scholarly journals Understanding barriers to linking novel consumer and lifestyle data for health research, results from the LifeInfo Survey: a topic modelling approach (Preprint)

2020 ◽  
Author(s):  
Holly Clarke ◽  
Stephen Clark ◽  
Mark Birkin ◽  
Heather Iles-Smith ◽  
Adam Glaser ◽  
...  
Keyword(s):  
Data Sharing ◽  
Large Scale ◽  
Best Practice ◽  
Latent Dirichlet Allocation ◽  
Data Linkage ◽  
Public Attitudes ◽  
Future Research ◽  
Store Loyalty ◽  
Topic Modelling ◽  
Personal Privacy

BACKGROUND Novel consumer and lifestyle data, for example those collected by supermarket loyalty cards or mobile phone exercise tracking apps, offer numerous benefits for researchers wishing to understand diet and exercise related risk factors for diseases. Yet, limited research has addressed public attitudes towards linking these data with individual health records for research purposes. OBJECTIVE The aim of this research was to identify key barriers for data linkage and recommend safeguards and procedures that would encourage individuals to share these data for potential future research. METHODS The LifeInfo Survey consulted the public on their attitudes towards sharing consumer and lifestyle data for research purposes. Where barriers to data sharing existed, participants provided unstructured survey responses detailing what would make them more likely to share data for linkage with their health record in the future. The topic modelling technique Latent Dirichlet Allocation (LDA) was used to analyse these textual responses to uncover common thematic topics within the texts. RESULTS Participants provided responses related to sharing their store loyalty card data (n = 2,338) and health/fitness app data (n = 1,531). Key barriers to data sharing identified through topic modelling included: data safety and security, personal privacy, requirements of further information, fear of data being accessed by others, problems with data accuracy, not understanding the reason for data linkage and not using data production services. We provide recommendations for addressing these issues to establish best practice for future researchers wishing to utilise these data. CONCLUSIONS This study formulates large-scale consultation of public attitudes towards data linkage of this kind, as such, it is an important first step in understanding and addressing barriers to participation for research utilising novel consumer and lifestyle data.

Ensemble Methods for Improving Classification of Data Produced by Latent Dirichlet Allocation

2019 ◽  
Vol 0 (8/2018) ◽  
pp. 17-28
Author(s):  
Maciej Jankowski
Keyword(s):  
Text Analysis ◽  
Large Scale ◽  
Latent Dirichlet Allocation ◽  
Previous Analysis ◽  
Ensemble Methods ◽  
Topic Modelling ◽  
New Methods ◽  
Data Scientist ◽  
Dirichlet Allocation

Topic models are very popular methods of text analysis. The most popular algorithm for topic modelling is LDA (Latent Dirichlet Allocation). Recently, many new methods were proposed, that enable the usage of this model in large scale processing. One of the problem is, that a data scientist has to choose the number of topics manually. This step, requires some previous analysis. A few methods were proposed to automatize this step, but none of them works very well if LDA is used as a preprocessing for further classification. In this paper, we propose an ensemble approach which allows us to use more than one model at prediction phase, at the same time, reducing the need of finding a single best number of topics. We have also analyzed a few methods of estimating topic number.

The use of exercises to enhance and assess interlocal collaboration in preparedness: A qualitative analysis

2016 ◽  
Vol 13 (6) ◽  
pp. 499
Author(s):  
Nicole A. Errett, PhD, MSPH, CPH, CE ◽  
Shannon Frattaroli, PhD, MPH ◽  
Daniel J. Barnett, MD, MPH ◽  
Beth A. Resnick, MPH ◽  
Lainie Rutkow, PhD, JD, MPH
Keyword(s):  
Emergency Preparedness ◽  
Policy Development ◽  
Large Scale ◽  
Best Practice ◽  
Future Research ◽  
Emergency Plan ◽  
Semistructured Interviews ◽  
Development Support ◽  
Assessment Strategies

