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- 저자 : ( Weixia Chen ) (검색결과 2 건)
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( Sixuan Chen ),( Weixia Zou ),( Xuefeng Liu ),( Yang Zhao ),( Zheng Zhou ) 한국인터넷정보학회 2018 KSII Transactions on Internet and Information Syst Vol.12 No.10
The dynamic opportunistic device-to-device (DO-D2D) network will frequently emerge in the fifth generation (5G) wireless communication due to high-density and fast-moving mobile devices. In order to improve the Quality of Experience (QoE) of users with different computing capacity devices in the DO-D2D network, in this paper, we focus on the study of how to reduce the packets retransmission delay and satisfy heterogeneous devices. To select as many devices as possible to transmit simultaneously without interference, the concurrent transmitters-selecting algorithm is firstly put forward. It jointly considers the number of packets successfully received by each device and the device’s connectivity. Then, to satisfy different devices’ demands while primarily ensuring the base-layer packets successfully received by all the devices, the layer-cooperation instantly decodable network coding is presented, which is used to select transmission packets combination for each transmitter. Simulation results illustrate that there is an appreciable retransmission delay gain especially in the poor channel quality network compared to the traditional base-station (BS) retransmission algorithm. In addition, our proposed algorithms perform well to satisfy the different demands of users with heterogeneous devices.
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( Junyi Shen ),( Linye He ),( Chuan Li ),( Tianfu Wen ),( Weixia Chen ),( Changli Lu ),( Lvnan Yan ),( Bo Li ),( Jiayin Yang ) 대한간학회 2017 Gut and Liver Vol.11 No.5
Background/Aims: Solitary hepatocellular carcinoma (HCC) is a subgroup of HCCs. We aimed to establish nomograms for predicting the survival of solitary HCC patients after hepatectomy. Methods: A total of 538 solitary HCC patients were randomly classified into training and validation sets. A Cox model was used to identify predictors of overall survival (OS) in the training set. A nomogram was generated based on these predictors and was validated using the validation set. Results: Tumor size, microvascular invasion, and major vascular invasion were significantly associated with OS in the training set. Nomograms were developed based on these predictors in the multivariate analysis. The C-index was 0.75 for the OS nomogram and 0.72 for the recurrence-free sur-vival nomogram. Compared to the index of conventional stag-ing systems for predicting survival (0.71 for Barcelona Clinic Liver Cancer, 0.66 for the seventh American Joint Committee on Cancer, 0.68 for Cancer of the Liver Italian Program, and 0.70 for Hong Kong Liver Cancer), the index of the OS nomo-gram was significantly higher. Moreover, the calibration curve fitted well between the predicted and observed survival rate. Similarly, in the validation set, the nomogram discrimination was superior to those of the four staging systems (p<0.001). Conclusions: The nomograms demonstrated good discrimi-nation performance in predicting 3- and 5-year survival rates for solitary HCCs after hepatectomy. (Gut Liver 2017;11:684- 692)
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