Descriptive Anatomy and Three-Dimensional Reconstruction of the Skull of the Early Tetrapod Acanthostega gunnari Jarvik, 1952

The early tetrapod Acanthostega gunnari is an iconic fossil taxon exhibiting skeletal morphology reflecting the transition of vertebrates from water onto land. Computed tomography data of two Acanthostega skulls was segmented using visualization software to digitally separate bone from matrix and individual bones of the skull from each other. A revised description of cranial and lower jaw anatomy in this taxon based on CT data includes new details of sutural morphology, the previously undescribed quadrate and articular bones, and the mandibular symphysis. Sutural morphology is used to infer loading regime in the skull during feeding, and suggests Acanthostega used its anterior jaws to initially seize prey while smaller posterior teeth were used to restrain struggling prey during ingestion. Novel methods were used to repair and retrodeform the skull, resulting in a three-dimensional digital reconstruction that features a longer postorbital region and more strongly hooked anterior lower jaw than previous attempts while supporting the presence of a midline gap between the nasals and median rostrals

A novel square-wave converter with bidirectional power flow

Author name used in this publication: K. W. E. ChengAuthor name used in this publication: D. SutantoVersion of RecordPublishe

Finite element analysis on piezoelectric ring transformer

2004-2005 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

Extra unit-speed machines are almost as powerful as speedy machines for flow time scheduling

We study online scheduling of jobs to minimize the flow time and stretch on parallel machines. We consider algorithms that are given extra resources so as to compensate for the lack of future information. Recent results show that a modest increase in machine speed can provide very competitive performance; in particular, using O(1) times faster machines, the algorithm SRPT (shortest remaining processing time) is 1-competitive for both flow time [C. A. Phillips et al., in Proceedings of STOC, ACM, New York, 1997, pp. 140-149] and stretch [W. T. Chan et al., in Proceedings of MFCS, Springer-Verlag, Berlin, 2005, pp. 236-247] and HDF (highest density first) is O(1)-competitive for weighted flow time [L. Becchetti et al., in Proceedings of RANDOM-APPROX, Springer-Verlag, Berlin, 2001, pp. 36-47]. Using extra unit-speed machines instead of faster machines to achieve competitive performance is more challenging, as a faster machine can speed up a job but extra unit-speed machines cannot. This paper gives a nontrivial relationship between the extra-speed and extra-machine analyses. It shows that competitive results via faster machines can be transformed to similar results via extra machines, hence giving the first algorithms that, using O(1) times unit-speed machines, are 1-competitive for flow time and stretch and O(1)-competitive for weighted flow time. © 2008 Society for Industrial and Applied Mathematics.published_or_final_versio

Superconducting self-resonant air-core transformer

Author name used in this publication: K. W. E. ChengAuthor name used in this publication: D. SutantoVersion of RecordPublishe

Examination of T8-T5 electronic ballast adaptor

Author name used in this publication: K. W. E. ChengRefereed conference paper2006-2007 > Academic research: refereed > Refereed conference paperVersion of RecordPublishe

Experimental demonstration of a fiber-optic gas sensor network addressed by FMCW

Author name used in this publication: H. L. HoAuthor name used in this publication: W. JinAuthor name used in this publication: M. S. DemokanAuthor name used in this publication: K. C. Chan2000-2001 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

Recognizing hyperelliptic graphs in polynomial time

Recently, a new set of multigraph parameters was defined, called "gonalities". Gonality bears some similarity to treewidth, and is a relevant graph parameter for problems in number theory and multigraph algorithms. Multigraphs of gonality 1 are trees. We consider so-called "hyperelliptic graphs" (multigraphs of gonality 2) and provide a safe and complete sets of reduction rules for such multigraphs, showing that for three of the flavors of gonality, we can recognize hyperelliptic graphs in O(n log n+m) time, where n is the number of vertices and m the number of edges of the multigraph.Comment: 33 pages, 8 figure

Study on magnetic materials used in power transformer and inductor

Author name used in this publication: K. W. E. ChengRefereed conference paper2006-2007 > Academic research: refereed > Refereed conference paperVersion of RecordPublishe

Dynamic dictionary matching and compressed suffix trees

Recent breakthrough in compressed indexing data structures has reduced the space for indexing a text (or a collection of texts) of length n from O(n log n) bits to O(n) bits, while allowing very efficient pattern matching. Yet the compressed nature of such indices also makes them difficult to update dynamically. This paper presents the first O(n)-bit representation of a suffix tree for a dynamic collection of texts whose total length is n, which supports insertion and deletion of a text T in O(|T| log2 n) time, as well as all suffix tree traversal operations, including forward and backward suffix links. This work can be regarded as a generalization of the compressed representation of static texts. Our new suffix tree representation serves as a core part in a compact solution for the dynamic dictionary matching problem, i.e., providing an O(d)-bit data structure for a dynamic collection of patterns of total length d that can support the dictionary matching query efficiently. When compared with the O(d log d)-bit suffix tree based solution of Amir et al., the compact solution increases the query time by roughly a factor of log d only. In the study of the above results, we also derive the first O(n)-bit representation for maintaining n pairs of balanced parentheses in O(log n/log log n) time per operation, matching the time complexity of the previous O(n log n)-bit solution.published_or_final_versio