M. Saqib Nawaz

Bio: M. Saqib Nawaz is an academic researcher from Harbin Institute of Technology. The author has contributed to research in topics: Computer science & Mathematical proof. The author has an hindex of 10, co-authored 30 publications receiving 219 citations. Previous affiliations of M. Saqib Nawaz include Peking University & University of Sargodha.

Using artificial intelligence techniques for COVID-19 genome analysis

Abstract: The genome of the novel coronavirus (COVID-19) disease was first sequenced in January 2020, approximately a month after its emergence in Wuhan, capital of Hubei province, China. COVID-19 genome sequencing is critical to understanding the virus behavior, its origin, how fast it mutates, and for the development of drugs/vaccines and effective preventive strategies. This paper investigates the use of artificial intelligence techniques to learn interesting information from COVID-19 genome sequences. Sequential pattern mining (SPM) is first applied on a computer-understandable corpus of COVID-19 genome sequences to see if interesting hidden patterns can be found, which reveal frequent patterns of nucleotide bases and their relationships with each other. Second, sequence prediction models are applied to the corpus to evaluate if nucleotide base(s) can be predicted from previous ones. Third, for mutation analysis in genome sequences, an algorithm is designed to find the locations in the genome sequences where the nucleotide bases are changed and to calculate the mutation rate. Obtained results suggest that SPM and mutation analysis techniques can reveal interesting information and patterns in COVID-19 genome sequences to examine the evolution and variations in COVID-19 strains respectively.

Research Synthesis and Thematic Analysis of Twitter Through Bibliometric Analysis

Abstract: In literature, there is a shortage of comprehensive documents that can provide proper details about Twitter in research community. This study conducted a first descriptive bibliometric analysis to examine the most influential journals, institutions, and countries on Twitter. Similarly, bibliometric mapping analysis is carried out to explore different research themes in Twitter publications. VOSviewer was employed to process the 11,006 Twitter publications retrieved from the Web of Science (WoS) from 2009 to 2018. Obtained results suggest that USA and China received the highest number of publications on Twitter research, while the University of Illinois was the most productive institute. Furthermore, the five major themes have emerged in Twitter publications, and its remarkable role has been found in event detection, sentiment analysis, education, health, politics, and crisis as well as risk management. The authors believe that this study will open new doors for researchers to use online Twitter social networking communities in beauty salons, consulting companies, banks, and airlines.

Bibliometric Analysis of Social Media as a Platform for Knowledge Management

Abstract: The purpose of this study is to conduct a bibliometric analysis to examine the most influential journals, institutions, and countries in social media (SM) publications related to knowledge management (KM). Moreover, various research themes in SM KM publications are also explored. VOSviewer was employed to process 234 SM KM publications retrieved from Web of Science (WoS) in the time period 2009-2019. Different methodologies were used according to the nature of bibliometric analysis and explained in each section. Journal of Knowledge Management was the most influential journal in SM KM publications. USA and England ranked first and second respectively, while the Tampere University of Technology was the most productive institute in SM KM research. Four emerged themes indicated an explicit contribution of SM users in KM through big data, knowledge sharing, innovation, Enterprise 2.0, and social capital. This is the first bibliometric study that explores the overall contribution of SM publications in the KM field.

Predicting The Cricket Match Outcome Using Crowd Opinions On Social Networks: A Comparative Study Of Machine Learning Methods

Abstract: Social media has become a platform of first choice where one can express his/her feelings with freedom. The sports and matches being played are also discussed on social media such as Twitter. In this article, efforts are made to investigate the feasibility of using collective knowledge obtained from microposts posted on Twitter to predict the winner of a Cricket match. For predictions, we use three different methods that depend on the total number of tweets before the game for each team, fans sentiments toward each team and fans score predictions on Twitter. By combining these three methods, we classify winning team prediction in a Cricket game before the start of game. Our results are promising enough to be used for winning team forecast. Furthermore, the effectiveness of supervised learning algorithms is evaluated where Support Vector Machine (SVM) has shown advantage over other classifiers.

Molecular Biology of the Gene.

Abstract: No wonder you activities are, reading will be always needed. It is not only to fulfil the duties that you need to finish in deadline time. Reading will encourage your mind and thoughts. Of course, reading will greatly develop your experiences about everything. Reading molecular biology of the gene is also a way as one of the collective books that gives many advantages. The advantages are not only for you, but for the other peoples with those meaningful benefits.

Trustworthy Electronic Voting Using Adjusted Blockchain Technology

Abstract: The electronic voting has emerged over time as a replacement to the paper-based voting to reduce the redundancies and inconsistencies. The historical perspective presented in the last two decades suggests that it has not been so successful due to the security and privacy flaws observed over time. This paper suggests a framework by using effective hashing techniques to ensure the security of the data. The concept of block creation and block sealing is introduced in this paper. The introduction of a block sealing concept helps in making the blockchain adjustable to meet the need of the polling process. The use of consortium blockchain is suggested, which ensures that the blockchain is owned by a governing body (e.g., election commission), and no unauthorized access can be made from outside. The framework proposed in this paper discusses the effectiveness of the polling process, hashing algorithms’ utility, block creation and sealing, data accumulation, and result declaration by using the adjustable blockchain method. This paper claims to apprehend the security and data management challenges in blockchain and provides an improved manifestation of the electronic voting process.

The Longest Month: Analyzing COVID-19 Vaccination Opinions Dynamics From Tweets in the Month Following the First Vaccine Announcement

Abstract: The coronavirus outbreak has brought unprecedented measures, which forced the authorities to make decisions related to the instauration of lockdowns in the areas most hit by the pandemic. Social media has been an important support for people while passing through this difficult period. On November 9, 2020, when the first vaccine with more than 90% effective rate has been announced, the social media has reacted and people worldwide have started to express their feelings related to the vaccination, which was no longer a hypothesis but closer, each day, to become a reality. The present paper aims to analyze the dynamics of the opinions regarding COVID-19 vaccination by considering the one-month period following the first vaccine announcement, until the first vaccination took place in UK, in which the civil society has manifested a higher interest regarding the vaccination process. Classical machine learning and deep learning algorithms have been compared to select the best performing classifier. 2 349 659 tweets have been collected, analyzed, and put in connection with the events reported by the media. Based on the analysis, it can be observed that most of the tweets have a neutral stance, while the number of in favor tweets overpasses the number of against tweets. As for the news, it has been observed that the occurrence of tweets follows the trend of the events. Even more, the proposed approach can be used for a longer monitoring campaign that can help the governments to create appropriate means of communication and to evaluate them in order to provide clear and adequate information to the general public, which could increase the public trust in a vaccination campaign.