, expand upon the class content and have a closer in-person interaction with students. © 2022

10.
129th ASEE Annual Conference and Exposition: Excellence Through Diversity, ASEE 2022 ; 2022.
Article in English | Scopus | ID: covidwho-2046988

ABSTRACT

Microcontroller programming is an essential part of K-12 Science, Technology, Engineering, and Mathematics (STEM) education. Experience with microcontroller programming is a gateway to many topics in this discipline, such as electrical engineering and programming. Hands-on experiences using microcontrollers are critical for student engagement and deeper understanding. However, as classes and field trips transitioned online due to the COVID-19 pandemic, educators encountered many difficulties adapting the microcontroller experiments to remote online education. One challenge is that traditional computer software for microcontroller experiments is not easy to set up. In remote education, students cannot be expected to install the software and do the configurations on their own computers at home. The second problem is that it is hard to monitor the students' progress and give feedback in real-time. Even though there are many online collaborative coding platforms, none of them support microcontrollers. In this paper, we introduce a comprehensive solution for remote education featuring microcontrollers. An online education platform was developed that allows the students to program the microcontroller using CircuitPython with no software installation or configuration. It also allows instructors to monitor students' work remotely in real-time. In addition, a microcontroller development board for experiments in which students apply programming knowledge to the function of traffic lights was designed. A CircuitPython module for the development board was also developed, which allowed the students to focus more on the logic of the traffic lights and less on potential hardware issues. This online education solution can also be adapted to meet different needs by designing different development boards for different scenarios, including breadboard experiments to focus on circuits, adopting more powerful microcontrollers for advanced programming, and a variety of other applications for use in differentiated instruction. The proposed traffic lights engineering academy was provided to a local school district and got positive feedback. The experiences and best practices are also discussed in this paper. © American Society for Engineering Education, 2022.

11.
129th ASEE Annual Conference and Exposition: Excellence Through Diversity, ASEE 2022 ; 2022.
Article in English | Scopus | ID: covidwho-2045998

ABSTRACT

During the closure of K-12 schools and universities due to the COVID-19 pandemic, many educators turned to web conferencing tools such as Zoom and WebEx to deliver online lectures. For courses with labs, some teachers provide recorded videos of real labs. Watching recorded lab videos is a passive experience, as the procedures and point of view are fixed, and students do not have any control of the lab and thus miss the opportunity to explore different options, including making mistakes that is important part of the learning process. One approach that holds great potential to enhance laboratory experience for online education is the use of computer-based modeling and simulation tools. Simulation based virtual laboratories emulate lab equipment and configurations in highly realistic 3D environments and can provide very effective learning experiences. While there exist limited interactive lab computer simulations for various subjects, their presentations are still very primitive and often lack realism and complexity. This paper presents methodologies and preliminary findings on rapid development of advanced virtual labs using modeling and simulation for in-person and online education. The importance of modeling and simulation has long been recognized by the scientific community and agencies such as DoD and NSF. However, high-quality simulations are not commonplace, and simulations have not been widely employed in education. Existing simulations for education lack interoperability and compatibility. While there are sporadic uses of computer-based simulations in education that were developed in a piecemeal fashion, there was never systematic development at an industry level for such purposes. Virtual lab development usually require substantial amount of effort and lack of systematic research on rapid virtual lab development hinders their wide use in education. This paper proposes a wholistic and systematic approach for addressing the issues in rapid lab simulation development from several perspectives, including rapid generation of virtual environment, integration of state-of-the-art industry leading software tools, advanced software design techniques that enables large scale software reuse, and innovative user interface design that facilitate the configuration and use of virtual labs by instructors and students. This paper will implement a virtual circuit lab that emulates a circuit lab for the course PHYS 303 offered at Old Dominion University and will be used to elucidate the crucial methodologies for rapid virtual lab development. The virtual lab contains highly realistic visual renderings and accurate functional representations of sophisticated equipment, such as digital oscilloscopes, function generators, and digital multimeters, and authentic rendition of the lab space. The virtual lab allows analog and digital circuit simulation by integrating the de-facto industry standard circuit simulation engine SPICE and Xspice, supporting the circuit labs in course PHYS 303. The Unity game engine is used to develop the front end of the virtual lab. Advanced software development methodologies will be investigated to facilitate software reuse and rapid development, e.g., the same simulation code can be used to support equipment manufactured by different vendors. The paper will also investigate the impact of fidelity of the virtual lab, e.g., equipment and lab room, on student learning outcomes and efficacy. © American Society for Engineering Education, 2022.

