ABSTRACT
Humor is a cognitive construct that predominantly evokes the feeling of mirth. During the COVID-19 pandemic, the situations that arouse out of the pandemic were so incongruous to the world we knew that even factual statements often had a humorous reaction. In this paper, we present a dataset of 2510 samples hand-annotated with labels such as humor style, type, theme, target and stereotypes formed or exploited while creating the humor in addition to 909 memes. Our dataset comprises Reddit posts, comments, Onion news headlines, real news headlines, and tweets. We evaluate the task of humor detection and maladaptive humor detection on state-of-the-art models namely RoBERTa and GPT-3. The finetuned models trained on our dataset show significant gains over zero-shot models including GPT-3 when detecting humor. Even though GPT-3 is good at generating meaningful explanations, we observed that it fails to detect maladaptive humor due to the absence of overt targets and profanities. We believe that the presented dataset will be helpful in designing computational methods for topical humor processing as it provides a unique sample set to study the theory of incongruity in a post-pandemic world. The data is available to research community at https://github.com/smritae01/Covid19-Humor. © 2023 ACM.
ABSTRACT
Diabetes has become a common and critical disease which generally occurs due to the presence of high sugar in blood for long time. A diabetic patient has to follow different rules and restrictions where he/she has to be under proper attention by measuring diabetes level frequently to avoid unexpected risk. The risk become more when patient even doesn't know that he/she is already having diabetes and doesn't follow those restrictions. To prevent this risk, everyone should check the diabetes status to be sure. With the same target different system using machine learning techniques have been introduced which can predict the diabetes status of a patient. But the challenging fact is that the performances and accuracy of those models are questionable where there may be a huge risk of patient's life. The conventional systems are not able to show that which level of diabetes a patient can have using the previous records. To solve this issue, through this paper an efficient system has been proposed with which the diabetes status can be predicted correctly. The proposed system can also show the complexity of diabetes as well as the Covid-19 risk percentage that can also be possible to measure. After comparing several machine learning techniques, the suitable model has been selected where high level of accuracy has been ensured in term of predicting the disease. © 2022 IEEE.
ABSTRACT
The novel Corona virus has been proclaimed as a worldwide pandemic through World Health Organization in the March 2020 has immensely affected the world with its ferocity. By observation, the scientists got to know that it transmits from one human to other by droplets which range from larger respiratory droplets to smaller aerosols or direct contact with an infected person. Its impurity has been assessed to have an incubation time of 6.4 days than a simple reproduction amount of 2.24-3.58.[19] The transmission rate and spread of infection is quite rapid as compared to other fatal viral infections encountered till date. A massive loss of human life was faced even by the developed countries which had the best health-care facilities. According to WHO, COVID-19 has been confirmed in 238,521,855 people over the world, with 4,863,818 deaths as of October 9th, 2021. After experiencing the second covid wave, the number of cases had got dropped drastically but the increase in their number in the recent days is a major cause of concern. This stresses us to build some prediction models which could help in providing relief to the virus-prone areas. In this study, we are using time series for predicting forthcoming cases of corona virus. © 2022 IEEE.
