Identifying ambient service location problems and its application using a humanized computing model

2018 ◽  
Vol 10 (6) ◽  
pp. 2345-2359
Author(s):  
You-Shyang Chen ◽  
Heng-Hsing Chu ◽  
Arun Kumar Sangaiah
KOMPUTEK ◽  
2017 ◽  
Vol 1 (1) ◽  
pp. 37
Author(s):  
Irfan Khoirul Arifin ◽  
Aliyadi Aliyadi ◽  
Yovi Litanianda

The number of vehicles in Indonesia continues to increase every year. This also happened in Ponorogo regency. It will also be directly proportional to the number of people who have problems with their vehicles, such as leaked tire quotes for being nailed or other causes. And will also increase the need for tire services. For motorists who are less aware of the surrounding area when experiencing damage to motorcycle tires, then of course to find a place nearest tire patch will be quite difficult. Therefore in this study developed information media for Android-based applications to map the locations - tire patch locations in Ponorogo, as well as looking for the closest tire patch with the rider. This app is a location-based service (location-based service) to the driver with the nearest patch of the banal location. Based on the results of testing this application can help users find the location of location preservation, tar bambal patch location, tire repair shop list, and tire repair shop list distance. This application can also show each other the location in accordance with the location of google maps applications. 


2011 ◽  
Vol 71-78 ◽  
pp. 4501-4505
Author(s):  
Ming Chen ◽  
Wan Zhou

Although modern bridge are carefully designed and well constructed, damage may occur in them due to unexpected causes. Currently, many different techniques have been proposed and investigated in bridge condition assessment. However, evaluation efficiency of condition assessment has not been paid much attention by the researchers. A fast evaluation of the urban railway bridge condition based on the cloud computing is presented. In this paper dynamic FE model and Artificial neural networks technique is applied to model updating. The cloud computing model provides the basis for fast analyses. It was found that when applied to the actually railway bridges, the proposed method provided results similar to those obtained by experts, but can improve efficiency of bridge


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