scholarly journals A Hybrid Computational Framework for Intelligent Inter- continent SARS-CoV-2 Sub-strains Characterization and Prediction

2021 ◽  
Author(s):  
Moses E. Ekpenyong ◽  
Mercy Edoho ◽  
Udoinyang Inyang ◽  
Faith-Michael Uzoka ◽  
Itemobong S. Ekaidem ◽  
...  
Keyword(s):  
State Of The Art ◽  
Close Association ◽  
Research Direction ◽  
Future Research ◽  
Genome Diversity ◽  
Cognitive Approach ◽  
Comparative Performance ◽  
Computational Framework ◽  
Machine Learning Methods ◽  
Global Initiative

Abstract Whereas accelerated attention beclouded early stages of the coronavirus spread, knowledge of actual pathogenicity and origin of possible sub-strains remained unclear. By harvesting the Global initiative on Sharing All Influenza Data (GISAID) database (https://www.gisaid.org/), between December 2019 and January 15, 2021, a total of 8864 human SARS-CoV-2 complete genome sequences processed by gender, across 6 continents (88 countries) of the world, Antarctica exempt, were analyzed. We hypothesized that data speaks for itself and can discern true and explainable patterns of the disease. Identical genome diversity and pattern correlates analysis performed using a hybrid of biotechnology and machine learning methods corroborate the emergence of inter- and intra- SARS-CoV-2 sub-strains. Interestingly, some viral sub-strain patterns progressively transformed into new sub-strain clusters indicating varying amino acid and strong nucleotide association derived from same lineage. A novel cognitive approach to knowledge mining from enriched genome datasets and output classification targets, helped intelligent prediction of emerging or new viral sub-strains. Classification results outsmarted state-of-the-art methods and sustained an increase in sub-strains within the various continents with nucleotide mutations dynamically varying between individuals in close association with the virus adaptability to its host/environment. They also offer explanations for the growing concerns and next wave(s) of the virus. Defuzzifying confusable pattern clusters for comparative performance with the proposed cognitive solution is a possible future research direction of this paper.

scholarly journals A hybrid computational framework for intelligent inter-continent SARS-CoV-2 sub-strains characterization and prediction

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Moses Effiong Ekpenyong ◽  
Mercy Ernest Edoho ◽  
Udoinyang Godwin Inyang ◽  
Faith-Michael Uzoka ◽  
Itemobong Samuel Ekaidem ◽  
...  
Keyword(s):  
State Of The Art ◽  
Close Association ◽  
Contact Tracing ◽  
Genome Diversity ◽  
Cognitive Approach ◽  
Computational Framework ◽  
Machine Learning Methods ◽  
Global Initiative ◽  
Future Direction ◽  
Better Than

AbstractWhereas accelerated attention beclouded early stages of the coronavirus spread, knowledge of actual pathogenicity and origin of possible sub-strains remained unclear. By harvesting the Global initiative on Sharing All Influenza Data (GISAID) database (https://www.gisaid.org/), between December 2019 and January 15, 2021, a total of 8864 human SARS-CoV-2 complete genome sequences processed by gender, across 6 continents (88 countries) of the world, Antarctica exempt, were analyzed. We hypothesized that data speak for itself and can discern true and explainable patterns of the disease. Identical genome diversity and pattern correlates analysis performed using a hybrid of biotechnology and machine learning methods corroborate the emergence of inter- and intra- SARS-CoV-2 sub-strains transmission and sustain an increase in sub-strains within the various continents, with nucleotide mutations dynamically varying between individuals in close association with the virus as it adapts to its host/environment. Interestingly, some viral sub-strain patterns progressively transformed into new sub-strain clusters indicating varying amino acid, and strong nucleotide association derived from same lineage. A novel cognitive approach to knowledge mining helped the discovery of transmission routes and seamless contact tracing protocol. Our classification results were better than state-of-the-art methods, indicating a more robust system for predicting emerging or new viral sub-strain(s). The results therefore offer explanations for the growing concerns about the virus and its next wave(s). A future direction of this work is a defuzzification of confusable pattern clusters for precise intra-country SARS-CoV-2 sub-strains analytics.

scholarly journals A Hybrid Computational Framework for Intelligent Inter-continent SARS-CoV-2 Sub-strains Characterization and Prediction

