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关键词： Elements   Algorithms   Optimization   Inorganic carbon compounds   Lattices  

摘要： On-lattice kinetic Monte Carlo (KMC) is a computational method used to simulate (among others) physicochemical processes on catalytic surfaces. The KMC algorithm propagates the system through discrete configurations by selecting (with the use of random numbers) the next elementary process to be simulated, e.g., adsorption, desorption, diffusion, or reaction. An implementation of such a selection procedure is the first-reaction method in which all realizable elementary processes are identified and assigned a random occurrence time based on their rate constant. The next event to be executed will then be the one with the minimum interarrival time. Thus, a fast and efficient algorithm for selecting the most imminent process and performing all of the necessary updates on the list of realizable processes post execution is of great importance. In the current work, we implement five data-structures to handle the elementary process queue during a KMC run: an unsorted list, a binary heap, a pairing heap, a one-way skip list, and finally, a novel two-way skip list with a mapping array specialized for KMC simulations. We also investigate the effect of compiler optimizations on the performance of these data-structures on three benchmark models, capturing CO oxidation, a simplified water gas shift mechanism, and a temperature-programmed desorption run. Excluding the least efficient and impractical for large-problems unsorted list, we observe a 3x speedup of the binary or pairing heaps (most efficient) compared to the one-way skip list (least efficient). Compiler optimizations deliver a speedup of up to 1.8x. These benchmarks provide valuable insight into the importance of, often-overlooked, implementation-related aspects of KMC simulations, such as the queueing data-structures. Our results could be particularly useful in guiding the choice of data-structures and algorithms that would minimize the computational cost of large-scale simulations.

关键词： Binary decision diagrams  

摘要： A derivative structure is a nonequivalent substitutional atomic configuration derived from a given primitive cell. The enumeration of derivative structures plays an essential role in searching for the ground states in multicomponent systems. However, it is computationally difficult to enumerate derivative structures if the number of derivative structures of a target system becomes huge. In this study, we introduce a novel compact data structure of the zero-suppressed binary decision diagram (ZDD) for enumerating derivative structures much more efficiently. We show its simple applications to the enumeration of structures derived from the face-centered cubic and hexagonal close-packed lattices in binary, ternary, and quaternary systems. The present ZDD-based procedure should contribute to computational approaches based on derivative structures in physics and materials science.

关键词： Majorities on trees   Succinct data structures  

摘要： We present the first solution to finding tau-majorities on tree paths. Given a tree of nnodes, each with a label from [1..sigma], and a fixed threshold 0 < tau 1, such a query gives two nodes u nd v nd asks for all the labels that appear more than tau center dot vertical bar P-uv vertical bar times in the path P-uv from u to v, where vertical bar P-uv vertical bar denotes the number of nodes in P-uv. Note that the answer to any query is of size up to 1/tau. On a w-bit RAM, we obtain a linearspace data structure with O((1/t) lg lg(w sigma)) query time, which is worst-case optimal for polylogarithmic-sized alphabets. We also describe two succinct-space solutions with query time O((1/tau) lg* n lglg(w sigma)). One uses 2nH+ 4n + o(n)(H+ 1) bits, where H <= lg sigma is the entropy of the label distribution;the other uses nH+ O(n) + O(nH) bits. By using just o(n lg sigma) extra bits, our succinct structures allow tau to be specified at query time. We obtain analogous results to find a tau-minority, that is, an element that appears between 1 and tau . vertical bar P-uv vertical bar times in P-uv. (c) 2020 Elsevier B.V. All rights reserved.

关键词： 数据结构   大数据   数字化时代   数字化生存   《标准》   描述数据   教学建议   信息技术课程标准  

摘要： 《普通高中信息技术课程标准(2017年版2020修订)》(以下简称《标准》)指出:“在数字化时代,数据对科学发现、技术进步、经济发展以及人们的日常生活有着越来越深刻的影响。理解数据的作用及价值,对学生适应信息社会、学会数字化生存有着十分重要的意义。”同时,要求通过“数据与数据结构”模块的学习,让学生进一步了解数据(包括大数据)的作用,并能够运用生活中的实例描述数据的内涵与外延。

关键词： 数据结构   课程改善  

摘要： "数据结构"是计算机专业一门重要的专业基础课程。该文在应用型人才培养视角下,从学生学习状态分析开始,对"以学生为中心"的教学理念、"内容为王"的教学根本、多元化、差异化评价机制等方面进行课程改善,通过学生评教等方面展示三轮教学后的改善效果,并对下一步的建设提出展望。

关键词： BOPPPS有效教学法   数据结构   线上教学  

摘要： 在当前新工科背景下,对于高校工科类专业课程的教学也有着越来越高的要求,而线上教学作为课程教学中的新型方式,提升其效果也就十分必要。因此,在当前数据结构课程教学中,教师需要用于有效的教学方法开展线上教学,而BOPPPS有效教学法就是其中比较重要的一种,对于教学效果的提升十分有利,也就需要教师充分掌握并利用该教学方法进行教学,以得到理想效果。

关键词： OBE   直播课堂   学习评价   数据结构  

摘要： 基于OBE理论,以应用型本科数据结构课程为例,提出直播课堂"三个环节,两个维度"的学习评价体系,从课前、课中、课后三个环节,学习成果和学习态度两个维度,以学习成果评价为主,介绍直播课堂学习评价体系构建过程,每个环节从以数据结构"算法和算法分析"部分为例,阐述直播课堂学习评价体系的应用。

关键词： 高中信息技术   数据素养   必修模块   数据结构   大数据   数据安全   问题情境   气象数据  

摘要： “数据及其价值”是高中信息技术选择性必修模块1中的第一单元,本单元项目从课程内容的广度、深度和问题情境等方面,对必修模块1“数据和大数据”相关内容进行了提升。让学生通过调查分析的方法了解气象数据,以及这些数据对企业决策的影响和存在的个人隐私安全风险,提出有效保护数据安全的建议,从而进一步提升学生的数据素养。

关键词： 数据结构 高等学校 教材 JAVA语言 程序设计  

ISBN: (纸本)9787302551348

摘要： 本书系统地介绍了各种常用的数据结构以及查找和排序的各种算法，阐述了各种数据结构的逻辑关系、存储表示及基本运算，并采用Java语言描述数据组织和算法实现，所有算法的程序均在Java1.8中调试通过。全书既注重原理又注重实践，配有大量图表和示例，内容丰富，概念讲解清楚，表达严谨，逻辑性强，语言精练，可读性好。书中提供了丰富的练习题、实验题和在线编程题，配套的《数据结构教程（Java）学习与实验指导》详细给出了本书练习题的解题思路和参考答案，以及在线编程题的AC代码。本书内容涉及的广度和深度符合本科培养目标的要求?

关键词： 数据结构   单元教学   高中信息技术   教与学   后续学习   模块   选择性   价值  

摘要： 高中信息技术选择性必修模块1“数据与数据结构”包括“数据及其价值”“数据结构”“数据结构应用”三部分内容。“数据及其价值”是模块的起始内容,是后续学习的基础。要想策划和实施好这一部分的教与学可以从备课、实施和评价三方面入手。