Agenda for Future Research and Concluding Comments

2019 ◽  
pp. 810-818
Author(s):  
Sandra A. Brown ◽  
Robert A. Zucker
Keyword(s):  
Substance Abuse ◽  
Big Data ◽  
Drugs Of Abuse ◽  
Causal Structure ◽  
Frame Of Reference ◽  
Future Research ◽  
Clinical Symptomatology ◽  
Cross Domain ◽  
Collection Programs

This concluding chapter highlights issues we see as especially important next-step agendas for the field. The issues we have highlighted concern (a) the implications that a developmental frame of reference provides in characterizing and parsing the etiology and course of addictive behavior; (b) the relevance of event-level predictors occurring in microtime and the extent to which they will supercede the more summative indicators that currently dominate the substance abuse field; (c) the increasing awareness, and characterization of drug-specific influences, and the degree to which these influences are useful in evaluating the vulnerability potential of drugs of abuse; (d) the differences in characterization of clinical symptomatology and course that have the potential to occur when evaluation of psychopathology and the details of intervention methods are unpacked with a specifically developmental lens; (e) the insights that new big data collection programs will create in understanding the cross-domain causal structure of substance abuse.

scholarly journals Big Data Characterization of Learner Behaviour in a Highly Technical MOOC Engineering Course

2016 ◽  
Vol 3 (3) ◽  
pp. 170-192 ◽  
Author(s):  
Kerrie Anna Douglas ◽  
Peter Bermel ◽  
Md Monzurul Alam ◽  
Krishna Madhavan
Keyword(s):  
Big Data ◽  
Learning Analytics ◽  
Statistical Test ◽  
Future Research ◽  
User Behaviour ◽  
Significant Difference ◽  
Nonparametric Statistical Test ◽  
Nonparametric Statistical

MOOCs attract a large number of users with unknown diversity in terms of motivation, ability, and goals. To understand more about learners in a MOOC, the authors explored clusters of user clickstream patterns in a highly technical MOOC, Nanophotonic Modelling through the algorithm k-means++.  Five clusters of user behaviour emerged: Fully Engaged, Consistent Viewers, One-Week Engaged, Two-Week Engaged, and Sporadic users. Assessment behaviours and scores are then examined within each cluster, and found different between clusters. Nonparametric statistical test, Kruskal-Wallis yielded a significant difference between user behaviour in each cluster. To make accurate inferences about what occurs in a MOOC, a first step is to understand the patterns of user behaviour. The latent characteristics that contribute to user behaviour must be explored in future research. Keywords: MOOCs, Learning Analytics, Assessment

Parasite defense mechanisms in bees: behavior, immunity, antimicrobials, and symbionts

2019 ◽  
Vol 4 (1) ◽  
pp. 59-76 ◽  
Author(s):  
Alison E. Fowler ◽  
Rebecca E. Irwin ◽  
Lynn S. Adler
Keyword(s):  
Defense Mechanisms ◽  
Poor Quality ◽  
Future Research ◽  
Immune Priming ◽  
Social Bees ◽  
Bee Health ◽  
Landscape Scales ◽  
And Function ◽  
Solitary Species

Parasites are linked to the decline of some bee populations; thus, understanding defense mechanisms has important implications for bee health. Recent advances have improved our understanding of factors mediating bee health ranging from molecular to landscape scales, but often as disparate literatures. Here, we bring together these fields and summarize our current understanding of bee defense mechanisms including immunity, immunization, and transgenerational immune priming in social and solitary species. Additionally, the characterization of microbial diversity and function in some bee taxa has shed light on the importance of microbes for bee health, but we lack information that links microbial communities to parasite infection in most bee species. Studies are beginning to identify how bee defense mechanisms are affected by stressors such as poor-quality diets and pesticides, but further research on this topic is needed. We discuss how integrating research on host traits, microbial partners, and nutrition, as well as improving our knowledge base on wild and semi-social bees, will help inform future research, conservation efforts, and management.

scholarly journals Comparison of disclosure/concealment of medical information given to conversational agents or to physicians

