947674
Visual exploration of genetic likelihood space
Linkage analysis is used to localize human disease genes on the genome and it can involve the exploration and interpretation of a seven-dimensional genetic likelihood space. Existing genetic likelihood exploration techniques are quite cumbersome and slow, and do not help provide insight into the shape and features of the high-dimensional likelihood surface. The objective of our visualization is to provide an efficient visual exploration of the complex genetic likelihood space so that researchers can assimilate more information in the least possible time. In this paper, we present new visualization tools for interactive and efficient exploration of the multi-dimensional likelihood space. Our tools provide interactive manipulation of active ranges of the six model parameters determining the dependent variable, scaled genetic likelihood, or HLOD. Using filtering, color, and an approach inspired by "worlds-within-worlds" [5, 6], researchers can quickly obtain a more informative and insightful visual interpretation of the space.
36445748
InCore: Accounting and Charging Heterogeneous Unix Systems
9747098
A Selection Algorithm with a Practical Upper Bound on Expected Number
A selection algorithm to find the Irth smallest element of a elements is presented. The algorithm mainly consists of the partition procedure and an improved method to choose a partitioning element. The algorithm estimates the partitioning element from a small sample so that the icth element is contained in the smaller partition between two partitions resulting from partitioning. The partitioning element is determined by using estimation of the cumulative frequency distribution in the theory of non-parametric statistics. The expected number of comparisons is found to be n + min(k, n-k) + O(n2/3) through experimental tests where the sample size is approximately n2/3. The experimental results show that the performance of the algorithm is improved, compared to the two known selection algorithms, particularly when the selection index is near to the median.
17114395
Efficient multicast stream authentication using erasure codes
We describe a novel method for authenticating multicast packets that is robust against packet loss. Our focus is to minimize the size of the communication overhead required to authenticate the packets. Our approach is to encode the hash values and the signatures with Rabin's Information Dispersal Algorithm (IDA) to construct an authentication scheme that amortizes a single signature operation over multiple packets. This strategy is especially efficient in terms of space overhead, because just the essential elements needed for authentication (i.e., one hash per packet and one signature per group of packets) are used in conjunction with an erasure code that is space optimal. Using asymptotic techniques, we derive the authentication probability of our scheme using two different bursty loss models. A lower bound of the authentication probability is also derived for one of the loss models. To evaluate the performance of our scheme, we compare our technique with four other previously proposed schemes using empirical results.
16813459
Scenario-based multitasking for real-time object-oriented models
Abstract Contemporary embedded systems quite often employ extremely complicated software consisting of a number of interrelated components, and this has made object-oriented design methodologies widely used in practice. To implement an object-oriented model in given target hardware, it is imperative to derive a set of tasks from the designed objects. This process of determining tasks and the events they handle greatly influences the real-time performance of the resultant system including response times and real-time guarantees. However, the innate discrepancies between objects and tasks make this exceedingly difficult, and many developers are forced to find their task sets through trial and error. In this paper, we propose Scenario-based Implementation Synthesis Architecture (SISA), an architecture consisting of a method for deriving a task set from a given object-oriented model and the development tools and run-time system architecture to support the method. A system developed with SISA guarantees the optimal response time for each event while deriving the smallest possible number of tasks. We have fully implemented SISA by extending the RoseRT development tool and applied it to an existing industrial PBX (private branch exchange) system. The experimental results show that SISA outperforms the best known conventional techniques by reducing maximum response times an average of 30.3%.
5761929
Dual-beam structured-light scanning for 3-D object modeling
In this paper we present our Dual-Beam Structured-Light Scanner (DSLS), a scanning system that generates range maps much richer than those obtained from a conventional structured-light scanning system. Range maps produced by DSLS require fewer registrations for 3-D modeling. We show that the DSLS system more easily satisfies what are often difficult-to-satisfy conditions for determining the 3-D coordinates of an arbitrary object point. Two specific advantages of DSLS over conventional structured-light scanning are: (1) A single scan by the DSLS system is capable of generating range data on more surfaces than possible with the conventional approach using the same number of camera images. And (2) since the data collected by DSLS is more free of self-occlusions, the object needs be examined from a smaller number of viewpoints.
14381469
Using lexical similarity in handwritten word recognition
Recognition using only visual evidence cannot always be successful due to limitations of information and resources available during training. Considering relation among lexicon entries is sometimes useful for decision making. In this paper we present a method to capture lexical similarity of a lexicon and reliability of a character recognizer which serve to capture the dynamism of the environment. A parameter, lexical similarity, is defined by measuring these two factors as edit distance between lexicon entries and separability of each character's recognition results. Our experiments show that a utility function considering lexical similarity in a decision stage can enhance the performance of a conventional word recognizer.