The Impact of Real-Time Data in Improving the Efficiency, Safety and Productivity of Wells During the Installation of Lower Completion Assemblies in the Complex Deepwater Environment

2019 ◽  
Author(s):  
Andrew Hawthorn ◽  
Lei Fang ◽  
Ed O'Malley
Keyword(s):  
Real Time ◽  
Time Data ◽  
Real Time Data ◽  
The Impact

Why Ecological Momentary Assessment Surveys Go Incomplete?: When It Happens and How It Impacts Data

2020 ◽  
Author(s):  
Yu-Hsiang Wu ◽  
Jingjing Xu ◽  
Elizabeth Stangl ◽  
Shareka Pentony ◽  
Dhruv Vyas ◽  
...  
Keyword(s):  
Real Time ◽  
Self Report ◽  
Data Logging ◽  
Time Data ◽  
Real Time Data ◽  
Report Data ◽  
Self Report Data ◽  
Ecological Momentary ◽  
The Impact ◽  
Momentary Assessment

Abstract Background Ecological momentary assessment (EMA) often requires respondents to complete surveys in the moment to report real-time experiences. Because EMA may seem disruptive or intrusive, respondents may not complete surveys as directed in certain circumstances. Purpose This article aims to determine the effect of environmental characteristics on the likelihood of instances where respondents do not complete EMA surveys (referred to as survey incompletion), and to estimate the impact of survey incompletion on EMA self-report data. Research Design An observational study. Study Sample Ten adults hearing aid (HA) users. Data Collection and Analysis Experienced, bilateral HA users were recruited and fit with study HAs. The study HAs were equipped with real-time data loggers, an algorithm that logged the data generated by HAs (e.g., overall sound level, environment classification, and feature status including microphone mode and amount of gain reduction). The study HAs were also connected via Bluetooth to a smartphone app, which collected the real-time data logging data as well as presented the participants with EMA surveys about their listening environments and experiences. The participants were sent out to wear the HAs and complete surveys for 1 week. Real-time data logging was triggered when participants completed surveys and when participants ignored or snoozed surveys. Data logging data were used to estimate the effect of environmental characteristics on the likelihood of survey incompletion, and to predict participants' responses to survey questions in the instances of survey incompletion. Results Across the 10 participants, 715 surveys were completed and survey incompletion occurred 228 times. Mixed effects logistic regression models indicated that survey incompletion was more likely to happen in the environments that were less quiet and contained more speech, noise, and machine sounds, and in the environments wherein directional microphones and noise reduction algorithms were enabled. The results of survey response prediction further indicated that the participants could have reported more challenging environments and more listening difficulty in the instances of survey incompletion. However, the difference in the distribution of survey responses between the observed responses and the combined observed and predicted responses was small. Conclusion The present study indicates that EMA survey incompletion occurs systematically. Although survey incompletion could bias EMA self-report data, the impact is likely to be small.

scholarly journals Financing entrepreneurship in times of crisis: Exploring the impact of COVID-19 on the market for entrepreneurial finance in the United Kingdom

2020 ◽  
Vol 38 (5) ◽  
pp. 380-390 ◽  
Author(s):  
Ross Brown ◽  
Augusto Rocha ◽  
Marc Cowling
Keyword(s):  
United Kingdom ◽  
Real Time ◽  
Entrepreneurial Finance ◽  
Time Data ◽  
Face To Face ◽  
Policy Interventions ◽  
The United Kingdom ◽  
Real Time Data ◽  
Start Ups ◽  
The Impact

This commentary explores the manner in which the current COVID-19 crisis is affecting key sources of entrepreneurial finance in the United Kingdom. We posit that the unique relational nature of entrepreneurial finance may make it highly susceptible to such a shock owing to the need for face-to-face interaction between investors and entrepreneurs. The article explores this conjecture by scrutinising a real-time data source of equity investments. Our findings suggest that the volume of new equity transactions in the United Kingdom has declined markedly since the outbreak of the COVID-19 pandemic. It appears that seed finance is the main type of entrepreneurial finance most acutely affected by the crisis, which typically goes to the most nascent entrepreneurial start-ups facing the greatest obstacles obtaining finance. Policy makers can utilise these real-time data sources to help inform their strategic policy interventions to assist the firms most affected by crisis events.

