scholarly journals Robust modeling of additive and nonadditive variation with intuitive inclusion of expert knowledge

Genetics ◽  
2021 ◽  
Author(s):  
Ingeborg Gullikstad Hem ◽  
Maria Lie Selle ◽  
Gregor Gorjanc ◽  
Geir-Arne Fuglstad ◽  
Andrea Riebler
Keyword(s):  
Expert Knowledge ◽  
Future Research ◽  
Central Component ◽  
Research Areas ◽  
Model Parameterization ◽  
Parent Selection ◽  
Variety Selection ◽  
Sources Of Variation ◽  
Likelihood Approach

Abstract We propose a novel Bayesian approach that robustifies genomic modeling by leveraging expert knowledge (EK) through prior distributions. The central component is the hierarchical decomposition of phenotypic variation into additive and nonadditive genetic variation, which leads to an intuitive model parameterization that can be visualized as a tree. The edges of the tree represent ratios of variances, for example broad-sense heritability, which are quantities for which EK is natural to exist. Penalized complexity priors are defined for all edges of the tree in a bottom-up procedure that respects the model structure and incorporates EK through all levels. We investigate models with different sources of variation and compare the performance of different priors implementing varying amounts of EK in the context of plant breeding. A simulation study shows that the proposed priors implementing EK improve the robustness of genomic modeling and the selection of the genetically best individuals in a breeding program. We observe this improvement in both variety selection on genetic values and parent selection on additive values; the variety selection benefited the most. In a real case study, EK increases phenotype prediction accuracy for cases in which the standard maximum likelihood approach did not find optimal estimates for the variance components. Finally, we discuss the importance of EK priors for genomic modeling and breeding, and point to future research areas of easy-to-use and parsimonious priors in genomic modeling.

scholarly journals Robust Modelling of Additive and Non-additive Variation with Intuitive Inclusion of Expert Knowledge

2020 ◽  
Author(s):  
Ingeborg Gullikstad Hem ◽  
Maria Lie Selle ◽  
Gregor Gorjanc ◽  
Geir-Arne Fuglstad ◽  
Andrea Riebler
Keyword(s):  
Expert Knowledge ◽  
Future Research ◽  
Central Component ◽  
Research Areas ◽  
Model Parameterization ◽  
Parent Selection ◽  
Variety Selection ◽  
Sources Of Variation ◽  
Robust Modelling ◽  
Likelihood Approach

AbstractWe propose a novel Bayesian approach that robustifies genomic modelling by leveraging expert knowledge through prior distributions. The central component is the hierarchical decomposition of phenotypic variation into additive and non-additive genetic variation, which leads to an intuitive model parameterization that can be visualised as a tree. The edges of the tree represent ratios of variances, for example broad-sense heritability, which are quantities for which expert knowledge is natural to exist. Penalized complexity priors are defined for all edges of the tree in a bottom-up procedure that respects the model structure and incorporates expert knowledge through all levels. We investigate models with different sources of variation and compare the performance of different priors implementing varying amounts of expert knowledge in the context of plant breeding. A simulation study shows that the proposed priors implementing expert knowledge improve the robustness of genomic modelling and the selection of the genetically best individuals in a breeding program. We observe this improvement in both variety selection on genetic values and parent selection on additive values; the variety selection benefited the most. In a real case study expert knowledge increases phenotype prediction accuracy for cases in which the standard maximum likelihood approach did not find optimal estimates for the variance components. Finally, we discuss the importance of expert knowledge priors for genomic modelling and breeding, and point to future research areas of easy-to-use and parsimonious priors in genomic modelling.

Evaluating IT-Enabled Transformation in Public Services

2009 ◽  
pp. 379-394
Author(s):  
Sevgi Ozkan ◽  
Murat Cakir
Keyword(s):  
Information Systems ◽  
Evaluation Methodology ◽  
Future Research ◽  
Management Support ◽  
Government Organization ◽  
Top Management Support ◽  
Relative Term ◽  
Research Areas ◽  
Organizational Features

While the paradigm for organizations evolves into an information perspective and information systems’ (IS) role shifts from efficiency to effectiveness, among the top issues of IS management is measuring and improving IS effectiveness. This chapter offers an IS effectiveness evaluation methodology applied on a government organization in Turkey. IS maturity is taken as a reference for determining independent variables of the research. The chapter supports that “IS effectiveness” is a relative term conceptualized by organizational features. The case study suggests future research areas. A number of findings and propositions have been presented, including the alignment of technology and business process, integrating stakeholders’ trust and commitment, the significance of top management support, top-down vs. bottom-up approaches, which can enhance the adoption and institutionalization of information systems implementations within a government organization.

scholarly journals POINT CLOUD APPLICATIONS FOR DISASTER REMEDIATION: A CASE STUDY

2017 ◽  
Vol 1 (1) ◽  
pp. 40-45 ◽  
Author(s):  
Glenda Mayo
Keyword(s):  
Disaster Mitigation ◽  
Future Research ◽  
Process Data ◽  
Research Areas ◽  
Industry Applications ◽  
Time Savings ◽  
New Applications ◽  
Cloud Applications ◽  
Post Disaster

