3篇
您的检索式：作者名="Sichen Jin"
|
|
|
题名
|
作者
|
年代
|
出处
|
被引量
|
| 1 | Visual analytics of taxi trajectory data via topical sub-trajectories显示文摘GPS-based taxi trajectories contain valuable knowledge about movement patterns for transportation and urban planning.Topic modeling is an effective tool to extract semantic information from taxi trajectory data.However,previous methods generally ignore trajectory directions that are important in the analysis of movement patterns.In this paper,we employ the bigram topic model rather than traditional topic models to analyze textualized trajectories and consider the direction information of trajectories.We further propose a modified Apriori algorithm to extract topical sub-trajectories and use them to represent each topic.Finally,we design a visual analytics system with several linked views to facilitate users to interactively explore movement patterns from topics and topical sub-trajectories.The case studies with Chengdu taxi trajectory data demonstrate the effectiveness of the proposed system. | Huan Liu Sichen Jin Yuyu Yan Yubo Tao Hai Lin | 2019 | Visual Informatics2019，3，3： | 3 |
| 2 | Anomaly Detection of Multivariate Time Series Based on Metric Learning显示文摘Most of the current methods for anomaly detection in time series are unsupervised.However,unsupervised learning assumes the distribution of the data and cannot obtain satisfactory results in some scenarios.In this paper,we design a semisupervised time series anomaly detection algorithm based on metric learning.The algorithm model mines the features in the time series from the perspectives of the time domain and frequency domain.Furthermore,we design a loss function for anomaly detection.Different from the two-class loss function,in the scenario of the loss function we designed,the normal data will be clustered and distributed in the embedding space,and the abnormal data will be far from the normal data distribution.Furthermore,we extend our designed metric learning model to a semisupervised learning model,extending the labeled dataset with the unlabeled dataset by setting different confidence levels.We conduct experiments on different public datasets and compare them with commonly used time series anomaly detection algorithms.The results show that our model has a good effect.At the same time the semisupervised setting does improve the accuracy of model detection. | Hongkai Wang Jun Feng Liangying Peng Sichen Pan Shuai Zhao Helin Jin | 2022 | 国际计算机前沿大会会议论文集2022，，1： | 0 |
| 3 | Ablation of Zfhx4 results in early postnatal lethality by disrupting the respiratory center in mice显示文摘Breathing is an integrated motor behavior that is driven and controlled by a network of brainstem neurons.Zfhx4 is a zinc finger transcription factor and our results showed that it was specifically expressed in several regions of the mouse brainstem.Mice lacking Zfhx4 died shortly after birth from an apparent inability to initiate respiration.We also found that the electrical rhythm of brainstem‒spinal cord preparations was significantly depressed in Zfhx4-null mice compared to wild-type mice.Immunofluorescence staining revealed that Zfhx4 was coexpressed with Phox2b and Math1 in the brainstem and that Zfhx4 ablation greatly decreased the expression of these proteins,especially in the retrotrapezoid nucleus.Combined ChIP‒seq and mRNA expression microarray analysis identified Phox2b as the direct downstream target gene of Zfhx4,and this finding was validated by ChIP‒qPCR.Previous studies have reported that both Phox2b and Math1 play key roles in the development of the respiratory center,and Phox2b and Math1 knockout mice are neonatal lethal due to severe central apnea.On top of this,our study revealed that Zfhx4 is a critical regulator of Phox2b expression and essential for perinatal breathing. | Meiqin Zhang Sichen Du Huayuan Ou Renjie Cui Nan Jiang Yifeng Lin Runsheng Ge Duan Ma Jin Zhang | 2021 | Journal of Molecular Cell Biology2021，13，3： | 0 |
您所在的机构暂未开通此部分的功能，请联系管理员