Travel Modes Recognition Method Based on Mobile Phone Signaling Data

Author(s):  
Ying Xia ◽  
Jie Tang ◽  
Xu Zhang ◽  
Hae-young Bae
Author(s):  
Zixuan Wang ◽  
Jian Tang ◽  
Chengyu Cui ◽  
Weitao Li ◽  
Zhe Xu ◽  
...  

2013 ◽  
Vol 2013 ◽  
pp. 1-13
Author(s):  
Chih-Yu Hsu ◽  
Pei-Shan Lee ◽  
Kuo-Kun Tseng ◽  
Yifan Li

Security certification is drawing more and more attention in recent years; the biometric technology is used in a variety of different areas of security certification. In this paper, we propose a palm image recognition method to identify an individual for vehicular application; it uses palm image as a key for detecting the car owner. We used mobile phone cameras to take palm images and performed a new identification approach by using feature regularization of palm contour. After identification is confirmed, the phone uses Bluetooth/WiFi to connect the car to unlock it. In our evaluation, the experiments show that our approach is effective and feasible.


2014 ◽  
Vol 35 (3) ◽  
pp. 158-165 ◽  
Author(s):  
Christian Montag ◽  
Konrad Błaszkiewicz ◽  
Bernd Lachmann ◽  
Ionut Andone ◽  
Rayna Sariyska ◽  
...  

In the present study we link self-report-data on personality to behavior recorded on the mobile phone. This new approach from Psychoinformatics collects data from humans in everyday life. It demonstrates the fruitful collaboration between psychology and computer science, combining Big Data with psychological variables. Given the large number of variables, which can be tracked on a smartphone, the present study focuses on the traditional features of mobile phones – namely incoming and outgoing calls and SMS. We observed N = 49 participants with respect to the telephone/SMS usage via our custom developed mobile phone app for 5 weeks. Extraversion was positively associated with nearly all related telephone call variables. In particular, Extraverts directly reach out to their social network via voice calls.


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