ABSTRACT Photorealistic, LiDAR-based 3D imaging provides accurate and precise documentation of existing conditions and measurable geometry. The quality and accuracy of the data generated by LiDAR cannot be economically recreated using more traditional measurement and CAD techniques. While earlier forms of this technology have been used for many years, recent innovations have provided opportunities for numerous new uses that will soon change the way many professionals obtain, analyze and process data. The use of 3D scanning equipment for new applications is gaining momentum and one such application, its use for disaster mitigation, was explored in a case study. The study reviews scanning industry applications and improvements for precision and also includes a case study in the application of a historic church post disaster, which was documented with the beneficial applications (such as safety and time savings) as well as what the authors believed to be future research areas for similar projects.

scholarly journals Microplastics as contaminants in marine environment

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Patric Paul ◽  
Aravind K Mohan ◽  
Geethika Dev ◽  
Sunil Kumar P G
Keyword(s):  
Marine Environment ◽  
Temporal Trends ◽  
Marine Organisms ◽  
Future Research ◽  
Review Of The Literature ◽  
Chemical Additives ◽  
Research Areas ◽  
Ocean Gyres ◽  
Spatial And Temporal Trends

ABSTRACT Since the mass production of plastics began in the 1940s, microplastic contamination of the marine environment has been a growing problem. Here, a review of the literature has been conducted with the following objectives: To summarise what are microplastics; To discuss the routes by which microplastics enter the marine environment; To assess spatial and temporal trends of microplastic abundance; to discuss the environmental impact of microplastics; and remedial measures; Microplastics are both abundant and widespread within the marine environment, found in their highest concentrations along coastlines and within mid-ocean gyres. Ingestion of microplastics has been demonstrated in a range of marine organisms, a process which may facilitate the transfer of chemical additives or hydrophobic waterborne pollutants to biota. A case study has also been done about the ingestion of microplastics by zooplankton groups in Kenya’s marine environment. We conclude by highlighting key future research areas for scientists and policymakers. Keywords—Micro plastics; marine organisms; marine environment

scholarly journals Graduate Transitions

2020 ◽  
Vol 30 ◽  
pp. 264-289
Author(s):  
Jordan Stouck ◽  
Lori Walter
Keyword(s):  
Graduate Students ◽  
Academic Writing ◽  
Academic Literacy ◽  
Future Research ◽  
Focus Group Interviews ◽  
Research Areas ◽  
Institutional Expectations ◽  
Group Interviews ◽  
Perceived Experiences

This exploratory study researches the experiences of Canadian graduate students as they pursue writing tasks for their degree. It also explores the supports currently utilized by such students and the need for additional supports. The research uses a case study design based on qualitative focus group interviews to provide detailed information regarding graduate students' perceived experiences with their academic writing tasks and available supports. The approach is informed by academic literacy theory. Graduate students who participated in this study identified a transition in voice, increased pressure to publish and professionalize, and misalignments between their own and supervisory and institutional expectations, which resulted in some interrogation of institutional norms. They utilized Writing Centre, online and supervisory supports, but called for additional ongoing and peer support. The study has implications for the development of new, collaborative and peer-based writing supports, as well as identifying future research areas related to interdisciplinary degrees.

scholarly journals A Survey on Temporal Reasoning for Temporal Information Extraction from Text

2019 ◽  
Vol 66 ◽  
pp. 341-380 ◽  
Author(s):  
Artuur Leeuwenberg ◽  
Marie-Francine Moens
Keyword(s):  
Information Extraction ◽  
Temporal Reasoning ◽  
Temporal Information ◽  
Future Research ◽  
Research Areas ◽  
Temporal Cues ◽  
Comprehensive Survey ◽  
Temporal Information Extraction ◽  
Current Systems

Time is deeply woven into how people perceive, and communicate about the world. Almost unconsciously, we provide our language utterances with temporal cues, like verb tenses, and we can hardly produce sentences without such cues. Extracting temporal cues from text, and constructing a global temporal view about the order of described events is a major challenge of automatic natural language understanding. Temporal reasoning, the process of combining different temporal cues into a coherent temporal view, plays a central role in temporal information extraction. This article presents a comprehensive survey of the research from the past decades on temporal reasoning for automatic temporal information extraction from text, providing a case study on how combining symbolic reasoning with machine learning-based information extraction systems can improve performance. It gives a clear overview of the used methodologies for temporal reasoning, and explains how temporal reasoning can be, and has been successfully integrated into temporal information extraction systems. Based on the distillation of existing work, this survey also suggests currently unexplored research areas. We argue that the level of temporal reasoning that current systems use is still incomplete for the full task of temporal information extraction, and that a deeper understanding of how the various types of temporal information can be integrated into temporal reasoning is required to drive future research in this area.

