Significant Applications of IoT in Covid Pandemic: A Systematic Review

Today the entire world is in the exigency state-COVID-19 quarantine days. We should stay home to live. To avoid a fight over the spread of corona, the governments of all the countries have enforced a nationwide lockdown. Though the lockdown may have helped to control the spread of COVID, it has had a devastating impact on numerous domains like health, agriculture, education, global supply chains, trade, and various industries like automotive, power – electronics, travel, aeronautical, tourism industry…etc, which are the basic roots of the growth of a nation. This censorious situation can be wielded with the eminent technology “IoT”. Anytime, Anything, Anywhere”- this is the most significant feature of IoT. Any real-world object can be transformed into an intelligent object by the technology “IoT”. Because of the affordability and availability of smart devices, the entire world is more connected with IoT than ever before. From this standpoint, the authors have chosen five real-time areas health, education, industry, agriculture, and society. This survey initiates from the impacts of COVID in the above-chosen areas, how it diminishes the day-to-day events of human life, the vitality of IoT, how it helps to tackle the COVID issues without any quality degradation in this quarantine period. This systematic review completely appraises the innovations and contributions of IoT used by various researchers to defend the impacts of COVID and concludes with the pros and cons. A detailed exploration has been done in this article particularly on “IoT in COVID pandemic”. This will be more useful to the researchers to acquire clear-cut knowledge about the power of IoT, in particular how IoT plays a significant role in the period of COVID and further assists them to travel towards an innovative and serviceable direction in their research.

Various Phytochemicals Present in Maida Lakdi Litsea glutinosa (Lour) acts in the Management of Waja ul Mafasil (Arthritis) in a Clinical Trials

Litsea glutinosa (Lour) Maida Lakdi is an evergreen tree belonging to family Lauraceae it is a native to India.1,2,3 Ethinomedically the bark is used by the traditional practitioners as a demulcent, emollient and in the treatment of diarrhea and dysentery. According to ancient Unani classical text books by our ancient scholars which was used for mostly bony diseaseslike Fracture (kasar), Joint pain(Hudaar), gout(Naqras), sciatica(lrqun nasa), anti inflammatory(Muhalil e Auram), spacity of nerves(Tashannunj e Asab), nervine tonic(Muqavi e Asab)etc. and now a days further activities were found by various scientific studies paving a way for multi functional activities like Anti oxidant , analgesic anti inflammatory, anti pyretic, anti microbial, anti bacterial, anti fungal anti helminthic, wound healing, hepatoprotective, nephro protective, anti infertility,anti hyperglycemic and anti hyperlipidemic.

Role of Unani Herbal Formulation of Sumbul-Ut-teeb (Nardostachys jatamansi) & Khulanjan (Alpinia galangal) in the Management of Tashhamul kabid (Fatty Liver) in a Clinical Study

sumbul-ut-teeb (Nardostachys jatamansi) & khulanjan (Alpinia galanga)are extensively used drugs by our ancient Unani physicians for the management of Gastro hepatic diseases due to cold temperament such as gastritis,metabolic disorders, tashhamul kabid (fatty liver)

Sentiment Analysis on Twitter Data: A Comparative Approach

Sentiment analysis is the methodical recognition, extraction, quantification, and learning of affective states and subjective information using natural language processing, text analysis, computational linguistics, and biometrics. People frequently use Twitter, one of numerous popular social media platforms, to convey their thoughts and opinions about a business, a product, or a service. Analysis of tweet sentiments is particularly useful in detecting if people have a good, negative, or neutral opinion. This study assesses public opinion about an individual, activity, commodity, or organization. The Twitter API is utilised in this article to directly get tweets from Twitter and develop a sentiment categorization for the tweets. This paper has used Twitter data for two separate approaches, viz., Lexicon & Machine Learning. Lexicon based approach further categorized in Corpus-based and Dictionary-based. And various Machine learning-based approaches like Support Vector Machine (SVM), Naïve Bayes, Maximum entropy are used to analyse Twitter data. Neural Network (NN), Decision tree-based sentiment analysis is also covered in this research work, to find out better accuracy of the approaches in the various data range. Graphs and confusion matrices are used to visualise the results of the analysis for positive, negative, and neutral remarks regarding their opinions.

Security and Usability Issues in Captcha Design

Captcha stands for Completely Automated Public Turing test to tell Computers and Humans Apart. Captcha is a challenge response test which determines whether the user on Internet is human or a spam robot. They are also called as Human interactive proof. Captcha is used to prevent the automated attacks by the computer robots. The Captcha test generates a simple task which can be easily solved by humans and hard for bots to complete the task. Thus Captcha prevents the unauthorized entry of bots into the websites and web services.