2021 ◽  
Vol 27 (1) ◽  
pp. 146045822199486
Author(s):  
Nicholas RJ Frick ◽  
Felix Brünker ◽  
Björn Ross ◽  
Stefan Stieglitz
Keyword(s):  
Natural Language ◽  
Medical Information ◽  
Frame Of Reference ◽  
Future Research ◽  
Negative Consequences ◽  
Conversational Agents ◽  
Online Questionnaire ◽  
Computer Based

Within the anamnesis, medical information is frequently withheld, incomplete, or incorrect, potentially causing negative consequences for the patient. The use of conversational agents (CAs), computer-based systems using natural language to interact with humans, may mitigate this problem. The present research examines whether CAs differ from physicians in their ability to elicit truthful disclosure and discourage concealment of medical information. We conducted an online questionnaire with German participants ( N = 148) to assess their willingness to reveal medical information. The results indicate that patients would rather disclose medical information to a physician than to a CA; there was no difference in the tendency to conceal information. This research offers a frame of reference for future research on applying CAs during the anamnesis to support physicians. From a practical view, physicians might gain better understanding of how the use of CAs can facilitate the anamnesis.

scholarly journals Crowdsourcing and open innovation: a systematic literature review, an integrated framework and a research agenda

2021 ◽  
Author(s):  
Livio Cricelli ◽  
Michele Grimaldi ◽  
Silvia Vermicelli
Keyword(s):  
Literature Review ◽  
Systematic Literature Review ◽  
Open Innovation ◽  
Innovation Management ◽  
Academic Research ◽  
Future Research ◽  
Four Dimensions ◽  
Word Analysis ◽  
The Relationship

AbstractIn recent years, Open Innovation (OI) and crowdsourcing have been very popular topics in the innovation management literature, attracting significant interest and attention, and inspiring a rich production of publications. Although these two topics share common themes and address similar managerial challenges, to the best of our knowledge, there is no systematic literature review that digs deep into the intersection of both fields. To fill in this gap a joint review of crowdsourcing and OI topics is both timely and of interest. Therefore, the main objective of this study is to carry out a comprehensive, systematic, and objective review of academic research to help shed light on the relationship between OI and crowdsourcing. For this purpose, we reviewed the literature published on these two topics between 2008 and 2019, applying two bibliometric techniques, co-citation and co-word analysis. We obtained the following results: (i) we provide a qualitative analysis of the emerging and trending themes, (ii) we discuss a characterization of the intersection between OI and crowdsourcing, identifying four dimensions (strategic, managerial, behavioral, and technological), (iii) we present a schematic reconceptualization of the thematic clusters, proposing an integrated view. We conclude by suggesting promising opportunities for future research.

Ferrous materials degradation: characterisation of rust by colour – an overview

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Desmond E. P. Klenam ◽  
Michael O. Bodunrin ◽  
Stefania Akromah ◽  
Emmanuel Gikunoo ◽  
Anthony Andrews ◽  
...  
Keyword(s):  
Yellow Rust ◽  
Brown Rust ◽  
Future Research ◽  
Stable Form ◽  
Low Oxygen ◽  
High Moisture ◽  
Oxygen Environment ◽  
Causative Factors ◽  
Analytical Tools

Abstract An overview of the characterisation of rust by colour is presented. Each distinct rust colour is caused by atmospheric impurities, high or low moisture content and high or low oxygen environment over time. Yellow rust is mainly due to the high moisture environment over a period of time, which drips. Brown rust is dry, crusty and due to water and oxygen contact with localised patches on component surfaces. Black rust, the most stable form, occurs in low moisture and low oxygen environment. The rust residue shows where the reaction started, especially in contact with chlorides. The causative factors of red rust are atmospheric and similar to black rust in a chloride-containing environment. The effect of packaging, manufacturing and environmental factors on rust colour is briefly discussed. Visual characterization of rust could pre-empt root causes and analytical tools for validation. The limitations of these concepts are mentioned and directions for future research highlighted.

