scholarly journals Mesophotic.org: a repository for scientific information on mesophotic ecosystems

Database ◽  
2019 ◽  
Vol 2019 ◽  
Author(s):  
Pim Bongaerts ◽  
Gonzalo Perez-Rosales ◽  
Veronica Z Radice ◽  
Gal Eyal ◽  
Andrea Gori ◽  
...  
Keyword(s):  
Large Scale ◽  
Scientific Information ◽  
Temporal Trends ◽  
Light Availability ◽  
Research Community ◽  
Future Research ◽  
Photosynthetic Organisms ◽  
Future Research Directions ◽  
Available Information ◽  
Reduced Light

Abstract Mesophotic coral ecosystems (MCEs) and temperate mesophotic ecosystems (TMEs) occur at depths of roughly 30–150 m depth and are characterized by the presence of photosynthetic organisms despite reduced light availability. Exploration of these ecosystems dates back several decades, but our knowledge remained extremely limited until about a decade ago, when a renewed interest resulted in the establishment of a rapidly growing research community. Here, we present the ‘mesophotic.org’ database, a comprehensive and curated repository of scientific literature on mesophotic ecosystems. Through both manually curated and automatically extracted metadata, the repository facilitates rapid retrieval of available information about particular topics (e.g. taxa or geographic regions), exploration of spatial/temporal trends in research and identification of knowledge gaps. The repository can be queried to comprehensively obtain available data to address large-scale questions and guide future research directions. Overall, the ‘mesophotic.org’ repository provides an independent and open-source platform for the ever-growing research community working on MCEs and TMEs to collate and expedite our understanding of the occurrence, composition and functioning of these ecosystems. Database URL: http://mesophotic.org/

Enhancing Emergency Response Management using Emergency Description Information Technology (EDIT)

2016 ◽  
pp. 1264-1278
Author(s):  
Michael A. Erskine ◽  
Will Pepper
Keyword(s):  
Emergency Response ◽  
Process Model ◽  
Large Scale ◽  
Design Science ◽  
Future Research ◽  
Sporting Events ◽  
Emergency Responder ◽  
Response Information ◽  
Novel Approach ◽  
Future Research Directions

This paper presents a novel approach toward facilitating the effective collection and communication of information during an emergency. Initially, this research examines current emergency response information workflows and emergency responder dispatch criteria. A process for the optimization of these workflows and criteria, along with a suggested method to improve data collection accuracy and emergency response time using a mobile device application, are suggested. Specifically, a design-science approach incorporating the development of an expert system designed to facilitate efficient and effective sharing of emergency information is applied. The resulting benefits could improve emergency communications during large-scale international gatherings, such as sporting events or festivals, as well as the sharing of industry-specific safety incidents. A process model for conducting analyses of additional emergency response processes is also presented. Finally, future research directions are discussed.

scholarly journals IoT Technology Applications-Based Smart Cities: Research Analysis

Electronics ◽  
2020 ◽  
Vol 9 (8) ◽  
pp. 1246 ◽  
Author(s):  
Mariana-Daniela González-Zamar ◽  
Emilio Abad-Segura ◽  
Esteban Vázquez-Cano ◽  
Eloy López-Meneses
Keyword(s):  
Smart Cities ◽  
Scientific Activity ◽  
Urban Environments ◽  
Scientific Production ◽  
Future Research ◽  
Iot Applications ◽  
Technology Applications ◽  
Future Research Directions ◽  
Available Information ◽  
Electronic Sensors

The development of technologies enables the application of the Internet of Things (IoT) in urban environments, creating smart cities. Hence, the optimal management of data generated in the interconnection of electronic sensors in real time improves the quality of life. The objective of this study is to analyze global research on smart cities based on IoT technology applications. For this, bibliometric techniques were applied to 1232 documents on this topic, corresponding to the period 2011–2019, to obtain findings on scientific activity and the main thematic areas. Scientific production has increased annually, so that the last triennium has accumulated 83.23% of the publications. The most outstanding thematic areas were Computer Science and Engineering. Seven lines have been identified in the development of research on smart cities based on IoT applications. In addition, the study has detected seven new future research directions. The growing trend at the global level of scientific production shows the interest in developing aspects of smart cities based on IoT applications. This study contributes to the academic, scientific, and institutional discussion to improve decision making based on the available information.

scholarly journals Biogeography and ecology: towards the integration of two disciplines

2011 ◽  
Vol 366 (1576) ◽  
pp. 2438-2448 ◽  
Author(s):  
Robert E. Ricklefs ◽  
David G. Jenkins
Keyword(s):  
Evolutionary Biology ◽  
Plate Tectonics ◽  
Large Scale ◽  
Open Systems ◽  
Ecological Factors ◽  
Future Research ◽  
Ecological Communities ◽  
History Of ◽  
Future Research Directions ◽  
Synthetic Approaches

