Finding the Consensus Shape for a Protein Family

We define and prove properties of the consensus shape for a protein family, a protein-like structure that provides a compact summary of the significant structural information for a protein family. If all members of the protein family exhibit a geometric relationship between corresponding -carbons, then that relationship is preserved in the consensus shape. In particular, distances and angles that are consistent across family members are preserved. For the consensus shape, the spacing between successive -carbons is variable, with small distances in regions where the members of the protein family exhibit significant variation and large distances (up to the standard spacing of about 3.8 Å) in regions where the family members agree. Despite this non-protein-like characteristic, the consensus shape preserves and highlights important structural information. We describe an iterative algorithm for computing the consensus shape and prove that the algorithm converges. As a by-product we produce a multiple structure alignment for the family members. We present the results of experiments in which we build consensus shapes for several known protein families.     

Editors: Two for the price of one

Text editors designed for interactive use on visual display units offer significant advantages, particularly in simplicity of use, but non-visual editors can provide facilities which are difficult to incorporate into a VDU editor without undermining these advantages. This paper describes a text editing system which offers both a visual and non-visual mode of use, via two user interfaces to a common set of editing primitives, and allows the user to switch freely between modes during the course of an edit. The visual editing interface consists of a set of single-key control functions which require no unusual VDU characteristics, while non-visual editing is provided by a set of context editing commands which both duplicate these control functions and offer extra facilities, particularly for repetitive editing.     

A remark on the subsequence problem for arc-annotated sequences with pairwise nested arcs

The Arc-Preserving Subsequence (APS) problem appears in the comparison of RNA structures in computational biology. Given two arc-annotated sequences of length n and m<n, APS asks if the shorter sequence can be obtained from the longer one by deleting certain elements along with their incident arcs. It is known that APS with pairwise nested arcs can be solved in O(mn) time. We give an algorithm running in O(m²+n) time in the worst case, actually it is even faster in particular if the shorter sequence has many arcs. The result may serve as a building block for improved APS algorithms in the general case.     

Improving the design of sequences for DNA computing: A multiobjective evolutionary approach

Designing oligonucleotide strands that selectively hybridize to reduce undesired reactions is a critical step for successful DNA computing. To accomplish this, DNA molecules must be restricted to a wide window of thermodynamical and logical conditions, which in turn facilitate and control the algorithmic processes implemented by chemical reactions. In this paper, we propose a multiobjective evolutionary algorithm for DNA sequence design that, unlike preceding evolutionary approaches, uses a matrix-based chromosome as encoding strategy. Computational results show that a matrix-based GA along with its specific genetic operators may improve the performance for DNA sequence optimization compared to previous methods.     

Cluster editing problem for points on the real line: A polynomial time algorithm

In this paper we consider the cluster editing problem for a special type of graphs, where the vertices represent points on the real line and there is an edge between each two vertices for which the distance between their corresponding points on the line is less than a given constant. We give a polynomial time cluster editing algorithm for this class of graphs.     

A Coarse-Grained Multicomputer algorithm for the detection of repetitions

The paper presents a Coarse-Grained Multicomputer algorithm that solves the problem of detection of repetitions. This algorithm can be implemented in the CGM model with P processors in in time and O(P) communication steps. It is the first CGM algorithm for this problem. We present also experimental results showing that the CGM algorithm is very efficient.     

Analysis, design and implementation of a novel scheme for in-vivo control of synthetic gene regulatory networks

This paper is concerned with the design and implementation of a simple but effective switching control strategy to regulate the dynamics of synthetic gene networks. The testbed circuit is IRMA, a recently developed network in S. Cerevisiae which is proposed as a suitable benchmark problem for control design. The proof-of-concept of an implementation of the control strategy in vivo is presented which is based on the use of microfluidics devices and fluorescence microscopy. Preliminary experimental results are given showing the good matching between the model predictions and the experimental observations.     