12.
129th ASEE Annual Conference and Exposition: Excellence Through Diversity, ASEE 2022 ; 2022.
Article in English | Scopus | ID: covidwho-2045990

ABSTRACT

All first-year students at the J. B. Speed School of Engineering (SSoE) at the University of Louisville (UofL) are required to complete a two-course sequence. The purpose of the two-course sequence is to introduce incoming students to the fundamentals and profession of engineering. The first course in the sequence is titled Engineering Methods, Tools, & Practice I (ENGR 110) and primarily focuses on introduction to and practice with fundamental engineering skills. The second course Engineering Methods, Tools, & Practice II (ENGR 111) is a makerspace-based course primarily focused on application and integration of the fundamentals learned in ENGR 110. ENGR 111 includes a variety of fundamental skills in its instruction, one of which is programming. Therefore, all disciplines of SSoE engineering students are exposed to the basics and applications of programming through this course sequence. Programming instruction in ENGR 111 is designed to include relevant software development skills that students might encounter in the engineering profession. The students have learned initial programming skills in their ENGR 110 course through the Python programming language. In ENGR 111, students practice programming skills learned in ENGR 110 on two different platforms: Arduino Microcontrollers (Arduino) and Programmable Logic Controllers (PLCs). In normal face-to-face semesters, students are put into teams of 3 to 4 and given modules to develop and practice these skills (two for Arduino, two for PLCs). Due to the COVID-19 pandemic, ENGR 111 was augmented into a synchronous remote course to avoid close proximity and shared tools in the makerspace. Arduino programming instruction was performed using Tinkercad (tinkercad.com), a website that allows for Arduino programming and circuitry simulations. PLC instruction was performed utilizing a free online PLC simulator website, “PLCfiddle” [1]. At the end of each semester, students take a survey on their perceptions of the course. Included in this survey are questions pertaining to programming instruction. These questions assess student confidence in programming and platform preference. Results of these questions from Spring 2019 (a makerspace iteration) and Spring 2021 (a remote iteration) are compared in this paper. © American Society for Engineering Education, 2022.

13.
129th ASEE Annual Conference and Exposition: Excellence Through Diversity, ASEE 2022 ; 2022.
Article in English | Scopus | ID: covidwho-2045602

ABSTRACT

The challenges associated with achieving hypersonic flight, developing advanced propulsion systems, and designing reusable launch platforms are strongly interdisciplinary. Exposing undergraduate students to interdisciplinary research is recognized as a means to equip society's future engineers and scientists with the broad skillset necessary to contribute to these areas. The jointly funded NSF-DoD REU site Advanced Technologies for Hypersonic Propulsive, Energetic and Reusable Platforms (HYPER) unites multidisciplinary interests to study advanced structures and systems with application to hypersonics, space, propulsion, and energy. Over the course of two 10-week summer sessions (2019 and 2021), participants have gained hands-on training in contemporary challenges such as: (1) utilizing advanced manufacturing techniques for high-value components, (2) integrating in situ monitoring of stress-strain evolution, (3) developing novel methods for improved internal cooling and heat transfer effectiveness, (4) mitigating flutter through advanced rotor dynamic control, etc. Eleven research projects have been crafted to engage students in PhD-level topics. Many of these challenges rely on approaches that cut across disciplines and research techniques (e.g., experiments and computer simulation). The present reporting serves as a synopsis of challenges, advances, and lessons learned conducting the research thus far. The site HYPER has six core objectives that relate to: (1) preparing students for graduate school and/or research-oriented careers, (2) fostering technical skills in student participants, (3) improving participants' communication skills, (4) marketing to and recruiting a diverse group of participants, and more. Assessment of the program outcomes according to these objectives are reported here with data gathered after two years. Program outcomes were conducted with an external evaluator affiliated within the University of Central Florida's Program Evaluation and Educational Research Group (PEER). Results demonstrate a very effective site with strongly positive outcomes for all participants. Insights are provided so this research effort may be confirmed by other independent sites. It should be noted that the 2020 session was postponed out of an abundance of caution based on the uncertain and evolving conditions facilitated by the COVID-19 pandemic. © American Society for Engineering Education, 2022.

