教学课程资源库 更多>>

关键词： 大数据时代   计算机科学   技术专业   综合改革  

摘要： 社会生活的很多领域都已经运用计算机科学与技术。计算机科学与技术对社会的发展方向产生明显的影响,属于社会发展中的关键性内容。人们的生产生活已经不能离开计算机科学技术的帮助。计算机科学技术积极地改善了人们生活质量,带给人们更多的舒适度以及便捷性。文章分析大数据时代的计算机科学与技术专业综合改革相关内容,作为实践工作的有效指导。

关键词： 全球环境治理   格局重构   扰沌   创造性毁灭   结构性权力  

摘要： 新冠疫情对世界秩序和全球治理带来巨大的挑战,成为历史进程中的一个重要分水岭。疫情对全球环境治理活动及政策执行产生重大影响,并涉及全球生态、卫生、政治和经济等多个领域,牵涉国际合作中的众多行为主体,已成为影响国际格局的主要力量之一。在百年大变局背景下,此次新冠疫情也将催化全球环境治理格局加速变迁。坚持"辩证思维、创新思维、全球思维"对于在新冠疫情冲击下中国有效参与重构和拓展国际环境合作,把握全球环境治理趋势具有重要的启发和指导意义。该文尝试引入全球治理的"扰沌"、社会技术系统转型的"创造性毁灭"、国际政治博弈的"结构性权力"等理论工具,在"辩证思维、创新思维、全球思维"思想启发下,从跨学科视角对疫情影响下国际格局和全球环境治理趋势进行分析解读,以求知己知彼,以使中国有效参与重构和拓展国际环境合作,对接联合国"重建得更好"议程,更好地推动共建人类绿色命运共同体。

关键词： Middle school science   computer models   computer models in science  

摘要： When middle school students encounter computer models of science phenomena in science class, how do they think those computer models work? Computer models operationalize real-world behaviors of selected variables, and can simulate interactions between the modeled elements through programmed instructions. This study explores how middle school students think about the high-level semantic meaning of those instructions, which we term rules. To investigate this aspect of students' computational thinking, we developed the Computational Modeling Inventory and administered it to 253 7th grade students. The Inventory included three computer models that students interacted with during the assessment. In our sample, 99% of students identified at least one key rule underlying a model, but only 14% identified all key rules;65% believed that model rules can contradict;and 98% could not distinguish between emergent patterns and behaviors that directly resulted from model rules. Despite these misconceptions, compared to the "typical" questions about the science content alone, questions about model rules elicited deeper science thinking, with 2-10 times more responses including reasoning about scientific mechanisms. These results suggest that incorporating computational thinking instruction into middle school science courses might yield deeper learning and more precise assessments around scientific models.

关键词： Adders   Hardware   Computer architecture   Parallel processing   Digital signal processors   Computer science   Arithmetic unit   modular arithmetic   parallel prefix adder   residue number system   reverse converter  

摘要： The class of moduli sets in the form of {2(k), 2(n) - 1, 2(n) + 1, m(4)} with m(4) is an element of{2(r) + 1, 2(r) - 1} has earned significant popularity in the implementation of the Residue Number System (RNS)-based computational systems, mainly thanks to the efficient arithmetic unit and a high degree of parallelism. However, its complicated inter-modulo computation leads to a high overhead associated with the complex reverse converter. This overhead is the main barrier for energy-efficient implementation of RNS-based devices, particularly for edge computing applications. This brief presents a new approach that embeds the reverse converter into the arithmetic unit of the RNS processor for the aforesaid well-known class of moduli sets. The effective hardware reuse in the proposed approach leads to an area and energy-efficient RNS realization for this class of moduli set. The experimental results based on 65 nm CMOS technology indicate the superiority of RNS realization by employing the proposed design methodology. The proposed architecture for a given RNS provides a substantial 17.4% area-saving and 13.32% less power-consumption on average compared to the traditional design approach, with the negligible penalty in delay.

关键词： 电子计算机  

ISBN: (纸本)9787115550699

摘要： 本书主要讲解了计算机的基础知识、新技术及应用。本书按照新版全国计算机等级考试大纲的要求，以Windows 10操作系统、Office 2016为基础，向读者介绍了计算机基础概论、计算机基础知识、Windows 10操作系统、文字处理软件Word 2016、电子表格软件Excel 2016、文稿演示软件PowerPoint 2016及计算机网络与应用，以及计算机新技术与应用等内容。

关键词： Learning systems   Linear programming   Computer science   Task analysis   Clustering methods   Diversity reception   Training data   Clustering ensemble   consensus learning   self-paced learning  

摘要： The clustering ensemble has emerged as an important extension of the classical clustering problem. It provides an elegant framework to integrate multiple weak base clusterings to generate a strong consensus result. Most existing clustering ensemble methods usually exploit all data to learn a consensus clustering result, which does not sufficiently consider the adverse effects caused by some difficult instances. To handle this problem, we propose a novel self-paced clustering ensemble (SPCE) method, which gradually involves instances from easy to difficult ones into the ensemble learning. In our method, we integrate the evaluation of the difficulty of instances and ensemble learning into a unified framework, which can automatically estimate the difficulty of instances and ensemble the base clusterings. To optimize the corresponding objective function, we propose a joint learning algorithm to obtain the final consensus clustering result. Experimental results on benchmark data sets demonstrate the effectiveness of our method.

