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Sensor based algorithms need to extract features from raw sensor data. However, different devices have different sensor data distributions. This distribution differences lead to a problem that model trained on device A may be invalid when applied to device B. However, it is labor-consuming to collect data and label them on device B from scratch. To solve the problem, a solution is proposed to learn...
Step change is a key factor affecting the user trajectory and distance, to determine the trajectory of the user is a common indoor positioning method based on inertial navigation line calculation model, the prediction step is mainly based on the linear sensor, acceleration sensor data and the movement of the periodic estimation of pedestrians every step of the displacement distance. In order to improve...
Spare parts are indispensable resources to ensure equipment the normal operation and continuous production, especially for urban raü vehicles. When the spare parts storage is insufficient, the equipment can't be replaced or repair ed in time, which can cause serious loss. Therefore, it is important to forecast the demand of the urban rail vehicle spare parts. A combination forecasting method based...
This paper proposed to utilize bug knowledge graph for bug resolution. Bug knowledge graph provide more comprehensive and relevant bug information (i.e., bug reports, commits, relevant developers, etc.). Moreover, our approach can automatically update bug knowledge graph based on the the lifelong learning topic model. Preliminary results show that bug knowledge graph can provide more accurate and...
With big data growth in biomedical and healthcare communities, accurate analysis of medical data benefits early disease detection, patient care, and community services. However, the analysis accuracy is reduced when the quality of medical data is incomplete. Moreover, different regions exhibit unique characteristics of certain regional diseases, which may weaken the prediction of disease outbreaks...
We study the problem of zero-shot classification in which we don't have labeled data in target domain. Existing approaches learn a model from source domain and apply it without adaptation to target domain, which is prone to domain shift problem. To solve the problem, we propose a novel Learning Discriminative Instance Attribute(LDIA) method. Specifically, we learn a projection matrix for both the...
In survival analysis, the primary goal is to monitor several entities and model the occurrence of a particular event of interest. In such applications, it is quite often the case that the event of interest may not always be observed during the study period and this gives rise to the problem of censoring which cannot be easily handled in the standard regression approaches. In addition, obtaining sufficient...
Virtual simulation is one of the core techniques and essential steps of realizing digital city. As a miniature of digital city, virtual campus was widely built in colleges and universities. Combining 3ds Max with MultiGen Creator, the 3D model of virtual campus of South China Agricultural University was built according to the merits of the two major modeling software. And the paper introduced the...
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