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Mobile phone technology made tremendous progress today. In this current ongoing Coronavirus disease (COVID-19) pandemic situation worldwide, mobile phones have an essential role due to its number of applications. To save lives through proper guidelines and information, it is necessary to retain the people up to date. That's why well-needed applications are required that aim to decline the rampant increase of COVID-19 cases country-wide. Today with the increasing pandemic Covid-19, several applications have been developed to inform people about safety measures and keep them updated with the public health measures. COVID-19 applications relate to large public, hence, usability of these applications has far larger impact than any other type of applications which generally have a specific user group. Therefore, in this article, a systematic review is taken by considering their range of functions, target user groups, name, languages, size, user ratings, available interfaces, response time, release date, up-dating date and up to date cases. There exist several methods for evaluating usability. In this work, we use user-based usability evaluation methods to explore usability issues in COVID-19 apps. By performing analysis on the extracted data, we examine some facts like the impact of gender on usability, impact of age, usability dimensions, and the effect of app functions on usability to see whether they affect usability positively or negatively

In this essay, we have emphasized the educational practices of the students during COVID-19 and evaluated the parents' role in enhancing their children's learning attitude. Four hundred individuals from various educational institutions provided information, which was then processed for SPSS data analysis. We initially evaluated the questionnaire's consistency and discovered that it was better. When we later calculated some summary statistics, we saw that most queries displayed normality. According to chi-square analysis, it was found that parents with higher educations helped their kids with their online learning—high-speed internet service. Parents with education helped their kids manage their time so they could study online with a positive attitude. They supported the purchase of the online learning equipment financially and encouraged their children to change their behavior towards it.

In this essay, we have emphasized the educational practices of the students during COVID-19 and evaluated the parents' role in enhancing their children's learning attitude. Four hundred individuals from various educational institutions provided information, which was then processed for SPSS data analysis. We initially evaluated the questionnaire's consistency and discovered that it was better. When we later calculated some summary statistics, we saw that most queries displayed normality. According to chi-square analysis, it was found that parents with higher educations helped their kids with their online learning—high-speed internet service. Parents with education helped their kids manage their time so they could study online with a positive attitude. They supported the purchase of the online learning equipment financially and encouraged their children to change their behavior towards it.

Mobile phone technology made tremendous progress today. In this current ongoing Coronavirus disease (COVID-19) pandemic situation worldwide, mobile phones have an essential role due to its number of applications. To save lives through proper guidelines and information, it is necessary to retain the people up to date. That's why well-needed applications are required that aim to decline the rampant increase of COVID-19 cases country-wide. Today with the increasing pandemic Covid-19, several applications have been developed to inform people about safety measures and keep them updated with the public health measures. COVID-19 applications relate to large public, hence, usability of these applications has far larger impact than any other type of applications which generally have a specific user group. Therefore, in this article, a systematic review is taken by considering their range of functions, target user groups, name, languages, size, user ratings, available interfaces, response time, release date, up-dating date and up to date cases. There exist several methods for evaluating usability. In this work, we use user-based usability evaluation methods to explore usability issues in COVID-19 apps. By performing analysis on the extracted data, we examine some facts like the impact of gender on usability, impact of age, usability dimensions, and the effect of app functions on usability to see whether they affect usability positively or negatively

Mobile phone technology made tremendous progress today. In this current ongoing Coronavirus disease (COVID-19) pandemic situation worldwide, mobile phones have an essential role due to its number of applications. To save lives through proper guidelines and information, it is necessary to retain the people up to date. That's why well-needed applications are required that aim to decline the rampant increase of COVID-19 cases country-wide. Today with the increasing pandemic Covid-19, several applications have been developed to inform people about safety measures and keep them updated with the public health measures. COVID-19 applications relate to large public, hence, usability of these applications has far larger impact than any other type of applications which generally have a specific user group. Therefore, in this article, a systematic review is taken by considering their range of functions, target user groups, name, languages, size, user ratings, available interfaces, response time, release date, up-dating date and up to date cases. There exist several methods for evaluating usability. In this work, we use user-based usability evaluation methods to explore usability issues in COVID-19 apps. By performing analysis on the extracted data, we examine some facts like the impact of gender on usability, impact of age, usability dimensions, and the effect of app functions on usability to see whether they affect usability positively or negatively

In this essay, we have emphasized the educational practices of the students during COVID-19 and evaluated the parents' role in enhancing their children's learning attitude. Four hundred individuals from various educational institutions provided information, which was then processed for SPSS data analysis. We initially evaluated the questionnaire's consistency and discovered that it was better. When we later calculated some summary statistics, we saw that most queries displayed normality. According to chi-square analysis, it was found that parents with higher educations helped their kids with their online learning—high-speed internet service. Parents with education helped their kids manage their time so they could study online with a positive attitude. They supported the purchase of the online learning equipment financially and encouraged their children to change their behavior towards it.