scholarly journals Internet of Things based Customer Relationship Management – A Research Perspective

2018 ◽  
Vol 7 (2.7) ◽  
pp. 444 ◽  
Author(s):  
Samir Yerpude ◽  
Dr Tarun Kumar Singhal
Keyword(s):  
Internet Of Things ◽  
Real Time ◽  
Customer Relationship Management ◽  
Relationship Management ◽  
Mobile Internet ◽  
Customer Relationship ◽  
Time Data ◽  
Crm System ◽  
Real Time Data ◽  
The Impact

Objectives: To study the impact of Internet of things (IoT) on the Customer Relationship Management process and evaluate the benefits in terms of customer satisfaction and customer retention. Methods: An extensive literature review was conducting wherein the constructs of CRM and IoT are studied. Various preliminary information on IoT and CRM system along with the components of Digital enablers have been evaluated. References from research papers, journals, Internet sites, statistical data sites and books were used to collate the relevant content on the subject. The study of all the relevant scenarios where there is a possible impact of IoT origin real time data on CRM was undertaken. Findings: Customer demands are continuously evolving and it is very relevant for all the organizations to align and keep pace with the change. Organizations need to be customer centric and agile to the changing market scenarios. Evaluation of the trends in mobile internet vs desktop internet was also conducted to validate the findings. Application: The usage of real time data emerging out of the IoT landscape has become a reality with the data transmitted over the Internet and consumed by the CRM system. It improves the control on the customer relationship function helping the organizations to operate within healthy and sustained profit  

scholarly journals Metamorphosis of COVID-19 Pandemic

2020 ◽  
Author(s):  
Farhan Saif
Keyword(s):  
Real Time ◽  
Growth Model ◽  
Exponential Growth ◽  
Impact Point ◽  
Time Data ◽  
Slowing Down ◽  
Real Time Data ◽  
The Usa ◽  
Mathematical Techniques ◽  
The Impact

We show phase-wise growth of COVID 19 pandemic and explain it by comparing real time data with Discrete Generalized Growth model and Discrete Generalized Richard Model. The comparison of COVID 19 is made for China, Italy, Japan and the USA. The mathematical techniques makes it possible to calculate the rate of exponential growth of active cases, estimates the size of the outbreak, and measures the deviation from the exponential growth indicating slowing down effect. The phase-wise pandemic evolution following the real time data of active cases defines the impact-point when the preventive steps, taken to eradicate the pandemic, becomes effective. The study is important to devise the measures to handle emerging threat of similar COVID-19 outbreaks in other countries, especially in the absence of a medicine.

scholarly journals Adoption of Cloud-based E-Health Record through the Technology, Organization and Environment Perspective

2018 ◽  
Vol 7 (4.35) ◽  
pp. 609 ◽  
Author(s):  
Hidayah Sulaiman ◽  
Asma Magaireh ◽  
Rohaini Ramli
Keyword(s):  
Cloud Computing ◽  
Real Time ◽  
Data Access ◽  
Healthcare Setting ◽  
Easy Access ◽  
Management Support ◽  
Computing Technology ◽  
Time Data ◽  
Real Time Data ◽  
The Impact

With the ever increasing cost of investing in technological innovations and the amount of patient data to be processed on daily basis, healthcare organizations are in dire need for solutions that could provide easy access and better management of real time data with lower cost.  The emerging trend of organizations optimizing cost in investing less on physical hardware has brought about the use of cloud computing technology in various industries including healthcare.  The use of cloud computing technology has brought better efficiency in providing real time data access, bigger storage capacity and reduction of cost in terms of maintenance. Although numerous benefits have been publicized for organizations to adopt the technology, nevertheless the rate of adoption is still at is infancy. Hence, this study explores factors that may affect the adoption of cloud-based technology particularly within the healthcare context. A quantitative study was conducted through the distribution of survey in Jordanian healthcare facilities. The survey was conducted to gauge the understanding of cloud-based EHR concepts identified through literature and validate the factors that could potentially provide an impact towards the cloud-based EHR adoption. The theoretical underpinnings of Technology-Organization-Environment (TOE) were investigated in studying the impact towards the adoption of cloud-based EHR. Results indicate that Technology-Organization-Environment factors such as privacy, reliability, security, top management support, organizational readiness, competition and regulatory environment are critical factors towards the adoption of cloud technology within a healthcare setting.

