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关键词： 数据结构   算法   人工智能   实验设计  

摘要： 在人工智能领域研究背景下提出了数据结构与算法课程的实验教学的内容设计,通过人工智能算法中的遗传算法、蚁群算法、模拟退火算法与基础算法中的动态规划对旅行商问题和实际数据处理结果的性能对比实验,培养学生的算法设计能力和处理实际数据的能力,实践证明实验课程的内容改革能有效的提高学生的学习兴趣和热情,了解和掌握前沿的算法和研究领域,培养学生应用算法解决实际问题的能力,提升学生的创造力和科学研究的能力,培养社会急需的计算机人才。

关键词： 数据结构   BOPPPS模式   体验式教学   类比教学法   图解教学法  

摘要： 为了改进传统教学方式的不足,将BOPPPS模式引入《数据结构实验》的教学过程。以“抽象数据类型三元组”为例,提出基于BOPPPS模式的教学设计方案。在参与式学习阶段,为了帮助学生增强信心和激发学习兴趣,将实验内容划分为“由易到难”的三个阶段。通过精心设置“陷阱”,使学生在动手实践过程中深入体会函数参数的“传值”调用与“传地址”调用的差别,达到体验式教学的效果。此外,在教学过程中综合运用“雨课堂”工具、类比教学法和图解教学法等辅助手段,确保了教学目标的顺利达成。

关键词： 数据结构   C语言  

ISBN: (纸本)9787121362248

摘要： 本书共分10章，包括引论、表、栈、队列、排序与选择、树、散列表、优先队列、并查集、图等。全书采用C语言作为描述语言，内容丰富，叙述简明，理论与实践并重。

关键词： Yerba mate (Ilex paraguariensis)   Fluorescence spectroscopy   First- and second-order data   Variable selection   Classification  

摘要： This paper uses fluorescence spectroscopy in order to evaluate the potential of this technique to classify Argentinean yerba mate from three commercial categories. An extraction method based on ultrasound for sample preparation is proposed. Acquired fluorescence first- and second-order data were analyzed by different chemometric approaches. Aimed at enhancing data interpretability and to reduce redundant information among the retained variables and maximize their relationship regarding the sample, several variable selection algorithms were evaluated. Two three-way algorithms, PARAFAC and n-PLS, were applied to EEMs. Several two-way algorithms such as PCA, SPA, GA, PLS were used previous to model data gathered from emission spectra recorded at the 410 nm excitation and unfolded EEMs. Sample categorization was performed using LDA or QDA as classification techniques. The ability of the models to predict samples was evaluated based on sensitivity and specificity. First-order models reached 89.6% on sensitivity and 90.9% on specificity. Second-order models achieved up to 100% sensitivity and specificity demonstrating that the EEM matrix provides relevant additional information revealing a significant effect on the classification results.

关键词： Dynamic tree data structures   evolutionary algorithms (EAs)   tree representations  

摘要： Optimization methods for spanning tree problems may require efficient data structures. The node-depth-degree representation (NDDR) has achieved relevant results for direct spanning tree representation together with evolutionary algorithms (EAs). Its two mutation operators have average time O(root n), where n is the number of vertices of the graph, while similar operators implemented by predecessor arrays, a typical tree data structure, have time O(n). Dynamic trees are also relevant when investigating tree representations since they have low time complexity, but there is no proper extension of them for EAs. Using aspects of both a dynamic tree and NDDR, namely, Euler tours and structural sharing, we propose a data structure called 2LETT, whose mutation operators have time O(root n) in the worst case. Experiments with the mutation operators using 2LETT, predecessor arrays, and NDDR are carried out for graphs with up to 300 000 vertices. For a mutation operator that exchanges any two valid edges, predecessor arrays present the best performance for random trees with fewer than 10 000 vertices;while 2LETT has the best performance for trees with more than 10 000 vertices. Especially, noteworthy is the fact that 2LETT is the only structure whose running time is independent of tree diameter.

