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Data mapping among different data standards in health institutes is often a necessity when data exchanges occur among different institutes. However, no matter rule-based approaches or traditional machine learning methods, none of these methods have achieved satisfactory results yet. In this work, we propose a deep learning method, mixture feature embedding convolutional neural network (MfeCNN), to...
Under-bump metallization Rc is a critical metric for high-density interconnect in electronic devices. We developed a test vehicle to characterize the impact of unit processes on Rc for 10-$\mu \text{m}$ polymer passivation opening. We demonstrate that advanced preclean is necessary to achieve low (Rc < 20 $\text{m}\Omega$ ) for future node extendibility, owing to reduction of both Al oxide and...
Nowadays, RFID systems have been widely deployed for applications such as supply chain management and inventory control. One of their most essential operations is to swiftly identify individual tags to distinguish their associated objects. Most existing solutions identify tags sequentially in the temporal dimension to avoid signal collisions, whose performance degrades significantly as the system...
Objective To research and implement converting HL7 Version 2.x medical messages ER7 (Encoding Rules 7) standard format to XML format and vice versa. Methods By parsing HL7 message structure, using HAPI as supportive toolkit and based on object-oriented programming, format conversion of the medical information message is accomplished. Results Lots of HL7 messages such as patient demographic information,...
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