Enhancing New Product Development Effectiveness With Internet of Things Origin Real Time Data

2018 ◽  
Vol 20 (3) ◽  
pp. 21-35 ◽  
Author(s):  
Samir Yerpude ◽  
Tarun Kumar Singhal
Keyword(s):  
Product Development ◽  
Real Time ◽  
New Product Development ◽  
New Product ◽  
Product Development Process ◽  
Primary Data ◽  
Time Data ◽  
Organizational Boundaries ◽  
Real Time Data ◽  
The Impact

The purpose of this article is twofold. First is to ascertain and establish the collaboration required between different stakeholders in the fundamental process of New Product Development (NPD). Augmentation of the process with the IoT origin real time data to enrich the efficacy of the New Product Development process forms the second part of the study. The primary data is collated from over 100 plus professionals while the qualitative data required for the second part is collated with the help of focused group interviews. The Likert scale with five points was deployed to record the opinions. The empirical analysis supports the theory that an effective collaboration is required between the different entities such as Sales, Marketing, R&D and going beyond the organizational boundaries Suppliers & Customers for the new product to be fruitful and successful in the market. The impact of using the IoT origin real time data on the effectiveness of the New Product Development is evaluated. In the current scenario for an organization to lead the market, it is essential that it has a descent product roadmap and an effective NPD. The current study reveals the importance of the NPD and contributes towards making it more effective with the IoT origin real time data.

The MediShout App: Communication, Control and Capturing Staff Voice During Covid-19 (Preprint)

2020 ◽  
Author(s):  
Ashish Kalraiya ◽  
Ben Walker ◽  
Shiron Rajendran ◽  
Sayinthen Vivekanantham ◽  
Danny Sharpe ◽  
...  
Keyword(s):  
Real Time ◽  
Impact Analysis ◽  
Clinical Care ◽  
Efficient Solutions ◽  
World Health ◽  
Time Data ◽  
Frontline Staff ◽  
Mobile Phone Application ◽  
Real Time Data ◽  
The Impact

BACKGROUND Covid-19 is exacerbating pre-existing pressures on healthcare systems. Frontline staff are relying more than usual on effective logistics and infrastructure to deliver patient care, for example provision of PPE, stock, facilities and equipment. Staff must adapt their ways of working in response to new challenges. Traditional communication channels within hospitals are often inefficient and not digitised, preventing healthcare organisations from adequately supporting staff and providing efficient solutions to problems. OBJECTIVE This study deployed the MediShout mobile phone application (app) to capture real-time data, on problems with logistics and infrastructure occurring in hospitals during the Covid-19 pandemic. The main objectives were to determine whether; healthcare staff would use the app, reporting led to immediate improvements, and data-collection could drive long-term transformational change and improve responses to future pandemics. METHODS The app was used by staff to report issues with logistics and infrastructure across two hospital emergency departments (EDs) at Imperial College Healthcare Trust, UK. These reports were acted upon by senior physicians and nurses, operational managers and service helpdesks. Data was collected from the start of the first peak of Covid-19 in the UK, between March and April 2020. Data from each report were retrospectively analysed across multiple categories, including problem description and time of submission. To gauge the impact of each issue on clinical care, reports were scored against an impact scoring tool using a modified version of the World Health Organisation’s ‘quality of care’ definition. RESULTS During this study, 94 reports were submitted. Reporting peaks were observed at times corresponding to clinical handovers. Peaks were also observed when changes had occurred to existing processes within the EDs. Impact analysis highlighted that every report sent had ‘impact’ or ‘significant impact’ on various aspects of care, including efficiency, patient safety and timely treatment. CONCLUSIONS The MediShout app captured valuable real-time data from frontline staff during the peak of Covid-19. Staff readily adopted the digital technology as it provided a more efficient way to resolve issues. This enabled hospitals to better allocate scarce resources, such as PPE, to those who needed it most. This study suggests listening to the voice of frontline staff during times of crisis allows more effective responses. Capturing data during pandemics is critical for healthcare organisations to learn lessons and maintain control. During this study, it was established that most problems occurred due to changes in practice, such as dividing EDs into Covid-19 and non-Covid-19 zones, rather than increased caseload. Logistical and infrastructure issues were categorised as being “material” (stock, equipment, medicines, or estates and facilities) or “workflow” (task-management, new ways of working, infection control and communication) in nature. This provides healthcare organisations with a methodical tool for risk-assessing and coordinating future pandemic responses. CLINICALTRIAL n/a

