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Displaying 1-9 out of 9 total
Prokaryote Phylogeny without Sequence Alignment: From Avoidance Signature to Composition Distance
Found in: Computational Systems Bioinformatics Conference, International IEEE Computer Society
By Bailin Hao, Ji Qi
Issue Date:August 2003
pp. 375
A new and essentially simple method to reconstruct prokaryotic phylogenetic trees from their complete genome data without using sequence alignment is proposed. It is based on the appearance frequency of oligopeptides of a fixed length (up to K = 6) in thei...
 
Robust head pose estimation via semi-supervised manifold learning with l
Found in: Biometrics, International Joint Conference on
By Hao Ji, Fei Su, Yujia Zhu
Issue Date:October 2011
pp. 1-6
In this paper, a new l
 
Design and Evaluation of an Efficient Semispace-based Memory Reclamation Scheme
Found in: Instrumentation, Measurement, Computer, Communication and Control, International Conference on
By Wu Hao,Ji Zhen-Zhou
Issue Date:October 2011
pp. 212-215
Now that in language with garbage collection (GC) mechanism such as Java, the GC should be a direct impact on the performance of the program, and the requirement of real time GC is even higher in a real-time system. We proposed a memory reclamation scheme ...
 
Incremental nonparametric discriminant analysis for robust object tracking
Found in: Multimedia and Expo, IEEE International Conference on
By Hao Ji, Fei Su, Yujia Zhu
Issue Date:July 2011
pp. 1-6
In this paper, a new adaptive subspace learning model based on incremental nonparametric discriminant analysis (INDA) is proposed for visual tracking. Traditional subspace trackers focus on updating eigenvectors in handling with appearance variation of the...
 
Design and Implementation of the Self-Test Module in Web Courses
Found in: Computers in Education, International Conference on
By Yu-Jin Zhang, Fan Jiang, Hao-Ji Hu, Dan Xu
Issue Date:December 2002
pp. 1092
This paper is focused on the design, development and implementation of self-test module and its question units. First, several general considerations in designing the self-test module for web course are introduced and discussed. The factors should be consi...
 
How to Efficiently Capture On-Chip Inductance Effects: Introducing a New Circuit Element K
Found in: Computer-Aided Design, International Conference on
By Anirudh Devgan, Hao Ji, Wayne Dai
Issue Date:November 2000
pp. 150
On-chip inductance extraction and analysis is becoming increasing critical. Inductance extraction can be difficult, cumbersome and impractical on large designs as inductance depends on the current return path - which is typically unknown prior to extractin...
 
SPICE Compatible Circuit Models for Partial Reluctance K
Found in: Asia and South Pacific Design Automation Conference
By Hao Ji, Qingjian Yu, Wayne Dai
Issue Date:January 2004
pp. 786-791
We are the first to develop SPICE compatible circuit model for partial reluctance K. It can be combined with any partial reluctance based extraction method to perform RLC simulation directly without the need of inverting partial reluctance matrix back into...
 
Biased metric learning for person-independent head pose estimation
Found in: Proceedings of the 19th ACM international conference on Multimedia (MM '11)
By Fei Su, Hao Ji
Issue Date:November 2011
pp. 969-972
In this paper, a new biased metric learning (BML) method is proposed for human head pose estimation problem. Traditional approaches focus on modeling a smooth low-dimensional manifold embedded in the high dimensional feature space. Such manifold-embedding ...
     
KSim: a stable and efficient RKC simulator for capturing on-chip inductance effect
Found in: Proceedings of the conference on Asia South Pacific Design Automation Conference (ASP-DAC '01)
By Anirudh Devgan, Hao Ji, Wayne Dai
Issue Date:January 2001
pp. 379-384
On-chip inductance extraction is difficult due to the global effect of inductance, and simulating the resulting dense partial inductance matrix is even more difficult. Furthermore, it is well known that simply discarding smallest terms to sparsify the indu...
     
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