ABSTRACT
Because of health concerns and factory operational scale backs during the recent COVID-19 pandemic, we now need factory automation more than ever to maintain our productivity. However, most of our factories cannot operate remotely, and none can function without considerable human input and oversight. Trying to automate our factory highlights gaps in our technology, as it seems far behind our expectations, needs, and vision. Thus, this paper aims to fill this gap by showing how we have developed practical methodologies and applied technology to enhance legacy factories and their equipment. Specifically, we present the ORiON Production Interface (OPI) unit to run the factory as a smart networked edge device for virtually any machine or process. We have also implemented various computer vision algorithms in the OPI unit to detect errors autonomously, make decentralized decisions, and even control the quality. Although Industry 4.0 is a known concept to equip our factory to see, understand, and predict, we know that many machines today are closed source and cannot even communicate, let alone join a network. This research provides a workable solution to realize Industry 4.0 truly in existing factories with legacy equipment. Experimental results show that this system has a variety of applications, including process monitoring, part positioning, broken tool detection, etc. This novel intelligent networked system can enable our factories to be more innovative and responsive. It also allows for remote operations that can be unattended or lightly tended—a trend needed for the future. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
ABSTRACT
In the late December 2019, a new virus named corona virus which bewildered the world for a year. This novel coronavirus created a huge pandemic outbreak and expanded globally. The infectious virus spread from person to person through the respiratory routes of an infected person. As we all know that prevention is better than cure, we must identify the infected person first so that we can reduce the spread. It is advised to sanitize our hands often and keep our surroundings hygienic. In this pandemic situation, we prefer health and hygiene as the first and foremost way to save ourselves from this virus. And the world requires everything to be automated, so as a result our project provides automatic safety one step above in public places. Since this COVID-19 threat continues to the second wave we have to be more cautious and we cannot also give excuses to our work. In this inexorable situation, the only challenge is to continue our duties and work with more safety precautions and most importantly 'No Physical Contact!' must be ensured wherever we go. We all know that prevention is better than cure! Since mankind survived through various challenges from the early stages, the current pandemic situation is more threatening. We all are cautious about our health and personal hygiene. The aim of our project is based on attaining safety one step above in public places. It is necessary to be aware of sanitizing hands often. Since this covid19 threat continues for nearly a year, we could not keep calm and give excuses to our work. In this inevitable situation, the real challenge is how much we are conscious of our safety precautions about the diseases. We know that 'No physical contact' is the perfect slogan for this situation. The main objective is to ensure personal health wherever we go. © 2022 IEEE.
ABSTRACT
As we know that COVID-19 Pandemic persists and it is resilient for students to attend classroom due to health concerns. Almost every academic institution has shifted towards an online education system. It is mandatory to encounter problems which are usually faced by students during online education. A survey was conducted to spot whether a student is contented with this new era of online education or not, by foreseeing the complications and outcomes of online education. A questionnaire with variegated sections was shared among students to cover supplementary issues faced by them and a response about the same was received from 263 students in total. Proposed model of classification will acquire data for training from the survey. It will predict the sentiment of students towards online education. Along with the model, the survey data is useful to discover additional problems faced by students and also do the needful in favor of students. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ABSTRACT
The voting mechanism is extremely important in a democratic country like India. And we all know that any flaw in the voting mechanism will raise serious concerns about the entire electoral process. Creating a crowd in the existing scenario of Covid-19 also adds a lot of complications. As a result, in such a situation, the online voting system will be a huge success in the election. However, the online system's security and transparency raise certain concerns. So incorporating blockchain into online E-voting will eliminate all of these flaws. The method allows voters to register and vote for any candidate. The vote will be saved in a secure block chain, but all other information, such as the voter's name, city, and whether they voted or not, will be accessible to anybody via the website. This system will provide security by denying duplication of votes. © 2022 IEEE.
ABSTRACT
This paper presents the precautionary robot which can warn and also help the people from affecting with deadly corona virus. We know that the Novel Corona virus had shown a great impact on the world population, many of the people are dying due to this deadly virus because of not following the safety measures and not taking any precautions to overcome the virus.Health-care workersare playing a major role in this pandemic by helping the affected patients to recover from the virus infections. Not only health-care workers but also robots are playing a major part in this pandemic. Robots are being used in laboratories and hospitals for various purposes like disinfection, spraying, manufacturing of medicines/vaccines, surveillance and many more applications. Robots are also equally contributed as healthcare workers around the world to adapt the present needs in order to combat with COVID-19. Mainly in this pandemic robot act as a tool, used in applications which are focused primarily in the area of health and services. The proposed work is to design and implement a robot for the covid applications. This robot is proposed by analyzing the present day's scenario on this pandemic. The proposed robot is user friendly and works particularly for 4 functions like mask detection on people, sanitizer spraying/disinfecting, temperature detection, and finally moving from one place to another place in the hospital or wherever it is required. © 2022 IEEE.
