This paper demonstrates a high-efficiency modular multilevel resonant DC-DC converter (MMRC) with zero-voltage switching (ZVS) capability. In order to minimize the conduction loss in the converter, optimizing the root-mean-square (RMS) current flowing through switching devices is considered an effective approach. The analysis of circuit configuration and operating principle show that the RMS value of the current flowing through switching devices is closely related to the factors such as the resonant tank parameters, switching frequency, converter output voltage and current, etc. A quantitative analysis that considers all these factors has been performed to evaluate the RMS current of all the components in the circuit. When the circuit parameters are carefully designed, the switch current waveform can be close to the square waveform, which has a low RMS value and results in low conduction loss. And a design example based on the theoretical analysis is presented to show the design procedures of the presented converter. A 600 W 48 V-to-12 V prototype is built with the parameters obtained from the design example section. Simulation and experiments have been performed to verify the high-efficiency feature of the designed converter. The measured converter peak efficiency reaches 99.55% when it operates at 200 kHz. And its power density can be as high as 795 W/in 3 .
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Accurate, Fast, But Not Always Cheap: Evaluating “Crowdcoding” as an Alternative Approach to Analyze Social Media Data
Crowdcoding, a method that outsources “coding” tasks to numerous people on the internet, has emerged as a popular approach for annotating texts and visuals. However, the performance of this approach for analyzing social media data in the context of journalism and mass communication research has not been systematically assessed. This study evaluated the validity and efficiency of crowdcoding based on the analysis of 4,000 tweets about the 2016 U.S. presidential election. The results show that compared with the traditional quantitative content analysis, crowdcoding yielded comparably valid results and was superior in efficiency, but was more expensive under most circumstances.
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- Award ID(s):
- 1838193
- NSF-PAR ID:
- 10204906
- Date Published:
- Journal Name:
- Journalism & Mass Communication Quarterly
- Volume:
- 97
- Issue:
- 3
- ISSN:
- 1077-6990
- Page Range / eLocation ID:
- 811 to 834
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1177/1077699019891437