Although ecology and biogeography had common origins in the natural history of the nineteenth century, they diverged substantially during the early twentieth century as ecology became increasingly hypothesis-driven and experimental. This mechanistic focus narrowed ecology's purview to local scales of time and space, and mostly excluded large-scale phenomena and historical explanations. In parallel, biogeography became more analytical with the acceptance of plate tectonics and the development of phylogenetic systematics, and began to pay more attention to ecological factors that influence large-scale distributions. This trend towards unification exposed problems with terms such as ‘community’ and ‘niche,’ in part because ecologists began to view ecological communities as open systems within the contexts of history and geography. The papers in this issue represent biogeographic and ecological perspectives and address the general themes of (i) the niche, (ii) comparative ecology and macroecology, (iii) community assembly, and (iv) diversity. The integration of ecology and biogeography clearly is a natural undertaking that is based on evolutionary biology, has developed its own momentum, and which promises novel, synthetic approaches to investigating ecological systems and their variation over the surface of the Earth. We offer suggestions on future research directions at the intersection of biogeography and ecology.

Introduction to L2 attrition

2019 ◽  
pp. 329-348 ◽  
Author(s):  
Teodora H. Mehotcheva ◽  
Barbara Köpke
Keyword(s):  
Second Language ◽  
Large Scale ◽  
First Language ◽  
Foreign Languages ◽  
Future Research ◽  
Theoretical Frameworks ◽  
Research Directions ◽  
Short Overview ◽  
Future Research Directions ◽  
The Subject

As the introduction to the section on second language (L2) attrition, this chapter provides a broad presentation to research on attrition of L2 and foreign languages (FL). We will first discuss the terminology used in the field, focusing on some important differences in the terminology used in first language (L1) attrition studies. It provides a short overview of the development of the field, outlining major challenges and obstacles that research on the topic has to deal with. Next, it briefly describes the major findings and knowledge amassed on the subject before reviewing in more detail the findings of some of the most significant and large-scale projects carried out on L2/FL attrition. A final presentation of several theoretical frameworks of interest for L2/FL attrition research will allow us to show how L2/FL attrition is commonly explained but also to provide some ideas for future research directions.

scholarly journals Graph Neural Networks: Taxonomy, Advances, and Trends

2022 ◽  
Vol 13 (1) ◽  
pp. 1-54
Author(s):  
Yu Zhou ◽  
Haixia Zheng ◽  
Xin Huang ◽  
Shufeng Hao ◽  
Dengao Li ◽  
...  
Keyword(s):  
Neural Networks ◽  
Real World ◽  
Research Community ◽  
Future Research ◽  
Research Directions ◽  
Comprehensive Review ◽  
Future Research Directions ◽  
Graph Neural Networks ◽  
Low Dimensional

Graph neural networks provide a powerful toolkit for embedding real-world graphs into low-dimensional spaces according to specific tasks. Up to now, there have been several surveys on this topic. However, they usually lay emphasis on different angles so that the readers cannot see a panorama of the graph neural networks. This survey aims to overcome this limitation and provide a systematic and comprehensive review on the graph neural networks. First of all, we provide a novel taxonomy for the graph neural networks, and then refer to up to 327 relevant literatures to show the panorama of the graph neural networks. All of them are classified into the corresponding categories. In order to drive the graph neural networks into a new stage, we summarize four future research directions so as to overcome the challenges faced. It is expected that more and more scholars can understand and exploit the graph neural networks and use them in their research community.

scholarly journals New approaches to an old problem: Dollar spot of turfgrass

2021 ◽  
Author(s):  
Suraj Sapkota ◽  
Katherine E. Catching ◽  
Paul L. Raymer ◽  
Alfredo D. Martinez-Espinoza ◽  
Bochra Bahri
Keyword(s):  
Fungal Pathogens ◽  
Large Scale ◽  
Resistance Breeding ◽  
Future Research ◽  
Dollar Spot ◽  
Sources Of Resistance ◽  
Aesthetic Value ◽  
Sequencing Technologies ◽  
Host Pathogen ◽  
Available Information

Dollar spot, caused by the fungal pathogens Clarireedia spp. (formerly Sclerotinia homoeocarpa), is the most common and widely distributed disease of turfgrass worldwide. It can drastically reduce the quality of turfgrass species and impact their aesthetic value and playability. Management of dollar spot typically includes a costly program of multiple applications of fungicides within a growing season. Consequently, there have been reported cases of fungicide resistance in populations of Clarireedia spp. Host resistance could be an important component of dollar spot management; however, this approach has been hampered by the lack of sources of resistance as nearly all known warm- and cool-season turfgrass species are susceptible. With the recent advancement in genome sequencing technologies, studies on pathogen genomics and host-pathogen interactions are emerging with the hope to reveal candidate resistance genes in turfgrass and genes for virulence and pathogenicity in Clarireedia spp. Large-scale screening of turfgrass germplasm and quantitative trait loci (QTL) analysis for dollar spot resistance are important for resistance breeding, but only a handful of such studies have been conducted to date. This review summarizes currently available information on the dollar spot pathosystem, taxonomy, pathogen genomics, host-pathogen interaction, genetics of resistance, QTL mapping, and also provides some thoughts for future research prospects to better manage this disease.