ABSTRACT
As we all know that the use of gloves are increasing day by day due to the emergence of various viruses causing new diseases. World Health Organization (WHO) declared the COVID-19 outbreak a pandemic. Everyone nowadays use gloves especially in medical field. The process of donning and doffing of gloves is becoming a difficult task. So we introduce a new machine that could automatically don and doff gloves without any hardship. This equipment consist of three pair of chambers, top one for donning of gloves, one for sanitization and drying and one for the doffing of gloves. © 2021 IEEE
ABSTRACT
Businesses using e-commerce have experienced a sharp increase since the COVID-19 pandemic. The use of e-commerce has increased by five to ten times. The use of e-commerce for business transactions must be considered in purchasing, especially business transactions for purchasing products such as food and beverages. Because, in Islam itself, every Muslim must consume halal food. The purpose of this study is to determine the availability of halal information in e-commerce and find out what improvements can be made by e-commerce business actors. Data were obtained through the observations of e-commerce products. The method used in this research is descriptive analysis. From the results of the study, we know that the form of inclusion of halal information in e-commerce is currently in the form of halal information on product titles, halal labels on product photos, and halal information on product descriptions based on halal certification and statements of business actors. Furthermore, improvements that can be made by business actors are to pay more attention to halal information on the products they sell by providing product halal information. So it is concluded that based on observations on e-commerce, the existence of halal information is still limited. © 2021 IEEE.
ABSTRACT
COVID-19 pandemic was one of the worst things we saw in the decade. With new information rolling out every day it became very difficult for everyone to organize things and stay put. A minor difference between the crisis that happened in the past and COVID was that people had better access to technology and resources. Everyone knew that technology would play an important role in this pandemic and it eventually did.Here we will explore how Topic Analysis can help in such situations. Here we will analyze and compare existing topic modelling methods such as LDA and BTM, which is designed to work with short texts such as twitter with our proposed solution which addresses some of the shortcomings of BTM. Here, we will use time based aggregation for Bi-Term topic model and compare it with our baseline models such as LDA and BTM. We plan to analyse the quality of topics generated by all these topic models and do a comparative study. © 2021 IEEE.
ABSTRACT
The COVID-19 pandemic disrupted education on all fronts with no warning. While universities largely adapted by moving lectures from in-person to online, the response from the K-12 community was not as straightforward. Existing issues of equity, access, and inclusion required school districts, schools, and teachers to adopt a variety of untested solutions, including online instruction, canceled classes, and shipping materials/supplies to students at home. The pilot year of a project meant to introduce engineering to K-12 students, e4usa was largely running as anticipated when the COVID disruption derailed the pilot cohort of teachers. This unexpected transition provides a unique opportunity to understand changes that were made and the drivers for those changes, especially when implementing a new and innovative engineering curriculum. We know that high schools adapted quickly. This work-in-progress discusses initial findings from teacher interviews on their experience during this unforeseen and unique transition. Teacher interviews were analyzed to examine the impact of the COVID-19 disruption from the perspective of a teacher new to an engineering curriculum. Specifically, we will begin to examine the following research question: How did the pilot year e4usa teachers adapt and deliver the curriculum during the COVID-19 disruption? We explored teacher delivery of the e4usa curriculum through a variety of levels to capture the drivers that prompted decisions, identify pedagogical adjustments, and identify drivers behind the chosen changes. © American Society for Engineering Education, 2021
ABSTRACT
Future always starts now;we simply do not know that! COVID-19 has triggered a new phase of human evolution! It disrupted every aspect of our life. It created new norms for everything, from education to supply chains to employment to healthcare to economy to personal hygiene! We are still in the middle of the pandemic, and the impact on both economic and social levels is not clear yet, and its severity would depend on how long the pandemic would endure. Based on that the paper outlines the disruptions prior to the virus outbreak and acted as a double-edged sword, such as the infodemic phenomena, digital transformation, platform organizations, workplace and workforce dynamics. Then, the paper illustrates the characteristics of the new world, World X.0. This includes the future of work, education, economy and public health. Resilience is not a luxury anymore! Therefore, the paper identifies a pathway towards resilience. This is by having a dynamic ecosystem driven system in place. A system that is capable to deal with uncertainties in a swift manner. The paper pinpoints this system, as well as the outlook of the required transformation that should take place on different levels related to production, workforce, business' policies and procedures, supply chain, technological platform, and environment. The approach used in the paper is based on thorough analysis of the latest reports issued by international institutions, and literature in the areas of modernization, technological disruption, COVID-19 impact on the different social and economic levels, and outlook of the new world in post COVID-19 era. Copyright © 2021 by Naudé Scribante. Permission granted to IAMOT to publish and use.