A large proportion of publications in the field of evolutionary computation describe algorithm specialisation and experimentation. algorithms are variously described using text, tables, flowcharts, functions or pseudo...
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ISBN:
(纸本)9781450305570
A large proportion of publications in the field of evolutionary computation describe algorithm specialisation and experimentation. algorithms are variously described using text, tables, flowcharts, functions or pseudocode. However, ambiguity that can limit the efficiency of communication is common. Evolutionary System Definition Language (ESDL) is a conceptual model and language for describing evolutionary systems efficiently and with reduced ambiguity, including systems with multiple populations and adaptive parameters. ESDL may also be machine-interpreted, allowing algorithms to be tested without requiring a hand-coded implementation, as may already be done using the esec framework. The style is distinct from existing notations used within the field and is easily recognisable. This paper describes the case for ESDL, provides an overview of ESDL and examples of its use.
We consider the quantum query model for computing Boolean functions. The definition of the function is known, but a black box contains the input X=(x(1), x(2), ..., x(n)). Black box can be accessed by querying xi valu...
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ISBN:
(纸本)9781424481262
We consider the quantum query model for computing Boolean functions. The definition of the function is known, but a black box contains the input X=(x(1), x(2), ..., x(n)). Black box can be accessed by querying xi values. The goal is to develop an algorithm, which would compute the function value for arbitrary input using as few queries to the black box as possible. We present two different quantum query algorithms for computing the basic Boolean function - logical AND of two bits. Both algorithms use only one query to determine the function value. Correct answer probability for the first algorithm is 80%, but for the second algorithm it is 90%. To compute this function with the same probability in the classical model, two queries are necessary. We analyze algorithms implementation differences and propose a way to extend the first algorithm to compute AND of two functions.
Automatic dietary monitoring (ADM) offers new perspectives to reduce the self-reporting burden for participants in diet coaching programs. This paper presents an approach to predict weight of individual bites taken. W...
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Automatic dietary monitoring (ADM) offers new perspectives to reduce the self-reporting burden for participants in diet coaching programs. This paper presents an approach to predict weight of individual bites taken. We utilize a pattern recognition procedure to spot chewing cycles and food type in continuous data from an ear-pad chewing sound sensor. The recognized information is used to predict bite weight. We present our recognition procedure and demonstrate its operation on a set of three selected foods of different bite weights. Our evaluation is based on chewing sensor data of eight healthy study participants performing 504 habitual bites in total. The sound-based chewing recognition achieved recalls of 80% at 60%-70% precision. Food classification of chewing sequences resulted in an average accuracy of 94%. In total, 50 variables were derived from the chewing microstructure, and were analyzed for correlations between chewing behavior and bite weight. A subset of four variables was selected to predict bite weight using linear food-specific models. Mean weight prediction error was lowest for apples (19.4%) and largest for lettuce (31%) using the sound-based recognition. We conclude that bite weight prediction using acoustic chewing recordings is a feasible approach for solid foods, and should be further investigated.
Being numerous, the insect and disease pests were organized within classifications described as a dendriform hierarchical (tree-shape) structure The data of the structure were managed by database management system (DB...
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ISBN:
(纸本)9780769535708
Being numerous, the insect and disease pests were organized within classifications described as a dendriform hierarchical (tree-shape) structure The data of the structure were managed by database management system (DBMS), tables were designed to store the information about the species/category and related characteristics The characteristics were related to the species/category to construct a junction/x-ref table as the knowledge base of the expert system for insect and disease pest identification, including sets of identification characteristics for all species/category in the table Relational calculus was employed to estimate the potential species/category of the insect and disease pests in relation to inclusion of the set of characters selected by users and the sets of identification characteristics in the knowledge base of the system The system can be used as an open and flexible platform for professional users involved in plant protection to establish new expert application systems that provide pest identification services for common agricultural users
Our earlier paper introduced a parallel scheduling problem where a directed acyclic graph modeling t tasks and their dependencies needs to be executed on n unreliable workers. Worker i executes task j correctly with p...
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ISBN:
(纸本)9780898716108
Our earlier paper introduced a parallel scheduling problem where a directed acyclic graph modeling t tasks and their dependencies needs to be executed on n unreliable workers. Worker i executes task j correctly with probability p(i,j). The goal is to find a regimen Sigma, that dictates how workers get assigned to tasks (possibly in parallel and redundantly) throughout execution, to minimize the expected completion time. The paper provided a polynomial time algorithm for the problem restricted to the case when dag width and the number of workers are at most a constant, and showed necessity of these restrictions, unless P=NP. The current paper describes algorithm engineering approaches used to produce an efficient implementation of the algorithm, and experiments demonstrating how the algorithm scales.
This paper demonstrates implementation of some CDMA system compatible antenna array algorithms namely LMS and space code correlator (SCC) on an FPGA. A comparative study of FPGA and DSP implementation issues such as a...