Introduction: Interlocal collaboration, or collaboration among neighboring independent municipalities, has been generally accepted as an emergency preparedness strategy. In the absence of large-scale disasters, emergency preparedness exercises may serve to test the effectiveness of interlocal collaboration on emergency preparedness. However, the use of emergency preparedness exercises to enhance or assess interlocal collaboration, or its impact on preparedness, requires additional empirical exploration. Hypothesis/problem: This exploratory study aims to understand the perspectives of key informants (KIs) with broad knowledge of the history, goals, and implementation of the Urban Area Security Initiative (UASI) program, as well as knowledge of interlocal collaboration exercises conducted as part of the UASI program, about the role of exercises in improving and assessing interlocal collaboration for emergency preparedness.Method: In early 2014, 28 KIs were interviewed during 24 semistructured interviews. Interviews were recorded and analyzed to identify key themes related to emergency preparedness exercises and the enhancement and assessment of interlocal collaboration.Results: KIs perceived exercises to enhance interlocal collaboration in preparedness by promoting regional, interlocal: risk assessment; emergency plan testing and operationalization; relationship development; support for regional plans and operational structures; capability delivery practice; best practice sharing across interlocal collaborations; and engagement of elected or senior leadership in interlocal preparedness endeavors. Exercise participants, scenarios, administration, formats, and assessment strategies to promote interlocal collaboration were identified. Conclusions: Seven distinct mechanisms by which exercises can enhance interlocal collaboration that can be used to guide future research and policy development were identified. The format, scenario, participation, and administration of emergency preparedness exercises can be tailored to enhance collaboration.

scholarly journals Big Data, Big Responsibility! Building best-practice privacy strategies into a large-scale neuroinformatics platform

2017 ◽  
Vol 1 (1) ◽  
Author(s):  
Christina Popovich ◽  
Francis Jeanson ◽  
Brendan Behan ◽  
Shannon Lefaivre ◽  
Aparna Shukla
Keyword(s):  
Big Data ◽  
Data Sharing ◽  
Patient Information ◽  
Neurological Disorders ◽  
Large Scale ◽  
Best Practice ◽  
Patient Data ◽  
Multidimensional Data ◽  
Neuroscience Research ◽  
Secure Data

ABSTRACT ObjectiveThe Ontario Brain Institute (OBI) has begun to catalyze scientific discovery in the field of neuroscience through its’ large-scale informatics platform, known as Brain-CODE (Centre for Ontario Data Exploration). Brain-CODE manages the acquisition, storage, processing, and analytics of multidimensional data collected from patients with a variety of brain disorders. Our vision is for the platform to act as an informatics catalyst; encouraging multidisciplinary research collaboration, data integration, and innovation in neuroscience research. Brain-CODE’s infrastructure was designed with best-practice privacy strategies built at the forefront to enable secure data capture of sensitive patient information in a manner that abides by government legislation while fostering data sharing and linking opportunities. ApproachPrivacy and security features have been incorporated into the very foundation of Brain-CODE’s comprehensive guidelines, which are reinforced by our state-of-the-art approaches to keep patient data safe. To ensure clarity for study participants, we have developed standard consent language outlining how sensitive patient data will be collected, entered, de-identified, and shared using Brain-CODE. Moreover, our tiered approach to data accessibility enables the storage of encrypted Ontario Health Card Numbers as well as other patient information, secure long-term storage of de-identified data, and data sharing opportunities by request from third parties following risk-based analysis re-identification techniques. OBI has also established a comprehensive Information Security Policy and Informatics Governance Policies, as well as a carried out a Privacy Impact Assessment and Threat Risk Assessment for Brain-CODE. ResultsBrain-CODE is proudly named a "Privacy by Design" Ambassador by the Office of the Information and Privacy Commissioner of Ontario, Canada. Moreover, approximately 200 neuroscience researchers and 35 institutions from across Canada have adopted our standard consent language to enable secure data sharing within and across neurological disorders as well as linkage opportunities with national and international databases in a secure environment. ConclusionOBI’s rigorous approach to data sharing in the field of neuroscience maintains the accessibility of research data for big discoveries without compromising patient privacy and security. We believe that Brain-CODE is a powerful and advantageous tool; moving neuroscience research from independent silos to an integrative system approach for improving patient health. OBI’s vision for improved brain health for patients living with neurological disorders paired with Brain-CODE’s best-practice strategies in privacy protection of patient data offer a novel and innovative approach to “big data” initiatives aimed towards improving public health and society world-wide.

