scholarly journals Key Applications of State-of-the-Art Technologies to Mitigate and Eliminate COVID-19

2020 ◽  
Author(s):  
Sarfraz Nawaz Brohi ◽  
NZ Jhanjhi ◽  
Nida Nawaz Brohi ◽  
Muhammad Nawaz Brohi
Keyword(s):  
Global Economy ◽  
High Performance ◽  
State Of The Art ◽  
Human Life ◽  
Big Data Analytics ◽  
Future Research ◽  
Free Access ◽  
Medical Practitioners ◽  
Use Of Technology ◽  
Primary Reference

COVID-19 has stunned the global economy and threatened human life. Due to rapidly emerging fatalities and enormous cases appearing every day, researchers across the globe are producing significant contributions to mitigate this pandemic. Besides the race for discovering a vaccine and treatment for COVID-19, there is utmost focus on flattening the curve by undertaking appropriate measures. The remarkable role of frontline medical practitioners, who are eagerly treating the affected people will be penned in the history books. The efforts of scientists and technologists will be remembered for their extraordinary contributions to assist healthcare professionals and governments in mitigating the threats of COVID-19. Leading technology firms have formed consortiums and research groups, which provide funding and free access to supercomputers for solving complex computational problems to eliminate COVID-19. In this research, we have unveiled five state-of-the-art technologies and their remarkable applications that can be used to mitigate and eliminate the problems of COVID-19. These technologies include Artificial Intelligence (AI), 3D Printing Technology (3DPT), Big Data Analytics (BDA), High Performance Computing (HPC) and Telecommunication Technology (TT). This research investigates the use of technology to encounter COVID-19 and aims to serve as the primary reference for promoting future research as well as developments to produce solutions for COVID-19 using AI, 3DPT, BDA, HPC and TT.

scholarly journals Key Applications of State-of-the-Art Technologies to Mitigate and Eliminate COVID-19

2020 ◽  
Author(s):  
Sarfraz Nawaz Brohi ◽  
NZ Jhanjhi ◽  
Nida Nawaz Brohi ◽  
Muhammad Nawaz Brohi
Keyword(s):  
Global Economy ◽  
High Performance ◽  
State Of The Art ◽  
Human Life ◽  
Big Data Analytics ◽  
Future Research ◽  
Free Access ◽  
Medical Practitioners ◽  
Use Of Technology ◽  
Primary Reference

COVID-19 has stunned the global economy and threatened human life. Due to rapidly emerging fatalities and enormous cases appearing every day, researchers across the globe are producing significant contributions to mitigate this pandemic. Besides the race for discovering a vaccine and treatment for COVID-19, there is utmost focus on flattening the curve by undertaking appropriate measures. The remarkable role of frontline medical practitioners, who are eagerly treating the affected people will be penned in the history books. The efforts of scientists and technologists will be remembered for their extraordinary contributions to assist healthcare professionals and governments in mitigating the threats of COVID-19. Leading technology firms have formed consortiums and research groups, which provide funding and free access to supercomputers for solving complex computational problems to eliminate COVID-19. In this research, we have unveiled five state-of-the-art technologies and their remarkable applications that can be used to mitigate and eliminate the problems of COVID-19. These technologies include Artificial Intelligence (AI), 3D Printing Technology (3DPT), Big Data Analytics (BDA), High Performance Computing (HPC) and Telecommunication Technology (TT). This research investigates the use of technology to encounter COVID-19 and aims to serve as the primary reference for promoting future research as well as developments to produce solutions for COVID-19 using AI, 3DPT, BDA, HPC and TT.

scholarly journals Key Applications of State-of-the-Art Technologies to Mitigate and Eliminate COVID-19.pdf

2020 ◽  
Author(s):  
Sarfraz Nawaz Brohi ◽  
NZ Jhanjhi ◽  
Nida Nawaz Brohi ◽  
Muhammad Nawaz Brohi
Keyword(s):  
Global Economy ◽  
High Performance ◽  
State Of The Art ◽  
Human Life ◽  
Big Data Analytics ◽  
Future Research ◽  
Free Access ◽  
Medical Practitioners ◽  
Use Of Technology ◽  
Primary Reference

