scholarly journals Influence of COVID-19 Lockdowns on the Usage of a Vision Assistance App Among Global Users With Visual Impairment: Big Data Analytics Study (Preprint)

2020 ◽  
Author(s):  
Gang Luo ◽  
Shrinivas Pundlik
Keyword(s):  
Big Data ◽  
Visual Impairment ◽  
Seasonal Changes ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Assistive Technologies ◽  
Significant Decline ◽  
Daily Activities ◽  
Visual Aids ◽  
Insight Into

BACKGROUND Millions of individuals with visual impairment use vision assistance apps to help with their daily activities. The most widely used vision assistance apps are magnifier apps. It is still largely unknown what the apps are used for. Lack of insight into the visual needs of individuals with visual impairment is a hurdle for the development of more effective assistive technologies. OBJECTIVE This study aimed to investigate how needs for visual aids may vary with social activities, by observing the changes in the usage of a smartphone magnifier app when many users take breaks from work. METHODS The number of launches of the SuperVision Magnifier app was determined retrospectively from 2018 to 2020 from among active users worldwide. The fluctuation in app usage was examined by comparing weekday vs weekend periods, Christmas and new year vs nonholiday seasons, and COVID-19 lockdowns vs the easing of restriction during the pandemic. RESULTS On average, the app was used 262,466 times by 38,237 users each month in 2020 worldwide. There were two major trough points on the timeline of weekly app usage, one aligned with the COVID-19 lockdowns in April 2020 and another aligned with the Christmas and new year week in 2018 and 2019. The app launches declined by 6947 (11% decline; <i>P</i>&lt;.001) during the lockdown and by 5212 (9% decline; <i>P</i>=.001) during the holiday weeks. There was no significant decline during March to May 2019. App usage compensated for seasonal changes was 8.6% less during weekends than during weekdays (<i>P</i>&lt;.001). CONCLUSIONS The need for vision assistance technology was slightly lower during breaks and lockdowns, probably because the activities at home were different and less visually demanding. Nevertheless, for the entire user population, the needs for visual aids are still substantial.

Big Data Analytics in Action

2019 ◽  
pp. 266-294 ◽  
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Insight Into

Have you ever wondered how companies that adopt big data and analytics have generated value? Which algorithm are they using for which situation? And what was the result? These points will be discussed in this chapter in order to highlight the importance of big data analytics. To this end, and in order to give a quick introduction to what is being done in data analytics applications and to trigger the reader's interest, the author introduces some applications examples. This will allow you, in more detail, to gain more insight into the types and uses of algorithms for data analysis. So, enjoy the examples.

Big-Data-Based Architectures and Techniques

2019 ◽  
pp. 19-50
Author(s):  
Gopala Krishna Behara
Keyword(s):  
Big Data ◽  
Real World ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Data Sources ◽  
Reference Architecture ◽  
The Real ◽  
Key Concepts ◽  
Insight Into

This chapter covers the essentials of big data analytics ecosystems primarily from the business and technology context. It delivers insight into key concepts and terminology that define the essence of big data and the promise it holds to deliver sophisticated business insights. The various characteristics that distinguish big data datasets are articulated. It also describes the conceptual and logical reference architecture to manage a huge volume of data generated by various data sources of an enterprise. It also covers drivers, opportunities, and benefits of big data analytics implementation applicable to the real world.

scholarly journals A Research on the Importance of Big Data Analytics in Health Care and Government Sectors

2019 ◽  
Vol 9 (1) ◽  
pp. 5471-5473
Keyword(s):  
Health Care ◽  
Big Data ◽  
Data Analytics ◽  
Data Use ◽  
Big Data Analytics ◽  
Use Cases ◽  
State Of Affairs ◽  
Important Purpose ◽  
Insight Into

This paper provides associate insight into but, we are able to uncover further worth from the information produced by health care and govt. associate oversized quantity of varied info is produced by these sectors. However, whereas not correct info analytics ways, this info became of no use. Big Data Analytics victimization Hadoop plays an honest responsibility in enjoying important purpose analysis of the big volume of knowledge and prepared to guess the pressing state of affairs things prior to that happens. It explains the Big Data use-cases in health care and govt. sectors.

scholarly journals Exploring Big Data Analytic Approaches to Cancer Blog Text Analysis (Preprint)

2018 ◽  
Author(s):  
Viju Raghupathi ◽  
Yilu Zhou ◽  
Wullianallur Raghupathi
Keyword(s):  
Social Media ◽  
Big Data ◽  
Data Analytics ◽  
Word Association ◽  
Early Stage ◽  
Big Data Analytics ◽  
Free Text ◽  
Health Related ◽  
Data Analytic ◽  
Insight Into

