6543572
Findings from Observational Studies of Collaborative Work
Abstract The work activity of small groups of three to four people was videotaped and analysed in order to understand collaborative work and to guide the development of tools to support it. The analysis focused on the group's shared drawing activity—their listing, drawing, gesturing and talking around a shared drawing surface. This analysis identified specific features of collaborative work activity that raise design implications for collaborative technology: (1) collaborators use hand gestures to uniquely communicate significant information; (2) the process of creating and using drawings conveys much information not contained in the resulting drawings; (3) the drawing space is an important resource for the group in mediating their collaboration; (4) there is a fluent mix of activity in the drawing space; and (5) the spatial orientation among the collaborators and the drawing space has a role in structuring their activity. These observations are illustrated with examples from the video data, and the design implications they raise are discussed.
215951331
Videodraw: a video interface for collaborative drawing
357440
Scaling up accurate phylogenetic reconstruction from gene-order data
MOTIVATION
Phylogenetic reconstruction from gene-order data has attracted increasing attention from both biologists and computer scientists over the last few years. Methods used in reconstruction include distance-based methods (such as neighbor-joining), parsimony methods using sequence-based encodings, Bayesian approaches, and direct optimization. The latter, pioneered by Sankoff and extended by us with the software suite GRAPPA, is the most accurate approach, but cannot handle more than about 15 genomes of limited size (e.g. organelles).


RESULTS
We report here on our successful efforts to scale up direct optimization through a two-step approach: the first step decomposes the dataset into smaller pieces and runs the direct optimization (GRAPPA) on the smaller pieces, while the second step builds a tree from the results obtained on the smaller pieces. We used the sophisticated disk-covering method (DCM) pioneered by Warnow and her group, suitably modified to take into account the computational limitations of GRAPPA. We find that DCM-GRAPPA scales gracefully to at least 1000 genomes of a few hundred genes each and retains surprisingly high accuracy throughout the range: in our experiments, the topological error rate rarely exceeded a few percent. Thus, reconstruction based on gene-order data can now be accomplished with high accuracy on datasets of significant size.
46493478
QoS-Driven Asynchronous Uplink Subchannel Allocation Algorithms for Space-Time OFDM-CDMA Systems in Wireless Networks
In order to support the diverse quality of service (QoS) requirements for differentiated data applications in broadband wireless networks, advanced techniques such as space-time coding (STC) and orthogonal frequency division multiplexing (OFDM) are implemented at the physical layer. However, the employment of such techniques evidently affects the subchannel-allocation algorithms at the medium access control (MAC) layer. In this paper, we propose the QoS-driven cross-layer subchannel-allocation algorithms for data transmissions over asynchronous uplink space-time OFDM-CDMA systems. We mainly focus on QoS requirements of maximizing the best-effort throughput and proportional bandwidth fairness, while minimizing the upper-bound of scheduling delay. Our extensive simulations show that the proposed infrastructure and algorithms can achieve high bandwidth fairness and system throughput while reducing scheduling delay over wireless networks.
1134742
Improving Tree Search in Phylogenetic Reconstruction from Genome Rearrangement Data
A major task in evolutionary biology is to determine the ancestral relationships among the known species, a process generally referred as phylogenetic reconstruction. In the past decade, a new type of data based on genome rearrangements has attracted increasing attention from both biologists and computer scientists. Methods for reconstructing phylogeny based on genome rearrangement data include distance-based methods, direct optimization methods (GRAPPA and MGR), and Markov Chain Monte Carlo (MCMC) methods (Badger). Extensive testing on simulated and biological datasets showed that the latter three methods are currently the best methods for genome rearrangement phylogeny. However, all these tools are dealing with extremely large searching spaces; the total number of possible trees grows exponentially when the number of genomes increases and makes it computationally very expensive. Various heuristics are used to explore the tree space but with no guarantee of optimum being found. In this paper, we present a new method to efficiently search the large tree space. This method is motivated by the concept of particle filtration (also known as Sequential Monte Carlo), which was originally proposed to boost the efficiency of MCMC methods on massive data. We tested and compared this new method on simulated datasets in different scenarios. The results show that the new method achieves a significant improvement in efficiency, while still retains very high topological accuracy.
4332072
A Component Retrieval Method Based on Facet-Weight Self-learning
Component-based development method has been a new software development paradigm. How to get the needed components quickly and accurately is one of the basic problems about reusing software component automatically. In this paper, an intelligent component retrieval model – FWRM. is proposed. Facet presentation is used to model query and component. Multiple types of facets are defined which extends traditional keyword-based facet presentation. Genetic algorithm based facet weight self-learning algorithm can change the facet weight dynamically in order to improve retrieval accuracy. Corresponding similarity functions are defined also. In addition, risk minimization-based component sampling method is used to solve the insufficiency of training data. All these algorithms and methods are integrated into FWRM’s three main implementation parts: Facet-Weight Optimize System, Component Retrieve System and Resource. The experimental results prove that this method is feasible and can improve component retrieval effectively.
27349578
On multilevel voting
SummaryIn a distributed system mutual exclusion is often used to maintain consistency when restricted operations are performed. Mechanisms guaranteeing mutual exclusions should be both resilient and efficient. Resiliency implies high resource availability in the face of failures, while efficiency implies low overhead incurred by performing restricted operations. In this paper, we propose and study a general paradigm, called multilevel voting, which provides a general framework to assist in the design of resilient and efficient mutual exclusion mechanisms. The proposed method uses multiple level quorum consensus. Unlike another method based on the use of multiple quorum consensus, the proposed model only contains one type of integrity constraints. This has the benefit of being conceptually simple and easy to reason about. The strong resemblance with the traditional quorum consensus makes it easy for the proposed paradigm to embed any technique based on traditional quorum schemes. We show that the proposed model represents the exact class of coteries. This means that not only does it have all the power of coteries, but also all schemes under the model are correct. Thus, should the need arise, we can interchange two schemes freely without using any extra mechanisms to ensure correctness. We study a number of issues that have impact on performance such as the degree of a multilevel scheme and the order of a coterie. We explain how the model can be extended also to model the schemes for the synchronization of read and write of replicated data. We provide algorithms for the design of multilevel schemes in the context of mutual exclusion and that of read and write of replicated data.