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关键词： Cloud computing   Cryptography   Sensors   Internet of Things   Data models   Costs   Computer science   Brute-force attacks   fog-cloud network   frequency analysis   message equality information   similar data deduplication  

摘要： Distributed fog computing has received wide attention recently. It enables distributed computing and data management on the network nodes within the close vicinity of IoT devices. An important service of fog-cloud based systems is data deduplication. With the increasing concern of privacy, some privacy-preserving data deduplication schemes have been proposed. However, they cannot support lossless deduplication of encrypted similar data in the fog-cloud network. Meanwhile, no existing design can protect message equality information while resisting brute-force and frequency analysis attacks. In this paper, we propose a privacy-preserving and compression-based data deduplication system under the fog-cloud network, which supports lossless deduplication of similar data in the encrypted domain. Specifically, we first use the generalized deduplication technique and cryptographic primitives to implement secure deduplication over similar data. Then, we devise a two-level deduplication protocol that can perform secure and efficient deduplication at distributed fog nodes and the cloud. The proposed system can not only resist brute-force and frequency analysis attacks but also ensure that only the data operator can capture the message equality information. We formally analyze the security of our design. Performance evaluations demonstrate that our proposed design is efficient in computing, storage, and communication.

关键词： Motion detection   Perception   Network models   Computer science   Human behaviour  

摘要： How the human visual system leverages the rich structure in object motion for perception remains unclear. Here, Bill et al. propose a theory of how the brain could infer motion relations in real time and offer a unifying explanation for various perceptual phenomena. Identifying the structure of motion relations in the environment is critical for navigation, tracking, prediction, and pursuit. Yet, little is known about the mental and neural computations that allow the visual system to infer this structure online from a volatile stream of visual information. We propose online hierarchical Bayesian inference as a principled solution for how the brain might solve this complex perceptual task. We derive an online Expectation-Maximization algorithm that explains human percepts qualitatively and quantitatively for a diverse set of stimuli, covering classical psychophysics experiments, ambiguous motion scenes, and illusory motion displays. We thereby identify normative explanations for the origin of human motion structure perception and make testable predictions for future psychophysics experiments. The proposed online hierarchical inference model furthermore affords a neural network implementation which shares properties with motion-sensitive cortical areas and motivates targeted experiments to reveal the neural representations of latent structure.

关键词： Computer science   Quantum physics   Technology  

摘要： The holographic principle, theorized to be a property of quantum gravity, postulates that the description of a volume of space can be encoded on a lower-dimensional boundary. The anti-de Sitter (AdS)/conformal field theory correspondence or duality(1) is the principal example of holography. The Sachdev-Ye-Kitaev (SYK) model of N >> 1 Majorana fermions(2,3) has features suggesting the existence of a gravitational dual in AdS(2), and is a new realization of holography(4-6). We invoke the holographic correspondence of the SYK many-body system and gravity to probe the conjectured ER=EPR relation between entanglement and spacetime geometry(7,8) through the traversable wormhole mechanism as implemented in the SYK model(9,10). A qubit can be used to probe the SYK traversable wormhole dynamics through the corresponding teleportation protocol(9). This can be realized as a quantum circuit, equivalent to the gravitational picture in the semiclassical limit of an infinite number of qubits(9). Here we use learning techniques to construct a sparsified SYK model that we experimentally realize with 164 two-qubit gates on a nine-qubit circuit and observe the corresponding traversable wormhole dynamics. Despite its approximate nature, the sparsified SYK model preserves key properties of the traversable wormhole physics: perfect size winding(11-13), coupling on either side of the wormhole that is consistent with a negative energy shockwave(14), a Shapiro time delay(15), causal time-order of signals emerging from the wormhole, and scrambling and thermalization dynamics(16,17). Our experiment was run on the Google Sycamore processor. By interrogating a two-dimensional gravity dual system, our work represents a step towards a program for studying quantum gravity in the laboratory. Future developments will require improved hardware scalability and performance as well as theoretical developments including higher-dimensional quantum gravity duals(18) and other SYK-like models(19).

关键词： Metadata  

摘要： The number of scientific publications continues to rise exponentially, especially in Computer Science (CS). However, our ability to analyze those publications does not follow the same speed, which prevents us from finding and understanding implicit patterns hidden in their metadata (e.g., venues, document types). Current solutions are limited by restricting access behind a paywall, offering no features for visual analysis, limiting access to their data, only focusing on niches or sub-fields, and/or not being flexible and modular enough to be transferred to other datasets. In this thesis, we conduct a scientometric analysis to uncover those implicit patterns hidden in CS metadata and to determine the state of CS research. Specifically, we investigate trends of the quantity, impact, and topics for authors, venues, document types (conferences vs. journals), and fields of study (compared to, e.g., medicine). To achieve this we introduce the Computer Science Insights (CS-Insights) system, an interactive web application to analyze CS publications through multiple perspectives. The data underlying this system is the DBLP Discovery Dataset (D3), which contains metadata from 5 million scholarly publications in CS. We create D3 with data from DBLP, the largest open-access bibliography for scientific papers and articles in CS, and enrich it with further metadata (e.g., abstracts, citations). CS-Insights offers dedicated dashboards with multiple visualizations for all main features of D3 (e.g., publications, authors, venues, and citations) and multiple filters for more fine-grained analysis. Both D3 and CS-Insights are open-access, and CS-Insights can be easily adapted to other datasets in the future. The most interesting findings of our scientometric analysis include that i) there has been a stark increase in publications, authors, and venues in the last two decades, ii) many authors only recently joined the field, iii) the most cited authors and venues focus on computer visio