The detection of temporal entities within natural language texts is an interesting information extractionproblem. Temporal entities help to estimate authorship dates, enhance information retrieval capabilities, detect andtrack topics in news articles, and augment electronic news reader experience. Research has been performed on thedetection, normalization and annotation guidelines for English temporal entities. However, research for Urdulanguage lags far behind and there is a need for lot of work to be done in this regard especially when huge quantityof Urdu data is being generated on online social networks on daily basis. In this paper, we propose a rule-basedapproach for temporal entity extraction for Urdu language. Comparing our approach with existing Urdu temporalentity extraction approaches, our approach dominates on behalf of accuracy and on tackling with all types of Urdutemporal entity types. We use a publicly available Urdu data corpus for our experiments which consists of 206 datetags. We extend this dataset by adding 200 Urdu Fully Qualified Date (UFQD) tags. We also introduce a new datetype for Urdu language called Urdu Partially Fully Qualified. Our proposed system achieved average (0.97, 0.98and 0.98) (Precision, Recall and F1-Measure) respectively for UFQD and Urdu Partially Fully Qualified Date.Some challenges and issues of other date types in Urdu Textual Language i.e. Deictic and Anaphoric are alsodiscussed in detail.

The detection of temporal entities within natural language texts is an interesting information extractionproblem. Temporal entities help to estimate authorship dates, enhance information retrieval capabilities, detect andtrack topics in news articles, and augment electronic news reader experience. Research has been performed on thedetection, normalization and annotation guidelines for English temporal entities. However, research for Urdulanguage lags far behind and there is a need for lot of work to be done in this regard especially when huge quantityof Urdu data is being generated on online social networks on daily basis. In this paper, we propose a rule-basedapproach for temporal entity extraction for Urdu language. Comparing our approach with existing Urdu temporalentity extraction approaches, our approach dominates on behalf of accuracy and on tackling with all types of Urdutemporal entity types. We use a publicly available Urdu data corpus for our experiments which consists of 206 datetags. We extend this dataset by adding 200 Urdu Fully Qualified Date (UFQD) tags. We also introduce a new datetype for Urdu language called Urdu Partially Fully Qualified. Our proposed system achieved average (0.97, 0.98and 0.98) (Precision, Recall and F1-Measure) respectively for UFQD and Urdu Partially Fully Qualified Date.Some challenges and issues of other date types in Urdu Textual Language i.e. Deictic and Anaphoric are alsodiscussed in detail.

The detection of temporal entities within natural language texts is an interesting information extractionproblem. Temporal entities help to estimate authorship dates, enhance information retrieval capabilities, detect andtrack topics in news articles, and augment electronic news reader experience. Research has been performed on thedetection, normalization and annotation guidelines for English temporal entities. However, research for Urdulanguage lags far behind and there is a need for lot of work to be done in this regard especially when huge quantityof Urdu data is being generated on online social networks on daily basis. In this paper, we propose a rule-basedapproach for temporal entity extraction for Urdu language. Comparing our approach with existing Urdu temporalentity extraction approaches, our approach dominates on behalf of accuracy and on tackling with all types of Urdutemporal entity types. We use a publicly available Urdu data corpus for our experiments which consists of 206 datetags. We extend this dataset by adding 200 Urdu Fully Qualified Date (UFQD) tags. We also introduce a new datetype for Urdu language called Urdu Partially Fully Qualified. Our proposed system achieved average (0.97, 0.98and 0.98) (Precision, Recall and F1-Measure) respectively for UFQD and Urdu Partially Fully Qualified Date.Some challenges and issues of other date types in Urdu Textual Language i.e. Deictic and Anaphoric are alsodiscussed in detail.