A 0.1-pJ/b/dB 1.62-to-10.8-Gb/s Video Interface Receiver With Jointly Adaptive CTLE and DFE Using Biased Data-Level Reference

2020 ◽  
Vol 55 (8) ◽  
pp. 2186-2195
Author(s):  
Jinhyung Lee ◽  
Kwangho Lee ◽  
Hyojun Kim ◽  
Byungmin Kim ◽  
Kwanseo Park ◽  
...  
Keyword(s):  
2014 ◽  
Vol 33 (4) ◽  
pp. 221-245 ◽  
Author(s):  
Alexander Kogan ◽  
Michael G. Alles ◽  
Miklos A. Vasarhelyi ◽  
Jia Wu

SUMMARY: This study develops a framework for a continuous data level auditing system and uses a large sample of procurement data from a major health care provider to simulate an implementation of this framework. In this framework, the first layer monitors compliance with deterministic business process rules and the second layer consists of analytical monitoring of business processes. A distinction is made between exceptions identified by the first layer and anomalies identified by the second one. The unique capability of continuous auditing to investigate (and possibly remediate) the identified anomalies in “pseudo-real time” (e.g., on a daily basis) is simulated and evaluated. Overall, evidence is provided that continuous auditing of complete population data can lead to superior results, but only when audit practices change to reflect the new reality of data availability. Data Availability: The data are proprietary. Please contact the authors for details.


2021 ◽  
Vol 554 ◽  
pp. 157-176
Author(s):  
Zhi Chen ◽  
Jiang Duan ◽  
Li Kang ◽  
Guoping Qiu

2021 ◽  
Vol 30 ◽  
pp. 458-471
Author(s):  
Xuehao Wang ◽  
Shuai Li ◽  
Chenglizhao Chen ◽  
Yuming Fang ◽  
Aimin Hao ◽  
...  

2015 ◽  
Vol 31 (2) ◽  
pp. 231-247 ◽  
Author(s):  
Matthias Schnetzer ◽  
Franz Astleithner ◽  
Predrag Cetkovic ◽  
Stefan Humer ◽  
Manuela Lenk ◽  
...  

Abstract This article contributes a framework for the quality assessment of imputations within a broader structure to evaluate the quality of register-based data. Four quality-related hyperdimensions examine the data processing from the raw-data level to the final statistics. Our focus lies on the quality assessment of different imputation steps and their influence on overall data quality. We suggest classification rates as a measure of accuracy of imputation and derive several computational approaches.


2010 ◽  
Vol 7 (1) ◽  
pp. 189-200 ◽  
Author(s):  
Haitao Wei ◽  
Yu Junqing ◽  
Li Jiang

As a video coding standard, H.264 achieves high compress rate while keeping good fidelity. But it requires more intensive computation than before to get such high coding performance. A Hierarchical Multi-level Parallelisms (HMLP) framework for H.264 encoder is proposed which integrates four level parallelisms - frame-level, slice-level, macroblock-level and data-level into one implementation. Each level parallelism is designed in a hierarchical parallel framework and mapped onto the multi-cores and SIMD units on multi-core architecture. According to the analysis of coding performance on each level parallelism, we propose a method to combine different parallel levels to attain a good compromise between high speedup and low bit-rate. The experimental results show that for CIF format video, our method achieves the speedup of 33.57x-42.3x with 1.04x-1.08x bit-rate increasing on 8-core Intel Xeon processor with SIMD Technology.


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