2020 ◽  
Author(s):  
Moses Ekpenyong ◽  
Mercy Edoho ◽  
Udoinyang Inyang ◽  
Faith-Michael Uzoka ◽  
Itemobong Ekaidem ◽  
...  
Keyword(s):  
Machine Learning ◽  
Amino Acid ◽  
Genome Diversity ◽  
Genome Sequences ◽  
Computational Framework ◽  
Machine Learning Methods ◽  
Novel Approach ◽  
The World ◽  
Global Initiative ◽  
Cognitive Knowledge

Abstract Whereas accelerated attention beclouded early stages of the coronavirus spread, knowledge of actual pathogenicity and origin of possible sub-strains remained unclear. By harvesting the Global initiative on Sharing All Influenza Data (GISAID) database (https://www.gisaid.org/), between December 2019 and August 20, 2020, a total of 157 human SARS-CoV-2 (complete) genome sequences processed by gender, across 6 continents of the world, were analyzed. We hypothesized that data speaks for itself and can discern true and explainable patterns of the disease. Identical genome diversity and pattern correlates analysis performed using a hybrid of biotechnology and machine learning methods corroborate multiple emergence of SARS-CoV-2 sub-strains and explained the diversity of the SARS-CoV-2. Interestingly, some viral sub-strains progressively transformed into new sub-strain clusters indicating varying amino acid and strong nucleotide association derived from same origin. A novel approach to cognitive knowledge mining from enriched genome datasets and output targets labeling, helped intelligent prediction of emerging or new viral sub-strains.

scholarly journals A Hybrid Computational Framework for Intelligent Inter-continent SARS-CoV-2 Sub-strains Characterization and Prediction

2020 ◽  
Author(s):  
Moses Ekpenyong ◽  
Mercy Edoho ◽  
Udoinyang Inyang ◽  
Faith-Michael Uzoka ◽  
Itemobong Ekaidem ◽  
...  
Keyword(s):  
Machine Learning ◽  
Amino Acid ◽  
Genome Diversity ◽  
Genome Sequences ◽  
Computational Framework ◽  
Machine Learning Methods ◽  
Novel Approach ◽  
The World ◽  
Global Initiative ◽  
Cognitive Knowledge

Abstract Whereas accelerated attention beclouded early stages of the coronavirus spread, knowledge of actual pathogenicity and origin of possible sub-strains remained unclear. By harvesting the Global initiative on Sharing All Influenza Data (GISAID) database (https://www.gisaid.org/), between December 2019 and August 20, 2020, a total of 157 human SARS-CoV-2 (complete) genome sequences processed by gender, across 6 continents of the world, were analyzed. We hypothesized that data speaks for itself and can discern true and explainable patterns of the disease. Identical genome diversity and pattern correlates analysis performed using a hybrid of biotechnology and machine learning methods corroborate multiple emergence of SARS-CoV-2 sub-strains and explained the diversity of the SARS-CoV-2. Interestingly, some viral sub-strains progressively transformed into new sub-strain clusters indicating varying amino acid and strong nucleotide association derived from same origin. A novel approach to cognitive knowledge mining from enriched genome datasets and output targets labeling, helped intelligent prediction of emerging or new viral sub-strains.

scholarly journals A Systematic Review on Indoor Environmental Quality in Naturally Ventilated School Classrooms: A Way Forward

2021 ◽  
Vol 2021 ◽  
pp. 1-19
Author(s):  
Nishant Raj Kapoor ◽  
Ashok Kumar ◽  
Chandan Swaroop Meena ◽  
Anuj Kumar ◽  
Tabish Alam ◽  
...  
Keyword(s):  
Environmental Quality ◽  
Indoor Air ◽  
State Of The Art ◽  
Research Direction ◽  
Future Research ◽  
School Buildings ◽  
Indoor Environmental Quality ◽  
Future Research Direction ◽  
Art Practices ◽  
Acoustic Comfort

This review presents the existing state-of-the-art practices of indoor environmental quality (IEQ) in naturally ventilated school buildings and is mainly focused on the components of IEQ like thermal comfort, indoor air quality with ventilation, and visual and acoustic comfort. This article also discusses the impacts of COVID-19 on naturally ventilated school buildings, highlighting the obviousness of dynamic applications that concentrate on reducing COVID-19 effects in naturally ventilated school buildings. The importance of the concerned issues and factors are discussed in detail for future research direction. This review is a step toward the development of the IEQ standard for naturally ventilated school buildings.