COVID-19 has stunned the global economy and threatened human life. Due to rapidly emerging fatalities and enormous cases appearing every day, researchers across the globe are producing significant contributions to mitigate this pandemic. Besides the race for discovering a vaccine and treatment for COVID-19, there is utmost focus on flattening the curve by undertaking appropriate measures. The remarkable role of frontline medical practitioners, who are eagerly treating the affected people will be penned in the history books. The efforts of scientists and technologists will be remembered for their extraordinary contributions to assist healthcare professionals and governments in mitigating the threats of COVID-19. Leading technology firms have formed consortiums and research groups, which provide funding and free access to supercomputers for solving complex computational problems to eliminate COVID-19. In this research, we have unveiled five state-of-the-art technologies and their remarkable applications that can be used to mitigate and eliminate the problems of COVID-19. These technologies include Artificial Intelligence (AI), 3D Printing Technology (3DPT), Big Data Analytics (BDA), High Performance Computing (HPC) and Telecommunication Technology (TT). This research investigates the use of technology to encounter COVID-19 and aims to serve as the primary reference for promoting future research as well as developments to produce solutions for COVID-19 using AI, 3DPT, BDA, HPC and TT.

scholarly journals The Influence of Big Data Analytics on E-Commerce: Case Study of the U.S. and China

2021 ◽  
Vol 2021 ◽  
pp. 1-20
Author(s):  
Weiqing Zhuang
Keyword(s):  
Big Data ◽  
Global Economy ◽  
Data Analytics ◽  
Big Data Analytics ◽  
The United States ◽  
Mediating Effect ◽  
Theoretical Research ◽  
Business Strategies ◽  
Future Research ◽  
The U.S

Big data analytics (BDA) is a wide and deep application in e-commerce, which impacts positively on the global economy, especially the U.S. and China who have done well. This paper seeks to examine the relative influence of theoretical research and practical activities of BDA in e-commerce to explain the differences between the U.S. and China according to the two main literature databases, Web of Science and CNKI, respectively, and by employing other samples that present retail e-commerce sales and the number of some data companies founded in the U.S. and China each year. We further determine the reasons leading to the difference between the U.S. and China in BDA in e-commerce, which can help managers devise appropriate business strategies in e-commerce for each of them, and provide a proof of the significant relationship of theoretical research and practical activities in BDA in e-commerce. In addition, the variables related to big data companies show a moderation effect rather than mediating effect relative to the practice of theoretical research in e-commerce in the United States, but they show a moderate effect and mediating effects in China. The results of this study help clarify doubts regarding the development of China’s e-commerce. Moreover, three orientations in e-commerce using BDA and the use of quantum computing in e-commerce to solve existing e-commerce problems are explored to provide better evidence for decision-making that could be valuable in future research.

Tourist gaze and beyond: state of the art

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
W.H.M.S. Samarathunga ◽  
Li Cheng
Keyword(s):  
State Of The Art ◽  
Qualitative Content Analysis ◽  
Future Research ◽  
Research Directions ◽  
Content Type ◽  
Tourist Gaze ◽  
The Gaze ◽  
Use Of Technology ◽  
Future Research Directions ◽  
Gaze Theory

Purpose The tourist gaze remains a key concept in tourism research. The purpose of this paper is to comprehend the theoretical and empirical development of the tourist gaze notion and its contributions to tourism knowledge, identifying potential research directions by reviewing and analyzing articles that have defined, refined and applied the concept of the tourist gaze. Design/methodology/approach The study identified 109 relevant research papers primarily through the Web of Science and Scopus databases. Google Scholar, ResearchGate.net and Academia.edu were used to capturing additional work not indexed in the key databases. Qualitative content analysis was used to map the evolution of the concept, distinguish between different perspectives and identify gaps in the tourist gaze literature. Findings This “state of the art” paper on tourist gaze outlines Foucault’s original work on gaze and power, which underpins subsequent theorization within tourism. The study identifies how the tourist gaze operates in different contexts and circumstances allowing the development of gaze theory. Importantly, the evolution of the gaze theory is presented after analyzing the knowledge gaps, the contexts in which it was used, the methodologies with which it was applied. Based on the findings, the study proposes future works of gaze with the use of technology, science, nature and social media. Originality/value This paper is among one of the first states of the art papers in tourism literature that comprehensively analyzes the works on the tourist gaze, tracing its evolution and identifying future research directions to address gaps in existing knowledge.