Change of Attitude, Technology and Practice: Identifying the Change for Increased Value Creation with Customer Co-creation

2017 ◽  
Vol 5 (1) ◽  
pp. 70-82
Author(s):  
Soumi Paul ◽  
Paola Peretti ◽  
Saroj Kumar Datta
Keyword(s):  
Social Media ◽  
New Product Development ◽  
Value Creation ◽  
Large Scale ◽  
Customer Orientation ◽  
Customer Relationships ◽  
Future Research ◽  
Management Competencies ◽  
Business Decisions ◽  
Prime Concern

Building customer relationships and customer equity is the prime concern in today’s business decisions. The emergence of internet, especially social media like Facebook and Twitter, changed traditional marketing thought to a great extent. The importance of customer orientation is reflected in the axiom, “The customer is the king”. A good number of organizations are engaging customers in their new product development activities via social media platforms. Co-creation, a new perspective in which customers are active co-creators of the products they buy and use, is currently challenging the traditional paradigm. The concept of co-creation involving the customer’s knowledge, creativity and judgment to generate value is considered not only an upcoming trend that introduces new products or services but also fitting their need and increasing value for money. Knowledge and innovation are inseparable. Knowledge management competencies and capacities are essential to any organization that aspires to be distinguished and innovative. The present work is an attempt to identify the change in value creation procedure along with one area of business, where co-creation can return significant dividends. It is on extending the brand or brand category through brand extension or line extension. This article, through an in depth literature review analysis, identifies the changes in every perspective of this paradigm shift and it presents a conceptual model of company-customer-brand-based co-creation activity via social media. The main objective is offering an agenda for future research of this emerging trend and ensuring the way to move from theory to practice. The paper acts as a proposal; it allows the organization to go for this change in a large scale and obtain early feedback on the idea presented. 

Overview of Subsynchronous Oscillation in Grid-connected Wind Farm

2020 ◽  
Vol 13 (7) ◽  
pp. 969-979
Author(s):  
Xu Pei-Zhen ◽  
Lu Yong-Geng ◽  
Cao Xi-Min
Keyword(s):  
Power Systems ◽  
Wind Turbine ◽  
Large Scale ◽  
Wind Farm ◽  
Wind Farms ◽  
Induction Generator ◽  
Future Research ◽  
Stable Operation ◽  
Subsynchronous Oscillation ◽  
Different Types

Background: Over the past few years, the subsynchronous oscillation (SSO) caused by the grid-connected wind farm had a bad influence on the stable operation of the system and has now become a bottleneck factor restricting the efficient utilization of wind power. How to mitigate and suppress the phenomenon of SSO of wind farms has become the focus of power system research. Methods: This paper first analyzes the SSO of different types of wind turbines, including squirrelcage induction generator based wind turbine (SCIG-WT), permanent magnet synchronous generator- based wind turbine (PMSG-WT), and doubly-fed induction generator based wind turbine (DFIG-WT). Then, the mechanisms of different types of SSO are proposed with the aim to better understand SSO in large-scale wind integrated power systems, and the main analytical methods suitable for studying the SSO of wind farms are summarized. Results: On the basis of results, using additional damping control suppression methods to solve SSO caused by the flexible power transmission devices and the wind turbine converter is recommended. Conclusion: The current development direction of the SSO of large-scale wind farm grid-connected systems is summarized and the current challenges and recommendations for future research and development are discussed.

scholarly journals ‘CTRL’: an online, Dynamic Consent and participant engagement platform working towards solving the complexities of consent in genomic research

2021 ◽  
Author(s):  
Matilda A. Haas ◽  
Harriet Teare ◽  
Megan Prictor ◽  
Gabi Ceregra ◽  
Miranda E. Vidgen ◽  
...  
Keyword(s):  
Large Scale ◽  
Genomic Medicine ◽  
International Standards ◽  
Security And Privacy ◽  
Genomic Research ◽  
Return Of Results ◽  
Future Research ◽  
Design And Development ◽  
Participant Engagement ◽  
Dynamic Consent