scholarly journals Compressing Large-Scale Transformer-Based Models: A Case Study on BERT

2021 ◽  
Vol 9 ◽  
pp. 1061-1080
Author(s):  
Prakhar Ganesh ◽  
Yao Chen ◽  
Xin Lou ◽  
Mohammad Ali Khan ◽  
Yin Yang ◽  
...  
Keyword(s):  
Language Processing ◽  
Large Scale ◽  
State Of The Art ◽  
Future Research ◽  
Research Directions ◽  
Research Attention ◽  
Model Compression ◽  
Future Research Directions ◽  
Or Applications

Abstract Pre-trained Transformer-based models have achieved state-of-the-art performance for various Natural Language Processing (NLP) tasks. However, these models often have billions of parameters, and thus are too resource- hungry and computation-intensive to suit low- capability devices or applications with strict latency requirements. One potential remedy for this is model compression, which has attracted considerable research attention. Here, we summarize the research in compressing Transformers, focusing on the especially popular BERT model. In particular, we survey the state of the art in compression for BERT, we clarify the current best practices for compressing large-scale Transformer models, and we provide insights into the workings of various methods. Our categorization and analysis also shed light on promising future research directions for achieving lightweight, accurate, and generic NLP models.

scholarly journals Automated Machine Learning on Graphs: A Survey

2021 ◽  
Author(s):  
Ziwei Zhang ◽  
Xin Wang ◽  
Wenwu Zhu
Keyword(s):  
Machine Learning ◽  
Learning Algorithm ◽  
Research Community ◽  
Future Research ◽  
Research Directions ◽  
Vast Number ◽  
Neural Architecture ◽  
Future Research Directions ◽  
Automated Machine Learning ◽  
Optimal Machine

Machine learning on graphs has been extensively studied in both academic and industry. However, as the literature on graph learning booms with a vast number of emerging methods and techniques, it becomes increasingly difficult to manually design the optimal machine learning algorithm for different graph-related tasks. To solve this critical challenge, automated machine learning (AutoML) on graphs which combines the strength of graph machine learning and AutoML together, is gaining attention from the research community. Therefore, we comprehensively survey AutoML on graphs in this paper, primarily focusing on hyper-parameter optimization (HPO) and neural architecture search (NAS) for graph machine learning. We further overview libraries related to automated graph machine learning and in-depth discuss AutoGL, the first dedicated open-source library for AutoML on graphs. In the end, we share our insights on future research directions for automated graph machine learning. This paper is the first systematic and comprehensive review of automated machine learning on graphs to the best of our knowledge.

Bug Handling in Service Sector Software

2017 ◽  
pp. 54-73
Author(s):  
Anjali Goyal ◽  
Neetu Sardana
Keyword(s):  
Financial Services ◽  
Large Scale ◽  
Service Sector ◽  
Service Industry ◽  
Predictive Analysis ◽  
Mining Machine ◽  
Future Research ◽  
Software Systems ◽  
Future Research Directions ◽  
Mathematical Optimisation

The technology enabled service industry is emerging as the most dynamic sectors in world's economy. Various service sector industries such as financial services, banking solutions, telecommunication, investment management, etc. completely rely on using large scale software for their smooth operations. Any malwares or bugs in these software is an issue of big concern and can have serious financial consequences. This chapter addresses the problem of bug handling in service sector software. Predictive analysis is a helpful technique for keeping software systems error free. Existing research in bug handling focus on various predictive analysis techniques such as data mining, machine learning, information retrieval, optimisation, etc. for bug resolving. This chapter provides a detailed analysis of bug handling in large service sector software. The main emphasis of this chapter is to discuss research involved in applying predictive analysis for bug handling. The chapter also presents some possible future research directions in bug resolving using mathematical optimisation techniques.

Ethical, Cultural and Socio- Economic Factors of Software Piracy Determinants in a Developing Country

2009 ◽  
pp. 354-372
Author(s):  
Arsalan Butt
Keyword(s):  
University Students ◽  
Cultural Values ◽  
Software Industry ◽  
Empirical Studies ◽  
Software Piracy ◽  
Research Community ◽  
Future Research ◽  
Research Directions ◽  
The World ◽  
Future Research Directions

Consumer software piracy is widespread in many parts of the world. P2P based websites have made it easier to access pirated software, which has resulted in an increased emphasis on the issue of software piracy in both the software industry and research community. Some factors that determine piracy include poverty, cultural values, ethical attitudes, and education. Earlier empirical studies have looked at software piracy as an intentional behaviour. This study explores the demographic, ethical and socioeconomical factors that can represent software piracy as a social norm among a developing country’s university students. The authors have conducted a comparative analysis of university students from Pakistan and Canada, two countries that differ economically, socially, and culturally. The results of the study indicate that software piracy behaviour is different in both groups of students, but that there are also some similarities. Future research directions and implications are also presented.

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