scholarly journals A Comprehensive Survey on Local Differential Privacy

2020 ◽  
Vol 2020 ◽  
pp. 1-29 ◽  
Author(s):  
Xingxing Xiong ◽  
Shubo Liu ◽  
Dan Li ◽  
Zhaohui Cai ◽  
Xiaoguang Niu
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Statistical Learning ◽  
Data Privacy ◽  
Statistical Estimation ◽  
Differential Privacy ◽  
Future Research ◽  
Reference Source ◽  
Complex Data ◽  
Comprehensive Survey

With the advent of the era of big data, privacy issues have been becoming a hot topic in public. Local differential privacy (LDP) is a state-of-the-art privacy preservation technique that allows to perform big data analysis (e.g., statistical estimation, statistical learning, and data mining) while guaranteeing each individual participant’s privacy. In this paper, we present a comprehensive survey of LDP. We first give an overview on the fundamental knowledge of LDP and its frameworks. We then introduce the mainstream privatization mechanisms and methods in detail from the perspective of frequency oracle and give insights into recent studied on private basic statistical estimation (e.g., frequency estimation and mean estimation) and complex statistical estimation (e.g., multivariate distribution estimation and private estimation over complex data) under LDP. Furthermore, we present current research circumstances on LDP including the private statistical learning/inferencing, private statistical data analysis, privacy amplification techniques for LDP, and some application fields under LDP. Finally, we identify future research directions and open challenges for LDP. This survey can serve as a good reference source for the research of LDP to deal with various privacy-related scenarios to be encountered in practice.

Production of Bio Gas from Vegetable and Flowers Wastes Using Anaerobic Digestion

2015 ◽  
Vol 787 ◽  
pp. 803-808 ◽  
Author(s):  
A. Deepanraj ◽  
S. Vijayalakshmi ◽  
J. Ranjitha
Keyword(s):  
Anaerobic Digestion ◽  
Biogas Production ◽  
Research Work ◽  
Pressure Gauge ◽  
Pig Manure ◽  
Future Research ◽  
Digital Pressure ◽  
Vegetable Wastes ◽  
Main Component

The present research paper describes about the anaerobic digestion of vegetable (Banana, Cauliflower, potato, and sweet potato) and flower wastes (Rose, sambangi, gulmohar, marigold, golden shower tree, silk tree mimosa) in a 1L capacity of anaerobic digestor using pig manure as an inoculums. The digester was operated in the ratio of 1:1 of substrate to inoculums at RT. The substrate concentrations are varied such as 5%, 7%, and 10% was used and amount of gas produced was analysed using digital pressure gauge. The results obtained showed that, marigold flower had given higher yield of biogas than vegetable wastes and the digestion period was less. The average biogas production potential of withered flowers was observed as 14.36 g/kg in 5 days, where in case of vegetable wastes it was 10.0234 g/kg in 6 days. The study showed that flowers which are available in abundant in India is thrown away within a day, in the environment. These feedstocks are good feed stock for the production of biogas. The generation of biogas from flowers and vegetable waste upholds the concept of waste to wealth in enhancing sustainability of development. The future research work is mainly focused on the characterization of the main component present in the bio-gas using sophisticated instruments.

Big data analysis of trends in the second-hand apparel market: a comparison between 2014 and 2019

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sanghee Kim ◽  
Hongjoo Woo
Keyword(s):  
Big Data ◽  
Design Methodology ◽  
Semantic Network ◽  
Distribution Channels ◽  
Subject Area ◽  
Future Research ◽  
Semantic Network Analysis ◽  
Content Type ◽  
The Past ◽  
Network Patterns

Purpose According to the perspective of evolutionary economic theory, the marketplace continuously evolves over time, following the changing needs of both customers and firms. In accordance with the theory, the second-hand apparel market has been rapidly expanding by meeting consumers’ diverse preferences and promoting sustainability since 2014. To understand what changes in consumers’ consumption behaviors regarding used apparel have driven this growth, the purpose of this study is to examine how the second-hand apparel market product types, distribution channels and consumers’ motives have changed over the past five years. Design/methodology/approach This study collected big data from Google through Textom software by extracting all Web-exposed text in 2014, and again in 2019, that contained the keyword “second-hand apparel,” and used the Node XL program to visualize the network patterns of these words through the semantic network analysis. Findings The results indicate that the second-hand apparel market has evolved with various changes over the past five years in terms of consumer motives, product types and distribution channels. Originality/value This study provides a comprehensive understanding of the changing demands of consumers toward used apparel over the past five years, providing insights for retailers as well as future research in this subject area.

