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关键词： Predictive markers   Computer science  

摘要： Cardiorespiratory fitness is an established predictor of metabolic disease and mortality. Fitness is directly measured as maximal oxygen consumption (VO(2)max), or indirectly assessed using heart rate responses to standard exercise tests. However, such testing is costly and burdensome because it requires specialized equipment such as treadmills and oxygen masks, limiting its utility. Modern wearables capture dynamic real-world data which could improve fitness prediction. In this work, we design algorithms and models that convert raw wearable sensor data into cardiorespiratory fitness estimates. We validate these estimates' ability to capture fitness profiles in free-living conditions using the Fenland Study (N=11,059), along with its longitudinal cohort (N = 2675), and a third external cohort using the UK Biobank Validation Study (N = 181) who underwent maximal VO(2)max testing, the gold standard measurement of fitness. Our results show that the combination of wearables and other biomarkers as inputs to neural networks yields a strong correlation to ground truth in a holdout sample (r = 0.82, 95CI 0.80-0.83), outperforming other approaches and models and detects fitness change over time (e.g., after 7 years). We also show how the model's latent space can be used for fitness-aware patient subtyping paving the way to scalable interventions and personalized trial recruitment. These results demonstrate the value of wearables for fitness estimation that today can be measured only with laboratory tests.

关键词： Computer science   Machine learning  

摘要： Game-playing AIs that interact with humans are laying important groundwork for real-world applications.

关键词： 信任   信誉   可信性   信任模型  

摘要： 在计算机科学中,信任被看作是分布式网络环境中必不可少的安全关系,已成为解决安全问题的一种有效途径。首先概述国内外对于信任问题的相关研究,接着介绍信任基本概念、性质与分类,重点是信任相关概念及其相互关系,最后讨论计算机科学中信任的应用。

关键词： Measurement   Optimization   Relays   Shape   Complexity theory   Germanium   Computer science   Geodesic distance queries   saddle vertices   high dimension embedding   cascaded optimization  

摘要： In this article, we develop a novel method for fast geodesic distance queries. The key idea is to embed the mesh into a high-dimensional space, such that the euclidean distance in the high-dimensional space can induce the geodesic distance in the original manifold surface. However, directly solving the high-dimensional embedding problem is not feasible due to the large number of variables and the fact that the embedding problem is highly nonlinear. We overcome the challenges with two novel ideas. First, instead of taking all vertices as variables, we embed only the saddle vertices, which greatly reduces the problem complexity. We then compute a local embedding for each non-saddle vertex. Second, to reduce the large approximation error resulting from the purely euclidean embedding, we propose a cascaded optimization approach that repeatedly introduces additional embedding coordinates with a non-euclidean function to reduce the approximation residual. Using the precomputation data, our approach can determine the geodesic distance between any two vertices in near-constant time. Computational testing results show that our method is more desirable than previous geodesic distance queries methods.

关键词： Visualization   Data visualization   Task analysis   Organizations   Systematics   Periodic structures   Computer science   Cross-view data relationship   multiple views   visual analytics  

摘要： Due to the scale of data and the complexity of analysis tasks, insight discovery often requires coordinating multiple visualizations (views), with each view displaying different parts of data or the same data from different perspectives. For example, to analyze car sales records, a marketing analyst uses a line chart to visualize the trend of car sales, a scatterplot to inspect the price and horsepower of different cars, and a matrix to compare the transaction amounts in types of deals. To explore related information across multiple views, current visual analysis tools heavily rely on brushing and linking techniques, which may require a significant amount of user effort (e.g., many trial-and-error attempts). There may be other efficient and effective ways of displaying cross-view data relationships to support data analysis with multiple views, but currently there are no guidelines to address this design challenge. In this article, we present systematic design considerations for visualizing cross-view data relationships, which leverages descriptive aspects of relationships and usable visual context of multi-view visualizations. We discuss pros and cons of different designs for showing cross-view data relationships, and provide a set of recommendations for helping practitioners make design decisions.

关键词： Computer Science   College Education   University Social Responsibility  

摘要： Carrying out executive education in computer science(CS)brings both opportunities and *** major advantages are that it helps research programs with funding,data and reallife cases,and both professors and students can benefit from it by having greater engagement with ***,the main challenge is that most CS professors and doctoral students are currently not interested in executive education because they are more interested in their academic *** paper first introduces the background of the Singapore government’s initiative for lifelong education for public,then presents the response from the National University of Singapore(NUS)that ultimately led to several executive education *** attention is given to the experience of the NUS School of Computing in carrying out computer science executive education.

关键词： 计算思维   纽约州中小学   计算机科学教育   信息科技教育  

摘要： 计算思维是智能时代人才必备的素养,以培养计算思维为目标旨向的计算机科学教育愈加受到国内外基础教育领域的重视。美国纽约州作为开展K-12计算机科学教育的典范,其在目标旨向方面,确立了提供高品质计算机科学教育机会以促进个体成长、培养STEM从业人员与维护弱势群体教育公平以适应社会需求、完善素养导向的育人体系以推动教育革新等目标。在行动主体上,纽约州形成了决策层规划教育战略、管理层统筹教育资源、执行层组织教育实践活动的“三级互联”机制,确保行动主体间分工、权责明晰。并且通过开设优质计算机科学教育课程、开发配套软件并提供教学设备,在实践落地上实现软硬件双重保障。此外,纽约州注重建立法规、资金、培训、技术和协同等方面的运行支持,来打造优质K-12计算机科学教育体系。纽约州发展K-12计算机科学教育的经验对我国优化中小学信息科技教育体系与强化中小学生计算思维的培养提供了借鉴。

关键词： Social networking (online)   Message service   Knowledge engineering   Computer science   Terminology   Instant messaging   IEEE Fellows   Social networks   social influence   information diffusion   user behavior   user modeling  

摘要： WeChat is the largest social instant messaging platform in China, with 1.1 billion monthly active users. "Top Stories" is a novel friend-enhanced recommendation engine in WeChat, in which users can read articles based on preferences of both their own and their friends. Specifically, when a user reads an article by opening it, the "click" behavior is private. Moreover, if the user clicks the "wow" button, (only) her/his direct connections will be aware of this action/preference. Based on the unique WeChat data, we aim to understand user preferences and "wow" diffusion in Top Stories at different levels. We have made some interesting discoveries. For instance, the "wow" probability of one user is negatively correlated with the number of connected components that are formed by her/his active friends, but the click probability is the opposite. We further study to what extent users' "wow" and click behavior can be predicted from their social connections. To address this problem, we present a hierarchical graph representation learning based model DiffuseGNN, which is capable of capturing the structure-based social observations discovered above. Our experiments show that the proposed method can significantly improve the prediction performance compared with alternative methods.