scholarly journals Using AI to Learn Industry Specific Big Data for Business Operation and Crisis Management

2021 ◽  
Author(s):  
Yew Kee Wong
Keyword(s):  
Big Data ◽  
Crisis Management ◽  
Social Life ◽  
Decision Makers ◽  
Advanced Technology ◽  
Business Operation ◽  
Business Operations ◽  
The World ◽  
Tools And Techniques ◽  
Management Domains

Artificial intelligence has been a buzz word that is impacting every industry in the world. With the rise of such advanced technology, there will be always a question regarding its impact on our social life, environment and economy thus impacting all efforts exerted towards sustainable development. In the information era, enormous amounts of data have become available on hand to decision makers. Big data refers to datasets that are not only big, but also high in variety and velocity, which makes them difficult to handle using traditional tools and techniques. Due to the rapid growth of such data, solutions need to be studied and provided in order to handle and extract value and knowledge from these datasets for different industries and business operations. Numerous use cases have shown that AI can ensure an effective supply of information to citizens, users and customers in times of crisis. This paper aims to analyse some of the different methods and scenario which can be applied to AI and big data, as well as the opportunities provided by the application in various business operations and crisis management domains.

scholarly journals Dealing Crisis Management using AI

2021 ◽  
Author(s):  
Yew Kee Wong
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Crisis Management ◽  
Social Life ◽  
Decision Makers ◽  
Advanced Technology ◽  
Business Operations ◽  
The World ◽  
Tools And Techniques ◽  
Management Domains

Artificial intelligence has been a buzz word that is impacting every industry in the world. With the rise of such advanced technology, there will be always a question regarding its impact on our social life, environment and economy thus impacting all efforts exerted towards sustainable development. In the information era, enormous amounts of data have become available on hand to decision makers. Big data refers to datasets that are not only big, but also high in variety and velocity, which makes them difficult to handle using traditional tools and techniques. Due to the rapid growth of such data, solutions need to be studied and provided in order to handle and extract value and knowledge from these datasets for different industries and business operations. Numerous use cases have shown that AI can ensure an effective supply of information to citizens, users and customers in times of crisis. This paper aims to analyse some of the different methods and scenario which can be applied to AI and big data, as well as the opportunities provided by the application in various business operations and crisis management domains.

scholarly journals Dealing Crisis Management using AI

2021 ◽  
Vol 11 (05) ◽  
pp. 15-22
Author(s):  
Yew Kee Wong
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Crisis Management ◽  
Social Life ◽  
Decision Makers ◽  
Advanced Technology ◽  
Business Operations ◽  
The World ◽  
Tools And Techniques ◽  
Management Domains

Artificial intelligence has been a buzz word that is impacting every industry in the world. With the rise of such advanced technology, there will be always a question regarding its impact on our social life, environment and economy thus impacting all efforts exerted towards sustainable development. In the information era, enormous amounts of data have become available on hand to decision makers. Big data refers to datasets that are not only big, but also high in variety and velocity, which makes them difficult to handle using traditional tools and techniques. Due to the rapid growth of such data, solutions need to be studied and provided in order to handle and extract value and knowledge from these datasets for different industries and business operations. Numerous use cases have shown that AI can ensure an effective supply of information to citizens, users and customers in times of crisis. This paper aims to analyse some of the different methods and scenario which can be applied to AI and big data, as well as the opportunities provided by the application in various business operations and crisis management domains.

scholarly journals Applying AI and Big Data for Sensitive Operations and Disaster Management

2021 ◽  
Author(s):  
Yew Kee Wong
Keyword(s):  
Artificial Intelligence ◽  
Sustainable Development ◽  
Big Data ◽  
Disaster Management ◽  
Social Life ◽  
Decision Makers ◽  
Advanced Technology ◽  
Business Operations ◽  
The World ◽  
Tools And Techniques

Artificial intelligence has been a buzz word that is impacting every industry in the world. With the rise of such advanced technology, there will be always a question regarding its impact on our social life, environment and economy thus impacting all efforts exerted towards sustainable development. In the information era, enormous amounts of data have become available on hand to decision makers. Big data refers to datasets that are not only big, but also high in variety and velocity, which makes them difficult to handle using traditional tools and techniques. Due to the rapid growth of such data, solutions need to be studied and provided in order to handle and extract value and knowledge from these datasets for different industries and business operations. Numerous use cases have shown that AI can ensure an effective supply of information to citizens, users and customers in times of crisis. This paper aims to analyse some of the different methods and scenario which can be applied to AI and big data, as well as the opportunities provided by the application in various sensitive operations and disaster management.

