105,301 research outputs found
Challenges in identifying and interpreting organizational modules in morphology
Form is a rich concept that agglutinates information about the proportions and topological arrangement of body parts. Modularity is readily measurable in both features, the variation of proportions (variational modules) and the organization of topology (organizational modules). The study of variational modularity and of organizational modularity faces similar challenges regarding the identification of meaningful modules and the validation of generative processes; however, most studies in morphology focus solely on variational modularity, while organizational modularity is much less understood. A possible cause for this bias is the successful development in the last twenty years of morphometrics, and specially geometric morphometrics, to study patters of variation. This contrasts with the lack of a similar mathematical framework to deal with patterns of organization. Recently, a new mathematical framework has been proposed to study the organization of gross anatomy using tools from Network Theory, soâcalled Anatomical Network Analysis (AnNA). In this essay, I explore the potential use of this new frameworkâand the challenges it faces in identifying and validating biologically meaningful modules in morphological systemsâby providing working examples of a complete analysis of modularity of the human skull and upper limb. Finally, I suggest further directions of research that may bridge the gap between variational and organizational modularity studies, and discuss how alternative modeling strategies of morphological systems using networks can benefit from each other
Segmenting broadcast news streams using lexical chains
In this paper we propose a course-grained NLP approach to text segmentation based on the
analysis of lexical cohesion within text. Most work in this area has focused on the discovery of textual
units that discuss subtopic structure within documents. In contrast our segmentation task requires the discovery of topical units of text i.e. distinct news stories from broadcast news programmes. Our system SeLeCT first builds a set of lexical chains, in order to model the discourse structure of the text. A boundary detector is then used to search for breaking points in this structure indicated by patterns of cohesive strength and weakness within the text. We evaluate this technique on a test set of concatenated CNN news story transcripts and compare it with an established statistical approach to segmentation called TextTiling
Rough Sets Clustering and Markov model for Web Access Prediction
Discovering user access patterns from web access log is increasing the importance of information to build up adaptive web server according to the individual userâs behavior. The variety of user behaviors on accessing information also grows, which has a great impact on the network utilization. In this paper, we present a rough set clustering to cluster web transactions from web access logs and using Markov model for next access prediction. Using this approach, users can effectively mine web log records to discover and predict access patterns. We perform experiments using real web trace logs collected from www.dusit.ac.th servers. In order to improve its prediction ration, the model includes a rough sets scheme in which search similarity measure to compute the similarity between two sequences using upper approximation
Complex Networks on a Rock Joint
A complex network approach on a rough fracture is developed. In this manner,
some hidden metric spaces (similarity measurements) between apertures profiles
are set up and a general evolutionary network in two directions (in parallel
and perpendicular to the shear direction) is constructed. Also, an algorithm
(COmplex Networks on Apertures: CONA) is proposed in which evolving of a
network is accomplished using preferential detachments and attachments of edges
(based on a competition and game manner) while the number of nodes is fixed.
Also, evolving of clustering coefficients and number of edges display similar
patterns as well as are appeared in shear stress, hydraulic conductivity and
dilation changes, which can be engaged to estimate shear strength distribution
of asperities.Comment: ROCKENG09: Proceedings of the 3rd CANUS Rock Mechanics Symposium,
Toronto, May 2009 (Ed: M.Diederichs and G. Grasselli
A Pattern Language for High-Performance Computing Resilience
High-performance computing systems (HPC) provide powerful capabilities for
modeling, simulation, and data analytics for a broad class of computational
problems. They enable extreme performance of the order of quadrillion
floating-point arithmetic calculations per second by aggregating the power of
millions of compute, memory, networking and storage components. With the
rapidly growing scale and complexity of HPC systems for achieving even greater
performance, ensuring their reliable operation in the face of system
degradations and failures is a critical challenge. System fault events often
lead the scientific applications to produce incorrect results, or may even
cause their untimely termination. The sheer number of components in modern
extreme-scale HPC systems and the complex interactions and dependencies among
the hardware and software components, the applications, and the physical
environment makes the design of practical solutions that support fault
resilience a complex undertaking. To manage this complexity, we developed a
methodology for designing HPC resilience solutions using design patterns. We
codified the well-known techniques for handling faults, errors and failures
that have been devised, applied and improved upon over the past three decades
in the form of design patterns. In this paper, we present a pattern language to
enable a structured approach to the development of HPC resilience solutions.
The pattern language reveals the relations among the resilience patterns and
provides the means to explore alternative techniques for handling a specific
fault model that may have different efficiency and complexity characteristics.
Using the pattern language enables the design and implementation of
comprehensive resilience solutions as a set of interconnected resilience
patterns that can be instantiated across layers of the system stack.Comment: Proceedings of the 22nd European Conference on Pattern Languages of
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