Conclusions and Open Research Problems

Author(s):  
Dirk Beyer ◽  
Feng Cheng ◽  
Suresh P. Sethi ◽  
Michael Taksar
2021 ◽  
Vol 54 (2) ◽  
pp. 1-37
Author(s):  
Dhivya Chandrasekaran ◽  
Vijay Mago

Estimating the semantic similarity between text data is one of the challenging and open research problems in the field of Natural Language Processing (NLP). The versatility of natural language makes it difficult to define rule-based methods for determining semantic similarity measures. To address this issue, various semantic similarity methods have been proposed over the years. This survey article traces the evolution of such methods beginning from traditional NLP techniques such as kernel-based methods to the most recent research work on transformer-based models, categorizing them based on their underlying principles as knowledge-based, corpus-based, deep neural network–based methods, and hybrid methods. Discussing the strengths and weaknesses of each method, this survey provides a comprehensive view of existing systems in place for new researchers to experiment and develop innovative ideas to address the issue of semantic similarity.


2020 ◽  
Author(s):  
Nasir Saeed ◽  
Mohamed Habib Loukil ◽  
Hadi Sarieddeen ◽  
Tareq Y. Al-Naffouri ◽  
Mohamed-Slim Alouini

<div>Following recent advancements in Terahertz (THz)</div><div>technology, THz communications are currently being celebrated as key enablers for various applications in future generations of communication networks. While typical communication use cases are over medium-range air interfaces, the inherently small beamwidths and transceiver footprints at THz frequencies support nano-communication paradigms. In particular, the use of the THz band for in-body and on-body communications has been gaining attention recently. By exploiting the accurate THz sensing and imaging capabilities, body-centric THz biomedical applications can transcend the limitations of molecular, acoustic, and radio-frequency solutions. In this paper, we study the use of the THz band for body-centric networks, by surveying works on THz device technologies, channel and noise modeling, modulation schemes, and networking topologies. We also promote THz sensing and imaging applications in the healthcare sector, especially for detecting zootonic viruses such as Coronavirus. We</div><div>present several open research problems for body-centric THz networks.</div>


IEEE Network ◽  
2020 ◽  
Vol 34 (3) ◽  
pp. 134-142 ◽  
Author(s):  
Walid Saad ◽  
Mehdi Bennis ◽  
Mingzhe Chen

Author(s):  
Jian Ying Zhang ◽  
◽  
Hepu Deng ◽  
Ryszard Kowalczyk ◽  

In this paper we introduce fuzzy causal network as a qualitative model for service oriented computing. Firstly, we give a brief description of fuzzy causal network. Secondly, we explain how fuzzy causal network can be used as a qualitative model for service oriented computing. Thirdly, We use fuzzy causal network to model a real world problem in the area of service oriented computing to demonstrate the correctness and effectiveness of this model. Finally, we outline some open research problems for further study. The proposed model has potential to become a good framework for causal discovery and decision support in service oriented computing, especially in the cases where intensive interaction among various services are involved.


Heliyon ◽  
2019 ◽  
Vol 5 (6) ◽  
pp. e01802 ◽  
Author(s):  
Emmanuel Gbenga Dada ◽  
Joseph Stephen Bassi ◽  
Haruna Chiroma ◽  
Shafi'i Muhammad Abdulhamid ◽  
Adebayo Olusola Adetunmbi ◽  
...  

Author(s):  
Bernard P. Zeigler ◽  
Alexandre Muzy ◽  
Ernesto Kofman

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