scholarly journals Baby steps: the gender division of childcare during the COVID-19 pandemic

2020 ◽  
Vol 36 (Supplement_1) ◽  
pp. S169-S186 ◽  
Author(s):  
Almudena Sevilla ◽  
Sarah Smith
Keyword(s):  
Mental Health ◽  
Adverse Effects ◽  
Real Time ◽  
Time Data ◽  
Daily Lives ◽  
Real Time Data ◽  
The Future ◽  
Families With Children ◽  
The Impact

Abstract The nature and scale of the shocks to the demand for, and the supply of, home childcare during the COVID-19 pandemic provide a unique opportunity to increase our understanding of the division of home labour and the determinants of specialization within the household. We collected real-time data on daily lives to document the impact of measures to control COVID-19 on UK families with children under the age of 12. We document that these families have been doing the equivalent of a working week in childcare, with mothers bearing most of the burden. The additional hours of childcare done by women are less sensitive to their employment than they are for men, leaving many women juggling work and (a lot more) childcare, with likely adverse effects on their mental health and future careers. However, some households, those in which men have not been working, have taken greater steps towards an equal allocation, offering the prospect of sharing the burden of childcare more equally in the future.

Advancements in the National Vital Statistics System to Meet the Real-Time Data Needs of a Pandemic

2021 ◽  
Vol 111 (12) ◽  
pp. 2133-2140
Author(s):  
Farida B. Ahmad ◽  
Robert N. Anderson ◽  
Karen Knight ◽  
Lauren M. Rossen ◽  
Paul D. Sutton
Keyword(s):  
Real Time ◽  
Death Certificate ◽  
Vital Statistics ◽  
Mortality Data ◽  
Annual Data ◽  
Health Statistics ◽  
Time Data ◽  
Real Time Data ◽  
Data Files ◽  
The Impact

The National Center for Health Statistics’ (NCHS’s) National Vital Statistics System (NVSS) collects, processes, codes, and reviews death certificate data and disseminates the data in annual data files and reports. With the global rise of COVID-19 in early 2020, the NCHS mobilized to rapidly respond to the growing need for reliable, accurate, and complete real-time data on COVID-19 deaths. Within weeks of the first reported US cases, NCHS developed certification guidance, adjusted internal data processing systems, and stood up a surveillance system to release daily updates of COVID-19 deaths to track the impact of the COVID-19 pandemic on US mortality. This report describes the processes that NCHS took to produce timely mortality data in response to the COVID-19 pandemic. (Am J Public Health. 2021;111(12):2133–2140. https://doi.org/10.2105/AJPH.2021.306519 )

scholarly journals Frontiers of Real-Time Data Analysis

2011 ◽  
Vol 49 (1) ◽  
pp. 72-100 ◽  
Author(s):  
Dean Croushore
Keyword(s):  
Data Analysis ◽  
Real Time ◽  
Data Sets ◽  
Current Analysis ◽  
Time Data ◽  
The Past ◽  
Data Revisions ◽  
The World ◽  
Real Time Data ◽  
The Impact

In the past ten years, researchers have explored the impact of data revisions in many different contexts. Researchers have examined the properties of data revisions, how structural modeling is affected by data revisions, how data revisions affect forecasting, the impact of data revisions on monetary policy analysis, and the use of real-time data in current analysis. This paper summarizes many of the questions for which real-time data analysis has provided answers. In addition, researchers and institutions have developed better real-time data sets around the world. Still, additional research is needed in key areas and research to date has uncovered even more fruitful areas worth exploring. (JEL C52, C53, C80, E01)

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