scholarly journals Avian Group D Rotaviruses: Structure, Epidemiology, Diagnosis, and Perspectives on Future Research Challenges

Pathogens ◽  
2017 ◽  
Vol 6 (4) ◽  
pp. 53 ◽  
Author(s):  
Pallavi Deol ◽  
Jobin Kattoor ◽  
Shubhankar Sircar ◽  
Souvik Ghosh ◽  
Krisztián Bányai ◽  
...  
Keyword(s):  
Future Research ◽  
Research Challenges ◽  
Group D ◽  
Avian Group

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.

Services and Service Composition – An Introduction (Services und Service Komposition – Eine Einführung)

2008 ◽  
Vol 50 (2) ◽  
Author(s):  
Shahram Dustdar ◽  
Mike P. Papazoglou
Keyword(s):  
Web Services ◽  
Service Composition ◽  
Web Applications ◽  
Future Research ◽  
Basic Principles ◽  
Service Oriented Computing ◽  
Research Challenges ◽  
Internet Computing ◽  
The Future ◽  
Service Oriented

SummaryIn this overview paper, we discuss the basic principles underlying service-oriented computing in general, and (Web) services in particular. We discuss the important differences between (Web) services and Web applications and other models in Internet computing. Finally, we discuss where we see the future research challenges in the area of service composition.

Blockchain for Digital Twins: Recent Advances and Future Research Challenges

IEEE Network ◽  
2020 ◽  
Vol 34 (5) ◽  
pp. 290-298 ◽  
Author(s):  
Ibrar Yaqoob ◽  
Khaled Salah ◽  
Mueen Uddin ◽  
Raja Jayaraman ◽  
Mohammed Omar ◽  
...  
Keyword(s):  
Future Research ◽  
Research Challenges ◽  
Recent Advances ◽  
Digital Twins

Machine Learning in 5G Multimedia Communications

2021 ◽  
pp. 204-225
Author(s):  
Dragorad A. Milovanovic ◽  
Zoran S. Bojkovic ◽  
Dragan D. Kukolj
Keyword(s):  
Machine Learning ◽  
Wireless Networks ◽  
Deep Learning ◽  
Complex Networks ◽  
Future Research ◽  
Fifth Generation ◽  
Data Formats ◽  
Research Challenges ◽  
Wireless Environments ◽  
Special Case

Machine learning (ML) has evolved to the point that this technique enhances communications and enables fifth-generation (5G) wireless networks. ML is great to get insights about complex networks that use large amounts of data, and for predictive and proactive adaptation to dynamic wireless environments. ML has become a crucial technology for mobile broadband communication. Special case goes to deep learning (DL) in immersive media. Through this chapter, the goal is to present open research challenges and applications of ML. An exploration of the potential of ML-based solution approaches in the context of 5G primary eMBB, mMTC, and uHSLLC services is presented, evaluating at the same time open issues for future research, including standardization activities of algorithms and data formats.

scholarly journals Toward a Computational Model of Transfer

AI Magazine ◽  
2011 ◽  
Vol 32 (2) ◽  
pp. 126 ◽  
Author(s):  
Daniel Oblinger
Keyword(s):  
Computational Model ◽  
Transfer Learning ◽  
Future Research ◽  
Learning Program ◽  
Research Challenges ◽  
Program Research

This article focuses on a broad framing of the DARPA Transfer Learning Program research and an assessment of its progress, limitations, and challenges, from an admittedly personal but DARPA-influenced perspective. I will focus on a broad framing of TL that that will allow us to talk about this body of work as a whole, and use this to look towards work yet to be done in this area. I will consider both indicated application areas for transfer learning, as well as indicated future research challenges. With each of these I will also venture assessment of the "ripeness" of each of these subareas for follow on work-of course this assessment will be a very personal estimation based on the effort and progress made during the TL program.

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