scholarly journals Next-Generation Big Data Analytics: State of the Art, Challenges, and Future Research Topics

2017 ◽  
Vol 13 (4) ◽  
pp. 1891-1899 ◽  
Author(s):  
Zhihan Lv ◽  
Houbing Song ◽  
Pablo Basanta-Val ◽  
Anthony Steed ◽  
Minho Jo
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
State Of The Art ◽  
Big Data Analytics ◽  
Future Research ◽  
Next Generation ◽  
Research Topics

Elastic Parallel Systems for High Performance Cloud Computing: State-of-the-Art and Future Directions

2019 ◽  
Vol 29 (02) ◽  
pp. 1950006 ◽  
Author(s):  
Stefan Kehrer ◽  
Wolfgang Blochinger
Keyword(s):  
Conceptual Framework ◽  
High Performance ◽  
State Of The Art ◽  
Specific Property ◽  
Parallel Systems ◽  
Future Research ◽  
Future Directions ◽  
Ex Post ◽  
Depth Analysis ◽  
Performance Computing

With on-demand access to compute resources, pay-per-use, and elasticity, the cloud evolved into an attractive execution environment for High Performance Computing (HPC). Whereas elasticity, which is often referred to as the most beneficial cloud-specific property, has been heavily used in the context of interactive (multi-tier) applications, elasticity-related research in the HPC domain is still in its infancy. Existing parallel computing theory as well as traditional metrics to analytically evaluate parallel systems do not comprehensively consider elasticity, i.e., the ability to control the number of processing units at runtime. To address these issues, we introduce a conceptual framework to understand elasticity in the context of parallel systems, define the term elastic parallel system, and discuss novel metrics for both elasticity control at runtime as well as the ex-post performance evaluation of elastic parallel systems. Based on the conceptual framework, we provide an in-depth analysis of existing research in the field to describe the state-of-the-art and compile our findings into a research agenda for future research on elastic parallel systems.

scholarly journals Big Data Knowledge Discovery Platforms: A 360 Degree Perspective

2019 ◽  
Vol 9 (2) ◽  
pp. 2424-2433
Keyword(s):  
Big Data ◽  
Knowledge Discovery ◽  
High Performance ◽  
Big Data Analytics ◽  
Analytical Techniques ◽  
Fundamental Aspect ◽  
Future Research ◽  
Data Sets ◽  
Discovery Process ◽  
Future Research Directions

Big Datais a buzzword affecting nearly every domain and providing different set new opportunity for the development of knowledge discovery process. Although it comes with challengeslike abundance, extensiveness and diversity, timeliness and dynamism, messiness and vagueness, and with an uncertainty as all the data generated does not relates to any specific question and can be associated with another process or activity. To address these challenges are certainly cannot be handled by the traditional infrastructure, platforms and frameworks. New analytical techniques and high performance computing architecture came into picture to handle this explosion. These platforms and architecture are giving a cutting edge to the Big Data Knowledge Discovery process by using Artificial Intelligence, Machine Learning and Expert systems. This study encompasses a comprehensive review of Big Data analytical platforms and frameworks with their comparative analysis. A Knowledge Discovery architecture for Big Data Analytics is also proposed while considering the fundamental aspect of gaining insights from Big Data sets and focus of this analysis is to provide the open challenges associated with these techniques and future research directions.

scholarly journals Deep Learning-Based Big Data Analytics for Internet of Vehicles: Taxonomy, Challenges, and Research Directions