scholarly journals Artificial Intelligence Technologies for Sign Language

Sensors ◽  
2021 ◽  
Vol 21 (17) ◽  
pp. 5843
Author(s):  
Ilias Papastratis ◽  
Christos Chatzikonstantinou ◽  
Dimitrios Konstantinidis ◽  
Kosmas Dimitropoulos ◽  
Petros Daras
Keyword(s):  
Sign Language ◽  
Social Inclusion ◽  
State Of The Art ◽  
Research Direction ◽  
Hearing Impaired ◽  
Future Research ◽  
Future Research Direction ◽  
Comprehensive Review ◽  
Impaired People ◽  
Language Technologies

AI technologies can play an important role in breaking down the communication barriers of deaf or hearing-impaired people with other communities, contributing significantly to their social inclusion. Recent advances in both sensing technologies and AI algorithms have paved the way for the development of various applications aiming at fulfilling the needs of deaf and hearing-impaired communities. To this end, this survey aims to provide a comprehensive review of state-of-the-art methods in sign language capturing, recognition, translation and representation, pinpointing their advantages and limitations. In addition, the survey presents a number of applications, while it discusses the main challenges in the field of sign language technologies. Future research direction are also proposed in order to assist prospective researchers towards further advancing the field.

scholarly journals Approaches for Recognizing Disease Genes Based on Network

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Quan Zou ◽  
Jinjin Li ◽  
Chunyu Wang ◽  
Xiangxiang Zeng
Keyword(s):  
Large Scale ◽  
Research Direction ◽  
Disease Association ◽  
Future Research ◽  
Disease Genes ◽  
The Core ◽  
Machine Learning Methods ◽  
Genetic Abnormalities ◽  
Gene Functions ◽  
The Relationship

Diseases are closely related to genes, thus indicating that genetic abnormalities may lead to certain diseases. The recognition of disease genes has long been a goal in biology, which may contribute to the improvement of health care and understanding gene functions, pathways, and interactions. However, few large-scale gene-gene association datasets, disease-disease association datasets, and gene-disease association datasets are available. A number of machine learning methods have been used to recognize disease genes based on networks. This paper states the relationship between disease and gene, summarizes the approaches used to recognize disease genes based on network, analyzes the core problems and challenges of the methods, and outlooks future research direction.

Reverse supply chain management in manufacturing industry: a systematic review

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Kaliyan Mathiyazhagan ◽  
Sonu Rajak ◽  
Swayam Sampurna Panigrahi ◽  
Vernika Agarwal ◽  
Deepa Manani
Keyword(s):  
Supply Chain ◽  
Manufacturing Industry ◽  
State Of The Art ◽  
Reverse Flow ◽  
Public Awareness ◽  
Research Direction ◽  
Literature Survey ◽  
Future Research ◽  
Reverse Supply Chain ◽  
Content Type

PurposeIn a quest to meet increasing pressure to incorporate environmental and sustainability factors due to the legislations and growing public awareness, companies are rethinking of strategizing their supply chain network to take control of the reverse flow of products as well. This growing interest has also led to tremendous growth in publications occurring in several reputed journals in the last few years. In this context, the purpose of this article is to perform a systematic literature survey of recent and state-of-the-art papers in order to draw insights and highlight the future directions.Design/methodology/approachThis paper has selected and reviewed 204 papers published from the year 2002–2017. The papers were collected from the web of science and Google scholar database which have the DOI number. The selected papers were then categorized into main five core areas of RSC management namely reverse supply chain (RSC), Reverse Logistics (RL), Remanufacturing, Closed-Loop Supply Chain (CLSC) and Product Recovery Systems (PRS) and then analyzed with great detail. Finally, the research gaps that were identified from the study have been highlighted for future research opportunities.FindingsThis paper would serve as a roadmap to the managers who wish to align their forward and reverse supply chains for overall growth and development. It provides an in-depth knowledge on RSC to the researchers working in this domain. The scholars would be able to identify the areas of RSC which have been already addressed and the areas which remain unaddressed.Originality/valueThis paper presents a systematic literature survey of state-of-the-art papers that was published in the reputed journal in the area of RSC. Total 204 numbers of papers which were published in the reputed journals between 2002 and 2017 are reviewed, categorized and analysed to draw the opportunities and future research direction in the area of RSC.

