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This paper presents a scalable estimation theoretic framework to address the time-sensitive truth discovery problem with accuracy assessment in social sensing applications. Social sensing has emerged as a new application paradigm that provides us with an unprecedented opportunity to collect observations about the physical world from humans or devices on their behalf. A fundamental challenge in social sensing applications lies in ascertaining the correctness of claims and the reliability of data sources without knowing either of them a priori, which is referred to as truth discovery. While significant progress has been made to solve the truth discovery problem, there exists three important limitations: (1) The information of users and claims in time dimension has not been fully exploited in the truth discovery solutions; (2) An analytical framework to rigorously assess the accuracy of the truth discovery results is lacking; and (3) Many current truth discovery schemes perform sequential operations, which are not scalable to large-scale social sensing events. To address the above limitations, we propose a scalable time-sensitive truth discovery (TS-TD) scheme that explicitly incorporates the source responsiveness and the claim lifespan into an estimation theoretical framework. Furthermore, we develop new confidence bounds to rigorously assess the accuracy of the truth discovery results. We also implement a parallel TS-TD algorithm on a graphic processing unit platform with thousands of cores to improve the computational efficiency. Finally, we evaluate the TS-TD scheme through three real-world case studies using Twitter data feeds and a simulation study. The evaluation results demonstrate the effectiveness and efficiency of our scheme.

The ZiYuan-3 (ZY-3) remote sensing satellite is China's first civilian high-resolution stereo mapping satellite. Because the interior orientation parameters measured before launch are biased, the multispectral (four-band) images collected by ZY-3 exhibit low-accuracy band-to-band registration, which affects their subsequent applications. This paper presents a valid method for interior orientation determination of the ZY-3 multispectral sensor by determining the look angles of the charge-coupled device arrays for all bands. One band is chosen as the benchmark band, and its interior orientation is determined using the relevant ZY-3 image collected over the calibration field and the corresponding digital orthoimage map and digital elevation model. The remaining bands are then calibrated using the benchmark band as control data. The quality of the calibration is further enhanced by shortening the calibration period and by combining images collected over different calibration fields, which decreases the negative effects of errors in the satellite's attitude and position data. The interior orientation of the multispectral sensor in ZY-3 was determined using data sets taken over two calibration fields, namely, Dengfeng (Henan Province) and Tianjin. Evaluation experiments were performed using ZY-3 multispectral images and ground control points (GCPs) collected over several different periods and areas. The positioning accuracy of the ZY-3 multispectral images with a limited number of GCPs after calibration of the interior orientation was better than 0.3 pixels, and the band-to-band registration accuracy was up to 0.15 pixels. [ABSTRACT FROM PUBLISHER]