2021 ◽  
Vol 2021 ◽  
pp. 1-20
Author(s):  
Haruna Chiroma ◽  
Shafi’i M. Abdulhamid ◽  
Ibrahim A. T. Hashem ◽  
Kayode S. Adewole ◽  
Absalom E. Ezugwu ◽  
...  
Keyword(s):  
Big Data ◽  
Deep Learning ◽  
Data Analytics ◽  
High Performance ◽  
Theoretical Perspective ◽  
Big Data Analytics ◽  
Research Area ◽  
Future Research ◽  
Internet Of Vehicles ◽  
Active Attention

The Internet of Vehicles (IoV) is a developing technology attracting attention from the industry and the academia. Hundreds of millions of vehicles are projected to be connected within the IoV environments by 2035. Each vehicle in the environment is expected to generate massive amounts of data. Currently, surveys on leveraging deep learning (DL) in the IoV within the context of big data analytics (BDA) are scarce. In this paper, we present a survey and explore the theoretical perspective of the role of DL in the IoV within the context of BDA. The study has unveiled substantial research opportunities that cut across DL, IoV, and BDA. Exploring DL in the IoV within BDA is an infant research area requiring active attention from researchers to fully understand the emerging concept. The survey proposes a model of IoV environment integrated into the cloud equipped with a high-performance computing server, DL architecture, and Apache Spark for data analytics. The current developments, challenges, and opportunities for future research are presented. This study can guide expert and novice researchers on further development of the application of DL in the IoV within the context of BDA.

scholarly journals Coastal Waste Detection Based on Deep Convolutional Neural Networks

Sensors ◽  
2021 ◽  
Vol 21 (21) ◽  
pp. 7269
Author(s):  
Chengjuan Ren ◽  
Hyunjun Jung ◽  
Sukhoon Lee ◽  
Dongwon Jeong
Keyword(s):  
Data Augmentation ◽  
State Of The Art ◽  
Human Life ◽  
Model Performance ◽  
Multiple Scale ◽  
The State ◽  
Future Research ◽  
Deep Convolutional Neural Networks ◽  
Destructive Effect ◽  
Sorting Efficiency

Coastal waste not only has a seriously destructive effect on human life and marine ecosystems, but it also poses a long-term economic and environmental threat. To solve the issues of a poor manual coastal waste sorting environment, such as low sorting efficiency and heavy tasks, we develop a novel deep convolutional neural network by combining several strategies to realize intelligent waste recognition and classification based on the state-of-the-art Faster R-CNN framework. Firstly, to effectively detect small objects, we consider multiple-scale fusion to get rich semantic information from the shallower feature map. Secondly, RoI Align is introduced to solve positioning deviation caused by the regions of interest pooling. Moreover, it is necessary to correct key parameters and take on data augmentation to improve model performance. Besides, we create a new waste object dataset, named IST-Waste, which is made publicly to facilitate future research in this field. As a consequence, the experiment shows that the algorithm’s mAP reaches 83%. Detection performance is significantly better than Faster R-CNN and SSD. Thus, the developed scheme achieves higher accuracy and better performance against the state-of-the-art alternative.

Big data and the measurement of public organizations’ performance and efficiency: The state-of-the-art

2017 ◽  
Vol 32 (4) ◽  
pp. 263-281 ◽  
Author(s):  
Nicky Rogge ◽  
Tommaso Agasisti ◽  
Kristof De Witte
Keyword(s):  
Big Data ◽  
Public Sector ◽  
Statistical Data ◽  
State Of The Art ◽  
Big Data Analytics ◽  
Public Organizations ◽  
Future Research ◽  
The Public ◽  
Academic Literature ◽  
Public Sector Organizations

The increasing availability of statistical data raises opportunities for ‘big’ data and learning analytics. Here, we review the academic literature and research relating to the use of big data analytics in the public sector, and its contribution to public organizations’ performance and efficiency. We outline the advantages as well as the limitations of using big data in public sector organizations and identify research gaps in recent studies and interesting areas for future research.

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