14.
PLoS Global Public Health ; 2(7), 2022.
Article in English | CAB Abstracts | ID: covidwho-2021475

ABSTRACT

This study uses two existing data sources to examine how patients' symptoms can be used to differentiate COVID-19 from other respiratory diseases. One dataset consisted of 839,288 laboratory-confirmed, symptomatic, COVID-19 positive cases reported to the Centers for Disease Control and Prevention (CDC) from March 1, 2019, to September 30, 2020. The second dataset provided the controls and included 1,814 laboratory-confirmed influenza positive, symptomatic cases, and 812 cases with symptomatic influenza-like-illnesses. The controls were reported to the Influenza Research Database of the National Institute of Allergy and Infectious Diseases (NIAID) between January 1, 2000, and December 30, 2018. Data were analyzed using case-control study design. The comparisons were done using 45 scenarios, with each scenario making different assumptions regarding prevalence of COVID-19 (2%, 4%, and 6%), influenza (0.01%, 3%, 6%, 9%, 12%) and influenza-like-illnesses (1%, 3.5% and 7%). For each scenario, a logistic regression model was used to predict COVID-19 from 2 demographic variables (age, gender) and 10 symptoms (cough, fever, chills, diarrhea, nausea and vomiting, shortness of breath, runny nose, sore throat, myalgia, and headache). The 5-fold cross-validated Area under the Receiver Operating Curves (AROC) was used to report the accuracy of these regression models. The value of various symptoms in differentiating COVID-19 from influenza depended on a variety of factors, including (1) prevalence of pathogens that cause COVID-19, influenza, and influenza-like-illness;(2) age of the patient, and (3) presence of other symptoms. The model that relied on 5-way combination of symptoms and demographic variables, age and gender, had a cross-validated AROC of 90%, suggesting that it could accurately differentiate influenza from COVID-19. This model, however, is too complex to be used in clinical practice without relying on computer-based decision aid. Study results encourage development of web-based, stand-alone, artificial Intelligence model that can interview patients and help clinicians make quarantine and triage decisions.

15.
29th International Conference on Systems, Signals and Image Processing, IWSSIP 2022 ; 2022-June, 2022.
Article in English | Scopus | ID: covidwho-2018927

ABSTRACT

This article describes the implementation of a distance learning course in programmable logic control designed and delivered during the Covid 19 pandemic. The course has a strong practical orientation, so it was a particular challenge to maintain this orientation in the remote implementation of the course. The goal was achieved through a combination of software simulation tools, remote access to computers in the lab and interactive sessions with an instructor. © 2022 IEEE.

16.
57th International Scientific Conference on Information, Communication and Energy Systems and Technologies, ICEST 2022 ; 2022.
Article in English | Scopus | ID: covidwho-2018824

ABSTRACT

This paper proposes pandemic support system design exercises from both hardware and software perspective as constituent part of higher education computer science courses. Two case studies in context of computer science and automation study programmes at University of Niš, Faculty of Electronic Engineering in Serbia ae covered: Intelligent Information Systems and Microcontroller Programming. In case of the first one, the topics cover information system implementation relying on Java Enterprise Edition (JEE) technology with presence of machine learning elements provided by Weka API, so smart vaccination process support information system is presented as example. On the other side, the focus on the second course is on PIC16 family microcontrollers and RTOS-based system implementation using CCS C compiler and presented example represents control unit for indoor coronavirus safety control. © 2022 IEEE.

17.
11th IFAC Symposium on Control of Power and Energy Systems, CPES 2022 ; 55:479-484, 2022.
Article in English | Scopus | ID: covidwho-2015378

ABSTRACT

This paper describes a microclimate monitoring system consisting of a LoRaWAN network of wireless climate sensors, a data collector and analytical software. The system is a part of the ICS RAS SmartGrid Centre project for predicting building energy consumption. During the design phase, the authors considered the concept of comfort, which is involved in setting control objectives for HVAC plants. It was necessary to overcome some characteristics of the LoRaWAN protocol, such as floating data transmission period and limited intensity of sensor communication. These have been overcome by post-processing the data with Python software, using libraries numpy and scipy. The collected data was passed through an interpolation filter for synchronization, and the resulting data is freely available in dataset format on our website for all interested researchers. Additionally, weather data was collected using a local meteostation to be considered as external disturbances in analysis problems. This paper also considers an approach to passive identification of the thermal protection parameters of a building. The coronavirus lockdown period was chosen to assume the impact of visitors negligible. The parameters are supposed to be estimated by correlation analysis. The estimates obtained should be compared with the values calculated according to ISO and Russian construction standards for diagnostic reasons. © 2022 Elsevier B.V.. All rights reserved.