Introduction to Use and Analysis of Big Data in E-Learning

2019 ◽  
pp. 75-87
Author(s):  
Renuka Mahajan
Keyword(s):  
Big Data ◽  
Big Data Analysis ◽  
Vital Role ◽  
Interaction Data ◽  
The World ◽  
Learner Interaction ◽  
E Learning ◽  
One Year ◽  
Tools And Techniques ◽  
Data Analytic

In today's world everything is connected and is either consuming data or generating data. The world is changing so fast that even one-year-old data may not be useful, and hence, big data analysis plays a very vital role for higher management of any organizations for decision making. Data warehousing helps in gathering and storing verifiable information into a single entity. Data can be of different types like speech, text, etc. It can be structured or unstructured. Each data point is characterized in terms of volume or variety. This chapter gives an overview of how to utilize the learner interaction data from a particular website and how patterns can be captured by analyzing learner interaction data with big data analytic tools. Big data has risen in the field of education and has many challenges like storage, combining, analysis, and scalability of big data. It covers tools and techniques that can be used. The results from this study will have implications for new learners to the e-learning website, website designers, and academicians.

scholarly journals Lessons from COVID-19 Pandemic: A Preliminary Analysis of Bangladesh’s Responses

2021 ◽  
Vol 5 (2) ◽  
pp. 165-177
Author(s):  
Rifat Mahmud
Keyword(s):  
Content Analysis ◽  
Data Collection ◽  
Crisis Management ◽  
Preliminary Analysis ◽  
Decision Makers ◽  
Policy Makers ◽  
The World ◽  
The Government ◽  
Crisis Responses ◽  
Second Wave

The first wave of the COVID- 19 disease has caused a daunting and unprecedented challenge for governments of the world. Decision-makers worldwide, including that of Bangladesh, had to initiate responses that were beyond the conventional measures. This paper offers the decision-makers in Bangladesh on the possible learning in the field of crisis management during this pandemic. The paper aims in focusing on the first phase of responses to COVID-19 (March-May) from the initial lockdown to the reopening of offices by the government of Bangladesh. Methodologically, the paper is a content analysis involving netnography approach of data collection from websites. The paper presents a finding of possible lessons of crisis responses in Bangladesh. The paper aims to create an agenda for learning lessons from the situation of the largest crisis to hit the world in centuries. The paper induces substantial value for policy-makers to be prepared for the second wave of the COVID- 19 crisis, to meet the challenges of the pandemic.

Big Data Analytics in Undergraduate Advertising Curricula

2022 ◽  
pp. 1958-1973
Author(s):  
Kenneth C. C. Yang ◽  
Yowei Kang
Keyword(s):  
Higher Education ◽  
Big Data ◽  
Data Analytics ◽  
Higher Education Institutions ◽  
Big Data Analytics ◽  
Past Research ◽  
Data Driven ◽  
The World ◽  
Tools And Techniques ◽  
Personalized Advertising

The rapid ascent of data-driven advertising practices has allowed advertising professionals to develop highly-targeted and personalized advertising campaigns. The success of data-driven advertising relies on if future professionals are proficient with basics of Big Data analytics. However, past research of undergraduate advertising curricula around the world has shown that higher education institutions tend to fall behind in offering the most up-to-dated training for advertising students. Findings have shown that undergraduate advertising programs have slowly taken advantage of the potential of the data analytics tools and techniques. This trend is observed among higher education institutions around the world. Practical, research, and pedagogical implications are discussed.

Machine Learning and Deep Learning Technologies

2021 ◽  
Author(s):  
Yew Kee Wong
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Big Data ◽  
Deep Learning ◽  
Model Building ◽  
Learning Technologies ◽  
Decision Makers ◽  
Human Intervention ◽  
Learning Techniques ◽  
Tools And Techniques

In the information era, enormous amounts of data have become available on hand to decision makers. Big data refers to datasets that are not only big, but also high in variety and velocity, which makes them difficult to handle using traditional tools and techniques. Due to the rapid growth of such data, solutions need to be studied and provided in order to handle and extract value and knowledge from these datasets. Machine learning is a method of data analysis that automates analytical model building. It is a branch of artificial intelligence based on the idea that systems can learn from data, identify patterns and make decisions with minimal human intervention. Such minimal human intervention can be provided using machine learning, which is the application of advanced deep learning techniques on big data. This paper aims to analyse some of the different machine learning and deep learning algorithms and methods, aswell as the opportunities provided by the AI applications in various decision making domains.