AbstractThe complexities of the informed consent process for participating in research in genomic medicine are well-documented. Inspired by the potential for Dynamic Consent to increase participant choice and autonomy in decision-making, as well as the opportunities for ongoing participant engagement it affords, we wanted to trial Dynamic Consent and to do so developed our own web-based application (web app) called CTRL (control). This paper documents the design and development of CTRL, for use in the Australian Genomics study: a health services research project building evidence to inform the integration of genomic medicine into mainstream healthcare. Australian Genomics brought together a multi-disciplinary team to develop CTRL. The design and development process considered user experience; security and privacy; the application of international standards in data sharing; IT, operational and ethical issues. The CTRL tool is now being offered to participants in the study, who can use CTRL to keep personal and contact details up to date; make consent choices (including indicate preferences for return of results and future research use of biological samples, genomic and health data); follow their progress through the study; complete surveys, contact the researchers and access study news and information. While there are remaining challenges to implementing Dynamic Consent in genomic research, this study demonstrates the feasibility of building such a tool, and its ongoing use will provide evidence about the value of Dynamic Consent in large-scale genomic research programs.

scholarly journals Cyberstalking Victimization Model Using Criminological Theory: A Systematic Literature Review, Taxonomies, Applications, Tools, and Validations

Electronics ◽  
2021 ◽  
Vol 10 (14) ◽  
pp. 1670
Author(s):  
Waheeb Abu-Ulbeh ◽  
Maryam Altalhi ◽  
Laith Abualigah ◽  
Abdulwahab Ali Almazroi ◽  
Putra Sumari ◽  
...  
Keyword(s):  
Data Analysis ◽  
Structural Equation ◽  
Large Scale ◽  
Review Paper ◽  
Essential Element ◽  
Routine Activities ◽  
Criminological Theory ◽  
Equation Modeling ◽  
Future Research ◽  
Proposed Model

Cyberstalking is a growing anti-social problem being transformed on a large scale and in various forms. Cyberstalking detection has become increasingly popular in recent years and has technically been investigated by many researchers. However, cyberstalking victimization, an essential part of cyberstalking, has empirically received less attention from the paper community. This paper attempts to address this gap and develop a model to understand and estimate the prevalence of cyberstalking victimization. The model of this paper is produced using routine activities and lifestyle exposure theories and includes eight hypotheses. The data of this paper is collected from the 757 respondents in Jordanian universities. This review paper utilizes a quantitative approach and uses structural equation modeling for data analysis. The results revealed a modest prevalence range is more dependent on the cyberstalking type. The results also indicated that proximity to motivated offenders, suitable targets, and digital guardians significantly influences cyberstalking victimization. The outcome from moderation hypothesis testing demonstrated that age and residence have a significant effect on cyberstalking victimization. The proposed model is an essential element for assessing cyberstalking victimization among societies, which provides a valuable understanding of the prevalence of cyberstalking victimization. This can assist the researchers and practitioners for future research in the context of cyberstalking victimization.

scholarly journals Large-Scale Object Monitoring in Internet-of-Things: Energy-Efficient Perspectives

Electronics ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 461
Author(s):  
Yongbin Yim ◽  
Euisin Lee ◽  
Seungmin Oh
Keyword(s):  
Energy Efficient ◽  
Large Scale ◽  
Future Research ◽  
Technological Evolution ◽  
Node Density ◽  
Mobile Objects ◽  
Research Challenges ◽  
Energy Efficient Communication ◽  
Efficient Communication ◽  
Architectural Principles

Recently, the demand for monitoring a certain object covering large and dynamic scopes such as wildfires, glaciers, and radioactive contaminations, called large-scale fluid objects (LFOs), is coming to the fore due to disasters and catastrophes that lately happened. This article provides an analytic comparison of such LFOs and typical individual mobile objects (IMOs), namely animals, humans, vehicles, etc., to figure out inherent characteristics of LFOs. Since energy-efficient monitoring of IMOs has been intensively researched so far, but such inherent properties of LFOs hinder the direct adaptation of legacy technologies for IMOs, this article surveys technological evolution and advances of LFOs along with ones of IMOs. Based on the communication cost perspective correlated to energy efficiency, three technological phases, namely concentration, integration, and abbreviation, are defined in this article. By reviewing various methods and strategies employed by existing works with the three phases, this article concludes that LFO monitoring should achieve not only decoupling from node density and network structure but also trading off quantitative reduction against qualitative loss as architectural principles of energy-efficient communication to break through inherent properties of LFOs. Future research challenges related to this topic are also discussed.

