scholarly journals Attempt for automated detection of building damage areas due to recent earthquakes using aerial television images.

2002 ◽  
pp. 267-278 ◽  
Author(s):  
Hajime MITOMI ◽  
Masashi MATSUOKA ◽  
Fumio YAMAZAKI
Keyword(s):  
Building Damage ◽  
Automated Detection ◽  
Recent Earthquakes

Re-evaluation of building damage during recent earthquakes in Turkey

2008 ◽  
Vol 30 (2) ◽  
pp. 412-427 ◽  
Author(s):  
Mehmet Inel ◽  
Hayri Baytan Ozmen ◽  
Huseyin Bilgin
Keyword(s):  
Building Damage ◽  
Recent Earthquakes

Automated detection of epithelial changes in colorectal carcinoma

2012 ◽  
Vol 50 (05) ◽  
Author(s):  
G Valcz ◽  
I Bándi ◽  
B Wichmann ◽  
A Patai ◽  
D Szabó ◽  
...  
Keyword(s):  
Colorectal Carcinoma ◽  
Automated Detection

Failure Analysis Of Buried Gas Pipelines Crossing Seismic Faults

2020 ◽  
Vol 3 (2) ◽  
pp. 781-790
Author(s):  
M. Rizwan Akram ◽  
Ali Yesilyurt ◽  
A.Can. Zulfikar ◽  
F. Göktepe
Keyword(s):  
Ground Deformation ◽  
Warning System ◽  
Strike Slip ◽  
Gas Pipelines ◽  
Steel Pipes ◽  
Seismic Fault ◽  
Fault Parameters ◽  
Dip Angle ◽  
Permanent Ground Deformation ◽  
Recent Earthquakes

Research on buried gas pipelines (BGPs) has taken an important consideration due to their failures in recent earthquakes. In permanent ground deformation (PGD) hazards, seismic faults are considered as one of the major causes of BGPs failure due to accumulation of impermissible tensile strains. In current research, four steel pipes such as X-42, X-52, X-60, and X-70 grades crossing through strike-slip, normal and reverse seismic faults have been investigated. Firstly, failure of BGPs due to change in soil-pipe parameters have been analyzed. Later, effects of seismic fault parameters such as change in dip angle and angle between pipe and fault plane are evaluated. Additionally, effects due to changing pipe class levels are also examined. The results of current study reveal that BGPs can resist until earthquake moment magnitude of 7.0 but fails above this limit under the assumed geotechnical properties of current study. In addition, strike-slip fault can trigger early damage in BGPs than normal and reverse faults. In the last stage, an early warning system is proposed based on the current procedure. 

Machine Learning in Agriculture

2018 ◽  
Vol 8 (6) ◽  
pp. 26 ◽  
Author(s):  
Matthew N. O. Sadiku ◽  
Chandra M. M Kotteti ◽  
Sarhan M. Musa
Keyword(s):  
Climate Change ◽  
Artificial Intelligence ◽  
Machine Learning ◽  
Disease Diagnosis ◽  
Automated Detection ◽  
Disease Prediction ◽  
Paper Briefly ◽  
Agriculture Sector ◽  
Modern Agriculture ◽  
Crop Disease

Machine learning is an emerging field of artificial intelligence which can be applied to the agriculture sector. It refers to the automated detection of meaningful patterns in a given data.  Modern agriculture seeks ways to conserve water, use nutrients and energy more efficiently, and adapt to climate change.  Machine learning in agriculture allows for more accurate disease diagnosis and crop disease prediction. This paper briefly introduces what machine learning can do in the agriculture sector.

Notices of recent earthquakes; No. 4

1874 ◽  
Vol s3-7 (40) ◽  
pp. 384-387
Author(s):  
C. G. Rockwood
Keyword(s):  
Recent Earthquakes

TSUNAMI ACEH 2004 SEBAGAI DASAR PENATAAN RUANG KOTA MEULABOH

2013 ◽  
Vol 13 (2) ◽  
Author(s):  
Wisyanto Wisyanto
Keyword(s):  
Coastal Area ◽  
Building Damage ◽  
Tsunami Hazard ◽  
The Road ◽  
Tsunami Disaster ◽  
Landuse Planning ◽  
The Future ◽  
Tsunami Mitigation ◽  
Potential Losses ◽  
The Impact

Tsunami which was generated by the 2004 Aceh eartquake has beenhaunting our life. The building damage due to the tsunami could be seenthroughout Meulaboh Coastal Area. Appearing of the physical loss wasclose to our fault. It was caused by the use dan plan of the land withoutconsidering a tsunami disaster threat. Learning from that event, we haveconducted a research on the pattern of damage that caused by the 2004tsunami. Based on the analysis of tsunami hazard intensity and thepattern of building damage, it has been made a landuse planning whichbased on tsunami mitigation for Meulaboh. Tsunami mitigation-based ofMeulaboh landuse planning was made by intergrating some aspects, suchas tsunami protection using pandanus greenbelt, embankment along withhigh plants and also arranging the direction of roads and setting of building forming a rhombus-shaped. The rhombus-shaped of setting of the road and building would reduce the impact of tsunamic wave. It is expected that these all comprehensive landuse planning will minimize potential losses in the future .

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