Integrating Big Data Analytics into Advertising Curriculum

2017 ◽  
pp. 228-250
Author(s):  
Kenneth C. C. Yang ◽  
Yowei Kang
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics ◽  
The World ◽  
Challenges And Opportunities ◽  
The Status ◽  
Consumer Data ◽  
Tools And Techniques ◽  
Data Analytic ◽  
Collection Methods

With the assistance of new computing technologies and consumer data collection methods, advertising professionals are capable of generating better targeted advertising campaigns. Big Data analytics are particularly worth noticing and have presented ample opportunities for advertising researchers and practitioners around the world. Although Big Data analytic courses have been offered at major universities, existing advertising curricula have yet to address the opportunities and challenges offered by Big Data. This chapter collects curricular data from major universities around the world to examine what Big Data has posed challenges and opportunities to existing advertising curricula in an international context. Curricula of 186 universities around the world are reviewed to describe the status of integrating these developments into better preparing advertising students for these changes. Findings show that only selected advertising programs in the U.S. have begun to explore the potential of the data analytics tools and techniques. Practical and educational implications are discussed.

A Study on Tools and Techniques of Big Data Analytics for Text Summarization From Multi-Documents

2021 ◽  
pp. 19-32
Author(s):  
Martin Aruldoss ◽  
Miranda Lakshmi Travis
Keyword(s):  
Big Data ◽  
Search Algorithm ◽  
Big Data Analytics ◽  
Text Summarization ◽  
Advanced Technology ◽  
Document Summarization ◽  
Extractive Summarization ◽  
Internet Resources ◽  
Abstractive Summarization ◽  
Tools And Techniques

Multi-document summarization extracts and summarizes the information without affecting its original context from the different sources of documents. It has been carried out using extractive text summarization and abstractive text summarization. Extractive summarization extracts summaries from verbatim lines, and abstractive summarization extracts new lines of summary from the source documents. Abstractive summarization is an advanced technology compared to extractive summarization. This research studies extractive summarization of multi documents from internet resources using word frequency counting and with maximum coverage using K-means clustering. In an internet search, the search algorithm shows the results from different websites using crawling and indexing. However, the search and text summary take place from hundreds, thousands, maybe millions of documents. To handle and manipulate these huge amounts of information, big data and its techniques are applied widely. This research also addresses big data techniques and tools that are available for multi-document summarization.

Recifes de Coral de Profundidade: Corais Construtores e sua Distribuição no Brasil

2016 ◽  
Vol 19 (3) ◽  
Author(s):  
Débora De Oliveira Pires
Keyword(s):  
Coral Reefs ◽  
Deep Sea ◽  
Decision Makers ◽  
Advanced Technology ◽  
Marine Biodiversity ◽  
Brazilian Coast ◽  
Lophelia Pertusa ◽  
Deep Waters ◽  
The World ◽  
The Impact

Deep-sea coral reefs and coral habitats are hotspots of biodiversity and provide numerous resources for fishing, bioprospecting and science. The deep-water coral reefs and coral aggregates were first discovered in locations off the coast of Norway, in 1865. The increase of commercial operations in deep waters, and the use of advanced technology in offshore areas have revealed the true scale of deep-sea coral ecosystems of Europe, until then virtually unknown. From the 1990’s, there was a considerable increase in the number of important scientific contributions on deep-sea coral habitats. So, today is known that the occurrence of coral reefs is not restricted to shallow waters of tropical and subtropical regions and that there are deep-sea coral reefs spread out of the world, including Brazil. The goal of this study was to indicate the existence of potential areas of deep-sea coral reefs/habitats along the Brazilian coast, from records of occurrence of coral reef builders species (Lophelia pertusa, Madrepora oculata, Solenosmilia variabilis, Dendrophyllia alternata and Enallopsammia rostrata). The examination of the records/specimens demonstrated an extensive and almost continuous latitudinal distribution of the coral species along the Brazilian coast. Fishing is the main cause of impact to deep-sea coral reefs in several regions of the world. For more than a decade the deep demersal fishing has been held in Brazil and the extent of the impact caused by fishing nets, used by the boats close to the reefs, is unknown. The data presented here provide a contribution not only to the scientific community, but also to the decision makers regarding the uses of areas of the Brazilian shelf and slope, which represent reservoirs of rich marine biodiversity.

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