scholarly journals News media attention in Climate Action: latent topics and open access

2021 ◽  
Author(s):  
Tahereh Dehdarirad ◽  
Kalle Karlsson
Keyword(s):  
Sustainable Development ◽  
Regression Analysis ◽  
Open Access ◽  
News Media ◽  
Latent Dirichlet Allocation ◽  
Topic Modelling ◽  
Sustainable Development Goal ◽  
Data Set ◽  
Development Goal ◽  
Climate Action

AbstractIn this study we investigated whether open access could assist the broader dissemination of scientific research in Climate Action (Sustainable Development Goal 13) via news outlets. We did this by comparing (i) the share of open and non-open access documents in different Climate Action topics, and their news counts, and (ii) the mean of news counts for open access and non-open access documents. The data set of this study comprised 70,206 articles and reviews in Sustainable Development Goal 13, published during 2014–2018, retrieved from SciVal. The number of news mentions for each document was obtained from Altmetrics Details Page API using their DOIs, whereas the open access statuses were obtained using Unpaywall.org. The analysis in this paper was done using a combination of (Latent Dirichlet allocation) topic modelling, descriptive statistics, and regression analysis. The covariates included in the regression analysis were features related to authors, country, journal, institution, funding, readability, news source category and topic. Using topic modelling, we identified 10 topics, with topics 4 (meteorology) [21%], 5 (adaption, mitigation, and legislation) [18%] and 8 (ecosystems and biodiversity) [14%] accounting for 53% of the research in Sustainable Development Goal 13. Additionally, the results of regression analysis showed that while keeping all the variables constant in the model, open access papers in Climate Action had a news count advantage (8.8%) in comparison to non-open access papers. Our findings also showed that while a higher share of open access documents in topics such as topic 9 (Human vulnerability to risks) might not assist with its broader dissemination, in some others such as topic 5 (adaption, mitigation, and legislation), even a lower share of open access documents might accelerate its broad communication via news outlets.

scholarly journals Enhanced Wastewater Treatment by Immobilized Enzymes

2021 ◽  
Author(s):  
Jakub Zdarta ◽  
Katarzyna Jankowska ◽  
Karolina Bachosz ◽  
Oliwia Degórska ◽  
Karolina Kaźmierczak ◽  
...  
Keyword(s):  
Wastewater Treatment ◽  
Process Optimization ◽  
Organic Pollutants ◽  
Large Scale ◽  
Removal Rate ◽  
Immobilized Enzymes ◽  
Future Research ◽  
Process Conditions ◽  
Removal Rates ◽  
Catalytic Cycles

Abstract Purpose of Review In the presented review, we have summarized recent achievements on the use of immobilized oxidoreductases for biodegradation of hazardous organic pollutants including mainly dyes, pharmaceuticals, phenols, and bisphenols. In order to facilitate process optimization and achievement of high removal rates, effect of various process conditions on biodegradation has been highlighted and discussed. Recent Findings Current reports clearly show that immobilized oxidoreductases are capable of efficient conversion of organic pollutants, usually reaching over 90% of removal rate. Further, immobilized enzymes showed great recyclability potential, allowing their reuse in numerous of catalytic cycles. Summary Collected data clearly indicates immobilized oxidoreductases as an efficient biocatalytic tools for removal of hazardous phenolic compounds, making them a promising option for future water purification. Data shows, however, that both immobilization and biodegradation conditions affect conversion efficiency; therefore, process optimization is required to achieve high removal rates. Nevertheless, we have demonstrated future trends and highlighted several issues that have to be solved in the near-future research, to facilitate large-scale application of the immobilized oxidoreductases in wastewater treatment.

Sign in / Sign up

Export Citation Format

Share Document