Strategic issues of big data analytics applications for managing health-care sector: a systematic literature review and future research agenda

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Rajesh Kumar Singh ◽  
Saurabh Agrawal ◽  
Abhishek Sahu ◽  
Yigit Kazancoglu
Keyword(s):  
Health Care ◽  
Big Data ◽  
Literature Review ◽  
Systematic Literature Review ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Health Care Sector ◽  
Future Research ◽  
Research Gaps ◽  
Content Type

PurposeThe proposed article is aimed at exploring the opportunities, challenges and possible outcomes of incorporating big data analytics (BDA) into health-care sector. The purpose of this study is to find the research gaps in the literature and to investigate the scope of incorporating new strategies in the health-care sector for increasing the efficiency of the system.Design/methodology/approachFora state-of-the-art literature review, a systematic literature review has been carried out to find out research gaps in the field of healthcare using big data (BD) applications. A detailed research methodology including material collection, descriptive analysis and categorization is utilized to carry out the literature review.FindingsBD analysis is rapidly being adopted in health-care sector for utilizing precious information available in terms of BD. However, it puts forth certain challenges that need to be focused upon. The article identifies and explains the challenges thoroughly.Research limitations/implicationsThe proposed study will provide useful guidance to the health-care sector professionals for managing health-care system. It will help academicians and physicians for evaluating, improving and benchmarking the health-care strategies through BDA in the health-care sector. One of the limitations of the study is that it is based on literature review and more in-depth studies may be carried out for the generalization of results.Originality/valueThere are certain effective tools available in the market today that are currently being used by both small and large businesses and corporations. One of them is BD, which may be very useful for health-care sector. A comprehensive literature review is carried out for research papers published between 1974 and 2021.

Bibliometric analysis and critical review of the research on big data in the construction industry

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Yusheng Lu ◽  
Jiantong Zhang
Keyword(s):  
Big Data ◽  
Construction Industry ◽  
Bibliometric Analysis ◽  
Critical Review ◽  
Rapid Development ◽  
Heterogeneous Data ◽  
The Body ◽  
Future Research ◽  
Temporal And Spatial Distribution ◽  
Content Type

PurposeThe digital revolution and the use of big data (BD) in particular has important applications in the construction industry. In construction, massive amounts of heterogeneous data need to be analyzed to improve onsite efficiency. This article presents a systematic review and identifies future research directions, presenting valuable conclusions derived from rigorous bibliometric tools. The results of this study may provide guidelines for construction engineering and global policymaking to change the current low-efficiency of construction sites.Design/methodology/approachThis study identifies research trends from 1,253 peer-reviewed papers, using general statistics, keyword co-occurrence analysis, critical review, and qualitative-bibliometric techniques in two rounds of search.FindingsThe number of studies in this area rapidly increased from 2012 to 2020. A significant number of publications originated in the UK, China, the US, and Australia, and the smallest number from one of these countries is more than twice the largest number in the remaining countries. Keyword co-occurrence is divided into three clusters: BD application scenarios, emerging technology in BD, and BD management. Currently developing approaches in BD analytics include machine learning, data mining, and heuristic-optimization algorithms such as graph convolutional, recurrent neural networks and natural language processes (NLP). Studies have focused on safety management, energy reduction, and cost prediction. Blockchain integrated with BD is a promising means of managing construction contracts.Research limitations/implicationsThe study of BD is in a stage of rapid development, and this bibliometric analysis is only a part of the necessary practical analysis.Practical implicationsNational policies, temporal and spatial distribution, BD flow are interpreted, and the results of this may provide guidelines for policymakers. Overall, this work may develop the body of knowledge, producing a reference point and identifying future development.Originality/valueTo our knowledge, this is the first bibliometric review of BD in the construction industry. This study can also benefit construction practitioners by providing them a focused perspective of BD for emerging practices in the construction industry.

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