大面阵CCD相机高速图像压缩系统设计

针对大面阵CCD相机高分辨率、高帧频等特点,提出了一种适用于大面阵CCD相机高速实时图像压缩的系统。实验结果表明,该方案在压缩比为53:1时峰值信噪比可以达到36 dB,取得了很好的压缩性能。     

An evolutionary real options framework for the design and management of projects and systems with complex real options and exercising conditions

To address the issue of decision support for designing and managing flexible projects and systems in the face of uncertainties, this paper integrates real options valuation, decision analysis techniques, Monte Carlo simulations and evolutionary algorithms in an evolutionary real options framework. The proposed evolutionary real options framework searches for an optimized portfolio of real options and makes adaptive plans to cope with uncertainties as the future unfolds. Exemplified through a test case, the evolutionary framework not only compares favorably with traditional fixed design approaches but also delivers considerable improvements over prevailing real options practices.     

动态规划法中返求最优可靠度分配的实用算法

本文简单介绍动态规划法应用,并着重对动态规划法中返求最优可靠度分配的算法进行研究,提出了一种比较简单实用的实现算法,该方法的优点在于：简单实用,易于编程和实现,解决参数化编程求解问题。     

EASYLOCAL++: an object‐oriented framework for the flexible design of local‐search algorithms

Local search is a paradigm for search and optimization problems, which has recently evidenced to be very effective for a large number of combinatorial problems. Despite the increasing interest of the research community in this subject, there is still a lack of a widely‐accepted software tools for local search. We propose EASY LOCAL , an object‐oriented framework for the design and the analysis of local‐search algorithms. The abstract classes that compose the framework specify and implement the invariant part of the algorithm and are meant to be specialized by concrete classes that supply the problem‐dependent part. The framework provides the full control structures of the algorithms, and the user has only to write the problem‐specific code. Furthermore, the framework comes with some tools that simplify the analysis of the algorithms. The architecture of EASY LOCAL provides a principled modularization for the solution of combinatorial problems by local search and helps the user by deriving a neat conceptual scheme of the application. It also supports the design of combinations of basic techniques and/or neighborhood structures. The framework has been tested in some applicative domains and has proved to be flexible enough in the implementation of algorithms for the solution of various scheduling problems. Copyright © 2003 John Wiley & Sons, Ltd.     

《程序设计基础》实验教学模式改革研究

本文在分析了《程序设计基础》课程实验教学现状的基础上,从教学内容,教学方法以及实验环境等方面对教学模式改革进行了研究,所做的研究具有一定的实用价值。     

An integrated synthetic value of fuzzy judgments and nonlinear programming methodology for ranking the facility layout patterns

In this paper, the goal is to incorporate qualitative criteria in addition to quantitative criteria to facility layout design (FLD) problem. To this end, we present an integrated methodology based on the synthetic value of fuzzy judgments and nonlinear programming (SVFJ-NLP). The facility layout patterns (FLPs) together with their performance measures of total cost of material handling are generated by a computer-aided layout-design tool, CRAFT. Also, the performance measures of second quantitative criterion (construction cost of width walls) are calculated by appraising these FLPs. The SVFJ is then applied to collect the performance measures related to qualitative criteria and finally, a non-linear programming (NLP) model is proposed to solve the FLD. Results obtained from a real case study validate the effectiveness of the proposed model.     

Algorithms for a class of computer-aided design problems: A review

This paper reviews some recent results on algorithms for a class of computer aided design problems arising in control, circuit theory and steel structure design.     

Linear Programming Models for the User and System Optimal Dynamic Network Design Problem: Formulations,Comparisons and Extensions

In this paper we formulate a network design model in which the traffic flows satisfy dynamic user equilibrium conditions for a single destination. The model presented here incorporates the Cell Transmission Model (CTM); a traffic flow model capable of capturing shockwaves and link spillovers. Comparisons are made between the properties of the Dynamic User equilibrium Network Design Problem (DUE NDP) and an existing Dynamic System Optimal (DSO) NDP formulation. Both network design models have different objective functions with similar constraint sets which are linear and convex. Numerical demonstrations are made on multiple networks to demonstrate the efficacy of the model and demonstrate important differences between the DUE and DSO NDP approaches. In addition, the flexibility of the approach is demonstrated by extending the formulation to account for demand uncertainty. This is formulated as a stochastic programming problem and initial test results are demonstrated on test networks. It is observed that not accounting for demand uncertainty explicitly, provides sub-optimal solution to the DUE NDP problem.     