关键词： Task analysis   Multiplexing   Feature extraction   Computer science   Complex networks   Topology   Social networking (online)   Network embedding   Structural proximity   Structural equivalence   Multiplex networks   Graphlet degree vector   Cross-layer random walks  

摘要： Node embedding aims to encode network nodes as a set of low-dimensional vectors while preserving certain structural properties of the network. In recent years, extensive studies have been conducted to preserve network communities, i.e., structural proximity of network nodes. However, few of them have focused on preserving the structural equivalence of network nodes, which describes the similarity of structural roles between network nodes. In this paper, we focus on a hybrid network embedding problem of how to flexibly and simultaneously preserve both structural proximity and equivalence. Here, we introduce the concept of graphlet degree vector (GDV) to describe structure roles of network nodes, and further measure structural equivalence based on their similarity. Specifically, we capture both structural proximity and equivalence by building a multiplex network, where both unsupervised and semi-supervised cross-layer random walk (CL-Walk) methods are implemented. By carrying out experiments on both synthetic and real-world datasets, we evaluate the performance of the proposed CL-Walk methods for the tasks of node clustering, node classification, and label prediction. The experimental results indicate that the CL-Walk method outperforms several state-of-the-art methods when both structural proximity and structural equivalence are relevant to specific network analytic task.

关键词： Artificial intelligence   Technological innovation   Big Data   Innovation management   Computer science   Decision making   Organizations   Artificial intelligence (AI)   digitization   inno-vation process   product innovation   self-innovating artificial intelligence (SAI)  

摘要： Through recent leaps in application, artificial intelligence (AI) has become one of the most promising digital technologies, attracting significant attention from scholars and practitioners alike. Prior innovation research has mainly focused on the opportunities for and challenges to infusing digital technologies into the innovation process. However, understanding the general effects of digital technologies is insufficient as their specific fields of application differ. AI is distinct from other digital technologies, given its potential to evolve into both a general-purpose technology and a method of inventing, and several firms are beginning to integrate AI into their innovation processes. We capture this phenomenon by introducing a concept we term self-innovating artificial intelligence (SAI), defined as the organizational utilization of AI with the aim of incrementally advancing existing or developing new products, based on insights from continuously combining and analyzing multiple data sources. As SAI is about to fundamentally change how innovations are created, this article describes the underlying AI technology;conceptualizes and outlines how firms may incorporate SAI into their innovation processes with the aim of developing increasingly complex products;and offers potential avenues for further research in this intriguing domain.

关键词： PET   quantification   molecular imaging   theranostics   multimodality   computer science  

摘要： PET/CT molecular imaging has been imposed in clinical oncological practice over the past 20 years, driven by its two well-grounded foundations: quantification and radiolabeled molecular probe vectorization. From basic visual interpretation to more sophisticated full kinetic modeling, PET technology provides a unique opportunity to characterize various biological processes with different levels of analysis. In clinical practice, many efforts have been made during the last two decades to standardize image analyses at the international level, but advanced metrics are still under use in practice. In parallel, the integration of PET imaging with radionuclide therapy, also known as radiolabeled theranostics, has paved the way towards highly sensitive radionuclide-based precision medicine, with major breakthroughs emerging in neuroendocrine tumors and prostate cancer. PET imaging of tumor immunity and beyond is also emerging, emphasizing the unique capabilities of PET molecular imaging to constantly adapt to emerging oncological challenges. However, these new horizons face the growing complexity of multidimensional data. In the era of precision medicine, statistical and computer sciences are currently revolutionizing image-based decision making, paving the way for more holistic cancer molecular imaging analyses at the whole-body level.

关键词： Measurement   Security   Control systems   Differential privacy   Cyber-physical systems   Computer science   Approximation algorithms   Approximate simulation relations   finite abstractions   opacity   symbolic models  

摘要： Opacity is an important information-flow security property in the analysis of cyber-physical systems. It captures the plausible deniability of the system's secret behavior in the presence of an intruder that may access the information flow. Existing works on opacity only consider nonmetric systems by assuming that the intruder can always distinguish between two different outputs precisely. In this article, we extend the concept of opacity to systems whose output sets are equipped with metrics. Such systems are widely used in the modeling of many real-world systems whose measurements are physical signals. A new concept called approximate opacity is proposed in order to quantitatively evaluate the security guarantee level with respect to the measurement precision of the intruder. Then, we propose a new simulation-type relation, called approximate opacity-preserving simulation relation, which characterizes how close two systems are in terms of the satisfaction of approximate opacity. This allows us to verify approximate opacity for large-scale, or even infinite, systems using their abstractions. We also discuss how to construct approximate opacity-preserving symbolic models for a class of discrete-time control systems. Our results extend the definitions and analysis techniques for opacity from nonmetric systems to metric systems.