Graduate Transitions

2020 ◽  
Vol 30 ◽  
pp. 264-285
Author(s):  
Jordan Stouck ◽  
Lori Walter
Keyword(s):  
Graduate Students ◽  
Academic Writing ◽  
Academic Literacy ◽  
Future Research ◽  
Focus Group Interviews ◽  
Research Areas ◽  
Institutional Expectations ◽  
Group Interviews ◽  
Perceived Experiences

This exploratory study researches the experiences of Canadian graduate students as they pursue writing tasks for their degree. It also explores the supports currently utilized by such students and the need for additional supports. The research uses a case study design based on qualitative focus group interviews to provide detailed information regarding graduate students’ perceived experiences with their academic writing tasks and available supports. The approach is informed by academic literacy theory. Graduate students who participated in this study identified a transition in voice, increased pressure to publish and professionalize, and misalignments between their own and supervisory and institutional expectations, which resulted in some interrogation of institutional norms. They utilized Writing Centre, online and supervisory supports, but called for additional ongoing and peer support. The study has implications for the development of new, collaborative and peer-based writing supports, as well as identifying future research areas related to interdisciplinary degrees.

scholarly journals Unmanned Aerial Vehicles enabled IoT Platform for Disaster Management

Energies ◽  
2019 ◽  
Vol 12 (14) ◽  
pp. 2706 ◽  
Author(s):  
Waleed Ejaz ◽  
Muhammad Awais Azam ◽  
Salman Saadat ◽  
Farkhund Iqbal ◽  
Abdul Hanan
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Disaster Management ◽  
Future Research ◽  
Wildfire Management ◽  
Holistic View ◽  
Main Research ◽  
Research Areas ◽  
Aerial Vehicles ◽  
Iot Platform

Efficient and reliable systems are required to detect and monitor disasters such as wildfires as well as to notify the people in the disaster-affected areas. Internet of Things (IoT) is the key paradigm that can address the multitude problems related to disaster management. In addition, an unmanned aerial vehicles (UAVs)-enabled IoT platform connected via cellular network can further enhance the robustness of the disaster management system. The UAV-enabled IoT platform is based on three main research areas: (i) ground IoT network; (ii) communication technologies for ground and aerial connectivity; and (iii) data analytics. In this paper, we provide a holistic view of a UAVs-enabled IoT platform which can provide ubiquitous connectivity to both aerial and ground users in challenging environments such as wildfire management. We then highlight key challenges for the design of an efficient and reliable IoT platform. We detail a case study targeting the design of an efficient ground IoT network that can detect and monitor fire and send notifications to people using named data networking (NDN) architecture. The use of NDN architecture in a sensor network for IoT integrates pull-based communication to enable reliable and efficient message dissemination in the network and to notify the users as soon as possible in case of disastrous situations. The results of the case study show the enormous impact on the performance of IoT platform for wildfire management. Lastly, we draw the conclusion and outline future research directions in this field.

The Natural and Supernatural

2016 ◽  
Author(s):  
Ute Lotz-Heumann
Keyword(s):  
Early Modern ◽  
Early Modern Period ◽  
Future Research ◽  
Early Modern Europe ◽  
Major Research ◽  
Research Areas ◽  
Modern Period ◽  
The Reformation ◽  
The Subject

This chapter provides an overview of the historiography on the natural and supernatural in early modern Europe with a particular emphasis on Protestantism. It considers the ways in which this subject is closely intertwined with other major research areas in early modern historiography, especially the subject of popular and elite religion and the question of Protestantism and desacralization/secularization. Next, this chapter introduces a case study on the interpretation of healing waters in German Lutheranism in order to provide readers with an example of the complex relationship between the natural and the supernatural following the Reformation. Finally, this article sketches an agenda for future research on Protestantism and the natural and supernatural in the early modern period.

scholarly journals An Investigation on Responsible Innovation in the Emerging Shared Bicycle Industry: Case Study of a Chinese Firm

2019 ◽  
Vol 5 (3) ◽  
pp. 42 ◽  
Author(s):  
Liu ◽  
Ma ◽  
Zhu ◽  
Ji
Keyword(s):  
Sharing Economy ◽  
Responsible Innovation ◽  
Future Research ◽  
The Public ◽  
Bicycle Industry ◽  
Chinese Firm ◽  
Research Areas ◽  
Key Dimensions ◽  
Shared Bicycle

In the current era of Industrial 4.0, open innovation, and the sharing economy, innovation ecosystems are formed through government-industry-university (triple helix) interaction. The concept of responsible innovation has emerged to explore how innovation can be conducted in a transparent, trustworthy, and sustainable way so as to respond to the public interest. While current literature provides a conceptual framework, details of how responsible innovation can be formed, developed, and sustained in the sharing economy, in particular in developing countries, have been under-explored. This paper aims to explore factors of responsible innovation, linking dimensions with business practice, and identify the dynamic stages of the industry life cycle. Through an in-depth case study of China’s shared bicycle industry and the firm Hellobike, this paper has prioritized factors which lead to responsibility, such as user safety and friendliness in product design, real-time operations combined with big data, collaboration between industry and local government for industry standardization, and user credit systems. It has enriched key dimensions based on literature and case studies and proposed dynamic interaction models for industry, government, users, and universities at different stages of responsible innovation in the shared bicycle sector. From this empirical study, future research areas have been identified.

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