On the design of high-performance algorithms for aligning multiple protein sequences on mesh-based multiprocessor architectures

In this paper, we address the problem of multiple sequence alignment (MSA) for handling very large number of proteins sequences on mesh-based multiprocessor architectures. As the problem has been conclusively shown to be computationally complex, we employ divisible load paradigm (also, referred to as divisible load theory, DLT) to handle such large number of sequences. We design an efficient computational engine that is capable of conducting MSAs by exploiting the underlying parallelism embedded in the computational steps of multiple sequence algorithms. Specifically, we consider the standard Smith–Waterman (SW) algorithm in our implementation, however, our approach is by no means restrictive to SW class of algorithms alone. The treatment used in this paper is generic to a class of similar dynamic programming problems. Our approach is recursive in the sense that the quality of solutions can be refined continuously till an acceptable level of quality is achieved. After first phase of computation, we design a heuristic scheme that renders the final solution for MSA. We conduct rigorous simulation experiments using several hundreds of homologous protein sequences derived from the Rattus Norvegicus and Mus Musculus databases of olfactory receptors. We quantify the performance based on speed-up metric. We compare our algorithms to serial or single machine processing approaches. We testify our findings by comparing with conventional equal load partitioning (ELP) strategy that is commonly used in the parallel processing literature. Based on our extensive simulation study, we observe that DLT paradigm offers an excellent speed-up characteristics and provides avenues for its use in several other biological sequence processing related problem. This study is a first time attempt in using the DLT paradigm to devise efficient strategies to handle large scale multiple protein sequence alignment problem on mesh-based multiprocessor systems.     

Multiple-objective genetic optimization of the spatial design for packing and distribution carton boxes

Packing and cutting problems, which dealt with filling up a space of known dimension with small pieces, have been an attractive research topic to both industry and academia. Comparatively, the number of reported studies is smaller for container spatial design, i.e., defining the optimal container dimension for packing small pieces of goods with known sizes so that the container space utilization is maximized. This paper aims at searching an optimal set of carton boxes for a towel manufacturer so as to lower the overall future distribution costs by improving the carton space utilization and reducing the number of carton types required. A multi-objective genetic algorithm (MOGA) is used to search the optimal design of carton boxes for a one-week sales forecast and a 53-week sales forecast. Clustering techniques are then used to study the order pattern of towel products in order to validate the genetically generated results. The results demonstrate that MOGA effectively search the best carton box spatial design to reduce unfilled space as well as the number of required carton types. It is important to note that the proposed methodology for optimal container design is not limited to the apparel industry but practically attractive and applicable to every industry which aims for distribution costs reduction.     

Logic programming: a computing tool for the architect of the future

Computer-aided architectural design is reviewed with particular reference to new software techniques that are becoming available. The needs of the designer are examined leading to a specification for the computing tools that may serve architects in the future. The paper concludes by reporting on the results of early studies into one radically new technique: logic programming. The research work referred to in this paper is sponsored by the Science and Engineering Research Council under grant numbers GR/A80341 and GR/A88774.     

Entrepreneurship as design: A design process for the emergence and development of entrepreneurial opportunities

Although firms constantly seek opportunities to launch new products, services, or business models, little is known about the way opportunities emerge and develop. In particular, despite current ontological and epistemological knowledge of entrepreneurial opportunities, the process that drives their emergence and development remains understudied. To enrich our understanding, we conduct an exploratory multiple-case study of six design agencies that supported firms in developing their entrepreneurial endeavours by leveraging design sprint, a hybrid method combining design and entrepreneurship. A primary contribution of our study is the conceptualization of a process model illustrating how design (sprint) can support the emergence and development of entrepreneurial opportunities. The model advances four actions that enable translating insights into opportunities: defining, framing, experimenting, and learning. Our findings also offer interesting insights on the role of third-party agents in this process. Indeed, design agencies can act as facilitators in enacting entrepreneurship as design by supporting the emergence and development of entrepreneurial opportunities. Our research also contributes to the debate on the timing of entrepreneurial endeavours, offering an empirical portrayal of their chronology. In this sense, our model also contributes to managerial practice, providing a sequence of actions that can guide the emergence and development of entrepreneurial opportunities.