Graph data structures and algorithms play an essential role in computer science, and one of the ultimate goals of learning graphs is to solve more complicated algorithm design problems with them. A common way to solve...
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Sorting any m target suffixes of an input string X of n characters from a constant alphabet is a key task for building the sparse suffix array SSA(X) for index construction. A number of probabilistic and deterministic...
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Sorting any m target suffixes of an input string X of n characters from a constant alphabet is a key task for building the sparse suffix array SSA(X) for index construction. A number of probabilistic and deterministic algorithms have been proposed for sorting sparse suffixes with varying time and space complexities, but only some experimental results are available for performance evaluation of these algorithms. We design a divide-and-conquer algorithm called sSAIS for computing SSA(X) in O(n log m log(n/m)) time and O(m) workspace by using the induced sorting principle, and conduct an experimental performance study on real and artificial datasets. This work reveals that to design an efficient deterministic algorithm for sorting sparse suffixes is a tough challenge and the density of target suffixes might be considered as a critical design parameter.
A unified processing approach for the detection and localization of satellites or other exoatmospheric targets is presented. Enhanced filtering and centroid determination algorithms were developed based on real-time i...
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A unified processing approach for the detection and localization of satellites or other exoatmospheric targets is presented. Enhanced filtering and centroid determination algorithms were developed based on real-time implementation constraints, mission conditions including accuracy requirements, and signature structure. The signature structure consisted of target returns, high-frequency random noise, low-frequency structured noise, and contamination sources resulting from debris and cosmic events. Detailed signal processing analyses were performed to verify the required subsample accuracy and the sensitivity to hardware and system constraints. The resultant system design was functionally verified in a real-time breadboard processor.
With the aid of information communications technology, telemedicine can break the limitation of physical space, which has a promising future. Nowadays, there are numerous telemedicine systems, but most of them lack th...
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ISBN:
(纸本)9781538665800
With the aid of information communications technology, telemedicine can break the limitation of physical space, which has a promising future. Nowadays, there are numerous telemedicine systems, but most of them lack the active interaction with users. Under this background, based on data mining, we construct push service for telemedicine system, which includes disease differentiation, doctor recommendation and diagnosis prediction, and design k-nearest neighbor classification, nearest neighbor recommendation and FP-growth as main algorithms of them respectively. Moreover, we carry out an empirical research by using data from a public Chinese telemedicine system.
algorithm design usually has two ways to approach, deducing from a theory or inducing from practice. Many of algorithms for image processing were induced from practice. This paper will show how anew algorithm for medi...
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ISBN:
(纸本)1932415432
algorithm design usually has two ways to approach, deducing from a theory or inducing from practice. Many of algorithms for image processing were induced from practice. This paper will show how anew algorithm for medical image processing could be induced in a Matlab environment[1]. As an example, a new segmentation approach based on image algebraic operations for cryosection image background removing has been designed, implemented and tested by Matlab in a short time, which has showed that the Matlab Image Processing Toolbox from Math Works is an effective and easy been mastered tool for image processing algorithm design.
Active optics is an enabling technology for future large space telescopes. Image-based wavefront control uses an image-sharpness metric to evaluate the optical performance. A control algorithm iteratively adapts a cor...
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ISBN:
(纸本)9781510619289
Active optics is an enabling technology for future large space telescopes. Image-based wavefront control uses an image-sharpness metric to evaluate the optical performance. A control algorithm iteratively adapts a corrective element to maximize this metric, without reconstructing the wavefront. We numerically study a sharpness metric in the space of Zernike modes, and reveal that for large aberrations the Zernike modes are not orthogonal with respect to this metric. The findings are experimentally verified by using a unimorph deformable mirror as corrective element. We discuss the implications for the correction process and the design of control algorithms.
The concept of Pareto optimality is applied to the study of choice tradeoffs between reflectivity and thickness in the design of multilayer microwave absorbers, Absorbers composed of a given number of layers of absorb...
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The concept of Pareto optimality is applied to the study of choice tradeoffs between reflectivity and thickness in the design of multilayer microwave absorbers, Absorbers composed of a given number of layers of absorbing materials selected from a predefined database of available materials are considered. Three types of Pareto genetic algorithms for absorber synthesis are introduced and compared to each other, as well as to methods operating with the weighted Tchebycheff method for Pareto optimization. The Pareto genetic algorithms are applied to construct Pareto fronts for microwave absorbers with five layers of materials selected from a representative database of available materials in the 0.2-2 GHz, 2-8 GHz, and 9-11 GHz bands.
K-mer can be used for the description of biological sequences and k-mer distribution is a tool for solving sequences analysis problems in *** can use k-mer vector as a representation method of the k-mer distribution o...
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K-mer can be used for the description of biological sequences and k-mer distribution is a tool for solving sequences analysis problems in *** can use k-mer vector as a representation method of the k-mer distribution of the biological ***,such as similarity calculations or sequence assembly,can be described in the k-mer vector *** helps us to identify new features of an old sequence-based problem in bioinformatics and develop new algorithms using the concepts and methods from linear space *** this study,we defined the k-mer vector space for the generalized biological *** meaning of corresponding vector operations is explained in the biological *** presented the vector/matrix form of several widely seen sequence-based problems,including read quantification,sequence assembly,and pattern detection *** advantages and disadvantages are ***,we implement a tool for the sequence assembly problem based on the concepts of k-mer vector *** shows the practicability and convenience of this algorithm design strategy.
Towards building a systematic methodology of algorithm design for applications of networked sensor systems, we formally define two link-wise communication models, the Collision Free Model (CFM) and the Collision Aware...
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Towards building a systematic methodology of algorithm design for applications of networked sensor systems, we formally define two link-wise communication models, the Collision Free Model (CFM) and the Collision Aware Model (CAM). While CFM provides ease of programming and analysis for high level application functionality, CAM enables more accurate performance analysis and hence more efficient algorithms through cross-layer optimization, at the expense of increased programming and analysis complexity. These communication models are part of an abstract network model, above which algorithm design and performance optimization is performed. We use the example of optimizing a probability based broadcasting scheme under CAM to illustrate algorithm optimization based on the defined models. Specifically, we present an analytical framework that facilitates an accurate modeling and analysis for the probability based broadcasting in CAM (PB_CAM). Our analytical results indicate that (1) the optimal broadcast probability for either maximizing the reachability within a given latency constraint or minimizing the latency for a given reachability constraint decreases rapidly with node density, and (2) the optimal probability for either maximizing the reachability with a given energy constraint or minimizing the energy cost for a given reachability constraint varies slowly between 0 and 0.1 over the entire range of the variations in node density. Our analysis is also confirmed by extensive simulation results. (C) 2005 Elsevier B.V. All rights reserved.
The analysis and execution of partial algorithm descriptions is an important element of the algorithm design process. A language for representing partially designed algorithms and a process called developmental evalu...
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The analysis and execution of partial algorithm descriptions is an important element of the algorithm design process. A language for representing partially designed algorithms and a process called developmental evaluation are described that can disclose useful knowledge to guide design. A system called designER is constructed that automatically designs algorithms. Developmental evaluation is compared to execution and analysis techniques used for testing complete programs and for validation of abstract specifications. Concepts similar to those found in developmental evaluation are thus shown to be applicable to all periods of the software life cycle. It is claimed that, in uncovering opportunities for refinement of a data-flow algorithm representation, developmental evaluation is the primary method guiding design in the absence of specific control knowledge.
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