科研成果 by Type: Conference Paper

2016
Zhang M, Zhu F, Qu T, Wu X. An asynchronous HRTF measurement method based on phase alignment, in Proceedings of the 22nd International Congress on Acoustics. Buenos Airs, Argentina; 2016:342.
Wang Y, Xu C, You S, Xu C, Tao D. CNNpack: Packing Convolutional Neural Networks in the Frequency Domain, in NeurIPS.; 2016.
Zhang Y. Y., Jin Z. J., Sun Z. D. The Comparison between Full-stack Data and Pure P-wave Data on Deeply Buried Ordovician Paleokarst Reservoir Prediction, in 78th EAGE Expanded Abstract.; 2016. 访问链接
Wang Y, LIU Y, JIANG M, JIA S, Zhang X. Delay-locked loop based frequency quadrupler with wide operating range and fast locking characteristics, in IEEE International Symposium on Circuits and Systems (ISCAS). Montreal, Canada; 2016:1-4.
Hu X, Li B, Zhang Y, Zhou C, Ma H. Detecting compromised email accounts from the perspective of graph topology, in Proceedings of the 11th International Conference on Future Internet Technologies. ACM; 2016:76–82.
Zhang K, Gu Y. Dynamic Behaviour and Phase Change of Rising Supercritical CO2 Bubbles in a Vertical Capillary Tube Filled with a Light Crude Oil, in ; 2016.
Jia J, Chen Z. The Effect of Smart Phones' Application in Regular University English Class on Students' Learning Performance, in Proceedings - 2015 International Conference of Educational Innovation Through Technology, EITT 2015.; 2016:131-136. 访问链接
Zhang C, Wu D, Sun J, Sun G, Luo G, Cong J. Energy-Efficient CNN Implementation on a Deeply Pipelined FPGA Cluster, in Proceedings of the 2016 International Symposium on Low Power Electronics and Design - ISLPED '16. New York, New York, USA: ACM Press; 2016:326–331. 访问链接
Li J, Tan Y. Enhancing interaction in the fireworks algorithm by dynamic resource allocation and fitness-based crowdedness-avoiding strategy, in 2016 IEEE Congress on Evolutionary Computation (CEC). IEEE; 2016:4015–4021. 访问链接
Huang Z, Gao S, Qu T, Li L, Wu X. An environment adaptive loudspeaker calibration method for Ambisonics decoding system, in the 5th International Conference on Audio, Language and Image Processing. Shanghai, China; 2016:277.
Xing Y(Master student), Fu Z, Wu X, Chen J *. Evaluation of Apple iOS-based automated audiometry, in 22nd International Congress on Acoustics. La Plate, Argentina; 2016.
Jia T, Fan Y, Joseph R, Gu J. Exploration of associative power management with instruction governed operation for ultra-low power design, in Design Automation Conference (DAC).; 2016.
Pi Y, Wang N, Zhang J, Wang W, Luo G, Miao M, Xu W, Jin Y. A Fast and Low Computation Consumption Model for System-Level Thermal Management in 3D IC, in 2016 IEEE 66th Electronic Components and Technology Conference (ECTC). IEEE; 2016:1933–1939. 访问链接
Sun Q, Yang C, Wu C, Li L, Liu F. Fast parallel stream compaction for IA-based multi/many-core processors, in Proc. 16th IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing (CCGrid'16). IEEE; 2016:736–745. 访问链接
Yang T, Liu AX, Fu Q, Yang D, Uhlig S, Li X. Fit the elephant in a box-towards IP lookup at on-chip memory access speed, in IEEE ICNP poster.; 2016.
Xu J, Fu H, Gan L, Yang C, Xue W, Xu S, Zhao W, Wang X, Chen B, Yang G. Generalized GPU acceleration for applications employing finite-volume methods, in Proc. 16th IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing (CCGrid'16). IEEE; 2016:126–135. 访问链接
Luo F, Wang S, Zhang N, Ma S, Gao W. GPU based sample adaptive offset parameter decision and perceptual optimization for HEVC, in IEEE International Symposium on Circuits and Systems, ISCAS 2016, Montréal, QC, Canada, May 22-25, 2016.; 2016:2687–2690. 访问链接
Hu Y. Harvesting the hidden energy for self-powered systems, in Nanotechnology (IEEE-NANO), 2016 IEEE 16th International Conference on. IEEE; 2016:928–930.
Makar PA, Stroud C, Zhang J, Moran M, Akingunola A, Gong W, Gravel S, Pabla B, Cheung P, Zheng Q, et al. High Resolution Model Simulations of the Canadian Oil Sands with Comparisons to Field Study Observations, in AIR POLLUTION MODELING AND ITS APPLICATION XXIV.; 2016:503-508.Abstract
The governments of Canada and Alberta are implementing a joint plan for oil sands monitoring that includes investigating emissions, transport and downwind chemistry associated with the Canadian oil sands region. As part of that effort, Environment Canada's Global Environmental Multiscale-Modelling Air-quality And CHemistry (GEM-MACH) system was reconfigured for the first time to create nested forecasts of air quality at model grid resolutions down to 2.5 km, with the highest resolution domain including the Canadian provinces of Alberta and Saskatchewan. The forecasts were used to direct an airborne research platform during a summer 2013 monitoring intensive. Subsequent work with the modelling system has included an in-depth comparison of the model predictions to monitoring network observations, and to field intensive airborne and surface supersite observations. A year of model predictions and monitoring network observations were compared, as were model and aircraft flight track values. The relative impact of different model versions (including modified emissions and feedbacks between weather and air pollution) will be discussed. Model-based predictions of indicators of human-health (i.e., Air Quality Health Index) and ecosystem (i.e. deposition of pollutants) impacts for the region will also be described.
Zhang P, Liu C, Hansen P. I Need More Time!: The Influence of Native Language on Search Behavior and Experience., in CLEF (Working Notes).; 2016:1166–1182.

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