教学课程资源库 更多>>

关键词： Computer science   Statistics  

摘要： Modern datasets are characterized by numerous features related by complex dependency structures. To deal with these data, dimensionality reduction techniques are essential. Many of these techniques rely on the concept of intrinsic dimension (id), a measure of the complexity of the dataset. However, the estimation of this quantity is not trivial: often, the id depends rather dramatically on the scale of the distances among data points. At short distances, the id can be grossly overestimated due to the presence of noise, becoming smaller and approximately scale-independent only at large distances. An immediate approach to examining the scale dependence consists in decimating the dataset, which unavoidably induces non-negligible statistical errors at large scale. This article introduces a novel statistical method, Gride, that allows estimating the id as an explicit function of the scale without performing any decimation. Our approach is based on rigorous distributional results that enable the quantification of uncertainty of the estimates. Moreover, our method is simple and computationally efficient since it relies only on the distances among data points. Through simulation studies, we show that Gride is asymptotically unbiased, provides comparable estimates to other state-of-the-art methods, and is more robust to short-scale noise than other likelihood-based approaches.

ISBN: (纸本)9781450397476

关键词： Computer science   Data processing   Databases   Civil engineering   Sustainability  

摘要： Having accurate building information is paramount for a plethora of applications, including humanitarian efforts, city planning, scientific studies, and navigation systems. While volunteered geographic information from sources such as OpenStreetMap (OSM) has good building geometry coverage, descriptive attributes such as the type of a building are sparse. To fill this gap, this study proposes a supervised learning-based approach to provide meaningful, semantic information for OSM data without manual intervention. We present a basic demonstration of our approach that classifies buildings into either residential or non-residential types for three study areas: Fairfax County in Virginia (VA), Mecklenburg County in North Carolina (NC), and the City of Boulder in Colorado (CO). The model leverages (i) available OSM tags capturing non-spatial attributes, (ii) geometric and topological properties of the building footprints including adjacent types of roads, proximity to parking lots, and building size. The model is trained and tested using ground truth data available for the three study areas. The results show that our approach achieves high accuracy in predicting building types for the selected areas. Additionally, a trained model is transferable with high accuracy to other regions where ground truth data is unavailable. The OSM and data science community are invited to build upon our approach to further enrich the volunteered geographic information in an automated manner.

关键词： Curricula  

摘要： What should the curriculum of undergraduate computer science programs be in the 2020s? What are the best curricular practices in creating and sustaining such programs? Since the late 1960s, in almost every decade, the Association for Computing Machinery (ACM) has created successive curricular guidelines for computer science to help answer these questions, with the IEEEComputer Society collaborating on the effort since the 1990s. The latest iteration—Computer Science Curricula 2023 (CS2023)—is being carried out by a joint task force of three leading computing professional societies. This article presents a preview of this effort including its vision, structure, and status, and invites readers to contribute to and improve CS2023 before it is finalized. © 2022 Association for Computing Machinery. All rights reserved.

关键词： Authentication   Internet of Things   Security   Wireless sensor networks   Blockchain   Device-to-device communication   Computer science   Device-to-Device (D2D) authentication   hash media access control destination sequence distance vector (Hash-MAC-DSDV)   Internet of Things (IoT)   local and public chains   security  

摘要： Cyber-physical systems (CPS) connected in the form of Internet of Things (IoT) are vulnerable to various security threats, due to the infrastructure-less deployment of IoT devices. Device-to-Device (D2D) authentication of these networks ensures the integrity, authenticity, and confidentiality of information in the deployed area. The literature suggests different approaches to address security issues in CPS technologies. However, they are mostly based on centralized techniques or specific system deployments with a higher cost of computation and communication. It is therefore necessary to develop an effective scheme that can resolve the security problems in CPS technologies of IoT devices. In this article, a lightweight hash media access control destination sequence distance vector (Hash-MAC-DSDV) routing scheme is proposed to resolve authentication issues in CPS technologies, connected in the form of IoT networks. For this purpose, a CPS of IoT devices (multi-WSNs) is developed from the local chain and public chain, respectively. The proposed scheme ensures D2D authentication by the Hash-MAC-DSDV mutual scheme, where the MAC addresses of individual devices are registered in the first phase and advertised in the network in the second phase. The proposed scheme allows legitimate devices to modify their routing table and unicast the one-way hash authentication mechanism to transfer their captured data from the source toward the destination. Our evaluation results demonstrate that Hash-MAC-DSDV outweighs the existing schemes in terms of attack detection, energy consumption, and communication metrics.