BACKGROUND In recent years researchers have begun to realize the value of social media as a source for data that helps us understand health-related phenomena. Health blogs in particular are rich with information for decision-making. While there are web crawlers and blog analysis software that generate statistics related to blogs, these are relatively primitive and are not useful computationally to aid with the analysis and understanding of the social networks and medical blogs that are evolving around healthcare. There is a need for sophisticated tools to fill this gap. Furthermore, to our knowledge there are not many big data studies or applications in the text analytics of cancer blogs. This study attempts to fill this specific gap while analyzing cancer blogs. OBJECTIVE In this exploratory research, we examine the potential of applying big data analytic techniques to the analysis of blogs that exist in the cancer domain. Our objective is twofold: to extract from the blogs, patterns and insight about cancer diagnosis, treatment, and management; and to apply advanced computation techniques in processing large amounts of unstructured health data. METHODS We applied the big data analytics architecture of Hadoop MapReduce via the Cloudera platform to the analysis of cancer blog content, in order to extract patterns and insight on cancer diagnoses. We apply a series of algorithms to gain insight into the content and develop a vocabulary and taxonomy of keywords based on existing medical nomenclature. By applying a number of algorithms, we gained insight into the blog content. The study identifies, for instance, the most discussed topics as well as associations that relate to key phenomena RESULTS Using several text analytic algorithms, including word count, word association, clustering, and classification, we were able to identify and analyze the patterns and keywords in cancer blog postings. This gave insight into some of the key issues that are discussed in blogs such as the type of cancer (breast cancer being the dominant topic), diagnosis, treatments, and others. CONCLUSIONS In general, big data analytics has the potential to transform the way practitioners and researchers gain insight from health social media, especially those in free text, unstructured form. Big data analytics and applications in health-related social media are still at an early stage, and rapid acceleration is possible with the advancements in models, tools, and technologies.

scholarly journals A Novel Customized Big Data Analytics Framework for Drug Discovery

2018 ◽  
Author(s):  
A. Jainul Fathima ◽  
G. Murugaboopathi
Keyword(s):  
Big Data ◽  
Drug Discovery ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Pharmaceutical Companies ◽  
Biomedical Data ◽  
Analytic Framework ◽  
Computational Tools ◽  
Computational Drug Discovery ◽  
Insight Into

Drug discovery is related to analytics as the method requires a technique to handle the extremely large volume of structured and unstructured biomedical data of multi-dimensional and complexity from pharmaceutical companies. To tackle the complexity of data and to get better insight into the data, big data analytics can be used to integrate the massive amount of pharmaceutical data and computational tools in an analytic framework. This paper presents an overview of big data analytics in the field of drug discovery and outlines an analytic framework which can be applied to computational drug discovery process and briefly discuss the challenges. Hence, big data analytics may contribute to better drug discovery.  

scholarly journals Impact of Healthcare Predictions with Big Data Analytics and Cognitive Computing Techniques

2019 ◽  
Vol 8 (2) ◽  
pp. 4757-4762
Keyword(s):  
Big Data ◽  
Information Society ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Extensive Study ◽  
Comprehensive Analysis ◽  
Cognitive Computing ◽  
The World ◽  
Complex Relationships ◽  
Insight Into

The world has transformed into an information society that exceedingly depends on data. Since information frameworks create large measures of records each day, consistently, it appears the world is achieving the level of data overload. Big data is used to process the enormous volumes of data into revealing shrouded designs, complex relationships, and other helpful information. This work has done a comprehensive analysis of enormous information investigation in medicinal services. A brief insight into the importance of cognitive computing in healthcare has been presented. The extensive study concludes that the Cognitive computing has more impact on healthcare predictions than the big data analytics.

scholarly journals Big Data Analytics: A Spotify Case Study

2021 ◽  
Vol 9 (10) ◽  
pp. 1823-1829
Author(s):  
Suraj Ingle
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Customer Satisfaction ◽  
Customer Loyalty ◽  
Data Analytics ◽  
Exploratory Data Analysis ◽  
Big Data Analytics ◽  
Exploratory Data ◽  
Insight Into

Abstract: By developing products that are in line with consumer needs, anticipating their profitability and manufacturing them, Big Data has opened up a lot of possibilities for building customer loyalty and commercial business by proactively engaging and comprehensively streamlining offers across all customer touch points. The use of big data to determine the best, most efficient ways to engage and interact with their customers will be discussed in this paper. An insight into how Spotify intends to provide music lovers additional ways to find their favourite songs, interact with artists, and improve Spotify recommendations has been provided. Keywords: Big Data, Data Analytics, Customer Satisfaction, Exploratory Data Analysis

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