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JSCE Magazine Summary & Index

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vol.103 No.2 February 2018

 

Will Deep Learning Change Civil Engineering Processes? : Exploring the Use of Artificial Intelligence

Artificial intelligence (AI) recently attracts attention of public, and “deep learning,” a type of machine learning that utilizes multi-layered neural networks, is a center of attention among the other AI techniques. Deep learning is well known for its surpassing capability beyond human for some information processing tasks such as image recognition. The limit of capability is not clear yet; it would be enhanced by the increase in amount of observation data of the real world in the future.
The feature articles focused on deep learning and tried to inspect its applicability in civil engineering processes. First we briefly described the basics of neural network and deep learning, then we introduced its theoretical progress and prospect, applicability in industries, and the power of graphical processing unit (GPU) in the analysis. Next we introduced applications in civil engineering: “evaluation of geological features,” “monitoring of construction progress,” “monitoring of railway truck,” and “remote construction” as field applications, and “prediction of flood,” “feature extraction of microtremor data,” and “forecast of water quality” as research applications. The information of a book on deep learning, as well as a website were introduced in this magazine.
If you are interested in this feature article, please check the book and website.


≪Index≫

(02) the Special Discussion
ZAMMA Rieko, OHISHI Hisakazu

(06) Feature article
Will Deep Learning Change Civil Engineering Processes?: Exploring the Use of Artificial Intelligence

(08) What is “Artificial Intelligence?” What is “Deep Learning?”

(10) Will Deep Learning Change Civil Engineering Processes?: Image recognition and robotics advance automated construction and inspection works
MATSUO Yutaka

(14) Deep Learning Changes Industry’s Future: Introduce It at Right Places in Business Flows
NOMURA Naoyuki

(18) Accelerating Deep Learning Industry Application - GPU realizing High-performance AI Training and Inference -
BAJI Toru

(22) Construction of a geological information management system using AI, CIM and image processing technology
UTSUKI Shinji

(24) Construction progress estimation system - Construction management by artificial intelligence -
NAKABAYASHI Takuma

(26) Track facility monitoring device to detect a failure of railway track - Detection of rail surface failure using transfer learning -
KOMATSU Yoshihiro

(28) The innovative remote construction system for lunar base and construction site on the earth by cooperation of remote and autonomous control
HAMAMOTO Kenniti

(30) Flood prediction using artificial intelligence - Improvement of accuracy by applying deep learning -
HITOKOTO Masayuki

(32) Automatic Processing of Microtremor Data using Convolutional Neural Network - Feature Extraction of Timeseries Data based on Deep Learning -
MIYAMOTO Takashi

(34) Forecast of water quality in a river estuary using a deep learning model
NAKATANI Yusuke

(36) Further Studies for Deep Learning

(38) Admiration of Civil Engineering Heritages by JSCE:Civil Engineering Heritage Sites Section
Krippen groins on The Kiso-River - Typical works of the river improvement in Meiji era -
YASUI Masahiko

(40) Let's go abroad
PPP Projects Looking Towards Regional Development in Butuan City, Mindanao Island - As a Lifework from the Viewpoint of Academia and Business -
KATO Satoshi

(42) Alumni of DOBOKU - The pages for people linked to Japan -
Advancing Civil Engineering Expertise and Education through Research Collaboration and Networking in Japan
Andres Winston C. Oreta

(44) Report Experiment Facilities
Testing Rock as discontinuous,inhomogeneous and anisotropic materials - Multipurpose Testing Machine for Rock Mass -
SUZUKI Kenichiro

(46) Numerical Analysis Seminar for Civil Engineer without a mathematical formula
Numerical simulation of fatigue crack growth in steel bridges by XFEM
SHIBANUMA Kazuki

(48) Let's try to learn great civil engineers
Load who made his dream come true “Hiroyoshi Kikkawa”
YODA Teruhiko

(50) My Bookshelf
HORIGUCHI Ryota

(51) JSCE Publications

(52) Professional Skills Necessary for Construction

(54) JSCE Member's Report
Prospects for the solution to problems of litter on riverside and beach
NAKAI Keiji, ITO Hiroko

(56) Trial of Japanese Style Education for National Institute of Technology in Mongolia
FUKUDA Makoto, KIMURA Tomohiro

(58) Messages from outside
SHIMIZU Yoshinari

(60) Advisers' Column

(62) International Activities Center

(64) JSCE Update

(71) CE Careers

(72) JSCE Calendar

(74) Next Issues

 


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