关键词： 数据结构   C语言  

ISBN: (纸本)9787121362248

摘要： 本书共分为10章，包括引论、表、栈、队列、排序与选择、树、散列表、优先队列、并查集、图等。

关键词： Algorithmic library   data structures   graph theory   network analysis  

摘要： Mathematical software and graph-theoretical algorithmic packages to efficiently model, analyze, and query graphs are crucial in an era where large-scale spatial, societal, and economic network data are abundantly available. One such package is JGraphT, a programming library that contains very efficient and generic graph data structures along with a large collection of state-of-the-art algorithms. The library is written in Java with stability, interoperability, and performance in mind. A distinctive feature of this library is its ability to model vertices and edges as arbitrary objects, thereby permitting natural representations of many common networks, including transportation, social, and biological networks. Besides classic graph algorithms such as shortest-paths and spanning-tree algorithms, the library contains numerous advanced algorithms: graph and subgraph isomorphism, matching and flow problems, approximation algorithms for NP-hard problems such as independent set and the traveling salesman problem, and several more exotic algorithms such as Berge graph detection. Due to its versatility and generic design, JGraphT is currently used in large-scale commercial products, as well as noncommercial and academic research projects. In this work, we describe in detail the design and underlying structure of the library, and discuss its most important features and algorithms. A computational study is conducted to evaluate the performance of JGraphT versus several similar libraries. Experiments on a large number of graphs over a variety of popular algorithms show that JGraphT is highly competitive with other established libraries such as NetworkX or the BGL.

关键词： dynamic modeling   material flow analysis (MFA)   open science   Python   software   substance flow analysis (SFA)  

摘要： Material flow analysis (MFA) studies the stocks and flows of goods and substances in systems. The methods and algorithms of MFA have improved over the last few years, but a flexible platform that integrates recent modeling advances such as simultaneous consideration of the product, component, material and chemical element levels, lifetime models, and uncertainty treatment is not available. There is also no versatile data format for exchanging data between projects. This lack of research infrastructure is detrimental to scientific progress. To fill that gap, we propose a novel industrial ecology community model for MFA. The Open Dynamic Material Systems Model (ODYM) is an open source framework for material systems modeling programmed in Python. The description of systems, processes, stocks, flows, and parameters is object-based, which facilitates the development of modular software and testing routines for individual model blocks. ODYM MFA models can handle any depth of flow and stock specification: products, components, sub-components, materials, alloys, waste, and chemical elements can be traced simultaneously. ODYM features a new data structure for material flow analysis;all input and output data are stored in a standardized file format and can thus be exchanged across projects. It also comes with an extended library for dynamic stock modeling. We present the features, design principles, software, and data structure of ODYM, describe its main methods and functions, and give an outlook on current and future applications.

关键词： C语言  

ISBN: (纸本)9787302549987

摘要： 本教材涵盖基本数据结构、排序和查找等主要内容, 以逻辑结构为主线系统介绍线性表、栈与队列、串、树和图等各种基本数据结构内容, 从算法的角度系统介绍各类排序、查找算法, 注重对不同数据结构和算法的比较分析及其应用。同时, 融合互联网技术, 将课程的重点、难点、疑点全部采用纸质和通过嵌入二维码获取数学媒体两种形式呈现, 并且使媒体素材集知识性、趣味性与互动性于一体, 较好地保证教材内容的可更新性和可扩展性。

关键词： single-cell transcriptomics   dimensionality reduction   visualization   single-cell analysis   data analysis   unsupervised learning  

摘要： High-dimensional data, such as those generated by single-cell RNA sequencing (scRNA-seq), present challenges in interpretation and visualization. Numerical and computational methods for dimensionality reduction allow for low-dimensional representation of genome-scale expression data for downstream clustering, trajectory reconstruction, and biological interpretation. However, a comprehensive and quantitative evaluation of the performance of these techniques has not been established. We present an unbiased framework that defines metrics of global and local structure preservation in dimensionality reduction transformations. Using discrete and continuous real-world and synthetic scRNA-seq datasets, we show how input cell distribution and method parameters are largely determinant of global, local, and organizational data structure preservation by 11 common dimensionality reduction methods.