Cognitive psychology and tourism research: state of the art

2017 ◽  
Vol 72 (2) ◽  
pp. 221-237 ◽  
Author(s):  
Liubov Skavronskaya ◽  
Noel Scott ◽  
Brent Moyle ◽  
Dung Le ◽  
Arghavan Hadinejad ◽  
...  
Keyword(s):  
Cognitive Psychology ◽  
State Of The Art ◽  
Practical Importance ◽  
Destination Image ◽  
Advertising Effectiveness ◽  
Future Research ◽  
Appraisal Theory ◽  
Cognitive Approach ◽  
Content Type ◽  
Visitor Satisfaction

PurposeThis review aims to discuss concepts and theories from cognitive psychology, identifies tourism studies applying them and discusses key areas for future research. The paper aims to demonstrate the usefulness of cognitive psychology for understanding why tourists and particularly pleasure travellers demonstrate the behaviour they exhibit. Design/methodology/approachThe paper reviews 165 papers from the cognitive psychology and literature regarding pleasure travel related to consciousness, mindfulness, flow, retrospection, prospection, attention, schema and memory, feelings and emotions. The papers are chosen to demonstrate the state of the art of the literature and provide guidance on how these concepts are vital for further research. FindingsThe paper demonstrates that research has favoured a behaviourist rather than cognitive approach to the study of hedonic travel. Cognitive psychology can help to understand the mental processes connecting perception of stimuli with behaviour. Numerous examples are provided: top-down and bottom-up attention processes help to understand advertising effectiveness, theories of consciousness and memory processes help to distinguish between lived and recalled experience, cognitive appraisal theory predicts the emotion elicited based on a small number of appraisal dimensions such as surprise and goals, knowledge of the mental organisation of autobiographical memory and schema support understanding of destination image formation and change and the effect of storytelling on decision-making, reconstructive bias in prospection or retrospection about a holiday inform the study of pleasurable experience. These findings indicate need for further cognitive psychology research in tourism generally and studies of holiday travel experiences. Research limitations/implicationsThis review is limited to cognitive psychology and excludes psychoanalytic studies. Practical implicationsCognitive psychology provides insight into key areas of practical importance. In general, the use of a cognitive approach allows further understanding of leisure tourists’ behaviour. The concept of attention is vital to understand destination advertising effectiveness, biases in memory process help to understand visitor satisfaction and experience design and so on. Use of cognitive psychology theory will lead to better practical outcomes for tourists seeking pleasurable experiences and destination managers. Originality valueThis is the first review that examines the application of concepts from cognitive psychology to the study of leisure tourism in particular. The concepts studied are also applicable to study of travellers generally.

A Systematic Literature Review of the EFQM Excellence Model from 1991 to 2019

1970 ◽  
Vol 2 (2) ◽  
pp. 11-15
Author(s):  
Muhammad Yousaf ◽  
Petr Bris
Keyword(s):  
Quality Management ◽  
Data Collection ◽  
Literature Review ◽  
Systematic Literature Review ◽  
Quantitative Research ◽  
Web Of Science ◽  
State Of The Art ◽  
Future Research ◽  
European Foundation ◽  
The Subject

A systematic literature review (SLR) from 1991 to 2019 is carried out about EFQM (European Foundation for Quality Management) excellence model in this paper. The aim of the paper is to present state of the art in quantitative research on the EFQM excellence model that will guide future research lines in this field. The articles were searched with the help of six strings and these six strings were executed in three popular databases i.e. Scopus, Web of Science, and Science Direct. Around 584 peer-reviewed articles examined, which are directly linked with the subject of quantitative research on the EFQM excellence model. About 108 papers were chosen finally, then the purpose, data collection, conclusion, contributions, and type of quantitative of the selected papers are discussed and analyzed briefly in this study. Thus, this study identifies the focus areas of the researchers and knowledge gaps in empirical quantitative literature on the EFQM excellence model. This article also presents the lines of future research.

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