A Framework of Fine-Grained Mobile Sensing Data Collection and Behavior Analysis in an Energy-Configurable Way

Author(s):  
Xiaoyun Mo ◽  
Dianxi Shi ◽  
Ruosong Yang ◽  
Han Li ◽  
ZheHang Tong ◽  
...  
2014 ◽  
Vol 42 (10) ◽  
pp. 1067-1073 ◽  
Author(s):  
Krista L. Hinz ◽  
Heather M. McGee ◽  
Bradley E. Huitema ◽  
Alyce M. Dickinson ◽  
Richard A. Van Enk

2018 ◽  
Vol 2018 ◽  
pp. 1-25 ◽  
Author(s):  
Yingying Ren ◽  
Anfeng Liu ◽  
Ming Zhao ◽  
Changqin Huang ◽  
Tian Wang

The vehicular communication networks, which can employ mobile, intelligent sensing devices with participatory sensing to gather data, could be an efficient and economical way to build various applications based on big data. However, high quality data gathering for vehicular communication networks which is urgently needed faces a lot of challenges. So, in this paper, a fine-grained data collection framework is proposed to cope with these new challenges. Different from classical data gathering which concentrates on how to collect enough data to satisfy the requirements of applications, a Quality Utilization Aware Data Gathering (QUADG) scheme is proposed for vehicular communication networks to collect the most appropriate data and to best satisfy the multidimensional requirements (mainly including data gathering quantity, quality, and cost) of application. In QUADG scheme, the data sensing is fine-grained in which the data gathering time and data gathering area are divided into very fine granularity. A metric named “Quality Utilization” (QU) is to quantify the ratio of quality of the collected sensing data to the cost of the system. Three data collection algorithms are proposed. The first algorithm is to ensure that the application which has obtained the specified quantity of sensing data can minimize the cost and maximize data quality by maximizing QU. The second algorithm is to ensure that the application which has obtained two requests of application (the quantity and quality of data collection, or the quantity and cost of data collection) could maximize the QU. The third algorithm is to ensure that the application which aims to satisfy the requirements of quantity, quality, and cost of collected data simultaneously could maximize the QU. Finally, we compare our proposed scheme with the existing schemes via extensive simulations which well justify the effectiveness of our scheme.


2006 ◽  
Vol 7 (3) ◽  
pp. 335-350 ◽  
Author(s):  
William O'Donohue ◽  
Kyle E. Ferguson

2020 ◽  
Author(s):  
SUSIATI

The word 'politeness' can be interpreted as 'politeness'. Although often aligned and paired, polite words and polite words have different meanings. The Big Indonesian Dictionary defines the word polite as respectful and reverent and orderly according to good tradition. Meanwhile, the word courtesy means the subtle and kind nature of his language and behavior. Thus, manners can be interpreted as the nature of respect, orderly to the prevailing norms, smooth and kind language, and good behavior. Therefore, someone who has good manners is someone who is respectful, obedient to the prevailing norms, refined and well-mannered, and has good behavior. This study aims to describe the ambiguity of the Indonesian language used by Cia-cia districk Buru. This type of research is qualitative research that is naturally or in the context of a wholeness. by using descriptive collected in the form of words and not numbers. The data in this study are data that contain ambiguity using the theories of experts when analyzing. Data collection techniques namely after describing the form of words and phrases in Indonesian written by students after that are analyzed according to theory. the results showed that in students' essays there were words and phrases that contained ambiguity.


2021 ◽  
Vol 13 (11) ◽  
pp. 2067
Author(s):  
Haoyu Liu ◽  
Xianwen He ◽  
Yanbing Bai ◽  
Xing Liu ◽  
Yilin Wu ◽  
...  

The official method of collecting county-level GDP values in the Chinese Mainland relies mainly on administrative reporting data and suffers from high costs of time, money, and human labor. To date, a series of studies have been conducted to generate fine-grained maps of socioeconomic indicators from the easily accessed remote sensing data and achieved satisfactory results. This paper proposes a transfer learning framework that regards nightlight intensities as a proxy of economic activity degrees to estimate county-level GDP around the Chinese Mainland. In the framework, paired daytime satellite images and nightlight intensity levels were applied to train a VGG-16 architecture, and the output features at a specific layer, after dimensional reduction and statistics calculation, were fed into a simple regressor to estimate county-level GDP. We trained the model with data of 2017 and utilized it to predict county-level GDP of 2018, achieving an R-squared of 0.71. Furthermore, the results of gradient visualization confirmed the validity of the proposed framework qualitatively. To the best of our knowledge, this is the first time that county-level GDP values around the Chinese Mainland have been estimated from both daytime and nighttime remote sensing data relying on attention-augmented CNN. We believe that our work will shed light on both the evolution of fine-grained socioeconomic surveys and the application of remote sensing data in economic research.


Author(s):  
Mohammad Lutfur Rahman

Purpose Among the many studies about risk perception, only a few deal with Bangladesh. Paul and Bhuiyan’s (2010) study has shown the earthquake-preparedness level of residents of Dhaka, but there are some biases in the data collection. This paper aims to examine the seismic-risk perception and the level of knowledge on earthquake and preparedness among the residents of Dhaka. Design/methodology/approach A questionnaire was developed, and data collection was undertaken through home and sidewalk surveys. This paper investigates how attitude, perception and behavior differ depending on gender, age, education and casualty awareness. This research tries to examine and make a comparison of the risk perception and preparedness level between different groups of gender, age and level of education. Findings This research shows that female respondents have a much better risk perception of and are better prepared for earthquakes than male respondents; younger people have a higher knowledge about earthquake preparedness than older people and less-educated people are at a higher risk of unpreparedness than more-educated people. Research limitations/implications This research is only limited to the Dhaka Division. Originality/value This paper concludes by noting that public awareness on seismic-risk perception and mitigation is poor, and their knowledge on basic theory and emergency response must be improved.


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