18.
Revista Latinoamericana de Ciencias Sociales, Niñez y Juventud ; 20(3):1-33, 2022.
Article in Spanish | ProQuest Central | ID: covidwho-2002676

ABSTRACT

Este estudio tiene como objetivo describir la adaptación de las ideas de la cognición 4E en el estudio del aprendizaje de las matemáticas en la investigación contemporánea, de manera que pueda proporcionar estrategias para cualificar los procesos pedagógicos y didácticos en las aulas en tiempos de pospandemia. Se realizó la búsqueda de artículos a texto completo en las bases de datos Science Direct y Ebsco Academic Search Ultimate, de los últimos cuatro años. Se seleccionaron 56 artículos, que se analizaron mediante análisis de conglomerados, nubes de palabras y mapas jerárquicos en Nvivo 11. Se obtuvieron cuatro núcleos temáticos (andamiaje, trayectoria sociocultural, numerosidad y adquisición de conceptos básicos en matemáticas y exploración de nichos matemáticos) que permiten avanzar en la implementación de mejoras en la enseñanza y el aprendizaje en pospandemia.Alternate :This study aims to describe the adaptation of the ideas of 4E cognition in research on Mathematics learning in contemporary research. These ideas can provide strategies to improve pedagogical and didactic processes in classrooms during the post-pandemic period. Full-text articles published in the last 4 years were searched for in the Science Direct and Ebsco Academic Search Ultimate databases. A total of 56 articles were selected and were analyzed through the generation of cluster analysis, word clouds and hierarchical maps in the NVivo 11 software. Four thematic cores were identified (scaffolding;sociocultural trajectory;numeracy and acquisition of basic concepts in mathematics;and exploration of mathematical niches) that contribute to improvements in teaching and learning in the post-pandemic period.Alternate :Este estudo tem como objetivo descrever a adaptação das ideias da cognição 4E no estudo da aprendizagem da Matemática na pesquisa contemporânea, de modo que possa fornecer estratégias para qualificar processos pedagógicos e didáticos em sala de aula em tempos pós-pandêmicos. Artigos de texto completo foram pesquisados nas bases de dados Science Direct e Ebsco Academic Search Ultimate nos últimos 4 anos. Foram selecionados 56 artigos, os quais foram analisados por meio de análise de cluster, nuvem de palavras e mapas hierárquicos no Nvivo 11. Foram obtidos quatro núcleos temáticos (andaimes, trajetória sociocultural, multiplicidade e aquisição de conceitos básicos em matemática e exploração de nichos matemáticos) que permitem avançar na implementação de melhorias no ensino e aprendizagem no pós-pandemia.

19.
Alinteri Journal of Agriculture Science ; 36(2):94-103, 2021.
Article in English | CAB Abstracts | ID: covidwho-1975876

ABSTRACT

The Covid-19 pandemic has shown that food supply chains are the most critical component of economic and human activities. It has also created a lot of interest among researchers, practitioners and policymakers to study the significant challenges of the food supply chain caused by the pandemic. Therefore this work wanted to investigate the critical supply chain challenges due to Covid-19 with the help of a systematic literature review of well-established articles published in interdisciplinary journals. The selection of thirty one papers was made through a research protocol that helped select and identify research papers which were coded with the help of qualitative software Atlasti 9.0 to study which supply chain challenge amongst disruption, forecasting and inventory was most prominently studied in the literature. Results of software coding revealed that disruption was coded 170 times whereas forecasting 10 times and inventory 37 times as challenges of food Supply Chain Management (SCM). Therefore, it was concluded that most of the researchers considered disruption as one of the significant food supply chain challenges. Further coding also revealed that lockdown and labour related issues were the primary reasons for food supply chain disruption.

20.
4th International Conference on Computational Intelligence, Communications and Business Analytics, CICBA 2022 ; 1579 CCIS:403-416, 2022.
Article in English | Scopus | ID: covidwho-1971567

ABSTRACT

Electronic commerce (E-commerce) along with online shopping is rapidly increasing now-a-days specially in current scenario of COVID 19 pandemic. Such immensely expanding online marketing creates a plethora of opportunities for the companies to trade wider on the globe as well as enabling the customers to avail better products at their increased convenience. In this paper, we have addressed the affects of financial loss related to the return and replacement policy of online shopping particularly in Cash-on-Delivery (CoD) payment method. We have proposed a software solution using semaphore programming tool for the efficient management of CoD payment method. Analysing the customer’s previous transaction records, the proposed method determines suitable policy for the return and replacement option of the concerned customer. The objective is to minimize the financial loss for an unnecessary cancellation and replacement policy without hampering customers’ interest. Hence we have proposed an algorithm for efficient CoD management. The proposed algorithm uses counting semaphore to implement a customer reputation variable which will help the companies to keep track of each customer for each transaction precisely and determine a suitable penalty policy for the return and replacement option of the said customer. The working principle is demonstrated through a flow chart. We have performed extensive simulations in python to establish the novelty of the proposed approach. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

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