Optical Fiber and the Future of Communication

Physics Today ◽  
2008 ◽  
Keyword(s):  
Optical Fiber ◽  
The Future

scholarly journals Measurement of Bangudae Rock Joint Using Non-adhesive, Non-contact Inclinometer Slope Laser Measuring System

2021 ◽  
Vol 37 (6) ◽  
pp. 617-625
Author(s):  
Jae Hyun Kim ◽  
Sang Ok Lee ◽  
Kwang Yong Chung ◽  
Min Su Han
Keyword(s):  
Optical Fiber ◽  
Rock Joint ◽  
Measuring System ◽  
Measuring Instrument ◽  
Contact Type ◽  
Short Period ◽  
Cultural Properties ◽  
The Future ◽  
Yangsan Fault ◽  
Provincial Park

Daegokcheon Stream in Daegok-ri, Ulju-gun, is an area with a developed valley and bedrock from Gajisan Provincial Park to the confluence of the Taehwa River across the Yangsan Fault. To measure the rock of Bangudae petroglyphs, the mineralogical weathering, joints, and scours or cavities at the bottom were confirmed. The measurement was carried out for a short period of time on the joint of the bedrock on which the Bangudae petroglyphs were engraved. Compared to the measured value obtained using existing optical fiber (Ch4 150 µm), a displacement value of 300 µm was obtained using the non-attached, non-contact type of measuring instrument. In the future, it is inferred that this instrument could be used for various cultural properties if the HSV-value suitable for illuminance and various measurement experiences are stored.

scholarly journals The future of plastic optical fiber

2009 ◽  
Vol 1 (1) ◽  
pp. 22-28 ◽  
Author(s):  
Yasuhiro Koike ◽  
Makoto Asai
Keyword(s):  
Optical Fiber ◽  
Plastic Optical Fiber ◽  
The Future

scholarly journals MACHINE LEARNING BASED NONLINEARITY DETERMINATION FOR OPTICAL FIBER COMMUNICATION-REVIEW

2019 ◽  
Vol 2019 (02) ◽  
pp. 121-127 ◽  
Author(s):  
Subarna Shakya
Keyword(s):  
Machine Learning ◽  
Optical Fiber ◽  
Nonlinear Effects ◽  
Optical Fiber Communication ◽  
Machine Learning Techniques ◽  
Digital Information ◽  
Fiber Communication ◽  
The Future ◽  
Optic Fiber Communication ◽  
Almost All

The technological growth in our day to day life and its integration advancements in the communication network to activate a seamless communication have led to digital transformation in almost all applications. This causes a huge set of digital information conveyance via email, audio and video calls connecting people at all times. These data that are presently conveyed with the aid of the optic fiber communication technology would become outdated in the future years due to the growing demands of the digital information due to its intrinsic nonlinear effects. The machine learning appears as the promising technology to handle the complexities to be faced in the future systems by identify novel methodologies and utilizing available resources. The paper is to present the review on the nonlinearities experienced in the optical fiber and the promising solution provided by the machine learning techniques to enhance the capabilities of the optical fiber communication.

An Overview of Optical Voltage Sensor Based on Pockels Effect

2013 ◽  
Vol 694-697 ◽  
pp. 987-991 ◽  
Author(s):  
Li Jing Li ◽  
Wen Hui Zhang ◽  
Hui Li ◽  
Rui Pan
Keyword(s):  
Optical Fiber ◽  
Research Direction ◽  
Voltage Sensor ◽  
Future Research ◽  
Pockels Cell ◽  
Pockels Effect ◽  
Future Research Direction ◽  
Voltage Sensors ◽  
Optical Circuit ◽  
The Future

This paper presents a thorough review of optical voltage sensors (OVS) based on Pockels effect which contain many design schemes over the last decades. The principle and optical circuit of each scheme are described respectively, such as Integrated-optic Pockels cell, multi-segment OVS, quasi-reciprocal reflective OVS, dual-crystal OVS and OVS with special optical fiber. The main strengths and weaknesses in every scheme are analyzed. Finally, we summarized the remaining problems in OVS and the future research direction as well to improve the performance of OVS based on Pockels effect.

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