关键词： Bibliometrics   Education   Databases   Computer science   Software   Productivity   Economics   general literary works   journal impact study   learning technologies  

摘要： IEEE Transactions on Learning Technologies (IEEE-TLT) is a leading journal in the fields of computer science and educational research with a focus on learning technologies. It published its first issue in 2008 and commemorated its 15th anniversary in 2022. Inspired by this event, this article provides a general lifetime overview of the journal using bibliometric indicators and science mapping analysis. The main objective is to provide a complete overview of the main components that have affected the journal. This analysis includes key factors such as the most cited articles and the leading authors, institutions, and countries for the journal, along with an insight into the publication and the citation structure. We use the Web of Science Core Collection database to analyze the bibliometric data and VOSviewer software to graphically map the bibliographic material using a bibliographic coupling, cocitation, and co-occurrence of author keywords. With this analysis, we gain a deeper understanding of how IEEE-TLT is connected to other journals and researchers across the globe and how it contributes to scientific communities. Results indicate that IEEE-TLT is a high-impact journal in computer Science and education and has been referenced by a wide range of authors, institutions, countries, and the main topics related to learning technologies from all over the world.

关键词： computer   Computer   discipline  

摘要： To explore the nature of computer science and promote the development of the computer science discipline,Tsinghua University organized a global forum during the 60th anniversary of the Department of Computer Science and Technology at *** forum aimed to bring together leaders of the top computer science departments in the world to discuss the fundamentals of computer science,improve the quality of talent cultivation,and promote the development of the global computer science discipline.

关键词： Logic gates   Bandwidth   Service level agreements   Packet loss   Computer science   Cloud computing   Wide area networks   Network function virtualization   network load detection   flow bandwidth prediction   stateful scaling   service level agreements  

摘要： Network function virtualization (NFV) enables elastic scaling to middlebox deployment and management. Therefore, efficient stateful scaling is an important task because operators often need to shift traffic and the associated flow states across VNF instances to deal with time-varying loads. Existing NFV scaling methods, however, typically focus on one aspect of the scaling pipeline and does not offer an end-to-end scaling framework. This article presents ScaleFlux, a complete stateful scaling system that efficiently reduces flow-level latency and achieves near-optimal resource usage. ScaleFlux (1) monitors traffic load for each VNF instance and adopts a queue-based mechanism to detect load burstiness timely, (2) deploys a flow bandwidth predictor to predict flow bandwidth time-series with the ABCNN-LSTM model, and (3) schedules the necessary flow and state migration using the simulated annealing algorithm to achieve both flow-level latency guarantee and resource usage minimization. Testbed evaluation with a five-machine cluster shows that ScaleFlux reduces flow completion time by at least 8.7x for all the workloads and achieves near-optimal CPU usage during scaling.

关键词： 地方性高校   研究生培养   培养模式  

摘要： 当前我国经济与科技的快速增长,加大了对应用型人才的需求,同时,也对高等院校的研究生培养提出了更高要求。以计算机科学与技术专业为例,系统分析了地方性高校中研究生的培养现状及存在问题,提出了提高生源质量、提高教师水平和加强研究生培养的三种针对性措施,并结合实际案例在加强研究生培养的针对性方面进行探索,以地方性为出发点、以学生为主体、以人工智能课程体系为框架、以校地—校企—校校合作为实施途径、以应用型人才为目标,从培养模式、课程体系、课堂教学、实施途径方面进行系统分析,探索和研究地方性院校研究生培养的“四位一体”新模式。

关键词： 地域文化   艺术色彩   民间艺术   郝青青“喜盒子”   “黑色”色彩  

摘要： 地域文化中的地理环境和人文环境是艺术色彩形成的基础,艺术色彩受地理环境因素的影响和制约,也受人文环境的感染和驱使。同时地域文化的环境特征与人的审美心理有着不可分割的联系,艺术审美心理在特定地域因素影响下形成特定的艺术色彩风格。民间艺术是人文精神、人文观念和人文情感之下的产物,人文环境的构成因素与所处的自然地理环境有着多层次、多方面的关系。这赋予了民间艺术具有很直观的地域代表性和象征性,及民俗文化性和社会特征性。本文主要以研究艺术色彩与地域文化关系为主,分析了地域文化的影响及艺术色彩的形成因素,论述了地域文化在艺术色彩中的表现。采用资料收集法和实地考察法相结合研究出郝青青喜盒子中“黑色”色彩的应用原因,分析郝青青喜盒子中独特的“黑色”色彩与“地域文化”之间的关系。深入挖掘红岛地域文化,从而分析出郝青青喜盒子如何受地域文化的影响形成独特审美观念。