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关键词： Privacy   Collaborative work   Cryptography   Information theory   Differential privacy   Computer science   Computational modeling  

摘要： Privacy has become an emerging challenge in both information theory and computer science due to massive (centralized) collection of user data. In this article, we overview privacy-preserving mechanisms and metrics from the lenses of information theory, and unify different privacy metrics, including f-divergences, Rényi divergences, and differential privacy (DP), in terms of the probability likelihood ratio (and its logarithm). We review recent progress on the design of privacy-preserving mechanisms according to the privacy metrics in computer science, where DP is the standard privacy notion which controls the output shift given small input perturbation, and information theory, where the privacy is guaranteed by minimizing information leakage. In particular, for DP, we include its important variants (e.g., Rényi DP, Pufferfish privacy) and properties, discuss its connections with information-theoretic quantities, and provide the operational interpretations of its additive noise mechanisms. For information-theoretic privacy, we cover notable frameworks, including the privacy funnel, originated from rate-distortion theory and information bottleneck, to privacy guarantee against statistical inference/guessing, and information obfuscation on samples and features. Finally, we discuss the implementations of these privacy-preserving mechanisms in current data-driven machine learning scenarios, including deep learning, information obfuscation, federated learning, and dataset sharing.

关键词： 计算机科学   应用型教学   创新教学设计  

摘要： 阐述应用型计算机教学的实践策略,需要创新教学设计、改进教学大纲、转变观念、提升教学评价、与企业合作,开拓资源,从而推动区域内教育技术的平衡发展。

关键词： 计算机   现代化   互联网   科学技术   产品  

摘要： 随着经济发展水平的不断提高,科技也在日新月异地发展,现代化计算机技术愈来愈广泛地运用到生活中,方方面面带来极大的便利。计算机技术的应用也推动智能化进程的加速发展,从"互联网+"到人工智能(AI)技术,都加快现代化技术的进一步的发展,以计算机为核心支持而发展起来的各种新兴技术,广泛地被用在信息的交流与互动上、净化网络环境与维护网络安全上,或其它一些智能产品的改造和升级上,都在追求卓越的品质和体验更好地为人类现代化社会服务。

关键词： Machine learning   Protein function predictions   Applied mathematics   Computer science  

摘要： Despite recent advances in high-throughput combinatorial mutagenesis assays, the number of labeled sequences available to predict molecular functions has remained small for the vastness of the sequence space combined with the ruggedness of many fitness functions. While deep neural networks (DNNs) can capture high-order epistatic interactions among the mutational sites, they tend to overfit to the small number of labeled sequences available for training. Here, we developed Epistatic Net (EN), a method for spectral regularization of DNNs that exploits evidence that epistatic interactions in many fitness functions are sparse. We built a scalable extension of EN, usable for larger sequences, which enables spectral regularization using fast sparse recovery algorithms informed by coding theory. Results on several biological landscapes show that EN consistently improves the prediction accuracy of DNNs and enables them to outperform competing models which assume other priors. EN estimates the higher-order epistatic interactions of DNNs trained on massive sequence spaces-a computational problem that otherwise takes years to solve. Finding a biologically-relevant inductive bias for training DNNs on large fitness landscapes is challenging. Here, the authors propose a method called Epistatic Net that improves DNN prediction accuracy and interpretation speed by integrating the knowledge that higher-order epistatic interactions are usually sparse.

关键词： Computational methods   Computer science   Deep learning   Engineering science and mechanics   Sustainable energy   Wind engineering  

摘要： Large variations in wind energy production over a period of minutes to hours is a challenge for electricity balancing authorities. The use of reliable tools for the prediction of wind power and wind power ramp events is essential for the operator of the electrical system. The main objective of this work is to analyze the wind power and wind power ramp forecasting at Brazil and Uruguay. To achieve this goal the wavelet decomposition applying 48 different mother wavelet functions and deep learning techniques are used. The recurrent neural network was trained to perform the forecasting of 1 h ahead, and then, using it, the trained network was applied to recursively infer the forecasting for the next hours of the wind speed. After this computational procedure, the wind power and the wind power ramp were predicted. The results showed good accuracy and can be used as a tool to help national grid operators for the energy supply. The wavelet discrete Meyer family (dmey) demonstrates greater precision in the decomposition of the wind speed signals. Therefore, it is proven that the wavelet dmey is the most accurate in the decomposition of temporal wind signals, whether using signals from tropical or subtropical regions. (c) 2021 Elsevier Ltd. All rights reserved.

关键词： 信息技术   初中英语   融合教学   策略  

摘要： 在教育信息化背景下,信息技术与学科教学深度融合是促进教育现代化、提升教学实效的重要手段。在信息技术与初中英语跨学科融合教学中,如何找到融合点、如何实现各教学环节的自然衔接以及如何突出教师主导和学生主体地位是值得研究的课题。文章以人教版八年级英语《I am going to study computer science》教学为例,从课题的选取、融合点的确立和多种信息技术的应用等方面进行了实践,探究信息技术与初中英语跨学科融合教学的过程和策略,为信息技术与初中英语跨学科融合教学提供实践经验。

关键词： 智慧教学   应用型本科   计算机专业   操作系统  

摘要： 针对新建应用型本科院校课堂教学现状的分析,以“操作系统”课程为例,提出了一个面向应用型本科的计算机专业课程的智慧课堂教学框架,并从课前、课中、课后等多个角度分析教学实施与教学设计过程,目的在于探索并构建适合于应用型人才培养目标的课堂教学模式与方法,达到提高应用型人才培养质量的目的。

关键词： 在线课程   交互学习   影响   评价  

摘要： 本文以联通主义等相关在线学习理论为依据,基于"生死学"在线课程实践的思考,阐述在线交互学习行为中环境、内容、学习者及教师四个基本因素的影响作用。在线交互学习行为评价遵循从初级交互、中级交互再到高级交互发展过程的动态维度与在线交互的各种形式的结构维度评价相结合的评价体系建构。

关键词： Artificial Intelligence   Computer Science   general   Engineering Economics   Organization   Logistics   Marketing   Control   Robotics   Mechatronics   Performing Arts   Methodology of the Social Sciences