关键词： Engineering   Mathematical achievement   Sex and race   ethnicity   Postsecondary education   Intersectionality  

摘要： Background Numerous efforts worldwide have been made to increase diversity in engineering and computer science (ECS), fields that pay well and promote upward mobility. However, in the United States (U.S.), females and students from underrepresented racial/ethnic minority groups (URM) still pursue ECS training far less than do their peers. The current study explored sex and racial/ethnic differences in ECS college enrollment as a function of math and verbal SAT score patterns (balanced or imbalanced) using an intersectional approach within a U.S. context. Data represented a census of students who took the SAT, graduated from all Virginia public high schools between 2006 and 2015, and enrolled in a 4-year college (N = 344,803). Results Our findings show, within each sex, URM students were at least as likely as their non-URM peers to enroll in ECS programs when they scored within similar SAT score ranges. Students were more likely to enroll in ECS programs if their SAT profile favored math, compared to students with similar math and verbal SAT scores (balanced profile). This overall pattern is notably less pronounced for URM female students;their propensity to major in ECS appeared to be largely independent of verbal scores. Conclusions Our findings inform strategies to diversify ECS enrollment. If programs continue to emphasize SAT scores during admission decisions or if more systemic issues of resource allocation in secondary schools are not addressed, other efforts to broaden participation in ECS programs may fall short of goals. Our findings also highlight the importance of considering the intersection of sex and race/ethnicity for recruitment or other educational promotions.

关键词： Computer science   Communication   Publishing   Authorship  

摘要： Large language models can draft abstracts or suggest research directions, but these artificial-intelligence tools are a work in progress.

关键词： Task analysis   Big Data   Cloud computing   Security   Codes   Java   Computer science   Trusted computing   Intel SGX   AMD SEV   big data workflow   heterogeneous cloud  

摘要： Big data workflow management systems (BDWMS)s have recently emerged as popular data analytics platforms to conduct large-scale data analytics in the cloud. However, the protection of data confidentiality and secure execution of workflow applications remains an important and challenging problem. Although a few data analytics systems, such as VC3 and Opaque, were developed to address security problems, they are limited to specific domains such as Map-Reduce-style and SQL query workflows. A generic secure framework for BDWMSs is still missing. In this article, we propose SecDATAVIEW, a distributed BDWMS that employs heterogeneous workers, such as Intel SGX and AMD SEV, to protect both workflow and workflow data execution, addressing three major security challenges: (1) Reducing the TCB size of the big data workflow management system in the untrusted cloud by leveraging the hardware-assisted TEE and software attestation;(2) Supporting Java-written workflow tasks to overcome the limitation of SGX's lack of support for Java programs;and (3) Reducing the adverse impact of SGX enclave memory paging overhead through a "Hybrid" workflow task scheduling system that selectively deploys sensitive tasks to a mix of SGX and SEV worker nodes. Our experimental results show that SecDATAVIEW imposes moderate overhead on the workflow execution time.

关键词： 复杂工程问题   创新实践   计算机类   新工科  

摘要： 为培养计算机类本科生解决复杂工程问题的能力,以新工科专业认证毕业要求指标点为抓手,以培养计算机人才解决复杂工程问题的能力为目标,构建大学生创新创业能力培养体系,设计出适合普通本科类学生的创新实践课程体系和实验内容。根据“两贯通六着重”创新实践项目的实践结果,分析普通本科高校培养计算机类本科生解决复杂工程问题能力的方法和实施方案,探索工科类学生学习的长效运行机制和激励机制,以切实提高理工科学生的学习实效。

关键词： 智能化建筑   计算机科学与技术   建筑数据  

摘要： 随着我国社会体系的不断建设与发展,我国较多的建筑单位在设计与建设过程中,都逐渐应用计算机科学以及相关技术,促进了我国建筑智能化的发展,为智能化建筑相关功能平稳运行提供了保障,使其可以发挥最大价值。其中,应用较为关键的领域则是智能化建筑物的智能系统服务,文章将根据智能化建筑的含义与优势,对智能化建筑中计算机科学与技术的实际应用与价值进行分析,希望能为相关人员提供参考与借鉴。