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ISBN:
(纸本)9781424403974
This paper demonstrates implementation of some CDMA system compatible antenna array algorithms namely LMS and space code correlator (SCC) on an FPGA. A comparative study of FPGA and DSP implementation issues such as architecture complexity and weight vector computation time is also given. The implementations of the algorithms are performed on Xilinx Virtex 11 Pro FPGA and Texas Instruments (TI) TMS320C67x floating-point DSP platforms. For the signal modeling, cdma2000 reverse link signal model is considered for uniform linear array topology and varying multipath propagation conditions. Results show that the both algorithms, which were implemented on Xilinx XC2VP4 and TMS320C6713 DSP, provides weight vector computation time smaller than 10 ms period.
In the literature on generalized pattern search algorithms, convergence to a stationary point of a once continuously differentiable cost function is established under the assumption that the cost function can be evalu...
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In the literature on generalized pattern search algorithms, convergence to a stationary point of a once continuously differentiable cost function is established under the assumption that the cost function can be evaluated exactly. However, there is a large class of engineering problems where the numerical evaluation of the cost function involves the solution of systems of differential algebraic equations. Since the termination criteria of the numerical solvers often depend on the design parameters, computer code for solving these systems usually defines a numerical approximation to the cost function that is discontinuous with respect to the design parameters. Standard generalized pattern search algorithms have been applied heuristically to such problems, but no convergence properties have been stated. In this paper we extend a class of generalized pattern search algorithms to include a subprocedure that adaptively controls the precision of the approximating cost functions. The numerical approximations to the cost function need not de. ne a continuous function. Our algorithms can be used for solving linearly constrained problems with cost functions that are at least locally Lipschitz continuous. Assuming that the cost function is smooth, we prove that our algorithms converge to a stationary point. Under the weaker assumption that the cost function is only locally Lipschitz continuous, we show that our algorithms converge to points at which the Clarke generalized directional derivatives are nonnegative in predefined directions. An important feature of our adaptive precision scheme is the use of coarse approximations in the early iterations, with the approximation precision controlled by a test. We show by numerical experiments that such an approach leads to substantial time savings in minimizing computationally expensive functions.
Design solutions have been proposed to implement generic data structures, however such techniques dedicated to algorithms are not well known. This article discusses various recurrent problems encountered when designin...
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Design solutions have been proposed to implement generic data structures, however such techniques dedicated to algorithms are not well known. This article discusses various recurrent problems encountered when designing reusable, extensible algorithms for operations research. It explains how to use object-oriented concepts and the notion of genericity to design algorithms that are independent of the data structures and the algorithms they use, but that can still interact deeply with them. An object-oriented design is sometimes considered to be less efficient than a classical one, and operations research is one of these scientific fields where efficiency really matters. Hence, the main goal of this article is to explain how to design algorithms that are both generic and efficient. It also discusses specific recurring design issues for operations research software and proposes solutions that improve the genericity of the algorithms. Copyright (c) 2005 John Wiley & Sons, Ltd.
We propose a simulation-precision control algorithm that can be used with a family of derivative free optimization algorithms to solve optimization problems in which the cost function is defined through the solutions ...
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We propose a simulation-precision control algorithm that can be used with a family of derivative free optimization algorithms to solve optimization problems in which the cost function is defined through the solutions of a coupled system of differential algebraic equations (DAEs). Our optimization algorithms use coarse precision approximations to the solutions of the DAE system in the early iterations and progressively increase the precision as the optimization approaches a solution. Such schemes often yield a significant reduction in computation time. We assume that the cost function is smooth but that it can only be approximated numerically by approximating cost functions that are discontinuous in the design parameters. We show that this situation is typical for many building energy optimization problems. We present a new building energy and daylighting simulation program, which constructs approximations to the cost function that converge uniformly on bounded sets to a smooth function as precision is increased. We prove that for our simulation program, our optimization algorithms construct sequences of iterates with stationary accumulation points. We present numerical experiments in which we minimize the annual energy consumption of an office building for lighting, cooling and heating. In these examples, our precision control algorithm reduces the computation time up to a factor of four. (c) 2004 Elsevier B.V. All rights reserved.
In this paper, we apply different software complexity measures to a set of shortest-path algorithms. Our intention is to study what kind of new information about the algorithms the complexity measures (lines-of-code, ...
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In this paper, we apply different software complexity measures to a set of shortest-path algorithms. Our intention is to study what kind of new information about the algorithms the complexity measures (lines-of-code, Halstead's volume, and cyclomatic number) are able to give, to study which software complexity measures are the most useful ones in algorithm comparison, and to analyze when the software complexity comparisons are appropriate. The experiment indicates that the software complexity measures give a new dimension to empirical algorithm comparison. The results explicitly show the trade-off between speed and implementation complexity: a faster algorithm typically requires a more complex implementation. Different complexity measures correlate strongly. Therefore, even the simple lines-of-code measure gives useful results. As the software complexity measures are easy to calculate and since they give useful information, the study suggests that such measures should be included in empirical algorithm comparisons. Unfortunately, for meaningful results, all the algorithms have to be developed in the same fashion which makes the comparison of independent implementations difficult.
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